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 pandas as pd
from sqlalchemy import create_engine
class DataRetriever:
def retrieveAllData():
global fof_data
global monthly #balance sheet
global annually #balance sheet
fof_data = DataRetriever.retrieve("records")
monthly = DataRetriever.retrieve("monthly")
... | DataRetrieve.py | import pandas as pd
from sqlalchemy import create_engine
class DataRetriever:
def retrieveAllData():
global fof_data
global monthly #balance sheet
global annually #balance sheet
fof_data = DataRetriever.retrieve("records")
monthly = DataRetriever.retrieve("monthly")
... | 0.190988 | 0.183557 |
import os
from typing import Dict, List, Optional, Tuple, Union
from urllib.request import pathname2url
import webbrowser
from PyQt5.QtWidgets import QFileDialog, QTableWidgetItem, QWidget
_TypeList = Optional[
Union[
List[Tuple[str, str]],
Dict[str, str],
... | widgets.py | import os
from typing import Dict, List, Optional, Tuple, Union
from urllib.request import pathname2url
import webbrowser
from PyQt5.QtWidgets import QFileDialog, QTableWidgetItem, QWidget
_TypeList = Optional[
Union[
List[Tuple[str, str]],
Dict[str, str],
... | 0.808332 | 0.214034 |
from credoscript import adaptors, models
from tests import CredoAdaptorTestCase
class ContactAdaptorTestCase(CredoAdaptorTestCase):
def setUp(self):
self.adaptor = adaptors.ContactAdaptor()
self.expected_entity = models.Contact
def test_fetch_by_contact_id(self):
"""Fetch a single Cont... | tests/adaptors/contactadaptortestcase.py | from credoscript import adaptors, models
from tests import CredoAdaptorTestCase
class ContactAdaptorTestCase(CredoAdaptorTestCase):
def setUp(self):
self.adaptor = adaptors.ContactAdaptor()
self.expected_entity = models.Contact
def test_fetch_by_contact_id(self):
"""Fetch a single Cont... | 0.729423 | 0.451871 |
import mock
import nose
import ckan.new_tests.helpers as helpers
import ckanext.datastore.db as db
assert_equal = nose.tools.assert_equal
class TestCreateIndexes(object):
def test_creates_fts_index_by_default(self):
connection = mock.MagicMock()
context = {
'connection': connection
... | ckanext/datastore/tests/test_db.py | import mock
import nose
import ckan.new_tests.helpers as helpers
import ckanext.datastore.db as db
assert_equal = nose.tools.assert_equal
class TestCreateIndexes(object):
def test_creates_fts_index_by_default(self):
connection = mock.MagicMock()
context = {
'connection': connection
... | 0.593491 | 0.227491 |
import json
from alipay.aop.api.constant.ParamConstants import *
class AccessProduceQrcode(object):
def __init__(self):
self._batch_id = None
self._core_url = None
self._produce_order_id = None
self._qrcode = None
@property
def batch_id(self):
return self._batch_... | alipay/aop/api/domain/AccessProduceQrcode.py | import json
from alipay.aop.api.constant.ParamConstants import *
class AccessProduceQrcode(object):
def __init__(self):
self._batch_id = None
self._core_url = None
self._produce_order_id = None
self._qrcode = None
@property
def batch_id(self):
return self._batch_... | 0.540681 | 0.075687 |
import matplotlib
matplotlib.use('TkAgg', warn=False)
import scipy
import numpy as np
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
from Tkinter import *
from tkFont i... | puq/read.py | import matplotlib
matplotlib.use('TkAgg', warn=False)
import scipy
import numpy as np
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib.figure import Figure
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
from Tkinter import *
from tkFont i... | 0.255065 | 0.12408 |
import unittest
from Calculator import Calculator
from CsvReader import CsvReader
class MyTestCase(unittest.TestCase):
def setUp(self) -> None:
self.calculator = Calculator()
def test_instantiate_calculator(self):
self.assertIsInstance(self.calculator, Calculator)
def test_subtract(self... | src/CalculatorTests.py | import unittest
from Calculator import Calculator
from CsvReader import CsvReader
class MyTestCase(unittest.TestCase):
def setUp(self) -> None:
self.calculator = Calculator()
def test_instantiate_calculator(self):
self.assertIsInstance(self.calculator, Calculator)
def test_subtract(self... | 0.635675 | 0.585397 |
import lxml.html
from billy.utils.fulltext import text_after_line_numbers
from .bills import WABillScraper
from .legislators import WALegislatorScraper
from .committees import WACommitteeScraper
from .events import WAEventScraper
settings = dict(SCRAPELIB_TIMEOUT=300)
metadata = dict(
name='Washington',
abbre... | openstates/openstates-master/openstates/wa/__init__.py | import lxml.html
from billy.utils.fulltext import text_after_line_numbers
from .bills import WABillScraper
from .legislators import WALegislatorScraper
from .committees import WACommitteeScraper
from .events import WAEventScraper
settings = dict(SCRAPELIB_TIMEOUT=300)
metadata = dict(
name='Washington',
abbre... | 0.350199 | 0.150715 |
import numpy as np
from scipy.stats import norm
from scipy.spatial.distance import cdist
from .sbom import SBOM
class BayesianOptimizer(SBOM):
def __init__(self, init_positions, space_dim, opt_para):
super().__init__(init_positions, space_dim, opt_para)
self.regr = self._opt_args_.gpr
... | gradient_free_optimizers/sequence_model/bayesian_optimization.py |
import numpy as np
from scipy.stats import norm
from scipy.spatial.distance import cdist
from .sbom import SBOM
class BayesianOptimizer(SBOM):
def __init__(self, init_positions, space_dim, opt_para):
super().__init__(init_positions, space_dim, opt_para)
self.regr = self._opt_args_.gpr
... | 0.678433 | 0.36869 |
__author__ = "<NAME>, <NAME>"
__copyright__ = "Copyright 2016, EOSS GmbH"
__credits__ = ["<NAME>", "<NAME>"]
__license__ = "GPL"
__version__ = "1.0.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__status__ = "Production"
import ujson
import requests
from manage import ICatalog
from model.plain_models import Catalo... | catalog/manage/eosscatalog.py | __author__ = "<NAME>, <NAME>"
__copyright__ = "Copyright 2016, EOSS GmbH"
__credits__ = ["<NAME>", "<NAME>"]
__license__ = "GPL"
__version__ = "1.0.0"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__status__ = "Production"
import ujson
import requests
from manage import ICatalog
from model.plain_models import Catalo... | 0.512693 | 0.072047 |
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
def load_dataset():
train_dataset = h5py.File('train_catvnoncat.h5', "r")
train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # your train set features... | LR.py | import matplotlib
import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import Image
from scipy import ndimage
def load_dataset():
train_dataset = h5py.File('train_catvnoncat.h5', "r")
train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # your train set features... | 0.505859 | 0.580768 |
