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 |
|---|---|---|---|---|
import discord
from discord.ext import commands
import aiohttp
import random
import textwrap
class Reddit(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command(name="reddit")
async def _reddit(self, ctx, subreddit):
bl_users = await self.bot.db.fetch("SELECT * FROM bl WH... | Nora/cogs/reddit.py | import discord
from discord.ext import commands
import aiohttp
import random
import textwrap
class Reddit(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command(name="reddit")
async def _reddit(self, ctx, subreddit):
bl_users = await self.bot.db.fetch("SELECT * FROM bl WH... | 0.431345 | 0.288344 |
from lab11 import *
# Q5
def hailstone(n):
"""
>>> for num in hailstone(10):
... print(num)
...
10
5
16
8
4
2
1
"""
while n is not 1:
yield n
if n % 2 == 0:
n //= 2
else:
n = n * 3 + 1
yield n
# Q6
def repe... | labs/lab11/lab11_extra.py |
from lab11 import *
# Q5
def hailstone(n):
"""
>>> for num in hailstone(10):
... print(num)
...
10
5
16
8
4
2
1
"""
while n is not 1:
yield n
if n % 2 == 0:
n //= 2
else:
n = n * 3 + 1
yield n
# Q6
def repe... | 0.627495 | 0.598606 |
import slicer
import unittest
import vtk
from slicer.util import VTKObservationMixin
class Foo(VTKObservationMixin):
def __init__(self):
VTKObservationMixin.__init__(self)
self.ModifiedEventCount = {}
def onObjectModified(self, caller, event):
self.ModifiedEventCount[caller] = self.modifiedEventCount... | Base/Python/slicer/tests/test_slicer_util_VTKObservationMixin.py | import slicer
import unittest
import vtk
from slicer.util import VTKObservationMixin
class Foo(VTKObservationMixin):
def __init__(self):
VTKObservationMixin.__init__(self)
self.ModifiedEventCount = {}
def onObjectModified(self, caller, event):
self.ModifiedEventCount[caller] = self.modifiedEventCount... | 0.750278 | 0.365655 |
import collections.abc
import dataclasses
import inspect
import typing_inspect
from erdantic.base import Field, Model, register_model_adapter
from erdantic.etyping import GenericAlias, get_args, get_origin
from typing import Any, Callable, List, Union
class DataClassField(Field[dataclasses.Field]):
"""Concrete f... | erdantic/edataclasses.py | import collections.abc
import dataclasses
import inspect
import typing_inspect
from erdantic.base import Field, Model, register_model_adapter
from erdantic.etyping import GenericAlias, get_args, get_origin
from typing import Any, Callable, List, Union
class DataClassField(Field[dataclasses.Field]):
"""Concrete f... | 0.885879 | 0.235592 |
import argparse
import logging
import sys
from os import path
from time import sleep
from typing import Any, Dict, Optional
import yaml
from boto import ec2
from boto.utils import get_instance_identity, get_instance_metadata
from .modules import Etcd, HostedZone, Hostname, TinyCert
log = logging.getLogger(__name__)
... | nodereg/run.py | import argparse
import logging
import sys
from os import path
from time import sleep
from typing import Any, Dict, Optional
import yaml
from boto import ec2
from boto.utils import get_instance_identity, get_instance_metadata
from .modules import Etcd, HostedZone, Hostname, TinyCert
log = logging.getLogger(__name__)
... | 0.468547 | 0.047514 |
from renderer import SimRenderer
import numpy as np
import scipy.optimize
import redmax_py as redmax
if __name__ == '__main__':
sim = redmax.make_sim("TorqueFingerFlick-Demo", "BDF2")
ndof_r, ndof_m, ndof_u = sim.ndof_r, sim.ndof_m, sim.ndof_u
print('ndof_r = ', ndof_r)
print('ndof_m = ', ndof_m)... | examples/test_finger_flick_optimize.py | from renderer import SimRenderer
import numpy as np
import scipy.optimize
import redmax_py as redmax
if __name__ == '__main__':
sim = redmax.make_sim("TorqueFingerFlick-Demo", "BDF2")
ndof_r, ndof_m, ndof_u = sim.ndof_r, sim.ndof_m, sim.ndof_u
print('ndof_r = ', ndof_r)
print('ndof_m = ', ndof_m)... | 0.675658 | 0.428771 |
from typing import List
import numpy as np
from ..AShape import AShape
from ..AAxes import AAxes
from ..backend import Kernel
from ..HKernel import HKernel
from ..HType import HType
from ..info import SliceInfo
from ..SCacheton import SCacheton
from ..Tensor import Tensor
def split(input_t : Tensor, axis, keepdims=... | xlib/avecl/_internal/op/slice_.py | from typing import List
import numpy as np
from ..AShape import AShape
from ..AAxes import AAxes
from ..backend import Kernel
from ..HKernel import HKernel
from ..HType import HType
from ..info import SliceInfo
from ..SCacheton import SCacheton
from ..Tensor import Tensor
def split(input_t : Tensor, axis, keepdims=... | 0.81231 | 0.610134 |
import argparse
import json
import multiprocessing as mp
import os
import re
import shutil
import sys
import tarfile
import unicodedata
from dataclasses import dataclass
from datetime import date, timedelta, datetime
from os import path, makedirs, listdir
from typing import List, Dict, Any
import requests
def parse_... | backup.py | import argparse
import json
import multiprocessing as mp
import os
import re
import shutil
import sys
import tarfile
import unicodedata
from dataclasses import dataclass
from datetime import date, timedelta, datetime
from os import path, makedirs, listdir
from typing import List, Dict, Any
import requests
def parse_... | 0.634204 | 0.17037 |
import subprocess
from tensorflow.keras.callbacks import (
TensorBoard,
ReduceLROnPlateau,
EarlyStopping
)
import constants
import helpers
import models.custom_callbacks as custom_callbacks
from visualization.visualize import plot_history
def train(model, epochs: int, train_data, val_data, save_freq: in... | src/models/train.py | import subprocess
from tensorflow.keras.callbacks import (
TensorBoard,
ReduceLROnPlateau,
EarlyStopping
)
import constants
import helpers
import models.custom_callbacks as custom_callbacks
from visualization.visualize import plot_history
def train(model, epochs: int, train_data, val_data, save_freq: in... | 0.825167 | 0.353651 |
from alembic import op
from sqlalchemy.dialects.postgresql import BYTEA
from sqlalchemy.schema import Sequence, CreateSequence, DropSequence
import os
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '0008'
down_revision = '0007'
branch_labels = None
depends_on = None
sequence_key_table = ... | backend/database/migrations/versions/0008_add_card_request_table.py | from alembic import op
from sqlalchemy.dialects.postgresql import BYTEA
from sqlalchemy.schema import Sequence, CreateSequence, DropSequence
import os
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '0008'
down_revision = '0007'
branch_labels = None
depends_on = None
sequence_key_table = ... | 0.396419 | 0.129375 |
from Products.CMFPlone.utils import safe_unicode
from bika.lims.controlpanel.bika_analysisservices import AnalysisServicesView
from bika.lims import bikaMessageFactory as _
from bika.lims.utils import t
from plone.app.content.browser.interfaces import IFolderContentsView
from zope.interface import implements
class A... | bika/lims/browser/accreditation.py |
from Products.CMFPlone.utils import safe_unicode
from bika.lims.controlpanel.bika_analysisservices import AnalysisServicesView
from bika.lims import bikaMessageFactory as _
from bika.lims.utils import t
from plone.app.content.browser.interfaces import IFolderContentsView
from zope.interface import implements
class A... | 0.5083 | 0.195575 |
from tensorflow import keras
import numpy as np
def get_test_data(keras_dataset='mnist', num_samples=None, preprocess=True, preprocessing_function=None, **kwargs):
"""
Returns (x_test, y_test) of a chosen built-in Keras dataset.
Also preprocesses the image datasets (mnist, fashion_mnist, cifar10, cifar100... | flox/utils.py | from tensorflow import keras
import numpy as np
def get_test_data(keras_dataset='mnist', num_samples=None, preprocess=True, preprocessing_function=None, **kwargs):
"""
Returns (x_test, y_test) of a chosen built-in Keras dataset.
