code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from search_engine_parser.core.base import BaseSearch, ReturnType, SearchItem
from search_engine_parser.core.exceptions import IncorrectKeyWord
class Search(BaseSearch):
"""
Searches GitHub for string
"""
name = "GitHub"
base_url = "https://github.com"
search_url = base_url + "/search?"
su... | search_engine_parser/core/engines/github.py | from search_engine_parser.core.base import BaseSearch, ReturnType, SearchItem
from search_engine_parser.core.exceptions import IncorrectKeyWord
class Search(BaseSearch):
"""
Searches GitHub for string
"""
name = "GitHub"
base_url = "https://github.com"
search_url = base_url + "/search?"
su... | 0.551815 | 0.201067 |
class TrajectoryFile():
def __init__(self, filepath=None, mode='read'):
self.opened = False
self.path = None
self.mount_point = None
self.form = None
self.n_structures = 0
self.n_atoms = 0
self.atom_indices = None
if filepath is not None and mode=='... | molsysmt/native/trajectory_file.py | class TrajectoryFile():
def __init__(self, filepath=None, mode='read'):
self.opened = False
self.path = None
self.mount_point = None
self.form = None
self.n_structures = 0
self.n_atoms = 0
self.atom_indices = None
if filepath is not None and mode=='... | 0.336876 | 0.188716 |
import json
import os
import pathlib
from src import misc
import requests
fullpath = str(pathlib.Path(__file__).parent.absolute())+"/data.json"
def total_cases(user_input):
with open(fullpath,"r") as JsonFile:
data = json.load(JsonFile)
array = user_input.split()
if len(array) == 1:
... | src/functions.py | import json
import os
import pathlib
from src import misc
import requests
fullpath = str(pathlib.Path(__file__).parent.absolute())+"/data.json"
def total_cases(user_input):
with open(fullpath,"r") as JsonFile:
data = json.load(JsonFile)
array = user_input.split()
if len(array) == 1:
... | 0.071624 | 0.098816 |
""" P1 tests for Scaling up Vm
"""
#Import Local Modules
import marvin
from marvin.cloudstackTestCase import *
from marvin.cloudstackAPI import *
from marvin.sshClient import SshClient
from marvin.lib.utils import *
from marvin.lib.base import *
from marvin.lib.common import *
from nose.plugins.attrib import attr
#Impo... | test/integration/smoke/test_resource_detail.py | """ P1 tests for Scaling up Vm
"""
#Import Local Modules
import marvin
from marvin.cloudstackTestCase import *
from marvin.cloudstackAPI import *
from marvin.sshClient import SshClient
from marvin.lib.utils import *
from marvin.lib.base import *
from marvin.lib.common import *
from nose.plugins.attrib import attr
#Impo... | 0.287068 | 0.176033 |
import math
import numpy as np
from numpy import random as nprand
import random
from sklearn.metrics.pairwise import pairwise_distances
### COST MEASURES TO TEST
def l1_norm(obs_to_interprete, observation):
l1 = sum(map(abs, obs_to_interprete - observation))
return l1
def weighted_l1(obs_to_interprete, obse... | growingspheres/old_/uniform_growing_spheres.py |
import math
import numpy as np
from numpy import random as nprand
import random
from sklearn.metrics.pairwise import pairwise_distances
### COST MEASURES TO TEST
def l1_norm(obs_to_interprete, observation):
l1 = sum(map(abs, obs_to_interprete - observation))
return l1
def weighted_l1(obs_to_interprete, obse... | 0.450601 | 0.49231 |
import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class GraphConvolution(nn.Module):
def __init__(self, input_dim, output_dim, dropout, bias=False):
super(GraphConvolution, self).__init__()
self.input_dim = input_dim
self.output_dim = output_dim
self.weight... | src/vgae/model.py | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class GraphConvolution(nn.Module):
def __init__(self, input_dim, output_dim, dropout, bias=False):
super(GraphConvolution, self).__init__()
self.input_dim = input_dim
self.output_dim = output_dim
self.weight... | 0.920785 | 0.529446 |
from __future__ import print_function
import tensorflow as tf
import numpy as np
import os
import shutil
import codecs
import psutil
from scipy import sparse
import pandas as pd
import bottleneck as bn
from math import isinf
import sys
import pickle
import ConfigParser
from Base_Recommender.MultiVAE import MultiVAE... | Codes/test.py | from __future__ import print_function
import tensorflow as tf
import numpy as np
import os
import shutil
import codecs
import psutil
from scipy import sparse
import pandas as pd
import bottleneck as bn
from math import isinf
import sys
import pickle
import ConfigParser
from Base_Recommender.MultiVAE import MultiVAE... | 0.378 | 0.147524 |
import json
import ast
import math
import pandas as pd
import numpy as np
import datetime
from influxdb import DataFrameClient
from api_service.db import resultdb
from logger import get_logger
from config import get_config
NANOSECONDS_PER_SECOND = 1000000000
class Status():
SUCCESS = "success"
BAD_CONFIG = ... | utilization/sizing_analyzer.py | import json
import ast
import math
import pandas as pd
import numpy as np
import datetime
from influxdb import DataFrameClient
from api_service.db import resultdb
from logger import get_logger
from config import get_config
NANOSECONDS_PER_SECOND = 1000000000
class Status():
SUCCESS = "success"
BAD_CONFIG = ... | 0.267121 | 0.099383 |
import unittest
from test import EnableSchemaValidation
import jsonschema
import numpy as np
import sklearn
import sklearn.datasets
import sklearn.metrics
import sklearn.model_selection
import xgboost
from lale.lib.lale import Hyperopt
from lale.lib.sklearn import (
SVC,
DecisionTreeClassifier,
DecisionT... | test/test_lale_lib_versions.py |
import unittest
from test import EnableSchemaValidation
import jsonschema
import numpy as np
import sklearn
import sklearn.datasets
import sklearn.metrics
import sklearn.model_selection
import xgboost
from lale.lib.lale import Hyperopt
from lale.lib.sklearn import (
SVC,
DecisionTreeClassifier,
DecisionT... | 0.725551 | 0.640158 |
__all__ = ('DarjeelingEventProducer',)
from typing import Iterator, List, Any
import abc
from loguru import logger
from .event import DarjeelingEvent
from .handler import DarjeelingEventHandler
class DarjeelingEventProducer:
"""Objects that implement this interface may produce Darjeeling events."""
def __i... | src/darjeeling/events/producer.py | __all__ = ('DarjeelingEventProducer',)
from typing import Iterator, List, Any
import abc
from loguru import logger
from .event import DarjeelingEvent
from .handler import DarjeelingEventHandler
class DarjeelingEventProducer:
"""Objects that implement this interface may produce Darjeeling events."""