BUILD_PATH = "../build/"
LIBNAME = "libTwitter.so"
import sys
sys.path.append(BUILD_PATH)
import ctypes
import os
ctypes.CDLL(BUILD_PATH + LIBNAME, mode=os.RTLD_LAZY)
from twitwi import Twitter
import json
from random import randint
import time
class TwitterRef:
def __init__(self):
self.tweetMap = {}
... | test/run.py | BUILD_PATH = "../build/"
LIBNAME = "libTwitter.so"
import sys
sys.path.append(BUILD_PATH)
import ctypes
import os
ctypes.CDLL(BUILD_PATH + LIBNAME, mode=os.RTLD_LAZY)
from twitwi import Twitter
import json
from random import randint
import time
class TwitterRef:
def __init__(self):
self.tweetMap = {}
... | 0.121048 | 0.075858 |
import unittest
from riskquant import loss
class FixedValueModel(object):
def __init__(self, value):
self.value = value
def draw(self, n=1):
return [self.value] * n
class TestLoss(unittest.TestCase):
def test_simulate_losses_one_year(self):
loss_model = loss.Loss(FixedValueMode... | tests/test_loss.py | import unittest
from riskquant import loss
class FixedValueModel(object):
def __init__(self, value):
self.value = value
def draw(self, n=1):
return [self.value] * n
class TestLoss(unittest.TestCase):
def test_simulate_losses_one_year(self):
loss_model = loss.Loss(FixedValueMode... | 0.810779 | 0.625638 |
class ShortestWay:
@classmethod
def find_shortest_way_1(cls, arr):
if arr is None or len(arr) == 0:
return 0
my_arr = list()
row_count = len(arr)
col_count = len(arr[0])
for row in arr:
my_arr.append([0 for _ in row])
for i in range(col_c... | dp/q2.py | class ShortestWay:
@classmethod
def find_shortest_way_1(cls, arr):
if arr is None or len(arr) == 0:
return 0
my_arr = list()
row_count = len(arr)
col_count = len(arr[0])
for row in arr:
my_arr.append([0 for _ in row])
for i in range(col_c... | 0.276105 | 0.310498 |
import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn.functional as F
import torchvision.transforms as T
from kornia.feature.hardnet import HardNet8
from kornia.feature.tfeat import TFeat
from kornia.morphology import erosion
from kornia.filters import laplacian
from src.models.hog_layer impo... | src/losses/pixelwise_contrastive_loss_2.py | import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn.functional as F
import torchvision.transforms as T
from kornia.feature.hardnet import HardNet8
from kornia.feature.tfeat import TFeat
from kornia.morphology import erosion
from kornia.filters import laplacian
from src.models.hog_layer impo... | 0.774029 | 0.772874 |
from wikidataintegrator import wdi_login, wdi_core, wdi_helpers
from scheduled_bots.geneprotein import HelperBot
from scheduled_bots.geneprotein.ProteinBot import main, Protein, PROPS
from pymongo import MongoClient
from scheduled_bots.local import WDUSER, WDPASS
def _test_write_one_protein(qid, entrezgene, taxid):
... | scheduled_bots/geneprotein/test_ProteinBot.py | from wikidataintegrator import wdi_login, wdi_core, wdi_helpers
from scheduled_bots.geneprotein import HelperBot
from scheduled_bots.geneprotein.ProteinBot import main, Protein, PROPS
from pymongo import MongoClient
from scheduled_bots.local import WDUSER, WDPASS
def _test_write_one_protein(qid, entrezgene, taxid):
... | 0.317532 | 0.27677 |
import argparse
import shutil
from functools import partial
from pathlib import Path
import numpy as np
from python_tools.generic import namespace_as_string
from python_tools.ml import metrics
from python_tools.ml.default.neural_models import EnsembleModel, MLPModel
from python_tools.ml.default.transformations import ... | train.py | import argparse
import shutil
from functools import partial
from pathlib import Path
import numpy as np
from python_tools.generic import namespace_as_string
from python_tools.ml import metrics
from python_tools.ml.default.neural_models import EnsembleModel, MLPModel
from python_tools.ml.default.transformations import ... | 0.531696 | 0.391348 |
import torch.nn as nn
import torch.nn.functional as F
def conv_2d(ni, nf, stride=1, ks=3):
"""3x3 convolution with 1 pixel padding"""
return nn.Conv2d(in_channels=ni, out_channels=nf,
kernel_size=ks, stride=stride,
padding=ks//2, bias=False)
def bn_relu_conv(ni, nf)... | wrn.py | import torch.nn as nn
import torch.nn.functional as F
def conv_2d(ni, nf, stride=1, ks=3):
"""3x3 convolution with 1 pixel padding"""
return nn.Conv2d(in_channels=ni, out_channels=nf,
kernel_size=ks, stride=stride,
padding=ks//2, bias=False)
def bn_relu_conv(ni, nf)... | 0.959677 | 0.469581 |
from django.shortcuts import reverse
from django.views import generic
from django.contrib.auth.mixins import LoginRequiredMixin
from agents.mixins import OrganiserAndLoginRequiredMixin
from .models import Lead, Category, Agent
from .forms import (
LeadModelForm, CustomUserCreationForm,
AssignAgentForm, LeadCa... | leads/views.py | from django.shortcuts import reverse
from django.views import generic
from django.contrib.auth.mixins import LoginRequiredMixin
from agents.mixins import OrganiserAndLoginRequiredMixin
from .models import Lead, Category, Agent
from .forms import (
LeadModelForm, CustomUserCreationForm,
AssignAgentForm, LeadCa... | 0.532425 | 0.102844 |
import logging
from init_program import (
init_prog,
start_browser,
login_base
)
from full_cycle import menu_full_cycle_go, page_full_cycle_go
from serializer import write_serialize_data, read_serialize_data, delete_screens_and_log
from toolbox import log_record, exit_prog
from scenario_mod import... | retail-smoke/main.py | import logging
from init_program import (
init_prog,
start_browser,
login_base
)
from full_cycle import menu_full_cycle_go, page_full_cycle_go
from serializer import write_serialize_data, read_serialize_data, delete_screens_and_log
from toolbox import log_record, exit_prog
from scenario_mod import... | 0.110916 | 0.120051 |
from restclients.pws import PWS
from restclients.sws import encode_section_label
from restclients.dao import SWS_DAO
from restclients.exceptions import DataFailureException
from restclients.models.sws import GradeRoster, GradeRosterItem
from restclients.models.sws import GradeSubmissionDelegate
from lxml import etree
i... | restclients/sws/v5/graderoster.py | from restclients.pws import PWS
from restclients.sws import encode_section_label
from restclients.dao import SWS_DAO
from restclients.exceptions import DataFailureException
from restclients.models.sws import GradeRoster, GradeRosterItem
from restclients.models.sws import GradeSubmissionDelegate
from lxml import etree
i... | 0.449151 | 0.158012 |
import logging
import numpy as np
from .evolutionary_optimizer import EvolutionaryOptimizer
from ..util.argument_validation import argument_validation
LOGGER = logging.getLogger(__name__)
class Island(EvolutionaryOptimizer):
"""
Island: a basic unit of evolutionary optimization. It performs the
genera... | bingo/evolutionary_optimizers/island.py | import logging