Also preprocesses the image datasets (mnist, fashion_mnist, cifar10, cifar100... | 0.853852 | 0.716999 |
import os
import re
import pandas as pd
import json
import nltk
nltk.download('punkt')
from nltk.tokenize import sent_tokenize
from collections import Counter
from tqdm.auto import tqdm
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from transformers import pipeline
def get_file_paths():... | model/sentiment_analysics_model/sentiment_analysis.py |
import os
import re
import pandas as pd
import json
import nltk
nltk.download('punkt')
from nltk.tokenize import sent_tokenize
from collections import Counter
from tqdm.auto import tqdm
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from transformers import pipeline
def get_file_paths():... | 0.508788 | 0.208119 |
from telegram.ext import Updater, CommandHandler, MessageHandler, Filters, CallbackContext
from telegram import Update
import logging, view, dao, config
from coin import CoinHandler
token = config.env['TOKEN_TELEGRAM']
# Enable logging
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',... | main.py | from telegram.ext import Updater, CommandHandler, MessageHandler, Filters, CallbackContext
from telegram import Update
import logging, view, dao, config
from coin import CoinHandler
token = config.env['TOKEN_TELEGRAM']
# Enable logging
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',... | 0.598312 | 0.063222 |
from torchvision.datasets.vision import VisionDataset
from PIL import Image
import os
import os.path
import torch
import numpy as np
# TODO: remove `device`?
def convert_ann(ann, device):
xmin, ymin, w, h = ann['bbox']
# DEBUG
if w <= 0 or h <= 0:
raise ValueError("Degenerate bbox (x, y, w, h): ",... | object-detection/baseline/coco.py | from torchvision.datasets.vision import VisionDataset
from PIL import Image
import os
import os.path
import torch
import numpy as np
# TODO: remove `device`?
def convert_ann(ann, device):
xmin, ymin, w, h = ann['bbox']
# DEBUG
if w <= 0 or h <= 0:
raise ValueError("Degenerate bbox (x, y, w, h): ",... | 0.673836 | 0.474631 |
# Copyright 2022 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | bet500.py |
# Copyright 2022 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | 0.503174 | 0.149904 |
from PIL import Image
from DDRDataTypes import DDRScreenshot, DDRParsedData
from IIDXDataTypes import IIDXScreenshot, IIDXParsedData
import sys, requests, io, os
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: DDRGenie.py [path to screenshot image file]")
exit(0)
sshot = Image.op... | Genie.py | from PIL import Image
from DDRDataTypes import DDRScreenshot, DDRParsedData
from IIDXDataTypes import IIDXScreenshot, IIDXParsedData
import sys, requests, io, os
if __name__ == "__main__":
if len(sys.argv) < 2:
print("Usage: DDRGenie.py [path to screenshot image file]")
exit(0)
sshot = Image.op... | 0.180793 | 0.106226 |
"""This module models elements from UTAU, hence the name."""
import abc
import logging
from typing import Tuple
from pydub import AudioSegment, effects # noqa
from . import utau
from .jsonclasses import dataclass
_log = logging.getLogger("putao")
@dataclass
class Note:
"""Notes are the combination of a durat... | putao/model.py | """This module models elements from UTAU, hence the name."""
import abc
import logging
from typing import Tuple
from pydub import AudioSegment, effects # noqa
from . import utau
from .jsonclasses import dataclass
_log = logging.getLogger("putao")
@dataclass
class Note:
"""Notes are the combination of a durat... | 0.914839 | 0.499023 |
from .Emulator import Emulator, Device
from external.containers.emu import docker_device, emu_docker, emu_downloads_menu
import subprocess
import logging
import time
import sys
class DockerEmulator(Emulator):
def __init__(self, path_config, configuration, ):
Device.__init__(self, path_config, configurat... | lib/adb/DockerEmulator.py | from .Emulator import Emulator, Device
from external.containers.emu import docker_device, emu_docker, emu_downloads_menu
import subprocess
import logging
import time
import sys
class DockerEmulator(Emulator):
def __init__(self, path_config, configuration, ):
Device.__init__(self, path_config, configurat... | 0.099328 | 0.062703 |
from __future__ import print_function
import sys
import os
import argparse
from dark.reads import (
addFASTACommandLineOptions, parseFASTACommandLineOptions, unambiguousBases)
parser = argparse.ArgumentParser(
description=(
'Given FASTA on standard input, and bases to look for, write the '
'... | bin/fasta-base-indices.py |
from __future__ import print_function
import sys
import os
import argparse
from dark.reads import (
addFASTACommandLineOptions, parseFASTACommandLineOptions, unambiguousBases)
parser = argparse.ArgumentParser(
description=(
'Given FASTA on standard input, and bases to look for, write the '
'... | 0.486332 | 0.342957 |
import os
import time
import sys
import threading
from pkg_resources import resource_filename
import thriftpy
from thriftpy.rpc import make_client
from thriftpy.protocol.binary import TBinaryProtocolFactory
from thriftpy.transport.buffered import TBufferedTransportFactory
from .wpwithin_types import Error
from .conve... | wrappers/python/wpwithin_python/wpwithin_python/wpwithin.py |
import os
import time
import sys
import threading
from pkg_resources import resource_filename
import thriftpy
from thriftpy.rpc import make_client
from thriftpy.protocol.binary import TBinaryProtocolFactory
from thriftpy.transport.buffered import TBufferedTransportFactory
from .wpwithin_types import Error
from .conve... | 0.493409 | 0.061961 |
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import string
messages = pd.read_csv('SMSSpamCollection', sep='\t',
names=["label", "message"])
from nltk.corpus import stopwords
# tokenization and pre-processing
def text_process(mess):
nopunc = [char for char ... | code/spam.py | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import string
messages = pd.read_csv('SMSSpamCollection', sep='\t',
names=["label", "message"])
from nltk.corpus import stopwords
# tokenization and pre-processing
def text_process(mess):
nopunc = [char for char ... | 0.327883 | 0.227491 |
import os
import sys
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import transformers as tfm
from models.text2brain_model import Text2BrainModel
from utils.parser import init_args
from utils.dataset ... | train.py | import os
import sys
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
import transformers as tfm
from models.text2brain_model import Text2BrainModel
from utils.parser import init_args
from utils.dataset ... | 0.707809 | 0.219892 |
import os
import time
import logging
from typing import List
import wx # pip install wxPython
import wx.xrc
from .node import Node
from .encryption import Encryption
from .validation import is_valid_node
from .message import Message, OwnMessage
from .utils import get_date_from_timestamp
from .wxdisp... | sami/controller.py |
import os
import time
import logging
from typing import List
import wx # pip install wxPython
import wx.xrc
from .node import Node
from .encryption import Encryption
from .validation import is_valid_node
from .message import Message, OwnMessage
from .utils import get_date_from_timestamp
from .wxdisp... | 0.576423 | 0.095097 |
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from quadtree.node import Node
from quadtree.point import Point
from quadtree.utils import recursive_subdivide, contains, find_children,leaf_nodes, get_neighbor_of_greater_or_equal_size,Direction,has_to_split, DEBUG_MODE
class QTree():
def __ini... | quadtree/quadtree.py | import matplotlib.pyplot as plt
import matplotlib.patches as patches
from quadtree.node import Node
from quadtree.point import Point
from quadtree.utils import recursive_subdivide, contains, find_children,leaf_nodes, get_neighbor_of_greater_or_equal_size,Direction,has_to_split, DEBUG_MODE
class QTree():
def __ini... | 0.698535 | 0.567517 |
import math
import time
import arcade
# Do the math to figure out our screen dimensions
SCREEN_WIDTH = 1280
SCREEN_HEIGHT = 720
SCREEN_TITLE = "Basic Renderer"
class MyGame(arcade.Window):
def __init__(self, width, height, title):
super().__init__(width, height, title)
# vsync must... | env/lib/python3.8/site-packages/arcade/experimental/query_demo.py | import math
import time
