repo_name
stringlengths 7
94
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stringlengths 4
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stringlengths 40
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| content
stringlengths 10
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| apis
stringlengths 2
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|---|---|---|---|---|
Inrixia/pyais | examples/single_message.py | b50fd4d75c687d71b3c70ee939ac9112cfec991e | from pyais.messages import NMEAMessage
message = NMEAMessage(b"!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C")
print(message.decode())
# or
message = NMEAMessage.from_string("!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C")
print(message.decode())
| [((3, 10, 3, 73), 'pyais.messages.NMEAMessage', 'NMEAMessage', ({(3, 22, 3, 72): "b'!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C'"}, {}), "(b'!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C')", False, 'from pyais.messages import NMEAMessage\n'), ((8, 10, 8, 84), 'pyais.messages.NMEAMessage.from_string', 'NMEAMessage.from_string', ({(8, 34, 8, 83): '"""!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C"""'}, {}), "('!AIVDM,1,1,,B,15M67FC000G?ufbE`FepT@3n00Sa,0*5C')", False, 'from pyais.messages import NMEAMessage\n')] |
sercangul/HackerRank | 30_days_of_code_10.py | e6d7056babe03baafee8d7f1cacdca7c28b72ded | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 3 19:02:33 2019
@author: sercangul
"""
def maxConsecutiveOnes(x):
# Initialize result
count = 0
# Count the number of iterations to
# reach x = 0.
while (x!=0):
# This operation reduces length
# of every sequence of 1s by one.
x = (x & (x << 1))
count=count+1
return count
if __name__ == '__main__':
n = int(input())
result = maxConsecutiveOnes(n)
print(result) | [] |
artap-framework/artap | artap/algorithm_cmaes.py | 7e4b01abbe5ca0fce9fa87a1a307ebd11ace36b4 | import numpy as np
from .problem import Problem
from .algorithm_genetic import GeneralEvolutionaryAlgorithm
from .individual import Individual
from .operators import CustomGenerator, nondominated_truncate, RandomGenerator, UniformGenerator
import time
class CMA_ES(GeneralEvolutionaryAlgorithm):
"""
Implementation of CMA_ES, Covariance Matrix Adaptation Evolutionary strategy (CMA_ES).
The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) [1] is one of the most effective approaches
for black-box optimization, in which objective functions cannot be specified explicitly in general.
CMA-ES outperformed over 100 black-box optimization approaches for a variety of benchmark problems [2].
The CMA-ES algorithm selects solutions from a multivariate gaussian distribution. Following the evaluation of
all solutions, the solutions are sorted by evaluation values, and the distribution parameters
(i.e., the mean vector and the covariance matrix) are updated depending on the ranking of evaluation values.
[1] Nikolaus Hansen and Andreas Ostermeier. Completely derandomized self-adaptation in evolution strategies.
Evol. Comput., 9(2):159–195, June 2001.
DOI: http://dx.doi.org/10.1162/106365601750190398.
[2] Nikolaus Hansen. The CMA Evolution Strategy: A Comparing Review, pages 75–102. Springer Berlin Heidelberg,
Berlin, Heidelberg, 2006.
DOI: https://doi.org/10.1007/3-540-32494-1_4.
"""
def __init__(self, problem: Problem, name="Covariance Matrix Adaptation Evolutionary Strategy"):
super().__init__(problem, name)
# Population Size
self.n_samples = self.options['max_population_size']
# Number of generation
self.t = self.options['max_population_number']
self.individual_features['velocity'] = dict()
self.individual_features['best_cost'] = dict()
self.individual_features['best_vector'] = dict()
self.individual_features['dominate'] = []
self.individual_features['crowding_distance'] = 0
self.individual_features['domination_counter'] = 0
# Add front_number feature
self.individual_features['front_number'] = 0
self.dim_theta = len(self.problem.parameters)
# Elite ratio percentage
self.top_p = 30
# Range of values
self.min_val = 0
self.max_val = 1
# Number of Runs
self.runs = 1
self.theta_mean = np.random.uniform(self.min_val, self.max_val, self.dim_theta)
# self.individuals = []
theta_std = np.random.uniform(self.max_val - 1, self.max_val, self.dim_theta)
self.theta_cov = np.diag(theta_std)
self.generator = CustomGenerator(self.problem.parameters, self.individual_features)
# self.fit_gaussian()
def fit_gaussian(self):
"""
generates individuals from a multivariate gaussian distribution
:param
:return population: list of individuals
"""
theta = np.random.multivariate_normal(self.theta_mean, self.theta_cov, self.options['max_population_size'])
individuals = np.clip(theta, self.min_val, self.max_val)
self.generator.init(individuals)
individuals = self.generator.generate()
return individuals
def take_elite(self, candidates):
"""
Based on the fitness, it will take top individuals
:param candidates
:return elite: list of top individuals
"""
n_top = int((self.n_samples * self.top_p) / 100)
elite = candidates[:n_top]
return elite
def compute_new_mean(self, e_candidates):
"""
Update distribution parameters. Here, the mean vector will be updated depending on the ranking of
evaluation values.
:param e_candidates
:return new_means vector
"""
new_means = np.mean(e_candidates, axis=0)
return new_means
def compute_new_cov(self, e_candidates):
"""
Update distribution parameters. Here, the covariance matrix will be updated depending on the ranking of
evaluation values
:param e_candidates
:return new_covariance matrix
"""
e_candidates = np.array(e_candidates)
I = np.identity(self.dim_theta)
cov = np.zeros((self.dim_theta, self.dim_theta))
for i in range(self.dim_theta):
for j in range(self.dim_theta):
cov[i, j] = np.sum(
((e_candidates[:, i] - self.theta_mean[i]) * (e_candidates[:, j] - self.theta_mean[j])), axis=0)
return 1 / e_candidates.shape[0] * cov + I * 1e-3
def run(self):
mean_fitness = []
best_fitness = []
worst_fitness = []
fitness = []
individuals = self.fit_gaussian()
for individual in individuals:
# append to problem
self.problem.individuals.append(individual)
# add to population
individual.population_id = 0
self.problem.data_store.sync_individual(individual)
self.evaluate(individuals)
start = time.time()
self.problem.logger.info("CMA_ES: {}/{}".format(self.options['max_population_number'],
self.options['max_population_size']))
for it in range(self.options['max_population_number']):
lists = []
for individual in individuals:
# fitness.append(individual.costs)
lists.append(individual.costs)
lists = np.array(lists)
mean_fitness.append(np.mean(lists))
best_fitness.append(np.min(lists))
worst_fitness.append(np.max(lists))
fitness.append(lists)
elite = self.take_elite(individuals)
e_candidates = [i.vector for i in elite]
self.theta_cov = self.compute_new_cov(e_candidates)
self.theta_mean = self.compute_new_mean(e_candidates)
individuals = self.fit_gaussian()
# individuals = nondominated_truncate(new_individuals, self.options['max_population_size'])
self.evaluate(individuals)
for individual in individuals:
# add to population
individual.population_id = it + 1
# append to problem
self.problem.individuals.append(individual)
# sync to datastore
self.problem.data_store.sync_individual(individual)
t = time.time() - start
self.problem.logger.info("CMA_ES: elapsed time: {} s".format(t))
# sync changed individual informations
self.problem.data_store.sync_all()
| [((55, 26, 55, 87), 'numpy.random.uniform', 'np.random.uniform', ({(55, 44, 55, 56): 'self.min_val', (55, 58, 55, 70): 'self.max_val', (55, 72, 55, 86): 'self.dim_theta'}, {}), '(self.min_val, self.max_val, self.dim_theta)', True, 'import numpy as np\n'), ((57, 20, 57, 85), 'numpy.random.uniform', 'np.random.uniform', ({(57, 38, 57, 54): 'self.max_val - 1', (57, 56, 57, 68): 'self.max_val', (57, 70, 57, 84): 'self.dim_theta'}, {}), '(self.max_val - 1, self.max_val, self.dim_theta)', True, 'import numpy as np\n'), ((58, 25, 58, 43), 'numpy.diag', 'np.diag', ({(58, 33, 58, 42): 'theta_std'}, {}), '(theta_std)', True, 'import numpy as np\n'), ((68, 16, 68, 115), 'numpy.random.multivariate_normal', 'np.random.multivariate_normal', ({(68, 46, 68, 61): 'self.theta_mean', (68, 63, 68, 77): 'self.theta_cov', (68, 79, 68, 114): "self.options['max_population_size']"}, {}), "(self.theta_mean, self.theta_cov, self.options\n ['max_population_size'])", True, 'import numpy as np\n'), ((69, 22, 69, 64), 'numpy.clip', 'np.clip', ({(69, 30, 69, 35): 'theta', (69, 37, 69, 49): 'self.min_val', (69, 51, 69, 63): 'self.max_val'}, {}), '(theta, self.min_val, self.max_val)', True, 'import numpy as np\n'), ((92, 20, 92, 49), 'numpy.mean', 'np.mean', (), '', True, 'import numpy as np\n'), ((102, 23, 102, 45), 'numpy.array', 'np.array', ({(102, 32, 102, 44): 'e_candidates'}, {}), '(e_candidates)', True, 'import numpy as np\n'), ((103, 12, 103, 39), 'numpy.identity', 'np.identity', ({(103, 24, 103, 38): 'self.dim_theta'}, {}), '(self.dim_theta)', True, 'import numpy as np\n'), ((104, 14, 104, 56), 'numpy.zeros', 'np.zeros', ({(104, 23, 104, 55): '(self.dim_theta, self.dim_theta)'}, {}), '((self.dim_theta, self.dim_theta))', True, 'import numpy as np\n'), ((128, 16, 128, 27), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((136, 20, 136, 35), 'numpy.array', 'np.array', ({(136, 29, 136, 34): 'lists'}, {}), '(lists)', True, 'import numpy as np\n'), ((162, 12, 162, 23), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((107, 28, 108, 116), 'numpy.sum', 'np.sum', (), '', True, 'import numpy as np\n'), ((138, 32, 138, 46), 'numpy.mean', 'np.mean', ({(138, 40, 138, 45): 'lists'}, {}), '(lists)', True, 'import numpy as np\n'), ((139, 32, 139, 45), 'numpy.min', 'np.min', ({(139, 39, 139, 44): 'lists'}, {}), '(lists)', True, 'import numpy as np\n'), ((140, 33, 140, 46), 'numpy.max', 'np.max', ({(140, 40, 140, 45): 'lists'}, {}), '(lists)', True, 'import numpy as np\n')] |
hagino3000/apns-proxy-client-py | apns_proxy_client/core.py | b5ce34be940a8f8a990dc369e293408380d0c359 | # -*- coding: utf-8 -*-
"""
APNS Proxy Serverのクライアント
"""
import time
import zmq
import simplejson as json
READ_TIMEOUT = 1500 # msec
FLUSH_TIMEOUT = 5000 # msec
COMMAND_ASK_ADDRESS = b'\1'
COMMAND_SEND = b'\2'
COMMAND_FEEDBACK = b'\3'
DEVICE_TOKEN_LENGTH = 64
JSON_ALERT_KEY_SET = set(['body', 'action_loc_key', 'loc_key', 'loc_args', 'launch_image'])
class APNSProxyClient(object):
def __init__(self, host, port, application_id):
"""
ZMQコンテキストとソケットの初期化
"""
if host is None or not isinstance(host, str):
raise ValueError("host must be string")
if port is None or not isinstance(port, int):
raise ValueError("host must be int type")
self.host = host
self.port = port
self.context = zmq.Context()
self.context.setsockopt(zmq.LINGER, FLUSH_TIMEOUT)
self.communicator = self.context.socket(zmq.REQ)
self.publisher = self.context.socket(zmq.PUSH)
self.connected = False
if not isinstance(application_id, str):
raise ValueError("application_id must be string type")
self.application_id = application_id
def __enter__(self):
self.connect()
def connect(self):
"""リモートサーバーへ接続"""
if self.connected is False:
self.communicator.connect(self.build_address(self.port))
push_port = self.get_push_port()
self.publisher.connect(self.build_address(push_port))
self.connected = True
def build_address(self, port):
return "tcp://%s:%s" % (self.host, port)
def get_push_port(self):
"""
PUSH-PULL接続用のポートを取得する
"""
self.communicator.send(COMMAND_ASK_ADDRESS)
poller = zmq.Poller()
poller.register(self.communicator, zmq.POLLIN)
if poller.poll(READ_TIMEOUT):
return self.communicator.recv()
else:
self.close()
raise IOError("Cannot connect to APNs Proxy Server. Timeout!!")
def send(self, token, alert, sound='default', badge=None, content_available=False,
custom=None, expiry=None, priority=None, test=False):
"""
デバイストークンの送信
"""
self._check_token(token)
self._check_alert(alert)
self._check_custom(custom)
self.publisher.send(self._serialize(
COMMAND_SEND, token, alert, sound, badge, content_available, custom,
expiry, priority, test
))
def get_feedback(self):
data = {
'appid': self.application_id,
}
command = COMMAND_FEEDBACK + json.dumps(data, ensure_ascii=True)
self.communicator.send(command)
return json.loads(self.communicator.recv())
@staticmethod
def _check_token(token):
if len(token) != DEVICE_TOKEN_LENGTH:
raise ValueError('Invalid token length %s' % token)
@staticmethod
def _check_alert(alert):
if (alert is None or isinstance(alert, basestring)):
return
elif isinstance(alert, dict):
if len(set(alert.keys()) - JSON_ALERT_KEY_SET) > 0:
raise ValueError('JSON Alert allows only'
'body, action_loc_key, loc_key, loc_args, launch_image')
else:
raise ValueError('alert must be string, unicode or dict type')
@staticmethod
def _check_custom(custom):
if custom is None or isinstance(custom, dict):
return
raise ValueError('custom must be dict type')
def _serialize(self, command, token, alert, sound, badge, content_available, custom,
expiry, priority, test):
"""
送信データのフォーマット
"""
aps = {}
if alert is not None:
aps['alert'] = alert
if sound is not None:
aps['sound'] = sound
if badge is not None:
aps['badge'] = badge
if content_available is True:
aps['content_available'] = True
if custom is not None:
aps['custom'] = custom
data = {
'appid': self.application_id,
'token': token,
'aps': aps,
'test': test
}
if expiry is not None:
data['expiry'] = expiry
if priority is not None:
data['priority'] = priority
return command + json.dumps(data, ensure_ascii=True)
def __exit__(self, exc_type, exc_value, traceback):
if exc_type:
self._close()
return False
self.close()
def close(self):
start_time = time.time()
self._close()
end_time = time.time()
if (end_time - start_time) > (FLUSH_TIMEOUT - 20)/1000.0:
raise IOError('Timeout close operation. Some messages may not reached to server.')
return True
def _close(self):
self.publisher.close()
self.communicator.close()
self.context.term()
| [((35, 23, 35, 36), 'zmq.Context', 'zmq.Context', ({}, {}), '()', False, 'import zmq\n'), ((65, 17, 65, 29), 'zmq.Poller', 'zmq.Poller', ({}, {}), '()', False, 'import zmq\n'), ((153, 21, 153, 32), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((155, 19, 155, 30), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((90, 37, 90, 72), 'simplejson.dumps', 'json.dumps', (), '', True, 'import simplejson as json\n'), ((144, 25, 144, 60), 'simplejson.dumps', 'json.dumps', (), '', True, 'import simplejson as json\n')] |
svetlanama/snowball | 003_joint_probabilities.py | a41865a866dae124b4a22134f091a7d09bd0896e | import sys
sys.path.insert(0, '..')
import numpy
import time
import ConfigParser
import topicmodel
def main():
# read configuration file
config = ConfigParser.ConfigParser()
config.readfp(open('config.ini'))
dataDir = config.get('main', 'dataDir')
io = topicmodel.io(dataDir)
model = topicmodel.model(dataDir)
wordDictionary = io.load_csv_as_dict('out-word-dictionary-rare-words-excluded.csv')
model.set_word_dictionary(wordDictionary)
# print wordDictionary
# return
wwcovar=model.coccurences('tmp-all-paper-tokens.csv','+','.')
numpy.save(dataDir + '/tmp-joint-probabilities.npy', wwcovar)
return
if __name__ == "__main__":
t0 = time.time()
main()
t1 = time.time()
print "finished"
print "time=", t1 - t0
| [] |
FirebirdSQL/firebird-qa | tests/bugs/core_4318_test.py | 96af2def7f905a06f178e2a80a2c8be4a4b44782 | #coding:utf-8
#
# id: bugs.core_4318
# title: Regression: Predicates involving PSQL variables/parameters are not pushed inside the aggregation
# decription:
# tracker_id: CORE-4318
# min_versions: ['3.0']
# versions: 3.0
# qmid: None
import pytest
from firebird.qa import db_factory, isql_act, Action
# version: 3.0
# resources: None
substitutions_1 = []
init_script_1 = """
recreate table t2 (
id integer not null,
t1_id integer
);
commit;
recreate table t1 (
id integer not null
);
commit;
set term ^;
execute block
as
declare variable i integer = 0;
begin
while (i < 1000) do begin
i = i + 1;
insert into t2(id, t1_id) values(:i, mod(:i, 10));
merge into t1 using (
select mod(:i, 10) as f from rdb$database
) src on t1.id = src.f
when not matched then
insert (id) values(src.f);
end -- while (i < 1000) do begin
end^
set term ;^
commit;
alter table t1 add constraint pk_t1 primary key (id);
alter table t2 add constraint pk_t2 primary key (id);
alter table t2 add constraint fk_t2_ref_t1 foreign key (t1_id) references t1(id);
commit;
"""
db_1 = db_factory(page_size=4096, sql_dialect=3, init=init_script_1)
test_script_1 = """
set explain on;
set planonly;
set term ^;
execute block
returns (
s integer
)
as
declare variable v integer = 1;
begin
with t as (
select t1_id as t1_id, sum(id) as s
from t2
group by 1
)
select s
from t
where t1_id = :v
into :s;
suspend;
end
^
set term ;^
-- In 3.0.0.30837 plan was:
-- Select Expression
-- -> Singularity Check
-- -> Filter
-- -> Aggregate
-- -> Table "T T2" Access By ID
-- -> Index "FK_T2_REF_T1" Scan
-- (i.e. there was NO "Filter" between "Aggregate" and "Table "T T2" Access By ID")
"""
act_1 = isql_act('db_1', test_script_1, substitutions=substitutions_1)
expected_stdout_1 = """
Select Expression
-> Singularity Check
-> Filter
-> Aggregate
-> Filter
-> Table "T2" as "T T2" Access By ID
-> Index "FK_T2_REF_T1" Range Scan (full match)
"""
@pytest.mark.version('>=3.0')
def test_1(act_1: Action):
act_1.expected_stdout = expected_stdout_1
act_1.execute()
assert act_1.clean_stdout == act_1.clean_expected_stdout
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WilliamHackspeare/profanity-percentage | dictionary.py | 4aab708620b7543a2a5cb30c9cee8404dcc836cb | #Import the json library to parse JSON file to Python
import json
#Import list of punctuation characters from the string library
from string import punctuation as p
#This method checks if the given word is a profanity
def is_profanity(word):
#Open the JSON file
words_file = open('data.json')
#Parse the JSON file as a dictionary and extract the values
bad_words = json.load(words_file).values()
#Check and return if the word is a bad work
return word in bad_words
#This method calculates the degree of profanity for a list of strings
def calculate_profanity(sentence):
#Initialise the count of bad words
count_bad = 0
#Initialise the total count of words
count = 0
#Loop through the list of words
for word in sentence:
#Check if the word, stripped of any leading or trailing punctuations or spaces, is a bad word and update count
if is_profanity(word.strip(p+" ")):
count_bad += 1
count += 1
#Calculate the degree of the list
deg = (count_bad/count)*100
#Return the degree
return deg | [((14, 14, 14, 35), 'json.load', 'json.load', ({(14, 24, 14, 34): 'words_file'}, {}), '(words_file)', False, 'import json\n')] |
cyfrmedia/cerridwen | setup.py | 6ac9193d41d7c6fdea0abab5e5f207132844fb4e | from setuptools import setup
import os
here = os.path.abspath(os.path.dirname(__file__))
README = open(os.path.join(here, 'README.rst')).read()
#NEWS = open(os.path.join(here, 'NEWS.txt')).read()
rootdir = os.path.dirname(os.path.abspath(__file__))
exec(open(rootdir + '/cerridwen/version.py').read())
version = __VERSION__
setup(name='cerridwen',
version=version,
description='Accurate solar system data for everyone',
long_description=README,
author='Leslie P. Polzer',
author_email='[email protected]',
url='http://cerridwen.bluemagician.vc/',
license='MIT',
classifiers=[
# Get strings from http://pypi.python.org/pypi?%3Aaction=list_classifiers
"Development Status :: 4 - Beta"
, "Environment :: Console"
, "Intended Audience :: Science/Research"
, "Intended Audience :: Developers"
, "License :: OSI Approved :: MIT License"
, "Operating System :: OS Independent"
, "Programming Language :: Python :: 3"
, "Topic :: Scientific/Engineering :: Astronomy"
, "Topic :: Other/Nonlisted Topic"
, "Topic :: Software Development :: Libraries :: Python Modules"
, "Topic :: Utilities"
],
maintainer='Leslie P. Polzer',
maintainer_email='[email protected]',
packages=['cerridwen'],
requires=['pyswisseph', 'numpy', 'astropy(>=0.4)'],
extras_require={'Flask':['flask']},
entry_points={
'console_scripts':
['cerridwen = cerridwen.cli:main',
'cerridwen-server = cerridwen.api_server:main [Flask]']
})
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JoachimFlottorp/pajbot | pajbot/apiwrappers/authentication/access_token.py | 4fb88c403dedb20d95be80e38da72be1ed064901 | import datetime
from abc import ABC, abstractmethod
import pajbot
class AccessToken(ABC):
SHOULD_REFRESH_THRESHOLD = 0.9
"""Fraction between 0 and 1 indicating what fraction/percentage of the specified full validity period
should actually be utilized. E.g. if this is set to 0.9, the implementation will refresh the token
once at least 90% of the full validity period (expires_in) is over."""
def __init__(self, access_token, created_at, expires_in, token_type, refresh_token, scope):
self.access_token = access_token
self.created_at = created_at
# can both be None
self.expires_in = expires_in
if self.expires_in is not None:
self.expires_at = self.created_at + self.expires_in
else:
self.expires_at = None
self.token_type = token_type
# can be None
self.refresh_token = refresh_token
# always a list, can be empty list
self.scope = scope
@abstractmethod
def can_refresh(self):
pass
def should_refresh(self):
"""Returns True if less than 10% of the token's lifetime remains, False otherwise"""
if not self.can_refresh():
return False
# intended lifetime of the token
if self.expires_at is not None:
expires_after = self.expires_at - self.created_at
else:
# this is a token that never expires
# because we don't want any issues, refresh it anyways
expires_after = datetime.timedelta(hours=1)
# how much time has passed since token creation
token_age = pajbot.utils.now() - self.created_at
# maximum token age before token should be refreshed (90% of the total token lifetime)
max_token_age = expires_after * self.SHOULD_REFRESH_THRESHOLD
# expired?
return token_age >= max_token_age
def jsonify(self):
"""serialize for storage"""
if self.expires_in is None:
expires_in_milliseconds = None
else:
expires_in_milliseconds = self.expires_in.total_seconds() * 1000
return {
"access_token": self.access_token,
"created_at": self.created_at.timestamp() * 1000,
"expires_in": expires_in_milliseconds,
"token_type": self.token_type,
"refresh_token": self.refresh_token,
"scope": self.scope,
}
@classmethod
def from_json(cls, json_data):
"""deserialize json produced by jsonify()"""
if json_data["expires_in"] is None:
expires_in = None
else:
expires_in = datetime.timedelta(milliseconds=json_data["expires_in"])
return cls(
access_token=json_data["access_token"],
created_at=pajbot.utils.datetime_from_utc_milliseconds(json_data["created_at"]),
expires_in=expires_in,
token_type=json_data["token_type"],
refresh_token=json_data["refresh_token"],
scope=json_data["scope"],
)
@classmethod
def from_api_response(cls, response):
"""Construct new object from twitch response json data"""
# expires_in is only missing for old Client-IDs to which twitch will respond with
# infinitely-lived tokens (the "expires_in" field is absent in that case).
expires_in_seconds = response.get("expires_in", None)
if expires_in_seconds is None:
expires_in = None
else:
expires_in = datetime.timedelta(seconds=expires_in_seconds)
return cls(
access_token=response["access_token"],
created_at=pajbot.utils.now(),
expires_in=expires_in,
token_type=response["token_type"],
refresh_token=response.get("refresh_token", None),
scope=response.get("scope", []),
)
@abstractmethod
def refresh(self, api):
pass
class UserAccessToken(AccessToken):
def can_refresh(self):
return self.refresh_token is not None
def refresh(self, api):
if not self.can_refresh():
raise ValueError("This user access token cannot be refreshed, it has no refresh token")
return api.refresh_user_access_token(self.refresh_token)
@staticmethod
def from_implicit_auth_flow_token(access_token):
return UserAccessToken(
access_token=access_token,
created_at=None,
expires_in=None,
token_type="bearer",
refresh_token=None,
scope=[],
)
class AppAccessToken(AccessToken):
def can_refresh(self):
return True
def refresh(self, api):
return api.get_app_access_token(self.scope)
| [((50, 28, 50, 55), 'datetime.timedelta', 'datetime.timedelta', (), '', False, 'import datetime\n'), ((53, 20, 53, 38), 'pajbot.utils.now', 'pajbot.utils.now', ({}, {}), '()', False, 'import pajbot\n'), ((83, 25, 83, 81), 'datetime.timedelta', 'datetime.timedelta', (), '', False, 'import datetime\n'), ((104, 25, 104, 71), 'datetime.timedelta', 'datetime.timedelta', (), '', False, 'import datetime\n'), ((87, 23, 87, 91), 'pajbot.utils.datetime_from_utc_milliseconds', 'pajbot.utils.datetime_from_utc_milliseconds', ({(87, 67, 87, 90): "json_data['created_at']"}, {}), "(json_data['created_at'])", False, 'import pajbot\n'), ((108, 23, 108, 41), 'pajbot.utils.now', 'pajbot.utils.now', ({}, {}), '()', False, 'import pajbot\n')] |
RadicalAjay/Ghost_data | GHOST.py | b151b0b92d27c3b8454e28d4f037eafb587d7b23 | #! /usr/bin/python3
# Description: Data_Ghost, concealing data into spaces and tabs making it imperceptable to human eyes.
# Author: Ajay Dyavathi
# Github: Radical Ajay
class Ghost():
def __init__(self, file_name, output_format='txt'):
''' Converts ascii text to spaces and tabs '''
self.file_name = file_name
self.output_format = output_format
def ascii2bin(self, asc):
''' Converting ascii to bianry '''
return ''.join('{:08b}'.format(ord(i)) for i in asc)
def bin2ascii(self, bid):
''' Converting binary to ascii '''
return ''.join(chr(int(bid[i:i + 8], 2)) for i in range(0, len(bid), 8))
def ghost(self, filename):
''' Ghosting data converting it to spaces and tabs '''
with open(filename, 'w') as out_f:
with open(self.file_name, 'r') as in_f:
for in_data in in_f.readlines():
bin_data = self.ascii2bin(in_data)
out_data = bin_data.replace('1', '\t')
out_data = out_data.replace('0', ' ')
out_f.write(out_data)
def unghost(self, in_filename, out_filename):
''' Unghosting data converting back from spaces and tabs to human-readable text '''
with open(out_filename, 'w') as out_f:
with open(in_filename, 'r') as in_f:
for line in in_f.readlines():
line = line.replace('\t', '1')
line = line.replace(' ', '0')
out_f.write(self.bin2ascii(line))
# USAGE:
# ghoster = Ghost('data.txt')
# ghoster.ghost('ghosted.txt')
# ghoster.unghost('ghosted.txt', 'unghosted.txt')
| [] |
ychu196/chicago_scan | scan_predict.py | ed5f32a9f27fd5b9350cb3232a2631c3aaa60744 | # Image classification using AWS Sagemaker and Linear Learner
# Program set up and import libraries
import numpy as np
import pandas as pd
import os
from sagemaker import get_execution_role
role = get_execution_role()
bucket = 'chi-hackathon-skin-images'
# Import Data
import boto3
from sagemaker import get_execution_role
role = get_execution_role()
bucket='chi-hackathon-skin-images'
data_key = 'ISIC_0000000.json' # need a way to go through entire library
data_location = 's3://{}/{}'.format(bucket, data_key)
metadata_set = pd.read_json(data_location)
image_set = np.asarray(data_location)
# TBD - transform json data to array
# TBD - transform image data to dataframe
train_set = zip(image_set, metadata_set)
# Split Data into Train and Validate
import random
random.seed(9001)
split = np.random.rand(len(df)) < 0.8
valid_set = train_set[split]
train_set = train_set[~split]
# Train Model
import boto
import sagemaker
data_location = 's3://{}/linearlearner_highlevel_example/data'.format(bucket)
output_location = 's3://{}/linearlearner_highlevel_example/output'.format(bucket)
print('training data will be uploaded to: {}'.format(data_location))
print('training artifacts will be uploaded to: {}'.format(output_location))
sess = sagemaker.Session()
linear = sagemaker.estimator.Estimator(container, role, train_instance_count=1, rain_instance_type='ml.c4.xlarge',
output_path=output_location, sagemaker_session=sess)
linear.set_hyperparameters(feature_dim=784, predictor_type='binary_classifier', mini_batch_size=200)
linear.fit({'train': train_set})
# Deploy Model
linear_predictor = linear.deploy(initial_instance_count=1, instance_type='ml.m4.xlarge')
# Validate
from sagemaker.predictor import csv_serializer, json_deserializer
linear_predictor.content_type = 'text/csv'
linear_predictor.serializer = csv_serializer
linear_predictor.deserializer = json_deserializer
result = linear_predictor.predict(train_set[0][30:31])
print(result)
| [((9, 7, 9, 27), 'sagemaker.get_execution_role', 'get_execution_role', ({}, {}), '()', False, 'from sagemaker import get_execution_role\n'), ((16, 7, 16, 27), 'sagemaker.get_execution_role', 'get_execution_role', ({}, {}), '()', False, 'from sagemaker import get_execution_role\n'), ((21, 15, 21, 42), 'pandas.read_json', 'pd.read_json', ({(21, 28, 21, 41): 'data_location'}, {}), '(data_location)', True, 'import pandas as pd\n'), ((22, 12, 22, 37), 'numpy.asarray', 'np.asarray', ({(22, 23, 22, 36): 'data_location'}, {}), '(data_location)', True, 'import numpy as np\n'), ((30, 0, 30, 17), 'random.seed', 'random.seed', ({(30, 12, 30, 16): '(9001)'}, {}), '(9001)', False, 'import random\n'), ((44, 7, 44, 26), 'sagemaker.Session', 'sagemaker.Session', ({}, {}), '()', False, 'import sagemaker\n'), ((46, 9, 47, 56), 'sagemaker.estimator.Estimator', 'sagemaker.estimator.Estimator', (), '', False, 'import sagemaker\n')] |
FixturFab/pcb-tools | gerber/am_statements.py | 7b8d1c6ccd9c242c162ede47557bb816233cf66f | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# copyright 2015 Hamilton Kibbe <[email protected]> and Paulo Henrique Silva
# <[email protected]>
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from math import asin
import math
from .primitives import *
from .utils import validate_coordinates, inch, metric, rotate_point
# TODO: Add support for aperture macro variables
__all__ = ['AMPrimitive', 'AMCommentPrimitive', 'AMCirclePrimitive',
'AMVectorLinePrimitive', 'AMOutlinePrimitive', 'AMPolygonPrimitive',
'AMMoirePrimitive', 'AMThermalPrimitive', 'AMCenterLinePrimitive',
'AMLowerLeftLinePrimitive', 'AMUnsupportPrimitive']
class AMPrimitive(object):
""" Aperture Macro Primitive Base Class
Parameters
----------
code : int
primitive shape code
exposure : str
on or off Primitives with exposure on create a slid part of
the macro aperture, and primitives with exposure off erase the
solid part created previously in the aperture macro definition.
.. note::
The erasing effect is limited to the aperture definition in
which it occurs.
Returns
-------
primitive : :class: `gerber.am_statements.AMPrimitive`
Raises
------
TypeError, ValueError
"""
def __init__(self, code, exposure=None):
VALID_CODES = (0, 1, 2, 4, 5, 6, 7, 20, 21, 22, 9999)
if not isinstance(code, int):
raise TypeError('Aperture Macro Primitive code must be an integer')
elif code not in VALID_CODES:
raise ValueError('Invalid Code. Valid codes are %s.' %
', '.join(map(str, VALID_CODES)))
if exposure is not None and exposure.lower() not in ('on', 'off'):
raise ValueError('Exposure must be either on or off')
self.code = code
self.exposure = exposure.lower() if exposure is not None else None
def to_inch(self):
raise NotImplementedError('Subclass must implement `to-inch`')
def to_metric(self):
raise NotImplementedError('Subclass must implement `to-metric`')
@property
def _level_polarity(self):
if self.exposure == 'off':
return 'clear'
return 'dark'
def to_primitive(self, units):
""" Return a Primitive instance based on the specified macro params.
"""
print('Rendering {}s is not supported yet.'.format(str(self.__class__)))
def __eq__(self, other):
return self.__dict__ == other.__dict__
class AMCommentPrimitive(AMPrimitive):
""" Aperture Macro Comment primitive. Code 0
The comment primitive has no image meaning. It is used to include human-
readable comments into the AM command.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.1:** Comment, primitive code 0
Parameters
----------
code : int
Aperture Macro primitive code. 0 Indicates an AMCommentPrimitive
comment : str
The comment as a string.
Returns
-------
CommentPrimitive : :class:`gerbers.am_statements.AMCommentPrimitive`
An Initialized AMCommentPrimitive
Raises
------
ValueError
"""
@classmethod
def from_gerber(cls, primitive):
primitive = primitive.strip()
code = int(primitive[0])
comment = primitive[1:]
return cls(code, comment)
def __init__(self, code, comment):
if code != 0:
raise ValueError('Not a valid Aperture Macro Comment statement')
super(AMCommentPrimitive, self).__init__(code)
self.comment = comment.strip(' *')
def to_inch(self):
pass
def to_metric(self):
pass
def to_gerber(self, settings=None):
return '0 %s *' % self.comment
def to_primitive(self, units):
"""
Returns None - has not primitive representation
"""
return None
def __str__(self):
return '<Aperture Macro Comment: %s>' % self.comment
class AMCirclePrimitive(AMPrimitive):
""" Aperture macro Circle primitive. Code 1
A circle primitive is defined by its center point and diameter.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.2:** Circle, primitive code 1
Parameters
----------
code : int
Circle Primitive code. Must be 1
exposure : string
'on' or 'off'
diameter : float
Circle diameter
position : tuple (<float>, <float>)
Position of the circle relative to the macro origin
Returns
-------
CirclePrimitive : :class:`gerbers.am_statements.AMCirclePrimitive`
An initialized AMCirclePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(',')
code = int(modifiers[0])
exposure = 'on' if float(modifiers[1]) == 1 else 'off'
diameter = float(modifiers[2])
position = (float(modifiers[3]), float(modifiers[4]))
return cls(code, exposure, diameter, position)
@classmethod
def from_primitive(cls, primitive):
return cls(1, 'on', primitive.diameter, primitive.position)
def __init__(self, code, exposure, diameter, position):
validate_coordinates(position)
if code != 1:
raise ValueError('CirclePrimitive code is 1')
super(AMCirclePrimitive, self).__init__(code, exposure)
self.diameter = diameter
self.position = position
def to_inch(self):
self.diameter = inch(self.diameter)
self.position = tuple([inch(x) for x in self.position])
def to_metric(self):
self.diameter = metric(self.diameter)
self.position = tuple([metric(x) for x in self.position])
def to_gerber(self, settings=None):
data = dict(code=self.code,
exposure='1' if self.exposure == 'on' else 0,
diameter=self.diameter,
x=self.position[0],
y=self.position[1])
return '{code},{exposure},{diameter},{x},{y}*'.format(**data)
def to_primitive(self, units):
return Circle((self.position), self.diameter, units=units, level_polarity=self._level_polarity)
class AMVectorLinePrimitive(AMPrimitive):
""" Aperture Macro Vector Line primitive. Code 2 or 20.
A vector line is a rectangle defined by its line width, start, and end
points. The line ends are rectangular.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.3:** Vector Line, primitive code 2 or 20.
Parameters
----------
code : int
Vector Line Primitive code. Must be either 2 or 20.
exposure : string
'on' or 'off'
width : float
Line width
start : tuple (<float>, <float>)
coordinate of line start point
end : tuple (<float>, <float>)
coordinate of line end point
rotation : float
Line rotation about the origin.
Returns
-------
LinePrimitive : :class:`gerbers.am_statements.AMVectorLinePrimitive`
An initialized AMVectorLinePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_primitive(cls, primitive):
return cls(2, 'on', primitive.aperture.width, primitive.start, primitive.end, 0)
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(',')
code = int(modifiers[0])
exposure = 'on' if float(modifiers[1]) == 1 else 'off'
width = float(modifiers[2])
start = (float(modifiers[3]), float(modifiers[4]))
end = (float(modifiers[5]), float(modifiers[6]))
rotation = float(modifiers[7])
return cls(code, exposure, width, start, end, rotation)
def __init__(self, code, exposure, width, start, end, rotation):
validate_coordinates(start)
validate_coordinates(end)
if code not in (2, 20):
raise ValueError('VectorLinePrimitive codes are 2 or 20')
super(AMVectorLinePrimitive, self).__init__(code, exposure)
self.width = width
self.start = start
self.end = end
self.rotation = rotation
def to_inch(self):
self.width = inch(self.width)
self.start = tuple([inch(x) for x in self.start])
self.end = tuple([inch(x) for x in self.end])
def to_metric(self):
self.width = metric(self.width)
self.start = tuple([metric(x) for x in self.start])
self.end = tuple([metric(x) for x in self.end])
def to_gerber(self, settings=None):
fmtstr = '{code},{exp},{width},{startx},{starty},{endx},{endy},{rotation}*'
data = dict(code=self.code,
exp=1 if self.exposure == 'on' else 0,
width=self.width,
startx=self.start[0],
starty=self.start[1],
endx=self.end[0],
endy=self.end[1],
rotation=self.rotation)
return fmtstr.format(**data)
def to_primitive(self, units):
"""
Convert this to a primitive. We use the Outline to represent this (instead of Line)
because the behaviour of the end caps is different for aperture macros compared to Lines
when rotated.
"""
# Use a line to generate our vertices easily
line = Line(self.start, self.end, Rectangle(None, self.width, self.width))
vertices = line.vertices
aperture = Circle((0, 0), 0)
lines = []
prev_point = rotate_point(vertices[-1], self.rotation, (0, 0))
for point in vertices:
cur_point = rotate_point(point, self.rotation, (0, 0))
lines.append(Line(prev_point, cur_point, aperture))
return Outline(lines, units=units, level_polarity=self._level_polarity)
class AMOutlinePrimitive(AMPrimitive):
""" Aperture Macro Outline primitive. Code 4.
An outline primitive is an area enclosed by an n-point polygon defined by
its start point and n subsequent points. The outline must be closed, i.e.
the last point must be equal to the start point. Self intersecting
outlines are not allowed.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.6:** Outline, primitive code 4.
Parameters
----------
code : int
OutlinePrimitive code. Must be 6.
exposure : string
'on' or 'off'
start_point : tuple (<float>, <float>)
coordinate of outline start point
points : list of tuples (<float>, <float>)
coordinates of subsequent points
rotation : float
outline rotation about the origin.
Returns
-------
OutlinePrimitive : :class:`gerber.am_statements.AMOutlineinePrimitive`
An initialized AMOutlinePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_primitive(cls, primitive):
start_point = (round(primitive.primitives[0].start[0], 6), round(primitive.primitives[0].start[1], 6))
points = []
for prim in primitive.primitives:
points.append((round(prim.end[0], 6), round(prim.end[1], 6)))
rotation = 0.0
return cls(4, 'on', start_point, points, rotation)
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
exposure = "on" if float(modifiers[1]) == 1 else "off"
n = int(float(modifiers[2]))
start_point = (float(modifiers[3]), float(modifiers[4]))
points = []
for i in range(n):
points.append((float(modifiers[5 + i * 2]),
float(modifiers[5 + i * 2 + 1])))
rotation = float(modifiers[-1])
return cls(code, exposure, start_point, points, rotation)
def __init__(self, code, exposure, start_point, points, rotation):
""" Initialize AMOutlinePrimitive
"""
validate_coordinates(start_point)
for point in points:
validate_coordinates(point)
if code != 4:
raise ValueError('OutlinePrimitive code is 4')
super(AMOutlinePrimitive, self).__init__(code, exposure)
self.start_point = start_point
if points[-1] != start_point:
raise ValueError('OutlinePrimitive must be closed')
self.points = points
self.rotation = rotation
def to_inch(self):
self.start_point = tuple([inch(x) for x in self.start_point])
self.points = tuple([(inch(x), inch(y)) for x, y in self.points])
def to_metric(self):
self.start_point = tuple([metric(x) for x in self.start_point])
self.points = tuple([(metric(x), metric(y)) for x, y in self.points])
def to_gerber(self, settings=None):
data = dict(
code=self.code,
exposure="1" if self.exposure == "on" else "0",
n_points=len(self.points),
start_point="%.6g,%.6g" % self.start_point,
points=",\n".join(["%.6g,%.6g" % point for point in self.points]),
rotation=str(self.rotation)
)
return "{code},{exposure},{n_points},{start_point},{points},{rotation}*".format(**data)
def to_primitive(self, units):
"""
Convert this to a drawable primitive. This uses the Outline instead of Line
primitive to handle differences in end caps when rotated.
"""
lines = []
prev_point = rotate_point(self.start_point, self.rotation)
for point in self.points:
cur_point = rotate_point(point, self.rotation)
lines.append(Line(prev_point, cur_point, Circle((0,0), 0)))
prev_point = cur_point
if lines[0].start != lines[-1].end:
raise ValueError('Outline must be closed')
return Outline(lines, units=units, level_polarity=self._level_polarity)
class AMPolygonPrimitive(AMPrimitive):
""" Aperture Macro Polygon primitive. Code 5.
A polygon primitive is a regular polygon defined by the number of
vertices, the center point, and the diameter of the circumscribed circle.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.8:** Polygon, primitive code 5.
Parameters
----------
code : int
PolygonPrimitive code. Must be 5.
exposure : string
'on' or 'off'
vertices : int, 3 <= vertices <= 12
Number of vertices
position : tuple (<float>, <float>)
X and Y coordinates of polygon center
diameter : float
diameter of circumscribed circle.
rotation : float
polygon rotation about the origin.
Returns
-------
PolygonPrimitive : :class:`gerbers.am_statements.AMPolygonPrimitive`
An initialized AMPolygonPrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_primitive(cls, primitive):
return cls(5, 'on', primitive.sides, primitive.position, primitive.diameter, primitive.rotation)
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
exposure = "on" if float(modifiers[1]) == 1 else "off"
vertices = int(float(modifiers[2]))
position = (float(modifiers[3]), float(modifiers[4]))
try:
diameter = float(modifiers[5])
except:
diameter = 0
rotation = float(modifiers[6])
return cls(code, exposure, vertices, position, diameter, rotation)
def __init__(self, code, exposure, vertices, position, diameter, rotation):
""" Initialize AMPolygonPrimitive
"""
if code != 5:
raise ValueError('PolygonPrimitive code is 5')
super(AMPolygonPrimitive, self).__init__(code, exposure)
if vertices < 3 or vertices > 12:
raise ValueError('Number of vertices must be between 3 and 12')
self.vertices = vertices
validate_coordinates(position)
self.position = position
self.diameter = diameter
self.rotation = rotation
def to_inch(self):
self.position = tuple([inch(x) for x in self.position])
self.diameter = inch(self.diameter)
def to_metric(self):
self.position = tuple([metric(x) for x in self.position])
self.diameter = metric(self.diameter)
def to_gerber(self, settings=None):
data = dict(
code=self.code,
exposure="1" if self.exposure == "on" else "0",
vertices=self.vertices,
position="%.4g,%.4g" % self.position,
diameter='%.4g' % self.diameter,
rotation=str(self.rotation)
)
fmt = "{code},{exposure},{vertices},{position},{diameter},{rotation}*"
return fmt.format(**data)
def to_primitive(self, units):
return Polygon(self.position, self.vertices, self.diameter / 2.0, 0, rotation=math.radians(self.rotation), units=units, level_polarity=self._level_polarity)
class AMMoirePrimitive(AMPrimitive):
""" Aperture Macro Moire primitive. Code 6.
The moire primitive is a cross hair centered on concentric rings (annuli).
Exposure is always on.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.9:** Moire, primitive code 6.
Parameters
----------
code : int
Moire Primitive code. Must be 6.
position : tuple (<float>, <float>)
X and Y coordinates of moire center
diameter : float
outer diameter of outer ring.
ring_thickness : float
thickness of concentric rings.
gap : float
gap between concentric rings.
max_rings : float
maximum number of rings
crosshair_thickness : float
thickness of crosshairs
crosshair_length : float
length of crosshairs
rotation : float
moire rotation about the origin.
Returns
-------
MoirePrimitive : :class:`gerbers.am_statements.AMMoirePrimitive`
An initialized AMMoirePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
position = (float(modifiers[1]), float(modifiers[2]))
diameter = float(modifiers[3])
ring_thickness = float(modifiers[4])
gap = float(modifiers[5])
max_rings = int(float(modifiers[6]))
crosshair_thickness = float(modifiers[7])
crosshair_length = float(modifiers[8])
rotation = float(modifiers[9])
return cls(code, position, diameter, ring_thickness, gap, max_rings, crosshair_thickness, crosshair_length, rotation)
def __init__(self, code, position, diameter, ring_thickness, gap, max_rings, crosshair_thickness, crosshair_length, rotation):
""" Initialize AMoirePrimitive
"""
if code != 6:
raise ValueError('MoirePrimitive code is 6')
super(AMMoirePrimitive, self).__init__(code, 'on')
validate_coordinates(position)
self.position = position
self.diameter = diameter
self.ring_thickness = ring_thickness
self.gap = gap
self.max_rings = max_rings
self.crosshair_thickness = crosshair_thickness
self.crosshair_length = crosshair_length
self.rotation = rotation
def to_inch(self):
self.position = tuple([inch(x) for x in self.position])
self.diameter = inch(self.diameter)
self.ring_thickness = inch(self.ring_thickness)
self.gap = inch(self.gap)
self.crosshair_thickness = inch(self.crosshair_thickness)
self.crosshair_length = inch(self.crosshair_length)
def to_metric(self):
self.position = tuple([metric(x) for x in self.position])
self.diameter = metric(self.diameter)
self.ring_thickness = metric(self.ring_thickness)
self.gap = metric(self.gap)
self.crosshair_thickness = metric(self.crosshair_thickness)
self.crosshair_length = metric(self.crosshair_length)
def to_gerber(self, settings=None):
data = dict(
code=self.code,
position="%.4g,%.4g" % self.position,
diameter=self.diameter,
ring_thickness=self.ring_thickness,
gap=self.gap,
max_rings=self.max_rings,
crosshair_thickness=self.crosshair_thickness,
crosshair_length=self.crosshair_length,
rotation=self.rotation
)
fmt = "{code},{position},{diameter},{ring_thickness},{gap},{max_rings},{crosshair_thickness},{crosshair_length},{rotation}*"
return fmt.format(**data)
def to_primitive(self, units):
#raise NotImplementedError()
return None
class AMThermalPrimitive(AMPrimitive):
""" Aperture Macro Thermal primitive. Code 7.
The thermal primitive is a ring (annulus) interrupted by four gaps.
Exposure is always on.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.10:** Thermal, primitive code 7.
Parameters
----------
code : int
Thermal Primitive code. Must be 7.
position : tuple (<float>, <float>)
X and Y coordinates of thermal center
outer_diameter : float
outer diameter of thermal.
inner_diameter : float
inner diameter of thermal.
gap : float
gap thickness
rotation : float
thermal rotation about the origin.
Returns
-------
ThermalPrimitive : :class:`gerbers.am_statements.AMThermalPrimitive`
An initialized AMThermalPrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
position = (float(modifiers[1]), float(modifiers[2]))
outer_diameter = float(modifiers[3])
inner_diameter = float(modifiers[4])
gap = float(modifiers[5])
rotation = float(modifiers[6])
return cls(code, position, outer_diameter, inner_diameter, gap, rotation)
def __init__(self, code, position, outer_diameter, inner_diameter, gap, rotation):
if code != 7:
raise ValueError('ThermalPrimitive code is 7')
super(AMThermalPrimitive, self).__init__(code, 'on')
validate_coordinates(position)
self.position = position
self.outer_diameter = outer_diameter
self.inner_diameter = inner_diameter
self.gap = gap
self.rotation = rotation
def to_inch(self):
self.position = tuple([inch(x) for x in self.position])
self.outer_diameter = inch(self.outer_diameter)
self.inner_diameter = inch(self.inner_diameter)
self.gap = inch(self.gap)
def to_metric(self):
self.position = tuple([metric(x) for x in self.position])
self.outer_diameter = metric(self.outer_diameter)
self.inner_diameter = metric(self.inner_diameter)
self.gap = metric(self.gap)
def to_gerber(self, settings=None):
data = dict(
code=self.code,
position="%.4g,%.4g" % self.position,
outer_diameter=self.outer_diameter,
inner_diameter=self.inner_diameter,
gap=self.gap,
rotation=self.rotation
)
fmt = "{code},{position},{outer_diameter},{inner_diameter},{gap},{rotation}*"
return fmt.format(**data)
def _approximate_arc_cw(self, start_angle, end_angle, radius, center):
"""
Get an arc as a series of points
Parameters
----------
start_angle : The start angle in radians
end_angle : The end angle in radians
radius`: Radius of the arc
center : The center point of the arc (x, y) tuple
Returns
-------
array of point tuples
"""
# The total sweep
sweep_angle = end_angle - start_angle
num_steps = 10
angle_step = sweep_angle / num_steps
radius = radius
center = center
points = []
for i in range(num_steps + 1):
current_angle = start_angle + (angle_step * i)
nextx = (center[0] + math.cos(current_angle) * radius)
nexty = (center[1] + math.sin(current_angle) * radius)
points.append((nextx, nexty))
return points
def to_primitive(self, units):
# We start with calculating the top right section, then duplicate it
inner_radius = self.inner_diameter / 2.0
outer_radius = self.outer_diameter / 2.0
# Calculate the start angle relative to the horizontal axis
inner_offset_angle = asin(self.gap / 2.0 / inner_radius)
outer_offset_angle = asin(self.gap / 2.0 / outer_radius)
rotation_rad = math.radians(self.rotation)
inner_start_angle = inner_offset_angle + rotation_rad
inner_end_angle = math.pi / 2 - inner_offset_angle + rotation_rad
outer_start_angle = outer_offset_angle + rotation_rad
outer_end_angle = math.pi / 2 - outer_offset_angle + rotation_rad
outlines = []
aperture = Circle((0, 0), 0)
points = (self._approximate_arc_cw(inner_start_angle, inner_end_angle, inner_radius, self.position)
+ list(reversed(self._approximate_arc_cw(outer_start_angle, outer_end_angle, outer_radius, self.position))))
# Add in the last point since outlines should be closed
points.append(points[0])
# There are four outlines at rotated sections
for rotation in [0, 90.0, 180.0, 270.0]:
lines = []
prev_point = rotate_point(points[0], rotation, self.position)
for point in points[1:]:
cur_point = rotate_point(point, rotation, self.position)
lines.append(Line(prev_point, cur_point, aperture))
prev_point = cur_point
outlines.append(Outline(lines, units=units, level_polarity=self._level_polarity))
return outlines
class AMCenterLinePrimitive(AMPrimitive):
""" Aperture Macro Center Line primitive. Code 21.
The center line primitive is a rectangle defined by its width, height, and center point.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.4:** Center Line, primitive code 21.
Parameters
----------
code : int
Center Line Primitive code. Must be 21.
exposure : str
'on' or 'off'
width : float
Width of rectangle
height : float
Height of rectangle
center : tuple (<float>, <float>)
X and Y coordinates of line center
rotation : float
rectangle rotation about its center.
Returns
-------
CenterLinePrimitive : :class:`gerbers.am_statements.AMCenterLinePrimitive`
An initialized AMCenterLinePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_primitive(cls, primitive):
width = primitive.width
height = primitive.height
center = primitive.position
rotation = math.degrees(primitive.rotation)
return cls(21, 'on', width, height, center, rotation)
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
exposure = 'on' if float(modifiers[1]) == 1 else 'off'
width = float(modifiers[2])
height = float(modifiers[3])
center = (float(modifiers[4]), float(modifiers[5]))
rotation = float(modifiers[6])
return cls(code, exposure, width, height, center, rotation)
def __init__(self, code, exposure, width, height, center, rotation):
if code != 21:
raise ValueError('CenterLinePrimitive code is 21')
super(AMCenterLinePrimitive, self).__init__(code, exposure)
self.width = width
self.height = height
validate_coordinates(center)
self.center = center
self.rotation = rotation
def to_inch(self):
self.center = tuple([inch(x) for x in self.center])
self.width = inch(self.width)
self.height = inch(self.height)
def to_metric(self):
self.center = tuple([metric(x) for x in self.center])
self.width = metric(self.width)
self.height = metric(self.height)
def to_gerber(self, settings=None):
data = dict(
code=self.code,
exposure = '1' if self.exposure == 'on' else '0',
width = self.width,
height = self.height,
center="%.4g,%.4g" % self.center,
rotation=self.rotation
)
fmt = "{code},{exposure},{width},{height},{center},{rotation}*"
return fmt.format(**data)
def to_primitive(self, units):
x = self.center[0]
y = self.center[1]
half_width = self.width / 2.0
half_height = self.height / 2.0
points = []
points.append((x - half_width, y + half_height))
points.append((x - half_width, y - half_height))
points.append((x + half_width, y - half_height))
points.append((x + half_width, y + half_height))
aperture = Circle((0, 0), 0)
lines = []
prev_point = rotate_point(points[3], self.rotation, self.center)
for point in points:
cur_point = rotate_point(point, self.rotation, self.center)
lines.append(Line(prev_point, cur_point, aperture))
return Outline(lines, units=units, level_polarity=self._level_polarity)
class AMLowerLeftLinePrimitive(AMPrimitive):
""" Aperture Macro Lower Left Line primitive. Code 22.
The lower left line primitive is a rectangle defined by its width, height, and the lower left point.
.. seealso::
`The Gerber File Format Specification <http://www.ucamco.com/files/downloads/file/81/the_gerber_file_format_specification.pdf>`_
**Section 4.12.3.5:** Lower Left Line, primitive code 22.
Parameters
----------
code : int
Center Line Primitive code. Must be 22.
exposure : str
'on' or 'off'
width : float
Width of rectangle
height : float
Height of rectangle
lower_left : tuple (<float>, <float>)
X and Y coordinates of lower left corner
rotation : float
rectangle rotation about its origin.