import numpy as np
from .evolutionary_optimizer import EvolutionaryOptimizer
from ..util.argument_validation import argument_validation
LOGGER = logging.getLogger(__name__)
class Island(EvolutionaryOptimizer):
"""
Island: a basic unit of evolutionary optimization. It performs the
genera... | 0.923631 | 0.798933 |
from pathlib import Path
import cv2
import numpy as np
import pytorch_lightning as pl
import torch
import torchvision
from pytorch_lightning.callbacks import ModelCheckpoint
from torch.nn import functional as F
from torch.utils.data import DataLoader
from core.dataloaders.mit_dataloader import MitData
from core.netwo... | src/core/trainers/filter_trainer.py | from pathlib import Path
import cv2
import numpy as np
import pytorch_lightning as pl
import torch
import torchvision
from pytorch_lightning.callbacks import ModelCheckpoint
from torch.nn import functional as F
from torch.utils.data import DataLoader
from core.dataloaders.mit_dataloader import MitData
from core.netwo... | 0.882028 | 0.385086 |
from online_monitor.receiver.receiver import Receiver
from zmq.utils import jsonapi
import numpy as np
import time
from PyQt4 import Qt
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph.ptime as ptime
from pyqtgraph.dockarea import DockArea, Dock
from online_monitor.utils import utils
... | silab_online_monitor/receiver/pybar_fei4.py | from online_monitor.receiver.receiver import Receiver
from zmq.utils import jsonapi
import numpy as np
import time
from PyQt4 import Qt
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import pyqtgraph.ptime as ptime
from pyqtgraph.dockarea import DockArea, Dock
from online_monitor.utils import utils
... | 0.478041 | 0.16654 |
import base64
import json
import logging
import os
from flask import Flask
from flask import request
import googleapiclient.discovery
import google.cloud.bigquery
import google.cloud.pubsub_v1
logging.basicConfig(level=logging.DEBUG)
PROJECT_ID = os.environ['GOOGLE_CLOUD_PROJECT']
MODEL_NAME = os.environ['MODEL_NAME']... | examples/e2e-home-appliance-status-monitoring/server/main.py | import base64
import json
import logging
import os
from flask import Flask
from flask import request
import googleapiclient.discovery
import google.cloud.bigquery
import google.cloud.pubsub_v1
logging.basicConfig(level=logging.DEBUG)
PROJECT_ID = os.environ['GOOGLE_CLOUD_PROJECT']
MODEL_NAME = os.environ['MODEL_NAME']... | 0.410874 | 0.148726 |
import argparse
import os
import sys
import tifffile.tifffile as tf
import numpy as np
_description = """Normalizes image stacks against background.
Uses background.tif if it already exists in the current working directory;
otherwise, computes the background image at each (x,y) location as the 5th
percentile of that... | elisa/normalize_bg.py | import argparse
import os
import sys
import tifffile.tifffile as tf
import numpy as np
_description = """Normalizes image stacks against background.
Uses background.tif if it already exists in the current working directory;
otherwise, computes the background image at each (x,y) location as the 5th
percentile of that... | 0.395484 | 0.213767 |
import numpy as np
import cupy as cp
import cupyx.scipy.ndimage as cpndi
from .mathtools import wrapToPi
def cuGPA(image, kvec, sigma=22):
"""Perform spatial lock-in on an image
GPU version of `optGPA()`.
Parameters
----------
image : np.array
2D image input image
kvec : 2-tuple or ... | pyGPA/cuGPA.py | import numpy as np
import cupy as cp
import cupyx.scipy.ndimage as cpndi
from .mathtools import wrapToPi
def cuGPA(image, kvec, sigma=22):
"""Perform spatial lock-in on an image
GPU version of `optGPA()`.
Parameters
----------
image : np.array
2D image input image
kvec : 2-tuple or ... | 0.762601 | 0.590573 |
import numpy as np
import numpy.ma as ma
from math import hypot
from filters import get_filters
get_filters(globals()) # imports all filters at once
def comp_range(blob): # compare rng-distant pixels within blob: a component of intra_blob
rng = blob.rng + 1
p__ = ma.array(blob.dert__[:, :, 0], mask=~blob.... | frame_2D_alg/comp_range.py | import numpy as np
import numpy.ma as ma
from math import hypot
from filters import get_filters
get_filters(globals()) # imports all filters at once
def comp_range(blob): # compare rng-distant pixels within blob: a component of intra_blob
rng = blob.rng + 1
p__ = ma.array(blob.dert__[:, :, 0], mask=~blob.... | 0.464173 | 0.635873 |
from __future__ import absolute_import, division, unicode_literals, print_function, nested_scopes
import getpass
import logging
from .cache import SSHConnectionCache, SSHNoConnectionCache
MAXSSHBUF = 16 * 1024
g_no_cache = SSHNoConnectionCache()
g_cmd_cache = SSHConnectionCache("SSH Command Cache")
logger = logging.ge... | sshutil/conn.py | from __future__ import absolute_import, division, unicode_literals, print_function, nested_scopes
import getpass
import logging
from .cache import SSHConnectionCache, SSHNoConnectionCache
MAXSSHBUF = 16 * 1024
g_no_cache = SSHNoConnectionCache()
g_cmd_cache = SSHConnectionCache("SSH Command Cache")
logger = logging.ge... | 0.626238 | 0.140013 |
import string
import random
import math
import numpy as np
from itertools import izip_longest
from collections import namedtuple
from fractions import gcd
PublicKey = namedtuple("PublicKey", ['e', 'n'])
PrivateKey = namedtuple("PrivateKey", ['d', 'n', 'phi_n'])
def genkeys(bits, e):
p = nextprime(random.getrandbi... | Labs/RSA/solutions.py | import string
import random
import math
import numpy as np
from itertools import izip_longest
from collections import namedtuple
from fractions import gcd
PublicKey = namedtuple("PublicKey", ['e', 'n'])
PrivateKey = namedtuple("PrivateKey", ['d', 'n', 'phi_n'])
def genkeys(bits, e):
p = nextprime(random.getrandbi... | 0.325199 | 0.297732 |
from validator import ip_address, user_name, password, boolean, platform, MAX_PASSWD_LEN
from shlex import quote
import pytest
@pytest.mark.parametrize('value', ['0.0.0.0', '255.255.255.255', '1.1.1.1'])
def test_ip_address_must_not_raise_if_valid_value_provided(value):
assert ip_address(value) == value
@pytes... | app/validator_test.py | from validator import ip_address, user_name, password, boolean, platform, MAX_PASSWD_LEN
from shlex import quote
import pytest
@pytest.mark.parametrize('value', ['0.0.0.0', '255.255.255.255', '1.1.1.1'])
def test_ip_address_must_not_raise_if_valid_value_provided(value):
assert ip_address(value) == value
@pytes... | 0.511961 | 0.334426 |
from __future__ import print_function, division, absolute_import
import os
import sys
import pkgutil
import traceback
import importlib
from collections import OrderedDict
from tpDcc.libs.python import python
def import_module(module_name):
"""
Static function used to import a function given its complete nam... | tpDcc/libs/python/importer.py | from __future__ import print_function, division, absolute_import
