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from typing import Any, List, Dict from anytree import Node, RenderTree, ContRoundStyle class RenderState: " Render state class. View shablbot module active in tree style. " def render(self, style = ContRoundStyle) -> None: """ Render tree with state bot modules. Args: style ([type], optional): Style how need rendered items. Defaults to ContRoundStyle. """ print(RenderTree(self.node, style=style()).by_attr()) def render_state(name_module: str, module: Any) -> None: """ Render state module bot. Use tree. Args: name_module (str): Modules name module (Any): Object for check node """ render_state = RenderState({ name_module: module }) render_state.render() def render_state_all_components(list_components: List[Any]) -> None: """ Render state all modules bot in tree style. Args: list_components (List[Any]): components bot for need rebder state. All componnets have 'get_main_data_object()' function" """ render_state = RenderState( modules={ comp.__class__.__name__ : comp.get_main_data_object() for comp in list_components }, main_root=Node("Shablbot") ) render_state.render()
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# %% import matplotlib.pyplot as plt from torch_geometric.data import download_url, extract_tar from foam_graph.utils.graph_from_foam import read_foam from foam_graph.visualization.graph_plotting import plot_graph # %% Extract tar and read case as a graph download_url("https://github.com/gfngoncalves/openfoam_cases/blob/main/damBreak.tar.xz?raw=true", ".") extract_tar("damBreak.tar.xz", ".", mode="r:xz") graph = read_foam( "damBreak", ("alpha.water",), read_boundaries=True, ) #%% Plot alpha field for 2D case field_name_plot = "alpha.water" field_component_plot = 0 time = -1 fig, ax = plt.subplots(figsize=(10, 10)) plot_graph(graph[time], field_name_plot, field_component_plot, ax=ax) plt.tight_layout() plt.show()
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from __future__ import annotations from typing import Type, Optional, List from Exceptions.BranchHaveDiverged import BranchHaveDiverged from Exceptions.BranchNotExist import BranchNotExist from Exceptions.GitMergeConflictError import GitMergeConflictError from Exceptions.NotCleanWorkingTree import NotCleanWorkingTree from FlexioFlow.StateHandler import StateHandler from Branches.Branches import Branches from Log.Log import Log from VersionControl.Git.Branches.GitFlowCmd import GitFlowCmd from VersionControl.Git.GitCmd import GitCmd from VersionControlProvider.Github.Message import Message from VersionControlProvider.Issue import Issue from VersionControlProvider.Topic import Topic from ConsoleColors.Fg import Fg from Core.ConfigHandler import ConfigHandler
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from dataclasses import fields from pydantic import conint from pydantic.fields import Field import numpy as np from .bounding_box import BoundingBox from .trajectory import Trajectory from ..settings import DefaultValues from ..enums import ReferenceTypes from ..geometry import BBXCornersClass from ..reference_resolving import * import xarray as xr def in_timespan(obj, birth, death): """ birth = first timestamp idx death = last timestamp idx """ return birth <= obj.end and death >= obj.birth
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import calendar import datetime import logging import operator import os import pytz from pdb import set_trace from django.db import models from django.conf import settings from django.contrib.auth.models import User from django.utils.translation import ugettext_lazy as _ from django.utils.encoding import DjangoUnicodeDecodeError from django_fields.fields import EncryptedCharField from django_vcs_watch.settings import \ REVISION_LIMIT, \ CHECK_INTERVAL_MIN, \ CHECK_INTERVAL_MAX, \ POSTPROCESS_COMMIT from django_vcs_watch.utils import \ timedelta_to_string, \ strip_timezone, \ mongo, \ get_user_feed_slug from pymongo import DESCENDING from mongobongo import Document if 'django_globals' not in settings.INSTALLED_APPS: raise Exception('Please, install django_globals application.') if 'django_globals.middleware.User' not in settings.MIDDLEWARE_CLASSES: raise Exception('Please, add django_globals.middleware.User to the MIDDLEWARE_CLASSES.') from django.db.models.signals import class_prepared class_prepared.connect(_init_mongo_connection) from django.db.models import signals signals.post_save.connect(create_user_feed, sender = User)
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#!/usr/bin/env python3 # # Adobe Photoshop "*.act" palette file conversion to GIMP "*.gpl" palette # format (which is also recognized by many other tools). # # How to use: # ./act_to_gpl.py some_palette.act > some_palette.gpl # # Code based on swatchbook/codecs/adobe_act.py from: # http://www.selapa.net/swatchbooker/ import os.path import struct import sys if __name__ == '__main__': sys.stdout.write( return_gimp_palette(parse_adobe_act(sys.argv[1]), sys.argv[1]) )
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from flask import Flask, request, redirect, render_template from werkzeug.utils import secure_filename import os import tensorflow as tf import numpy as np import cv2 food_classes = ['Broken street sign', 'Damaged bollard', 'Damaged street light', 'Pothole'] app = Flask(__name__, static_url_path='/static') app.config["IMAGE_UPLOADS"] = './static' app.config["ALLOWED_IMAGE_EXTENSIONS"] = ["JPEG", "JPG", "PNG"] food_prediction_model = tf.keras.models.load_model('./deeplearning_model') @app.route("/", methods=["GET", "POST"]) @app.route("/showing-image/<image_name>", methods=["GET", "POST"]) if __name__ == '__main__': app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 8080)))
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import numpy as np from numba import jit import matplotlib.pyplot as plt import quantecon as qe from quantecon.distributions import BetaBinomial n, a, b = 50, 200, 100 w_min, w_max = 10, 60 w_vals = np.linspace(w_min, w_max, n+1) dist = BetaBinomial(n, a, b) psi_vals = dist.pdf() reservation_wage = compute_reservation_wage(w_vals, psi_vals) print(reservation_wage)
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import xmlrpc.client as xmlrpclib import json config_path = "./blog_config.json" def have_config(): ''' return bool value : whether config file exists ''' try: with open(config_path, "r", encoding = "utf-8") as f: try: cfg = json.load(f) return cfg != {} except json.decoder.JSONDecodeError: return False except: with open(config_path, "w", encoding = "utf-8") as f: json.dump({}, f) return False def create_config(): ''' create config file if it doesnt exist only save ensured data usr provided, if not print ERROR ''' # Provide EXAMPLE Here for test_times in range(0, 2): cfg = {} for item in [("url", "metaWeblog url"), ("appkey", "blogaddress"), ("usr", "usrname"), ("passwd", "password")]: cfg[item[0]] = input(item[1] + " : ") try: server = xmlrpclib.ServerProxy(cfg["url"]) userInfo = server.blogger.getUsersBlogs( cfg["appkey"], cfg["usr"], cfg["passwd"]) print (userInfo[0]) cfg["bolgid"] = userInfo[0]["blogid"] break except: print ("ERROR!!!") print ("Please Check It Again") with open(config_path, "w", encoding = "utf-8") as f: json.dump(cfg, f, indent = 4, ensure_ascii = False) if __name__ == "__main__": if have_config() == False: create_config() print ("End")
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1.988722
798
# Generated by Django 3.1.6 on 2021-02-11 12:42 from django.db import migrations, models
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2.84375
32
import traceback from flask import current_app from numbers import Real from decimal import Decimal from itertools import tee, filterfalse class DeferredSourceMatcher(object): """ # Defer loading of the actual source matcher to runtime to save on # startup time when we don't need it. """ def __getattr__(self, att_name): """ :param att_name: :return: """ if att_name=='__bases__': return (object,) elif att_name=='__name__': return 'Unready source matcher' return getattr(current_app.extensions['source_matcher'], att_name) SOURCE_MATCHER = DeferredSourceMatcher() class Evidences(object): """ a measure of confidence of a match. All scoring functions working on one aspect are supposed to give a float between -1 and 1, where -1 is "I'm pretty sure it's wrong" and 1 is "I'm almost certain it's right". They put this score into the the add_evidence function. The individual evidences are kept by this class, but there's a get_score method that munges them together to yield a number between -1 and 1 that we hope to be a useful measure for the relative credibility of solutions. The individual evidences typically come from tailored matching functions (e.g., authors.compute_author_evidence). Those are free to abstain from voting; if no evidences are collected, get_score will return None (which should allow for easy filtering of those). These evidences stand in as scores in that, when compared, they are ordered according to what get_score returns. """ def __init__(self): """ """ self.evidences = [] self.labels = [] # _score is cached; None means "not computed yet or invalid" self.score = None self.min_score = current_app.config['EVIDENCE_SCORE_RANGE'][0] self.max_score = current_app.config['EVIDENCE_SCORE_RANGE'][1] def __lt__(self, other): """ :param other: :return: """ try: return self.get_score() < other.get_score() except (AttributeError, TypeError): if other: return self.get_score() < float(other) return False def __le__(self, other): """ :param other: :return: """ try: return self.get_score() <= other.get_score() except (AttributeError, TypeError): if other: return self.get_score() <= float(other) return False def __gt__(self, other): """ :param other: :return: """ try: return self.get_score() > other.get_score() except (AttributeError, TypeError): if other: return self.get_score() > float(other) return False def __ge__(self, other): """ :param other: :return: """ try: return self.get_score() >= other.get_score() except (AttributeError, TypeError): if other: return self.get_score() >= float(other) return False def __eq__(self, other): """ :param other: :return: """ try: return self.get_score() == other.get_score() except (AttributeError, TypeError): if other: return self.get_score() == float(other) return False def __len__(self): """ :return: """ return len(self.evidences) def __str__(self): """ :return: """ return 'Evidences(%s)'%', '.join('%s=%s'%item for item in zip (self.labels, self.evidences)) def __add__(self, other): """ :param other: :return: """ for ev in other.evidences: assert self.min_score <= ev <= self.max_score self.score = None self.evidences += other.evidences self.labels +=other.labels return self def sum(self): """ :return: """ return sum(self.evidences) def avg(self): """ :return: """ if len(self.evidences) != 0: return round(self.sum()/len(self.evidences), 1) return 0 def add_evidence(self, evidence, label): """ adds evidence (a float between -1 and 1) to our evidence collection under label. :param evidence: :param label: :return: """ assert self.min_score <= evidence <= self.max_score self.score = None self.evidences.append(evidence) self.labels.append(label) def get_score(self): """ returns some float between -1 and 1 representative of the collective evidence collected. :return: """ if not self.evidences: current_app.logger.error('No evidence, rejecting') return 0 if self.score is None: self.score = sum(self.evidences) return self.score def has_veto(self): """ returns false if all evidence is strictly positive. :return: """ for e in self.evidences: if e<=0: return True return False def single_veto_from(self, field_label): """ returns true if there is exactly one veto and it originates from what has field_label. :param field_label: :return: """ neg_inds = [ind for ind, ev in enumerate(self.evidences) if ev<=0] if len(neg_inds)==1: return (self.labels[neg_inds[0]]==field_label) return False def count_votes(self): """ return true if the combination of terms all have high scores :return: """ d = dict(zip(self.labels, self.evidences)) combinations = [ ['authors', 'pubstring', 'volume', 'year'], ['authors', 'year', 'page'] ] for fields in combinations: vote = 0 for term in fields: if term in d and d[term] == current_app.config['EVIDENCE_SCORE_RANGE'][1]: vote += 1 if vote == len(fields): return True return False def __getitem__(self, label): """ returns the score for the field label if exist :param label: :return: """ if label in self.labels: d = dict(zip(self.labels, self.evidences)) return d[label] return None class Solution(object): """ a container for a solution and some ancillary metadata. Ancillary metadata includes: * citing_bibcode * score * source_hypothesis (the hypothesis that eventually got it right) """ def __init__(self, cited_bibcode, score, source_hypothesis='not given', citing_bibcode=None): """ :param cited_bibcode: :param score: :param source_hypothesis: :param citing_bibcode: """ self.cited_bibcode = cited_bibcode self.score = score self.citing_bibcode = str(citing_bibcode) self.source_hypothesis = source_hypothesis def __str__(self): """ :return: """ if isinstance(self.score, Evidences): return '%.1f %s'%(self.score.avg(),self.cited_bibcode) raise NoSolution("NotResolved") class Hypothesis(object): """A container for expectations to a reference. Constraints have a dict of fields to show to the search engine (the hints, get them from the attribute), and a get_score(response_record, hypothesis)->Evidences method. See common.Evidences for details. The get_score function receives a result record, i.e., a dictionary containing at most the fields given in the apiQueryFields configuration. How it compares this against what's in the record is basically up to the class. Additionally, it gets the hypotheses that generated the response. This is a simple way to pass information from the hints generator to the matching function -- usually, you should just construct the Hypothesis with additional keyword arguments ("details"); you should query for them in get_score using the get_detail(str) -> anything method (that returns None for keys not passed). For debugging, you should give hypotheses short, but somewhat expressive names. See below for examples. """ def __init__(self, name, hints, get_score_function, **details): """ :param name: :param hints: :param get_score_function: :param details: """ self.name = name self.hints, self.get_score_function = hints, get_score_function self.details = details def get_score(self, response_record, hints): """ :param response_record: :param hints: :return: """ return self.get_score_function(response_record, hints) def get_detail(self, detail_name): """ :param detail_name: :return: """ if detail_name in self.details: return self.details.get(detail_name) return None def get_hint(self, hint_name): """ :param hint_name: :return: """ if hint_name in self.hints: return self.hints.get(hint_name) return None class NotResolved(object): """ a sentinel class holding unresolved references. """ def __init__(self, raw_ref, citing_bibcode): """ :param raw_ref: :param citing_bibcode: """ self.raw_ref = raw_ref self.citing_bibcode = str(citing_bibcode) def __str__(self): """ :return: """ return 'NOT RESOLVED: %s...'%(self.raw_ref[:40]) class Error(Exception): """ the base class for all exceptions. """ pass class NoSolution(Error): """ is raised when a solution could not be found. NoSolution is constructed with an explanation string and the Reference instance that failed. """ class Undecidable(NoSolution): """ is raised when the resolver needs to make a decision but cannot. In addition to the reference string, this also contains solutions_considered, pairs of evidence and solutions that were considered tied. """ class Overflow(Error): """is raised when too many matches come back from solr. It should be taken as "please try another, more specific hypothesis". """ class OverflowOrNone(Error): """ is rasided either if too many matches or no records come back from solr """ class Solr(Error): """ is raised when solr returns an error. """ class Incomplete(Error): """ is raised when parsed reference is incomplete and hence not able to resolve the reference. """ def round_two_significant_digits(num): """ :param num: :return: """ return float('%s' % float('%.1g' % num)) def sorted2(iterable): """ source: https://stackoverflow.com/a/43456510 :param iterable: An iterable (array or alike) entity which elements should be sorted. :return: List with sorted elements. """ t1, t2 = tee(iterable) numbers = filter(predicate, t1) non_numbers = filterfalse(predicate, t2) sorted_numbers = sorted(numbers) sorted_non_numbers = sorted(non_numbers, key=str) return sorted_numbers + sorted_non_numbers
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""" filename: TraceGenerator.py contents: this script calls the GenerateSyntheticTrace method that creates and stream of memory references that models the memory performance of the input application or applications author: Trevor Gale date: 3.4.16""" import h5py as h5 import numpy as np import ConfigParser import json import sys import traceback import lib.TraceFormats as TraceFormats import lib.PreProcessing as PreProc # dictionary for all available trace formats traceFormats = {"STL":TraceFormats.STL, \ "OVP":TraceFormats.OVP, \ "Din":TraceFormats.Din} # usage string usage_info = "USAGE: python TraceGenerator.py <config_file> \n\ config_file: file specifying the configuration for the trace generator\n\n\ all options for generator must be under header \"[generator]\" \n\ generator options: \n\ \t- traceFile: string indicating the name of the file that contains\n\ \tthe trace to be analyzed (plain-text)\n\n\ \t- traceLength: desired length of the synthetic address\n\ \ttrace (in memory references)\n\n\ \tappProfiles: lists (in brackets, separated by commas, no spaces)\n\ \tof the names of application profiles to model. At least one must \n\ \tbe specified. If len(appProfiles) > 1, the applications profiles\n\ \t are mixed by creating a linear combination with the weights\n\ \tspecified by the \"weights\" parameters. If weights is left as\n\ \tdefault, a uniform distribution is used\n\n\ \t- weights: list (in brackets, separated by commas, no spaces)\n\ \tof the weights of each application. Defaults to evenly weighted\n\ \tapplications\n\n\ \t- formatAccess: name of callback function that is called to print the\n\ \tmemory access. Function must be defined in the lib/TraceFormats and be\n\ \tpresent in the \"traceFormats\" dictionary at the top of this file\n" # TODO: # 1. Tool to generate profiles based on a PMF # 2. Print runtime generation details & progress def GenerateSyntheticTrace(traceFile, traceLength, appProfiles, weights=[], formatAccess=TraceFormats.STL): """ GenerateSyntheticTrace: this function takes in application profiles generated by the \"ApplicationProfiler\" script and generates a synthetic address trace that models the properties of the input applications args: - traceFile: string specifying the name of the file to write the synthetic address trace to (plain-text) - traceLength: desired length of the synthetic trace (in memory references) - appProfiles: python list of the names of the application profiles to model. At least one must be specified. If len(appProfiles) > 1, the applications profiles are mixed by creating a linear combination with the weights specified by the "weights" parameters. If weights is left as default, a uniform distribution is used - weights: python list specifying the weights of each application. Defaults to evenly weighted applications - formatAccess: callback function that is called to print the memory references. Function arguments must be (cycle, accessType, memAddress)""" # validate inputs if not len(appProfiles): raise ValueError("(in GenerateSyntheticTrace) must input >= 1 app profile") if traceLength <= 0: raise ValueError("(in GenerateSyntheticTrace) traceLength must be > 0)") numProfiles = len(appProfiles) if numProfiles > 1 and not(len(weights) == 0 or len(weights) == numProfiles): raise ValueError("(in GenerateSyntheticTrace) if len(appProfiles) > 1, len(weights) must be 0 or len(appProfiles)") # create even weights if weights is left as default if len(weights) == 0: weights = np.ones(numProfiles) for i in xrange(numProfiles): if weights[i] < 0: raise ValueError("(in GenerateSyntheticTrace) weights must be > 0") # markov model for cycle activity blockSize = np.zeros(numProfiles, dtype = np.int) # open application profiles & find size of largest reusePMF numReuseDistances = 0 for i in xrange(numProfiles): appProfiles[i] = h5.File(appProfiles[i]) # get blocksizes blockSize[i] = appProfiles[i]['blockSize'][()] # if current size larger than previous largest rPMF if len(appProfiles[i]['reusePMF']) > numReuseDistances: numReuseDistances = len(appProfiles[i]['reusePMF']) # make sure all blocksizes are the same for i in xrange(1, numProfiles): if blockSize[i] != blockSize[i-1]: raise ValueError("(in GenerateSyntheticTrace) all profiles must have the same blockSize") blockSize = blockSize[0] # set blocksize # build markov model activityMarkov = np.zeros((2,2), dtype = np.float) PreProc.BuildMarkovModel(appProfiles, weights, activityMarkov) # create weighted PMF for each reuse distance reusePMF = np.zeros(numReuseDistances, dtype = np.float) PreProc.BuildReusePMF(appProfiles, weights, reusePMF) # create load proportions for each reuse distance loadProp = np.zeros(numReuseDistances, dtype = np.float) PreProc.BuildLoadProp(appProfiles, weights, loadProp) # initialize application's working set workingSet = PreProc.BuildWorkingSet(appProfiles).tolist() wsSize = len(workingSet) lruStack = workingSet # create alphaForest alphaForest = [] PreProc.BuildAlphaForest(appProfiles, weights, alphaForest, wsSize, blockSize) # close application profiles for i in xrange(numProfiles): appProfiles[i].close() # open traceFile traceFile = open(traceFile, 'w') # get reference to random generator choice = np.random.choice # indicates previous cycle's activity previousCycle = 0 # counts unique accesses uniqueAddrs = 0 # generation loop cycle = -1 accesses = 0 while (accesses < traceLength): if not choice(2, p=activityMarkov[previousCycle,:]): # if inactive cycle # process inactive cycle cycle += 1 previousCycle = 0 continue # else, active cycle cycle += 1 previousCycle = 1 accesses += 1 # select reuse distance reuseDist = choice(numReuseDistances, p = reusePMF) # compulsory cache miss if not reuseDist: # if we run out of addresses, print message and exit if uniqueAddrs >= wsSize: print "Exiting on cycle %d: cannot exceed size of working set" exit() # select new cache block to reference memAddress = lruStack[uniqueAddrs] # update lru stack lruStack.remove(memAddress) lruStack.insert(0, memAddress) else: # keep track of unique accesses if reuseDist > uniqueAddrs: uniqueAddrs += 1 # get block at this reuse distance memAddress = lruStack[reuseDist - 1] # update lruStack lruStack.remove(memAddress) lruStack.insert(0, memAddress) # select type of access rand = np.random.rand() if rand < loadProp[reuseDist]: accessType = 0 # load else: accessType = 1 # store # select 4-byte word address based on alpha values blockIndex = workingSet.index(memAddress) memAddress = memAddress | alphaForest[blockIndex].GenerateAccess(reuseDist - 1) # print access formatAccess(traceFile, cycle, accessType, memAddress) # ## main function # if __name__ == "__main__": try: if len(sys.argv) != 2: raise IndexError("Invalid number of arguments. Only config file should be specified") # setup config parser with default args config = ConfigParser.RawConfigParser({'weights': [], 'formatAccess': traceFormats['STL']}) config.read(sys.argv[1]) # pull arguments traceFile = config.get('generator', 'traceFile') traceLength = int(config.get('generator', 'traceLength')) appProfiles = json.loads(config.get('generator', 'appProfiles')) weights = json.loads(config.get('generator', 'weights')) formatAccess = config.get('generator', 'formatAccess') GenerateSyntheticTrace(traceFile, traceLength, appProfiles, weights, traceFormats[formatAccess]) except IOError as error: print "IOError: " + str(error) except ValueError as error: tb = sys.exc_info()[2] traceback.print_tb(tb) print "ValueError: ", error except ConfigParser.NoOptionError as error: print "Invalid Args: ", error, "\n" print usage_info except ConfigParser.NoSectionError as error: print "Invalid Config: ", error, "\n" print usage_info except KeyError as error: print "KeyError: ", error except IndexError as error: print "IndexError: ", error, "\n" print usage_info
