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from .exceptions import ConsumerUnhealthyException from .exceptions import HandlerTaskCancelled from .exceptions import StopConsumer from .exceptions import UnhandledMessage from .metrics import CONSUMED_MESSAGE_TIME from .metrics import CONSUMED_MESSAGES from .metrics import CONSUMED_MESSAGES_BATCH_SIZE from .metrics import CONSUMER_HEALTH from .metrics import CONSUMER_REBALANCED from .metrics import CONSUMER_TOPIC_OFFSET from .metrics import MESSAGE_LEAD_TIME from .metrics import NOERROR from kafka.structs import TopicPartition import aiokafka import asyncio import fnmatch import functools import inspect import logging import opentracing import orjson import pydantic import time import typing if typing.TYPE_CHECKING: # pragma: no cover from .app import Application else: Application = None logger = logging.getLogger(__name__) def build_handler( coro: typing.Callable, app: "Application", consumer: "BatchConsumer" ) -> typing.Callable: """Introspection on the coroutine signature to inject dependencies""" sig = inspect.signature(coro) param_name = [k for k in sig.parameters.keys()][0] annotation = sig.parameters[param_name].annotation handler = _raw_msg_handler if annotation and annotation != sig.empty: if annotation == bytes: handler = _bytes_msg_handler # type: ignore elif annotation == aiokafka.ConsumerRecord: handler = _record_msg_handler # type: ignore else: handler = functools.partial(_pydantic_msg_handler, annotation) # type: ignore it = iter(sig.parameters.items()) # first argument is required and its the payload next(it) kwargs: typing.Dict[str, typing.Any] = getattr(coro, "__extra_kwargs__", {}) for key, param in it: if key == "schema": kwargs["schema"] = None elif key == "record": kwargs["record"] = None elif key == "app": kwargs["app"] = app elif key == "subscriber": kwargs["subscriber"] = consumer elif issubclass(param.annotation, opentracing.Span): kwargs[key] = opentracing.Span return inner
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2.660147
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# Generated by Django 3.2.5 on 2021-09-26 23:32 from django.db import migrations, models
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2.84375
32
import os, shutil from unittest import mock import swiftclient from django.test import TestCase, tag from django.contrib.auth.models import User from django.conf import settings from feeds.models import Feed, FeedFile from plugins.models import Plugin, PluginParameter, PluginInstance from plugins.models import ComputeResource
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3.638298
94
#!/usr/bin/python3 # -*- conding:utf-8 -*- from . import config from .thread_manager import ThreadManager from .db import Db from .db import BookInfo import os import re import typer import time import requests import logging import rich from urllib.parse import quote from tomd import Tomd from bs4 import BeautifulSoup
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3.23
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from abc import ABC
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3.5
6
""" py_proj ~~~~~~~ Пустой проект на питоне. """ __version__ = '0.0.0'
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import os #import unittest import pybbcsig import binascii def _is_windows(): """ """ return os.name == "nt" sig = pybbcsig.PyBBcSigSecp256k1() in_privkey = b'\xd6Y\xbc#I\xfe\xed\x00\xe1x\xaa\xb4V\xd0\x9c\x01\xe2\x9a\xfd\xd2a\xabf\xcb\x14\xacM\x8e\xca2=\xbb' in_pubkey = b'\x04\x0fd(\xdd\x8fR\xf7@\x86\xe7\x04\x06\xc3K\xecu\xd9\xfe\xe9de\x95\x8c\x16\x0esJ\xe8\x12Q`\xad).\xbd\xfb\x1c\x80\x96p\x12\xb5o\xfdr;\xd8\xa6`\xec\x85i\xad\x14\xceks8\x17&\x7f\xee\xd0\xc1' in_pubkey_compressed = b'\x03\x0fd(\xdd\x8fR\xf7@\x86\xe7\x04\x06\xc3K\xecu\xd9\xfe\xe9de\x95\x8c\x16\x0esJ\xe8\x12Q`\xad' in_test_digest = binascii.a2b_hex("aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa") in_signature_nt = b'Dz\xe5\x84$\xf5_\x19\x9d\xda\x83\x00(O\x91\xec\x18MP\xbd\xef\xa2\x9b\x96\xb3\x9d\xea\xb5\xf9\x93;\xa4\xafB\xe9:\x9e\xa5G\xc79\xe1\xb7\xfaS)\xfd\x82\x0e\xa7\x13|\xe6\xc8\xebX\x91[\x8a$\xe3\xf0\xf4\r' in_signature_posix = b'B)\n@\xe666\xb310z5\x8c\x99\x06u\xe7\xa9}\\\xdc\xa5\x93\x8a\xc6\xb2by\xe1`L\xe8\x95\x18\xd3?\x1f\x1d\x81\x96\xd6\x01\x96\xe2\x80y\x0fz3\xde\xd8\x18\xbd\xbc\xce\xc2\xf6\xdf\xde\x8c\xdd\xb8\xb0\xd5' if _is_windows(): in_signature = in_signature_nt else: in_signature = in_signature_posix in_der_nt = b'0\x82\x01\x13\x02\x01\x01\x04 \xd6Y\xbc#I\xfe\xed\x00\xe1x\xaa\xb4V\xd0\x9c\x01\xe2\x9a\xfd\xd2a\xabf\xcb\x14\xacM\x8e\xca2=\xbb\xa0\x81\xa50\x81\xa2\x02\x01\x010,\x06\x07*\x86H\xce=\x01\x01\x02!\x00\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xfe\xff\xff\xfc/0\x06\x04\x01\x00\x04\x01\x07\x04A\x04y\xbef~\xf9\xdc\xbb\xacU\xa0b\x95\xce\x87\x0b\x07\x02\x9b\xfc\xdb-\xce(\xd9Y\xf2\x81[\x16\xf8\x17\x98H:\xdaw&\xa3\xc4e]\xa4\xfb\xfc\x0e\x11\x08\xa8\xfd\x17\xb4H\xa6\x85T\x19\x9cG\xd0\x8f\xfb\x10\xd4\xb8\x02!\x00\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xff\xfe\xba\xae\xdc\xe6\xafH\xa0;\xbf\xd2^\x8c\xd06AA\x02\x01\x01\xa1D\x03B\x00\x04\x0fd(\xdd\x8fR\xf7@\x86\xe7\x04\x06\xc3K\xecu\xd9\xfe\xe9de\x95\x8c\x16\x0esJ\xe8\x12Q`\xad).\xbd\xfb\x1c\x80\x96p\x12\xb5o\xfdr;\xd8\xa6`\xec\x85i\xad\x14\xceks8\x17&\x7f\xee\xd0\xc1' in_der_posix = b'0t\x02\x01\x01\x04 \xd6Y\xbc#I\xfe\xed\x00\xe1x\xaa\xb4V\xd0\x9c\x01\xe2\x9a\xfd\xd2a\xabf\xcb\x14\xacM\x8e\xca2=\xbb\xa0\x07\x06\x05+\x81\x04\x00\n\xa1D\x03B\x00\x04\x0fd(\xdd\x8fR\xf7@\x86\xe7\x04\x06\xc3K\xecu\xd9\xfe\xe9de\x95\x8c\x16\x0esJ\xe8\x12Q`\xad).\xbd\xfb\x1c\x80\x96p\x12\xb5o\xfdr;\xd8\xa6`\xec\x85i\xad\x14\xceks8\x17&\x7f\xee\xd0\xc1' if _is_windows(): in_der = in_der_nt else: in_der = in_der_posix in_pem_nt = b'-----BEGIN EC PRIVATE KEY-----\nMIIBEwIBAQQg1lm8I0n+7QDheKq0VtCcAeKa/dJhq2bLFKxNjsoyPbuggaUwgaIC\nAQEwLAYHKoZIzj0BAQIhAP////////////////////////////////////7///wv\nMAYEAQAEAQcEQQR5vmZ++dy7rFWgYpXOhwsHApv82y3OKNlZ8oFbFvgXmEg62ncm\no8RlXaT7/A4RCKj9F7RIpoVUGZxH0I/7ENS4AiEA/////////////////////rqu\n3OavSKA7v9JejNA2QUECAQGhRANCAAQPZCjdj1L3QIbnBAbDS+x12f7pZGWVjBYO\nc0roElFgrSkuvfscgJZwErVv/XI72KZg7IVprRTOa3M4FyZ/7tDB\n-----END EC PRIVATE KEY-----\n\x00' in_pem_posix = b'-----BEGIN EC PRIVATE KEY-----\nMHQCAQEEINZZvCNJ/u0A4XiqtFbQnAHimv3SYatmyxSsTY7KMj27oAcGBSuBBAAK\noUQDQgAED2Qo3Y9S90CG5wQGw0vsddn+6WRllYwWDnNK6BJRYK0pLr37HICWcBK1\nb/1yO9imYOyFaa0UzmtzOBcmf+7QwQ==\n-----END EC PRIVATE KEY-----\n\x00' if _is_windows(): in_pem = in_pem_nt else: in_pem = in_pem_posix def test_keypair(): """ """ pubkey, privkey = sig.generate_keypair(0) # print("pubkey = {}".format(pubkey)) # print("privkey = {}".format(privkey)) assert (len(privkey) == 32) assert (len(pubkey) == 65) def test_sign(): """ """ assert (len(in_privkey) == 32) signature = sig.sign(in_privkey, in_test_digest) # 毎回変わる # print("signature = {}".format(signature)) assert (len(signature) == 64) def test_der(): """ """ assert (len(in_privkey) == 32) der = sig.output_der(in_privkey) # print("der = {}".format(der)) # print("len(der) = {}".format(len(der))) if _is_windows(): assert (len(der) == 279) else: assert (len(der) == 118) assert (der == in_der) def test_from_der(): """ """ pubkey, privkey = sig.convert_from_der(in_der, 0) # print("pubkey = {}".format(pubkey)) # print("privkey = {}".format(privkey)) assert (len(privkey) == 32) assert (len(pubkey) == 65) assert (privkey == in_privkey) assert (pubkey == in_pubkey) def test_from_der2(): """ """ if _is_windows(): der = in_der_posix else: der = in_der_nt pubkey, privkey = sig.convert_from_der(der, 0) # print("pubkey = {}".format(pubkey)) # print("privkey = {}".format(privkey)) assert (len(privkey) == 32) assert (len(pubkey) == 65) assert (privkey == in_privkey) assert (pubkey == in_pubkey) def test_pubkey_compressed(): """ """ assert (len(in_privkey) == 32) pubkey = sig.get_public_key_compressed(in_privkey) # print("pubkey = {}".format(pubkey)) # print("len(pubkey) = {}".format(len(pubkey))) assert (len(pubkey) == 33) assert (pubkey == in_pubkey_compressed) def test_pubkey_uncompressed(): """ """ assert (len(in_privkey) == 32) pubkey = sig.get_public_key_uncompressed(in_privkey) # print("pubkey = {}".format(pubkey)) # print("len(pubkey) = {}".format(len(pubkey))) assert (len(pubkey) == 65) assert (pubkey == in_pubkey) def test_verify(): """ """ # print("len(in_signature) = {}".format(len(in_signature))) assert (len(in_signature) == 64) ret = sig.verify(in_pubkey, in_test_digest, in_signature) # print("ret = {}".format(ret)) assert (ret > 0) assert (ret == 1) def test_verify2(): """ """ if _is_windows(): signature = in_signature_posix else: signature = in_signature_nt # print("len(signature) = {}".format(len(signature))) assert (len(signature) == 64) ret = sig.verify(in_pubkey, in_test_digest, signature) # print("ret = {}".format(ret)) assert (ret > 0) assert (ret == 1) def test_pem(): """ """ assert (len(in_privkey) == 32) pem = sig.output_pem(in_privkey) # print("pem = {}".format(pem)) # print("len(pem) = {}".format(len(pem))) if _is_windows(): assert (len(pem) == (438 + 1)) else: assert(len(pem) == (223 + 1)) assert (pem == in_pem) def test_from_pem(): """ """ pubkey, privkey = sig.convert_from_pem(in_pem, 0) # print("pubkey = {}".format(pubkey)) # print("privkey = {}".format(privkey)) assert (len(privkey) == 32) assert (len(pubkey) == 65) assert (privkey == in_privkey) assert(pubkey == in_pubkey) def test_from_pem2(): """ """ if _is_windows(): pem = in_pem_posix else: pem = in_pem_nt pubkey, privkey = sig.convert_from_pem(pem, 0) # print("pubkey = {}".format(pubkey)) # print("privkey = {}".format(privkey)) assert (len(privkey) == 32) assert (len(pubkey) == 65) assert (privkey == in_privkey) assert (pubkey == in_pubkey)
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1.793129
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__author__ = 'pruthvi kumar'
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#!/usr/bin/env python3 # # MIT License # # (C) Copyright 2022 Hewlett Packard Enterprise Development LP # # 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. # import ipaddress import sys import logging, datetime ''' Simple script to ensure that the dhcp-range in the /etc/dnsmasq.d/{net}.conf files are in the correct order. This error was encountered on surtur and caused problems The location of the files is already known, as well as the file names. If that changes this script will break. Because of the number of files in dnsmasq.d this is the only way this check can be accomplished (Can't check all files in the directory) Note: It's possible to get the filenames from GOSS variables, so if the names change, which is a concern, they would only need to be changed in the variables file. USAGE: pyTest-dhcp-reange-in-dnsmasq_d-in-correct-order.py Goss will search the output for the word FAIL ''' # In case we want to make this script more user-friendly and add argparse or configparser # CRITICAL 50, ERROR 40, WARNING 30, INFO 20, DEBUG 10, NOTSET 0 l_lvl = logging.INFO # Start the logger logging.basicConfig(filename='/tmp/' + sys.argv[0].split('/')[-1] + '.log', level=l_lvl) logging.info(now()+" Starting up") fileDir = "/etc/dnsmasq.d/" fileNames = ['CAN', 'NMN', 'HMN', 'mtl' ] contents =[] if __name__ == '__main__': # Iterate over the list of filenames and try to open the file for fileName in fileNames: # clear the start and end strings logging.info(now()+" Checking %s.", fileDir+fileName) start = end = '' try: f = open(fileDir+fileName+".conf", 'r') #contents = f.read().split('\n') except: logging.critical(now()+" Couldn't open %s.", fileDir+fileName+'.conf') print("Unable to open file: "+fileName+".conf") sys.exit(1) # if the contents of the file !NULL - read the file line-by-line # and check if the line contains 'dhcp-range' # it's a really good bet that the format of that line will not change line = f.readline() while line: logging.debug(now() + " line from %s: %s", fileName, line.strip()) # If the line continas 'dhcp-range' extract the start and end addresses if 'dhcp-range' in line: start = line.split(',')[1] end = line.split(',')[2] logging.debug("Start IP = %s, End IP = %s.", start, end) line = f.readline() # If we found the start IP, ensure that it is less than the end IP if start: # They really should be valid ip addresses, but using try/except just in case try: start_ip = ipaddress.ip_address(start) end_ip = ipaddress.ip_address(end) except: logging.critical(now()+" Could not convert either start = %s or end = %s to IP addresses.", start, end) print("FAIL: Conversion of strings to IP addresses failed") sys.exit(2) if start_ip < end_ip: print("PASS") else: logging.error( now()+" The file %s failed. Start IP (%s) >= End IP (%s).", fileDir + fileName + ".conf", start, end) print("FAIL for file:" + fileDir + fileName + ".conf") else: print("FAIL - no starting IP address found")
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2.695679
1,643
from lingrex.copar import CoPaR, density assert CoPaR and density __version__ = "1.1.2.dev0"
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2.611111
36
import os import numpy as np from spherecluster import VonMisesFisherMixture, sample_vMF np.random.seed(1234)
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2.829268
41
import shutil import tempfile import unittest import queuelib from scrapy.squeues import ( PickleFifoDiskQueue, PickleLifoDiskQueue, MarshalFifoDiskQueue, MarshalLifoDiskQueue, FifoMemoryQueue, LifoMemoryQueue, ) from scrapy.http import Request from scrapy.spiders import Spider from scrapy.utils.test import get_crawler """ Queues that handle requests """
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2.821429
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# -*- coding: utf-8 -*- __author__ = 'Ramiro Gómez' __email__ = '[email protected]' __version__ = '5.0.0'
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import bteve as eve gd = eve.Gameduino() gd.init() import pong import fruit import temperature demos = (pong, fruit, temperature) # demos[0].run(gd) sel = 0 prev_touch = False while True: gd.finish() c = gd.controllers()[0] if not prev_touch: if c['bdu']: sel = (sel - 1) if c['bdd']: sel = (sel + 1) sel %= len(demos) prev_touch = any(c[b] for b in ['bdu', 'bdd']) if c['ba']: demos[sel].run(gd) gd.cmd_romfont(30, 30) gd.cmd_romfont(31, 31) gd.Clear() gd.cmd_text(640, 60, 31, eve.OPT_CENTER, "CircuitPython demos") gd.cmd_text(640, 640, 30, eve.OPT_CENTER, "Press A to launch, HOME to return to this menu") for i,d in enumerate(demos): y = 180 + 120 * i if i == sel: gd.cmd_fgcolor(0xa06000) else: gd.cmd_fgcolor(0x003030) gd.cmd_button(320, y, 640, 100, 31, eve.OPT_FLAT, d.__name__) gd.swap()
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#!/usr/bin/env python import pyDNase, pyDNase.footprinting import numpy as np from clint.textui import progress import multiprocessing as mp import argparse __version__ = "0.1.0" parser = argparse.ArgumentParser(description='Scores Differential Footprints using Wellington-Bootstrap.') parser.add_argument("-fp", "--footprint-sizes", help="Range of footprint sizes to try in format \"from,to,step\" (default: 11,26,2)", default="11,26,2", type=str) parser.add_argument("-fdr","--FDR_cutoff", help="Detect footprints using the FDR selection method at a specific FDR (default: 0.01)", default=0.01, type=float) parser.add_argument("-fdriter", "--FDR_iterations", help="How many randomisations to use when performing FDR calculations (default: 100)", default=100, type=int) parser.add_argument("-fdrlimit", "--FDR_limit", help="Minimum p-value to be considered significant for FDR calculation (default: -20)", default=-20, type=int) parser.add_argument("-p", "--processes", help="Number of processes to use (default: uses all CPUs)", default=0, type=int) parser.add_argument("-A", action="store_true", help="ATAC-seq mode (default: False)", default=False) parser.add_argument("treatment_bam", help="BAM file for treatment") parser.add_argument("control_bam", help="BAM file for control") parser.add_argument("bedsites", help="BED file of genomic locations to search in") parser.add_argument("treatment_only_output", help="File to write treatment specific fooprints scores to") parser.add_argument("control_only_output", help="File to write control specific footprint scores to") args = parser.parse_args() # Sanity check parameters from the user try: args.footprint_sizes = xrange_from_string(args.footprint_sizes) except ValueError: raise RuntimeError("Footprint sizes must be supplied as from,to,step") assert 0 < args.FDR_cutoff < 1, "FDR must be between 0 and 1" assert args.FDR_limit <= 0, "FDR limit must be less than or equal to 0 (to disable)" # Treatment reads2 = pyDNase.BAMHandler(args.treatment_bam, caching=0, ATAC=args.A) # Control reads1 = pyDNase.BAMHandler(args.control_bam, caching=0, ATAC=args.A) # Regions of Interest regions = pyDNase.GenomicIntervalSet(args.bedsites) # Output treatment_output = open(args.treatment_only_output, "w", buffering=1) control_output = open(args.control_only_output, "w", buffering=1) # Determine Number of CPUs to use if args.processes: CPUs = args.processes else: CPUs = mp.cpu_count() # NOTE: This roughly scales at about 450mb per 300 regions held in memory max_regions_cached_in_memory = 50 * CPUs p = mp.Pool(CPUs) print("Performing differential footprinting...") for i in progress.bar(regions): # Make sure the interval is actually big enough to footprint to begin with if len(i) < 120: i.startbp -= 60 i.endbp += 60 # Make the optional arguments fp_args = {'footprint_sizes': args.footprint_sizes, 'FDR_cutoff': args.FDR_cutoff, 'FDR_iterations': args.FDR_iterations} # Perform both comparisons - A against B and B against A fp = Diffwell(reads2=reads1, min_score=args.FDR_limit, interval=i, reads=reads2, **fp_args) fp2 = Diffwell(reads2=reads2, min_score=args.FDR_limit, interval=i, reads=reads1, **fp_args) # Push these tasks to the queue p.apply_async(fp, callback=write_treat_to_disk) p.apply_async(fp2, callback=write_control_to_disk) # Hold here while the queue is bigger than the number of reads we're happy to store in memory while p._taskqueue.qsize() > max_regions_cached_in_memory: pass