import os
import sys
import pkgutil
import traceback
import importlib
from collections import OrderedDict
from tpDcc.libs.python import python
def import_module(module_name):
"""
Static function used to import a function given its complete nam... | 0.32306 | 0.07971 |
import random
import arcade
from constants import *
from randomly_place_sprite import randomly_place_sprite
from wander_sprite import WanderSprite
def _create_grid_with_cells(width, height):
""" Create a grid with empty cells on odd row/column combinations. """
grid = []
for row in range(height):
... | source/level_2.py | import random
import arcade
from constants import *
from randomly_place_sprite import randomly_place_sprite
from wander_sprite import WanderSprite
def _create_grid_with_cells(width, height):
""" Create a grid with empty cells on odd row/column combinations. """
grid = []
for row in range(height):
... | 0.415373 | 0.48377 |
from Sanitize import *
def TicTacToe():
board = [" ", " ", " ", " ", " ", " ", " ", " ", " "]
def print_board():
print("", board[0], "|", board[1], "|", board[2])
print("---+---+---")
print("", board[3], "|", board[4], "|", board[5])
print("---+---+---")
print("", boar... | TicTacToeOpt.py | from Sanitize import *
def TicTacToe():
board = [" ", " ", " ", " ", " ", " ", " ", " ", " "]
def print_board():
print("", board[0], "|", board[1], "|", board[2])
print("---+---+---")
print("", board[3], "|", board[4], "|", board[5])
print("---+---+---")
print("", boar... | 0.298696 | 0.645511 |
from os import X_OK
import torch
import torchvision
from net.cvt_offical import get_cvt13_pretrained
from utils import train_transform, test_transform,initialize,smooth_crossentropy
from config import device
from ptflops import get_model_complexity_info
import torch.nn.functional as F
import torch.nn as nn
initial... | cmp_resnet.py | from os import X_OK
import torch
import torchvision
from net.cvt_offical import get_cvt13_pretrained
from utils import train_transform, test_transform,initialize,smooth_crossentropy
from config import device
from ptflops import get_model_complexity_info
import torch.nn.functional as F
import torch.nn as nn
initial... | 0.554712 | 0.386821 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['TransformArgs', 'Transform']
@pulumi.input_type
class TransformArgs:
def __init__(__self__, *,
... | sdk/python/pulumi_azure/media/transform.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _utilities
from . import outputs
from ._inputs import *
__all__ = ['TransformArgs', 'Transform']
@pulumi.input_type
class TransformArgs:
def __init__(__self__, *,
... | 0.85753 | 0.095307 |
import pandas as pd
import time
import numpy as np
import re
import os
import sys
import inspect
from pathlib import Path
# local modules
from fastsim import simdrive, vehicle, cycle
def main(use_jitclass=True, err_tol=1e-4):
"""Runs test test for 26 vehicles and 3 cycles.
Test compares cumulative positive... | fastsim-2021a/fastsim/tests/test26veh3cyc.py | import pandas as pd
import time
import numpy as np
import re
import os
import sys
import inspect
from pathlib import Path
# local modules
from fastsim import simdrive, vehicle, cycle
def main(use_jitclass=True, err_tol=1e-4):
"""Runs test test for 26 vehicles and 3 cycles.
Test compares cumulative positive... | 0.313735 | 0.341912 |
import pygame
from ..base import Manual
from ...enums import Effects
class ManualSquare(Manual):
inputs = {
'up': pygame.key.key_code('Z'),
'left': pygame.key.key_code('Q'),
'down': pygame.key.key_code('S'),
'right': pygame.key.key_code('D'),
}
def run_one_step(self, ke... | leveltwo/algorithm/square/manual.py | import pygame
from ..base import Manual
from ...enums import Effects
class ManualSquare(Manual):
inputs = {
'up': pygame.key.key_code('Z'),
'left': pygame.key.key_code('Q'),
'down': pygame.key.key_code('S'),
'right': pygame.key.key_code('D'),
}
def run_one_step(self, ke... | 0.810854 | 0.285602 |
import matplotlib.pyplot as plt
plt.rcParams['font.size']=6
import os
root_path = os.path.dirname(os.path.abspath('__file__'))
# root_path = os.path.abspath(os.path.join(root_path,os.path.pardir))
graphs_path = root_path+'/results_analysis/graphs/'
import sys
sys.path.append(root_path)
from plot_pacfs import plot_pacf... | results_analysis/plot_pacf_for_all.py | import matplotlib.pyplot as plt
plt.rcParams['font.size']=6
import os
root_path = os.path.dirname(os.path.abspath('__file__'))
# root_path = os.path.abspath(os.path.join(root_path,os.path.pardir))
graphs_path = root_path+'/results_analysis/graphs/'
import sys
sys.path.append(root_path)
from plot_pacfs import plot_pacf... | 0.238107 | 0.148541 |
import numpy as np
import cv2
import argparse
from collections import deque
import time
from pynput.keyboard import Key, Controller
class CameraCapture():
def __init__(self):
self.cap = cv2.VideoCapture(0)
self.Lower_green = np.array([110,50,50])
self.Upper_green = np.array([130,255,255])
... | new_try.py | import numpy as np
import cv2
import argparse
from collections import deque
import time
from pynput.keyboard import Key, Controller
class CameraCapture():
def __init__(self):
self.cap = cv2.VideoCapture(0)
self.Lower_green = np.array([110,50,50])
self.Upper_green = np.array([130,255,255])
... | 0.392919 | 0.200088 |
import glob
import os
from datetime import datetime
from enum import IntEnum, auto
from logging import Logger
from typing import Final, Optional, Union
import openpyxl
import pandas as pd
import python_lib_for_me as pyl
from openpyxl.worksheet.worksheet import Worksheet
from styleframe import StyleFrame, St... | src/fgo_farm_report_collection/logic/farm_report_gen_result_merge.py | import glob
import os
from datetime import datetime
from enum import IntEnum, auto
from logging import Logger
from typing import Final, Optional, Union
import openpyxl
import pandas as pd
import python_lib_for_me as pyl
from openpyxl.worksheet.worksheet import Worksheet
from styleframe import StyleFrame, St... | 0.330039 | 0.092647 |
from werkzeug.contrib.cache import (BaseCache, NullCache, SimpleCache, MemcachedCache,
GAEMemcachedCache, FileSystemCache)
class SASLMemcachedCache(MemcachedCache):
def __init__(self, servers=None, default_timeout=300, key_prefix=None,
username=None, password=<... | src/lib/flask_cache/backends.py | from werkzeug.contrib.cache import (BaseCache, NullCache, SimpleCache, MemcachedCache,
GAEMemcachedCache, FileSystemCache)
class SASLMemcachedCache(MemcachedCache):
def __init__(self, servers=None, default_timeout=300, key_prefix=None,
username=None, password=<... | 0.464173 | 0.047338 |
def setup():
try:
from importlib import metadata
except ImportError:
# Running on pre-3.8 Python; use importlib-metadata package
import importlib_metadata as metadata