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import pandas as pd def read_filter_lbmp(path): """ Read one csv file with pandas. Convert the Time Stamp field to pandas datetime format. Filter out non-NYC nodes and only keep required columns. Change column names to snake case for easier access. Parameters ---------- path : str or other object for read_csv filepath parameter Path to csv file with LBMP data Returns ------- DataFrame df with 3 columns (time stamp, name of node, LBMP) """ df = pd.read_csv(path, parse_dates=['Time Stamp']) df = df.loc[df.Name == 'N.Y.C.', ['Time Stamp', 'Name', 'LBMP ($/MWHr)']] df.columns = ['time_stamp', 'name', 'lbmp'] return df def read_all_nyc(data_path): """ Reads and combines individual LBMP data files. Parameters ---------- data_path : Path object This is a pathlib Path object pointing to the LBMP data folder with .csv files. Returns ------- DataFrame df with 4 columns (time stamp, name of node, LBMP, hour of year) """ fnames = data_path.glob('**/*.csv') dfs = [read_filter_lbmp(name) for name in fnames] df = pd.concat(dfs) df.sort_values('time_stamp', inplace=True) df.reset_index(inplace=True, drop=True) df['hour'] = df.index return df
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#!/usr/bin/env python3 # -*- coding: utf-8 -*- import logging import os.path from concurrent.futures import as_completed import requests from ..download import FuturesSessionFlex from ..processor import IndexFileProcessor logger = logging.getLogger('update.IndexUpdate')
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## TODO: define the convolutional neural network architecture import torch from torch.autograd import Variable import torch.nn as nn import torch.nn.functional as F # can use the below import should you choose to initialize the weights of your Net import torch.nn.init as I
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#! /usr/bin/env python import pygame import sys import random def main (): """Main function""" rt = Robot() p = rt.init_probability_map() while True: #rt.display_robot() rt.display_probability_map(p) m = rt.robot_random_move() rt.perception() rt.localisation(m,p) #print("x : " +str(rt.x)) #print("y : " +str(rt.y)) #rt.display_prob(p) #print(m) #print("Perception: I receive: "+str(rt.z)) if __name__ == "__main__": main()
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import json from io import StringIO import argparse if __name__ == '__main__': parser = argparse.ArgumentParser(description=""" Generate Java Utility class from GeoJson Input for AnyLogic GISShape """) parser.add_argument('geojsonfile', help='path to geojson file of regions', metavar='regions.geojson', type=str) parser.add_argument("-o", help="path of output Java file", metavar='output.java', type=str, default='InitGISRegions.java') args = parser.parse_args() genFile(args.geojsonfile, args.o)
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import pytest from tests.constants import public_key, private_key, auth_result_url @pytest.fixture(scope="session")
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# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. import logging import time import azure.functions logger = logging.getLogger('my function')
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"""Url configuration for the auth module.""" from django.conf.urls import include, url from .views import ( IdPRedirectView, inactive_user_view, lti_login_and_complete_view, post_to_custom_auth_form, saml_metadata_view ) urlpatterns = [ url(r'^auth/inactive', inactive_user_view, name="third_party_inactive_redirect"), url(r'^auth/custom_auth_entry', post_to_custom_auth_form, name='tpa_post_to_custom_auth_form'), url(r'^auth/saml/metadata.xml', saml_metadata_view), url(r'^auth/login/(?P<backend>lti)/$', lti_login_and_complete_view), url(r'^auth/idp_redirect/(?P<provider_slug>[\w-]+)', IdPRedirectView.as_view(), name="idp_redirect"), url(r'^auth/', include('social_django.urls', namespace='social')), url(r'^auth/saml/v0/', include('common.djangoapps.third_party_auth.samlproviderconfig.urls')), url(r'^auth/saml/v0/', include('common.djangoapps.third_party_auth.samlproviderdata.urls')), url(r'^auth/saml/v0/', include('common.djangoapps.third_party_auth.saml_configuration.urls')), ]
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# Licensed under a 3-clause BSD style license - see LICENSE.rst """Functions to rebin light curves and frequency spectra.""" from __future__ import (absolute_import, unicode_literals, division, print_function) import numpy as np from .io import get_file_type from .io import save_data from .io import MP_FILE_EXTENSION, get_file_extension from .base import _empty, _assign_value_if_none import logging def const_rebin(x, y, factor, yerr=None, normalize=True): """Rebin any pair of variables. Might be time and counts, or freq and pds. Also possible to rebin the error on y. Parameters ---------- x : array-like y : array-like factor : int Rebin factor yerr : array-like, optional Uncertainties of y values (it is assumed that the y are normally distributed) Returns ------- new_x : array-like The rebinned x array new_y : array-like The rebinned y array new_err : array-like The rebinned yerr array Other Parameters ---------------- normalize : bool """ arr_dtype = y.dtype if factor <= 1: res = [x, y] if yerr is not None: res.append(yerr) else: res.append(np.zeros(len(y), dtype=arr_dtype)) return res factor = np.long(factor) nbin = len(y) new_nbins = np.int(nbin / factor) y_resh = np.reshape(y[:new_nbins * factor], (new_nbins, factor)) x_resh = np.reshape(x[:new_nbins * factor], (new_nbins, factor)) new_y = np.sum(y_resh, axis=1) new_x = np.sum(x_resh, axis=1) / factor if yerr is not None: yerr_resh = np.reshape(yerr[:new_nbins * factor], (new_nbins, factor)) new_yerr = np.sum(yerr_resh ** 2, axis=1) else: new_yerr = np.zeros(len(new_x), dtype=arr_dtype) if normalize: return new_x, new_y / factor, np.sqrt(new_yerr) / factor else: return new_x, new_y, np.sqrt(new_yerr) def geom_bin(freq, pds, bin_factor=None, pds_err=None, npds=None): """Given a PDS, bin it geometrically. Parameters ---------- freq : array-like pds : array-like bin_factor : float > 1 pds_err : array-like Returns ------- retval : object An object containing all the following attributes flo : array-like Lower boundaries of the new frequency bins fhi : array-like Upper boundaries of the new frequency bins pds : array-like The rebinned PDS epds : array-like The uncertainties on the rebinned PDS points (be careful. Check with simulations if it works in your case) nbins : array-like, optional The new number of bins averaged in each PDS point. Other Parameters ---------------- npds : int The number of PDSs averaged to obtain the input PDS Notes ----- Some parts of the code are copied from an algorithm in isisscripts.sl """ from numpy import log10 df = np.diff(freq) assert np.max(df) - np.min(df) < 1e-5 * np.max(df), \ 'This only works for not previously rebinned spectra' df = freq[1] - freq[0] npds = _assign_value_if_none(npds, 1.) pds_err = _assign_value_if_none(pds_err, np.zeros(len(pds))) if freq[0] < 1e-10: freq = freq[1:] pds = pds[1:] pds_err = pds_err[1:] if bin_factor <= 1: logging.warning("Bin factor must be > 1!!") f0 = freq - df / 2. f1 = freq + df / 2. retval = _empty() retval.flo = f0 retval.fhi = f1 retval.pds = pds retval.epds = pds_err retval.nbins = np.ones(len(pds)) * npds return retval # Input frequencies are referred to the center of the bin. But from now on # I'll be interested in the start and stop of each frequency bin. freq = freq - df / 2 fmin = min(freq) fmax = max(freq) + df logstep = log10(bin_factor) # maximum number of bins nmax = np.int((log10(fmax) - log10(fmin)) / logstep + 0.5) # Low frequency grid flo = fmin * 10. ** (np.arange(nmax) * logstep) flo = np.append(flo, [fmax]) # Now the clever part: building a histogram of frequencies pds_dtype = pds.dtype pdse_dtype = pds_err.dtype bins = np.digitize(freq.astype(np.double), flo.astype(np.double)) newpds = np.zeros(nmax, dtype=pds_dtype) - 1 newpds_err = np.zeros(nmax, dtype=pdse_dtype) newfreqlo = np.zeros(nmax) new_nbins = np.zeros(nmax, dtype=np.long) for i in range(nmax): good = bins == i ngood = np.count_nonzero(good) new_nbins[i] = ngood if ngood == 0: continue newpds[i] = np.sum(pds[good]) / ngood newfreqlo[i] = np.min(freq[good]) newpds_err[i] = np.sqrt(np.sum(pds_err[good] ** 2)) / ngood good = new_nbins > 0 new_nbins = new_nbins[good] * npds newfreqlo = newfreqlo[good] newpds = newpds[good] newpds_err = newpds_err[good] newfreqhi = newfreqlo[1:] newfreqhi = np.append(newfreqhi, [fmax]) retval = [newfreqlo, newfreqhi, newpds, newpds_err, new_nbins] retval = _empty() retval.flo = newfreqlo retval.fhi = newfreqhi retval.pds = newpds retval.epds = newpds_err retval.nbins = new_nbins return retval def rebin_file(filename, rebin): """Rebin the contents of a file, be it a light curve or a spectrum.""" ftype, contents = get_file_type(filename) do_dyn = False if 'dyn{0}'.format(ftype) in contents.keys(): do_dyn = True if ftype == 'lc': x = contents['time'] y = contents['lc'] ye = np.sqrt(y) logging.info('Applying a constant rebinning') x, y, ye = \ const_rebin(x, y, rebin, ye, normalize=False) contents['time'] = x contents['lc'] = y if 'rebin' in list(contents.keys()): contents['rebin'] *= rebin else: contents['rebin'] = rebin elif ftype in ['pds', 'cpds']: x = contents['freq'] y = contents[ftype] ye = contents['e' + ftype] # if rebin is integer, use constant rebinning. Otherwise, geometrical if rebin == float(int(rebin)): logging.info('Applying a constant rebinning') if do_dyn: old_dynspec = contents['dyn{0}'.format(ftype)] old_edynspec = contents['edyn{0}'.format(ftype)] dynspec = [] edynspec = [] for i_s, spec in enumerate(old_dynspec): _, sp, spe = \ const_rebin(x, spec, rebin, old_edynspec[i_s], normalize=True) dynspec.append(sp) edynspec.append(spe) contents['dyn{0}'.format(ftype)] = np.array(dynspec) contents['edyn{0}'.format(ftype)] = np.array(edynspec) x, y, ye = \ const_rebin(x, y, rebin, ye, normalize=True) contents['freq'] = x contents[ftype] = y contents['e' + ftype] = ye contents['rebin'] *= rebin else: logging.info('Applying a geometrical rebinning') if do_dyn: old_dynspec = contents['dyn{0}'.format(ftype)] old_edynspec = contents['edyn{0}'.format(ftype)] dynspec = [] edynspec = [] for i_s, spec in enumerate(old_dynspec): retval = geom_bin(x, spec, rebin, old_edynspec[i_s]) dynspec.append(retval.pds) edynspec.append(retval.epds) contents['dyn{0}'.format(ftype)] = np.array(dynspec) contents['edyn{0}'.format(ftype)] = np.array(edynspec) retval = geom_bin(x, y, rebin, ye) del contents['freq'] contents['flo'] = retval.flo contents['fhi'] = retval.fhi contents[ftype] = retval.pds contents['e' + ftype] = retval.epds contents['nbins'] = retval.nbins contents['rebin'] *= retval.nbins else: raise Exception('Format was not recognized:', ftype) outfile = filename.replace(get_file_extension(filename), '_rebin%g' % rebin + MP_FILE_EXTENSION) logging.info('Saving %s to %s' % (ftype, outfile)) save_data(contents, outfile, ftype) def main(args=None): """Main function called by the `MPrebin` command line script.""" import argparse description = 'Rebin light curves and frequency spectra. ' parser = argparse.ArgumentParser(description=description) parser.add_argument("files", help="List of light curve files", nargs='+') parser.add_argument("-r", "--rebin", type=float, default=1, help="Rebinning to apply. Only if the quantity to" + " rebin is a (C)PDS, it is possible to specify a" + " non-integer rebin factor, in which case it is" + " interpreted as a geometrical binning factor") parser.add_argument("--loglevel", help=("use given logging level (one between INFO, " "WARNING, ERROR, CRITICAL, DEBUG; " "default:WARNING)"), default='WARNING', type=str) parser.add_argument("--debug", help="use DEBUG logging level", default=False, action='store_true') args = parser.parse_args(args) files = args.files if args.debug: args.loglevel = 'DEBUG' numeric_level = getattr(logging, args.loglevel.upper(), None) logging.basicConfig(filename='MPrebin.log', level=numeric_level, filemode='w') rebin = args.rebin for f in files: rebin_file(f, rebin)
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import faulthandler import atexit import signal import traceback import os import multiprocessing # To test with doctest... if not __package__: # pragma: no cover LIB_PATH = "." else: from .. import LIB_PATH # Global configuration DUMP_DIRECTORY = LIB_PATH + "/dump/" DUMP_CURRENT_PROCESS = DUMP_DIRECTORY + "%(ppid)s/" DUMP_FILENAME = DUMP_CURRENT_PROCESS + "%(pid)s.dump" def get_stack(): # pragma: no cover # nothing to test here """Returns the current stack trace as a string.""" return traceback.format_exc() class StackDumper: """ Dumps the stack of the current process and all of its threads when it receives a SIGUSR1 signal. The stack will go in dump/<main process id>/<real process id>.dump file. You do not need to create this object yourself, instead, use `init_stack_dumper()` """ def init_stack_dumper(): """ Initalize the stack dumper for current process. This method should be called for all subprocesses (but not for threads) >>> import os >>> from signal import SIGUSR1 >>> init_stack_dumper() >>> # From your terminal send the SIGUSR1 signal >>> # kill -SIGUSR1 <pid> >>> os.kill(os.getpid(), SIGUSR1) # send the SIGUSR1 signal >>> print(open(DUMP_FILENAME % dict(ppid=os.getpid(), pid=os.getpid()), "r").read()) # doctest: +ELLIPSIS Current thread ... (most recent call first):... """ StackDumper()
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# -*- coding: utf-8 -*- """ Created on Fri May 7 11:32:58 2021 @author: helena """ class IcebergCalc(): """ Class declaration for the IcebergCalc class. Provides methods for calculating an iceberg's area, volume and mass. """ def __init__(self, lidardata, radardata, seaice_m): """ Constructor function initialises the attributes of the IcebergCalc class. Parameters ---------- lidardata : list of intergers List of the lidar data radardata : list of integers List of the radar data seaice_m : list Empty list for the ice variables to be appended Returns ------- None. """ self.lidardata = lidardata self.radardata = radardata self.seaice_m = [] def find_ice(self, radardata, seaice_m): """ This function finds if there is ice within this section of the sea. Ice has radar data values of over 100, so this function finds those values over 100 and prints these values. Parameters ---------- radardata : list of integers List of the radar data seaice_m : list Empty list for the ice variables to be appended. The default is None. Returns ------- None. """ for i in range(len(radardata)): if i >= 100.0: seaice_m.append(i) print("Areas of ice are " + str(seaice_m)) #print(seaice_m) def find_mass(self, lidardata): """ This function calculates the area, volume and mass of the ice. The lidar data is in cm. The area of the icberg is calculated then multiplied by the by the height to calculate the volume. The volume is multiplied by the density of ice to calculate the mass of the iceberg. The density of ice is a set value. The total volume of the mass of the iceberg is calculated by multiplying by 10 (as only 10% of the iceberg is currently above the water line) to calculate 100% of the iceberg mass. These variables are printed. Parameters ---------- lidardata : list of integers List of the lidar data Returns ------- Integer. The total mass of the iceberg. """ global total_volume global total_mass total_pixels = 0 total_volume = 0 for row in lidardata: for i in row: if i >= 100.0: total_pixels += 1 # Area of the iceberg total_volume += i*0.1 # Convert cm to m as 0.1 = 10cm # Density of ice = 917km/m^3 iceberg_mass = total_volume * 917 total_mass = iceberg_mass * 10 print("The area of iceberg is" + " " + str(total_pixels) + " m^2") print("The volume of iceberg is" + " " + str(total_volume) + " m^3") print("The mass of the iceberg is" + " " + str(iceberg_mass) + " kg/m^3") print("The total mass of the iceberg is" + " " + str(total_mass) + " kg/m^3") return(total_mass) def total_volume(self): """ This function defines the variable total volume of the iceberg. Returns ------- Integer The total volume of the iceberg. """ return int(total_volume) def total_mass(self): """ This function defines the variable total mass of the iceberg. Returns ------- Integer The total mass of the iceberg. """ return int(total_mass) def determine_drag(self): """ This function determines whether the iceberg is within size range to be towed by the company tug boat. If the iceberg is larger than 36 million kg in mass, it cannot be towed by the tug boat. Returns ------- String . If the iceberg is within size range to be towed by the company. """ global within_range global outside_range within_range = "Can tow iceberg" outside_range = "Cannot tow iceberg" if total_mass > 36000000: return(outside_range) return(within_range)
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from keras.layers import Conv2D, BatchNormalization, Input, DepthwiseConv2D, Lambda, Concatenate from keras.layers import GlobalAveragePooling2D, Reshape, ReLU, Add, Dropout import keras.backend as K from ..functions.mutations import channel_split, channel_shuffle # Emulate class behaviour for parameterization def SeperableConvBlock(output_filters=None, ReLU_Max=None, strides=(1, 1)): r""" x->DWConv(3x3)->BN->ReLU(max)->Conv2D(1x1)->BN ``` output_filters: int, size of last axis output ReLU_Max: float, max value as output of a ReLU in this block, if < 0, it will be Linear (no ReLU) strides: int/tuple-int, same as in keras.layers.Conv2D ``` From MnasNet https://arxiv.org/pdf/1807.11626.pdf Also used in MobileConvBlock as subblock """ return stub def MobileConvBlock(output_filters, latent_filters, ReLU_Max=None, skipFunction=None, strides=(1, 1)): r""" ``` /-------------------------------------------\ x->Conv(1x1,lat)->ReLU->{SeperableConvBlock}-=?>skip ``` ``` output_filters: int, size of last axis output latent_filters: int, size of filters at first Conv 1x1 (see MnasNet), If None shape[-1] is used - *_filters is generally 'k * shape[-1]' as expansion factor ReLU_Max: float, max value as output of a ReLU in this block skipFunction: def, a function combining 2 equi-shaped tensors (e.g. keras.layers.add) strides: int/tuple-int, same as in keras.layers.Conv2D ``` skipFunction (if not None) is an keras function with the same interface as keras.layers.{add|multiply} if None there will be no attention added Stride block from MobileNetV2 (fixed ) ``` Strides=1: ReLU_Max=6, skipFunction=keras.layers.add Strides=2: ReLU_Max=6, strides=(2,2) ``` MBConv6 from MnasNet ``` latent_filters=6*output_filters, skipFunction=keras.layers.add ``` From MobileNetV2 https://arxiv.org/pdf/1801.04381.pdf (When RELU6) From MnasNet https://arxiv.org/pdf/1807.11626.pdf (When RELU) """ return stub def ShuffleBasic(out_channels, bottleneck_factor): r""" ``` /->Conv(1x1,BN,RelU)->{SeperableConvBlock}-\ x->ChSplit------------------------------------Concat(axis=-1)->ChShuffle ``` """ return stub def ShuffleStride(out_channels, bottleneck_factor, strides=(2, 2)): r""" ``` /-Conv(1x1,bn,relu)->{SeperableConvBlock}->ReLU-\ x-{SeperableConvBlock}->ReLU---------------->Concat(axis=-1)->ChShuffle ``` """ return stub def ResnetBlock(): r""" ``` /->BN->ReLU->Conv(k=3)->BN->ReLU->Conv(k=1)-\ x--------------------------------------------->Add ``` """ return stub def ApesBlock(k, r): r""" ``` /->BN->ReLU->Conv(k=1)->BN->ReLU->Conv(k=k)->BN-\ x->BN---------------------------------------------->Add->ReLU->Dropout(r) ``` """ return stub
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outer = {"inner": {"hooray": "python"}}
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from selenium import webdriver driver = webdriver.Chrome() driver.get('https://web.whatsapp.com/') all_names = ['Sachin Yadav'] msg = input('Enter the message') count = int(input('no.of times to send message')) input('click any random key after qr scanning') for name in all_names: user = driver.find_element_by_xpath("//span[@title = '{}']".format(name)) user.click() msgbox = driver.find_element_by_class_name('_3u328') for i in range (count): msgbox.send_keys(msg) button = driver.find_element_by_class_name('_3M-N-') button.click()
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248
from django.conf import settings from django.contrib.auth import get_user_model from django.utils import timezone from wagtail.contrib.modeladmin.options import ModelAdmin, modeladmin_register from home.models import SiteSettings from iogt_users.filters import GroupsFilter modeladmin_register(UsersExportAdmin)
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3.632184
87
from .constants import BLOCK_TAGS def add_0x(string): """Add 0x to string at start. """ if isinstance(string, bytes): string = string.decode('utf-8') return '0x' + str(string) def hex_to_dec(x): """Convert hex to decimal """ return int(x, 16) def wei_to_ether(wei): """Convert wei to ether """ return 1.0 * wei / 10**18 def gwei_to_ether(wei): """Convert gwei to ether """ return 1.0 * wei / 10**9 def ether_to_wei(ether): """Convert ether to wei """ return int(ether * 10**18) def ether_to_gwei(ether): """Convert ether to Gwei """ return int(ether * 10**9) def validate_block(block): """Validate block on tag or hex int """ if isinstance(block, str): if block not in BLOCK_TAGS: raise ValueError('Invalid block tag.') elif isinstance(block, int): block = hex(block) else: raise ValueError('Invalid block type.') return block
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2.334123
422
from .models import RedirectVariable
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4.625
8
from enum import Enum, auto from autorepr import AutoRepr from birdway import Unary, Type, Binary for name in [ "KeywordMeta", "KeywordArgs", "KeywordParam", "KeywordRun", "KeywordIf", "KeywordThen", "KeywordElse", "KeywordPrintln", "KeywordOption", "BlockBegin", "BlockEnd", "TableBegin", "TableEnd", "OpeningParens", "ClosingParens", "FormattedStringDelimiter", "StringDelimiter", "LineEnd", "Association", "Separator", "Assignment", "Return", "FormattingExpressionBegin", "KeywordStruct", "KeywordEnum", "KeywordFunc", "KeywordFor", "KeywordFrom", "KeywordTo", "KeywordDo", "KeywordTry", "KeywordOn", "Range", "KeywordUse", "KeywordIn", ]: exec(f"class {name} (Token, AutoRepr): pass") del name
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2.242105
380
file1 = open('input_7.txt', 'r') Lines = file1.readlines() bingo_numbers = Lines[0].split(",") bingo_tables = [] bingo_win = 0 bingo_row_number = 0 for line in Lines[2:]: new_row = [] if line == '\n': continue row = line.split(" ") for element in row: if element == '\n' or element == '': continue new_row.append(element.strip()) bingo_tables.append(new_row) bingo_row_result = [0] * len(bingo_tables) bingo = False for number in bingo_numbers: counter = 0 for row in bingo_tables: try: index = row.index(number) bingo_row_result[counter] += 1 row[row.index(number)] = 0 if bingo_row_result[counter] == 5: bingo = True bingo_row_number = counter bingo_win = int(number) print('Bingo %s' % number) break except: pass for c in range(0, 5): bingo_test = 0 for r in range(0, len(bingo_tables)): if r % 5 == 0: bingo_test = 0 bingo_test += int(bingo_tables[r][c]) if bingo_test == 0: bingo = True bingo_row_number = counter bingo_win = int(number) print('Bingo %s' % number) break counter += 1 if bingo: break bingo_row_number = bingo_row_number - (bingo_row_number % 5) total = 0 for row in bingo_tables[bingo_row_number:bingo_row_number+5]: for x in row: total += int(x) print(bingo_tables) print(total*bingo_win)
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1.854402
886
username = input("Please enter your name : ") print(type(username)) print(f'Your name is : {username}')
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3.322581
31
