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import unirest
import time
import socket
import uuid
HOSTNAME = 'localhost'
PORT = 3000
PLOTTA_ENABLED = True
# API endpoint wrappers
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import cv2
import numpy as np
total = 0
for i in range(29):
original = cv2.imread(str(i) + "GroundTruth.png", 0)
predicted = cv2.imread(str(i) + "Prediction_Threshold.png", 0)
#print(np.shape(original))
original = original.flatten()
predicted = predicted.flatten()
original = (original>127)
predicted = (predicted>127)
#print(np.unique(predicted))
#print(np.unique(original))
print(i)
if np.sum(np.invert(original)) != 0:
sum0 = np.sum((np.invert(predicted) * np.invert(original))*1) / np.sum(np.invert(original))
else:
sum0 = 1
if np.sum(original) != 0:
sum1 = np.sum((predicted * original)*1) / np.sum(original)
else:
sum1 = 1
print("SUM: " + str( np.sum(original)))
#print("SUM: " + str( np.sum(np.invert(original))))
#print("MUL : " + str(np.sum(np.invert(original) * original)))
IoU = ((sum0 + sum1) / 2) * 100
print("IoU: " + str(sum0) + " " + str(sum1) + " " + str(IoU))
total += IoU
print(total/29)
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import psychopy.core
import psychopy.event
import psychopy.visual
import pandas as pd
import numpy as np
import psychopy.gui
import psychopy.sound
import os
import yaml
import json
from pathlib import Path
import random
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"""RAK811 CLI interface.
Provides a command line interface for the RAK811 module (Firmware V2.0).
Copyright 2019, 2021 Philippe Vanhaesendonck
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.
SPDX-License-Identifier: Apache-2.0
"""
from json import dumps
import logging
import click
from .rak811 import Mode, RecvEx, Reset
from .rak811 import Rak811
from .rak811 import Rak811Error
from .rak811 import Rak811EventError, Rak811ResponseError, Rak811TimeoutError
# Valid configuration keys for LoRaWan
LW_CONFIG_KEYS = ('dev_addr', 'dev_eui', 'app_eui', 'app_key', 'nwks_key',
'apps_key', 'tx_power', 'pwr_level', 'adr', 'dr',
'public_net', 'rx_delay1', 'ch_list', 'ch_mask', 'max_chs',
'rx2', 'join_cnt', 'nbtrans', 'retrans', 'class', 'duty')
# Valid configuration keys for LoRaP2P
P2P_CONFIG_KEYS = {
'freq': click.FloatRange(min=860.000, max=929.900, clamp=False),
'sf': click.IntRange(min=6, max=12, clamp=False),
'bw': click.IntRange(min=0, max=2, clamp=False),
'cr': click.IntRange(min=1, max=4, clamp=False),
'prlen': click.IntRange(min=8, max=65535, clamp=False),
'pwr': click.IntRange(min=5, max=20, clamp=False)
}
class KeyValueParamTypeLW(click.ParamType):
"""Basic KEY=VALUE pair parameter type for LoRaWan."""
name = 'key-value-lorawan'
class KeyValueParamTypeP2P(click.ParamType):
"""Basic KEY=VALUE pair parameter type for LoRaP2P."""
name = 'key-value-p2p'
def print_exception(e):
"""Print exception raised by the Rak811 library."""
if isinstance(e, Rak811ResponseError):
click.echo('RAK811 response error {}: {}'.format(e.errno, e.strerror))
elif isinstance(e, Rak811EventError):
click.echo('RAK811 event error {}: {}'.format(e.errno, e.strerror))
elif isinstance(e, Rak811TimeoutError):
click.echo('RAK811 timeout: {}'.format(e))
else:
click.echo('RAK811 unexpected exception {}'.format(e))
@click.group()
@click.option(
'-v',
'--verbose',
is_flag=True,
help='Verbose mode'
)
@click.option(
'-d',
'--debug',
is_flag=True,
help='Debug mode'
)
@click.version_option()
@click.pass_context
def cli(ctx, verbose, debug):
"""Command line interface for the RAK811 module."""
ctx.ensure_object(dict)
ctx.obj['VERBOSE'] = verbose
logging.basicConfig(level=logging.DEBUG if debug else logging.INFO)
@cli.command(name='hard-reset')
@click.pass_context
def hard_reset(ctx):
"""Hardware reset of the module.
Hard reset should not be required in normal operation. It needs to be
issued once after host boot, or module restart.
"""
lora = Rak811()
lora.hard_reset()
if ctx.obj['VERBOSE']:
click.echo('Hard reset complete')
lora.close()
"""System commands."""
@cli.command()
@click.pass_context
def version(ctx):
"""Get module version."""
lora = Rak811()
click.echo(lora.version)
lora.close()
@cli.command()
@click.pass_context
def sleep(ctx):
"""Enter sleep mode."""
lora = Rak811()
lora.sleep()
if ctx.obj['VERBOSE']:
click.echo('Sleeping')
lora.close()
@cli.command(name='wake-up')
@click.pass_context
def wake_up(ctx):
"""Wake up."""
lora = Rak811()
lora.wake_up()
if ctx.obj['VERBOSE']:
click.echo('Alive!')
lora.close()
@cli.command()
@click.argument(
'reset_type',
required=True,
type=click.Choice(['module', 'lora'])
)
@click.pass_context
def reset(ctx, reset_type):
"""Reset Module or LoRaWan stack."""
lora = Rak811()
if reset_type == 'module':
lora.reset(Reset.Module)
else:
lora.reset(Reset.LoRa)
if ctx.obj['VERBOSE']:
click.echo('{0} reset complete.'.format(
'Module' if reset_type == 'module' else 'LoRa'))
lora.close()
@cli.command()
@click.pass_context
def reload(ctx):
"""Set LoRaWan or LoRaP2P configurations to default."""
lora = Rak811()
lora.reload()
if ctx.obj['VERBOSE']:
click.echo('Configuration reloaded.')
lora.close()
@cli.command()
@click.argument(
'mode',
required=False,
type=click.Choice(['LoRaWan', 'LoRaP2P'], case_sensitive=False)
)
@click.pass_context
def mode(ctx, mode):
"""Get/Set mode to LoRaWan or LoRaP2P."""
lora = Rak811()
if mode is None:
click.echo('LoRaWan' if lora.mode == Mode.LoRaWan else 'LoRaP2P')
else:
mode = mode.lower()
if mode == 'lorawan':
lora.mode = Mode.LoRaWan
else:
lora.mode = Mode.LoRaP2P
if ctx.obj['VERBOSE']:
click.echo('Mode set to {0}.'.format(
'LoRaWan' if mode == 'lorawan' else 'LoRaP2P'))
lora.close()
@cli.command()
@click.argument(
'recv_ex',
required=False,
type=click.Choice(['enable', 'disable'])
)
@click.pass_context
def recv_ex(ctx, recv_ex):
"""RSSI & SNR report on receive."""
lora = Rak811()
if recv_ex is None:
click.echo('Enabled' if lora.recv_ex == RecvEx.Enabled else 'Disabled')
else:
lora.recv_ex = (
RecvEx.Enabled if recv_ex == 'enable' else RecvEx.Disabled
)
if ctx.obj['VERBOSE']:
click.echo('RSSI & SNR report on receive {0}.'.format(
'Enabled' if recv_ex == 'enable' else 'Disabled'))
lora.close()
"""LoRaWan commands."""
@cli.command()
@click.argument(
'band',
required=False,
type=click.Choice(
['EU868', 'US915', 'AU915', 'KR920', 'AS923', 'IN865'],
case_sensitive=False
)
)
@click.pass_context
def band(ctx, band):
"""Get/Set LoRaWan region."""
lora = Rak811()
if band is None:
click.echo(lora.band)
else:
band = band.upper()
lora.band = band
if ctx.obj['VERBOSE']:
click.echo('LoRaWan region set to {0}.'.format(band))
lora.close()
@cli.command()
@click.argument(
'key_values',
metavar='KEY=VALUE...',
required=True,
type=KeyValueParamTypeLW(),
nargs=-1
)
@click.pass_context
def set_config(ctx, key_values):
"""Set LoraWAN configuration.
\b
Arguments are specified as KEY=VALUE pairs, e.g.:
set-config app_eui='APP_EUI' app_key='APP_KEY'
"""
lora = Rak811()
kv_args = dict(key_values)
try:
lora.set_config(**kv_args)
if ctx.obj['VERBOSE']:
click.echo('LoRaWan parameters set')
except Rak811Error as e:
print_exception(e)
lora.close()
@cli.command()
@click.argument(
'key',
required=True,
type=click.Choice(LW_CONFIG_KEYS)
)
@click.pass_context
def get_config(ctx, key):
"""Get LoraWan configuration."""
lora = Rak811()
try:
click.echo(lora.get_config(key))
except Rak811Error as e:
print_exception(e)
lora.close()
@cli.command()
@click.pass_context
def join_otaa(ctx):
"""Join the configured network in OTAA mode."""
lora = Rak811()
try:
lora.join_otaa()
if ctx.obj['VERBOSE']:
click.echo('Joined in OTAA mode')
except Rak811Error as e:
print_exception(e)
lora.close()
@cli.command()
@click.pass_context
def join_abp(ctx):
"""Join the configured network in ABP mode."""
lora = Rak811()
try:
lora.join_abp()
if ctx.obj['VERBOSE']:
click.echo('Joined in ABP mode')
except Rak811Error as e:
print_exception(e)
lora.close()
@cli.command()
@click.pass_context
def signal(ctx):
"""Get (RSSI,SNR) from latest received packet."""
lora = Rak811()
(rssi, snr) = lora.signal
if ctx.obj['VERBOSE']:
click.echo('RSSI: {0} - SNR: {1}'.format(rssi, snr))
else:
click.echo('{} {}'.format(rssi, snr))
lora.close()
@cli.command()
@click.argument(
'dr',
required=False,
type=click.INT
)
@click.pass_context
def dr(ctx, dr):
"""Get/Set next send data rate."""
lora = Rak811()
if dr is None:
click.echo(lora.dr)
else:
try:
lora.dr = dr
if ctx.obj['VERBOSE']:
click.echo('Data rate set to {0}.'.format(dr))
except Rak811Error as e:
print_exception(e)
lora.close()
@cli.command()
@click.pass_context
def link_cnt(ctx):
"""Get up & downlink counters."""
lora = Rak811()
(uplink, downlink) = lora.link_cnt
if ctx.obj['VERBOSE']:
click.echo('Uplink: {0} - Downlink: {1}'.format(uplink, downlink))
else:
click.echo('{} {}'.format(uplink, downlink))
lora.close()
@cli.command()
@click.pass_context
def abp_info(ctx):
"""Get ABP info.
When using OTAA, returns the necessary info to re-join in ABP mode. The
following tuple is returned: (NetworkID, DevAddr, Nwkskey, Appskey)
"""
lora = Rak811()
(nwk_id, dev_addr, nwks_key, apps_key) = lora.abp_info
if ctx.obj['VERBOSE']:
click.echo('NwkId: {}'.format(nwk_id))
click.echo('DevAddr: {}'.format(dev_addr))
click.echo('Nwkskey: {}'.format(nwks_key))
click.echo('Appskey: {}'.format(apps_key))
else:
click.echo('{} {} {} {}'.format(nwk_id, dev_addr, nwks_key, apps_key))
lora.close()
@cli.command()
@click.option(
'-p', '--port',
default=1,
type=click.IntRange(1, 223),
help='port number to use (1-223)'
)
@click.option(
'--confirm',
is_flag=True,
help='regular or confirmed send'
)
@click.option(
'--binary',
is_flag=True,
help='Data is binary (hex encoded)'
)
@click.argument(
'data',
required=True
)
@click.option(
'--json',
is_flag=True,
help='Output downlink in JSON format'
)
@click.pass_context
def send(ctx, port, confirm, binary, data, json):
"""Send LoRaWan message and check for downlink."""
if binary:
try:
data = bytes.fromhex(data)
except ValueError:
click.echo('Invalid binary data')
return
lora = Rak811()
try:
lora.send(data, confirm=confirm, port=port)
except Rak811Error as e:
print_exception(e)
lora.close()
return
if ctx.obj['VERBOSE']:
click.echo('Message sent.')
if lora.nb_downlinks:
downlink = lora.get_downlink()
downlink['data'] = downlink['data'].hex()
if json:
click.echo(dumps(downlink, indent=4))
elif ctx.obj['VERBOSE']:
click.echo('Downlink received:')
click.echo('Port: {}'.format(downlink['port']))
if downlink['rssi']:
click.echo('RSSI: {}'.format(downlink['rssi']))
click.echo('SNR: {}'.format(downlink['snr']))
click.echo('Data: {}'.format(downlink['data']))
else:
click.echo(downlink['data'])
elif ctx.obj['VERBOSE']:
click.echo('No downlink available.')
lora.close()
@cli.command()
@click.argument(
'key_values',
metavar='KEY=VALUE...',
required=False,
type=KeyValueParamTypeP2P(),
nargs=-1
)
@click.pass_context
def rf_config(ctx, key_values):
"""Get/Set LoraP2P configuration.
\b
Without argument, returns:
frequency, sf, bw, cr, prlen, pwr
\b
Otherwise set rf_config, Arguments are specified as KEY=VALUE pairs:
freq: frequency in MHz (860.000-929.900)
sf: strength factor (6-12)
bw: bandwidth (0:125KHz, 1:250KHz, 2:500KHz)
cr: coding rate (1:4/5, 2:4/6, 3:4/7, 4:4/8)
prlen: preamble length default (8-65535)
pwr: Tx power (5-20)
E.g.: rf-config freq=860.100 sf=7 pwr=16
"""
lora = Rak811()
config = dict(key_values)
if config == {}:
# No parameters: returns rc_config
config = lora.rf_config
if ctx.obj['VERBOSE']:
click.echo('Frequency: {}'.format(config['freq']))
click.echo('SF: {}'.format(config['sf']))
click.echo('BW: {}'.format(config['bw']))
click.echo('CR: {}'.format(config['cr']))
click.echo('PrLen: {}'.format(config['prlen']))
click.echo('Power: {}'.format(config['pwr']))
else:
click.echo('{} {} {} {} {} {}'.format(
config['freq'], config['sf'], config['bw'], config['cr'],
config['prlen'], config['pwr']
))
else:
# At least a parameter, set rc_config
lora.rf_config = config
if ctx.obj['VERBOSE']:
click.echo('rf_config set: ' + ', '.join('{}={}'.format(k, v) for
k, v in config.items()))
lora.close()
@cli.command()
@click.option(
'--cnt',
default=1,
type=click.IntRange(1, 65535),
help='tx counts (1-65535)'
)
@click.option(
'--interval',
default=60,
type=click.IntRange(1, 3600),
help=' tx interval (1-3600)'
)
@click.option(
'--binary',
is_flag=True,
help='Data is binary (hex encoded)'
)
@click.argument(
'data',
required=True
)
@click.pass_context
def txc(ctx, cnt, interval, binary, data):
"""Send LoRaP2P message."""
if binary:
try:
data = bytes.fromhex(data)
except ValueError:
click.echo('Invalid binary data')
return
lora = Rak811()
try:
lora.txc(data, cnt=cnt, interval=interval)
except Rak811Error as e:
print_exception(e)
lora.close()
return
if ctx.obj['VERBOSE']:
click.echo('Message sent.')
lora.close()
@cli.command()
@click.pass_context
def rxc(ctx):
"""Set module in LoraP2P receive mode."""
lora = Rak811()
lora.rxc()
if ctx.obj['VERBOSE']:
click.echo('Module set in receive mode.')
lora.close()
@cli.command()
@click.pass_context
def tx_stop(ctx):
"""Stop LoraP2P TX."""
lora = Rak811()
lora.tx_stop()
if ctx.obj['VERBOSE']:
click.echo('LoraP2P TX stopped.')
lora.close()
@cli.command()
@click.pass_context
def rx_stop(ctx):
"""Stop LoraP2P RX."""
lora = Rak811()
lora.rx_stop()
if ctx.obj['VERBOSE']:
click.echo('LoraP2P RX stopped.')
lora.close()
@cli.command()
@click.argument(
'timeout',
required=False,
default=60,
type=click.INT
)
@click.option(
'--json',
is_flag=True,
help='Output message in JSON format'
)
@click.pass_context
def rx_get(ctx, timeout, json):
"""Get LoraP2P message."""
lora = Rak811()
lora.rx_get(timeout)
if lora.nb_downlinks:
rx = lora.get_downlink()
rx['data'] = rx['data'].hex()
if json:
click.echo(dumps(rx, indent=4))
elif ctx.obj['VERBOSE']:
click.echo('Message received:')
if rx['rssi']:
click.echo('RSSI: {}'.format(rx['rssi']))
click.echo('SNR: {}'.format(rx['snr']))
click.echo('Data: {}'.format(rx['data']))
else:
click.echo(rx['data'])
elif ctx.obj['VERBOSE']:
click.echo('No message available.')
lora.close()
@cli.command()
@click.pass_context
def radio_status(ctx):
"""Get radio statistics.
Returns: TxSuccessCnt, TxErrCnt, RxSuccessCnt, RxTimeOutCnt, RxErrCnt,
Rssi, Snr.
"""
lora = Rak811()
(
tx_success_cnt, tx_err_cnt,
rx_success_cnt, rx_timeout_cnt, rx_err_cnt,
rssi, snr
) = lora.radio_status
if ctx.obj['VERBOSE']:
click.echo('TxSuccessCnt: {}'.format(tx_success_cnt))
click.echo('TxErrCnt: {}'.format(tx_err_cnt))
click.echo('RxSuccessCnt: {}'.format(rx_success_cnt))
click.echo('RxTimeOutCnt: {}'.format(rx_timeout_cnt))
click.echo('RxErrCnt: {}'.format(rx_err_cnt))
click.echo('RSSI: {}'.format(rssi))
click.echo('SNR: {}'.format(snr))
else:
click.echo('{} {} {} {} {} {} {}'.format(
tx_success_cnt, tx_err_cnt,
rx_success_cnt, rx_timeout_cnt, rx_err_cnt,
rssi, snr
))
lora.close()
@cli.command()
@click.pass_context
def clear_radio_status(ctx):
"""Clear radio statistics."""
lora = Rak811()
lora.clear_radio_status()
if ctx.obj['VERBOSE']:
click.echo('Radio statistics cleared.')
lora.close()
if __name__ == '__main__':
cli()
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] | 2.142109 | 7,825 |
import os
import numpy as np
import warnings
from . import genericsettings
scenario_rlbased = 'rlbased'
scenario_fixed = 'fixed'
scenario_biobjfixed = 'biobjfixed'
scenario_biobjrlbased = 'biobjrlbased'
scenario_biobjextfixed = 'biobjextfixed'
all_scenarios = [scenario_rlbased, scenario_fixed,
scenario_biobjfixed, scenario_biobjrlbased,
scenario_biobjextfixed]
testbed_name_single = 'bbob'
testbed_name_single_noisy = 'bbob-noisy'
testbed_name_bi = 'bbob-biobj'
testbed_name_bi_ext = 'bbob-biobj-ext'
default_testbed_single = 'GECCOBBOBTestbed'
default_testbed_single_noisy = 'GECCOBBOBNoisyTestbed'
default_testbed_bi = 'GECCOBiObjBBOBTestbed'
default_testbed_bi_ext = 'GECCOBiObjExtBBOBTestbed'
current_testbed = None
suite_to_testbed = {
'bbob' : default_testbed_single,
'bbob-noisy' : default_testbed_single_noisy,
'bbob-biobj' : default_testbed_bi,
'bbob-biobj-ext' : default_testbed_bi_ext
}
reference_values = {}
def get_reference_values(algorithm):
""" Returns the hash value of the hypervolume reference values
for the specified algorithm (if available, i.e. if the algorithm
has been run on the `bbob-biobj` testbed).
If algorithm=None, all hash values are returned as a set
(i.e. with no duplicates) if more than one hash is available
or as a string if all hashes are the same.
"""
global reference_values
if reference_values and algorithm in reference_values:
return reference_values[algorithm]
if reference_values and algorithm is None:
return set(reference_values.values()) if len(set(reference_values.values())) > 1 else reference_values.values()[0]
return None
class Testbed(object):
"""this might become the future way to have settings related to testbeds
TODO: how do we pass information from the benchmark to the post-processing?
"""
reference_algorithm_displayname = None
def info(self, fun_number=None):
"""info on the testbed if ``fun_number is None`` or one-line info
for function with number ``fun_number``.
"""
if fun_number is None:
return self.__doc__
for line in open(os.path.join(os.path.abspath(os.path.split(__file__)[0]),
self.info_filename)).readlines():
if line.split(): # ie if not empty
try: # empty lines are ignored
fun = int(line.split()[0])
if fun == fun_number:
return 'F' + str(fun) + ' ' + ' '.join(line.split()[1:])
except ValueError:
continue # ignore annotations
class GECCOBBOBTestbed(Testbed):
"""Testbed used in the GECCO BBOB workshops 2009, 2010, 2012, 2013, 2015,
and 2016.
"""
shortinfo_filename = 'bbob-benchmarkshortinfos.txt'
pptable_target_runlengths = [0.5, 1.2, 3, 10, 50] # used in config for expensive setting
pptable_targetsOfInterest = (10, 1, 1e-1, 1e-2, 1e-3, 1e-5, 1e-7) # for pptable and pptablemany
settings = dict(
info_filename = 'bbob-benchmarkinfos.txt',
shortinfo_filename = shortinfo_filename,
name = testbed_name_single,
short_names = get_short_names(shortinfo_filename),
hardesttargetlatex = '10^{-8}', # used for ppfigs, pptable, pptable2, and pptables
ppfigs_ftarget = 1e-8, # to set target runlength in expensive setting, use genericsettings.target_runlength
ppfig2_ftarget = 1e-8,
ppfigdim_target_values = (10, 1, 1e-1, 1e-2, 1e-3, 1e-5, 1e-8),
pprldistr_target_values = (10., 1e-1, 1e-4, 1e-8),
pprldmany_target_values = 10 ** np.arange(2, -8.2, -0.2),
pprldmany_target_range_latex = '$10^{[-8..2]}$',
ppscatter_target_values = np.logspace(-8, 2, 21), # 21 was 46
rldValsOfInterest = (10, 1e-1, 1e-4, 1e-8), # possibly changed in config
ppfvdistr_min_target = 1e-8,
functions_with_legend = (1, 24, 101, 130),
first_function_number = 1,
last_function_number = 24,
reference_values_hash_dimensions = [],
pptable_ftarget = 1e-8, # value for determining the success ratio in all tables
pptable_targetsOfInterest = pptable_targetsOfInterest,
pptable2_targetsOfInterest = (1e+1, 1e-1, 1e-3, 1e-5, 1e-7), # used for pptable2
pptablemany_targetsOfInterest = pptable_targetsOfInterest,
scenario = scenario_fixed,
reference_algorithm_filename = 'refalgs/best2009-bbob.tar.gz',
reference_algorithm_displayname = 'best 2009', # TODO: should be read in from data set in reference_algorithm_filename
#.reference_algorithm_filename = 'data/RANDOMSEARCH'
#.reference_algorithm_displayname = "RANDOMSEARCH" # TODO: should be read in from data set in reference_algorithm_filename
# expensive optimization settings:
pptable_target_runlengths = pptable_target_runlengths,
pptable2_target_runlengths = pptable_target_runlengths,
pptables_target_runlengths = pptable_target_runlengths,
instancesOfInterest = None # None: consider all instances
#.instancesOfInterest = {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1,
# 10: 1, 11: 1, 12: 1, 13: 1, 14: 1, 15: 1,
# 21: 1, 22: 1, 23: 1, 24: 1, 25: 1, 26: 1, 27: 1, 28: 1, 29: 1, 30: 1,
# 31: 1, 32: 1, 33: 1, 34: 1, 35: 1, 36: 1, 37: 1, 38: 1, 39: 1, 40: 1,
# 41: 1, 42: 1, 43: 1, 44: 1, 45: 1, 46: 1, 47: 1, 48: 1, 49: 1, 50: 1,
# 51: 1, 52: 1, 53: 1, 54: 1, 55: 1, 56: 1, 57: 1, 58: 1, 59: 1, 60: 1} # consider only 2009-2016 instances
#.instancesOfInterest = {1: 1, 2: 1}
)
class GECCOBBOBNoisyTestbed(GECCOBBOBTestbed):
"""The noisy testbed used in the GECCO BBOB workshops 2009, 2010, 2012,
2013, 2015, and 2016.
"""
shortinfo_filename = 'bbob-noisy-benchmarkshortinfos.txt'
settings = dict(
info_filename = 'bbob-noisy-benchmarkinfos.txt',
shortinfo_filename = shortinfo_filename,
short_names = get_short_names(shortinfo_filename),
name = testbed_name_single, # TODO: until we clean the code which uses this name, we need to use it also here.
functions_with_legend = (101, 130),
first_function_number = 101,
last_function_number = 130,
reference_algorithm_filename = 'refalgs/best2009-bbob-noisy.tar.gz',
reference_algorithm_displayname = 'best 2009' # TODO: should be read in from data set in reference_algorithm_filename
)
class GECCOBiObjBBOBTestbed(Testbed):
"""Testbed used in the BBOB workshops to display
data sets run on the `bbob-biobj` test suite.
"""
shortinfo_filename = 'bbob-biobj-benchmarkshortinfos.txt'
pptable_target_runlengths = [0.5, 1.2, 3, 10, 50] # used in config for expensive setting
pptable_targetsOfInterest = (10, 1, 1e-1, 1e-2, 1e-3, 1e-5, 1e-7) # for pptable and pptablemany
settings = dict(
info_filename = 'bbob-biobj-benchmarkinfos.txt',
shortinfo_filename = shortinfo_filename,
name = testbed_name_bi,
short_names = get_short_names(shortinfo_filename),
hardesttargetlatex = '10^{-5}', # used for ppfigs, pptable, pptable2, and pptables
ppfigs_ftarget = 1e-5, # to set target runlength in expensive setting, use genericsettings.target_runlength
ppfig2_ftarget = 1e-5,
ppfigdim_target_values = (1e-1, 1e-2, 1e-3, 1e-4, 1e-5),
pprldistr_target_values = (1e-1, 1e-2, 1e-3, 1e-5),
pprldmany_target_values = np.append(np.append(10 ** np.arange(0, -5.1, -0.1), [0]), -10 ** np.arange(-5, -3.9, 0.2)),
pprldmany_target_range_latex = '$\{-10^{-4}, -10^{-4.2}, $ $-10^{-4.4}, -10^{-4.6}, -10^{-4.8}, -10^{-5}, 0, 10^{-5}, 10^{-4.9}, 10^{-4.8}, \dots, 10^{-0.1}, 10^0\}$',
ppscatter_target_values = np.logspace(-5, 1, 21), # 21 was 51
rldValsOfInterest = (1e-1, 1e-2, 1e-3, 1e-4, 1e-5),
ppfvdistr_min_target = 1e-5,
functions_with_legend = (1, 30, 31, 55),
first_function_number = 1,
last_function_number = 55,
reference_values_hash_dimensions = [2, 3, 5, 10, 20],
pptable_ftarget = 1e-5, # value for determining the success ratio in all tables
pptable_targetsOfInterest = (1, 1e-1, 1e-2, 1e-3, 1e-4, 1e-5),
pptable2_targetsOfInterest = (1e-1, 1e-2, 1e-3, 1e-4, 1e-5), # used for pptable2
pptablemany_targetsOfInterest = (1, 1e-1, 1e-2, 1e-3), # used for pptables
scenario = scenario_biobjfixed,
reference_algorithm_filename = 'refalgs/best2016-bbob-biobj.tar.gz', # TODO produce correct best2016 algo and delete this line
reference_algorithm_displayname = 'best 2016', # TODO: should be read in from data set in reference_algorithm_filename
instancesOfInterest = {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1, 10: 1}, # None, # None: consider all instances
# expensive optimization settings:
pptable_target_runlengths = [0.5, 1.2, 3, 10, 50], # [0.5, 2, 10, 50] # used in config for expensive setting
pptable2_target_runlengths = [0.5, 1.2, 3, 10, 50], # [0.5, 2, 10, 50] # used in config for expensive setting
pptables_target_runlengths = [2, 10, 50] # used in config for expensive setting
)
class GECCOBiObjExtBBOBTestbed(GECCOBiObjBBOBTestbed):
"""Biobjective testbed to display data sets run on the `bbob-biobj-ext`
test suite.
"""
shortinfo_filename = 'bbob-biobj-benchmarkshortinfos.txt'
settings = dict(
info_filename = 'bbob-biobj-benchmarkinfos.txt',
shortinfo_filename = shortinfo_filename,
name = testbed_name_bi_ext,
short_names = get_short_names(shortinfo_filename),
functions_with_legend = (1, 30, 31, 60, 61, 92),
first_function_number = 1,
last_function_number = 92,
scenario = scenario_biobjextfixed,
reference_algorithm_filename = '', # TODO produce correct best2017 algo and delete this line
reference_algorithm_displayname = '', # TODO: should be read in from data set in reference_algorithm_filename
instancesOfInterest = {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1, 10: 1}, # None: consider all instances
)
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] | 2.250054 | 4,651 |
#!/usr/bin/env python
# Parallel Python Software: http://www.parallelpython.com
# Copyright (c) 2005-2009, Vitalii Vanovschi
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the author nor the names of its contributors
# may be used to endorse or promote products derived from this software
# without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
# THE POSSIBILITY OF SUCH DAMAGE.
"""
Parallel Python Software, Network Server
http://www.parallelpython.com - updates, documentation, examples and support
forums
"""
import logging
import getopt
import sys
import socket
import thread
import random
import string
import time
import os
import pptransport
import ppauto
from pp import Server
copyright = "Copyright (c) 2005-2009 Vitalii Vanovschi. All rights reserved"
version = "1.5.7"
# compartibility with Python 2.6
try:
import hashlib
sha_new = hashlib.sha1
except ImportError:
import sha
sha_new = sha.new
class _NetworkServer(Server):
"""Network Server Class
"""
def ncon_add(self, val):
"""Keeps track of the number of connections and time of the last one"""
self.ncon_lock.acquire()
self.ncon += val
self.last_con_time = time.time()
self.ncon_lock.release()
def check_timeout(self):
"""Checks if timeout happened and shutdowns server if it did"""
while True:
if self.ncon == 0:
idle_time = time.time() - self.last_con_time
if idle_time < self.timeout:
time.sleep(self.timeout - idle_time)
else:
logging.debug("exiting ppserver due to timeout (no client"\
" connections in last %i sec)", self.timeout)
os._exit(0)
else:
time.sleep(self.timeout)
def listen(self):
"""Initiates listenting to incoming connections"""
try:
ssocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
# following allows ppserver to restart faster on the same port
ssocket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
ssocket.bind((self.host, self.port))
ssocket.listen(5)
except socket.error:
logging.error("Cannot create socket with port " + str(self.port)
+ " (port is already in use)")
try:
while 1:
#accept connections from outside
(csocket, address) = ssocket.accept()
#now do something with the clientsocket
#in this case, we'll pretend this is a threaded server
thread.start_new_thread(self.crun, (csocket, ))
except:
logging.debug("Closing server socket")
ssocket.close()
def crun(self, csocket):
"""Authenticates client and handles its jobs"""
mysocket = pptransport.CSocketTransport(csocket)
#send PP version
mysocket.send(version)
#generate a random string
srandom = "".join([random.choice(string.ascii_letters)
for i in xrange(16)])
mysocket.send(srandom)
answer = sha_new(srandom+self.secret).hexdigest()
cleintanswer = mysocket.receive()
if answer != cleintanswer:
logging.warning("Authentification failed, client host=%s, port=%i"
% csocket.getpeername())
mysocket.send("FAILED")
csocket.close()
return
else:
mysocket.send("OK")
ctype = mysocket.receive()
logging.debug("Control message received: " + ctype)
self.ncon_add(1)
try:
if ctype == "STAT":
#reset time at each new connection
self.get_stats()["local"].time = 0.0
mysocket.send(str(self.get_ncpus()))
while 1:
mysocket.receive()
mysocket.send(str(self.get_stats()["local"].time))
elif ctype=="EXEC":
while 1:
sfunc = mysocket.creceive()
sargs = mysocket.receive()
fun = self.insert(sfunc, sargs)
sresult = fun(True)
mysocket.send(sresult)
except:
#print sys.excepthook(*sys.exc_info())
logging.debug("Closing client socket")
csocket.close()
self.ncon_add(-1)
def broadcast(self):
"""Initiaates auto-discovery mechanism"""
discover = ppauto.Discover(self)
thread.start_new_thread(discover.run,
((self.host, self.port),
(self.bcast, self.port)),
)
def parse_config(file_loc):
"""
Parses a config file in a very forgiving way.