def __i... | 0.854232 | 0.211376 |
import ckeditor.fields
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django_resized.forms
import taggit.managers
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_U... | student_gp/migrations/0001_initial.py |
import ckeditor.fields
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django_resized.forms
import taggit.managers
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_U... | 0.482673 | 0.153232 |
import sys
from scapy.layers.l2 import Ether
from scapy.layers.inet import IP, UDP
from ipaddress import ip_address
from resources.libraries.python.PacketVerifier import RxQueue, TxQueue
from resources.libraries.python.TrafficScriptArg import TrafficScriptArg
def _check_udp_checksum(pkt):
"""Check UDP checksum ... | resources/traffic_scripts/send_ipv4_udp_check_map_t.py | import sys
from scapy.layers.l2 import Ether
from scapy.layers.inet import IP, UDP
from ipaddress import ip_address
from resources.libraries.python.PacketVerifier import RxQueue, TxQueue
from resources.libraries.python.TrafficScriptArg import TrafficScriptArg
def _check_udp_checksum(pkt):
"""Check UDP checksum ... | 0.455441 | 0.09451 |
import glob
import logging
import os
import shutil
import subprocess
from django_grpc_bus.protobuf import generators
from django_grpc_bus.settings import message_bus_settings
from django_grpc_bus.utils import service_meta
logger = logging.getLogger(__name__)
class ProtoGenerator:
RETRY_COUNT = 0
def __init... | django_grpc_bus/utils/generators.py | import glob
import logging
import os
import shutil
import subprocess
from django_grpc_bus.protobuf import generators
from django_grpc_bus.settings import message_bus_settings
from django_grpc_bus.utils import service_meta
logger = logging.getLogger(__name__)
class ProtoGenerator:
RETRY_COUNT = 0
def __init... | 0.343672 | 0.06276 |
# Importing Modules
import tkinter as tk
import random as r
# Generating possible answer list
def read_answers():
answers = []
with open("../Solver/guesses.txt", "r") as f:
for line in f:
answers.append(line.strip())
return answers
# --- Defining Window --- #
cl... | Wordle/Game/wordleClasses.py |
# Importing Modules
import tkinter as tk
import random as r
# Generating possible answer list
def read_answers():
answers = []
with open("../Solver/guesses.txt", "r") as f:
for line in f:
answers.append(line.strip())
return answers
# --- Defining Window --- #
cl... | 0.3492 | 0.15785 |
import os
import numpy as np
from yolo.backend.decoder import YoloDecoder
from yolo.backend.loss import YoloLoss
from yolo.backend.network import create_yolo_network
from yolo.backend.batch_gen import create_batch_generator
from yolo.backend.utils.fit import train
from yolo.backend.utils.annotation import get_train_... | yolo/frontend.py |
import os
import numpy as np
from yolo.backend.decoder import YoloDecoder
from yolo.backend.loss import YoloLoss
from yolo.backend.network import create_yolo_network
from yolo.backend.batch_gen import create_batch_generator
from yolo.backend.utils.fit import train
from yolo.backend.utils.annotation import get_train_... | 0.785226 | 0.225097 |
import matplotlib.pyplot as plt
from pyspark.sql import SparkSession
cluster_seeds = ['127.0.0.1']
spark = SparkSession.builder.appName('Arrest History').config('spark.cassandra.connection.host', ','.join(cluster_seeds)).getOrCreate()
spark.sparkContext.setLogLevel('WARN')
sc = spark.sparkContext
KEYSPACE ='pirates'
... | arrests_history/arrests_history.py | import matplotlib.pyplot as plt
from pyspark.sql import SparkSession
cluster_seeds = ['127.0.0.1']
spark = SparkSession.builder.appName('Arrest History').config('spark.cassandra.connection.host', ','.join(cluster_seeds)).getOrCreate()
spark.sparkContext.setLogLevel('WARN')
sc = spark.sparkContext
KEYSPACE ='pirates'
... | 0.421909 | 0.417628 |
error_codes = {
"InvalidPoint": "InvalidInput",
"InvalidLinePolygon": "InvalidInput",
"InvalidPointInput": "InvalidInput",
}
error_code_corpus = {
"InvalidUnits": lambda units: f"'{units}' is not a valid unit.",
"InvalidLength": "<length> must be a positive number",
"InvalidArea": "<area> must ... | turf/utils/error_codes.py | error_codes = {
"InvalidPoint": "InvalidInput",
"InvalidLinePolygon": "InvalidInput",
"InvalidPointInput": "InvalidInput",
}
error_code_corpus = {
"InvalidUnits": lambda units: f"'{units}' is not a valid unit.",
"InvalidLength": "<length> must be a positive number",
"InvalidArea": "<area> must ... | 0.837421 | 0.62266 |
from __future__ import division, print_function
import pygame
import os
from pygame.locals import *
from time import localtime
from random import randint, choice
from itertools import *
from os.path import join
pygame.init()
info_screen = pygame.display.Info()
h = info_screen.current_h // 1.2
# CONFI... | src/game.py |
from __future__ import division, print_function
import pygame
import os
from pygame.locals import *
from time import localtime
from random import randint, choice
from itertools import *
from os.path import join
pygame.init()
info_screen = pygame.display.Info()
h = info_screen.current_h // 1.2
# CONFI... | 0.447219 | 0.162048 |
from __future__ import unicode_literals
import json
import re
from .common import InfoExtractor
from ..compat import compat_HTTPError
from ..utils import (
ExtractorError,
int_or_none,
parse_age_limit,
)
class ViewLiftBaseIE(InfoExtractor):
_API_BASE = 'https://prod-api.viewlift.com/'
_DOMAINS_R... | yt_dlp/extractor/viewlift.py | from __future__ import unicode_literals
import json
import re
from .common import InfoExtractor
from ..compat import compat_HTTPError
from ..utils import (
ExtractorError,
int_or_none,
parse_age_limit,
)
class ViewLiftBaseIE(InfoExtractor):
_API_BASE = 'https://prod-api.viewlift.com/'
_DOMAINS_R... | 0.374791 | 0.073663 |
import cmath
import random
import sys
__author__ = '<NAME>'
__project__ = 'This is My Simple Python Application '
'''
a = float(input('输入三角形第一边长：'))
b = float(input('输入三角形第二边长：'))
c = float(input('输入三角形第三边长：'))
while a + b <= c or a + c <= b or b + c <= a:
print('输入的边构不成三角形，请重新输入！！')
a = float(... | inputKeyboardInterrupt.py |
import cmath
import random
import sys
__author__ = '<NAME>'
__project__ = 'This is My Simple Python Application '
'''
a = float(input('输入三角形第一边长：'))
b = float(input('输入三角形第二边长：'))
c = float(input('输入三角形第三边长：'))
while a + b <= c or a + c <= b or b + c <= a:
print('输入的边构不成三角形，请重新输入！！')
a = float(... | 0.113481 | 0.16975 |
import tcod
from game_messages import Message
from random import randint
from yaml_functions import read_yaml, cout
from batchim import 받침
SYS_LOG = read_yaml("system_log.yaml")
class Fighter:
def __init__(self, hp, defense, power, sanity=0):
"""
체력, 방어력, 공격력
"""
s... | components/fighter.py | import tcod
from game_messages import Message
from random import randint
from yaml_functions import read_yaml, cout
from batchim import 받침
SYS_LOG = read_yaml("system_log.yaml")
class Fighter:
def __init__(self, hp, defense, power, sanity=0):
"""
체력, 방어력, 공격력
"""
s... | 0.397588 | 0.085251 |
"""A Gated Recurrent Unit (GRU) cell with peepholes."""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class ConditionalGRU(nn.Module):
"""A Gated Recurrent Unit (GRU) cell with peepholes."""
def __init__(self, input_dim, hidden_dim, dropout=0.0):
"""Initialize params... | utils_nlp/models/pytorch_modules/conditional_gru.py |
"""A Gated Recurrent Unit (GRU) cell with peepholes."""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class ConditionalGRU(nn.Module):
"""A Gated Recurrent Unit (GRU) cell with peepholes."""
def __init__(self, input_dim, hidden_dim, dropout=0.0):
"""Initialize params... | 0.973481 | 0.694724 |
import argparse
import numpy as np
from world import World
from PythonQt import QtGui
from net import Controller
from sensor import RaySensor
from director import applogic
from moving_object import Robot
from director import vtkAll as vtk
from director import objectmodel as om
from director.debugVis import DebugData
f... | simulator.py |
import argparse
import numpy as np
from world import World
from PythonQt import QtGui
from net import Controller
from sensor import RaySensor
from director import applogic
from moving_object import Robot
from director import vtkAll as vtk
from director import objectmodel as om
from director.debugVis import DebugData
f... | 0.805976 | 0.285036 |
import datetime
import logging
import sys
import uuid
from logging.handlers import TimedRotatingFileHandler
from tornado import gen
from tornado.log import access_log
from tornado.stack_context import run_with_stack_context, StackContext
class RequestIDContext:
class Data:
def __init__(self, request_id=0... | common/loggers.py | import datetime
import logging
import sys
import uuid
from logging.handlers import TimedRotatingFileHandler
from tornado import gen
from tornado.log import access_log
from tornado.stack_context import run_with_stack_context, StackContext
class RequestIDContext:
class Data:
def __init__(self, request_id=0... | 0.266548 | 0.10923 |
import anygen
import json
import os
import pathlib
import sys
import tinyshar
from . import _debugdump
def prefix_filter(d, prefix):
result = {}
prefix_len = len(prefix)
for k, v in d.items():
if k.startswith(prefix):
result[k[prefix_len:]] = v
return result
def main():
que... | src/terraform_anygen/_gen.py | import anygen
import json
import os
import pathlib
import sys
import tinyshar
from . import _debugdump
def prefix_filter(d, prefix):
result = {}
prefix_len = len(prefix)
for k, v in d.items():
if k.startswith(prefix):
result[k[prefix_len:]] = v
return result
def main():
que... | 0.129265 | 0.096195 |
import numpy as np
import matplotlib.pyplot as plt
import math
import visualization.visiualize_2d.data_point_visualization as visualization
import random
def poly_fit_and_show(x, y, order, save_path=None, show=True):
z1 = np.polyfit(x, y, order)
p1 = np.poly1d(z1)
print(p1) # 在屏幕上打印拟合多项式
if show:
... | Analysis/fitting_or_check.py | import numpy as np
import matplotlib.pyplot as plt
import math
import visualization.visiualize_2d.data_point_visualization as visualization
import random
def poly_fit_and_show(x, y, order, save_path=None, show=True):
z1 = np.polyfit(x, y, order)
p1 = np.poly1d(z1)
print(p1) # 在屏幕上打印拟合多项式
if show:
... | 0.398992 | 0.643021 |
import time
import torch
class _Timer:
"""Timer."""