import requests, json def userApiKey(apikey): """ Returns information about an apikey apikey: Your ApiKey from FileCrypt Attention: this API is limited to 10 requests for an timeframe of 1 hour. """ data={"api_key":apikey,"sub":"apikey","fn":"user"} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def userEarnings(apikey,year=None,month=None,day=None): """ Returns statistics from user income and the total available balance on the account apikey: Your ApiKey from FileCrypt year(optional): year (YYYY) (2019) month(optional): month (MM) (06) day(optional): month (DD) (13) """ data={"api_key":apikey,"sub":"earnings","fn":"user"} if year != None: data["year"] = str(year) if month != None: data["month"] = str(month) if day != None: data["day"] = str(day) return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerCreate(apikey,name,mirrors,password=None,captcha=None,allow_cnl=None,allow_dlc=None,allow_links=None,groupid=None): """ This function allows you to create an filecrypt.cc protected folder. apikey: Your ApiKey from FileCrypt name: name of your folder mirrors: mirrors in a tripple listed list example: [[[mirror_0_link1,mirror_0_link2],[mirror_0_backup_link1,mirror_0_backup_link2]],[[mirror_1_link1,mirror_1_link2],[mirror_1_backup_link1,mirror_1_backup_link2]]] prettyprinted example: [ [ [ "mirror_0_link1", "mirror_0_link2" ], [ "mirror_0_backup_link1", "mirror_0_backup_link2" ] ], [ [ "mirror_1_link1", "mirror_1_link2" ], [ "mirror_1_backup_link1", "mirror_1_backup_link2" ] ] ] all strings in the first and second list (where the other lists should be) will be skipped password(optional): password of your folder captcha(optional): enable captcha? Allowed Values: 0,1 allow_cnl(optional): enable cnl? Allowed Values: 0,1 allow_dlc(optional): enable dlc? Allowed Values: 0,1 allow_links(optional): enable links? Allowed Values: 0,1 groupid: group ID of your target group """ data={"api_key":apikey,"sub":"createV2","fn":"containerV2","name":name} for i in range(len(mirrors)): if isinstance(mirrors[i],str): continue for j in range(len(mirrors[i])): if isinstance(mirrors[i][j],str): continue for k in range(len(mirrors[i][j])): data["mirror_"+str(i+1)+"["+str(j)+"]["+str(k)+"]"] = mirrors[i][j][k] if password != None: data["folderpass"] = password if captcha != None: data["captcha"] = str(captcha) if allow_cnl != None: data["allow_cnl"] = str(allow_cnl) if allow_dlc != None: data["allow_dlc"] = str(allow_dlc) if allow_links != None: data["allow_links"] = str(allow_links) if groupid != None: data["group"] = str(groupid) return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerEdit(apikey,mirrors,container_id,name=None,password=None,captcha=None,allow_cnl=None,allow_dlc=None,allow_links=None,groupid=None): """ This function allows you to edit an filecrypt.cc protected folder. Once you submit mirror_1 all links are permanently removed from this folder and will be replaced with the once submitted. if you would like to replace just a mirror please use our info api to get informations about links inside this folder to build your request. For informations on statusimages please visit https://filecrypt.cc/docs/index.htm#api-General-Statusimages apikey: Your ApiKey from FileCrypt name(optional): name of your folder container_id: the container_id as string mirrors: same as containerCreate() password(optional): password of your folder captcha(optional): enable captcha? Allowed Values: 0,1 allow_cnl(optional): enable cnl? Allowed Values: 0,1 allow_dlc(optional): enable dlc? Allowed Values: 0,1 allow_links(optional): enable links? Allowed Values: 0,1 groupid: group ID of your target group """ data={"api_key":apikey,"sub":"editV2","fn":"containerV2","name":name,"container_id":container_id} for i in range(len(mirrors)): if isinstance(mirrors[i],str): continue for j in range(len(mirrors[i])): if isinstance(mirrors[i][j],str): continue for k in range(len(mirrors[i][j])): data["mirror_"+str(i+1)+"["+str(j)+"]["+str(k)+"]"] = mirrors[i][j][k] if name != None: data["name"] = name if password != None: data["folderpass"] = password if captcha != None: data["captcha"] = str(captcha) if allow_cnl != None: data["allow_cnl"] = str(allow_cnl) if allow_dlc != None: data["allow_dlc"] = str(allow_dlc) if allow_links != None: data["allow_links"] = str(allow_links) if groupid != None: data["group"] = str(groupid) return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerInfo(apikey,container_id): """ Returns an sorted object containing every link in your folder. apikey: Your ApiKey from FileCrypt container_id: the container_id as string """ data={"api_key":apikey,"sub":"info","fn":"containerV2","container_id":container_id} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerList(apikey,state=None,fav=None): """ Returns all Containers from your FileCrypt Account apikey: Your ApiKey from FileCrypt state(optional): filter by state of your folders. Allowed values: "unchecked", "ok", "uncheckable", "error", "offline", "partial" fav(optional): filter on favorite folders 1 = favorite, 0 = regular folder """ data={"api_key":apikey,"sub":"listV2","fn":"containerV2"} if state != None: data["state"] = state if fav != None: data["fav"] = str(fav) return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerMyFolder(apikey,state=None,groupid=None): """ returns a short list of your own folders filtered by state (if passed as parameter). Please note every Object child of the container-Node starts with a trailing _. apikey: Your ApiKey from FileCrypt state(optional): filter by state of your folders. Allowed values: "unchecked", "ok", "uncheckable", "error", "offline", "partial" groupid(optional): filter for specified group """ data={"api_key":apikey,"fn":"containerV2","sub":"myfolder"} if state != None: data["state"] = state if groupid != None: data["group"] = str(groupid) return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerRemove(apikey,container_id): """ *Move* folder from public to trashbin the folder will not be public available. apikey: Your ApiKey from FileCrypt container_id: the container_id as string """ data={"api_key":apikey,"fn":"containerV2","sub":"remove","container_id":container_id} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def containerStatus(apikey,container_id): """ Get status of an filecrypt.cc folder: https://filecrypt.cc/docs/index.htm#api-General-Statusimages apikey: Your ApiKey from FileCrypt container_id: the container_id as string """ data={"api_key":apikey,"fn":"containerV2","sub":"statusV2","container_id":container_id} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def groupAdd(apikey,name): """ Creates a new Group with the chosen Name apikey: Your ApiKey from FileCrypt name: The name of your new group """ data={"api_key":apikey,"fn":"group","sub":"add","name":name,"parent":"0"} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def groupList(apikey): """ Returns all Groups existing in your FileCrypt Account apikey: Your ApiKey from FileCrypt """ data={"api_key":apikey,"fn":"group","sub":"list"} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def groupMove(apikey,groupid,container_id): """ Move your filecrypt.cc containers to a specified group apikey: Your ApiKey from FileCrypt groupid: the group ID(!) you want the containers to be in container_id: you can input a single Container via String or input a whole list with all containers. """ data={"api_key":apikey,"fn":"group","sub":"move","group":str(groupid)} if isinstance(container_id,str): data["container_id[0]"] = container_id elif isinstance(container_id,list): for i in range(len(container_id)): data["container_id["+str(i)+"]"]=container_id[i] return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text) def groupRemove(apikey,groupid): """ Removes the group and moves all containers to group 0 (ungrouped) apikey: Your ApiKey from FileCrypt groupid: the group ID(!) you want to delete """ data={"api_key":apikey,"fn":"group","sub":"remove","id":str(groupid)} return json.loads(requests.post("https://filecrypt.cc/api.php",data=data).text)
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2.554287
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#!/usr/bin/env python3 import RPi.GPIO as GPIO import sys import time if __name__ == '__main__': main(int(sys.argv[1]))
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# Copyright (c) 2010 Tim Medina # # 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. # # The original code link is https://github.com/iamteem/redisco/tree/master/redisco/__init__.py import redis client = Client() connection = client.redis() __all__ = ['connection_setup', 'get_client']
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3.502646
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from app import db import datetime
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3.888889
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import numpy as np import random import xlwt # # 市界的地理坐标为:北纬39”26’至41”03’,东经115”25’至 117”30’ workbook = xlwt.Workbook(encoding='utf-8') worksheet = workbook.add_sheet("My Workbook") print(worksheet) a=[] for i in range(0,5107): x=random.uniform(115,117) y=random.uniform(39,41) a.append(str( ( str(y)))) print(a[0]) j=0 for i in a: worksheet.write(j,0,i) j=j+1 workbook.save("test.xls")
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# -*- coding: utf-8 -*- """ Created on Wed Feb 29 10:12:38 2012 Author: Josef Perktold License: BSD-3 """ import itertools try: #python 2.6, 2.7 zip_longest = itertools.izip_longest pass except AttributeError: #python 3.2 try: zip_longest = itertools.zip_longest pass except AttributeError: #python 2.5 def zip_longest(*args, **kwds): '''python 2.5 version for transposing a list of lists adds None for lists of shorter length, may not have the same behavior as python 2.6 izip_longest or python 3.2 zip_longest for other cases Parameters ---------- args : sequence of iterables iterables that will be combined in transposed way Returns ------- it : iterator iterator that generates tuples Examples -------- >>> lili = [['a0', 'b0', 'c0', 'd0'], ['a1', 'b1', 'c1'], ['a2', 'b2', 'c2', 'd2'], ['a3', 'b3', 'c3', 'd3'], ['a4', 'b4']] >>> list(izip_longest(*lili)) [('a0', 'a1', 'a2', 'a3', 'a4'), ('b0', 'b1', 'b2', 'b3', 'b4'), ('c0', 'c1', 'c2', 'c3', None), ('d0', None, 'd2', 'd3', None)] ''' # izip_longest('ABCD', 'xy', fillvalue='-') --> Ax By C- D- fillvalue = kwds.get('fillvalue') fillers = itertools.repeat(fillvalue) iters = [itertools.chain(it, sentinel(), fillers) for it in args] try: for tup in itertools.izip(*iters): yield tup except IndexError: pass try: from itertools import combinations except ImportError: #from python 2.6 documentation
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import paddle import numpy as np import torch import torch.optim.lr_scheduler as lr_scheduler from reprod_log import ReprodLogger from reprod_log import ReprodDiffHelper from mobilenetv3_paddle.paddlevision.models import mobilenet_v3_small as mv3_small_paddle from mobilenetv3_ref.torchvision.models import mobilenet_v3_small as mv3_small_torch if __name__ == "__main__": test_backward() # load data diff_helper = ReprodDiffHelper() torch_info = diff_helper.load_info("./result/losses_ref.npy") paddle_info = diff_helper.load_info("./result/losses_paddle.npy") # compare result and produce log diff_helper.compare_info(torch_info, paddle_info) diff_helper.report(path="./result/log/backward_diff.log")
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# ---------------------------------------------------------- #Erick Alberto Bustos Cruz A01378966 # # # ---------------------------------------------------------- from functools import total_ordering import math as m @total_ordering class Racional: """Instancias de esta clase representan números racionales con un numerador y un denominador. """ @property @property @numerador.setter @denominador.setter
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2.955414
157
import numpy as np import pandas as pd import json from mplsoccer.pitch import Pitch, VerticalPitch path = "C:/Users/brand/desktop/events/events_England.json" with open(path) as f: data = json.load(f) train = pd.DataFrame(data) path2 = "C:/Users/brand/desktop/players.json" with open(path2) as f: play = json.load(f) players = pd.DataFrame(play) lst = ['events_France.json','events_Germany.json','events_Italy.json','events_Spain.json'] pathway = "C:/Users/brand/desktop/events/" for country in lst: with open(pathway + country) as f: datal = json.load(f) tl = pd.DataFrame(datal) train = pd.concat([train,tl],ignore_index=True) #pd.unique(train['subEventName']) shots = train[train['subEventName'] == 'Shot'] print(len(shots)) shots_model = pd.DataFrame(columns=["Goal","X","Y"], dtype=object) for i,shot in shots.iterrows(): shots_model.at[i,'Header'] = 0 for tag in shot['tags']: if tag['id'] == 403: shots_model.at[i,'Header'] = 1 #take distance from center of goal at y = 50, x position of goal is always 100 shots_model.at[i,'X'] = 100-shot['positions'][0]['x'] shots_model.at[i,'Y'] = shot['positions'][0]['y'] shots_model.at[i,'C'] = abs(shot['positions'][0]['y'] - 50) #distance in meters x = shots_model.at[i,'X']* 105/100 y = shots_model.at[i,'C']* 65/100 shots_model.at[i,'Distance'] = np.sqrt(x**2 + y**2) angle = np.arctan(7.32 * x / (x**2 + y**2 - (7.32/2)**2)) if angle < 0: angle = np.pi + angle shots_model.at[i,'Angle'] = angle #goal check shots_model.at[i,'Goal'] = 0 shots_model.at[i,'Counter Attack'] = 0 shots_model.at[i, 'Blocked'] = 0 shots_model.at[i, 'Right Foot'] = 0 shots_model.at[i,'wyId'] = shot['playerId'] if shot['matchPeriod'] == '1H': shots_model.at[i, 'First Half'] = 1 else: shots_model.at[i,'First Half'] = 0 for tags in shot['tags']: if tags['id'] == 101: shots_model.at[i,'Goal'] = 1 if tags['id'] == 1901: shots_model.at[i, 'Counter Attack'] = 1 if tags['id'] == 2101: shots_model.at[i, 'Blocked'] = 1 if tags['id'] == 402: shots_model.at[i, 'Right Foot'] = 1 shots_model['angle_degrees'] = shots_model['Angle'] * 180 / np.pi shots_model = shots_model.merge(players, left_on = 'wyId' , right_on = 'wyId') for i,shot in shots_model.iterrows(): shots_model.at[i, 'strong foot'] = 0 if shot['Right Foot'] == 1: if shot['foot'] == 'right': shots_model.at[i, 'strong foot'] = 1 elif shot['Right Foot'] == 0: if shot['foot'] == 'left': shots_model.at[i, 'strong foot'] = 1 pitch = Pitch(pitch_color ='black', line_color = 'white', stripe=False,pitch_type='wyscout') fig,ax = pitch.draw(figsize=(10,8)) df = shots_model.loc[shots_model['Goal'] == 1] xpos = df["X"] ypos = df["Y"] df_nongoals = shots_model.loc[shots_model['Goal'] == 0] xpos2 = df_nongoals["X"] ypos2 = df_nongoals["Y"] head = shots_model[shots_model['Header'] == 1] counter = shots_model[shots_model['Counter Attack'] == 1] strong = shots_model[shots_model['strong foot'] == 1] first = shots_model[shots_model['First Half'] == 1] head_df = head.loc[head['Goal'] == 1] strong_goal = strong.loc[strong['Goal'] == 1] headed_goals = len(head_df) from sklearn.model_selection import train_test_split X_full = shots_model[["Header","Distance", "Angle","Counter Attack","strong foot", "First Half"]] y_full = shots_model[["Goal"]] y_full['Goal'] = y_full['Goal'].astype(int) print(X_full.head()) X_train,X_test,y_train,y_test = train_test_split(X_full,y_full,test_size = 0.15,random_state=2) X_train,X_val,y_train,y_val = train_test_split(X_train,y_train,test_size = 0.176, random_state=2) y_val = np.array(y_val.pop('Goal')) y_test = np.array(y_test.pop('Goal')) y_train = np.array(y_train.pop('Goal')) X_train = X_train.to_numpy() X_test = X_test.to_numpy() X_val = X_val.to_numpy() print(X_train.shape) print(y_train.shape) negative,positive = np.bincount(y_full['Goal']) print(positive/(negative+positive)) import tensorflow as tf from tensorflow import keras import sklearn from sklearn.preprocessing import StandardScaler scaler = StandardScaler() train_feats = scaler.fit_transform(X_train) val_feats = scaler.transform(X_val) test_feats = scaler.transform(X_test) train_feats = np.clip(train_feats,-5,5) val_feats = np.clip(val_feats,-5,5) test_feats = np.clip(test_feats,-5,5) boolean_train_labels = y_train != 0 METRICS = [ keras.metrics.TruePositives(name='tp'), keras.metrics.FalsePositives(name='fp'), keras.metrics.TrueNegatives(name='tn'), keras.metrics.FalseNegatives(name='fn'), keras.metrics.BinaryAccuracy(name='accuracy'), keras.metrics.Precision(name='precision'), keras.metrics.Recall(name='recall'), keras.metrics.AUC(name='auc'), keras.metrics.AUC(name='prc', curve='PR'), # precision-recall curve ] EPOCHS = 100 BATCH_SIZE = 256 early_stopping = tf.keras.callbacks.EarlyStopping(monitor = 'val_prc',verbose=1,patience=10,mode='max',restore_best_weights=True) model = make_model() model.summary() orig_bias = np.log([positive/negative]) model = make_model(output_bias=orig_bias) import os import tempfile initial_weights = os.path.join(tempfile.mkdtemp(), 'initial_weights') model.save_weights(initial_weights) model = make_model() model.load_weights(initial_weights) careful_bias_history = model.fit( train_feats, y_train, batch_size=BATCH_SIZE, epochs=100, validation_data=(val_feats, y_val), verbose=0) import matplotlib.pyplot as plt plot_loss(careful_bias_history,"Bias") model = make_model() model.load_weights(initial_weights) baseline_history = model.fit( train_feats, y_train, batch_size=256, epochs=100, callbacks=[early_stopping], validation_data=(val_feats, y_val)) colors = plt.rcParams['axes.prop_cycle'].by_key()['color'] plot_metrics(baseline_history) train_predictions_baseline = model.predict(train_feats) test_predictions_baseline = model.predict(test_feats) test_preds = [] test_probs = [] for i in test_predictions_baseline: if i > 0.5: test_preds.append(1) test_probs.append(i) else: test_preds.append(0) test_probs.append(i) TP = sum([(p and l) for (p,l) in zip(test_preds, y_test)]) FP = sum([(p and not l) for (p,l) in zip(test_preds, y_test)]) TN = sum([(not p and not l) for (p,l) in zip(test_preds, y_test)]) FN = sum([(not p and l) for (p,l) in zip(test_preds, y_test)]) TPR = TP/(TP+FN) TNR = TN/(TN+FP) BER = 1 - .5 * (TPR + TNR) precision = TP/(TP+FP) recall = TP/(TP + FN) F1 = 2 * (precision*recall)/(precision + recall) accuracy = (TP + TN)/(TP + FP + TN + FN) print(BER) print(precision) print(recall) print(F1) print(accuracy) from sklearn.linear_model import LinearRegression from sklearn.metrics import mean_squared_error, r2_score from yellowbrick.regressor import ResidualsPlot Y = [] X = [] count1 = 0 count2 = 0 for i in range(len(test_probs)): count1 += test_probs[i] count2 += y_test[i] X.append(count1) Y.append(count2) count1 = 0 count2 = 0 print(Y[0:10]) X = np.array(X) X = X.reshape(-1,1) lin = LinearRegression().fit(X,Y) print(lin.score(X,Y)) lpreds = lin.predict(X) print('Coeffs') print(lin.coef_) print(mean_squared_error(Y,lpreds)) print(r2_score(Y,lpreds)) visualizer = ResidualsPlot(lin) visualizer.fit(X,Y) visualizer.score(X,lpreds) visualizer.show() from sklearn.metrics import roc_curve, roc_auc_score r_probs = [0 for _ in range(len(y_test))] r_auc = roc_auc_score(y_test,r_probs) nn_auc = roc_auc_score(y_test,test_probs) r_fpr,r_tpr,_ = roc_curve(y_test,r_probs) nn_fpr,nn_tpr,_ = roc_curve(y_test,test_probs) plt.plot(r_fpr,r_tpr, label = 'Guess 0 Always',color='black') plt.plot(nn_fpr,nn_tpr, label = 'Baseline NN',color ='b') plt.title('ROC Plot Baseline Neural Network') plt.xlabel('FPR %') plt.ylabel('TPR %') plt.legend() plt.show() print(nn_auc) weight_0 = (1/negative) * (positive+negative/2.0) weight_1 = (1/positive) * (positive+negative/2.0) class_weight = {0: weight_0, 1: weight_1} print(weight_0) print(weight_1) weighted_model = make_model() weighted_model.load_weights(initial_weights) weighted_history = weighted_model.fit( train_feats, y_train, batch_size=256, epochs=100, callbacks=[early_stopping], validation_data=(val_feats, y_val), class_weight=class_weight) train_preds_weighted = weighted_model.predict(train_feats) test_preds_weighted = weighted_model.predict(test_feats) test_predictions_weighted = [] test_probs_weighted = [] for i in test_preds_weighted: if i > 0.5: test_predictions_weighted.append(1) test_probs_weighted.append(i) else: test_predictions_weighted.append(0) test_probs_weighted.append(i) TP = sum([(p and l) for (p,l) in zip(test_predictions_weighted, y_test)]) FP = sum([(p and not l) for (p,l) in zip(test_predictions_weighted, y_test)]) TN = sum([(not p and not l) for (p,l) in zip(test_predictions_weighted, y_test)]) FN = sum([(not p and l) for (p,l) in zip(test_predictions_weighted, y_test)]) TPR = TP/(TP+FN) TNR = TN/(TN+FP) BER = 1 - .5 * (TPR + TNR) precision = TP/(TP+FP) recall = TP/(TP + FN) F1 = 2 * (precision*recall)/(precision + recall) accuracy = (TP + TN)/(TP + FP + TN + FN) print("Balanced Error rate: " + str(BER)) print("Precision: " + str(precision)) print('Recall: ' + str(recall)) print('F1 score: ' + str(F1)) print('Total Classification Accuracy: ' + str(accuracy)) r_probs = [0 for _ in range(len(y_test))] r_auc = roc_auc_score(y_test,r_probs) nn_auc = roc_auc_score(y_test,test_probs_weighted) r_fpr,r_tpr,_ = roc_curve(y_test,r_probs) nn_fpr,nn_tpr,_ = roc_curve(y_test,test_probs_weighted) plt.plot(r_fpr,r_tpr, label = 'BER = 0',color='black') plt.plot(nn_fpr,nn_tpr, label = 'Weighted Class NN',color='b') plt.title('ROC Plot Weighte Classes Neural Network') plt.xlabel('FPR %') plt.ylabel('TPR %') plt.legend() plt.show() print(nn_auc) from sklearn.linear_model import LinearRegression from sklearn.metrics import mean_squared_error, r2_score from yellowbrick.regressor import ResidualsPlot Y = [] X = [] count1 = 0 count2 = 0 for i in range(len(test_probs_weighted)): count1 += test_probs_weighted[i] count2 += y_test[i] X.append(count1) Y.append(count2) count1 = 0 count2 = 0 print(Y[0:10]) X = np.array(X) X = X.reshape(-1,1) lin = LinearRegression().fit(X,Y) print(lin.score(X,Y)) lpreds = lin.predict(X) print('Coeffs') print(lin.coef_) print(mean_squared_error(Y,lpreds)) print(r2_score(Y,lpreds)) visualizer = ResidualsPlot(lin) visualizer.fit(X,Y) visualizer.score(X,lpreds) visualizer.show()
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2.096182
5,552
#!/usr/bin/env python # # Copyright 2014 - 2018 The BCE Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the license.txt file. # import bce.parser.interface.printer as _interface_printer class SubstituteError(Exception): """Molecule substitution error.""" pass class MoleculeParserInterface: """Interface for math expression parsers.""" def __init__(self): """Initialize.""" pass # noinspection PyMethodMayBeStatic def parse_expression( self, expression, options, mexp_protected_header_enabled=False, mexp_protected_header_prefix="X" ): """Parse an expression. :type expression: str :type options: bce.option.Option :type mexp_protected_header_enabled: bool :type mexp_protected_header_prefix: str :param expression: The expression. :param options: The options. :param mexp_protected_header_enabled: Whether the MEXP protected headers are enabled. :param mexp_protected_header_prefix: The prefix of the MEXP protected headers. :rtype : bce.parser.ast.molecule.ASTNodeMolecule | bce.parser.ast.molecule.ASTNodeHydrateGroup :return: The root node of the AST. """ raise RuntimeError("parse_expression() method should be overrided.") # noinspection PyMethodMayBeStatic def parse_ast( self, expression, ast_root, option, mexp_protected_header_enabled=False, mexp_protected_header_prefix="X" ): """Parse an AST. :type expression: str :type ast_root: bce.parser.ast.molecule.ASTNodeMolecule | bce.parser.ast.molecule.ASTNodeHydrateGroup :type option: bce.option.Option :type mexp_protected_header_enabled: bool :type mexp_protected_header_prefix: str :param expression: The expression. :param ast_root: The root node of the AST. :param option: The options. :param mexp_protected_header_enabled: Whether the MEXP protected headers are enabled. :param mexp_protected_header_prefix: The prefix of the MEXP protected headers. :rtype : dict :return: The parsed element dictionary. """ raise RuntimeError("parse_ast() method should be overrided.") # noinspection PyMethodMayBeStatic def substitute(self, ast_root, substitute_map=None): """Substitute a ast_root. :type ast_root: bce.parser.ast.molecule.ASTNodeMolecule | bce.parser.ast.molecule.ASTNodeHydrateGroup :type substitute_map: dict | None :param ast_root: The ast_root. :param substitute_map: The substitution map. :rtype : bce.parser.ast.molecule.ASTNodeMolecule | bce.parser.ast.molecule.ASTNodeHydrateGroup | None :return: The substituted AST root node. """ raise RuntimeError("substitute() method should be overrided.") # noinspection PyMethodMayBeStatic def print_out( self, ast_root, mexp_parser, mexp_protected_header_enabled=False, mexp_protected_header_prefix="X", printer_type=_interface_printer.PRINTER_TYPE_TEXT ): """Print a molecule. :type ast_root: bce.parser.ast.molecule.ASTNodeMolecule | bce.parser.ast.molecule.ASTNodeHydrateGroup :type mexp_parser: bce.parser.interface.mexp_parser.MathExpressionParserInterface :type mexp_protected_header_enabled: bool :type mexp_protected_header_prefix: str :type printer_type: int :param ast_root: The AST root. :param printer_type: The printer type. :param mexp_parser: The math expression parser. :param mexp_protected_header_enabled: Whether the MEXP protected headers are enabled. :param mexp_protected_header_prefix: The prefix of the MEXP protected headers. :rtype : str | bce.dom.mathml.all.Base :return: The printed string or MathML object. """ raise RuntimeError("print_out() method should be overrided.")