"""
# If we don't have configobj installed then let the user know and exit
try:
from configobj import ConfigObj
except ImportError, ie:
print >> sys.stderr, "ERROR: You must have configobj installed to use \
configuration files. You can still use command line switches."
sys.exit(1)
if not os.access(file_loc, os.F_OK):
print >> sys.stderr, "ERROR: Can not access %s." % arg
sys.exit(1)
# Load the configuration file
config = ConfigObj(file_loc)
# try each config item and use the result if it exists. If it doesn't
# then simply pass and move along
try:
args['secret'] = config['general'].get('secret')
except:
pass
try:
autodiscovery = config['network'].as_bool('autodiscovery')
except:
pass
try:
args['interface'] = config['network'].get('interface',
default="0.0.0.0")
except:
pass
try:
args['broadcast'] = config['network'].get('broadcast')
except:
pass
try:
args['port'] = config['network'].as_int('port')
except:
pass
try:
args['loglevel'] = config['general'].as_bool('debug')
except:
pass
try:
args['ncpus'] = config['general'].as_int('workers')
except:
pass
try:
args['proto'] = config['general'].as_int('proto')
except:
pass
try:
args['restart'] = config['general'].as_bool('restart')
except:
pass
try:
args['timeout'] = config['network'].as_int('timeout')
except:
pass
# Return a tuple of the args dict and autodiscovery variable
return args, autodiscovery
def print_usage():
"""Prints help"""
print "Parallel Python Network Server (pp-" + version + ")"
print "Usage: ppserver.py [-hdar] [-n proto] [-c config_path]"\
" [-i interface] [-b broadcast] [-p port] [-w nworkers]"\
" [-s secret] [-t seconds]"
print
print "Options: "
print "-h : this help message"
print "-d : debug"
print "-a : enable auto-discovery service"
print "-r : restart worker process after each"\
" task completion"
print "-n proto : protocol number for pickle module"
print "-c path : path to config file"
print "-i interface : interface to listen"
print "-b broadcast : broadcast address for auto-discovery service"
print "-p port : port to listen"
print "-w nworkers : number of workers to start"
print "-s secret : secret for authentication"
print "-t seconds : timeout to exit if no connections with "\
"clients exist"
print
print "Due to the security concerns always use a non-trivial secret key."
print "Secret key set by -s switch will override secret key assigned by"
print "pp_secret variable in .pythonrc.py"
print
print "Please visit http://www.parallelpython.com for extended up-to-date"
print "documentation, examples and support forums"
if __name__ == "__main__":
try:
opts, args = getopt.getopt(sys.argv[1:],
"hdarn:c:b:i:p:w:s:t:", ["help"])
except getopt.GetoptError:
print_usage()
sys.exit(1)
args = {}
autodiscovery = False
for opt, arg in opts:
if opt in ("-h", "--help"):
print_usage()
sys.exit()
elif opt == "-c":
args, autodiscovery = parse_config(arg)
elif opt == "-d":
args["loglevel"] = logging.DEBUG
elif opt == "-i":
args["interface"] = arg
elif opt == "-s":
args["secret"] = arg
elif opt == "-p":
args["port"] = int(arg)
elif opt == "-w":
args["ncpus"] = int(arg)
elif opt == "-a":
autodiscovery = True
elif opt == "-r":
args["restart"] = True
elif opt == "-b":
args["broadcast"] = arg
elif opt == "-n":
args["proto"] = int(arg)
elif opt == "-t":
args["timeout"] = int(arg)
server = _NetworkServer(**args)
if autodiscovery:
server.broadcast()
server.listen()
#have to destroy it here explicitelly otherwise an exception
#comes out in Python 2.4
del server
# Parallel Python Software: http://www.parallelpython.com
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] | 2.279607 | 4,678 |
from .config import *
import torch
import cv2
import numpy as np
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] | 3.142857 | 21 |
from django.contrib.auth.mixins import PermissionRequiredMixin
from django.urls import reverse_lazy
from django.views.generic.edit import FormMixin
from church_site.views import AdminListView, BaseCreateView, BaseUpdateView
from .forms import SpeakerCreateForm
from .models import Speaker
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# Autogenerated file for Relay
# Add missing from ... import const
_JD_SERVICE_CLASS_RELAY = const(0x183fe656)
_JD_RELAY_VARIANT_ELECTROMECHANICAL = const(0x1)
_JD_RELAY_VARIANT_SOLID_STATE = const(0x2)
_JD_RELAY_VARIANT_REED = const(0x3)
_JD_RELAY_REG_CLOSED = const(JD_REG_INTENSITY)
_JD_RELAY_REG_VARIANT = const(JD_REG_VARIANT)
_JD_RELAY_REG_MAX_SWITCHING_CURRENT = const(0x180)
_JD_RELAY_EV_ACTIVE = const(JD_EV_ACTIVE)
_JD_RELAY_EV_INACTIVE = const(JD_EV_INACTIVE) | [
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# Different Logging Levels
# 4: DEBUG
# 3: INFO
# 2: WARNING
# 1: ERROR
# 0: CRITICAL
log_level = 3
# When set true, if the script finds a user that already exists,
# the script will attempt to change the policy of that user,
# and add the emby connect account to that user.
overwrite = False
# The url to your Emby server
emby_base_url = 'http://localhost:8096'
# Login info for an account on your Emby server that has admin privileges
# Username
emby_admin_uname = ''
# Password
emby_admin_passwd = ''
# The script will avoid doing anything to these users AND admin_uname
avoid_users = [
'Python',
'Admin1122'
]
# number of seconds before the first request will timeout.
timeout = 2
# Determine whether or not to output in tsv format. Will be text if False
tsv_out = True
# If all thats provided is a connect username, this prefix will be put at
# the start of the username on the server
user_prefix = '!'
# These are the user policy changes that will be made. Can be empty
user_policy = {
'IsAdministrator': False, # True|False
'IsHidden': True, # True|False
'IsHiddenRemotely': True, # True|False
'IsDisabled': False, # True|False
# 'MaxParentalRating': None, # int|None
# 'BlockedTags': [], # string[]
# 'EnableUserPreferenceAccess': True, # True|False
# 'AccessSchedules': [], # [Configuration.AccessSchedule{...}]
# 'BlockUnratedItems': [], # string[Movie, Trailer, Series, Music, Game, Book, LiveTvChannel, LiveTvProgram, ChannelContent, Other]
'EnableRemoteControlOfOtherUsers': False, # True|False
'EnableSharedDeviceControl': True, # True|False
'EnableRemoteAccess': True, # True|False
'EnableLiveTvManagement': False, # True|False
'EnableLiveTvAccess': False, # True|False
'EnableMediaPlayback': True, # True|False
'EnableAudioPlaybackTranscoding': True, # True|False
'EnableVideoPlaybackTranscoding': True, # True|False
'EnablePlaybackRemuxing': True, # True|False
'EnableContentDeletion': False, # True|False
# 'EnableContentDeletionFromFolders': [], # string[]
'EnableContentDownloading': True, # True|False
'EnableSubtitleDownloading': False, # True|False
'EnableSubtitleManagement': False, # True|False
'EnableSyncTranscoding': False, # True|False
'EnableMediaConversion': False, # True|False
# 'EnabledDevices': [], # string[]
'EnableAllDevices': True, # True|False
# 'EnabledChannels': [], # string[]
'EnableAllChannels': True, # True|False
# 'EnabledFolders': [], # string[]
'EnableAllFolders': True, # True|False
# 'InvalidLoginAttemptCount': 10, # int
'EnablePublicSharing': False, # True|False
# 'BlockedMediaFolders': [], # string[]
# 'BlockedChannels': [], # string[]
# 'RemoteClientBitrateLimit': 12, # int
# 'AuthenticationProviderId': '', # string
# 'ExcludedSubFolders': [], # string[]
# 'DisablePremiumFeatures': False # True|False
}
| [
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] | 2.056186 | 1,851 |
"""
Author: Haoyin Xu
"""
import time
import numpy as np
import torchvision.datasets as datasets
from numpy.random import permutation
from sklearn.tree import DecisionTreeClassifier
def write_result(filename, acc_ls):
"""Writes results to specified text file"""
output = open(filename, "w")
for acc in acc_ls:
output.write(str(acc) + "\n")
def prediction(classifier):
"""Generates predictions from model"""
predictions = classifier.predict(X_test)
p_t = 0
for i in range(X_test.shape[0]):
if predictions[i] == y_test[i]:
p_t += 1
return p_t / X_test.shape[0]
def experiment_sdt():
"""Runs experiments for Stream Decision Tree"""
sdt_l = []
train_time_l = []
test_time_l = []
sdt = DecisionTreeClassifier()
for i in range(500):
X_t = X_r[i * 100 : (i + 1) * 100]
y_t = y_r[i * 100 : (i + 1) * 100]
# Train the model
start_time = time.perf_counter()
sdt.partial_fit(X_t, y_t, classes=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
end_time = time.perf_counter()
train_time_l.append(end_time - start_time)
# Test the model
start_time = time.perf_counter()
sdt_l.append(prediction(sdt))
end_time = time.perf_counter()
test_time_l.append(end_time - start_time)
# Reformat the train times
for i in range(1, 500):
train_time_l[i] += train_time_l[i - 1]
return sdt_l, train_time_l, test_time_l
# prepare CIFAR data
# normalize
scale = np.mean(np.arange(0, 256))
normalize = lambda x: (x - scale) / scale
# train data
cifar_trainset = datasets.CIFAR10(root="../", train=True, download=True, transform=None)
X_train = normalize(cifar_trainset.data)
y_train = np.array(cifar_trainset.targets)
# test data
cifar_testset = datasets.CIFAR10(root="../", train=False, download=True, transform=None)
X_test = normalize(cifar_testset.data)
y_test = np.array(cifar_testset.targets)
X_train = X_train.reshape(-1, 32 * 32 * 3)
X_test = X_test.reshape(-1, 32 * 32 * 3)
# Perform experiments
sdt_acc_l = []
sdt_train_t_l = []
sdt_test_t_l = []
for i in range(10):
p = permutation(X_train.shape[0])
X_r = X_train[p]
y_r = y_train[p]
sdt_acc, sdt_train_t, sdt_test_t = experiment_sdt()
sdt_acc_l.append(sdt_acc)
sdt_train_t_l.append(sdt_train_t)
sdt_test_t_l.append(sdt_test_t)
write_result("../sdt/cifar10_acc.txt", sdt_acc_l)
write_result("../sdt/cifar10_train_t.txt", sdt_train_t_l)
write_result("../sdt/cifar10_test_t.txt", sdt_test_t_l)
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] | 2.218858 | 1,156 |
import os
import sys
import h5py
import argparse
import net.proto_file as proto_file
import subprocess
import numpy as np
import scipy.io as sio
import data_analysis.find_caffe as find_caffe
import Config.ExpConfigInfo as Config
caffe_root = find_caffe.caffe_root
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="train bn net",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--spatial_info', type=str, default='5x5_mean_std',
help="1x1_mean', '3x3_mean', '3x3_mean_std', '5x5_mean', '5x5_mean_std")
parser.add_argument('--gpu', type=int, default=1,
help='the number of gpu id, only one number is required')
parser.add_argument('--dst_dir', type=str, default='bn_net_200',
help='the destination dir for the experiments')
parser.add_argument('--data_set', type=str, default='salina',
help='indian_pines, salina')
parser.add_argument('--max_iter', type=int, default=10000,
help='how many iters')
parser.add_argument('--train_nums', type=float, default=200,
help='how many samples for training or how much percents for training, 200 or 0.1')
args = parser.parse_args()
train(args=args) | [
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198,
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4512,
7,
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28,
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8
] | 2.293423 | 593 |
# -*- coding: utf-8 -*-
import io
import json
import os
import glob
import requests
import urllib.parse
import sys
import time
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument("-p", "--path",
help="log path", dest="p", default="app/static/line")
parser.add_argument("-i", "--id",
help="chrome extension id", dest="i", default="*")
parser.add_argument("-u", "--url",
help="server url", dest="u", default="http://localhost:8080")
parser.add_argument("-l", "--login",
help="login api", dest="l", default="/api/v1/security/login")
parser.add_argument("-c", "--concat",
help="concat api", dest="c", default="/api/1.0/contactmodelapi/add")
parser.add_argument("--username",
help="login username", dest="username", default="addline")
parser.add_argument("--password",
help="concat api", dest="password", default="ZAHVjB$WLM*@6fV46?B&$Y+ELW+fvd%q")
args = parser.parse_args()
#if len(files) is 0:
# sys.exit("no file, 81")
while True:
monitor_log()
time.sleep(1)
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] | 2.574879 | 414 |
# -*- coding: utf-8 -*-
"""
MIT License
Copyright (c) 2020 supr3me
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.
"""
RarityColor = RarityColour
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198,
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198,
49,
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10258,
796,
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5216,
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201,
198
] | 3.461078 | 334 |
#!/usr/bin/env python3
import math
# Binomial coeff 4ever
print(int(find_bin_coeff(40, 20))) | [
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# Fizz Buzz in Tensorflow!
# Our goal is to produce fizzbuzz for the numbers 1 to 100.
# So it would be unfair to include these in our training data.
# Accordingly, the training data corresponds to the numbers 101 to (2 ** NUM_DIGITS - 1).
# see http://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/
from PyBaseGUI.Mplot import plot_confusion_matrix as plot
import numpy #as np
import tensorflow.compat.v1 as tf
from sklearn import metrics
from sympy import sieve
from sympy.ntheory import factorint
#*************************************************************
# Maximum number to clasify
PROGRESS_SHOW = False
MAX_NUM = 2**10
#*************************************************************
# Binary Encoding
# Represent each input by an array of its binary digits.
#*************************************************************
# Primes Encoding
# Represent each input by an array of its primary number multiplier as digits.
#*************************************************************
# Create the network model.
# Generate random weights.
# Our model is a standard 1-hidden-layer multi-layer-perceptron with ReLU activation.
# The softmax (which turns arbitrary real-valued outputs into probabilities) gets applied in the cost function.
#Create optimization function.
#*************************************************************
# Network data place holders
# Our variables. The input has width in_digits, and the output has width out_digits.
#*************************************************************
# Network Training
# Create Labled training data.
# Fizz-Buzz data lables generation.
# One-hot encode the desired network outputs: [number, "fizz", "buzz", "fizzbuzz"])
# Finally, we need a way to turn a prediction (and an original number) into a fizz buzz output
fizz_buzz_names=["num", "fizz", "buzz", "fizzbuzz"];
# Mish-Buzz data lables generation.
# One-hot encode the desired outputs: [number, "fizz", "buzz", "fizzbuzz", "mish", "mishfizz", "mishbuzz"]
mish_buzz_names:list=["num", "mish", "fizz", "buzz", "mishfizz", "mishbuzz", "fizzbuzz"];
# Train the network using the labled data.
#*************************************************************
# Network testing.
#*************************************************************
# Performance report.
#Report the network performance.
#*************************************************************
# Run the network learning algorithm.
#*************************************************************
# Running experiments
# questions 1-4
#1. Take the FizzBuzz example and make it work: It works.
#2. Add to the code a function that analyzes the results.
# a. Print the accuracy of the classifier: See the report function and the batch accuracy reort.
# b. Generate a confusion matrix: See the report function.
#3. Run it once and put the results in a word file: the loop can be set to once or 10 times.
NUM_HIDDEN = 100 # How many units in the hidden layer.
NUM_IN_DIGITS = binary_digits(MAX_NUM) # Number of binary digits (Maximum number)
TRAIN_SIZE = 8
print("Run bizz buzz 1 time with progress combinations of 2,3,6,10")
for i in range (1):
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, binary_encode, fizz_buzz_encode, fizz_buzz_cls, fizz_buzz_name, MAX_NUM, NUM_IN_DIGITS, fizz_buzz_names, True);
#4. Rerun the algorithm 10 times and see if there are differences in the accuracy: The alogrithem is executed 10 times.
NUM_HIDDEN = 100 # How many units in the hidden layer.
NUM_IN_DIGITS = binary_digits(MAX_NUM) # Number of binary digits (Maximum number)
TRAIN_SIZE = 8
print("Run 8 times without progress report to compare results")
for i in range (9):
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, binary_encode, fizz_buzz_encode, fizz_buzz_cls, fizz_buzz_name, MAX_NUM, NUM_IN_DIGITS, fizz_buzz_names, False);
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, binary_encode, fizz_buzz_encode, fizz_buzz_cls, fizz_buzz_name, MAX_NUM, NUM_IN_DIGITS, fizz_buzz_names, True);
# questions 5-6
#5. Change the algorithm to also deal with the number 2 besides the numbers 3
# and 5 with all the relevant combinations (more classes2,3,5): we added the mish_buzz ancoding and class functions and class names.
#6. Run it once and put the results in a word file.
NUM_HIDDEN = 100 # How many units in the hidden layer.
print("Add mish buzz combinations of 2,3,5,6,10,15")
NUM_IN_DIGITS = binary_digits(MAX_NUM) # Number of binary digits (Maximum number)
TRAIN_SIZE = 8
for i in range (1):
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, binary_encode, mish_buzz_encode, mish_buzz_cls, mish_buzz_name, MAX_NUM, NUM_IN_DIGITS, mish_buzz_names, True);
# a question 7
#7. Try to improve the results by more training, change the network etc.
NUM_HIDDEN = 5000 # How many units in the hidden layer. we increase from 100 to 5000
NUM_IN_DIGITS = primes_digits(MAX_NUM) # Number of binary digits (Maximum number)
TRAIN_SIZE = 1
print("improve binary encode training and hidden layer")
for i in range (1):
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, primes_encode, mish_buzz_encode, mish_buzz_cls, mish_buzz_name, MAX_NUM, NUM_IN_DIGITS, mish_buzz_names, True);
# a question 8 for fizzbuzz
#8. Change the representation from binary to prime based(encode the numbers as
# prime number multiplayer). That means each number is coded by how many
# time each prime appears in the product. For large primes you can put them all
# in one bucket.
# Example: 24 is coded as 2^3* 3^1 -? [3,1,0,0,0,0…]
# Do you think the algorithms (first and second) will work better? Run them
# and write the results and compare them.
NUM_HIDDEN = 100 # How many units in the hidden layer.
NUM_IN_DIGITS = primes_digits(MAX_NUM) # Number of binary digits (Maximum number)
TRAIN_SIZE = 2
print("perform prim encoding with small hidden layer and small number of train")
for i in range(0):
TensorFlowRun(NUM_HIDDEN, TRAIN_SIZE, primes_encode, mish_buzz_encode, mish_buzz_cls, mish_buzz_name, MAX_NUM, NUM_IN_DIGITS, mish_buzz_names, True);
input("Press Enter to continue...") | [
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8
] | 3.213833 | 1,894 |
# uncompyle6 version 3.2.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 2.7.15 (v2.7.15:ca079a3ea3, Apr 30 2018, 16:30:26) [MSC v.1500 64 bit (AMD64)]
# Embedded file name: lib.coginvasion.hood.TownLoader
from panda3d.core import *
from direct.directnotify.DirectNotifyGlobal import directNotify
from direct.fsm.StateData import StateData
from direct.fsm.State import State
from direct.fsm.ClassicFSM import ClassicFSM
from direct.interval.IntervalGlobal import *
from QuietZoneState import QuietZoneState
import LinkTunnel, ZoneUtil, ToonInterior
from lib.coginvasion.cogoffice import CogOfficeInterior | [
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1504
] | 2.951923 | 208 |
########
# Copyright (c) 2013 GigaSpaces Technologies 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.
import uuid
from testenv import TestCase
from testenv.utils import get_resource as resource
from testenv.utils import deploy_application as deploy
from testenv.utils import create_rest_client
from cloudify_rest_client.exceptions import CloudifyClientError
| [
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62,
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62,
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62,
16366,
13,
1069,
11755,
1330,
10130,
1958,
11792,
12331,
628
] | 3.742739 | 241 |
import warnings
import pytest
@pytest.fixture(autouse=True)
def clear_session_after_test():
"""This wrapper runs for all the tests in the legacy directory (recursively).
"""
with warnings.catch_warnings():
warnings.filterwarnings('ignore', message=r'(.+) Keras 2 ',
category=UserWarning)
yield
| [
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import pytest
from tik.utils import _RotX, _RotY, _RotZ, Rot, Trans, homogeneous_transform
import numpy as np
ATOL = 1.e-8
@pytest.mark.parametrize(('theta', 'expected'), [
(0, np.eye(4)),
(2*np.pi, np.eye(4)),
])
@pytest.mark.parametrize(('roll','pitch','yaw','expected'), [
(0, 0, 0, np.eye(4)),
(2*np.pi,2*np.pi,2*np.pi, np.eye(4)),
(np.pi,np.pi,np.pi,np.eye(4))
])
@pytest.mark.parametrize(('x','y','z','expected'), [
(0, 0, 0, np.eye(4)),
])
@pytest.mark.parametrize('a,alpha,d,theta,expected', [
(0,0,0,0, np.eye(4))
]) | [
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7,
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31,
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13,
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380,
2736,
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64,
11,
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11,
67,
11,
1169,
8326,
11,
40319,
3256,
685,
198,
220,
220,
220,
357,
15,
11,
15,
11,
15,
11,
15,
11,
45941,
13,
25379,
7,
19,
4008,
198,
12962
] | 1.978648 | 281 |
import logging
log = logging.getLogger(__name__)
import sys
from otp.ai.passlib.utils.decor import deprecated_method
__all__ = [
'PasswordHash']
from abc import ABCMeta, abstractmethod, abstractproperty
@recreate_with_metaclass(ABCMeta)
| [
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] | 3.12987 | 77 |
from nodetasks.nodetasks import main
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from distutils.version import LooseVersion
from mongosql import SA_VERSION, SA_12, SA_13
def SA_VERSION_IN(min_version, max_version):
""" Check that SqlAlchemy version lies within a range
This is slow; only use in unit-tests!
"""
return LooseVersion(min_version) <= LooseVersion(SA_VERSION) <= LooseVersion(max_version)
def SA_SINCE(version):
""" Check SqlAlchemy >= version """
return LooseVersion(SA_VERSION) >= LooseVersion(version)
def SA_UNTIL(version):
""" Check SqlAlchemy <= version """
return LooseVersion(SA_VERSION) <= LooseVersion(version)
| [
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7,
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8,
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4944,
51,
4146,
7,
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2599,
198,
220,
220,
220,
37227,
6822,
311,
13976,
2348,
26599,
19841,
2196,
37227,
198,
220,
220,
220,
1441,
6706,
577,
14815,
7,
4090,
62,
43717,
8,
19841,
6706,
577,
14815,
7,
9641,
8,
198
] | 2.945274 | 201 |
import numpy as np
import cv2
red_lower = np.array([0,43,46])
red_upper = np.array([10,255,255])
blue_lower = np.array([100,43,46])
blue_upper = np.array([124,255,255])
cap = cv2.VideoCapture(0)
cap.set(3,320)
cap.set(4,240)
while 1:
ret,frame = cap.read()
frame = cv2.GaussianBlur(frame,(5,5),0)
hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2HSV)
mask = ChestRed()
ChestBule()
res = cv2.bitwise_and(frame,frame,mask=mask)
cnts = cv2.findContours(mask.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2]
if 20<len(cnts)<30:
print("Red!")
cv2.imshow("frame",frame)
cv2.imshow("mask",mask)
cv2.imshow("res",res)
if cv2.waitKey(5) == ord('q'):
break
cap.release()
cv2.destroyAllWindows() | [
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from __future__ import annotations
import tempfile
from contextlib import contextmanager
from dataclasses import dataclass
from typing import Any, Dict, Iterator, List, Optional
from commonmodel.base import Schema, SchemaLike
from dcp.data_format.handler import get_handler_for_name, infer_schema_for_name
from dcp.data_format.formats.memory.records import PythonRecordsHandler
from dcp.storage.base import Storage
from dcp.storage.database.utils import get_tmp_sqlite_db_url
from dcp.utils.common import rand_str
from dcp.utils.data import read_csv, read_json, read_raw_string_csv
from pandas import DataFrame
from snapflow import DataBlock, Environment, Graph, _Snap
from snapflow.core.module import SnapflowModule
from snapflow.core.node import DataBlockLog, Node, SnapLog
from sqlalchemy.orm import Session
from sqlalchemy.sql.expression import select
@dataclass
@contextmanager
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] | 3.507874 | 254 |
import pytest
| [
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#
# PySNMP MIB module CISCO-SME-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/CISCO-SME-MIB
# Produced by pysmi-0.3.4 at Wed May 1 12:12:18 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
Integer, ObjectIdentifier, OctetString = mibBuilder.importSymbols("ASN1", "Integer", "ObjectIdentifier", "OctetString")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsUnion, SingleValueConstraint, ValueRangeConstraint, ConstraintsIntersection, ValueSizeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "SingleValueConstraint", "ValueRangeConstraint", "ConstraintsIntersection", "ValueSizeConstraint")
ciscoMgmt, = mibBuilder.importSymbols("CISCO-SMI", "ciscoMgmt")
FcNameId, = mibBuilder.importSymbols("CISCO-ST-TC", "FcNameId")
ifDescr, InterfaceIndex = mibBuilder.importSymbols("IF-MIB", "ifDescr", "InterfaceIndex")
InetAddressType, InetAddress = mibBuilder.importSymbols("INET-ADDRESS-MIB", "InetAddressType", "InetAddress")
SnmpAdminString, = mibBuilder.importSymbols("SNMP-FRAMEWORK-MIB", "SnmpAdminString")
NotificationGroup, ModuleCompliance, ObjectGroup = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance", "ObjectGroup")
TimeTicks, ModuleIdentity, Bits, Integer32, Unsigned32, ObjectIdentity, Counter32, Counter64, IpAddress, MibIdentifier, iso, Gauge32, MibScalar, MibTable, MibTableRow, MibTableColumn, NotificationType = mibBuilder.importSymbols("SNMPv2-SMI", "TimeTicks", "ModuleIdentity", "Bits", "Integer32", "Unsigned32", "ObjectIdentity", "Counter32", "Counter64", "IpAddress", "MibIdentifier", "iso", "Gauge32", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "NotificationType")
StorageType, RowStatus, DisplayString, TruthValue, TextualConvention, TimeStamp = mibBuilder.importSymbols("SNMPv2-TC", "StorageType", "RowStatus", "DisplayString", "TruthValue", "TextualConvention", "TimeStamp")
ciscoSmeMIB = ModuleIdentity((1, 3, 6, 1, 4, 1, 9, 9, 632))
ciscoSmeMIB.setRevisions(('2008-03-28 00:00',))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
if mibBuilder.loadTexts: ciscoSmeMIB.setRevisionsDescriptions(('Initial version',))
if mibBuilder.loadTexts: ciscoSmeMIB.setLastUpdated('200803280000Z')
if mibBuilder.loadTexts: ciscoSmeMIB.setOrganization('Cisco Systems Inc. ')
if mibBuilder.loadTexts: ciscoSmeMIB.setContactInfo(' Cisco Systems Customer Service Postal: 170 W Tasman Drive San Jose, CA 95134 USA Tel: +1 800 553 -NETS E-mail: [email protected]')
if mibBuilder.loadTexts: ciscoSmeMIB.setDescription('MIB module to manage Storage Media Encryption (SME) service. SME is an encryption service provided by an encryption node residing on a linecard in a storage device. It receives clear-text data from host, encrypts it, then sends it to be written to tape or disk. It does the reverse in the opposite direction so the service is completely transparent to the host. The purpose of this service is to enhance data security in case the tape or disk is lost or stolen. As with any important service, user requires that it provides some level of fault tolerant in a graceful manner. SME provides this by allowing encryption nodes to be grouped into cluster. Nodes in the same cluster immediately pick up the work of a failed node so user does not see service disruption.')
ciscoSmeMIBNotifs = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 0))
ciscoSmeMIBObjects = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 1))
ciscoSmeMIBConform = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 2))
cSmeConfig = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1))
cSmeClusterTable = MibTable((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1), )
if mibBuilder.loadTexts: cSmeClusterTable.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterTable.setDescription('This table lists all the SME clusters that are configured on this device. As with any important service, user requires that it provides some level of fault tolerant in a graceful manner. SME provides this by allowing encryption nodes to be grouped into cluster. Nodes in the same cluster immediately pick up the work of a failed node so user does not see service disruption.')
cSmeClusterEntry = MibTableRow((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1), ).setIndexNames((0, "CISCO-SME-MIB", "cSmeClusterId"))
if mibBuilder.loadTexts: cSmeClusterEntry.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterEntry.setDescription('A conceptual row in the cSmeClusterTable. Each row represents a SME cluster in the system and provides the runtime and configuration information of a cluster.')
cSmeClusterId = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 1), CiscoSmeClusterIndex())
if mibBuilder.loadTexts: cSmeClusterId.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterId.setDescription('Globally unique index that identifies a SME cluster. This index must be generated in such a way that the same value is never reused even after cluster has been deleted.')
cSmeClusterName = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 2), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeClusterName.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterName.setDescription('The name of the SME cluster.')
cSmeClusterState = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 3), CiscoSmeClusterStatus()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeClusterState.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterState.setDescription('The operational state of the SME cluster.')
cSmeClusterMasterInetAddrType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 4), InetAddressType()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeClusterMasterInetAddrType.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMasterInetAddrType.setDescription('The type of Internet address of the SME cluster master. The Internet address of SME cluster master is specified by the value of the corresponding instance of cSmeClusterMasterInetAddr.')
cSmeClusterMasterInetAddr = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 5), InetAddress()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeClusterMasterInetAddr.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMasterInetAddr.setDescription('The Internet address of the SME cluster master device. The type of this Internet address is determined by the value of the corresponding instance of cSmeClusterMasterInetAddrType.')
cSmeClusterStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 6), StorageType()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeClusterStorageType.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterStorageType.setDescription('This object specifies the storage type for this conceptual row.')
cSmeClusterRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 1, 1, 7), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeClusterRowStatus.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterRowStatus.setDescription('The status of this conceptual row. There is no restriction on the value of other columns before a newly created row can be made active.')
cSmeClusterMembersTable = MibTable((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2), )
if mibBuilder.loadTexts: cSmeClusterMembersTable.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMembersTable.setDescription('This table lists the information of devices, local or remote, which are members of SME clusters configured on a device.')
cSmeClusterMembersEntry = MibTableRow((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1), ).setIndexNames((0, "CISCO-SME-MIB", "cSmeClusterId"), (0, "CISCO-SME-MIB", "cSmeMemberInetAddrType"), (0, "CISCO-SME-MIB", "cSmeMemberInetAddr"))
if mibBuilder.loadTexts: cSmeClusterMembersEntry.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMembersEntry.setDescription('A conceptual row in the cSmeClusterMembersTable. Each row represents a member device within a specified SME Cluster.')
cSmeMemberInetAddrType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 1), InetAddressType())
if mibBuilder.loadTexts: cSmeMemberInetAddrType.setStatus('current')
if mibBuilder.loadTexts: cSmeMemberInetAddrType.setDescription('The type of Internet address of a cluster member within a specified SME cluster. The Internet address of this device is specified by the value of the corresponding instance of cSmeMemberInetAddr.')
cSmeMemberInetAddr = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 2), InetAddress().subtype(subtypeSpec=ValueSizeConstraint(0, 32)))
if mibBuilder.loadTexts: cSmeMemberInetAddr.setStatus('current')
if mibBuilder.loadTexts: cSmeMemberInetAddr.setDescription('The Internet address of the cluster member device within a specified SME cluster. The type of this Internet address is determined by the value of the corresponding instance of cSmeMemberInetAddrType.')
cSmeFabric = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 3), SnmpAdminString().subtype(subtypeSpec=ValueSizeConstraint(1, 32))).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeFabric.setStatus('current')
if mibBuilder.loadTexts: cSmeFabric.setDescription('Refers to the name of physical fibre channel fabric in the SAN. A typical SAN deployment consists of a dual fabric topology which corresponds to two physical fabrics. In such a deployment, a VSAN and a cluster is configured in both fabrics to allow multi-pathing and redundancy. The user specifies the physical fabric to which a device belongs to when the cluster is configured.')
cSmeIsMemberLocal = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 4), TruthValue()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeIsMemberLocal.setStatus('current')
if mibBuilder.loadTexts: cSmeIsMemberLocal.setDescription("Identifies if the device is a local or remote member of this cluster. 'true' means this device is a local device. 'false' means this device is a remote device.")
cSmeMemberIsMaster = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 5), TruthValue()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeMemberIsMaster.setStatus('current')
if mibBuilder.loadTexts: cSmeMemberIsMaster.setDescription("Indicates if this device is currently the master of the SME cluster. The value 'true' means this device is the master. The value 'false' means this device is not the master. Devices in a cluster select one of the cluster member to be a master. The master is responsible for handling cluster membership.")
cSmeClusterMemberStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 6), StorageType()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeClusterMemberStorageType.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMemberStorageType.setDescription('This object specifies the storage type for this conceptual row.')
cSmeClusterMemberRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 2, 1, 7), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeClusterMemberRowStatus.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMemberRowStatus.setDescription('The status of this conceptual row. There is no restriction on the value of other columns before a newly created row can be made active. When a cluster is deleted, all entries in this table should be purged automatically.')
cSmeClusterMemberIfTable = MibTable((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 3), )
if mibBuilder.loadTexts: cSmeClusterMemberIfTable.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMemberIfTable.setDescription('This table lists the information of SME interfaces on all devices, local or remote, which are members of SME clusters configured on a device.')