Returns
-------
LowerLeftLinePrimitive : :class:`gerbers.am_statements.AMLowerLeftLinePrimitive`
An initialized AMLowerLeftLinePrimitive
Raises
------
ValueError, TypeError
"""
@classmethod
def from_gerber(cls, primitive):
modifiers = primitive.strip(' *').split(",")
code = int(modifiers[0])
exposure = 'on' if float(modifiers[1]) == 1 else 'off'
width = float(modifiers[2])
height = float(modifiers[3])
lower_left = (float(modifiers[4]), float(modifiers[5]))
rotation = float(modifiers[6])
return cls(code, exposure, width, height, lower_left, rotation)
def __init__(self, code, exposure, width, height, lower_left, rotation):
if code != 22:
raise ValueError('LowerLeftLinePrimitive code is 22')
super (AMLowerLeftLinePrimitive, self).__init__(code, exposure)
self.width = width
self.height = height
validate_coordinates(lower_left)
self.lower_left = lower_left
self.rotation = rotation
def to_inch(self):
self.lower_left = tuple([inch(x) for x in self.lower_left])
self.width = inch(self.width)
self.height = inch(self.height)
def to_metric(self):
self.lower_left = tuple([metric(x) for x in self.lower_left])
self.width = metric(self.width)
self.height = metric(self.height)
def to_gerber(self, settings=None):
data = dict(
code=self.code,
exposure = '1' if self.exposure == 'on' else '0',
width = self.width,
height = self.height,
lower_left="%.4g,%.4g" % self.lower_left,
rotation=self.rotation
)
fmt = "{code},{exposure},{width},{height},{lower_left},{rotation}*"
return fmt.format(**data)
class AMUnsupportPrimitive(AMPrimitive):
@classmethod
def from_gerber(cls, primitive):
return cls(primitive)
def __init__(self, primitive):
super(AMUnsupportPrimitive, self).__init__(9999)
self.primitive = primitive
def to_inch(self):
pass
def to_metric(self):
pass
def to_gerber(self, settings=None):
return self.primitive
| [((798, 29, 798, 64), 'math.asin', 'asin', ({(798, 34, 798, 63): 'self.gap / 2.0 / inner_radius'}, {}), '(self.gap / 2.0 / inner_radius)', False, 'from math import asin\n'), ((799, 29, 799, 64), 'math.asin', 'asin', ({(799, 34, 799, 63): 'self.gap / 2.0 / outer_radius'}, {}), '(self.gap / 2.0 / outer_radius)', False, 'from math import asin\n'), ((801, 23, 801, 50), 'math.radians', 'math.radians', ({(801, 36, 801, 49): 'self.rotation'}, {}), '(self.rotation)', False, 'import math\n'), ((877, 19, 877, 51), 'math.degrees', 'math.degrees', ({(877, 32, 877, 50): 'primitive.rotation'}, {}), '(primitive.rotation)', False, 'import math\n'), ((550, 86, 550, 113), 'math.radians', 'math.radians', ({(550, 99, 550, 112): 'self.rotation'}, {}), '(self.rotation)', False, 'import math\n'), ((783, 33, 783, 56), 'math.cos', 'math.cos', ({(783, 42, 783, 55): 'current_angle'}, {}), '(current_angle)', False, 'import math\n'), ((784, 33, 784, 56), 'math.sin', 'math.sin', ({(784, 42, 784, 55): 'current_angle'}, {}), '(current_angle)', False, 'import math\n')] |
DeividVM/heroquest | heroquest/migrations/0002_auto_20160819_1747.py | c693d664717a849de645908ae78d62ec2a5837a5 | # -*- coding: utf-8 -*-
# Generated by Django 1.9.9 on 2016-08-19 17:47
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('heroquest', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='player',
name='armor',
),
migrations.AlterField(
model_name='player',
name='spell',
field=models.ManyToManyField(related_name='spells', to='armery.Spell', verbose_name='Hechizos'),
),
]
| [((15, 8, 18, 9), 'django.db.migrations.RemoveField', 'migrations.RemoveField', (), '', False, 'from django.db import migrations, models\n'), ((22, 18, 22, 107), 'django.db.models.ManyToManyField', 'models.ManyToManyField', (), '', False, 'from django.db import migrations, models\n')] |
epervago/dask | dask/array/utils.py | 958732ce6c51ef6af39db4727d948bfa66a0a8d6 | from distutils.version import LooseVersion
import difflib
import os
import numpy as np
from .core import Array
from ..async import get_sync
if LooseVersion(np.__version__) >= '1.10.0':
allclose = np.allclose
else:
def allclose(a, b, **kwargs):
if kwargs.pop('equal_nan', False):
a_nans = np.isnan(a)
b_nans = np.isnan(b)
if not (a_nans == b_nans).all():
return False
a = a[~a_nans]
b = b[~b_nans]
return np.allclose(a, b, **kwargs)
def _not_empty(x):
return x.shape and 0 not in x.shape
def _maybe_check_dtype(a, dtype=None):
# Only check dtype matches for non-empty
if _not_empty(a):
assert a.dtype == dtype
def assert_eq(a, b, **kwargs):
if isinstance(a, Array):
adt = a.dtype
a = a.compute(get=get_sync)
_maybe_check_dtype(a, adt)
else:
adt = getattr(a, 'dtype', None)
if isinstance(b, Array):
bdt = b.dtype
assert bdt is not None
b = b.compute(get=get_sync)
_maybe_check_dtype(b, bdt)
else:
bdt = getattr(b, 'dtype', None)
if str(adt) != str(bdt):
diff = difflib.ndiff(str(adt).splitlines(), str(bdt).splitlines())
raise AssertionError('string repr are different' + os.linesep +
os.linesep.join(diff))
try:
if _not_empty(a) and _not_empty(b):
# Treat all empty arrays as equivalent
assert a.shape == b.shape
assert allclose(a, b, **kwargs)
return
except TypeError:
pass
c = a == b
if isinstance(c, np.ndarray):
assert c.all()
else:
assert c
return True
| [] |
inniyah/launchpad-py | launchpad_py/__init__.py | b8dd4815b05d7e75ba5ca09ced64ddc38f515bad | # more specific selections for Python 3 (ASkr, 2/2018)
from launchpad_py.launchpad import Launchpad
from launchpad_py.launchpad import LaunchpadMk2
from launchpad_py.launchpad import LaunchpadPro
from launchpad_py.launchpad import LaunchControlXL
from launchpad_py.launchpad import LaunchKeyMini
from launchpad_py.launchpad import Dicer
from launchpad_py import charset
| [] |
EvoCargo/mono_depth | networks/adabins/utils.py | 3a77291a7fc8f3eaad5f93aa17e2b60c9339a0b1 | import base64
import math
import re
from io import BytesIO
import matplotlib.cm
import numpy as np
import torch
import torch.nn
from PIL import Image
# Compute edge magnitudes
from scipy import ndimage
class RunningAverage:
def __init__(self):
self.avg = 0
self.count = 0
def append(self, value):
self.avg = (value + self.count * self.avg) / (self.count + 1)
self.count += 1
def get_value(self):
return self.avg
def denormalize(x, device='cpu'):
mean = torch.Tensor([0.485, 0.456, 0.406]).view(1, 3, 1, 1).to(device)
std = torch.Tensor([0.229, 0.224, 0.225]).view(1, 3, 1, 1).to(device)
return x * std + mean
class RunningAverageDict:
def __init__(self):
self._dict = None
def update(self, new_dict):
if self._dict is None:
self._dict = dict()
for key, _ in new_dict.items():
self._dict[key] = RunningAverage()
for key, value in new_dict.items():
self._dict[key].append(value)
def get_value(self):
return {key: value.get_value() for key, value in self._dict.items()}
def colorize(value, vmin=10, vmax=1000, cmap='magma_r'):
value = value.cpu().numpy()[0, :, :]
invalid_mask = value == -1
# normalize
vmin = value.min() if vmin is None else vmin
vmax = value.max() if vmax is None else vmax
if vmin != vmax:
value = (value - vmin) / (vmax - vmin) # vmin..vmax
else:
# Avoid 0-division
value = value * 0.0
# squeeze last dim if it exists
# value = value.squeeze(axis=0)
cmapper = matplotlib.cm.get_cmap(cmap)
value = cmapper(value, bytes=True) # (nxmx4)
value[invalid_mask] = 255
img = value[:, :, :3]
# return img.transpose((2, 0, 1))
return img
def count_parameters(model):
return sum(p.numel() for p in model.parameters() if p.requires_grad)
def compute_errors(gt, pred):
thresh = np.maximum((gt / pred), (pred / gt))
a1 = (thresh < 1.25).mean()
a2 = (thresh < 1.25 ** 2).mean()
a3 = (thresh < 1.25 ** 3).mean()
abs_rel = np.mean(np.abs(gt - pred) / gt)
sq_rel = np.mean(((gt - pred) ** 2) / gt)
rmse = (gt - pred) ** 2
rmse = np.sqrt(rmse.mean())
rmse_log = (np.log(gt) - np.log(pred)) ** 2
rmse_log = np.sqrt(rmse_log.mean())
err = np.log(pred) - np.log(gt)
silog = np.sqrt(np.mean(err ** 2) - np.mean(err) ** 2) * 100
log_10 = (np.abs(np.log10(gt) - np.log10(pred))).mean()
return dict(
a1=a1,
a2=a2,
a3=a3,
abs_rel=abs_rel,
rmse=rmse,
log_10=log_10,
rmse_log=rmse_log,
silog=silog,
sq_rel=sq_rel,
)
# Demo Utilities
def b64_to_pil(b64string):
image_data = re.sub('^data:image/.+;base64,', '', b64string)
# image = Image.open(cStringIO.StringIO(image_data))
return Image.open(BytesIO(base64.b64decode(image_data)))
def edges(d):
dx = ndimage.sobel(d, 0) # horizontal derivative
dy = ndimage.sobel(d, 1) # vertical derivative
return np.abs(dx) + np.abs(dy)
class PointCloudHelper:
def __init__(self, width=640, height=480):
self.xx, self.yy = self.worldCoords(width, height)
def worldCoords(self, width=640, height=480):
hfov_degrees, vfov_degrees = 57, 43
hFov = math.radians(hfov_degrees)
vFov = math.radians(vfov_degrees)
cx, cy = width / 2, height / 2
fx = width / (2 * math.tan(hFov / 2))
fy = height / (2 * math.tan(vFov / 2))
xx, yy = np.tile(range(width), height), np.repeat(range(height), width)
xx = (xx - cx) / fx
yy = (yy - cy) / fy
return xx, yy
def depth_to_points(self, depth):
depth[edges(depth) > 0.3] = np.nan # Hide depth edges
length = depth.shape[0] * depth.shape[1]
# depth[edges(depth) > 0.3] = 1e6 # Hide depth edges
z = depth.reshape(length)
return np.dstack((self.xx * z, self.yy * z, z)).reshape((length, 3))
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simbilod/gdsfactory | gdsfactory/types.py | 4d76db32674c3edb4d16260e3177ee29ef9ce11d | """In programming, a factory is a function that returns an object.
Functions are easy to understand because they have clear inputs and outputs.
Most gdsfactory functions take some inputs and return a Component object.
Some of these inputs parameters are also functions.
- Component: Object with.
- name.
- references: to other components (x, y, rotation).
- polygons in different layers.
- ports dict.
- Route: dataclass with 3 attributes.
- references: list of references (straights, bends and tapers).
- ports: dict(input=PortIn, output=PortOut).
- length: how long is this route?
Factories:
- ComponentFactory: function that returns a Component.
- RouteFactory: function that returns a Route.
Specs:
- ComponentSpec: Component, ComponentFactory or dict(component=mzi, settings=dict(delta_length=20)).
- LayerSpec: (3, 0), 3 (asumes 0 as datatype) or string.
"""
import json
import pathlib
from typing import Any, Callable, Dict, List, NewType, Optional, Tuple, Union
import numpy as np
from omegaconf import OmegaConf
from phidl.device_layout import Label as LabelPhidl
from phidl.device_layout import Path
from pydantic import BaseModel, Extra
from typing_extensions import Literal
from gdsfactory.component import Component, ComponentReference
from gdsfactory.cross_section import CrossSection
from gdsfactory.port import Port
Anchor = Literal[
"ce",
"cw",
"nc",
"ne",
"nw",
"sc",
"se",
"sw",
"center",
"cc",
]
Axis = Literal["x", "y"]
NSEW = Literal["N", "S", "E", "W"]
class Label(LabelPhidl):
@classmethod
def __get_validators__(cls):
yield cls.validate
@classmethod
def validate(cls, v):
"""check with pydantic Label valid type"""
assert isinstance(v, LabelPhidl), f"TypeError, Got {type(v)}, expecting Label"
return v
Float2 = Tuple[float, float]
Float3 = Tuple[float, float, float]
Floats = Tuple[float, ...]
Strs = Tuple[str, ...]
Int2 = Tuple[int, int]
Int3 = Tuple[int, int, int]
Ints = Tuple[int, ...]
Layer = Tuple[int, int]
Layers = Tuple[Layer, ...]
LayerSpec = NewType("LayerSpec", Union[Layer, int, str, None])
LayerSpecs = Tuple[LayerSpec, ...]
ComponentFactory = Callable[..., Component]
ComponentFactoryDict = Dict[str, ComponentFactory]
PathFactory = Callable[..., Path]
PathType = Union[str, pathlib.Path]
PathTypes = Tuple[PathType, ...]
ComponentOrPath = Union[PathType, Component]
ComponentOrReference = Union[Component, ComponentReference]
NameToFunctionDict = Dict[str, ComponentFactory]
Number = Union[float, int]
Coordinate = Tuple[float, float]
Coordinates = Tuple[Coordinate, ...]
ComponentOrPath = Union[Component, PathType]
CrossSectionFactory = Callable[..., CrossSection]
CrossSectionOrFactory = Union[CrossSection, Callable[..., CrossSection]]
PortSymmetries = Dict[str, Dict[str, List[str]]]
PortsDict = Dict[str, Port]
PortsList = Dict[str, Port]
ComponentSpec = NewType(
"ComponentSpec", Union[str, ComponentFactory, Component, Dict[str, Any]]
)
ComponentSpecOrList = Union[ComponentSpec, List[ComponentSpec]]
CellSpec = Union[str, ComponentFactory, Dict[str, Any]]
ComponentSpecDict = Dict[str, ComponentSpec]
CrossSectionSpec = NewType(
"CrossSectionSpec", Union[str, CrossSectionFactory, CrossSection, Dict[str, Any]]
)
MultiCrossSectionAngleSpec = List[Tuple[CrossSectionSpec, Tuple[int, ...]]]
class Route(BaseModel):
references: List[ComponentReference]
labels: Optional[List[Label]] = None
ports: Tuple[Port, Port]
length: float
class Config:
extra = Extra.forbid
class Routes(BaseModel):
references: List[ComponentReference]
lengths: List[float]
ports: Optional[List[Port]] = None
bend_radius: Optional[List[float]] = None
class Config:
extra = Extra.forbid
class ComponentModel(BaseModel):
component: Union[str, Dict[str, Any]]
settings: Optional[Dict[str, Any]]
class Config:
extra = Extra.forbid
class PlacementModel(BaseModel):
x: Union[str, float] = 0
y: Union[str, float] = 0
xmin: Optional[Union[str, float]] = None
ymin: Optional[Union[str, float]] = None
xmax: Optional[Union[str, float]] = None
ymax: Optional[Union[str, float]] = None
dx: float = 0
dy: float = 0
port: Optional[Union[str, Anchor]] = None
rotation: int = 0
mirror: bool = False
class Config:
extra = Extra.forbid
class RouteModel(BaseModel):
links: Dict[str, str]
settings: Optional[Dict[str, Any]] = None
routing_strategy: Optional[str] = None
class Config:
extra = Extra.forbid
class NetlistModel(BaseModel):
"""Netlist defined component.
Attributes:
instances: dict of instances (name, settings, component).
placements: dict of placements.
connections: dict of connections.
routes: dict of routes.
name: component name.
info: information (polarization, wavelength ...).
settings: input variables.
pdk: pdk module name.
ports: exposed component ports.
"""
instances: Dict[str, ComponentModel]
placements: Optional[Dict[str, PlacementModel]] = None
connections: Optional[List[Dict[str, str]]] = None
routes: Optional[Dict[str, RouteModel]] = None
name: Optional[str] = None
info: Optional[Dict[str, Any]] = None
settings: Optional[Dict[str, Any]] = None
pdk: Optional[str] = None
ports: Optional[Dict[str, str]] = None
class Config:
extra = Extra.forbid
# factory: Dict[str, ComponentFactory] = {}
# def add_instance(self, name: str, component: str, **settings) -> None:
# assert component in self.factory.keys()
# component_model = ComponentModel(component=component, settings=settings)
# self.instances[name] = component_model
# def add_route(self, port1: Port, port2: Port, **settings) -> None:
# self.routes = component_model
RouteFactory = Callable[..., Route]
class TypedArray(np.ndarray):
"""based on https://github.com/samuelcolvin/pydantic/issues/380"""
@classmethod
def __get_validators__(cls):
yield cls.validate_type
@classmethod
def validate_type(cls, val):
return np.array(val, dtype=cls.inner_type)
class ArrayMeta(type):
def __getitem__(self, t):
return type("Array", (TypedArray,), {"inner_type": t})
class Array(np.ndarray, metaclass=ArrayMeta):
pass
__all__ = (
"ComponentFactory",
"ComponentFactoryDict",
"ComponentSpec",
"ComponentOrPath",
"ComponentOrReference",
"Coordinate",
"Coordinates",
"CrossSectionFactory",
"CrossSectionOrFactory",
"MultiCrossSectionAngleSpec",
"Float2",
"Float3",
"Floats",
"Int2",
"Int3",
"Ints",
"Layer",
"Layers",
"NameToFunctionDict",
"Number",
"PathType",
"PathTypes",
"Route",
"RouteFactory",
"Routes",
"Strs",
)
def write_schema(model: BaseModel = NetlistModel) -> None:
s = model.schema_json()
d = OmegaConf.create(s)
dirpath = pathlib.Path(__file__).parent / "schemas"
f1 = dirpath / "netlist.yaml"
f1.write_text(OmegaConf.to_yaml(d))
f2 = dirpath / "netlist.json"
f2.write_text(json.dumps(OmegaConf.to_container(d)))
if __name__ == "__main__":
write_schema()
import jsonschema
import yaml
from gdsfactory.config import CONFIG
schema_path = CONFIG["schema_netlist"]
schema_dict = json.loads(schema_path.read_text())
yaml_text = """
name: mzi
pdk: ubcpdk
settings:
dy: -90
info:
polarization: te
wavelength: 1.55
description: mzi for ubcpdk
instances:
yr:
component: y_splitter
yl:
component: y_splitter
placements:
yr:
rotation: 180
x: 100
y: 0
routes:
route_top:
links:
yl,opt2: yr,opt3
settings:
cross_section: strip
route_bot:
links:
yl,opt3: yr,opt2
routing_strategy: get_bundle_from_steps
settings:
steps: [dx: 30, dy: '${settings.dy}', dx: 20]
cross_section: strip
ports:
o1: yl,opt1
o2: yr,opt1
"""
yaml_dict = yaml.safe_load(yaml_text)
jsonschema.validate(yaml_dict, schema_dict)
# from gdsfactory.components import factory
# c = NetlistModel(factory=factory)
# c.add_instance("mmi1", "mmi1x2", length=13.3)
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ahmetdaglarbas/e-commerce | tests/_site/myauth/models.py | ff190244ccd422b4e08d7672f50709edcbb6ebba | # -*- coding: utf-8 -*-
# Code will only work with Django >= 1.5. See tests/config.py
import re
from django.utils.translation import ugettext_lazy as _
from django.db import models
from django.core import validators
from django.contrib.auth.models import BaseUserManager
from oscar.apps.customer.abstract_models import AbstractUser
class CustomUserManager(BaseUserManager):
def create_user(self, username, email, password):
"""
Creates and saves a User with the given email and password.
"""
if not email:
raise ValueError('Users must have an email address')
user = self.model(
email=CustomUserManager.normalize_email(email),
username=username,
is_active=True,
)
user.set_password(password)
user.save(using=self._db)
return user
def create_superuser(self, username, email, password):
u = self.create_user(username, email, password=password)
u.is_admin = True
u.is_staff = True
u.save(using=self._db)
return u
class User(AbstractUser):
"""
Custom user based on Oscar's AbstractUser
"""
username = models.CharField(_('username'), max_length=30, unique=True,
help_text=_('Required. 30 characters or fewer. Letters, numbers and '
'@/./+/-/_ characters'),
validators=[
validators.RegexValidator(re.compile('^[\w.@+-]+$'), _('Enter a valid username.'), 'invalid')
])
extra_field = models.CharField(
_('Nobody needs me'), max_length=5, blank=True)
objects = CustomUserManager()
class Meta:
app_label = 'myauth'
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brouwa/CNNs-on-FPSPs | 5 - FC layers retraining/4 - FC weights to C++ code/weights_pck_to_cpp_unrolled_loop.py | 71bcc2335e6d71ad21ba66e04a651d4db218356d | import pickle
import numpy as np
INPUT_FILENAME = 'NP_WEIGHTS.pck'
PRECISION = 100
# Open weights
fc1_k, fc1_b, fc2_k, fc2_b = pickle.load(
open(INPUT_FILENAME, 'rb'))
# Round them
fc1_k, fc1_b, fc2_k, fc2_b = fc1_k*PRECISION//1, fc1_b*PRECISION//1, fc2_k*PRECISION//1, fc2_b*PRECISION*PRECISION//1
fc1_k, fc1_b, fc2_k, fc2_b = fc1_k.astype(np.int), fc1_b.astype(np.int), fc2_k.astype(np.int), fc2_b.astype(np.int)
"""
0: GENERATE C++ ARRAYS, TO BE USED IN A STANDARD LOOP
"""
OUTPUT_FILENAME = 'fc_weights_arrays.cpp'
def to_cpp_1_dim(array):
txt = '{\t'
for coeff in array[:-1]:
txt += str(coeff) + ',\t'
txt += str(array[-1]) + '}'
return txt
def to_cpp_2_dims(array):
txt = '{'
for line in array[:-1]:
txt += to_cpp_1_dim(line) + ',\n'
txt += to_cpp_1_dim(array[-1]) + '}'
return txt
# Generate .cpp text
out = 'int fc1_k[' + str(fc1_k.shape[0]) + '][' + str(fc1_k.shape[1]) + '] = '
out += to_cpp_2_dims(fc1_k) + ';\n\n'
out += 'int fc1_b[' + str(fc1_b.shape[0]) + '] = '
out += to_cpp_1_dim(fc1_b) + ';\n\n'
out += 'int fc2_k[' + str(fc2_k.shape[0]) + '][' + str(fc2_k.shape[1]) + '] = '
out += to_cpp_2_dims(fc2_k) + ';\n\n'
out += 'int fc2_b[' + str(fc2_b.shape[0]) + '] = '
out += to_cpp_1_dim(fc2_b) + ';\n\n'
# Output it
with open(OUTPUT_FILENAME, 'w+', encoding='utf-8') as f:
f.write(out)
"""
1: GENERATE C++ LOOP, USING THE ABOVE ARRAY
"""
OUTPUT_FILENAME = 'fc_loop_unrolled.cpp'
def to_cpp_function(k, b, function_name, in_dim, out_dim):
"""
Generates C++ code for computing a fully connected layer of int values,
applying weights k and bias b, with hardcoded values in the source code.
The function is names after function_name.
"""
out = ""
out += "inline void "+function_name+"(int in["+str(in_dim)+"], int out["+str(out_dim)+"]){\n"
for j in range(out_dim):
out += "\tout["+str(j)+"] = \n"
for i in range(in_dim):
out += "\t\tin["+str(i)+"]*("+k+"["+str(i)+"]["+str(j)+"]) +\n"
out += "\t\t("+b+"["+str(j)+"]);\n"
out += "}\n\n"
return out
## Generate .cpp text
out = ""
# First layer
out += to_cpp_function('fc1_k', 'fc1_b', 'fc_1', 27, 50)
# Second layer
out += to_cpp_function('fc2_k', 'fc2_b', 'fc_2', 50, 10)
# Output it
with open(OUTPUT_FILENAME, 'w+', encoding='utf-8') as f:
f.write(out)
"""
3: GENERATE C++ LOOP, WITH HARDCODED WEIGHTS
"""
OUTPUT_FILENAME = 'fc_loop_unrolled_hardcoded_weights.cpp'
def to_cpp_function(k, b, function_name):
"""
Generates C++ code for computing a fully connected layer of int values,
applying weights k and bias b, with hardcoded values in the source code.
The function is names after function_name.
"""
out = ""
(in_dim, out_dim) = k.shape
out += "inline void "+function_name+"(int in["+str(in_dim)+"], int out["+str(out_dim)+"]){\n"
for j in range(out_dim):
out += "\tout["+str(j)+"] = \n"
for i in range(in_dim):
out += "\t\tin["+str(i)+"]*("+str(k[i][j])+") +\n"
out += "\t\t("+str(b[j])+");\n"
out += "}\n\n"
return out
## Generate .cpp text
out = ""
# First layer
out += to_cpp_function(fc1_k, fc1_b, 'fc_1')
# Second layer
out += to_cpp_function(fc2_k, fc2_b, 'fc_2')
# Output it
with open(OUTPUT_FILENAME, 'w+', encoding='utf-8') as f:
f.write(out)
| [] |
yubaoliu/Computer-Vision | python/Canny_EdgeDetection.py | 2fe4d3e1db0a65ef8c9def5f84d5e494bec3faa9 |
import cv2
import numpy as np
import random
img = cv2.imread('../../Assets/Images/flower-white.jpeg', 1)
imgInfo = img.shape
height = imgInfo[0]
width = imgInfo[1]
cv2.imshow('img', img)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgG = cv2.GaussianBlur(gray, (3, 3), 0)
dst = cv2.Canny(img, 50, 50)
cv2.imshow('dst', dst)
cv2.waitKey(0) | [((6, 6, 6, 60), 'cv2.imread', 'cv2.imread', ({(6, 17, 6, 56): '"""../../Assets/Images/flower-white.jpeg"""', (6, 58, 6, 59): '1'}, {}), "('../../Assets/Images/flower-white.jpeg', 1)", False, 'import cv2\n'), ((12, 0, 12, 22), 'cv2.imshow', 'cv2.imshow', ({(12, 11, 12, 16): '"""img"""', (12, 18, 12, 21): 'img'}, {}), "('img', img)", False, 'import cv2\n'), ((14, 7, 14, 44), 'cv2.cvtColor', 'cv2.cvtColor', ({(14, 20, 14, 23): 'img', (14, 25, 14, 43): 'cv2.COLOR_BGR2GRAY'}, {}), '(img, cv2.COLOR_BGR2GRAY)', False, 'import cv2\n'), ((16, 7, 16, 40), 'cv2.GaussianBlur', 'cv2.GaussianBlur', ({(16, 24, 16, 28): 'gray', (16, 30, 16, 36): '(3, 3)', (16, 38, 16, 39): '0'}, {}), '(gray, (3, 3), 0)', False, 'import cv2\n'), ((17, 6, 17, 28), 'cv2.Canny', 'cv2.Canny', ({(17, 16, 17, 19): 'img', (17, 21, 17, 23): '50', (17, 25, 17, 27): '50'}, {}), '(img, 50, 50)', False, 'import cv2\n'), ((19, 0, 19, 22), 'cv2.imshow', 'cv2.imshow', ({(19, 11, 19, 16): '"""dst"""', (19, 18, 19, 21): 'dst'}, {}), "('dst', dst)", False, 'import cv2\n'), ((20, 0, 20, 14), 'cv2.waitKey', 'cv2.waitKey', ({(20, 12, 20, 13): '(0)'}, {}), '(0)', False, 'import cv2\n')] |
Guoxs/DODT | avod/core/trainer_stride.py | f354cda6ef08465018fdeec1a8b4be4002e6a71f | """Detection model trainer.
This file provides a generic training method to train a
DetectionModel.
"""
import datetime
import os
import tensorflow as tf
import time
from avod.builders import optimizer_builder
from avod.core import trainer_utils
from avod.core import summary_utils
slim = tf.contrib.slim
def train(model, train_config):
"""Training function for detection models.
Args:
model: The detection model object.
train_config: a train_*pb2 protobuf.
training i.e. loading RPN weights onto AVOD model.
"""
model = model
train_config = train_config
# Get model configurations
model_config = model.model_config
# Create a variable tensor to hold the global step
global_step_tensor = tf.Variable(
0, trainable=False, name='global_step')
#############################
# Get training configurations
#############################
max_iterations = train_config.max_iterations
summary_interval = train_config.summary_interval
checkpoint_interval = train_config.checkpoint_interval
max_checkpoints = train_config.max_checkpoints_to_keep
paths_config = model_config.paths_config
logdir = paths_config.logdir
if not os.path.exists(logdir):
os.makedirs(logdir)
checkpoint_dir = paths_config.checkpoint_dir
if not os.path.exists(checkpoint_dir):
os.makedirs(checkpoint_dir)
checkpoint_path = checkpoint_dir + '/' + \
model_config.checkpoint_name
pretrained_checkpoint_dir = checkpoint_dir + '/../../' + \
'pyramid_cars_with_aug_dt_5_tracking_corr_pretrained/checkpoints'
global_summaries = set([])
# The model should return a dictionary of predictions
prediction_dict = model.build()
summary_histograms = train_config.summary_histograms
summary_img_images = train_config.summary_img_images
summary_bev_images = train_config.summary_bev_images
# get variables to train
if not train_config.use_pretrained_model:
variable_to_train = None
else:
trainable_variables = tf.trainable_variables()
variable_to_train = trainable_variables[68:72] + \
trainable_variables[96:]
##############################
# Setup loss
##############################
losses_dict, total_loss = model.loss(prediction_dict)
# Optimizer
training_optimizer = optimizer_builder.build(
train_config.optimizer,
global_summaries,
global_step_tensor)
# Create the train op
with tf.variable_scope('train_op'):
train_op = slim.learning.create_train_op(
total_loss,
training_optimizer,
variables_to_train=variable_to_train,
clip_gradient_norm=1.0,
global_step=global_step_tensor)
# Add the result of the train_op to the summary
tf.summary.scalar("training_loss", train_op)
# Add maximum memory usage summary op
# This op can only be run on device with gpu
# so it's skipped on travis
is_travis = 'TRAVIS' in os.environ
if not is_travis:
# tf.summary.scalar('bytes_in_use',
# tf.contrib.memory_stats.BytesInUse())
tf.summary.scalar('max_bytes',
tf.contrib.memory_stats.MaxBytesInUse())
summaries = set(tf.get_collection(tf.GraphKeys.SUMMARIES))
summary_merged = summary_utils.summaries_to_keep(
summaries,
global_summaries,
histograms=summary_histograms,
input_imgs=summary_img_images,
input_bevs=summary_bev_images
)
allow_gpu_mem_growth = train_config.allow_gpu_mem_growth
if allow_gpu_mem_growth:
# GPU memory config
config = tf.ConfigProto()
config.gpu_options.allow_growth = allow_gpu_mem_growth
sess = tf.Session(config=config)
else:
sess = tf.Session()
# Create unique folder name using datetime for summary writer
datetime_str = str(datetime.datetime.now())
logdir = logdir + '/train'
train_writer = tf.summary.FileWriter(logdir + '/' + datetime_str,
sess.graph)
# Save checkpoints regularly.
saver = tf.train.Saver(max_to_keep=max_checkpoints, pad_step_number=True)
# Create init op
# if train_config.use_pretrained_model:
# init = tf.initialize_variables(variable_to_train)
# else:
# init = tf.global_variables_initializer()
init = tf.global_variables_initializer()
# Continue from last saved checkpoint
if not train_config.overwrite_checkpoints:
trainer_utils.load_checkpoints(checkpoint_dir,saver)
if len(saver.last_checkpoints) > 0:
checkpoint_to_restore = saver.last_checkpoints[-1]
saver.restore(sess, checkpoint_to_restore)
else:
sess.run(init)
# load pretrained model
if train_config.use_pretrained_model:
variable_to_restore = tf.trainable_variables()
variable_to_restore = variable_to_restore[:68] + \
variable_to_restore[72:96]
variable_to_restore = {var.op.name: var for var in variable_to_restore}
saver2 = tf.train.Saver(var_list=variable_to_restore)
print('Loading pretrained model...')
trainer_utils.load_checkpoints(pretrained_checkpoint_dir, saver2)
checkpoint_to_restore = saver2.last_checkpoints[11]
saver2.restore(sess, checkpoint_to_restore)
else:
sess.run(init)
# load pretrained model
if train_config.use_pretrained_model:
variable_to_restore = tf.trainable_variables()
variable_to_restore = variable_to_restore[:68] + \
variable_to_restore[72:96]
variable_to_restore = {var.op.name: var for var in variable_to_restore}
saver2 = tf.train.Saver(var_list=variable_to_restore)
print('Loading pretrained model...')
trainer_utils.load_checkpoints(pretrained_checkpoint_dir, saver2)
checkpoint_to_restore = saver2.last_checkpoints[11]
saver2.restore(sess, checkpoint_to_restore)
# Read the global step if restored
global_step = tf.train.global_step(sess, global_step_tensor)
print('Starting from step {} / {}'.format(
global_step, max_iterations))
# Main Training Loop
last_time = time.time()
for step in range(global_step, max_iterations + 1):
# Save checkpoint
if step % checkpoint_interval == 0:
global_step = tf.train.global_step(sess,
global_step_tensor)
saver.save(sess,
save_path=checkpoint_path,
global_step=global_step)
print('Step {} / {}, Checkpoint saved to {}-{:08d}'.format(
step, max_iterations,
checkpoint_path, global_step))
feed_dict = model.create_feed_dict()
# Write summaries and train op
if step % summary_interval == 0:
current_time = time.time()
time_elapsed = current_time - last_time
last_time = current_time
train_op_loss, summary_out = sess.run(
[train_op, summary_merged], feed_dict=feed_dict)
print('Step {}, Total Loss {:0.3f}, Time Elapsed {:0.3f} s'.format(
step, train_op_loss, time_elapsed))
train_writer.add_summary(summary_out, step)
else:
# Run the train op only
sess.run(train_op, feed_dict)
# Close the summary writers
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nickc92/django-rest-framework-hmac | rest_framework_hmac/hmac_key/models.py | c32e37cf00ef0c13957a6e02eb0a7fabac3d1ac1 | import binascii
import os
from django.conf import settings
from django.db import models
from django.utils.translation import ugettext_lazy as _
class HMACKey(models.Model):
"""
The default HMACKey model that can auto generate a
key/secret for HMAC Auth via a signal
"""
def generate_key():
"""
Returns a 40 character hex string based on binary random data
"""
return binascii.hexlify(os.urandom(20)).decode()
key = models.CharField(
_("Key"), primary_key=True, max_length=40, default=generate_key)
secret = models.CharField(
_("Secret"), max_length=40, default=generate_key)
user = models.OneToOneField(
settings.AUTH_USER_MODEL, related_name='hmac_key',
on_delete=models.CASCADE, verbose_name=_("User")
)
nonce = models.BigIntegerField(default=1)
created = models.DateTimeField(_("Created"), auto_now_add=True)
class Meta:
# Only create a DB table for this Model if this app is registered
abstract = 'rest_framework_hmac.hmac_key' \
not in settings.INSTALLED_APPS
verbose_name = _("HMACKey")
verbose_name_plural = _("HMACKey")
def __str__(self):
return self.key
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Geoiv/river | test/conftest.py | d013985145c09f263172b054819e811689002ae9 | import os
from tempfile import NamedTemporaryFile
import boto3
from moto import mock_s3
import pandas as pd
import pandavro as pdx
import pickle
import pytest
@pytest.fixture(autouse=True, scope='session')
def aws_credentials():
"""
Sets AWS credentials to invalid values. Applied to all test functions and
scoped to the entire testing session, so there's no chance of interfering
with production buckets.
"""
os.environ['AWS_ACCESS_KEY_ID'] = 'testing'
os.environ['AWS_SECRET_ACCESS_KEY'] = 'testing'
os.environ['AWS_SECURITY_TOKEN'] = 'testing'
os.environ['AWS_SESSION_TOKEN'] = 'testing'
@pytest.fixture
def test_bucket():
"""Universal bucket name for use throughout testing"""
return 'test_bucket'
@pytest.fixture
def test_keys():
"""List of keys to be used for populating a bucket with empty objects"""
return sorted([
'test_key_0.csv',
'folder0/test_key_1.pq',
'folder1/test_key_2.pkl',
'folder1/subfolder0/test_key_3.pkl',
'folder2/'
])
@pytest.fixture
def test_df_keys():
"""List of keys to be used for populating a bucket with DataFrames"""
return {
'avro': ['df.avro'],
'csv': ['df.csv'],
'csv.gz': ['df.csv.gz'],
'csv.zip': ['df.csv.zip'],
'csv.bz2': ['df.csv.bz2'],
'csv.xz': ['df.csv.xz'],
'psv': ['df.psv'],
'psv.gz': ['df.psv.gz'],
'psv.zip': ['df.psv.zip'],
'psv.bz2': ['df.psv.bz2'],
'psv.xz': ['df.psv.xz'],
'feather': ['df.feather'],
'json': ['df.json'],
'pkl': ['df.pkl', 'df.pickle'],
'pq': ['df.pq', 'df.parquet']
}
@pytest.fixture
def test_df():
"""
Universal dataframe for use throughout testing. Multiple data types
used to test for proper encoding/decoding.
"""
return pd.DataFrame({
'intcol': [1, 2, 3],
'strcol': ['four', 'five', 'six'],
'floatcol': [7.0, 8.5, 9.0]
})
@pytest.fixture
def mock_s3_client():
"""Mocks all s3 connections in any test or fixture that includes it"""
with mock_s3():
yield
@pytest.fixture
def setup_bucket_w_contents(mock_s3_client, test_bucket, test_keys):
"""
Sets up a bucket with objects containing the empty string, based off
keys in 'test_keys'
"""
s3 = boto3.client('s3')
s3.create_bucket(Bucket=test_bucket)
for key in test_keys:
s3.put_object(Bucket=test_bucket, Key=key, Body='')
yield
@pytest.fixture
def setup_bucket_wo_contents(mock_s3_client, test_bucket):
"""Sets up a bucket with no contents."""
s3 = boto3.client('s3')
s3.create_bucket(Bucket=test_bucket)
yield
@pytest.fixture
def setup_bucket_w_dfs(mock_s3_client, test_bucket, test_df, test_df_keys):
"""
Sets up a bucket populated with dataframes that contain the data as
defined in 'test_df', at the keys and storage formats defined in
'test_df_keys'
"""
s3 = boto3.client('s3')
s3.create_bucket(Bucket=test_bucket)
for key in test_df_keys['avro']:
with NamedTemporaryFile() as tmpfile:
pdx.to_avro(tmpfile, test_df)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['csv']:
with NamedTemporaryFile() as tmpfile:
test_df.to_csv(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['csv.gz']:
with NamedTemporaryFile(suffix='.csv.gz') as tmpfile:
test_df.to_csv(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['csv.zip']:
with NamedTemporaryFile(suffix='.csv.zip') as tmpfile:
test_df.to_csv(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['csv.bz2']:
with NamedTemporaryFile(suffix='.csv.bz2') as tmpfile:
test_df.to_csv(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['csv.xz']:
with NamedTemporaryFile(suffix='.csv.xz') as tmpfile:
test_df.to_csv(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['psv']:
with NamedTemporaryFile() as tmpfile:
test_df.to_csv(tmpfile.name, index=False, sep='|')
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['psv.gz']:
with NamedTemporaryFile(suffix='.psv.gz') as tmpfile:
test_df.to_csv(tmpfile.name, index=False, sep='|')
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['psv.zip']:
with NamedTemporaryFile(suffix='.psv.zip') as tmpfile:
test_df.to_csv(tmpfile.name, index=False, sep='|')
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['psv.bz2']:
with NamedTemporaryFile(suffix='.psv.bz2') as tmpfile:
test_df.to_csv(tmpfile.name, index=False, sep='|')
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['psv.xz']:
with NamedTemporaryFile(suffix='.psv.xz') as tmpfile:
test_df.to_csv(tmpfile.name, index=False, sep='|')
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['feather']:
with NamedTemporaryFile() as tmpfile:
test_df.to_feather(tmpfile.name)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['json']:
with NamedTemporaryFile() as tmpfile:
test_df.to_json(tmpfile.name)
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['pkl']:
with NamedTemporaryFile() as tmpfile:
pickle.dump(test_df, tmpfile, protocol=pickle.HIGHEST_PROTOCOL)
tmpfile.flush()
s3.upload_file(tmpfile.name, test_bucket, key)
for key in test_df_keys['pq']:
with NamedTemporaryFile() as tmpfile:
test_df.to_parquet(tmpfile.name, index=False)
s3.upload_file(tmpfile.name, test_bucket, key)
yield
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uktrade/directory-api | company/migrations/0021_auto_20161208_1113.py | 45a9024a7ecc2842895201cbb51420ba9e57a168 | # -*- coding: utf-8 -*-
# Generated by Django 1.9.10 on 2016-12-08 11:13
from __future__ import unicode_literals
from django.db import migrations
from company import helpers
def ensure_verification_code(apps, schema_editor):
Company = apps.get_model("company", "Company")
for company in Company.objects.filter(verification_code=''):
company.verification_code = helpers.generate_verification_code()
company.save()
class Migration(migrations.Migration):
dependencies = [
('company', '0020_auto_20161208_1056'),
]
operations = [
migrations.RunPython(ensure_verification_code),
]
| [((13, 36, 13, 72), 'company.helpers.generate_verification_code', 'helpers.generate_verification_code', ({}, {}), '()', False, 'from company import helpers\n'), ((25, 8, 25, 54), 'django.db.migrations.RunPython', 'migrations.RunPython', ({(25, 29, 25, 53): 'ensure_verification_code'}, {}), '(ensure_verification_code)', False, 'from django.db import migrations\n')] |
Toktar/indy-test-automation | system/indy-node-tests/TestAuthMapSuite.py | 4d583dda7cbf2a9f451b3a01312a90e55c7bacc8 | import pytest
import asyncio
from system.utils import *
from random import randrange as rr
import hashlib
import time
from datetime import datetime, timedelta, timezone
from indy import payment
import logging
logger = logging.getLogger(__name__)
@pytest.mark.usefixtures('docker_setup_and_teardown')
class TestAuthMapSuite:
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_nym(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
new_did, new_vk = await did.create_and_store_my_did(wallet_handler, '{}')
# add adder to add nym
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
# add editor to edit nym
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
req = await ledger.build_auth_rule_request(trustee_did, '1', 'ADD', 'role', '*', '',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
req = await ledger.build_auth_rule_request(trustee_did, '1', 'EDIT', 'verkey', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add nym with verkey by adder
res4 = await send_nym(pool_handler, wallet_handler, adder_did, new_did, adder_vk) # push adder vk
print(res4)
assert res4['op'] == 'REPLY'
# edit verkey by editor
res5 = await send_nym(pool_handler, wallet_handler, editor_did, new_did, editor_vk) # push editor vk
print(res5)
assert res5['op'] == 'REPLY'
# negative cases
if adder_role != editor_role:
# try to add another nym with editor did - should be rejected
res6 = await send_nym(pool_handler, wallet_handler, editor_did, random_did_and_json()[0])
print(res6)
assert res6['op'] == 'REJECT'
# try to edit initial nym one more time with adder did - should be rejected
res7 = await send_nym(pool_handler, wallet_handler, adder_did, new_did, adder_vk)
print(res7)
assert res7['op'] == 'REJECT'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_attrib(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add target nym
target_did, target_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, target_did, target_vk)
assert res['op'] == 'REPLY'
# add adder to add attrib
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
# add editor to edit attrib
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '100', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '100', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add attrib for target did by non-owner adder
res4 = await send_attrib(pool_handler, wallet_handler, adder_did, target_did,
None, json.dumps({'key1': 'value1'}), None)
print(res4)
assert res4['op'] == 'REPLY'
# edit attrib for target did by non-owner editor
res5 = await send_attrib(pool_handler, wallet_handler, editor_did, target_did,
None, json.dumps({'key1': 'value2'}), None)
print(res5)
assert res5['op'] == 'REPLY'
# negative cases
if adder_role != editor_role:
# try to add another attrib with editor did - should be rejected
res6 = await send_attrib(pool_handler, wallet_handler, editor_did, target_did,
None, json.dumps({'key2': 'value1'}), None)
print(res6)
assert res6['op'] == 'REJECT'
# try to edit initial attrib one more time with adder did - should be rejected
res7 = await send_attrib(pool_handler, wallet_handler, adder_did, target_did,
None, json.dumps({'key1': 'value3'}), None)
print(res7)
assert res7['op'] == 'REJECT'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.asyncio
async def test_case_schema(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num): # we can add schema only
trustee_did, _ = get_default_trustee
# add adder to add schema
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '101', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# add schema
res4 = await send_schema(pool_handler, wallet_handler, adder_did, 'schema1', '1.0', json.dumps(['attr1']))
print(res4)
assert res4[1]['op'] == 'REPLY'
# edit schema - nobody can edit schemas - should be rejected
res5 = await send_schema(pool_handler, wallet_handler, adder_did, 'schema1', '1.0',
json.dumps(['attr1', 'attr2']))
print(res5)
assert res5[1]['op'] == 'REJECT'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
# use the same did with different roles to ADD and EDIT since adder did is a part of unique cred def id
async def test_case_cred_def(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add adder to add cred def
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
schema_id, _ = await send_schema(pool_handler, wallet_handler, trustee_did,
'schema1', '1.0', json.dumps(["age", "sex", "height", "name"]))
await asyncio.sleep(1)
res = await get_schema(pool_handler, wallet_handler, trustee_did, schema_id)
schema_id, schema_json = await ledger.parse_get_schema_response(json.dumps(res))
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '102', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '102', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add cred def
cred_def_id, cred_def_json = \
await anoncreds.issuer_create_and_store_credential_def(wallet_handler, adder_did, schema_json, 'TAG1',
None, json.dumps({'support_revocation': False}))
request = await ledger.build_cred_def_request(adder_did, cred_def_json)
res4 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res4)
assert res4['op'] == 'REPLY'
if adder_role != editor_role:
# try to edit cred def as adder - should be rejected
_request = json.loads(request)
_request['operation']['data']['primary']['n'] = '123456789'
_request['reqId'] += _request['reqId']
res5 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(_request)))
print(res5)
assert res5['op'] == 'REJECT'
# change adder role to edit cred def
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, None, None, editor_role)
print(res)
assert res['op'] == 'REPLY'
# edit cred def
request = json.loads(request)
request['operation']['data']['primary']['n'] = '123456'
request['reqId'] += request['reqId']
res6 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(request)))
print(res6)
assert res6['op'] == 'REPLY'
if adder_role != editor_role:
# try to add another cred def as editor - should be rejected
cred_def_id, cred_def_json = \
await anoncreds.issuer_create_and_store_credential_def(wallet_handler, adder_did, schema_json, 'TAG2',
None, json.dumps({'support_revocation': True}))
request = await ledger.build_cred_def_request(adder_did, cred_def_json)
res7 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res7)
assert res7['op'] == 'REJECT'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
# use the same did with different roles to ADD and EDIT since adder did is a part of unique revoc reg def id
async def test_case_revoc_reg_def(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add adder to add revoc reg def
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
schema_id, _ = await send_schema(pool_handler, wallet_handler, trustee_did,
'schema1', '1.0', json.dumps(['age', 'sex', 'height', 'name']))
await asyncio.sleep(1)
res = await get_schema(pool_handler, wallet_handler, trustee_did, schema_id)
schema_id, schema_json = await ledger.parse_get_schema_response(json.dumps(res))
cred_def_id, _, res = await send_cred_def(pool_handler, wallet_handler, trustee_did, schema_json,
'cred_def_tag', None, json.dumps({'support_revocation': True}))
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '113', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '113', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add revoc reg def
tails_writer_config = json.dumps({'base_dir': 'tails', 'uri_pattern': ''})
tails_writer_handle = await blob_storage.open_writer('default', tails_writer_config)
revoc_reg_def_id, revoc_reg_def_json, revoc_reg_entry_json = \
await anoncreds.issuer_create_and_store_revoc_reg(wallet_handler, adder_did, None, 'TAG1',
cred_def_id, json.dumps({
'max_cred_num': 1,
'issuance_type': 'ISSUANCE_BY_DEFAULT'}),
tails_writer_handle)
request = await ledger.build_revoc_reg_def_request(adder_did, revoc_reg_def_json)
res4 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res4)
assert res4['op'] == 'REPLY'
if adder_role != editor_role:
# try to edit revoc reg def as adder - should be rejected
_request = json.loads(request)
_request['operation']['value']['tailsHash'] = random_string(30)
_request['reqId'] += _request['reqId']
res5 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(_request)))
print(res5)
assert res5['op'] == 'REJECT'
# change adder role to edit revoc reg def
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, None, None, editor_role)
print(res)
assert res['op'] == 'REPLY'
# edit revoc reg def
request = json.loads(request)
request['operation']['value']['tailsHash'] = random_string(20)
request['reqId'] += request['reqId']
res6 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(request)))
print(res6)
assert res6['op'] == 'REPLY'
if adder_role != editor_role:
# try to add another revoc reg def as editor - should be rejected
revoc_reg_def_id, revoc_reg_def_json, revoc_reg_entry_json = \
await anoncreds.issuer_create_and_store_revoc_reg(wallet_handler, adder_did, None, 'TAG2',
cred_def_id, json.dumps({
'max_cred_num': 2,
'issuance_type': 'ISSUANCE_BY_DEFAULT'}),
tails_writer_handle)
request = await ledger.build_revoc_reg_def_request(adder_did, revoc_reg_def_json)
res7 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res7)
assert res7['op'] == 'REJECT'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_revoc_reg_entry(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add adder to add revoc reg entry
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
schema_id, _ = await send_schema(pool_handler, wallet_handler, trustee_did,
'schema1', '1.0', json.dumps(['age', 'sex', 'height', 'name']))
await asyncio.sleep(1)
res = await get_schema(pool_handler, wallet_handler, trustee_did, schema_id)
schema_id, schema_json = await ledger.parse_get_schema_response(json.dumps(res))
cred_def_id, _, res = await send_cred_def(pool_handler, wallet_handler, trustee_did, schema_json,
'cred_def_tag', None, json.dumps({'support_revocation': True}))
# set rule for revoc reg def adding - network monitor case
req = await ledger.build_auth_rule_request(trustee_did, '113', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': '*',
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res21 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res21)
assert res21['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '114', 'ADD', '*', None, '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res22 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res22)
assert res22['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '114', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add revoc reg entry
tails_writer_config = json.dumps({'base_dir': 'tails', 'uri_pattern': ''})
tails_writer_handle = await blob_storage.open_writer('default', tails_writer_config)
revoc_reg_def_id, revoc_reg_def_json, revoc_reg_entry_json = \
await anoncreds.issuer_create_and_store_revoc_reg(wallet_handler, adder_did, None, 'TAG1',
cred_def_id, json.dumps({
'max_cred_num': 10,
'issuance_type': 'ISSUANCE_BY_DEFAULT'}),
tails_writer_handle)
req = await ledger.build_revoc_reg_def_request(adder_did, revoc_reg_def_json)
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
assert res['op'] == 'REPLY'
request = await ledger.build_revoc_reg_entry_request(adder_did, revoc_reg_def_id, 'CL_ACCUM',
revoc_reg_entry_json)
res4 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res4)
assert res4['op'] == 'REPLY'
if adder_role != editor_role:
# try to edit revoc reg entry as adder - should be rejected
_request = json.loads(request)
_request['operation']['value']['prevAccum'] = _request['operation']['value']['accum']
_request['operation']['value']['accum'] = random_string(20)
_request['operation']['value']['revoked'] = [7, 8, 9]
_request['reqId'] += _request['reqId']
res5 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(_request)))
print(res5)
assert res5['op'] == 'REJECT'
# change adder role to edit revoc reg def
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, None, None, editor_role)
print(res)
assert res['op'] == 'REPLY'
# edit revoc reg entry
request = json.loads(request)
request['operation']['value']['prevAccum'] = request['operation']['value']['accum']
request['operation']['value']['accum'] = random_string(10)
request['operation']['value']['revoked'] = [1, 2, 3]
request['reqId'] += request['reqId']
res6 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did,
json.dumps(request)))
print(res6)
assert res6['op'] == 'REPLY'
if adder_role != editor_role:
# try to add another revoc reg entry as editor - should be rejected
revoc_reg_def_id, revoc_reg_def_json, revoc_reg_entry_json = \
await anoncreds.issuer_create_and_store_revoc_reg(wallet_handler, adder_did, None, 'TAG2',
cred_def_id, json.dumps({
'max_cred_num': 20,
'issuance_type': 'ISSUANCE_BY_DEFAULT'}),
tails_writer_handle)
req = await ledger.build_revoc_reg_def_request(adder_did, revoc_reg_def_json)
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
assert res['op'] == 'REPLY'
request = await ledger.build_revoc_reg_entry_request(adder_did, revoc_reg_def_id, 'CL_ACCUM',
revoc_reg_entry_json)
res7 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, request))
print(res7)
assert res7['op'] == 'REJECT'
@pytest.mark.skip('INDY-2024')
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_node(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add adder to add node
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
# add editor to edit node
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '0', 'ADD', 'services', '*', str(['VALIDATOR']),
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '0', 'EDIT', 'services', str(['VALIDATOR']), str([]),
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# add node
alias = random_string(5)
client_ip = '{}.{}.{}.{}'.format(rr(1, 255), 0, 0, rr(1, 255))
client_port = rr(1, 32767)
node_ip = '{}.{}.{}.{}'.format(rr(1, 255), 0, 0, rr(1, 255))
node_port = rr(1, 32767)
req = await ledger.build_node_request(adder_did, adder_vk, # adder_vk is used as node target did here
json.dumps(
{
'alias': alias,
'client_ip': client_ip,
'client_port': client_port,
'node_ip': node_ip,
'node_port': node_port,
'services': ['VALIDATOR']
}))
res4 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res4)
assert res4['op'] == 'REPLY'
# edit node
req = await ledger.build_node_request(editor_did, adder_vk, # adder_vk is used as node target did here
json.dumps(
{
'alias': alias,
'services': []
}))
res5 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res5)
assert res5['op'] == 'REPLY'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_pool_upgrade(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, editor_role, editor_role_num):
trustee_did, _ = get_default_trustee
# add adder to start pool upgrdae
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
# add editor to cancel pool upgrade
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '109', 'ADD', 'action', '*', 'start',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '109', 'EDIT', 'action', 'start', 'cancel',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res3)
assert res3['op'] == 'REPLY'
# start pool upgrade
init_time = 30
version = '1.9.999'
name = 'upgrade' + '_' + version + '_' + datetime.now(tz=timezone.utc).strftime('%Y-%m-%dT%H:%M:%S%z')
_sha256 = hashlib.sha256().hexdigest()
_timeout = 5
reinstall = False
force = False
package = 'indy-node'
dests = ['Gw6pDLhcBcoQesN72qfotTgFa7cbuqZpkX3Xo6pLhPhv', '8ECVSk179mjsjKRLWiQtssMLgp6EPhWXtaYyStWPSGAb',
'DKVxG2fXXTU8yT5N7hGEbXB3dfdAnYv1JczDUHpmDxya', '4PS3EDQ3dW1tci1Bp6543CfuuebjFrg36kLAUcskGfaA',
'4SWokCJWJc69Tn74VvLS6t2G2ucvXqM9FDMsWJjmsUxe', 'Cv1Ehj43DDM5ttNBmC6VPpEfwXWwfGktHwjDJsTV5Fz8',
'BM8dTooz5uykCbYSAAFwKNkYfT4koomBHsSWHTDtkjhW']
docker_7_schedule = json.dumps(dict(
{dest: datetime.strftime(datetime.now(tz=timezone.utc) + timedelta(minutes=init_time + i * 5),
'%Y-%m-%dT%H:%M:%S%z')
for dest, i in zip(dests, range(len(dests)))}
))
req = await ledger.build_pool_upgrade_request(adder_did, name, version, 'start', _sha256, _timeout,
docker_7_schedule, None, reinstall, force, package)
res4 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res4)
assert res4['op'] == 'REPLY'
# cancel pool upgrade
req = await ledger.build_pool_upgrade_request(editor_did, name, version, 'cancel', _sha256, _timeout,
docker_7_schedule, None, reinstall, force, package)
res5 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res5)
assert res5['op'] == 'REPLY'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.asyncio
async def test_case_pool_restart(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num): # we can add pool restart only
trustee_did, _ = get_default_trustee
# add adder to restart pool
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
await asyncio.sleep(15)
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '118', 'ADD', 'action', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# restart pool
req = await ledger.build_pool_restart_request\
(adder_did, 'start', datetime.strftime(datetime.now(tz=timezone.utc) + timedelta(minutes=60),
'%Y-%m-%dT%H:%M:%S%z'))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
res3 = [json.loads(v) for k, v in res3.items()]
print(res3)
assert all([res['op'] == 'REPLY' for res in res3])
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.asyncio
async def test_case_validator_info(self, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num): # we can add validator info only
trustee_did, _ = get_default_trustee
# add adder to get validator info
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
await asyncio.sleep(15)
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '119', 'ADD', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
req = await ledger.build_get_validator_info_request(adder_did)
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
res3 = [json.loads(v) for k, v in res3.items()]
print(res3)
assert all([res['op'] == 'REPLY' for res in res3])
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_pool_config(self, pool_handler, wallet_handler, get_default_trustee,
editor_role, editor_role_num): # we can edit pool config only
trustee_did, _ = get_default_trustee
# add editor to edit pool config
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '111', 'EDIT', 'action', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
req = await ledger.build_pool_config_request(editor_did, False, False)
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res3)
assert res3['op'] == 'REPLY'
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.asyncio
async def test_case_auth_rule(self, pool_handler, wallet_handler, get_default_trustee,
editor_role, editor_role_num): # we can edit auth rule only
trustee_did, _ = get_default_trustee
# add editor to edit auth rule
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
# set rule for editing
req = await ledger.build_auth_rule_request(trustee_did, '120', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
await asyncio.sleep(15)
req = await ledger.build_auth_rule_request(editor_did, '111', 'EDIT', 'action', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': '*',
'sig_count': 5,
'need_to_be_owner': True,
'metadata': {}
}))
res3 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res3)
assert res3['op'] == 'REPLY'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('sig_count', [0, 1, 3])
@pytest.mark.asyncio
async def test_case_mint(self, payment_init, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, sig_count):
libsovtoken_payment_method = 'sov'
trustee_did, _ = get_default_trustee
address = await payment.create_payment_address(wallet_handler, libsovtoken_payment_method, json.dumps(
{"seed": str('0000000000000000000000000Wallet0')}))
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '10000', 'ADD', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': sig_count,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
if sig_count == 0:
# add identity owner adder to mint tokens
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, None)
assert res['op'] == 'REPLY'
req, _ = await payment.build_mint_req(wallet_handler, adder_did,
json.dumps([{"recipient": address, "amount": 100}]), None)
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res1)
assert res1['op'] == 'REPLY'
elif sig_count == 1:
# add adder to mint tokens
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
req, _ = await payment.build_mint_req(wallet_handler, adder_did,
json.dumps([{"recipient": address, "amount": 100}]), None)
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res1)
assert res1['op'] == 'REPLY'
else:
# add adders to mint tokens
adder_did1, adder_vk1 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did1, adder_vk1, None, adder_role)
assert res['op'] == 'REPLY'
adder_did2, adder_vk2 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did2, adder_vk2, None, adder_role)
assert res['op'] == 'REPLY'
adder_did3, adder_vk3 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did3, adder_vk3, None, adder_role)
assert res['op'] == 'REPLY'
req, _ = await payment.build_mint_req(wallet_handler, adder_did1,
json.dumps([{"recipient": address, "amount": 100}]), None)
req = await ledger.multi_sign_request(wallet_handler, adder_did1, req)
req = await ledger.multi_sign_request(wallet_handler, adder_did2, req)
req = await ledger.multi_sign_request(wallet_handler, adder_did3, req)
res1 = json.loads(await ledger.submit_request(pool_handler, req))
print(res1)
assert res1['op'] == 'REPLY'
@pytest.mark.parametrize('editor_role, editor_role_num', [
('NETWORK_MONITOR', '201'),
('TRUST_ANCHOR', '101'),
('STEWARD', '2'),
('TRUSTEE', '0')
])
@pytest.mark.parametrize('sig_count', [0, 1, 3])
@pytest.mark.asyncio
async def test_case_set_fees(self, payment_init, pool_handler, wallet_handler, get_default_trustee,
editor_role, editor_role_num, sig_count):
libsovtoken_payment_method = 'sov'
fees = {'1': 1, '100': 1, '101': 1, '102': 1, '113': 1, '114': 1, '10001': 1}
trustee_did, _ = get_default_trustee