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62, 448, 3419, 2446, 815, 307, 23170, 1384, 19570, 198 ]
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from moto.core.exceptions import JsonRESTError class NoSuchBucketException(JsonRESTError): """We are *only* validating that there is value that is not '' here.""" code = 400 class InvalidSNSTopicARNException(JsonRESTError): """We are *only* validating that there is value that is not '' here.""" code = 400
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# File: generators.py # Description: Examples on how to create and use generators in Python # Environment: PyCharm and Anaconda environment # # MIT License # Copyright (c) 2018 Valentyn N Sichkar # github.com/sichkar-valentyn # # Reference to: # [1] Valentyn N Sichkar. Examples on how to create and use generators in Python // GitHub platform [Electronic resource]. URL: https://github.com/sichkar-valentyn/Generators_in_Python (date of access: XX.XX.XXXX) from random import random # Creating the class for iterations # We add the method __iter__ if we want to iterate this class # Creating function as generator # Instead of return we use yield # In this way we remember the order till yield each time we call the function # Creating instance of class gen = random_generator(3) print(type(gen)) for i in gen: print(i) # More clear example about remembering the yield the order g = simple_gen() x = next(g) print(x) y = next(g) print(y) z = next(g) # Implementing the task - creating the methods for prime numbers
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#!/usr/bin/env python """ Loading data from Excel files stored at /src/data. """ # Copyright (c) 2014, Pavlo Bazilinskyy <[email protected]> # Department of Computer Science, National University of Ireland, Maynooth # # 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. __author__ = "Pavlo Bazilinskyy" __copyright__ = "Copyright 2008, National University of Ireland, Maynooth" __credits__ = "Ronan Reilly" __version__ = "1.0" __maintainer__ = "Pavlo Bazilinskyy" __email__ = "[email protected]" __status__ = "Production" import traceback from xlrd import open_workbook, cellname import csv import model import conf import random
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3.517021
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from django.urls import path, include from django.contrib import admin from django.contrib.auth import views from authentication.views import HomeView urlpatterns = [ path('admin/', admin.site.urls), path('', HomeView.as_view(), name='home'), path('auth/', include('authentication.urls')), path('', include('dashboard.urls')), ]
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2.982759
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from arbitrary_dateparser.dateparser import *
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3.916667
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import csv import os import time from selenium.webdriver.support.select import Select from Data.parameters import Data from filenames import file_extention from get_dir import pwd from reuse_func import GetData
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3.566667
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########################################################################################### # # # ObjectTracker 2.0 # # # ########################################################################################### # # # with ObjectTracker you can track the last updated time from any object in HA # # options are to give the last time an object was updated or the time that has gone by # # you have to set the following options in the appdaemon.cfg: # # # # object_type = the type you like to track (switch, input_boolean, sensor, etc) # # time_gone_by = True or False (false for showing last updated time) # # dir_name = the name of the directory you want the files with times saved # # time_format = any timeformat you like (python strftime type) without % # # H:M gives 01:27, Y-m-d H:M:S gives 2016-09-04 01:27:25, etc. # # total_objects = the amount off object you want to track # # object1 = HA entity_ID without the platform part. (for switch.light1 use light1) # # object2 = ... # # object3 = untill you reached youre total_object amount # # # # note that you need to set a new sections in the cfg for each type of object you like # # to track. if you want to track 1 switch and 1 sensor you need to make to sections. # # # # ObjectTracker depends on general_app_functions.py set as app and set in the cfg as # # [generalvars] # # # # Rene Tode ( [email protected] ) # # version 2.0 # # 2016/09/04 Germany # # # ########################################################################################### import appdaemon.plugins.hass.hassapi as hass import datetime
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import cv2 import mediapipe as mp mp_drawing = mp.solutions.drawing_utils # mp_drawing_styles = mp.solutions.drawing_styles mp_face_mesh = mp.solutions.face_mesh # for webcam input: if __name__ == '__main__': main()
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# Designed by Andy OConnell <[email protected]> <[email protected]> class CacheRow(object): """This represents a row of cache. Instance Variables Slot : middle 4 bits Valid : If the row is real data Tag : left 4 Bits Data : 16 Bytes of information from memory Dirty : is true if any data has been changed """
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from ckeditor.fields import RichTextFormField from django import forms from django.conf import settings from django.contrib.auth.models import User from django.db.models import Count from django.forms import ModelChoiceField from django.utils.module_loading import import_string from helpdesk.models import State, Comment, Ticket, Project from helpdesk.utils import DefaultProfile
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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- import uuid from msrest.pipeline import ClientRawResponse from msrestazure.azure_exceptions import CloudError from msrest.polling import LROPoller, NoPolling from msrestazure.polling.arm_polling import ARMPolling from .. import models class WorkspacesOperations(object): """WorkspacesOperations operations. :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = models def list_link_targets( self, custom_headers=None, raw=False, **operation_config): """Get a list of workspaces which the current user has administrator privileges and are not associated with an Azure Subscription. The subscriptionId parameter in the Url is ignored. :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: list or ClientRawResponse if raw=true :rtype: list[~azure.mgmt.loganalytics.models.LinkTarget] or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-03-20" # Construct URL url = self.list_link_targets.metadata['url'] path_format_arguments = { 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.get(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('[LinkTarget]', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized list_link_targets.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.OperationalInsights/linkTargets'} def get_schema( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Gets the schema for a given workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Log Analytics workspace name :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: SearchGetSchemaResponse or ClientRawResponse if raw=true :rtype: ~azure.mgmt.loganalytics.models.SearchGetSchemaResponse or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-03-20" # Construct URL url = self.get_schema.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.post(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('SearchGetSchemaResponse', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized get_schema.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/schema'} def get_search_results( self, resource_group_name, workspace_name, parameters, custom_headers=None, raw=False, polling=True, **operation_config): """Submit a search for a given workspace. The response will contain an id to track the search. User can use the id to poll the search status and get the full search result later if the search takes long time to finish. . :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Log Analytics workspace name :type workspace_name: str :param parameters: The parameters required to execute a search query. :type parameters: ~azure.mgmt.loganalytics.models.SearchParameters :param dict custom_headers: headers that will be added to the request :param bool raw: The poller return type is ClientRawResponse, the direct response alongside the deserialized response :param polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :return: An instance of LROPoller that returns SearchResultsResponse or ClientRawResponse<SearchResultsResponse> if raw==True :rtype: ~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.loganalytics.models.SearchResultsResponse] or ~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.loganalytics.models.SearchResultsResponse]] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ raw_result = self._get_search_results_initial( resource_group_name=resource_group_name, workspace_name=workspace_name, parameters=parameters, custom_headers=custom_headers, raw=True, **operation_config ) lro_delay = operation_config.get( 'long_running_operation_timeout', self.config.long_running_operation_timeout) if polling is True: polling_method = ARMPolling(lro_delay, **operation_config) elif polling is False: polling_method = NoPolling() else: polling_method = polling return LROPoller(self._client, raw_result, get_long_running_output, polling_method) get_search_results.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/search'} def update_search_results( self, resource_group_name, workspace_name, id, custom_headers=None, raw=False, **operation_config): """Gets updated search results for a given search query. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Log Analytics workspace name :type workspace_name: str :param id: The id of the search that will have results updated. You can get the id from the response of the GetResults call. :type id: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: SearchResultsResponse or ClientRawResponse if raw=true :rtype: ~azure.mgmt.loganalytics.models.SearchResultsResponse or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-03-20" # Construct URL url = self.update_search_results.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'id': self._serialize.url("id", id, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.post(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('SearchResultsResponse', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized update_search_results.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/search/{id}'} def purge( self, resource_group_name, workspace_name, table, filters, custom_headers=None, raw=False, polling=True, **operation_config): """Purges data in an Log Analytics workspace by a set of user-defined filters. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Log Analytics workspace name :type workspace_name: str :param table: Table from which to purge data. :type table: str :param filters: The set of columns and filters (queries) to run over them to purge the resulting data. :type filters: list[~azure.mgmt.loganalytics.models.WorkspacePurgeBodyFilters] :param dict custom_headers: headers that will be added to the request :param bool raw: The poller return type is ClientRawResponse, the direct response alongside the deserialized response :param polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :return: An instance of LROPoller that returns object or ClientRawResponse<object> if raw==True :rtype: ~msrestazure.azure_operation.AzureOperationPoller[object] or ~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[object]] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ raw_result = self._purge_initial( resource_group_name=resource_group_name, workspace_name=workspace_name, table=table, filters=filters, custom_headers=custom_headers, raw=True, **operation_config ) lro_delay = operation_config.get( 'long_running_operation_timeout', self.config.long_running_operation_timeout) if polling is True: polling_method = ARMPolling(lro_delay, **operation_config) elif polling is False: polling_method = NoPolling() else: polling_method = polling return LROPoller(self._client, raw_result, get_long_running_output, polling_method) purge.metadata = {'url': '/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/purge'} def disable_intelligence_pack( self, resource_group_name, workspace_name, intelligence_pack_name, custom_headers=None, raw=False, **operation_config): """Disables an intelligence pack for a given workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param intelligence_pack_name: The name of the intelligence pack to be disabled. :type intelligence_pack_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: None or ClientRawResponse if raw=true :rtype: None or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.disable_intelligence_pack.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'intelligencePackName': self._serialize.url("intelligence_pack_name", intelligence_pack_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.post(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp if raw: client_raw_response = ClientRawResponse(None, response) return client_raw_response disable_intelligence_pack.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/intelligencePacks/{intelligencePackName}/Disable'} def enable_intelligence_pack( self, resource_group_name, workspace_name, intelligence_pack_name, custom_headers=None, raw=False, **operation_config): """Enables an intelligence pack for a given workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param intelligence_pack_name: The name of the intelligence pack to be enabled. :type intelligence_pack_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: None or ClientRawResponse if raw=true :rtype: None or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.enable_intelligence_pack.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'intelligencePackName': self._serialize.url("intelligence_pack_name", intelligence_pack_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.post(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp if raw: client_raw_response = ClientRawResponse(None, response) return client_raw_response enable_intelligence_pack.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/intelligencePacks/{intelligencePackName}/Enable'} def list_intelligence_packs( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Lists all the intelligence packs possible and whether they are enabled or disabled for a given workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: list or ClientRawResponse if raw=true :rtype: list[~azure.mgmt.loganalytics.models.IntelligencePack] or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.list_intelligence_packs.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.get(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('[IntelligencePack]', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized list_intelligence_packs.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/intelligencePacks'} def get_shared_keys( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Gets the shared keys for a workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: SharedKeys or ClientRawResponse if raw=true :rtype: ~azure.mgmt.loganalytics.models.SharedKeys or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.get_shared_keys.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.post(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('SharedKeys', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized get_shared_keys.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/sharedKeys'} def list_usages( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Gets a list of usage metrics for a workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: An iterator like instance of UsageMetric :rtype: ~azure.mgmt.loganalytics.models.UsageMetricPaged[~azure.mgmt.loganalytics.models.UsageMetric] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Deserialize response deserialized = models.UsageMetricPaged(internal_paging, self._deserialize.dependencies) if raw: header_dict = {} client_raw_response = models.UsageMetricPaged(internal_paging, self._deserialize.dependencies, header_dict) return client_raw_response return deserialized list_usages.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/usages'} def list_management_groups( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Gets a list of management groups connected to a workspace. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: An iterator like instance of ManagementGroup :rtype: ~azure.mgmt.loganalytics.models.ManagementGroupPaged[~azure.mgmt.loganalytics.models.ManagementGroup] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Deserialize response deserialized = models.ManagementGroupPaged(internal_paging, self._deserialize.dependencies) if raw: header_dict = {} client_raw_response = models.ManagementGroupPaged(internal_paging, self._deserialize.dependencies, header_dict) return client_raw_response return deserialized list_management_groups.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}/managementGroups'} def list_by_resource_group( self, resource_group_name, custom_headers=None, raw=False, **operation_config): """Gets workspaces in a resource group. :param resource_group_name: The name of the resource group to get. The name is case insensitive. :type resource_group_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: An iterator like instance of Workspace :rtype: ~azure.mgmt.loganalytics.models.WorkspacePaged[~azure.mgmt.loganalytics.models.Workspace] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Deserialize response deserialized = models.WorkspacePaged(internal_paging, self._deserialize.dependencies) if raw: header_dict = {} client_raw_response = models.WorkspacePaged(internal_paging, self._deserialize.dependencies, header_dict) return client_raw_response return deserialized list_by_resource_group.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces'} def list( self, custom_headers=None, raw=False, **operation_config): """Gets the workspaces in a subscription. :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: An iterator like instance of Workspace :rtype: ~azure.mgmt.loganalytics.models.WorkspacePaged[~azure.mgmt.loganalytics.models.Workspace] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Deserialize response deserialized = models.WorkspacePaged(internal_paging, self._deserialize.dependencies) if raw: header_dict = {} client_raw_response = models.WorkspacePaged(internal_paging, self._deserialize.dependencies, header_dict) return client_raw_response return deserialized list.metadata = {'url': '/subscriptions/{subscriptionId}/providers/Microsoft.OperationalInsights/workspaces'} def create_or_update( self, resource_group_name, workspace_name, parameters, custom_headers=None, raw=False, polling=True, **operation_config): """Create or update a workspace. :param resource_group_name: The resource group name of the workspace. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param parameters: The parameters required to create or update a workspace. :type parameters: ~azure.mgmt.loganalytics.models.Workspace :param dict custom_headers: headers that will be added to the request :param bool raw: The poller return type is ClientRawResponse, the direct response alongside the deserialized response :param polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :return: An instance of LROPoller that returns Workspace or ClientRawResponse<Workspace> if raw==True :rtype: ~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.loganalytics.models.Workspace] or ~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.loganalytics.models.Workspace]] :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ raw_result = self._create_or_update_initial( resource_group_name=resource_group_name, workspace_name=workspace_name, parameters=parameters, custom_headers=custom_headers, raw=True, **operation_config ) lro_delay = operation_config.get( 'long_running_operation_timeout', self.config.long_running_operation_timeout) if polling is True: polling_method = ARMPolling(lro_delay, **operation_config) elif polling is False: polling_method = NoPolling() else: polling_method = polling return LROPoller(self._client, raw_result, get_long_running_output, polling_method) create_or_update.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}'} def delete( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Deletes a workspace instance. :param resource_group_name: The resource group name of the workspace. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: None or ClientRawResponse if raw=true :rtype: None or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.delete.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.delete(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200, 204]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp if raw: client_raw_response = ClientRawResponse(None, response) return client_raw_response delete.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}'} def get( self, resource_group_name, workspace_name, custom_headers=None, raw=False, **operation_config): """Gets a workspace instance. :param resource_group_name: The resource group name of the workspace. :type resource_group_name: str :param workspace_name: Name of the Log Analytics Workspace. :type workspace_name: str :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: Workspace or ClientRawResponse if raw=true :rtype: ~azure.mgmt.loganalytics.models.Workspace or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.get.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct and send request request = self._client.get(url, query_parameters) response = self._client.send(request, header_parameters, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('Workspace', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized get.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}'} def update( self, resource_group_name, workspace_name, parameters, custom_headers=None, raw=False, **operation_config): """Updates a workspace. :param resource_group_name: The resource group name of the workspace. :type resource_group_name: str :param workspace_name: The name of the workspace. :type workspace_name: str :param parameters: The parameters required to patch a workspace. :type parameters: ~azure.mgmt.loganalytics.models.Workspace :param dict custom_headers: headers that will be added to the request :param bool raw: returns the direct response alongside the deserialized response :param operation_config: :ref:`Operation configuration overrides<msrest:optionsforoperations>`. :return: Workspace or ClientRawResponse if raw=true :rtype: ~azure.mgmt.loganalytics.models.Workspace or ~msrest.pipeline.ClientRawResponse :raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>` """ api_version = "2015-11-01-preview" # Construct URL url = self.update.metadata['url'] path_format_arguments = { 'resourceGroupName': self._serialize.url("resource_group_name", resource_group_name, 'str'), 'workspaceName': self._serialize.url("workspace_name", workspace_name, 'str', max_length=63, min_length=4, pattern=r'^[A-Za-z0-9][A-Za-z0-9-]+[A-Za-z0-9]$'), 'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str') } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} header_parameters['Content-Type'] = 'application/json; charset=utf-8' if self.config.generate_client_request_id: header_parameters['x-ms-client-request-id'] = str(uuid.uuid1()) if custom_headers: header_parameters.update(custom_headers) if self.config.accept_language is not None: header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str') # Construct body body_content = self._serialize.body(parameters, 'Workspace') # Construct and send request request = self._client.patch(url, query_parameters) response = self._client.send( request, header_parameters, body_content, stream=False, **operation_config) if response.status_code not in [200]: exp = CloudError(response) exp.request_id = response.headers.get('x-ms-request-id') raise exp deserialized = None if response.status_code == 200: deserialized = self._deserialize('Workspace', response) if raw: client_raw_response = ClientRawResponse(deserialized, response) return client_raw_response return deserialized update.metadata = {'url': '/subscriptions/{subscriptionId}/resourcegroups/{resourceGroupName}/providers/Microsoft.OperationalInsights/workspaces/{workspaceName}'}
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import numpy as np import torch
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"""A command line interface that exposes softlearning examples to user. run_example_* methods, which run the experiments by invoking `tune.run_experiments` function. """ import click import sys sys.path.append('./') from examples.instrument import run_example_local @click.group() @cli.command( name='run_local', context_settings={'ignore_unknown_options': True}) @click.argument("example_module_name", required=True, type=str) @click.argument('example_argv', nargs=-1, type=click.UNPROCESSED) cli.add_command(run_example_local_cmd) if __name__ == "__main__": main()
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# Generated by Django 3.2.5 on 2021-07-31 21:18 from django.db import migrations, models