cSmeClusterMemberIfEntry = MibTableRow((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 3, 1), ).setIndexNames((0, "CISCO-SME-MIB", "cSmeClusterId"), (0, "CISCO-SME-MIB", "cSmeMemberInetAddrType"), (0, "CISCO-SME-MIB", "cSmeMemberInetAddr"), (0, "CISCO-SME-MIB", "cSmeClusterInterfaceIndex"))
if mibBuilder.loadTexts: cSmeClusterMemberIfEntry.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterMemberIfEntry.setDescription('A conceptual row in the cSmeClusterMemberIfTable. Each row represents a participating interface on local/remote device member within the specified SME cluster.')
cSmeClusterInterfaceIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 3, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: cSmeClusterInterfaceIndex.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterInterfaceIndex.setDescription('A unique Interface index for a SME interface on a device in this cluster. This is the same as ifIndex of the ifTable of RFC1213.')
cSmeClusterInterfaceState = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 3, 1, 2), CiscoSmeInterfaceStatus()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeClusterInterfaceState.setStatus('current')
if mibBuilder.loadTexts: cSmeClusterInterfaceState.setDescription('The operational state of this SME interface.')
cSmeInterfaceTable = MibTable((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4), )
if mibBuilder.loadTexts: cSmeInterfaceTable.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceTable.setDescription('This table lists all SME interfaces on the local device and its corresponding information.')
cSmeInterfaceEntry = MibTableRow((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1), ).setIndexNames((0, "CISCO-SME-MIB", "cSmeInterfaceIndex"))
if mibBuilder.loadTexts: cSmeInterfaceEntry.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceEntry.setDescription('A conceptual row in the cSmeInterfaceTable. Each row represents a particular SME interface on a local device.')
cSmeInterfaceIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1, 1), InterfaceIndex())
if mibBuilder.loadTexts: cSmeInterfaceIndex.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceIndex.setDescription('A unique Interface index for a SME interface on this device. This is the same as ifIndex of the ifTable of RFC1213.')
cSmeInterfaceState = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1, 2), CiscoSmeInterfaceStatus()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeInterfaceState.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceState.setDescription('Operational state of this SME interface.')
cSmeInterfaceClusterId = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1, 3), CiscoSmeClusterIndex()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeInterfaceClusterId.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceClusterId.setDescription('Identifies the cluster to which this SME interface belongs.')
cSmeInterfaceStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1, 4), StorageType()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeInterfaceStorageType.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceStorageType.setDescription('This object specifies the storage type for this conceptual row.')
cSmeInterfaceRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 4, 1, 5), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeInterfaceRowStatus.setStatus('current')
if mibBuilder.loadTexts: cSmeInterfaceRowStatus.setDescription('The status of this conceptual row. There is no restriction on the value of other columns before a newly created row can be made active. For example, cSmeInterfaceClusterId column can be set independently later.')
cSmeHostPortTable = MibTable((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5), )
if mibBuilder.loadTexts: cSmeHostPortTable.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortTable.setDescription('This table lists the hosts that are configured for SME. In the case of application servers, the disks that are accessed by the hosts may be encrypted. In the case of backup/restore master/media servers, the tapes accessed by the hosts may be encrypted.')
cSmeHostPortEntry = MibTableRow((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5, 1), ).setIndexNames((0, "CISCO-SME-MIB", "cSmeHostPortName"))
if mibBuilder.loadTexts: cSmeHostPortEntry.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortEntry.setDescription('A conceptual row in the cSmeHostPortTable. Each row represents a particular host configured for SME service in a particular cluster.')
cSmeHostPortName = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5, 1, 1), FcNameId())
if mibBuilder.loadTexts: cSmeHostPortName.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortName.setDescription('Fibre-channel Port name (P_WWN) of the Host Nx_Port.')
cSmeHostPortClusterId = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5, 1, 2), CiscoSmeClusterIndex()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeHostPortClusterId.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortClusterId.setDescription('Identifies the cluster to which this host port belongs.')
cSmeHostPortStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5, 1, 3), StorageType()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeHostPortStorageType.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortStorageType.setDescription('This object specifies the storage type for this conceptual row.')
cSmeHostPortRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 5, 1, 4), RowStatus()).setMaxAccess("readcreate")
if mibBuilder.loadTexts: cSmeHostPortRowStatus.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortRowStatus.setDescription('The status of this conceptual row. There is no restriction on the value of other columns before a newly created row can be made active.')
cSmeConfigTableLastChanged = MibScalar((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 6), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeConfigTableLastChanged.setStatus('current')
if mibBuilder.loadTexts: cSmeConfigTableLastChanged.setDescription('The value of sysUpTime when a change to any SME MIB table other than the cSmeHostPortTable last occurred.')
cSmeHostPortTableLastChanged = MibScalar((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 7), TimeStamp()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cSmeHostPortTableLastChanged.setStatus('current')
if mibBuilder.loadTexts: cSmeHostPortTableLastChanged.setDescription('The value of sysUpTime when a change to cSmeHostPortTable last occurred.')
cSmeNotifyEnable = MibScalar((1, 3, 6, 1, 4, 1, 9, 9, 632, 1, 1, 8), TruthValue().clone('true')).setMaxAccess("readwrite")
if mibBuilder.loadTexts: cSmeNotifyEnable.setStatus('current')
if mibBuilder.loadTexts: cSmeNotifyEnable.setDescription("This object specifies if the SME notifications should be generated or not. If the value of this object is 'true', then the notifications are generated. If the value of this object is 'false, then the notifications are not generated.")
ciscoSmeInterfaceCreate = NotificationType((1, 3, 6, 1, 4, 1, 9, 9, 632, 0, 1)).setObjects(("IF-MIB", "ifDescr"))
if mibBuilder.loadTexts: ciscoSmeInterfaceCreate.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeInterfaceCreate.setDescription('This notification is generated when a SME interface associated with a local device is created.')
ciscoSmeInterfaceDelete = NotificationType((1, 3, 6, 1, 4, 1, 9, 9, 632, 0, 2)).setObjects(("IF-MIB", "ifDescr"))
if mibBuilder.loadTexts: ciscoSmeInterfaceDelete.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeInterfaceDelete.setDescription('This notification is generated when a SME interface associated with a local device is deleted.')
ciscoSmeClusterNewMaster = NotificationType((1, 3, 6, 1, 4, 1, 9, 9, 632, 0, 3)).setObjects(("CISCO-SME-MIB", "cSmeClusterName"), ("CISCO-SME-MIB", "cSmeClusterMasterInetAddrType"), ("CISCO-SME-MIB", "cSmeClusterMasterInetAddr"))
if mibBuilder.loadTexts: ciscoSmeClusterNewMaster.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeClusterNewMaster.setDescription('This notification is generated when the sending device who is participating in a SME cluster has transitioned to be the master of the cluster.')
ciscoSmeMIBCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 1))
ciscoSmeMIBGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 2))
ciscoSmeMIBCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 1, 1)).setObjects(("CISCO-SME-MIB", "ciscoSmeConfigGroup"), ("CISCO-SME-MIB", "ciscoSmeNotifControlGroup"), ("CISCO-SME-MIB", "ciscoSmeNotifsGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
ciscoSmeMIBCompliance = ciscoSmeMIBCompliance.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeMIBCompliance.setDescription('The compliance statement for entities that implement SME.')
ciscoSmeConfigGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 2, 1)).setObjects(("CISCO-SME-MIB", "cSmeClusterState"), ("CISCO-SME-MIB", "cSmeClusterMasterInetAddrType"), ("CISCO-SME-MIB", "cSmeClusterMasterInetAddr"), ("CISCO-SME-MIB", "cSmeIsMemberLocal"), ("CISCO-SME-MIB", "cSmeClusterInterfaceState"), ("CISCO-SME-MIB", "cSmeInterfaceState"), ("CISCO-SME-MIB", "cSmeInterfaceClusterId"), ("CISCO-SME-MIB", "cSmeHostPortClusterId"), ("CISCO-SME-MIB", "cSmeConfigTableLastChanged"), ("CISCO-SME-MIB", "cSmeHostPortTableLastChanged"), ("CISCO-SME-MIB", "cSmeFabric"), ("CISCO-SME-MIB", "cSmeClusterName"), ("CISCO-SME-MIB", "cSmeInterfaceRowStatus"), ("CISCO-SME-MIB", "cSmeClusterRowStatus"), ("CISCO-SME-MIB", "cSmeMemberIsMaster"), ("CISCO-SME-MIB", "cSmeClusterMemberRowStatus"), ("CISCO-SME-MIB", "cSmeClusterStorageType"), ("CISCO-SME-MIB", "cSmeClusterMemberStorageType"), ("CISCO-SME-MIB", "cSmeInterfaceStorageType"), ("CISCO-SME-MIB", "cSmeHostPortStorageType"), ("CISCO-SME-MIB", "cSmeHostPortRowStatus"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
ciscoSmeConfigGroup = ciscoSmeConfigGroup.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeConfigGroup.setDescription('A collection of objects for SME configuration.')
ciscoSmeNotifControlGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 2, 2)).setObjects(("CISCO-SME-MIB", "cSmeNotifyEnable"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
ciscoSmeNotifControlGroup = ciscoSmeNotifControlGroup.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeNotifControlGroup.setDescription('A collection of objects for controlling SME notification.')
ciscoSmeNotifsGroup = NotificationGroup((1, 3, 6, 1, 4, 1, 9, 9, 632, 2, 2, 3)).setObjects(("CISCO-SME-MIB", "ciscoSmeInterfaceCreate"), ("CISCO-SME-MIB", "ciscoSmeInterfaceDelete"), ("CISCO-SME-MIB", "ciscoSmeClusterNewMaster"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
ciscoSmeNotifsGroup = ciscoSmeNotifsGroup.setStatus('current')
if mibBuilder.loadTexts: ciscoSmeNotifsGroup.setDescription('A collection of objects for notification of SME events.')
mibBuilder.exportSymbols("CISCO-SME-MIB", cSmeClusterMemberStorageType=cSmeClusterMemberStorageType, cSmeClusterTable=cSmeClusterTable, cSmeHostPortStorageType=cSmeHostPortStorageType, PYSNMP_MODULE_ID=ciscoSmeMIB, ciscoSmeNotifsGroup=ciscoSmeNotifsGroup, ciscoSmeConfigGroup=ciscoSmeConfigGroup, cSmeClusterStorageType=cSmeClusterStorageType, ciscoSmeInterfaceCreate=ciscoSmeInterfaceCreate, cSmeClusterEntry=cSmeClusterEntry, cSmeHostPortTable=cSmeHostPortTable, cSmeClusterMembersEntry=cSmeClusterMembersEntry, cSmeIsMemberLocal=cSmeIsMemberLocal, cSmeHostPortName=cSmeHostPortName, cSmeConfigTableLastChanged=cSmeConfigTableLastChanged, cSmeInterfaceIndex=cSmeInterfaceIndex, cSmeClusterInterfaceIndex=cSmeClusterInterfaceIndex, cSmeClusterMemberRowStatus=cSmeClusterMemberRowStatus, ciscoSmeClusterNewMaster=ciscoSmeClusterNewMaster, ciscoSmeMIB=ciscoSmeMIB, cSmeClusterInterfaceState=cSmeClusterInterfaceState, cSmeMemberIsMaster=cSmeMemberIsMaster, ciscoSmeInterfaceDelete=ciscoSmeInterfaceDelete, ciscoSmeMIBGroups=ciscoSmeMIBGroups, cSmeClusterMemberIfEntry=cSmeClusterMemberIfEntry, cSmeClusterMasterInetAddr=cSmeClusterMasterInetAddr, CiscoSmeClusterStatus=CiscoSmeClusterStatus, cSmeMemberInetAddrType=cSmeMemberInetAddrType, ciscoSmeNotifControlGroup=ciscoSmeNotifControlGroup, cSmeClusterMasterInetAddrType=cSmeClusterMasterInetAddrType, cSmeClusterName=cSmeClusterName, cSmeHostPortEntry=cSmeHostPortEntry, ciscoSmeMIBCompliance=ciscoSmeMIBCompliance, cSmeConfig=cSmeConfig, cSmeClusterId=cSmeClusterId, CiscoSmeInterfaceStatus=CiscoSmeInterfaceStatus, cSmeFabric=cSmeFabric, ciscoSmeMIBNotifs=ciscoSmeMIBNotifs, CiscoSmeClusterIndex=CiscoSmeClusterIndex, cSmeInterfaceState=cSmeInterfaceState, cSmeInterfaceStorageType=cSmeInterfaceStorageType, cSmeInterfaceTable=cSmeInterfaceTable, cSmeNotifyEnable=cSmeNotifyEnable, cSmeMemberInetAddr=cSmeMemberInetAddr, cSmeClusterMemberIfTable=cSmeClusterMemberIfTable, cSmeInterfaceEntry=cSmeInterfaceEntry, cSmeClusterMembersTable=cSmeClusterMembersTable, cSmeHostPortRowStatus=cSmeHostPortRowStatus, cSmeInterfaceRowStatus=cSmeInterfaceRowStatus, cSmeInterfaceClusterId=cSmeInterfaceClusterId, cSmeHostPortClusterId=cSmeHostPortClusterId, ciscoSmeMIBConform=ciscoSmeMIBConform, ciscoSmeMIBObjects=ciscoSmeMIBObjects, cSmeHostPortTableLastChanged=cSmeHostPortTableLastChanged, ciscoSmeMIBCompliances=ciscoSmeMIBCompliances, cSmeClusterState=cSmeClusterState, cSmeClusterRowStatus=cSmeClusterRowStatus)
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33,
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33,
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11,
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50,
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28,
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4861,
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11,
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50,
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5819,
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19580,
28,
66,
50,
1326,
2601,
5819,
25166,
19580,
8,
198
] | 2.898766 | 8,752 |
from __future__ import annotations
import typing as tp
from racketinterpreter.classes import data as d
from racketinterpreter.classes import errors as err
from racketinterpreter.predefined._base import BuiltInProc
if tp.TYPE_CHECKING:
from racketinterpreter.classes import ast
from racketinterpreter.processes import Interpreter
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] | 3.62766 | 94 |
import os
import json
from django.core.urlresolvers import reverse
from seaserv import seafile_api
from seahub.test_utils import BaseTestCase
| [
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] | 3.295455 | 44 |
import sys
import json
import numpy as np
solve() | [
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# Generated by Django 3.0.5 on 2020-11-28 14:53
from django.db import migrations, models
import django.db.models.deletion
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] | 2.795455 | 44 |
from jsonmodels_qdyk.fields import StringField, ListField, EmbeddedField
from jsonmodels_qdyk.models import Base
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] | 3.4 | 35 |
'''
_*_coding:utf-8 _*_
@Time :2022/1/28 19:00
@Author : qiaofengsheng
@File :dataset.py
@Software :PyCharm
'''
import os
from PIL import Image
from torch.utils.data import *
from model.utils import utils
from torchvision import transforms
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] | 2.524272 | 103 |
import glob
import shapefile
| [
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] | 3.666667 | 9 |
import os
import hydra
import jax
import jax.numpy as jnp
from flax.serialization import to_state_dict
from omegaconf import DictConfig, OmegaConf
from models.jax import get_model
from neural_kernels.nads import mixed_derivative_nad_decomposition
from utils.misc import get_apply_fn
@hydra.main(config_path="config/compute_nads", config_name="config")
if __name__ == "__main__":
main()
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198,
220,
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] | 2.911765 | 136 |
import pytest
from acousticsim.representations.intensity import Intensity
from numpy.testing import assert_array_almost_equal
@pytest.mark.xfail
| [
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31,
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] | 3.304348 | 46 |
import yaml
import csv
import os
from tqdm import tqdm
import requests
import time
with open("config.yml", "r", encoding="utf-8") as f:
config = yaml.safe_load(f)
API_KEY = config["API_KEY"]
CHANNELS_API_URL = "https://www.googleapis.com/youtube/v3/channels"
PLAYLIST_API_URL = "https://www.googleapis.com/youtube/v3/playlistItems"
OUTPUT_FOLDER = config["output_folder"]
OUTPUT_FIELDS = ["video_id", "title", "video_published_at"]
channel_ids = config["channel_ids"]
channels_params = {
"key": API_KEY,
"part": "contentDetails",
}
playlist_params = {
"key": API_KEY,
"part": "snippet",
"maxResults": 50,
}
for channel_id in channel_ids:
channels_params.update({"id": channel_id})
r = requests.get(
CHANNELS_API_URL,
params=channels_params,
).json()
# the uploads_id indicates the playlist where a channel's uploads are located
uploads_id = r["items"][0]["contentDetails"]["relatedPlaylists"]["uploads"]
playlist_params.update({"playlistId": uploads_id})
r = requests.get(
PLAYLIST_API_URL,
params=playlist_params,
).json()
if "items" in r:
channel_name = r["items"][0]["snippet"]["channelTitle"]
pageToken = r.get("nextPageToken")
print(f"Scraping {channel_name}'s videos:")
pbar = tqdm(total=r["pageInfo"]["totalResults"])
with open(
os.path.join(OUTPUT_FOLDER, f"{channel_name}.csv".replace(os.sep, "_")),
"w",
encoding="utf-8",
) as f:
w = csv.DictWriter(f, fieldnames=OUTPUT_FIELDS)
w.writeheader()
# process first page we already queried
for video in r["items"]:
w.writerow(process_video(video["snippet"]))
pbar.update(len(r["items"]))
# process the rest
while pageToken:
playlist_params.update({"pageToken": pageToken})
r = requests.get(
PLAYLIST_API_URL,
params=playlist_params,
).json()
for video in r["items"]:
w.writerow(process_video(video["snippet"]))
pbar.update(len(r["items"]))
pageToken = r.get("nextPageToken")
time.sleep(0.1)
pbar.close()
# reset pageToken for new channel
playlist_params.update({"pageToken": None})
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] | 2.09792 | 1,154 |
import hyperonpy as hp
from hyperonpy import AtomKind, init_logger
| [
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] | 3.285714 | 21 |
from neopixel import NeoPixel
import machine
import time
np = NeoPixel(machine.Pin(4),1)
for r in range(255):
for g in range(255):
for b in range(255):
np[0]=((r,g,b))
np.write()
time.sleep_ms(10)
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] | 2.158879 | 107 |
# -*- coding: utf-8 -*-
# Written by Olga Moskvyak ([email protected])
import logging
import torch.nn as nn
from torchvision import models as torchmodels # NOQA
from efficientnet_pytorch import EfficientNet
logger = logging.getLogger(__name__)
NAME_EMBEDDING_SIZE = {
'efficientnet-b0': 1280,
'efficientnet-b1': 1280,
'efficientnet-b2': 1408,
'efficientnet-b3': 1536,
'efficientnet-b4': 1792,
'efficientnet-b5': 2048,
'efficientnet-b6': 2304,
'efficientnet-b7': 2560,
}
class EfficientNetReid(nn.Module):
"""Re-id model with EfficientNet as a convolutional feature extractor.
Input:
core_name (string): name of core model, class from torchvision.models
"""
def _construct_fc_layer(self, fc_dims, input_dim, dropout_p=None):
"""Constructs fully connected layer
Args:
fc_dims (list or tuple): dimensions of fc layers, if None, no fc layers are constructed
input_dim (int): input dimension
dropout_p (float): dropout probability, if None, dropout is unused
"""
if fc_dims is None:
self.feature_dim = input_dim
return None
assert isinstance(
fc_dims, (list, tuple)
), 'fc_dims must be either list or tuple, but got {}'.format(type(fc_dims))
layers = []
for dim in fc_dims:
layers.append(nn.Linear(input_dim, dim))
layers.append(nn.BatchNorm1d(dim))
layers.append(nn.ReLU(inplace=True))
if dropout_p is not None:
layers.append(nn.Dropout(p=dropout_p))
input_dim = dim
self.feature_dim = fc_dims[-1]
return nn.Sequential(*layers)
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220,
220,
1441,
299,
77,
13,
44015,
1843,
46491,
75,
6962,
8,
628
] | 2.216113 | 782 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Refer to "https://hibiki-press.tech/algorithm/sum_2darray/698"
@author: hibikisan
"""
import random
if __name__ == '__main__':
dim = (5, 3) # the dimension of original data array
data = []
for i in range(dim[0]):
data.append([random.randint(0, 10) for n in range(dim[1])])
#print(data)
print('----Original data----')
for l in data:
print(l)
sum_data = raw_sum(data)
#print(sum_data)
print('----Adding the colomn of sum of each raw----')
for l in sum_data:
print(l) | [
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62,
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25,
198,
220,
220,
220,
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220,
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3601,
7,
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8
] | 2.188406 | 276 |
import matplotlib.pyplot as plt
import os
import numpy as np
| [
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] | 3.1 | 20 |
# Ω*
# ■ ■■■■■
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"""
Copyright (c) 2020.5.28 [el.ideal-ideas]
This software is released under the MIT License.
see LICENSE.txt or following URL.
https://www.el-ideal-ideas.com/MocaSystem/LICENSE/
"""
# -- Imports --------------------------------------------------------------------------
from typing import *
from pathlib import Path
from sys import stdout
from traceback import format_exc
from datetime import datetime, date
from .moca_variables import NEW_LINE, tz
from .moca_utils import location
from .moca_base_class import MocaClassCache, MocaNamedInstance
from multiprocessing import current_process
from threading import get_ident
from aiofiles import open as aio_open
from asyncio import get_event_loop
# -------------------------------------------------------------------------- Imports --
# -- Variables --------------------------------------------------------------------------
# -------------------------------------------------------------------------- Variables --
# -- LogLevel --------------------------------------------------------------------------
class LogLevel(object):
"""The logging level for Moca Log Class."""
DEBUG = 0
INFO = 1
WARNING = 2
ERROR = 3
CRITICAL = 4
@classmethod
@classmethod
# -------------------------------------------------------------------------- LogLevel --
# -- Moca File Log --------------------------------------------------------------------------
class MocaFileLog(MocaClassCache, MocaNamedInstance):
"""
Write logs to the log file.
Attributes
----------
self._filename: Path
The file path of the log file.
self._exc_filename: Path
the file path to save exceptions.
self._rotate: bool
rotate the log file or not.
self._file
the file object to write logs.
self._exc_file
the file object to write exceptions.
self._level: int
current logging level.
self._pid: Optional[int]
the process id.
self._last_modified: date
the last modification date.
"""
LogLevel = LogLevel
def __init__(self, filename: Union[str, Path], exc_filename: Union[str, Path], log_rotate: bool = True):
"""
:param filename: the file path of the log file.
:param exc_filename: the file path to save exceptions.
:param log_rotate: rotate the log file automatically.
"""
MocaClassCache.__init__(self)
MocaNamedInstance.__init__(self)
# set log rotation flag
self._rotate: bool = log_rotate
# set file path
self._filename: Path = Path(filename)
self._exc_filename: Path = Path(exc_filename)
# set file object
self._file = open(str(self._filename), mode='a', encoding='utf-8')
self._exc_file = open(str(self._exc_filename), mode='a', encoding='utf-8')
# set log level
self._level: int = LogLevel.INFO
# set process id
self._pid: Optional[int] = current_process().pid
# set last modified time
self._last_modified: date = datetime.now(tz=tz).date()
@property
@property
@property
@property
@property
@property
def start_log_rotate(self) -> None:
"""Start the auto-rotation"""
self._rotate = True
def stop_log_rotate(self) -> None:
"""Stop the auto-rotation"""
self._rotate = False
def set_log_level(self, level: int) -> None:
"""Set the log level."""
self._level = level
self.save(f"MocaFileLog: Logging level changed to {LogLevel.int_to_str(level)}!", LogLevel.INFO)
def save(self, message: str, level: int) -> None:
"""
Save a log message to the log file.
:param message: the log message.
:param level: the log level.
:return: None
Log Format
----------
[loglevel](time)<filename|caller|line number|process id|thread id>message
"""
if level >= self._level:
filename, caller, line = location()
current_time = datetime.now(tz=tz)
current_date = current_time.date()
if self._rotate and (current_date != self._last_modified):
self.rotate_log_file()
self._last_modified = current_date
msg = f"[{LogLevel.int_to_str(level)}]({str(current_time)})" \
f"<{filename}|{caller}|{line}|{self._pid or 0}|{get_ident()}>" \
f"{message}"
print(msg, end=NEW_LINE, file=self._file, flush=True)
error = format_exc()
if not error.startswith('NoneType'):
print(error, end='', file=self._exc_file, flush=True)
def save_exception(self) -> None:
"""Save the exception traceback information."""
print(format_exc(), end='', file=self._exc_file, flush=True)
def start_dev_mode(self) -> None:
"""Show all logs on the console."""
file = self._file
exc_file = self._exc_file
self._file = stdout
self._exc_file = stdout
file.close()
exc_file.close()
self.save_cache('log_level', self._level)
self._level = LogLevel.DEBUG
self.save("MocaFileLog: Development mode started!", LogLevel.INFO)
def stop_dev_mode(self) -> None:
"""Stop development mode."""
self.save("MocaFileLog: Development mode stopped!", LogLevel.INFO)
self._level = self.get_cache('log_level')
self._file = open(str(self._filename), mode='a', encoding='utf-8')
self._exc_file = open(str(self._exc_filename), mode='a', encoding='utf-8')
def get_all_logs(self) -> str:
"""Return today's logs'"""
with open(str(self._filename), mode='r', encoding='utf-8') as log_file:
return log_file.read()
def get_all_logs_as_list(self) -> List[str]:
"""Return a list of today's logs."""
return self.get_all_logs().splitlines()
def get_all_exceptions(self) -> str:
"""Return today's exceptions'"""
with open(str(self._exc_filename), mode='r', encoding='utf-8') as exc_file:
return exc_file.read()
def clear_logs(self) -> None:
"""Clear today's logs"""
self._file.close()
self._exc_file.close()
self._filename.unlink()
self._exc_filename.unlink()
self._file = open(str(self._filename), mode='a', encoding='utf-8')
self._exc_file = open(str(self._exc_filename), mode='a', encoding='utf-8')
self.save("MocaFileLog: Cleared logs!", LogLevel.INFO)
def rotate_log_file(self) -> None:
"""Rotate the log file."""
self._file.close()
self._exc_file.close()
time = str(datetime.now(tz=tz).date())
new_filename = self._filename.parent.joinpath(
f"{'.'.join(self._filename.name.split('.')[:-1])}-{time}.{self._filename.name.split('.')[-1]}"
)
new_exc_filename = self._exc_filename.parent.joinpath(
f"{'.'.join(self._exc_filename.name.split('.')[:-1])}-{time}.{self._exc_filename.name.split('.')[-1]}"
)
if new_filename.is_file():
new_filename.unlink()
if new_exc_filename.is_file():
new_exc_filename.unlink()
self._filename.rename(str(new_filename))
self._exc_filename.rename(str(new_exc_filename))
self._file = open(str(self._filename), mode='a', encoding='utf-8')
self._exc_file = open(str(self._exc_filename), mode='a', encoding='utf-8')
def get_old_logs(self, year: int, month: int, day: int) -> Optional[str]:
"""Return the old logs as list. If can't found the file, return None."""
old_filename, _ = self._old_filename(year, month, day)
if old_filename.is_file():
with open(str(old_filename), mode='r', encoding='utf-8') as log_file:
return log_file.read()
else:
return None
def get_old_logs_as_list(self, year: int, month: int, day: int) -> Optional[List[str]]:
"""Return the old logs. If can't found the file, return None."""
old_logs = self.get_old_logs(year, month, day)
if old_logs is None:
return None
else:
return old_logs.splitlines()
def get_old_exceptions(self, year: int, month: int, day: int) -> Optional[str]:
"""Return the old exceptions, If can't found the file, return None."""
_, old_filename = self._old_filename(year, month, day)
if old_filename.is_file():
with open(str(old_filename), mode='r', encoding='utf-8') as log_file:
return log_file.read()
else:
return None
def _old_filename(self, year: int, month: int, day: int) -> Tuple[Path, Path]:
"""Return the old filename."""
time = str(datetime(year, month, day).date())
exc_old_filename = self._exc_filename.parent.joinpath(
f"{'.'.join(self._exc_filename.name.split('.')[:-1])}-{time}.{self._exc_filename.name.split('.')[-1]}"
)
old_filename = self._filename.parent.joinpath(
f"{'.'.join(self._filename.name.split('.')[:-1])}-{time}.{self._filename.name.split('.')[-1]}"
)
return old_filename, exc_old_filename
# -------------------------------------------------------------------------- Moca File Log --
# -- Moca Asynchronous File Log --------------------------------------------------------------------------
class MocaAsyncFileLog(MocaClassCache, MocaNamedInstance):
"""
Write logs to the log file asynchronously.
Attributes
----------
self._filename: Path
The file path of the log file.
self._exc_filename: Path
the file path to save exceptions.
self._rotate: bool
rotate the log file or not.
self._file
the file object to write logs.
self._exc_file
the file object to write exceptions.
self._level: int
current logging level.
self._pid: Optional[int]
the process id.
self._last_modified: date
the last modification date.
self._dev_flag: bool
the development flag.
"""
LogLevel = LogLevel
def __init__(self, filename: Union[str, Path], exc_filename: Union[str, Path], log_rotate: bool = True):
"""
:param filename: the file path of the log file.
:param exc_filename: the file path to save exceptions.
:param log_rotate: rotate the log file automatically.
"""
MocaClassCache.__init__(self)
MocaNamedInstance.__init__(self)
# set log rotation flag
self._rotate: bool = log_rotate
# set file path
self._filename: Path = Path(filename)
self._exc_filename: Path = Path(exc_filename)
# set log level
self._level: int = LogLevel.INFO
# set process id
self._pid: Optional[int] = current_process().pid
# set last modified time
self._last_modified: date = datetime.now(tz=tz).date()
# set development flag
self._dev_flag: bool = False
# set file object
self._file = None
self._exc_file = None
@property
@property
@property
@property
@property
@property
def start_log_rotate(self) -> None:
"""Start the auto-rotation"""
self._rotate = True
def stop_log_rotate(self) -> None:
"""Stop the auto-rotation"""
self._rotate = False
async def set_log_level(self, level: int) -> None:
"""Set the log level."""
self._level = level
await self.save(f"MocaAsyncFileLog: Logging level changed to {LogLevel.int_to_str(level)}!", LogLevel.INFO)
async def save(self, message: str, level: int) -> None:
"""
Save a log message to the log file.
:param message: the log message.
:param level: the log level.
:return: None
Log Format
----------
[loglevel](time)<filename|caller|line number|process id|thread id>message
"""
if level >= self._level:
filename, caller, line = location()
current_time = datetime.now(tz=tz)
current_date = current_time.date()
if self._rotate and (current_date != self._last_modified):
await self.rotate_log_file()
self._last_modified = current_date
msg = f"[{LogLevel.int_to_str(level)}]({str(current_time)})" \
f"<{filename}|{caller}|{line}|{self._pid or 0}|{get_ident()}>" \
f"{message}"
if self._dev_flag:
print(msg, end=NEW_LINE)
else:
await self._file.write(msg)
await self._file.write(NEW_LINE)
await self._file.flush()
error = format_exc()
if not error.startswith('NoneType'):
if self._dev_flag:
print(error, end='')
else:
await self._exc_file.write(error)
await self._exc_file.flush()
async def save_exception(self) -> None:
"""Save the exception traceback information."""
if self._dev_flag:
print(format_exc(), end='')
else:
await self._exc_file.write(format_exc())
await self._exc_file.flush()
async def start_dev_mode(self) -> None:
"""Show all logs on the console."""
self.save_cache('log_level', self._level)
self._level = LogLevel.DEBUG
self._dev_flag = True
await self.save("MocaAsyncFileLog: Development mode started!", LogLevel.INFO)
async def stop_dev_mode(self) -> None:
"""Stop development mode."""
self._dev_flag = False
await self.save("MocaAsyncFileLog: Development mode stopped!", LogLevel.INFO)
self._level = self.get_cache('log_level')
async def get_all_logs(self) -> str:
"""Return today's logs'"""
async with aio_open(str(self._filename), mode='r', encoding='utf-8') as log_file:
return await log_file.read()
async def get_all_logs_as_list(self) -> List[str]:
"""Return a list of today's logs."""
logs = await self.get_all_logs()
return logs.splitlines()
async def get_all_exceptions(self) -> str:
"""Return today's exceptions'"""
async with aio_open(str(self._exc_filename), mode='r', encoding='utf-8') as exc_file:
return await exc_file.read()
async def clear_logs(self) -> None:
"""Clear today's logs"""
await self._file.close()
await self._exc_file.close()
self._filename.unlink()
self._exc_filename.unlink()
await self._init()
await self.save("MocaAsyncFileLog: Cleared logs!", LogLevel.INFO)
async def rotate_log_file(self) -> None:
"""Rotate the log file."""
await self._file.close()
await self._exc_file.close()
time = str(datetime.now(tz=tz).date())
new_filename = self._filename.parent.joinpath(
f"{'.'.join(self._filename.name.split('.')[:-1])}-{time}.{self._filename.name.split('.')[-1]}"
)
new_exc_filename = self._exc_filename.parent.joinpath(
f"{'.'.join(self._exc_filename.name.split('.')[:-1])}-{time}.{self._exc_filename.name.split('.')[-1]}"
)
if new_filename.is_file():
new_filename.unlink()
if new_exc_filename.is_file():
new_exc_filename.unlink()
self._filename.rename(str(new_filename))
self._exc_filename.rename(str(new_exc_filename))
await self._init()
async def get_old_logs(self, year: int, month: int, day: int) -> Optional[str]:
"""Return the old logs as list. If can't found the file, return None."""
old_filename, _ = self._old_filename(year, month, day)
if old_filename.is_file():
async with aio_open(str(old_filename), mode='r', encoding='utf-8') as log_file:
return await log_file.read()
else:
return None
async def get_old_logs_as_list(self, year: int, month: int, day: int) -> Optional[List[str]]:
"""Return the old logs. If can't found the file, return None."""
old_logs = await self.get_old_logs(year, month, day)
if old_logs is None:
return None
else:
return old_logs.splitlines()
async def get_old_exceptions(self, year: int, month: int, day: int) -> Optional[str]:
"""Return the old exceptions, If can't found the file, return None."""