import arcade
# Do the math to figure out our screen dimensions
SCREEN_WIDTH = 1280
SCREEN_HEIGHT = 720
SCREEN_TITLE = "Basic Renderer"
class MyGame(arcade.Window):
def __init__(self, width, height, title):
super().__init__(width, height, title)
# vsync must... | 0.391755 | 0.097347 |
import numpy as np
from utils import DotDict
def interpolate_min_x(f, x):
return 0.5 * (f[x-1] - f[x+1]) / (f[x-1] - 2 * f[x] + f[x+1]) + x
def rms(f):
return np.sqrt((f ** 2).mean())
def sine_wave(n):
return np.sin(np.linspace(0, 2*np.pi, n, endpoint=False))
def triangle_wave(n):
x = np.linspa... | analysis.py | import numpy as np
from utils import DotDict
def interpolate_min_x(f, x):
return 0.5 * (f[x-1] - f[x+1]) / (f[x-1] - 2 * f[x] + f[x+1]) + x
def rms(f):
return np.sqrt((f ** 2).mean())
def sine_wave(n):
return np.sin(np.linspace(0, 2*np.pi, n, endpoint=False))
def triangle_wave(n):
x = np.linspa... | 0.59796 | 0.656741 |
from __future__ import annotations
from functools import partial
from typing import TYPE_CHECKING
import click
from cherno.actor.exposer import Exposer
from cherno.astrometry import process_and_correct
from cherno.exceptions import ExposerError
from . import cherno_parser
if TYPE_CHECKING:
from . import Che... | cherno/actor/acquire.py |
from __future__ import annotations
from functools import partial
from typing import TYPE_CHECKING
import click
from cherno.actor.exposer import Exposer
from cherno.astrometry import process_and_correct
from cherno.exceptions import ExposerError
from . import cherno_parser
if TYPE_CHECKING:
from . import Che... | 0.844184 | 0.18954 |
import time
from datetime import datetime, timezone
import bme680
from influxdb_client import InfluxDBClient, Point, WritePrecision
from influxdb_client.client.write_api import SYNCHRONOUS
from pydantic import BaseSettings
class Settings(BaseSettings):
hive_name: str
token: str
org: str
bucket: str
... | hive/services/environment/environment.py | import time
from datetime import datetime, timezone
import bme680
from influxdb_client import InfluxDBClient, Point, WritePrecision
from influxdb_client.client.write_api import SYNCHRONOUS
from pydantic import BaseSettings
class Settings(BaseSettings):
hive_name: str
token: str
org: str
bucket: str
... | 0.566978 | 0.116186 |
#Usage:
#converter.py [-h]
#(-h2b | -h2a | -x2a | -a2h | -a2x | -b64d | -b64e | -urld | -urle)
#(-s <input> | -f <filename>) [-c]
#Usage examples:
#converter.py -a2h -s "ABCDabcd" -> 41 42 43 44 61 62 63 64
#converter.py -x2a -c -s "\x41\x42\x43\x44\x61\x62\x63\x64" -> ABCDabcd (to stdout and clipboard)
#co... | converter.py |
#Usage:
#converter.py [-h]
#(-h2b | -h2a | -x2a | -a2h | -a2x | -b64d | -b64e | -urld | -urle)
#(-s <input> | -f <filename>) [-c]
#Usage examples:
#converter.py -a2h -s "ABCDabcd" -> 41 42 43 44 61 62 63 64
#converter.py -x2a -c -s "\x41\x42\x43\x44\x61\x62\x63\x64" -> ABCDabcd (to stdout and clipboard)
#co... | 0.375936 | 0.278533 |
import copy
import inspect
from schema import Schema, Optional, And, Or, Use
from testplan.common.utils.interface import check_signature
from testplan.common.utils import logger
# A sentinel object meaning not defined, it is useful when you need to
# handle arbitrary objects (including None).
ABSENT = Optional._MARK... | testplan/common/config/base.py | import copy
import inspect
from schema import Schema, Optional, And, Or, Use
from testplan.common.utils.interface import check_signature
from testplan.common.utils import logger
# A sentinel object meaning not defined, it is useful when you need to
# handle arbitrary objects (including None).
ABSENT = Optional._MARK... | 0.883619 | 0.379493 |
import json
import redis
from ..util import merge, REQUIRED
from .driver import Driver
class RedisDriver(Driver):
client: redis.Redis
def __init__(self, args):
args = merge(args, {
"host": 'localhost',
"port": 6379,
"db": 0,
"password": <PASSWORD>,
... | qas/driver/redis_driver.py |
import json
import redis
from ..util import merge, REQUIRED
from .driver import Driver
class RedisDriver(Driver):
client: redis.Redis
def __init__(self, args):
args = merge(args, {
"host": 'localhost',
"port": 6379,
"db": 0,
"password": <PASSWORD>,
... | 0.442637 | 0.16455 |
from django import forms
from django.contrib import admin
from django.contrib.auth.models import Group
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from django.contrib.auth.forms import ReadOnlyPasswordHashField
from .models import Staff, Permission, Resource, Menu, Role
class StaffCreationForm... | jwt_auth/admin.py |
from django import forms
from django.contrib import admin
from django.contrib.auth.models import Group
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from django.contrib.auth.forms import ReadOnlyPasswordHashField
from .models import Staff, Permission, Resource, Menu, Role
class StaffCreationForm... | 0.368747 | 0.066327 |
from typing import Dict, List
from datetime import datetime, timedelta, date
from bs4 import BeautifulSoup
import requests
import json
def GetEPGFromNAVER(serviceId: str, period: int) -> List:
"""
NAVER에서 ServiceId에 해당하는 채널의 EPG를 받아옵니다.\n
@return [
{
'Title': '프로그램 이름',
'Su... | GetEPG/FromNAVER.py | from typing import Dict, List
from datetime import datetime, timedelta, date
from bs4 import BeautifulSoup
import requests
import json
def GetEPGFromNAVER(serviceId: str, period: int) -> List:
"""
NAVER에서 ServiceId에 해당하는 채널의 EPG를 받아옵니다.\n
@return [
{
'Title': '프로그램 이름',
'Su... | 0.635109 | 0.211641 |
from webob.request import Request
from webob.dec import wsgify
from webob.exc import no_escape
from webob.exc import strip_tags
from webob.exc import HTTPException
from webob.exc import WSGIHTTPException
from webob.exc import _HTTPMove
from webob.exc import HTTPMethodNotAllowed
from webob.exc import HTTPExceptionMiddle... | lib/WebOb-1.2.2/tests/test_exc.py | from webob.request import Request
from webob.dec import wsgify
from webob.exc import no_escape
from webob.exc import strip_tags
from webob.exc import HTTPException
from webob.exc import WSGIHTTPException
from webob.exc import _HTTPMove
from webob.exc import HTTPMethodNotAllowed
from webob.exc import HTTPExceptionMiddle... | 0.493897 | 0.213992 |
from opnreco.models import perms
from opnreco.models.db import File
from opnreco.models.db import FileLoopConfig
from opnreco.models.db import FileSync
from opnreco.models.db import Loop
from opnreco.models.db import Movement
from opnreco.models.db import OwnerLog
from opnreco.models.db import Peer
from opnreco.models.... | backend/opnreco/api/fileapi.py | from opnreco.models import perms
from opnreco.models.db import File
from opnreco.models.db import FileLoopConfig
from opnreco.models.db import FileSync
from opnreco.models.db import Loop
from opnreco.models.db import Movement
from opnreco.models.db import OwnerLog
from opnreco.models.db import Peer
from opnreco.models.... | 0.569972 | 0.180359 |
import os
from tqdm import tqdm
import numpy as np
from sklearn.preprocessing import StandardScaler
import torch
from torch import nn
from torch.optim import Adam
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.data import DataLoader
from model import BinClassifier
def train():
device = ['c... | 2d_navigation/imitation_learning/train_model.py | import os
from tqdm import tqdm
import numpy as np
from sklearn.preprocessing import StandardScaler
import torch
from torch import nn
from torch.optim import Adam
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.data import DataLoader
from model import BinClassifier
def train():
device = ['c... | 0.542621 | 0.324235 |
import sys
import unittest
import dask.array
import dask.distributed as dd
import numpy as np
import xarray as xr
# Import from directory structure if coverage test, or from installed
# packages otherwise
if "--cov" in str(sys.argv):
from src.geocat.comp import dewtemp, heat_index, relhum, relhum_ice, relhum_wate... | test/test_meteorology.py | import sys
import unittest
import dask.array
import dask.distributed as dd
import numpy as np
import xarray as xr
# Import from directory structure if coverage test, or from installed
# packages otherwise
if "--cov" in str(sys.argv):
from src.geocat.comp import dewtemp, heat_index, relhum, relhum_ice, relhum_wate... | 0.384912 | 0.502258 |
to BigQuery."""