def __init__(self, name):
self.name_ = name
self.elapsed_ = 0.0
self.started_ = False
self.start_time = time.time()
def start(self):
"""Start the timer."""
assert not self.started_, "timer has already be... | apex/transformer/pipeline_parallel/_timers.py | import time
import torch
class _Timer:
"""Timer."""
def __init__(self, name):
self.name_ = name
self.elapsed_ = 0.0
self.started_ = False
self.start_time = time.time()
def start(self):
"""Start the timer."""
assert not self.started_, "timer has already be... | 0.836688 | 0.273875 |
import logging
import os
import shutil
from typing import Any, Dict, List, NewType, Optional
from .DefBuilder import DefBuilder
from .DocModel import DocModel
from .TemplateOptions import TemplateOptions
from .TemplateRenderer import TemplateRenderer
from .utils import log_and_raise_errors, stringify_front_matter
log... | jtex/LatexBuilder.py | import logging
import os
import shutil
from typing import Any, Dict, List, NewType, Optional
from .DefBuilder import DefBuilder
from .DocModel import DocModel
from .TemplateOptions import TemplateOptions
from .TemplateRenderer import TemplateRenderer
from .utils import log_and_raise_errors, stringify_front_matter
log... | 0.498291 | 0.212518 |
from gunicorn.app.base import BaseApplication
import multiprocessing
from lump.keypress import InteractiveTerminalHandler
from multiprocessing import Process
import psutil
import logging
import os
from lump.humanreadable import format_metric
logger = logging.getLogger(__name__)
class GunicornApplication(BaseApplicat... | src/lump/gunicorn.py | from gunicorn.app.base import BaseApplication
import multiprocessing
from lump.keypress import InteractiveTerminalHandler
from multiprocessing import Process
import psutil
import logging
import os
from lump.humanreadable import format_metric
logger = logging.getLogger(__name__)
class GunicornApplication(BaseApplicat... | 0.550124 | 0.071203 |
import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_allclose
from pyqumo.distributions import Constant, Exponential, SemiMarkovAbsorb, \
LinComb, VarChoice, Normal, Uniform, LinearTransform
@pytest.mark.parametrize('value', [34, 42])
def test_constant_distribution(value):
c... | tests/statistical_tests/test_distributions.py | import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_allclose
from pyqumo.distributions import Constant, Exponential, SemiMarkovAbsorb, \
LinComb, VarChoice, Normal, Uniform, LinearTransform
@pytest.mark.parametrize('value', [34, 42])
def test_constant_distribution(value):
c... | 0.854187 | 0.876951 |
import sys, os
import subprocess
import numpy as np
import pandas as pd
from Bio.PDB import *
from Bio import SeqIO
from Bio import AlignIO
from Bio import Align
import itertools as it
def filterandparse_sequences(fastaOUT, theta):
"""
filter for gaps and N characters
"""
data = pd.read_csv("../../... | code/18SrRNA/pipeline_mapping/prepaln.py | import sys, os
import subprocess
import numpy as np
import pandas as pd
from Bio.PDB import *
from Bio import SeqIO
from Bio import AlignIO
from Bio import Align
import itertools as it
def filterandparse_sequences(fastaOUT, theta):
"""
filter for gaps and N characters
"""
data = pd.read_csv("../../... | 0.097998 | 0.156846 |
from tkinter import *
from PIL import ImageTk, Image
import pymysql
from tkinter import messagebox
from tkinter import ttk
from datetime import datetime, timedelta
import decimal
class exhibitDetail():
def __init__(self):
# Invoke createLoginWindow; Invoke buildLoginWindow, Set loginWindow as mainloop
... | Pages/exhibitDetail.py | from tkinter import *
from PIL import ImageTk, Image
import pymysql
from tkinter import messagebox
from tkinter import ttk
from datetime import datetime, timedelta
import decimal
class exhibitDetail():
def __init__(self):
# Invoke createLoginWindow; Invoke buildLoginWindow, Set loginWindow as mainloop
... | 0.370225 | 0.077343 |
import argparse
import json
import os
import os.path as osp
import random
import sys
import numpy as np
import torch
from tqdm import tqdm
def seed_worker(worker_id):
worker_seed = torch.initial_seed() % 2 ** 32
np.random.seed(worker_seed)
random.seed(worker_seed)
sys.path.append(osp.dirname(osp.dirnam... | registration/preprocess_data.py | import argparse
import json
import os
import os.path as osp
import random
import sys
import numpy as np
import torch
from tqdm import tqdm
def seed_worker(worker_id):
worker_seed = torch.initial_seed() % 2 ** 32
np.random.seed(worker_seed)
random.seed(worker_seed)
sys.path.append(osp.dirname(osp.dirnam... | 0.289271 | 0.126758 |
from keras.models import Sequential, model_from_json
import numpy as np
import et_cleartk_io as ctk_io
import sys
import os.path
import pickle
from keras.preprocessing.sequence import pad_sequences
def main(args):
if len(args) < 1:
sys.stderr.write("Error - one required argument: <model directory>\n")
... | ctakes-temporal/scripts/nn/cnn_classify.py |
from keras.models import Sequential, model_from_json
import numpy as np
import et_cleartk_io as ctk_io
import sys
import os.path
import pickle
from keras.preprocessing.sequence import pad_sequences
def main(args):
if len(args) < 1:
sys.stderr.write("Error - one required argument: <model directory>\n")
... | 0.258981 | 0.159152 |
import unittest
from ..TestCase import TestCase
class TestDomainRenew(TestCase):
def test_render_domain_renew_request(self):
self.assertRequest('''<?xml version="1.0" ?>
<epp xmlns="urn:ietf:params:xml:ns:epp-1.0">
<command>
<renew>
<domain:renew xmlns:domain="urn:ietf:params:xml... | tests/modules/domain/test_domain_renew.py |
import unittest
from ..TestCase import TestCase
class TestDomainRenew(TestCase):
def test_render_domain_renew_request(self):
self.assertRequest('''<?xml version="1.0" ?>
<epp xmlns="urn:ietf:params:xml:ns:epp-1.0">
<command>
<renew>
<domain:renew xmlns:domain="urn:ietf:params:xml... | 0.399929 | 0.361813 |
from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django.dispatch import receiver
# Create your models here.
class Neighbourhood(models.Model):