_, old_filename = self._old_filename(year, month, day)
if old_filename.is_file():
async with aio_open(str(old_filename), mode='r', encoding='utf-8') as log_file:
return await log_file.read()
else:
return None
def _old_filename(self, year: int, month: int, day: int) -> Tuple[Path, Path]:
"""Return the old filename."""
time = str(datetime(year, month, day).date())
exc_old_filename = self._exc_filename.parent.joinpath(
f"{'.'.join(self._exc_filename.name.split('.')[:-1])}-{time}.{self._exc_filename.name.split('.')[-1]}"
)
old_filename = self._filename.parent.joinpath(
f"{'.'.join(self._filename.name.split('.')[:-1])}-{time}.{self._filename.name.split('.')[-1]}"
)
return old_filename, exc_old_filename
# -------------------------------------------------------------------------- Moca Asynchronous File Log --
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] | 2.22027 | 8,140 |
from NN import NN
import numpy as np
import matplotlib.pylab as plt
layer_sizes = [2,4,1]
activations = ['relu','sigmoid']
N = NN(layer_sizes,activations)
#print(N.biases[4].shape)
input = np.array([[1,2,3],[3,5,4]])
N.forward_prop(input)
N.back_prop(np.array([[1,2,3]]))
N.derivative_check(m=6,verbose=False)
N.update_weights()
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19,
11907,
8,
198,
198,
45,
13,
11813,
62,
22930,
7,
15414,
8,
198,
45,
13,
1891,
62,
22930,
7,
37659,
13,
18747,
26933,
58,
16,
11,
17,
11,
18,
11907,
4008,
198,
45,
13,
1082,
452,
876,
62,
9122,
7,
76,
28,
21,
11,
19011,
577,
28,
25101,
8,
198,
45,
13,
19119,
62,
43775,
3419,
628,
198
] | 2.154839 | 155 |
from classes.structures.Atribuicao import Atribuicao
from classes.structures.Cabecalho import Cabecalho
from classes.structures.Escreva import Escreva
from classes.structures.Indice import Indice
from classes.structures.InicializacaoDeVariaveis import InicializacaoDeVariaveis
from classes.structures.Leia import Leia
from classes.structures.Repita import Repita
from classes.structures.Retorna import Retorna
from classes.structures.Se import Se
| [
6738,
6097,
13,
7249,
942,
13,
2953,
822,
84,
3970,
78,
1330,
1629,
822,
84,
3970,
78,
198,
6738,
6097,
13,
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942,
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34,
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544,
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41212,
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942,
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7249,
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1211,
64,
198,
6738,
6097,
13,
7249,
942,
13,
4653,
1330,
1001,
198
] | 3.286765 | 136 |
#!/usr/bin/env python
#
# 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-2.0OA
#
# Authors:
# - Wen Guan, <[email protected]>, 2020 - 2021
try:
import ConfigParser
except ImportError:
import configparser as ConfigParser
# try:
# from urllib import quote
# except ImportError:
# from urllib.parse import quote
import copy
import os
import re
import traceback
from idds.common import exceptions
from idds.common.constants import (TransformType, CollectionType, CollectionStatus,
ProcessingStatus, WorkStatus, ContentStatus)
from idds.workflow.work import Work, Processing
from idds.workflow.workflow import Condition
| [
2,
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220,
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220,
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28403,
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8,
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13,
1818,
11125,
13,
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11125,
1330,
24295,
628,
198
] | 2.992857 | 280 |
"""
Linux on Hyper-V and Azure Test Code, ver. 1.0.0
Copyright (c) Microsoft Corporation
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.
See the Apache Version 2.0 License for specific language governing
permissions and limitations under the License.
"""
from __future__ import print_function
import logging
import re
import sys
import csv
import fileinput
try:
import xml.etree.cElementTree as ElementTree
except ImportError:
import xml.etree.ElementTree as ElementTree
logger = logging.getLogger(__name__)
class ParseXML(object):
"""Class used to parse a specific xml test suite file
"""
def get_tests(self):
"""Iterates through the xml file looking for <test> sections
and initializes a dict for every test case returning them in
the end
Dict structure:
{ 'testName' : {} }
"""
tests_dict = dict()
for test in self.root.iter('suiteTest'):
tests_dict[test.text.lower()] = dict()
for test_case in self.root.iter('test'):
# Check if testCase was not commented out
if test_case.find('testName').text.lower() == \
test.text.lower():
logger.debug('Getting test details for - %s', test.text)
tests_dict[test.text.lower()] = \
self.get_test_details(test_case)
return tests_dict
@staticmethod
def get_test_details(test_root):
"""Gets and an XML object and iterates through it
parsing the test details into a dictionary
Dict structure:
{ 'testProperty' : [ value(s) ] }
"""
test_dict = dict()
for test_property in test_root.getchildren():
if test_property.tag == 'testName':
continue
elif not test_property.getchildren():
test_dict[test_property.tag.lower()] = \
test_property.text.strip().split()
else:
test_dict[test_property.tag.lower()] = list()
for item in test_property.getchildren():
if test_property.tag.lower() == 'testparams':
parameter = item.text.split('=')
test_dict[test_property.tag.lower()].append(
(parameter[0], parameter[1])
)
else:
test_dict[test_property.tag.lower()].append(item.text)
return test_dict
def get_vms(self):
"""Method searches for the 'vm' sections in the XML file
saving a dict for each vm found.
Dict structure:
{
vm_name: { vm_details }
}
"""
vm_dict = dict()
for machine in self.root.iter('vm'):
vm_dict[machine.find('vmName').text.lower()] = {
'hvServer': machine.find('hvServer').text.lower(),
'os': machine.find('os').text.lower()
}
return vm_dict
# TODO(bogdancarpusor): Narrow exception field
@staticmethod
def parse_from_string(xml_string):
"""Static method that parses xml content from a string
The method is used to parse the output of the PS command
that is sent to the vm in order to get more details
It returns a dict with the following structure:
{
vm_property: value
}
"""
try:
logger.debug('Converting XML string from KVP Command')
root = ElementTree.fromstring(xml_string.strip())
prop_name = ''
prop_value = ''
for child in root:
if child.attrib['NAME'] == 'Name':
prop_name = child[0].text
elif child.attrib['NAME'] == 'Data':
prop_value = child[0].text
return prop_name, prop_value
except RuntimeError:
logger.error('Failed to parse XML string,', exc_info=True)
logger.info('Terminating execution')
sys.exit(0)
def parse_ica_log(log_path):
""" Parser for the generated log file after a lisa run - ica.log
The method iterates until the start of the test outcome section. After that
it searches, using regex, for predefined fields and saves them in a
dict structure.
:param log_path:
:return:
"""
logger.debug(
'Iterating through %s file until the test results part', log_path
)
parsed_ica = dict()
parsed_ica['vms'] = dict()
parsed_ica['tests'] = dict()
with open(log_path, 'r') as log_file:
for line in log_file:
if line.strip() == 'Test Results Summary':
break
# Get timestamp
parsed_ica['timestamp'] = re.search('([0-9/]+) ([0-9:]+)',
log_file.next()).group(0)
vm_name = ""
for line in log_file:
line = line.strip().lower()
if re.search("^vm:", line) and len(line.split()) == 2:
vm_name = line.split()[1]
parsed_ica['vms'][vm_name] = dict()
# Check if there are any details about the VM
try:
parsed_ica['vms'][vm_name]['TestLocation'] = 'Hyper-V'
except KeyError:
parsed_ica['vms'][vm_name] = dict()
parsed_ica['vms'][vm_name]['TestLocation'] = 'Azure'
elif re.search('^test', line) and \
re.search('(success$|failed$|aborted$)', line):
test = line.split()
try:
parsed_ica['tests'][test[1].lower()] = (vm_name, test[3])
except KeyError:
logging.debug('Test %s was not listed in Test Suites '
'section.It will be ignored from the final'
'results', test)
elif re.search('^os', line):
parsed_ica['vms'][vm_name]['hostOS'] = line.split(':')[1].strip()
elif re.search('^server', line):
parsed_ica['vms'][vm_name]['hvServer'] = line.split(':')[1].strip()
elif re.search('^logs can be found at', line):
parsed_ica['logPath'] = line.split()[-1]
elif re.search('^lis version', line):
parsed_ica['lisVersion'] = line.split(':')[1].strip()
return parsed_ica
def parse_from_csv(csv_path):
"""
Strip and read csv file into a dict data type.
:param csv_path: csv file path
:return: <list of dict> e.g. [{'t_col1': 'val1',
't_col2': 'val2',
...
},
...]
None - on error
"""
# python [2.7.10, 3.0) does not support context manager for fileinput
# strip csv of empty spaces or tabs
f = fileinput.input(csv_path, inplace=True)
for line in f:
# redirect std to file write
print(' '.join(line.split()))
f.close()
list_csv_dict = []
with open(csv_path, 'rb') as f:
try:
csv_dialect = csv.Sniffer().sniff(f.read(), delimiters=";, ")
except Exception as e:
logger.error('Error reading csv file {}: {}'.format(csv_path, e))
return None
f.seek(0)
reader = csv.DictReader(f, dialect=csv_dialect)
for csv_dict in reader:
list_csv_dict.append(csv_dict)
return list_csv_dict
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] | 2.12165 | 3,806 |
#
# Autogenerated by Thrift Compiler (0.11.0)
#
# DO NOT EDIT UNLESS YOU ARE SURE THAT YOU KNOW WHAT YOU ARE DOING
#
# options string: py
#
from thrift.Thrift import TType, TMessageType, TFrozenDict, TException, TApplicationException
from thrift.protocol.TProtocol import TProtocolException
from thrift.TRecursive import fix_spec
import sys
import adaptive.interface.constants.datatypes.ttypes
import adaptive.interface.constants.exceptions.ttypes
import adaptive.interface.ad_event.ttypes
import adaptive.interface.ad_data.ttypes
import adaptive.interface.biz_data.ttypes
import adaptive.interface.user_data.ttypes
from thrift.transport import TTransport
all_structs = []
class UserAdRequest(object):
"""
Attributes:
- uid
- sysinfo
"""
class UserAdResponse(object):
"""
Attributes:
- timestamp
- adReqId
- adids
"""
class BizAdRequest(object):
"""
Attributes:
- bizid
- ad_info
- daily_budget
- lifetime_days
"""
class BizAdResponse(object):
"""
Attributes:
- timestamp
- adid
"""
all_structs.append(UserAdRequest)
UserAdRequest.thrift_spec = (
None, # 0
(1, TType.I32, 'uid', None, None, ), # 1
(2, TType.STRUCT, 'sysinfo', [adaptive.interface.user_data.ttypes.SystemInformation, None], None, ), # 2
)
all_structs.append(UserAdResponse)
UserAdResponse.thrift_spec = (
None, # 0
(1, TType.I32, 'timestamp', None, None, ), # 1
(2, TType.I32, 'adReqId', None, None, ), # 2
(3, TType.MAP, 'adids', (TType.I32, None, TType.I32, None, False), None, ), # 3
)
all_structs.append(BizAdRequest)
BizAdRequest.thrift_spec = (
None, # 0
(1, TType.I32, 'bizid', None, None, ), # 1
(2, TType.STRUCT, 'ad_info', [adaptive.interface.ad_data.ttypes.AdCreation, None], None, ), # 2
(3, TType.DOUBLE, 'daily_budget', None, None, ), # 3
(4, TType.I32, 'lifetime_days', None, None, ), # 4
)
all_structs.append(BizAdResponse)
BizAdResponse.thrift_spec = (
None, # 0
(1, TType.I32, 'timestamp', None, None, ), # 1
(2, TType.I32, 'adid', None, None, ), # 2
)
fix_spec(all_structs)
del all_structs
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312,
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8,
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62,
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82,
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33,
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11,
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11,
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220,
220,
357,
17,
11,
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6030,
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40,
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11,
10612,
220,
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362,
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8,
198,
13049,
62,
16684,
7,
439,
62,
7249,
82,
8,
198,
12381,
477,
62,
7249,
82,
198
] | 2.43982 | 889 |
import tensorflow as tf
import os
import pathlib
import numpy as np
if __name__ == '__main__':
import matplotlib.pyplot as plt
batch_size = 8
sample_batch_num = 4
dataset = CalligraphyDataset(data_dir='./data/chinese-calligraphy-dataset/',
character_csv='./data/label_character.csv',
batch_size=8,
repeat=False,
shuffle=False)
plt.figure()
plt.rcParams['font.sans-serif']=['SimHei']
for i_batch, (images, labels) in enumerate(dataset.dataset):
if i_batch >= sample_batch_num:
break
labels = np.array([dataset.characters[item.numpy().decode('utf-8')] for item in labels])
images = images.numpy()
print(i_batch, images.shape, labels.shape)
for i in range(images.shape[0]):
ax = plt.subplot(sample_batch_num, batch_size, i_batch * batch_size + i + 1)
ax.axis('off')
ax.set_title(list(dataset.characters.keys())[labels[i]])
plt.imshow(images[i])
plt.show()
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458,
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] | 1.935154 | 586 |
__version__ = '1.0.0-rc.1'
__author__ = 'Lorenzo Menghini, Martino Pulici, Alessandro Stockman, Luca Zucchini'
import argparse
import pandas as pd
import torch
from rate_severity_of_toxic_comments.model import create_model
from rate_severity_of_toxic_comments.utilities import parse_config, process_config
DEFAULT_CONFIG_FILE_PATH = 'config/default.json'
LOCAL_CONFIG_FILE_PATH = 'config/local.json'
BEST_MODELS_FILE_PATH = 'config/best_models.json'
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--model_file')
args = parser.parse_args()
CONFIG = parse_config(DEFAULT_CONFIG_FILE_PATH, LOCAL_CONFIG_FILE_PATH)
support_bag = process_config(pd.DataFrame(), CONFIG)
run_mode = CONFIG['options']['run_mode']
device = torch.device('cuda' if torch.cuda.is_available()
and CONFIG['options']['use_gpu'] else 'cpu')
model = create_model(
run_mode,
CONFIG['training'],
CONFIG[run_mode],
support_bag)
model.load_state_dict(torch.load(args.model_file))
model.to(device)
query = True
while query:
query = input('Type comment:')
inputs = support_bag['tokenizer'](
query,
truncation=True,
add_special_tokens=True,
max_length=128,
padding='max_length'
)
ids = inputs['input_ids']
mask = inputs['attention_mask']
score = model(
ids.unsqueeze(
dim=0).to(device), mask.unsqueeze(
dim=0).to(device), torch.tensor(
[0]).to(device))
print('Score:', score.item())
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5391,
28,
15,
737,
1462,
7,
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828,
28034,
13,
83,
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7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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220,
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220,
220,
685,
15,
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1462,
7,
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198,
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3601,
10786,
26595,
25,
3256,
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28955,
198
] | 2.23036 | 751 |
import argparse
import os
import sys
import unittest
from typing import List
import click # type: ignore
import coverage # type: ignore
from flask_migrate import Migrate # type: ignore
from application import create_app, sqla # type: ignore
from application.cmd import cre_main
# Hacky solutions to make this both a command line application with argparse and a flask application
app = create_app(mode=os.getenv("FLASK_CONFIG") or "default")
migrate = Migrate(app, sqla, render_as_batch=True)
# flask <x> commands
@app.cli.command() # type: ignore
@click.option(
"--cover/--no-cover", default=False, help="Run tests under code coverage."
) # type: ignore
@click.argument("test_names", nargs=-1) # type: ignore
# python cre.py --<x> commands
if __name__ == "__main__": # if we're called directly
main()
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11,
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611,
356,
821,
1444,
3264,
198,
220,
220,
220,
1388,
3419,
198
] | 3.176245 | 261 |
import fpga
import modelsim
import config_manager
import ascii_ui
import os
import time
import pathlib
import keyboard
screenIO = ascii_ui.ScreenIO()
screenIO.renderMessage("Config loading...")
configuration = initialise(screenIO)
run_lib(screenIO, configuration)
run_compile(screenIO, configuration)
run_simulation(screenIO, configuration)
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'''
rrsig_orphan - Record test: RrsigOrphan
.. Copyright (c) 2015 Neustar, Inc. All rights reserved.
.. See COPYRIGHT.txt for full notice. See LICENSE.txt for terms and conditions.
'''
import time
import dns.rdtypes.ANY.RRSIG
import dns.dnssec
import dns_sprockets_lib.validators as validators
class RrsigOrphan(validators.RecTest):
# pylint: disable=too-few-public-methods
'''
Checks for orphan RRSIGs.
'''
TEST_DNSSECTYPE = True
TEST_RRTYPE = 'RRSIG'
TEST_OPTARGS = {
'now': (None, 'Time to use for validating RRSIG time windows, e.g. 20150101123000'),
'now_offset': (None, 'Number of seconds to offset the "now" value, e.g. -86400)')}
# end of file
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] | 2.473684 | 285 |
import itertools
import os
from seasight_forecasting import global_vars
from threading import Thread
from time import sleep, time
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# -*- coding: utf-8 -*-
# This file is part of ModulemdTranslationHelpers
# Copyright (C) 2018 Stephen Gallagher
#
# Fedora-License-Identifier: MIT
# SPDX-2.0-License-Identifier: MIT
# SPDX-3.0-License-Identifier: MIT
#
# This program is free software.
# For more information on the license, see COPYING.
# For more information on free software, see
# <https://www.gnu.org/philosophy/free-sw.en.html>.
from __future__ import print_function
import click
import gi
import os
import os.path
import xmlrpc.client
from babel.messages import pofile
gi.require_version('Modulemd', '1.0')
from gi.repository import Modulemd
from ModulemdTranslationHelpers import get_module_catalog_from_tags
from ModulemdTranslationHelpers import get_modulemd_translations
from ModulemdTranslationHelpers.Fedora import KOJI_URL
from ModulemdTranslationHelpers.Fedora import get_fedora_rawhide_version
from ModulemdTranslationHelpers.Fedora import get_tags_for_fedora_branch
##############################################################################
# Common options for all commands #
##############################################################################
@click.group()
@click.option('--debug/--no-debug', default=False)
@click.option('-k', '--koji-url',
default=KOJI_URL,
type=str, help="The URL of the Koji build system.",
show_default=True,
metavar="<URL>")
@click.option('-b', '--branch', default="rawhide", type=str,
help="The distribution release",
metavar="<branch_name>")
@click.pass_context
def cli(ctx, debug, branch, koji_url):
"""Tools for managing modularity translations."""
ctx.obj = dict()
ctx.obj['debug'] = debug
ctx.obj['session'] = xmlrpc.client.ServerProxy(koji_url)
ctx.obj['branch'] = branch
if branch == "rawhide":
ctx.obj['branch'] = get_fedora_rawhide_version(ctx.obj['session'])
##############################################################################
# Subcommands #
##############################################################################
##############################################################################
# `ModulemdTranslationHelpers extract` #
##############################################################################
@cli.command()
@click.option('-p', '--pot-file',
default='fedora-modularity-translations.pot',
type=click.File(mode='wb', atomic=True, lazy=True),
show_default=True,
metavar="<PATH>",
help="Path to the portable object template (POT) file to hold "
"the translatable strings.")
@click.pass_context
def extract(ctx, pot_file):
"""
Extract translatable strings from modules.
Extract translations from all modules included in a particular version of
Fedora or EPEL.
"""
catalog = get_module_catalog_from_tags(
ctx.parent.obj['session'], get_tags_for_fedora_branch(
ctx.parent.obj['branch']),
debug=ctx.parent.obj['debug'])
pofile.write_po(pot_file, catalog, sort_by_file=True)
print("Wrote extracted strings for %s to %s" % (ctx.obj['branch'],
pot_file.name))
##############################################################################
# `ModulemdTranslationHelpers generate_metadata` #
##############################################################################
@cli.command()
@click.option('-d', '--pofile-dir',
default='.',
help="Path to a directory containing portable object (.po) "
"translation files",
type=click.Path(exists=True, dir_okay=True, resolve_path=True,
readable=True))
@click.option('-y', '--yaml-file',
default='fedora-modularity-translations.yaml',
type=click.File(mode='wb', atomic=True, lazy=True),
show_default=True,
metavar="<PATH>",
help="Path to the YAML file to hold the translated strings in "
"modulemd-translations format.")
@click.pass_context
def generate_metadata(ctx, pofile_dir, yaml_file):
"""
Generate modulemd-translations YAML.
:return: 0 on successful creation of modulemd-translation,
nonzero on failure.
"""
# Process all .po files in the provided directory
translation_files = [f for f in os.listdir(pofile_dir) if
os.path.isfile((os.path.join(pofile_dir, f))) and
f.endswith(".po")]
translations = get_modulemd_translations(translation_files,
debug=ctx.parent.obj['debug'])
yaml_file.write(Modulemd.dumps(sorted(translations)).encode('utf-8'))
print("Wrote modulemd-translations YAML to %s" % yaml_file.name)
if __name__ == "__main__":
cli(obj={})
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] | 2.506143 | 2,035 |
import datetime
from sqlalchemy import Column, Integer, Text, Table, DateTime
from sqlalchemy.orm import relationship, backref
from sqlalchemy.ext.declarative import declarative_base
base = declarative_base()
certs = Table(
"ssl_certificates",
base.metadata,
Column("cert_id", Integer, primary_key=True, nullable=False),
Column("cert_hostname", Text, nullable=False),
Column("cert_serial_number", Text, nullable=False)
)
| [
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] | 3 | 148 |
"""Rigging data storing.
This script has functions that allows maya to save the rigging tool process
results inside an empty network node that doesn't have transform info.
It is in charge of creating the node and the attributes to store the data.
It can also query the data or delete the attributes.
We are using this module to save the names of the controllers across the rigging
process and the groups that contain them. This way we can get the data later
to parent them correctly to the mainController. This allows us to create multiple
rigs of the same type (multiple wheels, treads, etc) and rig creation after
parenting (add more wheels or arms)
"""
from maya import cmds
class NodeData():
"""A class used to represent a Node that saves rigging data to Maya
It takes the name of the controllers and groups that drive the rigging processes and
saves them into a Network node in Maya, which doesn't have transforms or any other
kind of unnecesary data.
Attributes
----------
mainController : str
The name of the main nurbs curve that controls the rig
mainControllerGroup : str
The name of the group where the mainController is
controllerAttributeName : str
The name of the type of rig that is saved (i.e. wheelControllers, treadControllers, armControllers)
controllerGroupAttributeName : str
The name of the type of rig GROUP that is saved (i.e. wheelControllerGroups, treadControllerGroups, armControllerGroups)
Methods
-------
writeToNode()
Takes the rigging info and stores it in a node
"""
def __init__(self):
"""Initialize default values"""
self.mainController = ""
self.mainControllerGroup =""
self.controllerAttributeName = ""
self.controllerGroupAttributeName = ""
def writeToNode(self):
"""Takes the rigging info and stores it in a node"""
saveData(attributeName=self.controllerGroupAttributeName, value=self.mainControllerGroup)
saveData(attributeName=self.controllerAttributeName, value=self.mainController)
def createDataNode(nodeName):
"""Creates a new network node if it was not previously created
Parameters
----------
nodeName : str
The name of the rigging data node
"""
# Create node if it doesn't exist
if not cmds.objExists(nodeName):
cmds.createNode("network", name=nodeName)
def createDataAttribute(nodeName, attributeName):
"""Creates new attribute on the node if it doesn't exist.
It creates multi attributes, which are lists that can store multiple indices
of data of the same type (i.e. multiple strings)
Parameters
----------
nodeName : str
The name of the rigging data node to create a new attribute into
attributeName : str
The name of the desired attribute to store the info
"""
# Create attribute if it doesn't exist on the node
if not cmds.attributeQuery(attributeName, node=nodeName, exists=True):
cmds.addAttr(nodeName, shortName=attributeName, dataType="string", multi=True)
def saveData(nodeName="rigDataNode", attributeName="myAttr", value=""):
"""Save data in the specified attribute on the node.
Parameters
----------
nodeName : str
The name of the rigging data node to create a new attribute into
attributeName : str
The name of the desired attribute to store the info
value : str
The information to store (i.e. the namme of the controllers which will be used in other step)
"""
# Try to create a new node
createDataNode(nodeName)
# Trye to create an attribute on that node
createDataAttribute(nodeName, attributeName)
# Get the first element [0] of the attribute
theAttr = cmds.getAttr("{}.{}[0]".format(nodeName, attributeName))
# Check if that element is valid (the attribute list has at least one attribute)
if theAttr:
# Get entire list of attributes
attrList = getData(attributeName=attributeName)
# If the value is already in the list (e.g. object was deleted and created new one with the same name)
# exit the function
if value in attrList:
return
# The index where we want to save the new value is the same as the length of the list
# Because we want to store it in the end of the multi attribute
elementIndex = len(attrList)
# If the element is not valid (the list is empty),
# we add our value to the index 0
else:
elementIndex = 0
# Set the attribute value
# Using format function to put variables inside {}'s
# This way we build the attribute's name using the function's parameters
# String is {nodeName}.{attributeName}{elementIndex}
cmds.setAttr("{}.{}[{}]".format(nodeName, attributeName, elementIndex), value, type="string")
"""
theAttr = cmds.getAttr("{}.{}[*]".format(nodeName, attributeName))
size = cmds.getAttr("{}.{}".format(nodeName, attributeName),size=True)
"""
def getData(nodeName="rigDataNode", attributeName="myAttr"):
"""Get data from a specified attribute on the node.
Parameters
----------
nodeName : str
The name of the node where the attribute is located
attributeName : str
The name of the attribute to retrieve the info from
"""
# If the attribute doesn't exist, return an empty list
if not cmds.attributeQuery(attributeName, node=nodeName, exists=True):
return []
# Get the size of the attribute
# This is because when the attribute has only one element, it returns it as a single string
# but when it has multiple elements, it returns it as a list
size = cmds.getAttr("{}.{}".format(nodeName, attributeName),size=True)
# Get the attribute information
theAttr = cmds.getAttr("{}.{}[*]".format(nodeName, attributeName))
# If the size is one element, save it to a list and return it
if size == 1:
return [theAttr]
# Else, if the list has more than one element, return it as it is (already a list)
elif size>1:
return theAttr
# If the attribute is empty, return empty list
else:
return []
def deleteValue(nodeName="rigDataNode", attributeName="myAttr", value=""):
"""Delete a specified value from the attribute list on the node.
Parameters
----------
nodeName : str
The name of the rigging data node to delete a value from
attributeName : str
The name of the attribute containing that value
value : str
The exact value to delete from the attribute
"""
# Exit the function if the node doesn't exist
if not cmds.objExists(nodeName):
return
# Get the attribute list from the node
dataList = getData(nodeName=nodeName, attributeName=attributeName)
# If it is empty (or doesn't exist), exit the function
if not dataList:
return
# Delete each element on the attribute using their indexes
for index in xrange(len(dataList)):
# removeMultiInstance removes an element by giving the name of the attribute and the index of the element
cmds.removeMultiInstance("{}.{}[{}]".format(nodeName, attributeName, index))
# Create a new list containing only the elements that are not value
# This is a list comprehension. It uses a for statement to iterate over a list
# and at the same time compares the elements with the value given to see that they are not equal
# then every element that succeeds the verification is added to the new list
# [] are necessary to wrap the line to specify that we are saving a list
newList = [element for element in dataList if not element == value]
# Save each element on the new list to the node
for element in newList:
saveData(nodeName=nodeName, attributeName=attributeName, value=element)
def deleteDataAttribute(nodeName="rigDataNode", attributeName="myAttr"):
"""Delete the entire attribute from the node.