from google.cloud import bigquery
import uuid
def upload_metrics_to_bq(test_name, total_time, epochs, batch_size,
backend_type, backend_version, cpu_num_cores, cpu_memory, cpu_memory_info,
gpu_count, gpu_platform, platform_type, platform_machine_type,
keras_version, sample_type=Non... | scripts/keras_benchmarks/upload_benchmarks_bq.py | to BigQuery."""
from google.cloud import bigquery
import uuid
def upload_metrics_to_bq(test_name, total_time, epochs, batch_size,
backend_type, backend_version, cpu_num_cores, cpu_memory, cpu_memory_info,
gpu_count, gpu_platform, platform_type, platform_machine_type,
keras_version, sample_type=Non... | 0.604049 | 0.381335 |
from functools import partial
import simplejson as json
import os
import tempfile
from celery.exceptions import RetryTaskError
from celery.task import task
import pandas as pd
from bamboo.lib.async import call_async
from bamboo.lib.datetools import recognize_dates
from bamboo.lib.schema_builder import filter_schema
... | bamboo/lib/readers.py | from functools import partial
import simplejson as json
import os
import tempfile
from celery.exceptions import RetryTaskError
from celery.task import task
import pandas as pd
from bamboo.lib.async import call_async
from bamboo.lib.datetools import recognize_dates
from bamboo.lib.schema_builder import filter_schema
... | 0.560734 | 0.445891 |
from django.contrib import admin
from oscar.core.loading import get_model
Attachment = get_model('oscar_support', 'Attachment')
Line = get_model('order', 'Line')
Message = get_model('oscar_support', 'Message')
Priority = get_model("oscar_support", "Priority")
Product = get_model('catalogue', 'Product')
RelatedOrder = ... | oscar_support/admin.py | from django.contrib import admin
from oscar.core.loading import get_model
Attachment = get_model('oscar_support', 'Attachment')
Line = get_model('order', 'Line')
Message = get_model('oscar_support', 'Message')
Priority = get_model("oscar_support", "Priority")
Product = get_model('catalogue', 'Product')
RelatedOrder = ... | 0.36523 | 0.116613 |
import argparse
from pathlib import Path
import optuna
from optuna.pruners import SuccessiveHalvingPruner
import pytorch_lightning as pl
import torch
from torch import nn, optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
BATCH_SIZE = 128
D... | pytorch_lightning_optuna/main.py | import argparse
from pathlib import Path
import optuna
from optuna.pruners import SuccessiveHalvingPruner
import pytorch_lightning as pl
import torch
from torch import nn, optim
from torch.nn import functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
BATCH_SIZE = 128
D... | 0.880316 | 0.456289 |
import os, time, sys, shutil, urllib.request, urllib.parse
minify = False
def sources():
path = "./src/"
return [
os.path.join(base, f)
for base, folders, files in os.walk(path)
for f in files
if f.endswith(".js")
]
def build():
path = "./www/fsm.js"
data = "\n"... | build.py |
import os, time, sys, shutil, urllib.request, urllib.parse
minify = False
def sources():
path = "./src/"
return [
os.path.join(base, f)
for base, folders, files in os.walk(path)
for f in files
if f.endswith(".js")
]
def build():
path = "./www/fsm.js"
data = "\n"... | 0.251096 | 0.107204 |
import asyncio
from BubotObj.OcfDevice.subtype.Device.Device import Device
from Bubot.Core.DeviceLink import ResourceLink
from aio_modbus_client.ModbusProtocolOcf import ModbusProtocolOcf
from aio_modbus_client.ModbusDevice import ModbusDevice as ModbusDevice
from Bubot.Helpers.ExtException import ExtException, ExtTime... | src/BubotObj/OcfDevice/subtype/ModbusSlave/ModbusSlave.py | import asyncio
from BubotObj.OcfDevice.subtype.Device.Device import Device
from Bubot.Core.DeviceLink import ResourceLink
from aio_modbus_client.ModbusProtocolOcf import ModbusProtocolOcf
from aio_modbus_client.ModbusDevice import ModbusDevice as ModbusDevice
from Bubot.Helpers.ExtException import ExtException, ExtTime... | 0.266644 | 0.063279 |
from InstagramAPI import InstagramAPI
from core.imgur import im
import asyncio
import codecs
import core.constants as constants
#this class makes communicating with instagram api straightforward
class InstaAPI:
def __init__(self, username, password):
self.username = username
self.password = passwor... | core/instagram.py | from InstagramAPI import InstagramAPI
from core.imgur import im
import asyncio
import codecs
import core.constants as constants
#this class makes communicating with instagram api straightforward
class InstaAPI:
def __init__(self, username, password):
self.username = username
self.password = passwor... | 0.244093 | 0.147709 |
import os
import random
import tarfile
from rest_framework import viewsets
import requests
from .models import Answer, Activity
from .serializers import AnswerSerializer, ActivityImageSerializer
from core.permissions import IsProfessorCoordinatorOrAdminPermissionOrReadOnly
from rest_framework.response import Response... | activities/views.py | import os
import random
import tarfile
from rest_framework import viewsets
import requests
from .models import Answer, Activity
from .serializers import AnswerSerializer, ActivityImageSerializer
from core.permissions import IsProfessorCoordinatorOrAdminPermissionOrReadOnly
from rest_framework.response import Response... | 0.226955 | 0.07658 |
from ...imcmo import ManagedObject
from ...imccoremeta import MoPropertyMeta, MoMeta
from ...imcmeta import VersionMeta
class BiosVfSelectPprTypeConsts:
VP_SELECT_PPR_TYPE_DISABLED = "Disabled"
VP_SELECT_PPR_TYPE_HARD_PPR = "Hard PPR"
VP_SELECT_PPR_TYPE_SOFT_PPR = "Soft PPR"
_VP_SELECT_PPR_TYPE_DISAB... | imcsdk/mometa/bios/BiosVfSelectPprType.py |
from ...imcmo import ManagedObject
from ...imccoremeta import MoPropertyMeta, MoMeta
from ...imcmeta import VersionMeta
class BiosVfSelectPprTypeConsts:
VP_SELECT_PPR_TYPE_DISABLED = "Disabled"
VP_SELECT_PPR_TYPE_HARD_PPR = "Hard PPR"
VP_SELECT_PPR_TYPE_SOFT_PPR = "Soft PPR"
_VP_SELECT_PPR_TYPE_DISAB... | 0.420362 | 0.226634 |
import sys
import numpy as np
import random
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.distributions import Bernoulli
import gym
from PIL import Image
from time import sleep
from pathlib import Path
import cv2
# code for the only two actions in Pong... | pong/pong_play.py | import sys
import numpy as np
import random
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.distributions import Bernoulli
import gym
from PIL import Image
from time import sleep
from pathlib import Path
import cv2
# code for the only two actions in Pong... | 0.707 | 0.499023 |
from vas.shared.Deletable import Deletable
from vas.shared.MutableCollection import MutableCollection
from vas.shared.Resource import Resource
from vas.util.LinkUtils import LinkUtils
class Templates(MutableCollection):
"""Used to enumerate, create, and delete tc Server templates
:ivar `vas.shared.Security.... | vas/tc_server/Templates.py |
from vas.shared.Deletable import Deletable
from vas.shared.MutableCollection import MutableCollection
from vas.shared.Resource import Resource
from vas.util.LinkUtils import LinkUtils
class Templates(MutableCollection):
"""Used to enumerate, create, and delete tc Server templates
:ivar `vas.shared.Security.... | 0.828176 | 0.285216 |
from FileParsers.Parser import Parser
class PVTMetric(Parser):
def __init__(self, file):
super(PVTMetric, self).__init__(file)
# This class is not part of the configuration
@staticmethod
def metric_naming(file):
import re
stage = ""
syn = re.search(r'.*syn.*', file, re... | genCSV/FileParsers/Synopsys/PVTmetric.py | from FileParsers.Parser import Parser
class PVTMetric(Parser):
def __init__(self, file):
super(PVTMetric, self).__init__(file)
# This class is not part of the configuration
@staticmethod
def metric_naming(file):
import re
stage = ""
syn = re.search(r'.*syn.*', file, re... | 0.460895 | 0.087759 |
from kubernetes import client
from cowait.engine.const import LABEL_TASK_ID
from cowait.engine.kubernetes.affinity import create_affinity
def test_create_str_stack_affinity():
affinity = create_affinity('stack')
assert isinstance(affinity, client.V1Affinity)
assert affinity.pod_anti_affinity is None
i... | test/engine/kubernetes/test_affinity.py | from kubernetes import client
from cowait.engine.const import LABEL_TASK_ID
