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 twisted.internet import defer, reactor
from twisted.python import usage
from twisted.internet.endpoints import TCP4ClientEndpoint
from ooni.utils import log
from ooni.common.http_utils import extractTitle
from ooni.common.tcp_utils import TCPConnectFactory
from ooni.errors import failureToString
from ooni.templ... | ooni/nettests/blocking/telegram.py |
from twisted.internet import defer, reactor
from twisted.python import usage
from twisted.internet.endpoints import TCP4ClientEndpoint
from ooni.utils import log
from ooni.common.http_utils import extractTitle
from ooni.common.tcp_utils import TCPConnectFactory
from ooni.errors import failureToString
from ooni.templ... | 0.580709 | 0.083404 |
# python3 projects/citizen_dj/composition_pulses.py
import argparse
import inspect
import os
from pprint import pprint
import sys
# add parent directory to sys path to import relative modules
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir... | projects/citizen_dj/archive/composition_pulses.py |
# python3 projects/citizen_dj/composition_pulses.py
import argparse
import inspect
import os
from pprint import pprint
import sys
# add parent directory to sys path to import relative modules
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir... | 0.23546 | 0.125039 |
import tkinter as tk
import tkinter.ttk as ttk
from system.database import Database
from widgets.search_widget import searchWidget
from system.logger import *
@class_wrapper
class SelectDialog(tk.Toplevel):
'''
This class presents a simple select functionality on a single database
column. It returns the ro... | dialogs/select_dialog.py | import tkinter as tk
import tkinter.ttk as ttk
from system.database import Database
from widgets.search_widget import searchWidget
from system.logger import *
@class_wrapper
class SelectDialog(tk.Toplevel):
'''
This class presents a simple select functionality on a single database
column. It returns the ro... | 0.529507 | 0.126165 |
from __future__ import absolute_import
__authors__ = ["<NAME>"]
__license__ = "MIT"
__date__ = "15/09/2016"
import os
from .ProjectDef import ItemClassDef
from .ProjectItem import ProjectItem
from .AcqDataGroup import AcqDataGroup
from .IntensityGroup import IntensityGroup
from .QSpaceGroup import QSpaceGroup
@Ite... | xsocs/gui/project/XsocsProject.py |
from __future__ import absolute_import
__authors__ = ["<NAME>"]
__license__ = "MIT"
__date__ = "15/09/2016"
import os
from .ProjectDef import ItemClassDef
from .ProjectItem import ProjectItem
from .AcqDataGroup import AcqDataGroup
from .IntensityGroup import IntensityGroup
from .QSpaceGroup import QSpaceGroup
@Ite... | 0.723602 | 0.070688 |
from scripts.exceptions import EmployeeInTurnException
from scripts.exceptions import EmployeeNotInTurnException
from scripts.exceptions import KeyNotValidException
from datetime import datetime
import scripts.messages as msg
def VALID_H(h):
try:
datetime.strptime(str(h), '%H%M')
except ValueError:
... | scripts/turn.py | from scripts.exceptions import EmployeeInTurnException
from scripts.exceptions import EmployeeNotInTurnException
from scripts.exceptions import KeyNotValidException
from datetime import datetime
import scripts.messages as msg
def VALID_H(h):
try:
datetime.strptime(str(h), '%H%M')
except ValueError:
... | 0.710929 | 0.238528 |
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from django.contrib.auth.models import Group
from .forms import CustomUserChangeForm, CustomUserCreationForm
from .models import Address, CustomUser, Profile, TOTPRequest
# Register your models here.
admin.site.site_header = "پروژه فرو... | ecommerce/accounts/admin.py | from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from django.contrib.auth.models import Group
from .forms import CustomUserChangeForm, CustomUserCreationForm
from .models import Address, CustomUser, Profile, TOTPRequest
# Register your models here.
admin.site.site_header = "پروژه فرو... | 0.376279 | 0.126731 |
from __future__ import absolute_import
from __future__ import print_function
import math
class ResourceDefinition(object):
def __init__(self, name):
self.name = name
class OnchipMemoryDefinition(ResourceDefinition):
def __init__(self, name, size):
ResourceDefinition.__init__(self, name)
... | flipsyrup/configuration_reader/resource_definition.py | from __future__ import absolute_import
from __future__ import print_function
import math
class ResourceDefinition(object):
def __init__(self, name):
self.name = name
class OnchipMemoryDefinition(ResourceDefinition):
def __init__(self, name, size):
ResourceDefinition.__init__(self, name)
... | 0.366476 | 0.059237 |
import runtime.db as db
def fetch_samples(conn, query, n=1):
'''
Fetch n sample(s) at most according to the query statement.
Args:
conn: the connection object.
query (str): the select SQL statement.
n (int): the maximum sample number to query. Query all samples
if n <... | python/runtime/verifier/verifier.py |
import runtime.db as db
def fetch_samples(conn, query, n=1):
'''
Fetch n sample(s) at most according to the query statement.
Args:
conn: the connection object.
query (str): the select SQL statement.
n (int): the maximum sample number to query. Query all samples
if n <... | 0.827236 | 0.532668 |
import sys
import time
import traceback
from cStringIO import StringIO
import boto
from boto.s3.key import Key
from boto.s3.bucket import Bucket
from concurrent.futures import ThreadPoolExecutor
from threading import Semaphore
try:
from raven import Client
sentry_dsn = os.environ['ZSYNC_SENTRY_DSN']
client = C... | zsync/uploader.py | import sys
import time
import traceback
from cStringIO import StringIO
import boto
from boto.s3.key import Key
from boto.s3.bucket import Bucket
from concurrent.futures import ThreadPoolExecutor
from threading import Semaphore
try:
from raven import Client
sentry_dsn = os.environ['ZSYNC_SENTRY_DSN']
client = C... | 0.280616 | 0.07989 |
import numpy as np
import torch
import torchaudio
from pitchTracking import Pitch
class FFE:
def __init__(self, sr=16000):
self.sr = sr
self.pitch = Pitch(self.sr)
def __call__(self, y_ref, y_syn):
return self.calculate_ffe(y_ref, y_syn)
def calculate_ffe_path(self, ref_path, syn... | Metrics/f0_frame_error.py | import numpy as np
import torch
import torchaudio
from pitchTracking import Pitch
class FFE:
def __init__(self, sr=16000):
self.sr = sr
self.pitch = Pitch(self.sr)
def __call__(self, y_ref, y_syn):
return self.calculate_ffe(y_ref, y_syn)
def calculate_ffe_path(self, ref_path, syn... | 0.629433 | 0.555978 |
import sys
import random
import pytest
benchmark = pytest.importorskip('pytest_benchmark')
composite_object = {
'words': """
Lorem ipsum dolor sit amet, consectetur adipiscing
elit. Mauris adipiscing adipiscing placerat.
Vestibulum augue augue,
pellentesque quis sollicitudin id, ad... | benchmarks/test_benchmark.py | import sys
import random
import pytest
benchmark = pytest.importorskip('pytest_benchmark')
composite_object = {
'words': """
Lorem ipsum dolor sit amet, consectetur adipiscing
elit. Mauris adipiscing adipiscing placerat.