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ms1 = MyShow() ms1.showName()
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import numpy as np import matplotlib.pyplot as plt from matplotlib.colors import BoundaryNorm from matplotlib.ticker import MaxNLocator from matplotlib import ticker, cm from playground.laiZhaoGui.goa.get_lai_manual_fitting_res import read_lai_manual_fitting_res, read_lai_test_coordinate, pack_lai_manual_fitting_res, wrap_lai_data_4_contour from playground.laiZhaoGui.goa.get_GOAs_fitting_res import get_GOAs_best_fitting_res, pack_GOAs_fit_res, wrap_GOAs_data_4_contour def two_vertical_contour_0(x1_list, y1_list, z1_list, x2_list, y2_list, z2_list): """ Function: 我用各种ECM上最优的前五种GOA拟合的Chi-Squared误差,与赖拟合的误差,分别画在上下两个等高图上 Requirement: 1- 各自 或 一起 拥有colorbar 2- colorbar 上的刻度是对数分布的 3- the range of x-axis is: 0 ~ 17 mm; the range of y-axis is: 0 ~ 2 mm. :return: """ """ Lai Z: Min Max 0.0004402 0.04055 GOA Z: Min Max(1st, too big and weird, delete it) Max(2nd, better and normal) Max(3rd) 0.0033192209598534358 13891082844.471136 54.41158700914487 27.29493804319961 1- Delete the huge abnormal data in z2_list (GOAs' R(RC)_IS_lin-kk_res.txt), (x=1.3,y=0.458,z=13891082844.471136,fn=2-3,ECM-Num=9) 2- Set the value range of colorbar as 1e-4 ~ 1e2, 6 margins """ # 将z_min ~ z_max等分成15份,每个数值区间用一个颜色表示 # z_min = min(min(z1_list), min(z2_list)) # z_max = max(max(z1_list), max(z2_list)) # print(z_min, z_max) # levels = MaxNLocator(nbins=15).tick_values(z.min(), z.max()) # 1- Delete the huge abnormal data in z2_list (GOAs' R(RC)_IS_lin-kk_res.txt), (x=1.3,y=0.458,z=13891082844.471136,fn=2-3,ECM-Num=9) abnormal_index = z2_list.index(max(z2_list)) del x2_list[abnormal_index] del y2_list[abnormal_index] del z2_list[abnormal_index] """ The data format of x, y and z has to be 2D np.array laiZhaoGui has 125(Odd) pieces of data, in order to transfer them into 2D np.array, remove the last data(can not randomly add one piece of data). So laiZhaoGui's data will be 124 ==> 62, 2 Goa has 126(even) pieces of data, in order to transfer them into 2D np.array. So Goa's data will be 126 ==> 63, 2 """ # x,y的数值要按照逐渐变大或变小的规律有序排列,不然图像会乱 xyz1_list = [[x,y,z] for x,y,z in zip(x1_list, y1_list, z1_list)] # sort by y, then sort by x xyz1_list.sort(key=lambda xyz:(xyz[1], xyz[0]), reverse=False) x1_sorted_list = [xyz[0] for xyz in xyz1_list] y1_sorted_list = [xyz[1] for xyz in xyz1_list] z1_sorted_list = [xyz[2] for xyz in xyz1_list] x1_2D_arr = np.array(x1_sorted_list[:len(x1_sorted_list)-1]).reshape((62, 2)) y1_2D_arr = np.array(y1_sorted_list[:len(y1_sorted_list)-1]).reshape((62, 2)) z1_2D_arr = np.array(z1_sorted_list[:len(z1_sorted_list)-1]).reshape((62, 2)) # x1_2D_arr = np.array(x1_list[:len(x1_list)-1]).reshape((62, 2)) # y1_2D_arr = np.array(y1_list[:len(y1_list)-1]).reshape((62, 2)) # z1_2D_arr = np.array(z1_list[:len(z1_list)-1]).reshape((62, 2)) xyz2_list = [[x,y,z] for x,y,z in zip(x2_list, y2_list, z2_list)] xyz2_list.sort(key=lambda xyz:(xyz[1], xyz[0]), reverse=False) x2_sorted_list = [xyz[0] for xyz in xyz2_list] y2_sorted_list = [xyz[1] for xyz in xyz2_list] z2_sorted_list = [xyz[2] for xyz in xyz2_list] x2_2D_arr = np.array(x2_sorted_list).reshape((63, 2)) y2_2D_arr = np.array(y2_sorted_list).reshape((63, 2)) z2_2D_arr = np.array(z2_sorted_list).reshape((63, 2)) # x2_2D_arr = np.array(x2_list).reshape((63, 2)) # y2_2D_arr = np.array(y2_list).reshape((63, 2)) # z2_2D_arr = np.array(z2_list).reshape((63, 2)) # 将z_min ~ z_max等分成6份,每个数值区间用一个颜色表示 level_arr = np.array([10 ** i for i in range(-4, 3)]) # pick the desired colormap, sensible levels, and define a normalization # instance which takes data values and translates those into levels. # cmap = plt.get_cmap('PiYG') cmap = plt.get_cmap('viridis') norm = BoundaryNorm(level_arr, ncolors=cmap.N, clip=True) fig, (ax1, ax2) = plt.subplots(nrows=2) fig.suptitle('Title of two subplots') # contours are *point* based plots, so convert our bound into point # centers # cf1 = ax1.contourf(x1_list, y1_list, z1_list, levels=level_arr, cmap=cmap) # setting the log locator tells contourf to use a log scale: # cf1 = ax1.contourf(x1_2D_arr, y1_2D_arr, z1_2D_arr, locator=ticker.LogLocator(), levels=level_arr, cmap=cmap) # fig.colorbar(cf1, ax=ax1) # ax1.set_title('1 Lai R(RC)_IS_lin-kk_res.txt') # im = ax1.pcolormesh(x, y, z, cmap=cmap, norm=norm) im = ax1.pcolormesh(x1_2D_arr, y1_2D_arr, z1_2D_arr, cmap=cmap, norm=norm) fig.colorbar(im, ax=ax1) ax1.set_title('pcolormesh with levels') # cf2 = ax2.contourf(x2_list, y2_list, z2_list, levels=level_arr, cmap=cmap) cf2 = ax2.contourf(x2_2D_arr, y2_2D_arr, z2_2D_arr, locator=ticker.LogLocator(), levels=level_arr, cmap=cmap) fig.colorbar(cf2, ax=ax2) # ax2.xlim(0,20) # AttributeError: 'AxesSubplot' object has no attribute 'xlim' ax2.set_title('2 GOA R(RC)_IS_lin-kk_res.txt') # ax1.plot(x1, y1, 'o-') # ax1.set_ylabel('Damped oscillation') # ax2.plot(x2, y2, '.-') # ax2.set_xlabel('time (s)') # ax2.set_ylabel('Undamped') plt.xlim(0, 17) plt.ylim(0, 2) plt.show() # 1- Get Lai's manual fitting R(RC)_IS_lin-kk_res.txt and GOAs R(RC)_IS_lin-kk_res.txt # 1.1- Get Lai's manual fitting R(RC)_IS_lin-kk_res.txt lai_manual_fit_res_dict_list = read_lai_manual_fitting_res(ex_fp='../../../datasets/experiement_data/laiZhaoGui/eis/2020-07-22-阻抗类型整理2006.xlsx',\ sheet_name='statistic') coor_dict_list = read_lai_test_coordinate(ex_fp='../../../datasets/experiement_data/laiZhaoGui/eis/坐标.xlsx',\ sheet_name='Sheet1') lai_manual_fit_res_dict_list = pack_lai_manual_fitting_res(lai_manual_fit_res_dict_list,\ coor_dict_list) lai_x_list, lai_y_list, lai_z_list = wrap_lai_data_4_contour(lai_manual_fit_res_dict_list) # 1.2- Get GOAs R(RC)_IS_lin-kk_res.txt goa_fit_res_dict_list = get_GOAs_best_fitting_res(fp='../../playground/laiZhaoGui/goa/R(RC)_IS_lin-kk_res.txt/magNum=2_res') goa_fit_res_dict_list = pack_GOAs_fit_res(goa_fit_res_dict_list, coor_dict_list) goa_x_list, goa_y_list, goa_z_list = wrap_GOAs_data_4_contour(goa_fit_res_dict_list) # 2- Plot contour two_vertical_contour_0(x1_list=lai_x_list, y1_list=lai_y_list, z1_list=lai_z_list,\ x2_list=goa_x_list, y2_list=goa_y_list, z2_list=goa_z_list) """ 我认为失败的原因 1- python 的contourf 要求横纵坐标都是网格状的二维数组,但是我的实际数据(测试点的坐标)不是每行元素个数一致,创建二维数组就意味着,有些位置 上的数字是瞎编的,没有意义,如果填写0,反而意味着拟合的效果非常好,这是错的 2- 之前工作(三元合金)的contour就是用origin画的,应该是可行的 """
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1.745546
3,985
@SingleTon test1 = TestClass() test2 = TestClass() print test1.a, test2.a test1.a = 2 print test1.a, test2.a print id(test1), id(test2)
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2.241935
62
#!/usr/bin/env python3 """Ransom note""" import argparse import os import random # -------------------------------------------------- def get_args(): """Get command-line arguments""" parser = argparse.ArgumentParser( description='Ransom Note', formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('text', metavar='str', help='Input text or file') parser.add_argument('-s', '--seed', help='Random seed', metavar='int', type=int, default=None) args = parser.parse_args() if os.path.isfile(args.text): args.text = open(args.text).read().rstrip() return args # -------------------------------------------------- def choose(char): """Randomly choose an upper or lowercase letter to return""" return char.upper() if random.choice([0, 1]) else char.lower() # -------------------------------------------------- def test_choose(): """Test choose""" random.seed(1) assert choose('a') == 'a' assert choose('b') == 'b' assert choose('c') == 'C' assert choose('d') == 'd' random.seed(None) # -------------------------------------------------- def main(): """Make a jazz noise here""" args = get_args() random.seed(args.seed) # Method 2: Iterate each character, add to a list ransom = [] for char in args.text: ransom += choose(char) print(''.join(ransom)) # -------------------------------------------------- if __name__ == '__main__': main()
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2.656301
611
import pytest from yourcar import YourCarAPIClient, Place LAT_ROSTOCK = 54.0833 LON_ROSTOCK = 12.1333 @pytest.fixture @pytest.fixture @pytest.fixture(scope="module", autouse=True) @pytest.mark.vcr() def test_places_successful(client): """Tests an API call to get places near a location in a given range""" places = client.places(lat=LAT_ROSTOCK, lon=LON_ROSTOCK, distance=2000) assert isinstance(places, list) assert len(places) == 15 first = places[0] assert isinstance(first, Place) assert first.id == "4402" assert first.name == "August-Bebel-Str. 71" assert first.geo_position.latitude == 54.085047 assert first.geo_position.longitude == 12.133862 assert first.distance - 197.9 < 0.1
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from typing import Optional from pydantic import Field from pystratis.api import Model # noinspection PyUnresolvedReferences class ExtPubKeyRequest(Model): """A request model for the wallet/extpubkey endpoint. Args: wallet_name (str): The wallet name. account_name (str, optional): The account name. Default='account 0'. """ wallet_name: str = Field(alias='WalletName') account_name: Optional[str] = Field(default='account 0', alias='AccountName')
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3.141935
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import pandas, hashlib, base64 from Crypto import Random from Crypto.Cipher import AES from util import DataSetting DataFrame = pandas.DataFrame class AES256(DataSetting): """ | 암호화 기술 중 양방향 암호화(AES-256)를 구현한 클래스 | 모든 메소드는 생성자에 원본 데이터를 인자 값으로 넣으면 원본 데이터를 수정한다. Args: datas (pandas.DataFrame) : 양방향 암호화 기술(AES-256 암호화)을 적용할 DataFrame 지정 key (str) : AES-256 암호화에 사용될 암호키 지정 """ def encrypt(self, column: str): """ AES-256 암호화를 수행하는 메소드 Args: column (str) : AES-256 암호화를 적용할 컬럼 Returns: bool : 기술 적용 성공 시 True 리턴 """ datas = self._toList(column) result = [] for raw in datas: raw = self._pad(raw) iv = Random.new().read(AES.block_size) cipher = AES.new(self.key, AES.MODE_CBC, iv) cipherText = base64.b64encode(iv + cipher.encrypt(raw.encode())) result.append(cipherText.decode()) self.datas.loc[:, column] = result return True def decrypt(self, column: str): """ AES-256 복호화를 수행하는 메소드 Args: column (str) : AES-256 복호화를 적용할 컬럼 Returns: bool : 기술 적용 성공 시 True 리턴 """ datas = self._toList(column) result = [] for enc in datas: enc = base64.b64decode(enc.encode()) iv = enc[: AES.block_size] cipher = AES.new(self.key, AES.MODE_CBC, iv) plainText = self._unpad(cipher.decrypt(enc[AES.block_size :])).decode( "utf-8" ) result.append(plainText) self.datas.loc[:, column] = result return True @staticmethod
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#!/usr/bin/python import sys import testmodule config = int(sys.argv[1]) if config == 0: not_debug() not_windows() elif config == 1: not_debug() windows() elif config == 2: debug() not_windows() elif config == 3: debug() windows() else: sys.exit('Invalid argument') print 'checked', config
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2.496241
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# Copyright 2017-2021 Lawrence Livermore National Security, LLC and other # Hatchet Project Developers. See the top-level LICENSE file for details. # # SPDX-License-Identifier: MIT import pytest from hatchet.node import Node, MultiplePathError from hatchet.frame import Frame from hatchet.graph import Graph
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3.72093
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from __future__ import print_function, absolute_import, division #makes KratosMultiphysics backward compatible with python 2.6 and 2.7 from KratosMultiphysics import * from KratosMultiphysics.mpi import * from KratosMultiphysics.MetisApplication import * from KratosMultiphysics.IncompressibleFluidApplication import * from KratosMultiphysics.TrilinosApplication import * from KratosMultiphysics.FluidDynamicsApplication import * # # # # #
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"""A test that is run only by Github Actions This test makes real network requests, so environment variables should be specified in Github Actions. """ import os import pytest from asyncpraw import Reddit from asyncpraw.models import Submission @pytest.mark.skipif( not os.getenv("NETWORK_TEST_CLIENT_ID"), reason="Not running from the NETWORK_TEST ci task on praw-dev/asyncpraw", )
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3.245902
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from pathlib import Path DEFAULT_SEED = None DEFAULT_REPETITIONS = 1 DEFAULT_MAX_DECODER_STEPS = 3000 DEFAULT_SAVE_MEL_INFO_COPY_PATH = Path("/tmp/mel_out.json") # from paper DEFAULT_MCD_NO_OF_COEFFS_PER_FRAME = 16
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2.322581
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# coding:utf-8 import numpy as np import json import pandas as pd pred_file = 'sort_hypo_glge_xsum_ck20_bsz1.txt.dedup' sub_example = 'test_submission_example.jsonl' save_file = 'submit.jsonl' features = [] pred = [] example = [] with open(pred_file, 'r', encoding='utf-8') as infle: for line in infle.readlines(): pred.append(line) dict_pred = {"pred": pred} pd_pred = pd.DataFrame(dict_pred) pd_pred.drop_duplicates() with open(sub_example, 'r', encoding='utf-8') as infle: for line in infle.readlines(): line[pred_scene] example.append(line) with open(save_file, 'w', encoding="utf-8") as fout: for feature in features: fout.write(json.dumps(feature, ensure_ascii=False) + '\n')
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import itertools import operator import random import string from fplib.ident import Id from fplib.list import List from fplib.maybe import (Just, Nothing) from fplib.reader import Reader from fplib.state import State
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3.295775
71
"""Test cases for some parts of the settings.py file.""" from predicators.src import utils from predicators.src.settings import get_allowed_query_type_names def test_get_allowed_query_type_names(): """Test the get_allowed_query_type_names method.""" utils.reset_config() assert get_allowed_query_type_names() == set() utils.reset_config({ "option_learner": "direct_bc", }) assert get_allowed_query_type_names() == {"PathToStateQuery"} utils.reset_config({ "option_learner": "no_learning", "approach": "interactive_learning" }) assert get_allowed_query_type_names() == {"GroundAtomsHoldQuery"} utils.reset_config({ "option_learner": "no_learning", "approach": "unittest" }) assert get_allowed_query_type_names() == { "GroundAtomsHoldQuery", "DemonstrationQuery", "PathToStateQuery", "_MockQuery" }
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2.579545
352
import numpy as np import os from PIL import Image import torch from torch.utils.data import Dataset from data.base_dataset import get_posenet_transform
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3.25
48
from enum import Enum import datetime import base64 if __name__ == "__main__": print("Welcome to imagebusutil module")
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3.175
40
# ----------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # ----------------------------------------------------------------------------- from ..rule_decorators import command_group_rule from ..linter import RuleError @command_group_rule @command_group_rule
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5.390244
82
# Процесс делегирования в Python file = File() instance = Upcase(file) instance.write('test') instance.open() print(instance._outfile) #print(instance.hello()) #print(instance.hello()) #print(instance.write('test')) #print(instance._outfile) #print(instance.write('asd')) #print(instance._outfile) #print(instance._outfile)
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2.527132
129
import sys from yamlSupport.YamlConfigurationSupport import YamlConfigurationSupport from googleSheetSupport.GoogleSheetSupport import GoogleSheetSupport from iosSupport.iOSLocalizationSettings import iOSLocalizationSettings if __name__ == '__main__': args = sys.argv if len(args) < 2: log_menu() elif args[1] == "cnfg": YamlConfigurationSupport.create_default() elif args[1] == "fetch": config = YamlConfigurationSupport.get_config() localizations = GoogleSheetSupport.get_localizations() iOSLocalizationSettings.create(localizations, config) else: log_menu()