import logging
from pathlib import Path
import os
import sys
import platform
logger = logging.ge... | nexxT/__init__.py | def setup():
try:
from importlib import metadata
except ImportError:
# Running on pre-3.8 Python; use importlib-metadata package
import importlib_metadata as metadata
import logging
from pathlib import Path
import os
import sys
import platform
logger = logging.ge... | 0.232746 | 0.127381 |
from abc import ABC, abstractmethod
from datetime import datetime
from functools import wraps
import re
from typing import Any, Callable, Dict, Iterable, TypeVar
from urllib.parse import urljoin, urlparse, urlunparse, urlencode
from urllib.request import Request
from calculate_anything.currency.data import CurrencyData... | calculate_anything/currency/providers/base.py | from abc import ABC, abstractmethod
from datetime import datetime
from functools import wraps
import re
from typing import Any, Callable, Dict, Iterable, TypeVar
from urllib.parse import urljoin, urlparse, urlunparse, urlencode
from urllib.request import Request
from calculate_anything.currency.data import CurrencyData... | 0.755005 | 0.14436 |
from typing import Any, Dict, List, Set, Type, Optional, TYPE_CHECKING
from hqlib.typing import MetricValue
from ..base import DomainObject
if TYPE_CHECKING: # pragma: no cover
# pylint: disable=unused-import
from .metric import Metric
from .metric_source import MetricSource
class MeasurableObject(Domai... | backend/hqlib/domain/measurement/measurable.py | from typing import Any, Dict, List, Set, Type, Optional, TYPE_CHECKING
from hqlib.typing import MetricValue
from ..base import DomainObject
if TYPE_CHECKING: # pragma: no cover
# pylint: disable=unused-import
from .metric import Metric
from .metric_source import MetricSource
class MeasurableObject(Domai... | 0.914721 | 0.201853 |
import sqlite3
class dbHandler:
DB_TABLE_MEMBER = 'members'
DB_MEMBER_ID = 'id'
DB_MEMBER_TAG = 'tag'
DB_MEMBER_NAME = 'name'
DB_MEMBER_KEY_STATUS = 'keyStatus'
DB_TABLE_BATTLES = 'battles'
DB_BATTLES_ID = 'id'
DB_BATTLES_KEY_MEMBERID = 'memberId'
DB_BATTLES_KEY_MATCH = 'keyMatch'
DB_BATTLES_KEY... | ClanWarStatsModule/dbHandler.py |
import sqlite3
class dbHandler:
DB_TABLE_MEMBER = 'members'
DB_MEMBER_ID = 'id'
DB_MEMBER_TAG = 'tag'
DB_MEMBER_NAME = 'name'
DB_MEMBER_KEY_STATUS = 'keyStatus'
DB_TABLE_BATTLES = 'battles'
DB_BATTLES_ID = 'id'
DB_BATTLES_KEY_MEMBERID = 'memberId'
DB_BATTLES_KEY_MATCH = 'keyMatch'
DB_BATTLES_KEY... | 0.285272 | 0.050401 |
from django.shortcuts import render
from django.http import HttpResponseRedirect
from .models import registration
from django.http import HttpResponse
from django.shortcuts import redirect
import requests
# base url database
url_root = 'https://search-build.herokuapp.com'
def delete(request):
"""
User delet... | users/views.py | from django.shortcuts import render
from django.http import HttpResponseRedirect
from .models import registration
from django.http import HttpResponse
from django.shortcuts import redirect
import requests
# base url database
url_root = 'https://search-build.herokuapp.com'
def delete(request):
"""
User delet... | 0.502197 | 0.075176 |
import os
from datetime import datetime
from urlparse import urlparse
from flask import Flask, render_template, request, redirect, url_for, flash, session
from flaskext.seasurf import SeaSurf
from flaskext.bcrypt import Bcrypt
from flaskext.gravatar import Gravatar
from functools import wraps
import settings
from mon... | flask-job-board/app.py | import os
from datetime import datetime
from urlparse import urlparse
from flask import Flask, render_template, request, redirect, url_for, flash, session
from flaskext.seasurf import SeaSurf
from flaskext.bcrypt import Bcrypt
from flaskext.gravatar import Gravatar
from functools import wraps
import settings
from mon... | 0.361954 | 0.065009 |
"""Tests for plaso.output.l2t_csv."""
import StringIO
import unittest
from plaso.formatters import interface as formatters_interface
from plaso.lib import event
from plaso.lib import eventdata
from plaso.output import dynamic
class TestEvent(event.EventObject):
DATA_TYPE = 'test:dynamic'
def __init__(self):
... | plaso/output/dynamic_test.py | """Tests for plaso.output.l2t_csv."""
import StringIO
import unittest
from plaso.formatters import interface as formatters_interface
from plaso.lib import event
from plaso.lib import eventdata
from plaso.output import dynamic
class TestEvent(event.EventObject):
DATA_TYPE = 'test:dynamic'
def __init__(self):
... | 0.630344 | 0.252316 |
from trad_chiffre_mot import tradn
import os
import numpy as np
from scipy.sparse import csr_matrix
import pandas as pd
from nltk.tag import StanfordPOSTagger
from nltk.tokenize import RegexpTokenizer
from keras import Input
from keras.layers import Bidirectional, LSTM, Dropout, RepeatVector, Concatenate, Dense, Activa... | lecture.py | from trad_chiffre_mot import tradn
import os
import numpy as np
from scipy.sparse import csr_matrix
import pandas as pd
from nltk.tag import StanfordPOSTagger
from nltk.tokenize import RegexpTokenizer
from keras import Input
from keras.layers import Bidirectional, LSTM, Dropout, RepeatVector, Concatenate, Dense, Activa... | 0.569613 | 0.448185 |
import logging
import pathlib
import tempfile
import pytest
from foodx_devops_tools.pipeline_config import PipelineConfiguration
from foodx_devops_tools.pipeline_config._checks import (
_file_exists,
do_path_check,
)
from tests.ci.support.pipeline_config import MOCK_PATHS, MOCK_SECRET
log = logging.getLogge... | tests/ci/unit_tests/pipeline_config/test_checks.py |
import logging
import pathlib
import tempfile
import pytest
from foodx_devops_tools.pipeline_config import PipelineConfiguration
from foodx_devops_tools.pipeline_config._checks import (
_file_exists,
do_path_check,
)
from tests.ci.support.pipeline_config import MOCK_PATHS, MOCK_SECRET
log = logging.getLogge... | 0.472197 | 0.241311 |
import multi_half_bridge_py as mhb
from time import sleep
# Tle94112 Object on Shield 1
controller = mhb.Tle94112Rpi()
# Tle94112motor Objects on controller
motor = mhb.Tle94112Motor(controller)
# Enable motorController on all Shields and motors
# Note: Required to be done before starting to configure the motor
# co... | src/framework/raspberrypi/examples_py/errorDiagnosis.py | import multi_half_bridge_py as mhb
from time import sleep
# Tle94112 Object on Shield 1
controller = mhb.Tle94112Rpi()
# Tle94112motor Objects on controller
motor = mhb.Tle94112Motor(controller)
# Enable motorController on all Shields and motors
# Note: Required to be done before starting to configure the motor
# co... | 0.45423 | 0.336808 |
import pytest
from collections import namedtuple
from region_cache import RegionCache
@pytest.fixture(params=[
{'REGION_CACHE_URL': 'redis://localhost:6379/5'},