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#!/usr/bin/env python # Python imports import collections # Project imports import util import util_date NAMESPACE = 'LivingResources' DATE_RANGE = util_date.DATES[NAMESPACE] """ LivingResources data has 3 top-level categories (programs) -- Tidal Plankton Data, Tidal Benthic Data, and Nontidal Benthic Data. """ # https://data.chesapeakebay.net/api.json/LivingResources/Programs programs = util.download_and_jsonify(NAMESPACE, 'Programs') program_ids = sorted([d['ProgramId'] for d in programs]) # [{ # "ProgramId": "TidalPlankton", # "ProgramIdentifier": "TPD", # "ProgramName": "Tidal Plankton Data" # }, { # "ProgramId": "TidalBenthic", # "ProgramIdentifier": "TBD", # "ProgramName": "Tidal Benthic Data" # }, { # "ProgramId": "NontidalBenthic", # "ProgramIdentifier": "NBD", # "ProgramName": "Nontidal Benthic Data" # }] # Each of the 3 programs requires some study to understand and download properly. I doubt # they'll add/delete/change programs, but if they do, this code might break. That being the case, I # check here to ensure that the programs are what I expect them to be, and fail loudly if not. expected_program_ids = sorted(('TidalPlankton', 'TidalBenthic', 'NontidalBenthic')) if program_ids != expected_program_ids: print('Received programs: ' + ', '.join(program_ids)) print('Expected programs: ' + ', '.join(expected_program_ids)) raise ValueError('Unexpected or missing program(s)') # Each of the 3 programs has a number of different data types. They all behave the same, except # for /TidalPlankton/Station which requires special handling. I handle it here. # https://data.chesapeakebay.net/api.json/LivingResources/TidalPlankton/GeographicalAttributes geographical_types = util.download_and_jsonify(NAMESPACE, 'TidalPlankton', 'GeographicalAttributes') # The last two elements of the DataTypes URL seem backwards to me but that's what they are. # https://data.chesapeakebay.net/api.json/LivingResources/DataTypes/TidalPlankton data_types = util.download_and_jsonify(NAMESPACE, 'DataTypes', 'TidalPlankton') data_type_ids = [d['DataTypeId'] for d in data_types] # For TidalPlankton, geographical_types is a dicts of lists keyed by data type. Simplify. # ref: LivingResources.js (line 67) temp_geographical_types = collections.defaultdict(list) for data_type_id in data_type_ids: temp_geographical_types[data_type_id] = [d['GeoTypeId'] for d in geographical_types[data_type_id]] geographical_types = temp_geographical_types # geographical_types is now a dict like this -- # {'MonitorEvent': ['HUC8', 'HUC12', 'FIPS', 'CBSeg2003', 'Station'], # 'Reported': ['HUC8', 'HUC12', 'FIPS', 'CBSeg2003', 'Station'], # 'Station': ['HUC8', 'HUC12', 'FIPS', 'CBSeg2003', 'SegmentShed2009', 'Station']} # First handle program == TidalPlankton, geo type == Station for geographical_type_id in geographical_types['Station']: attributes = util.download_and_jsonify(NAMESPACE, 'TidalPlankton', 'Station', geographical_type_id) attribute_ids = util.extract_attribute_ids(geographical_type_id, attributes) attribute_ids = map(str, attribute_ids) if geographical_type_id == 'FIPS': # FIPS works differently than other geo types (why?) and requires POSTing data rather # than simple GETs. for attribute_id in attribute_ids: # e.g. https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/Station/FIPS util.post_single_attribute_id(attribute_id, NAMESPACE, 'TidalPlankton', 'Station', geographical_type_id) else: # e.g. https://data.chesapeakebay.net/api.json/LivingResources/TidalPlankton/Station/HUC8/ for attribute_id in attribute_ids: # e.g. https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/Station/HUC8/20 util.download(NAMESPACE, 'TidalPlankton', 'Station', geographical_type_id, attribute_id) # Remove Station since it was handled above data_type_ids = [data_type_id for data_type_id in data_type_ids if data_type_id != 'Station'] # https://data.chesapeakebay.net/api.json/LivingResources/Projects/TidalPlankton projects = util.download_and_jsonify(NAMESPACE, 'Projects', 'TidalPlankton') project_ids = [str(d['ProjectId']) for d in projects] # At this point, data_type_ids should be just ('MonitorEvent', 'Reported') for data_type_id in data_type_ids: for project_id in project_ids: for geographical_type_id in geographical_types[data_type_id]: # e.g. https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/MonitorEvent/1-16-1984/4-4-2017/9/HUC12 attributes = util.download_and_jsonify(NAMESPACE, 'TidalPlankton', data_type_id, DATE_RANGE.start.url_format, DATE_RANGE.end.url_format, project_id, geographical_type_id) attribute_ids = util.extract_attribute_ids(geographical_type_id, attributes) attribute_ids = map(str, attribute_ids) for attribute_id in attribute_ids: # e.g. https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/MonitorEvent/1-16-1984/4-4-2017/9/HUC12/767 util.download(NAMESPACE, 'TidalPlankton', data_type_id, DATE_RANGE.start.url_format, DATE_RANGE.end.url_format, project_id, geographical_type_id, attribute_id) # OK, that takes care of all 3 TidalPlankton data types. Remove TidalPlankton since it's been # handled. program_ids = [program_id for program_id in program_ids if program_id != 'TidalPlankton'] # And now for the remaining programs. At this point, program_ids should be just this -- # ('NontidalBenthic', 'TidalBenthic') for program_id in program_ids: print('Starting program {}...'.format(program_id)) # e.g. https://data.chesapeakebay.net/api.json/LivingResources/DataTypes/TidalBenthic data_types = util.download_and_jsonify(NAMESPACE, 'DataTypes', program_id) data_type_ids = [d['DataTypeId'] for d in data_types] # e.g. https://data.chesapeakebay.net/api.json/LivingResources/NontidalBenthic/GeographicalAttributes geographical_types = util.download_and_jsonify(NAMESPACE, program_id, 'GeographicalAttributes') geographical_type_ids = [d['GeoTypeId'] for d in geographical_types] for data_type_id in data_type_ids: print('Starting program {}, data type {}...'.format(program_id, data_type_id)) # e.g. https://data.chesapeakebay.net/api.json/LivingResources/Projects/TidalBenthic projects = util.download_and_jsonify(NAMESPACE, 'Projects', program_id) project_ids = [str(d['ProjectId']) for d in projects] for project_id in project_ids: params = (program_id, data_type_id, project_id) print('Starting program {}, data type {}, project {}...'.format(*params)) for geographical_type_id in geographical_type_ids: params = (program_id, data_type_id, project_id, geographical_type_id) print('Starting program {}, data type {}, project {}, geo type {}...'.format(*params)) # geographical_type_id is something like HUC8, FIPS, etc. # https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/MonitorEvent/4-4-2012/4-4-2017/17/HUC12 attributes = util.download_and_jsonify(NAMESPACE, program_id, data_type_id, DATE_RANGE.start.url_format, DATE_RANGE.end.url_format, project_id, geographical_type_id) attribute_ids = util.extract_attribute_ids(geographical_type_id, attributes) attribute_ids = map(str, attribute_ids) for attribute_id in attribute_ids: if (NAMESPACE == 'LivingResources') and (program_id == 'TidalBenthic') and \ (data_type_id == 'WaterQuality') and (geographical_type_id == 'Station'): # This is broken on the server side, skip for now. pass else: # e.g. https://data.chesapeakebay.net/api.JSON/LivingResources/TidalPlankton/MonitorEvent/4-4-2012/4-4-2017/17/HUC12/781 util.download(NAMESPACE, program_id, data_type_id, DATE_RANGE.start.url_format, DATE_RANGE.end.url_format, project_id, geographical_type_id, attribute_id)
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import csv import json from flask import Flask from flask import Response from flask import request from flask import render_template from flask.ext.triangle import Triangle import data.database_commands as database_commands app = Flask(__name__) Triangle(app) @app.route("/") @app.route("/tweets") # @app.route("/tweets") # def root(): # handle = request.args.get('handle') # tweets = database_commands.get_tweet_by_handle(handle) # data = 'handle,timestamp,data_type,data_id,status,tweet_text<br>' # for tweet in tweets: # data += str(tweet.twitter_handle) + "," # data += str(tweet.tweet_time) + "," # data += str(tweet.data_type) + "," # data += str(tweet.data_id) + "," # data += str(tweet.status) + "," # data += str(tweet.tweet_text) # data += '<br>' # return data @app.route("/export") if __name__ == '__main__': app.run( host= '0.0.0.0', debug=True, port=8080 )
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# -*- coding: utf-8 -*- import os import json from simmate.workflow_engine import ErrorHandler from simmate.calculators.vasp.inputs import Incar class RotationNonIntMatrix(ErrorHandler): """ This a simple error handler that is active when VASP finds an issue with the rotation matrix. """ is_monitor = True filename_to_check = "vasp.out" possible_error_messages = [ "Found some non-integer element in rotation matrix", "SGRCON", ]
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import sys import argparse import darshan if __name__ == "__main__": main()
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"""Main class for the Crownstone cloud cloud.""" from __future__ import annotations import asyncio import logging import aiohttp from crownstone_cloud.cloud_models.crownstones import Crownstone from crownstone_cloud.cloud_models.spheres import Spheres from crownstone_cloud.exceptions import CrownstoneNotFoundError from crownstone_cloud.helpers.conversion import password_to_hash from crownstone_cloud.helpers.requests import RequestHandler _LOGGER = logging.getLogger(__name__) class CrownstoneCloud: """Create a Crownstone cloud instance.""" cloud_data: Spheres access_token: str async def async_initialize(self) -> None: """ Login to Crownstone API & synchronize all cloud data. This method is a coroutine. """ # Login login_response = await self.request_handler.request_login(self.login_data) # Save access token & create cloud data object self.access_token = login_response["id"] self.cloud_data = Spheres(self, login_response["userId"]) _LOGGER.debug("Login to Crownstone Cloud successful") # Synchronize data await self.async_synchronize() async def async_synchronize(self) -> None: """ Sync all data from cloud. This method is a coroutine. """ _LOGGER.debug("Initiating all cloud data") # get the sphere data for this user_id await self.cloud_data.async_update_sphere_data() # get the data from the sphere attributes for sphere in self.cloud_data: await asyncio.gather( sphere.async_update_sphere_presence(), sphere.crownstones.async_update_crownstone_data(), sphere.locations.async_update_location_data(), sphere.locations.async_update_location_presence(), sphere.users.async_update_user_data(), ) _LOGGER.debug("Cloud data successfully initialized") def get_crownstone( self, crownstone_name: str, sphere_id: str | None = None ) -> Crownstone: """ Get a Crownstone object by providing the name and optionally a sphere id. :param crownstone_name: Name of the Crownstone. :param sphere_id: Sphere id that should match. :return: Crownstone object. """ for sphere in self.cloud_data: if sphere_id is not None: if sphere.cloud_id != sphere_id: continue for crownstone in sphere.crownstones: if crownstone.name == crownstone_name: return crownstone raise CrownstoneNotFoundError from None def get_crownstone_by_id( self, crownstone_id: str, sphere_id: str | None = None ) -> Crownstone: """ Get a Crownstone object by providing the id and optionally a sphere id. :param crownstone_id: The cloud id of the Crownstone. :param sphere_id: Sphere id that should match. :return: Crownstone object. """ for sphere in self.cloud_data: if sphere_id is not None: if sphere.cloud_id != sphere_id: continue for crownstone in sphere.crownstones: if crownstone.cloud_id == crownstone_id: return crownstone raise CrownstoneNotFoundError from None def get_crownstone_by_uid( self, crownstone_uid: int, sphere_id: str | None = None ) -> Crownstone: """ Get a Crownstone object by providing the uid and optionally a sphere id. :param crownstone_uid: The unique id of the Crownstone. :param sphere_id: Sphere id that should match. :return: Crownstone object. """ for sphere in self.cloud_data: if sphere_id is not None: if sphere.cloud_id != sphere_id: continue for crownstone in sphere.crownstones: if crownstone.unique_id == crownstone_uid: return crownstone raise CrownstoneNotFoundError from None async def async_close_session(self) -> None: """ Close the aiohttp clientsession after all requests are done. The session should always be closed when the program ends. When there's an external clientsession in use, DON'T use this method. This method is a coroutine. """ await self.request_handler.client_session.close()
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from corehq.apps.commtrack.models import SupplyPointCase from corehq.apps.products.models import Product from corehq.apps.locations.models import Location, SQLLocation from corehq.apps.domain.models import Domain from corehq.util.quickcache import quickcache from dimagi.utils.decorators.memoized import memoized from dimagi.utils.excel import flatten_json, json_to_headers from couchdbkit import ResourceNotFound from dimagi.utils.couch.loosechange import map_reduce from couchexport.writers import Excel2007ExportWriter from StringIO import StringIO from corehq.apps.consumption.shortcuts import get_loaded_default_monthly_consumption, build_consumption_dict def load_locs_json(domain, selected_loc_id=None, include_archived=False): """initialize a json location tree for drill-down controls on the client. tree is only partially initialized and branches will be filled in on the client via ajax. what is initialized: * all top level locs * if a 'selected' loc is provided, that loc and its complete ancestry """ loc_json = [ loc_to_json(loc) for loc in SQLLocation.root_locations( domain, include_archive_ancestors=include_archived ) ] # if a location is selected, we need to pre-populate its location hierarchy # so that the data is available client-side to pre-populate the drop-downs if selected_loc_id: selected = SQLLocation.objects.get( domain=domain, location_id=selected_loc_id ) lineage = selected.get_ancestors() parent = {'children': loc_json} for loc in lineage: # find existing entry in the json tree that corresponds to this loc this_loc = [k for k in parent['children'] if k['uuid'] == loc.location_id][0] this_loc['children'] = [ loc_to_json(loc) for loc in loc.child_locations(include_archive_ancestors=include_archived) ] parent = this_loc return loc_json def parent_child(domain): """ Returns a dict mapping from a location type to its possible child types """ return map_reduce(lambda (k, v): [(p, k) for p in v], data=dict(location_hierarchy_config(domain)).iteritems()) @quickcache(['domain'], timeout=60) def write_to_file(locations): """ locations = [ ('loc_type1', { 'headers': ['header1', 'header2', ...] 'rows': [ { 'header1': val1 'header2': val2 }, {...}, ] }) ] """ outfile = StringIO() writer = Excel2007ExportWriter() header_table = [(loc_type, [tab['headers']]) for loc_type, tab in locations] writer.open(header_table=header_table, file=outfile) for loc_type, tab in locations: headers = tab['headers'] tab_rows = [[row.get(header, '') for header in headers] for row in tab['rows']] writer.write([(loc_type, tab_rows)]) writer.close() return outfile.getvalue()
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2.461781
1,269
# Copyright 2017 The Forseti Security Authors. 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. """Enforcer runner. Usage for enforcing a single project's firewall: $ forseti_enforcer --enforce_project <project_id> \\ --policy_file <policy file path> """ import argparse import sys import threading from google.cloud.forseti.common.util import file_loader from google.cloud.forseti.common.util import logger from google.cloud.forseti.enforcer import batch_enforcer from google.cloud.forseti.enforcer import enforcer_log_pb2 LOGGER = logger.get_logger(__name__) class Error(Exception): """Base error class for the module.""" class InvalidParsedPolicyFileError(Error): """An invalid policy file was parsed.""" def initialize_batch_enforcer(global_configs, concurrent_threads, max_write_threads, max_running_operations, dry_run): """Initialize and return a BatchFirewallEnforcer object. Args: global_configs (dict): Global configurations. concurrent_threads (str): The number of parallel enforcement threads to execute. max_write_threads (str): The maximum number of enforcement threads that can be actively updating project firewalls. max_running_operations (str): [DEPRECATED] The maximum number of write operations per enforcement thread. dry_run (boolean): If True, will simply log what action would have been taken without actually applying any modifications. Returns: BatchFirewallEnforcer: A BatchFirewallEnforcer instance. """ if max_running_operations: LOGGER.warn('Deprecated argument max_running_operations set.') if max_write_threads: project_sema = threading.BoundedSemaphore(value=max_write_threads) else: project_sema = None enforcer = batch_enforcer.BatchFirewallEnforcer( global_configs=global_configs, dry_run=dry_run, concurrent_workers=concurrent_threads, project_sema=project_sema) return enforcer def enforce_single_project(enforcer, project_id, policy_filename): """Runs the enforcer on a single project. Args: enforcer (BatchFirewallEnforcer): An instance of the batch_enforcer.BatchFirewallEnforcer class. project_id (str): The project to enforce. policy_filename (str): The json encoded file to read the firewall policy from. Raises: InvalidParsedPolicyFileError: When the policy file can't be parsed. Returns: EnforcerLogProto: A instance of the proto. """ policy = file_loader.read_and_parse_file(policy_filename) if not isinstance(policy, list): raise InvalidParsedPolicyFileError( 'Invalid parsed policy file: found %s expected list' % type(policy)) project_policies = [(project_id, policy)] enforcer_results = enforcer.run(project_policies) for result in enforcer_results.results: result.gce_firewall_enforcement.policy_path = policy_filename result.run_context = enforcer_log_pb2.ENFORCER_ONE_PROJECT return enforcer_results def main(): """The main entry point for Forseti Security Enforcer runner.""" arg_parser = argparse.ArgumentParser() arg_parser.add_argument( '--forseti_config', default='/home/ubuntu/forseti-security/configs/' 'forseti_conf_server.yaml', help='Fully qualified path and filename of the Forseti config file.') arg_parser.add_argument( '--enforce_project', default=None, help='A single projectId to enforce the firewall on.' ' Must be used with the policy_file flag.') arg_parser.add_argument( '--policy_file', default=None, help='A json encoded policy file to enforce,' ' must contain a list of Firewall resources to' 'apply to the project. If in a GCS bucket, ' 'include full path, e.g. ' '"gs://<bucketname>/path/to/file".') arg_parser.add_argument( '--dry_run', default=False, help='If True will simulate the changes and not change' 'any policies.') arg_parser.add_argument( '--concurrent_threads', default=10, help='The number concurrent worker threads to use.') arg_parser.add_argument( '--maximum_firewall_write_operations', default=10, help='The maximum number of in flight write operations' 'on project firewalls. Each running thread is ' 'allowed up to this many running operations, ' 'so to limit the over all number of operations, ' 'limit the number of write threads using the' ' maximum_project_writer_threads flag.') arg_parser.add_argument( '--maximum_project_writer_threads', default=1, help='The maximum number of projects with active write ' 'operations on project firewalls.') flags = vars(arg_parser.parse_args()) forseti_config = flags['forseti_config'] if forseti_config is None: LOGGER.error('Path to Forseti Security config needs to be specified.') sys.exit() try: configs = file_loader.read_and_parse_file(forseti_config) except IOError: LOGGER.exception('Unable to open Forseti Security config file. ' 'Please check your path and filename and try again.') sys.exit() global_configs = configs.get('global') enforcer = initialize_batch_enforcer( global_configs, flags['concurrent_threads'], flags['maximum_project_writer_threads'], flags['maximum_firewall_write_operations'], flags['dry_run'] ) if flags['enforce_project'] and flags['policy_file']: enforcer_results = enforce_single_project(enforcer, flags['enforce_project'], flags['policy_file']) print enforcer_results else: print 'Batch mode not implemented yet.' if __name__ == '__main__': main()
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2.592421
2,586
from django.conf import settings from django.conf.urls import url, include urlpatterns = [] if 'admin_tools.menu' in settings.INSTALLED_APPS: urlpatterns.append(url(r'^menu/', include('admin_tools.menu.urls'))) if 'admin_tools.dashboard' in settings.INSTALLED_APPS: urlpatterns.append( url(r'^dashboard/', include('admin_tools.dashboard.urls')) )
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2.591549
142
from app.models.Note.note import Note from app.models.Message.message import Message from app.models.User.user import User from app.models.Analytics.analytics import Analytics from app.models.Benefits.benefits import Benefits from app.models.KeyManagement.key_management import KeyManagement from app.models.PaidTimeOff.paid_time_off import PaidTimeOff from app.models.Pay.pay import Pay from app.models.Performance.performance import Performance from app.models.Retirement.retirement import Retirement from app.models.Schedule.schedule import Schedule from app.models.WorkInfo.work_info import WorkInfo import app.signals
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3.839506
162
# Copyright (c) 2018 Cisco and/or its affiliates. # 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. """DUT setup library.""" from robot.api import logger from resources.libraries.python.Constants import Constants from resources.libraries.python.ssh import SSH, exec_cmd_no_error from resources.libraries.python.topology import NodeType, Topology class DUTSetup(object): """Contains methods for setting up DUTs.""" @staticmethod def get_service_logs(node, service): """Get specific service unit logs from node. :param node: Node in the topology. :param service: Service unit name. :type node: dict :type service: str """ if DUTSetup.running_in_container(node): command = ('echo $(< /var/log/supervisord.log);' 'echo $(< /tmp/*supervisor*.log)') else: command = ('journalctl --no-pager --unit={name} ' '--since="$(echo `systemctl show -p ' 'ActiveEnterTimestamp {name}` | ' 'awk \'{{print $2 $3}}\')"'. format(name=service)) message = 'Node {host} failed to get logs from unit {name}'.\ format(host=node['host'], name=service) exec_cmd_no_error(node, command, timeout=30, sudo=True, message=message) @staticmethod def get_service_logs_on_all_duts(nodes, service): """Get specific service unit logs from all DUTs. :param nodes: Nodes in the topology. :param service: Service unit name. :type nodes: dict :type service: str """ for node in nodes.values(): if node['type'] == NodeType.DUT: DUTSetup.get_service_logs(node, service) @staticmethod def restart_service(node, service): """Restart the named service on node. :param node: Node in the topology. :param service: Service unit name. :type node: dict :type service: str """ if DUTSetup.running_in_container(node): command = 'supervisorctl restart {name}'.format(name=service) else: command = 'service {name} restart'.format(name=service) message = 'Node {host} failed to restart service {name}'.\ format(host=node['host'], name=service) exec_cmd_no_error( node, command, timeout=180, sudo=True, message=message) DUTSetup.get_service_logs(node, service) @staticmethod def restart_service_on_all_duts(nodes, service): """Restart the named service on all DUTs. :param node: Nodes in the topology. :param service: Service unit name. :type node: dict :type service: str """ for node in nodes.values(): if node['type'] == NodeType.DUT: DUTSetup.restart_service(node, service) @staticmethod def start_service(node, service): """Start up the named service on node. :param node: Node in the topology. :param service: Service unit name. :type node: dict :type service: str """ # TODO: change command to start once all parent function updated. if DUTSetup.running_in_container(node): command = 'supervisorctl restart {name}'.format(name=service) else: command = 'service {name} restart'.format(name=service) message = 'Node {host} failed to start service {name}'.\ format(host=node['host'], name=service) exec_cmd_no_error( node, command, timeout=180, sudo=True, message=message) DUTSetup.get_service_logs(node, service) @staticmethod def start_service_on_all_duts(nodes, service): """Start up the named service on all DUTs. :param node: Nodes in the topology. :param service: Service unit name. :type node: dict :type service: str """ for node in nodes.values(): if node['type'] == NodeType.DUT: DUTSetup.start_service(node, service) @staticmethod def stop_service(node, service): """Stop the named service on node. :param node: Node in the topology. :param service: Service unit name. :type node: dict :type service: str """ if DUTSetup.running_in_container(node): command = 'supervisorctl stop {name}'.format(name=service) else: command = 'service {name} stop'.format(name=service) message = 'Node {host} failed to stop service {name}'.