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2.859729
221
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2.343994
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""" swearWords Class Author : Sorosh Safari @coci created date : 7 October, 2021 updated date : 11 October, 2021 """ # return string # return boolean # return nothing # return nothing # return boolean # return boolean # return string
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#!/usr/bin/python # -*- coding: utf-8 -*- """ CentralReport - Test script Launchs CentralReport in debug mode, without installation. Please verify CR is not installed on your host before launch this script. https://github.com/miniche/CentralReport/ """ import centralreport import sys import os print '--- CentralReport debug mode. ---' print 'This tool is only for debug purpose. For running CR in production env, use python centralreport.py start instead.' print '---------------------------------' print '' cr = centralreport.CentralReport('/tmp/centralreport_debug.pid') return_value = cr.debug() print '' print '---------------------------------' print 'Ending debug mode' print '---------------------------------' # CentralReport is now stopped, we can kill current process os.system('kill %d' % os.getpid()) sys.exit(0)
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from __future__ import unicode_literals import imaplib import logging import poplib from django.core.exceptions import ValidationError from django.core.files.base import ContentFile from django.db import models from django.utils.encoding import force_bytes from django.utils.translation import ugettext_lazy as _ from mayan.apps.common.serialization import yaml_load from mayan.apps.documents.models import Document from mayan.apps.metadata.api import set_bulk_metadata from mayan.apps.metadata.models import MetadataType from ..exceptions import SourceException from ..literals import ( DEFAULT_IMAP_MAILBOX, DEFAULT_IMAP_SEARCH_CRITERIA, DEFAULT_IMAP_STORE_COMMANDS, DEFAULT_METADATA_ATTACHMENT_NAME, DEFAULT_POP3_TIMEOUT, SOURCE_CHOICE_EMAIL_IMAP, SOURCE_CHOICE_EMAIL_POP3, SOURCE_UNCOMPRESS_CHOICE_N, SOURCE_UNCOMPRESS_CHOICE_Y, ) from .base import IntervalBaseModel __all__ = ('IMAPEmail', 'POP3Email') logger = logging.getLogger(__name__) class EmailBaseModel(IntervalBaseModel): """ POP3 email and IMAP email sources are non-interactive sources that periodically fetch emails from an email account using either the POP3 or IMAP email protocol. These sources are useful when users need to scan documents outside their office, they can photograph a paper document with their phones and send the image to a designated email that is setup as a Mayan POP3 or IMAP source. Mayan will periodically download the emails and process them as Mayan documents. """ host = models.CharField(max_length=128, verbose_name=_('Host')) ssl = models.BooleanField(default=True, verbose_name=_('SSL')) port = models.PositiveIntegerField(blank=True, null=True, help_text=_( 'Typical choices are 110 for POP3, 995 for POP3 over SSL, 143 for ' 'IMAP, 993 for IMAP over SSL.'), verbose_name=_('Port') ) username = models.CharField(max_length=96, verbose_name=_('Username')) password = models.CharField(max_length=96, verbose_name=_('Password')) metadata_attachment_name = models.CharField( default=DEFAULT_METADATA_ATTACHMENT_NAME, help_text=_( 'Name of the attachment that will contains the metadata type ' 'names and value pairs to be assigned to the rest of the ' 'downloaded attachments.' ), max_length=128, verbose_name=_('Metadata attachment name') ) subject_metadata_type = models.ForeignKey( blank=True, help_text=_( 'Select a metadata type valid for the document type selected in ' 'which to store the email\'s subject.' ), on_delete=models.CASCADE, null=True, related_name='email_subject', to=MetadataType, verbose_name=_('Subject metadata type') ) from_metadata_type = models.ForeignKey( blank=True, help_text=_( 'Select a metadata type valid for the document type selected in ' 'which to store the email\'s "from" value.' ), on_delete=models.CASCADE, null=True, related_name='email_from', to=MetadataType, verbose_name=_('From metadata type') ) store_body = models.BooleanField( default=True, help_text=_( 'Store the body of the email as a text document.' ), verbose_name=_('Store email body') ) objects = models.Manager() @staticmethod @staticmethod
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# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. from torch import nn from torch.nn import functional as F import torch from ..box_head.roi_box_feature_extractors import ResNet50Conv5ROIFeatureExtractor from maskrcnn_benchmark.modeling.poolers import Pooler from maskrcnn_benchmark.layers import Conv2d import pdb class PRCNNFeatureExtractor(nn.Module): ''' second stage extractor for paper: Cell Segmentation Proposal Network for Microscopy Image Analysis ''' class MaskRCNNFPNFeatureExtractor(nn.Module): """ Heads for FPN for classification """ def __init__(self, cfg): """ Arguments: num_classes (int): number of output classes input_size (int): number of channels of the input once it's flattened representation_size (int): size of the intermediate representation """ super(MaskRCNNFPNFeatureExtractor, self).__init__() resolution = cfg.MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION scales = cfg.MODEL.ROI_MASK_HEAD.POOLER_SCALES sampling_ratio = cfg.MODEL.ROI_MASK_HEAD.POOLER_SAMPLING_RATIO pooler = Pooler( output_size=(resolution, resolution), scales=scales, sampling_ratio=sampling_ratio, ) input_size = cfg.MODEL.BACKBONE.OUT_CHANNELS self.pooler = pooler layers = cfg.MODEL.ROI_MASK_HEAD.CONV_LAYERS next_feature = input_size self.blocks = [] for layer_idx, layer_features in enumerate(layers, 1): layer_name = "mask_fcn{}".format(layer_idx) module = Conv2d(next_feature, layer_features, 3, stride=1, padding=1) # Caffe2 implementation uses MSRAFill, which in fact # corresponds to kaiming_normal_ in PyTorch nn.init.kaiming_normal_(module.weight, mode="fan_out", nonlinearity="relu") nn.init.constant_(module.bias, 0) self.add_module(layer_name, module) next_feature = layer_features self.blocks.append(layer_name) _ROI_MASK_FEATURE_EXTRACTORS = { "ResNet50Conv5ROIFeatureExtractor": ResNet50Conv5ROIFeatureExtractor, "MaskRCNNFPNFeatureExtractor": MaskRCNNFPNFeatureExtractor, "PRCNNFeatureExtractor":PRCNNFeatureExtractor, 'DeeperExtractor':DeeperExtractor, 'MaskRCNNFPNAdaptor':MaskRCNNFPNAdaptor }
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from auditing.db.Models import Packet import datetime, json import dateutil.parser as dp
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# AUTOGENERATED BY NBDEV! DO NOT EDIT! __all__ = ["index", "modules", "custom_doc_links", "git_url"] index = {"instance_sort": "02_explore.ipynb", "instance_dcmread": "02_explore.ipynb", "instance_show": "02_explore.ipynb", "get_dicom_image": "02_explore.ipynb"} modules = ["one.py", "explore.py"] doc_url = "https://asvcode.github.io/test_fmi/" git_url = "https://github.com/asvcode/test_fmi/tree/master/"
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2.142857
210
f = open("Q3/inputs.txt","r") z = f.readlines() f.close() a = "" b = "" for i in zip(*z): lst = list(i) if lst.count("1") > len(lst)//2: a += "1" b += "0" else: a += "0" b += "1" print(int(a,2)*int(b,2)) f = open("Q3/inputs.txt","r") z = f.readlines() f.close() current_index = 0 while len(z) != 1: lst = list(list(zip(*z))[current_index]) if lst.count("1") > lst.count("0"): z = [i for i in z if i[current_index] == "1"] elif lst.count("1") < lst.count("0"): z = [i for i in z if i[current_index] == "0"] else: z = [i for i in z if i[current_index] == "1"] current_index += 1 a = int(z[0],2) f = open("Q3/inputs.txt","r") z = f.readlines() f.close() current_index = 0 while len(z) != 1: lst = list(list(zip(*z))[current_index]) if lst.count("1") > lst.count("0"): z = [i for i in z if i[current_index] == "0"] elif lst.count("1") < lst.count("0"): z = [i for i in z if i[current_index] == "1"] else: z = [i for i in z if i[current_index] == "0"] current_index += 1 b = int(z[0],2) print(a*b)
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1.923469
588
#!/usr/bin/env python3 import librosa import sys import numpy as np from os import path, listdir import json print('Content-Type: application/json\n\n') print(wav2json('./test.wav'))
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2.859375
64
import os from mfactcheck.utils.log_helper import LogHelper from mfactcheck.multi_retriever.sentences.data import SentProcessor from .mbert import MBert LogHelper.setup() logger = LogHelper.get_logger(os.path.splitext(os.path.basename(__file__))[0])
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2.875
88
import contextlib import datetime import os import logging import re import time from enum import Enum import gmpy2 import sqlite3 class EcmServer: """ECM Server Responsible for recording what curves have been run. """ SCHEMA_FILE = "schema.sql"
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3
91
# -*- coding: utf-8 -*- from __future__ import unicode_literals import logging from CommonMark import DocParser from CommonMark import HTMLRenderer from django.template import TemplateDoesNotExist from django.template.loader import render_to_string from django.utils.encoding import python_2_unicode_compatible from django.utils.functional import cached_property from django.utils.translation import ugettext_lazy as _ from django.db.models import CharField from .utils import valid_md_file from editregions.models import EditRegionChunk logger = logging.getLogger(__name__) @python_2_unicode_compatible
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3.454545
176
from jmetal.core.problem import FloatProblem from jmetal.core.solution import FloatSolution import numpy as np import math import datameclpps260421v1
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2.588235
68
from .core import API
[ 6738, 764, 7295, 1330, 7824 ]
4.2
5
# coding=utf-8 # Copyright 2015 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). from __future__ import (absolute_import, division, generators, nested_scopes, print_function, unicode_literals, with_statement) from pants.backend.python.tasks.checkstyle.new_style_classes import NewStyleClasses from pants_test.backend.python.tasks.checkstyle.plugin_test_base import CheckstylePluginTestBase
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3.150327
153
import urllib.request from pprint import pprint from html_table_parser.parser import HTMLTableParser import pandas as pd import os from parse import parse_taskmaster_csv if __name__ == "__main__": dir_path_to_temp_csvs="temp_csvs" dir_path_final_csvs="final_season_csvs" create_final_raw_csv(dir_path_to_temp_csvs, dir_path_final_csvs) merge_final_dataset(inpath_final_individual_csvs=dir_path_final_csvs)
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2.591463
164
import math import numpy as np import cv2 import sys # # Implement the functions below. def extract_red(image): """ Returns the red channel of the input image. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input RGB (BGR in OpenCV) image. Returns: numpy.array: Output 2D array containing the red channel. """ # Since Red is last index, we want all rows, columns, and the last channel. return np.copy(image[:, :, 2]) def extract_green(image): """ Returns the green channel of the input image. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input RGB (BGR in OpenCV) image. Returns: numpy.array: Output 2D array containing the green channel. """ # Return green channel, all rows, columns return np.copy(image[:, :, 1]) def extract_blue(image): """ Returns the blue channel of the input image. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input RGB (BGR in OpenCV) image. Returns: numpy.array: Output 2D array containing the blue channel. """ # Since blue is the first index, get first channel. return np.copy(image[:, :, 0]) def swap_green_blue(image): """ Returns an image with the green and blue channels of the input image swapped. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input RGB (BGR in OpenCV) image. Returns: numpy.array: Output 3D array with the green and blue channels swapped. """ temp_image = np.copy(image) temp_image[:, :, 0] = extract_green(image) temp_image[:, :, 1] = extract_blue(image) return temp_image def copy_paste_middle(src, dst, shape): """ Copies the middle region of size shape from src to the middle of dst. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Note: Assumes that src and dst are monochrome images, i.e. 2d arrays. Note: Where 'middle' is ambiguous because of any difference in the oddness or evenness of the size of the copied region and the image size, the function rounds downwards. E.g. in copying a shape = (1,1) from a src image of size (2,2) into an dst image of size (3,3), the function copies the range [0:1,0:1] of the src into the range [1:2,1:2] of the dst. Args: src (numpy.array): 2D array where the rectangular shape will be copied from. dst (numpy.array): 2D array where the rectangular shape will be copied to. shape (tuple): Tuple containing the height (int) and width (int) of the section to be copied. Returns: numpy.array: Output monochrome image (2D array) """ src = np.copy(src) dst = np.copy(dst) # height is rows, width is columns src_rows, src_cols = src.shape dst_rows, dst_cols = dst.shape # shape size mid points. shape_mid_rows = int(np.floor(shape[0] / 2)) shape_mid_cols = int(np.floor(shape[1] / 2)) # mid point of the "copy" image copy_mid_row = int(np.floor(src_rows / 2)) copy_mid_col = int(np.floor(src_cols / 2)) # mid points of the paste image. paste_mid_row = int(np.floor(dst_rows / 2)) paste_mid_col = int(np.floor(dst_cols / 2)) # calculate the shifts to make sure copy is correct. r1_dst, r2_dst, c1_dst, c2_dst, r1_src, r2_src, c1_src, c2_src = [ paste_mid_row - shape_mid_rows, paste_mid_row + shape_mid_rows, paste_mid_col - shape_mid_cols, paste_mid_col + shape_mid_cols, copy_mid_row - shape_mid_rows, copy_mid_row + shape_mid_rows, copy_mid_col - shape_mid_cols, copy_mid_col + shape_mid_cols ] dst[r1_dst: r2_dst, c1_dst: c2_dst] = src[r1_src: r2_src, c1_src: c2_src] return dst def image_stats(image): """ Returns the tuple (min,max,mean,stddev) of statistics for the input monochrome image. In order to become more familiar with Numpy, you should look for pre-defined functions that do these operations i.e. numpy.min. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input 2D image. Returns: tuple: Four-element tuple containing: min (float): Input array minimum value. max (float): Input array maximum value. mean (float): Input array mean / average value. stddev (float): Input array standard deviation. """ return 1.*np.min(image), 1.*np.max(image), 1.*np.mean(image), 1.*np.std(image) def center_and_normalize(image, scale): """ Returns an image with the same mean as the original but with values scaled about the mean so as to have a standard deviation of "scale". Note: This function makes no defense against the creation of out-of-range pixel values. Consider converting the input image to a float64 type before passing in an image. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input 2D image. scale (int or float): scale factor. Returns: numpy.array: Output 2D image. """ i_min, i_max, i_mean, i_std = image_stats(image) # take the mean from the image, then divide by the std deviation. We then scale by the # scale factor and then add the mean back into the image. normal_image = (((image-i_mean) / i_std) * scale) + i_mean return normal_image def shift_image_left(image, shift): """ Outputs the input monochrome image shifted shift pixels to the left. The returned image has the same shape as the original with the BORDER_REPLICATE rule to fill-in missing values. See http://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/copyMakeBorder/copyMakeBorder.html?highlight=copy for further explanation. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): Input 2D image. shift (int): Displacement value representing the number of pixels to shift the input image. This parameter may be 0 representing zero displacement. Returns: numpy.array: Output shifted 2D image. """ temp_image = np.copy(image) # take the temp image, all rows, from column defined in shift to end, move shift using border replicate. return cv2.copyMakeBorder(temp_image[:, shift:], 0, 0, 0, shift, cv2.BORDER_REPLICATE) def difference_image(img1, img2): """ Returns the difference between the two input images (img1 - img2). The resulting array must be normalized and scaled to fit [0, 255]. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: img1 (numpy.array): Input 2D image. img2 (numpy.array): Input 2D image. Returns: numpy.array: Output 2D image containing the result of subtracting img2 from img1. """ difference = img1.astype(np.float) - img2.astype(np.float) output_image = np.zeros(difference.shape) cv2.normalize(difference, output_image, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX) # print("Max Value is ", max(output_image.flatten())) # print("Min Value is ", min(output_image.flatten())) return output_image def add_noise(image, channel, sigma): """ Returns a copy of the input color image with Gaussian noise added to channel (0-2). The Gaussian noise mean must be zero. The parameter sigma controls the standard deviation of the noise. The returned array values must not be clipped or normalized and scaled. This means that there could be values that are not in [0, 255]. Note: This function makes no defense against the creation of out-of-range pixel values. Consider converting the input image to a float64 type before passing in an image. It is highly recommended to make a copy of the input image in order to avoid modifying the original array. You can do this by calling: temp_image = np.copy(image) Args: image (numpy.array): input RGB (BGR in OpenCV) image. channel (int): Channel index value. sigma (float): Gaussian noise standard deviation. Returns: numpy.array: Output 3D array containing the result of adding Gaussian noise to the specified channel. """ # generate random noise using the image.shape tuple as the dimensions. gaussian_noise = np.random.randn(*image.shape) * sigma temp_image = np.copy(image) temp_image = (temp_image * 1.0) # make it a float temp_image[:, :, channel] += gaussian_noise[:, :, channel] return temp_image