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '20000', 'EDIT', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': editor_role_num,
'sig_count': sig_count,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
if sig_count == 0:
# add identity owner editor to set fees
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, None)
assert res['op'] == 'REPLY'
req = await payment.build_set_txn_fees_req(wallet_handler, editor_did, libsovtoken_payment_method,
json.dumps(fees))
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res1)
assert res1['op'] == 'REPLY'
elif sig_count == 1:
# add editor to set fees
editor_did, editor_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did, editor_vk, None, editor_role)
assert res['op'] == 'REPLY'
req = await payment.build_set_txn_fees_req(wallet_handler, editor_did, libsovtoken_payment_method,
json.dumps(fees))
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, editor_did, req))
print(res1)
assert res1['op'] == 'REPLY'
else:
# add editors to set fees
editor_did1, editor_vk1 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did1, editor_vk1, None, editor_role)
assert res['op'] == 'REPLY'
editor_did2, editor_vk2 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did2, editor_vk2, None, editor_role)
assert res['op'] == 'REPLY'
editor_did3, editor_vk3 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, editor_did3, editor_vk3, None, editor_role)
assert res['op'] == 'REPLY'
req = await payment.build_set_txn_fees_req(wallet_handler, editor_did1, libsovtoken_payment_method,
json.dumps(fees))
req = await ledger.multi_sign_request(wallet_handler, editor_did1, req)
req = await ledger.multi_sign_request(wallet_handler, editor_did2, req)
req = await ledger.multi_sign_request(wallet_handler, editor_did3, req)
res1 = json.loads(await ledger.submit_request(pool_handler, req))
print(res1)
assert res1['op'] == 'REPLY'
@pytest.mark.parametrize('adder_role, adder_role_num', [
('TRUSTEE', '0'),
('STEWARD', '2'),
('TRUST_ANCHOR', '101'),
('NETWORK_MONITOR', '201')
])
@pytest.mark.parametrize('sig_count', [0, 1, 3])
@pytest.mark.asyncio
async def test_case_payment(self, payment_init, pool_handler, wallet_handler, get_default_trustee,
adder_role, adder_role_num, sig_count):
libsovtoken_payment_method = 'sov'
trustee_did, _ = get_default_trustee
address1 = await payment.create_payment_address(wallet_handler, libsovtoken_payment_method, json.dumps(
{"seed": str('0000000000000000000000000Wallet1')}))
address2 = await payment.create_payment_address(wallet_handler, libsovtoken_payment_method, json.dumps(
{"seed": str('0000000000000000000000000Wallet2')}))
# set rule for easier mint adding
req = await ledger.build_auth_rule_request(trustee_did, '10000', 'ADD', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': '*',
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}))
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res1)
assert res1['op'] == 'REPLY'
# set rule for adding
req = await ledger.build_auth_rule_request(trustee_did, '10001', 'ADD', '*', '*', '*',
json.dumps({
'constraint_id': 'ROLE',
'role': adder_role_num,
'sig_count': sig_count,
'need_to_be_owner': False,
'metadata': {}
}))
res2 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res2)
assert res2['op'] == 'REPLY'
# initial minting
req, _ = await payment.build_mint_req(wallet_handler, trustee_did,
json.dumps([{"recipient": address1, "amount": 100}]), None)
res11 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
print(res11)
assert res11['op'] == 'REPLY'
req, _ = await payment.build_get_payment_sources_request(wallet_handler, trustee_did, address1)
res111 = await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req)
source1 = \
json.loads(await payment.parse_get_payment_sources_response(libsovtoken_payment_method,
res111))[0]['source']
if sig_count == 0:
# add identity owner adder to send xfer
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, None)
assert res['op'] == 'REPLY'
req, _ = await payment.build_payment_req(wallet_handler, adder_did,
json.dumps([source1]),
json.dumps([{"recipient": address2, "amount": 100}]), None)
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res1)
assert res1['op'] == 'REPLY'
elif sig_count == 1:
# add adder to send xfer
adder_did, adder_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did, adder_vk, None, adder_role)
assert res['op'] == 'REPLY'
req, _ = await payment.build_payment_req(wallet_handler, adder_did,
json.dumps([source1]),
json.dumps([{"recipient": address2, "amount": 100}]), None)
res1 = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, adder_did, req))
print(res1)
assert res1['op'] == 'REPLY'
else:
# add adders to send xfer
adder_did1, adder_vk1 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did1, adder_vk1, None, adder_role)
assert res['op'] == 'REPLY'
adder_did2, adder_vk2 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did2, adder_vk2, None, adder_role)
assert res['op'] == 'REPLY'
adder_did3, adder_vk3 = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, adder_did3, adder_vk3, None, adder_role)
assert res['op'] == 'REPLY'
req, _ = await payment.build_payment_req(wallet_handler, adder_did1,
json.dumps([source1]),
json.dumps([{"recipient": address2, "amount": 100}]), None)
req = await ledger.multi_sign_request(wallet_handler, adder_did1, req)
req = await ledger.multi_sign_request(wallet_handler, adder_did2, req)
req = await ledger.multi_sign_request(wallet_handler, adder_did3, req)
res1 = json.loads(await ledger.submit_request(pool_handler, req))
print(res1)
assert res1['op'] == 'REPLY'
# TODO might make sense to move to separate module since other tests here
# organized per txn type
@pytest.mark.asyncio
async def test_case_forbidden(self, pool_handler, wallet_handler, get_default_trustee):
trustee_did, _ = get_default_trustee
trustee_role, trustee_role_num = 'TRUSTEE', '0'
logger.info("1 Adding new trustee to ledger")
new_trustee_did, new_trustee_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, trustee_did, new_trustee_did, new_trustee_vk, None, trustee_role
)
assert res['op'] == 'REPLY'
logger.info("2 Setting forbidden auth rule for adding trustees")
req = await ledger.build_auth_rule_request(trustee_did, '1', 'ADD', 'role', '*', trustee_role_num,
json.dumps({
'constraint_id': 'FORBIDDEN',
}))
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
assert res['op'] == 'REPLY'
logger.info("3 Getting newly set forbidden constraint")
req = await ledger.build_get_auth_rule_request(trustee_did, '1', 'ADD', 'role', '*', trustee_role_num)
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
assert res['op'] == 'REPLY'
assert res['result']['data'][0]['constraint']['constraint_id'] == 'FORBIDDEN'
logger.info("4 Trying to add one more trustee")
one_more_new_trustee_did, one_more_new_trustee_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, trustee_did, one_more_new_trustee_did, one_more_new_trustee_vk, None, trustee_role
)
assert res['op'] == 'REJECT'
# TODO might make sense to move to separate module since other tests here
# organized per txn type
@pytest.mark.asyncio
async def test_case_auth_rules(self, pool_handler, wallet_handler, get_default_trustee):
trustee_did, _ = get_default_trustee
trustee_role, trustee_role_num = 'TRUSTEE', '0'
steward_role, steward_role_num = 'STEWARD', '2'
logger.info("1 Creating new steward")
steward_did, steward_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, steward_did, steward_vk, None, steward_role)
assert res['op'] == 'REPLY'
logger.info("2 Creating some new trustee")
_new_trustee_did, _new_trustee_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did, _new_trustee_did, _new_trustee_vk, None, trustee_role)
assert res['op'] == 'REPLY'
logger.info("3 Trying to add new trustee using steward as submitter")
new_trustee_did, new_trustee_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, steward_did, new_trustee_did, new_trustee_vk, None, trustee_role
)
assert res['op'] == 'REJECT'
logger.info("4 Trying to add new steward using steward as submitter")
new_steward_did, new_steward_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, steward_did, new_steward_did, new_steward_vk, None, trustee_role
)
assert res['op'] == 'REJECT'
logger.info("5 Send auth rules txn to allow stewards to add new trustees and stewrds")
one_steward_constraint = {
'constraint_id': 'ROLE',
'role': steward_role_num,
'sig_count': 1,
'need_to_be_owner': False,
'metadata': {}
}
req = await ledger.build_auth_rules_request(trustee_did, json.dumps([
{
'auth_type': '1',
'auth_action': 'ADD',
'field': 'role',
'old_value': '*',
'new_value': trustee_role_num,
'constraint': one_steward_constraint
}, {
'auth_type': '1',
'auth_action': 'ADD',
'field': 'role',
'old_value': '*',
'new_value': steward_role_num,
'constraint': one_steward_constraint
},
]))
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
assert res['op'] == 'REPLY'
logger.info("6 Getting recently set auth rules")
for role_num in (trustee_role_num, steward_role_num):
req = await ledger.build_get_auth_rule_request(trustee_did, '1', 'ADD', 'role', '*', role_num)
res = json.loads(await ledger.sign_and_submit_request(pool_handler, wallet_handler, trustee_did, req))
assert res['op'] == 'REPLY'
assert res['result']['data'][0]['constraint'] == one_steward_constraint
logger.info("7 Trying to add new trustee using trustee as submitter")
res = await send_nym(
pool_handler, wallet_handler, trustee_did, new_trustee_did, new_trustee_vk, None, trustee_role
)
assert res['op'] == 'REJECT'
logger.info("8 Trying to add new steward using trustee as submitter")
res = await send_nym(
pool_handler, wallet_handler, trustee_did, new_trustee_did, new_steward_vk, None, trustee_role
)
assert res['op'] == 'REJECT'
logger.info("9 Adding new trustee using steward as submitter")
new_trustee_did, new_trustee_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, steward_did, new_trustee_did, new_trustee_vk, None, trustee_role
)
assert res['op'] == 'REPLY'
logger.info("10 Adding new steward using steward as submitter")
new_steward_did, new_steward_vk = await did.create_and_store_my_did(wallet_handler, '{}')
res = await send_nym(
pool_handler, wallet_handler, steward_did, new_steward_did, new_steward_vk, None, trustee_role
)
assert res['op'] == 'REPLY'
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767, 5): "[('NETWORK_MONITOR', '201'), ('TRUST_ANCHOR', '101'), ('STEWARD', '2'), (\n 'TRUSTEE', '0')]"}, {}), "('editor_role, editor_role_num', [('NETWORK_MONITOR',\n '201'), ('TRUST_ANCHOR', '101'), ('STEWARD', '2'), ('TRUSTEE', '0')])", False, 'import pytest\n'), ((801, 5, 806, 6), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(801, 29, 801, 57): '"""adder_role, adder_role_num"""', (801, 59, 806, 5): "[('TRUSTEE', '0'), ('STEWARD', '2'), ('TRUST_ANCHOR', '101'), (\n 'NETWORK_MONITOR', '201')]"}, {}), "('adder_role, adder_role_num', [('TRUSTEE', '0'), (\n 'STEWARD', '2'), ('TRUST_ANCHOR', '101'), ('NETWORK_MONITOR', '201')])", False, 'import pytest\n'), ((807, 5, 807, 52), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(807, 29, 807, 40): '"""sig_count"""', (807, 42, 807, 51): '[0, 1, 3]'}, {}), "('sig_count', [0, 1, 3])", False, 'import pytest\n'), ((867, 5, 872, 6), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(867, 29, 867, 59): '"""editor_role, editor_role_num"""', (867, 61, 872, 5): "[('NETWORK_MONITOR', '201'), ('TRUST_ANCHOR', '101'), ('STEWARD', '2'), (\n 'TRUSTEE', '0')]"}, {}), "('editor_role, editor_role_num', [('NETWORK_MONITOR',\n '201'), ('TRUST_ANCHOR', '101'), ('STEWARD', '2'), ('TRUSTEE', '0')])", False, 'import pytest\n'), ((873, 5, 873, 52), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(873, 29, 873, 40): '"""sig_count"""', (873, 42, 873, 51): '[0, 1, 3]'}, {}), "('sig_count', [0, 1, 3])", False, 'import pytest\n'), ((932, 5, 937, 6), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(932, 29, 932, 57): '"""adder_role, adder_role_num"""', (932, 59, 937, 5): "[('TRUSTEE', '0'), ('STEWARD', '2'), ('TRUST_ANCHOR', '101'), (\n 'NETWORK_MONITOR', '201')]"}, {}), "('adder_role, adder_role_num', [('TRUSTEE', '0'), (\n 'STEWARD', '2'), ('TRUST_ANCHOR', '101'), ('NETWORK_MONITOR', '201')])", False, 'import pytest\n'), ((938, 5, 938, 52), 'pytest.mark.parametrize', 'pytest.mark.parametrize', ({(938, 29, 938, 40): '"""sig_count"""', (938, 42, 938, 51): '[0, 1, 3]'}, {}), "('sig_count', [0, 1, 3])", False, 'import pytest\n'), ((557, 22, 557, 34), 'random.randrange', 'rr', ({(557, 25, 557, 26): '1', (557, 28, 557, 33): '32767'}, {}), '(1, 32767)', True, 'from random import randrange as rr\n'), ((559, 20, 559, 32), 'random.randrange', 'rr', ({(559, 23, 559, 24): '1', (559, 26, 559, 31): '32767'}, {}), '(1, 32767)', True, 'from random import randrange as rr\n'), ((218, 14, 218, 30), 'asyncio.sleep', 'asyncio.sleep', ({(218, 28, 218, 29): '(1)'}, {}), '(1)', False, 'import asyncio\n'), ((307, 14, 307, 30), 'asyncio.sleep', 'asyncio.sleep', ({(307, 28, 307, 29): '(1)'}, {}), '(1)', False, 'import asyncio\n'), ((405, 14, 405, 30), 'asyncio.sleep', 'asyncio.sleep', ({(405, 28, 405, 29): '(1)'}, {}), '(1)', False, 'import asyncio\n'), ((556, 41, 556, 51), 'random.randrange', 'rr', ({(556, 44, 556, 45): '1', (556, 47, 556, 50): '255'}, {}), '(1, 255)', True, 'from random import randrange as rr\n'), ((556, 59, 556, 69), 'random.randrange', 'rr', ({(556, 62, 556, 63): '1', (556, 65, 556, 68): '255'}, {}), '(1, 255)', True, 'from random import randrange as rr\n'), ((558, 39, 558, 49), 'random.randrange', 'rr', ({(558, 42, 558, 43): '1', (558, 45, 558, 48): '255'}, {}), '(1, 255)', True, 'from random import randrange as rr\n'), ((558, 57, 558, 67), 'random.randrange', 'rr', ({(558, 60, 558, 61): '1', (558, 63, 558, 66): '255'}, {}), '(1, 255)', True, 'from random import randrange as rr\n'), ((676, 14, 676, 31), 'asyncio.sleep', 'asyncio.sleep', ({(676, 28, 676, 30): '(15)'}, {}), '(15)', False, 'import asyncio\n'), ((712, 14, 712, 31), 'asyncio.sleep', 'asyncio.sleep', ({(712, 28, 712, 30): '(15)'}, {}), '(15)', False, 'import asyncio\n'), ((788, 14, 788, 31), 'asyncio.sleep', 'asyncio.sleep', ({(788, 28, 788, 30): '(15)'}, {}), '(15)', False, 'import asyncio\n'), ((978, 23, 978, 103), 'indy.payment.build_get_payment_sources_request', 'payment.build_get_payment_sources_request', ({(978, 65, 978, 79): 'wallet_handler', (978, 81, 978, 92): 'trustee_did', (978, 94, 978, 102): 'address1'}, {}), '(wallet_handler, trustee_did, address1\n )', False, 'from indy import payment\n'), ((636, 18, 636, 34), 'hashlib.sha256', 'hashlib.sha256', ({}, {}), '()', False, 'import hashlib\n'), ((635, 49, 635, 78), 'datetime.datetime.now', 'datetime.now', (), '', False, 'from datetime import datetime, timedelta, timezone\n'), ((691, 51, 691, 80), 'datetime.datetime.now', 'datetime.now', (), '', False, 'from datetime import datetime, timedelta, timezone\n'), ((691, 83, 691, 104), 'datetime.timedelta', 'timedelta', (), '', False, 'from datetime import datetime, timedelta, timezone\n'), ((981, 29, 982, 79), 'indy.payment.parse_get_payment_sources_response', 'payment.parse_get_payment_sources_response', ({(981, 72, 981, 98): 'libsovtoken_payment_method', (982, 72, 982, 78): 'res111'}, {}), '(libsovtoken_payment_method, res111)', False, 'from indy import payment\n'), ((646, 37, 646, 66), 'datetime.datetime.now', 'datetime.now', (), '', False, 'from datetime import datetime, timedelta, timezone\n'), ((646, 69, 646, 105), 'datetime.timedelta', 'timedelta', (), '', False, 'from datetime import datetime, timedelta, timezone\n')] |
jgough/opensearch-curator | test/integration/test_reindex.py | e8d7eb4d969eac551db9f99bd021d0c05e28dc35 | import opensearchpy
import curator
import os
import json
import string
import random
import tempfile
import click
from click import testing as clicktest
import time
from . import CuratorTestCase
from unittest.case import SkipTest
from . import testvars as testvars
import logging
logger = logging.getLogger(__name__)
host, port = os.environ.get('TEST_ES_SERVER', 'localhost:9200').split(':')
rhost, rport = os.environ.get('REMOTE_ES_SERVER', 'localhost:9201').split(':')
port = int(port) if port else 9200
rport = int(rport) if rport else 9201
class TestActionFileReindex(CuratorTestCase):
def test_reindex_manual(self):
wait_interval = 1
max_wait = 3
source = 'my_source'
dest = 'my_dest'
expected = 3
self.create_index(source)
self.add_docs(source)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, source, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_selected(self):
wait_interval = 1
max_wait = 3
source = 'my_source'
dest = 'my_dest'
expected = 3
self.create_index(source)
self.add_docs(source)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, 'REINDEX_SELECTION', dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_empty_list(self):
wait_interval = 1
max_wait = 3
source = 'my_source'
dest = 'my_dest'
expected = '.tasks'
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, source, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, curator.get_indices(self.client)[0])
def test_reindex_selected_many_to_one(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
dest = 'my_dest'
expected = 6
self.create_index(source1)
self.add_docs(source1)
self.create_index(source2)
for i in ["4", "5", "6"]:
ver = curator.get_version(self.client)
if ver >= (7, 0, 0):
self.client.create(
index=source2, doc_type='doc', id=i, body={"doc" + i :'TEST DOCUMENT'})
else:
self.client.create(
index=source2, doc_type='doc', id=i, body={"doc" + i :'TEST DOCUMENT'})
# Decorators make this pylint exception necessary
# pylint: disable=E1123
self.client.indices.flush(index=source2, force=True)
self.client.indices.refresh(index=source2)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(
self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, 'REINDEX_SELECTION', dest)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.client.indices.refresh(index=dest)
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_selected_empty_list_fail(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
dest = 'my_dest'
expected = 6
self.create_index(source1)
self.add_docs(source1)
self.create_index(source2)
for i in ["4", "5", "6"]:
self.client.create(
index=source2, doc_type='log', id=i,
body={"doc" + i :'TEST DOCUMENT'},
)
# Decorators make this pylint exception necessary
# pylint: disable=E1123
self.client.indices.flush(index=source2, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex_empty_list.format('false', wait_interval, max_wait, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(_.exit_code, 1)
def test_reindex_selected_empty_list_pass(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
dest = 'my_dest'
expected = 6
self.create_index(source1)
self.add_docs(source1)
self.create_index(source2)
for i in ["4", "5", "6"]:
self.client.create(
index=source2, doc_type='log', id=i,
body={"doc" + i :'TEST DOCUMENT'},
)
# Decorators make this pylint exception necessary
# pylint: disable=E1123
self.client.indices.flush(index=source2, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex_empty_list.format('true', wait_interval, max_wait, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(_.exit_code, 0)
def test_reindex_from_remote(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
prefix = 'my_'
dest = 'my_dest'
expected = 6
# Build remote client
try:
rclient = curator.get_client(
host=rhost, port=rport, skip_version_test=True)
rclient.info()
except:
raise SkipTest(
'Unable to connect to host at {0}:{1}'.format(rhost, rport))
# Build indices remotely.
counter = 0
for rindex in [source1, source2]:
rclient.indices.create(index=rindex)
for i in range(0, 3):
rclient.create(
index=rindex, doc_type='log', id=str(counter+1),
body={"doc" + str(counter+i) :'TEST DOCUMENT'},
)
counter += 1
# Decorators make this pylint exception necessary
# pylint: disable=E1123
rclient.indices.flush(index=rindex, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.remote_reindex.format(
wait_interval,
max_wait,
'http://{0}:{1}'.format(rhost, rport),
'REINDEX_SELECTION',
dest,
prefix
)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
# Do our own cleanup here.
rclient.indices.delete(index='{0},{1}'.format(source1, source2))
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_migrate_from_remote(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
prefix = 'my_'
dest = 'MIGRATION'
expected = 3
# Build remote client
try:
rclient = curator.get_client(
host=rhost, port=rport, skip_version_test=True)
rclient.info()
except:
raise SkipTest(
'Unable to connect to host at {0}:{1}'.format(rhost, rport))
# Build indices remotely.
counter = 0
for rindex in [source1, source2]:
rclient.indices.create(index=rindex)
for i in range(0, 3):
rclient.create(
index=rindex, doc_type='log', id=str(counter+1),
body={"doc" + str(counter+i) :'TEST DOCUMENT'},
)
counter += 1
# Decorators make this pylint exception necessary
# pylint: disable=E1123
rclient.indices.flush(index=rindex, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.remote_reindex.format(
wait_interval,
max_wait,
'http://{0}:{1}'.format(rhost, rport),
'REINDEX_SELECTION',
dest,
prefix
)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
# Do our own cleanup here.
rclient.indices.delete(index='{0},{1}'.format(source1, source2))
# And now the neat trick of verifying that the reindex worked to both
# indices, and they preserved their names
self.assertEqual(expected, self.client.count(index=source1)['count'])
self.assertEqual(expected, self.client.count(index=source2)['count'])
def test_reindex_migrate_from_remote_with_pre_suf_fixes(self):
wait_interval = 1
max_wait = 3
source1 = 'my_source1'
source2 = 'my_source2'
prefix = 'my_'
dest = 'MIGRATION'
expected = 3
mpfx = 'pre-'
msfx = '-fix'
# Build remote client
try:
rclient = curator.get_client(
host=rhost, port=rport, skip_version_test=True)
rclient.info()
except:
raise SkipTest(
'Unable to connect to host at {0}:{1}'.format(rhost, rport))
# Build indices remotely.
counter = 0
for rindex in [source1, source2]:
rclient.indices.create(index=rindex)
for i in range(0, 3):
rclient.create(
index=rindex, doc_type='log', id=str(counter+1),
body={"doc" + str(counter+i) :'TEST DOCUMENT'},
)
counter += 1
# Decorators make this pylint exception necessary
# pylint: disable=E1123
rclient.indices.flush(index=rindex, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.migration_reindex.format(
wait_interval,
max_wait,
mpfx,
msfx,
'http://{0}:{1}'.format(rhost, rport),
'REINDEX_SELECTION',
dest,
prefix
)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
# Do our own cleanup here.
rclient.indices.delete(index='{0},{1}'.format(source1, source2))
# And now the neat trick of verifying that the reindex worked to both
# indices, and they preserved their names
self.assertEqual(expected, self.client.count(index='{0}{1}{2}'.format(mpfx,source1,msfx))['count'])
self.assertEqual(expected, self.client.count(index='{0}{1}{2}'.format(mpfx,source1,msfx))['count'])
def test_reindex_from_remote_no_connection(self):
wait_interval = 1
max_wait = 3
bad_port = 70000
dest = 'my_dest'
expected = 1
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.remote_reindex.format(
wait_interval,
max_wait,
'http://{0}:{1}'.format(rhost, bad_port),
'REINDEX_SELECTION',
dest,
'my_'
)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, _.exit_code)
def test_reindex_from_remote_no_indices(self):
wait_interval = 1
max_wait = 3
source1 = 'wrong1'
source2 = 'wrong2'
prefix = 'my_'
dest = 'my_dest'
expected = 1
# Build remote client
try:
rclient = curator.get_client(
host=rhost, port=rport, skip_version_test=True)
rclient.info()
except:
raise SkipTest(
'Unable to connect to host at {0}:{1}'.format(rhost, rport))
# Build indices remotely.
counter = 0
for rindex in [source1, source2]:
rclient.indices.create(index=rindex)
for i in range(0, 3):
rclient.create(
index=rindex, doc_type='log', id=str(counter+1),
body={"doc" + str(counter+i) :'TEST DOCUMENT'},
)
counter += 1
# Decorators make this pylint exception necessary
# pylint: disable=E1123
rclient.indices.flush(index=rindex, force=True)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.remote_reindex.format(
wait_interval,
max_wait,
'http://{0}:{1}'.format(rhost, rport),
'REINDEX_SELECTION',
dest,
prefix
)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
# Do our own cleanup here.
rclient.indices.delete(index='{0},{1}'.format(source1, source2))
self.assertEqual(expected, _.exit_code)
def test_reindex_into_alias(self):
wait_interval = 1
max_wait = 3
source = 'my_source'
dest = 'my_dest'
expected = 3
alias_body = {'aliases' : {dest : {}}}
self.client.indices.create(index='dummy', body=alias_body)
self.add_docs(source)
self.write_config(self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(
self.args['actionfile'], testvars.reindex.format(wait_interval, max_wait, source, dest)
)
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_manual_date_math(self):
wait_interval = 1
max_wait = 3
source = '<source-{now/d}>'
dest = '<target-{now/d}>'
expected = 3
self.create_index(source)
self.add_docs(source)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, source, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, self.client.count(index=dest)['count'])
def test_reindex_bad_mapping(self):
# This test addresses GitHub issue #1260
wait_interval = 1
max_wait = 3
source = 'my_source'
dest = 'my_dest'
expected = 1
ver = curator.get_version(self.client)
if ver < (7, 0, 0):
request_body = {
"settings": { "number_of_shards": 1, "number_of_replicas": 0},
"mappings": { "doc": { "properties": { "doc1": { "type": "keyword" }}}}
}
else:
request_body = {
"settings": { "number_of_shards": 1, "number_of_replicas": 0},
"mappings": { "properties": { "doc1": { "type": "keyword" }}}
}
self.client.indices.create(index=source, body=request_body)
self.add_docs(source)
# Create the dest index with a different mapping.
if ver < (7, 0, 0):
request_body['mappings']['doc']['properties']['doc1']['type'] = 'integer'
else:
request_body['mappings']['properties']['doc1']['type'] = 'integer'
self.client.indices.create(index=dest, body=request_body)
self.write_config(
self.args['configfile'], testvars.client_config.format(host, port))
self.write_config(self.args['actionfile'],
testvars.reindex.format(wait_interval, max_wait, source, dest))
test = clicktest.CliRunner()
_ = test.invoke(
curator.cli,
['--config', self.args['configfile'], self.args['actionfile']],
)
self.assertEqual(expected, _.exit_code)
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naivekun/libhustpass | libhustpass/login.py | d8d487e3af996898e4a7b21b924fbf0fc4fbe419 | import libhustpass.sbDes as sbDes
import libhustpass.captcha as captcha
import requests
import re
import random
def toWideChar(data):
data_bytes = bytes(data, encoding="utf-8")
ret = []
for i in data_bytes:
ret.extend([0, i])
while len(ret) % 8 != 0:
ret.append(0)
return ret
def Enc(data, first_key, second_key, third_key):
data_bytes = toWideChar(data)
key1_bytes = toWideChar(first_key)
key2_bytes = toWideChar(second_key)
key3_bytes = toWideChar(third_key)
ret_ = []
i = 0
while i < len(data_bytes):
tmp = data_bytes[i : i + 8]
x = 0
y = 0
z = 0
while x < len(key1_bytes):
enc1_ = sbDes.des(key1_bytes[x : x + 8], sbDes.ECB)
tmp = list(enc1_.encrypt(tmp))
x += 8
while y < len(key2_bytes):
enc2_ = sbDes.des(key2_bytes[y : y + 8], sbDes.ECB)
tmp = list(enc2_.encrypt(tmp))
y += 8
while z < len(key3_bytes):
enc3_ = sbDes.des(key3_bytes[z : z + 8], sbDes.ECB)
tmp = list(enc3_.encrypt(tmp))
z += 8
ret_.extend(tmp)
i += 8
ret = ""
for i in ret_:
ret += "%02X" % i
return ret
def login(username, password, url):
r = requests.session()
login_html = r.get(url)
captcha_content = r.get("https://pass.hust.edu.cn/cas/code?"+str(random.random()), stream=True)
captcha_content.raw.decode_content = True
nonce = re.search(
'<input type="hidden" id="lt" name="lt" value="(.*)" />', login_html.text
).group(1)
action = re.search(
'<form id="loginForm" action="(.*)" method="post">', login_html.text
).group(1)
post_params = {
"code": captcha.deCaptcha(captcha_content.raw),
"rsa": Enc(username + password + nonce, "1", "2", "3"),
"ul": len(username),
"pl": len(password),
"lt": nonce,
"execution": "e1s1",
"_eventId": "submit",
}
redirect_html = r.post(
"https://pass.hust.edu.cn" + action, data=post_params, allow_redirects=False
)
try:
return redirect_html.headers["Location"]
except:
raise Exception("login failed")
| [((52, 8, 52, 26), 'requests.session', 'requests.session', ({}, {}), '()', False, 'import requests\n'), ((63, 16, 63, 54), 'libhustpass.captcha.deCaptcha', 'captcha.deCaptcha', ({(63, 34, 63, 53): 'captcha_content.raw'}, {}), '(captcha_content.raw)', True, 'import libhustpass.captcha as captcha\n'), ((30, 20, 30, 63), 'libhustpass.sbDes.des', 'sbDes.des', ({(30, 30, 30, 51): 'key1_bytes[x:x + 8]', (30, 53, 30, 62): 'sbDes.ECB'}, {}), '(key1_bytes[x:x + 8], sbDes.ECB)', True, 'import libhustpass.sbDes as sbDes\n'), ((34, 20, 34, 63), 'libhustpass.sbDes.des', 'sbDes.des', ({(34, 30, 34, 51): 'key2_bytes[y:y + 8]', (34, 53, 34, 62): 'sbDes.ECB'}, {}), '(key2_bytes[y:y + 8], sbDes.ECB)', True, 'import libhustpass.sbDes as sbDes\n'), ((38, 20, 38, 63), 'libhustpass.sbDes.des', 'sbDes.des', ({(38, 30, 38, 51): 'key3_bytes[z:z + 8]', (38, 53, 38, 62): 'sbDes.ECB'}, {}), '(key3_bytes[z:z + 8], sbDes.ECB)', True, 'import libhustpass.sbDes as sbDes\n'), ((56, 12, 58, 5), 're.search', 're.search', ({(57, 8, 57, 64): '"""<input type="hidden" id="lt" name="lt" value="(.*)" />"""', (57, 66, 57, 81): 'login_html.text'}, {}), '(\'<input type="hidden" id="lt" name="lt" value="(.*)" />\',\n login_html.text)', False, 'import re\n'), ((59, 13, 61, 5), 're.search', 're.search', ({(60, 8, 60, 59): '"""<form id="loginForm" action="(.*)" method="post">"""', (60, 61, 60, 76): 'login_html.text'}, {}), '(\'<form id="loginForm" action="(.*)" method="post">\', login_html.text)', False, 'import re\n'), ((54, 69, 54, 84), 'random.random', 'random.random', ({}, {}), '()', False, 'import random\n')] |
Asadullah-Dal17/contours-detection-advance | code/contours_sorting_by_area.py | 45522492363cc01cb8c66b18790b1859c4efe44d | import cv2 as cv
import numpy as np
def areaFinder(contours):
areas = []
for c in contours:
a =cv.contourArea(c)
areas.append(a)
return areas
def sortedContoursByArea(img, larger_to_smaller=True):
edges_img = cv.Canny(img, 100, 150)
contours , h = cv.findContours(edges_img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)
sorted_contours = sorted(contours, key=cv.contourArea, reverse=larger_to_smaller)
return sorted_contours
img = cv.imread('./Images/sample-image.png')
sorted_contours = sortedContoursByArea(img, larger_to_smaller=True)
# print(areaFinder(contours))
print(areaFinder(sorted_contours))
for c in sorted_contours:
cv.drawContours(img, c, -1, 244, 3)
cv.imshow('img', img)
cv.waitKey(0)
cv.destroyAllWindows() | [((14, 6, 14, 44), 'cv2.imread', 'cv.imread', ({(14, 16, 14, 43): '"""./Images/sample-image.png"""'}, {}), "('./Images/sample-image.png')", True, 'import cv2 as cv\n'), ((22, 0, 22, 22), 'cv2.destroyAllWindows', 'cv.destroyAllWindows', ({}, {}), '()', True, 'import cv2 as cv\n'), ((10, 16, 10, 39), 'cv2.Canny', 'cv.Canny', ({(10, 25, 10, 28): 'img', (10, 30, 10, 33): '100', (10, 35, 10, 38): '150'}, {}), '(img, 100, 150)', True, 'import cv2 as cv\n'), ((11, 19, 11, 85), 'cv2.findContours', 'cv.findContours', ({(11, 35, 11, 44): 'edges_img', (11, 46, 11, 62): 'cv.RETR_EXTERNAL', (11, 64, 11, 84): 'cv.CHAIN_APPROX_NONE'}, {}), '(edges_img, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_NONE)', True, 'import cv2 as cv\n'), ((19, 4, 19, 40), 'cv2.drawContours', 'cv.drawContours', ({(19, 20, 19, 23): 'img', (19, 25, 19, 26): 'c', (19, 29, 19, 31): '(-1)', (19, 33, 19, 36): '(244)', (19, 38, 19, 39): '(3)'}, {}), '(img, c, -1, 244, 3)', True, 'import cv2 as cv\n'), ((20, 4, 20, 25), 'cv2.imshow', 'cv.imshow', ({(20, 14, 20, 19): '"""img"""', (20, 21, 20, 24): 'img'}, {}), "('img', img)", True, 'import cv2 as cv\n'), ((21, 4, 21, 17), 'cv2.waitKey', 'cv.waitKey', ({(21, 15, 21, 16): '(0)'}, {}), '(0)', True, 'import cv2 as cv\n'), ((6, 11, 6, 28), 'cv2.contourArea', 'cv.contourArea', ({(6, 26, 6, 27): 'c'}, {}), '(c)', True, 'import cv2 as cv\n')] |
ChrisRBXiong/MatchZoo-py | matchzoo/metrics/precision.py | 8883d0933a62610d71fec0215dce643630e03b1c | """Precision for ranking."""
import numpy as np
from matchzoo.engine.base_metric import (
BaseMetric, sort_and_couple, RankingMetric
)
class Precision(RankingMetric):
"""Precision metric."""
ALIAS = 'precision'
def __init__(self, k: int = 1, threshold: float = 0.):
"""
:class:`PrecisionMetric` constructor.
:param k: Number of results to consider.
:param threshold: the label threshold of relevance degree.
"""
self._k = k
self._threshold = threshold
def __repr__(self) -> str:
""":return: Formated string representation of the metric."""
return f"{self.ALIAS}@{self._k}({self._threshold})"
def __call__(self, y_true: np.array, y_pred: np.array) -> float:
"""
Calculate precision@k.
Example:
>>> y_true = [0, 0, 0, 1]
>>> y_pred = [0.2, 0.4, 0.3, 0.1]
>>> Precision(k=1)(y_true, y_pred)
0.0
>>> Precision(k=2)(y_true, y_pred)
0.0
>>> Precision(k=4)(y_true, y_pred)
0.25
>>> Precision(k=5)(y_true, y_pred)
0.2
:param y_true: The ground true label of each document.
:param y_pred: The predicted scores of each document.
:return: Precision @ k
:raises: ValueError: len(r) must be >= k.
"""
if self._k <= 0:
raise ValueError(f"k must be greater than 0."
f"{self._k} received.")
coupled_pair = sort_and_couple(y_true, y_pred)
precision = 0.0
for idx, (label, score) in enumerate(coupled_pair):
if idx >= self._k:
break
if label > self._threshold:
precision += 1.
return precision / self._k
| [((52, 23, 52, 54), 'matchzoo.engine.base_metric.sort_and_couple', 'sort_and_couple', ({(52, 39, 52, 45): 'y_true', (52, 47, 52, 53): 'y_pred'}, {}), '(y_true, y_pred)', False, 'from matchzoo.engine.base_metric import BaseMetric, sort_and_couple, RankingMetric\n')] |
forkunited/ltprg | src/main/py/ltprg/config/seq.py | 4e40d3571d229023df0f845c68643024e04bc202 | from mung.torch_ext.eval import Loss
from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput
from ltprg.model.seq import VariableLengthNLLLoss
# Expects config of the form:
# {
# data_parameter : {
# seq : [SEQUENCE PARAMETER NAME]
# input : [INPUT PARAMETER NAME]
# }
# name : [ID FOR MODEL]
# arch_type : [SequenceModelNoInput|SequenceModelInputToHidden]
# dropout : [DROPOUT]
# rnn_layers : [RNN_LAYERS]
# rnn_size : [SIZE OF RNN HIDDEN LAYER]
# embedding_size : [EMBEDDING_SIZE]
# rnn_type : [RNN TYPE]
# (SequenceModelAttendedInput) attn_type : [EMBEDDING|OUTPUT]
# (SequenceModelInputToHidden) conv_input : [INDICATOR OF WHETHER OR NOT TO CONVOLVE THE INPUT]
# (SequenceModelInputToHidden|SequenceModelAttendedInput) conv_kernel : [KERNEL SIZE FOR CONVOLUTION]
# (SequenceModelInputToHidden|SequenceModelAttendedInput) conv_stride : [STRIDE LENGTH FOR CONVOLUTION]
# }
def load_seq_model(config, D, gpu=False):
data_parameter = DataParameter.make(**config["data_parameter"])
seq_field = data_parameter["seq"]
utterance_size = D[seq_field].get_matrix(0).get_feature_set().get_token_count()
dropout = float(config["dropout"])
rnn_layers = int(config["rnn_layers"])
rnn_size = int(config["rnn_size"])
embedding_size = int(config["embedding_size"])
rnn_type = config["rnn_type"]
if config["arch_type"] == "SequenceModelNoInput":
model = SequenceModelNoInput(config["name"], utterance_size, \
embedding_size, rnn_size, rnn_layers, dropout=dropout, rnn_type=rnn_type)
elif config["arch_type"] == "SequenceModelAttendedInput":
input_field = data_parameter["input"]
input_size = D[input_field].get_feature_set().get_token_count()
conv_kernel = int(config["conv_kernel"])
conv_stride = int(config["conv_stride"])
attn_type = "EMBEDDING"
if "attn_type" in config:
attn_type = config["attn_type"]
model = SequenceModelAttendedInput(config["name"], utterance_size, input_size, \
embedding_size, rnn_size, rnn_layers, dropout=dropout, rnn_type=rnn_type, \
conv_kernel=conv_kernel, conv_stride=conv_stride, attn_type=attn_type)
else:
input_field = data_parameter["input"]
input_size = D[input_field].get_feature_set().get_token_count()
conv_input = False
conv_kernel = 1
conv_stride = 1
if "conv_input" in config:
conv_input = bool(int(config["conv_input"]))
conv_kernel = int(config["conv_kernel"])
conv_stride = int(config["conv_stride"])
model = SequenceModelInputToHidden(config["name"], utterance_size, input_size, \
embedding_size, rnn_size, rnn_layers, dropout=dropout, rnn_type=rnn_type, \
conv_input=conv_input, conv_kernel=conv_kernel, conv_stride=conv_stride)
return data_parameter, model
# Expects config of the form:
# {
# data_parameter : {
# seq : [SEQUENCE PARAMETER NAME]
# input : [INPUT PARAMETER NAME]
# },
# evaluations : [
# name : [NAME FOR EVALUATION]
# type : (VariableLengthNLLLoss)
# data : [NAME OF DATA SUBSET]
# (Optional) data_size : [SIZE OF RANDOM SUBET OF DATA TO TAKE]
# ]
# }
def load_evaluations(config, D, gpu=False):
data_parameter = DataParameter.make(**config["data_parameter"])
evaluations = []
loss_criterion = VariableLengthNLLLoss(norm_dim=True)
if gpu:
loss_criterion = loss_criterion.cuda()
for eval_config in config["evaluations"]:
data = D[eval_config["data"]]
if "data_size" in eval_config:
data = data.get_random_subset(int(eval_config["data_size"]))
if eval_config["type"] == "VariableLengthNLLLoss":
loss = Loss(eval_config["name"], data, data_parameter, loss_criterion, norm_dim=True)
evaluations.append(loss)
else:
raise ValueError("Invalid seq evaluation type in config (" + str(eval_config["type"]))
return evaluations
| [((24, 21, 24, 67), 'ltprg.model.seq.DataParameter.make', 'DataParameter.make', ({}, {}), "(**config['data_parameter'])", False, 'from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput\n'), ((78, 21, 78, 67), 'ltprg.model.seq.DataParameter.make', 'DataParameter.make', ({}, {}), "(**config['data_parameter'])", False, 'from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput\n'), ((81, 21, 81, 57), 'ltprg.model.seq.VariableLengthNLLLoss', 'VariableLengthNLLLoss', (), '', False, 'from ltprg.model.seq import VariableLengthNLLLoss\n'), ((35, 16, 36, 81), 'ltprg.model.seq.SequenceModelNoInput', 'SequenceModelNoInput', (), '', False, 'from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput\n'), ((45, 16, 47, 78), 'ltprg.model.seq.SequenceModelAttendedInput', 'SequenceModelAttendedInput', (), '', False, 'from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput\n'), ((58, 16, 60, 80), 'ltprg.model.seq.SequenceModelInputToHidden', 'SequenceModelInputToHidden', (), '', False, 'from ltprg.model.seq import DataParameter, SequenceModelNoInput, SequenceModelInputToHidden, SequenceModelAttendedInput\n'), ((91, 19, 91, 97), 'mung.torch_ext.eval.Loss', 'Loss', (), '', False, 'from mung.torch_ext.eval import Loss\n')] |
sigseg5/nometa-tg | src/Utilities/metadata_worker.py | 7d0d9f0cf5d8fd98a3808c07a5c44d30f1b13032 | from shutil import move
import piexif
from PIL import Image
def delete_metadata(full_path_to_img):
"""
This function used for remove metadata only from documents, if you send image 'as image' Telegram automatically
removes all metadata at sending. This function removes all metadata via 'piexif' lib, saved image in '/app'
folder, and after that move it to 'documents' folder.
:param full_path_to_img: path to folder with documents e.g.'documents/image.jpg'
"""
piexif.remove(full_path_to_img, "clean_image.jpg")
move("clean_image.jpg", "documents/clean_image.jpg")
def delete_metadata_from_png(full_path_to_img):
"""
This function used for remove metadata only from png documents, if you send image 'as image' Telegram
automatically removes all metadata at sending. This function removes all metadata via 'PIL' lib and saved image
in 'documents' folder.
:param full_path_to_img: path to folder with documents e.g.'documents/image.png'
"""
image = Image.open(full_path_to_img)
image.save("documents/clean_image.png")
| [((14, 4, 14, 54), 'piexif.remove', 'piexif.remove', ({(14, 18, 14, 34): 'full_path_to_img', (14, 36, 14, 53): '"""clean_image.jpg"""'}, {}), "(full_path_to_img, 'clean_image.jpg')", False, 'import piexif\n'), ((15, 4, 15, 56), 'shutil.move', 'move', ({(15, 9, 15, 26): '"""clean_image.jpg"""', (15, 28, 15, 55): '"""documents/clean_image.jpg"""'}, {}), "('clean_image.jpg', 'documents/clean_image.jpg')", False, 'from shutil import move\n'), ((25, 12, 25, 40), 'PIL.Image.open', 'Image.open', ({(25, 23, 25, 39): 'full_path_to_img'}, {}), '(full_path_to_img)', False, 'from PIL import Image\n')] |
pbarton666/virtual_classroom | dkr-py310/docker-student-portal-310/course_files/begin_advanced/py_unit_2.py | a9d0dc2eb16ebc4d2fd451c3a3e6f96e37c87675 | #py_unit_2.py
import unittest
class FirstTest(unittest.TestCase):
def setUp(self):
"setUp() runs before every test"
self.msg="Sorry, Charlie, but {} is not the same as {}."
def tearDown(self):
"tearDown runs after every test"
pass
def test_me(self):
"this test should pass"
first=1
second=2
self.assertEqual(first,1, msg=self.msg.format(first, second))
def test_failing(self):
"this test should fail"
first=1
second=2
self.assertEqual(second,1, msg=self.msg.format(first, second))
def test_passing(self):
"this test should pass, too"
self.assertEqual("b", "b")
def test_passing_a_failing_test(self):
"this test should pass, even though it 'fails'"
self.assertNotEqual("a", "b")
if __name__=='__main__':
unittest.main() | [((30, 1, 30, 16), 'unittest.main', 'unittest.main', ({}, {}), '()', False, 'import unittest\n')] |
Sciocatti/python_scheduler_and_clean_forced_exit | src/scheduled_task/__init__.py | 4e5373ba33798c08096087058773412257230662 | from .scheduled_task import ScheduledTask | [] |
davidnegrazis/PyPlayText-Workshop | scripts/game.py | 70156b73c1d2ab52daaef839b72450e331ff1e80 | from sys import exit
# ------------------------------------------------------------------------------
global dev_name
global game_title
dev_name = "" # enter your name in the quotes!
game_title = "" # enter the game title in the quotes!
# ------------------------------------------------------------------------------
# ---------- initial values ----------
# these are used to define the starting values of your game variables
init_health = 100
init_mana = 200
init_boss_health = 50
# ---------- game variables ----------
# these will be used during the game
health = 0
mana = 0
boss_health = 0
# ---------- some useful functions ----------
# initialize game variables
def init():
global health
global mana
health = init_health
mana = init_mana
# game over
def game_over(msg):
print(msg)
print("Play again? (y / n)")
while (True):
choice = input("> ")
if (choice == "y"):
start()
break
elif (choice == "n"):
exit(0)
else:
print("Options: y / n")
# ---------- room definitions ----------
# here is where you'll create the flow of the game!
# room 0: where the game starts
def room_0():
global health
print("This is the first stage of the game. Create a custom description and get coding!")
print("Current health: " + str(health))
choice = input("> ");
if "end" in choice:
game_over("The game is over")
def start():
start_msg = "Now playing " + game_title + " by " + dev_name
print(start_msg)
init()
room_0()
# ---------- game start ----------
start()
| [((43, 12, 43, 19), 'sys.exit', 'exit', ({(43, 17, 43, 18): '(0)'}, {}), '(0)', False, 'from sys import exit\n')] |
moheed/algo | lc1108_defangip.py | 921bb55852fa49d97e469694a64bffe6c285319e | class Solution:
def defangIPaddr(self, address: str) -> str:
i=0
j=0
strlist=list(address)
defang=[]
while i< len(strlist):
if strlist[i] == '.':
defang.append('[')
defang.append('.')
defang.append(']')
else:
defang.append(address[i])
i+=1
retstr=""
# return string
return (retstr.join(defang))
| [] |
gregbunce/assign_vista_pcts_to_sgid_addrpnts | src/elections_address_files/commands/zip_files.py | c1a3210e68c8c1e94c0b68547d0c26697de77ff7 | import os, zipfile
# Zip files.
def zipfiles(directory):
# File extension to zip.
#ext = ('.gdb', '.csv')
ext = ('.gdb')
# Iterate over all files and check for desired extentions for zipping.
for file in os.listdir(directory):
if file.endswith(ext):
#: Zip it.
input_fgdb_name = file.rsplit( ".", 1)[0]
output_zipped_fgdb_name = "/" + input_fgdb_name + "_gdb.zip"
full_path_to_fgdb = directory + "/" + file
print(" Zipping " + str(full_path_to_fgdb))
outFile = f'{full_path_to_fgdb[0:-4]}_gdb.zip'
gdbName = os.path.basename(full_path_to_fgdb)
with zipfile.ZipFile(outFile,mode='w',compression=zipfile.ZIP_DEFLATED,allowZip64=True) as myzip:
for f in os.listdir(full_path_to_fgdb):
if f[-5:] != '.lock':
myzip.write(os.path.join(full_path_to_fgdb,f),gdbName+'\\'+os.path.basename(f))
else:
continue
| [((11, 16, 11, 37), 'os.listdir', 'os.listdir', ({(11, 27, 11, 36): 'directory'}, {}), '(directory)', False, 'import os, zipfile\n'), ((21, 22, 21, 57), 'os.path.basename', 'os.path.basename', ({(21, 39, 21, 56): 'full_path_to_fgdb'}, {}), '(full_path_to_fgdb)', False, 'import os, zipfile\n'), ((23, 17, 23, 99), 'zipfile.ZipFile', 'zipfile.ZipFile', (), '', False, 'import os, zipfile\n'), ((24, 25, 24, 54), 'os.listdir', 'os.listdir', ({(24, 36, 24, 53): 'full_path_to_fgdb'}, {}), '(full_path_to_fgdb)', False, 'import os, zipfile\n'), ((26, 36, 26, 69), 'os.path.join', 'os.path.join', ({(26, 49, 26, 66): 'full_path_to_fgdb', (26, 67, 26, 68): 'f'}, {}), '(full_path_to_fgdb, f)', False, 'import os, zipfile\n'), ((26, 83, 26, 102), 'os.path.basename', 'os.path.basename', ({(26, 100, 26, 101): 'f'}, {}), '(f)', False, 'import os, zipfile\n')] |
erezsh/tartiflette | tartiflette/parser/nodes/node.py | c945b02e9025e2524393c1eaec2191745bfc38f4 | class Node:
def __init__(self, path, libgraphql_type, location, name):
self.path = path
self.parent = None
self.children = []
self.libgraphql_type = libgraphql_type
self.location = location
self.name = name
def __repr__(self):
return "%s(%s)" % (self.libgraphql_type, self.name)
| [] |
yuyiming/mars | mars/services/web/tests/test_core.py | 5e6990d1ea022444dd646c56697e596ef5d7e747 | # Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import asyncio
import os
import sys
import pytest
from tornado import httpclient
from .... import oscar as mo
from ....utils import get_next_port
from .. import WebActor, web_api, MarsServiceWebAPIHandler, MarsWebAPIClientMixin
from ..api.web import MarsApiEntryHandler
class TestAPIHandler(MarsServiceWebAPIHandler):
__test__ = False
_root_pattern = "/api/test/(?P<test_id>[^/]+)"
@web_api("", method="get")
def get_method_root(self, test_id):
self.write(f"get_root_value_{test_id}")
@web_api("", method="post")
def post_method_root(self, test_id):
self.write(f"post_root_value_{test_id}")
@web_api("subtest/(?P<subtest_id>[^/]+)", method="get")
def get_method_sub_patt(self, test_id, subtest_id):
self.write(f"get_sub_value_{test_id}_{subtest_id}")
@web_api("subtest/(?P<subtest_id>[^/]+)", method="get", arg_filter={"action": "a1"})
async def get_method_sub_patt_match_arg1(self, test_id, subtest_id):
self.write(f"get_sub_value_{test_id}_{subtest_id}_action1")
@web_api("subtest/(?P<subtest_id>[^/]+)", method="get", arg_filter={"action": "a2"})
async def get_method_sub_patt_match_arg2(self, test_id, subtest_id):
self.write(f"get_sub_value_{test_id}_{subtest_id}_action2")
@web_api("subtest_error", method="get")
def get_with_error(self, test_id):
raise ValueError
@web_api("subtest_delay", method="get")
async def get_with_timeout(self, test_id):
await asyncio.sleep(100)
raise ValueError(test_id)
@pytest.fixture
async def actor_pool():
start_method = (
os.environ.get("POOL_START_METHOD", "forkserver")
if sys.platform != "win32"
else None
)
pool = await mo.create_actor_pool(
"127.0.0.1", n_process=0, subprocess_start_method=start_method
)
async with pool:
web_config = {
"host": "127.0.0.1",
"port": get_next_port(),
"web_handlers": {
"/api": MarsApiEntryHandler,
TestAPIHandler.get_root_pattern(): TestAPIHandler,
},
"extra_discovery_modules": ["mars.services.web.tests.extra_handler"],
}
await mo.create_actor(WebActor, web_config, address=pool.external_address)
yield pool, web_config["port"]
class SimpleWebClient(MarsWebAPIClientMixin):
async def fetch(self, path, method="GET", **kwargs):
return await self._request_url(method, path, **kwargs)
@pytest.mark.asyncio
async def test_web_api(actor_pool):
_pool, web_port = actor_pool
recorded_urls = []
def url_recorder(request):
recorded_urls.append(request.url)
return request
client = SimpleWebClient()
client.request_rewriter = url_recorder
res = await client.fetch(f"http://localhost:{web_port}/")
assert res.body.decode()
res = await client.fetch(f"http://localhost:{web_port}/api")
assert res.body.decode()
res = await client.fetch(f"http://localhost:{web_port}/api/test/test_id")
assert res.body.decode() == "get_root_value_test_id"
res = await client.fetch(
f"http://localhost:{web_port}/api/test/test_id", method="POST", data=b""
)
assert res.body.decode() == "post_root_value_test_id"
res = await client.fetch(
f"http://localhost:{web_port}/api/test/test_id/subtest/sub_tid"
)
assert res.body.decode() == "get_sub_value_test_id_sub_tid"
res = await client.fetch(
f"http://localhost:{web_port}/api/test/test_id/subtest/sub_tid?action=a1"
)
assert res.body.decode() == "get_sub_value_test_id_sub_tid_action1"
res = await client.fetch(
f"http://localhost:{web_port}/api/test/test_id/subtest/sub_tid?action=a2"
)
assert res.body.decode() == "get_sub_value_test_id_sub_tid_action2"
with pytest.raises(httpclient.HTTPError) as excinfo:
await client.fetch(f"http://localhost:{web_port}/api/test/test_id/non_exist")
assert excinfo.value.code == 404
with pytest.raises(ValueError):
await client.fetch(
f"http://localhost:{web_port}/api/test/test_id/subtest_error"
)
with pytest.raises(TimeoutError):
await client.fetch(
f"http://localhost:{web_port}/api/test/test_id/subtest_delay",
request_timeout=0.5,
)
res = await client.fetch(f"http://localhost:{web_port}/api/extra_test")
assert "Test" in res.body.decode()
assert len(recorded_urls) > 0
| [((65, 8, 65, 57), 'os.environ.get', 'os.environ.get', ({(65, 23, 65, 42): '"""POOL_START_METHOD"""', (65, 44, 65, 56): '"""forkserver"""'}, {}), "('POOL_START_METHOD', 'forkserver')", False, 'import os\n'), ((132, 9, 132, 44), 'pytest.raises', 'pytest.raises', ({(132, 23, 132, 43): 'httpclient.HTTPError'}, {}), '(httpclient.HTTPError)', False, 'import pytest\n'), ((136, 9, 136, 34), 'pytest.raises', 'pytest.raises', ({(136, 23, 136, 33): 'ValueError'}, {}), '(ValueError)', False, 'import pytest\n'), ((141, 9, 141, 36), 'pytest.raises', 'pytest.raises', ({(141, 23, 141, 35): 'TimeoutError'}, {}), '(TimeoutError)', False, 'import pytest\n'), ((58, 14, 58, 32), 'asyncio.sleep', 'asyncio.sleep', ({(58, 28, 58, 31): '(100)'}, {}), '(100)', False, 'import asyncio\n')] |
caizhanjin/deepseg | test/test.py | 5e91a387683ad73075b51b49da8957d8f4bb6b7f | """
例子为MNIST，对手写图片进行分类。
神经网络hello world。
"""
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
# 封装网络用到的API
def weight_variable(shape):
initial = tf.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial)
def bias_variable(shape):
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial)
def conv2d(x, W):
return tf.nn.conv2d(x,
W,
strides= [1, 1, 1, 1],
padding= 'SAME')
def max_pool_2x2(x):
return tf.nn.max_pool(x,
ksize= [1, 2, 2, 1],
strides= [1, 2, 2, 1],
padding='SAME')
"""
MNIST进阶
"""
sess = tf.InteractiveSession()
# [batch_size, 784]
x = tf.placeholder('float', shape=[None, 784])
y_ = tf.placeholder('float', shape=[None, 10])
"""
第一层卷积
"""
W_conv1 = weight_variable([5, 5, 1, 32])
b_conv1 = bias_variable([32])
# [batch_size, 28, 28, 1]
x_image = tf.reshape(x, [-1, 28, 28, 1])
# [batch_size, 28, 28, 32]
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
# [batch_size, 14, 14, 32]
h_pool1 = max_pool_2x2(h_conv1)
"""
第二层卷积
"""
W_conv2 = weight_variable([5, 5, 32, 64])
b_conv2 = bias_variable([64])
# [batch_size, 14, 14, 64]
h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
# [batch_size, 7, 7, 64]
h_pool2 = max_pool_2x2(h_conv2)
"""
全连接层
"""
w_fc1 = weight_variable([7 * 7 * 64, 1024])
b_fc1 = bias_variable([1024])
# [batch_size, 7*7*64]
h_pool2_flat = tf.reshape(h_pool2, [-1, 7 * 7 * 64])
# [batch_size, 1024]
h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, w_fc1) + b_fc1)
"""
dropout
"""
keep_prob = tf.placeholder("float")
h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)
"""
输出层
"""
W_fc2 = weight_variable([1024, 10])
b_fc2 = bias_variable([10])
# [batch_size, 10]
y_conv = tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2)
y_sum = tf.reduce_sum(y_conv[0])
# 计算损失和添加优化器
cross_entropy = -tf.reduce_sum(y_ * tf.log(y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
# 评估模型
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
# 初始化
sess.run(tf.initialize_all_variables())
for i in range(1):
batch = mnist.train.next_batch(50)
# train_accuracy = accuracy.eval(feed_dict={x:batch[0],
# y_: batch[1],
# keep_prob: 1.0})
# print("step %d, training accuracy %g" % (i, train_accuracy))
y_conv_re = y_conv.eval(feed_dict={x: batch[0],
y_: batch[1],
keep_prob: 1.0})
# print(y_conv_re.shape)
print(y_conv_re)
y_sum_re = y_sum.eval(feed_dict={x: batch[0],
y_: batch[1],
keep_prob: 1.0})
print(y_sum_re)
train_step.run(feed_dict={x: batch[0],
y_: batch[1],
keep_prob: 0.5})
print("test accuracy %g" % accuracy.eval(feed_dict={x: mnist.test.images,
y_: mnist.test.labels,
keep_prob: 1.0}))
| [((8, 8, 8, 61), 'tensorflow.examples.tutorials.mnist.input_data.read_data_sets', 'input_data.read_data_sets', (), '', False, 'from tensorflow.examples.tutorials.mnist import input_data\n'), ((40, 7, 40, 30), 'tensorflow.InteractiveSession', 'tf.InteractiveSession', ({}, {}), '()', True, 'import tensorflow as tf\n'), ((42, 4, 42, 46), 'tensorflow.placeholder', 'tf.placeholder', (), '', True, 'import tensorflow as tf\n'), ((43, 5, 43, 46), 'tensorflow.placeholder', 'tf.placeholder', (), '', True, 'import tensorflow as tf\n'), ((52, 10, 52, 40), 'tensorflow.reshape', 'tf.reshape', ({(52, 21, 52, 22): 'x', (52, 24, 52, 39): '[-1, 28, 28, 1]'}, {}), '(x, [-1, 28, 28, 1])', True, 'import tensorflow as tf\n'), ((77, 15, 77, 52), 'tensorflow.reshape', 'tf.reshape', ({(77, 26, 77, 33): 'h_pool2', (77, 35, 77, 51): '[-1, 7 * 7 * 64]'}, {}), '(h_pool2, [-1, 7 * 7 * 64])', True, 'import tensorflow as tf\n'), ((84, 12, 84, 35), 'tensorflow.placeholder', 'tf.placeholder', ({(84, 27, 84, 34): '"""float"""'}, {}), "('float')", True, 'import tensorflow as tf\n'), ((85, 13, 85, 44), 'tensorflow.nn.dropout', 'tf.nn.dropout', ({(85, 27, 85, 32): 'h_fc1', (85, 34, 85, 43): 'keep_prob'}, {}), '(h_fc1, keep_prob)', True, 'import tensorflow as tf\n'), ((95, 8, 95, 32), 'tensorflow.reduce_sum', 'tf.reduce_sum', ({(95, 22, 95, 31): 'y_conv[0]'}, {}), '(y_conv[0])', True, 'import tensorflow as tf\n'), ((14, 14, 14, 52), 'tensorflow.truncated_normal', 'tf.truncated_normal', (), '', True, 'import tensorflow as tf\n'), ((15, 11, 15, 31), 'tensorflow.Variable', 'tf.Variable', ({(15, 23, 15, 30): 'initial'}, {}), '(initial)', True, 'import tensorflow as tf\n'), ((19, 14, 19, 43), 'tensorflow.constant', 'tf.constant', (), '', True, 'import tensorflow as tf\n'), ((20, 11, 20, 31), 'tensorflow.Variable', 'tf.Variable', ({(20, 23, 20, 30): 'initial'}, {}), '(initial)', True, 'import tensorflow as tf\n'), ((24, 11, 27, 40), 'tensorflow.nn.conv2d', 'tf.nn.conv2d', (), '', True, 'import tensorflow as tf\n'), ((31, 11, 34, 41), 'tensorflow.nn.max_pool', 'tf.nn.max_pool', (), '', True, 'import tensorflow as tf\n'), ((102, 30, 102, 50), 'tensorflow.argmax', 'tf.argmax', ({(102, 40, 102, 46): 'y_conv', (102, 48, 102, 49): '1'}, {}), '(y_conv, 1)', True, 'import tensorflow as tf\n'), ((102, 52, 102, 68), 'tensorflow.argmax', 'tf.argmax', ({(102, 62, 102, 64): 'y_', (102, 66, 102, 67): '1'}, {}), '(y_, 1)', True, 'import tensorflow as tf\n'), ((103, 26, 103, 62), 'tensorflow.cast', 'tf.cast', ({(103, 34, 103, 52): 'correct_prediction', (103, 54, 103, 61): '"""float"""'}, {}), "(correct_prediction, 'float')", True, 'import tensorflow as tf\n'), ((106, 9, 106, 38), 'tensorflow.initialize_all_variables', 'tf.initialize_all_variables', ({}, {}), '()', True, 'import tensorflow as tf\n'), ((79, 19, 79, 49), 'tensorflow.matmul', 'tf.matmul', ({(79, 29, 79, 41): 'h_pool2_flat', (79, 43, 79, 48): 'w_fc1'}, {}), '(h_pool2_flat, w_fc1)', True, 'import tensorflow as tf\n'), ((94, 23, 94, 51), 'tensorflow.matmul', 'tf.matmul', ({(94, 33, 94, 43): 'h_fc1_drop', (94, 45, 94, 50): 'W_fc2'}, {}), '(h_fc1_drop, W_fc2)', True, 'import tensorflow as tf\n'), ((99, 13, 99, 41), 'tensorflow.train.AdamOptimizer', 'tf.train.AdamOptimizer', ({(99, 36, 99, 40): '0.0001'}, {}), '(0.0001)', True, 'import tensorflow as tf\n'), ((98, 36, 98, 50), 'tensorflow.log', 'tf.log', ({(98, 43, 98, 49): 'y_conv'}, {}), '(y_conv)', True, 'import tensorflow as tf\n')] |
jwvhewitt/gearhead-caramel | game/content/ghplots/lancemates.py | dfe1bc5dbf2960b82a97577f4bf687b60040d8bf | import pbge
from game.content.plotutility import LMSkillsSelfIntro
from game.content import backstory
from pbge.plots import Plot
from pbge.dialogue import Offer, ContextTag
from game.ghdialogue import context
import gears
import game.content.gharchitecture
import game.content.ghterrain
import random
from game import memobrowser
Memo = memobrowser.Memo
# *******************
# *** UTILITIES ***
# *******************
def get_hire_cost(camp, npc):
return (npc.renown * npc.renown * (200 - npc.get_reaction_score(camp.pc, camp)))//10
# **************************
# *** RANDOM_LANCEMATE ***
# **************************
class UtterlyRandomLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
def custom_init(self, nart):
npc = gears.selector.random_character(rank=min(random.randint(10, 50),random.randint(10, 50)),
mecha_colors=gears.color.random_mecha_colors(),
local_tags=tuple(self.elements["METROSCENE"].attributes),
combatant=True)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
specialties = [sk for sk in gears.stats.NONCOMBAT_SKILLS if sk in npc.statline]
if random.randint(-12,3) > len(specialties):
npc.statline[random.choice(gears.stats.NONCOMBAT_SKILLS)] += random.randint(1,4)
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class UtterlyGenericLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
JOBS = ("Mecha Pilot","Arena Pilot","Recon Pilot","Mercenary","Bounty Hunter")
def custom_init(self, nart):
npc = gears.selector.random_character(rank=min(random.randint(10, 50),random.randint(10, 50)),
job=gears.jobs.ALL_JOBS[random.choice(self.JOBS)],
mecha_colors=gears.color.random_mecha_colors(),
local_tags=tuple(self.elements["METROSCENE"].attributes),
combatant=True)
if random.randint(1,20) == 1:
npc.statline[random.choice(gears.stats.NONCOMBAT_SKILLS)] += random.randint(1,4)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class GiftedNewbieLancemate(Plot):