{
'REGION_CACHE_URL': 'redis://localhost:6379/5',
'REGION_CACHE_RR_URL': 'redis://localhost:6379/5'
},
{
'REGION_CAC... | tests/test_region_cache.py | import pytest
from collections import namedtuple
from region_cache import RegionCache
@pytest.fixture(params=[
{'REGION_CACHE_URL': 'redis://localhost:6379/5'},
{
'REGION_CACHE_URL': 'redis://localhost:6379/5',
'REGION_CACHE_RR_URL': 'redis://localhost:6379/5'
},
{
'REGION_CAC... | 0.64646 | 0.284792 |
from __future__ import absolute_import
import sys
from gevent.pywsgi import WSGIServer as GeventWSGIServer
from slimta import logging
__all__ = ['WsgiServer']
log = logging.getHttpLogger(__name__)
class WsgiServer(object):
"""Implements the base class for a WSGI server that logs its requests and
response... | slimta/http/wsgi.py | from __future__ import absolute_import
import sys
from gevent.pywsgi import WSGIServer as GeventWSGIServer
from slimta import logging
__all__ = ['WsgiServer']
log = logging.getHttpLogger(__name__)
class WsgiServer(object):
"""Implements the base class for a WSGI server that logs its requests and
response... | 0.688259 | 0.247544 |
import asyncio
import logging
import random
import re
import string
import time
from copy import copy
from datetime import datetime, timedelta
import discord
from discord.errors import HTTPException
from typing import Union, List, Tuple, Literal
from redbot.core import Config, commands, checks
from redbot.core.utils i... | cash/cash.py | import asyncio
import logging
import random
import re
import string
import time
from copy import copy
from datetime import datetime, timedelta
import discord
from discord.errors import HTTPException
from typing import Union, List, Tuple, Literal
from redbot.core import Config, commands, checks
from redbot.core.utils i... | 0.655667 | 0.175009 |
from google.longrunning.operations_pb2 import (
CancelOperationRequest,
DeleteOperationRequest,
GetOperationRequest,
ListOperationsRequest,
ListOperationsResponse,
Operation,
google_dot_protobuf_dot_empty__pb2,
)
from grpc.beta import implementations as beta_implementations
from grpc.beta im... | Janaagraha Bot/venv/Lib/site-packages/gcloud/bigtable/_generated_v2/operations_grpc_pb2.py | from google.longrunning.operations_pb2 import (
CancelOperationRequest,
DeleteOperationRequest,
GetOperationRequest,
ListOperationsRequest,
ListOperationsResponse,
Operation,
google_dot_protobuf_dot_empty__pb2,
)
from grpc.beta import implementations as beta_implementations
from grpc.beta im... | 0.731538 | 0.138928 |
import os
import sys
import subprocess
import pickle
import numpy
from distutils.util import strtobool
from lib.Regression import Regression
class userInterface():
def __init__(self):
self.inputTitle = ['縣市', '鄉鎮市區',
'有無管理組織', '建物型態',
'土地移轉總面積平方公尺', '車... | lib/userInterface.py | import os
import sys
import subprocess
import pickle
import numpy
from distutils.util import strtobool
from lib.Regression import Regression
class userInterface():
def __init__(self):
self.inputTitle = ['縣市', '鄉鎮市區',
'有無管理組織', '建物型態',
'土地移轉總面積平方公尺', '車... | 0.147832 | 0.171876 |
from typing import Dict, List
from copy import deepcopy
import itertools
import numpy as np
from QCompute.QPlatform.QEnv import QEnv
from QCompute.QPlatform.QRegPool import QRegPool
from QCompute.QPlatform.QOperation.RotationGate import RX, RY
from QCompute.QPlatform.QOperation.FixedGate import H, S, CX
from QCompute.Q... | Example/QAPP/qapp/circuit/pauli_measurement_circuit.py | from typing import Dict, List
from copy import deepcopy
import itertools
import numpy as np
from QCompute.QPlatform.QEnv import QEnv
from QCompute.QPlatform.QRegPool import QRegPool
from QCompute.QPlatform.QOperation.RotationGate import RX, RY
from QCompute.QPlatform.QOperation.FixedGate import H, S, CX
from QCompute.Q... | 0.930054 | 0.617743 |
import re
filename = "input.txt"
valid_props = {
'byr',
'iyr',
'eyr',
'hgt',
'hcl',
'ecl',
'pid'
}
f = open(filename, 'r')
passports=[]
passport=''
for line in f.readlines():
line = line.strip()
passport = passport + line + ' '
if line == "":
passports.append(passport.... | day_4/passport_processing_part_2.py | import re
filename = "input.txt"
valid_props = {
'byr',
'iyr',
'eyr',
'hgt',
'hcl',
'ecl',
'pid'
}
f = open(filename, 'r')
passports=[]
passport=''
for line in f.readlines():
line = line.strip()
passport = passport + line + ' '
if line == "":
passports.append(passport.... | 0.117965 | 0.124426 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
from numba import jit
import numpy as np
import copy
import math
import hparams as hp
import utils
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
def get_sinusoid_encoding_table(n_position,... | modules.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
from numba import jit
import numpy as np
import copy
import math
import hparams as hp
import utils
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
def get_sinusoid_encoding_table(n_position,... | 0.914575 | 0.378057 |
import os
import argparse
import instrument_benchmark as bench
from statistics import mean, stdev
import numpy as np
import matplotlib.pyplot as plt
lout = None
def lprint(message):
print("{}".format(message))
if lout is not None:
lout.write("{}\n".format(message))
def plot(x, y, yerr, label, fna... | examples/execute.py |
import os
import argparse
import instrument_benchmark as bench
from statistics import mean, stdev
import numpy as np
import matplotlib.pyplot as plt
lout = None
def lprint(message):
print("{}".format(message))
if lout is not None:
lout.write("{}\n".format(message))
def plot(x, y, yerr, label, fna... | 0.409103 | 0.294722 |
from enum import Enum, auto
from typing import Optional
from shimmer.display.data_structures import Color
from shimmer.display.alignment import (
HorizontalAlignment,
VerticalAlignment,
)
from shimmer.display.components.box import Box, BoxDefinition
from shimmer.display.widgets.text_box import TextBoxDefinitio... | est8/frontend/card.py | from enum import Enum, auto
from typing import Optional
from shimmer.display.data_structures import Color
from shimmer.display.alignment import (
HorizontalAlignment,
VerticalAlignment,
)
from shimmer.display.components.box import Box, BoxDefinition
from shimmer.display.widgets.text_box import TextBoxDefinitio... | 0.753739 | 0.109658 |
_version_major = 0
_version_minor = 1
_version_micro = 0
_version_extra = '.dev'
def get_nipype_gitversion():
"""Nipype version as reported by the last commit in git
Returns
-------
None or str
Version of NiPype according to git.
"""
import os
import subprocess
try:
impor... | bips/info.py | _version_major = 0
_version_minor = 1
_version_micro = 0
_version_extra = '.dev'
def get_nipype_gitversion():
"""Nipype version as reported by the last commit in git
Returns
-------
None or str
Version of NiPype according to git.