Parameters
----------
nodeName : str
The name of the node that contains the attribute
attributeName : str
The name of the attribute that is going to be deleted
"""
# Exit the function if the node doesn't exist
if not cmds.objExists(nodeName):
return
# Delete the attribute if it exists
if cmds.attributeQuery(attributeName, node=nodeName, exists=True):
cmds.deleteAttr(nodeName, attribute=attributeName) | [
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] | 3.108688 | 2,751 |
"""Test RevokeHandler."""
import pytest
from ......config.settings import Settings
from ......core.event_bus import EventBus, MockEventBus
from ......core.in_memory import InMemoryProfile
from ......core.profile import Profile
from ......messaging.request_context import RequestContext
from ......messaging.responder import MockResponder, BaseResponder
from ...messages.revoke import Revoke
from ..revoke_handler import RevokeHandler
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.mark.asyncio
@pytest.mark.asyncio
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] | 3.384615 | 169 |
# Copyright 2017 Rice University
#
# 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 __future__ import print_function
from copy import deepcopy
from program_helper.ast.ops import *
from program_helper.ast.ops.concepts.DAPICallMulti import DAPICallMulti
from program_helper.ast.ops.concepts.DExceptionVarDecl import DExceptionVarDecl
from program_helper.ast.ops.concepts.DInfix import DInfix
from program_helper.ast.ops.concepts.DInternalAPICall import DInternalAPICall
from program_helper.ast.ops.concepts.DReturnVar import DReturnVar
| [
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] | 3.528814 | 295 |
import numpy as np
import numpy.testing as npt
from statsmodels.tools import sequences
| [
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] | 3.64 | 25 |
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: book_doc_details.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='book_doc_details.proto',
package='BookDocDetails',
syntax='proto2',
serialized_pb=_b('\n\x16\x62ook_doc_details.proto\x12\x0e\x42ookDocDetails\"v\n\x0b\x42ookDetails\x12\x11\n\tpublisher\x18\x04 \x01(\t\x12\x17\n\x0fpublicationDate\x18\x05 \x01(\t\x12\x0c\n\x04isbn\x18\x06 \x01(\t\x12\x15\n\rnumberOfPages\x18\x07 \x01(\x05\x12\x16\n\x0e\x61\x62outTheAuthor\x18\x11 \x01(\tB2\n com.google.android.finsky.protosB\x0e\x42ookDocDetails')
)
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
_BOOKDETAILS = _descriptor.Descriptor(
name='BookDetails',
full_name='BookDocDetails.BookDetails',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='publisher', full_name='BookDocDetails.BookDetails.publisher', index=0,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='publicationDate', full_name='BookDocDetails.BookDetails.publicationDate', index=1,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='isbn', full_name='BookDocDetails.BookDetails.isbn', index=2,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='numberOfPages', full_name='BookDocDetails.BookDetails.numberOfPages', index=3,
number=7, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='aboutTheAuthor', full_name='BookDocDetails.BookDetails.aboutTheAuthor', index=4,
number=17, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=_b("").decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
syntax='proto2',
extension_ranges=[],
oneofs=[
],
serialized_start=42,
serialized_end=160,
)
DESCRIPTOR.message_types_by_name['BookDetails'] = _BOOKDETAILS
BookDetails = _reflection.GeneratedProtocolMessageType('BookDetails', (_message.Message,), dict(
DESCRIPTOR = _BOOKDETAILS,
__module__ = 'book_doc_details_pb2'
# @@protoc_insertion_point(class_scope:BookDocDetails.BookDetails)
))
_sym_db.RegisterMessage(BookDetails)
DESCRIPTOR.has_options = True
DESCRIPTOR._options = _descriptor._ParseOptions(descriptor_pb2.FileOptions(), _b('\n com.google.android.finsky.protosB\016BookDocDetails'))
# @@protoc_insertion_point(module_scope)
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] | 2.490183 | 1,528 |
import asyncio
import beneath
from datetime import datetime, timedelta
from config import BLACKLIST
asyncio.run(main())
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] | 3.542857 | 35 |
import asyncio
from time import sleep, time
import pytest
from ansq import open_connection
from ansq.tcp.connection import NSQConnection
from ansq.tcp.exceptions import ConnectionClosedError
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
@pytest.mark.asyncio
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] | 2.673759 | 141 |
# 054 - LER ANO DE NASCIMENTO DE 07 PESSOAS E MOSTRAR QUANTAS PESSOAS SÂO MAIORES DE IDADE.
from datetime import date
atual = date.today().year
tmaior = 0
tmenor = 0
for pessoa in range(1, 8):
nasc = int(input(f'Em que ano {pessoa}° a pessoa nasceu? '))
idade = atual - nasc
if idade >= 21:
tmaior += 1
else:
tmenor += 1
print(f'Ao todo tivemos {tmaior} pessoas maiores de idade')
print(f'E também tivemos {tmenor} pessoas menores de ideade')
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] | 2.106195 | 226 |
from functools import reduce
from rest_framework.permissions import BasePermission, SAFE_METHODS
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import shutil
import click
from .main import main
from ..settings import service_template
@main.group("install")
def install():
"""Install a configuration or service"""
@install.command()
@click.pass_context
@click.option('--path', '-p', help="Path to installed file")
def sera(ctx, path):
"""Locally install systemd service"""
if ctx.parent.params['watcher']:
click.echo("This command runs locally")
raise click.Abort
path = path or '/etc/systemd/system/sera.service'
if ctx.obj['verbosity']:
click.echo('Installing service at %s' % path)
output = service_template.substitute(
executable=shutil.which('sera'),
user='root')
with open(path, 'w') as file:
file.write(output)
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] | 2.725632 | 277 |
import os
from datetime import timedelta
from dotenv import load_dotenv
load_dotenv()
SECRET_KEY = os.urandom(32)
# SQLite Database Config
APP_PATH = os.path.dirname(os.path.abspath(__file__))
SQLALCHEMY_DATABASE_URI = 'sqlite:///' + APP_PATH + '/models/sqlite.db'
SQLALCHEMY_TRACK_MODIFICATIONS = True
# setting up email server variables
MAIL_SERVER = 'smtp.live.com'
MAIL_PORT = 587
MAIL_USE_TLS = True
MAIL_USERNAME = os.getenv('MAIL_USERNAME')
MAIL_PASSWORD = os.getenv('MAIL_PASSWORD')
ADMINS = ['[email protected]']
PERMANTENT_SESSION_LIFETIME = timedelta(hours=24)
MAX_CONTENT_LENGTH = 4 * 8 * 1024 * 1024 # 2MB
ALLOWED_EXTENSIONS = set(
['jpg', 'JPG', 'jpeg', 'JPEG', 'png', 'PNG', 'bmp', 'BMP'])
UPLOAD_FOLDER = "./app/static/uploads/"
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] | 2.375 | 320 |
"""
# NOTE (for Sam): Run on "QSTrader" Conda Virtual Enviroment
> "source activate QSTrader"
> Run via "python coincap_ERC-20_ranker.py"
Summary of script
1) Open Top ERC-20 file & create a DataFrame with the info
2) Get ID's for all ERC-20 tokens using Global API
3) Use Ticker(Specific Currency) API to get info on each ERC-20 token
4) Create a DataFrame with all the info
5) Write DataFrame to .xlsx file
# NOTE: Code must be run on a Virtual Environment in order to import "prettytable" (as least this was the case for me)
"""
import re
import xlrd
import json
import requests
import datetime
import numpy as np
import pandas as pd
from openpyxl import load_workbook
from colorama import Fore, Back, Style
### 1) Open Top ERC-20 Tokens File
file_path = r"/Users/YoungFreeesh/Visual Studio Code/_Python/Web Scraping/TokenScraper/CoinMarketCap Dev API/CMC-ID-Map.xlsx"
# top_ERC_df = pd.read_csv(file_path, header=0,index_col=0) # for .csv
top_ERC_df = pd.read_excel(file_path, sheetname = "Top ERC-20") # read all data from "Top ERC-20"
headers = list(top_ERC_df.columns.values) # get the headers --> ERC-20 Token, Ticker, ID, CoinMarketCap URL, Market Cap (yyyy-mm-dd)
top_ERC_df = pd.DataFrame(top_ERC_df) # convert top_ERC_df to a DateFrame
# Get IDs
ERC_ID_List = top_ERC_df.iloc[:,2]
# print(ERC_ID_List)
# Set Currency
convert = 'USD'
### CoinMarketCap API
# EXAMPLE API KEY Call --> https://pro-api.coinmarketcap.com/v1/cryptocurrency/map?CMC_PRO_API_KEY=a3e5008f-c6b1-471d-9b4c-c4424e8b7d1f
API_Key = Sorry # Sam's personal API Key
# listings_url = 'https://pro-api.coinmarketcap.com/v1/cryptocurrency/listings/historical' + API_Key # Not Supported in Free subscription plan
listings_url = 'https://pro-api.coinmarketcap.com/v1/cryptocurrency/listings/latest' + API_Key # Listings Latest
url_end = '?structure=array&convert=' + convert # Might not be necessary anymore
request = requests.get(listings_url)
results = request.json()
data = results['data'] # All Data
#currencyData = results['data'][0] # All Currencies
# print(json.dumps(results, sort_keys=True, indent=4))
### Initilaize List elements --> will be used to create DataFrame --> used to create .xlsx file
id_num_List = list()
name_List = list()
symbol_List = list()
website_slug_List = list()
cmc_rank_List = list()
num_markets_List = list()
circulating_supply_List = list()
total_supply_List = list()
percent_total_supply_circulating_List = list()
max_supply_List = list()
last_updated_List = list()
# ['quote']['USD']
price_List = list()
volume_24h_List = list()
market_cap_List = list()
percent_change_1h_List = list()
percent_change_24h_List = list()
percent_change_7d_List = list()
jjj = 0
#for currency in currencyData: # For each
for currency in data: # For each
if currency['id'] in ERC_ID_List.values: # ONLY FOR ERC-20 Tokens
### Get Data for ticker
id_num = currency['id']
rank = currency['cmc_rank']
name = currency['name']
symbol = currency['symbol']
website_slug = currency['slug']
website_slug = "https://coinmarketcap.com/currencies/" + website_slug + "/"
num_markets = currency['num_markets']
circulating_supply = currency['circulating_supply']
total_supply = currency['total_supply']
if circulating_supply is None:
circulating_supply = 0
if total_supply is None:
total_supply = 0
percent_total_supply_circulating = "None"
else:
# percent_total_supply_circulating = int(round(circulating_supply/total_supply*100))
percent_total_supply_circulating = round(circulating_supply/total_supply*100)
max_supply = currency['max_supply']
last_updated = currency['last_updated']
# Quotes
quotes = currency['quote'][convert]
price = round(quotes['price'],4)
volume = round(quotes['volume_24h'])
percent_change_1h = quotes['percent_change_1h']
percent_change_24h = quotes['percent_change_24h']
percent_change_7d = quotes['percent_change_7d']
market_cap = quotes['market_cap']
print(jjj,': ', name, " (", symbol, ")")
jjj += 1
### Append List Elements
id_num_List.append(id_num)
cmc_rank_List.append(rank)
name_List.append(name)
symbol_List.append(symbol)
website_slug_List.append(website_slug)
num_markets_List.append(num_markets)
circulating_supply_List.append(circulating_supply)
total_supply_List.append(total_supply)
max_supply_List.append(max_supply)
last_updated_List.append(last_updated)
price_List.append(price)
volume_24h_List.append(volume)
percent_change_1h_List.append(percent_change_1h)
percent_change_24h_List.append(percent_change_24h)
percent_change_7d_List.append(percent_change_7d)
market_cap_List.append(market_cap)
### Create DataFrame from Lists
##df = pd.DataFrame(data=temp, index=ranking)
ranker_List = pd.DataFrame(
list(zip(cmc_rank_List, name_List, symbol_List, price_List, market_cap_List,
volume_24h_List, num_markets_List, percent_total_supply_circulating_List,
circulating_supply_List, total_supply_List, max_supply_List,
percent_change_1h_List, percent_change_24h_List, percent_change_7d_List,
id_num_List, last_updated_List, website_slug_List)),
columns=['Name',
'Ticker',
'Price ($)',
'Market Cap ($)',
'Daily Volume ($)',
'Number of Markets',
'% of Total Supply Circulating',
'Circulating Supply',
'Total Supply',
'Max Supply',
'% Change: 1h',
'% Change: 24h',
'% Change: 7d',
'ID',
'Last Updated',
'CoinMarketCap URL'],
index=cmc_rank_List)
ranker_List.index.name = "CMC Rank" # Rename Index
#print(name_List)
print(name_List)
print(ranker_List)
"""
### Ordering in Excel Sheet
cmc_rank_List
name_List
symbol_List
price_List
market_cap_List
volume_24h_List
num_markets_List
percent_total_supply_circulating_List
circulating_supply_List
total_supply_List
max_supply_List
percent_change_1h_List
percent_change_24h_List
percent_change_7d_List
id_num_List
last_updated_List
website_slug_List
"""
# Get Time stamp for market cap
timeStamp = str(datetime.datetime.today().strftime(' (%Y-%m-%d)')) # Today, as an Integer
### Create Excel File
fileName = "MASTER-ERC-20" + timeStamp
file_path_HardDrive = r"/Users/YoungFreeesh/Visual Studio Code/_Python/Web Scraping/TokenScraper/CoinMarketCap Dev API/" + fileName + ".xlsx"
writer_HardDrive = pd.ExcelWriter(file_path_HardDrive)#, engine='openpyxl')
ranker_List.to_excel(writer_HardDrive, startrow= 0 , index=True, sheet_name= 'Summary') # write to "MASTER-Ercot.xlsx" spreadsheet
writer_HardDrive.save()
writer_HardDrive.close()
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628,
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] | 2.27984 | 3,259 |
# WIP
# DreamBNC Bot 2
# (c) DreamBNC
# Loading essential libraries (needed for connecting to IRC)
import zirc, ssl
print("DreamBNC Service Bot")
print("(c) 2016 DreamBNC dev team.")
print("Initalizing.")
# setting variables
bncprovider = DreamBNC
bncweb = dreambnc.xyz
server1 = Mushroom
print("Initalized; connecting...")
# connecting using zirc
self.config = zirc.IRCConfig(host="irc.freenode.net",
port=6697,
nickname="%bncprovider",
ident="%bncprovider",
realname="%bncprovider Service Bot - http://%bncweb",
# variables are being an pain; we have to hard code this
# We should also probably add some way to input a server pass
channels=['#DreamBNC'],
sasl_user="user",
sasl_pass="pw")
self.connect(self.config)
self.start()
Bot()
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] | 2.89272 | 261 |
from sus.engines import telegram, reddit, rss
import vcr
import unittest
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] | 2.405405 | 37 |
import tensorflow as tf
import numpy as np
import Quantizers
import math
import time
import struct
from tensorflow.python.ops import standard_ops
from tensorflow.python.ops import nn
hex_lambda = lambda x : hex(struct.unpack('<I', struct.pack('<f', x))[0])
toHex = np.vectorize(hex_lambda)
input_width = input_height = 4
batch_size = 2
input_channels = 2
entries = input_width*input_height*batch_size*input_channels
testdata_scale=10
threshold = 5
inputs_vals = np.random.normal(size=(batch_size,input_width,input_height,input_channels))*testdata_scale
#inputs_vals = 1.0 - 2.0**-np.arange(entries)
inputs = tf.constant(inputs_vals,dtype=tf.float32)
#inputs = tf.zeros_like(inputs)
quantizer_log = Quantizers.LogarithmicQuantizer()
output_log = quantizer_log.quantize(inputs)
gold_output_log = log2(inputs)
quantizer_sparse = Quantizers.SparseQuantizer(threshold)
output_sparse = quantizer_sparse.quantize(inputs)
gold_output_sparse = sparse(inputs, threshold)
quantizer_halffp = Quantizers.HalffpQuantizer()
output_halffp = quantizer_halffp.quantize(inputs)
gold_output_halffp = halffp(inputs)
with tf.Session() as sess:
'''
print('input:')
print(toHex(sess.run(inputs)))
print('quantized:')
print(toHex(sess.run(output_halffp)))
print('gold quantized:')
print(toHex(sess.run(gold_output_halffp)))
'''
result_log=np.sum(
np.absolute(gold_output_log.eval().flatten()-output_log.eval().flatten()))
result_sparse=np.sum(
np.absolute(gold_output_sparse.eval().flatten()-output_sparse.eval().flatten()))
# rounding in TF FP16 format is different than in Halffp kernel implementation!
# mantissa is rounded up in TF FP16 and cut in kernel.
# rounding bit in integer representation has value 8192, difference between TF FP16 and
# kernel is 0 or that number.
gold_output_halffp = np.array(
[struct.unpack('<I', struct.pack('<f', x))[0]
for x in gold_output_halffp.eval().flatten()])
output_halffp = np.array(
[struct.unpack('<I', struct.pack('<f', x))[0]
for x in output_halffp.eval().flatten()])
result_halffp = gold_output_halffp-output_halffp
result_halffp = np.absolute(
np.sum( (result_halffp==0).astype(np.int32)
+ (result_halffp==8192).astype(np.int32) )
- result_halffp.size)
#result_halffp=np.sum(np.absolute(gold_output_halffp.eval().flatten()-output_halffp.eval().flatten()))
'''
start=time.time()
for i in range(100000):
output_halffp.eval()
runtime = time.time()-start
print('kernel-version time: %fs'%runtime)
start=time.time()
for i in range(100000):
gold_output_halffp.eval()
runtime = time.time()-start
print('tf-version time: %fs'%runtime)
'''
print('LogQuantizer test:')
check(result_log)
print('SparseQuantizer test:')
check(result_sparse)
print('HalffpQuantizer test:')
check(result_halffp)
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] | 2.485934 | 1,173 |
# -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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 airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils.decorators import apply_defaults
class HivePartitionSensor(BaseSensorOperator):
"""
Waits for a partition to show up in Hive.
Note: Because ``partition`` supports general logical operators, it
can be inefficient. Consider using NamedHivePartitionSensor instead if
you don't need the full flexibility of HivePartitionSensor.
:param table: The name of the table to wait for, supports the dot
notation (my_database.my_table)
:type table: str
:param partition: The partition clause to wait for. This is passed as
is to the metastore Thrift client ``get_partitions_by_filter`` method,
and apparently supports SQL like notation as in ``ds='2015-01-01'
AND type='value'`` and comparison operators as in ``"ds>=2015-01-01"``
:type partition: str
:param metastore_conn_id: reference to the metastore thrift service
connection id
:type metastore_conn_id: str
"""
template_fields = ('schema', 'table', 'partition',)
ui_color = '#C5CAE9'
@apply_defaults
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] | 3.343643 | 582 |
from flask import request, render_template, url_for, g, Flask, redirect, flash, abort, json, jsonify, session
from peewee import DoesNotExist
from playhouse.shortcuts import model_to_dict, dict_to_model
import json
from datetime import datetime
from dateutil import parser
from app import app
from app.models.program import Program
from app.models.event import Event
from app.models.facilitator import Facilitator
from app.models.eventParticipant import EventParticipant
from app.models.eventRsvp import EventRsvp
from app.models.user import User
from app.models.term import Term
from app.models.eventTemplate import EventTemplate
from app.models.outsideParticipant import OutsideParticipant
from app.models.eventParticipant import EventParticipant
from app.models.programEvent import ProgramEvent
from app.logic.participants import trainedParticipants
from app.logic.volunteers import getEventLengthInHours
from app.logic.utils import selectSurroundingTerms
from app.logic.events import deleteEvent, getAllFacilitators, attemptSaveEvent, preprocessEventData, calculateRecurringEventFrequency
from app.logic.courseManagement import pendingCourses, approvedCourses
from app.controllers.admin import admin_bp
from app.controllers.admin.volunteers import getVolunteers
from app.controllers.admin.userManagement import manageUsers
@admin_bp.route('/switch_user', methods=['POST'])
@admin_bp.route('/template_select')
@admin_bp.route('/event/<templateid>/create', methods=['GET','POST'])
@admin_bp.route('/event/<templateid>/<programid>/create', methods=['GET','POST'])
@admin_bp.route('/event/<eventId>/edit', methods=['GET','POST'])
@admin_bp.route('/event/<eventId>/delete', methods=['POST'])
@admin_bp.route('/makeRecurringEvents', methods=['POST'])
@admin_bp.route('/volunteerProfile', methods=['POST'])
@admin_bp.route('/search_student', methods=['GET'])
@admin_bp.route('/addParticipants', methods = ['GET'])
def addParticipants():
'''Renders the page, will be removed once merged with full page'''
return render_template('addParticipants.html',
title="Add Participants")
@admin_bp.route('/courseManagement', methods = ['GET', 'POST'])
@admin_bp.route('/courseManagement/<term>', methods = ['GET', 'POST'])
def courseManagement(term = None):
'''
Renders the page for admins to manage Course Proposals
'''
term = Term.get_or_none(Term.id == term)
if not term:
term = g.current_term
pending = pendingCourses(term)
approved = approvedCourses(term)
terms = selectSurroundingTerms(g.current_term)
return render_template('/admin/courseManagement.html',
pendingCourses = pending,
approvedCourses = approved,
terms = terms,
term = term)
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] | 2.949117 | 963 |
import cv2 as cv
import functions
import os
cam = cv.VideoCapture(0) #Iniciando WebCam
file_name = "haarcascade_frontalface_alt2.xml"
classifier = cv.CascadeClassifier(f"{cv.haarcascades}{os.sep}{file_name}") #Modelo para reconhecer faces
dataframe = functions.load_dataframe() #Cargando dataframe com las imagenes para entrenamiento
X_train, y_train = functions.train_test(dataframe) #Dividindo conjuntos de treino e teste
pca = functions.pca_model(X_train) #Modelo PCA para extracion de contornos de imagen
X_train = pca.transform(X_train) #Conjunto de contornos extraídos
knn = functions.knn(X_train, y_train) #Entrenando con modelo de clasificacion KNN
#Rótulo de clasificaciones
label = {
0: "Sin mascara",
1: "Con mascara"
}
#Abriendo Webcam...
while True:
status, frame = cam.read() #Leyendo imagen y extrayendo frame
if not status:
break
if cv.waitKey(1) & 0xff == ord('q'):
break
#Transformando la imagen en escala de griz
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
#Detectando rostros en imagen
faces = classifier.detectMultiScale(gray)
#Iterando las caras encontradas
for x,y,w,h in faces:
gray_face = gray[y:y+h, x:x+w] #Recortando region de la cara
if gray_face.shape[0] >= 200 and gray_face.shape[1] >= 200:
gray_face = cv.resize(gray_face, (160,160)) #Redimensionando
vector = pca.transform([gray_face.flatten()]) #Extrayendo contornos de la imagem
pred = knn.predict(vector)[0] #Clasificando la imagen
classification = label[pred]
#Mostrando rectangulos alrededor del rostro
if pred == 0:
cv.rectangle(frame, (x,y), (x+w, y+h), (0,0,255), 3)
print("\a")
elif pred == 1:
cv.rectangle(frame, (x,y), (x+w, y+h), (0,255,0), 3)
#Escribiendo clasificacion y cantidad de rostros vistos
cv.putText(frame, classification, (x - 20,y + h + 50), cv.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2, cv.LINE_AA)
cv.putText(frame, f"{len(faces)} rostros identificados",(20,20), cv.FONT_HERSHEY_SIMPLEX, 0.5, (255,0,0), 2, cv.LINE_AA)
#Mostrando frame
cv.imshow("Cam", frame)
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13,
2554,
9248,
7,
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11,
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11,
88,
828,
357,
87,
10,
86,
11,
331,
10,
71,
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357,
15,
11,
13381,
11,
15,
828,
513,
8,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1303,
36,
40075,
72,
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537,
292,
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49443,
331,
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32482,
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686,
48288,
410,
396,
418,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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269,
85,
13,
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7,
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220,
220,
220,
220,
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269,
85,
13,
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8206,
7,
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11,
277,
1,
90,
11925,
7,
32186,
38165,
686,
48288,
1852,
811,
22484,
1600,
7,
1238,
11,
1238,
828,
269,
85,
13,
37,
35830,
62,
39,
4877,
13909,
56,
62,
48913,
16437,
55,
11,
657,
13,
20,
11,
357,
13381,
11,
15,
11,
15,
828,
362,
11,
269,
85,
13,
24027,
62,
3838,
8,
628,
220,
220,
220,
1303,
6943,
25192,
78,
5739,
198,
220,
220,
220,
269,
85,
13,
320,
12860,
7203,
21701,
1600,
5739,
8,
198
] | 2.157593 | 1,047 |
from PIL import Image
import urllib.request as request
import requests
from io import BytesIO, StringIO
from bs4 import BeautifulSoup
import numpy as np
def get_images_links(address):
"""
Scrap website from images links
:param address: website address example: https://www.youtube.com/
:return: images links
"""
page = request.urlopen(address) # html
soup = BeautifulSoup(page, 'html.parser')
tags = soup.findAll('img') # all images
print(tags)
images = []
# scrap from images links in a look
for img in tags:
try:
images.append(img['src'])
except:
pass
return images
def get_images_bytes(links):
"""
Transform images links into bytes format to load as Pillow object later
:param address: list of images links
:return: images as bytes
"""
images = []
# transform to bytes in a look
for link in links:
try:
img = image_from_url(link) # download as Pillow object
img = image_to_bytes(img) # transform into bytes format as a universal solution
images.append(img) # add
except:
pass
return images
def image_from_url(url):
"""
Download image from url
:param url: url of image
:return: image Pillow object
"""
response = requests.get(url)
return Image.open(BytesIO(response.content))
def image_to_bytes(image: Image):
"""
Transform image to bytes format
:param image: image Pillow object
:return: bytes
"""
imgByteArr = BytesIO()
image.save(imgByteArr, format=image.format)
imgByteArr = imgByteArr.getvalue()
return imgByteArr
def bytes_to_image(bytes):
"""
Inverse transform of bytes into image
(To use for others)
:param bytes: mage in bytes format
:return: image Pillow object
"""
return Image.open(BytesIO(bytes))
| [
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7,
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220,
220,
554,
4399,
6121,
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9881,
656,
2939,
198,
220,
220,
220,
357,
2514,
779,
329,
1854,
8,
198,
220,
220,
220,
1058,
17143,
9881,
25,
29241,
287,
9881,
5794,
198,
220,
220,
220,
1058,
7783,
25,
2939,
19770,
322,
2134,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
1441,
7412,
13,
9654,
7,
45992,
9399,
7,
33661,
4008,
198
] | 2.635862 | 725 |
import http.client
import threading
import typing
| [
11748,
2638,
13,
16366,
198,
11748,
4704,
278,
198,
11748,
19720,
628
] | 4.25 | 12 |
"""
@Time : 2019-1-9 04:41
@Author : TaylorMei
@Email : [email protected]
@Project : iccv
@File : dsc.py
@Function:
"""
import torch
import torch.nn.functional as F
from torch import nn
from backbone.resnext.resnext101_regular import ResNeXt101
# Module Function
# Module Class
# Network Class
| [
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6738,
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1874,
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55,
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2,
19937,
15553,
628,
198,
2,
19937,
5016,
628,
628,
198,
2,
7311,
5016,
198
] | 2.584615 | 130 |
import torch.nn as nn
import torch.nn.functional as F
| [
11748,
28034,
13,
20471,
355,
299,
77,
198,
11748,
28034,
13,
20471,
13,
45124,
355,
376,
628
] | 3.235294 | 17 |
from .generating import OutputsGenerator
| [
6738,
764,
8612,
803,
1330,
25235,
82,
8645,
1352,
198
] | 4.1 | 10 |
try:
import cloudscraper
except ModuleNotFoundError:
raise ModuleNotFoundError("Unable to load cloudscraper")
def access(endpoint=""):
"""The function used to access the entirety of nitrotype.
Endpoint
--------
https://www.nitrotype.com/{endpoint}
endpoint : str
The end url to access.
Returns
-------
str
A string of the html of the webpage, or of a json from the api.
"""
base_url = "https://www.nitrotype.com/"
scraper = None
try:
scraper = cloudscraper.create_scraper()
except:
scraper = cloudscraper.CloudScraper()
finally:
if scraper:
return scraper.get(base_url + str(endpoint)).text
return False
| [
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220,
220,
220,
3443,
25,
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220,
220,
220,
220,
220,
220,
220,
611,
19320,
525,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1441,
19320,
525,
13,
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7,
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62,
6371,
1343,
965,
7,
437,
4122,
29720,
5239,
628,
220,
220,
220,
1441,
10352,
198
] | 2.525773 | 291 |
# Generated by Django 3.0.8 on 2021-11-22 09:10
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
15,
13,
23,
319,
33448,
12,
1157,
12,
1828,
7769,
25,
940,
198,
198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
#!/usr/bin/env python
"""Controls when data collection is suspended, in case the X-ray beam is
down
Friedrich Schotte,
Date created: 2017-02-24
Date last modified: 2018-03-15
"""
__version__ = "1.2.9" # logging
from checklist import checklist
import wx, wx3_compatibility
from EditableControls import TextCtrl,ComboBox
from logging import debug,info,warn,error
if __name__ == '__main__':
from pdb import pm
import logging
from tempfile import gettempdir
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s %(levelname)s %(module)s.%(funcName)s: %(message)s",
filename=gettempdir()+"/ChecklistPanel.log",
)
import autoreload
# Needed to initialize WX library
app = wx.App(redirect=False)
ChecklistPanel()
app.MainLoop()
| [
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# Bibliotecas
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy.stats import shapiro
from scipy.stats import chi2
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import StandardScaler
from sklearn.feature_selection import SelectKBest, f_classif
# !pip install imbalanced-learn
from imblearn.over_sampling import SMOTE
from sklearn.naive_bayes import GaussianNB
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_validate
from sklearn.metrics import classification_report
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import GradientBoostingClassifier
# !pip install xgboost
from xgboost import XGBClassifier
from sklearn.model_selection import GridSearchCV
from sklearn.metrics import confusion_matrix
import pickle
# Config pandas
pd.set_option("max_columns", 1000)
# In[2]:
# Datasets
treino_raw = pd.read_csv("../Datasets/telecom_treino.csv", sep = ",")
teste_raw = pd.read_csv("../Datasets/telecom_teste.csv", sep = ",")
# ## 3.0 - Análise Exploratória de Dados
# In[3]:
# Primeiras linhas do dataset
treino_raw.head()
# A coluna "Unnamed: 0" pode ser removida do dataset porque é um índice e para o treinamento do modelo a coluna não tem relevância.<br/>
# As colunas categóricas e TARGET estão com o tipo de dados em String, será realizado um LabelEncoder (Transformação de categorias em valores numéricos) para melhor performance do modelo.
# In[4]:
# Dimensões do dataset
treino_raw.shape
# O dataset tem um bom número de registro, porém tem que ter cuidado ao realizar remoção de registros para não afetar a performance do modelo.
# In[5]:
# Tipo de dado de cada atributo
treino_raw.dtypes
# Conforme visto anteriormente, o dataset tem algumas variáveis com o tipo Object (Strings) que representam variáveis categóricas, devem ser transformadas para números.
# In[6]:
# Valores missing
treino_raw.isna().sum()
# O dataset não contem valores missing.
# In[7]:
# Valores unicos de cada atributo
for i in treino_raw.columns:
print(i, "-> ", treino_raw[i].nunique(), sep="")
# O dataset tem muitos valores unicos, o que indica que temos bastantes variáveis numéricas, pode-se fazer quantization das variáveis númericas para uma melhor performance do modelo
# In[8]:
# Separar atributos númericos e categóricos
variaveis_numericas = []
variaveis_categoricas = []
for i in treino_raw.columns:
if ( treino_raw[i].dtype == 'O' ):
variaveis_categoricas.append(i)
else:
variaveis_numericas.append(i)
# In[9]:
# Retirar o atributo "Unnamed: 0" da lista de variaveis numericas
variaveis_numericas.remove("Unnamed: 0")
# ### Variáveis numéricas
# In[10]:
# Sumário estatístico das variáveis numéricas
treino_raw[variaveis_numericas].describe()
# A média e mediana das variáveis numéricas estão muito aproximadas, o desvio padrão está com valor baixo, indica que os dados estão próximos da média.
# In[11]:
# Gráfico de dispersão entre as variáveis total_day_minutes e total_day_charge
fig = plt.figure(figsize=(10,6))
sns.scatterplot(data = treino_raw[variaveis_numericas], x = "total_day_minutes", y = "total_day_charge")
plt.title("Relação de total_day_minutes e total_day_charge")
plt.show()
# De acordo com o scatterplot, temos uma correlação positiva das variáveis, conforme cresce os minutos falados no dia, sobe o custo.
# In[12]:
# Gráfico de dispersão entre as variáveis total_eve_minutes e total_eve_charge
fig = plt.figure(figsize=(10,6))
sns.scatterplot(data = treino_raw[variaveis_numericas], x = "total_eve_minutes", y = "total_eve_charge")
plt.title("Relação de total_eve_minutes e total_eve_charge")
plt.show()
# De acordo com o scatterplot, temos uma correlação positiva das variáveis, conforme cresce os minutos falados na vespera, sobe o custo, porém o custo é menor do que os minutos falados no dia e custo do dia.
# In[13]:
# Histograma
treino_raw[variaveis_numericas].hist(figsize=(16,10))
plt.show()
# De acordo com os histogramas, as variáveis númericas estão aparentemente em uma distribuição normal com exceção da variável "number_vmail_messages"
# In[14]:
# Boxplot
treino_raw[variaveis_numericas].plot(kind='box', layout=(5,3), subplots=True, figsize=(20,15))
plt.show()
# De acordo com os boxplots, todas as variáveis numéricas tem valores outliers, a maioria dos outliers estão concentrados no 1º e 3º quartil.
# In[15]:
# Teste de hipótese para validar distribuição gaussiana
# H0 -> É uma distribuição gaussiana
# Ha -> Não é uma distribuição gaussiana
# In[16]:
for i in variaveis_numericas:
teste_gaussiano(i, treino_raw[i])
# Algumas variáveis não estão em uma distribuição normal, será realizado normalização nas variáveis para melhor performance do modelo preditivo.
# In[17]:
# Correlação das variáveis numéricas
figure = plt.figure(figsize=(16,10))
sns.heatmap(treino_raw[variaveis_numericas].corr(),
cmap='BrBG', vmin=-1, vmax=1, annot=True)
plt.show()
# O dataset tem poucas variáveis correlacionadas, porém as correlações existentes são fortes.
# In[18]:
# Simetria das variáveis numéricas
treino_raw[variaveis_numericas].skew()
# As variáveis estão simétricas, algumas com uma leve distorção para a cauda esquerda e outras para a cauda direita, mas o valor da distorção é muito baixo.
# ### Variáveis categóricas
# In[19]:
# Barplot de cada variável agrupado pela variável TARGET (Churn)
for i in treino_raw[variaveis_categoricas].drop("churn", axis = 1).columns:
pd.crosstab(treino_raw[i], treino_raw["churn"]).plot(kind = "bar",
stacked = True,
figsize = (12,6),
title = i)
# In[20]:
# Countplot para contar os valores das variáveis categóricas
for i in variaveis_categoricas:
if ( i == "state" ):
val_figsize = (16,6)
else:
val_figsize = (10,6)
fig = plt.figure(figsize=val_figsize)
sns.countplot(x = i, data = treino_raw)
plt.show()
# De acordo com os gráfico de barras, os estados com mais registros são WV e MN, o código de área com mais registro é area_code_415, a maioria dos registros não tem plano internacional e não tem plano de correio de voz. A variável TARGET (churn) está desbalanceada, tem mais de 2500 registros com churn no e aproximadamente 500 registros com churn yes, para melhor performance do modelo preditivo, precisa-se balancear a variável churn.
# In[21]:
# Label Encoder das variáveis categóricas para realizar análise de correlação
treino_raw_le = treino_raw.copy()
for i in variaveis_categoricas:
print("Realizando label encoder da variável", i)
le = LabelEncoder()
le.fit(treino_raw[i])
treino_raw_le[i] = le.transform(treino_raw_le[i])
# In[22]:
# Exibir primeiras linhas do dataset depois do labelencoder das variáveis categóricas
treino_raw_le.head()
# In[23]:
# Análise de correlação com Spearman
sns.heatmap(treino_raw_le[variaveis_categoricas].corr(method="spearman"),
cmap='BrBG', vmin=-1, vmax=1, annot=True)
plt.show()
# Realizado LabelEncoder nas variáveis para realizar análise de correlação. A correlação das variáveis preditoras com a variável target é fraca, muito próxima de zero, a variável preditora que tem mais correlação com a variável target é International_Plan.
# ## 4.0 - Manipulação de dados
# In[24]:
# Cópia do dataset original para efetuar as manipulações
treino_munging = treino_raw.copy()
# Declarar função para estruturar e manipular os dados do dataset para treinar o modelo de machine learning.<br/>
# As técnicas utilizadas dentro da função "estruturar_dados" foram criadas de acordo com as necessidades descobertas na análise exploratória.