from cowait.engine.kubernetes.affinity import create_affinity
def test_create_str_stack_affinity():
affinity = create_affinity('stack')
assert isinstance(affinity, client.V1Affinity)
assert affinity.pod_anti_affinity is None
i... | 0.678647 | 0.735202 |
from dlkp.models import KeyphraseTagger
from dlkp.extraction import (
KEDataArguments,
KEModelArguments,
KETrainingArguments,
)
model_name = "bloomberg/KBIR"
print("Training: ", model_name)
training_args = KETrainingArguments(
output_dir=f"/data/models/keyphrase/dlkp/inspec/extraction/{model_name}/fin... | examples/ke/ke_tagger.py | from dlkp.models import KeyphraseTagger
from dlkp.extraction import (
KEDataArguments,
KEModelArguments,
KETrainingArguments,
)
model_name = "bloomberg/KBIR"
print("Training: ", model_name)
training_args = KETrainingArguments(
output_dir=f"/data/models/keyphrase/dlkp/inspec/extraction/{model_name}/fin... | 0.651687 | 0.225566 |
import argparse
import os
import pandas
import numpy
import matplotlib.pyplot
import matplotlib.dates
import datetime
fig_dir = 'fig'
table_dir = 'table'
class Pointing:
def __init__(self, data_path):
self.file_base, _ = os.path.splitext(os.path.basename(data_path))
self.data_raw = pandas.read_c... | qlp_plot.py |
import argparse
import os
import pandas
import numpy
import matplotlib.pyplot
import matplotlib.dates
import datetime
fig_dir = 'fig'
table_dir = 'table'
class Pointing:
def __init__(self, data_path):
self.file_base, _ = os.path.splitext(os.path.basename(data_path))
self.data_raw = pandas.read_c... | 0.342462 | 0.254251 |
import time
from celery.utils.log import get_task_logger
from django.core.mail import send_mail
from django.template.loader import render_to_string
from images.models import Image
from dominion import base
from dominion.app import APP
from dominion.engine import EXIT_STATUS, PiemanDocker
from dominion.exceptions im... | dominion/tasks.py |
import time
from celery.utils.log import get_task_logger
from django.core.mail import send_mail
from django.template.loader import render_to_string
from images.models import Image
from dominion import base
from dominion.app import APP
from dominion.engine import EXIT_STATUS, PiemanDocker
from dominion.exceptions im... | 0.304145 | 0.098729 |
import sys, os, time
import scipy.io as si
import numpy as np
import ggmm.gpu as ggmm
# Matlab inteface imports
import matlab.engine
'''
Functions:
'''
def readEngine(file):
try:
X = si.loadmat(file)['output']
except:
X = np.array([])
return X
def EMEngine(X, thresh_, n_... | experiment/Matlab/emgmm.py | import sys, os, time
import scipy.io as si
import numpy as np
import ggmm.gpu as ggmm
# Matlab inteface imports
import matlab.engine
'''
Functions:
'''
def readEngine(file):
try:
X = si.loadmat(file)['output']
except:
X = np.array([])
return X
def EMEngine(X, thresh_, n_... | 0.200088 | 0.178777 |
import abc
import random
import six
from optinum.algorithm import base
from optinum.common import objects
__all__ = ['HCFirstImprovement', 'HCBestImprovement']
@six.add_metaclass(abc.ABCMeta)
class HillClimbing(base.Algorithm):
def __init__(self, name="HillClimbing", max_evaluations=50):
super(HillCli... | optinum/algorithm/hillclimbing.py | import abc
import random
import six
from optinum.algorithm import base
from optinum.common import objects
__all__ = ['HCFirstImprovement', 'HCBestImprovement']
@six.add_metaclass(abc.ABCMeta)
class HillClimbing(base.Algorithm):
def __init__(self, name="HillClimbing", max_evaluations=50):
super(HillCli... | 0.710427 | 0.153899 |
import sys
sys.path.append('/home/george2/Raise/ProgramRepair/CodeSeer/projects/src/main/python')
from CodeJam.Y11R5P1.dennislissov.A import *
def func_3ba6780ca418469a885da55554034725(y, x):
area += (x - px) * (y + py) / 2
px, py = x, y
return py
def func_16bfa03b301e43139f8f644e5e7cbce6(y, x):
area... | projects/src/main/python/CodeJam/Y11R5P1/dennislissov/generated_py_bb93a4d1acf540c3b7c8dfd80359bd28.py | import sys
sys.path.append('/home/george2/Raise/ProgramRepair/CodeSeer/projects/src/main/python')
from CodeJam.Y11R5P1.dennislissov.A import *
def func_3ba6780ca418469a885da55554034725(y, x):
area += (x - px) * (y + py) / 2
px, py = x, y
return py
def func_16bfa03b301e43139f8f644e5e7cbce6(y, x):
area... | 0.313 | 0.415432 |
import os
import torch as t
from config import Config
from utils import get_data_loader, fgsm, repeat_error_verfication
from datetime import datetime
import sys
opt = Config()
def test(**kwargs):
"""Test models"""
opt.parse(**kwargs)
opt.print()
# device
device = t.device('cuda') i... | test.py | import os
import torch as t
from config import Config
from utils import get_data_loader, fgsm, repeat_error_verfication
from datetime import datetime
import sys
opt = Config()
def test(**kwargs):
"""Test models"""
opt.parse(**kwargs)
opt.print()
# device
device = t.device('cuda') i... | 0.255529 | 0.13452 |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patheffects as path_effects
# Setup
fig = plt.figure(figsize=(6, 6))
ax = plt.subplot(1, 1, 1, projection="polar", frameon=True)
ax.set_thetalim(0, 2 * np.pi)
ax.set_rlim(0, 1000)
ax.set_xticks([])
ax.set_xticklabels([])
ax.set_yticks(np.linspace(100... | code/scales-projections/projection-polar-histogram.py | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patheffects as path_effects
# Setup
fig = plt.figure(figsize=(6, 6))
ax = plt.subplot(1, 1, 1, projection="polar", frameon=True)
ax.set_thetalim(0, 2 * np.pi)
ax.set_rlim(0, 1000)
ax.set_xticks([])
ax.set_xticklabels([])
ax.set_yticks(np.linspace(100... | 0.640861 | 0.711223 |
from flask import Flask, request,render_template
import sys
#sys.path.append("C:/Users/Freddie/Documents/Desktop/dbTest/Front-end/antlr")
sys.path.append("../antlr")
import runSQL
app = Flask(__name__)
currentDB = " "
errors = ""
@app.route('/home')
@app.route("/")
def hello():
return render_template('home.html... | Front-end/web/routesFile.py | from flask import Flask, request,render_template
import sys
#sys.path.append("C:/Users/Freddie/Documents/Desktop/dbTest/Front-end/antlr")
sys.path.append("../antlr")
import runSQL
app = Flask(__name__)
currentDB = " "
errors = ""
@app.route('/home')
@app.route("/")
def hello():
return render_template('home.html... | 0.070776 | 0.038829 |
from __future__ import division, absolute_import, print_function, unicode_literals
from collections import defaultdict
from django.utils import six
from .util import DoesNotExist
from .mappings import OldValues
from .descriptors import _inject_descriptors
__all__ = ('SaveTheChange', 'UpdateTogether', 'TrackChang... | save_the_change/decorators.py |
from __future__ import division, absolute_import, print_function, unicode_literals
from collections import defaultdict
from django.utils import six
from .util import DoesNotExist
from .mappings import OldValues
from .descriptors import _inject_descriptors
__all__ = ('SaveTheChange', 'UpdateTogether', 'TrackChang... | 0.747155 | 0.117294 |
import json
import os
import sys
import pandas.io.sql as psql
import requests
crypto_tools_dir = os.getcwd().split('/scripts/')[0] + '/scripts/'
sys.path.append(crypto_tools_dir)
from crypto_tools import *
class PopulateKraken(object):
"""
"""
def __init__(self):
"""
"""
self.po... | scripts/populate_database/populate_kraken.py | import json
import os
import sys
import pandas.io.sql as psql
import requests
crypto_tools_dir = os.getcwd().split('/scripts/')[0] + '/scripts/'
sys.path.append(crypto_tools_dir)
from crypto_tools import *
class PopulateKraken(object):
"""
"""
def __init__(self):
"""
"""
self.po... | 0.202601 | 0.076304 |
from azure.cli.core.commands.parameters import (
get_three_state_flag,
get_enum_type
)
from azure.cli.core.commands.validators import validate_file_or_dict
from azext_planner.action import (
AddCategoryDescriptions,
AddApplication,
AddBucketTaskBoardFormat,
AddProgressTaskBoardFormat
)
def lo... | msgraph/cli/command_modules/planner/azext_planner/generated/_params.py |
from azure.cli.core.commands.parameters import (
get_three_state_flag,
get_enum_type
)
from azure.cli.core.commands.validators import validate_file_or_dict
from azext_planner.action import (
AddCategoryDescriptions,
AddApplication,
AddBucketTaskBoardFormat,
AddProgressTaskBoardFormat
)
def lo... | 0.601828 | 0.090695 |
"""Test the UI."""