Vestibulum augue augue,
pellentesque quis sollicitudin id, ad... | 0.254694 | 0.296126 |
import os
import face_recognition
import cv2
import numpy as np
class Face:
def __init__(self):
# Using Camera 0
self.video = cv2.VideoCapture(0)
# 필요한 변수들 생성
self.face_locations = []
self.face_encodings = []
self.fileName = None
self.check = True
... | rpi-client/face/face.py | import os
import face_recognition
import cv2
import numpy as np
class Face:
def __init__(self):
# Using Camera 0
self.video = cv2.VideoCapture(0)
# 필요한 변수들 생성
self.face_locations = []
self.face_encodings = []
self.fileName = None
self.check = True
... | 0.311741 | 0.331228 |
import csv
import datetime
import numpy as np
from scipy.stats import stats
class Experiment:
def __init__(self, conditions, grouper, simplifier, stat_function, db_manager):
self.conditions = conditions
self.grouper = grouper
self.simplifier = simplifier
self.db_manager = db_man... | stat_classes.py | import csv
import datetime
import numpy as np
from scipy.stats import stats
class Experiment:
def __init__(self, conditions, grouper, simplifier, stat_function, db_manager):
self.conditions = conditions
self.grouper = grouper
self.simplifier = simplifier
self.db_manager = db_man... | 0.286469 | 0.129238 |
from __future__ import annotations
from typing import Dict,Sequence,List
from dmt.entity import Entity
from dmt.blueprint import Blueprint
from .blueprints.combinedloadingproperties import CombinedLoadingPropertiesBlueprint
from typing import Dict
from sima.riflex.elementreference import ElementReference
from sima.sima... | src/sima/riflex/combinedloadingproperties.py | from __future__ import annotations
from typing import Dict,Sequence,List
from dmt.entity import Entity
from dmt.blueprint import Blueprint
from .blueprints.combinedloadingproperties import CombinedLoadingPropertiesBlueprint
from typing import Dict
from sima.riflex.elementreference import ElementReference
from sima.sima... | 0.85555 | 0.348174 |
import numpy as np
import pytest
from ..sim_utils import Sim
PIXEL_SCALE = 0.263
@pytest.mark.parametrize('gal_type', ['exp'])
@pytest.mark.parametrize('psf_type', ['gauss', 'ps'])
@pytest.mark.parametrize('homogenize_psf', [False, True])
@pytest.mark.parametrize('n_coadd_psf', [1, 2, 3])
def test_sim_seeding_repr... | mdetsims/tests/test_sim_seeding.py | import numpy as np
import pytest
from ..sim_utils import Sim
PIXEL_SCALE = 0.263
@pytest.mark.parametrize('gal_type', ['exp'])
@pytest.mark.parametrize('psf_type', ['gauss', 'ps'])
@pytest.mark.parametrize('homogenize_psf', [False, True])
@pytest.mark.parametrize('n_coadd_psf', [1, 2, 3])
def test_sim_seeding_repr... | 0.486088 | 0.46308 |
import os
import sys
import errno
import shutil
import unittest
from tempfile import mkdtemp, mkstemp
try:
import landsat.general_helper as g
except ImportError:
sys.path.append(os.path
.abspath(os.path
.join(os.path.dirname(__file__),
... | tests/test_general_helper.py | import os
import sys
import errno
import shutil
import unittest
from tempfile import mkdtemp, mkstemp
try:
import landsat.general_helper as g
except ImportError:
sys.path.append(os.path
.abspath(os.path
.join(os.path.dirname(__file__),
... | 0.226441 | 0.286094 |
from unittest import TestCase
import rasterio
import numpy as np
import niche_vlaanderen
import pytest
from niche_vlaanderen.exception import NicheException
def raster_to_numpy(filename):
"""Read a GDAL grid as numpy array
Notes
------
No-data values are -99 for integer types and np.nan for real typ... | tests/test_acidity.py | from unittest import TestCase
import rasterio
import numpy as np
import niche_vlaanderen
import pytest
from niche_vlaanderen.exception import NicheException
def raster_to_numpy(filename):
"""Read a GDAL grid as numpy array
Notes
------
No-data values are -99 for integer types and np.nan for real typ... | 0.693161 | 0.726571 |
from django.conf import settings
import django.contrib.auth.models
import django.contrib.auth.validators
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0011_updat... | lifes/migrations/0001_initial.py |
from django.conf import settings
import django.contrib.auth.models
import django.contrib.auth.validators
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0011_updat... | 0.524151 | 0.151435 |
from subprocess import getoutput
from pathlib import Path
from transonic.util import timeit
statements = {
("cmorph", "_dilate"): "_dilate(image, selem, out, shift_x, shift_y)",
(
"_greyreconstruct",
"reconstruction_loop",
): "reconstruction_loop(ranks, prev, next_, strides, current_idx, i... | doc/for_dev/scikit-image/bench_util.py | from subprocess import getoutput
from pathlib import Path
from transonic.util import timeit
statements = {
("cmorph", "_dilate"): "_dilate(image, selem, out, shift_x, shift_y)",
(
"_greyreconstruct",
"reconstruction_loop",
): "reconstruction_loop(ranks, prev, next_, strides, current_idx, i... | 0.482429 | 0.194139 |
from unittest.mock import patch
from django.test import TestCase
from django.contrib.auth import get_user_model
from core import models
def sample_user(email='<EMAIL>', password='<PASSWORD>'):
"""Cria um usuario simples"""
return get_user_model().objects.create_user(email, password)
class ModelTests(TestC... | app/core/tests/test_models.py | from unittest.mock import patch
from django.test import TestCase
from django.contrib.auth import get_user_model
from core import models
def sample_user(email='<EMAIL>', password='<PASSWORD>'):
"""Cria um usuario simples"""
return get_user_model().objects.create_user(email, password)
class ModelTests(TestC... | 0.564819 | 0.368264 |
import unittest
from termcolor import colored
from game import Game, Status
class TestGame(unittest.TestCase):
def test_guess(self):
game = Game("POINT", False)
game.guess("SLITS")
self.assertDictEqual(game._correct_letters, {"I": {2}})
def test_guess_handles_casing(self):
... | pywordle/test_game.py | import unittest
from termcolor import colored
from game import Game, Status
class TestGame(unittest.TestCase):
def test_guess(self):
game = Game("POINT", False)
game.guess("SLITS")
self.assertDictEqual(game._correct_letters, {"I": {2}})
def test_guess_handles_casing(self):
... | 0.637482 | 0.649356 |
"""Command to delete a node pool in an Anthos cluster on AWS."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.api_lib.container import util as gke_util
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.contain... | lib/surface/container/aws/node_pools/delete.py | """Command to delete a node pool in an Anthos cluster on AWS."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.api_lib.container import util as gke_util
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.contain... | 0.680242 | 0.135575 |
import json
import os
import uuid
from datetime import datetime, timedelta, timezone
from urllib.parse import quote, unquote
import pytz
from crum import get_current_user
from dateutil import parser
from django.conf import settings
from django.contrib.auth.models import User
from django.core.files.storage import Defau... | customcalendar/models/calendarsettings.py | import json
import os
import uuid
from datetime import datetime, timedelta, timezone
from urllib.parse import quote, unquote
import pytz
from crum import get_current_user
from dateutil import parser
from django.conf import settings
from django.contrib.auth.models import User
from django.core.files.storage import Defau... | 0.394784 | 0.180467 |
import pytest
import logging
from azure.iot.device.provisioning.security.sk_security_client import SymmetricKeySecurityClient
logging.basicConfig(level=logging.DEBUG)
fake_symmetric_key = "<KEY>"
key_name = "registration"
fake_provisioning_host = "beauxbatons.academy-net"
fake_registration_id = "MyPensieve"
module_i... | azure-iot-device/tests/provisioning/security/test_sk_security_client.py |
import pytest
import logging
from azure.iot.device.provisioning.security.sk_security_client import SymmetricKeySecurityClient
logging.basicConfig(level=logging.DEBUG)
fake_symmetric_key = "<KEY>"
key_name = "registration"
fake_provisioning_host = "beauxbatons.academy-net"
fake_registration_id = "MyPensieve"
module_i... | 0.529993 | 0.131145 |
import logging
import re
import csv
from rdflib.namespace import RDF
from rdflib import Literal, Graph, URIRef
from .baseClasses import Person, User
from ..common.namespaces import AfelNamespacesManager, concatenate_uriref
__all__ = ['LearnerMappingParser', 'AFELLearner']
LOG = logging.getLogger(__name__)
class AFE... | afelTraces2rdf/tracesLoaders/learners.py | import logging
import re
import csv
from rdflib.namespace import RDF
from rdflib import Literal, Graph, URIRef
from .baseClasses import Person, User
from ..common.namespaces import AfelNamespacesManager, concatenate_uriref
__all__ = ['LearnerMappingParser', 'AFELLearner']
LOG = logging.getLogger(__name__)
class AFE... | 0.520984 | 0.121373 |
import numpy as np
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--inputfile', type=str, default='/home/wangjue/biodata/scData/scRNA_And_scATAC_Files/Processed_Data/GeneSymbolMat.dic',
help='inputfile name')
parser.add_argument('--outputfile', type=str, default='/home/wan... | Preprocessing_benchmark.py |
import numpy as np
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--inputfile', type=str, default='/home/wangjue/biodata/scData/scRNA_And_scATAC_Files/Processed_Data/GeneSymbolMat.dic',
help='inputfile name')
parser.add_argument('--outputfile', type=str, default='/home/wan... | 0.121334 | 0.085289 |
import logging
import pathlib
from abc import ABC
from collections import defaultdict
from logging import Logger
from operator import itemgetter
from typing import Collection, Mapping, Optional, Sequence, Tuple, TypeVar, Union
import pandas
import torch
from sklearn.cluster import KMeans
from .base import RankingMeth... | src/arclus/models/zero_shot.py | import logging
import pathlib
from abc import ABC
from collections import defaultdict
from logging import Logger
from operator import itemgetter
from typing import Collection, Mapping, Optional, Sequence, Tuple, TypeVar, Union
import pandas
import torch
from sklearn.cluster import KMeans
from .base import RankingMeth... | 0.91799 | 0.36608 |
import io
import pytest
import binobj
from binobj import errors
from binobj import fields
from binobj.pep526 import dataclass
class BasicStruct(binobj.Struct):
"""A basic structure."""