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from collections import defaultdict import re from utils import open_file from random import random, seed class FixedProbCounter(): '''Reads file in chunks counts the letters and stores the event gets the dictionary with the number of occurrences of each letter using a fixed probability of 1 / 8 '''
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#!/usr/bin/python import sys import numpy as np import matplotlib.pyplot as plt from easypyplot import pdf, color from easypyplot import format as fmt if __name__ == '__main__': main()
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# Generated by Django 2.2.6 on 2019-11-05 16:16 from django.db import migrations, models import django.db.models.deletion
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# # Copyright (c) 2014-2015 Sylvain Peyrefitte # # This file is part of rdpy. # # rdpy is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. # """ RDP Standard security layer """ import sha, md5 import lic, tpkt from t125 import gcc, mcs from rdpy.core.type import CompositeType, CallableValue, Stream, UInt32Le, UInt16Le, String, sizeof, UInt8 from rdpy.core.layer import LayerAutomata, IStreamSender from rdpy.core.error import InvalidExpectedDataException from rdpy.core import log from rdpy.security import rc4 import rdpy.security.rsa_wrapper as rsa class SecurityFlag(object): """ @summary: Microsoft security flags @see: http://msdn.microsoft.com/en-us/library/cc240579.aspx """ SEC_EXCHANGE_PKT = 0x0001 SEC_TRANSPORT_REQ = 0x0002 RDP_SEC_TRANSPORT_RSP = 0x0004 SEC_ENCRYPT = 0x0008 SEC_RESET_SEQNO = 0x0010 SEC_IGNORE_SEQNO = 0x0020 SEC_INFO_PKT = 0x0040 SEC_LICENSE_PKT = 0x0080 SEC_LICENSE_ENCRYPT_CS = 0x0200 SEC_LICENSE_ENCRYPT_SC = 0x0200 SEC_REDIRECTION_PKT = 0x0400 SEC_SECURE_CHECKSUM = 0x0800 SEC_AUTODETECT_REQ = 0x1000 SEC_AUTODETECT_RSP = 0x2000 SEC_HEARTBEAT = 0x4000 SEC_FLAGSHI_VALID = 0x8000 class InfoFlag(object): """ Client capabilities informations """ INFO_MOUSE = 0x00000001 INFO_DISABLECTRLALTDEL = 0x00000002 INFO_AUTOLOGON = 0x00000008 INFO_UNICODE = 0x00000010 INFO_MAXIMIZESHELL = 0x00000020 INFO_LOGONNOTIFY = 0x00000040 INFO_COMPRESSION = 0x00000080 INFO_ENABLEWINDOWSKEY = 0x00000100 INFO_REMOTECONSOLEAUDIO = 0x00002000 INFO_FORCE_ENCRYPTED_CS_PDU = 0x00004000 INFO_RAIL = 0x00008000 INFO_LOGONERRORS = 0x00010000 INFO_MOUSE_HAS_WHEEL = 0x00020000 INFO_PASSWORD_IS_SC_PIN = 0x00040000 INFO_NOAUDIOPLAYBACK = 0x00080000 INFO_USING_SAVED_CREDS = 0x00100000 INFO_AUDIOCAPTURE = 0x00200000 INFO_VIDEO_DISABLE = 0x00400000 INFO_CompressionTypeMask = 0x00001E00 class PerfFlag(object): """ Network performances flag """ PERF_DISABLE_WALLPAPER = 0x00000001 PERF_DISABLE_FULLWINDOWDRAG = 0x00000002 PERF_DISABLE_MENUANIMATIONS = 0x00000004 PERF_DISABLE_THEMING = 0x00000008 PERF_DISABLE_CURSOR_SHADOW = 0x00000020 PERF_DISABLE_CURSORSETTINGS = 0x00000040 PERF_ENABLE_FONT_SMOOTHING = 0x00000080 PERF_ENABLE_DESKTOP_COMPOSITION = 0x00000100 class AfInet(object): """ IPv4 or IPv6 address style """ AF_INET = 0x00002 AF_INET6 = 0x0017 def saltedHash(inputData, salt, salt1, salt2): """ @summary: Generate particular signature from combination of sha1 and md5 @see: http://msdn.microsoft.com/en-us/library/cc241992.aspx @param inputData: strange input (see doc) @param salt: salt for context call @param salt1: another salt (ex : client random) @param salt2: another another salt (ex: server random) @return : MD5(Salt + SHA1(Input + Salt + Salt1 + Salt2)) """ sha1Digest = sha.new() md5Digest = md5.new() sha1Digest.update(inputData) sha1Digest.update(salt[:48]) sha1Digest.update(salt1) sha1Digest.update(salt2) sha1Sig = sha1Digest.digest() md5Digest.update(salt[:48]) md5Digest.update(sha1Sig) return md5Digest.digest() def finalHash(key, random1, random2): """ @summary: MD5(in0[:16] + in1[:32] + in2[:32]) @param key: in 16 @param random1: in 32 @param random2: in 32 @return MD5(in0[:16] + in1[:32] + in2[:32]) """ md5Digest = md5.new() md5Digest.update(key) md5Digest.update(random1) md5Digest.update(random2) return md5Digest.digest() def masterSecret(secret, random1, random2): """ @summary: Generate master secret @param secret: {str} secret @param clientRandom : {str} client random @param serverRandom : {str} server random @see: http://msdn.microsoft.com/en-us/library/cc241992.aspx """ return saltedHash("A", secret, random1, random2) + saltedHash("BB", secret, random1, random2) + saltedHash("CCC", secret, random1, random2) def sessionKeyBlob(secret, random1, random2): """ @summary: Generate master secret @param secret: secret @param clientRandom : client random @param serverRandom : server random """ return saltedHash("X", secret, random1, random2) + saltedHash("YY", secret, random1, random2) + saltedHash("ZZZ", secret, random1, random2) def macData(macSaltKey, data): """ @see: http://msdn.microsoft.com/en-us/library/cc241995.aspx @param macSaltKey: {str} mac key @param data: {str} data to sign @return: {str} signature """ sha1Digest = sha.new() md5Digest = md5.new() #encode length dataLength = Stream() dataLength.writeType(UInt32Le(len(data))) sha1Digest.update(macSaltKey) sha1Digest.update("\x36" * 40) sha1Digest.update(dataLength.getvalue()) sha1Digest.update(data) sha1Sig = sha1Digest.digest() md5Digest.update(macSaltKey) md5Digest.update("\x5c" * 48) md5Digest.update(sha1Sig) return md5Digest.digest() def macSaltedData(macSaltKey, data, encryptionCount): """ @see: https://msdn.microsoft.com/en-us/library/cc240789.aspx @param macSaltKey: {str} mac key @param data: {str} data to sign @param encryptionCount: nb encrypted packet @return: {str} signature """ sha1Digest = sha.new() md5Digest = md5.new() #encode length dataLengthS = Stream() dataLengthS.writeType(UInt32Le(len(data))) encryptionCountS = Stream() encryptionCountS.writeType(UInt32Le(encryptionCount)) sha1Digest.update(macSaltKey) sha1Digest.update("\x36" * 40) sha1Digest.update(dataLengthS.getvalue()) sha1Digest.update(data) sha1Digest.update(encryptionCountS.getvalue()) sha1Sig = sha1Digest.digest() md5Digest.update(macSaltKey) md5Digest.update("\x5c" * 48) md5Digest.update(sha1Sig) return md5Digest.digest() def tempKey(initialKey, currentKey): """ @see: http://msdn.microsoft.com/en-us/library/cc240792.aspx @param initialKey: {str} key computed first time @param currentKey: {str} key actually used @return: {str} temp key """ sha1Digest = sha.new() md5Digest = md5.new() sha1Digest.update(initialKey) sha1Digest.update("\x36" * 40) sha1Digest.update(currentKey) sha1Sig = sha1Digest.digest() md5Digest.update(initialKey) md5Digest.update("\x5c" * 48) md5Digest.update(sha1Sig) return md5Digest.digest() def gen40bits(data): """ @summary: generate 40 bits data from 128 bits data @param data: {str} 128 bits data @return: {str} 40 bits data @see: http://msdn.microsoft.com/en-us/library/cc240785.aspx """ return "\xd1\x26\x9e" + data[:8][-5:] def gen56bits(data): """ @summary: generate 56 bits data from 128 bits data @param data: {str} 128 bits data @return: {str} 56 bits data @see: http://msdn.microsoft.com/en-us/library/cc240785.aspx """ return "\xd1" + data[:8][-7:] def generateKeys(clientRandom, serverRandom, method): """ @param method: {gcc.Encryption} @param clientRandom: {str[32]} client random @param serverRandom: {str[32]} server random @see: http://msdn.microsoft.com/en-us/library/cc240785.aspx @return: MACKey, initialFirstKey128(ClientdecryptKey, serverEncryptKey), initialSecondKey128(ServerDecryptKey, ClientEncryptKey) """ preMasterHash = clientRandom[:24] + serverRandom[:24] masterHash = masterSecret(preMasterHash, clientRandom, serverRandom) sessionKey = sessionKeyBlob(masterHash, clientRandom, serverRandom) macKey128 = sessionKey[:16] initialFirstKey128 = finalHash(sessionKey[16:32], clientRandom, serverRandom) initialSecondKey128 = finalHash(sessionKey[32:48], clientRandom, serverRandom) #generate valid key if method == gcc.EncryptionMethod.ENCRYPTION_FLAG_40BIT: return gen40bits(macKey128), gen40bits(initialFirstKey128), gen40bits(initialSecondKey128) elif method == gcc.EncryptionMethod.ENCRYPTION_FLAG_56BIT: return gen56bits(macKey128), gen56bits(initialFirstKey128), gen56bits(initialSecondKey128) elif method == gcc.EncryptionMethod.ENCRYPTION_FLAG_128BIT: return macKey128, initialFirstKey128, initialSecondKey128 raise InvalidExpectedDataException("Bad encryption method") def updateKey(initialKey, currentKey, method): """ @summary: update session key @param initialKey: {str} Initial key @param currentKey: {str} Current key @return newKey: {str} key to use @see: http://msdn.microsoft.com/en-us/library/cc240792.aspx """ #generate valid key if method == gcc.EncryptionMethod.ENCRYPTION_FLAG_40BIT: tempKey128 = tempKey(initialKey[:8], currentKey[:8]) return gen40bits(rc4.crypt(rc4.RC4Key(tempKey128[:8]), tempKey128[:8])) elif method == gcc.EncryptionMethod.ENCRYPTION_FLAG_56BIT: tempKey128 = tempKey(initialKey[:8], currentKey[:8]) return gen56bits(rc4.crypt(rc4.RC4Key(tempKey128[:8]), tempKey128[:8])) elif method == gcc.EncryptionMethod.ENCRYPTION_FLAG_128BIT: tempKey128 = tempKey(initialKey, currentKey) return rc4.crypt(rc4.RC4Key(tempKey128), tempKey128) class ClientSecurityExchangePDU(CompositeType): """ @summary: contain client random for basic security @see: http://msdn.microsoft.com/en-us/library/cc240472.aspx """ class RDPInfo(CompositeType): """ @summary: Client informations Contains credentials (very important packet) @see: http://msdn.microsoft.com/en-us/library/cc240475.aspx """ class RDPExtendedInfo(CompositeType): """ @summary: Add more client informations """ class SecLayer(LayerAutomata, IStreamSender, tpkt.IFastPathListener, tpkt.IFastPathSender, mcs.IGCCConfig): """ @summary: Standard RDP security layer This layer is Transparent as possible for upper layer """ def __init__(self, presentation): """ @param presentation: Layer (generally pdu layer) """ LayerAutomata.__init__(self, presentation) #thios layer is like a fastpath proxy self._fastPathTransport = None self._fastPathPresentation = None #credentials self._info = RDPInfo(extendedInfoConditional = lambda:(self.getGCCServerSettings().SC_CORE.rdpVersion.value == gcc.Version.RDP_VERSION_5_PLUS)) #True if classic encryption is enable self._enableEncryption = False #Enable Secure Mac generation self._enableSecureCheckSum = False #initialise decrypt and encrypt keys self._macKey = None self._initialDecrytKey = None self._initialEncryptKey = None self._currentDecrytKey = None self._currentEncryptKey = None #counter before update self._nbEncryptedPacket = 0 self._nbDecryptedPacket = 0 #current rc4 tab self._decryptRc4 = None self._encryptRc4 = None def readEncryptedPayload(self, s, saltedMacGeneration): """ @summary: decrypt basic RDP security payload @param s: {Stream} encrypted stream @param saltedMacGeneration: {bool} use salted mac generation @return: {Stream} decrypted """ #if update is needed if self._nbDecryptedPacket == 4096: log.debug("update decrypt key") self._currentDecrytKey = updateKey( self._initialDecrytKey, self._currentDecrytKey, self.getGCCServerSettings().SC_SECURITY.encryptionMethod.value) self._decryptRc4 = rc4.RC4Key(self._currentDecrytKey) self._nbDecryptedPacket = 0 signature = String(readLen = CallableValue(8)) encryptedPayload = String() s.readType((signature, encryptedPayload)) decrypted = rc4.crypt(self._decryptRc4, encryptedPayload.value) #ckeck signature if not saltedMacGeneration and macData(self._macKey, decrypted)[:8] != signature.value: raise InvalidExpectedDataException("bad signature") if saltedMacGeneration and macSaltedData(self._macKey, decrypted, self._nbDecryptedPacket)[:8] != signature.value: raise InvalidExpectedDataException("bad signature") #count self._nbDecryptedPacket += 1 return Stream(decrypted) def writeEncryptedPayload(self, data, saltedMacGeneration): """ @summary: sign and crypt data @param data: {Type} raw stream @param saltedMacGeneration: {bool} use salted mac generation @return: {Tuple} (signature, encryptedData) """ if self._nbEncryptedPacket == 4096: log.debug("update encrypt key") self._currentEncryptKey = updateKey( self._initialEncryptKey, self._currentEncryptKey, self.getGCCServerSettings().SC_SECURITY.encryptionMethod.value) self._encryptRc4 = rc4.RC4Key(self._currentEncryptKey) self._nbEncryptedPacket = 0 self._nbEncryptedPacket += 1 s = Stream() s.writeType(data) if saltedMacGeneration: return (String(macSaltedData(self._macKey, s.getvalue(), self._nbEncryptedPacket - 1)[:8]), String(rc4.crypt(self._encryptRc4, s.getvalue()))) else: return (String(macData(self._macKey, s.getvalue())[:8]), String(rc4.crypt(self._encryptRc4, s.getvalue()))) def recv(self, data): """ @summary: if basic RDP security layer is activate decrypt else pass to upper layer @param data : {Stream} input Stream """ if not self._enableEncryption: self._presentation.recv(data) return securityFlag = UInt16Le() securityFlagHi = UInt16Le() data.readType((securityFlag, securityFlagHi)) if securityFlag.value & SecurityFlag.SEC_ENCRYPT: data = self.readEncryptedPayload(data, securityFlag.value & SecurityFlag.SEC_SECURE_CHECKSUM) self._presentation.recv(data) def send(self, data): """ @summary: if basic RDP security layer is activate encrypt else pass to upper layer @param data: {Type | Tuple} """ if not self._enableEncryption: self._transport.send(data) return flag = SecurityFlag.SEC_ENCRYPT if self._enableSecureCheckSum: flag |= SecurityFlag.SEC_SECURE_CHECKSUM self.sendFlagged(flag, data) def sendFlagged(self, flag, data): """ @summary: explicit send flag method for particular packet (info packet or license packet) If encryption is enable apply it @param flag: {integer} security flag @param data: {Type | Tuple} """ if flag & SecurityFlag.SEC_ENCRYPT: data = self.writeEncryptedPayload(data, flag & SecurityFlag.SEC_SECURE_CHECKSUM) self._transport.send((UInt16Le(flag), UInt16Le(), data)) def recvFastPath(self, secFlag, fastPathS): """ @summary: Call when fast path packet is received @param secFlag: {SecFlags} @param fastPathS: {Stream} """ if self._enableEncryption and secFlag & tpkt.SecFlags.FASTPATH_OUTPUT_ENCRYPTED: fastPathS = self.readEncryptedPayload(fastPathS, secFlag & tpkt.SecFlags.FASTPATH_OUTPUT_SECURE_CHECKSUM) self._fastPathPresentation.recvFastPath(secFlag, fastPathS) def setFastPathListener(self, fastPathListener): """ @param fastPathListener : {IFastPathListener} """ self._fastPathPresentation = fastPathListener def sendFastPath(self, secFlag, fastPathS): """ @summary: Send fastPathS Type as fast path packet @param secFlag: {SecFlags} @param fastPathS: {Stream} type transform to stream and send as fastpath """ if self._enableEncryption: secFlag |= tpkt.SecFlags.FASTPATH_OUTPUT_ENCRYPTED if self._enableSecureCheckSum: secFlag |= tpkt.SecFlags.FASTPATH_OUTPUT_SECURE_CHECKSUM fastPathS = self.writeEncryptedPayload(fastPathS, self._enableSecureCheckSum) self._fastPathTransport.sendFastPath(secFlag, fastPathS) def setFastPathSender(self, fastPathSender): """ @param fastPathSender: {tpkt.FastPathSender} """ self._fastPathTransport = fastPathSender def getUserId(self): """ @return: {integer} mcs user id @see: mcs.IGCCConfig """ return self._transport.getUserId() def getChannelId(self): """ @return: {integer} return channel id of proxy @see: mcs.IGCCConfig """ return self._transport.getChannelId() def getGCCClientSettings(self): """ @return: {gcc.Settings} mcs layer gcc client settings @see: mcs.IGCCConfig """ return self._transport.getGCCClientSettings() def getGCCServerSettings(self): """ @return: {gcc.Settings} mcs layer gcc server settings @see: mcs.IGCCConfig """ return self._transport.getGCCServerSettings() class Client(SecLayer): """ @summary: Client side of security layer """ def connect(self): """ @summary: send client random if needed and send info packet """ self._enableEncryption = self.getGCCClientSettings().CS_CORE.serverSelectedProtocol == 0 if self._enableEncryption: self.sendClientRandom() self.sendInfoPkt() def sendInfoPkt(self): """ @summary: send information packet (with credentials) next state -> recvLicenceInfo """ secFlag = SecurityFlag.SEC_INFO_PKT if self._enableEncryption: secFlag |= SecurityFlag.SEC_ENCRYPT self.sendFlagged(secFlag, self._info) self.setNextState(self.recvLicenceInfo) def sendClientRandom(self): """ @summary: generate and send client random and init session keys """ #generate client random clientRandom = rsa.random(256) self._macKey, self._initialDecrytKey, self._initialEncryptKey = generateKeys( clientRandom, self.getGCCServerSettings().SC_SECURITY.serverRandom.value, self.getGCCServerSettings().SC_SECURITY.encryptionMethod.value) #initialize keys self._currentDecrytKey = self._initialDecrytKey self._currentEncryptKey = self._initialEncryptKey self._decryptRc4 = rc4.RC4Key(self._currentDecrytKey) self._encryptRc4 = rc4.RC4Key(self._currentEncryptKey) #verify certificate if not self.getGCCServerSettings().SC_SECURITY.serverCertificate.certData.verify(): log.warning("cannot verify server identity") #send client random encrypted with serverPublicKey = self.getGCCServerSettings().SC_SECURITY.serverCertificate.certData.getPublicKey() message = ClientSecurityExchangePDU() #reverse because bignum in little endian message.encryptedClientRandom.value = rsa.encrypt(clientRandom[::-1], serverPublicKey)[::-1] self.sendFlagged(SecurityFlag.SEC_EXCHANGE_PKT, message) def recvLicenceInfo(self, s): """ @summary: Read license info packet and check if is a valid client info Wait Demand Active PDU @param s: Stream """ #packet preambule securityFlag = UInt16Le() securityFlagHi = UInt16Le() s.readType((securityFlag, securityFlagHi)) if not (securityFlag.value & SecurityFlag.SEC_LICENSE_PKT): raise InvalidExpectedDataException("waiting license packet") if self._licenceManager.recv(s): self.setNextState() #end of connection step of self._presentation.connect() class Server(SecLayer): """ @summary: Client side of security layer """ def __init__(self, presentation): """ @param presentation: {Layer} """ SecLayer.