# Amazing stats, amazingly crap skills.
LABEL = "RANDOM_LANCEMATE"
JOBS = ("Mecha Pilot","Arena Pilot","Citizen","Explorer","Factory Worker")
UNIQUE = True
def custom_init(self, nart):
npc = gears.selector.random_character(statline=gears.base.Being.random_stats(random.randint(100, 110)),
rank=random.randint(5, 15),
job=gears.jobs.ALL_JOBS[random.choice(self.JOBS)],
mecha_colors=gears.color.random_mecha_colors(),
local_tags=tuple(self.elements["METROSCENE"].attributes),
combatant=True, birth_year=nart.camp.year - random.randint(18,23))
if random.randint(1,10) == 1:
npc.statline[random.choice(gears.stats.NONCOMBAT_SKILLS)] += random.randint(1,4)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class OlderMentorLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
UNIQUE = True
def custom_init(self, nart):
npc = gears.selector.random_character(rank=random.randint(41, 85),
mecha_colors=gears.color.random_mecha_colors(),
local_tags=tuple(self.elements["METROSCENE"].attributes),
combatant=True, birth_year=nart.camp.year - random.randint(32,50))
npc.statline[random.choice(gears.stats.NONCOMBAT_SKILLS)] += random.randint(1, 4)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class DeadzonerInGreenZoneLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
JOBS = ("Mercenary","Bandit","Scavenger","Aristo","Tekno","Sheriff")
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return gears.personality.GreenZone in pstate.elements["METROSCENE"].attributes
def custom_init(self, nart):
npc = gears.selector.random_character(rank=min(random.randint(20, 55),random.randint(20, 55)),
job=gears.jobs.ALL_JOBS[random.choice(self.JOBS)],
mecha_colors=gears.color.random_mecha_colors(),
local_tags=(gears.personality.DeadZone,),
combatant=True)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class GladiatorLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return gears.personality.DeadZone in pstate.elements["METROSCENE"].attributes
def custom_init(self, nart):
npc = gears.selector.random_character(rank=min(random.randint(25, 65),random.randint(25, 65)),
can_cyberize=True,
job=gears.jobs.ALL_JOBS["Gladiator"],
mecha_colors=gears.color.random_mecha_colors(),
local_tags=(gears.personality.DeadZone,),
combatant=True)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate: gears.GearHeadScene):
return isinstance(candidate,pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class MutantLancemate(Plot):
LABEL = "RANDOM_LANCEMATE"
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return {gears.personality.GreenZone,gears.personality.DeadZone}.intersection(pstate.elements["METROSCENE"].attributes)
def custom_init(self, nart):
npc = gears.selector.random_character(rank=random.randint(20, 45),
mecha_colors=gears.color.random_mecha_colors(),
local_tags=tuple(self.elements["METROSCENE"].attributes),
combatant=True)
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
mutation = random.choice(gears.personality.MUTATIONS)
mutation.apply(npc)
npc.personality.add(mutation)
specialties = [sk for sk in gears.stats.NONCOMBAT_SKILLS if sk in npc.statline]
if random.randint(-12,3) > len(specialties):
npc.statline[random.choice(gears.stats.NONCOMBAT_SKILLS)] += random.randint(1,4)
self.register_element("NPC", npc, dident="LOCALE")
self.add_sub_plot(nart, "RLM_Relationship")
return True
def _is_best_scene(self,nart,candidate):
return isinstance(candidate, pbge.scenes.Scene) and gears.tags.SCENE_PUBLIC in candidate.attributes
class FormerLancemateReturns(Plot):
LABEL = "RANDOM_LANCEMATE"
active = True
scope = "METRO"
def custom_init(self, nart):
npc: gears.base.Character = nart.camp.egg.seek_dramatis_person(nart.camp, self._is_good_npc, self)
if npc:
scene = self.seek_element(nart, "LOCALE", self._is_best_scene, scope=self.elements["METROSCENE"])
self.register_element("NPC", npc, dident="LOCALE")
#print(npc,scene)
self.bs = backstory.Backstory(("LONGTIMENOSEE",),keywords=[t.name.upper() for t in npc.get_tags()])
return npc
def _is_good_npc(self,nart,candidate):
return isinstance(candidate, gears.base.Character) and candidate.relationship and gears.relationships.RT_LANCEMATE in candidate.relationship.tags
def _is_best_scene(self,nart,candidate):
return isinstance(candidate,gears.GearHeadScene) and gears.tags.SCENE_PUBLIC in candidate.attributes
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if npc is self.elements["NPC"]:
for k in self.bs.results.keys():
mygram[k] = [self.bs.get_one(k),]
else:
mygram["[News]"] = ["{NPC} has been hanging out at {LOCALE}".format(**self.elements), ]
return mygram
def NPC_offers(self, camp):
mylist = list()
mylist.append(Offer("[INFO_PERSONAL]",
context=ContextTag([context.PERSONAL]),
no_repeats=True, effect=self.end_plot))
return mylist
def t_START(self, camp):
if self.elements["NPC"] in camp.party:
self.end_plot(camp)
# **************************
# *** RLM_Relationship ***
# **************************
# Elements:
# NPC: The NPC who needs a personality
# METROSCENE: The city or whatever that the NPC calls home
#
# These subplots contain a personality for a random (potential) lancemate.
# Also include a means for the lancemate to gain the "RT_LANCEMATE" tag.
class RLM_Beginner(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return pstate.elements["NPC"].renown < 25
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(attitude=gears.relationships.A_JUNIOR)
# This character gets fewer mecha points.
npc.relationship.data["mecha_level_bonus"] = -10
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
mylist.append(Offer("I can't believe you asked me... [LETSGO]",
context=ContextTag((context.JOIN,)),
effect=self._join_lance
))
mylist.append(Offer(
"[HELLO] Some day I want to become a cavalier like you.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
# This is an NPC in Wujung. Give them some news.
mygram["[News]"] = ["{} has dreams of someday becoming a cavalier".format(self.elements["NPC"]), ]
return mygram
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="As far as I know {} usually hangs out at {}.".format(mynpc,mynpc.get_scene()),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo( "{} dreams of becoming a cavalier.".format(mynpc)
, mynpc.get_scene()
)
class RLM_Friendly(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(attitude=gears.relationships.A_FRIENDLY)
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate() and npc.get_reaction_score(camp.pc, camp) > 0:
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] [LETSGO]",
context=ContextTag((context.JOIN,)),
effect=self._join_lance
))
mylist.append(Offer(
"[HELLO] [WAITINGFORMISSION]", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
# This is an NPC in Wujung. Give them some news.
mygram["[News]"] = ["{} is looking for a lance to join".format(self.elements["NPC"]), ]
return mygram
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="You can usually find {} at {}, if you're planning to invite {} to join your lance.".format(mynpc,mynpc.get_scene(),mynpc.gender.object_pronoun),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo( "{} is looking for a lance to join.".format(mynpc)
, mynpc.get_scene()
)
class RLM_Medic(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
VIRTUES = (gears.personality.Peace,gears.personality.Fellowship)
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return pstate.elements["NPC"].job and gears.tags.Medic in pstate.elements["NPC"].job.tags
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(expectation=gears.relationships.E_GREATERGOOD)
new_virtue = random.choice(self.VIRTUES)
if new_virtue not in npc.personality:
npc.personality.add(new_virtue)
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] [LETSGO]",
context=ContextTag((context.JOIN,)),
effect=self._join_lance
))
else:
mylist.append(Offer("You've got a full crew right now, but if you ever find yourself in need of a qualified medic come back and find me.",
context=ContextTag((context.JOIN,)),
effect=self._defer_join
))
mylist.append(Offer(
"[HELLO] Lately I've been spending too much time here, when I'd rather be out in the danger zone saving lives.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
# This is an NPC in Wujung. Give them some news.
mygram["[News]"] = ["{} wants to leave {} so {} can make a positive difference in the world".format(self.elements["NPC"],self.elements["NPC"].get_scene(),self.elements["NPC"].gender.subject_pronoun), ]
return mygram
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _defer_join(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
self.end_plot(camp)
class RLM_Mercenary(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return pstate.elements["NPC"].job and {gears.tags.Adventurer,gears.tags.Military}.intersection(pstate.elements["NPC"].job.tags)
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(expectation=gears.relationships.E_MERCENARY)
# This character gets extra mecha points, showing their good investment sense.
npc.relationship.data["mecha_level_bonus"] = 10
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
self.hire_cost = get_hire_cost(camp,npc)
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
mylist.append(Offer("I'll join your lance for a mere ${}. [DOYOUACCEPTMYOFFER]".format(self.hire_cost),
context=ContextTag((context.PROPOSAL, context.JOIN)),
data={"subject": "joining my lance"},
subject=self, subject_start=True,
))
mylist.append(Offer("[DENY_JOIN] [GOODBYE]",
context=ContextTag((context.DENY, context.JOIN)), subject=self
))
if camp.credits >= self.hire_cost:
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] [LETSGO]",
context=ContextTag((context.ACCEPT, context.JOIN)), subject=self,
effect=self._join_lance
))
mylist.append(Offer(
"[HELLO] I am a mercenary pilot, looking for my next contract.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
# This is an NPC in Wujung. Give them some news.
mygram["[News]"] = ["{} is hoping to make some quick cash".format(self.elements["NPC"]), ]
return mygram
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
camp.credits -= self.hire_cost
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="As far as I know {} can usually be found at {}.".format(mynpc,mynpc.get_scene()),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo("{} is a mercenary pilot looking for a job.".format(mynpc)
, mynpc.get_scene()
)
class RLM_Professional(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
@classmethod
def matches( self, pstate ):
"""Returns True if this plot matches the current plot state."""
return pstate.elements["NPC"].renown > 20
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(expectation=gears.relationships.E_PROFESSIONAL)
# This character gets 10 extra stat points, showing their elite nature.
npc.roll_stats(10, clear_first=False)
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
self.hire_cost = get_hire_cost(camp,npc)
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
mylist.append(Offer(
"[NOEXPOSURE] I think ${} is a fair signing price. [DOYOUACCEPTMYOFFER]".format(self.hire_cost),
context=ContextTag((context.PROPOSAL, context.JOIN)), data={"subject": "joining my lance"},
subject=self, subject_start=True,
))
mylist.append(Offer("[DENY_JOIN] [GOODBYE]",
context=ContextTag((context.DENY, context.JOIN)), subject=self
))
if camp.credits >= self.hire_cost:
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] [LETSGO]",
context=ContextTag((context.ACCEPT, context.JOIN)), subject=self,
effect=self._join_lance
))
mylist.append(Offer(
"[HELLO] I see you are also a cavalier.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
# This is an NPC in Wujung. Give them some news.
mygram["[News]"] = ["{} is an experienced pilot looking for work".format(self.elements["NPC"]), ]
return mygram
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
camp.credits -= self.hire_cost
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="You can usually find {} at {}. Bring cash if you're planning to hire {}.".format(mynpc,mynpc.get_scene(),mynpc.gender.object_pronoun),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo( "{} is an experienced pilot looking for work.".format(mynpc)
, mynpc.get_scene()
)
class RLM_RatherGeneric(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship()
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
self.hire_cost = get_hire_cost(camp,npc)
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
if npc.get_reaction_score(camp.pc, camp) > 60:
mylist.append(Offer("[IWOULDLOVETO] [THANKS_FOR_CHOOSING_ME]",
context=ContextTag((context.PROPOSAL, context.JOIN)),
data={"subject": "joining my lance"},
effect=self._join_lance
))
else:
mylist.append(Offer("My regular signing rate is ${}. [DOYOUACCEPTMYOFFER]".format(self.hire_cost),
context=ContextTag((context.PROPOSAL, context.JOIN)),
data={"subject": "joining my lance"},
subject=self, subject_start=True,
))
mylist.append(Offer("[DENY_JOIN] [GOODBYE]",
context=ContextTag((context.DENY, context.JOIN)), subject=self
))
if camp.credits >= self.hire_cost:
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] [LETSGO]",
context=ContextTag((context.ACCEPT, context.JOIN)), subject=self,
effect=self._pay_to_join
))
mylist.append(Offer(
"[HELLO] [WAITINGFORMISSION]", context=ContextTag((context.HELLO,))
))
else:
mylist.append(Offer(
"[HELLO] Must be nice going off, having adventures with your lancemates. I'd like to do that again someday.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
mygram["[News]"] = ["{} is looking for a new lance to join".format(self.elements["NPC"]), ]
return mygram
def _pay_to_join(self,camp):
camp.credits -= self.hire_cost
self._join_lance(camp)
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="You can find {} at {}.".format(mynpc,mynpc.get_scene()),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo("{} is looking for a new lance.".format(mynpc)
, mynpc.get_scene()
)
class RLM_DamagedGoodsSale(Plot):
LABEL = "RLM_Relationship"
active = True
scope = True
UNIQUE = True
def custom_init(self, nart):
npc = self.elements["NPC"]
npc.relationship = gears.relationships.Relationship(expectation=gears.relationships.E_IMPROVER)
# This NPC gets a stat bonus but a crappy mech to show their history.
npc.relationship.data["mecha_level_bonus"] = -15
npc.roll_stats(5, clear_first=False)
self._got_rumor = False
return True
def NPC_offers(self, camp):
mylist = list()
npc = self.elements["NPC"]
self.hire_cost = get_hire_cost(camp,npc)//2
if gears.relationships.RT_LANCEMATE not in npc.relationship.tags:
if camp.can_add_lancemate():
if npc.get_reaction_score(camp.pc, camp) > 20:
mylist.append(Offer("[IWOULDLOVETO] I'll do my best to not let you down.",
context=ContextTag((context.PROPOSAL, context.JOIN)),
data={"subject": "joining my lance"},
effect=self._join_lance
))
else:
mylist.append(Offer("I'll sign up with you for just ${}. [DOYOUACCEPTMYOFFER]".format(self.hire_cost),
context=ContextTag((context.PROPOSAL, context.JOIN)),
data={"subject": "joining my lance"},
subject=self, subject_start=True,
))
mylist.append(Offer("[DENY_JOIN] [GOODBYE]",
context=ContextTag((context.DENY, context.JOIN)), subject=self
))
if camp.credits >= self.hire_cost:
mylist.append(Offer("[THANKS_FOR_CHOOSING_ME] I'll do my best to not let you down.",
context=ContextTag((context.ACCEPT, context.JOIN)), subject=self,
effect=self._pay_to_join
))
mylist.append(Offer(
"[HELLO] The life of a cavalier is full of ups and downs... right now I'm in one of those downs.", context=ContextTag((context.HELLO,))
))
else:
mylist.append(Offer(
"[HELLO] Be careful out there... all it takes is one little mistake to cost you everything.", context=ContextTag((context.HELLO,))
))
mylist.append(LMSkillsSelfIntro(npc))
return mylist
def _get_dialogue_grammar(self, npc, camp):
mygram = dict()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"]:
mygram["[News]"] = ["{NPC} is a down on {NPC.gender.possessive_determiner} luck cavalier looking for another chance".format(**self.elements), ]
return mygram
def _pay_to_join(self,camp):
camp.credits -= self.hire_cost
self._join_lance(camp)
def _join_lance(self, camp):
npc = self.elements["NPC"]
npc.relationship.tags.add(gears.relationships.RT_LANCEMATE)
effect = game.content.plotutility.AutoJoiner(npc)
effect(camp)
self.end_plot(camp)
def _get_generic_offers(self, npc, camp):
"""Get any offers that could apply to non-element NPCs."""
goffs = list()
if camp.scene.get_root_scene() is self.elements["METROSCENE"] and npc is not self.elements["NPC"] and not self._got_rumor:
mynpc = self.elements["NPC"]
goffs.append(Offer(
msg="You can find {} at {}. Don't say that you weren't warned.".format(mynpc,mynpc.get_scene()),
context=ContextTag((context.INFO,)), effect=self._get_rumor,
subject=str(mynpc), data={"subject": str(mynpc)}, no_repeats=True
))
return goffs
def _get_rumor(self,camp):
mynpc = self.elements["NPC"]
self._got_rumor = True
self.memo = Memo( "{} is looking for a new lance.".format(mynpc)
, mynpc.get_scene()
)
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zzzzzz0407/detectron2 | projects/detr/scripts/dd.py | 021fc5b1502bbba54e4714735736898803835ab0 | import json
if __name__ == '__main__':
jsonFile = '/data00/home/zhangrufeng1/projects/detectron2/projects/detr/datasets/mot/mot17/annotations/mot17_train_half.json'
with open(jsonFile, 'r') as f:
infos = json.load(f)
count_dict = dict()
for info in infos["images"]:
if info["file_name"] in ["MOT17-02-FRCNN/img1/000091.jpg"]:
for ann in infos['annotations']:
if ann["image_id"] not in count_dict.keys() and ann["iscrowd"] == 0 and ann["bbox"][2] >= 1e-5 and ann["bbox"][3] >= 1e-5:
count_dict[ann["image_id"]] = 1
elif ann["image_id"] in count_dict.keys() and ann["iscrowd"] == 0:
count_dict[ann["image_id"]] += 1
max_count = 0
min_count = 999
num_freq = 0
for key, value in count_dict.items():
max_count = max(max_count, value)
min_count = min(min_count, value)
if value > 100:
num_freq += 1
print("max_count: {}".format(max_count))
print("min_count: {}".format(min_count))
print("num_freq: {}".format(num_freq))
| [] |
wesleibarboza/natasha-virtual | app/app.py | 74c5ef9a4db5ce98dd72499d40775bfd65d34974 | # -*- coding: utf-8 -*-
"""Archivo principal para el echobot. Main File for the echobot"""
from fbmq import Page
from flask import Flask, request
# Token generado por la página web. Generated token in the facebook web page
PAGE_ACCESS_TOKEN = "COPY_HERE_YOUR_PAGE_ACCES_TOKEN"
# Token generado por nosotros. Token generated by us
VERIFY_TOKEN = "EchoBotChido" # Si cambias este token, asegúrate de cambiarlo también en la página de configuración del webhook. If you change this token, verify that you changed it too in the webhook configuration.
app = Flask(__name__)
page = Page(PAGE_ACCESS_TOKEN) # Generamos la instancia de la página de facebook. We make the facebook page instance
@app.route('/')
def hello_world():
"""La página principal del servidor. The server main page."""
return 'Inicio del servidor'
@app.route('/webhook', methods=['GET', 'POST'])
def webhook():
"""El método que se ejecuta cuando Facebook se conecta. This method executes as Facebook connect to us."""
if request.method == 'POST': # if the message is a POST, we handle it with message_handler. Si el mensaje es POST, se maneja con el message_handler
# Facebook sends the user messages with a POST. Facebook manda los mensajes del usuario con un POST.
page.handle_webhook(request.get_data(as_text=True))
return 'ok'
elif request.method == 'GET': # if the message is a GET, we handle it here. Si el mensaje es un GET, lo manejamos aquí.
# The first you configure the webhook, FB sends a GET to your webhook to verify that it really is you, and you're not working on someone's else page.
# La primera vez que se configura el webhook, FB manda un mensaje GET para ver que realmente eres tú, y no estás trabajando en la página de alguien más.
if request.args.get('hub.verify_token') == VERIFY_TOKEN:
# If the verify token in the url matches our verify token we answer with the challenge to prove our identity.
# Si el verify token de la url concuerda con el de nosotros le respondemos con el challenge o reto para verificar que somos nosotros
return request.args.get('hub.challenge')
return 'Wrong Verify token'
@page.handle_message
def message_handler(event):
"""Este método se ejecuta cuando nos llega un mensaje a la página. This method executes whenever a message is sent to our page."""
# Se saca el id del sender. We get the sender id.
sender_id = event.sender_id
# Vemos si el mensaje es un texto o un adjunto (imagen, gif, sticker, etc)
# We see if the message is a text or an attachment (image, GIF, sticker, etc)
if event.is_text_message:
# We get the message from the event variable and sent it back7
# Obtenemos el mensaje de la variable event y se lo regresamos al usuario
page.send(sender_id, "Hey, you send me: {}".format(event.message_text))
elif event.is_attachment_message:
page.send(sender_id, "Boo, you didn't send a text. ")
if __name__ == '__main__':
app.run(host="127.0.0.1", port=5000, debug=True, threaded=True)
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Water2style/FCN-pytorch-CanRun | Camvid/CamVid_utlis.py | b2994f98930580cd2c32f58d19f94becb68a3ccb | # -*- coding: utf-8 -*-
from __future__ import print_function
from matplotlib import pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import scipy.misc
import random
import os
import imageio
#############################
# global variables #
#############################
root_dir = "/home/water/DATA/camvid-master"
data_dir = os.path.join(root_dir, "701_StillsRaw_full") # train data
label_dir = os.path.join(root_dir, "LabeledApproved_full") # train label
label_colors_file = os.path.join(root_dir, "label_colors.txt") # color to label
val_label_file = os.path.join(root_dir, "val.csv") # validation file
train_label_file = os.path.join(root_dir, "train.csv") # train file
# create dir for label index
label_idx_dir = os.path.join(root_dir, "Labeled_idx")
if not os.path.exists(label_idx_dir):
os.makedirs(label_idx_dir)
label2color = {}
color2label = {}
label2index = {}
index2label = {}
def divide_train_val(val_rate=0.1, shuffle=True, random_seed=None):
data_list = os.listdir(data_dir) #返回这个目录里，所有内容，‘图1’‘，图2’......
data_len = len(data_list) #702个图片 #注意这里是训练集
val_len = int(data_len * val_rate) #训练集700张，分10%的数量给验证集
if random_seed: #设置随机种子
random.seed(random_seed) #看看后面哪里用
if shuffle:
#sample(seq, n) 从序列seq中选择n个随机且独立的元素
data_idx = random.sample(range(data_len), data_len)
# data_idx 是从0到702 随机排序的数组
else:
data_idx = list(range(data_len)) #这个就是从0到702 依次排序
val_idx = [data_list[i] for i in data_idx[:val_len]] # 前70个，图片名 List
train_idx = [data_list[i] for i in data_idx[val_len:]] # 71到702个
# !创建 create val.csv
# "w"打开一个文件只用于写入。如果该文件已存在则打开文件，
# 并从开头开始编辑，即原有内容会被删除。
# 如果该文件不存在，创建新文件。
v = open(val_label_file, "w")
v.write("img,label\n") #write() 方法用于向文件中写入指定字符串
for idx, name in enumerate(val_idx):
if 'png' not in name: ##跳过损坏文件
continue
img_name = os.path.join(data_dir, name)
lab_name = os.path.join(label_idx_dir, name)
lab_name = lab_name.split(".")[0] + "_L.png.npy"
v.write("{},{}\n".format(img_name, lab_name))
#最后生成了一个.csv文件，位于根目录
## 装的信息是： 2列，一列是验证集，70张 生图路径+名字，第二列是验证集对应的：标签图+名字+.npy
#png.npy ：后面parse_label函数，就是在标签图路径里 生成 标签图+名字+.npy 文件！！！
# create train.csv 所以这2个.csv文件，这里存放的是信息 ，是： 生图信息和标签图+npy信息
t = open(train_label_file, "w")
t.write("img,label\n")
for idx, name in enumerate(train_idx):
if 'png' not in name:
continue
img_name = os.path.join(data_dir, name)
lab_name = os.path.join(label_idx_dir, name)
lab_name = lab_name.split(".")[0] + "_L.png.npy"
t.write("{},{}\n".format(img_name, lab_name))
#parse：分析 分析标签
def parse_label():
# change label to class index
#“r”：以只读方式打开文件。文件的指针将会放在文件的开头。这是默认模式。
#label_colors.txt :！！装的是颜色和对应标签 64 128 64\tAnimal 颜色\t类别
# 只读，读好了之后 #不igore 就会bug
f = open(label_colors_file, "r").read().split("\n")[:-1] # ignore the last empty line
for idx, line in enumerate(f):
label = line.split()[-1] #提取所有label形成一个字符串 #动物，人，墙..
color = tuple([int(x) for x in line.split()[:-1]]) #形成一个元组 对应动物，人，墙..
#的颜色，比如动物的颜色是红色 ：[128,0,0]....
print(label, color)
#d[key] = value
#设置d[key]的值为value，如果该key不存在，则为新增
#label2color[label] = color 运行后：
#就形成了1个字典： 以label做key，以color做value的新字典
#包含内容：{'Animal': (64, 128, 64), 'Archway': (192, 0, 128).....}
#后面有精彩用法....
label2color[label] = color
color2label[color] = label #{颜色：标签}
label2index[label] = idx # {标签：idx} {'Animal': 0, 'Archway': 1...}
index2label[idx] = label # {idx:标签}
#下面是作者自己标注的：
# rgb = np.zeros((255, 255, 3), dtype=np.uint8)
# rgb[..., 0] = color[0]
# rgb[..., 1] = color[1]
# rgb[..., 2] = color[2]
# imshow(rgb, title=label)
#enumerate ：迭代器，0号，内容0;1号，内容1
for idx, name in enumerate(os.listdir(label_dir)): #os.listdir(label_dir) 是标签集里所有图片
#idx就是从0开始的序号 name是图片名 #os.listdir() 方法用于返回指定的文件夹包含的文件或文件夹的名字的列表，这个列表以字母顺序。
filename = os.path.join(label_idx_dir, name) # labeled_idx/所有图片名
if os.path.exists(filename + '.npy'): #检查是否有图片名.png.npy，当前应该是没有的
print("Skip %s" % (name)) #有了就跳过这个图 npy是numpy文件
continue
print("Parse %s" % (name)) ## 打出：Parse 图片名（不包含路径）
img = os.path.join(label_dir, name) ## img是路径，LabeledApproved_full/所有图片名
## 区分一下 和 filename之间的用法和关联？
img = imageio.imread(img) #用numpy(npy)格式打开一个图
height, weight, _ = img.shape # numpy存储图片格式（高，宽，3通道）
#Tensor是（3，高，宽）
#在大for循环里，对每一张图执行下面操作 img是上面读取的一个npy格式的图哈
idx_mat = np.zeros((height, weight)) #720*960
for h in range(height):
for w in range(weight): #前面也有个color啊，不同作用域功能不同
color = tuple(img[h, w]) # tuple(序列)，把序列转为元组
#这里应该是把img[h,w]这个！像素点！（128,64,64）
# 抓出来弄成了一个元组，又因为遍历
#所以color是一个有 height*weight个元素的tuple
#color包含着这个图片里，所有的颜色
try: #try，except： 异常检测，try里顺序执行，如果，去执行except
#tuple类型的color在这里作为key，输出相应的value，也就是label值，dict的存储是一一对应的
#所以 出来的label是和输入的color 一一对应
label = color2label[color] # 给彩图像素点，返回像素点的label，就像是上面那图里只有猫和北京，返回：cat space
index = label2index[label] # 给label返回类型代表的号码，给cat sapce，返回1,5
idx_mat[h, w] = index #构成了一个由颜色到标签到标签序号处理后的图，一个点一个点送？
except:
print("error: img:%s, h:%d, w:%d" % (name, h, w))
idx_mat = idx_mat.astype(np.uint8) #转换数据类型
np.save(filename, idx_mat) #numpy.save(file, arr, allow_pickle=True, fix_imports=True)
#把当前（因为这个for里是逐像素点处理一张图）这个图的信息(numpy)存起来
print("Finish %s" % (name))
#跳出for，这个位置就是处理好了所有的图，生成了702个 png.npy图
#生成的这个是一个numpy图，每个图上，是标记好的序号
#就像 一个张图里是 建筑和空白，建筑位置上显示：4，4 = buildings标签 = buildings颜色[128,0,0]
# test some pixels' label ～～～～～～～～～～～～～～～～～～～～～～～～～～`
#img = os.path.join(label_dir, os.listdir(label_dir)[0]) #img数据：img[height,weight,rgb]
#img = imageio.imread(img)
#test_cases = [(555, 405), (0, 0), (380, 645), (577, 943)] # img[555,405]:此图此点的！位置信息！
#test_ans = ['Car', 'Building', 'Truck_Bus', 'Car'] #这个是肉眼去看哈，看上面的位置，对应的是啥label
#for idx, t in enumerate(test_cases):
#color = img[t] #相当于访问 img上的4个点的位置信息，输出的是这4个点对应的像素值(img是labeled，就那32个规整的颜色)
#assert color2label[tuple(color)] == test_ans[idx] ##检查一下对不对
#上面是作者乱标的，所以报错，我在jupyter通过肉眼看图并且调试，就对了哈！！
'''debug function'''
def imshow(img, title=None):
try:
img = mpimg.imread(img) #mpimg： matplotlib.image 输入的img是个地址哈，不是啥处理后的numpy数组
imgplot = plt.imshow(img)
except:
plt.imshow(img, interpolation='nearest')
if title is not None:
plt.title(title)
plt.show()
if __name__ == '__main__':
print("it starts working")
divide_train_val(random_seed=1)
parse_label()
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patrik999/AdaptiveStreamReasoningMonitoring | stream-reasoner/ws_client.py | 7bbfa1a394e0127e0c4ea670a632be216c83faea | #!/usr/bin/env python
import websocket
import time
try:
import thread
except ImportError:
import _thread as thread
runs = 100
def on_message(ws, message):
print(message)
def on_error(ws, error):
print(error)
def on_close(ws):
print("### closed ###")
def on_open(ws):
def run(*args):
for i in range(runs):
time.sleep(5)
ws.send("Ping")
time.sleep(1)
ws.close()
print("thread terminating...")
thread.start_new_thread(run, ())
if __name__ == "__main__":
websocket.enableTrace(True)
url = "ws://localhost:8082"
ws = websocket.WebSocketApp(url, on_message = on_message, on_error = on_error, on_close = on_close)
ws.on_open = on_open
ws.run_forever()
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samuelterra22/Data-Mining | Main.py | 0237bc6e86f28f7bf1306dfb60c41987f5e41bbd | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
import seaborn as sns
from matplotlib import rcParams
import statsmodels.api as sm
from statsmodels.formula.api import ols
df = pd.read_csv('kc_house_data.csv')
# print(df.head())
# print(df.isnull().any())
# print(df.describe())
# fig = plt.figure(figsize=(12, 6))
# sqft = fig.add_subplot(121)
# cost = fig.add_subplot(122)
#
# sqft.hist(df.sqft_living, bins=80)
# sqft.set_xlabel('Ft^2')
# sqft.set_title("Histogram of House Square Footage")
#
# cost.hist(df.price, bins=80)
# cost.set_xlabel('Price ($)')
# cost.set_title("Histogram of Housing Prices")
#
# plt.show()
# m = ols('price ~ sqft_living', df).fit()
# print(m.summary())
# m = ols('price ~ sqft_living + bedrooms + grade + condition',df).fit()
# print (m.summary())
sns.jointplot(x="sqft_living", y="price", data=df, kind='reg', fit_reg=True, size=7)
plt.show()
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11uc/whole_cell_patch | whole_cell_patch/filterDialog.py | 84e11bbb904b363a6bb5af878d46e23d789c5be0 | # Dialogs for setting filter parameters.
from PyQt5.QtWidgets import QLabel, QGridLayout, QPushButton, \
QLineEdit, QVBoxLayout, QHBoxLayout, QDialog, QComboBox, QWidget
from PyQt5.QtCore import pyqtSignal
class FilterDialog(QDialog):
'''
Dialog for choosing filter types.
'''
def __init__(self, default, parent = None):
'''
Build ui and set up parameter setting
Parameters
----------
default: list
List of filters, which are dictionaries with names under
key "name" and parameter elements.
parent: QWidget, optional
Parent widget.
Attributes
----------
fnames: dictionary
Names of filters, two nested dictionaries to specify two
properties about the type of filters.
'''
self.defaultFilters = default
super().__init__(parent)
self.filterCb = QComboBox(self) # Filter type
self.bandCb = QComboBox(self) # Band type
self.fnames = {}
count = 0
for f in default:
names = f["name"].split(',')
if names[0] not in self.fnames:
self.fnames[names[0]] = {}
self.filterCb.addItem(names[0])
if len(names) > 1:
if names[1] not in self.fnames[names[0]]:
self.fnames[names[0]][names[1]] = count
else:
self.fnames[names[0]][''] = count
count += 1
okBtn = QPushButton("OK", self)
cancelBtn = QPushButton("Cancel", self)
okBtn.clicked.connect(self.accept)
cancelBtn.clicked.connect(self.reject)
self.filterCb.currentTextChanged.connect(self.updateBand)
topVB = QVBoxLayout(self)
topVB.addWidget(self.filterCb)
topVB.addWidget(self.bandCb)
topVB.addWidget(okBtn)
topVB.addWidget(cancelBtn)
def updateBand(self, name):
'''
Update list of band in the band combobox.
Parameters
----------
name: str
Name of filter type.
'''
self.bandCb.clear()
self.bandCb.addItems(list(self.fnames[name].keys()))
def exec_(self):
'''
Override QDialog exec_ function. Alter return code to -1 for rejection
and integer number for chosen filter's id.
'''
ret = super().exec_()
if ret:
return self.fnames[self.filterCb.currentText()][
self.bandCb.currentText()]
else:
return -1
class FilterParamDialog(QDialog):
'''
Dialog for setting filter parameters.
'''
def __init__(self, parent = None):
'''
Build ui and set up connections.
Parameters
----------
parent: QWidget, optional
Parent widget.
Attributes
----------
form: dictionary
Parameter names as keys and corresponding QLineEdit object
as values.
formWd: QWidget
Container for displaying the parameter setting form.
'''
super().__init__(parent)
self.form = {}
okBtn = QPushButton("OK", self)
cancelBtn = QPushButton("Cancel", self)
topVB = QVBoxLayout(self)
self.formVB = QVBoxLayout()
self.formWd = None
btnHB = QHBoxLayout()
btnHB.addWidget(okBtn)
btnHB.addWidget(cancelBtn)
cancelBtn.clicked.connect(self.reject)
okBtn.clicked.connect(self.accept)
topVB.addLayout(self.formVB)
topVB.addLayout(btnHB)
def makeForm(self, filt):
'''
Build parameters setting grid layout for filter filt.
Parameters
----------
filt: dictionary
Filter information, parameters are in string format.
'''
# clear the previous form widget
if self.formWd != None:
self.formVB.removeWidget(self.formWd)
self.form = {}
self.formWd.setParent(None)
del self.formWd
self.formWd = None
self.formWd = QWidget()
formGrid = QGridLayout(self.formWd)
row = 0
for k, v in filt.items():
if k != "name":
self.form[k] = QLineEdit(v, self.formWd)
formGrid.addWidget(QLabel(k, self.formWd), row, 0)
formGrid.addWidget(self.form[k], row, 1)
row = row + 1
self.formVB.addWidget(self.formWd)
def getForm(self):
'''
Get the parameters filled in the QLineEdit objects.
Returns
-------
filt: dictionary
Filter information, without name.
'''
filt = {}
for k, v in self.form.items():
filt[k] = v.text()
return filt
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zl930216/ParlAI | projects/controllable_dialogue/tasks/agents.py | abf0ad6d1779af0f8ce0b5aed00d2bab71416684 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import copy
from .build import build, make_path
from parlai.utils.misc import warn_once
from parlai.core.teachers import ParlAIDialogTeacher
def _path(opt):
build(opt)
datatype = opt['datatype'].split(':')[0]
if datatype == 'test':
warn_once("WARNING: Test set not included. Setting datatype to valid.")
datatype = 'valid'
return make_path(opt, datatype + '.txt')
class DefaultTeacher(ParlAIDialogTeacher):
def __init__(self, opt, shared=None):
opt = copy.deepcopy(opt)
opt['parlaidialogteacher_datafile'] = _path(opt)
super().__init__(opt, shared)
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davisschenk/project-euler-python | problems/p009.py | 1375412e6c8199ab02250bd67223c758d4df1725 | from math import ceil, sqrt
from problem import Problem
from utils.math import gcd
class PythagoreanTriplet(Problem, name="Special Pythagorean triplet", expected=31875000):
@Problem.solution()
def brute_force(self, ts=1000):
for a in range(3, round((ts - 3) / 2)):
for b in range(a + 1, round((ts - 1 - a) / 2)):
c = ts - a - b
if c * c == a * a + b * b:
return a * b * c
@Problem.solution()
def parametrisation(self, ts=1000):
s2 = ts / 2
mlimit = ceil(sqrt(s2)) - 1
for m in range(2, mlimit):
if s2 % m == 0:
sm = s2 / m
while sm % 2 == 0:
sm /= 2
if m % 2 == 1:
k = m + 2
else:
k = m + 1
while k < 2 * m and k <= sm:
if sm % k == 0 and gcd(k, m) == 1:
d = s2 / (k * m)
n = k - m
a = d * (m * m - n * n)
b = 2 * d * m * n
c = d * (m * m + n * n)
return a * b * c
k += 2
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murbanec/Roche2D | Roche.py | a4d7e85e893fd6f18c12b682c2c8ca33b2b549a6 |
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 14 10:37:04 2021
@author: martin urbanec
"""
#calculates trajectory of small mass positioned close to L4 Lagrange point
#creates gif as output
import math
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, PillowWriter
DistanceJ = 778570000000. # m JUPITER FROM SUN
G = 6.67259*10**-11
Jupiter_mass = 1.8982*10**27 # kg
Sun_mass = 1.989*10**30 # kg
M1=Sun_mass
M2=Jupiter_mass
a=DistanceJ
Ang_vel=math.sqrt(G*(M1+M2)/(a**3)) #FROM KEPLER LAW
P=2.*math.pi/Ang_vel #Period
#center of mass is located at [0,0] massive object (Sun) is located at -r1, secondary object (Jupiter) is located at +r2
r2=M1*a/(M1+M2)
r1=M2*a/(M1+M2)
# Calculations are done in corotating frame
# s1, s2 are distances from sources of gravity (Sun, Jupiter)
def pot(x,y):
r=math.sqrt(x*x + y*y)
if x==0:
if y>0:
theta=math.pi/2.
if y<0:
theta=math.pi/2.
if x>0:
theta=math.atan(abs(y)/x)
else:
theta=math.pi-math.atan(abs(y)/x)
s1=math.sqrt(r1*r1 + r*r + 2.*r1*r*math.cos(theta))
s2=math.sqrt(r2*r2 + r*r - 2.*r2*r*math.cos(theta))
result = -G*(M1/s1 + M2/s2) -1.*Ang_vel*Ang_vel*r*r/2.
return result
#Force per unit mass (acceleration) in x direction
# ax = \partial pot(x,y) / \partial x - 2 \Omega \times v
# in our case \Omega=(0,0,\Omega) and v=(vx,vy,0)
# second term is corresponding to Coriolis force
def ax(x,y,vx,vy):
dx=a/1000.
# result=-(pot(x+dx,y) -pot(x-dx,y))/(2.*dx) + 2.* Ang_vel*vy
result=-(-pot(x+2.*dx,y) + 8.*pot(x+dx,y) - 8.*pot(x-dx,y) + pot(x-2.*dx,y))/(12.*dx) + 2.* Ang_vel*vy
return result
def ay(x,y,vx,vy):
dy=a/1000.
# result=-( pot(x,y+dy)-pot(x,y-dy))/(dy*2.) - 2.* Ang_vel*vx
result=-(-pot(x,y+2.*dy) + 8.*pot(x,y+dy) - 8.*pot(x,y-dy) + pot(x,y-2*dy))/(dy*12.) - 2.* Ang_vel*vx
return result
pot2=np.vectorize(pot)
#TRAJECTORY OF ASTEROID CLOSE STARTING CLOSE TO L4 in rest with respect to the rotating frame
x0=a/2.-r1
y0=math.sqrt(3)*a/2.
x0=1.005*x0
y0=1.005*y0
vx0=0.
vy0=0.
steps=300000
#initialize arrays
x= np.linspace(0, 10, steps)
y= np.linspace(0, 10, steps)
vx=np.linspace(0, 10, steps)
vy=np.linspace(0, 10, steps)
t= np.linspace(0, 10, steps)
x[0]=x0
vx[0]=vx0
y[0]=y0
vy[0]=vy0
t[0]=0.
i=0
timescale = math.sqrt((a*a)**1.5 / G/(M1+M2))
dt=timescale/1000.
#using 4th order Runge-Kutta to solve the a_x= d v_x/ dt
# dt is constant set to timescale/1000
for i in range (1,steps):
t[i]=(t[i-1]+dt)
Kx1=dt*ax(x[i-1],y[i-1],vx[i-1],vy[i-1])
Kx2=dt*ax(x[i-1],y[i-1],vx[i-1]+Kx1/2.,vy[i-1])
Kx3=dt*ax(x[i-1],y[i-1],vx[i-1]+Kx2/2.,vy[i-1])
Kx4=dt*ax(x[i-1],y[i-1],vx[i-1]+Kx3,vy[i-1])
vx[i]=vx[i-1] + Kx1/6. + Kx2/3. + Kx3/3. + Kx4/6.
Ky1=dt*ay(x[i-1],y[i-1],vx[i-1],vy[i-1])
Ky2=dt*ay(x[i-1],y[i-1],vx[i-1],vy[i-1]+Ky1/2.)
Ky3=dt*ay(x[i-1],y[i-1],vx[i-1],vy[i-1]+Ky2/2.)
Ky4=dt*ay(x[i-1],y[i-1],vx[i-1],vy[i-1]+Ky3)
vy[i]=vy[i-1] + Ky1/6. + Ky2/3. + Ky3/3. + Ky4/6.
x[i]=x[i-1] + (vx[i-1]+vx[i])*dt/2. #taking the average of velocities
y[i]=y[i-1] + (vy[i-1]+vy[i])*dt/2.
dt=timescale/1000.
#LAGRANGE POINTS
#L3, L1 and L2 points are lying on x-axis (left to right) for small values of alpha=M2/(M1+M2) the positions can are given analytically (to first order in alpha)
alpha=M2/(M1+M2)
L1X=a*(1.-(alpha/3.)**(1./3.))
L1Y=0.
P1=pot(L1X,L1Y)
L2X=a*(1.+(alpha/3.)**(1./3.))
L2Y=0.
P2=pot(L2X,L2Y)
L3X=-a*(1. + 5.*alpha/12)
L3Y=0.
P3=pot(L3X,L3Y)
L4X=a/2.-r1
L4Y=math.sqrt(3)*a/2.
P4=pot2(L4X,L4Y)
P0=pot(x0,y0)
steps=301
xx= np.arange(-2*a, 2.*a,a/steps)
yy= np.arange(-1.5*a, 1.5*a,a/steps)
X, Y = np.meshgrid(xx, yy)
Z1=pot2(X,Y)
fig, ax = plt.subplots()
ax.set_aspect('equal','box')
ln1, = plt.plot([],[], 'k+')
ln2, = plt.plot([], [], 'm*')
XXX,YYY=[],[]
def init():
ax.set_xlim(-1.25,1.25)
ax.set_ylim(-1.25,1.25)
ax.contour(X/a, Y/a, Z1,levels=[P1,P2,P3,P0],colors=('r', 'green', 'blue', 'm'))
def update(i):
ln1.set_data(x[1000*i]/a, y[1000*i]/a)
zed= np.arange(60)
ani = FuncAnimation(fig, update, np.arange(300), init_func=init)
plt.show()
writer = PillowWriter(fps=25)
ani.save("Animation.gif", writer=writer)
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LyleH/youtube-dl | youtube_dl/extractor/azubu.py | 7564b09ef5c09454908f78cb91c3bd2d6daacac5 | from __future__ import unicode_literals
import json
from .common import InfoExtractor
from ..utils import (
ExtractorError,
float_or_none,
sanitized_Request,
)
class AzubuIE(InfoExtractor):
_VALID_URL = r'https?://(?:www\.)?azubu\.tv/[^/]+#!/play/(?P<id>\d+)'
_TESTS = [
{
'url': 'http://www.azubu.tv/GSL#!/play/15575/2014-hot6-cup-last-big-match-ro8-day-1',
'md5': 'a88b42fcf844f29ad6035054bd9ecaf4',
'info_dict': {
'id': '15575',
'ext': 'mp4',
'title': '2014 HOT6 CUP LAST BIG MATCH Ro8 Day 1',
'description': 'md5:d06bdea27b8cc4388a90ad35b5c66c01',
'thumbnail': 're:^https?://.*\.jpe?g',
'timestamp': 1417523507.334,
'upload_date': '20141202',
'duration': 9988.7,
'uploader': 'GSL',
'uploader_id': 414310,
'view_count': int,
},
},
{
'url': 'http://www.azubu.tv/FnaticTV#!/play/9344/-fnatic-at-worlds-2014:-toyz---%22i-love-rekkles,-he-has-amazing-mechanics%22-',
'md5': 'b72a871fe1d9f70bd7673769cdb3b925',
'info_dict': {
'id': '9344',
'ext': 'mp4',
'title': 'Fnatic at Worlds 2014: Toyz - "I love Rekkles, he has amazing mechanics"',
'description': 'md5:4a649737b5f6c8b5c5be543e88dc62af',
'thumbnail': 're:^https?://.*\.jpe?g',
'timestamp': 1410530893.320,
'upload_date': '20140912',
'duration': 172.385,
'uploader': 'FnaticTV',
'uploader_id': 272749,
'view_count': int,
},
'skip': 'Channel offline',
},
]
def _real_extract(self, url):
video_id = self._match_id(url)
data = self._download_json(
'http://www.azubu.tv/api/video/%s' % video_id, video_id)['data']
title = data['title'].strip()
description = data.get('description')
thumbnail = data.get('thumbnail')
view_count = data.get('view_count')
user = data.get('user', {})
uploader = user.get('username')
uploader_id = user.get('id')
stream_params = json.loads(data['stream_params'])
timestamp = float_or_none(stream_params.get('creationDate'), 1000)
duration = float_or_none(stream_params.get('length'), 1000)
renditions = stream_params.get('renditions') or []
video = stream_params.get('FLVFullLength') or stream_params.get('videoFullLength')
if video:
renditions.append(video)
if not renditions and not user.get('channel', {}).get('is_live', True):
raise ExtractorError('%s said: channel is offline.' % self.IE_NAME, expected=True)
formats = [{
'url': fmt['url'],
'width': fmt['frameWidth'],
'height': fmt['frameHeight'],
'vbr': float_or_none(fmt['encodingRate'], 1000),
'filesize': fmt['size'],
'vcodec': fmt['videoCodec'],
'container': fmt['videoContainer'],
} for fmt in renditions if fmt['url']]
self._sort_formats(formats)
return {
'id': video_id,
'title': title,
'description': description,
'thumbnail': thumbnail,
'timestamp': timestamp,
'duration': duration,
'uploader': uploader,
'uploader_id': uploader_id,
'view_count': view_count,
'formats': formats,
}
class AzubuLiveIE(InfoExtractor):
_VALID_URL = r'https?://(?:www\.)?azubu\.tv/(?P<id>[^/]+)$'
_TEST = {
'url': 'http://www.azubu.tv/MarsTVMDLen',
'only_matching': True,
}
def _real_extract(self, url):
user = self._match_id(url)
info = self._download_json(
'http://api.azubu.tv/public/modules/last-video/{0}/info'.format(user),
user)['data']
if info['type'] != 'STREAM':
raise ExtractorError('{0} is not streaming live'.format(user), expected=True)
req = sanitized_Request(
'https://edge-elb.api.brightcove.com/playback/v1/accounts/3361910549001/videos/ref:' + info['reference_id'])
req.add_header('Accept', 'application/json;pk=BCpkADawqM1gvI0oGWg8dxQHlgT8HkdE2LnAlWAZkOlznO39bSZX726u4JqnDsK3MDXcO01JxXK2tZtJbgQChxgaFzEVdHRjaDoxaOu8hHOO8NYhwdxw9BzvgkvLUlpbDNUuDoc4E4wxDToV')
bc_info = self._download_json(req, user)
m3u8_url = next(source['src'] for source in bc_info['sources'] if source['container'] == 'M2TS')
formats = self._extract_m3u8_formats(m3u8_url, user, ext='mp4')
self._sort_formats(formats)
return {
'id': info['id'],
'title': self._live_title(info['title']),
'uploader_id': user,
'formats': formats,
'is_live': True,
'thumbnail': bc_info['poster'],
}
| [((67, 24, 67, 57), 'json.loads', 'json.loads', ({(67, 35, 67, 56): "data['stream_params']"}, {}), "(data['stream_params'])", False, 'import json\n')] |
dan-blanchard/conda-build | conda_build/main_develop.py | 2db31bb2c48d2459e16df80172967d906f43b355 | # (c) Continuum Analytics, Inc. / http://continuum.io
# All Rights Reserved
#
# conda is distributed under the terms of the BSD 3-clause license.
# Consult LICENSE.txt or http://opensource.org/licenses/BSD-3-Clause.
from __future__ import absolute_import, division, print_function
import sys
from os.path import join, isdir, abspath, expanduser, exists
import shutil
from conda.cli.common import add_parser_prefix, get_prefix
from conda.cli.conda_argparse import ArgumentParser
from conda_build.main_build import args_func
from conda_build.post import mk_relative_osx
from conda_build.utils import _check_call, rec_glob
from conda.install import linked
def main():
p = ArgumentParser(
description="""
Install a Python package in 'development mode'.
This works by creating a conda.pth file in site-packages."""
# TODO: Use setup.py to determine any entry-points to install.
)
p.add_argument(
'source',
action="store",
metavar='PATH',
nargs='+',
help="Path to the source directory."
)
p.add_argument('-npf', '--no-pth-file',
action='store_true',
help=("Relink compiled extension dependencies against "
"libraries found in current conda env. "
"Do not add source to conda.pth."))
p.add_argument('-b', '--build_ext',
action='store_true',
help=("Build extensions inplace, invoking: "
"python setup.py build_ext --inplace; "
"add to conda.pth; relink runtime libraries to "
"environment's lib/."))
p.add_argument('-c', '--clean',
action='store_true',
help=("Invoke clean on setup.py: "
"python setup.py clean "
"use with build_ext to clean before building."))
p.add_argument('-u', '--uninstall',
action='store_true',
help=("Removes package if installed in 'development mode' "
"by deleting path from conda.pth file. Ignore other "
"options - just uninstall and exit"))
add_parser_prefix(p)
p.set_defaults(func=execute)
args = p.parse_args()
args_func(args, p)
def relink_sharedobjects(pkg_path, build_prefix):
'''
invokes functions in post module to relink to libraries in conda env
:param pkg_path: look for shared objects to relink in pkg_path
:param build_prefix: path to conda environment which contains lib/. to find
runtime libraries.
.. note:: develop mode builds the extensions in place and makes a link to
package in site-packages/. The build_prefix points to conda environment
since runtime libraries should be loaded from environment's lib/. first
'''
# find binaries in package dir and make them relocatable
bin_files = rec_glob(pkg_path, ['.so'])
for b_file in bin_files:
if sys.platform == 'darwin':
mk_relative_osx(b_file, build_prefix)
else:
print("Nothing to do on Linux or Windows.")
def write_to_conda_pth(sp_dir, pkg_path):
'''
Append pkg_path to conda.pth in site-packages directory for current
environment. Only add path if it doens't already exist.
:param sp_dir: path to site-packages/. directory
:param pkg_path: the package path to append to site-packes/. dir.