string = fields.String(size=7)
int64 = fields.Int64(endian="big")
uint24 = fields.UnsignedInteger(size=3, endian=... | tests/structures_test.py |
import io
import pytest
import binobj
from binobj import errors
from binobj import fields
from binobj.pep526 import dataclass
class BasicStruct(binobj.Struct):
"""A basic structure."""
string = fields.String(size=7)
int64 = fields.Int64(endian="big")
uint24 = fields.UnsignedInteger(size=3, endian=... | 0.739705 | 0.663533 |
import os
import click
from . import init as user_init
from . import scan as user_scan
from . import utility as user_utility
from . import drive as user_drive
@click.command()
def init():
''' Initializes the local directory structure '''
user_init.main_init_process()
@click.command()
def status():
"""... | src/main.py |
import os
import click
from . import init as user_init
from . import scan as user_scan
from . import utility as user_utility
from . import drive as user_drive
@click.command()
def init():
''' Initializes the local directory structure '''
user_init.main_init_process()
@click.command()
def status():
"""... | 0.243912 | 0.075007 |
from __future__ import absolute_import, division, print_function, unicode_literals
import logging
from typing import List, Optional, Tuple, Union, TYPE_CHECKING
import numpy as np
from art.attacks.attack import PoisoningAttackWhiteBox
from art.attacks.poisoning.backdoor_attack import PoisoningAttackBackdoor
from art... | art/attacks/poisoning/hidden_trigger_backdoor/hidden_trigger_backdoor.py | from __future__ import absolute_import, division, print_function, unicode_literals
import logging
from typing import List, Optional, Tuple, Union, TYPE_CHECKING
import numpy as np
from art.attacks.attack import PoisoningAttackWhiteBox
from art.attacks.poisoning.backdoor_attack import PoisoningAttackBackdoor
from art... | 0.937182 | 0.38318 |
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeRegressor
from sklearn import tree
def apply... | Parcial1/ExamenParcial/examenParcial1.py | import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeRegressor
from sklearn import tree
def apply... | 0.425009 | 0.599895 |
# In[2]:
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.utils import to_categorical
from sklearn.preprocessing import LabelEncoder
import gensim
from sklearn.metrics import classification_report, accuracy_score
from sklearn.model_selection import train_test_split
from tensorflow.keras.l... | code/kag.py |
# In[2]:
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.utils import to_categorical
from sklearn.preprocessing import LabelEncoder
import gensim
from sklearn.metrics import classification_report, accuracy_score
from sklearn.model_selection import train_test_split
from tensorflow.keras.l... | 0.751466 | 0.601359 |
from unittest.mock import patch
import pytest
import auditor
from constants import content_types
from db.models.searches import Search
from events.registry import search as searches_events
from factories.factory_projects import ProjectFactory
from tests.test_auditor.utils import AuditorBaseTest
@pytest.mark.audit... | platform/core/tests/test_auditor/test_auditor_search.py |
from unittest.mock import patch
import pytest
import auditor
from constants import content_types
from db.models.searches import Search
from events.registry import search as searches_events
from factories.factory_projects import ProjectFactory
from tests.test_auditor.utils import AuditorBaseTest
@pytest.mark.audit... | 0.640973 | 0.306294 |
import unittest
from http import HTTPStatus
from unittest.mock import patch, MagicMock
from submission_validator.services.ena_taxonomy import EnaTaxonomy
class TestEnaTaxonomy(unittest.TestCase):
def setUp(self):
self.maxDiff = None
self.ena_taxonomy = EnaTaxonomy(ena_url='')
@staticmethod
... | tests/unit/submission_validator/services/test_ena_taxonomy.py | import unittest
from http import HTTPStatus
from unittest.mock import patch, MagicMock
from submission_validator.services.ena_taxonomy import EnaTaxonomy
class TestEnaTaxonomy(unittest.TestCase):
def setUp(self):
self.maxDiff = None
self.ena_taxonomy = EnaTaxonomy(ena_url='')
@staticmethod
... | 0.710126 | 0.405979 |
import datetime
from flask import Flask, request, jsonify, flash
from flask_cors import CORS
app = Flask(__name__)
import json
CORS(app)
# Establishing connection to aws rds instance
import pymysql
connection = pymysql.connect(
#database-1.cxedn5oo3lwl.ap-south-1.rds.amazonaws.com
host = 'database-1.cxedn5oo3lwl.a... | Backend/app.py | import datetime
from flask import Flask, request, jsonify, flash
from flask_cors import CORS
app = Flask(__name__)
import json
CORS(app)
# Establishing connection to aws rds instance
import pymysql
connection = pymysql.connect(
#database-1.cxedn5oo3lwl.ap-south-1.rds.amazonaws.com
host = 'database-1.cxedn5oo3lwl.a... | 0.156523 | 0.075041 |
from time import perf_counter
from typing import List
from kivy.uix.behaviors.focus import FocusBehavior
from kivy.uix.scatter import Scatter
from kivy.properties import NumericProperty, BooleanProperty
from kivy.app import App
from kivy.graphics.vertex_instructions import Point
from kivy.graphics.transformation impor... | ceed/view/view_widgets.py | from time import perf_counter
from typing import List
from kivy.uix.behaviors.focus import FocusBehavior
from kivy.uix.scatter import Scatter
from kivy.properties import NumericProperty, BooleanProperty
from kivy.app import App
from kivy.graphics.vertex_instructions import Point
from kivy.graphics.transformation impor... | 0.914939 | 0.362828 |
aligned BAM file"""
import os
import subprocess
import click
@click.command()
@click.version_option()
@click.argument('inbam', type=click.Path(exists=True))
@click.argument('gdb', type=click.Path(exists=True))
@click.option('--cigar-errors', is_flag=True, help='CIGAR errors result in reads being classified as misali... | mitty/benchmarking/bam_accuracy.py | aligned BAM file"""
import os
import subprocess
import click
@click.command()
@click.version_option()
@click.argument('inbam', type=click.Path(exists=True))
@click.argument('gdb', type=click.Path(exists=True))
@click.option('--cigar-errors', is_flag=True, help='CIGAR errors result in reads being classified as misali... | 0.414543 | 0.212988 |
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding model 'VersionSite'
db.create_table('begood_sites_versionsite', (
('id', self.gf('django.db.models.fiel... | begood_sites/migrations/0001_initial.py | import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding model 'VersionSite'
db.create_table('begood_sites_versionsite', (
('id', self.gf('django.db.models.fiel... | 0.390243 | 0.212079 |
# Example for individual entry in metadata.json:
# "10": {
# "id": 10,
# "devicename": "C1",
# "filename": "C1.zip",
# "size": 13230419,
# "version": "2.x.2.43",
# "vendor": "Foscam",
# "hash_sum": "6d83527bac41aa174162279c3a746c7212ca85f2b0141704dea6afd329951237"
# }
import os
import tarfile
import jso... | code/utils/firmware.py |
# Example for individual entry in metadata.json:
# "10": {
# "id": 10,
# "devicename": "C1",
# "filename": "C1.zip",
# "size": 13230419,
# "version": "2.x.2.43",
# "vendor": "Foscam",
# "hash_sum": "6d83527bac41aa174162279c3a746c7212ca85f2b0141704dea6afd329951237"
# }
import os
import tarfile
import jso... | 0.469763 | 0.190423 |
from io import StringIO
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
class Logger(object):
"""Logging in tensorboard without tensorflow ops."""
def __init__(self, log_dir, graph=None):
"""Creates a summary writer logging to log_dir.