\ format(host=node['host'], name=service) exec_cmd_no_error( node, command, timeout=180, sudo=True, message=message) DUTSetup.get_service_logs(node, service) @staticmethod def stop_service_on_all_duts(nodes, service): """Stop the named service on all DUTs. :param node: Nodes in the topology. :param service: Service unit name. :type node: dict :type service: str """ for node in nodes.values(): if node['type'] == NodeType.DUT: DUTSetup.stop_service(node, service) @staticmethod def get_vpp_pid(node): """Get PID of running VPP process. :param node: DUT node. :type node: dict :returns: PID :rtype: int :raises RuntimeError: If it is not possible to get the PID. """ ssh = SSH() ssh.connect(node) for i in range(3): logger.trace('Try {}: Get VPP PID'.format(i)) ret_code, stdout, stderr = ssh.exec_command('pidof vpp') if int(ret_code): raise RuntimeError('Not possible to get PID of VPP process ' 'on node: {0}\n {1}'. format(node['host'], stdout + stderr)) pid_list = stdout.split() if len(pid_list) == 1: return int(stdout) elif not pid_list: logger.debug("No VPP PID found on node {0}". format(node['host'])) continue else: logger.debug("More then one VPP PID found on node {0}". format(node['host'])) return [int(pid) for pid in pid_list] return None @staticmethod def get_vpp_pids(nodes): """Get PID of running VPP process on all DUTs. :param nodes: DUT nodes. :type nodes: dict :returns: PIDs :rtype: dict """ pids = dict() for node in nodes.values(): if node['type'] == NodeType.DUT: pids[node['host']] = DUTSetup.get_vpp_pid(node) return pids @staticmethod def crypto_device_verify(node, crypto_type, numvfs, force_init=False): """Verify if Crypto QAT device virtual functions are initialized on all DUTs. If parameter force initialization is set to True, then try to initialize or remove VFs on QAT. :param node: DUT node. :crypto_type: Crypto device type - HW_DH895xcc or HW_C3xxx. :param numvfs: Number of VFs to initialize, 0 - disable the VFs. :param force_init: If True then try to initialize to specific value. :type node: dict :type crypto_type: string :type numvfs: int :type force_init: bool :returns: nothing :raises RuntimeError: If QAT VFs are not created and force init is set to False. """ pci_addr = Topology.get_cryptodev(node) sriov_numvfs = DUTSetup.get_sriov_numvfs(node, pci_addr) if sriov_numvfs != numvfs: if force_init: # QAT is not initialized and we want to initialize with numvfs DUTSetup.crypto_device_init(node, crypto_type, numvfs) else: raise RuntimeError('QAT device failed to create VFs on {host}'. format(host=node['host'])) @staticmethod def crypto_device_init(node, crypto_type, numvfs): """Init Crypto QAT device virtual functions on DUT. :param node: DUT node. :crypto_type: Crypto device type - HW_DH895xcc or HW_C3xxx. :param numvfs: Number of VFs to initialize, 0 - disable the VFs. :type node: dict :type crypto_type: string :type numvfs: int :returns: nothing :raises RuntimeError: If failed to stop VPP or QAT failed to initialize. """ if crypto_type == "HW_DH895xcc": kernel_mod = "qat_dh895xcc" kernel_drv = "dh895xcc" elif crypto_type == "HW_C3xxx": kernel_mod = "qat_c3xxx" kernel_drv = "c3xxx" else: raise RuntimeError('Unsupported crypto device type on {host}'. format(host=node['host'])) pci_addr = Topology.get_cryptodev(node) # QAT device must be re-bound to kernel driver before initialization. DUTSetup.verify_kernel_module(node, kernel_mod, force_load=True) # Stop VPP to prevent deadlock. DUTSetup.stop_service(node, Constants.VPP_UNIT) current_driver = DUTSetup.get_pci_dev_driver( node, pci_addr.replace(':', r'\:')) if current_driver is not None: DUTSetup.pci_driver_unbind(node, pci_addr) # Bind to kernel driver. DUTSetup.pci_driver_bind(node, pci_addr, kernel_drv) # Initialize QAT VFs. if numvfs > 0: DUTSetup.set_sriov_numvfs(node, pci_addr, numvfs) @staticmethod def get_virtfn_pci_addr(node, pf_pci_addr, vf_id): """Get PCI address of Virtual Function. :param node: DUT node. :param pf_pci_addr: Physical Function PCI address. :param vf_id: Virtual Function number. :type node: dict :type pf_pci_addr: str :type vf_id: int :returns: Virtual Function PCI address. :rtype: int :raises RuntimeError: If failed to get Virtual Function PCI address. """ command = "sh -c "\ "'basename $(readlink /sys/bus/pci/devices/{pci}/virtfn{vf_id})'".\ format(pci=pf_pci_addr, vf_id=vf_id) message = 'Failed to get virtual function PCI address.' stdout, _ = exec_cmd_no_error(node, command, timeout=30, sudo=True, message=message) return stdout.strip() @staticmethod def get_sriov_numvfs(node, pf_pci_addr): """Get number of SR-IOV VFs. :param node: DUT node. :param pf_pci_addr: Physical Function PCI device address. :type node: dict :type pf_pci_addr: str :returns: Number of VFs. :rtype: int :raises RuntimeError: If PCI device is not SR-IOV capable. """ command = 'cat /sys/bus/pci/devices/{pci}/sriov_numvfs'.\ format(pci=pf_pci_addr.replace(':', r'\:')) message = 'PCI device {pci} is not a SR-IOV device.'.\ format(pci=pf_pci_addr) for _ in range(3): stdout, _ = exec_cmd_no_error(node, command, timeout=30, sudo=True, message=message) try: sriov_numvfs = int(stdout) except ValueError: logger.trace('Reading sriov_numvfs info failed on {host}'. format(host=node['host'])) else: return sriov_numvfs @staticmethod def set_sriov_numvfs(node, pf_pci_addr, numvfs=0): """Init or reset SR-IOV virtual functions by setting its number on PCI device on DUT. Setting to zero removes all VFs. :param node: DUT node. :param pf_pci_addr: Physical Function PCI device address. :param numvfs: Number of VFs to initialize, 0 - removes the VFs. :type node: dict :type pf_pci_addr: str :type numvfs: int :raises RuntimeError: Failed to create VFs on PCI. """ command = "sh -c "\ "'echo {num} | tee /sys/bus/pci/devices/{pci}/sriov_numvfs'".\ format(num=numvfs, pci=pf_pci_addr.replace(':', r'\:')) message = 'Failed to create {num} VFs on {pci} device on {host}'.\ format(num=numvfs, pci=pf_pci_addr, host=node['host']) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) @staticmethod def pci_driver_unbind(node, pci_addr): """Unbind PCI device from current driver on node. :param node: DUT node. :param pci_addr: PCI device address. :type node: dict :type pci_addr: str :raises RuntimeError: If PCI device unbind failed. """ command = "sh -c "\ "'echo {pci} | tee /sys/bus/pci/devices/{pcie}/driver/unbind'".\ format(pci=pci_addr, pcie=pci_addr.replace(':', r'\:')) message = 'Failed to unbind PCI device {pci} on {host}'.\ format(pci=pci_addr, host=node['host']) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) @staticmethod def pci_driver_bind(node, pci_addr, driver): """Bind PCI device to driver on node. :param node: DUT node. :param pci_addr: PCI device address. :param driver: Driver to bind. :type node: dict :type pci_addr: str :type driver: str :raises RuntimeError: If PCI device bind failed. """ message = 'Failed to bind PCI device {pci} to {driver} on host {host}'.\ format(pci=pci_addr, driver=driver, host=node['host']) command = "sh -c "\ "'echo {driver} | tee /sys/bus/pci/devices/{pci}/driver_override'".\ format(driver=driver, pci=pci_addr.replace(':', r'\:')) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) command = "sh -c "\ "'echo {pci} | tee /sys/bus/pci/drivers/{driver}/bind'".\ format(pci=pci_addr, driver=driver) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) command = "sh -c "\ "'echo | tee /sys/bus/pci/devices/{pci}/driver_override'".\ format(pci=pci_addr.replace(':', r'\:')) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) @staticmethod def pci_vf_driver_unbind(node, pf_pci_addr, vf_id): """Unbind Virtual Function from driver on node. :param node: DUT node. :param pf_pci_addr: PCI device address. :param vf_id: Virtual Function ID. :type node: dict :type pf_pci_addr: str :type vf_id: int :raises RuntimeError: If Virtual Function unbind failed. """ vf_pci_addr = DUTSetup.get_virtfn_pci_addr(node, pf_pci_addr, vf_id) vf_path = "/sys/bus/pci/devices/{pf_pci_addr}/virtfn{vf_id}".\ format(pf_pci_addr=pf_pci_addr.replace(':', r'\:'), vf_id=vf_id) command = "sh -c "\ "'echo {vf_pci_addr} | tee {vf_path}/driver/unbind'".\ format(vf_pci_addr=vf_pci_addr, vf_path=vf_path) message = 'Failed to unbind VF {vf_pci_addr} to on {host}'.\ format(vf_pci_addr=vf_pci_addr, host=node['host']) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) @staticmethod def pci_vf_driver_bind(node, pf_pci_addr, vf_id, driver): """Bind Virtual Function to driver on node. :param node: DUT node. :param pf_pci_addr: PCI device address. :param vf_id: Virtual Function ID. :param driver: Driver to bind. :type node: dict :type pf_pci_addr: str :type vf_id: int :type driver: str :raises RuntimeError: If PCI device bind failed. """ vf_pci_addr = DUTSetup.get_virtfn_pci_addr(node, pf_pci_addr, vf_id) vf_path = "/sys/bus/pci/devices/{pf_pci_addr}/virtfn{vf_id}".\ format(pf_pci_addr=pf_pci_addr.replace(':', r'\:'), vf_id=vf_id) message = 'Failed to bind VF {vf_pci_addr} to {driver} on {host}'.\ format(vf_pci_addr=vf_pci_addr, driver=driver, host=node['host']) command = "sh -c "\ "'echo {driver} | tee {vf_path}/driver_override'".\ format(driver=driver, vf_path=vf_path) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) command = "sh -c "\ "'echo {vf_pci_addr} | tee /sys/bus/pci/drivers/{driver}/bind'".\ format(vf_pci_addr=vf_pci_addr, driver=driver) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) command = "sh -c "\ "'echo | tee {vf_path}/driver_override'".\ format(vf_path=vf_path) exec_cmd_no_error(node, command, timeout=120, sudo=True, message=message) @staticmethod def get_pci_dev_driver(node, pci_addr): """Get current PCI device driver on node. .. note:: # lspci -vmmks 0000:00:05.0 Slot: 00:05.0 Class: Ethernet controller Vendor: Red Hat, Inc Device: Virtio network device SVendor: Red Hat, Inc SDevice: Device 0001 PhySlot: 5 Driver: virtio-pci :param node: DUT node. :param pci_addr: PCI device address. :type node: dict :type pci_addr: str :returns: Driver or None :raises RuntimeError: If PCI rescan or lspci command execution failed. :raises RuntimeError: If it is not possible to get the interface driver information from the node. """ ssh = SSH() ssh.connect(node) for i in range(3): logger.trace('Try number {0}: Get PCI device driver'.format(i)) cmd = 'lspci -vmmks {0}'.format(pci_addr) ret_code, stdout, _ = ssh.exec_command(cmd) if int(ret_code): raise RuntimeError("'{0}' failed on '{1}'" .format(cmd, node['host'])) for line in stdout.splitlines(): if not line: continue name = None value = None try: name, value = line.split("\t", 1) except ValueError: if name == "Driver:": return None if name == 'Driver:': return value if i < 2: logger.trace('Driver for PCI device {} not found, executing ' 'pci rescan and retrying'.format(pci_addr)) cmd = 'sh -c "echo 1 > /sys/bus/pci/rescan"' ret_code, _, _ = ssh.exec_command_sudo(cmd) if int(ret_code) != 0: raise RuntimeError("'{0}' failed on '{1}'" .format(cmd, node['host'])) return None @staticmethod def verify_kernel_module(node, module, force_load=False): """Verify if kernel module is loaded on node. If parameter force load is set to True, then try to load the modules. :param node: Node. :param module: Module to verify. :param force_load: If True then try to load module. :type node: dict :type module: str :type force_load: bool :raises RuntimeError: If module is not loaded or failed to load. """ command = 'grep -w {module} /proc/modules'.format(module=module) message = 'Kernel module {module} is not loaded on host {host}'.\ format(module=module, host=node['host']) try: exec_cmd_no_error(node, command, timeout=30, sudo=False, message=message) except RuntimeError: if force_load: # Module is not loaded and we want to load it DUTSetup.load_kernel_module(node, module) else: raise @staticmethod def verify_kernel_module_on_all_duts(nodes, module, force_load=False): """Verify if kernel module is loaded on all DUTs. If parameter force load is set to True, then try to load the modules. :param node: DUT nodes. :param module: Module to verify. :param force_load: If True then try to load module. :type node: dict :type module: str :type force_load: bool """ for node in nodes.values(): if node['type'] == NodeType.DUT: DUTSetup.verify_kernel_module(node, module, force_load) @staticmethod def verify_uio_driver_on_all_duts(nodes): """Verify if uio driver kernel module is loaded on all DUTs. If module is not present it will try to load it. :param node: DUT nodes. :type node: dict """ for node in nodes.values(): if node['type'] == NodeType.DUT: uio_driver = Topology.get_uio_driver(node) DUTSetup.verify_kernel_module(node, uio_driver, force_load=True) @staticmethod def load_kernel_module(node, module): """Load kernel module on node. :param node: DUT node. :param module: Module to load. :type node: dict :type module: str :returns: nothing :raises RuntimeError: If loading failed. """ command = 'modprobe {module}'.format(module=module) message = 'Failed to load {module} on host {host}'.\ format(module=module, host=node['host']) exec_cmd_no_error(node, command, timeout=30, sudo=True, message=message) @staticmethod def install_vpp_on_all_duts(nodes, vpp_pkg_dir): """Install VPP on all DUT nodes. Start the VPP service in case of systemd is not available or does not support autostart. :param nodes: Nodes in the topology. :param vpp_pkg_dir: Path to directory where VPP packages are stored. :type nodes: dict :type vpp_pkg_dir: str :raises RuntimeError: If failed to remove or install VPP. """ for node in nodes.values(): message = 'Failed to install VPP on host {host}!'.\ format(host=node['host']) if node['type'] == NodeType.DUT: command = 'ln -s /dev/null /etc/sysctl.d/80-vpp.conf || true' exec_cmd_no_error(node, command, sudo=True) command = '. /etc/lsb-release; echo "${DISTRIB_ID}"' stdout, _ = exec_cmd_no_error(node, command) if stdout.strip() == 'Ubuntu': exec_cmd_no_error(node, 'apt-get purge -y "*vpp*" || true', timeout=120, sudo=True) exec_cmd_no_error(node, 'dpkg -i --force-all {dir}*.deb'. format(dir=vpp_pkg_dir), timeout=120, sudo=True, message=message) exec_cmd_no_error(node, 'dpkg -l | grep vpp', sudo=True) if DUTSetup.running_in_container(node): DUTSetup.restart_service(node, Constants.VPP_UNIT) else: exec_cmd_no_error(node, 'yum -y remove "*vpp*" || true', timeout=120, sudo=True) exec_cmd_no_error(node, 'rpm -ivh {dir}*.rpm'. format(dir=vpp_pkg_dir), timeout=120, sudo=True, message=message) exec_cmd_no_error(node, 'rpm -qai *vpp*', sudo=True) DUTSetup.restart_service(node, Constants.VPP_UNIT) @staticmethod def running_in_container(node): """This method tests if topology node is running inside container. :param node: Topology node. :type node: dict :returns: True if running in docker container, false if not or failed to detect. :rtype: bool """ command = "fgrep docker /proc/1/cgroup" message = 'Failed to get cgroup settings.' try: exec_cmd_no_error(node, command, timeout=30, sudo=False, message=message) except RuntimeError: return False return True @staticmethod def get_docker_mergeddir(node, uuid): """Get Docker overlay for MergedDir diff. :param node: DUT node. :param uuid: Docker UUID. :type node: dict :type uuid: str :returns: Docker container MergedDir. :rtype: str :raises RuntimeError: If getting output failed. """ command = "docker inspect --format='"\ "{{{{.GraphDriver.Data.MergedDir}}}}' {uuid}".format(uuid=uuid) message = 'Failed to get directory of {uuid} on host {host}'.\ format(uuid=uuid, host=node['host']) stdout, _ = exec_cmd_no_error(node, command, sudo=True, message=message) return stdout.strip() @staticmethod def get_huge_page_size(node): """Get default size of huge pages in system. :param node: Node in the topology. :type node: dict :returns: Default size of free huge pages in system. :rtype: int :raises RuntimeError: If reading failed for three times. """ ssh = SSH() ssh.connect(node) for _ in range(3): ret_code, stdout, _ = ssh.exec_command_sudo( "grep Hugepagesize /proc/meminfo | awk '{ print $2 }'") if ret_code == 0: try: huge_size = int(stdout) except ValueError: logger.trace('Reading huge page size information failed') else: break else: raise RuntimeError('Getting huge page size information failed.') return huge_size @staticmethod def get_huge_page_free(node, huge_size): """Get number of free huge pages in system. :param node: Node in the topology. :param huge_size: Size of hugepages. :type node: dict :type huge_size: int :returns: Number of free huge pages in system. :rtype: int :raises RuntimeError: If reading failed for three times. """ # TODO: add numa aware option ssh = SSH() ssh.connect(node) for _ in range(3): ret_code, stdout, _ = ssh.exec_command_sudo( 'cat /sys/kernel/mm/hugepages/hugepages-{0}kB/free_hugepages'. format(huge_size)) if ret_code == 0: try: huge_free = int(stdout) except ValueError: logger.trace('Reading free huge pages information failed') else: break else: raise RuntimeError('Getting free huge pages information failed.') return huge_free @staticmethod def get_huge_page_total(node, huge_size): """Get total number of huge pages in system. :param node: Node in the topology. :param huge_size: Size of hugepages. :type node: dict :type huge_size: int :returns: Total number of huge pages in system. :rtype: int :raises RuntimeError: If reading failed for three times. """ # TODO: add numa aware option ssh = SSH() ssh.connect(node) for _ in range(3): ret_code, stdout, _ = ssh.exec_command_sudo( 'cat /sys/kernel/mm/hugepages/hugepages-{0}kB/nr_hugepages'. format(huge_size)) if ret_code == 0: try: huge_total = int(stdout) except ValueError: logger.trace('Reading total huge pages information failed') else: break else: raise RuntimeError('Getting total huge pages information failed.') return huge_total @staticmethod def check_huge_page(node, huge_mnt, mem_size, allocate=False): """Check if there is enough HugePages in system. If allocate is set to true, try to allocate more HugePages. :param node: Node in the topology. :param huge_mnt: HugePage mount point. :param mem_size: Requested memory in MB. :param allocate: Whether to allocate more memory if not enough. :type node: dict :type huge_mnt: str :type mem_size: str :type allocate: bool :raises RuntimeError: Mounting hugetlbfs failed or not enough HugePages or increasing map count failed. """ # TODO: split function into smaller parts. ssh = SSH() ssh.connect(node) # Get huge pages information huge_size = DUTSetup.get_huge_page_size(node) huge_free = DUTSetup.get_huge_page_free(node, huge_size) huge_total = DUTSetup.get_huge_page_total(node, huge_size) # Check if memory reqested is available on host if (mem_size * 1024) > (huge_free * huge_size): # If we want to allocate hugepage dynamically if allocate: mem_needed = (mem_size * 1024) - (huge_free * huge_size) huge_to_allocate = ((mem_needed / huge_size) * 2) + huge_total max_map_count = huge_to_allocate*4 # Increase maximum number of memory map areas a process may have ret_code, _, _ = ssh.exec_command_sudo( 'echo "{0}" | sudo tee /proc/sys/vm/max_map_count'. format(max_map_count)) if int(ret_code) != 0: raise RuntimeError('Increase map count failed on {host}'. format(host=node['host'])) # Increase hugepage count ret_code, _, _ = ssh.exec_command_sudo( 'echo "{0}" | sudo tee /proc/sys/vm/nr_hugepages'. format(huge_to_allocate)) if int(ret_code) != 0: raise RuntimeError('Mount huge pages failed on {host}'. format(host=node['host'])) # If we do not want to allocate dynamicaly end with error else: raise RuntimeError('Not enough free huge pages: {0}, {1} MB'. format(huge_free, huge_free * huge_size)) # Check if huge pages mount point exist has_huge_mnt = False ret_code, stdout, _ = ssh.exec_command('cat /proc/mounts') if int(ret_code) == 0: for line in stdout.splitlines(): # Try to find something like: # none /mnt/huge hugetlbfs rw,relatime,pagesize=2048k 0 0 mount = line.split() if mount[2] == 'hugetlbfs' and mount[1] == huge_mnt: has_huge_mnt = True break # If huge page mount point not exist create one if not has_huge_mnt: ret_code, _, _ = ssh.exec_command_sudo( 'mkdir -p {mnt}'.format(mnt=huge_mnt)) if int(ret_code) != 0: raise RuntimeError('Create mount dir failed on {host}'. format(host=node['host'])) ret_code, _, _ = ssh.exec_command_sudo( 'mount -t hugetlbfs -o pagesize=2048k none {mnt}'. format(mnt=huge_mnt)) if int(ret_code) != 0: raise RuntimeError('Mount huge pages failed on {host}'. format(host=node['host']))
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2.054498
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import coreutil import unittest
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3.666667
9
#!usr/bin/env python # coding=utf-8 # Created by [email protected] on 2016/11/16. """ 启动 """ from scrapy import cmdline cmdline.execute("scrapy crawl biquge".split())
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from cx_Freeze import setup, Executable files = {"include_files": [ "command/", ], "packages": []} setup( name="pykage", version="0.1.5", description="npmjs en python", options={'build_exe': files}, executables=[Executable("pykage.py", base=None)])
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from onegov.core.framework import Framework from onegov.core.security import Public, Personal, Private, Secret @Framework.setting_section(section="roles") def get_roles_setting(): """ Returns the default roles available to onegov.core applications. Applications building on onegov.core may add more roles and permissions, or replace the existing ones entirely, though it's not something that one should do carelessly. The default roles are: **admin** Has access to everything **editor** Has access to most things **member** Has access their own data. Be careful though, core doesn't know about personal data, so this is just a role to implement registered users. As with all permissions, making sure the right information is shown is up to the applications. **anonymous** Has access to public things """ return { # the admin role has access to everything 'admin': set(( Public, Private, Personal, Secret )), # the editor can do most things 'editor': set(( Public, Private, Personal, )), # registered users can do a few things 'member': set(( Public, Personal, )), # the public has some access 'anonymous': set(( Public, )) }
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575
# Copyright: 2006 Brian Harring <[email protected]> # License: GPL2/BSD from snakeoil.test.mixins import TempDirMixin from pkgcore.cache import flat_hash from pkgcore.test.cache import util, test_base
[ 2, 15069, 25, 4793, 8403, 2113, 1806, 1279, 2232, 1806, 65, 31, 14816, 13, 785, 29, 198, 2, 13789, 25, 38644, 17, 14, 21800, 198, 198, 6738, 17522, 9437, 13, 9288, 13, 19816, 1040, 1330, 24189, 35277, 35608, 259, 198, 198, 6738, 279, 10025, 7295, 13, 23870, 1330, 6228, 62, 17831, 198, 6738, 279, 10025, 7295, 13, 9288, 13, 23870, 1330, 7736, 11, 1332, 62, 8692, 628, 198 ]
3.029412
68
# -*- coding: utf-8 -*- # 版权所有 2019 深圳米筐科技有限公司(下称“米筐科技”) # # 除非遵守当前许可,否则不得使用本软件。 # # * 非商业用途(非商业用途指个人出于非商业目的使用本软件,或者高校、研究所等非营利机构出于教育、科研等目的使用本软件): # 遵守 Apache License 2.0(下称“Apache 2.0 许可”), # 您可以在以下位置获得 Apache 2.0 许可的副本:http://www.apache.org/licenses/LICENSE-2.0。 # 除非法律有要求或以书面形式达成协议,否则本软件分发时需保持当前许可“原样”不变,且不得附加任何条件。 # # * 商业用途(商业用途指个人出于任何商业目的使用本软件,或者法人或其他组织出于任何目的使用本软件): # 未经米筐科技授权,任何个人不得出于任何商业目的使用本软件(包括但不限于向第三方提供、销售、出租、出借、转让本软件、 # 本软件的衍生产品、引用或借鉴了本软件功能或源代码的产品或服务),任何法人或其他组织不得出于任何目的使用本软件, # 否则米筐科技有权追究相应的知识产权侵权责任。 # 在此前提下,对本软件的使用同样需要遵守 Apache 2.0 许可,Apache 2.0 许可与本许可冲突之处,以本许可为准。 # 详细的授权流程,请联系 [email protected] 获取。 from inspect import signature from typing import Callable, Union, Iterable from functools import wraps, lru_cache as origin_lru_cache cached_functions = []
[ 2, 532, 9, 12, 19617, 25, 3384, 69, 12, 23, 532, 9, 12, 198, 2, 13328, 231, 230, 30266, 225, 33699, 222, 17312, 231, 13130, 10545, 115, 109, 28839, 111, 163, 109, 111, 163, 255, 238, 163, 100, 239, 162, 232, 222, 17312, 231, 165, 247, 238, 17739, 105, 20998, 116, 171, 120, 230, 10310, 233, 163, 100, 108, 447, 250, 163, 109, 111, 163, 255, 238, 163, 100, 239, 162, 232, 222, 447, 251, 171, 120, 231, 198, 2, 198, 2, 16268, 247, 97, 165, 251, 252, 34402, 113, 22522, 230, 37605, 241, 30298, 235, 164, 106, 116, 20998, 107, 171, 120, 234, 28938, 99, 26344, 247, 38834, 36181, 245, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 16764, 198, 2, 198, 2, 220, 220, 220, 220, 1635, 16268, 251, 252, 161, 243, 228, 10310, 248, 18796, 101, 34460, 242, 171, 120, 230, 165, 251, 252, 161, 243, 228, 10310, 248, 18796, 101, 34460, 242, 162, 234, 229, 10310, 103, 21689, 49035, 118, 12859, 236, 165, 251, 252, 161, 243, 228, 10310, 248, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 234, 22755, 244, 38519, 165, 45865, 43718, 94, 23513, 163, 254, 242, 163, 102, 114, 33699, 222, 163, 255, 231, 165, 251, 252, 164, 238, 98, 26344, 102, 17312, 118, 162, 252, 226, 49035, 118, 12859, 236, 46763, 247, 164, 224, 110, 23513, 163, 100, 239, 163, 254, 242, 163, 255, 231, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 231, 171, 120, 248, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 16268, 223, 113, 22522, 230, 24843, 13789, 362, 13, 15, 171, 120, 230, 10310, 233, 163, 100, 108, 447, 250, 25189, 4891, 362, 13, 15, 5525, 106, 116, 20998, 107, 447, 251, 171, 120, 231, 171, 120, 234, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 10545, 224, 101, 20998, 107, 20015, 98, 28839, 101, 20015, 98, 10310, 233, 19526, 235, 163, 121, 106, 164, 236, 115, 36181, 245, 24843, 362, 13, 15, 5525, 106, 116, 20998, 107, 21410, 30298, 107, 17312, 105, 171, 120, 248, 4023, 1378, 2503, 13, 43073, 13, 2398, 14, 677, 4541, 14, 43, 2149, 24290, 12, 17, 13, 15, 16764, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 16268, 247, 97, 165, 251, 252, 37345, 243, 36181, 233, 17312, 231, 17358, 223, 162, 109, 224, 22755, 244, 20015, 98, 20046, 99, 165, 251, 95, 37605, 95, 28156, 237, 164, 122, 122, 22755, 238, 39355, 237, 164, 106, 106, 171, 120, 234, 28938, 99, 26344, 247, 17312, 105, 164, 121, 107, 20015, 114, 26344, 228, 20998, 239, 33768, 114, 165, 250, 222, 46479, 251, 162, 234, 223, 37605, 241, 30298, 235, 164, 106, 116, 20998, 107, 447, 250, 43889, 253, 43718, 115, 447, 251, 38834, 20998, 246, 171, 120, 234, 10310, 242, 38834, 36181, 245, 165, 247, 226, 27950, 254, 20015, 119, 19526, 243, 30266, 94, 20015, 114, 16764, 198, 2, 198, 2, 220, 220, 220, 220, 1635, 10263, 243, 228, 10310, 248, 18796, 101, 34460, 242, 171, 120, 230, 161, 243, 228, 10310, 248, 18796, 101, 34460, 242, 162, 234, 229, 10310, 103, 21689, 49035, 118, 12859, 236, 20015, 119, 19526, 243, 161, 243, 228, 10310, 248, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 234, 22755, 244, 38519, 37345, 243, 21689, 22755, 244, 17739, 114, 20015, 244, 163, 119, 226, 163, 119, 229, 49035, 118, 12859, 236, 20015, 119, 19526, 243, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 231, 171, 120, 248, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 42164, 103, 163, 119, 237, 163, 109, 111, 163, 255, 238, 163, 100, 239, 162, 232, 222, 162, 236, 230, 30266, 225, 171, 120, 234, 20015, 119, 19526, 243, 10310, 103, 21689, 38834, 36181, 245, 49035, 118, 12859, 236, 20015, 119, 19526, 243, 161, 243, 228, 10310, 248, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 230, 44293, 227, 162, 233, 105, 19526, 228, 38834, 165, 247, 238, 12859, 236, 28938, 239, 163, 105, 105, 49011, 43095, 162, 237, 238, 160, 122, 249, 23513, 165, 242, 222, 161, 242, 106, 23513, 49035, 118, 163, 100, 253, 23513, 49035, 118, 161, 222, 253, 23513, 164, 121, 105, 164, 106, 102, 17312, 105, 164, 121, 107, 20015, 114, 23513, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 42164, 105, 164, 121, 107, 20015, 114, 21410, 26193, 235, 37955, 12859, 100, 161, 241, 223, 23513, 28156, 243, 18796, 101, 22755, 244, 161, 222, 253, 165, 231, 112, 12859, 228, 17312, 105, 164, 121, 107, 20015, 114, 27950, 253, 47797, 121, 22755, 244, 162, 118, 238, 47987, 163, 254, 223, 21410, 12859, 100, 161, 241, 223, 22755, 244, 17312, 235, 27950, 94, 171, 120, 231, 171, 120, 234, 20015, 119, 19526, 243, 37345, 243, 21689, 22755, 244, 17739, 114, 20015, 244, 163, 119, 226, 163, 119, 229, 38834, 36181, 245, 49035, 118, 12859, 236, 20015, 119, 19526, 243, 33566, 106, 21410, 45635, 18796, 101, 17312, 105, 164, 121, 107, 20015, 114, 171, 120, 234, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 10263, 238, 99, 26344, 247, 163, 109, 111, 163, 255, 238, 163, 100, 239, 162, 232, 222, 17312, 231, 30266, 225, 164, 4204, 163, 102, 114, 33566, 116, 41753, 242, 21410, 163, 253, 98, 46237, 228, 12859, 100, 30266, 225, 160, 122, 113, 30266, 225, 164, 112, 96, 20015, 119, 16764, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 10263, 250, 101, 29826, 97, 30298, 235, 162, 237, 238, 10310, 233, 171, 120, 234, 43380, 117, 17312, 105, 164, 121, 107, 20015, 114, 21410, 45635, 18796, 101, 28938, 234, 43718, 115, 165, 250, 222, 17358, 223, 34402, 113, 22522, 230, 24843, 362, 13, 15, 5525, 106, 116, 20998, 107, 171, 120, 234, 25189, 4891, 362, 13, 15, 5525, 106, 116, 20998, 107, 10310, 236, 17312, 105, 164, 106, 116, 20998, 107, 37863, 110, 163, 103, 223, 45298, 13783, 226, 171, 120, 234, 20015, 98, 17312, 105, 164, 106, 116, 20998, 107, 10310, 118, 49035, 228, 16764, 198, 2, 220, 220, 220, 220, 220, 220, 220, 220, 5525, 107, 99, 163, 119, 228, 21410, 162, 236, 230, 30266, 225, 38184, 223, 163, 101, 233, 171, 120, 234, 46237, 115, 164, 223, 242, 163, 111, 119, 1171, 31, 20970, 40972, 13, 785, 5525, 236, 115, 20998, 244, 16764, 198, 198, 6738, 10104, 1330, 9877, 198, 6738, 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0.752868