HOODS = (
('NairobiWest','Nairobi West',),
('SouthC','South C'),
('SouthB','South B'... | app/models.py | from django.db import models
from django.contrib.auth.models import User
from django.db.models.signals import post_save
from django.dispatch import receiver
# Create your models here.
class Neighbourhood(models.Model):
HOODS = (
('NairobiWest','Nairobi West',),
('SouthC','South C'),
('SouthB','South B'... | 0.414069 | 0.077973 |
from iso8601 import parse_date
from openprocurement.api.utils import error_handler, raise_operation_error, get_now
from openprocurement.api.validation import OPERATIONS, validate_data, validate_json_data
from openprocurement.tender.cfaselectionua.constants import TENDER_PERIOD_MINIMAL_DURATION
from openprocurement.te... | src/openprocurement/tender/cfaselectionua/validation.py | from iso8601 import parse_date
from openprocurement.api.utils import error_handler, raise_operation_error, get_now
from openprocurement.api.validation import OPERATIONS, validate_data, validate_json_data
from openprocurement.tender.cfaselectionua.constants import TENDER_PERIOD_MINIMAL_DURATION
from openprocurement.te... | 0.496582 | 0.206234 |
import time
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from modl.datasets.image import load_image
from modl.decomposition.image import ImageDictFact, DictionaryScorer
from modl.feature_extraction.image import LazyCleanPatchExtractor
from modl.plotting.image import plot_patches
batch_... | examples/decompose_images.py | import time
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from modl.datasets.image import load_image
from modl.decomposition.image import ImageDictFact, DictionaryScorer
from modl.feature_extraction.image import LazyCleanPatchExtractor
from modl.plotting.image import plot_patches
batch_... | 0.425128 | 0.337504 |
import pytest
import numpy as np
import galois
from .helper import random_errors
CODES = [
(15, 13), # GF(2^4) with t=1
(15, 11), # GF(2^4) with t=2
(15, 9), # GF(2^4) with t=3
(15, 7), # GF(2^4) with t=4
(15, 5), # GF(2^4) with t=5
(15, 3), # GF(2^4) with t=6
(15, 1), # GF(2^4) wi... | tests/codes/test_rs_decode.py | import pytest
import numpy as np
import galois
from .helper import random_errors
CODES = [
(15, 13), # GF(2^4) with t=1
(15, 11), # GF(2^4) with t=2
(15, 9), # GF(2^4) with t=3
(15, 7), # GF(2^4) with t=4
(15, 5), # GF(2^4) with t=5
(15, 3), # GF(2^4) with t=6
(15, 1), # GF(2^4) wi... | 0.604632 | 0.646844 |
import numpy as np
import pandas as pd
from collections import Counter
from optlang.interface import (
OPTIMAL,
NUMERIC,
FEASIBLE,
SUBOPTIMAL,
ITERATION_LIMIT,
)
from optlang.symbolics import Zero
from itertools import chain
from functools import partial
from cobra.exceptions import OptimizationErr... | micom/solution.py |
import numpy as np
import pandas as pd
from collections import Counter
from optlang.interface import (
OPTIMAL,
NUMERIC,
FEASIBLE,
SUBOPTIMAL,
ITERATION_LIMIT,
)
from optlang.symbolics import Zero
from itertools import chain
from functools import partial
from cobra.exceptions import OptimizationErr... | 0.836154 | 0.479869 |
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: ovirt_user
short_description: Module to manage users in oVirt/RHV
version_added: "2.3"
author: "<NAME> (@machacekondra)"
description:
- "Modul... | ansible/my_env/lib/python2.7/site-packages/ansible/modules/cloud/ovirt/ovirt_user.py |
ANSIBLE_METADATA = {'metadata_version': '1.1',
'status': ['preview'],
'supported_by': 'community'}
DOCUMENTATION = '''
---
module: ovirt_user
short_description: Module to manage users in oVirt/RHV
version_added: "2.3"
author: "<NAME> (@machacekondra)"
description:
- "Modul... | 0.659405 | 0.3229 |
import rospy
class RegisterMonitor(type):
def __init__(cls, name, bases, nmspc):
super(RegisterMonitor, cls).__init__(name, bases, nmspc)
if not hasattr(cls, 'registry'):
cls.registry = {}
cls.registry[cls.name] = cls
# Remove base classes
for b in bases:
... | watchdog_node/src/watchdog_node/monitors/base_monitor.py | import rospy
class RegisterMonitor(type):
def __init__(cls, name, bases, nmspc):
super(RegisterMonitor, cls).__init__(name, bases, nmspc)
if not hasattr(cls, 'registry'):
cls.registry = {}
cls.registry[cls.name] = cls
# Remove base classes
for b in bases:
... | 0.480235 | 0.067209 |
import logging
import os
import sys
import shutil
import datetime
logging.basicConfig(filename="tools.log", level=logging.INFO)
log = logging.getLogger("tools")
class FileTools:
output_dir = None
log = logging.getLogger("file_tools")
def __init__(self, output_dir):
self.output_dir = output_dir... | tools.py |
import logging
import os
import sys
import shutil
import datetime
logging.basicConfig(filename="tools.log", level=logging.INFO)
log = logging.getLogger("tools")
class FileTools:
output_dir = None
log = logging.getLogger("file_tools")
def __init__(self, output_dir):
self.output_dir = output_dir... | 0.114121 | 0.066266 |
# standard library
import re
from typing import TYPE_CHECKING, Callable, Optional, Union
# first-party
from tcex.input.field_types.exception import (
InvalidEmptyValue,
InvalidLengthValue,
InvalidPatternValue,
InvalidType,
InvalidVariableType,
)
if TYPE_CHECKING: # pragma: no cover
# third-pa... | tcex/input/field_types/string.py | # standard library
import re
from typing import TYPE_CHECKING, Callable, Optional, Union
# first-party
from tcex.input.field_types.exception import (
InvalidEmptyValue,
InvalidLengthValue,
InvalidPatternValue,
InvalidType,
InvalidVariableType,
)
if TYPE_CHECKING: # pragma: no cover
# third-pa... | 0.912619 | 0.289562 |
import argparse
import torch
from pytorch_lightning import Trainer, seed_everything
from pytorch_lightning.loggers import TensorBoardLogger, CSVLogger
from pytorch_lightning.callbacks import ModelCheckpoint
import route_distances.lstm.defaults as defaults
from route_distances.lstm.data import TreeDataModule
from rout... | route_distances/tools/train_lstm_model.py | import argparse
import torch
from pytorch_lightning import Trainer, seed_everything
from pytorch_lightning.loggers import TensorBoardLogger, CSVLogger
from pytorch_lightning.callbacks import ModelCheckpoint
import route_distances.lstm.defaults as defaults
from route_distances.lstm.data import TreeDataModule
from rout... | 0.763836 | 0.285372 |
import glob
import shutil
import tempfile
import unittest
from html_classes_obfuscator import html_classes_obfuscator
class TestHtmlClassesObfuscator(unittest.TestCase):
TMP_FOLDER = tempfile.mkdtemp()
@classmethod
def setUpClass(cls) -> None:
shutil.copytree('./tests/tests_1', cls.TMP_FOLDER +... | tests/test_html_classes_obfuscator.py | import glob
import shutil
import tempfile
import unittest
from html_classes_obfuscator import html_classes_obfuscator
class TestHtmlClassesObfuscator(unittest.TestCase):
TMP_FOLDER = tempfile.mkdtemp()
@classmethod
def setUpClass(cls) -> None:
shutil.copytree('./tests/tests_1', cls.TMP_FOLDER +... | 0.503174 | 0.383006 |
import unittest
import os
from robot.errors import DataError
from robot.tidy import TidyCommandLine
from robot.utils.asserts import assert_raises_with_msg, assert_equals, assert_true
class TestArgumentValidation(unittest.TestCase):
def test_valid_explicit_format(self):
opts, _ = self._validate(format='t... | utest/tidy/test_argument_validation.py | import unittest
import os
from robot.errors import DataError
from robot.tidy import TidyCommandLine
from robot.utils.asserts import assert_raises_with_msg, assert_equals, assert_true
class TestArgumentValidation(unittest.TestCase):
def test_valid_explicit_format(self):
opts, _ = self._validate(format='t... | 0.645567 | 0.607605 |
from django.core.urlresolvers import reverse, NoReverseMatch
import pytz
from corehq.apps.reports.standard.deployments import DeploymentsReport
from corehq.apps.reports.datatables import DataTablesHeader, DataTablesColumn
from dimagi.utils.timezones import utils as tz_utils
from couchforms.models import XFormError
from... | corehq/apps/receiverwrapper/reports.py | from django.core.urlresolvers import reverse, NoReverseMatch
import pytz
from corehq.apps.reports.standard.deployments import DeploymentsReport
from corehq.apps.reports.datatables import DataTablesHeader, DataTablesColumn
from dimagi.utils.timezones import utils as tz_utils
from couchforms.models import XFormError
from... | 0.568176 | 0.185209 |
from logging import getLogger
from typing import Optional, Tuple
import click
from eth_typing import URI, HexAddress, HexStr
from eth_utils import encode_hex
from web3.contract import Contract
from raiden_contracts.constants import (
CONTRACT_CUSTOM_TOKEN,
CONTRACT_TOKEN_NETWORK,
CONTRACT_TOKEN_NETWORK_RE... | raiden_contracts/tests/deprecation_switch_testnet.py | from logging import getLogger
from typing import Optional, Tuple
import click
from eth_typing import URI, HexAddress, HexStr