:param: log_dir: system path to logs
:... | l2l/logger.py | from io import StringIO
import tensorflow as tf
import matplotlib.pyplot as plt
import numpy as np
class Logger(object):
"""Logging in tensorboard without tensorflow ops."""
def __init__(self, log_dir, graph=None):
"""Creates a summary writer logging to log_dir.
:param: log_dir: system path to logs
:... | 0.955651 | 0.609175 |
from playsound import playsound
from datetime import datetime
from os import system
from os import system, name
import win32gui
import pyttsx3
import speech_recognition as sr
import os
import webbrowser
import subprocess
import time
import pathlib
#Enviroment Config
appname = 'Command Prompt'
xpos = 1260
ypos = 1
wid... | main.py | from playsound import playsound
from datetime import datetime
from os import system
from os import system, name
import win32gui
import pyttsx3
import speech_recognition as sr
import os
import webbrowser
import subprocess
import time
import pathlib
#Enviroment Config
appname = 'Command Prompt'
xpos = 1260
ypos = 1
wid... | 0.215846 | 0.066782 |
from telethon import TelegramClient, sync, events
from telethon.tl.functions.channels import GetMessagesRequest
from pathlib import Path
import unittest
import time
import requests
from unittest.mock import patch
import main_pars
from main_pars import pars_vv,pars_gor,pars_tts,pars_asna,pars_mag,pars_puma,pars_metro,pa... | tests.py | from telethon import TelegramClient, sync, events
from telethon.tl.functions.channels import GetMessagesRequest
from pathlib import Path
import unittest
import time
import requests
from unittest.mock import patch
import main_pars
from main_pars import pars_vv,pars_gor,pars_tts,pars_asna,pars_mag,pars_puma,pars_metro,pa... | 0.41253 | 0.217109 |
from django.urls import reverse
from rest_framework import status
from rest_framework.response import Response
from rest_framework.test import APITestCase
class V1TestCase(APITestCase):
def _create_new_work(self) -> Response:
url = reverse('v1:work-list')
with open('/sample/invoice-cs-CZ.pdf', 'b... | src/endpoints/tests/v1_tests.py | from django.urls import reverse
from rest_framework import status
from rest_framework.response import Response
from rest_framework.test import APITestCase
class V1TestCase(APITestCase):
def _create_new_work(self) -> Response:
url = reverse('v1:work-list')
with open('/sample/invoice-cs-CZ.pdf', 'b... | 0.538741 | 0.135375 |
import nltk
import sys
import os
import time
import itertools
import jieba
import numpy
import scipy.sparse
TEXT_ENCODING="utf-8"
print("loading stop words...")
nltk.download('stopwords')
en_stop_words = set(nltk.corpus.stopwords.words('english'))
en_stop_words.add('nsbp') #skip &nsbp;
with open("dict/stop.txt", 'r',... | prepare_tf.py | import nltk
import sys
import os
import time
import itertools
import jieba
import numpy
import scipy.sparse
TEXT_ENCODING="utf-8"
print("loading stop words...")
nltk.download('stopwords')
en_stop_words = set(nltk.corpus.stopwords.words('english'))
en_stop_words.add('nsbp') #skip &nsbp;
with open("dict/stop.txt", 'r',... | 0.085956 | 0.08043 |
from cursesmenu import CursesMenu
from cursesmenu.items import FunctionItem
from collections import OrderedDict
from prettytable import PrettyTable
from bust.utils import json_parser
from bust.utils import cont
from bust.utils import is_int
from bust.utils import clear_screen
from bust.utils import write_string_to_fil... | bust/editor.py | from cursesmenu import CursesMenu
from cursesmenu.items import FunctionItem
from collections import OrderedDict
from prettytable import PrettyTable
from bust.utils import json_parser
from bust.utils import cont
from bust.utils import is_int
from bust.utils import clear_screen
from bust.utils import write_string_to_fil... | 0.523908 | 0.114517 |
import logging
import time
import os
import torch
from tqdm import tqdm
import numpy as np
from fcos_core.config import cfg
from fcos_core.modeling.poolers import Pooler
from fcos_core.data.datasets.evaluation import evaluate
from ..utils.comm import is_main_process, get_world_size
from ..utils.comm import all_gather... | fcos_core/engine/feature_extractor.py | import logging
import time
import os
import torch
from tqdm import tqdm
import numpy as np
from fcos_core.config import cfg
from fcos_core.modeling.poolers import Pooler
from fcos_core.data.datasets.evaluation import evaluate
from ..utils.comm import is_main_process, get_world_size
from ..utils.comm import all_gather... | 0.416915 | 0.253001 |
import time
import cv2 as cv
import argparse
import psutil
import os
# Import OpenVINO Inference Engine
from openvino.inference_engine import IECore, IENetwork
mobilenet_ssd_labels = {0:'background',
1: 'aeroplane',
2: 'bicycle',
3: 'bird',
... | openvino_basic_object_detection.py |
import time
import cv2 as cv
import argparse
import psutil
import os
# Import OpenVINO Inference Engine
from openvino.inference_engine import IECore, IENetwork
mobilenet_ssd_labels = {0:'background',
1: 'aeroplane',
2: 'bicycle',
3: 'bird',
... | 0.598077 | 0.26092 |
import numpy as np
from py_diff_stokes_flow.env.env_base import EnvBase
from py_diff_stokes_flow.common.common import ndarray
class FlowAveragerEnv3d(EnvBase):
def __init__(self, seed, folder):
np.random.seed(seed)
cell_nums = (64, 64, 4)
E = 100
nu = 0.499
vol_tol = 1e-2
... | python/py_diff_stokes_flow/env/flow_averager_env_3d.py | import numpy as np
from py_diff_stokes_flow.env.env_base import EnvBase
from py_diff_stokes_flow.common.common import ndarray
class FlowAveragerEnv3d(EnvBase):
def __init__(self, seed, folder):
np.random.seed(seed)
cell_nums = (64, 64, 4)
E = 100
nu = 0.499
vol_tol = 1e-2
... | 0.644784 | 0.565899 |
import skil_client
import time
import uuid
import numpy as np
import requests
import json
import os
try:
import cv2
except ImportError:
cv2 = None
class Service:
"""Service
A service is a deployed model.
# Arguments:
skil: `Skil` server instance
model: `skil.Model` instance
... | skil/services.py | import skil_client
import time
import uuid
import numpy as np
import requests
import json
import os
try:
import cv2
except ImportError:
cv2 = None
class Service:
"""Service
A service is a deployed model.