'''
c_file = join(sp_dir, 'conda.pth')
with open(c_file, 'a') as f:
with open(c_file, 'r') as cf:
# make sure file exists, before we try to read from it hence nested
# in append with block
# expect conda.pth to be small so read it all in at once
pkgs_in_dev_mode = cf.readlines()
# only append pkg_path if it doesn't already exist in conda.pth
if pkg_path + '\n' in pkgs_in_dev_mode:
print("path exits, skipping " + pkg_path)
else:
f.write(pkg_path + '\n')
print("added " + pkg_path)
def get_site_pkg(prefix, py_ver):
'''
Given the path to conda environment, find the site-packages directory
:param prefix: path to conda environment. Look here for current
environment's site-packages
:returns: absolute path to site-packages directory
'''
# get site-packages directory
stdlib_dir = join(prefix, 'Lib' if sys.platform == 'win32' else
'lib/python%s' % py_ver)
sp_dir = join(stdlib_dir, 'site-packages')
return sp_dir
def get_setup_py(path_):
''' Return full path to setup.py or exit if not found '''
# build path points to source dir, builds are placed in the
setup_py = join(path_, 'setup.py')
if not exists(setup_py):
sys.exit("No setup.py found in {0}. Exiting.".format(path_))
return setup_py
def clean(setup_py):
'''
This invokes:
$ python setup.py clean
:param setup_py: path to setup.py
'''
# first call setup.py clean
cmd = ['python', setup_py, 'clean']
_check_call(cmd)
print("Completed: " + " ".join(cmd))
print("===============================================")
def build_ext(setup_py):
'''
Define a develop function - similar to build function
todo: need to test on win32 and linux
It invokes:
$ python setup.py build_ext --inplace
:param setup_py: path to setup.py
'''
# next call setup.py develop
cmd = ['python', setup_py, 'build_ext', '--inplace']
_check_call(cmd)
print("Completed: " + " ".join(cmd))
print("===============================================")
def uninstall(sp_dir, pkg_path):
'''
Look for pkg_path in conda.pth file in site-packages directory and remove
it. If pkg_path is not found in conda.pth, it means package is not
installed in 'development mode' via conda develop.
:param sp_dir: path to site-packages/. directory
:param pkg_path: the package path to be uninstalled.
'''
o_c_pth = join(sp_dir, 'conda.pth')
n_c_pth = join(sp_dir, 'conda.pth.temp')
found = False
with open(n_c_pth, 'w') as new_c:
with open(o_c_pth, 'r') as orig_c:
for line in orig_c:
if line != pkg_path + '\n':
new_c.write(line)
else:
print("uninstalled: " + pkg_path)
found = True
if not found:
print("conda.pth does not contain path: " + pkg_path)
print("package not installed via conda develop")
shutil.move(n_c_pth, o_c_pth)
def execute(args, parser):
prefix = get_prefix(args)
if not isdir(prefix):
sys.exit("""\
Error: environment does not exist: %s
#
# Use 'conda create' to create the environment first.
#""" % prefix)
for package in linked(prefix):
name, ver, _ = package .rsplit('-', 2)
if name == 'python':
py_ver = ver[:3] # x.y
break
else:
raise RuntimeError("python is not installed in %s" % prefix)
# current environment's site-packages directory
sp_dir = get_site_pkg(prefix, py_ver)
for path in args.source:
pkg_path = abspath(expanduser(path))
if args.uninstall:
# uninstall then exit - does not do any other operations
uninstall(sp_dir, pkg_path)
sys.exit(0)
if args.clean or args.build_ext:
setup_py = get_setup_py(pkg_path)
if args.clean:
clean(setup_py)
if not args.build_ext:
sys.exit(0)
# build extensions before adding to conda.pth
if args.build_ext:
build_ext(setup_py)
if not args.no_pth_file:
write_to_conda_pth(sp_dir, pkg_path)
# go through the source looking for compiled extensions and make sure
# they use the conda environment for loading libraries at runtime
relink_sharedobjects(pkg_path, prefix)
print("completed operation for: " + pkg_path)
if __name__ == '__main__':
main()
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ltgoslo/norBERT | benchmarking/experiments/sanity_check.py | d75d5c12d9b7f9cc11c65757f2228b7e6070b69b | #!/bin/env python3
from transformers import TFBertForTokenClassification
from data_preparation.data_preparation_pos import MBERTTokenizer as MBERT_Tokenizer_pos
import sys
if __name__ == "__main__":
if len(sys.argv) > 1:
modelname = sys.argv[1]
else:
modelname = "ltgoslo/norbert"
model = TFBertForTokenClassification.from_pretrained(modelname, from_pt=True)
tokenizer = MBERT_Tokenizer_pos.from_pretrained(modelname, do_lower_case=False)
print(tokenizer)
| [((12, 12, 12, 81), 'transformers.TFBertForTokenClassification.from_pretrained', 'TFBertForTokenClassification.from_pretrained', (), '', False, 'from transformers import TFBertForTokenClassification\n'), ((13, 16, 13, 83), 'data_preparation.data_preparation_pos.MBERTTokenizer.from_pretrained', 'MBERT_Tokenizer_pos.from_pretrained', (), '', True, 'from data_preparation.data_preparation_pos import MBERTTokenizer as MBERT_Tokenizer_pos\n')] |
WosunOO/nca_xianshu | nca47/api/controllers/v1/firewall/securityZone.py | bbb548cb67b755a57528796d4c5a66ee68df2678 | from oslo_serialization import jsonutils as json
from nca47.api.controllers.v1 import base
from nca47.common.i18n import _
from nca47.common.i18n import _LI, _LE
from nca47.common.exception import Nca47Exception
from oslo_log import log
from nca47.api.controllers.v1 import tools
from nca47.manager.central import CentralManager
from nca47.common.exception import ParamFormatError
from amqp.five import string
from nca47.common.exception import BadRequest
from oslo_messaging import RemoteError
from nca47.common import exception
LOG = log.getLogger(__name__)
class SecurityZoneController(base.BaseRestController):
def __init__(self):
self.manager = CentralManager.get_instance()
super(SecurityZoneController, self).__init__()
def create(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone create", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['tenant_id', 'dc_name', 'network_zone',
'name', 'ifnames', 'priority', 'vfwname']
values = tools.validat_values(body_values, valid_attributes)
LOG.info(_LI("input the SecurityZone values with dic format \
is %(json)s"),
{"json": body_values})
values["name"] = (values["tenant_id"] + "_" +
values["network_zone"] +
"_" + values["name"])
response = self.manager.create_securityZone(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
def remove(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone del", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['tenant_id', 'dc_name', 'network_zone', 'id']
values = tools.validat_values(body_values, valid_attributes)
# input the SecurityZone values with dic format
LOG.info(_LI("delete the SecurityZone values with dic forma \
is %(json)s"),
{"json": body_values})
response = self.manager.del_securityZone(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
def list(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone getAll", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['tenant_id', 'dc_name',
'network_zone', 'vfwname']
values = tools.validat_values(body_values, valid_attributes)
# get_all the SecurityZone values with dic format
LOG.info(_LI("get_all the SecurityZone values with dic format \
is %(json)s"),
{"json": body_values})
response = self.manager.get_securityZones(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
def show(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone get", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['id']
values = tools.validat_values(body_values, valid_attributes)
# get the staticnat values with dic format
LOG.info(_LI("get the SecurityZone values with dic format\
is %(json)s"),
{"json": body_values})
response = self.manager.get_securityZone(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
def addif(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone add vlan", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['tenant_id', 'dc_name', 'network_zone', 'id',
'ifname']
values = tools.validat_values(body_values, valid_attributes)
# input the SecurityZone values with dic format
LOG.info(_LI("input the SecurityZone values with dic formatO is\
%(json)s"),
{"json": body_values})
response = self.manager.get_securityZone(context, values)
if not isinstance(values["ifname"], string):
raise ParamFormatError(param_name="ifname")
if values["ifname"] in response.ifnames:
message = ("securityZone with ifname=" +
values["ifname"] + " already exists")
return tools.ret_info("400", message)
response.ifnames.append(values["ifname"])
values["ifnames"] = response.ifnames
response = self.manager.update_securityZone(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
def delif(self, req, *args, **kwargs):
try:
url = req.url
if len(args) > 1:
raise BadRequest(resource="SecurityZone del vlan", msg=url)
context = req.context
body_values = json.loads(req.body)
valid_attributes = ['tenant_id', 'dc_name', 'network_zone', 'id',
'ifname']
values = tools.validat_values(body_values, valid_attributes)
# input the SecurityZone values with dic format
LOG.info(_LI("input the SecurityZone values with dic format\
is %(json)s"),
{"json": body_values})
response = self.manager.get_securityZone(context, values)
if not isinstance(values["ifname"], string):
raise ParamFormatError(param_name="ifname")
if values["ifname"] not in response.ifnames:
message = ("securityZone with ifname=" +
values["ifname"]+" don't exist!")
return tools.ret_info("400", message)
response.ifnames.remove(values["ifname"])
values["ifnames"] = response.ifnames
response = self.manager.update_securityZone(context, values)
return response
except Nca47Exception as e:
self.response.status = e.code
LOG.error(_LE('Error exception! error info: %' + e.message))
LOG.exception(e)
self.response.status = e.code
return tools.ret_info(e.code, e.message)
except RemoteError as exception:
self.response.status = 500
message = exception.value
return tools.ret_info(self.response.status, message)
except Exception as e:
LOG.exception(e)
self.response.status = 500
return tools.ret_info(self.response.status, e.message)
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gitter-badger/mlmodels | mlmodels/model_tch/nbeats/model.py | f08cc9b6ec202d4ad25ecdda2f44487da387569d | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
def seasonality_model(thetas, t, device):
p = thetas.size()[-1]
assert p < 10, 'thetas_dim is too big.'
p1, p2 = (p // 2, p // 2) if p % 2 == 0 else (p // 2, p // 2 + 1)
s1 = torch.tensor([np.cos(2 * np.pi * i * t) for i in range(p1)]).float() # H/2-1
s2 = torch.tensor([np.sin(2 * np.pi * i * t) for i in range(p2)]).float()
S = torch.cat([s1, s2])
return thetas.mm(S.to(device))
def trend_model(thetas, t, device):
p = thetas.size()[-1]
assert p <= 4, 'thetas_dim is too big.'
T = torch.tensor([t ** i for i in range(p)]).float()
return thetas.mm(T.to(device))
def linspace(backcast_length, forecast_length):
lin_space = np.linspace(-backcast_length, forecast_length, backcast_length + forecast_length)
b_ls = lin_space[:backcast_length]
f_ls = lin_space[backcast_length:]
return b_ls, f_ls
class Block(nn.Module):
def __init__(self, units, thetas_dim, device, backcast_length=10, forecast_length=5, share_thetas=False):
super(Block, self).__init__()
self.units = units
self.thetas_dim = thetas_dim
self.backcast_length = backcast_length
self.forecast_length = forecast_length
self.share_thetas = share_thetas
self.fc1 = nn.Linear(backcast_length, units)
self.fc2 = nn.Linear(units, units)
self.fc3 = nn.Linear(units, units)
self.fc4 = nn.Linear(units, units)
self.device = device
self.backcast_linspace, self.forecast_linspace = linspace(backcast_length, forecast_length)
if share_thetas:
self.theta_f_fc = self.theta_b_fc = nn.Linear(units, thetas_dim)
else:
self.theta_b_fc = nn.Linear(units, thetas_dim)
self.theta_f_fc = nn.Linear(units, thetas_dim)
def forward(self, x):
x = F.relu(self.fc1(x.to(self.device)))
x = F.relu(self.fc2(x))
x = F.relu(self.fc3(x))
x = F.relu(self.fc4(x))
return x
def __str__(self):
block_type = type(self).__name__
return f'{block_type}(units={self.units}, thetas_dim={self.thetas_dim}, ' \
f'backcast_length={self.backcast_length}, forecast_length={self.forecast_length}, ' \
f'share_thetas={self.share_thetas}) at @{id(self)}'
class SeasonalityBlock(Block):
def __init__(self, units, thetas_dim, device, backcast_length=10, forecast_length=5):
super(SeasonalityBlock, self).__init__(units, thetas_dim, device, backcast_length,
forecast_length, share_thetas=True)
def forward(self, x):
x = super(SeasonalityBlock, self).forward(x)
backcast = seasonality_model(self.theta_b_fc(x), self.backcast_linspace, self.device)
forecast = seasonality_model(self.theta_f_fc(x), self.forecast_linspace, self.device)
return backcast, forecast
class TrendBlock(Block):
def __init__(self, units, thetas_dim, device, backcast_length=10, forecast_length=5):
super(TrendBlock, self).__init__(units, thetas_dim, device, backcast_length,
forecast_length, share_thetas=True)
def forward(self, x):
x = super(TrendBlock, self).forward(x)
backcast = trend_model(self.theta_b_fc(x), self.backcast_linspace, self.device)
forecast = trend_model(self.theta_f_fc(x), self.forecast_linspace, self.device)
return backcast, forecast
class GenericBlock(Block):
def __init__(self, units, thetas_dim, device, backcast_length=10, forecast_length=5):
super(GenericBlock, self).__init__(units, thetas_dim, device, backcast_length, forecast_length)
self.backcast_fc = nn.Linear(thetas_dim, backcast_length)
self.forecast_fc = nn.Linear(thetas_dim, forecast_length)
def forward(self, x):
# no constraint for generic arch.
x = super(GenericBlock, self).forward(x)
theta_b = F.relu(self.theta_b_fc(x))
theta_f = F.relu(self.theta_f_fc(x))
backcast = self.backcast_fc(theta_b) # generic. 3.3.
forecast = self.forecast_fc(theta_f) # generic. 3.3.
return backcast, forecast
class NBeatsNet(nn.Module):
SEASONALITY_BLOCK = 'seasonality'
TREND_BLOCK = 'trend'
GENERIC_BLOCK = 'generic'
def __init__(self,
device,
stack_types=[TREND_BLOCK, SEASONALITY_BLOCK],
nb_blocks_per_stack=3,
forecast_length=5,
backcast_length=10,
thetas_dims=[4, 8],
share_weights_in_stack=False,
hidden_layer_units=256, ):
super(NBeatsNet, self).__init__()
self.forecast_length = forecast_length
self.backcast_length = backcast_length
self.hidden_layer_units = hidden_layer_units
self.nb_blocks_per_stack = nb_blocks_per_stack
self.share_weights_in_stack = share_weights_in_stack
self.stack_types = stack_types
self.stacks = []
self.thetas_dim = thetas_dims
self.parameters = []
self.device = device
print(f'| N-Beats')
for stack_id in range(len(self.stack_types)):
self.stacks.append(self.create_stack(stack_id))
self.parameters = nn.ParameterList(self.parameters)
self.to(self.device)
def create_stack(self, stack_id):
stack_type = self.stack_types[stack_id]
print(f'| -- Stack {stack_type.title()} (#{stack_id}) (share_weights_in_stack={self.share_weights_in_stack})')
blocks = []
for block_id in range(self.nb_blocks_per_stack):
block_init = NBeatsNet.select_block(stack_type)
if self.share_weights_in_stack and block_id != 0:
block = blocks[-1] # pick up the last one to make the
else:
block = block_init(self.hidden_layer_units, self.thetas_dim[stack_id],
self.device, self.backcast_length, self.forecast_length)
self.parameters.extend(block.parameters())
print(f' | -- {block}')
blocks.append(block)
return blocks
@staticmethod
def select_block(block_type):
if block_type == NBeatsNet.SEASONALITY_BLOCK:
return SeasonalityBlock
elif block_type == NBeatsNet.TREND_BLOCK:
return TrendBlock
else:
return GenericBlock
def forward(self, backcast):
forecast = torch.zeros(size=(backcast.size()[0], self.forecast_length,)) # maybe batch size here.
for stack_id in range(len(self.stacks)):
for block_id in range(len(self.stacks[stack_id])):
b, f = self.stacks[stack_id][block_id](backcast)
backcast = backcast.to(self.device) - b
forecast = forecast.to(self.device) + f
return backcast, forecast
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chaya-v/AI-ML-Lab-Programs | BACKPROPAGATION/Backprop.py | cb2e91cf62376f5f95395e89357fa0bef730deed | from math import exp
from random import seed
from random import random
def initialize_network(n_inputs, n_hidden, n_outputs):
network = list()
hidden_layer = [{'weights':[random() for i in range(n_inputs + 1)]} for i in range(n_hidden)]
network.append(hidden_layer)
output_layer = [{'weights':[random() for i in range(n_hidden + 1)]} for i in range(n_outputs)]
network.append(output_layer)
return network
def activate(weights, inputs):
activation = weights[-1]
for i in range(len(weights)-1):
activation += weights[i] * inputs[i]
return activation
def transfer(activation):
return 1.0 / (1.0 + exp(-activation))
def forward_propagate(network, row):
inputs = row
for layer in network:
new_inputs = []
for neuron in layer:
activation = activate(neuron['weights'], inputs)
neuron['output'] = transfer(activation)
new_inputs.append(neuron['output'])
inputs = new_inputs
return inputs
def transfer_derivative(output):
return output * (1.0 - output)
def backward_propagate_error(network, expected):
for i in reversed(range(len(network))):
layer = network[i]
errors = list()
if i != len(network)-1:
for j in range(len(layer)):
error = 0.0
for neuron in network[i + 1]:
error += (neuron['weights'][j] * neuron['delta'])
errors.append(error)
else:
for j in range(len(layer)):
neuron = layer[j]
errors.append(expected[j] - neuron['output'])
for j in range(len(layer)):
neuron = layer[j]
neuron['delta'] = errors[j] * transfer_derivative(neuron['output'])
def update_weights(network, row, l_rate):
for i in range(len(network)):
inputs = row[:-1]
if i != 0:
inputs = [neuron['output'] for neuron in network[i - 1]]
for neuron in network[i]:
for j in range(len(inputs)):
neuron['weights'][j] += l_rate * neuron['delta'] * inputs[j]
neuron['weights'][-1] += l_rate * neuron['delta']
def train_network(network, train, l_rate, n_epoch, n_outputs):
for epoch in range(n_epoch):
sum_error = 0
for row in train:
outputs = forward_propagate(network, row)
expected = [0 for i in range(n_outputs)]
expected[row[-1]] = 1
sum_error += sum([(expected[i]-outputs[i])**2 for i in range(len(expected))])
backward_propagate_error(network, expected)
update_weights(network, row, l_rate)
print('>epoch=%d, lrate=%.3f, error=%.3f' % (epoch, l_rate, sum_error))
seed(1)
dataset = [[2.7810836,2.550537003,0],
[1.465489372,2.362125076,0],
[3.396561688,4.400293529,0],
[1.38807019,1.850220317,0],
[3.06407232,3.005305973,0],
[7.627531214,2.759262235,1],
[5.332441248,2.088626775,1],
[6.922596716,1.77106367,1],
[8.675418651,-0.242068655,1],
[7.673756466,3.508563011,1]]
n_inputs = len(dataset[0]) - 1
n_outputs = len(set([row[-1] for row in dataset]))
network = initialize_network(n_inputs, 2, n_outputs)
train_network(network, dataset, 0.5, 30, n_outputs)
for layer in network:
print(layer) | [((84, 0, 84, 7), 'random.seed', 'seed', ({(84, 5, 84, 6): '(1)'}, {}), '(1)', False, 'from random import seed\n'), ((23, 21, 23, 37), 'math.exp', 'exp', ({(23, 25, 23, 36): '(-activation)'}, {}), '(-activation)', False, 'from math import exp\n'), ((8, 29, 8, 37), 'random.random', 'random', ({}, {}), '()', False, 'from random import random\n'), ((10, 29, 10, 37), 'random.random', 'random', ({}, {}), '()', False, 'from random import random\n')] |
benoitc/hypercouch | tests/multi_design_test.py | 23055c26529a7f2198288b249b45d05b796e78bf | """\
Copyright (c) 2009 Paul J. Davis <[email protected]>
This file is part of hypercouch which is released uner the MIT license.
"""
import time
import unittest
import couchdb
COUCHURI = "http://127.0.0.1:5984/"
TESTDB = "hyper_tests"
class MultiDesignTest(unittest.TestCase):
def setUp(self):
self.srv = couchdb.Server(COUCHURI)
if TESTDB in self.srv:
del self.srv[TESTDB]
self.db = self.srv.create(TESTDB)
self.db["_design/test1"] = {
"ft_index": """\
function(doc) {
if(doc.body) index(doc.body);
if(doc.foo != undefined) property("foo", doc.foo);
}
"""
}
self.db["_design/test2"] = {
"ft_index": """\
function(doc) {
if(doc.bar) property("bar", doc.bar)
}
"""
}
self._wait()
def tearDown(self):
del self.srv[TESTDB]
def _query(self, **kwargs):
resp, data = self.db.resource.get("_fti", **kwargs)
return data
def _wait(self, expect=0, retries=10):
data = self._query(q="*.**")
while retries > 0 and len(data["rows"]) != expect:
retries -= 1
time.sleep(0.2)
data = self._query(q="*.**")
if retries < 1:
raise RuntimeError("Failed to find expected index state.")
def test_attr(self):
docs = [{"_id": str(i), "body": "This is document %d" % i, "foo": i, "bar": str(i*i)} for i in range(10)]
self.db.update(docs)
self._wait(expect=10)
data = self._query(q="*.**", foo="NUMEQ 3", bar="NUMEQ 9")
self.assertEqual(data["total_rows"], 1)
self.assertEqual(data["rows"][0]["id"], "3")
data = self._query(q="*.**")
self.assertEqual(len(data["rows"]), 10)
for row in data["rows"]:
self.assertEqual(int(row["foo"]) ** 2, int(row["bar"]))
| [((14, 19, 14, 43), 'couchdb.Server', 'couchdb.Server', ({(14, 34, 14, 42): 'COUCHURI'}, {}), '(COUCHURI)', False, 'import couchdb\n'), ((43, 12, 43, 27), 'time.sleep', 'time.sleep', ({(43, 23, 43, 26): '(0.2)'}, {}), '(0.2)', False, 'import time\n')] |
DanieleMancini/xled_plus | xled_plus/samples/colmeander.py | a6e9f3da56f95f508ec4fa2bb6ceae005450e654 | from .sample_setup import *
ctr = setup_control()
eff = ColorMeanderEffect(ctr, "solid")
eff.launch_rt()
input()
eff.stop_rt()
ctr.turn_off()
| [] |
wcyjames/dgl | python/dgl/nn/pytorch/sparse_emb.py | 00a668ac6898971aa154a8a3fe851010034fd6bf | """Torch NodeEmbedding."""
from datetime import timedelta
import torch as th
from ...backend import pytorch as F
from ...utils import get_shared_mem_array, create_shared_mem_array
_STORE = None
class NodeEmbedding: # NodeEmbedding
'''Class for storing node embeddings.
The class is optimized for training large-scale node embeddings. It updates the embedding in
a sparse way and can scale to graphs with millions of nodes. It also supports partitioning
to multiple GPUs (on a single machine) for more acceleration. It does not support partitioning
across machines.
Currently, DGL provides two optimizers that work with this NodeEmbedding
class: ``SparseAdagrad`` and ``SparseAdam``.
The implementation is based on torch.distributed package. It depends on the pytorch
default distributed process group to collect multi-process information and uses
``torch.distributed.TCPStore`` to share meta-data information across multiple gpu processes.
It use the local address of '127.0.0.1:12346' to initialize the TCPStore.
Parameters
----------
num_embeddings : int
The number of embeddings. Currently, the number of embeddings has to be the same as
the number of nodes.
embedding_dim : int
The dimension size of embeddings.
name : str
The name of the embeddings. The name should uniquely identify the embeddings in the system.
init_func : callable, optional
The function to create the initial data. If the init function is not provided,
the values of the embeddings are initialized to zero.
Examples
--------
Before launching multiple gpu processes
>>> def initializer(emb):
th.nn.init.xavier_uniform_(emb)
return emb
In each training process
>>> emb = dgl.nn.NodeEmbedding(g.number_of_nodes(), 10, 'emb', init_func=initializer)
>>> optimizer = dgl.optim.SparseAdam([emb], lr=0.001)
>>> for blocks in dataloader:
... ...
... feats = emb(nids, gpu_0)
... loss = F.sum(feats + 1, 0)
... loss.backward()
... optimizer.step()
'''
def __init__(self, num_embeddings, embedding_dim, name,
init_func=None):
global _STORE
# Check whether it is multi-gpu training or not.
if th.distributed.is_initialized():
rank = th.distributed.get_rank()
world_size = th.distributed.get_world_size()
else:
rank = -1
world_size = 0
self._rank = rank
self._world_size = world_size
host_name = '127.0.0.1'
port = 12346
if rank <= 0:
emb = create_shared_mem_array(name, (num_embeddings, embedding_dim), th.float32)
if init_func is not None:
emb = init_func(emb)
if rank == 0:
if world_size > 1:
# for multi-gpu training, setup a TCPStore for
# embeding status synchronization across GPU processes
if _STORE is None:
_STORE = th.distributed.TCPStore(
host_name, port, world_size, True, timedelta(seconds=30))
for _ in range(1, world_size):
# send embs
_STORE.set(name, name)
elif rank > 0:
# receive
if _STORE is None:
_STORE = th.distributed.TCPStore(
host_name, port, world_size, False, timedelta(seconds=30))
_STORE.wait([name])
emb = get_shared_mem_array(name, (num_embeddings, embedding_dim), th.float32)
self._store = _STORE
self._tensor = emb
self._num_embeddings = num_embeddings
self._embedding_dim = embedding_dim
self._name = name
self._optm_state = None # track optimizer state
self._trace = [] # track minibatch
def __call__(self, node_ids, device=th.device('cpu')):
"""
node_ids : th.tensor
Index of the embeddings to collect.
device : th.device
Target device to put the collected embeddings.
"""
emb = self._tensor[node_ids].to(device)
if F.is_recording():
emb = F.attach_grad(emb)
self._trace.append((node_ids.to(device, non_blocking=True), emb))
return emb
@property
def store(self):
"""Return torch.distributed.TCPStore for
meta data sharing across processes.
Returns
-------
torch.distributed.TCPStore
KVStore used for meta data sharing.
"""
return self._store
@property
def rank(self):
"""Return rank of current process.
Returns
-------
int
The rank of current process.
"""
return self._rank
@property
def world_size(self):
"""Return world size of the pytorch distributed training env.
Returns
-------
int
The world size of the pytorch distributed training env.
"""
return self._world_size
@property
def name(self):
"""Return the name of NodeEmbedding.
Returns
-------
str
The name of NodeEmbedding.
"""
return self._name
@property
def num_embeddings(self):
"""Return the number of embeddings.
Returns
-------
int
The number of embeddings.
"""
return self._num_embeddings
def set_optm_state(self, state):
"""Store the optimizer related state tensor.
Parameters
----------
state : tuple of torch.Tensor
Optimizer related state.
"""
self._optm_state = state
@property
def optm_state(self):
"""Return the optimizer related state tensor.
Returns
-------
tuple of torch.Tensor
The optimizer related state.
"""
return self._optm_state
@property
def trace(self):
"""Return a trace of the indices of embeddings
used in the training step(s).
Returns
-------
[torch.Tensor]
The indices of embeddings used in the training step(s).
"""
return self._trace
def reset_trace(self):
"""Clean up the trace of the indices of embeddings
used in the training step(s).
"""
self._trace = []
@property
def emb_tensor(self):
"""Return the tensor storing the node embeddings
Returns
-------
torch.Tensor
The tensor storing the node embeddings
"""
return self._tensor
| [((63, 11, 63, 42), 'torch.distributed.is_initialized', 'th.distributed.is_initialized', ({}, {}), '()', True, 'import torch as th\n'), ((104, 40, 104, 56), 'torch.device', 'th.device', ({(104, 50, 104, 55): '"""cpu"""'}, {}), "('cpu')", True, 'import torch as th\n'), ((64, 19, 64, 44), 'torch.distributed.get_rank', 'th.distributed.get_rank', ({}, {}), '()', True, 'import torch as th\n'), ((65, 25, 65, 56), 'torch.distributed.get_world_size', 'th.distributed.get_world_size', ({}, {}), '()', True, 'import torch as th\n'), ((84, 59, 84, 80), 'datetime.timedelta', 'timedelta', (), '', False, 'from datetime import timedelta\n'), ((92, 56, 92, 77), 'datetime.timedelta', 'timedelta', (), '', False, 'from datetime import timedelta\n')] |
seukjung/sentry-custom | tests/sentry/web/frontend/test_create_team.py | c5f6bb2019aef3caff7f3e2b619f7a70f2b9b963 | from __future__ import absolute_import
from django.core.urlresolvers import reverse
from sentry.models import OrganizationMember, OrganizationMemberTeam, Team
from sentry.testutils import TestCase, PermissionTestCase
class CreateTeamPermissionTest(PermissionTestCase):
def setUp(self):
super(CreateTeamPermissionTest, self).setUp()
self.path = reverse('sentry-create-team', args=[self.organization.slug])
def test_teamless_admin_can_load(self):
self.assert_teamless_admin_can_access(self.path)
def test_team_admin_can_load(self):
self.assert_team_admin_can_access(self.path)
def test_member_cannot_load(self):
self.assert_member_cannot_access(self.path)
def test_owner_can_load(self):
self.assert_owner_can_access(self.path)
class CreateTeamTest(TestCase):
def test_renders_with_context(self):
organization = self.create_organization()
path = reverse('sentry-create-team', args=[organization.slug])
self.login_as(self.user)
resp = self.client.get(path)
assert resp.status_code == 200
self.assertTemplateUsed(resp, 'sentry/create-team.html')
assert resp.context['organization'] == organization
assert resp.context['form']
def test_submission(self):
organization = self.create_organization()
path = reverse('sentry-create-team', args=[organization.slug])
self.login_as(self.user)
resp = self.client.post(path, {
'name': 'bar',
})
assert resp.status_code == 302, resp.context['form'].errors
team = Team.objects.get(organization=organization, name='bar')
member = OrganizationMember.objects.get(
user=self.user,
organization=organization,
)
assert OrganizationMemberTeam.objects.filter(
organizationmember=member,
team=team,
is_active=True,
).exists()
redirect_uri = reverse('sentry-create-project', args=[organization.slug])
assert resp['Location'] == 'http://testserver%s?team=%s' % (
redirect_uri, team.slug)
def test_admin_can_create_team(self):
organization = self.create_organization()
path = reverse('sentry-create-team', args=[organization.slug])
admin = self.create_user('[email protected]')
self.create_member(
organization=organization,
user=admin,
role='admin',
teams=[],
)
self.login_as(admin)
resp = self.client.post(path, {
'name': 'bar',
})
assert resp.status_code == 302, resp.context['form'].errors
assert Team.objects.filter(
organization=organization,
name='bar',
).exists()
| [((12, 20, 12, 80), 'django.core.urlresolvers.reverse', 'reverse', (), '', False, 'from django.core.urlresolvers import reverse\n'), ((30, 15, 30, 70), 'django.core.urlresolvers.reverse', 'reverse', (), '', False, 'from django.core.urlresolvers import reverse\n'), ((40, 15, 40, 70), 'django.core.urlresolvers.reverse', 'reverse', (), '', False, 'from django.core.urlresolvers import reverse\n'), ((47, 15, 47, 70), 'sentry.models.Team.objects.get', 'Team.objects.get', (), '', False, 'from sentry.models import OrganizationMember, OrganizationMemberTeam, Team\n'), ((49, 17, 52, 9), 'sentry.models.OrganizationMember.objects.get', 'OrganizationMember.objects.get', (), '', False, 'from sentry.models import OrganizationMember, OrganizationMemberTeam, Team\n'), ((60, 23, 60, 81), 'django.core.urlresolvers.reverse', 'reverse', (), '', False, 'from django.core.urlresolvers import reverse\n'), ((66, 15, 66, 70), 'django.core.urlresolvers.reverse', 'reverse', (), '', False, 'from django.core.urlresolvers import reverse\n'), ((54, 15, 58, 9), 'sentry.models.OrganizationMemberTeam.objects.filter', 'OrganizationMemberTeam.objects.filter', (), '', False, 'from sentry.models import OrganizationMember, OrganizationMemberTeam, Team\n'), ((83, 15, 86, 9), 'sentry.models.Team.objects.filter', 'Team.objects.filter', (), '', False, 'from sentry.models import OrganizationMember, OrganizationMemberTeam, Team\n')] |
eym55/mango-client-python | baseCli.py | 2cb1ce77d785343c24ecba913eaa9693c3db1181 | import abc
import datetime
import enum
import logging
import time
import typing
import aysncio
import Layout as layouts
from decimal import Decimal
from pyserum.market import Market
from pyserum.open_orders_account import OpenOrdersAccount
from solana.account import Account
from solana.publickey import PublicKey
from solana.rpc.commitment import Single
from solana.rpc.types import MemcmpOpts, TokenAccountOpts, RPCMethod, RPCResponse
from spl.token.client import Token as SplToken
from spl.token.constants import TOKEN_PROGRAM_ID
from Constants import NUM_MARKETS, NUM_TOKENS, SOL_DECIMALS, SYSTEM_PROGRAM_ADDRESS, MAX_RATE,OPTIMAL_RATE,OPTIMAL_UTIL
from Context import Context
from Decoder import decode_binary, encode_binary, encode_key
class Version(enum.Enum):
UNSPECIFIED = 0
V1 = 1
V2 = 2
V3 = 3
V4 = 4
V5 = 5
class InstructionType(enum.IntEnum):
InitMangoGroup = 0
InitMarginAccount = 1
Deposit = 2
Withdraw = 3
Borrow = 4
SettleBorrow = 5
Liquidate = 6
DepositSrm = 7
WithdrawSrm = 8
PlaceOrder = 9
SettleFunds = 10
CancelOrder = 11
CancelOrderByClientId = 12
ChangeBorrowLimit = 13
PlaceAndSettle = 14
ForceCancelOrders = 15
PartialLiquidate = 16
def __str__(self):
return self.name
class AccountInfo:
def __init__(self, address: PublicKey, executable: bool, lamports: Decimal, owner: PublicKey, rent_epoch: Decimal, data: bytes):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.address: PublicKey = address
self.executable: bool = executable
self.lamports: Decimal = lamports
self.owner: PublicKey = owner
self.rent_epoch: Decimal = rent_epoch
self.data: bytes = data
def encoded_data(self) -> typing.List:
return encode_binary(self.data)
def __str__(self) -> str:
return f"""« AccountInfo [{self.address}]:
Owner: {self.owner}
Executable: {self.executable}
Lamports: {self.lamports}
Rent Epoch: {self.rent_epoch}
»"""
def __repr__(self) -> str:
return f"{self}"
@staticmethod
async def load(context: Context, address: PublicKey) -> typing.Optional["AccountInfo"]:
response: RPCResponse = context.client.get_account_info(address)
result = context.unwrap_or_raise_exception(response)
if result["value"] is None:
return None
return AccountInfo._from_response_values(result["value"], address)
@staticmethod
async def load_multiple(context: Context, addresses: typing.List[PublicKey]) -> typing.List["AccountInfo"]:
address_strings = list(map(PublicKey.__str__, addresses))
response = await context.client._provider.make_request(RPCMethod("getMultipleAccounts"), address_strings)
response_value_list = zip(response["result"]["value"], addresses)
return list(map(lambda pair: AccountInfo._from_response_values(pair[0], pair[1]), response_value_list))
@staticmethod
def _from_response_values(response_values: typing.Dict[str, typing.Any], address: PublicKey) -> "AccountInfo":
executable = bool(response_values["executable"])
lamports = Decimal(response_values["lamports"])
owner = PublicKey(response_values["owner"])
rent_epoch = Decimal(response_values["rentEpoch"])
data = decode_binary(response_values["data"])
return AccountInfo(address, executable, lamports, owner, rent_epoch, data)
@staticmethod
def from_response(response: RPCResponse, address: PublicKey) -> "AccountInfo":
return AccountInfo._from_response_values(response["result"]["value"], address)
class AddressableAccount(metaclass=abc.ABCMeta):
def __init__(self, account_info: AccountInfo):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.account_info = account_info
@property
def address(self) -> PublicKey:
return self.account_info.address
def __repr__(self) -> str:
return f"{self}"
class SerumAccountFlags:
def __init__(self, version: Version, initialized: bool, market: bool, open_orders: bool,
request_queue: bool, event_queue: bool, bids: bool, asks: bool, disabled: bool):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.initialized = initialized
self.market = market
self.open_orders = open_orders
self.request_queue = request_queue
self.event_queue = event_queue
self.bids = bids
self.asks = asks
self.disabled = disabled
@staticmethod
def from_layout(layout: layouts.SERUM_ACCOUNT_FLAGS) -> "SerumAccountFlags":
return SerumAccountFlags(Version.UNSPECIFIED, layout.initialized, layout.market,
layout.open_orders, layout.request_queue, layout.event_queue,
layout.bids, layout.asks, layout.disabled)
def __str__(self) -> str:
flags: typing.List[typing.Optional[str]] = []
flags += ["initialized" if self.initialized else None]
flags += ["market" if self.market else None]
flags += ["open_orders" if self.open_orders else None]
flags += ["request_queue" if self.request_queue else None]
flags += ["event_queue" if self.event_queue else None]
flags += ["bids" if self.bids else None]
flags += ["asks" if self.asks else None]
flags += ["disabled" if self.disabled else None]
flag_text = " | ".join(flag for flag in flags if flag is not None) or "None"
return f"« SerumAccountFlags: {flag_text} »"
def __repr__(self) -> str:
return f"{self}"
class MangoAccountFlags:
def __init__(self, version: Version, initialized: bool, group: bool, margin_account: bool, srm_account: bool):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.initialized = initialized
self.group = group
self.margin_account = margin_account
self.srm_account = srm_account
@staticmethod
def from_layout(layout: layouts.MANGO_ACCOUNT_FLAGS) -> "MangoAccountFlags":
return MangoAccountFlags(Version.UNSPECIFIED, layout.initialized, layout.group, layout.margin_account,
layout.srm_account)
def __str__(self) -> str:
flags: typing.List[typing.Optional[str]] = []
flags += ["initialized" if self.initialized else None]
flags += ["group" if self.group else None]
flags += ["margin_account" if self.margin_account else None]
flags += ["srm_account" if self.srm_account else None]
flag_text = " | ".join(flag for flag in flags if flag is not None) or "None"
return f"« MangoAccountFlags: {flag_text} »"
def __repr__(self) -> str:
return f"{self}"
class Index:
def __init__(self, version: Version, last_update: datetime.datetime, borrow: Decimal, deposit: Decimal):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.last_update: datetime.datetime = last_update
self.borrow: Decimal = borrow
self.deposit: Decimal = deposit
@staticmethod
def from_layout(layout: layouts.INDEX, decimals: Decimal) -> "Index":
borrow = layout.borrow / Decimal(10 ** decimals)
deposit = layout.deposit / Decimal(10 ** decimals)
return Index(Version.UNSPECIFIED, layout.last_update, borrow, deposit)
def __str__(self) -> str:
return f"« Index: Borrow: {self.borrow:,.8f}, Deposit: {self.deposit:,.8f} [last update: {self.last_update}] »"
def __repr__(self) -> str:
return f"{self}"
class AggregatorConfig:
def __init__(self, version: Version, description: str, decimals: Decimal, restart_delay: Decimal,
max_submissions: Decimal, min_submissions: Decimal, reward_amount: Decimal,
reward_token_account: PublicKey):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.description: str = description
self.decimals: Decimal = decimals
self.restart_delay: Decimal = restart_delay
self.max_submissions: Decimal = max_submissions
self.min_submissions: Decimal = min_submissions
self.reward_amount: Decimal = reward_amount
self.reward_token_account: PublicKey = reward_token_account
@staticmethod
def from_layout(layout: layouts.AGGREGATOR_CONFIG) -> "AggregatorConfig":
return AggregatorConfig(Version.UNSPECIFIED, layout.description, layout.decimals,
layout.restart_delay, layout.max_submissions, layout.min_submissions,
layout.reward_amount, layout.reward_token_account)
def __str__(self) -> str:
return f"« AggregatorConfig: '{self.description}', Decimals: {self.decimals} [restart delay: {self.restart_delay}], Max: {self.max_submissions}, Min: {self.min_submissions}, Reward: {self.reward_amount}, Reward Account: {self.reward_token_account} »"
def __repr__(self) -> str:
return f"{self}"
class Round:
def __init__(self, version: Version, id: Decimal, created_at: datetime.datetime, updated_at: datetime.datetime):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.id: Decimal = id
self.created_at: datetime.datetime = created_at
self.updated_at: datetime.datetime = updated_at
@staticmethod
def from_layout(layout: layouts.ROUND) -> "Round":
return Round(Version.UNSPECIFIED, layout.id, layout.created_at, layout.updated_at)
def __str__(self) -> str:
return f"« Round[{self.id}], Created: {self.updated_at}, Updated: {self.updated_at} »"
def __repr__(self) -> str:
return f"{self}"
class Answer:
def __init__(self, version: Version, round_id: Decimal, median: Decimal, created_at: datetime.datetime, updated_at: datetime.datetime):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.version: Version = version
self.round_id: Decimal = round_id
self.median: Decimal = median
self.created_at: datetime.datetime = created_at
self.updated_at: datetime.datetime = updated_at
@staticmethod
def from_layout(layout: layouts.ANSWER) -> "Answer":
return Answer(Version.UNSPECIFIED, layout.round_id, layout.median, layout.created_at, layout.updated_at)
def __str__(self) -> str:
return f"« Answer: Round[{self.round_id}], Median: {self.median:,.8f}, Created: {self.updated_at}, Updated: {self.updated_at} »"
def __repr__(self) -> str:
return f"{self}"
class Aggregator(AddressableAccount):
def __init__(self, account_info: AccountInfo, version: Version, config: AggregatorConfig,
initialized: bool, name: str, owner: PublicKey, round_: Round,
round_submissions: PublicKey, answer: Answer, answer_submissions: PublicKey):
super().__init__(account_info)
self.version: Version = version
self.config: AggregatorConfig = config
self.initialized: bool = initialized
self.name: str = name
self.owner: PublicKey = owner
self.round: Round = round_
self.round_submissions: PublicKey = round_submissions
self.answer: Answer = answer
self.answer_submissions: PublicKey = answer_submissions
@property
def price(self) -> Decimal:
return self.answer.median / (10 ** self.config.decimals)
@staticmethod
def from_layout(layout: layouts.AGGREGATOR, account_info: AccountInfo, name: str) -> "Aggregator":
config = AggregatorConfig.from_layout(layout.config)
initialized = bool(layout.initialized)
round_ = Round.from_layout(layout.round)
answer = Answer.from_layout(layout.answer)
return Aggregator(account_info, Version.UNSPECIFIED, config, initialized, name, layout.owner,
round_, layout.round_submissions, answer, layout.answer_submissions)
@staticmethod
def parse(context: Context, account_info: AccountInfo) -> "Aggregator":
data = account_info.data
if len(data) != layouts.AGGREGATOR.sizeof():
raise Exception(f"Data length ({len(data)}) does not match expected size ({layouts.AGGREGATOR.sizeof()})")
name = context.lookup_oracle_name(account_info.address)
layout = layouts.AGGREGATOR.parse(data)
return Aggregator.from_layout(layout, account_info, name)
@staticmethod
def load(context: Context, account_address: PublicKey):
account_info = AccountInfo.load(context, account_address)
if account_info is None:
raise Exception(f"Aggregator account not found at address '{account_address}'")
return Aggregator.parse(context, account_info)
def __str__(self) -> str:
return f"""
« Aggregator '{self.name}' [{self.version}]:
Config: {self.config}
Initialized: {self.initialized}
Owner: {self.owner}
Round: {self.round}
Round Submissions: {self.round_submissions}
Answer: {self.answer}
Answer Submissions: {self.answer_submissions}
»
"""
class Token:
def __init__(self, name: str, mint: PublicKey, decimals: Decimal):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.name: str = name.upper()
self.mint: PublicKey = mint
self.decimals: Decimal = decimals
def round(self, value: Decimal) -> Decimal:
rounded = round(value, int(self.decimals))
return Decimal(rounded)
def name_matches(self, name: str) -> bool:
return self.name.upper() == name.upper()
@staticmethod
def find_by_name(values: typing.List["Token"], name: str) -> "Token":
found = [value for value in values if value.name_matches(name)]
if len(found) == 0:
raise Exception(f"Token '{name}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{name}' matched multiple tokens in values: {values}")
return found[0]
@staticmethod
def find_by_mint(values: typing.List["Token"], mint: PublicKey) -> "Token":
found = [value for value in values if value.mint == mint]
if len(found) == 0:
raise Exception(f"Token '{mint}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{mint}' matched multiple tokens in values: {values}")
return found[0]
# TokenMetadatas are equal if they have the same mint address.
def __eq__(self, other):
if hasattr(other, 'mint'):
return self.mint == other.mint
return False
def __str__(self) -> str:
return f"« Token '{self.name}' [{self.mint} ({self.decimals} decimals)] »"
def __repr__(self) -> str:
return f"{self}"
SolToken = Token("SOL", SYSTEM_PROGRAM_ADDRESS, SOL_DECIMALS)
class TokenLookup:
@staticmethod
def find_by_name(context: Context, name: str) -> Token:
if SolToken.name_matches(name):
return SolToken
mint = context.lookup_token_address(name)
if mint is None:
raise Exception(f"Could not find token with name '{name}'.")
return Token(name, mint, Decimal(6))
@staticmethod
def find_by_mint(context: Context, mint: PublicKey) -> Token:
if SolToken.mint == mint:
return SolToken
name = context.lookup_token_name(mint)
if name is None:
raise Exception(f"Could not find token with mint '{mint}'.")
return Token(name, mint, Decimal(6))
class BasketToken:
def __init__(self, token: Token, vault: PublicKey, index: Index):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.token: Token = token
self.vault: PublicKey = vault
self.index: Index = index
@staticmethod
def find_by_name(values: typing.List["BasketToken"], name: str) -> "BasketToken":
found = [value for value in values if value.token.name_matches(name)]
if len(found) == 0:
raise Exception(f"Token '{name}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{name}' matched multiple tokens in values: {values}")
return found[0]
@staticmethod
def find_by_mint(values: typing.List["BasketToken"], mint: PublicKey) -> "BasketToken":
found = [value for value in values if value.token.mint == mint]
if len(found) == 0:
raise Exception(f"Token '{mint}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{mint}' matched multiple tokens in values: {values}")
return found[0]
@staticmethod
def find_by_token(values: typing.List["BasketToken"], token: Token) -> "BasketToken":
return BasketToken.find_by_mint(values, token.mint)
# BasketTokens are equal if they have the same underlying token.
def __eq__(self, other):
if hasattr(other, 'token'):
return self.token == other.token
return False
def __str__(self) -> str:
return f"""« BasketToken [{self.token}]:
Vault: {self.vault}
Index: {self.index}
»"""
def __repr__(self) -> str:
return f"{self}"
class TokenValue:
def __init__(self, token: Token, value: Decimal):
self.token = token
self.value = value
@staticmethod
async def fetch_total_value_or_none(context: Context, account_public_key: PublicKey, token: Token) -> typing.Optional["TokenValue"]:
opts = TokenAccountOpts(mint=token.mint)
token_accounts_response = await context.client.get_token_accounts_by_owner(account_public_key, opts, commitment=context.commitment)
token_accounts = token_accounts_response["result"]["value"]
if len(token_accounts) == 0:
return None
total_value = Decimal(0)
for token_account in token_accounts:
result = await context.client.get_token_account_balance(token_account["pubkey"], commitment=context.commitment)
value = Decimal(result["result"]["value"]["amount"])
decimal_places = result["result"]["value"]["decimals"]
divisor = Decimal(10 ** decimal_places)
total_value += value / divisor
return TokenValue(token, total_value)
@staticmethod
def fetch_total_value(context: Context, account_public_key: PublicKey, token: Token) -> "TokenValue":
value = TokenValue.fetch_total_value_or_none(context, account_public_key, token)
if value is None:
return TokenValue(token, Decimal(0))
return value
@staticmethod
def report(reporter: typing.Callable[[str], None], values: typing.List["TokenValue"]) -> None:
for value in values:
reporter(f"{value.value:>18,.8f} {value.token.name}")
@staticmethod
def find_by_name(values: typing.List["TokenValue"], name: str) -> "TokenValue":
found = [value for value in values if value.token.name_matches(name)]
if len(found) == 0:
raise Exception(f"Token '{name}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{name}' matched multiple tokens in values: {values}")
return found[0]
@staticmethod
def find_by_mint(values: typing.List["TokenValue"], mint: PublicKey) -> "TokenValue":
found = [value for value in values if value.token.mint == mint]
if len(found) == 0:
raise Exception(f"Token '{mint}' not found in token values: {values}")
if len(found) > 1:
raise Exception(f"Token '{mint}' matched multiple tokens in values: {values}")
return found[0]
@staticmethod
def find_by_token(values: typing.List["TokenValue"], token: Token) -> "TokenValue":
return TokenValue.find_by_mint(values, token.mint)
@staticmethod
def changes(before: typing.List["TokenValue"], after: typing.List["TokenValue"]) -> typing.List["TokenValue"]:
changes: typing.List[TokenValue] = []
for before_balance in before:
after_balance = TokenValue.find_by_token(after, before_balance.token)
result = TokenValue(before_balance.token, after_balance.value - before_balance.value)
changes += [result]
return changes
def __str__(self) -> str:
return f"« TokenValue: {self.value:>18,.8f} {self.token.name} »"
def __repr__(self) -> str:
return f"{self}"
class OwnedTokenValue:
def __init__(self, owner: PublicKey, token_value: TokenValue):
self.owner = owner
self.token_value = token_value
@staticmethod
def find_by_owner(values: typing.List["OwnedTokenValue"], owner: PublicKey) -> "OwnedTokenValue":
found = [value for value in values if value.owner == owner]
if len(found) == 0:
raise Exception(f"Owner '{owner}' not found in: {values}")
if len(found) > 1:
raise Exception(f"Owner '{owner}' matched multiple tokens in: {values}")
return found[0]
@staticmethod
def changes(before: typing.List["OwnedTokenValue"], after: typing.List["OwnedTokenValue"]) -> typing.List["OwnedTokenValue"]:
changes: typing.List[OwnedTokenValue] = []
for before_value in before:
after_value = OwnedTokenValue.find_by_owner(after, before_value.owner)
token_value = TokenValue(before_value.token_value.token, after_value.token_value.value - before_value.token_value.value)
result = OwnedTokenValue(before_value.owner, token_value)
changes += [result]
return changes
def __str__(self) -> str:
return f"[{self.owner}]: {self.token_value}"
def __repr__(self) -> str:
return f"{self}"
class MarketMetadata:
def __init__(self, name: str, address: PublicKey, base: BasketToken, quote: BasketToken,
spot: PublicKey, oracle: PublicKey, decimals: Decimal):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.name: str = name
self.address: PublicKey = address
self.base: BasketToken = base
self.quote: BasketToken = quote
self.spot: PublicKey = spot
self.oracle: PublicKey = oracle
self.decimals: Decimal = decimals
self._market = None
async def fetch_market(self, context: Context) -> Market:
if self._market is None:
self._market = await Market.load(context.client, self.spot)
return self._market
def __str__(self) -> str:
return f"""« Market '{self.name}' [{self.spot}]:
Base: {self.base}
Quote: {self.quote}
Oracle: {self.oracle} ({self.decimals} decimals)
»"""
def __repr__(self) -> str:
return f"{self}"
class Group(AddressableAccount):
def __init__(self, account_info: AccountInfo, version: Version, context: Context,
account_flags: MangoAccountFlags, basket_tokens: typing.List[BasketToken],
markets: typing.List[MarketMetadata],
signer_nonce: Decimal, signer_key: PublicKey, dex_program_id: PublicKey,
total_deposits: typing.List[Decimal], total_borrows: typing.List[Decimal],
maint_coll_ratio: Decimal, init_coll_ratio: Decimal, srm_vault: PublicKey,
admin: PublicKey, borrow_limits: typing.List[Decimal]):
super().__init__(account_info)
self.version: Version = version
self.context: Context = context
self.account_flags: MangoAccountFlags = account_flags
self.basket_tokens: typing.List[BasketToken] = basket_tokens
self.markets: typing.List[MarketMetadata] = markets
self.signer_nonce: Decimal = signer_nonce
self.signer_key: PublicKey = signer_key
self.dex_program_id: PublicKey = dex_program_id
self.total_deposits: typing.List[Decimal] = total_deposits
self.total_borrows: typing.List[Decimal] = total_borrows
self.maint_coll_ratio: Decimal = maint_coll_ratio
self.init_coll_ratio: Decimal = init_coll_ratio
self.srm_vault: PublicKey = srm_vault
self.admin: PublicKey = admin
self.borrow_limits: typing.List[Decimal] = borrow_limits
self.mint_decimals: typing.List[int] = [token.mint for token in basket_tokens]
@property
def shared_quote_token(self) -> BasketToken:
return self.basket_tokens[-1]
@staticmethod
def from_layout(layout: layouts.GROUP, context: Context, account_info: AccountInfo) -> "Group":
account_flags = MangoAccountFlags.from_layout(layout.account_flags)
indexes = list(map(lambda pair: Index.from_layout(pair[0], pair[1]), zip(layout.indexes, layout.mint_decimals)))
basket_tokens: typing.List[BasketToken] = []
for index in range(NUM_TOKENS):
token_address = layout.tokens[index]
token_name = context.lookup_token_name(token_address)
if token_name is None:
raise Exception(f"Could not find token with mint '{token_address}' in Group.")
token = Token(token_name, token_address, layout.mint_decimals[index])
basket_token = BasketToken(token, layout.vaults[index], indexes[index])
basket_tokens += [basket_token]
markets: typing.List[MarketMetadata] = []
for index in range(NUM_MARKETS):
market_address = layout.spot_markets[index]
market_name = context.lookup_market_name(market_address)
base_name, quote_name = market_name.split("/")
base_token = BasketToken.find_by_name(basket_tokens, base_name)
quote_token = BasketToken.find_by_name(basket_tokens, quote_name)
market = MarketMetadata(market_name, market_address, base_token, quote_token,
layout.spot_markets[index],
layout.oracles[index],
layout.oracle_decimals[index])
markets += [market]
maint_coll_ratio = layout.maint_coll_ratio.quantize(Decimal('.01'))
init_coll_ratio = layout.init_coll_ratio.quantize(Decimal('.01'))
return Group(account_info, Version.UNSPECIFIED, context, account_flags, basket_tokens, markets,
layout.signer_nonce, layout.signer_key, layout.dex_program_id, layout.total_deposits,
layout.total_borrows, maint_coll_ratio, init_coll_ratio, layout.srm_vault,
layout.admin, layout.borrow_limits)
@staticmethod
def parse(context: Context, account_info: AccountInfo) -> "Group":
data = account_info.data
if len(data) != layouts.GROUP.sizeof():
raise Exception(f"Data length ({len(data)}) does not match expected size ({layouts.GROUP.sizeof()})")
layout = layouts.GROUP.parse(data)
return Group.from_layout(layout, context, account_info)
@staticmethod
def load(context: Context):
account_info = AccountInfo.load(context, context.group_id)
if account_info is None:
raise Exception(f"Group account not found at address '{context.group_id}'")
return Group.parse(context, account_info)
#TODO Test this method, implement get_ui_total_borrow,get_ui_total_deposit
def get_deposit_rate(self,token_index: int):
borrow_rate = self.get_borrow_rate(token_index)
total_borrows = self.get_ui_total_borrow(token_index)
total_deposits = self.get_ui_total_deposit(token_index)
if total_deposits == 0 and total_borrows == 0: return 0
elif total_deposits == 0: return MAX_RATE
utilization = total_borrows / total_deposits
return utilization * borrow_rate
#TODO Test this method, implement get_ui_total_borrow, get_ui_total_deposit
def get_borrow_rate(self,token_index: int):
total_borrows = self.get_ui_total_borrow(token_index)
total_deposits = self.get_ui_total_deposit(token_index)
if total_deposits == 0 and total_borrows == 0: return 0
if total_deposits <= total_borrows : return MAX_RATE
utilization = total_borrows / total_deposits
if utilization > OPTIMAL_UTIL:
extra_util = utilization - OPTIMAL_UTIL
slope = (MAX_RATE - OPTIMAL_RATE) / (1 - OPTIMAL_UTIL)
return OPTIMAL_RATE + slope * extra_util
else:
slope = OPTIMAL_RATE / OPTIMAL_UTIL
return slope * utilization
def get_token_index(self, token: Token) -> int:
for index, existing in enumerate(self.basket_tokens):
if existing.token == token:
return index
return -1
def get_prices(self) -> typing.List[TokenValue]:
started_at = time.time()
# Note: we can just load the oracle data in a simpler way, with:
# oracles = map(lambda market: Aggregator.load(self.context, market.oracle), self.markets)
# but that makes a network request for every oracle. We can reduce that to just one request
# if we use AccountInfo.load_multiple() and parse the data ourselves.
#
# This seems to halve the time this function takes.
oracle_addresses = list([market.oracle for market in self.markets])
oracle_account_infos = AccountInfo.load_multiple(self.context, oracle_addresses)
oracles = map(lambda oracle_account_info: Aggregator.parse(self.context, oracle_account_info),
oracle_account_infos)
prices = list(map(lambda oracle: oracle.price, oracles)) + [Decimal(1)]
token_prices = []
for index, price in enumerate(prices):
token_prices += [TokenValue(self.basket_tokens[index].token, price)]
time_taken = time.time() - started_at
self.logger.info(f"Faster fetching prices complete. Time taken: {time_taken:.2f} seconds.")