__init__(self, presentation) self._rsaPublicKey, self._rsaPrivateKey = rsa.newkeys(512) def connect(self): """ @summary: init automata to wait info packet """ self._enableEncryption = self.getGCCClientSettings().CS_CORE.serverSelectedProtocol == 0 if self._enableEncryption: self.setNextState(self.recvClientRandom) else: self.setNextState(self.recvInfoPkt) def getCertificate(self): """ @summary: generate proprietary certificate from rsa public key """ certificate = gcc.ProprietaryServerCertificate() certificate.PublicKeyBlob.modulus.value = rsa.int2bytes(self._rsaPublicKey.n)[::-1] certificate.PublicKeyBlob.pubExp.value = self._rsaPublicKey.e certificate.sign() return gcc.ServerCertificate(certificate) def recvClientRandom(self, s): """ @summary: receive client random and generate session keys @param s: {Stream} """ #packet preambule securityFlag = UInt16Le() securityFlagHi = UInt16Le() s.readType((securityFlag, securityFlagHi)) if not (securityFlag.value & SecurityFlag.SEC_EXCHANGE_PKT): raise InvalidExpectedDataException("waiting client random") message = ClientSecurityExchangePDU() s.readType(message) clientRandom = rsa.decrypt(message.encryptedClientRandom.value[::-1], self._rsaPrivateKey)[::-1] self._macKey, self._initialEncryptKey, self._initialDecrytKey = generateKeys( clientRandom, self.getGCCServerSettings().SC_SECURITY.serverRandom.value, self.getGCCServerSettings().SC_SECURITY.encryptionMethod.value) #initialize keys self._currentDecrytKey = self._initialDecrytKey self._currentEncryptKey = self._initialEncryptKey self._decryptRc4 = rc4.RC4Key(self._currentDecrytKey) self._encryptRc4 = rc4.RC4Key(self._currentEncryptKey) self.setNextState(self.recvInfoPkt) def recvInfoPkt(self, s): """ @summary: receive info packet from client Client credentials Send License valid error message Send Demand Active PDU Wait Confirm Active PDU @param s: {Stream} """ securityFlag = UInt16Le() securityFlagHi = UInt16Le() s.readType((securityFlag, securityFlagHi)) if not (securityFlag.value & SecurityFlag.SEC_INFO_PKT): raise InvalidExpectedDataException("Waiting info packet") if securityFlag.value & SecurityFlag.SEC_ENCRYPT: s = self.readEncryptedPayload(s, securityFlag.value & SecurityFlag.SEC_SECURE_CHECKSUM) s.readType(self._info) #next state send error license self.sendLicensingErrorMessage() #reinit state self.setNextState() self._presentation.connect() def sendLicensingErrorMessage(self): """ @summary: Send a licensing error data """ self.sendFlagged(SecurityFlag.SEC_LICENSE_PKT, lic.createValidClientLicensingErrorMessage())
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import pymongo from django.conf import settings from sqlalchemy import create_engine, inspect from sqlalchemy import MetaData from pymongo_schema.extract import extract_pymongo_client_schema from pymongo_schema.tosql import mongo_schema_to_mapping from apps.schema.models import Database, Table, Column, Index if __name__ == '__main__': run()
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114
#!/usr/bin/python3 import sys sys.path.append('../ry') from libry import * K = Config() D = K.view() K.addFile('../test/kitchen.g') K.addFile('../rai-robotModels/pr2/pr2.g') K.addFrame('item1', 'sink1', 'type:ssBox Q:<t(-.1 -.1 .52)> size:[.1 .1 .25 .02] color:[1. 0. 0.], contact' ) K.addFrame('item2', 'sink1', 'type:ssBox Q:<t(.1 .1 .52)> size:[.1 .1 .25 .02] color:[1. 1. 0.], contact' ) K.addFrame("tray", "stove1", "type:ssBox Q:<t(.0 .0 .42)> size:[.2 .2 .05 .02] color:[0. 1. 0.], contact" ) obj1 = 'item2' obj2 = 'item1' arm='pr2L' tray = "tray"; table='_12' T = 6 komo = K.komo_CGO(T) #komo.makeObjectsFree([obj1, obj2]) komo.addObjective(confs=[3], type=OT.ineq, feature=FS.distance, frames=[obj1, obj2], target=[-.05]) # distance between objects! komo.addObjective(type=OT.eq, feature=FS.accumulatedCollisions) komo.addObjective(type=OT.ineq, feature=FS.jointLimits) komo.add_StableRelativePose(confs=[0, 1], gripper=arm, object=obj1) komo.add_StableRelativePose(confs=[2, 3], gripper=arm, object=obj2) komo.add_StableRelativePose(confs=[4, 5], gripper=arm, object=tray) komo.add_StableRelativePose(confs=[1,2,3,4,5], gripper=tray, object=obj1) komo.add_StableRelativePose(confs=[3,4,5], gripper=tray, object=obj2) komo.add_StablePose(confs=[-1, 0], object=obj1) komo.add_StablePose(confs=[-1, 0, 1, 2], object=obj2) komo.add_StablePose(confs=[-1, 0, 1, 2, 3, 4], object=tray) komo.add_grasp(0, arm, obj1) komo.add_place(1, obj1, tray) komo.add_grasp(2, arm, obj2) komo.add_place(3, obj2, tray) komo.add_grasp(4, arm, tray) komo.add_place(5, tray, table) # komo.add_resting(-1, 0, obj1) # komo.add_restingRelative(0, 1 , obj1, arm) # komo.add_resting(1, 2, obj1) # komo.add_resting(2, 3, obj1) # komo.add_resting(-1, 0, obj2) # komo.add_resting(0, 1, obj2) # komo.add_resting(1, 2, obj2) # komo.add_restingRelative(2, 3 , obj2, arm) komo.optimize() for t in range(-1, T): komo.getConfiguration(t) input("Press Enter to continue...")
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2.090234
942
import pytest @pytest.fixture
[ 11748, 12972, 9288, 628, 198, 31, 9078, 9288, 13, 69, 9602, 198 ]
2.666667
12
#!/usr/bin/env python # -*- coding: utf-8 -*- """ ------------------------------------------------- @ Author : pengj @ date : 2019/11/25 21:07 @ IDE : PyCharm @ GitHub : https://github.com/JackyPJB @ Contact : [email protected] ------------------------------------------------- Description : ------------------------------------------------- """ import base64 import io from flask import Flask, request, g, send_file from flask_cors import CORS from app import jsonReturn from app.utils.jwt import JWT from app.models.User import User, Role, Permission from config import load_config __author__ = 'Max_Pengjb'
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2.796813
251
import invoke #import minchin.releaser try: from minchin.releaser import make_release, vendorize except ImportError: print("[WARN] minchin.releaser not installed")
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3.035088
57
#-*- coding: utf-8 -*- from __future__ import unicode_literals import Image import ImageDraw import time import ImageFont from rgbmatrix import Adafruit_RGBmatrix # Rows and chain length are both required parameters: matrix = Adafruit_RGBmatrix(32, 4) font=ImageFont.load_default() font=ImageFont.truetype("DejaVuSerif.ttf",size=11) img=Image.new('RGB',(128,32)) text1="Fååm fååm" text2="Fååm fååm" text3="Fåm vi lite upp i kosi" text4="Jengan gå jengan gå jengan gå jengan teee" for n in range(1,3,1): time.sleep(0.5) img=Image.new('RGB',(128,32)) d=ImageDraw.Draw(img) d.text((-1,0),text1,fill=(0,200,200),font=font) matrix.SetImage(img.im.id, 0, 0) time.sleep(3) img=Image.new('RGB',(128,32)) d=ImageDraw.Draw(img) d.text((-1,0),text2,fill=(200,200,0),font=font) matrix.SetImage(img.im.id, 65, 0) time.sleep(3) img=Image.new('RGB',(128,32)) d=ImageDraw.Draw(img) d.text((-1,0),text3,fill=(0,200,0),font=font) matrix.SetImage(img.im.id, 0, 15) time.sleep(5.5) matrix.Clear() font=ImageFont.truetype("DejaVuSerif.ttf",size=14) img=Image.new('RGB',(300,32)) d=ImageDraw.Draw(img) d.text((1,0),text4,fill=(200,0,200),font=font) for n in range(128, -img.size[0], -1): # Scroll R to L matrix.SetImage(img.im.id, n, 8) time.sleep(0.018) # //: Fåm, fåm, fåm, fåm, fåm vi lite opp i kosa :// # Jen gang och jen gang och jen gang och jen gang te # Jen gang och jen gang och jen gang och jen gang te
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2.146526
662
# coding: utf-8 # In[17]: import datetime from kafka import KafkaConsumer import boto3 import json import base64 # Fire up the Kafka Consumer topic = "testpico" brokers = ["35.189.130.4:9092"] # Initialising Kafka consumer(Lambda) with topic consumer = KafkaConsumer( topic, bootstrap_servers=brokers, value_deserializer=lambda m: json.loads(m.decode('utf-8'))) # In[18]: # Initialising AWS session using Secrey Keys session = boto3.session.Session(aws_access_key_id='XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX', aws_secret_access_key='XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX', region_name='us-west-2') # Reading every message in the consumer topic(queue) followed by decoding at the producer for msg in consumer: img_bytes = base64.b64decode(msg.value['image_bytes']) # Initializing the AWS Rekognition System rekog_client = session.client('rekognition') # Sending the Image byte array to the AWS Rekognition System to detect the text in the image response = rekog_client.detect_text(Image={'Bytes':img_bytes}) # Capturing the text detections from the AWS Rekognition System response textDetections=response['TextDetections'] for text in textDetections: print ('Detected text:' + text['DetectedText']) print ('Confidence: ' + "{:.2f}".format(text['Confidence']) + "%") print("#"*50) # In[ ]:
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2.548276
580
import json import pathlib from substratools import algo, exceptions from substratools.workspace import CompositeAlgoWorkspace import pytest @pytest.fixture(autouse=True) @pytest.fixture @pytest.fixture @pytest.fixture @pytest.mark.parametrize("fake_data,n_fake_samples,expected_pred", [ (False, 0, []), (True, 1, []), ]) @pytest.mark.parametrize('algo_class', ( NoSavedTrunkModelAggregateAlgo, NoSavedHeadModelAggregateAlgo, WrongSavedTrunkModelAggregateAlgo, WrongSavedHeadModelAggregateAlgo ))
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2.568075
213
# -------------------------------------------------------------------------- # 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. # -------------------------------------------------------------------------- # pylint: disable=protected-access # pylint: disable=no-self-use import argparse from collections import defaultdict from knack.util import CLIError
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4.618705
139
""" Defining Class of custom environment for V-Rep @author: hussein """ import vrep_env from vrep_env import vrep import os vrep_scenes_path = os.environ['/home/hussein/Desktop/Multi-agent-path-planning/Reinforcement Learning/examples/scenes'] import rclpy from rclpy.node import Node from tf2_msgs.msg import TFMessage from std_msgs.msg import Float32 import sim import math import gym from gym import spaces from gym.utils import seeding import numpy as np import time L = 1 # Parameter of robot d = 0.5 # Parameter of robot A = np.ones(6) - np.identity(6) # Adjancency Matrix fully connected case 6x6 ux = np.zeros((6,1)) # 6x1 uy = np.zeros((6,1)) # 6x1 " Connecting to V-Rep " sim.simxFinish(-1) # just in case, close all opened connections clientID=sim.simxStart('127.0.0.1',19997,True,True,-500000,5) # Connect to CoppeliaSim N_SCENES = 80 scenes = np.hstack(( np.random.uniform(-2,2,size=(N_SCENES,2)), np.random.uniform(0,np.pi,size=(N_SCENES,1)), np.random.uniform(-2,2,(N_SCENES,2)), np.random.uniform(0,np.pi,size=(N_SCENES,1)) )) """ Description: Consensus environment of 6 robots, where each episode they converge towards each other. DQN applied to robot 1 and rest are controlled with the consensus algorithm. Source: This environment corresponds to V-Rep simulator, integrated with ROS to publish actions & subscribe to observations. Observation: Type: Box(4) Num Observation Min Max 0 Mx -4.8 4.8 1 My -4.8 4.8 2 Phix -4.8 4.8 3 Phiy -4.8 4.8 Actions: Type: Discrete(4) Num Action 0 Move the robot upwards 1 Move the robot downwards 2 Move the robot to the left 3 Move the robot to the right """
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2.207719
881
# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: mixer/v1/config/client/service.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from gogoproto import gogo_pb2 as gogoproto_dot_gogo__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='mixer/v1/config/client/service.proto', package='istio.mixer.v1.config.client', syntax='proto3', serialized_options=_b('Z#istio.io/api/mixer/v1/config/client\310\341\036\000\250\342\036\000\360\341\036\000\330\342\036\001'), serialized_pb=_b('\n$mixer/v1/config/client/service.proto\x12\x1cistio.mixer.v1.config.client\x1a\x14gogoproto/gogo.proto\"\xc7\x01\n\x0cIstioService\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x11\n\tnamespace\x18\x02 \x01(\t\x12\x0e\n\x06\x64omain\x18\x03 \x01(\t\x12\x0f\n\x07service\x18\x04 \x01(\t\x12\x46\n\x06labels\x18\x05 \x03(\x0b\x32\x36.istio.mixer.v1.config.client.IstioService.LabelsEntry\x1a-\n\x0bLabelsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\x42\x35Z#istio.io/api/mixer/v1/config/client\xc8\xe1\x1e\x00\xa8\xe2\x1e\x00\xf0\xe1\x1e\x00\xd8\xe2\x1e\x01\x62\x06proto3') , dependencies=[gogoproto_dot_gogo__pb2.DESCRIPTOR,]) _ISTIOSERVICE_LABELSENTRY = _descriptor.Descriptor( name='LabelsEntry', full_name='istio.mixer.v1.config.client.IstioService.LabelsEntry', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='key', full_name='istio.mixer.v1.config.client.IstioService.LabelsEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='value', full_name='istio.mixer.v1.config.client.IstioService.LabelsEntry.value', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=_b('8\001'), is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=247, serialized_end=292, ) _ISTIOSERVICE = _descriptor.Descriptor( name='IstioService', full_name='istio.mixer.v1.config.client.IstioService', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='name', full_name='istio.mixer.v1.config.client.IstioService.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='namespace', full_name='istio.mixer.v1.config.client.IstioService.namespace', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='domain', full_name='istio.mixer.v1.config.client.IstioService.domain', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='service', full_name='istio.mixer.v1.config.client.IstioService.service', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='labels', full_name='istio.mixer.v1.config.client.IstioService.labels', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[_ISTIOSERVICE_LABELSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=93, serialized_end=292, ) _ISTIOSERVICE_LABELSENTRY.containing_type = _ISTIOSERVICE _ISTIOSERVICE.fields_by_name['labels'].message_type = _ISTIOSERVICE_LABELSENTRY DESCRIPTOR.message_types_by_name['IstioService'] = _ISTIOSERVICE _sym_db.RegisterFileDescriptor(DESCRIPTOR) IstioService = _reflection.GeneratedProtocolMessageType('IstioService', (_message.Message,), { 'LabelsEntry' : _reflection.GeneratedProtocolMessageType('LabelsEntry', (_message.Message,), { 'DESCRIPTOR' : _ISTIOSERVICE_LABELSENTRY, '__module__' : 'mixer.v1.config.client.service_pb2' # @@protoc_insertion_point(class_scope:istio.mixer.v1.config.client.IstioService.LabelsEntry) }) , 'DESCRIPTOR' : _ISTIOSERVICE, '__module__' : 'mixer.v1.config.client.service_pb2' # @@protoc_insertion_point(class_scope:istio.mixer.v1.config.client.IstioService) }) _sym_db.RegisterMessage(IstioService) _sym_db.RegisterMessage(IstioService.LabelsEntry) DESCRIPTOR._options = None _ISTIOSERVICE_LABELSENTRY._options = None # @@protoc_insertion_point(module_scope)