from eth_utils import encode_hex
from web3.contract import Contract
from raiden_contracts.constants import (
CONTRACT_CUSTOM_TOKEN,
CONTRACT_TOKEN_NETWORK,
CONTRACT_TOKEN_NETWORK_RE... | 0.849441 | 0.126974 |
import json, requests, sys, getpass, os
def Init():
print("+===== Weaved CLI - <NAME> (c) =====+")
print("")
print("")
try:
username = input("Enter your email address: ")
password = getpass.getpass()
url = "https://api.weaved.com/v22/api/user/login/" + username + "/" + password
print("Conne... | weaved.py | import json, requests, sys, getpass, os
def Init():
print("+===== Weaved CLI - <NAME> (c) =====+")
print("")
print("")
try:
username = input("Enter your email address: ")
password = getpass.getpass()
url = "https://api.weaved.com/v22/api/user/login/" + username + "/" + password
print("Conne... | 0.065897 | 0.049199 |
from collections.abc import Iterator, Iterable
from typing import TypeVar, Optional, Any, Generic, Dict, List, Set
from untypy.error import UntypyAttributeError, UntypyTypeError
from untypy.impl.wrappedclass import WrappedType
from untypy.interfaces import TypeCheckerFactory, TypeChecker, CreationContext, ExecutionCon... | untypy/impl/interface.py | from collections.abc import Iterator, Iterable
from typing import TypeVar, Optional, Any, Generic, Dict, List, Set
from untypy.error import UntypyAttributeError, UntypyTypeError
from untypy.impl.wrappedclass import WrappedType
from untypy.interfaces import TypeCheckerFactory, TypeChecker, CreationContext, ExecutionCon... | 0.828384 | 0.160924 |
import einops
from einops import rearrange
import torch
import torch.nn as nn
class Fastformer(nn.Module):
def __init__(self, dim = 3, decode_dim = 16):
super(Fastformer, self).__init__()
# Generate weight for Wquery、Wkey and Wvalue
self.to_qkv = nn.Linear(dim, decode_dim * 3, bias = False)... | Fastformer.py | import einops
from einops import rearrange
import torch
import torch.nn as nn
class Fastformer(nn.Module):
def __init__(self, dim = 3, decode_dim = 16):
super(Fastformer, self).__init__()
# Generate weight for Wquery、Wkey and Wvalue
self.to_qkv = nn.Linear(dim, decode_dim * 3, bias = False)... | 0.895393 | 0.502319 |
import os
from setuptools import setup, find_packages
here = os.path.abspath(os.path.dirname(__file__))
README = open(os.path.join(here, 'README.md')).read()
CHANGES = open(os.path.join(here, 'CHANGES.md')).read()
version = '0.1.2b0'
install_requires = [
'eduid_am >= 0.6.0',
'eduid_userdb >= 0.4.0b... | setup.py | import os
from setuptools import setup, find_packages
here = os.path.abspath(os.path.dirname(__file__))
README = open(os.path.join(here, 'README.md')).read()
CHANGES = open(os.path.join(here, 'CHANGES.md')).read()
version = '0.1.2b0'
install_requires = [
'eduid_am >= 0.6.0',
'eduid_userdb >= 0.4.0b... | 0.284775 | 0.100657 |
from typing import Optional, Sequence
def search_rotated_array(array, num):
if not array: return None
return _inner_search(array, num, 0, len(array) - 1)
def _inner_search(array, num, start, end):
middle = ((end - start) // 2) + start
if array[middle] == num: return middle
if end - start =... | ch10/q10-03.py | from typing import Optional, Sequence
def search_rotated_array(array, num):
if not array: return None
return _inner_search(array, num, 0, len(array) - 1)
def _inner_search(array, num, start, end):
middle = ((end - start) // 2) + start
if array[middle] == num: return middle
if end - start =... | 0.776199 | 0.670366 |
from . import stats
from .analysis import Analysis, PeriodData
class _PeriodData(PeriodData):
def __init__(self):
self.period_begin_ts = None
self.cpus = {}
self.tids = {}
class Cputop(Analysis):
def __init__(self, state, conf):
notification_cbs = {
'sched_migrat... | lttnganalyses/core/cputop.py |
from . import stats
from .analysis import Analysis, PeriodData
class _PeriodData(PeriodData):
def __init__(self):
self.period_begin_ts = None
self.cpus = {}
self.tids = {}
class Cputop(Analysis):
def __init__(self, state, conf):
notification_cbs = {
'sched_migrat... | 0.69987 | 0.438665 |
import copy as cp
import itertools
import os
import os.path as osp
import subprocess
import time
from concurrent.futures import ProcessPoolExecutor as Executor
from typing import Optional, Tuple, Union
import click
from mim.click import CustomCommand
from mim.utils import (
args2string,
echo_error,
echo_s... | mim/commands/gridsearch.py | import copy as cp
import itertools
import os
import os.path as osp
import subprocess
import time
from concurrent.futures import ProcessPoolExecutor as Executor
from typing import Optional, Tuple, Union
import click
from mim.click import CustomCommand
from mim.utils import (
args2string,
echo_error,
echo_s... | 0.612194 | 0.161188 |
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
# INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY... | neon_speech/plugins/modules/background/__init__.py |
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
# INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY... | 0.76366 | 0.057467 |
import numpy as np
import torch
import torch.fft
from skimage.transform import iradon
from torch.utils.data import Dataset
from fit.utils.utils import log_amplitudes, normalize_FC
class TRecFourierCoefficientDataset(Dataset):
def __init__(self, ds, angles, mag_min, mag_max, img_shape=42, inner_circle=True):
... | fit/datamodules/tomo_rec/TRecFCDataset.py | import numpy as np
import torch
import torch.fft
from skimage.transform import iradon
from torch.utils.data import Dataset
from fit.utils.utils import log_amplitudes, normalize_FC
class TRecFourierCoefficientDataset(Dataset):
def __init__(self, ds, angles, mag_min, mag_max, img_shape=42, inner_circle=True):
... | 0.681303 | 0.369258 |
"""Implement unit tests for the module recorder.
"""
import pytest
import dns.exception
import dns.resolver
import tlsmate.tls as tls
import tlsmate.structs as structs
import tlsmate.resolver as resolver
@pytest.fixture(autouse=True)
def clear_cache():
resolver._resolved = {}
def test_determine_l4_addr():
l... | tests/modules/test_module_resolver.py | """Implement unit tests for the module recorder.
"""
import pytest
import dns.exception
import dns.resolver
import tlsmate.tls as tls
import tlsmate.structs as structs
import tlsmate.resolver as resolver
@pytest.fixture(autouse=True)
def clear_cache():
resolver._resolved = {}
def test_determine_l4_addr():
l... | 0.65202 | 0.520009 |
import unittest
from unittest.mock import patch
from webservices.legal_docs import (
delete_murs_from_es,
delete_murs_from_s3,
index_regulations,
index_statutes,
load_archived_murs,
create_docs_index
)
from webservices.legal_docs.load_legal_docs import (
get_subject_tree,
get_title_26_s... | tests/test_load_legal_docs.py | import unittest
from unittest.mock import patch
from webservices.legal_docs import (
delete_murs_from_es,
delete_murs_from_s3,
index_regulations,
index_statutes,
load_archived_murs,
create_docs_index
)
from webservices.legal_docs.load_legal_docs import (
get_subject_tree,
get_title_26_s... | 0.556641 | 0.407157 |
__author__ = "<NAME>"
__copyright__ = "Copyright <NAME>, <NAME> (2020)"
__version__ = "0.1"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__date__ = "July 12 2020"
from setuptools import setup, Extension
import os
module_dir = os.path.dirname(os.path.abspath(__file__))
if __name__ == "__main__":
setup(
... | setup.py |
__author__ = "<NAME>"
__copyright__ = "Copyright <NAME>, <NAME> (2020)"
__version__ = "0.1"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__date__ = "July 12 2020"
from setuptools import setup, Extension
import os
module_dir = os.path.dirname(os.path.abspath(__file__))
if __name__ == "__main__":
setup(
... | 0.443841 | 0.102934 |
from typing import Any, List, Optional, Sequence, Union
import numpy as np
from ..argument_utility import (
ActionScalerArg,
AugmentationArg,
EncoderArg,
ScalerArg,
UseGPUArg,
check_augmentation,
check_encoder,
check_use_gpu,
)
from ..augmentation import AugmentationPipeline
from ..con... | d3rlpy-master/d3rlpy/algos/awr.py | from typing import Any, List, Optional, Sequence, Union
import numpy as np
from ..argument_utility import (
ActionScalerArg,
AugmentationArg,
EncoderArg,
ScalerArg,
UseGPUArg,
check_augmentation,
check_encoder,
check_use_gpu,
)
from ..augmentation import AugmentationPipeline
from ..con... | 0.95232 | 0.224523 |
import requests
import lxml
from lxml import etree
from lxml.html import fromstring
root = etree.parse(r'C:\Users\Kiril\PycharmProjects\Diploma2020\data\corpus.xml')
root = root.getroot()
corpus = etree.SubElement(root, "corpus")
source_examples = dict()
text_num = dict()
status_codes = dict()
failed_elements = dict(... | dataset/corrector.py | import requests
import lxml
from lxml import etree
from lxml.html import fromstring
root = etree.parse(r'C:\Users\Kiril\PycharmProjects\Diploma2020\data\corpus.xml')