1,133
from collections import namedtuple import numpy as np """ Templates for glycan residues """ AA_info = namedtuple('AA_info', 'coords atom_names bonds bb sc offset') BDP_info = AA_info(coords=np.array([[-14.69, 10.15, -18.15], [-15.46, 11.47, -18.33], [-16.33, 11.35, -19.46], [-14.45, 12.62, -18.54], [-15.15, 13.88, -18.62], [-13.41, 12.66, -17.39], [-12.36, 13.57, -17.75], [-12.76, 11.28, -17.17], [-11.74, 11.28, -16.03], [-10.58, 11.62, -16.19], [-12.26, 11.06, -14.85], [-13.8, 10.27, -17.01], [-14.09, 9.95, -19.04], [-16.06, 11.66, -17.43], [-13.92, 12.44, -19.49], [-13.9, 12.98, -16.46], [-12.19, 11.01, -18.07], [-16.99, 10.64, -19.31], [-14.59, 14.56, -19.03]]), atom_names=['C1', 'C2', 'O2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6A', 'O6B', 'OR', 'H1', 'H2', 'H3', 'H4', 'H5', 'H2o', 'H3o'], bb=[], sc=[], bonds=[(0, 1), (0, 11), (0, 12), (1, 2), (1, 3), (1, 13), (2, 17), (3, 4), (3, 5), (3, 14), (4, 18), (5, 6), (5, 7), (5, 15), (7, 8), (7, 11), (7, 16), (8, 9), (8, 10)], offset=19) NGA_info = AA_info(coords=np.array([[-15., 5.88, -16.15], [-15.3, 7.39, -16.33], [-16.63, 7.71, -15.78], [-15.24, 7.7, -17.85], [-15.52, 9.08, -18.1], [-13.87, 7.26, -18.45], [-12.73, 7.93, -17.9], [-13.71, 5.74, -18.23], [-12.4, 5.17, -18.83], [-12.36, 3.77, -18.58], [-17.03, 8.94, -15.35], [-16.27, 9.85, -15.15], [-18.54, 9.06, -15.17], [-13.75, 5.49, -16.79], [-17.3, 6.97, -15.77], [-15.8, 5.34, -16.66], [-14.56, 7.98, -15.81], [-16.02, 7.14, -18.36], [-13.91, 7.52, -19.51], [-14.54, 5.23, -18.71], [-19.05, 8.97, -16.13], [-18.78, 10.05, -14.75], [-18.91, 8.29, -14.49], [-12.37, 5.36, -19.91], [-11.52, 5.64, -18.37], [-12.52, 7.65, -16.98], [-12.35, 3.64, -17.61]]), atom_names=['C1', 'C2', 'N2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6', 'C7', 'O7', 'C8', 'OR', 'HN2', 'H1', 'H2', 'H3', 'H4', 'H5', 'H81', 'H82', 'H83', 'H6R', 'H6S', 'H4o', 'H6o'], bb=[], sc=[], bonds=[(0, 1), (0, 13), (0, 15), (1, 2), (1, 3), (1, 16), (2, 10), (2, 14), (3, 4), (3, 5), (3, 17), (5, 6), (5, 7), (5, 18), (6, 25), (7, 8), (7, 13), (7, 19), (8, 9), (8, 23), (8, 24), (9, 26), (10, 11), (10, 12), (12, 20), (12, 21), (12, 22)], offset=27) AFL_info = AA_info(coords=np.array([[ 3.54, -4.94, -9.76], [ 3.83, -3.48, -10.16], [ 3.92, -2.65, -9.01], [ 5.17, -3.41, -10.92], [ 5.41, -2.05, -11.31], [ 5.13, -4.33, -12.16], [ 4.22, -3.76, -13.11], [ 4.71, -5.76, -11.76], [ 4.44, -6.66, -12.99], [ 3.49, -5.74, -10.97], [ 2.58, -5. , -9.26], [ 3.03, -3.12, -10.81], [ 5.98, -3.74, -10.26], [ 6.13, -4.36, -12.61], [ 5.5 , -6.22, -11.15], [ 5.32, -6.68, -13.65], [ 4.23, -7.68, -12.67], [ 3.59, -6.29, -13.56], [ 4.24, -1.79, -9.36], [ 6.3 , -2.01, -11.67], [ 4.27, -2.8 , -13. ]]), atom_names = ['C1', 'C2', 'O2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'OR', 'H1', 'H2', 'H3', 'H4', 'H5', 'H61', 'H62', 'H63', 'H2o', 'H3o', 'H4o'], bb = [], sc = [], bonds = [(0, 1), (0, 9), (0, 10), (1, 2), (1, 3), (1, 11), (2, 18), (3, 4), (3, 5), (3, 12), (4, 19), (5, 6), (5, 7), (5, 13), (6, 20), (7, 8), (7, 9), (7, 14), (8, 15), (8, 16), (8, 17)], offset = 21) NAG_info = AA_info(coords=np.array([[ 0.7 , -7.06, -8.68], [ -0.47, -6.53, -7.82], [ -0.6 , -7.33, -6.59], [ -1.77, -6.52, -8.68], [ -2.86, -5.83, -8.05], [ -1.54, -5.79, -10.02], [ -2.72, -5.91, -10.8 ], [ -0.32, -6.38, -10.77], [ -0.01, -5.62, -12.08], [ 0.03, -4.21, -11.88], [ -1.35, -6.97, -5.53], [ -2.06, -6. , -5.51], [ -1.26, -7.89, -4.34], [ 0.83, -6.29, -9.9 ], [ 0.53, -8.1 , -8.97], [ -0.24, -5.51, -7.51], [ -2.09, -7.55, -8.86], [ -1.37, -4.73, -9.8 ], [ -0.5 , -7.43, -11. ], [ -0.35, -8.49, -4.36], [ 0.04, -8.12, -6.49], [ -2.13, -8.56, -4.33], [ -1.25, -7.3 , -3.42], [ -2.7 , -5.79, -7.09], [ -0.78, -5.86, -12.82], [ 0.96, -5.95, -12.45], [ -3.45, -5.7 , -10.19], [ -0.89, -3.9 , -11.9 ]]), atom_names = ['C1', 'C2', 'N2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6', 'C7', 'O7', 'C8', 'OR', 'H1', 'H2', 'H3', 'H4', 'H5', 'H81', 'H2n', 'H82', 'H83', 'H3o', 'H6R', 'H6S', 'H4o', 'H6o'], bb = [], sc = [], bonds = [(0, 1), (0, 13), (0, 14), (1, 2), (1, 3), (1, 15), (2, 10), (2, 20), (3, 4), (3, 5), (3, 16), (4, 23), (5, 6), (5, 7), (5, 17), (6, 26), (7, 8), (7, 13), (7, 18), (8, 9), (8, 24), (8, 25), (9, 27), (10, 11), (10, 12), (12, 19), (12, 21), (12, 22)], offset = 28) MAG_info = AA_info(coords=np.array([[ 5.63, -8.87, -7.81], [ 6.82, -9.65, -8.03], [ 5.68, -7.48, -8.46], [ 6.84, -6.71, -7.97], [ 4.37, -6.71, -8.2 ], [ 4.45, -5.46, -8.88], [ 3.1 , -7.58, -8.52], [ 1.94, -6.96, -7.95], [ 3.26, -8.98, -7.84], [ 2.14, -10.01, -8.14], [ 1.97, -10.17, -9.54], [ 7.69, -6.03, -8.75], [ 7.65, -6.05, -9.98], [ 8.75, -5.26, -8.01], [ 7.14, -9.94, -9.4 ], [ 4.48, -9.59, -8.28], [ 7.47, -9.03, -9.9 ], [ 6.26, -10.36, -9.91], [ 7.95, -10.67, -9.41], [ 5.54, -8.78, -6.72], [ 5.79, -7.59, -9.54], [ 4.3 , -6.47, -7.13], [ 2.96, -7.7 , -9.6 ], [ 3.31, -8.86, -6.76], [ 9.47, -5.95, -7.57], [ 6.93, -6.62, -6.96], [ 8.29, -4.67, -7.22], [ 9.27, -4.58, -8.69], [ 1.21, -9.7 , -7.67], [ 2.44, -10.98, -7.71], [ 2.82, -10.46, -9.9 ]]), atom_names = ['C1', 'O1', 'C2', 'N2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6', 'C7', 'O7', 'C8', 'CO1', 'OR', 'HCO1', 'HCO2', 'HCO3', 'H1', 'H2', 'H3', 'H4', 'H5', 'H81', 'H2n', 'H82', 'H83', 'H6R', 'H6S', 'H6o'], bb = [], sc = [], bonds = [(0, 1), (0, 2), (0, 15), (0, 19), (1, 14), (2, 3), (2, 4), (2, 20), (3, 11), (3, 25), (4, 5), (4, 6), (4, 21), (6, 7), (6, 8), (6, 22), (8, 9), (8, 15), (8, 23), (9, 10), (9, 28), (9, 29), (10, 30), (11, 12), (11, 13), (13, 24), (13, 26), (13, 27), (14, 16), (14, 17), (14, 18)], offset = 31) B6D_info = AA_info(coords=np.array([[ 1.95e+01, 3.45e+01, 1.77e+00], [ 1.85e+01, 3.49e+01, 2.70e+00], [ 1.99e+01, 3.57e+01, 8.50e-01], [ 1.88e+01, 3.62e+01, 1.03e-01], [ 2.11e+01, 3.53e+01, -5.60e-02], [ 2.16e+01, 3.64e+01, -7.50e-01], [ 2.23e+01, 3.47e+01, 7.93e-01], [ 2.35e+01, 3.43e+01, -1.70e-02], [ 2.18e+01, 3.35e+01, 1.71e+00], [ 2.29e+01, 3.30e+01, 2.67e+00], [ 1.80e+01, 3.55e+01, -7.76e-01], [ 1.82e+01, 3.44e+01, -1.05e+00], [ 1.69e+01, 3.63e+01, -1.37e+00], [ 2.48e+01, 3.32e+01, -1.65e+00], [ 2.35e+01, 3.33e+01, -9.47e-01], [ 2.25e+01, 3.26e+01, -1.18e+00], [ 2.07e+01, 3.40e+01, 2.52e+00], [ 1.91e+01, 3.36e+01, 1.20e+00], [ 2.03e+01, 3.65e+01, 1.51e+00], [ 2.08e+01, 3.45e+01, -7.86e-01], [ 2.26e+01, 3.55e+01, 1.46e+00], [ 2.14e+01, 3.27e+01, 1.11e+00], [ 1.86e+01, 3.72e+01, 2.98e-01], [ 2.24e+01, 3.23e+01, 3.35e+00], [ 2.37e+01, 3.26e+01, 2.12e+00], [ 2.33e+01, 3.38e+01, 3.27e+00], [ 2.43e+01, 3.49e+01, 1.15e-01], [ 1.84e+01, 3.42e+01, 3.32e+00], [ 1.73e+01, 3.73e+01, -1.75e+00], [ 1.61e+01, 3.65e+01, -6.10e-01], [ 1.64e+01, 3.58e+01, -2.20e+00], [ 2.55e+01, 3.27e+01, -9.86e-01], [ 2.47e+01, 3.25e+01, -2.54e+00], [ 2.52e+01, 3.41e+01, -1.96e+00]]), atom_names = ['C1', 'O1', 'C2', 'N2', 'C3', 'O3', 'C4', 'N4', 'C5', 'C6', 'C7', 'O7', 'C8', 'C9', 'C10', 'O10', 'OR', 'H1', 'H2', 'H3', 'H4', 'H5', 'H2N', 'H61', 'H62', 'H63', 'H4N', 'H1o', 'H81', 'H82', 'H83', 'H91', 'H92', 'H93'], bb = [], sc = [], bonds = [(0, 1), (0, 2), (0, 16), (0, 17), (1, 27), (2, 3), (2, 4), (2, 18), (3, 10), (3, 22), (4, 5), (4, 6), (4, 19), (6, 7), (6, 8), (6, 20), (7, 14), (7, 26), (8, 9), (8, 16), (8, 21), (9, 23), (9, 24), (9, 25), (10, 11), (10, 12), (12, 28), (12, 29), (12, 30), (13, 14), (13, 31), (13, 32), (13, 33), (14, 15)], offset = 34) A2G_info = AA_info(coords=np.array([[ 2.25e+01, 3.67e+01, -2.07e+00], [ 2.33e+01, 3.80e+01, -2.32e+00], [ 2.43e+01, 3.82e+01, -1.26e+00], [ 2.23e+01, 3.92e+01, -2.39e+00], [ 2.30e+01, 4.04e+01, -2.61e+00], [ 2.12e+01, 3.90e+01, -3.45e+00], [ 2.18e+01, 3.89e+01, -4.76e+00], [ 2.05e+01, 3.76e+01, -3.14e+00], [ 1.94e+01, 3.73e+01, -4.19e+00], [ 1.87e+01, 3.61e+01, -3.81e+00], [ 2.54e+01, 3.75e+01, -1.15e+00], [ 2.57e+01, 3.65e+01, -1.90e+00], [ 2.63e+01, 3.79e+01, -2.70e-02], [ 2.14e+01, 3.66e+01, -3.09e+00], [ 2.31e+01, 3.58e+01, -2.09e+00], [ 2.38e+01, 3.79e+01, -3.28e+00], [ 2.05e+01, 3.98e+01, -3.38e+00], [ 2.00e+01, 3.77e+01, -2.16e+00], [ 2.41e+01, 3.89e+01, -6.34e-01], [ 1.99e+01, 3.72e+01, -5.17e+00], [ 1.87e+01, 3.81e+01, -4.26e+00], [ 2.58e+01, 3.78e+01, 9.29e-01], [ 2.67e+01, 3.89e+01, -1.90e-01], [ 2.72e+01, 3.72e+01, 2.90e-02], [ 1.94e+01, 3.54e+01, -3.68e+00]]), atom_names = ['C1', 'C2', 'N2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6', 'C7', 'O7', 'C8', 'OR', 'H1', 'H2', 'H4', 'H5', 'H2N', 'H61', 'H62', 'H81', 'H82', 'H83', 'H6o'], bb = [], sc = [], bonds = [(0, 1), (0, 13), (0, 14), (1, 2), (1, 3), (1, 15), (2, 10), (2, 18), (3, 4), (3, 5), (5, 6), (5, 7), (5, 16), (7, 8), (7, 13), (7, 17), (8, 9), (8, 19), (8, 20), (9, 24), (10, 11), (10, 12), (12, 21), (12, 22), (12, 23)], offset = 25) BGC_info = AA_info(coords=np.array([[ 20.45, 43.74, -11.36], [ 19.72, 45.09, -11.42], [ 19.65, 45.66, -10.11], [ 18.29, 44.89, -11.94], [ 17.63, 46.15, -12.08], [ 18.32, 44.19, -13.32], [ 16.97, 43.96, -13.73], [ 19.11, 42.86, -13.22], [ 19.33, 42.2 , -14.6 ], [ 18.08, 41.74, -15.13], [ 20.43, 43.13, -12.67], [ 19.97, 43.07, -10.64], [ 20.27, 45.77, -12.08], [ 17.73, 44.27, -11.24], [ 18.81, 44.85, -14.05], [ 18.59, 42.16, -12.55], [ 18.22, 41.54, -16.07], [ 18.99, 46.38, -10.17], [ 16.82, 45.99, -12.59], [ 19.77, 42.93, -15.28], [ 20.01, 41.36, -14.49], [ 17. , 43.31, -14.46]]), atom_names = ['C1', 'C2', 'O2', 'C3', 'O3', 'C4', 'O4', 'C5', 'C6', 'O6', 'OR', 'H1', 'H2', 'H3', 'H4', 'H5', 'H6', 'H2o', 'H3o', 'H6R', 'H6S', 'H4o'], bb = [], sc = [], bonds = [(0, 1), (0, 10), (0, 11), (1, 2), (1, 3), (1, 12), (2, 17), (3, 4), (3, 5), (3, 13), (4, 18), (5, 6), (5, 7), (5, 14), (6, 21), (7, 8), (7, 10), (7, 15), (8, 9), (8, 19), (8, 20), (9, 16)], offset = 22) templates_gl = {'B': BDP_info, 'N': NGA_info, 'A':AFL_info, 'G':NAG_info, 'M':MAG_info, 'D':B6D_info, 'C':A2G_info, 'F':BGC_info} one_to_three_gl = {'B': 'BDP', 'N': 'NGA', 'A':'AFL', 'G':'NAG', 'M':'MAG', 'D':'B6D', 'C':'A2G', 'F':'BGC'} three_to_one_gl = {val: key for key, val in one_to_three_gl.items()}
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import torch from torch import nn import math
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""" ## Metadata Store The configuration of each pipeline, step, backend, and produced artifacts are all tracked within the metadata store. The metadata store is an SQL database, and can be `sqlite` or `mysql`. Metadata are the pieces of information tracked about the pipelines, experiments and configurations that you are running with CoML. """ from coalescenceml.metadata_store.base_metadata_store import BaseMetadataStore from coalescenceml.metadata_store.mysql_metadata_store import MySQLMetadataStore from coalescenceml.metadata_store.sqlite_metadata_store import ( SQLiteMetadataStore, ) __all__ = [ "BaseMetadataStore", "MySQLMetadataStore", "SQLiteMetadataStore", ]
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from django.test import TestCase from ..service import shift_client_priority from ..models import Client, ProductArea, FeatureRequest class TestShiftClientPriority(TestCase): """Test service.shift_client_priority""" def test_basic(self): """Should shift all priorities up by one""" # Add 10 features with ascending priority, store id added = [add_feature(self.client, self.area, client_priority=i).id for i in range(1, 11)] query = FeatureRequest.objects.filter(client=self.client) # Shift priorities to free up 1 shift_client_priority(1, query) # Actual list of [(id, client_priority) ... ] priorities = query.values_list('pk', 'client_priority')\ .order_by('pk') # Expected [(id, client_priority) ... ] should_be = list(zip(added, range(2, 12))) self.assertEqual(list(priorities), should_be) def test_find_gap(self): """Should find gap in sequence, minimizing affected models""" # Make contiguous range for i in range(1, 11): add_feature(self.client, self.area, client_priority=i) # Add more, leaving a gap at 11 for i in range(12, 15): add_feature(self.client, self.area, client_priority=i) query = FeatureRequest.objects.filter(client=self.client) shift_client_priority(1, query) priorities = query.values_list('client_priority', flat=True)\ .order_by('client_priority') assert list(priorities) == list(range(2, 15)) def test_returns_modified_models(self): """Should return list of all models that were modified""" # Set up data models = [add_feature(self.client, self.area, client_priority=i) for i in range(1,10)] query = FeatureRequest.objects.filter(client=self.client) modified = shift_client_priority(1, query) self.assertCountEqual(models, modified)
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#!/usr/bin/env python # Small web app to allow a user to top up their personal PaperCut balance # Add a custom URL to the PaperCut user web page, which is used by end users # when they want to add credit to their PaperCut personal account. The url # should refer to this small web app When the user clicks on the URL link # (in the PaperCut user web page) to the web app, the user identification details # are passed as part of the URL. This is explained at: # https://www.papercut.com/products/ng/manual/common/topics/customize-user-web-pages.html#customize-user-web-pages-nav-links # The URL neeeds to something like http://localhost:8081/simpleTopUpBalance/?user=%user%&return_url=%return_url% # Generally additional security should be provided. For example if the URL is http://localhost:8081/promptForPassword/?user=%user%&return_url=%return_url% # then the user will need to enter their PaperCut password to access the payment system # Handy Tip: By default the link will open in a separate winodow. You can edit the advanced config property user.web.custom-links and # change "_body" to "_self". You should then use the %return_url% to return the user to the PaperCut MF/NG web interface # This code is a basic example only. It should not be used for production import xmlrpc.client import sys from json import load as loadjs import logging import traceback # Bottle does not depend on any external libraries. # You can just download bottle.py into your project directory and using # $ wget http://bottlepy.org/bottle.py from bottle import route, run, template, request, debug, response # Prefer HTTPS connection # If not localhost then this address will need to be whitelisted in PaperCut host = "http://localhost:9191/rpc/api/xmlrpc" auth = "token" # Value defined in advanced config property "auth.webservices.auth-token". Should be random proxy = xmlrpc.client.ServerProxy(host) # For more information on this user database file refer to the custom auth and sync demo paperCutAccountInfoFile = 'c:\\Program Files\\PaperCut MF\\server\\custom\\config.json' paperCutAccountData = {} # The user is sent back to the Summary page as if they had just logged in, # assuming their session has not timed out # Therefore return url should be consistent redirect_url = '' @route('/') @route('/promptForPassword/') @route('/simpleTopUpBalance/', method='GET') @route("/topUp/") try: with open(paperCutAccountInfoFile) as f: paperCutAccountData = loadjs(f) except OSError: paperCutAccountData = None run(host='localhost', port=8081, debug=True, reloader=True)
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#!/usr/bin/env python import os, yaml, json, shlex, datetime import logging logging.basicConfig(level=logging.INFO) from jinja2 import Environment, FileSystemLoader from datetime import datetime from shutil import copyfile # Mimic Ansible addional Jinja filter # Prepare Jinja envs env = Environment(loader = FileSystemLoader("/awx"), trim_blocks=True, lstrip_blocks=True) env.filters['quote'] = quote # Register quote filer # put local config to root Jinja copyfile("/opt/local/config/values.yml", "/awx/config/values.yml") logging.info("Generating values") # Load default config values default_config_src = yaml.safe_load(open("/awx/config/default.values.yml.j2")) # Config file itself is a template => render it template = env.get_template("config/default.values.yml.j2") data = template.render(default_config_src) logging.debug("default values render : ") logging.debug(data) default_config_src = yaml.safe_load(data) # Load config values config_src = yaml.safe_load(open("/awx/config/values.yml")) # Config file itself may be a template => render it template = env.get_template("config/values.yml") data = template.render(config_src) logging.debug("values render : ") logging.debug(data) config_src = yaml.safe_load(data) # Merge config and defaults config_src = {**default_config_src, **config_src} logging.debug(config_src) # list templates source_template_dir='/awx/templates' templates = os.listdir(source_template_dir) logging.debug(templates) # Create target dir then iterate os.makedirs("/opt/local/.awx", exist_ok=True) for templateName in templates: logging.info("Generating from : %s", templateName) template = env.get_template("templates/" + templateName) data = template.render(config_src) logging.debug(data) # Render template target=os.path.join("/opt/local/.awx",os.path.splitext(templateName)[0]) logging.info("Dumping to : %s ", target) f = open(target, "w") f.write(data) f.close() logging.info("Create secret key file") # Dump static secret key f = open(os.path.join("/opt/local/.awx", "SECRET_KEY"), "w") f.write(config_src['secret_key']) f.close()
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"""Module: Creates a WeatherScraper class to scrape data from website.""" import urllib.request import datetime import time from time import strptime from html.parser import HTMLParser from html.entities import name2codepoint class WeatherScraper(HTMLParser): """This class contains HTMLParser functions.""" def __init__(self): """Create an instance of WeatherScraper.""" HTMLParser.__init__(self) self.inTr = self.inTh = self.inAabr = self.inA = self.inTd = \ self.isDate = self.inCaption = self.inTbody = False self.inMean = self.inMin = self.inMax = self.inAvg = \ self.inMyDate = False self.EqualData = True self.i = self.j = 0 self.keys = ["max", "min", "mean"] self.dictInner = {} self.dictOuter = {} self.myDate = '' self.myCaptionYear = '' self.myCaption = [] self.url_year = self.url_month = None def handle_starttag(self, tag, attrs): """Handle the starttag in a website.""" if tag == 'caption': """Only one caption in html""" try: self.inCaption = True except Exception as e: print("Error:", e) if tag == 'tbody': """Only one <tbody> in html""" try: self.inTbody = True except Exception as e: print("Error:", e) if tag == 'tr': """There are an average of 35 tr""" try: self.inTr = True except Exception as e: print("Error:", e) if tag == 'td': """First td is under column MAX and DAY 1""" try: """i = 1 -> column MAX TEMP; i = 2 -> column MIN TEMP; i = 3 -> column MEAN TEMP""" self.i += 1 self.inTd = True except Exception as e: print("Error:", e) if tag == 'th': """First th = DAY(0,0) in table. Date is inside a td>th>abbr(attr[1]). Total: 43 """ try: self.inTh = True except Exception as e: print("Error:", e) if tag == 'abbr': """Date is located in here, attr[1]. Total: 62""" try: self.inAabr = True except Exception as e: print("Error:", e) if tag == 'a': """Set tag <a> to true""" try: self.inA = True except Exception as e: print("Error:", e) for attr in attrs: """attrs are inside a tag. E.g id='test'.""" self.inMean = True # print(self.inTbody) if self.inTbody and self.inTr and self.inTh and self.inAabr and \ attr[0] == 'title' and not attr[0] == 'href' \ and not attr[1] == 'Average' and not attr[1] == 'Extreme': # print(attr) self.inMyDate = True try: # print(f" attr[1] {attr[1]}") self.myDate = datetime.datetime \ .strptime(attr[1], '%B %d, %Y') \ .date() \ .strftime('%Y/%m/%d') print(f" self.myDate {self.myDate}") self.isDate = True except Exception as e: print(f"Error: {attr[1]}", e) def handle_endtag(self, tag): """Handle the endtag in a website.""" if tag == 'caption': try: self.inCaption = False except Exception as e: print("Error:", e) if tag == 'tbody': """Only one <tbody> in html""" try: self.inTbody = False except Exception as e: print("Error:", e) if tag == 'tr': try: self.i = 0 self.inTr = False except Exception as e: print("Error:", e) if tag == 'td': try: self.inTd = False except Exception as e: print("Error:", e) if tag == 'th': try: self.inTh = False except Exception as e: print("Error:", e) if tag == 'abbr': try: self.inMean = False self.inAabr = False except Exception as e: print("Error:", e) if tag == 'a': """Set all tag <a>""" try: self.inA = False except Exception as e: print("Error:", e) def handle_data(self, data): """Handle the data inside a tag in a website and return dictionary.""" if data == 'Sum': self.inMyDate = False if self.inMyDate and self.inTd and self.i == 1: try: # print("Max Inner:", data) self.dictInner[self.keys[0]] = data except Exception as e: self.dictInner[self.keys[0]] = 0 print("Error:", e) if self.inMyDate and self.inTd and self.i == 2: try: # print("Min Inner:", data) self.dictInner[self.keys[1]] = data except Exception as e: self.dictInner[self.keys[1]] = 0 print("Error:", e) if self.inMyDate and self.inTd and self.i == 3: try: # print("Mean Inner:", data) self.dictInner[self.keys[2]] = data except Exception as e: self.dictInner[self.keys[2]] = 0 print("Error:", e) if self.inMyDate: self.dictOuter[self.myDate] = dict(self.dictInner) if self.inCaption: self.myCaption = data.split() self.myCaptionYear = self.myCaption[5] # print(f"inCaption - YEAR {self.myCaptionYear}") self.myCaptionMonth = self.myCaption[4] # print(f"inCaption - MONTH {self.myCaptionMonth}") m = {'jan': '01', 'feb': '02', 'mar': '03', 'apr': '04', 'may': '05', 'jun': '06', 'jul': '07', 'aug': '08', 'sep': '09', 'oct': '10', 'nov': '11', 'dec': '12'} s = self.myCaption[4].strip()[:3].lower() if str(self.url_month).zfill(2) == m[s] and str(self.url_year) \ in self.myCaptionYear: # print("EQUALLLLLL") self.EqualData = True else: # print("NOT EQUAL") self.EqualData = False
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1.789543
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import time, cv2 from threading import Thread from djitellopy import Tello FPS = 30 tello = Tello() tello.connect() print("Battery level:", tello.get_battery()) keepRecording = True tello.streamon() frame_read = tello.get_frame_read() # we need to run the recorder in a seperate thread, otherwise blocking options # would prevent frames from getting added to the video recorder = Thread(target=video_recorder) recorder.start() # tello.takeoff() # tello.move_up(100) # tello.rotate_counter_clockwise(360) # tello.land() start = time.time() while time.time() - start < 15: cv2.imshow("Drone", frame_read.frame) cv2.waitKey(1) keepRecording = False recorder.join() tello.end()
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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import utils.fields
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2.953488
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from textwrap import dedent import pytest from pylox.lox import Lox # Base cases from https://github.com/munificent/craftinginterpreters/blob/master/test/variable/use_local_in_initializer.lox TEST_SRC = dedent( """\ var a = "outer"; { var a = a; // Error at 'a': Can't read local variable in its own initializer. } """ ) EXPECTED_STDOUTS = ["3:11: LoxResolverError: Can't read local variable in its own initializer."]