from __future__ import absolute_import, print_function, unicode_literals
import responses
from gimme.helpers import CLOUD_RM
def test_not_logged_in(app):
"""Test what happens when we're not logged in.
Ensure we trigger the OAuth flow if we don't have a valid
session.
"""
res ... | tests/test_ui.py | """Test the UI."""
from __future__ import absolute_import, print_function, unicode_literals
import responses
from gimme.helpers import CLOUD_RM
def test_not_logged_in(app):
"""Test what happens when we're not logged in.
Ensure we trigger the OAuth flow if we don't have a valid
session.
"""
res ... | 0.789071 | 0.474875 |
from random import choice
class CardDeck():
'''
Esta classe descreve o baralho
'''
_card_list: list
def __init__(self):
self._card_list = []
# Geração do baralho
# Cada carta é gerada e depois é atribuída a algum naipe
suit = ''
for i in range(4):
... | Poker/cards.py | from random import choice
class CardDeck():
'''
Esta classe descreve o baralho
'''
_card_list: list
def __init__(self):
self._card_list = []
# Geração do baralho
# Cada carta é gerada e depois é atribuída a algum naipe
suit = ''
for i in range(4):
... | 0.416678 | 0.253971 |
import json
import base64
import requests
from uuid import UUID
from os import urandom
from time import timezone
from typing import BinaryIO, Union
from binascii import hexlify
from time import time as timestamp
from json_minify import json_minify
from . import client
from .utils import exceptions, headers, ... | proudcatowner/sub_client.py | import json
import base64
import requests
from uuid import UUID
from os import urandom
from time import timezone
from typing import BinaryIO, Union
from binascii import hexlify
from time import time as timestamp
from json_minify import json_minify
from . import client
from .utils import exceptions, headers, ... | 0.520009 | 0.069542 |
import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
import numpy as np
def gastrack(df: pd.DataFrame,
gas: list = None,
lims: list = None,
dtick: bool =False,
ax=None,
gas_range:list =[0.2,20000],
fontsize:int =8... | reservoirpy/welllogspy/tracks/gastrack.py | import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas as pd
import numpy as np
def gastrack(df: pd.DataFrame,
gas: list = None,
lims: list = None,
dtick: bool =False,
ax=None,
gas_range:list =[0.2,20000],
fontsize:int =8... | 0.477798 | 0.531939 |
import dash
from dash.exceptions import PreventUpdate
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
import utils.dash_reusable_components as drc
import dash_table
import plotly.express as ex
import plotl... | old experiments/UI_cars.py | import dash
from dash.exceptions import PreventUpdate
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
import dash_bootstrap_components as dbc
import utils.dash_reusable_components as drc
import dash_table
import plotly.express as ex
import plotl... | 0.478041 | 0.14919 |
# Adds sound to the visualisation
import os
import subprocess
from tempfile import mkstemp
import numpy as np
from scipy.io.wavfile import write as write_wav
from .utils import norm_and_centre
from SCE import gen_audio
def encode_audio(results, video_file, total_duration, sample_rate=44100, threads=1):
# Extra... | mandrake/sound.py |
# Adds sound to the visualisation
import os
import subprocess
from tempfile import mkstemp
import numpy as np
from scipy.io.wavfile import write as write_wav
from .utils import norm_and_centre
from SCE import gen_audio
def encode_audio(results, video_file, total_duration, sample_rate=44100, threads=1):
# Extra... | 0.431345 | 0.41324 |
import os
import sys
import re
# pyside2 package
from PySide2.QtWidgets import QFileDialog, QMessageBox, QProgressDialog
from PySide2.QtCore import Qt, QDir, QCoreApplication
from PySide2.QtSql import QSqlQuery, QSqlQueryModel
from PySide2.QtGui import QColor
# python-docx package
from docx import Document, oxml, sha... | QRegisterConst.py | import os
import sys
import re
# pyside2 package
from PySide2.QtWidgets import QFileDialog, QMessageBox, QProgressDialog
from PySide2.QtCore import Qt, QDir, QCoreApplication
from PySide2.QtSql import QSqlQuery, QSqlQueryModel
from PySide2.QtGui import QColor
# python-docx package
from docx import Document, oxml, sha... | 0.181916 | 0.083516 |
import wx
class TextPanel(wx.Panel):
"""A :class:`wx.PyPanel` which may be used to display a string of
text, oriented either horizontally or vertically.
"""
def __init__(self, parent, text=None, orient=wx.HORIZONTAL, **kwargs):
"""Create a ``TextPanel``.
:arg parent: The :mod:`wx` pa... | fsleyes_widgets/textpanel.py | import wx
class TextPanel(wx.Panel):
"""A :class:`wx.PyPanel` which may be used to display a string of
text, oriented either horizontally or vertically.
"""
def __init__(self, parent, text=None, orient=wx.HORIZONTAL, **kwargs):
"""Create a ``TextPanel``.
:arg parent: The :mod:`wx` pa... | 0.784402 | 0.23014 |
from typing import TYPE_CHECKING, Coroutine
if TYPE_CHECKING:
from Platforms.Discord.main_discord import PhaazebotDiscord
from Platforms.Web.main_web import PhaazebotWeb
import json
import asyncio
import discord
from aiohttp.web import Response
from Utils.Classes.discordserversettings import DiscordServerSettings
fr... | Platforms/Web/Processing/Api/Discord/Regulars/create.py | from typing import TYPE_CHECKING, Coroutine
if TYPE_CHECKING:
from Platforms.Discord.main_discord import PhaazebotDiscord
from Platforms.Web.main_web import PhaazebotWeb
import json
import asyncio
import discord
from aiohttp.web import Response
from Utils.Classes.discordserversettings import DiscordServerSettings
fr... | 0.605916 | 0.048812 |
import os
import paramiko
import socket
import sys
import threading
hostkey_file = input('HOSTKEY file name: ')
CWD = os.path.dirname(os.path.realpath(__file__))
# RSA key can be used to sign and verify SSH data during SSH2 negoatiation
HOSTKEY = paramiko.RSAKey(filename=os.path.join(CWD, hostkey_file))
class Sas... | SSHTools/ssh_server.py | import os
import paramiko
import socket
import sys
import threading
hostkey_file = input('HOSTKEY file name: ')
CWD = os.path.dirname(os.path.realpath(__file__))
# RSA key can be used to sign and verify SSH data during SSH2 negoatiation
HOSTKEY = paramiko.RSAKey(filename=os.path.join(CWD, hostkey_file))
class Sas... | 0.3027 | 0.068975 |
import os, sys
import numpy as np
import numpy as np
import os,sys
from sklearn import preprocessing
import pickle, logging
from sklearn.metrics import mean_squared_error
import dynet as dy
import time, random
'''
Assumes that input_full and output_full within a directory called data contain input and output features... | world/FFNN/MVP/map_small_dynet.py | import os, sys
import numpy as np
import numpy as np
import os,sys
from sklearn import preprocessing
import pickle, logging
from sklearn.metrics import mean_squared_error
import dynet as dy
import time, random
'''
Assumes that input_full and output_full within a directory called data contain input and output features... | 0.376623 | 0.412589 |
from dataclasses import dataclass
import copy
import numpy as np
"""
file that constains a few classes that do automatric unit management.