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from typing import List from src.types.header_block import HeaderBlock def verify_weight( tip: HeaderBlock, proof_blocks: List[HeaderBlock], fork_point: HeaderBlock ) -> bool: """ Verifies whether the weight of the tip is valid or not. Naively, looks at every block from genesis, verifying proof of space, proof of time, and difficulty resets. # TODO: implement """ for height, block in enumerate(proof_blocks): if not block.height == height + fork_point.height + 1: return False return True
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""" __author__: Jamin Becker ([email protected]) """ import os import sys import time import socket import logging import pathlib import warnings from hashlib import md5 import psutil import pyshark import progressbar from magic import from_buffer from terminaltables import AsciiTable from packettotal_sdk.packettotal_api import PacketTotalApi from honeybot.lib import const def capture_on_interface(interface, name, timeout=60): """ :param interface: The name of the interface on which to capture traffic :param name: The name of the capture file :param timeout: A limit in seconds specifying how long to capture traffic """ if timeout < 15: logger.error("Timeout must be over 15 seconds.") return if not sys.warnoptions: warnings.simplefilter("ignore") start = time.time() widgets = [ progressbar.Bar(marker=progressbar.RotatingMarker()), ' ', progressbar.FormatLabel('Packets Captured: %(value)d'), ' ', progressbar.Timer(), ] progress = progressbar.ProgressBar(widgets=widgets) capture = pyshark.LiveCapture(interface=interface, output_file=os.path.join('tmp', name)) pcap_size = 0 for i, packet in enumerate(capture.sniff_continuously()): progress.update(i) if os.path.getsize(os.path.join('tmp', name)) != pcap_size: pcap_size = os.path.getsize(os.path.join('tmp', name)) if not isinstance(packet, pyshark.packet.packet.Packet): continue if time.time() - start > timeout: break if pcap_size > const.PT_MAX_BYTES: break capture.clear() capture.close() return pcap_size def get_filepath_md5_hash(file_path): """ :param file_path: path to the file being hashed :return: the md5 hash of a file """ with open(file_path, 'rb') as afile: return get_file_md5_hash(afile) def get_mac_address_of_interface(interface): """ :param interface: The friendly name of a network interface :return: the MAC address associated with that interface """ for k,v in psutil.net_if_addrs().items(): if interface == k: for item in v: try: if item.family == socket.AF_LINK: return item.address except AttributeError: # Linux if item.family == socket.AF_PACKET: return item.address return None def gen_unique_id(interface): """ Generates a unique ID based on your MAC address that will be used to tag all PCAPs uploaded to PacketTotal.com This ID can be used to search and view PCAPs you have uploaded. :param interface: The friendly name of a network interface :return: A unique id """ mac_address = get_mac_address_of_interface(interface) if mac_address: return get_str_md5_hash(get_str_md5_hash(mac_address))[0:15] return None def get_file_md5_hash(fh): """ :param fh: file handle :return: the md5 hash of the file """ block_size = 65536 md5_hasher = md5() buf = fh.read(block_size) while len(buf) > 0: md5_hasher.update(buf) buf = fh.read(block_size) return md5_hasher.hexdigest() def get_network_interfaces(): """ :return: A list of valid interfaces and their addresses """ return psutil.net_if_addrs().items() def is_packet_capture(bytes): """ :param bytes: raw bytes :return: True is valid pcap or pcapng file """ result = from_buffer(bytes) valid = "pcap-ng" in result or "tcpdump" in result or "NetMon" in result or 'pcap capture file' in result return valid def mkdir_p(path): """ :param path: Path to the new directory to create """ pathlib.Path(path).mkdir(parents=True, exist_ok=True) def listen_on_interface(interface, timeout=60): """ :param interface: The name of the interface on which to capture traffic :return: generator containing live packets """ start = time.time() capture = pyshark.LiveCapture(interface=interface) for item in capture.sniff_continuously(): if timeout and time.time() - start > timeout: break yield item def print_network_interaces(): """ :return: Prints a human readable representation of the available network interfaces """ for intf, items in get_network_interfaces(): table = [["family", "address", "netmask", "broadcast", "ptp"]] for item in items: family, address, netmask, broadcast, ptp = item table.append([str(family), str(address), str(netmask), str(broadcast), str(ptp)]) print(AsciiTable(table_data=table, title=intf).table) print('\n') def print_pt_ascii_logo(): """ :return: Prints a PacketTotal.com (visit https://PacketTotal.com!) """ logo = """ ,,*****, ,****, ****/**, / ,*//*, ****/**, ,,**********,. ****** .. .,*****, .. ******** ************,. . . .,,***, ,******, .,***,,.. *****////***, ,***, ... ,******, ,******, .,******** *****////***,. ****, .,,****, ,******, ,******, ,******** ************, ./// /////* // ////// /( ////// /( *///// ************ ****,. ,,******. ,******. ,******, .******,,.,******,. * *****, ********, ,******, ,******, .,********.,******** ,*******, *****, ********, ,******, ,******, .,********.,******** ****//**, *****, /*******, ,******* *//////* ********/ ,******** ****//**, ////* / .////// ((.(((((( ## (((((( (& /((((( % ////// ,******** . ,,,,,. ,,,,,,,,. ,,*****, ,******, ,*****,,,..,,,,,,,. .,,,,,, *****, /*******, *//////* *//////* .*//////*/.*********,,*****, *****, /*******, *//////* (. ( *////////.*********,,****** *****, /******** */////(* ..,,,,,,.. (/////// ********* ******* ////* / ,/((((/ #@,####*..,**********,. /####. & /(((((. @ *//// ,,,,,. ..,,,,*,, ,**, ,*****////*****,./***,. ,,,,,,,.. .,,,,, ,***, /*****//* */// .,***//(##((/****, /////,*//******,,***, ****, /*****//* *//* ,****/(%&&%(//**,, ////(,*//******,,**** ****, /*****//* *//* ,***//(##(//***** *///( *//******.***, *** ( **///// #@//((. ******////****** /(((* @ //////* **, ,,. ..,,,,,,, ,****,. ************ .,****,. ,,,,,,,.. ,,* *, /******** *//////, ,****, ,////////.*********,,* * /*******, *//////* ,******, .*////////.*********,, /******** *//////* *//////* *//////*/ ********* *******,# ////////# ////////# //////* /****** ,,,,,..((.,,,,,,.(#.,,,,,,.(#.,,,,,,..(..,,,,, * *****, ,******, *//////* .,*******/.,***** ***, ,******, ,******, .,********.,*** / * ,*, ,******, ,******, ,********.,* . *******/ *******/ ,******* , ,,,,,..// .,,,,..// .,,,,, / .****, ,******, .,****, / / *** ,******, *** ******** # - honeybot: Capture and analyze network traffic; powered by PacketTotal.com : VERSION: {} """.format(const.VERSION) print(logo) # Setup Logging mkdir_p('logs/') mkdir_p('tmp/') logger = logging.getLogger('honeybot.utils') logger.setLevel(logging.DEBUG) fh = logging.FileHandler('logs/honeybot.log') ch = logging.StreamHandler() ch.setLevel(logging.DEBUG) fh.setLevel(logging.DEBUG) formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s') fh.setFormatter(formatter) ch.setFormatter(formatter) logger.addHandler(fh) logger.addHandler(ch)
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2.187232
3,728
import unittest from shexer.shaper import Shaper from test.const import G1, BASE_FILES, default_namespaces from shexer.consts import JSON, FIXED_SHAPE_MAP from test.t_utils import file_vs_str_tunned_comparison import os.path as pth from shexer.consts import TURTLE _BASE_DIR = BASE_FILES + "shape_map" + pth.sep
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2.683761
117
from django.contrib import admin from .models import * admin.site.register(Product) admin.site.register(Category) admin.site.register(Review)
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3.325581
43
# -*- coding: utf-8 -*- import logging from collections import namedtuple import aesara_theano_fallback.tensor as tt import numpy as np import pymc3 as pm import pytest from pymc3.tests.test_distributions import R, Unit, Vector from pymc3.tests.test_transforms import check_transform, get_values from scipy.stats import beta, halfnorm, kstest, rayleigh from exoplanet.distributions import transforms as tr from exoplanet.distributions.eccentricity import kipping13, vaneylen19 from exoplanet.distributions.physical import ImpactParameter, QuadLimbDark
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3.111111
180
from django import forms from django.core.validators import URLValidator from django.core.exceptions import ValidationError from bambu_webhooks.models import Receiver from bambu_webhooks import site
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3.6
55
""" Ansible module for determining if an installed version of Open vSwitch is incompatible with the currently installed version of OpenShift. """ from openshift_checks import OpenShiftCheck, OpenShiftCheckException, get_var from openshift_checks.mixins import NotContainerizedMixin class OvsVersion(NotContainerizedMixin, OpenShiftCheck): """Check that packages in a package_list are installed on the host and are the correct version as determined by an OpenShift installation. """ name = "ovs_version" tags = ["health"] openshift_to_ovs_version = { "3.6": "2.6", "3.5": "2.6", "3.4": "2.4", } # map major release versions across releases # to a common major version openshift_major_release_version = { "1": "3", } @classmethod def is_active(cls, task_vars): """Skip hosts that do not have package requirements.""" group_names = get_var(task_vars, "group_names", default=[]) master_or_node = 'masters' in group_names or 'nodes' in group_names return super(OvsVersion, cls).is_active(task_vars) and master_or_node def get_required_ovs_version(self, task_vars): """Return the correct Open vSwitch version for the current OpenShift version""" openshift_version = self._get_openshift_version(task_vars) if float(openshift_version) < 3.5: return self.openshift_to_ovs_version["3.4"] ovs_version = self.openshift_to_ovs_version.get(str(openshift_version)) if ovs_version: return self.openshift_to_ovs_version[str(openshift_version)] msg = "There is no recommended version of Open vSwitch for the current version of OpenShift: {}" raise OpenShiftCheckException(msg.format(openshift_version))
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2.717095
661
from .filealchemy import FileAlchemy, LoadError # NOQA from .common import ColumnMapping
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3.461538
26
from punting.twodim.twodimensions import to_flat_exacta,from_flat_exacta,to_flat_quinella, from_flat_quinella from punting.onedim.onenormalization import to_normalized_dividends, to_normalized_probabilities def to_normalized_quinella_probabilities(q,scr=-1): """ :param q: 2-d representation :param scr: :return: 2-d representation """ fq = to_normalized_probabilities( to_flat_quinella(q), scr=scr ) return from_flat_quinella(fq, diag_val=0) def to_normalized_quinella_dividends(q,scr=-1): """ Convert 2-d representation of probabilities to dividends :param q: :param scr: :return: """ fd = to_normalized_dividends( to_flat_quinella(q), scr=scr ) return from_flat_quinella(fd, diag_val=-1) def to_normalized_exacta_probabilities(x,scr=-1): """ :param x: 2-d representation :param scr: :return: 2-d representation """ fx = to_normalized_probabilities( to_flat_exacta(x), scr=scr ) return from_flat_exacta(fx, diag_value=0) def to_normalized_exacta_dividends(x,scr=-1): """ Convert 2-d representation of probabilities to dividends :param x: :param scr: :return: """ fx = to_normalized_dividends( to_flat_exacta(x), scr=scr ) return from_flat_exacta(fx, diag_value=scr)
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2.359489
548
#!/usr/bin/env python from ctypes import * from dwfconstants import * import time,sys
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2.966667
30
MINUTE_TIME_UNIT_MULTIPLIER = { "hours": 60, "minutes": 1 }
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1.914286
35
import math import torch import torch.nn as nn from torch.nn import init from torch.nn import functional as F from torch.nn import Parameter import numpy as np import cv2 from models.resnet import resnet50 from utils.calc_acc import calc_acc from layers import TripletLoss from layers import CenterTripletLoss from layers import CenterLoss from layers import cbam from layers import NonLocalBlockND
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3.526316
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#!/usr/bin/env python # coding: utf-8 if __name__ == '__main__': sol = Solution() print(sol.findErrorNums([1, 2, 2, 4])) print(sol.findErrorNums([2, 2]))
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# Copyright 2010 New Relic, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from graphql import ( GraphQLArgument, GraphQLField, GraphQLInt, GraphQLList, GraphQLNonNull, GraphQLObjectType, GraphQLSchema, GraphQLString, GraphQLUnionType, ) authors = [ { "first_name": "New", "last_name": "Relic", }, { "first_name": "Bob", "last_name": "Smith", }, { "first_name": "Leslie", "last_name": "Jones", }, ] books = [ { "id": 1, "name": "Python Agent: The Book", "isbn": "a-fake-isbn", "author": authors[0], "branch": "riverside", }, { "id": 2, "name": "Ollies for O11y: A Sk8er's Guide to Observability", "isbn": "a-second-fake-isbn", "author": authors[1], "branch": "downtown", }, { "id": 3, "name": "[Redacted]", "isbn": "a-third-fake-isbn", "author": authors[2], "branch": "riverside", }, ] magazines = [ {"id": 1, "name": "Reli Updates Weekly", "issue": 1, "branch": "riverside"}, {"id": 2, "name": "Reli Updates Weekly", "issue": 2, "branch": "downtown"}, {"id": 3, "name": "Node Weekly", "issue": 1, "branch": "riverside"}, ] libraries = ["riverside", "downtown"] libraries = [ { "id": i + 1, "branch": branch, "magazine": [m for m in magazines if m["branch"] == branch], "book": [b for b in books if b["branch"] == branch], } for i, branch in enumerate(libraries) ] storage = [] Author = GraphQLObjectType( "Author", { "first_name": GraphQLField(GraphQLString), "last_name": GraphQLField(GraphQLString), }, ) Book = GraphQLObjectType( "Book", { "id": GraphQLField(GraphQLInt), "name": GraphQLField(GraphQLString), "isbn": GraphQLField(GraphQLString), "author": GraphQLField(GraphQLList(Author)), "branch": GraphQLField(GraphQLString), }, ) Magazine = GraphQLObjectType( "Magazine", { "id": GraphQLField(GraphQLInt), "name": GraphQLField(GraphQLString), "issue": GraphQLField(GraphQLInt), "branch": GraphQLField(GraphQLString), }, ) Library = GraphQLObjectType( "Library", { "id": GraphQLField(GraphQLInt), "branch": GraphQLField(GraphQLString), "book": GraphQLField(GraphQLList(Book)), "magazine": GraphQLField(GraphQLList(Magazine)), }, ) Storage = GraphQLList(GraphQLString) try: hello_field = GraphQLField(GraphQLString, resolver=resolve_hello) library_field = GraphQLField( Library, resolver=resolve_library, args={"index": GraphQLArgument(GraphQLNonNull(GraphQLInt))}, ) search_field = GraphQLField( GraphQLList( GraphQLUnionType("Item", (Book, Magazine), resolve_type=resolve_search) ), args={"contains": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) echo_field = GraphQLField( GraphQLString, resolver=resolve_echo, args={"echo": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) storage_field = GraphQLField( Storage, resolver=resolve_storage, ) storage_add_field = GraphQLField( Storage, resolver=resolve_storage_add, args={"string": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) error_field = GraphQLField(GraphQLString, resolver=resolve_error) error_non_null_field = GraphQLField( GraphQLNonNull(GraphQLString), resolver=resolve_error ) except TypeError: hello_field = GraphQLField(GraphQLString, resolve=resolve_hello) library_field = GraphQLField( Library, resolve=resolve_library, args={"index": GraphQLArgument(GraphQLNonNull(GraphQLInt))}, ) search_field = GraphQLField( GraphQLList( GraphQLUnionType("Item", (Book, Magazine), resolve_type=resolve_search) ), args={"contains": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) echo_field = GraphQLField( GraphQLString, resolve=resolve_echo, args={"echo": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) storage_field = GraphQLField( Storage, resolve=resolve_storage, ) storage_add_field = GraphQLField( GraphQLString, resolve=resolve_storage_add, args={"string": GraphQLArgument(GraphQLNonNull(GraphQLString))}, ) error_field = GraphQLField(GraphQLString, resolve=resolve_error) error_non_null_field = GraphQLField( GraphQLNonNull(GraphQLString), resolve=resolve_error ) query = GraphQLObjectType( name="Query", fields={ "hello": hello_field, "library": library_field, "search": search_field, "echo": echo_field, "storage": storage_field, "error": error_field, "error_non_null": error_non_null_field, }, ) mutation = GraphQLObjectType( name="Mutation", fields={ "storage_add": storage_add_field, }, ) _target_application = GraphQLSchema(query=query, mutation=mutation)