# Arguments:
skil: `Skil` server instance
model: `skil.Model` instance
... | 0.620966 | 0.323768 |
import aiohttp
import aiojobs.aiohttp
import virtool.db.utils
import virtool.github
import virtool.hmm.db
import virtool.http.routes
import virtool.processes.db
import virtool.software.db
import virtool.software.utils
import virtool.utils
from virtool.api.response import bad_gateway, json_response, not_found
routes =... | virtool/software/api.py | import aiohttp
import aiojobs.aiohttp
import virtool.db.utils
import virtool.github
import virtool.hmm.db
import virtool.http.routes
import virtool.processes.db
import virtool.software.db
import virtool.software.utils
import virtool.utils
from virtool.api.response import bad_gateway, json_response, not_found
routes =... | 0.268749 | 0.06727 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
__all__ = [
'GetBitbucketServerConfigResult',
'AwaitableGetBitbucketServerConfigResult',
'get_bitbucket_server_config',
'get_bitbuck... | sdk/python/pulumi_google_native/cloudbuild/v1/get_bitbucket_server_config.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
__all__ = [
'GetBitbucketServerConfigResult',
'AwaitableGetBitbucketServerConfigResult',
'get_bitbucket_server_config',
'get_bitbuck... | 0.797439 | 0.050144 |
import pickle
from typing import List, NoReturn
import mongoengine
from . import events
from . import manager as _man
from .. import error
from .. import settings
from ..commodity import stock
from ...core import modules
from ...core import schedule
from ...core.algorithm import fsm
class Order(mongoengine.Documen... | leaf/selling/order/order.py |
import pickle
from typing import List, NoReturn
import mongoengine
from . import events
from . import manager as _man
from .. import error
from .. import settings
from ..commodity import stock
from ...core import modules
from ...core import schedule
from ...core.algorithm import fsm
class Order(mongoengine.Documen... | 0.50293 | 0.15511 |
from collections import deque, defaultdict
import sys
import typing
import pytest
from typing_validation.validation import (validate, _pseudotypes, _pseudotypes_dict)
if sys.version_info[1] >= 8:
from typing import Literal
else:
from typing_extensions import Literal
_basic_types = frozenset({
bool, int... | test/test_00_validate.py |
from collections import deque, defaultdict
import sys
import typing
import pytest
from typing_validation.validation import (validate, _pseudotypes, _pseudotypes_dict)
if sys.version_info[1] >= 8:
from typing import Literal
else:
from typing_extensions import Literal
_basic_types = frozenset({
bool, int... | 0.452052 | 0.469885 |
import argparse
import importlib
import os
import sys
from tqdm import tqdm
from fta.utils.distances import LINF
from fta.utils.torch_utils import image_utils
import pdb
# Example:
# python tools/generate.py --input_dir $INPUT_DIR --output_dir $OUTPUT_DIR --dataset_type $DATASET_TYPE --step_size $STEP_... | tools/generate.py | import argparse
import importlib
import os
import sys
from tqdm import tqdm
from fta.utils.distances import LINF
from fta.utils.torch_utils import image_utils
import pdb
# Example:
# python tools/generate.py --input_dir $INPUT_DIR --output_dir $OUTPUT_DIR --dataset_type $DATASET_TYPE --step_size $STEP_... | 0.264168 | 0.103703 |
from datetime import datetime
import os
class Warden:
path: str
format_string: str = '%(time)s | %(level)s (%(name)s)'
names: dict
level: int
printing: bool
USELESS = 0
DEBUG = 1
INFO = 2
WARNING = 3
ERROR = 4
CRITICAL = 5
def setup(self, path, format_string: str = Fa... | wtflog/logger.py | from datetime import datetime
import os
class Warden:
path: str
format_string: str = '%(time)s | %(level)s (%(name)s)'
names: dict
level: int
printing: bool
USELESS = 0
DEBUG = 1
INFO = 2
WARNING = 3
ERROR = 4
CRITICAL = 5
def setup(self, path, format_string: str = Fa... | 0.210766 | 0.156266 |
import numpy as np
from numpy import array
from numpy import *
import math
class Nodo:
def __init__(self,padre=None,pos=(0,0)):
self.padre = padre
self.pos = pos
self.g = 0
self.h = 0
self.f = 0
def calculate_h(self,objetivo): #Heuristica entre nodo actual y final
... | TP1/EJ2 Y 3/Aestrella.py | import numpy as np
from numpy import array
from numpy import *
import math
class Nodo:
def __init__(self,padre=None,pos=(0,0)):
self.padre = padre
self.pos = pos
self.g = 0
self.h = 0
self.f = 0
def calculate_h(self,objetivo): #Heuristica entre nodo actual y final
... | 0.209146 | 0.401923 |
from core.const.GlobalConst import HttpKey
from core.decorator.normal_functions import *
from core.model.ConfServiceLayer import ConfServiceLayer
from core.tools.DBTool import DBTool
from core.processor.Config import Config
class ConfHttpLayer(object):
"""
Http配置的类。
"""
def __init__(self):
sel... | AutotestFramework/core/model/ConfHttpLayer.py | from core.const.GlobalConst import HttpKey
from core.decorator.normal_functions import *
from core.model.ConfServiceLayer import ConfServiceLayer
from core.tools.DBTool import DBTool
from core.processor.Config import Config
class ConfHttpLayer(object):
"""
Http配置的类。
"""
def __init__(self):
sel... | 0.482917 | 0.051845 |
import tensorflow as tf
import numpy as np
from python.download import load_content
from python.operator import parse_sequence_example
class AutoCompleteFixed:
def __init__(self, sample: str,
observations: int=None, batch_size: int=128,
use_offsets=False,
repeat... | python/dataset/auto_complete_fixed.py | import tensorflow as tf
import numpy as np
from python.download import load_content
from python.operator import parse_sequence_example
class AutoCompleteFixed:
def __init__(self, sample: str,
observations: int=None, batch_size: int=128,
use_offsets=False,
repeat... | 0.870501 | 0.294019 |
import re
import os
WPA_SUPPLICANT_FILE = '/etc/wpa_supplicant/wpa_supplicant.conf'
# This works to reset autohotspot. If in hotspot, first search available networks and if not, start hotspot.
def reset_autohotspot():
sudoPassword = '<PASSWORD>'
command = '/usr/bin/autohotspot'
p = os.system('echo %s|sud... | scripts/hotspot_manager.py | import re
import os
WPA_SUPPLICANT_FILE = '/etc/wpa_supplicant/wpa_supplicant.conf'
# This works to reset autohotspot. If in hotspot, first search available networks and if not, start hotspot.
def reset_autohotspot():
sudoPassword = '<PASSWORD>'
command = '/usr/bin/autohotspot'
p = os.system('echo %s|sud... | 0.111882 | 0.068569 |
from datetime import timedelta
import django
import pytest
from django.contrib.auth import get_user_model
from ninja_jwt import authentication
from ninja_jwt.exceptions import AuthenticationFailed, InvalidToken
from ninja_jwt.models import TokenUser
from ninja_jwt.settings import api_settings
from ninja_jwt.tokens im... | tests/test_authentication.py | from datetime import timedelta
import django
import pytest
from django.contrib.auth import get_user_model
from ninja_jwt import authentication
from ninja_jwt.exceptions import AuthenticationFailed, InvalidToken
from ninja_jwt.models import TokenUser
from ninja_jwt.settings import api_settings
from ninja_jwt.tokens im... | 0.68941 | 0.266193 |
import logging
from gi.repository import Gst
from lib.config import Config
from lib.clock import Clock
class StreamBlanker(object):
log = logging.getLogger('StreamBlanker')
def __init__(self):
self.acaps = Config.get('mix', 'audiocaps')
self.vcaps = Config.get('mix', 'videocaps')
s... | voctocore/lib/streamblanker.py | import logging
from gi.repository import Gst
from lib.config import Config
from lib.clock import Clock
class StreamBlanker(object):
log = logging.getLogger('StreamBlanker')
def __init__(self):
self.acaps = Config.get('mix', 'audiocaps')
self.vcaps = Config.get('mix', 'videocaps')
s... | 0.509276 | 0.071397 |
import pytest
import pandas as pd
import numpy as np
import utils_nlp.dataset.preprocess as preprocess
@pytest.fixture(scope="module")
def df_sentences():
sentences = np.array(
[
"The man is playing the piano.",
"Some men are fighting.",
"A man is spreading shreded ch... | tests/unit/test_preprocess.py |
import pytest
import pandas as pd
import numpy as np
import utils_nlp.dataset.preprocess as preprocess
@pytest.fixture(scope="module")
def df_sentences():
sentences = np.array(
[
"The man is playing the piano.",
"Some men are fighting.",
"A man is spreading shreded ch... | 0.616128 | 0.646223 |
import string
from faker import Faker
import numpy as np
import string
class Factory:
def __init__(self, size: int):
"""
The Data Mocker object
"""
self._size = size
self._fake = Faker()
self._ranges = None
def build_column(self, column_description: str):
... | rawbuilder/factory/Factory.py | import string
from faker import Faker
import numpy as np
import string
class Factory:
def __init__(self, size: int):
"""
The Data Mocker object
"""
self._size = size
self._fake = Faker()
self._ranges = None
def build_column(self, column_description: str):
... | 0.73848 | 0.492005 |
import pickle
import torch
from torchtext.data import Iterator
from tqdm import tqdm
class BucketByLengthIterator(Iterator):
def __init__(self, *args, max_length=None, example_length_fn=None,
data_paths=None, **kwargs):
batch_size = kwargs['batch_size']
self.boundaries = self._b... | dataset/common.py | import pickle
import torch
from torchtext.data import Iterator
from tqdm import tqdm
class BucketByLengthIterator(Iterator):
def __init__(self, *args, max_length=None, example_length_fn=None,
data_paths=None, **kwargs):
batch_size = kwargs['batch_size']
self.boundaries = self._b... | 0.616705 | 0.238705 |
import logging
import warnings
import netCDF4
from femagtools import isa7
logger = logging.getLogger('femagtools.nc')
class Reader(object):
"""
Open and Read NetCDF file
Arguments:
filename: name of NetCDF nc file to be read
"""
def __init__(self, filename):
ds = netCDF4.Dataset... | femagtools/nc.py | import logging
import warnings
import netCDF4
from femagtools import isa7
logger = logging.getLogger('femagtools.nc')
class Reader(object):
"""
Open and Read NetCDF file
Arguments:
filename: name of NetCDF nc file to be read
"""
def __init__(self, filename):
ds = netCDF4.Dataset... | 0.330147 | 0.077727 |
import random
import re
from typing import List, Dict, Set
class Predictions:
"""Toy class for making randomly-selected predictions."""