# In[25]:
# Declarar e Treinar LabelEncoder para cada variável categorica
le = []
# Adicionar cada variável categorica no LabelEncoder
for i in variaveis_categoricas:
le.append((i, LabelEncoder()))
# Treinar LabelEncoder de cada variável categórica
for var, modelo in le:
modelo.fit(treino_munging[var])
print("Concluído LabelEncoder da variável", var)
# In[26]:
# Função para realizar a manipulação dos dados
standard_scaler = StandardScaler()
# Função para inverter o label encoder das variáveis categóricas e normalização das variáveis numéricas
# In[27]:
# Utilizar a função para realizar a manipulação dos dados (Remover variável "Unnamed: 0", tranformar variáveis categóricas que
# estão em formato texto para número e normalizar as variáveis númericas)
treino_munging = tratar_dados(treino_munging)
# In[28]:
# Exibir primeiras linhas do dataset manipulado
treino_munging.head()
# O dataset está com as variáveis categóricas transformadas para número e as variáveis numéricas estão normalizadas, mas será que essas variáveis numéricas estão mesmo normalizadas? Vamos plotar histograma para confirmar.
# In[29]:
# Histograma das variáveis numéricas
treino_munging[variaveis_numericas].hist(figsize=(15,10))
plt.show()
# As variáveis númericas com exceção da variável "number_vmail_messages" estão em formato de distribuição normal.
# In[30]:
# Boxplot das variáveis numéricas
treino_munging[variaveis_numericas].plot(kind='box', layout=(5,3), subplots=True, figsize=(20,15))
plt.show()
# De acordo com os graficos exibidos acima, as variáveis númericas do dataset tem muitos outliers, será realizado remoção dos outliers.
# In[31]:
# Função para remover outlier da variável com método do desvio padrão
# In[32]:
# Remover outliers do dataset utilizando a função criada a cima e gravar em uma nova variável #
# Copiar dataset e gravar em uma nova variável
treino_munging_no_outliers = treino_munging.copy()
# Percorrer cada variável numérica e retirar outlier de cada variável.
for i in variaveis_numericas:
treino_munging_no_outliers[i] = remover_outlier(treino_munging_no_outliers[i])
# A função remover_outlier deixa os valores outliers como nulos, vamos remover os valores nulos do dataset
treino_munging_no_outliers = treino_munging_no_outliers.dropna()
# In[33]:
# Boxplot das variáveis numéricas
treino_munging_no_outliers[variaveis_numericas].plot(kind='box', layout=(5,3), subplots=True, figsize=(20,15))
plt.show()
# De acordo com os gráficos acima, foram removidos os outliers do dataset.
# In[34]:
# Exibir primeiras linhas do dataset
treino_munging_no_outliers.head()
# In[35]:
# Dimensões do dataset
treino_munging_no_outliers.shape
# O dataset continua com uma boa quantidade de registros para o treinamento do modelo de machine learning, foram removidos 514 registros ao eliminar os outliers das variáveis numéricas.
# ## 5.0 - Feature Selection (Seleção de variáveis)
# In[36]:
# Utilizar o método SelectKBest do SKLearn com o método estatistico f_classif (ANOVA) para selecionas as melhores variáveis para o modelo de machine learning
predict = treino_munging_no_outliers.drop(["churn"], axis = 1)
target = treino_munging_no_outliers["churn"]
kbest = SelectKBest(f_classif, k=15)
kbest.fit_transform(
X = predict,
y = target)
print("Concluído treinamento do SelectKBest com método ANOVA")
# In[37]:
# Criar dataframe com o resultado da seleção de variáveis
resultado_fs = pd.DataFrame({
'Variavel': predict.columns,
'Selecionado': kbest.get_support(),
'Score': kbest.scores_
}).sort_values("Score", ascending = False).reset_index().drop("index", axis = 1)
# In[38]:
# 8 variáveis com mais score para o treinamento do modelo
variaveis_predict = resultado_fs.iloc[0:8].Variavel.values
# In[39]:
# Manter somente as variáveis que foram selecionadas na lista de variáveis numéricas
variaveis_numericas_novas = []
for i in variaveis_numericas.copy():
if ( i in variaveis_predict ):
variaveis_numericas_novas.append(i)
variaveis_numericas = variaveis_numericas_novas.copy()
# In[40]:
# Exibir variaveis preditoras selecionadas
variaveis_predict
# As variaveis exibidas acima serão utilizadas para o treinamento do modelo de machine learning porque são as variáveis que tiveram mais score na seleção de variáveis
# ## 6.0 - Preparar dataset de treino e teste para o treinamento
# In[41]:
# Primeiras linhas do dataset de teste
teste_raw.head()
# In[42]:
# Tratar o dataset de teste
teste_munging = tratar_dados(teste_raw)
# In[43]:
# Manter somente variáveis da feature selection (seleção de variáveis) nos datasets e separar dados de treino e de teste #
# Dataset de treino
x_treino = treino_munging_no_outliers[variaveis_predict]
y_treino = treino_munging_no_outliers["churn"]
# Dataset de teste
x_teste = teste_munging[variaveis_predict]
y_teste = teste_munging["churn"]
# In[44]:
# Primeiras linhas do dataset de teste sem a variável target após o tratamento dos dados
x_teste.head()
# In[45]:
# Balancear dataset de treino
x_treino_balanceado, y_treino_balanceado = SMOTE().fit_resample(x_treino, y_treino)
# In[46]:
# Dimensões do dataset de treino balanceado
print("Dimensões das variáveis preditoras:", x_treino_balanceado.shape)
print("Quantidade de registros da variável target:", y_treino_balanceado.count())
# Dataset está com 4940 registros, com 8 variáveis preditoras e uma variável target após o balanceamento da classe target.
# ## 7.0 - Treinamento do Modelo de Machine Learning
# In[47]:
# In[48]:
# Treinar modelos de regressão logistica e naive bayes com a técnica de cross validation
modelos = obter_modelos()
k = KFold(n_splits=10)
for nome, modelo in modelos:
cv = cross_validate(estimator = modelo,
X = x_treino_balanceado,
y = y_treino_balanceado,
cv = k,
scoring=['accuracy', 'recall', 'precision'])
print( "%s:\n\tAcurácia: %.3f \n\tRecall: %.3f \n\tPrecisão: %.3f \n" %
( nome,
np.mean(cv["test_accuracy"]),
np.mean(cv["test_recall"]),
np.mean(cv["test_precision"])) )
# Os modelos que apresentaram melhores resultados foram KNN e SVM, vamos realizar treinamento desses modelos individualmente para serem avaliados com dados de teste.
# In[49]:
# Treinamento do modelo KNN
modelo_knn_v1 = KNeighborsClassifier()
modelo_knn_v1.probability=True
modelo_knn_v1.fit(X = x_treino_balanceado, y = y_treino_balanceado)
print("Concluído treinamento do algoritmo KNN")
# In[50]:
# Treinamento do modelo SVM Classifier
modelo_svm_v1 = SVC()
modelo_svm_v1.probability=True
modelo_svm_v1.fit(X = x_treino_balanceado, y = y_treino_balanceado)
print("Concluído treinamento do algoritmo SVM")
# ## 8.0 - Avaliação do Modelo de Machine Learning
# Métricas escolhida para avalição do modelo: Recall
# In[51]:
# Avaliação do modelo KNN com os dados de teste
previsao_knn_v1 = modelo_knn_v1.predict(x_teste)
print( "Avaliação do modelo KNN:\n" )
print( classification_report(y_teste, previsao_knn_v1) )
# In[52]:
# Avaliação do modelo SVM com os dados de teste
previsao_svm_v1 = modelo_svm_v1.predict(x_teste)
print( "Avaliação do modelo SVM:\n" )
print( classification_report(y_teste, previsao_svm_v1) )
# O modelo SVM foi superior na métrica recall, esse modelo é o escolhido para receber otimização de hiperparametros.
# ## 9.0 - Otimização do Modelo de Machine Learning
# In[53]:
# Treinar modelo Random Forest para realizar otimização
modelo_rfc_v1 = RandomForestClassifier(n_estimators=1000)
modelo_rfc_v1.fit(x_treino_balanceado, y_treino_balanceado)
print("Concluído treinamento do algoritmo Random Forest")
# In[54]:
# Avaliação do modelo Random Forest com os dados de teste
previsao_rfc_v1 = modelo_rfc_v1.predict(x_teste)
print( "Avaliação do modelo Random Forest Classifier:\n" )
print( classification_report(y_teste, previsao_rfc_v1) )
# O modelo Random Forest não teve um recall superior ao modelo SVM.
# In[55]:
# Treinar modelo XGBoost para realizar otimização
modelo_xgb_v1 = XGBClassifier(n_estimators=500)
modelo_xgb_v1.fit(x_treino_balanceado, y_treino_balanceado)
print("Concluído treinamento do algoritmo XGBoost")
# In[56]:
# Avaliação do modelo XGBoost com os dados de teste
previsao_xgb_v1 = modelo_xgb_v1.predict(x_teste)
previsao_xgb_v1 = [round(value) for value in previsao_xgb_v1]
print( "Avaliação do modelo XGBoost Classifier:\n" )
print( classification_report(y_teste, previsao_xgb_v1) )
# O modelo XGBoost não teve um recall superior ao modelo SVM.
# In[57]:
# Otimizar hiperparametros do modelo SVM com GridSearchCV #
# Parametros do Grid
param_grid = {'C': [0.1],
'kernel': ['rbf'],
'gamma': ['scale'],
'tol': [0.001],
'class_weight': [{0:1.0, 1:1.10}, {0:1.0, 1:1.12}]
}
# Treinar GridSearchCV
grid = GridSearchCV(SVC(), param_grid, refit=True, verbose=2, cv=KFold(n_splits=6), scoring='recall')
grid.fit(x_treino_balanceado, y_treino_balanceado)
# In[58]:
# Exibir melhores parametros encontrados com o GridSearchCV
print("Melhores parametros:")
print(grid.best_params_)
# In[59]:
pd.DataFrame(grid.cv_results_).sort_values(["rank_test_score"]).head()
# In[60]:
# Avaliar modelo treinado com GridSearchCV utilizando os dados de teste
grid_previsoes = grid.predict(x_teste)
print( "Matriz de confusão:\n" )
print( confusion_matrix(y_teste, grid_previsoes) )
print( "\nRelatório de classificação:\n" )
print( classification_report(y_teste, grid_previsoes) )
# O modelo treinado com os hyperparametros ('C': 0.1, 'class_weight': {0: 1.0, 1: 1.12}, 'gamma': 'scale', 'kernel': 'rbf', 'tol': 0.001) será o modelo escolhido para entrega final do projeto.
# Modelo teve uma queda de 3% de recall para a classe 0 (No), porém teve um aumento de 5% de recall para a classe 1 (Yes).
# ## 10.0 - Salvar o Modelo de Machine Learning para Entrega Final do Projeto
# In[61]:
# Treinamento do modelo final
modelo_svm_final = SVC(C=0.1, class_weight={0:1.0, 1:1.12}, gamma='scale', kernel='rbf', tol=0.001)
modelo_svm_final.probability = True
modelo_svm_final.fit(x_treino_balanceado, y_treino_balanceado)
print( "Treinamento do Modelo SVM (Versão final) realizado com sucesso" )
# In[62]:
# Prever resultado de Churn e a probabilidade para os dados de teste
previsao_modelo_svm_final = modelo_svm_final.predict(x_teste)
previsao_prob_modelo_svm_final = modelo_svm_final.predict_proba(x_teste)
df_previsoes = pd.DataFrame({
'churn': pd.Series(previsao_modelo_svm_final, dtype=np.int32),
'Probabilidade_ChurnNo': pd.Series(np.round(previsao_prob_modelo_svm_final.transpose()[0], 2), dtype=np.float32),
'Probabilidade_ChurnYes': pd.Series(np.round(previsao_prob_modelo_svm_final.transpose()[1], 2), dtype=np.float32)
})
# In[63]:
# Dataset de teste com a previsão e probabilidade de churn
teste_resultado = inverter_dados(x_teste.join(df_previsoes))
teste_resultado.head()
# In[64]:
# Salvar modelo de machine learning
nome_arquivo = "../modelo/modelo_svm_final.sav"
pickle.dump(modelo_svm_final, open(nome_arquivo, 'wb'))
# ## FIM.
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] | 2.424197 | 7,968 |
__all__ = []
from .nodebuffer import NodeBuffer, NodeDescriptor, BufferSet
from .nodebuffer import Scanner as _Scanner
scan = _Scanner.scan
from .jit import JITCompiler as jit
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from __future__ import division
from __future__ import print_function
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--epochs', type=int, default=100, help='Number of epochs to train.')
parser.add_argument('--split',nargs='+', type=float, default=[0.9, 0.1, 0.], help="train, test, validation split, default = [0.8, 0.2] (No validation)")
parser.add_argument('--batch_size', type=int, default=10, help="batch-size, i.e, how many molecules get 'merged' to form a graph per iteration during traing")
parser.add_argument('--lr', type=float, default=0.001, help='Learning rate.')
parser.add_argument('--hidden_dims', nargs='+', type=int, default=[256, 128], help="hidden dimension 1")
parser.add_argument('--embedding_dim', type=int, default=64, help="node embedding dimension")
parser.add_argument('--html', type=str, default="results.html", help="File to save results to")
args = parser.parse_args()
import torch
from torch import optim
# import time
# import numpy as np
# import scipy.sparse as sp
import dgl
import pinot
from pinot.data.utils import batch, split
from pinot.generative.torch_gvae.model import GCNModelVAE
# from pinot.generative.torch_gvae.loss import negative_ELBO
# from pinot.app.experiment import Train, Test, TrainAndTest, MultipleTrainAndTest
from pinot.app.experiment import TrainAndTest
from pinot.app.report import html
################ METRICS ON EDGE PREDICTION ###################
if __name__ == '__main__':
run(args)
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] | 3.164179 | 469 |
import typing # noqa: F401
from kubernetes import client # noqa: F401
from kuber import kube_api as _kube_api # noqa: F401
from kuber import definitions as _kuber_definitions # noqa: F401
from kuber import _types # noqa: F401
from kuber.latest.meta_v1 import ListMeta # noqa: F401
from kuber.latest.meta_v1 import ObjectMeta # noqa: F401
from kuber.latest.meta_v1 import Status # noqa: F401
from kuber.latest.meta_v1 import StatusDetails # noqa: F401
class LocalSubjectAccessReview(_kuber_definitions.Resource):
"""
LocalSubjectAccessReview checks whether or not a user or
group can perform an action in a given namespace. Having a
namespace scoped resource makes it much easier to grant
namespace scoped policy that includes permissions checking.
"""
def __init__(
self,
metadata: "ObjectMeta" = None,
spec: "SubjectAccessReviewSpec" = None,
status: "SubjectAccessReviewStatus" = None,
):
"""Create LocalSubjectAccessReview instance."""
super(LocalSubjectAccessReview, self).__init__(
api_version="authorization/v1", kind="LocalSubjectAccessReview"
)
self._properties = {
"metadata": metadata if metadata is not None else ObjectMeta(),
"spec": spec if spec is not None else SubjectAccessReviewSpec(),
"status": status if status is not None else SubjectAccessReviewStatus(),
}
self._types = {
"apiVersion": (str, None),
"kind": (str, None),
"metadata": (ObjectMeta, None),
"spec": (SubjectAccessReviewSpec, None),
"status": (SubjectAccessReviewStatus, None),
}
@property
def metadata(self) -> "ObjectMeta":
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
return typing.cast(
"ObjectMeta",
self._properties.get("metadata"),
)
@metadata.setter
def metadata(self, value: typing.Union["ObjectMeta", dict]):
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
if isinstance(value, dict):
value = typing.cast(
ObjectMeta,
ObjectMeta().from_dict(value),
)
self._properties["metadata"] = value
@property
def spec(self) -> "SubjectAccessReviewSpec":
"""
Spec holds information about the request being evaluated.
spec.namespace must be equal to the namespace you made the
request against. If empty, it is defaulted.
"""
return typing.cast(
"SubjectAccessReviewSpec",
self._properties.get("spec"),
)
@spec.setter
def spec(self, value: typing.Union["SubjectAccessReviewSpec", dict]):
"""
Spec holds information about the request being evaluated.
spec.namespace must be equal to the namespace you made the
request against. If empty, it is defaulted.
"""
if isinstance(value, dict):
value = typing.cast(
SubjectAccessReviewSpec,
SubjectAccessReviewSpec().from_dict(value),
)
self._properties["spec"] = value
@property
def status(self) -> "SubjectAccessReviewStatus":
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
return typing.cast(
"SubjectAccessReviewStatus",
self._properties.get("status"),
)
@status.setter
def status(self, value: typing.Union["SubjectAccessReviewStatus", dict]):
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
if isinstance(value, dict):
value = typing.cast(
SubjectAccessReviewStatus,
SubjectAccessReviewStatus().from_dict(value),
)
self._properties["status"] = value
def create_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Creates the LocalSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the create is complete.
"""
names = [
"create_namespaced_local_subject_access_review",
"create_local_subject_access_review",
]
response = _kube_api.execute(
action="create",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict()},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def replace_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Replaces the LocalSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"replace_namespaced_local_subject_access_review",
"replace_local_subject_access_review",
]
response = _kube_api.execute(
action="replace",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def patch_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Patches the LocalSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"patch_namespaced_local_subject_access_review",
"patch_local_subject_access_review",
]
response = _kube_api.execute(
action="patch",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def get_resource_status(
self, namespace: "str" = None
) -> "SubjectAccessReviewStatus":
"""
Returns status information about the given resource within the cluster.
"""
names = [
"read_namespaced_local_subject_access_review",
"read_local_subject_access_review",
]
response = _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def read_resource(self, namespace: str = None):
"""
Reads the LocalSubjectAccessReview from the currently configured
Kubernetes cluster and returns the low-level definition object.
"""
names = [
"read_namespaced_local_subject_access_review",
"read_local_subject_access_review",
]
return _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
def delete_resource(
self,
namespace: str = None,
propagation_policy: str = "Foreground",
grace_period_seconds: int = 10,
):
"""
Deletes the LocalSubjectAccessReview from the currently configured
Kubernetes cluster.
"""
names = [
"delete_namespaced_local_subject_access_review",
"delete_local_subject_access_review",
]
body = client.V1DeleteOptions(
propagation_policy=propagation_policy,
grace_period_seconds=grace_period_seconds,
)
_kube_api.execute(
action="delete",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name, "body": body},
)
@staticmethod
def get_resource_api(
api_client: client.ApiClient = None, **kwargs
) -> "client.AuthorizationV1Api":
"""
Returns an instance of the kubernetes API client associated with
this object.
"""
if api_client:
kwargs["apl_client"] = api_client
return client.AuthorizationV1Api(**kwargs)
class NonResourceAttributes(_kuber_definitions.Definition):
"""
NonResourceAttributes includes the authorization attributes
available for non-resource requests to the Authorizer
interface
"""
def __init__(
self,
path: str = None,
verb: str = None,
):
"""Create NonResourceAttributes instance."""
super(NonResourceAttributes, self).__init__(
api_version="authorization/v1", kind="NonResourceAttributes"
)
self._properties = {
"path": path if path is not None else "",
"verb": verb if verb is not None else "",
}
self._types = {
"path": (str, None),
"verb": (str, None),
}
@property
def path(self) -> str:
"""
Path is the URL path of the request
"""
return typing.cast(
str,
self._properties.get("path"),
)
@path.setter
def path(self, value: str):
"""
Path is the URL path of the request
"""
self._properties["path"] = value
@property
def verb(self) -> str:
"""
Verb is the standard HTTP verb
"""
return typing.cast(
str,
self._properties.get("verb"),
)
@verb.setter
def verb(self, value: str):
"""
Verb is the standard HTTP verb
"""
self._properties["verb"] = value
class NonResourceRule(_kuber_definitions.Definition):
"""
NonResourceRule holds information that describes a rule for
the non-resource
"""
def __init__(
self,
non_resource_urls: typing.List[str] = None,
verbs: typing.List[str] = None,
):
"""Create NonResourceRule instance."""
super(NonResourceRule, self).__init__(
api_version="authorization/v1", kind="NonResourceRule"
)
self._properties = {
"nonResourceURLs": non_resource_urls
if non_resource_urls is not None
else [],
"verbs": verbs if verbs is not None else [],
}
self._types = {
"nonResourceURLs": (list, str),
"verbs": (list, str),
}
@property
def non_resource_urls(self) -> typing.List[str]:
"""
NonResourceURLs is a set of partial urls that a user should
have access to. *s are allowed, but only as the full, final
step in the path. "*" means all.
"""
return typing.cast(
typing.List[str],
self._properties.get("nonResourceURLs"),
)
@non_resource_urls.setter
def non_resource_urls(self, value: typing.List[str]):
"""
NonResourceURLs is a set of partial urls that a user should
have access to. *s are allowed, but only as the full, final
step in the path. "*" means all.
"""
self._properties["nonResourceURLs"] = value
@property
def verbs(self) -> typing.List[str]:
"""
Verb is a list of kubernetes non-resource API verbs, like:
get, post, put, delete, patch, head, options. "*" means
all.
"""
return typing.cast(
typing.List[str],
self._properties.get("verbs"),
)
@verbs.setter
def verbs(self, value: typing.List[str]):
"""
Verb is a list of kubernetes non-resource API verbs, like:
get, post, put, delete, patch, head, options. "*" means
all.
"""
self._properties["verbs"] = value
class ResourceAttributes(_kuber_definitions.Definition):
"""
ResourceAttributes includes the authorization attributes
available for resource requests to the Authorizer interface
"""
def __init__(
self,
group: str = None,
name: str = None,
namespace: str = None,
resource: str = None,
subresource: str = None,
verb: str = None,
version: str = None,
):
"""Create ResourceAttributes instance."""
super(ResourceAttributes, self).__init__(
api_version="authorization/v1", kind="ResourceAttributes"
)
self._properties = {
"group": group if group is not None else "",
"name": name if name is not None else "",
"namespace": namespace if namespace is not None else "",
"resource": resource if resource is not None else "",
"subresource": subresource if subresource is not None else "",
"verb": verb if verb is not None else "",
"version": version if version is not None else "",
}
self._types = {
"group": (str, None),
"name": (str, None),
"namespace": (str, None),
"resource": (str, None),
"subresource": (str, None),
"verb": (str, None),
"version": (str, None),
}
@property
def group(self) -> str:
"""
Group is the API Group of the Resource. "*" means all.
"""
return typing.cast(
str,
self._properties.get("group"),
)
@group.setter
def group(self, value: str):
"""
Group is the API Group of the Resource. "*" means all.
"""
self._properties["group"] = value
@property
def name(self) -> str:
"""
Name is the name of the resource being requested for a "get"
or deleted for a "delete". "" (empty) means all.
"""
return typing.cast(
str,
self._properties.get("name"),
)
@name.setter
def name(self, value: str):
"""
Name is the name of the resource being requested for a "get"
or deleted for a "delete". "" (empty) means all.
"""
self._properties["name"] = value
@property
def namespace(self) -> str:
"""
Namespace is the namespace of the action being requested.
Currently, there is no distinction between no namespace and
all namespaces "" (empty) is defaulted for
LocalSubjectAccessReviews "" (empty) is empty for cluster-
scoped resources "" (empty) means "all" for namespace scoped
resources from a SubjectAccessReview or
SelfSubjectAccessReview
"""
return typing.cast(
str,
self._properties.get("namespace"),
)
@namespace.setter
def namespace(self, value: str):
"""
Namespace is the namespace of the action being requested.
Currently, there is no distinction between no namespace and
all namespaces "" (empty) is defaulted for
LocalSubjectAccessReviews "" (empty) is empty for cluster-
scoped resources "" (empty) means "all" for namespace scoped
resources from a SubjectAccessReview or
SelfSubjectAccessReview
"""
self._properties["namespace"] = value
@property
def resource(self) -> str:
"""
Resource is one of the existing resource types. "*" means
all.
"""
return typing.cast(
str,
self._properties.get("resource"),
)
@resource.setter
def resource(self, value: str):
"""
Resource is one of the existing resource types. "*" means
all.
"""
self._properties["resource"] = value
@property
def subresource(self) -> str:
"""
Subresource is one of the existing resource types. "" means
none.
"""
return typing.cast(
str,
self._properties.get("subresource"),
)
@subresource.setter
def subresource(self, value: str):
"""
Subresource is one of the existing resource types. "" means
none.
"""
self._properties["subresource"] = value
@property
def verb(self) -> str:
"""
Verb is a kubernetes resource API verb, like: get, list,
watch, create, update, delete, proxy. "*" means all.
"""
return typing.cast(
str,
self._properties.get("verb"),
)
@verb.setter
def verb(self, value: str):
"""
Verb is a kubernetes resource API verb, like: get, list,
watch, create, update, delete, proxy. "*" means all.
"""
self._properties["verb"] = value
@property
def version(self) -> str:
"""
Version is the API Version of the Resource. "*" means all.
"""
return typing.cast(
str,
self._properties.get("version"),
)
@version.setter
def version(self, value: str):
"""
Version is the API Version of the Resource. "*" means all.
"""
self._properties["version"] = value
class ResourceRule(_kuber_definitions.Definition):
"""
ResourceRule is the list of actions the subject is allowed
to perform on resources. The list ordering isn't
significant, may contain duplicates, and possibly be
incomplete.
"""
def __init__(
self,
api_groups: typing.List[str] = None,
resource_names: typing.List[str] = None,
resources: typing.List[str] = None,
verbs: typing.List[str] = None,
):
"""Create ResourceRule instance."""
super(ResourceRule, self).__init__(
api_version="authorization/v1", kind="ResourceRule"
)
self._properties = {
"apiGroups": api_groups if api_groups is not None else [],
"resourceNames": resource_names if resource_names is not None else [],
"resources": resources if resources is not None else [],
"verbs": verbs if verbs is not None else [],
}
self._types = {
"apiGroups": (list, str),
"resourceNames": (list, str),
"resources": (list, str),
"verbs": (list, str),
}
@property
def api_groups(self) -> typing.List[str]:
"""
APIGroups is the name of the APIGroup that contains the
resources. If multiple API groups are specified, any action
requested against one of the enumerated resources in any API
group will be allowed. "*" means all.
"""
return typing.cast(
typing.List[str],
self._properties.get("apiGroups"),
)
@api_groups.setter
def api_groups(self, value: typing.List[str]):
"""
APIGroups is the name of the APIGroup that contains the
resources. If multiple API groups are specified, any action
requested against one of the enumerated resources in any API
group will be allowed. "*" means all.
"""
self._properties["apiGroups"] = value
@property
def resource_names(self) -> typing.List[str]:
"""
ResourceNames is an optional white list of names that the
rule applies to. An empty set means that everything is
allowed. "*" means all.
"""
return typing.cast(
typing.List[str],
self._properties.get("resourceNames"),
)
@resource_names.setter
def resource_names(self, value: typing.List[str]):
"""
ResourceNames is an optional white list of names that the
rule applies to. An empty set means that everything is
allowed. "*" means all.
"""
self._properties["resourceNames"] = value
@property
def resources(self) -> typing.List[str]:
"""
Resources is a list of resources this rule applies to. "*"
means all in the specified apiGroups.
"*/foo" represents the subresource 'foo' for all resources
in the specified apiGroups.
"""
return typing.cast(
typing.List[str],
self._properties.get("resources"),
)
@resources.setter
def resources(self, value: typing.List[str]):
"""
Resources is a list of resources this rule applies to. "*"
means all in the specified apiGroups.
"*/foo" represents the subresource 'foo' for all resources
in the specified apiGroups.
"""
self._properties["resources"] = value
@property
def verbs(self) -> typing.List[str]:
"""
Verb is a list of kubernetes resource API verbs, like: get,
list, watch, create, update, delete, proxy. "*" means all.
"""
return typing.cast(
typing.List[str],
self._properties.get("verbs"),
)
@verbs.setter
def verbs(self, value: typing.List[str]):
"""
Verb is a list of kubernetes resource API verbs, like: get,
list, watch, create, update, delete, proxy. "*" means all.
"""
self._properties["verbs"] = value
class SelfSubjectAccessReview(_kuber_definitions.Resource):
"""
SelfSubjectAccessReview checks whether or the current user
can perform an action. Not filling in a spec.namespace
means "in all namespaces". Self is a special case, because
users should always be able to check whether they can
perform an action
"""
def __init__(
self,
metadata: "ObjectMeta" = None,
spec: "SelfSubjectAccessReviewSpec" = None,
status: "SubjectAccessReviewStatus" = None,
):
"""Create SelfSubjectAccessReview instance."""
super(SelfSubjectAccessReview, self).__init__(
api_version="authorization/v1", kind="SelfSubjectAccessReview"
)
self._properties = {
"metadata": metadata if metadata is not None else ObjectMeta(),
"spec": spec if spec is not None else SelfSubjectAccessReviewSpec(),
"status": status if status is not None else SubjectAccessReviewStatus(),
}
self._types = {
"apiVersion": (str, None),
"kind": (str, None),
"metadata": (ObjectMeta, None),
"spec": (SelfSubjectAccessReviewSpec, None),
"status": (SubjectAccessReviewStatus, None),
}
@property
def metadata(self) -> "ObjectMeta":
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
return typing.cast(
"ObjectMeta",
self._properties.get("metadata"),
)
@metadata.setter
def metadata(self, value: typing.Union["ObjectMeta", dict]):
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
if isinstance(value, dict):
value = typing.cast(
ObjectMeta,
ObjectMeta().from_dict(value),
)
self._properties["metadata"] = value
@property
def spec(self) -> "SelfSubjectAccessReviewSpec":
"""
Spec holds information about the request being evaluated.
user and groups must be empty
"""
return typing.cast(
"SelfSubjectAccessReviewSpec",
self._properties.get("spec"),
)
@spec.setter
def spec(self, value: typing.Union["SelfSubjectAccessReviewSpec", dict]):
"""
Spec holds information about the request being evaluated.
user and groups must be empty
"""
if isinstance(value, dict):
value = typing.cast(
SelfSubjectAccessReviewSpec,
SelfSubjectAccessReviewSpec().from_dict(value),
)
self._properties["spec"] = value
@property
def status(self) -> "SubjectAccessReviewStatus":
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
return typing.cast(
"SubjectAccessReviewStatus",
self._properties.get("status"),
)
@status.setter
def status(self, value: typing.Union["SubjectAccessReviewStatus", dict]):
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
if isinstance(value, dict):
value = typing.cast(
SubjectAccessReviewStatus,
SubjectAccessReviewStatus().from_dict(value),
)
self._properties["status"] = value
def create_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Creates the SelfSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the create is complete.
"""
names = [
"create_namespaced_self_subject_access_review",
"create_self_subject_access_review",
]
response = _kube_api.execute(
action="create",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict()},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def replace_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Replaces the SelfSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"replace_namespaced_self_subject_access_review",
"replace_self_subject_access_review",
]
response = _kube_api.execute(
action="replace",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def patch_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Patches the SelfSubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"patch_namespaced_self_subject_access_review",
"patch_self_subject_access_review",
]
response = _kube_api.execute(
action="patch",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def get_resource_status(
self, namespace: "str" = None
) -> "SubjectAccessReviewStatus":
"""
Returns status information about the given resource within the cluster.
"""
names = [
"read_namespaced_self_subject_access_review",
"read_self_subject_access_review",
]
response = _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def read_resource(self, namespace: str = None):
"""
Reads the SelfSubjectAccessReview from the currently configured
Kubernetes cluster and returns the low-level definition object.
"""
names = [
"read_namespaced_self_subject_access_review",
"read_self_subject_access_review",
]
return _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
def delete_resource(
self,
namespace: str = None,
propagation_policy: str = "Foreground",
grace_period_seconds: int = 10,
):
"""
Deletes the SelfSubjectAccessReview from the currently configured
Kubernetes cluster.
"""
names = [
"delete_namespaced_self_subject_access_review",
"delete_self_subject_access_review",
]
body = client.V1DeleteOptions(
propagation_policy=propagation_policy,
grace_period_seconds=grace_period_seconds,
)
_kube_api.execute(
action="delete",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name, "body": body},
)
@staticmethod
def get_resource_api(
api_client: client.ApiClient = None, **kwargs
) -> "client.AuthorizationV1Api":
"""
Returns an instance of the kubernetes API client associated with
this object.