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2,472
from django.db import models from django.contrib.postgres.fields import JSONField from django.core.exceptions import ValidationError from django.utils.translation import gettext_lazy as _ from templatestore import app_settings as ts_settings import re
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3.555556
72
import argparse import json import copy import torch import razdel from tqdm import tqdm from transformers import AutoTokenizer, AutoModelForSeq2SeqLM from rudetox.util.io import read_jsonl, write_jsonl from rudetox.util.dl import gen_batch, set_random_seed from rudetox.ranker import Ranker if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--input-file", type=str, required=True) parser.add_argument("--output-file", type=str, required=True) parser.add_argument("--model-name", type=str, required=True) parser.add_argument("--sample-rate", type=float, default=1.0) parser.add_argument("--batch-size", type=int, default=1) parser.add_argument("--seed", type=int, default=42) parser.add_argument("--max-source-tokens-count", type=int, default=600) parser.add_argument("--max-target-tokens-count", type=int, default=200) parser.add_argument("--repetition-penalty", type=float, default=1.0) parser.add_argument("--length-penalty", type=float, default=1.0) parser.add_argument("--no-repeat-ngram-size", type=int, default=4) parser.add_argument("--num-beams", type=int, default=5) parser.add_argument("--num-return-sequences", type=int, default=1) parser.add_argument("--early-stopping", action="store_true", default=False) parser.add_argument("--style-token", type=str, default=None) parser.add_argument("--source-field", type=str, default="source") parser.add_argument("--ranker-config", type=str, default=None) args = parser.parse_args() predict(**vars(args))
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2.766667
570
from bamboo.core.parser import Parser from bamboo.core.calculator import calculate_columns from bamboo.lib.datetools import now, recognize_dates from bamboo.models.calculation import Calculation from bamboo.models.dataset import Dataset from bamboo.tests.test_base import TestBase
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3.76
75
from django.urls import path from . import views urlpatterns = [ path("registration/", views.registration, name="registration"), path("login/", views.login, name="login"), path("valid_registry", views.valid_registry, name="valid_registry"), path("valid_login", views.valid_login, name="valid_login"), path("logout/", views.logout, name="logout"), ]
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2.92126
127
from hashlib import sha3_256 from typing import Union, BinaryIO from pathlib import Path from importlib_metadata import pathlib def ensure_path( path: Union[str, Path], must_exist: bool = False ) -> Path: """ ensures that given path is of type Path and that HOME directory is resolved """ path = ( path if isinstance(path, Path) else Path(path) ).expanduser() if must_exist and not path.exists(): # path does not exist raise ValueError( f"The directory '{path}' does not exist!" ) return path def hash_file( filename: Union[str, Path], hash_func: callable = sha3_256 ) -> bytes: """ obtain the hash of the file with given hash function :param filename: file object on which hash is computed :type filename: Path :param hash_func: hash function that is used, defaults to sha3_256 :type hash_func: callable, optional :return: hash digest :rtype: bytes """ assert isinstance(filename, (str, Path)) assert callable(hash_func) # ensure that filename does exist filename = ensure_path(filename, must_exist=True) # initialize hash function h = hash_func() # read file chunkwise and update hash function with filename.open("rb") as f: while True: chunk = f.read(h.block_size) if not chunk: break h.update(chunk) return h.digest() def hash_directory( directory: Union[str, Path], glob: str = "**/*", exclude_suffixes: list = [], exclude_filenames: list = [], hash_func: callable = sha3_256 ) -> bytes: """ obtain the XORed hash of all files in the given directory with given hash function :param directory: directory from which all files are hashed :type directory: Path :param glob: glob to obtain files from directory, defaults to **/* :type glob: str, optional :param exclude_suffixes: suffixes that are ignored :type exclude_suffixes: list :param exclude_filenames: filenames that are ignored :type exclude_filenames: list :param hash_func: hash function that is used, defaults to sha3_256 :type hash_func: callable, optional :return: hash digest :rtype: bytes """ assert isinstance(directory, (str, Path)) assert isinstance(glob, str) assert callable(hash_func) # ensure that filename does exist directory = ensure_path(directory, must_exist=True) assert directory.is_dir() h = hash_func() digest = b"\0" * h.digest_size for fn in directory.glob(glob): if ( fn.suffix in exclude_suffixes or fn.name in exclude_filenames ): # skip excluded files continue # XOR digest with file's digest digest = bytes([ a ^ b for a, b in zip(digest, hash_file(fn, hash_func)) ]) return h.digest()
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2.546781
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""" Utilities for setting up PyTorch memory usage experiments. """ import csv from itertools import product as iter_product import os import subprocess import time import numpy as np from common import (check_file_exists, prepare_out_file, read_json, render_exception, write_json) MEASURED_KEYS = ['time', 'gpu_time', 'input_mem', 'model_mem', 'total_mem', 'sync_time', # profiling output 'base_compute_time', 'remat_compute_time', 'search_time', 'cost_time', 'memory_budget'] def run_trials(config_dir, python_cmd, experiment_name, model_name, specific_params, n_inputs, path_prefix, report_errors=False, append_to_csv=False, trial_run=False, trial_run_outfile='', cmd_id=0, conf_cnt=0): """ Responsible for recording the time and max memory usage from running a model (the user must provide a lambda for actually running the model because different kinds of models need different kinds of setup and a lambda that generates an input for running that model) :params: trial_run: When set to true, no persistent experiment data will be saved. It is used to run a baseline trial and record how much memory is used then set the memory budget for `ratio` commands of DTR experiments trial_run_out_file: the temporary file that stores the memory usage data of the baseline run cmd_id: the command id for current model, starting from 0 by default conf_cnt: the id of confguration generated from `unfold_settings`; this is used for tracking which exact configuration that caused errors. """ try: cwd = os.getcwd() params_file = 'specific_params.json' try: write_json(cwd, params_file, specific_params) if not trial_run: filename = prepare_out_file(path_prefix, '{}-{}.csv'.format(get_report_prefix(experiment_name, specific_params, cmd_id), model_name)) mode = 'a' if append_to_csv else 'w' with open(filename, mode, newline='') as csvfile: writer = create_csv_writer(csvfile, specific_params) if not append_to_csv: writer.writeheader() else: filename = '' shared_dir = os.path.dirname(os.path.abspath(__file__)) run_script = os.path.join(shared_dir, 'run_torch_trial.py') for i in range(n_inputs): try: subprocess.run( [python_cmd, run_script, '--config-dir', config_dir, '--experiment-mode', experiment_name, '--model-name', model_name, '--input-idx', str(i), '--params-file', params_file, '--out-file', filename, '--trial-run', str(trial_run), '--trial-run-outfile', trial_run_outfile ], check=True, timeout=specific_params.get('timeout', 60)) except (subprocess.CalledProcessError, subprocess.TimeoutExpired) as e: if not report_errors: raise e if trial_run: return (False, 'Baseline failed: {}'.format(render_exception(e))) log_error(experiment_name, model_name, specific_params, i, render_exception(e), path_prefix) return (False, 'successfully caught error') time.sleep(4) return (True, 'success') finally: os.remove(params_file) except Exception as e: return (False, 'Encountered exception on ({}, {}, {}):\n'.format( experiment_name, model_name, specific_params) + render_exception(e)) def process_command(command: dict, config_template: dict): ''' Generate a setting with all necessary fields according to the default setting and the type of the commands. :params: command: the command provided in the config.json config_template: default values for the settings that is required while running an experiment ''' result = command.copy() if result['type'] == 'baseline': if 'batch_size' not in result: result['batch_size'] = config_template['batch_size'] return result elif result['type'] == 'dtr' or result['type'] == 'simrd': for (k, v) in config_template.items(): if k not in command: result[k] = v return result else: raise Exception('Unknown type: {}'.format(result['type'])) def validate_setting(method, exp_config): ''' Check whether the settings for an experiment contains all the required values ''' return { 'dtr' : check_dtr, 'simrd': check_simrd, 'baseline': lambda: ('batch_size' in exp_config, '') }.get(method, lambda: (False, 'unknown kind'))() def unfold_settings(exp_config): ''' Unfold a command and get all possible settings. Returned as an Iterable. The possible settings are generated by taking a Cartesian product over list fields of the command Note: for `ratio` command, the `memory_budget` is calculated here in order to avoid multiple runs of baseline trial ''' setting_heading = list() list_fields = list() for (k, v) in exp_config.items(): if isinstance(v, list): setting_heading.append(k) list_fields.append(v) if not list_fields: yield exp_config else: for combo in iter_product(*list_fields): # necessary to copy each time # since the old data might be used later result = exp_config.copy() for i in range(len(list_fields)): result[setting_heading[i]] = combo[i] if result.get('kind') == 'ratio': result['memory_budget'] *= result['ratio'] yield result def run_baseline(model, exp_config, config, config_dir, output_dir): ''' Run a baseline triral and obtain memory usage. This is used for getting a reference memory usage for DTR `ratio` commands ''' baseline_config = { 'batch_size' : exp_config['batch_size'], 'timeout': exp_config.get('timeout', 60), # only doing a minimal number of runs because we are only getting the memory usage, # which should be identical between runs 'n_reps': 10, 'extra_params': exp_config.get('extra_params', {}) } if 'input_params' in exp_config: baseline_config['input_params'] = exp_config['input_params'] filename = str(time.time()) + '.json' temp_file = prepare_out_file(os.getcwd(), filename) success, msg = run_trials(config_dir, python_command('baseline', config), 'baseline', model, baseline_config, exp_config.get('n_inputs', config['n_inputs']), output_dir, report_errors=config['report_errors'], append_to_csv=False, trial_run=True, trial_run_outfile=temp_file) if not success: return False, 'Error while running baseline trial: \n{}'.format(msg) mem_usage = read_json(output_dir, temp_file) os.remove(temp_file) if 'mem' not in mem_usage: return False, 'failed to get baseline memory usage' return True, mem_usage['mem'] def parse_commands(model, config): ''' Parse a command and return a processed command, which can be used to generate settings for experiments :params: model: the name of the model config: the top-level config ''' if not config['dtr_settings'].get(model): yield False, 'No settings for {}'.format(model), None default_setting = config['dtr_settings'].get('default') model_commands = config['dtr_settings'].get(model) if default_setting is not None: config_template = default_setting.copy() else: config_template = dict() for command in model_commands: exp_config = process_command(command, config_template) if exp_config.get('kind') in ('ratio',): exp_config['memory_budget'] = -1.0 success, msg = validate_setting(exp_config['type'], exp_config) if not success: yield False, 'Malformat configuration for {}-{}: {}'.format(model, exp_config['type'], msg), None else: yield True, 'Success', exp_config def bootstrap_conf_intervals(data, stat, bootstrap_iters=10000, confidence=95, measure='mean'): """ Given an array of floats, performs bootstrap resampling for the specified number of iterations to estimate confidence intervals. """ summary_stat = None if measure == 'mean': summary_stat = np.mean elif measure == 'median': summary_stat = np.median else: raise Exception(f'Invalid measure, must be mean or median but received {measure}') assert summary_stat is not None estimates = [ summary_stat(np.random.choice(data, replace=True, size=len(data))) for i in range(bootstrap_iters) ] # To get C% confidence intervals, we exclude the bottom (100-C)/2 % and the top (100-C)/2 % conf_span = (100 - confidence) / 2 return (np.percentile(estimates, conf_span), np.percentile(estimates, 100 - conf_span)) def collect_raw_measurements(experiment_name, model, specific_params, path_prefix, cmd_id): """ Reads the raw data for the given experiment name and params and returns a tuple (metrics dictionary, memory budget if applicable, error message if there is no data file). The first two fields will be None if there is no data file. """ filename = '{}-{}.csv'.format(get_report_prefix(experiment_name, specific_params, cmd_id), model) if not check_file_exists(path_prefix, filename): return (None, None, 'Data file {} does not exist at {}'.format(filename, path_prefix)) full_path = os.path.join(path_prefix, filename) metrics = {} memory_budget = None with open(full_path, 'r', newline='') as csvfile: reader = csv.DictReader(csvfile) for row in reader: # In case there are commands for the same model # that have the same values for all configurations idx = int(row['input']) measured = { key: float(row[key]) for key in MEASURED_KEYS } if memory_budget is None and specific_params.get('kind') == 'ratio': memory_budget = float(row['memory_budget']) if idx not in metrics.keys(): metrics[idx] = { key: [] for key in MEASURED_KEYS } for key in MEASURED_KEYS: metrics[idx][key].append(measured[key]) return (metrics, memory_budget, 'success') def compute_slowdowns(exp_times, baseline_times): """ Given arrays of prototype times and baseline times of the same length, returns an array of slowdowns """ return [exp_times[i]/baseline_times[i] for i in range(len(exp_times))] def compute_throughputs(batch_size, gpu_times): """ Given a batch size and an array of time running on GPU, returns an array of throughputs """ return [batch_size / gpu_times[i] * 1000 for i in range(len(gpu_times))] def parse_data_file(experiment_name, model, config, specific_params, path_prefix, cmd_id=0, baseline_params=None): """ Given an experiment name, model name, directory, and number of inputs, parses the corresponding data file if it exists and computes summary statistics for the (wall-clock) time, GPU time, and memory used in that data file for choice of specific settings baseline_params: If the command is a ratio command, this will use the baseline to compute the slowdown per data point in order to better measure its distribution. Returns None and an error message if it fails """ try: report_errors = config['report_errors'] metrics, budget, msg = collect_raw_measurements(experiment_name, model, specific_params, path_prefix, cmd_id) if metrics is None: return (None, msg) if budget is not None and specific_params.get('kind') == 'ratio': specific_params['memory_budget'] = float(budget) summary = { 'specific_params': specific_params } # in case everything errored out, this ensure that we will have a record of the error if report_errors: if check_error(experiment_name, model, specific_params, path_prefix): summary['summary'] = 'error' return summary, 'success' # if this was a ratio experiment # and we have a baseline available, let's compute # the slowdown per data point, head to head # and bootstrap confidence intervals if (specific_params.get('type') != 'baseline' and specific_params.get('kind') == 'ratio' and baseline_params is not None): baseline_metrics, _, baseline_msg = collect_raw_measurements(baseline_params['type'], model, baseline_params['specific_params'], path_prefix, baseline_params['cmd_id']) if baseline_metrics is None: return (None, baseline_msg) # compute slowdown in metrics for i in range(config['n_inputs']): dtr_times = metrics[i]['gpu_time'] baseline_times = baseline_metrics[i]['gpu_time'] assert len(dtr_times) == len(baseline_times) metrics[i]['slowdown'] = compute_slowdowns(dtr_times, baseline_times) # Compute throughputs for baseline param_sweep commands if specific_params.get('kind') == 'param_sweep' or specific_params.get('type') == 'baseline': for i in range(config['n_inputs']): metrics[i]['throughput'] = compute_throughputs(specific_params['batch_size'], metrics[i]['gpu_time']) summary_stats = [] for (_, stat) in metrics.items(): summary_dict = { key: compute_summary_stats(stat[key], bootstrap=('time' in key)) for key in MEASURED_KEYS } if 'slowdown' in stat: summary_dict['slowdown'] = compute_summary_stats(stat['slowdown'], bootstrap=True) if 'throughput' in stat: summary_dict['throughput'] = compute_summary_stats(stat['throughput'], bootstrap=True) summary_stats.append(summary_dict) summary['summary'] = summary_stats return (summary, 'success') except Exception as e: return (None, 'Encountered exception on ({}, {}): '.format(experiment_name, model) + render_exception(e))