"""
import os
import subprocess
try:
impor... | 0.497315 | 0.184768 |
import re
import pytz
import copy
from dateutil.parser import parse
import WHOIS_parser
from WHOIS_connect import WHOIS_srv_connect
utc_timezone = pytz.utc # 设置utc时区
CHOSE_WHOIS_server = WHOIS_parser.WHOIS_info_extract_func()
WHOIS_RECORD = {
"domain": "", # 域名
"tld": "", # 顶级域
"flag": "", # 状态标记
... | WHOISpy/WHOIS_info_extract.py | import re
import pytz
import copy
from dateutil.parser import parse
import WHOIS_parser
from WHOIS_connect import WHOIS_srv_connect
utc_timezone = pytz.utc # 设置utc时区
CHOSE_WHOIS_server = WHOIS_parser.WHOIS_info_extract_func()
WHOIS_RECORD = {
"domain": "", # 域名
"tld": "", # 顶级域
"flag": "", # 状态标记
... | 0.116512 | 0.198763 |
import os
import yaml
import logging
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
from flask_securest.userstores import simple
from flask_securest.constants import FLASK_SECUREST_LOGGER_NAME
class FileUserstore(simple.SimpleUserstore, FileSystemEventHandler):
def _... | flask_securest/userstores/file_userstore.py | import os
import yaml
import logging
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
from flask_securest.userstores import simple
from flask_securest.constants import FLASK_SECUREST_LOGGER_NAME
class FileUserstore(simple.SimpleUserstore, FileSystemEventHandler):
def _... | 0.293708 | 0.062646 |
from wand.image import Image
from wand.drawing import Drawing
from wand.color import Color
import os
# this is original code.
font_normal = 'Noto-Sans'
font_italic = 'Noto-Sans-Italic'
font_bold = 'Noto-Sans-Bold'
if os.name == 'nt':
font_normal = 'Arial'
font_italic = 'Arial-Italic'
font_bold = 'Arial-B... | examples/text/sample14_more_attributes.py |
from wand.image import Image
from wand.drawing import Drawing
from wand.color import Color
import os
# this is original code.
font_normal = 'Noto-Sans'
font_italic = 'Noto-Sans-Italic'
font_bold = 'Noto-Sans-Bold'
if os.name == 'nt':
font_normal = 'Arial'
font_italic = 'Arial-Italic'
font_bold = 'Arial-B... | 0.429429 | 0.083404 |
import time
import pickle
import os.path
import re
from talon import (
Module,
Context,
actions,
registry,
)
from talon.grammar import Phrase
from talon import speech_system, Context
from talon.engines.vosk import VoskEngine
vosk_de = VoskEngine(model="vosk-model-small-de-0.15", language="de_DE")
vos... | adabru_talon/code/german.py |
import time
import pickle
import os.path
import re
from talon import (
Module,
Context,
actions,
registry,
)
from talon.grammar import Phrase
from talon import speech_system, Context
from talon.engines.vosk import VoskEngine
vosk_de = VoskEngine(model="vosk-model-small-de-0.15", language="de_DE")
vos... | 0.227813 | 0.102979 |
from __future__ import division
from __future__ import print_function
import os
import argparse
from argparse import Namespace
import array
import numpy as np
from scipy import signal
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import mlab
from myhdl import *
def _prep_... | examples/ex4_mathsop/test_verilogs/test_mathsop.py |
from __future__ import division
from __future__ import print_function
import os
import argparse
from argparse import Namespace
import array
import numpy as np
from scipy import signal
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import mlab
from myhdl import *
def _prep_... | 0.524882 | 0.372448 |
from subprocess import call
import pexpect
class LinuxInit():
def __init__(self):
pass
# 0.更新源和软件
def update_env(self):
# cmd = "sudo apt-get update;sudo apt-get upgrade;sudo apt-get install -y python-dev"
install_cmd = "sudo apt-get install -y python-dev"
process = pexpec... | linux_init/linux_init.py | from subprocess import call
import pexpect
class LinuxInit():
def __init__(self):
pass
# 0.更新源和软件
def update_env(self):
# cmd = "sudo apt-get update;sudo apt-get upgrade;sudo apt-get install -y python-dev"
install_cmd = "sudo apt-get install -y python-dev"
process = pexpec... | 0.280222 | 0.054224 |
import requests
import json
import sys
#get the secrets from your Google Cloud project, use the Oauth2 Playground for your refresh token
client_id=sys.argv[1]
client_secret=sys.argv[2]
refresh_token=sys.argv[3]
credentials=sys.argv[4]
def get_list_from_file(filename):
try:
# open and read the file into lis... | google-workspace/offboarding-email-archive/python/google-vault-offboarding.py | import requests
import json
import sys
#get the secrets from your Google Cloud project, use the Oauth2 Playground for your refresh token
client_id=sys.argv[1]
client_secret=sys.argv[2]
refresh_token=sys.argv[3]
credentials=sys.argv[4]
def get_list_from_file(filename):
try:
# open and read the file into lis... | 0.056165 | 0.114517 |
from typing import Mapping, Any, Type, Callable, Optional
import abc
import torch as tc
from drl.agents.heads.abstract import Head
from drl.agents.architectures.stateless.abstract import HeadEligibleArchitecture
class ValueHead(Head, metaclass=abc.ABCMeta):
"""
Value head abstract class.
"""
class Sim... | drl/agents/heads/value_heads.py | from typing import Mapping, Any, Type, Callable, Optional
import abc
import torch as tc
from drl.agents.heads.abstract import Head
from drl.agents.architectures.stateless.abstract import HeadEligibleArchitecture
class ValueHead(Head, metaclass=abc.ABCMeta):
"""
Value head abstract class.
"""
class Sim... | 0.94325 | 0.326781 |
revision = '7829789fc19c'
down_revision = 'cf<PASSWORD>b<PASSWORD>'
branch_labels = None
depends_on = None
from alembic import op
import sqlalchemy as sa
table_name = 'permissions_system'
column_name = 'permission'
type_name = 'sys_perms'
tmp_type_name = f"tmp_{type_name}"
old_options = ('SUPERUSER', )
new_options ... | web/server/codechecker_server/migrations/config/versions/7829789fc19c_global_permission_to_get_access_controls.py | revision = '7829789fc19c'
down_revision = 'cf<PASSWORD>b<PASSWORD>'
branch_labels = None
depends_on = None
from alembic import op
import sqlalchemy as sa
table_name = 'permissions_system'
column_name = 'permission'
type_name = 'sys_perms'
tmp_type_name = f"tmp_{type_name}"
old_options = ('SUPERUSER', )
new_options ... | 0.425725 | 0.111096 |
import os
import re
import argparse
import glob
def slurp_file(path):
data = ''
try:
with open(path, 'r') as fin:
data = fin.read()
except IOError:
pass
if not (data and not data.isspace()):
assent = input('Warning: ' + path + ' is empty; do you want to continue? [y... | tools/codegen/update_hdr_ftr_adoc.py | import os
import re
import argparse
import glob
def slurp_file(path):
data = ''
try:
with open(path, 'r') as fin:
data = fin.read()
except IOError:
pass
if not (data and not data.isspace()):
assent = input('Warning: ' + path + ' is empty; do you want to continue? [y... | 0.234407 | 0.110807 |
from util import database, toolchain, bitdiff, progress
with database.transact() as db:
for device_name, device in db.items():
progress(device_name)
package, pinout = next(iter(device['pins'].items()))
gclk3_pad = device['specials']['CLK3']
gclr_switch = device['globals']['GCLR']
... | fuzzers/028-gnet_invert/fuzzer.py | from util import database, toolchain, bitdiff, progress
with database.transact() as db:
for device_name, device in db.items():
progress(device_name)
package, pinout = next(iter(device['pins'].items()))
gclk3_pad = device['specials']['CLK3']
gclr_switch = device['globals']['GCLR']