root = root.getroot()
corpus = etree.SubElement(root, "corpus")
source_examples = dict()
text_num = dict()
status_codes = dict()
failed_elements = dict(... | 0.159217 | 0.077483 |
"""build module"""
import os
import json
import akg
from akg import tvm
from akg.utils.kernel_exec import ReturnType
from .split_stitch import split_stitch_attr
from .construct_args import get_construct_args, get_tune_construct_args, \
should_enable_attr, get_stmt_for_tune, add_attrs_in_segment_infos
from .constru... | python/akg/composite/build_module.py |
"""build module"""
import os
import json
import akg
from akg import tvm
from akg.utils.kernel_exec import ReturnType
from .split_stitch import split_stitch_attr
from .construct_args import get_construct_args, get_tune_construct_args, \
should_enable_attr, get_stmt_for_tune, add_attrs_in_segment_infos
from .constru... | 0.310485 | 0.170957 |
from z3c.dependencychecker.dotted_name import DottedName
from z3c.dependencychecker.db import ImportsDatabase
from z3c.dependencychecker.tests.utils import get_extras_requirements_names
from z3c.dependencychecker.tests.utils import get_requirements_names
from z3c.dependencychecker.tests.utils import get_requirements_na... | z3c/dependencychecker/tests/test_imports_database.py | from z3c.dependencychecker.dotted_name import DottedName
from z3c.dependencychecker.db import ImportsDatabase
from z3c.dependencychecker.tests.utils import get_extras_requirements_names
from z3c.dependencychecker.tests.utils import get_requirements_names
from z3c.dependencychecker.tests.utils import get_requirements_na... | 0.544075 | 0.329338 |
import io
from lxml import objectify
import pathlib
import pytest
import tempfile
from hpxml_version_translator.converter import (
convert_hpxml3_to_4,
convert_hpxml_to_version,
)
from hpxml_version_translator import exceptions as exc
hpxml_dir = pathlib.Path(__file__).resolve().parent / "hpxml_v3_files"
d... | test/test_converter_v3.py | import io
from lxml import objectify
import pathlib
import pytest
import tempfile
from hpxml_version_translator.converter import (
convert_hpxml3_to_4,
convert_hpxml_to_version,
)
from hpxml_version_translator import exceptions as exc
hpxml_dir = pathlib.Path(__file__).resolve().parent / "hpxml_v3_files"
d... | 0.533397 | 0.601594 |
from asynctest import test, Test, TestManager
from asyncirc.plugins import tracking
from blinker import signal
from _mocks import Client
client = Client()
client.netid = "mock for testing"
tracking.create_registry(client)
def join_example_user():
signal("raw").send(client, text=":example!<EMAIL> JOIN #example exa... | test/tracking.py | from asynctest import test, Test, TestManager
from asyncirc.plugins import tracking
from blinker import signal
from _mocks import Client
client = Client()
client.netid = "mock for testing"
tracking.create_registry(client)
def join_example_user():
signal("raw").send(client, text=":example!<EMAIL> JOIN #example exa... | 0.440951 | 0.206534 |
import os
from typing import Optional, Callable, Tuple, Any, List
import torchvision.datasets as datasets
from torchvision.datasets.folder import default_loader
class ImageList(datasets.VisionDataset):
"""A generic Dataset class for domain adaptation in image classification
Parameters:
- **root** (st... | lbi/dalib/vision/datasets/imagelist.py | import os
from typing import Optional, Callable, Tuple, Any, List
import torchvision.datasets as datasets
from torchvision.datasets.folder import default_loader
class ImageList(datasets.VisionDataset):
"""A generic Dataset class for domain adaptation in image classification
Parameters:
- **root** (st... | 0.919063 | 0.570989 |
import sys
import os
import glob
from os.path import join, abspath, dirname, normpath, basename
import unittest
if sys.version_info[0] == 3:
from urllib import request as urllib2
else:
import urllib2
import time
import signal
import re
import gevent
from gevent import socket
import mysubprocess as subprocess
fr... | greentest-py3/test__examples.py | import sys
import os
import glob
from os.path import join, abspath, dirname, normpath, basename
import unittest
if sys.version_info[0] == 3:
from urllib import request as urllib2
else:
import urllib2
import time
import signal
import re
import gevent
from gevent import socket
import mysubprocess as subprocess
fr... | 0.227041 | 0.289391 |
# Standard library modules.
from math import tan
import enum
# Third party modules.
from matplotlib.collections import PatchCollection
from matplotlib.path import Path
from matplotlib.patches import Wedge, Rectangle, Circle, PathPatch, RegularPolygon
from matplotlib.transforms import Affine2D
# Local modules.
from py... | pymontecarlo/figures/sample.py | # Standard library modules.
from math import tan
import enum
# Third party modules.
from matplotlib.collections import PatchCollection
from matplotlib.path import Path
from matplotlib.patches import Wedge, Rectangle, Circle, PathPatch, RegularPolygon
from matplotlib.transforms import Affine2D
# Local modules.
from py... | 0.843477 | 0.584449 |
import logging
import os
import re
from abc import ABC
from typing import Callable, Dict, List, Iterator, Optional
import pandas as pd
import yaml
from pandas import DataFrame
logger = logging.getLogger(__name__)
class PipelineBase(ABC):
_methods_settings: List[Dict] = []
_method_list: List[Callable] = []
... | adcpipeline/pipeline.py | import logging
import os
import re
from abc import ABC
from typing import Callable, Dict, List, Iterator, Optional
import pandas as pd
import yaml
from pandas import DataFrame
logger = logging.getLogger(__name__)
class PipelineBase(ABC):
_methods_settings: List[Dict] = []
_method_list: List[Callable] = []
... | 0.777342 | 0.263346 |
from collections import defaultdict
from day import Day
class Pots:
def __init__(self, initial_state, state_map):
self.state = defaultdict(lambda: '.')
for i in range(len(initial_state)):
self.state[i] = initial_state[i]
self.state_map = state_map
def range_string(self, p... | days/day12.py | from collections import defaultdict
from day import Day
class Pots:
def __init__(self, initial_state, state_map):
self.state = defaultdict(lambda: '.')
for i in range(len(initial_state)):
self.state[i] = initial_state[i]
self.state_map = state_map
def range_string(self, p... | 0.533884 | 0.413063 |
import airflow
from airflow import DAG
from airflow_training.operators.postgres_to_gcs import PostgresToGoogleCloudStorageOperator
from airflow_training.operators.http_to_gcs import HttpToGcsOperator
from airflow.contrib.operators.dataproc_operator import (
DataprocClusterCreateOperator,
DataprocClusterDeleteOp... | dags/etl.py | import airflow
from airflow import DAG
from airflow_training.operators.postgres_to_gcs import PostgresToGoogleCloudStorageOperator
from airflow_training.operators.http_to_gcs import HttpToGcsOperator
from airflow.contrib.operators.dataproc_operator import (
DataprocClusterCreateOperator,
DataprocClusterDeleteOp... | 0.358915 | 0.46478 |
import argparse
import csv
import json
import os
import shlex
import shutil
import sys
import tempfile
from unittest.mock import MagicMock, patch
import pandas as pd
from . import REPO_ROOT, TEST_DATA
from .helpers import ChDir, mock_worksheet_helper
try:
PATH = sys.path
sys.path.append(REPO_ROOT)
from ... | tests/test_core.py | import argparse
import csv
import json
import os
import shlex
import shutil
import sys
import tempfile
from unittest.mock import MagicMock, patch
import pandas as pd
from . import REPO_ROOT, TEST_DATA
from .helpers import ChDir, mock_worksheet_helper
try:
PATH = sys.path
sys.path.append(REPO_ROOT)
from ... | 0.397821 | 0.328529 |
import time
import json
import boto3
start_time = time.time()
ec2 = boto3.resource('ec2')
ec2_client = boto3.client('ec2')
subnet_main = ['subnet-xxxx1', 'subnet-xxxx2', 'subnet-xxxx3'] # Check instances on these subnets
owner_main = ['30995619944', '309956199498'] # this uses the owner of the AMI for reference on wh... | attach_second_eni.py | import time
import json
import boto3
start_time = time.time()
ec2 = boto3.resource('ec2')
ec2_client = boto3.client('ec2')
subnet_main = ['subnet-xxxx1', 'subnet-xxxx2', 'subnet-xxxx3'] # Check instances on these subnets
owner_main = ['30995619944', '309956199498'] # this uses the owner of the AMI for reference on wh... | 0.29972 | 0.117294 |
from typing import List, Sequence
from fauxmo.plugins import FauxmoPlugin
from paho.mqtt.client import Client, MQTTMessage
class MQTTPlugin(FauxmoPlugin):
"""Fauxmo plugin to interact with an MQTT server by way of paho."""
def __init__(
self,
*,
name: str,
port: int,
... | mqttplugin.py | from typing import List, Sequence
from fauxmo.plugins import FauxmoPlugin
from paho.mqtt.client import Client, MQTTMessage
class MQTTPlugin(FauxmoPlugin):
"""Fauxmo plugin to interact with an MQTT server by way of paho."""