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2.299335
6,765
import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import seaborn as sns import argparse import numpy as np import joblib import tensorflow as tf import os from sac.misc import utils from sac.policies.hierarchical_policy import FixedOptionPolicy from sac.misc.sampler import rollouts if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('file', type=str, help='Path to the snapshot file.') parser.add_argument('--max-path-length', '-l', type=int, default=100) parser.add_argument('--n_paths', type=int, default=1) parser.add_argument('--dim_0', type=int, default=0) parser.add_argument('--dim_1', type=int, default=1) parser.add_argument('--use_qpos', type=bool, default=False) parser.add_argument('--use_action', type=bool, default=False) parser.add_argument('--deterministic', '-d', dest='deterministic', action='store_true') parser.add_argument('--no-deterministic', '-nd', dest='deterministic', action='store_false') parser.set_defaults(deterministic=True) args = parser.parse_args() filename = '{}_{}_{}_trace.png'.format(os.path.splitext(args.file)[0], args.dim_0, args.dim_1) with tf.Session() as sess: data = joblib.load(args.file) policy = data['policy'] env = data['env'] num_skills = data['policy'].observation_space.flat_dim - data['env'].spec.observation_space.flat_dim plt.figure(figsize=(6, 6)) palette = sns.color_palette('hls', num_skills) with policy.deterministic(args.deterministic): for z in range(num_skills): fixed_z_policy = FixedOptionPolicy(policy, num_skills, z) for path_index in range(args.n_paths): obs = env.reset() if args.use_qpos: qpos = env.wrapped_env.env.model.data.qpos[:, 0] obs_vec = [qpos] else: obs_vec = [obs] for t in range(args.max_path_length): action, _ = fixed_z_policy.get_action(obs) (obs, _, _, _) = env.step(action) if args.use_qpos: qpos = env.wrapped_env.env.model.data.qpos[:, 0] obs_vec.append(qpos) elif args.use_action: obs_vec.append(action) else: obs_vec.append(obs) obs_vec = np.array(obs_vec) x = obs_vec[:, args.dim_0] y = obs_vec[:, args.dim_1] plt.plot(x, y, c=palette[z]) plt.savefig(filename) plt.close()
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# # Copyright (c) 2015-2019 Thierry Florac <tflorac AT ulthar.net> # All Rights Reserved. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED # WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS # FOR A PARTICULAR PURPOSE. # """PyAMS_layer.interfaces module This module provides all layers and skins related interfaces. """ from pyramid.interfaces import IRequest from zope.configuration.fields import GlobalInterface from zope.interface import Attribute, Interface, implementer from zope.interface.interfaces import IObjectEvent, ObjectEvent from zope.schema import Bool, Choice, TextLine from pyams_file.schema import FileField __docformat__ = 'restructuredtext' from pyams_layer import _ MANAGE_SKIN_PERMISSION = 'pyams.ManageSkin' '''Permission required to manage rendering skin''' class IResources(Interface): """Get list of CSS and Javascript resources associated with given context""" resources = Attribute("Resources to include") """Iterable of resources to include into page The best way to handle resources is to use Fanstatic to automatically include CSS and Javascript tags. """ PYAMS_BASE_SKIN_NAME = 'PyAMS base skin' class IBaseLayer(IRequest): """Base layer marker interface""" class IFormLayer(Interface): """Custom layer for forms management""" class IPyAMSLayer(IBaseLayer, IFormLayer): """PyAMS default layer""" class IPyAMSUserLayer(IPyAMSLayer): """PyAMS custom user layer This layer is the base for all custom skins. Any component should provide a look and feel for this layer. """ BASE_SKINS_VOCABULARY_NAME = 'pyams_layer.skins' USER_SKINS_VOCABULARY_NAME = 'pyams_layer.skin.user' class ISkin(Interface): """Skin interface Skins are registered as utilities implementing this interface and defining request layer as attribute. """ label = TextLine(title="Skin name") layer = GlobalInterface(title="Request layer", description="This interface will be used to tag request layer", required=True) class ISkinChangedEvent(IObjectEvent): """Skin changed event""" @implementer(ISkinChangedEvent) class SkinChangedEvent(ObjectEvent): """Request skin changed event""" class ISkinnable(Interface): """Skinnable content interface""" can_inherit_skin = Attribute("Check if skin can be inherited") inherit_skin = Bool(title=_("Inherit parent skin?"), description=_("Should we reuse parent skin?"), required=True, default=False) override_skin = Bool(title=_("Don't inherit parent skin?"), description=_("Should we override parent skin?"), required=True, default=True) skin_parent = Attribute("Skin parent (local or inherited)") skin = Choice(title=_("Custom graphic theme"), description=_("This theme will be used to handle graphic design (colors and " "images)"), vocabulary=USER_SKINS_VOCABULARY_NAME, required=False) def get_skin(self, request=None): """Get skin matching this content""" container_class = TextLine(title=_("Container class"), description=_("CSS class given to main page container element"), required=False) custom_stylesheet = FileField(title=_("Custom stylesheet"), description=_("This custom stylesheet will be used to override " "selected theme styles"), required=False) editor_stylesheet = FileField(title=_("Editor stylesheet"), description=_("Styles defined into this stylesheet will be " "available into HTML editor"), required=False) custom_script = FileField(title=_("Custom script"), description=_("This custom javascript file will be used to add " "dynamic features to selected theme"), required=False) class IUserSkinnable(ISkinnable): """User skinnable content interface"""
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from ..handler_request import get_resource_url
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14
from random import randint itens = ('Pedra', 'Papel', 'Tesoura') pc = randint(0, 2) print('''Suas opções: [ 0 ] PEDRA [ 1 ] PAPEL [ 2 ] TESOURA ''') op = int(input('Qual é a sua jogada: ')) print('-=' * 11) print('Computador jogou {}'.format(itens[pc])) print('jogador jogou {}'.format(itens[op])) print('-=' * 11) if pc == 0: if op == 0: print('\033[33mEMPATE!') elif op == 1: print('\033[32mJOGADOR VENCE!') elif op == 2: print('\033[31mCOMPUTADOR VENCE!') else: print('\033[31mJOGADA INVÁLIDA!') elif pc == 1: if op == 0: print('\033[31mCOMPUTADOR VENCE!') elif op == 1: print('\033[33mEMPATE!') elif op == 2: print('\033[32mJOGADOR VENCE!') else: print('\033[31mJOGADA INVÁLIDA!') elif pc == 2: if op == 0: print('\033[32mJOGADOR VENCE!') elif op == 1: print('\033[31mCOMPUTADOR VENCE!') elif op == 2: print('\033[33mEMPATE!') else: print('\033[31mJOGADA INVÁLDA!') else: print('\033[31mNÚMERO INVÁLIDO! Tente novamente....')
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1.888112
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# -*- coding: utf-8 -*- from south.utils import datetime_utils as datetime from south.db import db from south.v2 import SchemaMigration from django.db import models
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3.113208
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import os from dagster_examples.pyspark_pagerank.original import ( computeContribs, execute_pagerank, parseNeighbors, ) from .util import checks_for_helper_functions
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2.676471
68
from __future__ import (division, absolute_import, print_function, unicode_literals) import sqlalchemy import sqlalchemy.orm from .gtfs_entities import gtfs_all, Feed, Base class Schedule: """Represents the full database. The schedule is the most important object in pygtfs. It represents the entire dataset. Most of the properties come straight from the gtfs reference. Two of them were renamed: calendar is called `services`, and calendar_dates `service_exceptions`. One addition is the `feeds` table, which is here to support more than one feed in a database. Each of the properties is a list created upon access by sqlalchemy. Then, each element of the list as attributes following the gtfs reference. In addition, if they are related to another table, this can also be accessed by attribute. :param db_conection: Either a sqlalchemy database url or a filename to be used with sqlite. """ def drop_feed(self, feed_id): """ Delete a feed from a database by feed id""" # the following does not cascade unfortunatly. # self.session.query(Feed).filter(Feed.feed_id == feed_id).delete() feed = self.session.query(Feed).get(feed_id) self.session.delete(feed) self.session.commit() for entity in (gtfs_all + [Feed]): entity_doc = "A list of :py:class:`pygtfs.gtfs_entities.{0}` objects".format(entity.__name__) entity_raw_doc = ("A :py:class:`sqlalchemy.orm.Query` object to fetch " ":py:class:`pygtfs.gtfs_entities.{0}` objects" .format(entity.__name__)) entity_by_id_doc = "A list of :py:class:`pygtfs.gtfs_entities.{0}` objects with matching id".format(entity.__name__) setattr(Schedule, entity._plural_name_, _meta_query_all(entity, entity_doc)) setattr(Schedule, entity._plural_name_ + "_query", _meta_query_raw(entity, entity_raw_doc)) if hasattr(entity, 'id'): setattr(Schedule, entity._plural_name_ + "_by_id", _meta_query_by_id(entity, entity_by_id_doc))
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2.663694
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# Generated by Django 3.2.7 on 2021-10-11 12:43 from django.db import migrations
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2.766667
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################################################################################ # Copyright (C) 2019 drinfernoo # # # # This Program is free software; you can redistribute it and/or modify # # it under the terms of the GNU General Public License as published by # # the Free Software Foundation; either version 2, or (at your option) # # any later version. # # # # This Program is distributed in the hope that it will be useful, # # but WITHOUT ANY WARRANTY; without even the implied warranty of # # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # # GNU General Public License for more details. # # # # You should have received a copy of the GNU General Public License # # along with XBMC; see the file COPYING. If not, write to # # the Free Software Foundation, 675 Mass Ave, Cambridge, MA 02139, USA. # # http://www.gnu.org/copyleft/gpl.html # ################################################################################ import xbmc try: # Python 3 import zipfile except ImportError: # Python 2 from resources.libs import zipfile from resources.libs.common.config import CONFIG
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2.046308
799
#!/usr/bin/python3 # Example line: Step A must be finished before step L can begin. edges = [(ord(x[1]) - ord('A'), ord(x[7]) - ord('A')) for x in map(lambda x: x.split(), open('input.in').readlines())] workers = 5 for e in edges: print('{} → {}'.format(chr(ord('A') + e[0]),chr(ord('A') + e[1]))) graph = {} # for l in range(ord('Z') - ord('A') + 1): # graph[l] = Node(l) for source, target in edges: if source not in graph: graph[source] = Node(source) if target not in graph: graph[target] = Node(target) graph[source].insert_target(target, graph[target]) graph[target].insert_source(source, graph[source]) output = [] nodes_to_insert = [] graph_len = len(graph) time_point = 0 workers = [ -1 for i in range(6)] while(len(output) < graph_len): # print(len(output)) # print(len(graph)) for w in range(len(workers)): nodes_to_insert = [] for node in graph: # print('{} : {} → {}'.format(node, len(graph[node].inputs), len(graph[node].outputs))) # print('{}: {}'.format(node, graph[node])) if len(graph[node].inputs) == 0: nodes_to_insert.append(node) #print(nodes_to_insert) if len(nodes_to_insert) == 0: print('Total time: {} .'.format(time_point)) break nodes_to_insert.sort() limit = min(len(workers), len(nodes_to_insert)) processed_nodes = nodes_to_insert[:limit] for n in processed_nodes: if n in graph: if w != 0 and workers[w] == -1 and graph[n].busy == -1: print('Assigning {} to worker {} at time point: {}'.format(chr(n+ord('A')), w, time_point)) graph[n].begin_time = time_point graph[n].end_time = time_point + n + 1 + 60 workers[w] = n graph[n].busy = w if time_point == graph[n].end_time and graph[n].busy >= 0 and w == 0: for k in graph[n].outputs: out = graph[n].outputs[k] del out.inputs[n] print("Removing {} TP {}.".format(n, time_point)) output.append(n) workers[graph[n].busy] = -1 graph[n].busy = -1 del graph[n] time_point += 1 print('Total time: {} .'.format(time_point))
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2.00416
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# Generated by Django 3.0.2 on 2020-06-20 12:35 from django.db import migrations, models
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2.84375
32
#!/usr/bin/env python3 import sys import argparse from collections import Counter my_description = ''' Prune empty (or infrequent) slices from a tensor. With default options, this script scans a tensor file and removes empty slices. Those slices are then specified with "mode-X-gaps.map" files which map the old dimensionality into the new one. Infrequent items can also be pruned by specifying "--mode=MODE,FREQ" options. For example, "--mode=3,5" will remove any slices in the third mode with less than five non-zeros. NOTE: since this process removes non-zeros, it can cause slices in other modes to become infrequent or empty. If any non-zeros are pruned, this script should be re-run until no additional empty/infrequent slices are present. Map files should be merged with `merge_gap_keys.py` after each run, as they will be overwritten if a mode is pruned additional times. ''' parser = argparse.ArgumentParser(description=my_description, formatter_class=argparse.RawTextHelpFormatter) parser.add_argument('tensor', type=str, help='tensor to prune') parser.add_argument('output', type=str, help='output tensor') parser.add_argument('--mode', metavar='MODE,MIN-FREQ', action='append', help='min. frequency for a mode (default: 1)') args = parser.parse_args() # First get the number of modes nmodes = 0 with open(args.tensor, 'r') as fin: line = fin.readline() nmodes = len(line.split()[:-1]) # skip the val at the end # Get user-specified minimum frequencies mode_mins = [1] * nmodes if args.mode: for mode_tup in args.mode: mode_tup = mode_tup.split(',') m = int(mode_tup[0]) - 1 freq = int(mode_tup[1]) mode_mins[m] = freq print('minimum frequencies: {}'.format(mode_mins)) def read_tensor(fname): ''' Read each line of the tensor and return a list of indices and the value. This function skips comments and blank lines. ''' with open(fname, 'r') as fin: for line in fin: # skip comments and blank lines if line[0] == '#' or line is '': continue # convert to integers and return list line = line.strip().split() yield [int(x) for x in line[:-1]], line[-1] # Count appearances in each mode. ind_counts = [Counter() for x in range(nmodes)] for inds, val in read_tensor(args.tensor): for m in range(nmodes): ind_counts[m][inds[m]] += 1 # indmaps[m][i] gives the NEW index for original slice i ind_maps = [dict() for m in range(nmodes)] # Go over counts and prune infrequent slices gapped_modes = [] for m in range(nmodes): for index in ind_counts[m].keys(): if ind_counts[m][index] < mode_mins[m]: ind_counts[m][index] = 0 # prune keep = [x for x in sorted(ind_counts[m]) if ind_counts[m][x] >= mode_mins[m]] gaplen = max(ind_counts[m]) - len(keep) # Have we pruned any slices? if gaplen > 0: gapped_modes.append(m) print('mode-{}: {} empty slices'.format(m+1, gaplen)) # assign new IDs and write map file with open('mode-{}-gaps.map'.format(m+1), 'w') as mapfile: for i in keep: ind_maps[m][i] = len(ind_maps[m]) + 1 # invert map and write to file print('{}'.format(i), file=mapfile) if len(gapped_modes) == 0: print('no empty slices') sys.exit(0) # Go back over the tensor and map indices nnz = 0 pruned_nnz = 0 with open(args.output, 'w') as fout: for inds, val in read_tensor(args.tensor): pruned = False # map indices and check for pruned nnz for m in gapped_modes: if inds[m] in ind_maps[m]: inds[m] = ind_maps[m][inds[m]] else: pruned = True pruned_nnz += 1 # write non-zero if not pruned: print('{} {}'.format(' '.join(map(str, inds)), val), file=fout) nnz += 1 print('pruned nnz: {:,d} new nnz: {:,d}'.format(pruned_nnz, nnz))
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2.638062
1,445
"""Clean Code in Python - Chater 4, The SOLID Principles > Liskov's Substitution Principle (LSP) Detecting violatinos os LSP through tools (mypy, pylint, etc.) """
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3.12963
54