return token_prices
def fetch_balances(self, root_address: PublicKey) -> typing.List[TokenValue]:
balances: typing.List[TokenValue] = []
sol_balance = self.context.fetch_sol_balance(root_address)
balances += [TokenValue(SolToken, sol_balance)]
for basket_token in self.basket_tokens:
balance = TokenValue.fetch_total_value(self.context, root_address, basket_token.token)
balances += [balance]
return balances
def native_to_ui(self, amount, decimals) -> int:
return amount / (10 ** decimals)
def ui_to_native(self, amount, decimals) -> int:
return amount * (10 ** decimals)
def getUiTotalDeposit(self, tokenIndex: int) -> int:
return Group.ui_to_native(self.totalDeposits[tokenIndex] * self.indexes[tokenIndex].deposit, self.mint_decimals[tokenIndex])
def getUiTotalBorrow(self, tokenIndex: int) -> int:
return Group.native_to_ui(self.totalBorrows[tokenIndex] * self.indexes[tokenIndex].borrow, self.mint_decimals[tokenIndex])
def __str__(self) -> str:
total_deposits = "\n ".join(map(str, self.total_deposits))
total_borrows = "\n ".join(map(str, self.total_borrows))
borrow_limits = "\n ".join(map(str, self.borrow_limits))
return f"""
« Group [{self.version}] {self.address}:
Flags: {self.account_flags}
Tokens:
{self.basket_tokens}
Markets:
{self.markets}
DEX Program ID: « {self.dex_program_id} »
SRM Vault: « {self.srm_vault} »
Admin: « {self.admin} »
Signer Nonce: {self.signer_nonce}
Signer Key: « {self.signer_key} »
Initial Collateral Ratio: {self.init_coll_ratio}
Maintenance Collateral Ratio: {self.maint_coll_ratio}
Total Deposits:
{total_deposits}
Total Borrows:
{total_borrows}
Borrow Limits:
{borrow_limits}
»
"""
class TokenAccount(AddressableAccount):
def __init__(self, account_info: AccountInfo, version: Version, mint: PublicKey, owner: PublicKey, amount: Decimal):
super().__init__(account_info)
self.version: Version = version
self.mint: PublicKey = mint
self.owner: PublicKey = owner
self.amount: Decimal = amount
@staticmethod
def create(context: Context, account: Account, token: Token):
spl_token = await SplToken(context.client, token.mint, TOKEN_PROGRAM_ID, account)
owner = account.public_key()
new_account_address = spl_token.create_account(owner)
return TokenAccount.load(context, new_account_address)
@staticmethod
def fetch_all_for_owner_and_token(context: Context, owner_public_key: PublicKey, token: Token) -> typing.List["TokenAccount"]:
opts = TokenAccountOpts(mint=token.mint)
token_accounts_response = await context.client.get_token_accounts_by_owner(owner_public_key, opts, commitment=context.commitment)
all_accounts: typing.List[TokenAccount] = []
for token_account_response in token_accounts_response["result"]["value"]:
account_info = AccountInfo._from_response_values(token_account_response["account"], PublicKey(token_account_response["pubkey"]))
token_account = TokenAccount.parse(account_info)
all_accounts += [token_account]
return all_accounts
@staticmethod
def fetch_largest_for_owner_and_token(context: Context, owner_public_key: PublicKey, token: Token) -> typing.Optional["TokenAccount"]:
all_accounts = TokenAccount.fetch_all_for_owner_and_token(context, owner_public_key, token)
largest_account: typing.Optional[TokenAccount] = None
for token_account in all_accounts:
if largest_account is None or token_account.amount > largest_account.amount:
largest_account = token_account
return largest_account
@staticmethod
def fetch_or_create_largest_for_owner_and_token(context: Context, account: Account, token: Token) -> "TokenAccount":
all_accounts = TokenAccount.fetch_all_for_owner_and_token(context, account.public_key(), token)
largest_account: typing.Optional[TokenAccount] = None
for token_account in all_accounts:
if largest_account is None or token_account.amount > largest_account.amount:
largest_account = token_account
if largest_account is None:
return TokenAccount.create(context, account, token)
return largest_account
@staticmethod
def from_layout(layout: layouts.TOKEN_ACCOUNT, account_info: AccountInfo) -> "TokenAccount":
return TokenAccount(account_info, Version.UNSPECIFIED, layout.mint, layout.owner, layout.amount)
@staticmethod
def parse(account_info: AccountInfo) -> "TokenAccount":
data = account_info.data
if len(data) != layouts.TOKEN_ACCOUNT.sizeof():
raise Exception(f"Data length ({len(data)}) does not match expected size ({layouts.TOKEN_ACCOUNT.sizeof()})")
layout = layouts.TOKEN_ACCOUNT.parse(data)
return TokenAccount.from_layout(layout, account_info)
@staticmethod
def load(context: Context, address: PublicKey) -> typing.Optional["TokenAccount"]:
account_info = AccountInfo.load(context, address)
if account_info is None or (len(account_info.data) != layouts.TOKEN_ACCOUNT.sizeof()):
return None
return TokenAccount.parse(account_info)
def __str__(self) -> str:
return f"« Token: Mint: {self.mint}, Owner: {self.owner}, Amount: {self.amount} »"
class OpenOrders(AddressableAccount):
def __init__(self, account_info: AccountInfo, version: Version, program_id: PublicKey,
account_flags: SerumAccountFlags, market: PublicKey, owner: PublicKey,
base_token_free: Decimal, base_token_total: Decimal, quote_token_free: Decimal,
quote_token_total: Decimal, free_slot_bits: Decimal, is_bid_bits: Decimal,
orders: typing.List[Decimal], client_ids: typing.List[Decimal],
referrer_rebate_accrued: Decimal):
super().__init__(account_info)
self.version: Version = version
self.program_id: PublicKey = program_id
self.account_flags: SerumAccountFlags = account_flags
self.market: PublicKey = market
self.owner: PublicKey = owner
self.base_token_free: Decimal = base_token_free
self.base_token_total: Decimal = base_token_total
self.quote_token_free: Decimal = quote_token_free
self.quote_token_total: Decimal = quote_token_total
self.free_slot_bits: Decimal = free_slot_bits
self.is_bid_bits: Decimal = is_bid_bits
self.orders: typing.List[Decimal] = orders
self.client_ids: typing.List[Decimal] = client_ids
self.referrer_rebate_accrued: Decimal = referrer_rebate_accrued
# Sometimes pyserum wants to take its own OpenOrdersAccount as a parameter (e.g. in settle_funds())
def to_pyserum(self) -> OpenOrdersAccount:
return OpenOrdersAccount.from_bytes(self.address, self.account_info.data)
@staticmethod
def from_layout(layout: layouts.OPEN_ORDERS, account_info: AccountInfo,
base_decimals: Decimal, quote_decimals: Decimal) -> "OpenOrders":
account_flags = SerumAccountFlags.from_layout(layout.account_flags)
program_id = account_info.owner
base_divisor = 10 ** base_decimals
quote_divisor = 10 ** quote_decimals
base_token_free: Decimal = layout.base_token_free / base_divisor
base_token_total: Decimal = layout.base_token_total / base_divisor
quote_token_free: Decimal = layout.quote_token_free / quote_divisor
quote_token_total: Decimal = layout.quote_token_total / quote_divisor
nonzero_orders: typing.List[Decimal] = list([order for order in layout.orders if order != 0])
nonzero_client_ids: typing.List[Decimal] = list([client_id for client_id in layout.client_ids if client_id != 0])
return OpenOrders(account_info, Version.UNSPECIFIED, program_id, account_flags, layout.market,
layout.owner, base_token_free, base_token_total, quote_token_free, quote_token_total,
layout.free_slot_bits, layout.is_bid_bits, nonzero_orders, nonzero_client_ids,
layout.referrer_rebate_accrued)
@staticmethod
def parse(account_info: AccountInfo, base_decimals: Decimal, quote_decimals: Decimal) -> "OpenOrders":
data = account_info.data
if len(data) != layouts.OPEN_ORDERS.sizeof():
raise Exception(f"Data length ({len(data)}) does not match expected size ({layouts.OPEN_ORDERS.sizeof()})")
layout = layouts.OPEN_ORDERS.parse(data)
return OpenOrders.from_layout(layout, account_info, base_decimals, quote_decimals)
@staticmethod
async def load_raw_open_orders_account_infos(context: Context, group: Group) -> typing.Dict[str, AccountInfo]:
filters = [
MemcmpOpts(
offset=layouts.SERUM_ACCOUNT_FLAGS.sizeof() + 37,
bytes=encode_key(group.signer_key)
)
]
response = await context.client.get_program_accounts(group.dex_program_id, data_size=layouts.OPEN_ORDERS.sizeof(), memcmp_opts=filters, commitment=Single, encoding="base64")
account_infos = list(map(lambda pair: AccountInfo._from_response_values(pair[0], pair[1]), [(result["account"], PublicKey(result["pubkey"])) for result in response["result"]]))
account_infos_by_address = {key: value for key, value in [(str(account_info.address), account_info) for account_info in account_infos]}
return account_infos_by_address
@staticmethod
def load(context: Context, address: PublicKey, base_decimals: Decimal, quote_decimals: Decimal) -> "OpenOrders":
open_orders_account = AccountInfo.load(context, address)
if open_orders_account is None:
raise Exception(f"OpenOrders account not found at address '{address}'")
return OpenOrders.parse(open_orders_account, base_decimals, quote_decimals)
@staticmethod
async def load_for_market_and_owner(context: Context, market: PublicKey, owner: PublicKey, program_id: PublicKey, base_decimals: Decimal, quote_decimals: Decimal):
filters = [
MemcmpOpts(
offset=layouts.SERUM_ACCOUNT_FLAGS.sizeof() + 5,
bytes=encode_key(market)
),
MemcmpOpts(
offset=layouts.SERUM_ACCOUNT_FLAGS.sizeof() + 37,
bytes=encode_key(owner)
)
]
response = await context.client.get_program_accounts(context.dex_program_id, data_size=layouts.OPEN_ORDERS.sizeof(), memcmp_opts=filters, commitment=Single, encoding="base64")
accounts = list(map(lambda pair: AccountInfo._from_response_values(pair[0], pair[1]), [(result["account"], PublicKey(result["pubkey"])) for result in response["result"]]))
return list(map(lambda acc: OpenOrders.parse(acc, base_decimals, quote_decimals), accounts))
def __str__(self) -> str:
orders = ", ".join(map(str, self.orders)) or "None"
client_ids = ", ".join(map(str, self.client_ids)) or "None"
return f"""« OpenOrders:
Flags: {self.account_flags}
Program ID: {self.program_id}
Address: {self.address}
Market: {self.market}
Owner: {self.owner}
Base Token: {self.base_token_free:,.8f} of {self.base_token_total:,.8f}
Quote Token: {self.quote_token_free:,.8f} of {self.quote_token_total:,.8f}
Referrer Rebate Accrued: {self.referrer_rebate_accrued}
Orders:
{orders}
Client IDs:
{client_ids}
»"""
class BalanceSheet:
def __init__(self, token: Token, liabilities: Decimal, settled_assets: Decimal, unsettled_assets: Decimal):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.token: Token = token
self.liabilities: Decimal = liabilities
self.settled_assets: Decimal = settled_assets
self.unsettled_assets: Decimal = unsettled_assets
@property
def assets(self) -> Decimal:
return self.settled_assets + self.unsettled_assets
@property
def value(self) -> Decimal:
return self.assets - self.liabilities
@property
def collateral_ratio(self) -> Decimal:
if self.liabilities == Decimal(0):
return Decimal(0)
return self.assets / self.liabilities
def __str__(self) -> str:
name = "«Unspecified»"
if self.token is not None:
name = self.token.name
return f"""« BalanceSheet [{name}]:
Assets : {self.assets:>18,.8f}
Settled Assets : {self.settled_assets:>18,.8f}
Unsettled Assets : {self.unsettled_assets:>18,.8f}
Liabilities : {self.liabilities:>18,.8f}
Value : {self.value:>18,.8f}
Collateral Ratio : {self.collateral_ratio:>18,.2%}
»
"""
def __repr__(self) -> str:
return f"{self}"
class MarginAccount(AddressableAccount):
def __init__(self, account_info: AccountInfo, version: Version, account_flags: MangoAccountFlags,
mango_group: PublicKey, owner: PublicKey, deposits: typing.List[Decimal],
borrows: typing.List[Decimal], open_orders: typing.List[PublicKey]):
super().__init__(account_info)
self.version: Version = version
self.account_flags: MangoAccountFlags = account_flags
self.mango_group: PublicKey = mango_group
self.owner: PublicKey = owner
self.deposits: typing.List[Decimal] = deposits
self.borrows: typing.List[Decimal] = borrows
self.open_orders: typing.List[PublicKey] = open_orders
self.open_orders_accounts: typing.List[typing.Optional[OpenOrders]] = [None] * NUM_MARKETS
@staticmethod
def from_layout(layout: layouts.MARGIN_ACCOUNT, account_info: AccountInfo) -> "MarginAccount":
account_flags: MangoAccountFlags = MangoAccountFlags.from_layout(layout.account_flags)
deposits: typing.List[Decimal] = []
for index, deposit in enumerate(layout.deposits):
deposits += [deposit]
borrows: typing.List[Decimal] = []
for index, borrow in enumerate(layout.borrows):
borrows += [borrow]
return MarginAccount(account_info, Version.UNSPECIFIED, account_flags, layout.mango_group,
layout.owner, deposits, borrows, list(layout.open_orders))
@staticmethod
def parse(account_info: AccountInfo) -> "MarginAccount":
data = account_info.data
if len(data) != layouts.MARGIN_ACCOUNT.sizeof():
raise Exception(f"Data length ({len(data)}) does not match expected size ({layouts.MARGIN_ACCOUNT.sizeof()})")
layout = layouts.MARGIN_ACCOUNT.parse(data)
return MarginAccount.from_layout(layout, account_info)
@staticmethod
def load(context: Context, margin_account_address: PublicKey, group: typing.Optional[Group] = None) -> "MarginAccount":
account_info = AccountInfo.load(context, margin_account_address)
if account_info is None:
raise Exception(f"MarginAccount account not found at address '{margin_account_address}'")
margin_account = MarginAccount.parse(account_info)
if group is None:
group = Group.load(context)
margin_account.load_open_orders_accounts(context, group)
return margin_account
@staticmethod
def load_all_for_group(context: Context, program_id: PublicKey, group: Group) -> typing.List["MarginAccount"]:
filters = [
MemcmpOpts(
offset=layouts.MANGO_ACCOUNT_FLAGS.sizeof(), # mango_group is just after the MangoAccountFlags, which is the first entry
bytes=encode_key(group.address)
)
]
response = context.client.get_program_accounts(program_id, data_size=layouts.MARGIN_ACCOUNT.sizeof(), memcmp_opts=filters, commitment=Single, encoding="base64")
margin_accounts = []
for margin_account_data in response["result"]:
address = PublicKey(margin_account_data["pubkey"])
account = AccountInfo._from_response_values(margin_account_data["account"], address)
margin_account = MarginAccount.parse(account)
margin_accounts += [margin_account]
return margin_accounts
@staticmethod
def load_all_for_group_with_open_orders(context: Context, program_id: PublicKey, group: Group) -> typing.List["MarginAccount"]:
margin_accounts = MarginAccount.load_all_for_group(context, context.program_id, group)
open_orders = OpenOrders.load_raw_open_orders_account_infos(context, group)
for margin_account in margin_accounts:
margin_account.install_open_orders_accounts(group, open_orders)
return margin_accounts
@staticmethod
def load_all_for_owner(context: Context, owner: PublicKey, group: typing.Optional[Group] = None) -> typing.List["MarginAccount"]:
if group is None:
group = Group.load(context)
mango_group_offset = layouts.MANGO_ACCOUNT_FLAGS.sizeof() # mango_group is just after the MangoAccountFlags, which is the first entry.
owner_offset = mango_group_offset + 32 # owner is just after mango_group in the layout, and it's a PublicKey which is 32 bytes.
filters = [
MemcmpOpts(
offset=mango_group_offset,
bytes=encode_key(group.address)
),
MemcmpOpts(
offset=owner_offset,
bytes=encode_key(owner)
)
]
response = context.client.get_program_accounts(context.program_id, data_size=layouts.MARGIN_ACCOUNT.sizeof(), memcmp_opts=filters, commitment=Single, encoding="base64")
margin_accounts = []
for margin_account_data in response["result"]:
address = PublicKey(margin_account_data["pubkey"])
account = AccountInfo._from_response_values(margin_account_data["account"], address)
margin_account = MarginAccount.parse(account)
margin_account.load_open_orders_accounts(context, group)
margin_accounts += [margin_account]
return margin_accounts
@classmethod
def load_all_ripe(cls, context: Context) -> typing.List["MarginAccount"]:
logger: logging.Logger = logging.getLogger(cls.__name__)
started_at = time.time()
group = Group.load(context)
margin_accounts = MarginAccount.load_all_for_group_with_open_orders(context, context.program_id, group)
logger.info(f"Fetched {len(margin_accounts)} margin accounts to process.")
prices = group.get_prices()
nonzero: typing.List[MarginAccountMetadata] = []
for margin_account in margin_accounts:
balance_sheet = margin_account.get_balance_sheet_totals(group, prices)
if balance_sheet.collateral_ratio > 0:
balances = margin_account.get_intrinsic_balances(group)
nonzero += [MarginAccountMetadata(margin_account, balance_sheet, balances)]
logger.info(f"Of those {len(margin_accounts)}, {len(nonzero)} have a nonzero collateral ratio.")
ripe_metadata = filter(lambda mam: mam.balance_sheet.collateral_ratio <= group.init_coll_ratio, nonzero)
ripe_accounts = list(map(lambda mam: mam.margin_account, ripe_metadata))
logger.info(f"Of those {len(nonzero)}, {len(ripe_accounts)} are ripe 🥭.")
time_taken = time.time() - started_at
logger.info(f"Loading ripe 🥭 accounts complete. Time taken: {time_taken:.2f} seconds.")
return ripe_accounts
def load_open_orders_accounts(self, context: Context, group: Group) -> None:
for index, oo in enumerate(self.open_orders):
key = oo
if key != SYSTEM_PROGRAM_ADDRESS:
self.open_orders_accounts[index] = OpenOrders.load(context, key, group.basket_tokens[index].token.decimals, group.shared_quote_token.token.decimals)
def install_open_orders_accounts(self, group: Group, all_open_orders_by_address: typing.Dict[str, AccountInfo]) -> None:
for index, oo in enumerate(self.open_orders):
key = str(oo)
if key in all_open_orders_by_address:
open_orders_account_info = all_open_orders_by_address[key]
open_orders = OpenOrders.parse(open_orders_account_info,
group.basket_tokens[index].token.decimals,
group.shared_quote_token.token.decimals)
self.open_orders_accounts[index] = open_orders
def get_intrinsic_balance_sheets(self, group: Group) -> typing.List[BalanceSheet]:
settled_assets: typing.List[Decimal] = [Decimal(0)] * NUM_TOKENS
liabilities: typing.List[Decimal] = [Decimal(0)] * NUM_TOKENS
for index in range(NUM_TOKENS):
settled_assets[index] = group.basket_tokens[index].index.deposit * self.deposits[index]
liabilities[index] = group.basket_tokens[index].index.borrow * self.borrows[index]
unsettled_assets: typing.List[Decimal] = [Decimal(0)] * NUM_TOKENS
for index in range(NUM_MARKETS):
open_orders_account = self.open_orders_accounts[index]
if open_orders_account is not None:
unsettled_assets[index] += open_orders_account.base_token_total
unsettled_assets[NUM_TOKENS - 1] += open_orders_account.quote_token_total
balance_sheets: typing.List[BalanceSheet] = []
for index in range(NUM_TOKENS):
balance_sheets += [BalanceSheet(group.basket_tokens[index].token, liabilities[index],
settled_assets[index], unsettled_assets[index])]
return balance_sheets
def get_priced_balance_sheets(self, group: Group, prices: typing.List[TokenValue]) -> typing.List[BalanceSheet]:
priced: typing.List[BalanceSheet] = []
balance_sheets = self.get_intrinsic_balance_sheets(group)
for balance_sheet in balance_sheets:
price = TokenValue.find_by_token(prices, balance_sheet.token)
liabilities = balance_sheet.liabilities * price.value
settled_assets = balance_sheet.settled_assets * price.value
unsettled_assets = balance_sheet.unsettled_assets * price.value
priced += [BalanceSheet(
price.token,
price.token.round(liabilities),
price.token.round(settled_assets),
price.token.round(unsettled_assets)
)]
return priced
def get_balance_sheet_totals(self, group: Group, prices: typing.List[TokenValue]) -> BalanceSheet:
liabilities = Decimal(0)
settled_assets = Decimal(0)
unsettled_assets = Decimal(0)
balance_sheets = self.get_priced_balance_sheets(group, prices)
for balance_sheet in balance_sheets:
if balance_sheet is not None:
liabilities += balance_sheet.liabilities
settled_assets += balance_sheet.settled_assets
unsettled_assets += balance_sheet.unsettled_assets
# A BalanceSheet must have a token - it's a pain to make it a typing.Optional[Token].
# So in this one case, we produce a 'fake' token whose symbol is a summary of all token
# symbols that went into it.
#
# If this becomes more painful than typing.Optional[Token], we can go with making
# Token optional.
summary_name = "-".join([bal.token.name for bal in balance_sheets])
summary_token = Token(summary_name, SYSTEM_PROGRAM_ADDRESS, Decimal(0))
return BalanceSheet(summary_token, liabilities, settled_assets, unsettled_assets)
def get_intrinsic_balances(self, group: Group) -> typing.List[TokenValue]:
balance_sheets = self.get_intrinsic_balance_sheets(group)
balances: typing.List[TokenValue] = []
for index, balance_sheet in enumerate(balance_sheets):
if balance_sheet.token is None:
raise Exception(f"Intrinsic balance sheet with index [{index}] has no token.")
balances += [TokenValue(balance_sheet.token, balance_sheet.value)]
return balances
def __str__(self) -> str:
deposits = ", ".join([f"{item:,.8f}" for item in self.deposits])
borrows = ", ".join([f"{item:,.8f}" for item in self.borrows])
if all(oo is None for oo in self.open_orders_accounts):
open_orders = f"{self.open_orders}"
else:
open_orders_unindented = f"{self.open_orders_accounts}"
open_orders = open_orders_unindented.replace("\n", "\n ")
return f"""« MarginAccount: {self.address}
Flags: {self.account_flags}
Owner: {self.owner}
Mango Group: {self.mango_group}
Deposits: [{deposits}]
Borrows: [{borrows}]
Mango Open Orders: {open_orders}
»"""
class MarginAccountMetadata:
def __init__(self, margin_account: MarginAccount, balance_sheet: BalanceSheet, balances: typing.List[TokenValue]):
self.logger: logging.Logger = logging.getLogger(self.__class__.__name__)
self.margin_account = margin_account
self.balance_sheet = balance_sheet
self.balances = balances
@property
def assets(self):
return self.balance_sheet.assets
@property
def liabilities(self):
return self.balance_sheet.liabilities
@property
def collateral_ratio(self):
return self.balance_sheet.collateral_ratio
class LiquidationEvent:
def __init__(self, timestamp: datetime.datetime, signature: str, wallet_address: PublicKey, margin_account_address: PublicKey, balances_before: typing.List[TokenValue], balances_after: typing.List[TokenValue]):
self.timestamp = timestamp
self.signature = signature
self.wallet_address = wallet_address
self.margin_account_address = margin_account_address
self.balances_before = balances_before
self.balances_after = balances_after
def __str__(self) -> str:
changes = TokenValue.changes(self.balances_before, self.balances_after)
changes_text = "\n ".join([f"{change.value:>15,.8f} {change.token.name}" for change in changes])
return f"""« 🥭 Liqudation Event 💧 at {self.timestamp}
📇 Signature: {self.signature}
👛 Wallet: {self.wallet_address}
💳 Margin Account: {self.margin_account_address}
💸 Changes:
{changes_text}
»"""
def __repr__(self) -> str:
return f"{self}"
def _notebook_tests():
log_level = logging.getLogger().level
try:
logging.getLogger().setLevel(logging.CRITICAL)
from Constants import SYSTEM_PROGRAM_ADDRESS
from Context import default_context
balances_before = [
TokenValue(TokenLookup.find_by_name(default_context, "ETH"), Decimal(1)),
TokenValue(TokenLookup.find_by_name(default_context, "BTC"), Decimal("0.1")),
TokenValue(TokenLookup.find_by_name(default_context, "USDT"), Decimal(1000))
]
balances_after = [
TokenValue(TokenLookup.find_by_name(default_context, "ETH"), Decimal(1)),
TokenValue(TokenLookup.find_by_name(default_context, "BTC"), Decimal("0.05")),
TokenValue(TokenLookup.find_by_name(default_context, "USDT"), Decimal(2000))
]
timestamp = datetime.datetime(2021, 5, 17, 12, 20, 56)
event = LiquidationEvent(timestamp, "signature", SYSTEM_PROGRAM_ADDRESS, SYSTEM_PROGRAM_ADDRESS,
balances_before, balances_after)
assert(str(event) == """« 🥭 Liqudation Event 💧 at 2021-05-17 12:20:56
📇 Signature: signature
👛 Wallet: 11111111111111111111111111111111
💳 Margin Account: 11111111111111111111111111111111
💸 Changes:
0.00000000 ETH
-0.05000000 BTC
1,000.00000000 USDT
»""")
finally:
logging.getLogger().setLevel(log_level)
_notebook_tests()
del _notebook_tests
if __name__ == "__main__":
logging.getLogger().setLevel(logging.INFO)
import base64
from Constants import SYSTEM_PROGRAM_ADDRESS
from Context import default_context
# Just use any public key here
fake_public_key = SYSTEM_PROGRAM_ADDRESS
encoded = "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"
decoded = base64.b64decode(encoded)
group_account_info = AccountInfo(fake_public_key, False, Decimal(0), fake_public_key, Decimal(0), decoded)
group = Group.parse(default_context, group_account_info)
print("\n\nThis is hard-coded, not live information!")
print(group)
print(TokenLookup.find_by_name(default_context, "ETH"))
print(TokenLookup.find_by_name(default_context, "BTC"))
# USDT
print(TokenLookup.find_by_mint(default_context, PublicKey("Es9vMFrzaCERmJfrF4H2FYD4KCoNkY11McCe8BenwNYB")))
single_account_info = AccountInfo.load(default_context, default_context.dex_program_id)
print("DEX account info", single_account_info)
multiple_account_info = AccountInfo.load_multiple(default_context, [default_context.program_id, default_context.dex_program_id])
print("Mango program and DEX account info", multiple_account_info)
balances_before = [
TokenValue(TokenLookup.find_by_name(default_context, "ETH"), Decimal(1)),
TokenValue(TokenLookup.find_by_name(default_context, "BTC"), Decimal("0.1")),
TokenValue(TokenLookup.find_by_name(default_context, "USDT"), Decimal(1000))
]
balances_after = [
TokenValue(TokenLookup.find_by_name(default_context, "ETH"), Decimal(1)),
TokenValue(TokenLookup.find_by_name(default_context, "BTC"), Decimal("0.05")),
TokenValue(TokenLookup.find_by_name(default_context, "USDT"), Decimal(2000))
]
timestamp = datetime.datetime(2021, 5, 17, 12, 20, 56)
event = LiquidationEvent(timestamp, "signature", SYSTEM_PROGRAM_ADDRESS, SYSTEM_PROGRAM_ADDRESS,
balances_before, balances_after)
print(event) | [((1325, 14, 1325, 39), 'base64.b64decode', 'base64.b64decode', ({(1325, 31, 1325, 38): 'encoded'}, {}), '(encoded)', False, 'import base64\n'), ((1354, 16, 1354, 58), 'datetime.datetime', 'datetime.datetime', ({(1354, 34, 1354, 38): '2021', (1354, 40, 1354, 41): '5', (1354, 43, 1354, 45): '17', (1354, 47, 1354, 49): '12', (1354, 51, 1354, 53): '20', (1354, 55, 1354, 57): '56'}, {}), '(2021, 5, 17, 12, 20, 56)', False, 'import datetime\n'), ((58, 38, 58, 80), 'logging.getLogger', 'logging.getLogger', ({(58, 56, 58, 79): 'self.__class__.__name__'}, {}), '(self.__class__.__name__)', False, 'import logging\n'), ((67, 15, 67, 39), 'Decoder.encode_binary', 'encode_binary', ({(67, 29, 67, 38): 'self.data'}, {}), '(self.data)', False, 'from Decoder import decode_binary, encode_binary, encode_key\n'), ((101, 19, 101, 55), 'decimal.Decimal', 'Decimal', ({(101, 27, 101, 54): "response_values['lamports']"}, {}), "(response_values['lamports'])", False, 'from decimal import 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((656, 17, 656, 42), 'Layout.GROUP.parse', 'layouts.GROUP.parse', ({(656, 37, 656, 41): 'data'}, {}), '(data)', True, 'import Layout as layouts\n'), ((700, 21, 700, 32), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((791, 15, 791, 48), 'solana.rpc.types.TokenAccountOpts', 'TokenAccountOpts', (), '', False, 'from solana.rpc.types import MemcmpOpts, TokenAccountOpts, RPCMethod, RPCResponse\n'), ((838, 17, 838, 50), 'Layout.TOKEN_ACCOUNT.parse', 'layouts.TOKEN_ACCOUNT.parse', ({(838, 45, 838, 49): 'data'}, {}), '(data)', True, 'import Layout as layouts\n'), ((876, 15, 876, 81), 'pyserum.open_orders_account.OpenOrdersAccount.from_bytes', 'OpenOrdersAccount.from_bytes', ({(876, 44, 876, 56): 'self.address', (876, 58, 876, 80): 'self.account_info.data'}, {}), '(self.address, self.account_info.data)', False, 'from pyserum.open_orders_account import OpenOrdersAccount\n'), ((904, 17, 904, 48), 'Layout.OPEN_ORDERS.parse', 'layouts.OPEN_ORDERS.parse', ({(904, 43, 904, 47): 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({(1326, 98, 1326, 99): '0'}, {}), '(0)', False, 'from decimal import Decimal\n'), ((195, 33, 195, 56), 'decimal.Decimal', 'Decimal', ({(195, 41, 195, 55): '(10 ** decimals)'}, {}), '(10 ** decimals)', False, 'from decimal import Decimal\n'), ((196, 35, 196, 58), 'decimal.Decimal', 'Decimal', ({(196, 43, 196, 57): '(10 ** decimals)'}, {}), '(10 ** decimals)', False, 'from decimal import Decimal\n'), ((300, 24, 300, 51), 'Layout.AGGREGATOR.sizeof', 'layouts.AGGREGATOR.sizeof', ({}, {}), '()', True, 'import Layout as layouts\n'), ((385, 33, 385, 43), 'decimal.Decimal', 'Decimal', ({(385, 41, 385, 42): '(6)'}, {}), '(6)', False, 'from decimal import Decimal\n'), ((394, 33, 394, 43), 'decimal.Decimal', 'Decimal', ({(394, 41, 394, 42): '(6)'}, {}), '(6)', False, 'from decimal import Decimal\n'), ((461, 20, 461, 64), 'decimal.Decimal', 'Decimal', ({(461, 28, 461, 63): "result['result']['value']['amount']"}, {}), "(result['result']['value']['amount'])", False, 'from decimal import 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39), 'Decoder.encode_key', 'encode_key', ({(937, 33, 937, 38): 'owner'}, {}), '(owner)', False, 'from Decoder import decode_binary, encode_binary, encode_key\n'), ((941, 95, 941, 123), 'Layout.OPEN_ORDERS.sizeof', 'layouts.OPEN_ORDERS.sizeof', ({}, {}), '()', True, 'import Layout as layouts\n'), ((1056, 23, 1056, 59), 'Layout.MANGO_ACCOUNT_FLAGS.sizeof', 'layouts.MANGO_ACCOUNT_FLAGS.sizeof', ({}, {}), '()', True, 'import Layout as layouts\n'), ((1057, 22, 1057, 47), 'Decoder.encode_key', 'encode_key', ({(1057, 33, 1057, 46): 'group.address'}, {}), '(group.address)', False, 'from Decoder import decode_binary, encode_binary, encode_key\n'), ((1088, 22, 1088, 47), 'Decoder.encode_key', 'encode_key', ({(1088, 33, 1088, 46): 'group.address'}, {}), '(group.address)', False, 'from Decoder import decode_binary, encode_binary, encode_key\n'), ((1092, 22, 1092, 39), 'Decoder.encode_key', 'encode_key', ({(1092, 33, 1092, 38): 'owner'}, {}), '(owner)', False, 'from Decoder import decode_binary, 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{}), '()', True, 'import Layout as layouts\n'), ((936, 23, 936, 59), 'Layout.SERUM_ACCOUNT_FLAGS.sizeof', 'layouts.SERUM_ACCOUNT_FLAGS.sizeof', ({}, {}), '()', True, 'import Layout as layouts\n'), ((942, 115, 942, 142), 'solana.publickey.PublicKey', 'PublicKey', ({(942, 125, 942, 141): "result['pubkey']"}, {}), "(result['pubkey'])", False, 'from solana.publickey import PublicKey\n'), ((1036, 87, 1036, 118), 'Layout.MARGIN_ACCOUNT.sizeof', 'layouts.MARGIN_ACCOUNT.sizeof', ({}, {}), '()', True, 'import Layout as layouts\n')] |
afnmachado/univesp_pi_1 | agendamentos/migrations/0011_alter_agendamentosfuncionarios_table.py | e6f2b545faaf53d14d17f751d2fb32e6618885b7 | # Generated by Django 3.2.8 on 2021-11-29 05:47
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('agendamentos', '0010_agendamentosfuncionarios'),
]
operations = [
migrations.AlterModelTable(
name='agendamentosfuncionarios',
table='agendamento_funcionario',
),
]
| [((13, 8, 16, 9), 'django.db.migrations.AlterModelTable', 'migrations.AlterModelTable', (), '', False, 'from django.db import migrations\n')] |
teresa-ho/stx-openstacksdk | openstack/tests/unit/metric/v1/test_capabilities.py | 7d723da3ffe9861e6e9abcaeadc1991689f782c5 | # Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import testtools
from openstack.metric.v1 import capabilities
BODY = {
'aggregation_methods': ['mean', 'max', 'avg'],
}
class TestCapabilites(testtools.TestCase):
def test_basic(self):
sot = capabilities.Capabilities()
self.assertEqual('/capabilities', sot.base_path)
self.assertEqual('metric', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertTrue(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
def test_make_it(self):
sot = capabilities.Capabilities(**BODY)
self.assertEqual(BODY['aggregation_methods'],
sot.aggregation_methods)
| [((24, 14, 24, 41), 'openstack.metric.v1.capabilities.Capabilities', 'capabilities.Capabilities', ({}, {}), '()', False, 'from openstack.metric.v1 import capabilities\n'), ((34, 14, 34, 47), 'openstack.metric.v1.capabilities.Capabilities', 'capabilities.Capabilities', ({}, {}), '(**BODY)', False, 'from openstack.metric.v1 import capabilities\n')] |
yqliaohk/pyXDSM | pyxdsm/tests/test_xdsm.py | 3bcfab710543d6624ba0698093c6522bc94601e8 | import unittest
import os
from pyxdsm.XDSM import XDSM, __file__
from numpy.distutils.exec_command import find_executable
def filter_lines(lns):
# Empty lines are excluded.
# Leading and trailing whitespaces are removed
# Comments are removed.
return [ln.strip() for ln in lns if ln.strip() and not ln.strip().startswith('%')]
class TestXDSM(unittest.TestCase):
def setUp(self):
import os
import tempfile
self.startdir = os.getcwd()
self.tempdir = tempfile.mkdtemp(prefix='testdir-')
os.chdir(self.tempdir)
def tearDown(self):
import os
import shutil
os.chdir(self.startdir)
try:
shutil.rmtree(self.tempdir)
except OSError:
pass
def test_examples(self):
'''
This test just builds the three examples, and assert that the output files exist.
Unlike the other tests, this one requires LaTeX to be available.
'''
os.chdir(os.path.join(os.path.dirname(os.path.abspath(__file__)), '../examples'))
filenames = ['kitchen_sink', 'mdf']
for f in filenames:
os.system('python {}.py'.format(f))
self.assertTrue(os.path.isfile(f + '.tikz'))
self.assertTrue(os.path.isfile(f + '.tex'))
# look for the pdflatex executable
pdflatex = find_executable('pdflatex') is not None
# if no pdflatex, then do not assert that the pdf was compiled
self.assertTrue(not pdflatex or os.path.isfile(f + '.pdf'))
os.system('python mat_eqn.py')
self.assertTrue(os.path.isfile('mat_eqn_example.pdf'))
# change back to previous directory
os.chdir(self.tempdir)
def test_connect(self):
x = XDSM(use_sfmath=False)
x.add_system('D1', 'Function', 'D_1', label_width=2)
x.add_system('D2', 'Function', 'D_2', stack=False)
try:
x.connect('D1', 'D2', r'\mathcal{R}(y_1)', 'foobar')
except ValueError as err:
self.assertEquals(str(err), 'label_width argument must be an integer')
else:
self.fail('Expected ValueError')
def test_options(self):
filename = 'xdsm_test_options'
spec_dir = filename + '_specs'
# Change `use_sfmath` to False to use computer modern
x = XDSM(use_sfmath=False)
x.add_system('opt', 'Optimization', r'\text{Optimizer}')
x.add_system('solver', 'MDA', r'\text{Newton}')
x.add_system('D1', 'Function', 'D_1', label_width=2)
x.add_system('D2', 'Function', 'D_2', stack=False)
x.add_system('F', 'Function', 'F', faded=True)
x.add_system('G', 'Function', 'G', spec_name="G_spec")
x.connect('opt', 'D1', 'x, z')
x.connect('opt', 'D2', 'z')
x.connect('opt', 'F', 'x, z')
x.connect('solver', 'D1', 'y_2')
x.connect('solver', 'D2', 'y_1')
x.connect('D1', 'solver', r'\mathcal{R}(y_1)')
x.connect('solver', 'F', 'y_1, y_2')
x.connect('D2', 'solver', r'\mathcal{R}(y_2)')
x.connect('solver', 'G', 'y_1, y_2')
x.connect('F', 'opt', 'f')
x.connect('G', 'opt', 'g')
x.add_output('opt', 'x^*, z^*', side='right')
x.add_output('D1', 'y_1^*', side='left', stack=True)
x.add_output('D2', 'y_2^*', side='left')
x.add_output('F', 'f^*', side='left')
x.add_output('G', 'g^*')
x.write(filename)
x.write_sys_specs(spec_dir)
# Test if files where created
self.assertTrue(os.path.isfile(filename + '.tikz'))
self.assertTrue(os.path.isfile(filename + '.tex'))
self.assertTrue(os.path.isdir(spec_dir))
self.assertTrue(os.path.isfile(os.path.join(spec_dir, 'F.json')))
self.assertTrue(os.path.isfile(os.path.join(spec_dir, 'G_spec.json')))
def test_stacked_system(self):
x = XDSM()
x.add_system('test', 'Optimization', r'\text{test}', stack=True)
file_name = "stacked_test"
x.write(file_name)
tikz_file = file_name + '.tikz'
with open(tikz_file, "r") as f:
tikz = f.read()
self.assertIn(r"\node [Optimization,stack]", tikz)
def test_tikz_content(self):
# Check if TiKZ file was created.
# Compare the content of the sample below and the newly created TiKZ file.
sample_txt = r"""
%%% Preamble Requirements %%%
% \usepackage{geometry}
% \usepackage{amsfonts}
% \usepackage{amsmath}
% \usepackage{amssymb}
% \usepackage{tikz}
% Optional packages such as sfmath set through python interface
% \usepackage{sfmath}
% \usetikzlibrary{arrows,chains,positioning,scopes,shapes.geometric,shapes.misc,shadows}
%%% End Preamble Requirements %%%
\input{"path/to/diagram_styles"}
\begin{tikzpicture}
\matrix[MatrixSetup]{
%Row 0
\node [DataIO] (left_output_opt) {$x^*, z^*$};&
\node [Optimization] (opt) {$\text{Optimizer}$};&
&
\node [DataInter] (opt-D1) {$x, z$};&
\node [DataInter] (opt-D2) {$z$};&
\node [DataInter] (opt-F) {$x, z$};&
\\
%Row 1
&
&
\node [MDA] (solver) {$\text{Newton}$};&
\node [DataInter] (solver-D1) {$y_2$};&
\node [DataInter] (solver-D2) {$y_1$};&
\node [DataInter] (solver-F) {$y_1, y_2$};&
\node [DataInter] (solver-G) {$y_1, y_2$};\\
%Row 2
\node [DataIO] (left_output_D1) {$y_1^*$};&
&
\node [DataInter] (D1-solver) {$\mathcal{R}(y_1)$};&
\node [Function] (D1) {$D_1$};&
&
&
\\
%Row 3
\node [DataIO] (left_output_D2) {$y_2^*$};&
&
\node [DataInter] (D2-solver) {$\mathcal{R}(y_2)$};&
&
\node [Function] (D2) {$D_2$};&
&
\\
%Row 4
\node [DataIO] (left_output_F) {$f^*$};&
\node [DataInter] (F-opt) {$f$};&
&
&
&
\node [Function] (F) {$F$};&
\\
%Row 5
\node [DataIO] (left_output_G) {$g^*$};&
\node [DataInter] (G-opt) {$g$};&
&
&
&
&
\node [Function] (G) {$G$};\\
%Row 6
&
&
&
&
&
&
\\
};
% XDSM process chains
\begin{pgfonlayer}{data}
\path
% Horizontal edges
(opt) edge [DataLine] (opt-D1)
(opt) edge [DataLine] (opt-D2)
(opt) edge [DataLine] (opt-F)
(solver) edge [DataLine] (solver-D1)
(solver) edge [DataLine] (solver-D2)
(D1) edge [DataLine] (D1-solver)
(solver) edge [DataLine] (solver-F)
(D2) edge [DataLine] (D2-solver)
(solver) edge [DataLine] (solver-G)
(F) edge [DataLine] (F-opt)
(G) edge [DataLine] (G-opt)
(opt) edge [DataLine] (left_output_opt)
(D1) edge [DataLine] (left_output_D1)
(D2) edge [DataLine] (left_output_D2)
(F) edge [DataLine] (left_output_F)
(G) edge [DataLine] (left_output_G)
% Vertical edges
(opt-D1) edge [DataLine] (D1)
(opt-D2) edge [DataLine] (D2)
(opt-F) edge [DataLine] (F)
(solver-D1) edge [DataLine] (D1)
(solver-D2) edge [DataLine] (D2)
(D1-solver) edge [DataLine] (solver)
(solver-F) edge [DataLine] (F)
(D2-solver) edge [DataLine] (solver)
(solver-G) edge [DataLine] (G)
(F-opt) edge [DataLine] (opt)
(G-opt) edge [DataLine] (opt);
\end{pgfonlayer}
\end{tikzpicture}"""
filename = 'xdsm_test_tikz'
x = XDSM(use_sfmath=True)
x.add_system('opt', 'Optimization', r'\text{Optimizer}')
x.add_system('solver', 'MDA', r'\text{Newton}')
x.add_system('D1', 'Function', 'D_1')
x.add_system('D2', 'Function', 'D_2')
x.add_system('F', 'Function', 'F')
x.add_system('G', 'Function', 'G')
x.connect('opt', 'D1', 'x, z')
x.connect('opt', 'D2', 'z')
x.connect('opt', 'F', 'x, z')
x.connect('solver', 'D1', 'y_2')
x.connect('solver', 'D2', 'y_1')
x.connect('D1', 'solver', r'\mathcal{R}(y_1)')
x.connect('solver', 'F', 'y_1, y_2')
x.connect('D2', 'solver', r'\mathcal{R}(y_2)')
x.connect('solver', 'G', 'y_1, y_2')
x.connect('F', 'opt', 'f')
x.connect('G', 'opt', 'g')
x.add_output('opt', 'x^*, z^*', side='left')
x.add_output('D1', 'y_1^*', side='left')
x.add_output('D2', 'y_2^*', side='left')
x.add_output('F', 'f^*', side='left')
x.add_output('G', 'g^*', side='left')
x.write(filename)
# Check if file was created
tikz_file = filename + '.tikz'
self.assertTrue(os.path.isfile(tikz_file))
sample_lines = sample_txt.split('\n')
sample_lines = filter_lines(sample_lines)
with open(tikz_file, "r") as f:
new_lines = filter_lines(f.readlines())
sample_no_match = [] # Sample text
new_no_match = [] # New text
for new_line, sample_line in zip(new_lines, sample_lines):
if new_line.startswith(r'\input{'):
continue
if new_line != sample_line: # else everything is okay
# This can be because of the different ordering of lines or because of an error.
sample_no_match.append(new_line)
new_no_match.append(sample_line)
# Sort both sets of suspicious lines
sample_no_match.sort()
new_no_match.sort()
for sample_line, new_line in zip(sample_no_match, new_no_match):
# Now the lines should match, if only the ordering was different
self.assertEqual(new_line, sample_line)
# To be sure, check the length, otherwise a missing last line could get unnoticed because of using zip
self.assertEqual(len(new_lines), len(sample_lines))
if __name__ == "__main__":
unittest.main()
| [((316, 4, 316, 19), 'unittest.main', 'unittest.main', ({}, {}), '()', False, 'import unittest\n'), ((19, 24, 19, 35), 'os.getcwd', 'os.getcwd', ({}, {}), '()', False, 'import os\n'), ((20, 23, 20, 58), 'tempfile.mkdtemp', 'tempfile.mkdtemp', (), '', False, 'import tempfile\n'), ((22, 8, 22, 30), 'os.chdir', 'os.chdir', ({(22, 17, 22, 29): 'self.tempdir'}, {}), '(self.tempdir)', False, 'import os\n'), ((28, 8, 28, 31), 'os.chdir', 'os.chdir', ({(28, 17, 28, 30): 'self.startdir'}, {}), '(self.startdir)', False, 'import os\n'), ((51, 8, 51, 38), 'os.system', 'os.system', ({(51, 18, 51, 37): '"""python mat_eqn.py"""'}, {}), "('python mat_eqn.py')", False, 'import os\n'), ((54, 8, 54, 30), 'os.chdir', 'os.chdir', ({(54, 17, 54, 29): 'self.tempdir'}, {}), '(self.tempdir)', False, 'import os\n'), ((58, 12, 58, 34), 'pyxdsm.XDSM.XDSM', 'XDSM', (), '', False, 'from pyxdsm.XDSM import XDSM, __file__\n'), ((75, 12, 75, 34), 'pyxdsm.XDSM.XDSM', 'XDSM', (), '', False, 'from pyxdsm.XDSM import XDSM, __file__\n'), ((115, 12, 115, 18), 'pyxdsm.XDSM.XDSM', 'XDSM', ({}, {}), '()', False, 'from pyxdsm.XDSM import XDSM, __file__\n'), ((252, 12, 252, 33), 'pyxdsm.XDSM.XDSM', 'XDSM', (), '', False, 'from pyxdsm.XDSM import XDSM, __file__\n'), ((31, 12, 31, 39), 'shutil.rmtree', 'shutil.rmtree', ({(31, 26, 31, 38): 'self.tempdir'}, {}), '(self.tempdir)', False, 'import shutil\n'), ((52, 24, 52, 61), 'os.path.isfile', 'os.path.isfile', ({(52, 39, 52, 60): '"""mat_eqn_example.pdf"""'}, {}), "('mat_eqn_example.pdf')", False, 'import os\n'), ((106, 24, 106, 58), 'os.path.isfile', 'os.path.isfile', ({(106, 39, 106, 57): "(filename + '.tikz')"}, {}), "(filename + '.tikz')", False, 'import os\n'), ((107, 24, 107, 57), 'os.path.isfile', 'os.path.isfile', ({(107, 39, 107, 56): "(filename + '.tex')"}, {}), "(filename + '.tex')", False, 'import os\n'), ((108, 24, 108, 47), 'os.path.isdir', 'os.path.isdir', ({(108, 38, 108, 46): 'spec_dir'}, {}), '(spec_dir)', False, 'import os\n'), ((284, 24, 284, 49), 'os.path.isfile', 'os.path.isfile', ({(284, 39, 284, 48): 'tikz_file'}, {}), '(tikz_file)', False, 'import os\n'), ((45, 28, 45, 55), 'os.path.isfile', 'os.path.isfile', ({(45, 43, 45, 54): "(f + '.tikz')"}, {}), "(f + '.tikz')", False, 'import os\n'), ((46, 28, 46, 54), 'os.path.isfile', 'os.path.isfile', ({(46, 43, 46, 53): "(f + '.tex')"}, {}), "(f + '.tex')", False, 'import os\n'), ((48, 23, 48, 50), 'numpy.distutils.exec_command.find_executable', 'find_executable', ({(48, 39, 48, 49): '"""pdflatex"""'}, {}), "('pdflatex')", False, 'from numpy.distutils.exec_command import find_executable\n'), ((109, 39, 109, 71), 'os.path.join', 'os.path.join', ({(109, 52, 109, 60): 'spec_dir', (109, 62, 109, 70): '"""F.json"""'}, {}), "(spec_dir, 'F.json')", False, 'import os\n'), ((110, 39, 110, 76), 'os.path.join', 'os.path.join', ({(110, 52, 110, 60): 'spec_dir', (110, 62, 110, 75): '"""G_spec.json"""'}, {}), "(spec_dir, 'G_spec.json')", False, 'import os\n'), ((40, 46, 40, 71), 'os.path.abspath', 'os.path.abspath', ({(40, 62, 40, 70): '__file__'}, {}), '(__file__)', False, 'import os\n'), ((50, 44, 50, 70), 'os.path.isfile', 'os.path.isfile', ({(50, 59, 50, 69): "(f + '.pdf')"}, {}), "(f + '.pdf')", False, 'import os\n')] |
quanttide/wecom-sdk-py | wecom_sdk/base/callback.py | 1c71909c08d885e52e4ec38a9ddac0938a059e5a | # -*- coding: utf-8 -*-
from wecom_sdk.base.crypt import encrypt_msg, decrypt_msg
class WeChatWorkCallbackSDK(object):
"""
企业微信回调SDK基本类，用于实现内部系统和企业微信客户端的双向通信
详细说明：https://work.weixin.qq.com/api/doc/90000/90135/90930
"""
def __init__(self, token, encoding_aes_key):
self.token = token
self.encoding_aes_key = encoding_aes_key
def encrypt(self, data: dict) -> str:
"""
服务端加密数据
:param data:
:param timestamp:
:param nonce:
:return:
"""
return encrypt_msg(data, token=self.token, encoding_aes_key=self.encoding_aes_key)
def decrypt(self, xml, sign, timestamp, nonce) -> dict:
"""
验证并解密来自客户端的数据
:return:
"""
return decrypt_msg(xml_text=xml, encrypt_sign=sign, timestamp=timestamp, nonce=nonce,
token=self.token, encoding_aes_key=self.encoding_aes_key) | [((23, 15, 23, 90), 'wecom_sdk.base.crypt.encrypt_msg', 'encrypt_msg', (), '', False, 'from wecom_sdk.base.crypt import encrypt_msg, decrypt_msg\n'), ((30, 15, 31, 84), 'wecom_sdk.base.crypt.decrypt_msg', 'decrypt_msg', (), '', False, 'from wecom_sdk.base.crypt import encrypt_msg, decrypt_msg\n')] |
numankh/GRE-Vocab-Helper | scripts/get-table-schemas.py | c2858f3200f6d6673b1f316879e5ac482a6b7a83 | import psycopg2
from decouple import config
import pandas as pd
import dbconnect
cursor, connection = dbconnect.connect_to_db()
sql = """
SELECT "table_name","column_name", "data_type", "table_schema"
FROM INFORMATION_SCHEMA.COLUMNS
WHERE "table_schema" = 'public'
ORDER BY table_name
"""
df = pd.read_sql(sql, con=connection)
print(df.to_string()) | [((6, 21, 6, 46), 'dbconnect.connect_to_db', 'dbconnect.connect_to_db', ({}, {}), '()', False, 'import dbconnect\n'), ((13, 5, 13, 37), 'pandas.read_sql', 'pd.read_sql', (), '', True, 'import pandas as pd\n')] |
andriyor/agate | tests/test_table/test_pivot.py | 9b12d4bcc75bf3788e0774e23188f4409c3e7519 | #!/usr/bin/env python
# -*- coding: utf8 -*-
import sys
try:
from cdecimal import Decimal
except ImportError: # pragma: no cover
from decimal import Decimal
from agate import Table
from agate.aggregations import Sum
from agate.computations import Percent
from agate.data_types import Number, Text
from agate.testcase import AgateTestCase
class TestPivot(AgateTestCase):
def setUp(self):
self.rows = (
('joe', 'white', 'male', 20, 'blue'),
('jane', 'white', 'female', 20, 'blue'),
('josh', 'black', 'male', 20, 'blue'),
('jim', 'latino', 'male', 25, 'blue'),
('julia', 'white', 'female', 25, 'green'),
('joan', 'asian', 'female', 25, 'green')
)
self.number_type = Number()
self.text_type = Text()
self.column_names = ['name', 'race', 'gender', 'age', 'color']
self.column_types = [self.text_type, self.text_type, self.text_type, self.number_type, self.text_type]
def test_pivot(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('race', 'gender')
pivot_rows = (
('white', 1, 2),
('black', 1, 0),
('latino', 1, 0),
('asian', 0, 1)
)
self.assertColumnNames(pivot_table, ['race', 'male', 'female'])
self.assertRowNames(pivot_table, ['white', 'black', 'latino', 'asian'])
self.assertColumnTypes(pivot_table, [Text, Number, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_by_lambda(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot(lambda r: r['gender'])
pivot_rows = (
('male', 3),
('female', 3)
)
self.assertColumnNames(pivot_table, ['group', 'Count'])
self.assertRowNames(pivot_table, ['male', 'female'])
self.assertColumnTypes(pivot_table, [Text, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_by_lambda_group_name(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot(lambda r: r['gender'], key_name='gender')
pivot_rows = (
('male', 3),
('female', 3)
)
self.assertColumnNames(pivot_table, ['gender', 'Count'])
self.assertRowNames(pivot_table, ['male', 'female'])
self.assertColumnTypes(pivot_table, [Text, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_by_lambda_group_name_sequence_invalid(self):
table = Table(self.rows, self.column_names, self.column_types)
with self.assertRaises(ValueError):
table.pivot(['race', 'gender'], key_name='foo')
def test_pivot_no_key(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot(pivot='gender')
pivot_rows = (
(3, 3),
)
self.assertColumnNames(pivot_table, ['male', 'female'])
self.assertColumnTypes(pivot_table, [Number, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_no_pivot(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('race')
pivot_rows = (
('white', 3),
('black', 1),
('latino', 1),
('asian', 1)
)
self.assertColumnNames(pivot_table, ['race', 'Count'])
self.assertColumnTypes(pivot_table, [Text, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_sum(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('race', 'gender', Sum('age'))
pivot_rows = (
('white', 20, 45),
('black', 20, 0),
('latino', 25, 0),
('asian', 0, 25)
)
self.assertColumnNames(pivot_table, ['race', 'male', 'female'])
self.assertColumnTypes(pivot_table, [Text, Number, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_multiple_keys(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot(['race', 'gender'], 'age')
pivot_rows = (
('white', 'male', 1, 0),
('white', 'female', 1, 1),
('black', 'male', 1, 0),
('latino', 'male', 0, 1),
('asian', 'female', 0, 1),
)
self.assertRows(pivot_table, pivot_rows)
self.assertColumnNames(pivot_table, ['race', 'gender', '20', '25'])
self.assertRowNames(pivot_table, [
('white', 'male'),
('white', 'female'),
('black', 'male'),
('latino', 'male'),
('asian', 'female'),
])
self.assertColumnTypes(pivot_table, [Text, Text, Number, Number])
def test_pivot_multiple_keys_no_pivot(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot(['race', 'gender'])
pivot_rows = (
('white', 'male', 1),
('white', 'female', 2),
('black', 'male', 1),
('latino', 'male', 1),
('asian', 'female', 1),
)
self.assertRows(pivot_table, pivot_rows)
self.assertColumnNames(pivot_table, ['race', 'gender', 'Count'])
self.assertColumnTypes(pivot_table, [Text, Text, Number])
def test_pivot_default_value(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('race', 'gender', default_value=None)
pivot_rows = (
('white', 1, 2),
('black', 1, None),
('latino', 1, None),
('asian', None, 1)
)
self.assertColumnNames(pivot_table, ['race', 'male', 'female'])
self.assertColumnTypes(pivot_table, [Text, Number, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_compute(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('gender', computation=Percent('Count'))
pivot_table.print_table(output=sys.stdout)
pivot_rows = (
('male', Decimal(50)),
('female', Decimal(50)),
)
self.assertColumnNames(pivot_table, ['gender', 'Percent'])
self.assertColumnTypes(pivot_table, [Text, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_compute_pivots(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('gender', 'color', computation=Percent('Count'))
pivot_table.print_table(output=sys.stdout)
pivot_rows = (
('male', Decimal(50), 0),
('female', Decimal(1) / Decimal(6) * Decimal(100), Decimal(1) / Decimal(3) * Decimal(100)),
)
self.assertColumnNames(pivot_table, ['gender', 'blue', 'green'])
self.assertColumnTypes(pivot_table, [Text, Number, Number])
self.assertRows(pivot_table, pivot_rows)
def test_pivot_compute_kwargs(self):
table = Table(self.rows, self.column_names, self.column_types)
pivot_table = table.pivot('gender', 'color', computation=Percent('Count', total=8))
pivot_table.print_table(output=sys.stdout)
pivot_rows = (
('male', Decimal(3) / Decimal(8) * Decimal(100), 0),
('female', Decimal(1) / Decimal(8) * Decimal(100), Decimal(2) / Decimal(8) * Decimal(100)),
)
self.assertColumnNames(pivot_table, ['gender', 'blue', 'green'])
self.assertColumnTypes(pivot_table, [Text, Number, Number])
self.assertRows(pivot_table, pivot_rows)
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chengzhag/DeepPanoContext | external/pyTorchChamferDistance/chamfer_distance/__init__.py | 14f847e51ec2bd08e0fc178dd1640541752addb7 | import os
os.makedirs(os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'build')), exist_ok=True)
from .chamfer_distance import ChamferDistance
| [((2, 41, 2, 66), 'os.path.dirname', 'os.path.dirname', ({(2, 57, 2, 65): '__file__'}, {}), '(__file__)', False, 'import os\n')] |
georg-wolflein/impartial | test_impartial.py | a53819cefcb74a57e3c1148a6b8fa88aed9264d4 | from functools import partial
from impartial import impartial
def f(x: int, y: int, z: int = 0) -> int:
return x + 2*y + z
def test_simple_call_args():
assert impartial(f, 1)(2) == f(1, 2)
def test_simple_call_kwargs():
assert impartial(f, y=2)(x=1) == f(1, 2)
def test_simple_call_empty():
assert impartial(f, 1, y=2)() == f(1, 2)
def test_decorator():
@impartial
def f(x, y):
return x + 2*y
assert f.with_y(2)(1) == 5
def test_func():
assert impartial(f, 1).func is f
def test_with_kwargs():
assert impartial(f, 1).with_z(3)(2) == f(1, 2, 3)
def test_multiple_with_kwargs():
assert impartial(f, 1).with_z(3).with_y(2)() == f(1, 2, 3)
def test_with_kwargs_override():
assert impartial(f, 1, 2).with_z(3).with_z(4)() == f(1, 2, 4)
def test_nested_impartial():
imp = impartial(f, x=1, y=2)
imp = impartial(imp, x=2)
imp = impartial(imp, x=3)
assert imp() == f(3, 2)
assert not isinstance(imp.func, impartial)
assert imp.func is f
def test_nested_partial():
imp = partial(f, x=1, y=2)
imp = partial(imp, x=2)
imp = impartial(imp, x=3)
assert imp() == f(3, 2)
assert not isinstance(imp.func, partial)
assert imp.func is f
def test_configure():
assert impartial(f, 1, z=2).configure(2, z=3)() == f(1, 2, 3)
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smilechaser/screeps-script-caddy | manager.py | 11b6e809675dfd0a5a4ff917a492adc4a5a08bca | '''
Python script for uploading/downloading scripts for use with the game Screeps.
http://support.screeps.com/hc/en-us/articles/203022612-Commiting-scripts-using-direct-API-access
Usage:
#
# general help/usage
#
python3 manager.py --help
#
# retrieve all scripts from the game and store them
# in the folder "some_folder"
#
python3 manager.py from_game some_folder
#
# send all *.js files to the game
#
python3 manager.py to_game some_folder
WARNING: Use at your own risk! Make backups of all your game content!