"""
if api_client:
kwargs["apl_client"] = api_client
return client.AuthorizationV1Api(**kwargs)
class SelfSubjectAccessReviewSpec(_kuber_definitions.Definition):
"""
SelfSubjectAccessReviewSpec is a description of the access
request. Exactly one of ResourceAuthorizationAttributes and
NonResourceAuthorizationAttributes must be set
"""
def __init__(
self,
non_resource_attributes: "NonResourceAttributes" = None,
resource_attributes: "ResourceAttributes" = None,
):
"""Create SelfSubjectAccessReviewSpec instance."""
super(SelfSubjectAccessReviewSpec, self).__init__(
api_version="authorization/v1", kind="SelfSubjectAccessReviewSpec"
)
self._properties = {
"nonResourceAttributes": non_resource_attributes
if non_resource_attributes is not None
else NonResourceAttributes(),
"resourceAttributes": resource_attributes
if resource_attributes is not None
else ResourceAttributes(),
}
self._types = {
"nonResourceAttributes": (NonResourceAttributes, None),
"resourceAttributes": (ResourceAttributes, None),
}
@property
def non_resource_attributes(self) -> "NonResourceAttributes":
"""
NonResourceAttributes describes information for a non-
resource access request
"""
return typing.cast(
"NonResourceAttributes",
self._properties.get("nonResourceAttributes"),
)
@non_resource_attributes.setter
def non_resource_attributes(
self, value: typing.Union["NonResourceAttributes", dict]
):
"""
NonResourceAttributes describes information for a non-
resource access request
"""
if isinstance(value, dict):
value = typing.cast(
NonResourceAttributes,
NonResourceAttributes().from_dict(value),
)
self._properties["nonResourceAttributes"] = value
@property
def resource_attributes(self) -> "ResourceAttributes":
"""
ResourceAuthorizationAttributes describes information for a
resource access request
"""
return typing.cast(
"ResourceAttributes",
self._properties.get("resourceAttributes"),
)
@resource_attributes.setter
def resource_attributes(self, value: typing.Union["ResourceAttributes", dict]):
"""
ResourceAuthorizationAttributes describes information for a
resource access request
"""
if isinstance(value, dict):
value = typing.cast(
ResourceAttributes,
ResourceAttributes().from_dict(value),
)
self._properties["resourceAttributes"] = value
class SelfSubjectRulesReview(_kuber_definitions.Resource):
"""
SelfSubjectRulesReview enumerates the set of actions the
current user can perform within a namespace. The returned
list of actions may be incomplete depending on the server's
authorization mode, and any errors experienced during the
evaluation. SelfSubjectRulesReview should be used by UIs to
show/hide actions, or to quickly let an end user reason
about their permissions. It should NOT Be used by external
systems to drive authorization decisions as this raises
confused deputy, cache lifetime/revocation, and correctness
concerns. SubjectAccessReview, and LocalAccessReview are the
correct way to defer authorization decisions to the API
server.
"""
def __init__(
self,
metadata: "ObjectMeta" = None,
spec: "SelfSubjectRulesReviewSpec" = None,
status: "SubjectRulesReviewStatus" = None,
):
"""Create SelfSubjectRulesReview instance."""
super(SelfSubjectRulesReview, self).__init__(
api_version="authorization/v1", kind="SelfSubjectRulesReview"
)
self._properties = {
"metadata": metadata if metadata is not None else ObjectMeta(),
"spec": spec if spec is not None else SelfSubjectRulesReviewSpec(),
"status": status if status is not None else SubjectRulesReviewStatus(),
}
self._types = {
"apiVersion": (str, None),
"kind": (str, None),
"metadata": (ObjectMeta, None),
"spec": (SelfSubjectRulesReviewSpec, None),
"status": (SubjectRulesReviewStatus, None),
}
@property
def metadata(self) -> "ObjectMeta":
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
return typing.cast(
"ObjectMeta",
self._properties.get("metadata"),
)
@metadata.setter
def metadata(self, value: typing.Union["ObjectMeta", dict]):
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
if isinstance(value, dict):
value = typing.cast(
ObjectMeta,
ObjectMeta().from_dict(value),
)
self._properties["metadata"] = value
@property
def spec(self) -> "SelfSubjectRulesReviewSpec":
"""
Spec holds information about the request being evaluated.
"""
return typing.cast(
"SelfSubjectRulesReviewSpec",
self._properties.get("spec"),
)
@spec.setter
def spec(self, value: typing.Union["SelfSubjectRulesReviewSpec", dict]):
"""
Spec holds information about the request being evaluated.
"""
if isinstance(value, dict):
value = typing.cast(
SelfSubjectRulesReviewSpec,
SelfSubjectRulesReviewSpec().from_dict(value),
)
self._properties["spec"] = value
@property
def status(self) -> "SubjectRulesReviewStatus":
"""
Status is filled in by the server and indicates the set of
actions a user can perform.
"""
return typing.cast(
"SubjectRulesReviewStatus",
self._properties.get("status"),
)
@status.setter
def status(self, value: typing.Union["SubjectRulesReviewStatus", dict]):
"""
Status is filled in by the server and indicates the set of
actions a user can perform.
"""
if isinstance(value, dict):
value = typing.cast(
SubjectRulesReviewStatus,
SubjectRulesReviewStatus().from_dict(value),
)
self._properties["status"] = value
def create_resource(self, namespace: "str" = None) -> "SubjectRulesReviewStatus":
"""
Creates the SelfSubjectRulesReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the create is complete.
"""
names = [
"create_namespaced_self_subject_rules_review",
"create_self_subject_rules_review",
]
response = _kube_api.execute(
action="create",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict()},
)
output = SubjectRulesReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def replace_resource(self, namespace: "str" = None) -> "SubjectRulesReviewStatus":
"""
Replaces the SelfSubjectRulesReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"replace_namespaced_self_subject_rules_review",
"replace_self_subject_rules_review",
]
response = _kube_api.execute(
action="replace",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectRulesReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def patch_resource(self, namespace: "str" = None) -> "SubjectRulesReviewStatus":
"""
Patches the SelfSubjectRulesReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"patch_namespaced_self_subject_rules_review",
"patch_self_subject_rules_review",
]
response = _kube_api.execute(
action="patch",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectRulesReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def get_resource_status(
self, namespace: "str" = None
) -> "SubjectRulesReviewStatus":
"""
Returns status information about the given resource within the cluster.
"""
names = [
"read_namespaced_self_subject_rules_review",
"read_self_subject_rules_review",
]
response = _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
output = SubjectRulesReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def read_resource(self, namespace: str = None):
"""
Reads the SelfSubjectRulesReview from the currently configured
Kubernetes cluster and returns the low-level definition object.
"""
names = [
"read_namespaced_self_subject_rules_review",
"read_self_subject_rules_review",
]
return _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
def delete_resource(
self,
namespace: str = None,
propagation_policy: str = "Foreground",
grace_period_seconds: int = 10,
):
"""
Deletes the SelfSubjectRulesReview from the currently configured
Kubernetes cluster.
"""
names = [
"delete_namespaced_self_subject_rules_review",
"delete_self_subject_rules_review",
]
body = client.V1DeleteOptions(
propagation_policy=propagation_policy,
grace_period_seconds=grace_period_seconds,
)
_kube_api.execute(
action="delete",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name, "body": body},
)
@staticmethod
def get_resource_api(
api_client: client.ApiClient = None, **kwargs
) -> "client.AuthorizationV1Api":
"""
Returns an instance of the kubernetes API client associated with
this object.
"""
if api_client:
kwargs["apl_client"] = api_client
return client.AuthorizationV1Api(**kwargs)
class SelfSubjectRulesReviewSpec(_kuber_definitions.Definition):
"""
SelfSubjectRulesReviewSpec defines the specification for
SelfSubjectRulesReview.
"""
def __init__(
self,
namespace: str = None,
):
"""Create SelfSubjectRulesReviewSpec instance."""
super(SelfSubjectRulesReviewSpec, self).__init__(
api_version="authorization/v1", kind="SelfSubjectRulesReviewSpec"
)
self._properties = {
"namespace": namespace if namespace is not None else "",
}
self._types = {
"namespace": (str, None),
}
@property
def namespace(self) -> str:
"""
Namespace to evaluate rules for. Required.
"""
return typing.cast(
str,
self._properties.get("namespace"),
)
@namespace.setter
def namespace(self, value: str):
"""
Namespace to evaluate rules for. Required.
"""
self._properties["namespace"] = value
class SubjectAccessReview(_kuber_definitions.Resource):
"""
SubjectAccessReview checks whether or not a user or group
can perform an action.
"""
def __init__(
self,
metadata: "ObjectMeta" = None,
spec: "SubjectAccessReviewSpec" = None,
status: "SubjectAccessReviewStatus" = None,
):
"""Create SubjectAccessReview instance."""
super(SubjectAccessReview, self).__init__(
api_version="authorization/v1", kind="SubjectAccessReview"
)
self._properties = {
"metadata": metadata if metadata is not None else ObjectMeta(),
"spec": spec if spec is not None else SubjectAccessReviewSpec(),
"status": status if status is not None else SubjectAccessReviewStatus(),
}
self._types = {
"apiVersion": (str, None),
"kind": (str, None),
"metadata": (ObjectMeta, None),
"spec": (SubjectAccessReviewSpec, None),
"status": (SubjectAccessReviewStatus, None),
}
@property
def metadata(self) -> "ObjectMeta":
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
return typing.cast(
"ObjectMeta",
self._properties.get("metadata"),
)
@metadata.setter
def metadata(self, value: typing.Union["ObjectMeta", dict]):
"""
Standard list metadata. More info:
https://git.k8s.io/community/contributors/devel/sig-
architecture/api-conventions.md#metadata
"""
if isinstance(value, dict):
value = typing.cast(
ObjectMeta,
ObjectMeta().from_dict(value),
)
self._properties["metadata"] = value
@property
def spec(self) -> "SubjectAccessReviewSpec":
"""
Spec holds information about the request being evaluated
"""
return typing.cast(
"SubjectAccessReviewSpec",
self._properties.get("spec"),
)
@spec.setter
def spec(self, value: typing.Union["SubjectAccessReviewSpec", dict]):
"""
Spec holds information about the request being evaluated
"""
if isinstance(value, dict):
value = typing.cast(
SubjectAccessReviewSpec,
SubjectAccessReviewSpec().from_dict(value),
)
self._properties["spec"] = value
@property
def status(self) -> "SubjectAccessReviewStatus":
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
return typing.cast(
"SubjectAccessReviewStatus",
self._properties.get("status"),
)
@status.setter
def status(self, value: typing.Union["SubjectAccessReviewStatus", dict]):
"""
Status is filled in by the server and indicates whether the
request is allowed or not
"""
if isinstance(value, dict):
value = typing.cast(
SubjectAccessReviewStatus,
SubjectAccessReviewStatus().from_dict(value),
)
self._properties["status"] = value
def create_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Creates the SubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the create is complete.
"""
names = [
"create_namespaced_subject_access_review",
"create_subject_access_review",
]
response = _kube_api.execute(
action="create",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict()},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def replace_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Replaces the SubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"replace_namespaced_subject_access_review",
"replace_subject_access_review",
]
response = _kube_api.execute(
action="replace",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def patch_resource(self, namespace: "str" = None) -> "SubjectAccessReviewStatus":
"""
Patches the SubjectAccessReview in the currently
configured Kubernetes cluster and returns the status information
returned by the Kubernetes API after the replace is complete.
"""
names = [
"patch_namespaced_subject_access_review",
"patch_subject_access_review",
]
response = _kube_api.execute(
action="patch",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"body": self.to_dict(), "name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def get_resource_status(
self, namespace: "str" = None
) -> "SubjectAccessReviewStatus":
"""
Returns status information about the given resource within the cluster.
"""
names = [
"read_namespaced_subject_access_review",
"read_subject_access_review",
]
response = _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
output = SubjectAccessReviewStatus()
if response is not None:
output.from_dict(_kube_api.to_kuber_dict(response.status))
return output
def read_resource(self, namespace: str = None):
"""
Reads the SubjectAccessReview from the currently configured
Kubernetes cluster and returns the low-level definition object.
"""
names = [
"read_namespaced_subject_access_review",
"read_subject_access_review",
]
return _kube_api.execute(
action="read",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name},
)
def delete_resource(
self,
namespace: str = None,
propagation_policy: str = "Foreground",
grace_period_seconds: int = 10,
):
"""
Deletes the SubjectAccessReview from the currently configured
Kubernetes cluster.
"""
names = [
"delete_namespaced_subject_access_review",
"delete_subject_access_review",
]
body = client.V1DeleteOptions(
propagation_policy=propagation_policy,
grace_period_seconds=grace_period_seconds,
)
_kube_api.execute(
action="delete",
resource=self,
names=names,
namespace=namespace,
api_client=None,
api_args={"name": self.metadata.name, "body": body},
)
@staticmethod
def get_resource_api(
api_client: client.ApiClient = None, **kwargs
) -> "client.AuthorizationV1Api":
"""
Returns an instance of the kubernetes API client associated with
this object.
"""
if api_client:
kwargs["apl_client"] = api_client
return client.AuthorizationV1Api(**kwargs)
class SubjectAccessReviewSpec(_kuber_definitions.Definition):
"""
SubjectAccessReviewSpec is a description of the access
request. Exactly one of ResourceAuthorizationAttributes and
NonResourceAuthorizationAttributes must be set
"""
def __init__(
self,
extra: dict = None,
groups: typing.List[str] = None,
non_resource_attributes: "NonResourceAttributes" = None,
resource_attributes: "ResourceAttributes" = None,
uid: str = None,
user: str = None,
):
"""Create SubjectAccessReviewSpec instance."""
super(SubjectAccessReviewSpec, self).__init__(
api_version="authorization/v1", kind="SubjectAccessReviewSpec"
)
self._properties = {
"extra": extra if extra is not None else {},
"groups": groups if groups is not None else [],
"nonResourceAttributes": non_resource_attributes
if non_resource_attributes is not None
else NonResourceAttributes(),
"resourceAttributes": resource_attributes
if resource_attributes is not None
else ResourceAttributes(),
"uid": uid if uid is not None else "",
"user": user if user is not None else "",
}
self._types = {
"extra": (dict, None),
"groups": (list, str),
"nonResourceAttributes": (NonResourceAttributes, None),
"resourceAttributes": (ResourceAttributes, None),
"uid": (str, None),
"user": (str, None),
}
@property
def extra(self) -> dict:
"""
Extra corresponds to the user.Info.GetExtra() method from
the authenticator. Since that is input to the authorizer it
needs a reflection here.
"""
return typing.cast(
dict,
self._properties.get("extra"),
)
@extra.setter
def extra(self, value: dict):
"""
Extra corresponds to the user.Info.GetExtra() method from
the authenticator. Since that is input to the authorizer it
needs a reflection here.
"""
self._properties["extra"] = value
@property
def groups(self) -> typing.List[str]:
"""
Groups is the groups you're testing for.
"""
return typing.cast(
typing.List[str],
self._properties.get("groups"),
)
@groups.setter
def groups(self, value: typing.List[str]):
"""
Groups is the groups you're testing for.
"""
self._properties["groups"] = value
@property
def non_resource_attributes(self) -> "NonResourceAttributes":
"""
NonResourceAttributes describes information for a non-
resource access request
"""
return typing.cast(
"NonResourceAttributes",
self._properties.get("nonResourceAttributes"),
)
@non_resource_attributes.setter
def non_resource_attributes(
self, value: typing.Union["NonResourceAttributes", dict]
):
"""
NonResourceAttributes describes information for a non-
resource access request
"""
if isinstance(value, dict):
value = typing.cast(
NonResourceAttributes,
NonResourceAttributes().from_dict(value),
)
self._properties["nonResourceAttributes"] = value
@property
def resource_attributes(self) -> "ResourceAttributes":
"""
ResourceAuthorizationAttributes describes information for a
resource access request
"""
return typing.cast(
"ResourceAttributes",
self._properties.get("resourceAttributes"),
)
@resource_attributes.setter
def resource_attributes(self, value: typing.Union["ResourceAttributes", dict]):
"""
ResourceAuthorizationAttributes describes information for a
resource access request
"""
if isinstance(value, dict):
value = typing.cast(
ResourceAttributes,
ResourceAttributes().from_dict(value),
)
self._properties["resourceAttributes"] = value
@property
def uid(self) -> str:
"""
UID information about the requesting user.
"""
return typing.cast(
str,
self._properties.get("uid"),
)
@uid.setter
def uid(self, value: str):
"""
UID information about the requesting user.
"""
self._properties["uid"] = value
@property
def user(self) -> str:
"""
User is the user you're testing for. If you specify "User"
but not "Groups", then is it interpreted as "What if User
were not a member of any groups
"""
return typing.cast(
str,
self._properties.get("user"),
)
@user.setter
def user(self, value: str):
"""
User is the user you're testing for. If you specify "User"
but not "Groups", then is it interpreted as "What if User
were not a member of any groups
"""
self._properties["user"] = value
class SubjectAccessReviewStatus(_kuber_definitions.Definition):
"""
SubjectAccessReviewStatus
"""
def __init__(
self,
allowed: bool = None,
denied: bool = None,
evaluation_error: str = None,
reason: str = None,
):
"""Create SubjectAccessReviewStatus instance."""
super(SubjectAccessReviewStatus, self).__init__(
api_version="authorization/v1", kind="SubjectAccessReviewStatus"
)
self._properties = {
"allowed": allowed if allowed is not None else None,
"denied": denied if denied is not None else None,
"evaluationError": evaluation_error if evaluation_error is not None else "",
"reason": reason if reason is not None else "",
}
self._types = {
"allowed": (bool, None),
"denied": (bool, None),
"evaluationError": (str, None),
"reason": (str, None),
}
@property
def allowed(self) -> bool:
"""
Allowed is required. True if the action would be allowed,
false otherwise.
"""
return typing.cast(
bool,
self._properties.get("allowed"),
)
@allowed.setter
def allowed(self, value: bool):
"""
Allowed is required. True if the action would be allowed,
false otherwise.
"""
self._properties["allowed"] = value
@property
def denied(self) -> bool:
"""
Denied is optional. True if the action would be denied,
otherwise false. If both allowed is false and denied is
false, then the authorizer has no opinion on whether to
authorize the action. Denied may not be true if Allowed is
true.
"""
return typing.cast(
bool,
self._properties.get("denied"),
)
@denied.setter
def denied(self, value: bool):
"""
Denied is optional. True if the action would be denied,
otherwise false. If both allowed is false and denied is
false, then the authorizer has no opinion on whether to
authorize the action. Denied may not be true if Allowed is
true.
"""
self._properties["denied"] = value
@property
def evaluation_error(self) -> str:
"""
EvaluationError is an indication that some error occurred
during the authorization check. It is entirely possible to
get an error and be able to continue determine authorization
status in spite of it. For instance, RBAC can be missing a
role, but enough roles are still present and bound to reason
about the request.
"""
return typing.cast(
str,
self._properties.get("evaluationError"),
)
@evaluation_error.setter
def evaluation_error(self, value: str):
"""
EvaluationError is an indication that some error occurred
during the authorization check. It is entirely possible to
get an error and be able to continue determine authorization
status in spite of it. For instance, RBAC can be missing a
role, but enough roles are still present and bound to reason
about the request.
"""
self._properties["evaluationError"] = value
@property
def reason(self) -> str:
"""
Reason is optional. It indicates why a request was allowed
or denied.
"""
return typing.cast(
str,
self._properties.get("reason"),
)
@reason.setter
def reason(self, value: str):
"""
Reason is optional. It indicates why a request was allowed
or denied.
"""
self._properties["reason"] = value
class SubjectRulesReviewStatus(_kuber_definitions.Definition):
"""
SubjectRulesReviewStatus contains the result of a rules
check. This check can be incomplete depending on the set of
authorizers the server is configured with and any errors
experienced during evaluation. Because authorization rules
are additive, if a rule appears in a list it's safe to
assume the subject has that permission, even if that list is
incomplete.
"""
def __init__(
self,
evaluation_error: str = None,
incomplete: bool = None,
non_resource_rules: typing.List["NonResourceRule"] = None,
resource_rules: typing.List["ResourceRule"] = None,
):
"""Create SubjectRulesReviewStatus instance."""
super(SubjectRulesReviewStatus, self).__init__(
api_version="authorization/v1", kind="SubjectRulesReviewStatus"
)
self._properties = {
"evaluationError": evaluation_error if evaluation_error is not None else "",
"incomplete": incomplete if incomplete is not None else None,
"nonResourceRules": non_resource_rules
if non_resource_rules is not None
else [],
"resourceRules": resource_rules if resource_rules is not None else [],
}
self._types = {
"evaluationError": (str, None),
"incomplete": (bool, None),
"nonResourceRules": (list, NonResourceRule),
"resourceRules": (list, ResourceRule),
}
@property
def evaluation_error(self) -> str:
"""
EvaluationError can appear in combination with Rules. It
indicates an error occurred during rule evaluation, such as
an authorizer that doesn't support rule evaluation, and that
ResourceRules and/or NonResourceRules may be incomplete.
"""
return typing.cast(
str,
self._properties.get("evaluationError"),
)
@evaluation_error.setter
def evaluation_error(self, value: str):
"""
EvaluationError can appear in combination with Rules. It
indicates an error occurred during rule evaluation, such as
an authorizer that doesn't support rule evaluation, and that
ResourceRules and/or NonResourceRules may be incomplete.
"""
self._properties["evaluationError"] = value
@property
def incomplete(self) -> bool:
"""
Incomplete is true when the rules returned by this call are
incomplete. This is most commonly encountered when an
authorizer, such as an external authorizer, doesn't support
rules evaluation.
"""
return typing.cast(
bool,
self._properties.get("incomplete"),
)
@incomplete.setter
def incomplete(self, value: bool):
"""
Incomplete is true when the rules returned by this call are
incomplete. This is most commonly encountered when an
authorizer, such as an external authorizer, doesn't support
rules evaluation.
"""
self._properties["incomplete"] = value
@property
def non_resource_rules(self) -> typing.List["NonResourceRule"]:
"""
NonResourceRules is the list of actions the subject is
allowed to perform on non-resources. The list ordering isn't
significant, may contain duplicates, and possibly be
incomplete.
"""
return typing.cast(
typing.List["NonResourceRule"],
self._properties.get("nonResourceRules"),
)
@non_resource_rules.setter
def non_resource_rules(
self, value: typing.Union[typing.List["NonResourceRule"], typing.List[dict]]
):
"""
NonResourceRules is the list of actions the subject is
allowed to perform on non-resources. The list ordering isn't
significant, may contain duplicates, and possibly be
incomplete.
"""
cleaned: typing.List[NonResourceRule] = []
for item in value:
if isinstance(item, dict):
item = typing.cast(
NonResourceRule,
NonResourceRule().from_dict(item),
)
cleaned.append(typing.cast(NonResourceRule, item))
self._properties["nonResourceRules"] = cleaned
@property
def resource_rules(self) -> typing.List["ResourceRule"]:
"""
ResourceRules is the list of actions the subject is allowed
to perform on resources. The list ordering isn't
significant, may contain duplicates, and possibly be
incomplete.
"""
return typing.cast(
typing.List["ResourceRule"],
self._properties.get("resourceRules"),
)
@resource_rules.setter
def resource_rules(
self, value: typing.Union[typing.List["ResourceRule"], typing.List[dict]]
):
"""
ResourceRules is the list of actions the subject is allowed
to perform on resources. The list ordering isn't
significant, may contain duplicates, and possibly be
incomplete.
"""
cleaned: typing.List[ResourceRule] = []
for item in value:
if isinstance(item, dict):
item = typing.cast(
ResourceRule,
ResourceRule().from_dict(item),
)
cleaned.append(typing.cast(ResourceRule, item))
self._properties["resourceRules"] = cleaned
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220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
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13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
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12340,
198,
220,
220,
220,
220,
220,
220,
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1267,
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2488,
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13,
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220,
220,
825,
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7,
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25,
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13,
38176,
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8633,
60,
2599,
198,
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220,
220,
220,
220,
220,
220,
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198,
220,
220,
220,
220,
220,
220,
220,
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13,
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25,
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220,
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13,
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14,
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220,
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220,
220,
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14,
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13,
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2,
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1988,
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220,
220,
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220,
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220,
220,
220,
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1988,
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220,
220,
220,
220,
220,
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13,
220,
1002,
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318,
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220,
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220,
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19776,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
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13,
1136,
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12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
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13,
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353,
198,
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220,
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11,
1988,
25,
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13,
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60,
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220,
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220,
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220,
37227,
198,
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220,
220,
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6622,
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546,
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13,
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220,
220,
220,
220,
220,
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13,
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262,
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220,
220,
220,
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220,
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1028,
13,
220,
1002,
6565,
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340,
318,
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276,
13,
198,
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220,
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8633,
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220,
220,
220,
220,
220,
220,
220,
220,
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1988,
796,
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13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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198,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
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6738,
62,
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7,
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828,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
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16684,
8973,
796,
1988,
628,
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220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3722,
7,
944,
8,
4613,
366,
19776,
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19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
12678,
318,
5901,
287,
416,
262,
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290,
9217,
1771,
262,
198,
220,
220,
220,
220,
220,
220,
220,
2581,
318,
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393,
407,
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220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
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13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
19776,
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198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
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12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
13376,
13,
2617,
353,
198,
220,
220,
220,
825,
3722,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
19776,
15457,
14832,
19580,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
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262,
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290,
9217,
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262,
198,
220,
220,
220,
220,
220,
220,
220,
2581,
318,
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407,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15540,
15457,
14832,
19580,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15540,
15457,
14832,
19580,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
13376,
8973,
796,
1988,
628,
220,
220,
220,
825,
2251,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7921,
274,
262,
10714,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
2251,
318,
1844,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3891,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17953,
62,
14933,
32416,
62,
12001,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17953,
62,
12001,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
4808,
74,
3266,
62,
15042,
13,
41049,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
17953,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8271,
28,
944,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3891,
28,
14933,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25745,
28,
14933,
10223,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
16366,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
22046,
28,
4895,
2618,
1298,
2116,
13,
1462,
62,
11600,
3419,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
15540,
15457,
14832,
19580,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
13,
6738,
62,
11600,
28264,
74,
3266,
62,
15042,
13,
1462,
62,
74,
18478,
62,
11600,
7,
26209,
13,
13376,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5072,
628,
220,
220,
220,
825,
6330,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18407,
2114,
262,
10714,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
6330,
318,
1844,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3891,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
33491,
62,
14933,
32416,
62,
12001,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
33491,
62,
12001,
62,
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62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
4808,
74,
3266,
62,
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13,
41049,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
33491,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8271,
28,
944,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3891,
28,
14933,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25745,
28,
14933,
10223,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
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28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
22046,
28,
4895,
2618,
1298,
2116,
13,
1462,
62,
11600,
22784,
366,
3672,
1298,
2116,
13,
38993,
13,
3672,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
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5072,
796,
15540,
15457,
14832,
19580,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
13,
6738,
62,
11600,
28264,
74,
3266,
62,
15042,
13,
1462,
62,
74,
18478,
62,
11600,
7,
26209,
13,
13376,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5072,
628,
220,
220,
220,
825,
8529,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3208,
2052,
262,
10714,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
6330,
318,
1844,
13,
198,
220,
220,
220,
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13,
2617,
353,
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220,
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1448,
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11,
1988,
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220,
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13,
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1,
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198,
220,
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2116,
13557,
48310,
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8973,
796,
1988,
628,
220,
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2488,
26745,
198,
220,
220,
220,
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1438,
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944,
8,
4613,
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198,
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852,
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1,
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1988,
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19776,
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8,
318,
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19776,
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318,
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19776,
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1988,
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7,
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1988,
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1988,
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26745,
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15942,
7,
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4613,
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37227,
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49973,
318,
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3262,
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7824,
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11,
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25,
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11,
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11,
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11,
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11,
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11,
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11,
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13,
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1,
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13,
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11,
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220,
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220,
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2488,
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7,
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1988,
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1988,
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2488,
26745,
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10628,
318,
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7824,
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13,
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1,
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1988,
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1988,
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12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
10267,
48526,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
38993,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
38993,
13,
2617,
353,
198,
220,
220,
220,
825,
20150,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
10267,
48526,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
38993,
8973,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
1020,
7,
944,
8,
4613,
366,
24704,
19776,
15457,
14832,
22882,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18291,
6622,
1321,
546,
262,
2581,
852,
16726,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2836,
290,
2628,
1276,
307,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
24704,
19776,
15457,
14832,
22882,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
16684,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
16684,
13,
2617,
353,
198,
220,
220,
220,
825,
1020,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
24704,
19776,
15457,
14832,
22882,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18291,
6622,
1321,
546,
262,
2581,
852,
16726,
13,
198,
220,
220,
220,
220,
220,
220,
220,
2836,
290,
2628,
1276,
307,
6565,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12189,
19776,
15457,
14832,
22882,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12189,
19776,
15457,
14832,
22882,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
16684,
8973,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3722,
7,
944,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
12678,
318,
5901,
287,
416,
262,
4382,
290,
9217,
1771,
262,
198,
220,
220,
220,
220,
220,
220,
220,
2581,
318,
3142,
393,
407,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
19776,
15457,
14832,
19580,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
13376,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
13376,
13,
2617,
353,
198,
220,
220,
220,
825,
3722,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
19776,
15457,
14832,
19580,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
12678,
318,
5901,
287,
416,
262,
4382,
290,
9217,
1771,
262,
198,
220,
220,
220,
220,
220,
220,
220,
2581,
318,
3142,
393,
407,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15540,
15457,
14832,
19580,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
15540,
15457,
14832,
19580,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
13376,
8973,
796,
1988,
628,
220,
220,
220,
825,
2251,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
7921,
274,
262,
12189,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
2251,
318,
1844,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3891,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17953,
62,
14933,
32416,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17953,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
4808,
74,
3266,
62,
15042,
13,
41049,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
17953,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8271,
28,
944,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3891,
28,
14933,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25745,
28,
14933,
10223,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
16366,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
22046,
28,
4895,
2618,
1298,
2116,
13,
1462,
62,
11600,
3419,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
15540,
15457,
14832,
19580,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
13,
6738,
62,
11600,
28264,
74,
3266,
62,
15042,
13,
1462,
62,
74,
18478,
62,
11600,
7,
26209,
13,
13376,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5072,
628,
220,
220,
220,
825,
6330,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18407,
2114,
262,
12189,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
6330,
318,
1844,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3891,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
33491,
62,
14933,
32416,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
33491,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
4808,
74,
3266,
62,
15042,
13,
41049,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2223,
2625,
33491,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8271,
28,
944,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
3891,
28,
14933,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
25745,
28,
14933,
10223,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
16366,
28,
14202,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
22046,
28,
4895,
2618,
1298,
2116,
13,
1462,
62,
11600,
22784,
366,
3672,
1298,
2116,
13,
38993,
13,
3672,
5512,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
220,
220,
220,
220,
5072,
796,
15540,
15457,
14832,
19580,
3419,
198,
220,
220,
220,
220,
220,
220,
220,
611,
2882,
318,
407,
6045,
25,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
5072,
13,
6738,
62,
11600,
28264,
74,
3266,
62,
15042,
13,
1462,
62,
74,
18478,
62,
11600,
7,
26209,
13,
13376,
4008,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
5072,
628,
220,
220,
220,
825,
8529,
62,
31092,
7,
944,
11,
25745,
25,
366,
2536,
1,
796,
6045,
8,
4613,
366,
19776,
15457,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3208,
2052,
262,
12189,
19776,
15457,
14832,
287,
262,
3058,
198,
220,
220,
220,
220,
220,
220,
220,
17839,
12554,
527,
3262,
274,
13946,
290,
5860,
262,
3722,
1321,
198,
220,
220,
220,
220,
220,
220,
220,
4504,
416,
262,
12554,
527,
3262,
274,
7824,
706,
262,
6330,
318,
1844,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
3891,
796,
685,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17147,
62,
14933,
32416,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
17147,
62,
944,
62,
32796,
62,
15526,
62,
19023,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
2361,
628,
220,
220,
220,
220,
220,
220,
220,
2882,
796,
4808,
74,
3266,
62,
15042,
13,
41049,
7,
198,
220,
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220,
366,
15419,
26198,
29021,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
13159,
26198,
29021,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
13159,
62,
31092,
62,
1078,
7657,
13,
2617,
353,
198,
220,
220,
220,
825,
1729,
62,
31092,
62,
1078,
7657,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
1988,
25,
19720,
13,
38176,
14692,
15419,
26198,
29021,
1600,
8633,
60,
198,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8504,
26198,
29021,
8477,
1321,
329,
257,
1729,
12,
198,
220,
220,
220,
220,
220,
220,
220,
8271,
1895,
2581,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8504,
26198,
29021,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
8504,
26198,
29021,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
13159,
26198,
29021,
8973,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
8271,
62,
1078,
7657,
7,
944,
8,
4613,
366,
26198,
29021,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
20857,
13838,
1634,
29021,
8477,
1321,
329,
257,
198,
220,
220,
220,
220,
220,
220,
220,
8271,
1895,
2581,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
26198,
29021,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
31092,
29021,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
31092,
62,
1078,
7657,
13,
2617,
353,
198,
220,
220,
220,
825,
8271,
62,
1078,
7657,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
26198,
29021,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
20857,
13838,
1634,
29021,
8477,
1321,
329,
257,
198,
220,
220,
220,
220,
220,
220,
220,
8271,
1895,
2581,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20857,
29021,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
20857,
29021,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
31092,
29021,
8973,
796,
1988,
628,
198,
4871,
12189,
19776,
37766,
14832,
28264,
74,
18478,
62,
4299,
50101,
13,
26198,
2599,
198,
220,
220,
220,
37227,
198,
220,
220,
220,
12189,
19776,
37766,
14832,
27056,
689,
262,
900,
286,
4028,
262,
198,
220,
220,
220,
1459,
2836,
460,
1620,
1626,
257,
25745,
13,
383,
4504,
198,
220,
220,
220,
1351,
286,
4028,
743,
307,
17503,
6906,
319,
262,
4382,
338,
198,
220,
220,
220,
19601,
4235,
11,
290,
597,
8563,
5924,
1141,
262,
198,
220,
220,
220,
12660,
13,
12189,
19776,
37766,
14832,
815,
307,
973,
416,
471,
3792,
284,
198,
220,
220,
220,
905,
14,
24717,
4028,
11,
393,
284,
2952,
1309,
281,
886,
2836,
1738,
198,
220,
220,
220,
546,
511,
21627,
13,
632,
815,
5626,
1355,
973,
416,
7097,
198,
220,
220,
220,
3341,
284,
3708,
19601,
5370,
355,
428,
12073,
198,
220,
220,
220,
10416,
10636,
11,
12940,
10869,
14,
18218,
5040,
11,
290,
29409,
198,
220,
220,
220,
4786,
13,
15540,
15457,
14832,
11,
290,
10714,
15457,
14832,
389,
262,
198,
220,
220,
220,
3376,
835,
284,
29135,
19601,
5370,
284,
262,
7824,
198,
220,
220,
220,
4382,
13,
198,
220,
220,
220,
37227,
628,
220,
220,
220,
825,
11593,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
11,
198,
220,
220,
220,
220,
220,
220,
220,
20150,
25,
366,
10267,
48526,
1,
796,
6045,
11,
198,
220,
220,
220,
220,
220,
220,
220,
1020,
25,
366,
24704,
19776,
37766,
14832,
22882,
1,
796,
6045,
11,
198,
220,
220,
220,
220,
220,
220,
220,
3722,
25,
366,
19776,
37766,
14832,
19580,
1,
796,
6045,
11,
198,
220,
220,
220,
15179,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
16447,
12189,
19776,
37766,
14832,
4554,
526,
15931,
198,
220,
220,
220,
220,
220,
220,
220,
2208,
7,
24704,
19776,
37766,
14832,
11,
2116,
737,
834,
15003,
834,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
40391,
62,
9641,
2625,
9800,
1634,
14,
85,
16,
1600,
1611,
2625,
24704,
19776,
37766,
14832,
1,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
38993,
1298,
20150,
611,
20150,
318,
407,
6045,
2073,
9515,
48526,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
16684,
1298,
1020,
611,
1020,
318,
407,
6045,
2073,
12189,
19776,
37766,
14832,
22882,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
13376,
1298,
3722,
611,
3722,
318,
407,
6045,
2073,
15540,
37766,
14832,
19580,
22784,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
19199,
796,
1391,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
15042,
14815,
1298,
357,
2536,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
11031,
1298,
357,
2536,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
38993,
1298,
357,
10267,
48526,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
16684,
1298,
357,
24704,
19776,
37766,
14832,
22882,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
13376,
1298,
357,
19776,
37766,
14832,
19580,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
20150,
7,
944,
8,
4613,
366,
10267,
48526,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
10267,
48526,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
38993,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
38993,
13,
2617,
353,
198,
220,
220,
220,
825,
20150,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
10267,
48526,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
38993,
8973,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
1020,
7,
944,
8,
4613,
366,
24704,
19776,
37766,
14832,
22882,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18291,
6622,
1321,
546,
262,
2581,
852,
16726,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
24704,
19776,
37766,
14832,
22882,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
16684,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
16684,
13,
2617,
353,
198,
220,
220,
220,
825,
1020,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
24704,
19776,
37766,
14832,
22882,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
18291,
6622,
1321,
546,
262,
2581,
852,
16726,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12189,
19776,
37766,
14832,
22882,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
12189,
19776,
37766,
14832,
22882,
22446,
6738,
62,
11600,
7,
8367,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1267,
198,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
14692,
16684,
8973,
796,
1988,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
3722,
7,
944,
8,
4613,
366,
19776,
37766,
14832,
19580,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
12678,
318,
5901,
287,
416,
262,
4382,
290,
9217,
262,
900,
286,
198,
220,
220,
220,
220,
220,
220,
220,
4028,
257,
2836,
460,
1620,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
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2208,
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19776,
37766,
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11,
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737,
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834,
7,
198,
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220,
220,
220,
220,
220,
220,
220,
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40391,
62,
9641,
2625,
9800,
1634,
14,
85,
16,
1600,
1611,
2625,
24704,
19776,
37766,
14832,
22882,
1,
198,
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1782,
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944,
8,
4613,
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25,
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220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
28531,
10223,
284,
13446,
3173,
329,
13,
20906,
13,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
965,
11,
198,
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220,
220,
220,
220,
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220,
220,
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2116,
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825,
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7,
944,
11,
1988,
25,
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220,
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37227,
198,
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28531,
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8973,
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1988,
628,
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28264,
74,
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13,
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460,
1620,
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2223,
13,
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37227,
628,
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220,
825,
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834,
7,
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11,
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220,
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20150,
25,
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1,
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11,
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220,
1020,
25,
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1,
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3722,
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19776,
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1,
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11,
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4554,
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220,
220,
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2208,
7,
19776,
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7,
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62,
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1,
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318,
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220,
220,
220,
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220,
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366,
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318,
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366,
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11,
6045,
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220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
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1298,
357,
19776,
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14832,
22882,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
13376,
1298,
357,
19776,
15457,
14832,
19580,
11,
6045,
828,
198,
220,
220,
220,
220,
220,
220,
220,
1782,
628,
220,
220,
220,
2488,
26745,
198,
220,
220,
220,
825,
20150,
7,
944,
8,
4613,
366,
10267,
48526,
1298,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
1441,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
366,
10267,
48526,
1600,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
2116,
13557,
48310,
13,
1136,
7203,
38993,
12340,
198,
220,
220,
220,
220,
220,
220,
220,
1267,
628,
220,
220,
220,
2488,
38993,
13,
2617,
353,
198,
220,
220,
220,
825,
20150,
7,
944,
11,
1988,
25,
19720,
13,
38176,
14692,
10267,
48526,
1600,
8633,
60,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
8997,
1351,
20150,
13,
3125,
7508,
25,
198,
220,
220,
220,
220,
220,
220,
220,
3740,
1378,
18300,
13,
74,
23,
82,
13,
952,
14,
28158,
14,
3642,
2455,
669,
14,
2934,
626,
14,
82,
328,
12,
198,
220,
220,
220,
220,
220,
220,
220,
10959,
14,
15042,
12,
1102,
16593,
13,
9132,
2,
38993,
198,
220,
220,
220,
220,
220,
220,
220,
37227,
198,
220,
220,
220,
220,
220,
220,
220,
611,
318,
39098,
7,
8367,
11,
8633,
2599,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
1988,
796,
19720,
13,
2701,
7,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
11,
198,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
9515,
48526,
22446,
6738,
62,
11600,
7,
8367,
828,
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] | 2.336635 | 28,773 |
from django.test import TestCase
from eth_account import Account
from web3 import Web3
from gnosis.eth.tests.ethereum_test_case import EthereumTestCaseMixin
from ..models import EthereumTx, MultisigTransaction, SafeStatus
from ..services.index_service import (
EthereumBlockHashMismatch,
IndexService,
IndexServiceProvider,
TransactionNotFoundException,
)
from .factories import EthereumTxFactory, MultisigTransactionFactory, SafeStatusFactory
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] | 3.596899 | 129 |
from __future__ import print_function
from faker import Faker
from flask import Flask, request
from requests.auth import *
from flask_restful import Api
import json
from nose.tools import eq_
from halo_flask.exceptions import ApiError
from halo_flask.flask.utilx import status
from halo_bian.bian.abs_bian_srv import AbsBianMixin,ActivationAbsBianMixin,ConfigurationAbsBianMixin,FeedbackAbsBianMixin
from halo_bian.bian.db import AbsBianDbMixin
from halo_bian.bian.exceptions import BianException,BianError
from halo_flask.apis import *
from halo_flask.flask.utilx import Util
from halo_flask.flask.servicex import FoiBusinessEvent,SagaBusinessEvent
from halo_flask.flask.filter import RequestFilterClear
from halo_bian.bian.bian import BianCategory,ActionTerms,Feature,ControlRecord,GenericArtifact,BianContext,BianRequestFilter,FunctionalPatterns
from halo_flask.ssm import set_app_param_config,set_host_param_config
from halo_flask.flask.viewsx import load_global_data
from halo_flask.base_util import BaseUtil
import unittest
fake = Faker()
app = Flask(__name__)
api = Api(app)
class TestUserDetailTestCase(unittest.TestCase):
"""
Tests /users detail operations.