def __init__(self, predictions_file_path: str):
self.predictions_by_tag: Dict[str, List[str]] = {} # Predictions with tags
self.generic_predictions: List[str] ... | predictions.py | import random
import re
from typing import List, Dict, Set
class Predictions:
"""Toy class for making randomly-selected predictions."""
def __init__(self, predictions_file_path: str):
self.predictions_by_tag: Dict[str, List[str]] = {} # Predictions with tags
self.generic_predictions: List[str] ... | 0.83025 | 0.351283 |
import torch
import io
import posixpath
class ClassificationSummary:
""" Simple class to keep track of summaries of a classification problem. """
def __init__(self, num_outcomes=2, device=None):
""" Initializes a new summary class with the given number of outcomes.
Parameters
--------... | code/genric/model/summary.py | import torch
import io
import posixpath
class ClassificationSummary:
""" Simple class to keep track of summaries of a classification problem. """
def __init__(self, num_outcomes=2, device=None):
""" Initializes a new summary class with the given number of outcomes.
Parameters
--------... | 0.935273 | 0.748352 |
import socket
import hashlib
import base64
import logging
GEVENT = None
TCP_BUF_SIZE = 8192
WS_MAGIC_STRING = '258EAFA5-E914-47DA-95CA-C5AB0DC85B11'
RESPONSE_STRING = 'HTTP/1.1 101 Switching Protocols\r\nUpgrade: websocket\r\n' \
'Connection: Upgrade\r\nSec-WebSocket-Accept: {}\r\n\r\n'
logger = lo... | black/__init__.py |
import socket
import hashlib
import base64
import logging
GEVENT = None
TCP_BUF_SIZE = 8192
WS_MAGIC_STRING = '258EAFA5-E914-47DA-95CA-C5AB0DC85B11'
RESPONSE_STRING = 'HTTP/1.1 101 Switching Protocols\r\nUpgrade: websocket\r\n' \
'Connection: Upgrade\r\nSec-WebSocket-Accept: {}\r\n\r\n'
logger = lo... | 0.356895 | 0.064212 |
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from openlattice.api_client import ApiClient
from openlattice.exceptions import ( # noqa: F401
ApiTypeError,
ApiValueError
)
class SearchApi(object):
"""NOTE: This class is auto gene... | python/openlattice/api/search_api.py | from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from openlattice.api_client import ApiClient
from openlattice.exceptions import ( # noqa: F401
ApiTypeError,
ApiValueError
)
class SearchApi(object):
"""NOTE: This class is auto gene... | 0.774711 | 0.101545 |
from braidgenerator import MarkovChain
from braidgenerator import BraidWord
import pandas as pd
import unittest
class TestMarkovChainMethods(unittest.TestCase):
def test_aggregate(self):
'''
Should return non-empty self.braidagg
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.... | tests/test_markovchain.py | from braidgenerator import MarkovChain
from braidgenerator import BraidWord
import pandas as pd
import unittest
class TestMarkovChainMethods(unittest.TestCase):
def test_aggregate(self):
'''
Should return non-empty self.braidagg
'''
mc = MarkovChain(BraidWord([1, 2, 3]))
mc.... | 0.718693 | 0.580679 |
from enum import Enum
from io import BytesIO
from PIL import Image, ImageDraw
from PIL.Image import Image as IMG
from typing import Tuple, List, Optional
from .utils import legal_word, load_font, save_png
class GuessResult(Enum):
WIN = 0 # 猜出正确单词
LOSS = 1 # 达到最大可猜次数，未猜出正确单词
DUPLICATE = 2 # 单词重复
IL... | nonebot_plugin_wordle/data_source.py | from enum import Enum
from io import BytesIO
from PIL import Image, ImageDraw
from PIL.Image import Image as IMG
from typing import Tuple, List, Optional
from .utils import legal_word, load_font, save_png
class GuessResult(Enum):
WIN = 0 # 猜出正确单词
LOSS = 1 # 达到最大可猜次数，未猜出正确单词
DUPLICATE = 2 # 单词重复
IL... | 0.620392 | 0.172102 |
from Crypto.Cipher import AES
from Crypto.Hash import SHA3_256
from Crypto.Protocol.KDF import scrypt
from base64 import b64encode, b64decode
import csv
def filenotfound(): # создание файла и помещения туда трех элементов
password = input('input a password: ')
password_bytes = password.encode()
... | passwords/passwords (csv) encrypting.py | from Crypto.Cipher import AES
from Crypto.Hash import SHA3_256
from Crypto.Protocol.KDF import scrypt
from base64 import b64encode, b64decode
import csv
def filenotfound(): # создание файла и помещения туда трех элементов
password = input('input a password: ')
password_bytes = password.encode()
... | 0.266835 | 0.153581 |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import sem
import statsmodels.api as sm
from statsmodels.formula.api import ols
import statsmodels.stats.multicomp
PATH = "C:\\Users\\messinjf\\Desktop\\Results April 8th\\"
APF_RS = PATH + "APF-RS.csv"
APF_GA = PATH + "APF-GA.csv... | RDWGraphMaker.py | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import sem
import statsmodels.api as sm
from statsmodels.formula.api import ols
import statsmodels.stats.multicomp
PATH = "C:\\Users\\messinjf\\Desktop\\Results April 8th\\"
APF_RS = PATH + "APF-RS.csv"
APF_GA = PATH + "APF-GA.csv... | 0.364778 | 0.286459 |
import os,sys
def get_header():
f = open("attr.txt", "r")
lines = f.readlines()
f.close()
attrs = list()
for line in lines:
attrs.append(line.split("\t")[0])
attrs = attrs[3:]
attrs.append("ischeat")
header = "\t".join(attrs) + "\n"
attrs_type = "contin... | data/data-pre-1000.py | import os,sys
def get_header():
f = open("attr.txt", "r")
lines = f.readlines()
f.close()
attrs = list()
for line in lines:
attrs.append(line.split("\t")[0])
attrs = attrs[3:]
attrs.append("ischeat")
header = "\t".join(attrs) + "\n"
attrs_type = "contin... | 0.033337 | 0.099733 |
import numpy as np
import pandas as pd
from metrics import scores
from sklearn.model_selection import train_test_split
#load datasets
def load(filepath):
data = pd.read_csv(filepath, sep=" ", dtype=float,header=None)
data = data.drop(22, axis=1)
data = data.drop(23, axis=1)
data_np = data.to_nump... | q2.py | import numpy as np
import pandas as pd
from metrics import scores
from sklearn.model_selection import train_test_split
#load datasets
def load(filepath):
data = pd.read_csv(filepath, sep=" ", dtype=float,header=None)
data = data.drop(22, axis=1)
data = data.drop(23, axis=1)
data_np = data.to_nump... | 0.478773 | 0.443179 |
import pathlib
import tempfile
import unittest
from io import StringIO
from src.pipeline.handler_metrics_per_category import HandlerMetricsPerCategory, PredictedAnswer, Result
from src.unpack_data import Q_A, QuestionAnswerRecipe
class TestHandlerMetricsPerCategory(unittest.TestCase):
def test_handle_bad_categor... | tests/test_handler_metrics_per_category.py | import pathlib
import tempfile
import unittest
from io import StringIO
from src.pipeline.handler_metrics_per_category import HandlerMetricsPerCategory, PredictedAnswer, Result
from src.unpack_data import Q_A, QuestionAnswerRecipe
class TestHandlerMetricsPerCategory(unittest.TestCase):
def test_handle_bad_categor... | 0.52756 | 0.611498 |
import datetime
from bootstrap3_datetime.widgets import DateTimePicker
from django import forms
from django.utils.translation import ugettext_lazy as _
from django.core.exceptions import ValidationError
from django.utils import timezone
from django.views import generic
from django.forms import ModelForm
from django.co... | src/MainAPP/forms.py | import datetime
from bootstrap3_datetime.widgets import DateTimePicker
from django import forms
from django.utils.translation import ugettext_lazy as _
from django.core.exceptions import ValidationError
from django.utils import timezone
from django.views import generic
from django.forms import ModelForm
from django.co... | 0.466359 | 0.048316 |
import logging
import logging.config
import os
import sys
import yaml
from flask import Flask, g, session, current_app
from parrot.blueprints.api import constants as API
from parrot.blueprints.api import BP_API
from parrot.blueprints.api import BP_API_CONFIG
from parrot.blueprints.web import BP_WEB
from .cors import ... | parrot/core/app.py | import logging
import logging.config
import os
import sys
import yaml
from flask import Flask, g, session, current_app
from parrot.blueprints.api import constants as API
from parrot.blueprints.api import BP_API
from parrot.blueprints.api import BP_API_CONFIG
from parrot.blueprints.web import BP_WEB
from .cors import ... | 0.352982 | 0.070304 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import re
import os
from random import choice, shuffle
import nltk
def clean_str(string):
"""
Tokenization/string cleaning for all datasets except for SST.