'''
import sys
import os
import argparse
import json
import requests
from requests.auth import HTTPBasicAuth
SCREEPS_ENDPOINT = 'https://screeps.com/api/user/code'
USER_ENV = 'SCREEPS_USER'
PASSWORD_ENV = 'SCREEPS_PASSWORD'
TO_SCREEPS = 'to_game'
FROM_SCREEPS = 'from_game'
def get_user_from_env():
user = os.environ.get('SCREEPS_USER')
if not user:
print('You must provide a username, i.e. export '
'{}=<your email address>'.
format(USER_ENV))
sys.exit()
return user
def get_password_from_env():
password = os.environ.get('SCREEPS_PASSWORD')
if not password:
print('You must provide a password, i.e. export {}=<your password>'.
format(PASSWORD_ENV))
sys.exit()
return password
def get_data(user, password):
print('Retrieving data...')
response = requests.get(SCREEPS_ENDPOINT,
auth=HTTPBasicAuth(user, password))
response.raise_for_status()
data = response.json()
if data['ok'] != 1:
raise Exception()
return data
def send_data(user, password, modules):
auth = HTTPBasicAuth(user, password)
headers = {'Content-Type': 'application/json; charset=utf-8'}
data = {'modules': modules}
resp = requests.post(SCREEPS_ENDPOINT,
data=json.dumps(data),
headers=headers,
auth=auth)
resp.raise_for_status()
def check_for_collisions(target_folder, modules):
for module in modules:
target = os.path.join(target_folder, '{}.js'.format(module))
if os.path.exists(target):
print('File {} exists.'.format(target))
print('Specify --force to overwrite. Aborting...')
sys.exit()
def main():
parser = argparse.ArgumentParser(description='')
parser.add_argument('operation',
choices=(TO_SCREEPS, FROM_SCREEPS),
help='')
parser.add_argument('destination', help='')
parser.add_argument('--user', help='')
parser.add_argument('--password', help='')
parser.add_argument('--force', action='store_const', const=True,
help='force overwrite of files in an existing folder')
parser.add_argument('--merge', action='store_const', const=True,
help='merge scripts into a single main.js module')
args = parser.parse_args()
user = args.user if args.user else get_user_from_env()
password = args.password if args.password else get_password_from_env()
target_folder = os.path.abspath(args.destination)
if args.operation == FROM_SCREEPS:
data = get_data(user, password)
# does the folder exist?
if not os.path.isdir(target_folder):
# no - create it
print('Creating new folder "{}"...'.format(target_folder))
os.makedirs(target_folder)
else:
# yes - check for collisions (unless --force was specified)
if not args.force:
print('Checking for collisions...')
check_for_collisions(target_folder, data['modules'])
print('Ok, no collisions.')
# for each module, create a corresponding filename and put it in
# the target folder
for module in data['modules']:
target = os.path.join(target_folder, '{}.js'.format(module))
with open(target, 'w') as fout:
fout.write(data['modules'][module])
else:
modules = {}
for root, folders, files in os.walk(target_folder):
folders[:] = []
for target_file in files:
name, ext = os.path.splitext(target_file)
if ext != '.js':
continue
with open(os.path.join(root, target_file), 'r') as fin:
modules[name] = fin.read()
if args.merge:
merge_modules(modules)
# upload modules
send_data(user, password, modules)
def generate_header(filename):
return '''
// {border}
// {name}
// {border}
'''.format(border='-' * 25, name=filename)
def merge_modules(modules):
keys = [x for x in modules.keys()]
keys.sort()
merged = ''
for key in keys:
merged = merged + generate_header(key) + modules[key]
del(modules[key])
modules['main.js'] = merged
if __name__ == '__main__':
main()
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Nemfeto/python_training | contact.py | 4d04f07700da4b0d5b50736ba197ad85fd2ee549 | class Contact:
def __init__(self, first_name, last_name, nickname, address, mobile, email):
self.first_name = first_name
self.last_name = last_name
self.nickname = nickname
self.address = address
self.mobile = mobile
self.email = email
| [] |
Integreat/cms-v2 | integreat_cms/cms/views/dashboard/admin_dashboard_view.py | c79a54fd5abb792696420aa6427a5e5a356fa79c | import logging
from django.views.generic import TemplateView
from ...models import Feedback
from ..chat.chat_context_mixin import ChatContextMixin
logger = logging.getLogger(__name__)
class AdminDashboardView(TemplateView, ChatContextMixin):
"""
View for the admin dashboard
"""
#: The template to render (see :class:`~django.views.generic.base.TemplateResponseMixin`)
template_name = "dashboard/admin_dashboard.html"
#: The context dict passed to the template (see :class:`~django.views.generic.base.ContextMixin`)
extra_context = {"current_menu_item": "admin_dashboard"}
def get_context_data(self, **kwargs):
r"""
Returns a dictionary representing the template context
(see :meth:`~django.views.generic.base.ContextMixin.get_context_data`).
:param \**kwargs: The given keyword arguments
:type \**kwargs: dict
:return: The template context
:rtype: dict
"""
context = super().get_context_data(**kwargs)
context["admin_feedback"] = Feedback.objects.filter(
is_technical=True, read_by=None
)[:5]
return context
| [((8, 9, 8, 36), 'logging.getLogger', 'logging.getLogger', ({(8, 27, 8, 35): '__name__'}, {}), '(__name__)', False, 'import logging\n')] |
bhumikapahariapuresoftware/tangled-up-in-unicode | src/tangled_up_in_unicode/tangled_up_in_unicode_14_0_0.py | ee052e6f0fd4a0083178a163ec72dc37e2ad5d59 | from typing import Optional
import bisect
from tangled_up_in_unicode.u14_0_0_data.prop_list_to_property import prop_list_to_property
from tangled_up_in_unicode.u14_0_0_data.blocks_to_block_start import blocks_to_block_start
from tangled_up_in_unicode.u14_0_0_data.blocks_to_block_end import blocks_to_block_end
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_age_short_to_long import property_value_alias_age_short_to_long
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_bc_short_to_long import property_value_alias_bc_short_to_long
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_blk_long_to_short import property_value_alias_blk_long_to_short
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_ccc_short_to_long import property_value_alias_ccc_short_to_long
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_ea_short_to_long import property_value_alias_ea_short_to_long
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_gc_short_to_long import property_value_alias_gc_short_to_long
from tangled_up_in_unicode.u14_0_0_data.property_value_alias_sc_long_to_short import property_value_alias_sc_long_to_short
from tangled_up_in_unicode.u14_0_0_data.scripts_to_script_start import scripts_to_script_start
from tangled_up_in_unicode.u14_0_0_data.scripts_to_script_end import scripts_to_script_end
from tangled_up_in_unicode.u14_0_0_data.east_asian_width_to_east_asian_width_start import east_asian_width_to_east_asian_width_start
from tangled_up_in_unicode.u14_0_0_data.east_asian_width_to_east_asian_width_end import east_asian_width_to_east_asian_width_end
from tangled_up_in_unicode.u14_0_0_data.derived_age_to_age_start import derived_age_to_age_start
from tangled_up_in_unicode.u14_0_0_data.derived_age_to_age_end import derived_age_to_age_end
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_name_start import unicode_data_to_name_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_category_start import unicode_data_to_category_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_category_end import unicode_data_to_category_end
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_bidirectional_start import unicode_data_to_bidirectional_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_bidirectional_end import unicode_data_to_bidirectional_end
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_decimal_start import unicode_data_to_decimal_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_digit_start import unicode_data_to_digit_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_numeric_start import unicode_data_to_numeric_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_combining_start import unicode_data_to_combining_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_mirrored_start import unicode_data_to_mirrored_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_mirrored_end import unicode_data_to_mirrored_end
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_decomposition_start import unicode_data_to_decomposition_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_uppercase_start import unicode_data_to_uppercase_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_lowercase_start import unicode_data_to_lowercase_start
from tangled_up_in_unicode.u14_0_0_data.unicode_data_to_titlecase_start import unicode_data_to_titlecase_start
unidata_version = "14.0.0"
def name(chr: str, default=None) -> str:
"""Returns the name assigned to the character chr as a string.
If no name is defined, default is returned, or, if not given, ValueError is raised."""
idx = ord(chr)
try:
return unicode_data_to_name_start[idx]
except KeyError:
if default is None:
raise ValueError("no such name")
else:
return default
def category(chr: str) -> str:
"""Returns the general category assigned to the character chr as string."""
idx = ord(chr)
start_keys = sorted(unicode_data_to_category_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = unicode_data_to_category_start[key_start]
end_keys = sorted(unicode_data_to_category_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = unicode_data_to_category_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = unicode_data_to_category_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return "Zzzz"
except IndexError:
return "Zzzz"
def bidirectional(chr: str) -> str:
"""Returns the bidirectional class assigned to the character chr as string.
If no such value is defined, an empty string is returned."""
idx = ord(chr)
start_keys = sorted(unicode_data_to_bidirectional_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = unicode_data_to_bidirectional_start[key_start]
end_keys = sorted(unicode_data_to_bidirectional_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = unicode_data_to_bidirectional_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = unicode_data_to_bidirectional_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return ""
except IndexError:
return ""
def decimal(chr: str, default=None) -> int:
"""Returns the decimal value assigned to the character chr as integer.
If no such value is defined, default is returned, or, if not given, ValueError is raised."""
idx = ord(chr)
try:
return unicode_data_to_decimal_start[idx]
except KeyError:
if default is None:
raise ValueError("not a decimal")
else:
return default
def digit(chr: str, default=None) -> int:
"""Returns the digit value assigned to the character chr as integer.
If no such value is defined, default is returned, or, if not given, ValueError is raised."""
idx = ord(chr)
try:
return unicode_data_to_digit_start[idx]
except KeyError:
if default is None:
raise ValueError("not a digit")
else:
return default
def numeric(chr: str, default=None) -> float:
"""Returns the numeric value assigned to the character chr as float.
If no such value is defined, default is returned, or, if not given, ValueError is raised."""
idx = ord(chr)
try:
return unicode_data_to_numeric_start[idx]
except KeyError:
if default is None:
raise ValueError("not a numeric character")
else:
return default
def combining(chr: str) -> int:
"""Returns the canonical combining class assigned to the character chr as integer.
Returns 0 if no combining class is defined."""
idx = ord(chr)
try:
return unicode_data_to_combining_start[idx]
except KeyError:
return 0
def mirrored(chr: str) -> int:
"""Returns the mirrored property assigned to the character chr as integer.
Returns 1 if the character has been identified as a "mirrored" character in bidirectional text, 0 otherwise."""
idx = ord(chr)
start_keys = sorted(unicode_data_to_mirrored_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = unicode_data_to_mirrored_start[key_start]
end_keys = sorted(unicode_data_to_mirrored_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = unicode_data_to_mirrored_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = unicode_data_to_mirrored_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return 0
except IndexError:
return 0
def decomposition(chr: str) -> str:
"""Returns the character decomposition mapping assigned to the character chr as string.
An empty string is returned in case no such mapping is defined."""
idx = ord(chr)
try:
return unicode_data_to_decomposition_start[idx]
except KeyError:
return ""
def uppercase(chr: str) -> str:
""""""
idx = ord(chr)
try:
return unicode_data_to_uppercase_start[idx]
except KeyError:
return ""
def lowercase(chr: str) -> str:
""""""
idx = ord(chr)
try:
return unicode_data_to_lowercase_start[idx]
except KeyError:
return ""
def titlecase(chr: str) -> str:
""""""
idx = ord(chr)
try:
return unicode_data_to_titlecase_start[idx]
except KeyError:
return ""
def east_asian_width(chr: str, default=None) -> str:
"""Returns the east asian width assigned to the character chr as string."""
idx = ord(chr)
start_keys = sorted(east_asian_width_to_east_asian_width_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = east_asian_width_to_east_asian_width_start[key_start]
end_keys = sorted(east_asian_width_to_east_asian_width_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
key_end = end_keys[insertion_point]
result_end = east_asian_width_to_east_asian_width_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = east_asian_width_to_east_asian_width_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
if default is None:
raise ValueError("no east asian width")
else:
return default
def age(chr: str) -> str:
""""""
idx = ord(chr)
start_keys = sorted(derived_age_to_age_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = derived_age_to_age_start[key_start]
end_keys = sorted(derived_age_to_age_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = derived_age_to_age_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = derived_age_to_age_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return "1.0"
except IndexError:
return "1.0"
def block(chr: str) -> str:
""""""
idx = ord(chr)
start_keys = sorted(blocks_to_block_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = blocks_to_block_start[key_start]
end_keys = sorted(blocks_to_block_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = blocks_to_block_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = blocks_to_block_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return "Unknown"
except IndexError:
return "Unknown"
def script(chr: str) -> str:
""""""
idx = ord(chr)
start_keys = sorted(scripts_to_script_start.keys())
insertion_point = bisect.bisect_left(start_keys, idx)
if insertion_point == len(start_keys) or start_keys[insertion_point] != idx:
insertion_point -= 1
key_start = start_keys[insertion_point]
result_start = scripts_to_script_start[key_start]
end_keys = sorted(scripts_to_script_end.keys())
insertion_point = bisect.bisect_left(end_keys, idx)
try:
key_end = end_keys[insertion_point]
result_end = scripts_to_script_end[key_end]
if result_end != key_start:
result_end = result_start
key_end = key_start
else:
result_end = scripts_to_script_start[result_end]
if key_start <= idx <= key_end and result_start == result_end:
return result_start
else:
return "Unknown"
except IndexError:
return "Unknown"
def prop_list(chr: str) -> list:
""""""
idx = ord(chr)
try:
return prop_list_to_property[idx]
except KeyError:
return set()
def age_long(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_age_short_to_long[value]
except KeyError:
return None
def category_long(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_gc_short_to_long[value]
except KeyError:
return None
def east_asian_width_long(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_ea_short_to_long[value]
except KeyError:
return None
def bidirectional_long(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_bc_short_to_long[value]
except KeyError:
return None
def combining_long(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_ccc_short_to_long[value]
except KeyError:
return None
def block_abbr(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_blk_long_to_short[value]
except KeyError:
return None
def script_abbr(value: str) -> Optional[str]:
""""""
try:
return property_value_alias_sc_long_to_short[value]
except KeyError:
return None
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namib-project/weatherstation-image | to_display.py | ae6a11943bfd21135bf0ce5d113865b69c58bbe2 | from PIL import Image
from PIL import ImageDraw
from PIL import ImageFont
import sys
import ST7735
# Create ST7735 LCD display class object and set pin numbers and display hardware information.
disp = ST7735.ST7735(
dc=24,
cs=ST7735.BG_SPI_CS_BACK,
rst=25,
port=0,
width=122,
height=160,
rotation=270
)
# Initialize display.
disp.begin()
WIDTH = disp.width
HEIGHT = disp.height
img = Image.new('RGB', (WIDTH, HEIGHT), color=(0, 0, 0))
draw = ImageDraw.Draw(img)
font = ImageFont.truetype("/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf", 12)
# Initialize a secondary text with the empty string
text2 = ""
# Print test-output on the display if n oargument is given
if len(sys.argv) == 1:
text = "Temperature:\nHumidity:\nUV:\nRain:\nLight:"
text2 = "20°C\n50 %\n42\nyes\nOn"
# Print the argument if only one is given
elif len(sys.argv) == 2:
text = sys.argv[1]
# If 2 arguments are given use the second as the secondary text
elif len(sys.argv) == 3:
text = sys.argv[1]
text2 = sys.argv[2]
# For any other number of arguments draw them in one line each
else:
text = ''.join(i + "\n" for i in sys.argv[1:])
# Print both texts, with the secondary one starting with an 100 px offset
draw.text((10, 10), text, font=font, fill=(255, 255, 255))
draw.text((110, 10), text2, font=font, fill=(255, 255, 255))
disp.display(img)
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saransh808/Projects | Smart User Targeted Advertising/MinorPro/FINALPROJECT/Resources/testInsert.py | 7449ed6b53900ebb16a9084cff389cc50f3c9f6c | import sqlite3
conn=sqlite3.connect('Survey.db')
fo=open('insertcommand.txt')
str=fo.readline()
while str:
str="INSERT INTO data VALUES"+str
conn.execute(str)
#print(str)
str=fo.readline()
conn.commit()
conn.close()
fo.close()
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HyperionGray/python-chrome-devtools-protocol | cdp/headless_experimental.py | 5463a5f3d20100255c932961b944e4b37dbb7e61 | # DO NOT EDIT THIS FILE!
#
# This file is generated from the CDP specification. If you need to make
# changes, edit the generator and regenerate all of the modules.
#
# CDP domain: HeadlessExperimental (experimental)
from __future__ import annotations
from cdp.util import event_class, T_JSON_DICT
from dataclasses import dataclass
import enum
import typing
@dataclass
class ScreenshotParams:
'''
Encoding options for a screenshot.
'''
#: Image compression format (defaults to png).
format_: typing.Optional[str] = None
#: Compression quality from range [0..100] (jpeg only).
quality: typing.Optional[int] = None
def to_json(self) -> T_JSON_DICT:
json: T_JSON_DICT = dict()
if self.format_ is not None:
json['format'] = self.format_
if self.quality is not None:
json['quality'] = self.quality
return json
@classmethod
def from_json(cls, json: T_JSON_DICT) -> ScreenshotParams:
return cls(
format_=str(json['format']) if 'format' in json else None,
quality=int(json['quality']) if 'quality' in json else None,
)
def begin_frame(
frame_time_ticks: typing.Optional[float] = None,
interval: typing.Optional[float] = None,
no_display_updates: typing.Optional[bool] = None,
screenshot: typing.Optional[ScreenshotParams] = None
) -> typing.Generator[T_JSON_DICT,T_JSON_DICT,typing.Tuple[bool, typing.Optional[str]]]:
'''
Sends a BeginFrame to the target and returns when the frame was completed. Optionally captures a
screenshot from the resulting frame. Requires that the target was created with enabled
BeginFrameControl. Designed for use with --run-all-compositor-stages-before-draw, see also
https://goo.gl/3zHXhB for more background.
:param frame_time_ticks: *(Optional)* Timestamp of this BeginFrame in Renderer TimeTicks (milliseconds of uptime). If not set, the current time will be used.
:param interval: *(Optional)* The interval between BeginFrames that is reported to the compositor, in milliseconds. Defaults to a 60 frames/second interval, i.e. about 16.666 milliseconds.
:param no_display_updates: *(Optional)* Whether updates should not be committed and drawn onto the display. False by default. If true, only side effects of the BeginFrame will be run, such as layout and animations, but any visual updates may not be visible on the display or in screenshots.
:param screenshot: *(Optional)* If set, a screenshot of the frame will be captured and returned in the response. Otherwise, no screenshot will be captured. Note that capturing a screenshot can fail, for example, during renderer initialization. In such a case, no screenshot data will be returned.
:returns: A tuple with the following items:
0. **hasDamage** - Whether the BeginFrame resulted in damage and, thus, a new frame was committed to the display. Reported for diagnostic uses, may be removed in the future.
1. **screenshotData** - *(Optional)* Base64-encoded image data of the screenshot, if one was requested and successfully taken.
'''
params: T_JSON_DICT = dict()
if frame_time_ticks is not None:
params['frameTimeTicks'] = frame_time_ticks
if interval is not None:
params['interval'] = interval
if no_display_updates is not None:
params['noDisplayUpdates'] = no_display_updates
if screenshot is not None:
params['screenshot'] = screenshot.to_json()
cmd_dict: T_JSON_DICT = {
'method': 'HeadlessExperimental.beginFrame',
'params': params,
}
json = yield cmd_dict
return (
bool(json['hasDamage']),
str(json['screenshotData']) if 'screenshotData' in json else None
)
def disable() -> typing.Generator[T_JSON_DICT,T_JSON_DICT,None]:
'''
Disables headless events for the target.
'''
cmd_dict: T_JSON_DICT = {
'method': 'HeadlessExperimental.disable',
}
json = yield cmd_dict
def enable() -> typing.Generator[T_JSON_DICT,T_JSON_DICT,None]:
'''
Enables headless events for the target.
'''
cmd_dict: T_JSON_DICT = {
'method': 'HeadlessExperimental.enable',
}
json = yield cmd_dict
@event_class('HeadlessExperimental.needsBeginFramesChanged')
@dataclass
class NeedsBeginFramesChanged:
'''
Issued when the target starts or stops needing BeginFrames.
'''
#: True if BeginFrames are needed, false otherwise.
needs_begin_frames: bool
@classmethod
def from_json(cls, json: T_JSON_DICT) -> NeedsBeginFramesChanged:
return cls(
needs_begin_frames=bool(json['needsBeginFrames'])
)
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resurtm/wvflib | tests/test_geometry.py | 106f426cc2c63c8d21f3e0ec1b90b06450dfc547 | import unittest
from wvflib.geometry import Face
class TestGeometry(unittest.TestCase):
def test_constructor(self):
f = Face()
self.assertTrue(len(f.vertices) == 0)
if __name__ == '__main__':
unittest.main()
| [((13, 4, 13, 19), 'unittest.main', 'unittest.main', ({}, {}), '()', False, 'import unittest\n'), ((8, 12, 8, 18), 'wvflib.geometry.Face', 'Face', ({}, {}), '()', False, 'from wvflib.geometry import Face\n')] |
d066y/detectem | tests/test_core.py | 648ddff159e17777e41b1dd266a759e9f0774ea8 | import pytest
from detectem.core import Detector, Result, ResultCollection
from detectem.plugin import Plugin, PluginCollection
from detectem.settings import INDICATOR_TYPE, HINT_TYPE, MAIN_ENTRY, GENERIC_TYPE
from detectem.plugins.helpers import meta_generator
class TestDetector():
HAR_ENTRY_1 = {
'request': {
'url': 'http://domain.tld/libA-1.4.2.js'
},
'response': {
'url': 'http://domain.tld/libA-1.4.2.js'
},
}
HAR_NO_URL_REDIRECT = [
{
'request': {'url': 'http://domain.tld/'},
'response': {},
},
{
'request': {'url': 'http://domain.tld/js/script.js'},
'response': {},
}
]
HAR_URL_REDIRECT_PATH = [
{
'request': {'url': 'http://domain.tld/'},
'response': {'headers': [
{'name': 'Location', 'value': '/new/default.html'}
]},
},
{
'request': {'url': 'http://domain.tld/new/default.html'},
'response': {},
}
]
HAR_URL_REDIRECT_ABS = [
{
'request': {'url': 'http://domain.tld/'},
'response': {'headers': [
{'name': 'Location', 'value': 'http://other-domain.tld/'}
]},
},
{
'request': {'url': 'http://other-domain.tld/'},
'response': {},
}
]
URL = 'http://domain.tld/'
FOO_PLUGIN = {
'name': 'foo',
'homepage': 'foo',
'matchers': {
'url': 'foo.*-(?P<version>[0-9\.]+)\.js',
'header': ('FooHeader', 'Foo.* v(?P<version>[0-9\.]+)'),
'body': 'Foo.* v(?P<version>[0-9\.]+)',
'xpath': (meta_generator('foo-min'), '(?P<version>[0-9\.]+)'),
},
'indicators': {
'url': 'foo.*\.js',
'header': ('FooHeader', 'Foo'),
'body': 'Foo',
'xpath': "//meta[@name='generator']",
},
'modular_matchers': {
'url': 'foo-(?P<name>\w+)-.*\.js',
'header': ('FooHeader', 'Foo-(?P<name>\w+)'),
'body': 'Foo-(?P<name>\w+)',
'xpath': (meta_generator('foo-min'), 'foo-(?P<name>\w+)'),
},
}
FOO_RESULTS = [
[{'name': 'foo', 'version': '1.1'}],
[{'name': 'foo'}],
[{'name': 'foo-min', 'version': '1.1'}],
]
MATCHER_SOURCES = [
['matchers'],
['indicators'],
['matchers', 'modular_matchers'],
]
def test_detector_starts_with_empty_results(self):
d = Detector({'har': None, 'softwares': None}, [], None)
assert not d._results.get_results()
@pytest.mark.parametrize("har,index", [
(HAR_NO_URL_REDIRECT, 0),
(HAR_URL_REDIRECT_PATH, 1),
(HAR_URL_REDIRECT_ABS, 1),
])
def test_mark_main_entry(self, har, index):
d = self._create_detector(har, [])
assert d.har[index]['detectem']['type'] == MAIN_ENTRY
def test_convert_inline_script_to_har_entry(self):
script = 'Inline script'
d = Detector({'har': [], 'softwares': [], 'scripts': [script]}, None, self.URL)
e = d.har[0]
assert e['request']['url'] == self.URL
assert e['response']['content']['text'] == script
@pytest.mark.parametrize("scripts,n_entries", [
([], 0),
(['script1', 'script2'], 2),
])
def test_add_inline_scripts_to_har(self, scripts, n_entries):
d = Detector({'har': [], 'softwares': [], 'scripts': scripts}, None, self.URL)
assert len(d.har) == n_entries
def _create_plugin(self, template, sources, matchers):
class TestPlugin(Plugin):
name = template['name']
homepage = template['homepage']
p = TestPlugin()
for s in sources:
g = [{m: template[s][m]} for m in matchers]
setattr(p, s, g)
return p
def _create_detector(self, har, plugins):
pc = PluginCollection()
for p in plugins:
pc.add(p)
return Detector({'har': har, 'softwares': []}, pc, self.URL)
@pytest.mark.parametrize('sources,result', zip(MATCHER_SOURCES, FOO_RESULTS))
def test_match_from_headers(self, sources, result):
har = [
{
'request': {'url': self.URL},
'response': {
'url': self.URL,
'headers': [
{'name': 'FooHeader', 'value': 'Foo-min v1.1'}
]
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['header'])
d = self._create_detector(har, [p])
assert d.get_results() == result
@pytest.mark.parametrize('sources', MATCHER_SOURCES)
def test_match_from_headers_ignores_resource_entries(self, sources):
har = [
{
'request': {'url': self.URL},
'response': {
'url': self.URL,
'headers': [],
},
},
{
'request': {'url': 'http://foo.org/lib/foo.js'},
'response': {
'url': 'http://foo.org/lib/foo.js',
'headers': [
{'name': 'FooHeader', 'value': 'Foo-min v1.1'}
]
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['header'])
d = self._create_detector(har, [p])
assert not d.get_results()
@pytest.mark.parametrize('sources,result', zip(MATCHER_SOURCES, FOO_RESULTS))
def test_match_from_body(self, sources, result):
har = [
{
'request': {'url': self.URL},
'response': {
'url': self.URL,
'content': {'text': 'Main content'},
},
},
{
'request': {'url': 'http://foo.org/lib/foo.js'},
'response': {
'url': 'http://foo.org/lib/foo.js',
'content': {'text': 'Plugin Foo-min v1.1'},
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['body'])
d = self._create_detector(har, [p])
assert d.get_results() == result
@pytest.mark.parametrize('sources', MATCHER_SOURCES)
def test_match_from_body_excludes_main_entry(self, sources):
har = [
{
'request': {'url': self.URL},
'response': {
'url': self.URL,
'content': {'text': 'About Foo-min v1.1'},
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['body'])
d = self._create_detector(har, [p])
assert not d.get_results()
@pytest.mark.parametrize('sources,result', zip(MATCHER_SOURCES, FOO_RESULTS))
def test_match_from_url(self, sources, result):
har = [
{
'request': {'url': self.URL},
'response': {'url': self.URL},
},
{
'request': {'url': 'http://foo.org/lib/foo-min-1.1.js'},
'response': {
'url': 'http://foo.org/lib/foo-min-1.1.js',
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['url'])
d = self._create_detector(har, [p])
assert d.get_results() == result
@pytest.mark.parametrize('sources,result', zip(MATCHER_SOURCES, FOO_RESULTS))
def test_match_from_xpath(self, sources, result):
har = [
{
'request': {'url': self.URL},
'response': {
'url': self.URL,
'content': {
'text': '<meta name="generator" content="foo-min 1.1">'
},
},
},
]
p = self._create_plugin(self.FOO_PLUGIN, sources, ['xpath'])
d = self._create_detector(har, [p])
assert d.get_results() == result
def test_get_hints_with_valid_hint(self):
class TestPlugin(Plugin):
name = 'test'
homepage = 'test'
class BlaPlugin(Plugin):
name = 'bla'
hints = ['test']
detector = self._create_detector(None, [TestPlugin()])
hints = detector.get_hints(BlaPlugin())
assert hints
def test_get_hints_with_invalid_hint(self):
class BlaPlugin(Plugin):
name = 'bla'
hints = ['test']
detector = self._create_detector(None, [])
hints = detector.get_hints(BlaPlugin())
assert not hints
class TestResultCollection():
@staticmethod
def _assert_results(detected, results):
c = ResultCollection()
for d in detected:
c.add_result(d)
assert set(c.get_results()) == set(results)
@pytest.mark.parametrize('detected,results', [
(
[Result('pluginA', '1.1'), Result('pluginB', '3.8.7'), Result('pluginC', '4.0')],
[Result('pluginA', '1.1'), Result('pluginB', '3.8.7'), Result('pluginC', '4.0')]
),
(
[Result('pluginA', '1.3'), Result('pluginA', '1.2'), Result('pluginA', '1.1')],
[Result('pluginA', '1.1'), Result('pluginA', '1.2'), Result('pluginA', '1.3')],
),
(
[
Result('pluginA', '1.1'),
Result('pluginC', type=HINT_TYPE),
Result('pluginB', type=INDICATOR_TYPE),
Result('pluginD', type=GENERIC_TYPE),
],
[
Result('pluginA', '1.1'),
Result('pluginB', type=INDICATOR_TYPE),
Result('pluginC', type=HINT_TYPE),
Result('pluginD', type=GENERIC_TYPE),
]
),
])
def test_get_all_detected_plugins(self, detected, results):
self._assert_results(detected, results)
@pytest.mark.parametrize('detected,results', [
(
[Result('pluginA', '1.1'), Result('pluginA', '1.2'), Result('pluginA', '1.1')],
[Result('pluginA', '1.1'), Result('pluginA', '1.2')]
),
(
[
Result('pluginA', '1.1'),
Result('pluginA', type=INDICATOR_TYPE),
Result('pluginA', type=HINT_TYPE),
],
[Result('pluginA', '1.1')]
),
(
[Result('pluginB', type=HINT_TYPE), Result('pluginB', type=HINT_TYPE)],
[Result('pluginB', type=HINT_TYPE)]
),
(
[Result('pluginB', type=INDICATOR_TYPE), Result('pluginB', type=INDICATOR_TYPE)],
[Result('pluginB', type=INDICATOR_TYPE)]
),
(
[Result('pluginB', type=INDICATOR_TYPE), Result('pluginB', type=HINT_TYPE)],
[Result('pluginB', type=INDICATOR_TYPE)]
),
(
[Result('pluginB', type=INDICATOR_TYPE), Result('pluginB', type=GENERIC_TYPE)],
[Result('pluginB', type=INDICATOR_TYPE)]
),
])
def test_remove_duplicated_results(self, detected, results):
self._assert_results(detected, results)
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Mlitwin98/twitter-clone | twitter-clone/twitter/views.py | 4fbe754a4693c39ac4e9623f51ca42a7facecd2e | from django.dispatch.dispatcher import receiver
from django.shortcuts import get_object_or_404, redirect, render
from django.contrib.auth.decorators import login_required
from django.http.response import HttpResponse
from django.contrib.auth.models import User
from django.contrib.auth import authenticate, logout as auth_logout, login as auth_login
from django.contrib import messages
from django.db.models import Count
from django.template.loader import render_to_string
from django.http import HttpResponseRedirect, JsonResponse
from twitter.models import Tweet, Follow, Notification, Comment
from twitter.myDecor import check_if_user_logged
from twitter.forms import SignUpForm
# Create your views here.
@check_if_user_logged
def index(request):
return render(request, 'index.html')
@check_if_user_logged
def login(request):
if request.method == 'POST':
if 'login' in request.POST:
mail = request.POST['email']
pwd = request.POST['password']
user = authenticate(request, username=mail, password=pwd)
if user is not None:
auth_login(request, user)
return redirect('home')
else:
messages.error(request, 'Invalid credentials')
return render(request, 'login.html')
elif 'cancel' in request.POST:
return redirect('index')
else:
return render(request, 'login.html')
def logout(reqeuest):
auth_logout(reqeuest)
return redirect('index')
@check_if_user_logged
def register(request):
if request.method == 'POST':
if 'cancel' in request.POST:
return redirect('index')
elif 'register' in request.POST:
form = SignUpForm(request.POST)
if form.is_valid():
user = form.save()
email = form.cleaned_data.get('email')
raw_password = form.cleaned_data.get('password')
user.set_password(raw_password)
user.save()
user = authenticate(request, username=email, password = raw_password)
auth_login(request, user)
return redirect('home')
else:
form = SignUpForm()
messages.error(request, 'Invalid form fill')
return render(request, 'register.html', {'form':form})
else:
form = SignUpForm()
return render(request, 'register.html', {'form':form})
@login_required(redirect_field_name=None)
def home(request):
if request.method == 'POST':
author = request.user
content = request.POST['tweet']
tweet = Tweet(author=author, content=content)
tweet.save()
for follower in request.user.following.all().values_list('following_user_id', flat=True):
Notification.objects.create(sender = request.user, receiver = User.objects.get(id=follower), target = tweet, type = 'L')
return redirect('home')
else:
followedUsers = [request.user]
for followed in request.user.followers.all():
followedUsers.append(User.objects.get(id=followed.user_id_id))
tweets = Tweet.objects.filter(author__in=followedUsers).order_by('-timeStamp')
rec_profiles = User.objects.annotate(count=Count('followers')).order_by('followers').exclude(username=request.user.username).exclude(id__in=request.user.followers.all().values_list('user_id', flat=True))[:5]
return render(request, 'home.html', {'tweets':tweets, 'rec_profiles':rec_profiles})
def profile(request, username):
if request.method == 'POST':
user = User.objects.get(username=username)
user.profile.bio = request.POST['bio']
user.profile.profilePic = request.FILES['pic'] if 'pic' in request.FILES else user.profile.profilePic
user.profile.backgroundPic = request.FILES['banner'] if 'banner' in request.FILES else user.profile.backgroundPic
user.save()
return redirect('profile', username=username)
else:
try:
userProfile = User.objects.get(username=username)
except User.DoesNotExist:
return HttpResponse('User Not Found')
tweets = Tweet.objects.filter(author__exact=userProfile).order_by('-timeStamp')
is_following = False
for follow in request.user.followers.all():
if userProfile.id == follow.user_id_id:
is_following=True
rec_profiles = User.objects.annotate(count=Count('followers')).order_by('followers').exclude(username=request.user.username).exclude(username=username).exclude(id__in=request.user.followers.all().values_list('user_id', flat=True))[:5]
return render(request, 'profile.html', {'userProfile':userProfile, 'tweets':tweets, 'is_following':is_following, 'rec_profiles':rec_profiles})
@login_required(redirect_field_name=None)
def delete_post(request, tweetID):
if request.method == 'POST':
tweet = Tweet.objects.get(id=tweetID)
if tweet.author == request.user:
tweet.delete()
return redirect('profile', username=request.user.username)
else:
return redirect('home')
@login_required(redirect_field_name=None)
def like_post(request):
tweet = get_object_or_404(Tweet, id=request.POST.get('id'))
if tweet.likes.filter(id=request.user.id).exists():
tweet.likes.remove(request.user)
is_liked = False
else:
tweet.likes.add(request.user)
is_liked = True
if(request.user != tweet.author):
Notification.objects.create(sender = request.user, receiver = User.objects.get(username = tweet.author), target = tweet, type = 'L')
context = {
'tweet': tweet,
'is_liked': is_liked,
}
if request.is_ajax():
html = render_to_string('tweet.html', context, request=request)
return JsonResponse({'form':html})
@login_required(redirect_field_name=None)
def change_mode(request):
if request.method == 'POST':
usr = User.objects.get(id=request.user.id)
usr.profile.mode = request.POST['mode']
usr.save()
return HttpResponseRedirect(request.META.get('HTTP_REFERER'))
else:
return HttpResponseRedirect(request.META.get('HTTP_REFERER'))
@login_required(redirect_field_name=None)
def follow_profile(request):
followed_user = get_object_or_404(User, id=request.POST.get('id'))
if Follow.objects.filter(user_id=followed_user.id, following_user_id = request.user.id).exists():
Follow.objects.filter(user_id=followed_user.id, following_user_id = request.user.id).delete()
is_following = False
else:
Follow.objects.create(user_id=followed_user, following_user_id = request.user)
Notification.objects.create(sender = request.user, receiver = followed_user, target = None, type = 'F')
is_following = True
context = {
'profile':followed_user,
'userProfile':followed_user,
'is_following':is_following
}
if request.is_ajax():
html = render_to_string('follow_button.html', context, request=request)
return JsonResponse({'form':html})
def notifications(request):
notifics = request.user.your_notifications.all()
for notific in notifics:
notific.seen = True
notific.save()
notifics = request.user.your_notifications.all().order_by('-id')[:10]
return render(request, 'notifications.html', {'notifics':notifics})
def tweet_details(request, tweetID):
tweet = Tweet.objects.get(id=tweetID)
comments = tweet.main_tweet.all().order_by('-timeStamp')
return render(request, 'tweet_details.html', {'tweet':tweet, 'comments':comments})
def comment(request, tweetID):
if request.method == 'POST':
author = request.user
content = request.POST['comment']
tweet = Tweet.objects.get(id=tweetID)
Comment.objects.create(author=author, main_tweet=tweet, content=content)
if(request.user != tweet.author):
Notification.objects.create(sender = request.user, receiver = tweet.author, target = tweet, type = 'C')
return redirect(tweet_details, tweetID=tweetID)
else:
return redirect(home)
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Amruthaohm/custom_app | custom_app/custom_app/doctype/depart/test_depart.py | 03bc3fc11c3627251796611caf33b7117c46d69b | # Copyright (c) 2022, momscode and Contributors
# See license.txt
# import frappe
import unittest
class Testdepart(unittest.TestCase):
pass
| [] |
khdesai/cti-python-stix2 | stix2/__init__.py | 20a9bb316c43b7d9faaab686db8d51e5c89416da | """Python APIs for STIX 2.
.. autosummary::
:toctree: api
confidence
datastore
environment
equivalence
exceptions
markings
parsing
pattern_visitor
patterns
properties
serialization
utils
v20
v21
versioning
workbench
"""
# flake8: noqa
DEFAULT_VERSION = '2.1' # Default version will always be the latest STIX 2.X version
from .confidence import scales
from .datastore import CompositeDataSource
from .datastore.filesystem import (
FileSystemSink, FileSystemSource, FileSystemStore,
)
from .datastore.filters import Filter
from .datastore.memory import MemorySink, MemorySource, MemoryStore
from .datastore.taxii import (
TAXIICollectionSink, TAXIICollectionSource, TAXIICollectionStore,
)
from .environment import Environment, ObjectFactory
from .markings import (
add_markings, clear_markings, get_markings, is_marked, remove_markings,
set_markings,
)
from .parsing import _collect_stix2_mappings, parse, parse_observable
from .patterns import (
AndBooleanExpression, AndObservationExpression, BasicObjectPathComponent,
BinaryConstant, BooleanConstant, EqualityComparisonExpression,
FloatConstant, FollowedByObservationExpression,
GreaterThanComparisonExpression, GreaterThanEqualComparisonExpression,
HashConstant, HexConstant, InComparisonExpression, IntegerConstant,
IsSubsetComparisonExpression, IsSupersetComparisonExpression,
LessThanComparisonExpression, LessThanEqualComparisonExpression,
LikeComparisonExpression, ListConstant, ListObjectPathComponent,
MatchesComparisonExpression, ObjectPath, ObservationExpression,
OrBooleanExpression, OrObservationExpression, ParentheticalExpression,
QualifiedObservationExpression, ReferenceObjectPathComponent,
RepeatQualifier, StartStopQualifier, StringConstant, TimestampConstant,
WithinQualifier,
)
from .v21 import * # This import will always be the latest STIX 2.X version
from .version import __version__
from .versioning import new_version, revoke
_collect_stix2_mappings()
| [] |
chr0m3/boj-codes | 0/1/1436/1436.py | d71d0a22d0a3ae62c225f382442461275f56fe8f | count = int(input())
title = 0
while count > 0:
title += 1
if '666' in str(title):
count -= 1
print(title)
| [] |
jieatelement/quickstart-aws-industrial-machine-connectivity | functions/source/GreengrassLambda/idna/uts46data.py | ca6af4dcbf795ce4a91adcbec4b206147ab26bfa | # This file is automatically generated by tools/idna-data
# vim: set fileencoding=utf-8 :
"""IDNA Mapping Table from UTS46."""
__version__ = "11.0.0"
def _seg_0():
return [
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(0x1, '3'),
(0x2, '3'),
(0x3, '3'),
(0x4, '3'),
(0x5, '3'),
(0x6, '3'),
(0x7, '3'),
(0x8, '3'),
(0x9, '3'),
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(0x16, '3'),
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(0x18, '3'),
(0x19, '3'),
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(0x1B, '3'),
(0x1C, '3'),
(0x1D, '3'),
(0x1E, '3'),
(0x1F, '3'),
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(0x21, '3'),
(0x22, '3'),
(0x23, '3'),
(0x24, '3'),
(0x25, '3'),
(0x26, '3'),
(0x27, '3'),
(0x28, '3'),
(0x29, '3'),
(0x2A, '3'),
(0x2B, '3'),
(0x2C, '3'),
(0x2D, 'V'),
(0x2E, 'V'),
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(0x30, 'V'),
(0x31, 'V'),
(0x32, 'V'),
(0x33, 'V'),
(0x34, 'V'),
(0x35, 'V'),
(0x36, 'V'),
(0x37, 'V'),
(0x38, 'V'),
(0x39, 'V'),
(0x3A, '3'),
(0x3B, '3'),
(0x3C, '3'),
(0x3D, '3'),
(0x3E, '3'),
(0x3F, '3'),
(0x40, '3'),
(0x41, 'M', u'a'),
(0x42, 'M', u'b'),
(0x43, 'M', u'c'),
(0x44, 'M', u'd'),
(0x45, 'M', u'e'),
(0x46, 'M', u'f'),
(0x47, 'M', u'g'),
(0x48, 'M', u'h'),
(0x49, 'M', u'i'),
(0x4A, 'M', u'j'),
(0x4B, 'M', u'k'),
(0x4C, 'M', u'l'),
(0x4D, 'M', u'm'),
(0x4E, 'M', u'n'),
(0x4F, 'M', u'o'),
(0x50, 'M', u'p'),
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alex4321/ctp | tests/kbcr/smart/test_smart.py | 22a6a55442a648e5f7d8c10f90708a7340360720 | # -*- coding: utf-8 -*-
import numpy as np
import torch
from torch import nn
from kbcr.kernels import GaussianKernel
from kbcr.smart import NeuralKB
import pytest
@pytest.mark.light
def test_smart_v1():
embedding_size = 50
rs = np.random.RandomState(0)
for _ in range(32):
with torch.no_grad():
triples = [
('a', 'p', 'b'),
('c', 'q', 'd'),
('e', 'q', 'f'),
('g', 'q', 'h'),
('i', 'q', 'l'),
('m', 'q', 'n'),
('o', 'q', 'p'),
('q', 'q', 'r'),
('s', 'q', 't'),
('u', 'q', 'v')
]
entity_lst = sorted({s for (s, _, _) in triples} | {o for (_, _, o) in triples})
predicate_lst = sorted({p for (_, p, _) in triples})
nb_entities, nb_predicates = len(entity_lst), len(predicate_lst)
entity_to_index = {e: i for i, e in enumerate(entity_lst)}
predicate_to_index = {p: i for i, p in enumerate(predicate_lst)}
kernel = GaussianKernel()
entity_embeddings = nn.Embedding(nb_entities, embedding_size * 2, sparse=True)
predicate_embeddings = nn.Embedding(nb_predicates, embedding_size * 2, sparse=True)
fact_rel = torch.LongTensor(np.array([predicate_to_index[p] for (_, p, _) in triples]))
fact_arg1 = torch.LongTensor(np.array([entity_to_index[s] for (s, _, _) in triples]))
fact_arg2 = torch.LongTensor(np.array([entity_to_index[o] for (_, _, o) in triples]))
facts = [fact_rel, fact_arg1, fact_arg2]
model = NeuralKB(entity_embeddings=entity_embeddings, predicate_embeddings=predicate_embeddings,
kernel=kernel, facts=facts)
xs_np = rs.randint(nb_entities, size=32)
xp_np = rs.randint(nb_predicates, size=32)
xo_np = rs.randint(nb_entities, size=32)
xs_np[0] = 0
xp_np[0] = 0
xo_np[0] = 1
xs_np[1] = 2
xp_np[1] = 1
xo_np[1] = 3
xs = torch.LongTensor(xs_np)
xp = torch.LongTensor(xp_np)
xo = torch.LongTensor(xo_np)
xs_emb = entity_embeddings(xs)
xp_emb = predicate_embeddings(xp)
xo_emb = entity_embeddings(xo)
print('xp_emb', xp_emb.shape)
res_sp, res_po = model.forward(xp_emb, xs_emb, xo_emb)
inf = model.score(xp_emb, xs_emb, xo_emb)
assert inf[0] > 0.9
assert inf[1] > 0.9
scores_sp, emb_sp = res_sp
scores_po, emb_po = res_po
print(scores_sp.shape, emb_sp.shape)
print(scores_po.shape, emb_po.shape)
inf = inf.cpu().numpy()
scores_sp = scores_sp.cpu().numpy()
scores_po = scores_po.cpu().numpy()
print('AAA', inf)
print('BBB', scores_sp)
if __name__ == '__main__':
pytest.main([__file__])
# test_smart_v1()
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eseJiHeaLim/find_child | test.py | 29596529ccf39241492b092b01baf03b76d0eb3a | import tkinter
window=tkinter.Tk()
window.title("YUN DAE HEE")
window.geometry("640x400+100+100")
window.resizable(True, True)
image=tkinter.PhotoImage(file="opencv_frame_0.png")
label=tkinter.Label(window, image=image)
label.pack()
window.mainloop() | [((3, 7, 3, 19), 'tkinter.Tk', 'tkinter.Tk', ({}, {}), '()', False, 'import tkinter\n'), ((8, 6, 8, 51), 'tkinter.PhotoImage', 'tkinter.PhotoImage', (), '', False, 'import tkinter\n'), ((10, 6, 10, 40), 'tkinter.Label', 'tkinter.Label', (), '', False, 'import tkinter\n')] |
trujivan/climate-impact-changes | UMSLHackRestAPI/api/urls.py | 609b8197b0ede1c1fdac3aa82b34e73e6f4526e3 | from django.urls import path, include
from .views import main_view, PredictionView
#router = routers.DefaultRouter(trailing_slash=False)
#router.register('years', YearView, basename='years')
#router.register('predict', PredictionView, basename='predict')
urlpatterns = [
#path('api/', get_dummy_data),
#path('pollution/predict', get_prediction, name='test_predict'),
#path('myform/', api_form_view, name='year_form'),
#path('api/', include(router.urls)),
path(r'', main_view, name="main"),
path(r'api/v1/predict', PredictionView.as_view(), name='predict')
] | [((14, 4, 14, 37), 'django.urls.path', 'path', (), '', False, 'from django.urls import path, include\n')] |
appressoas/ievv_opensource | ievv_opensource/utils/ievv_colorize.py | 63e87827952ddc8f6f86145b79478ef21d6a0990 | from django.conf import settings
from termcolor import colored
#: Red color constant for :func:`.ievv_colorize`.
COLOR_RED = 'red'
#: Blue color constant for :func:`.ievv_colorize`.
COLOR_BLUE = 'blue'
#: Yellow color constant for :func:`.ievv_colorize`.
COLOR_YELLOW = 'yellow'
#: Grey color constant for :func:`.ievv_colorize`.
COLOR_GREY = 'grey'
#: Green color constant for :func:`.ievv_colorize`.
COLOR_GREEN = 'green'
def colorize(text, color, bold=False):
"""
Colorize a string for stdout/stderr.
Colors are only applied if :setting:`IEVV_COLORIZE_USE_COLORS` is
``True`` or not defined (so it defaults to ``True``).
Examples:
Print blue text::
from ievv_opensource.utils import ievv_colorize
print(ievv_colorize('Test', color=ievv_colorize.COLOR_BLUE))
Print bold red text::
print(ievv_colorize('Test', color=ievv_colorize.COLOR_RED, bold=True))
Args:
text: The text (string) to colorize.
color: The color to use.
Should be one of:
- :obj:`.COLOR_RED`
- :obj:`.COLOR_BLUE`
- :obj:`.COLOR_YELLOW`
- :obj:`.COLOR_GREY`
- :obj:`.COLOR_GREEN`
- ``None`` (no color)
bold: Set this to ``True`` to use bold font.