The idea of these modules is to provide the units that qcodes needs for plotting.
The setpoint_mgr is meant to run in segment object and can be conbined easily
for all the channels... | pulse_lib/segments/utility/setpoint_mgr.py | from dataclasses import dataclass
import copy
import numpy as np
"""
file that constains a few classes that do automatric unit management.
The idea of these modules is to provide the units that qcodes needs for plotting.
The setpoint_mgr is meant to run in segment object and can be conbined easily
for all the channels... | 0.761937 | 0.274698 |
import random
import logging
from ask_sdk_core.skill_builder import SkillBuilder
from ask_sdk_core.dispatch_components import (
AbstractRequestHandler, AbstractExceptionHandler,
AbstractRequestInterceptor, AbstractResponseInterceptor)
from ask_sdk_core.utils import is_request_type, is_intent_name
from ask_sdk_... | IndiaFacts/lambda/lambda_function.py | import random
import logging
from ask_sdk_core.skill_builder import SkillBuilder
from ask_sdk_core.dispatch_components import (
AbstractRequestHandler, AbstractExceptionHandler,
AbstractRequestInterceptor, AbstractResponseInterceptor)
from ask_sdk_core.utils import is_request_type, is_intent_name
from ask_sdk_... | 0.440951 | 0.069069 |
from connexion import request
from flask import make_response, jsonify
from src import db
from src.models import Quote, QuoteItem, Transaction
def create_quote(body): # noqa: E501
if request.is_json:
customer_id = body.get('customer_id')
date = body.get('date')
description = body.get('de... | services/server/src/quotes/views.py | from connexion import request
from flask import make_response, jsonify
from src import db
from src.models import Quote, QuoteItem, Transaction
def create_quote(body): # noqa: E501
if request.is_json:
customer_id = body.get('customer_id')
date = body.get('date')
description = body.get('de... | 0.357119 | 0.05752 |
from enum import Enum
from pathlib import Path
from typing import Callable, Dict, List, Optional, Set, Tuple, Union
import pytest
from typer.testing import CliRunner
from chessli.cli.main import app
runner = CliRunner()
main_commands = [
"--help",
"--version",
"-v",
"-vv",
"-vvv",
"--user D... | tests/test_cli_commands.py | from enum import Enum
from pathlib import Path
from typing import Callable, Dict, List, Optional, Set, Tuple, Union
import pytest
from typer.testing import CliRunner
from chessli.cli.main import app
runner = CliRunner()
main_commands = [
"--help",
"--version",
"-v",
"-vv",
"-vvv",
"--user D... | 0.694199 | 0.307124 |
import numpy as np
from scipy.optimize import check_grad
from deep_rlsp.solvers.value_iter import value_iter, evaluate_policy
from deep_rlsp.solvers.ppo import PPOSolver
from deep_rlsp.util.parameter_checks import check_in
def compute_g(mdp, policy, p_0, T, d_last_step_list, expected_features_list):
nS, nA, nF =... | src/deep_rlsp/rlsp.py | import numpy as np
from scipy.optimize import check_grad
from deep_rlsp.solvers.value_iter import value_iter, evaluate_policy
from deep_rlsp.solvers.ppo import PPOSolver
from deep_rlsp.util.parameter_checks import check_in
def compute_g(mdp, policy, p_0, T, d_last_step_list, expected_features_list):
nS, nA, nF =... | 0.673299 | 0.635208 |
from adapt.tools.text.trie import Trie
from six.moves import xrange
__author__ = 'seanfitz'
class EntityTagger(object):
"""
Known Entity Tagger
Given an index of known entities, can efficiently search for those entities within a provided utterance.
"""
def __init__(self, trie, tokenizer, regex_e... | adapt/entity_tagger.py |
from adapt.tools.text.trie import Trie
from six.moves import xrange
__author__ = 'seanfitz'
class EntityTagger(object):
"""
Known Entity Tagger
Given an index of known entities, can efficiently search for those entities within a provided utterance.
"""
def __init__(self, trie, tokenizer, regex_e... | 0.774669 | 0.436442 |
import os
import logging
import asyncio
import pickle
from pathlib import Path
from typing import Union
import numpy as np
import pandas as pd
from PIL import Image
from easydict import EasyDict
from sklearn.preprocessing import MultiLabelBinarizer
from sklearn.model_selection import train_test_split
from sklearn.exte... | src/database/read_db.py | import os
import logging
import asyncio
import pickle
from pathlib import Path
from typing import Union
import numpy as np
import pandas as pd
from PIL import Image
from easydict import EasyDict
from sklearn.preprocessing import MultiLabelBinarizer
from sklearn.model_selection import train_test_split
from sklearn.exte... | 0.640411 | 0.256622 |
_LAMP_DIGITS = {
'red': 0,
'yellow': 1,
'green': 2
}
_LAMP_STATES = {
'off': 0,
'on': 1,
'blink': 2,
'quickblink': 3
}
def build_lamp_flags(states):
"""Returns flags that be used as arguments of lamp control commands.
The structure of <states> is:
{'lamps': {<color>: <sta... | keiko/flags.py | _LAMP_DIGITS = {
'red': 0,
'yellow': 1,
'green': 2
}
_LAMP_STATES = {
'off': 0,
'on': 1,
'blink': 2,
'quickblink': 3
}
def build_lamp_flags(states):
"""Returns flags that be used as arguments of lamp control commands.