Original taken from
... | TensorFlow_part/data_util.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import re
import os
from random import choice, shuffle
import nltk
def clean_str(string):
"""
Tokenization/string cleaning for all datasets except for SST.
Original taken from
... | 0.77949 | 0.397208 |
import datetime
from datetime import timedelta
from django.conf import settings
from django.contrib.messages import get_messages
from django.contrib import messages
from django.test import Client
from django.test import TestCase
from django.urls import reverse
from ..factories import InstrumentFactory, LabAssistantFa... | server/booking_portal/tests/test_slots.py | import datetime
from datetime import timedelta
from django.conf import settings
from django.contrib.messages import get_messages
from django.contrib import messages
from django.test import Client
from django.test import TestCase
from django.urls import reverse
from ..factories import InstrumentFactory, LabAssistantFa... | 0.563378 | 0.349505 |
import errno
import select
import sys
import time
from .models.client import Client
if __name__ == "__main__":
if len(sys.argv) != 5:
print("Usage: python -m client <SERVER_IP> <PORT> <USERNAME> <PASSWORD>")
sys.exit(1)
# -- Perf counter --
start = time.perf_counter()
_, SERVER_IP, P... | app/client.py | import errno
import select
import sys
import time
from .models.client import Client
if __name__ == "__main__":
if len(sys.argv) != 5:
print("Usage: python -m client <SERVER_IP> <PORT> <USERNAME> <PASSWORD>")
sys.exit(1)
# -- Perf counter --
start = time.perf_counter()
_, SERVER_IP, P... | 0.155271 | 0.068009 |
import psycopg2
import datetime
class DatabaseConnector:
def __init__(self, connection, cursor):
self.connection = connection
self.cursor = cursor
# Connecting to the PostgreSQL database
def connect_db(self):
print('\nConnecting to the PostgreSQL database...')
self.connecti... | video-analytics/people_counter/classes/database_connector.py | import psycopg2
import datetime
class DatabaseConnector:
def __init__(self, connection, cursor):
self.connection = connection
self.cursor = cursor
# Connecting to the PostgreSQL database
def connect_db(self):
print('\nConnecting to the PostgreSQL database...')
self.connecti... | 0.255344 | 0.222004 |
import dis
import opcode
import weakref
import types
import copy
import importlib
def is_class_instance(o):
return bool(type(o).__flags__ & (1 << 9))
def walk_global_ops(code):
for instr in dis.get_instructions(code):
op = instr.opcode
if op in (opcode.opmap['STORE_GLOBAL'], opcode.opmap['DE... | universal_parser/object_converter.py | import dis
import opcode
import weakref
import types
import copy
import importlib
def is_class_instance(o):
return bool(type(o).__flags__ & (1 << 9))
def walk_global_ops(code):
for instr in dis.get_instructions(code):
op = instr.opcode
if op in (opcode.opmap['STORE_GLOBAL'], opcode.opmap['DE... | 0.284576 | 0.155431 |
from bandit import Normal
import unittest
class TestNormalBandit(unittest.TestCase):
"""
Tests the methods for a normal distribution bandit.
"""
def test_distribution_generation(self):
"""
Ensure that arm distributions have means on the range [-1, 1) and
standard deviations of... | bandit/tests/test_normal.py | from bandit import Normal
import unittest
class TestNormalBandit(unittest.TestCase):
"""
Tests the methods for a normal distribution bandit.
"""
def test_distribution_generation(self):
"""
Ensure that arm distributions have means on the range [-1, 1) and
standard deviations of... | 0.757525 | 0.759091 |
import json
import os
from PIL import Image
import yaml
from typing import List,Dict
def viaReg2cocoReg(region:Dict
):
"""Convert VIA x,y to COCO annotation
Extract super category infomation from via json (type : radio)
Args:
region (Dict): VIA annotation info (region_attributes)
Returns:... | vgg_coco.py | import json
import os
from PIL import Image
import yaml
from typing import List,Dict
def viaReg2cocoReg(region:Dict
):
"""Convert VIA x,y to COCO annotation
Extract super category infomation from via json (type : radio)
Args:
region (Dict): VIA annotation info (region_attributes)
Returns:... | 0.626124 | 0.274767 |
import astropy.io.fits as fits
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import os
from .parameters import Params, find_parameter_file
class Disc:
def __init__(self, dir=None, **kwargs):
# Correct path if needed
dir = os.path.normpath(os.path.expanduser(dir))... | pymcfost/disc_structure.py | import astropy.io.fits as fits
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import os
from .parameters import Params, find_parameter_file
class Disc:
def __init__(self, dir=None, **kwargs):
# Correct path if needed
dir = os.path.normpath(os.path.expanduser(dir))... | 0.515864 | 0.464416 |
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import ai_interface_pb2 as ai__interface__pb2
class AnalyServiceStub(object):
"""The ai analysis service definition.
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc... | src/video_base_management/ai_interface_pb2_grpc.py | """Client and server classes corresponding to protobuf-defined services."""
import grpc
import ai_interface_pb2 as ai__interface__pb2
class AnalyServiceStub(object):
"""The ai analysis service definition.