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2.656805
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import re import spacy spacy_en = spacy.load('en_core_web_sm') # Setting LF output values ABSTAIN_VAL = 0 SEIZURE_VAL = 1 NO_SEIZURE_VAL = -1 ###################################################################################################### ##### HELPFUL REGEXES AND ONTOLOGIES ###################################################################################################### # Defining useful regular expressions. SIMPLE_NORMAL_RE = re.compile('\snormal\s', re.IGNORECASE) # Nouns indicating an EEG EEGSYN = r'(EEG|study|record|electroencephalogram|ambulatory\s+EEG|video.EEG\sstudy)' # Phrases indicating a normal study NORMAL_STUDY_PHRASES = re.compile(rf'\snormal\s+{EEGSYN}' rf'|\snormal\s+awake\s+and\s+asleep\s+{EEGSYN}' rf'|\snormal\s+awake\s+{EEGSYN}' rf'|\snormal\s+awake\s+and\s+drowsy\s+{EEGSYN}' rf'|\snormal\s+asleep\s+{EEGSYN}' rf'|\s{EEGSYN}\s+(is|was)\s+normal' rf'|\srange\s+of\s+normal' # generous rf'|\s(is|was)\s+normal\s+for\s+age' #rf'|(EEG|study|record)\s+(is|was)\s+normal\s+for\s+age' #rf'|(EEG|study|record)\s+(is|was)\s+normal\s+for\s+age' rf'|{EEGSYN}\s+(is|was)\s+within\s+normal\s+' rf'|{EEGSYN}\s+(is|was)\s+borderline\+snormal' rf'|{EEGSYN}\s+(is|was)\s+at\s+the\s+borderline\s+of\s+being\s+normal' rf'|{EEGSYN}\s+capturing\s+wakefulness\s+and\s+sleep\s+(is|was)\s+normal' rf'|{EEGSYN}\s+capturing\s+wakefulness\s+(is|was)\s+normal', re.IGNORECASE) # Regex for abnormal ABNORMAL_RE = re.compile(r'abnormal', re.IGNORECASE) # Regex for seizure synonyms SEIZURE_SYNONYMS = r'seizure|seizures|spasm|spasms|status\sepilepticus|epilepsia\spartialis\scontinua|drop\sattack' SEIZURE_SYNONYMS_RE = re.compile(SEIZURE_SYNONYMS, re.IGNORECASE|re.UNICODE) # Regex for negation NEG_DET = ['no', 'not', 'without'] # Regex for no seizure in study NEG_SEIZURE = r'no seizures|no epileptiform activity or seizures'.replace(' ','\s') NEG_SEIZURE_RE = re.compile(NEG_SEIZURE, re.IGNORECASE) # Alternate section keys for INTERPRATION section of report candidate_interps = ['INTERPRETATION', 'Interpretation', 'Summary', 'impression', 'IMPRESSION', 'conclusion', 'conclusions'] CANDIDATE_INTERPS_LOWER = list({ss.lower() for ss in candidate_interps}) # Alternate regex for no seizures NOSEIZURE_PHRASE_RE = re.compile(r'\bno seizures\b|\bno\sepileptiform\sactivity\sor\sseizures\b' r'|\bno findings to indicate seizures\b' r'|no findings to indicate' r'|no new seizures' r'|with no seizures' r'|no evidence to support seizures' r'|nonepileptic' r'|non-epileptic' , re.IGNORECASE|re.UNICODE) # Defining negexes NEG_DET= r'(\bno\b|\bnot\b|\bwithout\sfurther\b|\bno\sfurther\b|without|neither)' BASIC_NEGEX_RE = re.compile(NEG_DET + '.*('+ SEIZURE_SYNONYMS + ')', re.IGNORECASE|re.UNICODE) REVERSED_NEGEX_RE = re.compile('('+ SEIZURE_SYNONYMS + ').*' + NEG_DET, re.IGNORECASE|re.UNICODE) ###################################################################################################### ##### HELPER FUNCTIONS ###################################################################################################### def is_not_abnormal_interp(interp): """ Check text of interpretation for abnormal mentions """ m = ABNORMAL_RE.search(interp) if not m: return True else: return False def abnormal_interp_with_seizure(interp_text): """ Tests for abnormal interpretation with seizure synonym """ if ABNORMAL_RE.search(interp_text): if SEIZURE_SYNONYMS_RE.search(interp_text): return SEIZURE_VAL else: return NO_SEIZURE_VAL else: return NO_SEIZURE_VAL def abnormal_interp_test(interp_text): """ Tests for abnormal text """ return ABNORMAL_RE.search(interp_text) def eval_interp_with_negex(interp): """ Looks at each sentence, if a sentence says there is a seizure, then that overrides all the negative sentences """ if is_not_abnormal_interp(interp): return NO_SEIZURE_VAL parsed_interp = spacy_en(interp) neg_found = 0 seizure_found_and_no_neg = 0 for sent in parsed_interp.sents: s = str(sent) m1 = BASIC_NEGEX_RE.search(s) if m1: neg_found=1 m2 = REVERSED_NEGEX_RE.search(s) if m2: neg_found =2 if not neg_found: m3 = SEIZURE_SYNONYMS_RE.search(s) if m3: seizure_found_and_no_neg = 1 if neg_found and not seizure_found_and_no_neg: return NO_SEIZURE_VAL elif seizure_found_and_no_neg: return SEIZURE_VAL return NO_SEIZURE_VAL def get_section_with_name(section_names, doc): """ Check exact matches for keys in section_names; this presumes a certain structure in EEGNote doc object """ text = '' for section in section_names: try: text = ' '.join([text, doc.sections[section]['text']]) except: pass try: text = ' '.join([text, doc.sections['narrative'][section]]) except: pass try: text = ' '.join([text, doc.sections['findings'][section]]) except: pass return ' '.join(text.split()) ###################################################################################################### ##### LABELING FUNCTIONS (LFs) ###################################################################################################### def lf_normal_interp_not_seizure(report): """ This LF looks for a top level interpretation section -- if none, no seizure """ for keyinterp in CANDIDATE_INTERPS_LOWER: if keyinterp in report.sections.keys(): interpretation = report.sections[keyinterp] interp_text = interpretation['text'] if SIMPLE_NORMAL_RE.search(interp_text): if NORMAL_STUDY_PHRASES.search(interp_text): return NO_SEIZURE_VAL else: return ABSTAIN_VAL else: return ABSTAIN_VAL return ABSTAIN_VAL def lf_abnormal_interp_with_seizure(report): """ Searching for abnormal interpretation section with seizure synonym """ if 'interpretation' in report.sections.keys(): interpretation = report.sections['interpretation'] interp_text = interpretation['text'] return abnormal_interp_with_seizure(interp_text) elif 'summary' in report.sections: return abnormal_interp_with_seizure(report.sections['summary']['text']) elif 'findings' in report.sections: # fall back to look in the findings if 'summary' in report.sections['findings']: # fall back to look for a summary instead return abnormal_interp_with_seizure(report.sections['findings']['summary']) if 'impression' in report.sections['findings']: return abnormal_interp_with_seizure(report.sections['findings']['impression']) return ABSTAIN_VAL elif 'narrative' in report.sections: # fall back to look in the findings ky = 'narrative' if 'summary' in report.sections[ky]: # fall back to look for a summary instead return abnormal_interp_with_seizure(report.sections[ky]['summary']) if 'impression' in report.sections[ky]: return abnormal_interp_with_seizure(report.sections[ky]['impression']) return ABSTAIN_VAL else: return ABSTAIN_VAL def lf_findall_interp_with_seizure(report): """ Check if interpretation sections are abnormal, then look for words indicating a seizure """ if 'interpretation' in report.sections.keys(): interpretation = report.sections['interpretation'] interp_text = interpretation['text'] return abnormal_interp_with_seizure(interp_text) else: candtext = get_section_with_name(CANDIDATE_INTERPS_LOWER, report) if candtext: return abnormal_interp_with_seizure(candtext) else: return ABSTAIN_VAL def lf_findall_abnl_interp_without_seizure(report): """ Check if interpretation sections are abnormal, then look for words indicating NO seizure """ if 'interpretation' in report.sections.keys(): interpretation = report.sections['interpretation'] interp_text = interpretation['text'] if abnormal_interp_test(interp_text): if NOSEIZURE_PHRASE_RE.search(interp_text): return NO_SEIZURE_VAL else: return ABSTAIN_VAL else: return ABSTAIN_VAL else: candtext = get_section_with_name(CANDIDATE_INTERPS_LOWER, report) if candtext: if abnormal_interp_test(candtext): if NOSEIZURE_PHRASE_RE.search(candtext): return NO_SEIZURE_VAL else: return ABSTAIN_VAL else: return ABSTAIN_VAL else: return ABSTAIN_VAL def lf_abnl_interp_negexsp_seizure(report): """ Check if top interpretation section is abnormal and if so, use negex to find indications that there is no seizure """ for topkey in CANDIDATE_INTERPS_LOWER: if topkey in report.sections.keys(): interpretation = report.sections[topkey] interp_text = interpretation['text'] return eval_interp_with_negex(interp_text) return ABSTAIN_VAL def lf_findall_interp_negex_seizure(report): """ Check if lower sections have abnormal text and if so, use negex to find indications of no seizure """ candtext = get_section_with_name(CANDIDATE_INTERPS_LOWER, report) if candtext: return eval_interp_with_negex(candtext) else: return ABSTAIN_VAL def lf_seizure_section(report): """ Checking to see if there is a 'seizure' section in the report """ if 'findings' in report.sections.keys(): seizure_keys = [key for key in report.sections['findings'].keys() if 'seizure' in key ] if not seizure_keys: return ABSTAIN_VAL else: for ky in seizure_keys: seizure_text = report.sections['findings'][ky] if 'None' in seizure_text: return NO_SEIZURE_VAL elif 'Many' in seizure_text: return SEIZURE_VAL elif len(seizure_text.split()) > 30: return SEIZURE_VAL else: return NO_SEIZURE_VAL else: return ABSTAIN_VAL def lf_impression_section_negative(report): """ Getting impression section, checking for specific terms """ impression_words = ['impression','interpretation','comments'] impression = get_section_with_name(impression_words, report) reg_normal = ['no epileptiform', 'absence of epileptiform', 'not epileptiform', 'normal EEG', 'normal aEEG','benign','non-specific','nonepileptic','idiopathic', 'no seizures','EEG is normal','normal study'] if any([re.search(reg, impression, re.IGNORECASE) for reg in reg_normal] ): return NO_SEIZURE_VAL else: return ABSTAIN_VAL def lf_impression_section_positive(report): """ Getting impression section, checking for specific terms """ impression_words = ['impression','interpretation','comments'] impression = get_section_with_name(impression_words, report) reg_abnormal = ['status epilepticus','spasms','abnormal continuous', 'tonic','subclinical','spike-wave', 'markedly abnormal'] if any([re.search(reg, impression, re.IGNORECASE) for reg in reg_abnormal] ): return SEIZURE_VAL else: return ABSTAIN_VAL def lf_spikes_in_impression(report): """ Checking for indications of spikes in the impression section """ impression_words = ['impression','interpretation','comments'] impression = get_section_with_name(impression_words, report) if re.search('spike',impression,re.IGNORECASE): return SEIZURE_VAL else: return ABSTAIN_VAL def lf_extreme_words_in_impression(report): """ Checking for words indicating extreme events in the impression section """ impression_words = ['impression','interpretation','comments'] impression = get_section_with_name(impression_words, report) reg_abnormal = ['excessive','frequent'] if any([re.search(reg, impression, re.IGNORECASE) for reg in reg_abnormal] ): return SEIZURE_VAL else: return ABSTAIN_VAL
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23428, 198 ]
2.186413
6,153
#Kunal Gautam #Codewars : @Kunalpod #Problem name: Find the missing term in an Arithmetic Progression #Problem level: 5 kyu
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3.1
40
import os import unittest from dataverk.datapackage import Datapackage from dataverk.exceptions.dataverk_exceptions import EnvironmentVariableNotSet from dataverk.utils import storage_paths valid_metadata = { 'title': 'title', 'readme': "readme", 'license': 'MIT', 'accessRights': 'Open', 'auth': 'unknown', 'description': 'unknown', 'source': 'unknown', 'keywords': ['unknown'], 'provenance': 'unknown', 'publisher': 'unknown', 'bucket': 'opendata', 'store': 'local', 'format': ['datapackage'], 'pii': '', 'purpose': 'open data', 'master': 'secret' }
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2.568465
241
from django.shortcuts import render,redirect from .models import * from django.contrib import messages from django.contrib.auth import login,logout,authenticate # Create your views here. from datetime import date
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3.754386
57
#!/usr/bin/env python3 # encoding: utf-8 """Classes used for representing Tables, TableRows and TableCells.""" from typing import List from itertools import chain, accumulate from inscriptis.html_properties import HorizontalAlignment, VerticalAlignment from inscriptis.annotation import Annotation, horizontal_shift from inscriptis.model.canvas import Canvas class TableCell(Canvas): """A table cell. Attributes: line_width: the original line widths per line (required to adjust annotations after a reformatting) vertical_padding: vertical padding that has been introduced due to vertical formatting rules. """ __slots__ = ('annotations', 'block_annotations', 'blocks', 'current_block', 'margin', 'annotation_counter', 'align', 'valign', '_width', 'line_width', 'vertical_padding') def normalize_blocks(self) -> int: """Split multi-line blocks into multiple one-line blocks. Returns: The height of the normalized cell. """ self._flush_inline() self.blocks = list(chain(*(line.split('\n') for line in self.blocks))) if not self.blocks: self.blocks = [''] return len(self.blocks) @property def height(self): """Compute the table cell's height. Returns: The cell's current height. """ return max(1, len(self.blocks)) @property def width(self): """Compute the table cell's width. Returns: The cell's current width. """ if self._width: return self._width return max((len(line) for line in chain(*(block.split('\n') for block in self.blocks)))) @width.setter def width(self, width): """Set the table's width and applies the cell's horizontal formatting. Args: The cell's expected width. """ # save the original line widths before reformatting self.line_width = [len(block) for block in self.blocks] # record new width and start reformatting self._width = width format_spec = '{{:{align}{width}}}'.format(align=self.align.value, width=width) self.blocks = [format_spec.format(b) for b in self.blocks] @height.setter def height(self, height: int): """Set the cell's height to the given value. Notes: Depending on the height and the cell's vertical formatting this might require the introduction of empty lines. """ rows = len(self.blocks) if rows < height: empty_line = [''] if self.valign == VerticalAlignment.bottom: self.vertical_padding = (height - rows) self.blocks = self.vertical_padding * empty_line + self.blocks elif self.valign == VerticalAlignment.middle: self.vertical_padding = (height - rows) // 2 self.blocks = self.vertical_padding * empty_line + \ self.blocks + ((height - rows + 1) // 2 * empty_line) else: self.blocks = self.blocks + ((height - rows) * empty_line) def get_annotations(self, idx: int, row_width: int) -> List[Annotation]: """Return a list of all annotations within the TableCell. Returns: A list of annotations that have been adjusted to the cell's position. """ self.current_block.idx = idx if not self.annotations: return [] # the easy case - the cell has only one line :) if len(self.blocks) == 1: annotations = horizontal_shift(self.annotations, self.line_width[0], self.width, self.align, idx) self.line_width[0] = self.width return annotations # the more challenging one - multiple cell lines line_break_pos = list(accumulate(self.line_width)) annotation_lines = [[] for _ in self.blocks] # assign annotations to the corresponding line for a in self.annotations: for no, line_break in enumerate(line_break_pos): if a.start <= (line_break + no): # consider newline annotation_lines[no + self.vertical_padding].append(a) break # compute the annotation index based on its line and delta :) result = [] idx += self.vertical_padding # newlines introduced by the padding for line_annotations, line_len in zip(annotation_lines, self.line_width): result.extend(horizontal_shift(line_annotations, line_len, self.width, self.align, idx)) idx += row_width - line_len self.line_width = [self.width for _ in self.line_width] return result class TableRow: """A single row within a table.""" __slots__ = ('columns', 'cell_separator') def get_text(self) -> str: """Return a text representation of the TableRow.""" row_lines = [self.cell_separator.join(line) for line in zip(*[column.blocks for column in self.columns])] return '\n'.join(row_lines) @property def width(self): """Compute and return the width of the current row.""" if not self.columns: return 0 return sum((cell.width for cell in self.columns)) + len( self.cell_separator) * (len(self.columns) - 1) class Table: """An HTML table. Attributes: rows: the table's rows. left_margin_len: length of the left margin before the table. """ __slots__ = ('rows', 'left_margin_len') def add_row(self): """Add an empty :class:`TableRow` to the table.""" self.rows.append(TableRow()) def add_cell(self, table_cell: TableCell): """Add a new :class:`TableCell` to the table's last row. .. note:: If no row exists yet, a new row is created. """ if not self.rows: self.add_row() self.rows[-1].columns.append(table_cell) def _set_row_height(self): """Set the cell height for all :class:`TableCell`s in the table.""" for row in self.rows: max_row_height = max((cell.normalize_blocks() for cell in row.columns)) \ if row.columns else 0 for cell in row.columns: cell.height = max_row_height def _set_column_width(self): """Set the column width for all :class:`TableCell`s in the table.""" # determine maximum number of columns max_columns = max((len(row.columns) for row in self.rows)) for cur_column_idx in range(max_columns): # determine the required column width for the current column max_column_width = max((row.columns[cur_column_idx].width for row in self.rows if len(row) > cur_column_idx)) # set column width for all TableCells in the current column for row in self.rows: if len(row) > cur_column_idx: row.columns[cur_column_idx].width = max_column_width def get_text(self): """Return and render the text of the given table.""" if not self.rows: return '\n' self._set_row_height() self._set_column_width() return '\n'.join((row.get_text() for row in self.rows)) + '\n' def get_annotations(self, idx: int, left_margin_len: int) -> List[Annotation]: r"""Return all annotations in the given table. Args: idx: the table's start index. left_margin_len: len of the left margin (required for adapting the position of annotations). Returns: A list of all :class:`~inscriptis.annotation.Annotation`\s present in the table. """ if not self.rows: return [] annotations = [] idx += left_margin_len for row in self.rows: if not row.columns: continue row_width = row.width + left_margin_len cell_idx = idx for cell in row.columns: annotations += cell.get_annotations(cell_idx, row_width) cell_idx += cell.width + len(row.cell_separator) idx += (row_width + 1) * cell.height # linebreak return annotations
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2.170582
4,086
from config import Config from flask import Flask
[ 6738, 4566, 1330, 17056, 198, 6738, 42903, 1330, 46947, 628, 198 ]
4.727273
11
data_x, data_x_unseen = prepare_data_x(normalized_data_close_price, window_size=config["data"]["window_size"]) data_y = prepare_data_y(normalized_data_close_price, window_size=config["data"]["window_size"]) # split dataset split_index = int(data_y.shape[0]*config["data"]["train_split_size"]) data_x_train = data_x[:split_index] data_x_val = data_x[split_index:] data_y_train = data_y[:split_index] data_y_val = data_y[split_index:] # prepare data for plotting to_plot_data_y_train = np.zeros(num_data_points) to_plot_data_y_val = np.zeros(num_data_points) to_plot_data_y_train[config["data"]["window_size"]:split_index+config["data"]["window_size"]] = scaler.inverse_transform(data_y_train) to_plot_data_y_val[split_index+config["data"]["window_size"]:] = scaler.inverse_transform(data_y_val) to_plot_data_y_train = np.where(to_plot_data_y_train == 0, None, to_plot_data_y_train) to_plot_data_y_val = np.where(to_plot_data_y_val == 0, None, to_plot_data_y_val) ## plots fig = figure(figsize=(25, 5), dpi=80) fig.patch.set_facecolor((1.0, 1.0, 1.0)) plt.plot(data_date, to_plot_data_y_train, label="Prices (train)", color=config["plots"]["color_train"]) plt.plot(data_date, to_plot_data_y_val, label="Prices (validation)", color=config["plots"]["color_val"]) xticks = [data_date[i] if ((i%config["plots"]["xticks_interval"]==0 and (num_data_points-i) > config["plots"]["xticks_interval"]) or i==num_data_points-1) else None for i in range(num_data_points)] # make x ticks nice x = np.arange(0,len(xticks)) plt.xticks(x, xticks, rotation='vertical') plt.title("Daily close prices for " + config["alpha_vantage"]["symbol"] + " - showing training and validation data") plt.grid(b=None, which='major', axis='y', linestyle='--') plt.legend() plt.show()
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import os BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', # Third Party Apps 'widget_tweaks', 'django_cleanup', 'django_cool_paginator', 'django.contrib.sites', 'allauth', 'allauth.account', # 'corsheaders', # 'rest_framework', # Local Apps 'accounts', 'system_data', 'suspicious', 'utils', 'contribution', ] SITE_ID = 1 AUTHENTICATION_BACKENDS = ( # Needed to login by username in Django admin, regardless of `allauth` # 'django.contrib.auth.backends.ModelBackend', # `allauth` specific authentication methods, such as login by e-mail 'allauth.account.auth_backends.AuthenticationBackend', ) MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', # CorsHeader Middleware before CommonMiddleware # 'corsheaders.middleware.CorsMiddleware', # CorsHeader Middleware 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'magfetch.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], # 'loaders': [ # ('django.template.loaders.cached.Loader', [ # 'django.template.loaders.filesystem.Loader', # 'django.template.loaders.app_directories.Loader', # ]), # ], }, }, ] WSGI_APPLICATION = 'magfetch.wsgi.application' AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization LANGUAGE_CODE = 'en-us' TIME_ZONE = 'Asia/Dhaka' USE_I18N = True USE_L10N = True USE_TZ = False # LANGUAGE_CODE = 'en-us' # TIME_ZONE = 'UTC' # USE_I18N = True # USE_L10N = True # USE_TZ = True # Allauth LOGIN_URL = '/account/login/' LOGOUT_URL = '/' LOGIN_REDIRECT_URL = '/' SITE_NAME = 'magFetch' ACCOUNT_EMAIL_CONFIRMATION_EXPIRE_DAYS = 7 ACCOUNT_LOGIN_ATTEMPTS_LIMIT = 5 ACCOUNT_LOGIN_ATTEMPTS_TIMEOUT = 300 ACCOUNT_USERNAME_MIN_LENGTH = 1 ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_USERNAME_REQUIRED = True ACCOUNT_SIGNUP_PASSWORD_VERIFICATION = True ACCOUNT_UNIQUE_EMAIL = True ACCOUNT_LOGOUT_ON_PASSWORD_CHANGE = True ACCOUNT_SIGNUP_PASSWORD_ENTER_TWICE = True ACCOUNT_EMAIL_CONFIRMATION_AUTHENTICATED_REDIRECT_URL = '/' ACCOUNT_AUTHENTICATION_METHOD = 'email' ACCOUNT_EMAIL_VERIFICATION = 'optional' ACCOUNT_EMAIL_SUBJECT_PREFIX = 'magFetch' ACCOUNT_USERNAME_BLACKLIST =['robot', 'hacker', 'virus', 'spam'] ACCOUNT_ADAPTER = 'magfetch.adapter.UsernameMaxAdapter' # Cool Paginator COOL_PAGINATOR_NEXT_NAME = "next" COOL_PAGINATOR_PREVIOUS_NAME = "previous" COOL_PAGINATOR_SIZE = "SMALL" COOL_PAGINATOR_ELASTIC = "300px" # File Validation Staffs ALLOWED_FILE_TYPES = ['.doc', '.docx', '.jpg', '.jpeg', '.png', '.svg', '.DOC', '.DOCX', '.JPG', '.JPEG', '.PNG', '.SVG'] FILE_TYPES = ['.doc', '.docx', '.jpg', '.jpeg', '.png', '.svg'] IMAGE_TYPES = ['.jpg', '.jpeg', '.png', '.svg'] DOCUMENT_TYPES = ['.doc', '.docx'] # 1.5MB - 1621440 # 2.5MB - 2621440 # 5MB - 5242880 # 10MB - 10485760 # 20MB - 20971520 # 50MB - 5242880 # 100MB 104857600 # 250MB - 214958080 # 500MB - 429916160 MAX_UPLOAD_SIZE = 2621440 # # Static Files # STATIC_URL = '/static/' # MEDIA_URL = '/media/' # STATICFILES_DIRS = [ # os.path.join(BASE_DIR, 'static_proj'), # ] # STATIC_ROOT = os.path.join('static_cdn', 'static_root') # MEDIA_ROOT = os.path.join('static_cdn', 'media_root') # STATICFILES_FINDERS = [ # 'django.contrib.staticfiles.finders.FileSystemFinder', # 'django.contrib.staticfiles.finders.AppDirectoriesFinder', # ] # Neededf for CorsHeader (accept connections from everywhere) # CORS_ORIGIN_ALLOW_ALL = True # CORS_ALLOW_HEADERS = ( # 'x-requested-with', # 'content-type', # 'accept', # 'origin', # 'authorization', # 'x-csrftoken', # 'token', # 'x-device-id', # 'x-device-type', # 'x-push-id', # 'dataserviceversion', # 'maxdataserviceversion' # ) # CORS_ALLOW_METHODS = ( # 'GET', # 'POST', # 'PUT', # 'PATCH', # 'DELETE', # 'OPTIONS' # )
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2.17905
2,463
# TESS - ToastmastErs Simple Scheduler # This simple script will create a shuffled list of suggested meeting roles for multiple meetings. from random import shuffle from os import linesep import csv import sys if __name__ == "__main__": main(sys.argv[1:])
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3.48
75
# Copyright 2008-2018 Univa Corporation # # 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 subprocess from tortuga.exceptions.commandFailed import CommandFailed # Convenience function for executing command. def executeCommand(command): """ Create subprocess and run it, return subprocess object. """ p = TortugaSubprocess(command) p.run() return p # Convenience function for executing command that may fail, and we do not # care about the failure. def executeCommandAndIgnoreFailure(command): """ Create subprocess, run it, ignore any failures, and return subprocess object. """ p = TortugaSubprocess(command) try: p.run() except CommandFailed: pass return p
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3.426593
361
import sshclient from launch_db import get_constellation_data from launch_db import log_msg
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3.615385
26
from .general import check_for_block_tag, check_for_comment, split_info_lines, read_face_column, dimension_reference from typing import List, Union, Any FORMAT: List[int] = [2, 1, 1, 10, 1, 10, 1, 10, 1, 10, 1, 10, 1, 10, 1, 10] # 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,10, 11,12, 13,14, 15
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2.146853
143
# -*- coding: utf-8 -*- ############################################################################# # # Copyright © Dragon Dollar Limited # contact: [email protected] # # This software is a collection of webservices designed to provide a secure # and scalable framework to build e-commerce websites. # # This software is governed by the CeCILL-B license under French law and # abiding by the rules of distribution of free software. You can use, # modify and/ or redistribute the software under the terms of the CeCILL-B # license as circulated by CEA, CNRS and INRIA at the following URL # " http://www.cecill.info". # # As a counterpart to the access to the source code and rights to copy, # modify and redistribute granted by the license, users are provided only # with a limited warranty and the software's author, the holder of the # economic rights, and the successive licensors have only limited # liability. # # In this respect, the user's attention is drawn to the risks associated # with loading, using, modifying and/or developing or reproducing the # software by the user in light of its specific status of free software, # that may mean that it is complicated to manipulate, and that also # therefore means that it is reserved for developers and experienced # professionals having in-depth computer knowledge. Users are therefore # encouraged to load and test the software's suitability as regards their # requirements in conditions enabling the security of their systems and/or # data to be ensured and, more generally, to use and operate it in the # same conditions as regards security. # # The fact that you are presently reading this means that you have had # knowledge of the CeCILL-B license and that you accept its terms. # ############################################################################# import copy from B2SUtils import db_utils
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4.37296
429
import mmcv import numpy as np import torch from mmhuman3d.core.parametric_model.builder import build_registrant from mmhuman3d.models.builder import build_body_model body_model_load_dir = 'data/body_models' batch_size = 2
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3.026667
75
""" * Python program to open, display, and save an image. * """ import skimage.io import skimage.viewer # read image image = skimage.io.imread(fname="chair.jpg") # display image and wait for keypress, using a resizable window viewer = skimage.viewer.ImageViewer(image) viewer.show() # save a new version in .tif format skimage.io.imsave(fname="chair.tif", arr=image)
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2.976
125
import pandas as pd import json from sklearn.feature_extraction.text import CountVectorizer import argparse from functools import reduce if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('-m', '--mode', help='What to do', required=True) parser.add_argument('-d', '--data', help='Data file', required=False) parser.add_argument('-o', '--out_file', help='Output file name prefix', required=False) parser.add_argument('-c', '--col', help='Name of data column to use', required=False) parser.add_argument('-k', '--k', help='Number of words to keep in vocabulary', required=False) args = vars(parser.parse_args()) if args['mode'] == '1': k = int(args['k']) outname = '{}_top{}.txt'.format(args['out_file'], k) prune_vocab_topk(args['data'], args['col'], outname, k=k) else: print("ERROR: doing nothing")
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import torch import torch.nn as nn import torch.nn.functional as F
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#!/usr/bin/env python3 import os import time import logging import requests from emoji import emojize from functools import wraps from pssh.clients import SSHClient from pssh.exceptions import AuthenticationException from requests.exceptions import RequestException from telegram import ReplyKeyboardMarkup, ChatAction, ParseMode from telegram.ext import (Updater, CommandHandler, MessageHandler, Filters, ConversationHandler, DictPersistence) #STATES CONFIGURE, CHOOSE_SERVER, API_CALL, TYPING_REPLY, TYPING_CHOICE, TYPING_CONFIRMATION = range(6) # TODO: proper logging logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO) logger = logging.getLogger(__name__) #keyboards configure_keyboard = [['Done']] configure_markup = ReplyKeyboardMarkup(configure_keyboard, one_time_keyboard=True) confirmation_keyboard = [['Yes', 'No']] confirmation_markup = ReplyKeyboardMarkup(confirmation_keyboard, one_time_keyboard=True) # TODO: dynamic keyboard so that user instead of typing server name can simply tap on the button choose_server_keyboard = [['Pick a server']] choose_server_markup = ReplyKeyboardMarkup(choose_server_keyboard, one_time_keyboard=True) api_calls_keyboard = [['Start all ACs', 'Stop all ACs', 'Get status'], ['Start KMD', 'Stop KMD', 'Available tickers'], ['Change server', 'Server info', 'Launch params']] api_calls_markup = ReplyKeyboardMarkup(api_calls_keyboard, one_time_keyboard=True) #typing action utility func def send_typing_action(func): """Sends typing action while processing func command.""" @wraps(func) return command_func @send_typing_action @send_typing_action #TYPING_REPLY # TODO: end-to-end test to check if the daemon is able to start. # TODO: check if we are able to parse output and provide user with feedback on what is going on during the installation process @send_typing_action #TYPING_CHOICE @send_typing_action @send_typing_action #### API CALLS @send_typing_action @send_typing_action @send_typing_action # STATUS @send_typing_action #START/STOP @send_typing_action @send_typing_action @send_typing_action @send_typing_action @send_typing_action @send_typing_action #CLEANUP @send_typing_action @send_typing_action @send_typing_action @send_typing_action def help(update, context): """Send a message when the command /help is issued.""" help_msg = 'This bot has 3 main states:\n' help_msg += '-----> CONFIGURATION_STATE\n' help_msg += '-----> PICK_SERVER_STATE\n' help_msg += '-----> API_CALL_STATE\n' help_msg += ' \n' help_msg += 'Commands that are accessible throughout all states:\n' help_msg += '/start - sets up a new server.\n' help_msg += '/help - prints this message.\n' help_msg += ' \n' help_msg += 'CONFIGURE_STATE:\n' help_msg += 'You can trigger that state with /start\n' help_msg += 'After you have provided data in the following format (server_name,ip,rootpass), simply tap Done and bot will start installation on a new server.\n' help_msg += 'It usually takes around 2-3 minutes for bot to install/download all dependencies and start API.\n' help_msg += 'If you\'ve provided server ip with already running API, bot will skip installation and forward you to PICK_SERVER_STATE.\n' help_msg += ' \n' help_msg += 'PICK_SERVER_STATE:\n' help_msg += 'In this state you can only pick a server that you\'ve previously added with /start command. Bot will forward you to API_CALL_STATE after you have successfully picked a server.\n' help_msg += ' \n' help_msg += 'API_CALL_STATE:\n' help_msg += 'You will be able to see all available commands on the keyboard. Other than the keyboard commands there are few others:\n' help_msg += '/start_sync AXO BET PANGEA - start tickers individually.\n' help_msg += ' /stop_sync AXO BET PANGEA - stop tickers individually with optional cleanup.\n' update.message.reply_text(help_msg) def error(update, context): """Log Errors caused by Updates.""" logger.warning('Update "{}" caused error "{}"\n\n'.format(update, context.error)) if __name__ == '__main__': main()
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