The structure of <states> is:
{'lamps': {<color>: <sta... | 0.842766 | 0.572633 |
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
import pandas as pd
import sklearn.metrics as sk_metrics
from .scorer import ScoreCalculator, Timeliness
@dataclass
class _ThreshRequired:
p_thresh: bool
p_hat_thresh: bool
def check_threshs_correct(
self, p... | epiquark/api.py | from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
import pandas as pd
import sklearn.metrics as sk_metrics
from .scorer import ScoreCalculator, Timeliness
@dataclass
class _ThreshRequired:
p_thresh: bool
p_hat_thresh: bool
def check_threshs_correct(
self, p... | 0.959978 | 0.460774 |
from unittest import TestCase
from collections import Counter
from dark.intervals import OffsetAdjuster, ReadIntervals
from dark.hsp import HSP
class TestReadIntervals(TestCase):
"""
Test the ReadIntervals class
"""
EMPTY = ReadIntervals.EMPTY
FULL = ReadIntervals.FULL
def testEmpty(self):
... | test/test_intervals.py | from unittest import TestCase
from collections import Counter
from dark.intervals import OffsetAdjuster, ReadIntervals
from dark.hsp import HSP
class TestReadIntervals(TestCase):
"""
Test the ReadIntervals class
"""
EMPTY = ReadIntervals.EMPTY
FULL = ReadIntervals.FULL
def testEmpty(self):
... | 0.864196 | 0.608972 |
import inspect
import os
from types import MethodType
from django import shortcuts
from django.conf import settings
from django.http import HttpResponseNotFound, HttpResponseServerError, HttpRequest, HttpResponse
from .util import logger
from .util import utils
from .util.utils import load_module
# 包名称
... | restful_dj/router.py | import inspect
import os
from types import MethodType
from django import shortcuts
from django.conf import settings
from django.http import HttpResponseNotFound, HttpResponseServerError, HttpRequest, HttpResponse
from .util import logger
from .util import utils
from .util.utils import load_module
# 包名称
... | 0.184878 | 0.061621 |
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AliyunAccount',
... | misaka/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AliyunAccount',
... | 0.4917 | 0.13707 |
import torch
from torch import nn
from gnn.emn import EMN
from gnn.modules import FeedForwardNetwork, GraphGather
class EMNImplementation(EMN):
def __init__(self, node_features, edge_features, message_passes, out_features,
edge_embedding_size,
edge_emb_depth=3, edge_emb_hidden_... | gnn/emn_implementations.py | import torch
from torch import nn
from gnn.emn import EMN
from gnn.modules import FeedForwardNetwork, GraphGather
class EMNImplementation(EMN):
def __init__(self, node_features, edge_features, message_passes, out_features,
edge_embedding_size,
edge_emb_depth=3, edge_emb_hidden_... | 0.850763 | 0.29348 |
import logging
import shutil
import subprocess
import sys
from typing import List, Optional
from codiga.exceptions.git_command_exception import GitCommandException
COMMAND_DIFF = 'diff'
def get_current_branch() -> Optional[str]:
"""
Returns the name of the current branch we are on
Use the following comm... | codiga/utils/git.py | import logging
import shutil
import subprocess
import sys
from typing import List, Optional
from codiga.exceptions.git_command_exception import GitCommandException
COMMAND_DIFF = 'diff'
def get_current_branch() -> Optional[str]:
"""
Returns the name of the current branch we are on
Use the following comm... | 0.608129 | 0.366193 |
from django.core.management.base import AppCommand
from drf_app_generators.compliers.app import AppConfig, AppOptions
from drf_app_generators.compliers.model import ModelMeta
from drf_app_generators.generators import (
AdminGenerator,
FactoryGenerator,
ApiGenerator,
SerializerGenerator,
UnitTestGene... | drf_app_generators/management/commands/app_update.py | from django.core.management.base import AppCommand
from drf_app_generators.compliers.app import AppConfig, AppOptions
from drf_app_generators.compliers.model import ModelMeta
from drf_app_generators.generators import (
AdminGenerator,
FactoryGenerator,
ApiGenerator,
SerializerGenerator,
UnitTestGene... | 0.477311 | 0.071203 |
import pytest
@pytest.mark.parametrize(
'path', [
'/images/hosted-logos/',
'/hosting-logos/',
],
)
@pytest.mark.parametrize(
'image', [
'berknow150x40.jpg',
'berknow150x40.png',
'binnov-157x46.gif',
'binnov-157x46.png',
'lighter152x41.gif',
'... | tests/main/hosting_logos_test.py | import pytest
@pytest.mark.parametrize(
'path', [
'/images/hosted-logos/',
'/hosting-logos/',
],
)
@pytest.mark.parametrize(
'image', [
'berknow150x40.jpg',
'berknow150x40.png',
'binnov-157x46.gif',
'binnov-157x46.png',
'lighter152x41.gif',
'... | 0.503174 | 0.585753 |
import mysql.connector
# Insere informações no bando de dados MySql
def insertDataBase(id, initial_dat, initial_time, final_dat, final_time, work_time):
connection = mysql.connector.connect(host='localhost', database='db_projects',
user='root', password='<PASSWORD>', auth_p... | defs/database.py | import mysql.connector
# Insere informações no bando de dados MySql
def insertDataBase(id, initial_dat, initial_time, final_dat, final_time, work_time):
connection = mysql.connector.connect(host='localhost', database='db_projects',
user='root', password='<PASSWORD>', auth_p... | 0.153454 | 0.128607 |
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AcademicTerms',
fields=[
... | dashboard/migrations/0001_initial.py | from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='AcademicTerms',
fields=[
... | 0.63375 | 0.115661 |
from collections import deque
from typing import Callable
TEST1 = """inp z
inp x
mul z 3
eql z x"""
TEST2 = """inp w
add z w
mod z 2
div w 2
add y w
mod y 2
div w 2
add x w
mod x 2
div w 2
mod w 2"""
def isinteger(s):
if s[0] in ('-', '+'):
return s[1:].isdigit()
return s.isdigit()
class Alu:
... | Advent2021/24.py | from collections import deque
from typing import Callable
TEST1 = """inp z
inp x
mul z 3
eql z x"""
TEST2 = """inp w
add z w
mod z 2
div w 2
add y w
mod y 2
div w 2
add x w
mod x 2
div w 2
mod w 2"""
def isinteger(s):
if s[0] in ('-', '+'):
return s[1:].isdigit()
return s.isdigit()
class Alu:
... | 0.86241 | 0.756627 |
import sys
import urllib
import json
import argparse
import urllib.request
import unicodedata
import collections
import os
import xml.etree.ElementTree as ET
import csv
import glob
# collection = "masukagami"
# collection = "imakagami"
# collection = "okagami"
# collection = "mizukagami"
collection = "azumakagami"... | src/nijl18/61_markDate.py | import sys
import urllib
import json
import argparse
import urllib.request
import unicodedata
import collections
import os
import xml.etree.ElementTree as ET
import csv
import glob
# collection = "masukagami"
# collection = "imakagami"
# collection = "okagami"
# collection = "mizukagami"
collection = "azumakagami"... | 0.031041 | 0.071235 |
import numpy as np
import torch
from torch.nn import LayerNorm
import torch.nn as nn
import torch.nn.functional as F
from .layers.crf import CRF
from transformers import BertModel, BertPreTrainedModel
from .layers.linears import PoolerEndLogits, PoolerStartLogits
from torch.nn import CrossEntropyLoss
from loss... | models/bert_for_ner.py | import numpy as np
import torch
from torch.nn import LayerNorm
import torch.nn as nn
import torch.nn.functional as F
from .layers.crf import CRF
from transformers import BertModel, BertPreTrainedModel
from .layers.linears import PoolerEndLogits, PoolerStartLogits
from torch.nn import CrossEntropyLoss
from loss... | 0.927232 | 0.334019 |
import sys
import os
import numpy as np
import argparse
from sklearn.metrics import f1_score, accuracy_score
import paddle as P
import paddle.fluid as F
import paddle.fluid.layers as L
import paddle.fluid.dygraph as D
from reader import ChnSentiCorp, pad_batch_data
from paddle_edl.distill.distill_reader import Distil... | example/distill/nlp/model.py |
import sys
import os
import numpy as np
import argparse
from sklearn.metrics import f1_score, accuracy_score
import paddle as P
import paddle.fluid as F
import paddle.fluid.layers as L
import paddle.fluid.dygraph as D
from reader import ChnSentiCorp, pad_batch_data
from paddle_edl.distill.distill_reader import Distil... | 0.594434 | 0.223695 |
from pyomo.environ import *
model = m = ConcreteModel()
m.x2 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x3 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x4 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x5 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x6 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x7... | models_nonconvex_simple2/gabriel01.py |
from pyomo.environ import *
model = m = ConcreteModel()
m.x2 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x3 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x4 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x5 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x6 = Var(within=Reals,bounds=(0,1),initialize=0)
m.x7... | 0.538741 | 0.192786 |
import torch
import matplotlib.pyplot as plt
import matplotlib.cm as CM
from mcnn_model import MCNN
from my_dataloader import CrowdDataset
def cal_mae(img_root,gt_dmap_root,model_param_path):
'''
Calculate the MAE of the test data.
img_root: the root of test image data.
gt_dmap_root: the root of test... | test.py | import torch
import matplotlib.pyplot as plt
import matplotlib.cm as CM
from mcnn_model import MCNN
from my_dataloader import CrowdDataset
def cal_mae(img_root,gt_dmap_root,model_param_path):
'''
Calculate the MAE of the test data.
img_root: the root of test image data.
gt_dmap_root: the root of test... | 0.499756 | 0.536738 |
"""Zeff commandline processing utilities."""
__author__ = """<NAME> <<EMAIL>>"""
__copyright__ = """Copyright © 2019, Ziff, Inc. — All Rights Reserved"""
__license__ = """
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may... | src/zeff/cli/pipeline.py | """Zeff commandline processing utilities."""
__author__ = """<NAME> <<EMAIL>>"""
__copyright__ = """Copyright © 2019, Ziff, Inc. — All Rights Reserved"""
__license__ = """
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may... | 0.88521 | 0.231913 |
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("core", "0039_generate_initial_topic_materialzed_paths"),
]
operations = [
migrations.AlterField(
model_name="topic",
name="path",
... | src/backend/partaj/core/migrations/0040_create_manytomany_referrals_units.py |
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("core", "0039_generate_initial_topic_materialzed_paths"),
]
operations = [
migrations.AlterField(
model_name="topic",
name="path",
... | 0.553385 | 0.202621 |