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc... | 0.795658 | 0.137185 |
import pickle
class No:
def __init__(self, chave, no_esquerdo, no_direito):
self.chave = chave
self.no_esquerdo = no_esquerdo
self.no_direito = no_direito
def exibir_chave(self):
print(self.chave)
class BinaryTree:
def __init__(self) -> None:
self.raiz = ... | pysimpletree/binarytree.py | import pickle
class No:
def __init__(self, chave, no_esquerdo, no_direito):
self.chave = chave
self.no_esquerdo = no_esquerdo
self.no_direito = no_direito
def exibir_chave(self):
print(self.chave)
class BinaryTree:
def __init__(self) -> None:
self.raiz = ... | 0.450601 | 0.157979 |
# code was heavily based on https://github.com/AliaksandrSiarohin/first-order-model
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from .builder import DISCRIMINATORS
from ...modules.first_order import ImagePyramide, detach_kp, kp2gaussian
from ...modules.utils import spectral_norm
@DISCRIM... | ppgan/models/discriminators/discriminator_firstorder.py |
# code was heavily based on https://github.com/AliaksandrSiarohin/first-order-model
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
from .builder import DISCRIMINATORS
from ...modules.first_order import ImagePyramide, detach_kp, kp2gaussian
from ...modules.utils import spectral_norm
@DISCRIM... | 0.864411 | 0.298249 |
import re
# Word delimiters and symbols that will not be preserved when re-casing.
# language=PythonRegExp
SYMBOLS = "[^a-zA-Z0-9]*"
# Optionally capitalized word.
# language=PythonRegExp
WORD = "[A-Z]*[a-z]*[0-9]*"
# Uppercase word, not followed by lowercase letters.
# language=PythonRegExp
WORD_UPPER = "[A-Z]+(?![... | src/betterproto/casing.py | import re
# Word delimiters and symbols that will not be preserved when re-casing.
# language=PythonRegExp
SYMBOLS = "[^a-zA-Z0-9]*"
# Optionally capitalized word.
# language=PythonRegExp
WORD = "[A-Z]*[a-z]*[0-9]*"
# Uppercase word, not followed by lowercase letters.
# language=PythonRegExp
WORD_UPPER = "[A-Z]+(?![... | 0.573678 | 0.370909 |
import re
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Protocol,
Type,
TypeVar,
Union,
)
from kolga.utils.general import unescape_string
from kolga.utils.models import BasicAuthUser
if TYPE_CHECKING:
from pydantic imp... | kolga/utils/fields.py | import re
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Generator,
Iterable,
List,
Optional,
Protocol,
Type,
TypeVar,
Union,
)
from kolga.utils.general import unescape_string
from kolga.utils.models import BasicAuthUser
if TYPE_CHECKING:
from pydantic imp... | 0.755366 | 0.251521 |
import contextlib
from recipe_engine import recipe_api
class NodeJSApi(recipe_api.RecipeApi):
def __init__(self, **kwargs):
super(NodeJSApi, self).__init__(**kwargs)
self._installed = {} # {Path: installed nodejs version there}
@contextlib.contextmanager
def __call__(self, version, path=None, cache=... | recipe_modules/nodejs/api.py |
import contextlib
from recipe_engine import recipe_api
class NodeJSApi(recipe_api.RecipeApi):
def __init__(self, **kwargs):
super(NodeJSApi, self).__init__(**kwargs)
self._installed = {} # {Path: installed nodejs version there}
@contextlib.contextmanager
def __call__(self, version, path=None, cache=... | 0.702632 | 0.145601 |
line_1 = input()
line_2 = input()
line_3 = input()
result = ""
if ((len(line_1) == len(line_2)) and (len(line_1) == len(line_3))):
if ((len(line_1) % 3) == 0):
i = 0
while i <= int((len(line_1)) - 1):
if (line_1[i] == " ") and (line_1[i + 1] == "_") and (line_1[i ... | codegame_1.py | line_1 = input()
line_2 = input()
line_3 = input()
result = ""
if ((len(line_1) == len(line_2)) and (len(line_1) == len(line_3))):
if ((len(line_1) % 3) == 0):
i = 0
while i <= int((len(line_1)) - 1):
if (line_1[i] == " ") and (line_1[i + 1] == "_") and (line_1[i ... | 0.030574 | 0.395864 |
# System imports
import os
# Third party imports
import nibabel
import numpy
from nilearn import plotting
import matplotlib.pyplot as plt
def triplanar(input_file, output_fileroot, title=None, nb_slices=1,
overlays=None, overlays_colors=None, overlay_opacities=None,
contours=False, edges=... | pyconnectome/plotting/slicer.py | # System imports
import os
# Third party imports
import nibabel
import numpy
from nilearn import plotting
import matplotlib.pyplot as plt
def triplanar(input_file, output_fileroot, title=None, nb_slices=1,
overlays=None, overlays_colors=None, overlay_opacities=None,
contours=False, edges=... | 0.779783 | 0.341418 |
import csv
import operator
import numpy as np
import get_data_set as gds
from random import shuffle
'''
n_features = Number of Features
n_samples = Number of data taken
'''
class perceptron:
def __init__(self, number_epochs, number_features):
self.n_epochs = number_epochs
self.n_features... | perceptron.py | import csv
import operator
import numpy as np
import get_data_set as gds
from random import shuffle
'''
n_features = Number of Features
n_samples = Number of data taken
'''
class perceptron:
def __init__(self, number_epochs, number_features):
self.n_epochs = number_epochs
self.n_features... | 0.47658 | 0.358199 |
from unittest import TestCase
from xrpl.models.exceptions import XRPLModelException
from xrpl.models.transactions import NFTokenCreateOffer, NFTokenCreateOfferFlag
_ACCOUNT = "<KEY>"
_ANOTHER_ACCOUNT = "<KEY>"
_FEE = "0.00001"
_SEQUENCE = 19048
_NFTOKEN_ID = "00090032B5F762798A53D543A014CAF8B297CFF8F2F937E844B17C9E00... | tests/unit/models/transactions/test_nftoken_create_offer.py | from unittest import TestCase
from xrpl.models.exceptions import XRPLModelException
from xrpl.models.transactions import NFTokenCreateOffer, NFTokenCreateOfferFlag
_ACCOUNT = "<KEY>"
_ANOTHER_ACCOUNT = "<KEY>"
_FEE = "0.00001"
_SEQUENCE = 19048
_NFTOKEN_ID = "00090032B5F762798A53D543A014CAF8B297CFF8F2F937E844B17C9E00... | 0.563138 | 0.311754 |
from __future__ import print_function
import math
import os
import numpy as np
import scipy.sparse as sps
from scipy import io
from sklearn.preprocessing import normalize
import utils
__outputFileName = "articlesSimiliarity.mtx"
__debug = False
def calculate(articleFeatures, recreate):
if recreate or not utils.... | notebooks/calcs/artSimBasedOnFeatures.py | from __future__ import print_function
import math
import os
import numpy as np
import scipy.sparse as sps
from scipy import io
from sklearn.preprocessing import normalize
import utils
__outputFileName = "articlesSimiliarity.mtx"
__debug = False
def calculate(articleFeatures, recreate):
if recreate or not utils.... | 0.268749 | 0.176494 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from . import _utilities
__all__ = ['ContainerRegistryDockerCredentialsArgs', 'ContainerRegistryDockerCredentials']
@pulumi.input_type
class ContainerRegistryDockerCredentialsArgs:
def __init_... | sdk/python/pulumi_digitalocean/container_registry_docker_credentials.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from . import _utilities
__all__ = ['ContainerRegistryDockerCredentialsArgs', 'ContainerRegistryDockerCredentials']
@pulumi.input_type
class ContainerRegistryDockerCredentialsArgs:
def __init_... | 0.825273 | 0.124719 |
import unittest
from logic.cidr_calculator import CIDRCalculator
from models.CustomExceptions import *
class TestIPRange(unittest.TestCase):
def test_calculate_ip_range_for_cidr_32(self):
ip = '192.168.127.12'
cidrRange = 32
cidr = CIDRCalculator()
result = cidr.calculateIPRange(i... | api/src/tests/test_ip_range.py | import unittest
from logic.cidr_calculator import CIDRCalculator
from models.CustomExceptions import *
class TestIPRange(unittest.TestCase):
def test_calculate_ip_range_for_cidr_32(self):
ip = '192.168.127.12'
cidrRange = 32
cidr = CIDRCalculator()
result = cidr.calculateIPRange(i... | 0.506347 | 0.501709 |
import tensorflow as tf
from util import loss_fns
def max_label_sample(labels, predicted_scores):
permutation_loss = loss_fns.get_listnet_loss(labels, predicted_scores)
predicted_scores = tf.reshape(predicted_scores, [-1, 1])
labels = tf.reshape(labels, [-1, 1])
n_data = tf.shape(labels)[0]
# # [[1. 0. 0.]]
tra... | src_rnn_rl_ratio/util/sample.py | import tensorflow as tf
from util import loss_fns
def max_label_sample(labels, predicted_scores):
permutation_loss = loss_fns.get_listnet_loss(labels, predicted_scores)
predicted_scores = tf.reshape(predicted_scores, [-1, 1])
labels = tf.reshape(labels, [-1, 1])
n_data = tf.shape(labels)[0]
# # [[1. 0. 0.]]
tra... | 0.606498 | 0.402744 |