def __init__(
self,
*,
name: str,
port: int,
... | 0.87364 | 0.09947 |
import cv2
import faceRecognization_OpenCV as fcv
import init_model as im
import sys
def classify_face(test_img, x, y, w, h):
crop_img = test_img[y:y+h, x:x+w]
crop_img = im.fix_image(crop_img)
result = model(crop_img)
label = im.get_label(result)
return label
def load_model():
global model
... | app_video.py | import cv2
import faceRecognization_OpenCV as fcv
import init_model as im
import sys
def classify_face(test_img, x, y, w, h):
crop_img = test_img[y:y+h, x:x+w]
crop_img = im.fix_image(crop_img)
result = model(crop_img)
label = im.get_label(result)
return label
def load_model():
global model
... | 0.197251 | 0.255059 |
from docassemble.base.util import DARedis, user_info, DAObject, get_config, interview_url, response, message, log
from docassemble.base.generate_key import random_alphanumeric
import oauth2client.client
import json
import string
import random
import httplib2
import re
import codecs
__all__ = ['DAOAuth']
def safeid(te... | docassemble_base/docassemble/base/oauth.py | from docassemble.base.util import DARedis, user_info, DAObject, get_config, interview_url, response, message, log
from docassemble.base.generate_key import random_alphanumeric
import oauth2client.client
import json
import string
import random
import httplib2
import re
import codecs
__all__ = ['DAOAuth']
def safeid(te... | 0.442637 | 0.072243 |
from collections import namedtuple
import threading
import queue
from logging import getLogger
import time
import socket
import os
import textwrap
import signal
import importlib
import pkgutil
import re
import sys
import glob
import functools
from concurrent.futures import ThreadPoolExecutor
from sauna import plugins,... | sauna/__init__.py | from collections import namedtuple
import threading
import queue
from logging import getLogger
import time
import socket
import os
import textwrap
import signal
import importlib
import pkgutil
import re
import sys
import glob
import functools
from concurrent.futures import ThreadPoolExecutor
from sauna import plugins,... | 0.39946 | 0.059537 |
import unittest
import json
import azure.functions as func
from GetAndResizeImage import main
# More an integration test using demo_key since really making http call.
class TestMainFunction(unittest.TestCase):
def test_main_basetest(self):
# Arrange
identifier = "20151031074844... | tests/test_GetAndResizeImage.py | import unittest
import json
import azure.functions as func
from GetAndResizeImage import main
# More an integration test using demo_key since really making http call.
class TestMainFunction(unittest.TestCase):
def test_main_basetest(self):
# Arrange
identifier = "20151031074844... | 0.397471 | 0.124719 |
from xtcocotools.coco import COCO
from xtcocotools.cocoeval import COCOeval
import numpy as np
gt_file = '../annotations/example_wholebody_val.json'
preds = '../annotations/example_wholebody_preds.json'
sigmas_body = [0.026, 0.025, 0.025, 0.035, 0.035, 0.079, 0.079, 0.072, 0.072, 0.062, 0.062, 0.107, 0.107, 0.... | demos/demo_coco_wholebody.py | from xtcocotools.coco import COCO
from xtcocotools.cocoeval import COCOeval
import numpy as np
gt_file = '../annotations/example_wholebody_val.json'
preds = '../annotations/example_wholebody_preds.json'
sigmas_body = [0.026, 0.025, 0.025, 0.035, 0.035, 0.079, 0.079, 0.072, 0.072, 0.062, 0.062, 0.107, 0.107, 0.... | 0.246715 | 0.390069 |
get_ipython().run_line_magic("load_ext", " autoreload")
get_ipython().run_line_magic("autoreload", " 2")
#hide
from nbdev.showdoc import *
#export
import numpy as np
import numpy.linalg as npla
from typing import Tuple
def npmaxabs(arr: np.ndarray) -> float:
return np.max(np.abs(arr))
def simulated_shares(... | .virtual_documents/00_core.ipynb.py | get_ipython().run_line_magic("load_ext", " autoreload")
get_ipython().run_line_magic("autoreload", " 2")
#hide
from nbdev.showdoc import *
#export
import numpy as np
import numpy.linalg as npla
from typing import Tuple
def npmaxabs(arr: np.ndarray) -> float:
return np.max(np.abs(arr))
def simulated_shares(... | 0.780077 | 0.822795 |
import math
import os
import tensorflow as tf
import cv2
from dataporcess.porcess import Data
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
def resize_image(image, height=64, width=64):
top, bottom, left, right=(0, 0, 0, 0)
h, w, _ = image.shape
longest_edge =max(h, w)
if h<longest_edge:
dw = longest_edge-h
top = ... | code/facenet/network.py | import math
import os
import tensorflow as tf
import cv2
from dataporcess.porcess import Data
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
def resize_image(image, height=64, width=64):
top, bottom, left, right=(0, 0, 0, 0)
h, w, _ = image.shape
longest_edge =max(h, w)
if h<longest_edge:
dw = longest_edge-h
top = ... | 0.412175 | 0.283397 |
class BoardStateParser:
def getColorCssClass(self, indexInTileCollection):
if indexInTileCollection == 0:
return "_tileBlue"
elif indexInTileCollection == 1:
return "_tileYellow"
elif indexInTileCollection == 2:
return "_tileRed"
elif indexInTileCo... | AzulGamesSite/AzulGameViewer/games/BoardStateParser.py | class BoardStateParser:
def getColorCssClass(self, indexInTileCollection):
if indexInTileCollection == 0:
return "_tileBlue"
elif indexInTileCollection == 1:
return "_tileYellow"
elif indexInTileCollection == 2:
return "_tileRed"
elif indexInTileCo... | 0.282889 | 0.405508 |
from authlib.jose import jwt
from datetime import datetime, timezone
from typing import Optional, Dict, Any, List
from ..models import OpenIDConnectToken
class SignaturgruppenToken(OpenIDConnectToken, Dict[str, Any]):
"""Token model used by the OIDC Identity Provider SignaturGruppen."""
@classmethod
def... | src/auth_api/oidc/signaturgruppen/models.py | from authlib.jose import jwt
from datetime import datetime, timezone
from typing import Optional, Dict, Any, List
from ..models import OpenIDConnectToken
class SignaturgruppenToken(OpenIDConnectToken, Dict[str, Any]):
"""Token model used by the OIDC Identity Provider SignaturGruppen."""