"""
if getattr(settings, 'IEVV_COLORIZE_USE_COLORS', True) and color:
attrs = []
if bold:
attrs.append('bold')
return colored(text, color=color, attrs=attrs)
else:
return text
| [((57, 15, 57, 54), 'termcolor.colored', 'colored', (), '', False, 'from termcolor import colored\n')] |
bluefin1986/tinyspark | RSICompute.py | 0b086d3af5316062c2f3aaa7d4492341ed5c71c2 |
# coding: utf-8
# In[1]:
import baostock as bs
import pandas as pd
import numpy as np
import talib as ta
import matplotlib.pyplot as plt
import KlineService
import BaoStockUtil
import math
import datetime
from scipy import integrate
from RSI import DayRSI,WeekRSI,MonthRSI,SixtyMinRSI
from concurrent.futures import ThreadPoolExecutor, as_completed
from Stock import Stock
import dbutil
from IPython.core.debugger import set_trace
#算积分用的节点数
INTEGRATE_CALC_RANGE = 4
RSI_OVER_BUY = 80
RSI_OVER_SELL = 20
RSI_OVER_BUY_12 = 75
RSI_OVER_SELL_12 = 25
RSI_OVER_BUY_24 = 70
RSI_OVER_SELL_24 = 30
RSI_MIDDLE = 50
#日线超卖区域积分阈值
RSI_INTE_OVERSELL_THRESHOLD_DAY = 50
# In[3]:
def findLatestRSIDate(period):
mydb = dbutil.connectDB()
collection = mydb[chooseRSICollection(period)]
cursor = collection.find().sort("date",-1).limit(1)
df = pd.DataFrame(list(cursor))
if df.empty:
return "1970-01-01"
return df["date"][0]
def clearRSI(period):
mydb = dbutil.connectDB()
collection = mydb[chooseRSICollection(period)]
collection.delete_many({})
indexes = collection.index_information()
if "code_1_date_1" in indexes.keys():
collection.drop_index( "code_1_date_1" )
def createIndex(period):
mydb = dbutil.connectDB()
collection = mydb[chooseRSICollection(period)]
collection.create_index( [("code", 1), ("date",1)])
def integrateValues(valuesArray):
return integrate.trapz(valuesArray, x=None, dx=1.0, axis=-1)
##
# 从数据库读指定日期RSI数据
#
#
def readRSI(period, stockCode, startDate, endDate):
mydb = dbutil.connectDB()
collection = mydb[chooseRSICollection(period)]
if type(startDate) == str:
startDate = datetime.datetime.strptime(startDate + "T00:00:00.000Z", "%Y-%m-%dT%H:%M:%S.000Z")
endDate = datetime.datetime.strptime(endDate + "T23:59:59.000Z", "%Y-%m-%dT%H:%M:%S.000Z")
cursor = collection.find({"code":stockCode,"date":{"$gte":startDate,"$lte":endDate}})
df = pd.DataFrame(list(cursor))
return df
##
# 写RSI数据库
#
#
def writeRSIToDB(period, stockCode, stockName, rsi_df):
dataList = []
for index,rsi in rsi_df.iterrows():
rsiDate = rsi['date']
if period == "day":
rsiObj = DayRSI(stockCode, stockName)
elif period == "week":
rsiObj = WeekRSI(stockCode, stockName)
elif period == "month":
rsiObj = MonthRSI(stockCode, stockName)
elif period == "5m":
rsiObj = FiveMinRSI(stockCode, stockName)
elif period == "15m":
rsiObj = FiftyMinRSI(stockCode, stockName)
elif period == "30m":
rsiObj = ThirtyMinRSI(stockCode, stockName)
elif period == "60m":
rsiObj = SixtyMinRSI(stockCode, stockName)
rsiObj.date = rsiDate
rsiObj.rsi_6 = rsi['rsi_6']
rsiObj.rsi_12 = rsi['rsi_12']
rsiObj.rsi_24 = rsi['rsi_24']
rsiObj.overBuy = rsi['overBuyFlag']
rsiObj.overSell = rsi['overSellFlag']
dataList.append(rsiObj.__dict__)
mydb = dbutil.connectDB()
collection = mydb[chooseRSICollection(period)]
if len(dataList) > 0:
collection.insert_many(dataList)
else:
raise RuntimeError("RSI数据为空")
def computeStockRSI(period, stockCode, stockName, startDate, endDate):
try:
# compute1 = datetime.datetime.now().timestamp()
df = KlineService.readStockKline(stockCode, period, startDate, endDate)
# compute2 = datetime.datetime.now().timestamp()
# print("read stockLine:", compute2 - compute1)
if df.empty:
return False
if period == "day":
# 剔除日线停盘数据
df = df[df['tradeStatus'] == '1']
rsi_df = computeRSI(df)
# compute3 = datetime.datetime.now().timestamp()
# print("compute rsi:", compute3 - compute2)
writeRSIToDB(period, stockCode, stockName, rsi_df)
# compute4 = datetime.datetime.now().timestamp()
# print("write to db:", compute4 - compute3)
return True
except BaseException as e:
print ("download " + stockCode + " error:" + str(e))
return False
##
# 选择不同的Kline Collection
#
def chooseRSICollection(period):
periodRSICollection = {
"day" : "RSI_Day",
"week" : "RSI_Week",
"month" : "RSI_Month",
"5m" : "RSI_5m",
"15m" : "RSI_15m",
"30m" : "RSI_30m",
"60m" : "RSI_60m"
}
return periodRSICollection.get(period)
def computeRSI(klineDataFrame):
rsi_12days = ta.RSI(klineDataFrame['closePrice'],timeperiod=12)
rsi_6days = ta.RSI(klineDataFrame['closePrice'],timeperiod=6)
rsi_24days = ta.RSI(klineDataFrame['closePrice'],timeperiod=24)
rsiFrame = pd.DataFrame(klineDataFrame, columns=["date"])
rsiFrame['rsi_6'] = rsi_6days
rsiFrame['rsi_12'] = rsi_12days
rsiFrame['rsi_24'] = rsi_24days
##添加参考线位置
rsiFrame['overBuy'] = RSI_OVER_BUY
rsiFrame['overSell'] = RSI_OVER_SELL
rsiFrame['middle'] = RSI_MIDDLE
# RSI超卖和超买
rsi_buy_position = rsiFrame['rsi_12'] > RSI_OVER_BUY_12
rsi_sell_position = rsiFrame['rsi_12'] < RSI_OVER_SELL_12
rsiFrame.loc[rsi_buy_position[(rsi_buy_position == True) & (rsi_buy_position.shift() == False)].index, 'overBuyFlag'] = 'Yes'
rsiFrame.loc[rsi_sell_position[(rsi_sell_position == True) & (rsi_sell_position.shift() == False)].index, 'overSellFlag'] = 'Yes'
return rsiFrame
##
# 计算自起始日期起的RSI
#
#
def computeAllRSIDataOfPeriod(period, startDate):
# currtime = datetime.datetime.now().timestamp()
print("begin clear RSI period:", period)
clearRSI(period)
print("cleared RSI period:", period)
# time1 = datetime.datetime.now().timestamp()
# print("clear finished:",time1 - currtime)
stockDict = KlineService.allStocks()
# time2 = datetime.datetime.now().timestamp()
# print("read stocks finished:",time2 - time1)
endDate = str(datetime.date.today())
jobStart = datetime.datetime.now().timestamp()
processCount = 0
failCount = 0
jobTotal = len(stockDict)
'''
#起线程池来跑，单线程太慢了, 事实证明慢个鬼
executor = ThreadPoolExecutor(max_workers=1)
funcVars = []
for key,stock in stockDict.items():
#指数没有分钟线，调过指数的RSI分钟线计算
if period.endswith("m") and (key.startswith("sh.000") or key.startswith("sz.399")):
continue
funcVars.append([period, key, stock["name"], startDate, endDate])
all_task = [executor.submit(computeStockRSI, funcVar[0], funcVar[1], funcVar[2], funcVar[3], funcVar[4])
for funcVar in funcVars]
for future in as_completed(all_task):
processCount = processCount + 1
if not future.result():
failCount = failCount + 1
if processCount % 100 == 0 and processCount > 0:
print ("rsi process:", processCount, " of ", jobTotal ," failed:", failCount)
'''
for key,stock in stockDict.items():
processCount = processCount + 1
#指数没有分钟线，调过指数的RSI分钟线计算
if period.endswith("m") and (key.startswith("sh.000") or key.startswith("sz.399")):
continue
result = computeStockRSI(period, key, stock["name"], startDate, endDate)
if not result:
failCount = failCount + 1
if processCount % 100 == 0 and processCount > 0:
print ("rsi process:", processCount, " of ", jobTotal ," failed:", failCount)
jobFinished = datetime.datetime.now().timestamp()
createIndex(period)
print("write all stock RSI to db finished, cost:", jobFinished - jobStart)
return True
##
# 计算指定日期的RSI积分
#
#
def computeAllRSIDataIntegrate(period, specifiedDateStr, includeST):
BaoStockUtil.customLogin()
specifiedDate = datetime.datetime.strptime(specifiedDateStr, "%Y-%m-%d")
today = datetime.date.today()
#如果把时间设成未来，自动调成今天
if specifiedDate > datetime.datetime.today():
specifiedDate = datetime.date.today()
#避免跨年问题，直接从去年开始取
startDate = specifiedDate - datetime.timedelta(days = 365)
#取交易日列表，用作倒推周期使用
rs = bs.query_trade_dates(start_date=datetime.datetime.strftime(startDate, "%Y-%m-%d"), end_date = specifiedDate)
BaoStockUtil.customLogout()
if rs.error_code != '0':
raise RuntimeError("交易日api调用失败了:" + rs.error_code)
tradeDates = []
while (rs.error_code == '0') & rs.next():
row = rs.get_row_data()
if row[1] == "1":
tradeDates.append(row[0])
if len(tradeDates) == 0:
raise RuntimeError("取不到最新的交易日")
#若期望计算的日期比库里RSI最新日期还晚，数据不全待补齐
rsiLatestDate = findLatestRSIDate(period)
rsiLatestDateStr = datetime.datetime.strftime(rsiLatestDate, "%Y-%m-%d")
if rsiLatestDate < specifiedDate:
raise RuntimeError(specifiedDateStr + " 的 " + period + " RSI的数据不存在，待补齐数据")
#找到指定日期以及rsi存量数据最近日期在交易日周期的序号
specifiedDateIndex = tradeDates.index(specifiedDateStr)
if specifiedDateIndex == -1:
raise RuntimeError(specifiedDateStr + " 可能不是交易日")
daysBefore = computeRSIDataStartTradeDateRange(period, specifiedDateStr)
startDateIndex = specifiedDateIndex - daysBefore
#起始日期index负数，说明rsi数据不够
if startDateIndex < 0:
raise RuntimeError(period + " rsi数据不够")
startDateStr = tradeDates[startDateIndex]
print("compute rsi tradeDates from ", startDateStr, "to", specifiedDateStr)
processCount = 0
failCount = 0
startDateIndex = -1
dictStocks = KlineService.allStocks()
klineDataFrame = KlineService.readAllStockKline(period, specifiedDateStr, specifiedDateStr)
klineDataFrame = klineDataFrame.set_index("code")
klineDict = klineDataFrame.to_dict('index')
jobTotal = len(dictStocks)
rsiValueArrs = []
for i in range(0, 6):
rsiValueArrs.append([])
for key,stock in dictStocks.items():
processCount = processCount + 1
#指数没有分钟线，跳过指数的RSI分钟线计算
if period.endswith("m") and stock.stockType != 1:
continue
#如果不计算ST，跳过
if not includeST and stock["isST"]:
continue
#退市股就不要算了
if "退" in stock["name"]:
continue
#科创板不达门槛没法买，不看
if key.startswith("sh.68"):
continue
try:
rsiDF = readRSI(period, key, startDateStr, specifiedDateStr)
rsiCount = len(rsiDF)
if rsiCount < INTEGRATE_CALC_RANGE:
raise RuntimeError("积分计算节点不够")
rsiValueArrs[0].append(key)
rsiValueArrs[1].append(stock["name"])
rsiValueArrs[2].append(klineDict[key]["closePrice"])
#取最近的数据用于计算积分
rsiValueArrs[3].append(rsiDF["rsi_6"][rsiCount - INTEGRATE_CALC_RANGE : rsiCount])
rsiValueArrs[4].append(rsiDF["rsi_12"][rsiCount - INTEGRATE_CALC_RANGE : rsiCount])
rsiValueArrs[5].append(rsiDF["rsi_24"][rsiCount - INTEGRATE_CALC_RANGE : rsiCount])
except BaseException as e:
failCount = failCount + 1
print ("compute rsi integrate " + key + " error:" + str(e))
if processCount % 100 == 0 and processCount > 0:
print ("compute rsi integrate process:", processCount, " of ", jobTotal ," failed:", failCount)
rsi6Arr = np.array(rsiValueArrs[3]).reshape(-1, INTEGRATE_CALC_RANGE)
rsi6InteArr = integrateValues(rsi6Arr)
rsi12Arr = np.array(rsiValueArrs[4]).reshape(-1, INTEGRATE_CALC_RANGE)
rsi12InteArr = integrateValues(rsi12Arr)
rsi24Arr = np.array(rsiValueArrs[5]).reshape(-1, INTEGRATE_CALC_RANGE)
rsi24InteArr = integrateValues(rsi24Arr)
rsiInteDF = pd.DataFrame()
rsiInteDF["code"] = rsiValueArrs[0]
rsiInteDF["name"] = rsiValueArrs[1]
rsiInteDF["closePrice"] = rsiValueArrs[2]
rsiInteDF["rsi_inte_6"] = rsi6InteArr
rsiInteDF["rsi_inte_12"] = rsi12InteArr
rsiInteDF["rsi_inte_24"] = rsi24InteArr
return rsiInteDF
#算出计算本周期下指定数据需要的起始交易日
#每个交易日一共4小时，所以取4小时为一天，而不是24小时
#每个计算周期一共至少需要4个节点，分钟线RSI统一除以4*60=240分钟算出所需计算数据天数，最少为一天
#日线不用除分钟
## TODO 周线没想好怎么算，更别说月线了。
def computeRSIDataStartTradeDateRange(period, specifiedDate):
daysBefore = 0
if period.endswith("m"):
daysBefore = math.ceil(INTEGRATE_CALC_RANGE * (int(period.replace("m", "")) + 1) / (60 * 4))
elif period == "day":
daysBefore = INTEGRATE_CALC_RANGE
else:
raise RuntimeError("周期有误")
return daysBefore
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{}), '()', False, 'import KlineService\n'), ((288, 21, 288, 95), 'KlineService.readAllStockKline', 'KlineService.readAllStockKline', ({(288, 52, 288, 58): 'period', (288, 60, 288, 76): 'specifiedDateStr', (288, 78, 288, 94): 'specifiedDateStr'}, {}), '(period, specifiedDateStr, specifiedDateStr)', False, 'import KlineService\n'), ((336, 16, 336, 30), 'pandas.DataFrame', 'pd.DataFrame', ({}, {}), '()', True, 'import pandas as pd\n'), ((76, 20, 76, 102), 'datetime.datetime.strptime', 'datetime.datetime.strptime', ({(76, 47, 76, 75): "startDate + 'T00:00:00.000Z'", (76, 77, 76, 101): '"""%Y-%m-%dT%H:%M:%S.000Z"""'}, {}), "(startDate + 'T00:00:00.000Z',\n '%Y-%m-%dT%H:%M:%S.000Z')", False, 'import datetime\n'), ((77, 18, 77, 98), 'datetime.datetime.strptime', 'datetime.datetime.strptime', ({(77, 45, 77, 71): "endDate + 'T23:59:59.000Z'", (77, 73, 77, 97): '"""%Y-%m-%dT%H:%M:%S.000Z"""'}, {}), "(endDate + 'T23:59:59.000Z', '%Y-%m-%dT%H:%M:%S.000Z'\n )", False, 'import datetime\n'), ((125, 13, 125, 79), 'KlineService.readStockKline', 'KlineService.readStockKline', ({(125, 41, 125, 50): 'stockCode', (125, 52, 125, 58): 'period', (125, 60, 125, 69): 'startDate', (125, 71, 125, 78): 'endDate'}, {}), '(stockCode, period, startDate, endDate)', False, 'import KlineService\n'), ((196, 18, 196, 39), 'datetime.date.today', 'datetime.date.today', ({}, {}), '()', False, 'import datetime\n'), ((246, 23, 246, 48), 'datetime.datetime.today', 'datetime.datetime.today', ({}, {}), '()', False, 'import datetime\n'), ((247, 24, 247, 45), 'datetime.date.today', 'datetime.date.today', ({}, {}), '()', False, 'import datetime\n'), ((249, 32, 249, 62), 'datetime.timedelta', 'datetime.timedelta', (), '', False, 'import datetime\n'), ((91, 21, 91, 49), 'RSI.DayRSI', 'DayRSI', ({(91, 28, 91, 37): 'stockCode', (91, 39, 91, 48): 'stockName'}, {}), '(stockCode, stockName)', False, 'from RSI import DayRSI, WeekRSI, MonthRSI, SixtyMinRSI\n'), ((197, 15, 197, 38), 'datetime.datetime.now', 'datetime.datetime.now', ({}, {}), '()', False, 'import datetime\n'), ((232, 18, 232, 41), 'datetime.datetime.now', 'datetime.datetime.now', ({}, {}), '()', False, 'import datetime\n'), ((251, 41, 251, 90), 'datetime.datetime.strftime', 'datetime.datetime.strftime', ({(251, 68, 251, 77): 'startDate', (251, 79, 251, 89): '"""%Y-%m-%d"""'}, {}), "(startDate, '%Y-%m-%d')", False, 'import datetime\n'), ((329, 14, 329, 39), 'numpy.array', 'np.array', ({(329, 23, 329, 38): 'rsiValueArrs[3]'}, {}), '(rsiValueArrs[3])', True, 'import numpy as np\n'), ((331, 15, 331, 40), 'numpy.array', 'np.array', ({(331, 24, 331, 39): 'rsiValueArrs[4]'}, {}), '(rsiValueArrs[4])', True, 'import numpy as np\n'), ((333, 15, 333, 40), 'numpy.array', 'np.array', ({(333, 24, 333, 39): 'rsiValueArrs[5]'}, {}), '(rsiValueArrs[5])', True, 'import numpy as np\n'), ((93, 21, 93, 50), 'RSI.WeekRSI', 'WeekRSI', ({(93, 29, 93, 38): 'stockCode', (93, 40, 93, 49): 'stockName'}, {}), '(stockCode, stockName)', False, 'from RSI import DayRSI, WeekRSI, MonthRSI, SixtyMinRSI\n'), ((95, 21, 95, 51), 'RSI.MonthRSI', 'MonthRSI', ({(95, 30, 95, 39): 'stockCode', (95, 41, 95, 50): 'stockName'}, {}), '(stockCode, stockName)', False, 'from RSI import DayRSI, WeekRSI, MonthRSI, SixtyMinRSI\n'), ((103, 21, 103, 54), 'RSI.SixtyMinRSI', 'SixtyMinRSI', ({(103, 33, 103, 42): 'stockCode', (103, 44, 103, 53): 'stockName'}, {}), '(stockCode, stockName)', False, 'from RSI import DayRSI, WeekRSI, MonthRSI, SixtyMinRSI\n')] |
abousselmi/OSNoise | osnoise/conf/base.py | f0e4baa51921f672179c014beb89555958c7ddca | # Copyright 2016 Orange
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from oslo_config import cfg
base_options = [
cfg.StrOpt(
'log_file_name',
default='osnoise.log',
help='Osnoise file name.'),
cfg.StrOpt(
'log_dir',
default='/var/log/osnoise/',
help='Osnoise log directory.'),
cfg.StrOpt(
'log_level',
default='info',
help='Log level.'),
cfg.StrOpt(
'log_file',
default='/var/log/osnoise/osnoise.log',
help='Log file'),
cfg.IntOpt(
'log_maxBytes',
default=1000000,
min=1000,
help='Log level.'),
cfg.IntOpt(
'log_backupCount',
default=5,
min=1,
help='Log level.'),
cfg.BoolOpt('log_config_append',
default=False,
deprecated_group='DEFAULT',
help='To append logs to existent log file or not.'),
]
def register_opts(conf):
conf.register_opts(base_options)
def list_opts():
return {'DEFAULT' : base_options} | [((19, 4, 22, 34), 'oslo_config.cfg.StrOpt', 'cfg.StrOpt', (), '', False, 'from oslo_config import cfg\n'), ((23, 4, 26, 38), 'oslo_config.cfg.StrOpt', 'cfg.StrOpt', (), '', False, 'from oslo_config import cfg\n'), ((27, 4, 30, 26), 'oslo_config.cfg.StrOpt', 'cfg.StrOpt', (), '', False, 'from oslo_config import cfg\n'), ((32, 4, 35, 24), 'oslo_config.cfg.StrOpt', 'cfg.StrOpt', (), '', False, 'from oslo_config import cfg\n'), ((37, 4, 41, 26), 'oslo_config.cfg.IntOpt', 'cfg.IntOpt', (), '', False, 'from oslo_config import cfg\n'), ((42, 4, 46, 26), 'oslo_config.cfg.IntOpt', 'cfg.IntOpt', (), '', False, 'from oslo_config import cfg\n'), ((47, 4, 50, 67), 'oslo_config.cfg.BoolOpt', 'cfg.BoolOpt', (), '', False, 'from oslo_config import cfg\n')] |
Ginkooo/ORION-sensor-visualizer | src/orionsensor/gui/sensors/proximitysensor.py | 550b2e692d711bb8104fe827570ef9b9112536d3 | from kivy.properties import NumericProperty
from gui.sensors.sensor import Sensor
import config
class ProximitySensor(Sensor):
"""Proximity sensor view"""
# maximum possible reading
max = NumericProperty(config.ProximitySensor.max)
# minimum possible reading
min = NumericProperty(config.ProximitySensor.min)
| [((11, 10, 11, 53), 'kivy.properties.NumericProperty', 'NumericProperty', ({(11, 26, 11, 52): 'config.ProximitySensor.max'}, {}), '(config.ProximitySensor.max)', False, 'from kivy.properties import NumericProperty\n'), ((13, 10, 13, 53), 'kivy.properties.NumericProperty', 'NumericProperty', ({(13, 26, 13, 52): 'config.ProximitySensor.min'}, {}), '(config.ProximitySensor.min)', False, 'from kivy.properties import NumericProperty\n')] |
gudtldn/DiscordStockBot | Cogs/HelpCommand.py | d1b06e49738092ccf3c5d5a26b35fd321a3bd0f2 | #도움말
import discord
from discord.ext import commands
from discord.ext.commands import Context
from define import *
class HelpCommand_Context(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command(name="도움말", aliases=["명령어", "?"])
@CommandExecutionTime
async def _HelpCommand(self, ctx: Context, command: str=None):
logger.info(f"[{type(ctx)}] {ctx.author.name}: {ctx.invoked_with} {command}")
if ctx.guild is None:
logger.info("Guild is None")
return
if command is not None:
if command.startswith("."):
command = command.replace(".", "", 1)
if command is None:
embed = discord.Embed(title="도움말", description="[] <-- 필수 입력항목 | <> <-- 선택 입력항목", color=RandomEmbedColor())
embed.add_field(name=".사용자등록", value="데이터 베이스에 사용자를 등록합니다.", inline=False)
embed.add_field(name=".자산정보", value="현재 자신의 자산정보를 확인합니다.", inline=False)
embed.add_field(name=".주가", value="현재 주가를 검색합니다.", inline=False)
embed.add_field(name=".매수", value="입력한 기업의 주식을 매수합니다.", inline=False)
embed.add_field(name=".매도", value="입력한 기업의 주식을 매도합니다.", inline=False)
embed.add_field(name=".지원금", value="1만원 ~ 10만원 사이의 돈을 랜덤으로 지급합니다.", inline=False)
embed.add_field(name=".초기화", value="자신의 자산정보를 초기화 합니다.", inline=False)
embed.add_field(name=".탈퇴", value="이 봇에 저장되어있는 사용자의 정보를 삭제합니다.", inline=False)
embed.add_field(name=".개인설정", value="개인설정을 확인 또는 수정합니다.", inline=False)
embed.add_field(name=".단축어설정", value="단축어목록을 확인하거나, 추가 또는 제거합니다.", inline=False)
embed.add_field(name=".관심종목", value="관심종목에 추가된 주식의 가격을 확인하거나, 추가 또는 제거합니다.", inline=False)
embed.set_footer(text="명령어를 자세히 보려면 「.도움말 <명령어 이름>」 을 써 주세요.")
await ctx.reply(embed=embed)
return
elif command in ("도움말", "명령어", "?"):
command_list = ["도움말", "명령어", "?"]
command_list.remove(command)
embed = discord.Embed(title="도움말", description="등록되어있는 명령어들을 출력합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("사용자등록", "등록"):
command_list = ["사용자등록", "등록"]
command_list.remove(command)
embed = discord.Embed(title="사용자등록", description="데이터 베이스에 사용자를 등록합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("자산정보", "자산조회"):
command_list = ["자산정보", "자산조회"]
command_list.remove(command)
embed = discord.Embed(title="자산정보", description="자신의 자산정보를 확인합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".자산정보 <@유저>", value="@유저의 자산정보를 확인합니다.", inline=False)
embed.add_field(name=".자산정보 <랭킹 | 순위>", value="이 서버에 있는 유저의 자산랭킹을 나열합니다.", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("주가", "시세"):
command_list = ["주가", "시세"]
command_list.remove(command)
embed = discord.Embed(title="주가", description="입력한 기업의 현재 주가를 확인합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".주가 [기업이름 | 기업번호]", value="기업이름 또는 기업번호로 검색합니다.", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("매수", "구매", "주식구매", "주식매수"):
command_list = ["매수", "구매", "주식구매", "주식매수"]
command_list.remove(command)
embed = discord.Embed(title="매수", description="입력한 기업의 주식을 매수합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".매수 [기업이름 | 기업번호] [매수 할 주식 개수]", value="입력한 기업의 주식을, 주식 개수만큼 매수합니다.", inline=False)
embed.add_field(name=".매수 [기업이름 | 기업번호] [풀매수 | 모두]", value="입력한 기업의 주식을 최대까지 매수합니다.", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("매도", "판매", "주식판매", "주식매도"):
command_list = ["매도", "판매", "주식판매", "주식매도"]
command_list.remove(command)
embed = discord.Embed(title="매도", description="입력한 기업의 주식을 매도합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".매도 [기업이름 | 기업번호] [매도 할 주식 개수]", value="입력한 기업의 주식을, 주식 개수만큼 매도합니다.", inline=False)
embed.add_field(name=".매도 [기업이름 | 기업번호] [반매도]", value="입력한 기업의 주식의 절반을 매도합니다.", inline=False)
embed.add_field(name=".매도 [기업이름 | 기업번호] [풀매도 | 모두]", value="입력한 기업의 주식을 모두 매도합니다.", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("지원금", "돈받기"):
command_list = ["지원금", "돈받기"]
command_list.remove(command)
embed = discord.Embed(title="지원금", description="1만원 ~ 10만원 사이의 돈을 랜덤으로 지급합니다. (쿨타임: 4시간)", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
await ctx.reply(embed=embed)
return
elif command == "초기화":
embed = discord.Embed(title="초기화", description="「초기화확인」를 입력해 자신의 자산정보를 초기화 합니다.", color=RandomEmbedColor())
embed.add_field(name=".초기화 [확인문구]", value="확인문구에는 「초기화확인」를 입력해 주세요.")
await ctx.reply(embed=embed)
return
elif command in ("탈퇴", "회원탈퇴"):
command_list = ["탈퇴", "회원탈퇴"]
command_list.remove(command)
embed = discord.Embed(title="탈퇴", description="「탈퇴확인」를 입력해 데이터 베이스에서 자신의 자산정보를 삭제합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".탈퇴 [확인문구]", value="확인문구에는 「탈퇴확인」를 입력해 주세요.")
await ctx.reply(embed=embed)
return
elif command in ("개인설정", "설정"):
command_list = ["개인설정", "설정"]
command_list.remove(command)
embed = discord.Embed(title="개인설정", description="개인설정을 확인 또는 수정합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".개인설정 설정정보", value="설정할 수 있는 목록을 확인합니다.", inline=False)
embed.add_field(name=".개인설정 자산정보 [true | false]", value="자산정보 공개여부를 설정합니다.", inline=False)
embed.add_field(name=".개인설정 지원금표시 [true | false]", value="지원금으로 얻은 돈 표시여부를 설정합니다.", inline=False)
embed.add_field(name=".개인설정 차트표시 [true | false]", value="`주가` 명령어에 차트를 표시합니다.", inline=False)
embed.add_field(name=".개인설정 쿨타임표시 [true | false]", value="`지원금` 명령어에 쿨타임을 바로 표시합니다.", inline=False)
embed.add_field(name=".개인설정 어제대비가격 [true | false]", value="`자산정보` 명령어에 현재 주가 대신, 어제 대비 가격을 표시합니다.", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("단축어설정", "단축어"):
command_list = ["단축어설정", "단축어"]
command_list.remove(command)
embed = discord.Embed(title="단축어설정", description="단축어목록을 확인하거나, 추가 또는 제거합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".단축어설정 목록", value="자신의 단축어 목록을 확인합니다.", inline=False)
embed.add_field(name=".단축어설정 추가 -이름 [기업이름] -번호 [기업번호]", value="단축어 목록에 단축어를 새로 추가합니다.\n\
사용 예: `.단축어 추가 -이름 삼전 -번호 005930`", inline=False)
embed.add_field(name=".단축어설정 추가 -번호 [기업번호]", value="단축어 목록에 단축어를 새로 추가합니다.(이름은 기업이름으로 설정됩니다)\n\
사용 예: `.단축어 추가 -번호 005930`", inline=False)
embed.add_field(name=".단축어설정 제거 -이름 [기업이름]", value="단축어 목록에 있는 단축어를 제거합니다.\n\
사용 예: `.단축어 제거 -이름 삼전`", inline=False)
await ctx.reply(embed=embed)
return
elif command in ("관심종목", "관심"):
command_list = ["관심종목", "관심"]
command_list.remove(command)
embed = discord.Embed(title="관심종목", description="관심종목에 추가된 주식의 가격을 확인하거나, 추가 또는 제거합니다.", color=RandomEmbedColor())
embed.add_field(name="다른이름", value=f"{', '.join(command_list)}", inline=False)
embed.add_field(name=".관심종목 주가", value="관심종목에 추가된 주식의 주가를 나열합니다.", inline=False)
embed.add_field(name=".관심종목 추가", value="관심종목에 주식을 추가합니다.", inline=False)
embed.add_field(name=".관심종목 제거", value="관심종목에서 주식을 제거합니다.", inline=False)
await ctx.reply(embed=embed)
return
else:
await ctx.reply("알 수 없는 명령어 입니다.")
return
def setup(bot: commands.Bot):
bot.add_cog(HelpCommand_Context(bot)) | [((13, 5, 13, 67), 'discord.ext.commands.command', 'commands.command', (), '', False, 'from discord.ext import commands\n')] |
SupermeLC/PyNeval | test/test_model/cprofile_test.py | 2cccfb1af7d97857454e9cbc3515ba75e5d8d4b0 | import cProfile
import pstats
import os
# 性能分析装饰器定义
def do_cprofile(filename):
"""
Decorator for function profiling.
"""
def wrapper(func):
def profiled_func(*args, **kwargs):
# Flag for do profiling or not.
DO_PROF = False
if DO_PROF:
profile = cProfile.Profile()
profile.enable()
result = func(*args, **kwargs)
profile.disable()
# Sort stat by internal time.
sortby = "tottime"
ps = pstats.Stats(profile).sort_stats(sortby)
ps.dump_stats(filename)
else:
result = func(*args, **kwargs)
return result
return profiled_func
return wrapper | [((16, 26, 16, 44), 'cProfile.Profile', 'cProfile.Profile', ({}, {}), '()', False, 'import cProfile\n'), ((22, 21, 22, 42), 'pstats.Stats', 'pstats.Stats', ({(22, 34, 22, 41): 'profile'}, {}), '(profile)', False, 'import pstats\n')] |
cyberhck/renku-python | renku/core/commands/providers/api.py | 2e52dff9dd627c93764aadb9fd1e91bd190a5de7 | # Copyright 2019 - Swiss Data Science Center (SDSC)
# A partnership between École Polytechnique Fédérale de Lausanne (EPFL) and
# Eidgenössische Technische Hochschule Zürich (ETHZ).
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""API for providers."""
import abc
class ProviderApi(abc.ABC):
"""Interface defining provider methods."""
@abc.abstractmethod
def find_record(self, uri):
"""Find record by uri."""
pass
@abc.abstractmethod
def get_exporter(self, dataset, secret):
"""Get export manager."""
pass
@staticmethod
@abc.abstractmethod
def supports(uri):
"""Whether or not this provider supports a given uri."""
pass
class ExporterApi(abc.ABC):
"""Interface defining exporter methods."""
@abc.abstractmethod
def set_access_token(self, access_token):
"""Set access token."""
pass
@abc.abstractmethod
def access_token_url(self):
"""Endpoint for creation of access token."""
pass
@abc.abstractmethod
def export(self, publish):
"""Execute export process."""
pass
| [] |
bluetech/cattrs | cattr/__init__.py | be438d5566bd308b584359a9b0011a7bd0006b06 | # -*- coding: utf-8 -*-
from .converters import Converter, UnstructureStrategy
__all__ = ('global_converter', 'unstructure', 'structure',
'structure_attrs_fromtuple', 'structure_attrs_fromdict',
'UnstructureStrategy')
__author__ = 'Tin Tvrtković'
__email__ = '[email protected]'
global_converter = Converter()
unstructure = global_converter.unstructure
structure = global_converter.structure
structure_attrs_fromtuple = global_converter.structure_attrs_fromtuple
structure_attrs_fromdict = global_converter.structure_attrs_fromdict
register_structure_hook = global_converter.register_structure_hook
register_structure_hook_func = global_converter.register_structure_hook_func
register_unstructure_hook = global_converter.register_unstructure_hook
register_unstructure_hook_func = \
global_converter.register_unstructure_hook_func
| [] |
zjzh/vega | vega/security/run_dask.py | aa6e7b8c69024262fc483ee06113b4d1bd5156d8 | # -*- coding: utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Run dask scheduler and worker."""
import os
import subprocess
import shutil
import logging
import socket
import random
from distributed import Client
from distributed.security import Security
from .conf import get_config
from .verify_cert import verify_cert
sec_cfg = get_config('server')
def get_client_security(address):
"""Get client."""
address = address.replace("tcp", "tls")
if not verify_cert(sec_cfg.ca_cert, sec_cfg.client_cert_dask):
logging.error(f"The cert {sec_cfg.ca_cert} and {sec_cfg.client_cert_dask} are invalid, please check.")
sec = Security(tls_ca_file=sec_cfg.ca_cert,
tls_client_cert=sec_cfg.client_cert_dask,
tls_client_key=sec_cfg.client_secret_key_dask,
require_encryption=True)
return Client(address, security=sec)
def get_address_security(master_host, master_port):
"""Get address."""
return "tls://{}:{}".format(master_host, master_port)
def run_scheduler_security(ip, port, tmp_file):
"""Run scheduler."""
if not verify_cert(sec_cfg.ca_cert, sec_cfg.server_cert_dask):
logging.error(f"The cert {sec_cfg.ca_cert} and {sec_cfg.server_cert_dask} are invalid, please check.")
return subprocess.Popen(
[
"dask-scheduler",
"--no-dashboard",
"--no-show",
f"--tls-ca-file={sec_cfg.ca_cert}",
f"--tls-cert={sec_cfg.server_cert_dask}",
f"--tls-key={sec_cfg.server_secret_key_dask}",
f"--host={ip}",
"--protocol=tls",
f"--port={port}",
f"--scheduler-file={tmp_file}",
f"--local-directory={os.path.dirname(tmp_file)}",
],
env=os.environ
)
def _available_port(min_port, max_port) -> int:
_sock = socket.socket()
while True:
port = random.randint(min_port, max_port)
try:
_sock.bind(('', port))
_sock.close()
return port
except Exception:
logging.debug('Failed to get available port, continue.')
continue
return None
def run_local_worker_security(slave_ip, address, local_dir):
"""Run dask-worker on local node."""
address = address.replace("tcp", "tls")
nanny_port = _available_port(30000, 30999)
worker_port = _available_port(29000, 29999)
pid = subprocess.Popen(
[
"dask-worker",
address,
'--nthreads=1',
'--nprocs=1',
'--memory-limit=0',
f"--local-directory={local_dir}",
f"--tls-ca-file={sec_cfg.ca_cert}",
f"--tls-cert={sec_cfg.client_cert_dask}",
f"--tls-key={sec_cfg.client_secret_key_dask}",
"--no-dashboard",
f"--host={slave_ip}",
"--protocol=tls",
f"--nanny-port={nanny_port}",
f"--worker-port={worker_port}",
],
env=os.environ
)
return pid
def run_remote_worker_security(slave_ip, address, local_dir):
"""Run dask-worker on remote node."""
address = address.replace("tcp", "tls")
nanny_port = _available_port(30000, 30999)
worker_port = _available_port(29000, 29999)
pid = subprocess.Popen(
[
"ssh",
slave_ip,
shutil.which("dask-worker"),
address,
'--nthreads=1',
'--nprocs=1',
'--memory-limit=0',
f"--local-directory={local_dir}",
f"--tls-ca-file={sec_cfg.ca_cert}",
f"--tls-cert={sec_cfg.client_cert_dask}",
f"--tls-key={sec_cfg.client_secret_key_dask}",
"--no-dashboard",
f"--host={slave_ip}",
"--protocol=tls",
f"--nanny-port={nanny_port}",
f"--worker-port={worker_port}",
],
env=os.environ
)
return pid
| [((38, 10, 41, 43), 'distributed.security.Security', 'Security', (), '', False, 'from distributed.security import Security\n'), ((42, 11, 42, 40), 'distributed.Client', 'Client', (), '', False, 'from distributed import Client\n'), ((73, 12, 73, 27), 'socket.socket', 'socket.socket', ({}, {}), '()', False, 'import socket\n'), ((91, 10, 109, 5), 'subprocess.Popen', 'subprocess.Popen', (), '', False, 'import subprocess\n'), ((37, 8, 37, 110), 'logging.error', 'logging.error', ({(37, 22, 37, 109): 'f"""The cert {sec_cfg.ca_cert} and {sec_cfg.client_cert_dask} are invalid, please check."""'}, {}), "(\n f'The cert {sec_cfg.ca_cert} and {sec_cfg.client_cert_dask} are invalid, please check.'\n )", False, 'import logging\n'), ((53, 8, 53, 110), 'logging.error', 'logging.error', ({(53, 22, 53, 109): 'f"""The cert {sec_cfg.ca_cert} and {sec_cfg.server_cert_dask} are invalid, please check."""'}, {}), "(\n f'The cert {sec_cfg.ca_cert} and {sec_cfg.server_cert_dask} are invalid, please check.'\n )", False, 'import logging\n'), ((75, 15, 75, 49), 'random.randint', 'random.randint', ({(75, 30, 75, 38): 'min_port', (75, 40, 75, 48): 'max_port'}, {}), '(min_port, max_port)', False, 'import random\n'), ((122, 12, 122, 39), 'shutil.which', 'shutil.which', ({(122, 25, 122, 38): '"""dask-worker"""'}, {}), "('dask-worker')", False, 'import shutil\n'), ((81, 12, 81, 68), 'logging.debug', 'logging.debug', ({(81, 26, 81, 67): '"""Failed to get available port, continue."""'}, {}), "('Failed to get available port, continue.')", False, 'import logging\n'), ((66, 33, 66, 58), 'os.path.dirname', 'os.path.dirname', ({(66, 49, 66, 57): 'tmp_file'}, {}), '(tmp_file)', False, 'import os\n')] |
NoaBrazilay/DeepLearningProject | MISSGANvsStarGAN/core/solver.py | 5c44d21069de1fc5fa2687c4121286670be3d773 | """
StarGAN v2
Copyright (c) 2020-present NAVER Corp.
This work is licensed under the Creative Commons Attribution-NonCommercial
4.0 International License. To view a copy of this license, visit
http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
"""
import os
from os.path import join as ospj
import time
import datetime
from munch import Munch
import torch
import torch.nn as nn
import torch.nn.functional as F
from core.model import build_model
from core.checkpoint import CheckpointIO
from core.data_loader import InputFetcher
import core.utils as utils
from metrics.eval import calculate_metrics
class Solver(nn.Module):
def __init__(self, args):
super().__init__()
self.args = args
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
self.nets, self.nets_ema, self.vgg, self.VggExtract = build_model(args)
self.instancenorm = nn.InstanceNorm2d(512, affine=False)
self.L1Loss = nn.L1Loss()
# below setattrs are to make networks be children of Solver, e.g., for self.to(self.device)
for name, module in self.nets.items():
utils.print_network(module, name)
setattr(self, name, module)
for name, module in self.nets_ema.items():
setattr(self, name + '_ema', module)
if args.mode == 'train':
self.optims = Munch()
for net in self.nets.keys():
if net == 'fan':
continue
self.optims[net] = torch.optim.Adam(
params=self.nets[net].parameters(),
lr=args.f_lr if net == 'mapping_network' else args.lr,
betas=[args.beta1, args.beta2],
weight_decay=args.weight_decay)
self.ckptios = [CheckpointIO(ospj(args.checkpoint_dir, '100000_nets.ckpt'), **self.nets),
CheckpointIO(ospj(args.checkpoint_dir, '100000_nets_ema.ckpt'), **self.nets_ema),
CheckpointIO(ospj(args.checkpoint_dir, '100000_optims.ckpt'), **self.optims)]
else:
self.ckptios = [CheckpointIO(ospj(args.checkpoint_dir, '100000_nets_ema.ckpt'), **self.nets_ema)]
self.to(self.device)
for name, network in self.named_children():
# Do not initialize the FAN parameters
if ('ema' not in name) and ('fan' not in name):
print('Initializing %s...' % name)
network.apply(utils.he_init)
def _save_checkpoint(self, step):
for ckptio in self.ckptios:
ckptio.save(step)
def _load_checkpoint(self, step):
for ckptio in self.ckptios:
ckptio.load(step)
def _reset_grad(self):
for optim in self.optims.values():
optim.zero_grad()
def train(self, loaders):
args = self.args
nets = self.nets
nets_ema = self.nets_ema
optims = self.optims
# fetch random validation images for debugging
fetcher = InputFetcher(loaders.src, loaders.ref, args.latent_dim, 'train')
fetcher_val = InputFetcher(loaders.val, None, args.latent_dim, 'val')
inputs_val = next(fetcher_val)
# resume training if necessary
if args.resume_iter > 0:
self._load_checkpoint(args.resume_iter)
# remember the initial value of ds weight
initial_lambda_ds = args.lambda_ds
print('Start training...')
start_time = time.time()
for i in range(args.resume_iter, args.total_iters):
# fetch images and labels
inputs = next(fetcher)
x_real, y_org = inputs.x_src, inputs.y_src
x_ref, x_ref2, y_trg = inputs.x_ref, inputs.x_ref2, inputs.y_ref
z_trg, z_trg2 = inputs.z_trg, inputs.z_trg2
masks = nets.fan.get_heatmap(x_real) if args.w_hpf > 0 else None
# train the discriminator
d_loss, d_losses_latent = compute_d_loss(
nets, args, x_real, y_org, y_trg, z_trg=z_trg, masks=masks)
self._reset_grad()
d_loss.backward()
optims.discriminator.step()
d_loss, d_losses_ref = compute_d_loss(
nets, args, x_real, y_org, y_trg, x_ref=x_ref, masks=masks)
self._reset_grad()
d_loss.backward()
optims.discriminator.step()
# train the generator
g_loss, g_losses_latent = compute_g_loss(
nets, args, x_real, y_org, y_trg, z_trgs=[z_trg, z_trg2], masks=masks,VggExtract=self.VggExtract, IN = self.instancenorm, L1Loss=self.L1Loss)
self._reset_grad()
g_loss.backward()
optims.generator.step()
optims.mapping_network.step()
optims.style_encoder.step()
g_loss, g_losses_ref = compute_g_loss(
nets, args, x_real, y_org, y_trg, x_refs=[x_ref, x_ref2], masks=masks, VggExtract=self.VggExtract, IN = self.instancenorm, L1Loss=self.L1Loss)
self._reset_grad()
g_loss.backward()
optims.generator.step()
# compute moving average of network parameters
moving_average(nets.generator, nets_ema.generator, beta=0.999)
moving_average(nets.mapping_network, nets_ema.mapping_network, beta=0.999)
moving_average(nets.style_encoder, nets_ema.style_encoder, beta=0.999)
# decay weight for diversity sensitive loss
if args.lambda_ds > 0:
args.lambda_ds -= (initial_lambda_ds / args.ds_iter)
# print out log info
if (i+1) % args.print_every == 0:
elapsed = time.time() - start_time
elapsed = str(datetime.timedelta(seconds=elapsed))[:-7]
log = "Elapsed time [%s], Iteration [%i/%i], " % (elapsed, i+1, args.total_iters)
all_losses = dict()
for loss, prefix in zip([d_losses_latent, d_losses_ref, g_losses_latent, g_losses_ref],
['D/latent_', 'D/ref_', 'G/latent_', 'G/ref_']):
for key, value in loss.items():
all_losses[prefix + key] = value
all_losses['G/lambda_ds'] = args.lambda_ds
log += ' '.join(['%s: [%.4f]' % (key, value) for key, value in all_losses.items()])
print(log)
# generate images for debugging
if (i+1) % args.sample_every == 0:
os.makedirs(args.sample_dir, exist_ok=True)
utils.debug_image(nets_ema, args, inputs=inputs_val, step=i+1)
# save model checkpoints
if (i+1) % args.save_every == 0:
self._save_checkpoint(step=i+1)
# compute FID and LPIPS if necessary
if (i+1) % args.eval_every == 0:
calculate_metrics(nets_ema, args, i+1, mode='latent')
calculate_metrics(nets_ema, args, i+1, mode='reference')
@torch.no_grad()
def sample(self, loaders):
args = self.args
nets_ema = self.nets_ema
os.makedirs(args.result_dir, exist_ok=True)
self._load_checkpoint(args.resume_iter)
src = next(InputFetcher(loaders.src, None, args.latent_dim, 'test'))
ref = next(InputFetcher(loaders.ref, None, args.latent_dim, 'test'))
fname = ospj(args.result_dir, 'reference.jpg')
print('Working on {}...'.format(fname))
utils.translate_using_reference(nets_ema, args, src.x, ref.x, ref.y, fname)
# fname = ospj(args.result_dir, 'video_ref.mp4')
# print('Working on {}...'.format(fname))
# utils.video_ref(nets_ema, args, src.x, ref.x, ref.y, fname)
@torch.no_grad()
def evaluate(self):
args = self.args
nets_ema = self.nets_ema
resume_iter = args.resume_iter
self._load_checkpoint(args.resume_iter)
calculate_metrics(nets_ema, args, step=resume_iter, mode='latent')
calculate_metrics(nets_ema, args, step=resume_iter, mode='reference')
def compute_d_loss(nets, args, x_real, y_org, y_trg, z_trg=None, x_ref=None, masks=None):
assert (z_trg is None) != (x_ref is None)
# with real images
x_real.requires_grad_()
out = nets.discriminator(x_real, y_org)
loss_real = adv_loss(out, 1)
loss_reg = r1_reg(out, x_real)
# with fake images
with torch.no_grad():
if z_trg is not None:
s_trg = nets.mapping_network(z_trg, y_trg)
else: # x_ref is not None
s_trg = nets.style_encoder(x_ref, y_trg)
x_fake,_ = nets.generator(x_real, s_trg, masks=masks)
out = nets.discriminator(x_fake, y_trg)
loss_fake = adv_loss(out, 0)
loss = loss_real + loss_fake + args.lambda_reg * loss_reg
return loss, Munch(real=loss_real.item(),
fake=loss_fake.item(),
reg=loss_reg.item())
def compute_g_loss(nets, args, x_real, y_org, y_trg, z_trgs=None, x_refs=None, masks=None, VggExtract= None, IN= None, L1Loss=None):
assert (z_trgs is None) != (x_refs is None)
if z_trgs is not None:
z_trg, z_trg2 = z_trgs
if x_refs is not None:
x_ref, x_ref2 = x_refs
# adversarial loss
if z_trgs is not None:
s_trg = nets.mapping_network(z_trg, y_trg)
else:
s_trg = nets.style_encoder(x_ref, y_trg)
x_fake, content_latent_real = nets.generator(x_real, s_trg, masks=masks)
out = nets.discriminator(x_fake, y_trg)
loss_adv = adv_loss(out, 1)
# style reconstruction loss
s_pred = nets.style_encoder(x_fake, y_trg)
loss_sty = torch.mean(torch.abs(s_pred - s_trg))
# diversity sensitive loss
if z_trgs is not None:
s_trg2 = nets.mapping_network(z_trg2, y_trg)
else:
s_trg2 = nets.style_encoder(x_ref2, y_trg)
x_fake2, content_latent_real2 = nets.generator(x_real, s_trg2, masks=masks)
x_fake2 = x_fake2.detach()
loss_ds = torch.mean(torch.abs(x_fake - x_fake2))
# cycle-consistency loss
masks = nets.fan.get_heatmap(x_fake) if args.w_hpf > 0 else None
s_org = nets.style_encoder(x_real, y_org)
x_rec, content_latent_reco = nets.generator(x_fake, s_org, masks=masks)
loss_cyc = torch.mean(torch.abs(x_rec - x_real))
loss_vgg = compute_vgg_loss(x_fake, x_real, VggExtract, IN, L1Loss) if args.vgg_w > 0 else 0
loss_sacl = utils.abs_criterion(content_latent_real, content_latent_reco) if args.loss_sacl > 0 else 0 # Loss style aware content loss
loss_sacl2 = utils.abs_criterion(content_latent_real2, content_latent_reco) if args.loss_sacl > 0 else 0 # Loss style aware content loss
loss = loss_adv + args.lambda_sty * loss_sty \
- args.lambda_ds * loss_ds + args.lambda_cyc * loss_cyc + args.lambda_vgg * loss_vgg + args.lambda_loss_sacl * loss_sacl+ args.lambda_loss_sacl * loss_sacl2
return loss, Munch(adv=loss_adv.item(),
sty=loss_sty.item(),
ds=loss_ds.item(),
cyc=loss_cyc.item())
def moving_average(model, model_test, beta=0.999):
for param, param_test in zip(model.parameters(), model_test.parameters()):
param_test.data = torch.lerp(param.data, param_test.data, beta)
def adv_loss(logits, target):
assert target in [1, 0]
targets = torch.full_like(logits, fill_value=target)
loss = F.binary_cross_entropy_with_logits(logits, targets)
return loss
def compute_vgg_loss(img, target, VggExtract, IN, L1Loss):
# img_vgg = utils.vgg_preprocess(img)
# target_vgg = utils.vgg_preprocess(target)
# img_fea = vgg(img_vgg)
# target_fea = vgg(target_vgg)
img_fea_dict = VggExtract(img)
target_fea_dict = VggExtract(target)
# loss = torch.mean((img_fea_dict['relu3_3'] - target_fea_dict['relu3_3']) ** 2)
# loss = torch.mean(torch.abs(img_fea_dict['relu3_3'] - target_fea_dict['relu3_3']))
loss = L1Loss(img_fea_dict['relu2_2'] , target_fea_dict['relu2_2'])
return loss
def r1_reg(d_out, x_in):
# zero-centered gradient penalty for real images
batch_size = x_in.size(0)
grad_dout = torch.autograd.grad(
outputs=d_out.sum(), inputs=x_in,
create_graph=True, retain_graph=True, only_inputs=True
)[0]
grad_dout2 = grad_dout.pow(2)
assert(grad_dout2.size() == x_in.size())
reg = 0.5 * grad_dout2.view(batch_size, -1).sum(1).mean(0)
return reg | [((174, 5, 174, 20), 'torch.no_grad', 'torch.no_grad', ({}, {}), '()', False, 'import torch\n'), ((192, 5, 192, 20), 'torch.no_grad', 'torch.no_grad', ({}, {}), '()', False, 'import torch\n'), ((282, 14, 282, 56), 'torch.full_like', 'torch.full_like', (), '', False, 'import torch\n'), ((283, 11, 283, 62), 'torch.nn.functional.binary_cross_entropy_with_logits', 'F.binary_cross_entropy_with_logits', ({(283, 46, 283, 52): 'logits', (283, 54, 283, 61): 'targets'}, {}), '(logits, targets)', True, 'import torch.nn.functional as F\n'), ((34, 62, 34, 79), 'core.model.build_model', 'build_model', ({(34, 74, 34, 78): 'args'}, {}), '(args)', False, 'from core.model import build_model\n'), ((35, 28, 35, 64), 'torch.nn.InstanceNorm2d', 'nn.InstanceNorm2d', (), '', True, 'import torch.nn as nn\n'), ((36, 22, 36, 33), 'torch.nn.L1Loss', 'nn.L1Loss', ({}, {}), '()', True, 'import torch.nn as nn\n'), ((87, 18, 87, 82), 'core.data_loader.InputFetcher', 'InputFetcher', ({(87, 31, 87, 42): 'loaders.src', (87, 44, 87, 55): 'loaders.ref', (87, 57, 87, 72): 'args.latent_dim', (87, 74, 87, 81): '"""train"""'}, {}), "(loaders.src, loaders.ref, args.latent_dim, 'train')", False, 'from core.data_loader import InputFetcher\n'), ((88, 22, 88, 77), 'core.data_loader.InputFetcher', 'InputFetcher', ({(88, 35, 88, 46): 'loaders.val', (88, 48, 88, 52): 'None', (88, 54, 88, 69): 'args.latent_dim', (88, 71, 88, 76): '"""val"""'}, {}), "(loaders.val, None, args.latent_dim, 'val')", False, 'from core.data_loader import InputFetcher\n'), ((99, 21, 99, 32), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((178, 8, 178, 51), 'os.makedirs', 'os.makedirs', (), '', False, 'import os\n'), ((184, 16, 184, 54), 'os.path.join', 'ospj', ({(184, 21, 184, 36): 'args.result_dir', (184, 38, 184, 53): '"""reference.jpg"""'}, {}), "(args.result_dir, 'reference.jpg')", True, 'from os.path import join as ospj\n'), ((186, 8, 186, 83), 'core.utils.translate_using_reference', 'utils.translate_using_reference', ({(186, 40, 186, 48): 'nets_ema', (186, 50, 186, 54): 'args', (186, 56, 186, 61): 'src.x', (186, 63, 186, 68): 'ref.x', (186, 70, 186, 75): 'ref.y', (186, 77, 186, 82): 'fname'}, {}), '(nets_ema, args, src.x, ref.x, ref.y, fname)', True, 'import core.utils as utils\n'), ((198, 8, 198, 74), 'metrics.eval.calculate_metrics', 'calculate_metrics', (), '', False, 'from metrics.eval import calculate_metrics\n'), ((199, 8, 199, 77), 'metrics.eval.calculate_metrics', 'calculate_metrics', (), '', False, 'from metrics.eval import calculate_metrics\n'), ((211, 9, 211, 24), 'torch.no_grad', 'torch.no_grad', ({}, {}), '()', False, 'import torch\n'), ((246, 26, 246, 51), 'torch.abs', 'torch.abs', ({(246, 36, 246, 50): 's_pred - s_trg'}, {}), '(s_pred - s_trg)', False, 'import torch\n'), ((255, 25, 255, 52), 'torch.abs', 'torch.abs', ({(255, 35, 255, 51): 'x_fake - x_fake2'}, {}), '(x_fake - x_fake2)', False, 'import torch\n'), ((261, 26, 261, 51), 'torch.abs', 'torch.abs', ({(261, 36, 261, 50): 'x_rec - x_real'}, {}), '(x_rec - x_real)', False, 'import torch\n'), ((264, 16, 264, 78), 'core.utils.abs_criterion', 'utils.abs_criterion', ({(264, 36, 264, 55): 'content_latent_real', (264, 58, 264, 77): 'content_latent_reco'}, {}), '(content_latent_real, content_latent_reco)', True, 'import core.utils as utils\n'), ((265, 17, 265, 80), 'core.utils.abs_criterion', 'utils.abs_criterion', ({(265, 37, 265, 57): 'content_latent_real2', (265, 60, 265, 79): 'content_latent_reco'}, {}), '(content_latent_real2, content_latent_reco)', True, 'import core.utils as utils\n'), ((277, 26, 277, 71), 'torch.lerp', 'torch.lerp', ({(277, 37, 277, 47): 'param.data', (277, 49, 277, 64): 'param_test.data', (277, 66, 277, 70): 'beta'}, {}), '(param.data, param_test.data, beta)', False, 'import torch\n'), ((39, 12, 39, 45), 'core.utils.print_network', 'utils.print_network', ({(39, 32, 39, 38): 'module', (39, 40, 39, 44): 'name'}, {}), '(module, name)', True, 'import core.utils as utils\n'), ((45, 26, 45, 33), 'munch.Munch', 'Munch', ({}, {}), '()', False, 'from munch import Munch\n'), ((181, 19, 181, 75), 'core.data_loader.InputFetcher', 'InputFetcher', ({(181, 32, 181, 43): 'loaders.src', (181, 45, 181, 49): 'None', (181, 51, 181, 66): 'args.latent_dim', (181, 68, 181, 74): '"""test"""'}, {}), "(loaders.src, None, args.latent_dim, 'test')", False, 'from core.data_loader import InputFetcher\n'), ((182, 19, 182, 75), 'core.data_loader.InputFetcher', 'InputFetcher', ({(182, 32, 182, 43): 'loaders.ref', (182, 45, 182, 49): 'None', (182, 51, 182, 66): 'args.latent_dim', (182, 68, 182, 74): '"""test"""'}, {}), "(loaders.ref, None, args.latent_dim, 'test')", False, 'from core.data_loader import InputFetcher\n'), ((32, 45, 32, 70), 'torch.cuda.is_available', 'torch.cuda.is_available', ({}, {}), '()', False, 'import torch\n'), ((162, 16, 162, 59), 'os.makedirs', 'os.makedirs', (), '', False, 'import os\n'), ((163, 16, 163, 78), 'core.utils.debug_image', 'utils.debug_image', (), '', True, 'import core.utils as utils\n'), ((171, 16, 171, 69), 'metrics.eval.calculate_metrics', 'calculate_metrics', (), '', False, 'from metrics.eval import calculate_metrics\n'), ((172, 16, 172, 72), 'metrics.eval.calculate_metrics', 'calculate_metrics', (), '', False, 'from metrics.eval import calculate_metrics\n'), ((55, 41, 55, 86), 'os.path.join', 'ospj', ({(55, 46, 55, 65): 'args.checkpoint_dir', (55, 67, 55, 85): '"""100000_nets.ckpt"""'}, {}), "(args.checkpoint_dir, '100000_nets.ckpt')", True, 'from os.path import join as ospj\n'), ((56, 29, 56, 78), 'os.path.join', 'ospj', ({(56, 34, 56, 53): 'args.checkpoint_dir', (56, 55, 56, 77): '"""100000_nets_ema.ckpt"""'}, {}), "(args.checkpoint_dir, '100000_nets_ema.ckpt')", True, 'from os.path import join as ospj\n'), ((57, 29, 57, 76), 'os.path.join', 'ospj', ({(57, 34, 57, 53): 'args.checkpoint_dir', (57, 55, 57, 75): '"""100000_optims.ckpt"""'}, {}), "(args.checkpoint_dir, '100000_optims.ckpt')", True, 'from os.path import join as ospj\n'), ((59, 41, 59, 90), 'os.path.join', 'ospj', ({(59, 46, 59, 65): 'args.checkpoint_dir', (59, 67, 59, 89): '"""100000_nets_ema.ckpt"""'}, {}), "(args.checkpoint_dir, '100000_nets_ema.ckpt')", True, 'from os.path import join as ospj\n'), ((148, 26, 148, 37), 'time.time', 'time.time', ({}, {}), '()', False, 'import time\n'), ((149, 30, 149, 65), 'datetime.timedelta', 'datetime.timedelta', (), '', False, 'import datetime\n')] |
vishweshwartyagi/Data-Structures-and-Algorithms-UCSD | 1. Algorithmic Toolbox/week2_algorithmic_warmup/4_lcm.py | de942b3a0eb2bf56f949f47c297fad713aa81489 | # Uses python3
import sys
def lcm_naive(a, b):
for l in range(1, a*b + 1):
if l % a == 0 and l % b == 0:
return l
return a*b
def gcd(a, b):
if a%b == 0:
return b
elif b%a == 0:
return a
if a > b:
return gcd(a%b, b)
else:
return gcd(b%a, a)
def lcm(a, b):
return int((a*b) / gcd(a, b))
if __name__ == '__main__':
# input = sys.stdin.read()
a, b = map(int, input().split())
# print(lcm_naive(a, b))
print(lcm(a, b))
| [] |
JoviCastillo/TH-Project-1-guessing-game- | guessing_game.py | efa5c7080b1a484b20655ddb01873dc3edefc415 | import random
highscore = []
def not_in_range(guess_it):
"""This is to check that the numbers inputted by the user are in range,
and will let the user know. If the numbers are in range then it passes.
"""
if guess_it < 1:
print('I am not thinking of negative numbers!')
elif guess_it > 10:
print('That number is way bigger than 10!')
else:
pass
def new_game(tries):
"""After the user has guessed the number correctly, the game
will ask the player if they would like to play again. Yes will start
the game again. No will exit the game. Highscore will be displayed
by the lowest amount of tries recorded.
"""
play_again = input('Would you like to play again? (Yes/No) ')
if play_again.upper() == 'YES':
highscore.append(tries)
highscore.sort
print('The highscore is {}.'.format(highscore[0]))
start_game()
elif play_again.upper() == 'NO':
exit()
else:
play_again = input('Please let me know by typing yes or no: ')
def start_game(): # title screen of the game
"""This is the start of the game which include the title screen and
is the main function that runs all the other functions as well.
"""
print('-' * 40)
print('Welcome to the Number Guessing Game!!!')
print('-' * 40)
print('I am thinking of a number between 1-10.')
random_number = random.randint(1, 10)
tries = 0
while True:
try:
guess_it = int(input('Can you guess it?: '))
except ValueError:
print('I said number, not gibberish!')
else:
while guess_it != random_number:
not_in_range(guess_it)
tries += 1
if guess_it > random_number:
print('That is too high!')
elif guess_it < random_number:
print('That is too low')
break
else:
print('You guessed it right! Your number was {}.'.format(random_number))
print('It took you {} tries.'.format(tries))
break
new_game(tries)
if __name__ == '__main__':
# Kick off the program by calling the start_game function.
start_game()
| [((44, 20, 44, 41), 'random.randint', 'random.randint', ({(44, 35, 44, 36): '1', (44, 38, 44, 40): '10'}, {}), '(1, 10)', False, 'import random\n')] |
dastacy/gve_devnet_unity_unread_voicemail_notifier | MAIL_SERVER.py | 445177d1107e465d90971d3d6ebb3249c5ed7b29 | #!/usr/bin/env python3
USER = r'server\user'
PASSWORD = 'server_password'
HOSTNAME = 'hostname.goes.here.com'
DOMAIN = 'domain.goes.here.com'
FROM_ADDR = '[email protected]'
| [] |
anetczuk/rsscast | src/testrsscast/rss/ytconverter_example.py | 8649d1143679afcabbe19e5499f104fa1325bff1 | #!/usr/bin/python3
#
# MIT License
#
# Copyright (c) 2021 Arkadiusz Netczuk <[email protected]>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
#
try:
## following import success only when file is directly executed from command line
## otherwise will throw exception when executing as parameter for "python -m"
# pylint: disable=W0611
import __init__
except ImportError as error:
## when import fails then it means that the script was executed indirectly
## in this case __init__ is already loaded
pass
import sys
import argparse
import rsscast.logger as logger
from rsscast.rss.ytconverter import convert_yt
if __name__ != '__main__':
sys.exit(0)
parser = argparse.ArgumentParser(description='YouTube convert example')
args = parser.parse_args()
logger.configure_console()
converted = convert_yt( "https://www.youtube.com/watch?v=BLRUiVXeZKU", "/tmp/yt_example.mp3" )
print("converted:", converted)
| [((47, 9, 47, 71), 'argparse.ArgumentParser', 'argparse.ArgumentParser', (), '', False, 'import argparse\n'), ((52, 0, 52, 26), 'rsscast.logger.configure_console', 'logger.configure_console', ({}, {}), '()', True, 'import rsscast.logger as logger\n'), ((55, 12, 55, 94), 'rsscast.rss.ytconverter.convert_yt', 'convert_yt', ({(55, 24, 55, 69): '"""https://www.youtube.com/watch?v=BLRUiVXeZKU"""', (55, 71, 55, 92): '"""/tmp/yt_example.mp3"""'}, {}), "('https://www.youtube.com/watch?v=BLRUiVXeZKU', '/tmp/yt_example.mp3'\n )", False, 'from rsscast.rss.ytconverter import convert_yt\n'), ((44, 4, 44, 15), 'sys.exit', 'sys.exit', ({(44, 13, 44, 14): '(0)'}, {}), '(0)', False, 'import sys\n')] |
palazzem/elmo-server | cli.py | b2e02d600a431dc1db31090f0d8dd09a8d586373 | import click
APP_YAML_TEMPLATE = """runtime: python37
env_variables:
ELMO_BASE_URL: '{BASE_URL}'
ELMO_VENDOR: '{VENDOR}'
handlers:
- url: /.*
script: auto
secure: always
redirect_http_response_code: 301
"""
@click.command()
@click.argument("base_url")
@click.argument("vendor")
def generate_app_yaml(base_url, vendor):
"""Use APP_YAML_TEMPLATE to generate app.yaml for AppEngine deployments.
Args:
base_url: defines ELMO_BASE_URL env variable in AppEngine config.
vendor: defines ELMO_VENDOR env variable in AppEngine config.
Returns:
Writes `app.yaml` file in the current folder.
"""
print("Writing the following deployment config to disk:")
app_yaml = APP_YAML_TEMPLATE.format(BASE_URL=base_url, VENDOR=vendor)
print(app_yaml)
with open("app.yaml", "w") as f:
f.write(app_yaml)
print("Done! You can deploy the service with `gcloud app deploy`")
if __name__ == "__main__":
generate_app_yaml()
| [((16, 1, 16, 16), 'click.command', 'click.command', ({}, {}), '()', False, 'import click\n'), ((17, 1, 17, 27), 'click.argument', 'click.argument', ({(17, 16, 17, 26): '"""base_url"""'}, {}), "('base_url')", False, 'import click\n'), ((18, 1, 18, 25), 'click.argument', 'click.argument', ({(18, 16, 18, 24): '"""vendor"""'}, {}), "('vendor')", False, 'import click\n')] |
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