"""
session_id = None
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] | 3.002469 | 405 |
# Copyright 2019 Red Hat, Inc.
#
# 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 concurrent import futures
import os
import pathlib
import tenacity
from oslo_concurrency import processutils
from oslo_config import cfg
from oslo_log import log as logging
from tripleo_common import constants
from tripleo_common.image.builder import base
from tripleo_common.utils import process
CONF = cfg.CONF
LOG = logging.getLogger(__name__ + ".BuildahBuilder")
class BuildahBuilder(base.BaseBuilder):
"""Builder to build container images with Buildah."""
log = LOG
def __init__(self, work_dir, deps, base='fedora', img_type='binary',
tag='latest', namespace='master',
registry_address='127.0.0.1:8787', push_containers=True,
volumes=[], excludes=[], build_timeout=None, debug=False):
"""Setup the parameters to build with Buildah.
:params work_dir: Directory where the Dockerfiles or Containerfiles
are generated by Kolla.
:params deps: Dictionary defining the container images
dependencies.
:params base: Base image on which the containers are built.
Default to fedora.
:params img_type: Method used to build the image. All TripleO images
are built from binary method. Can be set to false to remove it
from image name.
:params tag: Tag used to identify the images that we build.
Default to latest.
:params namespace: Namespace used to build the containers.
Default to master.
:params registry_address: IP + port of the registry where we push
the images. Default is 127.0.0.1:8787.
:params push: Flag to bypass registry push if False. Default is True
:params volumes: Bind mount volumes used during buildah bud.
Default to [].
:params excludes: List of images to skip. Default to [].
:params build_timeout: Timeout. Default to constants.BUILD_TIMEOUT
:params debug: Enable debug flag. Default to False.
"""
logging.register_options(CONF)
if debug:
CONF.debug = True
logging.setup(CONF, '')
super(BuildahBuilder, self).__init__()
if build_timeout is None:
self.build_timeout = constants.BUILD_TIMEOUT
else:
self.build_timeout = build_timeout
self.work_dir = work_dir
self.deps = deps
self.base = base
self.img_type = img_type
self.tag = tag
self.namespace = namespace
self.registry_address = registry_address
self.push_containers = push_containers
self.volumes = volumes
self.excludes = excludes
self.debug = debug
# Each container image has a Dockerfile or a Containerfile.
# Buildah needs to know the base directory later.
self.cont_map = {os.path.basename(root): root for root, dirs,
fnames in os.walk(self.work_dir)
if 'Dockerfile' in fnames or
'Containerfile' in fnames}
# Building images with root so overlayfs is used, and not fuse-overlay
# from userspace, which would be slower.
self.buildah_cmd = ['sudo', 'buildah']
if self.debug:
self.buildah_cmd.append('--log-level=debug')
def _find_container_dir(self, container_name):
"""Return the path of the Dockerfile/Containerfile directory.
:params container_name: Name of the container.
"""
if container_name not in self.cont_map:
self.log.error('Container not found in Kolla '
'deps: %s' % container_name)
return self.cont_map.get(container_name, '')
def _get_destination(self, container_name):
"""Return the destination of a container image to push.
:params container_name: Name of the container.
"""
destination = "{}/{}/{}".format(
self.registry_address,
self.namespace,
self.base,
)
if self.img_type:
destination += '-' + self.img_type
destination += '-' + container_name + ':' + self.tag
return destination
def _generate_container(self, container_name):
"""Generate a container image by building and pushing the image.
:params container_name: Name of the container.
"""
if container_name in self.excludes:
return
# NOTE(mwhahaha): Use a try catch block so we can better log issues
# as this is called in a multiprocess fashion so the exception
# loses some information when it reaches _multi_build
try:
self.build(container_name,
self._find_container_dir(container_name))
if self.push_containers:
self.push(self._get_destination(container_name))
except Exception as e:
self.log.exception(e)
raise
@tenacity.retry(
# Retry up to 5 times: 0, 1, 5, 21, 85
# http://exponentialbackoffcalculator.com/
reraise=True,
wait=tenacity.wait_random_exponential(multiplier=4, max=60),
stop=tenacity.stop_after_attempt(5),
before_sleep=tenacity.after_log(LOG, logging.WARNING)
)
def build(self, container_name, container_build_path):
"""Build an image from a given directory.
:params container_name: Name of the container.
:params container_build_path: Directory where the Dockerfile or
Containerfile and other files are located to build the image.
"""
# 'buildah bud' is the command we want because Kolla uses Dockefile to
# build images.
# TODO(emilien): Stop ignoring TLS. The deployer should either secure
# the registry or add it to insecure_registries.
logfile = container_build_path + '/' + container_name + '-build.log'
# TODO(ramishra) Hack to make the logfile readable by current user,
# as we're running buildah as root. This would be removed once we
# move to rootless buildah.
pathlib.Path(logfile).touch()
bud_args = ['bud']
for v in self.volumes:
bud_args.extend(['--volume', v])
if self.debug:
# TODO(bogdando): add --log-rusage for newer buildah
bud_args.extend(['--loglevel=3'])
# TODO(aschultz): drop --format docker when oci format is properly
# supported by the undercloud registry
bud_args.extend(['--format', 'docker', '--tls-verify=False',
'--logfile', logfile, '-t',
self._get_destination(container_name),
container_build_path])
args = self.buildah_cmd + bud_args
self.log.info("Building %s image with: %s" %
(container_name, ' '.join(args)))
process.execute(
*args,
check_exit_code=True,
run_as_root=False,
use_standard_locale=True
)
@tenacity.retry( # Retry up to 10 times with jittered exponential backoff
reraise=True,
wait=tenacity.wait_random_exponential(multiplier=1, max=15),
stop=tenacity.stop_after_attempt(10),
before_sleep=tenacity.after_log(LOG, logging.WARNING)
)
def push(self, destination):
"""Push an image to a container registry.
:params destination: URL to used to push the container. It contains
the registry address, namespace, base, img_type (optional),
container name and tag.
"""
# TODO(emilien): Stop ignoring TLS. The deployer should either secure
# the registry or add it to insecure_registries.
# TODO(emilien) We need to figure out how we can push to something
# else than a Docker registry.
args = self.buildah_cmd + ['push', '--tls-verify=False', destination,
'docker://' + destination]
self.log.info("Pushing %s image with: %s" %
(destination, ' '.join(args)))
if self.debug:
# buildah push logs to stderr, since there is no --log* opt
# so we'll use the current logging context for that
process.execute(*args, log_stdout=True, run_as_root=False,
use_standard_locale=True, logger=self.log,
loglevel=logging.DEBUG)
else:
process.execute(*args, run_as_root=False,
use_standard_locale=True)
def build_all(self, deps=None):
"""Build all containers.
This function will thread the build process allowing it to complete
in the shortest possible time.
:params deps: Dictionary defining the container images
dependencies.
"""
if deps is None:
deps = self.deps
container_deps = self._generate_deps(deps=deps, containers=list())
self.log.debug("All container deps: {}".format(container_deps))
for containers in container_deps:
self.log.info("Processing containers: {}".format(containers))
if isinstance(deps, (list,)):
self._multi_build(containers=containers)
else:
self._multi_build(containers=[containers])
def _generate_deps(self, deps, containers, prio_list=None):
"""Browse containers dependencies and return an an array.
When the dependencies are generated they're captured in an array,
which contains additional arrays. This data structure is later
used in a futures queue.
:params deps: Dictionary defining the container images
dependencies.
:params containers: List used to keep track of dependent containers.
:params prio_list: List used to keep track of nested dependencies.
:returns: list
"""
self.log.debug("Process deps: {}".format(deps))
if isinstance(deps, str):
if prio_list:
prio_list.append(deps)
else:
containers.append([deps])
elif isinstance(deps, (dict,)):
parents = list(deps.keys())
if prio_list:
prio_list.extend(parents)
else:
containers.append(parents)
for value in deps.values():
self.log.debug("Recursing with: {}".format(value))
self._generate_deps(
deps=value,
containers=containers
)
elif isinstance(deps, (list,)):
dep_list = list()
dep_rehash_list = list()
for item in deps:
if isinstance(item, str):
dep_list.append(item)
else:
dep_rehash_list.append(item)
if dep_list:
containers.append(dep_list)
for item in dep_rehash_list:
self.log.debug("Recursing with: {}".format(item))
self._generate_deps(
deps=item,
containers=containers,
prio_list=dep_list
)
self.log.debug("Constructed containers: {}".format(containers))
return containers
def _multi_build(self, containers):
"""Build mutliple containers.
Multi-thread the build process for all containers defined within
the containers list.
:params containers: List defining the container images.
"""
# Workers will use the processor core count with a max of 8. If
# the containers array has a length less-than the expected processor
# count, the workers will be adjusted to meet the expectations of the
# work being processed.
workers = min(
min(
8,
max(
2,
processutils.get_worker_count()
)
),
len(containers)
)
with futures.ThreadPoolExecutor(max_workers=workers) as executor:
future_to_build = {
executor.submit(
self._generate_container, container_name
): container_name for container_name in containers
}
done, not_done = futures.wait(
future_to_build,
timeout=self.build_timeout,
return_when=futures.FIRST_EXCEPTION
)
# NOTE(cloudnull): Once the job has been completed all completed
# jobs are checked for exceptions. If any jobs
# failed a SystemError will be raised using the
# exception information. If any job was loaded
# but not executed a SystemError will be raised.
exceptions = list()
for job in done:
if job._exception:
exceptions.append(
"\nException information: {exception}".format(
exception=job._exception
)
)
if exceptions:
raise RuntimeError(
'\nThe following errors were detected during '
'container build(s):\n{exceptions}'.format(
exceptions='\n'.join(exceptions)
)
)
if not_done:
error_msg = (
'The following jobs were incomplete: {}'.format(
[future_to_build[job] for job in not_done]
)
)
jobs_with_exceptions = [{
'container': future_to_build[job],
'exception': job._exception}
for job in not_done if job._exception]
if jobs_with_exceptions:
for job_with_exception in jobs_with_exceptions:
error_msg = error_msg + os.linesep + (
"%(container)s raised the following "
"exception: %(exception)s" %
job_with_exception)
raise SystemError(error_msg)
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] | 2.219035 | 6,693 |
import os
import re
import json
import pandas as pd
from deep_phospho import proteomics_utils as prot_utils
from deep_phospho.proteomics_utils.post_analysis import spectronaut as SN
def generate_spec_lib(
data_name,
output_folder,
pred_ion_path,
pred_rt_path,
min_frag_inten=5,
min_frag_num=4,
max_frag_num=15,
allowed_extra_min_frag_inten=3,
save_path=None,
logger=None
):
"""
:param data_name:
:param output_folder:
:param pred_ion_path:
:param pred_rt_path:
:param min_frag_inten: min fragment intensity to be kept
:param min_frag_num: min fragment number to keep this precursor
:param max_frag_num: max fragment number to be kept for one precursor
:param allowed_extra_min_frag_inten:
:param save_path:
:param logger:
"""
if logger is not None:
logger.info(f'Reading predicted results for {data_name}')
with open(pred_ion_path, 'r') as f:
pred_ion = json.load(f)
pred_rts = dict(pd.read_csv(pred_rt_path, sep='\t')[['sequence', 'pred']].values)
pred_lib_rows = []
loss_num = 0
if logger is not None:
logger.info(f'Start generating library for {data_name}')
for intprec, pred_spec in pred_ion.items():
if 'U' in intprec or 'X' in intprec:
continue
intpep, prec_charge = intprec.split('.')
modpep = SN.sn_utils.intseq_to_sn_modpep(intpep)
strip_pep = re.sub(r'\[.+?\]', '', modpep.replace('_', ''))
if intpep in pred_rts:
pred_rt = pred_rts[intpep]
else:
loss_num += 1
continue
prec = f'{modpep}.{prec_charge}'
prec_mz = prot_utils.calc.calc_prec_mz(prec)
prec_basic_data_list = [prec_charge, modpep, strip_pep, pred_rt, modpep, prec_mz]
pred_spec = prot_utils.calc.normalize_intensity(pred_spec, max_num=100)
pred_spec = prot_utils.calc.keep_top_n_inten(pred_spec, top_n=15)
for frag, inten in pred_spec.items():
frag_type, frag_num, frag_charge, frag_losstype = re.findall(r'([abcxyz])(\d+)\+(\d)-(.+)', frag)[0]
if int(frag_num) in (1, 2):
continue
if float(inten) <= 5:
continue
frag_mz = prot_utils.calc.calc_fragment_mz(modpep, frag_type, frag_num, frag_charge, frag_losstype)
frag_losstype = SN.sn_constant.LossType.Readable_to_SN[frag_losstype]
pred_lib_rows.append(prec_basic_data_list + [frag_losstype, frag_num, frag_type, frag_charge, frag_mz, inten])
pred_lib_df = pd.DataFrame(pred_lib_rows, columns=SN.SpectronautLibrary.LibBasicCols)
pred_lib_df['Prec'] = pred_lib_df['ModifiedPeptide'] + '.' + pred_lib_df['PrecursorCharge'].astype(str)
if logger is not None:
logger.info(f'Total {len(set(pred_lib_df["Prec"]))} precursors in initial {data_name} library')
pred_lib_df = pred_lib_df.groupby('Prec').filter(lambda x: len(x) >= 4)
if logger is not None:
logger.info(f'Total {len(set(pred_lib_df["Prec"]))} precursors in final {data_name} library')
pred_lib_df = pred_lib_df[SN.SpectronautLibrary.LibBasicCols]
if save_path is not None:
lib_path = save_path
else:
lib_path = os.path.join(output_folder, f'Library-{data_name}-DP_I5_n{max_frag_num}.xls')
if logger is not None:
logger.info(f'Saving generated library to {lib_path}')
pred_lib_df.to_csv(lib_path, sep='\t', index=False)
return lib_path
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] | 2.133052 | 1,661 |
#!/usr/bin/python3
import time
import signal
import sys
import os
import threading
import json
import Adafruit_CharLCD as LCD
import imp
from pythonosc import osc_message_builder
from pythonosc import udp_client
from pythonosc import dispatcher
from pythonosc import osc_server
from config import *
from lcd import *
global keyThreads
keyThreads = []
global importedModules
importedModules = {}
if __name__ == "__main__":
setup()
for serverName in config()['oscServers']:
print("Starting OSC UDP server: {}".format(serverName))
start_server(serverName)
start_keyThread(key_charLCD)
| [
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7,
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62,
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5639,
35,
8,
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] | 3.213904 | 187 |
# coding=utf-8
# Copyright (c) 2019 Alibaba PAI team.
#
# 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 json
import re
import os
import tensorflow as tf
from tensorflow.python import pywrap_tensorflow
from tensorflow.python.framework import errors_impl
from tensorflow.python.platform import gfile
from easytransfer.engines.model import FLAGS
from easytransfer import layers
| [
2,
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] | 3.733051 | 236 |
# Copyright 2020 Tensorforce Team. 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.
# ==============================================================================
import unittest
from test.unittest_base import UnittestBase
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] | 4.121547 | 181 |
#!/usr/bin/env python3
"""
Author : ktruong <ktruong@localhost>
Date : 2021-10-25
Purpose: Rock the Casbah
"""
import argparse
import sys
# --------------------------------------------------
def get_args():
"""Get command-line arguments"""
parser = argparse.ArgumentParser(
description='Rock the Casbah',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-n',
'--num',
help='A named integer argument',
metavar='int',
type=int,
default=10)
args = parser.parse_args()
if args.num < 1:
sys.exit(f'--num "{args.num}" must be greater than 0')
return args
# --------------------------------------------------
def main():
"""Make a jazz noise here"""
args = get_args()
# verses = []
# for number in range(args.num, 0, -1):
# verses.append(verse(number))
# verses = [verse(n) for n in range(args.num, 0,-1)]
verses = map(verse, range(args.num, 0, -1))
print('\n\n'.join(verses))
# --------------------------------------------------
def verse(bottle):
"""Number of the bottles"""
next_bottle = bottle - 1
s1 = '' if bottle == 1 else 's'
s2 = '' if next_bottle == 1 else 's'
num_next = 'No more' if next_bottle == 0 else next_bottle
return '\n'.join([
f'{bottle} bottle{s1} of beer on the wall,',
f'{bottle} bottle{s1} of beer,',
f'Take one down, pass it around,',
f'{num_next} bottle{s2} of beer on the wall!',
])
# --------------------------------------------------
def test_verse():
"""Test verse"""
last_verse = verse(1)
assert last_verse == '\n'.join([
'1 bottle of beer on the wall,', '1 bottle of beer,',
'Take one down, pass it around,',
'No more bottles of beer on the wall!'
])
two_bottles = verse(2)
assert two_bottles == '\n'.join([
'2 bottles of beer on the wall,', '2 bottles of beer,',
'Take one down, pass it around,', '1 bottle of beer on the wall!'
])
# --------------------------------------------------
if __name__ == '__main__':
main()
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12417,
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] | 2.40812 | 936 |
import string
from invert_index import Invert_Index
import config
import json
import numpy as np
import pandas as pd
import math
from file_reader import File_Reader
from file_writer import File_Writer
| [
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62,
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198,
6738,
2393,
62,
16002,
1330,
9220,
62,
34379,
198
] | 3.722222 | 54 |
#coding: utf-8
import sys
import socket
import os
PORT = 80 #porta padrão caso usuário não especifique
if len(sys.argv) == 1: # Verifica se o usuario passou pelo menos o parametro obrigatorio
print "Nao foi informado a url no paramentro!\n"
sys.exit()
if len(sys.argv) == 3: # Verifica se o usuario especificou a porta
PORT = int(sys.argv[2])
link = sys.argv[1].replace("https://", "").replace("http://", "") #remove http:// ou https:// do link
HOST = link.split('/') #separar o host do resto da url
HOST = HOST[0]
socketnav = socket.socket(socket.AF_INET, socket.SOCK_STREAM) #inicia o socket
socketnav.connect((HOST, PORT))
print "Conectando a " + HOST + "\n\n"
url = link.split('/')
nomearq = ''
if len(url) > 1:
nomearq = url[len(url)-1] #recebe o nome do arquivo caso seja especificado
del url[0]
caminho = ''
if type(url) == list:
for i in url:
caminho += '/' + i # monta o caminho para ser feita a requisicao
else:
caminho = '/'
if len(nomearq) == 0:
nomearq = "index.html"
requisicao = 'GET '+ caminho + ' HTTP/1.0\r\nHost: ' + HOST + '\r\n\r\n' # monta requisicao
socketnav.sendall(requisicao) # envia a requisicao
pagina = ''
while (True):
rcv = socketnav.recv(4096)
if not rcv:
break
pagina += rcv
linhas = pagina.split('\n'); #separa o conteudo recebido em linhas
i = 0
while(True): #separa o cabecalho da Cabeçalho HTTP do conteudo
if len(linhas[i]) == 1:
inicio = i + 1
break
i += 1
salvar = True
i = 0
print "Cabeçalho HTTP" #imprimindo o Cabeçalho HTTP na tela
while(i < inicio):
print(linhas[i])
i += 1
if "404" in linhas[i]: # se o arquivo nao existe nao salva
salvar = False
if salvar:
dir = './' + HOST # pasta pra salvar o conteudo
if not os.path.isdir(dir): # verifica se ja existe, se nao existe cria
os.makedirs(dir)
arqsaida = dir + '/' + nomearq
arquivo_saida = open(arqsaida,"w") # criando arquivo de saida
while (inicio < len(linhas)): # salvando o conteudo no arquivo
arquivo_saida.write(linhas[inicio])
arquivo_saida.write("\n")
inicio += 1
socketnav.close | [
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] | 2.25705 | 922 |
# -*- coding: utf-8 -*-
"""
Created on Mon May 13 11:22:01 2019
@author: DiPu
"""
from functools import reduce
people =[{'name': 'Mary', 'height': 160},
{'name': 'Isla', 'height': 80},
{'name': 'Sam'}]
b=(list(filter(lambda x: True if 'height' in x else False,people)))
g=list(map(lambda x:x['height'],b ))
c=len((list(filter(lambda x: True if 'height' in x else False,people))))
d=reduce(lambda x,y:x+y,g)
print("average height:",d/c) | [
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] | 2.362694 | 193 |
# @author ksdme
# abstracts methods on question model
from random import shuffle
from alan.db.models import ReplyModel
def getQuestion(qno, qmodel):
"""
read a question from the
given qmodel
"""
try:
return qmodel.get(qmodel.id == qno)
except qmodel.DoesNotExist:
return None
def getOffset(using, cycle=20):
"""
calculates the offset using
a number 'using' subject
"""
val = int(using)
val *= int(str(val)[0])
while val > cycle:
using = map(int, str(val))
val = sum(using)
return val
def getOffsettedQuestion(roll, qno, qmodel, cycle=20):
"""
calculates the question that
corrosponds to the databse
entry
"""
# ensure the qno is in range
if qno > cycle or qno < 1:
return None
return getQuestion(
(((getOffset(roll, cycle) + qno)%cycle) + 1), qmodel)
def shuffledAnswers(question):
"""
simply shuffles the ans
and returns the list
"""
answers = [
question.opt_a,
question.opt_b,
question.opt_c,
question.opt_d
]
shuffle(answers)
return answers
def getQuestionStatus(roll, qno, rmodel, cycle=20):
"""
this here lets you know the current
status of the question, i.e it has
been answered or is editable etc,
!!!you don't need offsetted qno!!!
"""
# ensure qno
if qno > cycle or qno < 1:
return None
try:
reply = rmodel.get(rmodel.roll == roll)
return reply.replies[unicode(qno)]
except rmodel.DoesNotExist:
return None
def isEditableQuestion(roll, qno, rmodel, cycle=20):
"""
check if the question is editable,
i.e returns true if it was unanswered
"""
status = getQuestionStatus(roll, qno, rmodel, cycle)
# ignore errors
if status is None:
return False
# if it still is unanswered
if status == ReplyModel.UNANSWERED:
return True
return False
def getAllReplied(roll, rmodel):
"""
returns all those questions to
which an answer has been submitted
"""
try:
model = rmodel.get(rmodel.roll == roll)
except rmodel.DoesNotExist:
return { "e": True }
# the questions that are empty
qs = map(lambda l: l[0] if l[1] != -1 else None,
model.replies.iteritems())
qs = filter(lambda l: l is not None, qs)
return qs
def verifyAnswer(question, answer):
"""
requires a question instance and
the submitted answer, validates it
"""
return question.answer == answer
def getPresentableQuestion(roll, qno, qmodel, rmodel, cycle=20):
"""
completely abstracts away the
question selection and forming
process, questions and options
"""
question = getOffsettedQuestion(
roll, qno, qmodel, cycle)
# ensure max
if question is None:
return { "e": True }
return {
"q": question.question,
"o": shuffledAnswers(question),
"l": not isEditableQuestion(roll, qno, rmodel, cycle)
}
def getPresentableSubmission(roll, qno, answer, qmodel, rmodel, rmodelgen, cycle=20):
"""
validates and lets you know if
the submitted answer was right
"""
# check if we have an answer
if answer is None or answer == "":
return { "e": True, "m": "e" }
# non-offset qno, now do it only if it is an editable one
if not isEditableQuestion(roll, qno, rmodel, cycle):
return { "e": True, "m": "l" }
question = getOffsettedQuestion(
roll, qno, qmodel, cycle)
# if bad question no
if question is None:
return { "e": True }
# verify the answer and do recording
correct = verifyAnswer(question, answer)
# this is the base thing that manages all
try:
player = rmodel.get(rmodel.roll == roll)
except reply.DoesNotExist:
return { "e": True, "m": "n" }
# apparetly json loads
# make the qno's unicode
qno = unicode(qno)
if player.replies[qno] == rmodelgen.UNANSWERED:
player.replies[qno] = rmodelgen.CORRECT if correct else rmodelgen.WRONG
player.save()
return { "e": False }
else:
return { "e": True, "m": "l" }
# let the guy know we
# didn't get any error
return { "e": True }
| [
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2,
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470,
651,
597,
4049,
198,
197,
7783,
1391,
366,
68,
1298,
6407,
1782,
198
] | 2.730361 | 1,413 |
from flask import render_template, Blueprint
from coh2stats.weeklystats.utils import get_players_stats
from coh2stats.weeklystats.utils import get_teams_stats
from coh2stats import dao
import os
stats = Blueprint('stats', __name__)
@stats.route('/weeklystats/1v1/latest')
@stats.route('/weeklystats/teams/latest')
| [
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1330,
8543,
62,
28243,
11,
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198,
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17,
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38629,
10786,
14,
45291,
34242,
14,
660,
4105,
14,
42861,
11537,
198
] | 3.255102 | 98 |
import sys
if __name__ == '__main__':
if len(sys.argv) == 2 and sys.argv[1] == 'extra':
extra()
else:
main()
| [
11748,
25064,
628,
628,
198,
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834,
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705,
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25,
198,
220,
220,
220,
220,
220,
220,
220,
1388,
3419,
198
] | 2.014706 | 68 |
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