@classmethod
def... | 0.865807 | 0.196537 |
import unittest
import numpy as np
from geomulator.surface import Surface
class TestTensorField(unittest.TestCase):
def test_metric(self):
u, v = np.meshgrid(np.linspace(-1, 1, 1001), np.linspace(-1, 1, 1001))
r = 1.5
surface = Surface(
[u, v, np.sqrt(r**2 - u**2 - v**2)],
... | tests/test_surface.py | import unittest
import numpy as np
from geomulator.surface import Surface
class TestTensorField(unittest.TestCase):
def test_metric(self):
u, v = np.meshgrid(np.linspace(-1, 1, 1001), np.linspace(-1, 1, 1001))
r = 1.5
surface = Surface(
[u, v, np.sqrt(r**2 - u**2 - v**2)],
... | 0.521959 | 0.75683 |
import numpy as np
from vimms.Agent import AbstractAgent
class DataDependantAction():
def __init__(self):
self.mz = None
self.rt = None
self.original_intensity = None
self.scaled_intensity = None
self.ms_level = 1
self.idx = None
self.valid = True
def t... | vimms_gym/agents.py | import numpy as np
from vimms.Agent import AbstractAgent
class DataDependantAction():
def __init__(self):
self.mz = None
self.rt = None
self.original_intensity = None
self.scaled_intensity = None
self.ms_level = 1
self.idx = None
self.valid = True
def t... | 0.689828 | 0.246511 |
import math
import cv2
import numpy as np
imgPPI = 300
inToM = 0.0254
posterMaxWidthIn = 17
posterMaxHeightIn = 23
posterMaxWidthM = posterMaxWidthIn * inToM
posterMaxHeightM = posterMaxHeightIn * inToM
charucoNSqVert = 10
charucoSqSizeM = float(posterMaxHeightM) / float(charucoNSqVert)
charucoMarkerSizeM = charuco... | skycam/maproom/constants.py | import math
import cv2
import numpy as np
imgPPI = 300
inToM = 0.0254
posterMaxWidthIn = 17
posterMaxHeightIn = 23
posterMaxWidthM = posterMaxWidthIn * inToM
posterMaxHeightM = posterMaxHeightIn * inToM
charucoNSqVert = 10
charucoSqSizeM = float(posterMaxHeightM) / float(charucoNSqVert)
charucoMarkerSizeM = charuco... | 0.381565 | 0.159938 |
import torch
import torch.nn as nn
from ..builder import BACKBONES
from .base_backbone import BaseBackbone
import torch.nn.functional as F
class BasicConv2d(nn.Module):
def __init__(self, input_channels, output_channels, kernel_size, padding=0, stride=1, **kwargs):
super().__init__()
self.conv ... | torchclas/models/backbones/inceptionv3.py |
import torch
import torch.nn as nn
from ..builder import BACKBONES
from .base_backbone import BaseBackbone
import torch.nn.functional as F
class BasicConv2d(nn.Module):
def __init__(self, input_channels, output_channels, kernel_size, padding=0, stride=1, **kwargs):
super().__init__()
self.conv ... | 0.960759 | 0.436862 |
from collections import Counter
import numpy as np
import unittest
from ray.rllib.utils.replay_buffers.prioritized_replay_buffer import (
PrioritizedReplayBuffer,
)
from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch
from ray.rllib.utils.test_utils import check
class TestPrioritizedReplayBuffe... | rllib/utils/replay_buffers/tests/test_prioritized_replay_buffer_replay_buffer_api.py | from collections import Counter
import numpy as np
import unittest
from ray.rllib.utils.replay_buffers.prioritized_replay_buffer import (
PrioritizedReplayBuffer,
)
from ray.rllib.policy.sample_batch import SampleBatch, MultiAgentBatch
from ray.rllib.utils.test_utils import check
class TestPrioritizedReplayBuffe... | 0.897977 | 0.465509 |
import argparse
from datetime import datetime, timedelta
import logging
from logging.handlers import RotatingFileHandler
import time
import sys
from bs4 import BeautifulSoup
import dateutil.parser
import requests
from utils import get_max_case_date, upsert_record, CASE_TYPES
from utils_details import parse_details
#... | scripts/get_new_civil_cases.py | import argparse
from datetime import datetime, timedelta
import logging
from logging.handlers import RotatingFileHandler
import time
import sys
from bs4 import BeautifulSoup
import dateutil.parser
import requests
from utils import get_max_case_date, upsert_record, CASE_TYPES
from utils_details import parse_details
#... | 0.622574 | 0.267588 |
import warnings
from functools import reduce
import networkx as nx
from kglib.utils.grakn.object.thing import build_thing
from kglib.utils.graph.thing.concept_dict_to_graph import concept_dict_to_graph
def concept_dict_from_concept_map(concept_map, tx):
"""
Given a concept map, build a dictionary of the var... | kglib/utils/graph/thing/queries_to_graph.py | import warnings
from functools import reduce
import networkx as nx
from kglib.utils.grakn.object.thing import build_thing
from kglib.utils.graph.thing.concept_dict_to_graph import concept_dict_to_graph
def concept_dict_from_concept_map(concept_map, tx):
"""
Given a concept map, build a dictionary of the var... | 0.838845 | 0.628094 |
import json
# You may need to install https://requests.readthedocs.io
import requests
api = 'http://localhost:1234'
hours_to_sim = '12:00:00'
def main():
# Make sure to start the simulation from the beginning
print('Did you just start the simulation? Time is currently', requests.get(api + '/sim/get-time').... | headless/examples/python_client.py |
import json
# You may need to install https://requests.readthedocs.io
import requests
api = 'http://localhost:1234'
hours_to_sim = '12:00:00'
def main():
# Make sure to start the simulation from the beginning
print('Did you just start the simulation? Time is currently', requests.get(api + '/sim/get-time').... | 0.556641 | 0.340074 |
import numpy as np
class Glorot(object):
"""
Understanding the difficulty of training deep feedforward neural networks
<NAME>, <NAME>
http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf
"""
def __init__(self, **kwargs):
pass
@staticmethod
def __str__():
return "Glo... | cottonwood/core/initializers.py | import numpy as np
class Glorot(object):
"""
Understanding the difficulty of training deep feedforward neural networks
<NAME>, <NAME>
http://proceedings.mlr.press/v9/glorot10a/glorot10a.pdf
"""
def __init__(self, **kwargs):
pass
@staticmethod
def __str__():
return "Glo... | 0.86342 | 0.504089 |
import random
from Game.Corak.dicio import salas, U, R, L, D, mapSize, rules
class keep():
def __init__(S, sala, at):
S.sala = sala
S.at = at
S.type = 1
keeper.append(S)
def hall(Do, obj):
out = 0
if Do[2] == "clear": clearall()
if Do[2] == "strt": out = strt()
if "g... | Playable/full builds/1.5 explorable map build/Game/Corak/Worldgen3.py | import random
from Game.Corak.dicio import salas, U, R, L, D, mapSize, rules
class keep():
def __init__(S, sala, at):
S.sala = sala
S.at = at
S.type = 1
keeper.append(S)
def hall(Do, obj):
out = 0
if Do[2] == "clear": clearall()
if Do[2] == "strt": out = strt()
if "g... | 0.087977 | 0.316277 |
import numpy as np
import collections
from .... import layers
__all__ = ['Pruner', 'StructurePruner']
class Pruner(object):
"""
Base class of all pruners.
"""
def __init__(self):
pass
def prune(self, param):
pass
class StructurePruner(Pruner):
"""
Pruner used to pruni... | python/paddle/fluid/contrib/slim/prune/pruner.py |
import numpy as np
import collections
from .... import layers
__all__ = ['Pruner', 'StructurePruner']
class Pruner(object):
"""
Base class of all pruners.
"""
def __init__(self):
pass
def prune(self, param):
pass
class StructurePruner(Pruner):
"""
Pruner used to pruni... | 0.878236 | 0.436982 |
# rospy for the subscriber
import rospy
# ROS Image message
from sensor_msgs.msg import Image
from std_msgs.msg import Bool
# ROS Image message -> OpenCV2 image converter
from cv_bridge import CvBridge, CvBridgeError
# OpenCV2 for saving an image
import cv2
# Instantiate CvBridge
bridge = CvBridge()
left=False
right=... | scripts/save_stereo_image.py |
# rospy for the subscriber
import rospy
# ROS Image message
from sensor_msgs.msg import Image
from std_msgs.msg import Bool
# ROS Image message -> OpenCV2 image converter
from cv_bridge import CvBridge, CvBridgeError
# OpenCV2 for saving an image
import cv2
# Instantiate CvBridge
bridge = CvBridge()
left=False
right=... | 0.222025 | 0.198705 |
import unittest
import functools
import random
import numpy as np
from tuplex import *
class TestArithmetic(unittest.TestCase):
def setUp(self):
self.conf = {"webui.enable": False, "driverMemory": "8MB", "partitionSize": "256KB"}
def test_add(self):
c = Context(self.conf)
res = c.par... | tuplex/python/tests/test_arithmetic.py |
import unittest
import functools
import random
import numpy as np
from tuplex import *
class TestArithmetic(unittest.TestCase):
def setUp(self):
self.conf = {"webui.enable": False, "driverMemory": "8MB", "partitionSize": "256KB"}
def test_add(self):
c = Context(self.conf)
res = c.par... | 0.404978 | 0.698445 |
import unittest
import mock
import json
import requests_mock
from certbot import errors
from certbot.compat import os
from certbot.errors import PluginError
from certbot.plugins import dns_test_common
from certbot.plugins.dns_test_common import DOMAIN
from certbot.tests import util as test_util
FAKE_PREFIX = "prefi... | certbot_dns_ionos/dns_ionos_test.py |
import unittest
import mock
import json
import requests_mock
from certbot import errors
from certbot.compat import os
from certbot.errors import PluginError
from certbot.plugins import dns_test_common
from certbot.plugins.dns_test_common import DOMAIN
from certbot.tests import util as test_util
FAKE_PREFIX = "prefi... | 0.401688 | 0.19544 |
"""Volume 1A: Linear Systems. Test driver."""
import signal
from functools import wraps
from matplotlib import pyplot as plt
def _autoclose(func):
"""Decorator for closing figures automatically."""
@wraps(func)
def wrapper(*args, **kwargs):
try:
plt.ion()
return func(*args,... | Vol1A/LinearSystems/testDriver.py | """Volume 1A: Linear Systems. Test driver."""
import signal
from functools import wraps
from matplotlib import pyplot as plt
def _autoclose(func):
"""Decorator for closing figures automatically."""
@wraps(func)
def wrapper(*args, **kwargs):
try:
plt.ion()
return func(*args,... | 0.882143 | 0.60364 |