... | 0.316158 | 0.255657 |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import CubicSpline
import json
"""
Please download the original bus signals data of each city from a2d2: https://www.a2d2.audi/a2d2/en/download.html
the available locations are "Gaimersheim", "Munich" and "Ingolstadt"
and ... | Clustering_approach/Data_interpolation.py | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import CubicSpline
import json
"""
Please download the original bus signals data of each city from a2d2: https://www.a2d2.audi/a2d2/en/download.html
the available locations are "Gaimersheim", "Munich" and "Ingolstadt"
and ... | 0.28897 | 0.577019 |
import argparse as arp
import os
import numpy as np
from reinforcement_learning import logger
from reinforcement_learning.gym.envs.donkey_car.donkey_env import DonkeyEnv
from reinforcement_learning.common.callbacks import CheckpointCallback
from reinforcement_learning.common.vec_env.subproc_vec_env import SubprocVecE... | train_expert_donkey.py | import argparse as arp
import os
import numpy as np
from reinforcement_learning import logger
from reinforcement_learning.gym.envs.donkey_car.donkey_env import DonkeyEnv
from reinforcement_learning.common.callbacks import CheckpointCallback
from reinforcement_learning.common.vec_env.subproc_vec_env import SubprocVecE... | 0.452536 | 0.200323 |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='MenuDetail',
fields=[
('id', models.AutoField(auto_created... | core/migrations/0001_initial.py |
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='MenuDetail',
fields=[
('id', models.AutoField(auto_created... | 0.510496 | 0.140248 |
import os.path
from typing import List, Optional, Tuple
import tensorflow as tf
from mlagents_envs.side_channel.engine_configuration_channel import EngineConfigurationChannel # type: ignore
from mlagents_envs.side_channel.environment_parameters_channel import EnvironmentParametersChannel # type: ignore
from tensorfl... | project/learner.py | import os.path
from typing import List, Optional, Tuple
import tensorflow as tf
from mlagents_envs.side_channel.engine_configuration_channel import EngineConfigurationChannel # type: ignore
from mlagents_envs.side_channel.environment_parameters_channel import EnvironmentParametersChannel # type: ignore
from tensorfl... | 0.885983 | 0.257888 |
from typing import Any, Union, ClassVar, NoReturn, Optional
from pathlib import Path
from urllib.parse import urlparse
import configparser
import attr
from omnipath.constants import License
from omnipath._core.cache._cache import Cache, FileCache, NoopCache, MemoryCache
from omnipath.constants._pkg_constants import D... | omnipath/_core/utils/_options.py | from typing import Any, Union, ClassVar, NoReturn, Optional
from pathlib import Path
from urllib.parse import urlparse
import configparser
import attr
from omnipath.constants import License
from omnipath._core.cache._cache import Cache, FileCache, NoopCache, MemoryCache
from omnipath.constants._pkg_constants import D... | 0.944203 | 0.239572 |
# namespace: FBOutput
import tdw.flatbuffers
class AvatarSimpleBody(object):
__slots__ = ['_tab']
@classmethod
def GetRootAsAvatarSimpleBody(cls, buf, offset):
n = tdw.flatbuffers.encode.Get(tdw.flatbuffers.packer.uoffset, buf, offset)
x = AvatarSimpleBody()
x.Init(bu... | Python/tdw/FBOutput/AvatarSimpleBody.py |
# namespace: FBOutput
import tdw.flatbuffers
class AvatarSimpleBody(object):
__slots__ = ['_tab']
@classmethod
def GetRootAsAvatarSimpleBody(cls, buf, offset):
n = tdw.flatbuffers.encode.Get(tdw.flatbuffers.packer.uoffset, buf, offset)
x = AvatarSimpleBody()
x.Init(bu... | 0.620047 | 0.235366 |
import pytest
from eth_abi.exceptions import (
ValueOutOfBounds,
)
from hypothesis import (
given,
strategies as st,
)
from web3._utils.events import (
DataArgumentFilter,
TopicArgumentFilter,
normalize_topic_list,
)
@pytest.mark.parametrize(
"topic_list,expected",
(
(
... | tests/core/utilities/test_event_filter_builder.py | import pytest
from eth_abi.exceptions import (
ValueOutOfBounds,
)
from hypothesis import (
given,
strategies as st,
)
from web3._utils.events import (
DataArgumentFilter,
TopicArgumentFilter,
normalize_topic_list,
)
@pytest.mark.parametrize(
"topic_list,expected",
(
(
... | 0.501953 | 0.560403 |
import os
from unittest import TestCase
from unittest.mock import MagicMock, patch
import gensim
from word_vectorizer.models.model_data import ModelData
from word_vectorizer.models.word2vec_vectorizer import Word2VecVectorizer
class TestWord2VecVectorizer(TestCase):
FOLDER_FOR_MODELS = os.path.join(os.path.dirn... | word_vectorizer/tests/unittest/models/test_word2VecVectorizer.py | import os
from unittest import TestCase
from unittest.mock import MagicMock, patch
import gensim
from word_vectorizer.models.model_data import ModelData
from word_vectorizer.models.word2vec_vectorizer import Word2VecVectorizer
class TestWord2VecVectorizer(TestCase):
FOLDER_FOR_MODELS = os.path.join(os.path.dirn... | 0.46952 | 0.273527 |
import smtplib
import re
import redis
class Emailer:
"""
Function description :
sends an email given certain details patterned from http://stackoverflow.com/questions/10147455/trying-to-send-email-gmail-as-mail-provider-using-python
Parameters:
details -> a dictionary that contains user info and email ifo
a... | modules/emailer/emailer.py | import smtplib
import re
import redis
class Emailer:
"""
Function description :
sends an email given certain details patterned from http://stackoverflow.com/questions/10147455/trying-to-send-email-gmail-as-mail-provider-using-python
Parameters:
details -> a dictionary that contains user info and email ifo
a... | 0.237576 | 0.235988 |
import os
import boto3
import logging
import datetime
import re
import time
__author__ = '<NAME> (<EMAIL>)'
__copyright__ = 'Shine Solutions'
__license__ = 'Apache License, Version 2.0'
# setting up logger
logger = logging.getLogger(__name__)
logger.setLevel(int(os.getenv('LOG_LEVEL', logging.INFO)))
def purge_ol... | lambda/purge_snapshots.py | import os
import boto3
import logging
import datetime
import re
import time
__author__ = '<NAME> (<EMAIL>)'
__copyright__ = 'Shine Solutions'
__license__ = 'Apache License, Version 2.0'
# setting up logger
logger = logging.getLogger(__name__)
logger.setLevel(int(os.getenv('LOG_LEVEL', logging.INFO)))
def purge_ol... | 0.269133 | 0.152631 |
import gym
import numpy as np
import matplotlib.pyplot as plt
from itertools import product
from gym import error, spaces, utils
from gym.utils import seeding
class MullerBrownContinuousEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self):
# state space
self.x_min = -1.5
... | gym_muller_brown/envs/muller_brown_continuous.py | import gym
import numpy as np
import matplotlib.pyplot as plt
from itertools import product
from gym import error, spaces, utils
from gym.utils import seeding
class MullerBrownContinuousEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self):
# state space
self.x_min = -1.5
... | 0.685739 | 0.386706 |
from . import testcases
from testing.testcases import tc_path_plan_a_star as testcase
from logger.logger import logger
import time
class test_planner(object):
'''
classdocs
'''
def __init__(self):
'''
Constructor
'''
self.list_tc = {}
self.lis... | src/testing/test_planner.py | from . import testcases
from testing.testcases import tc_path_plan_a_star as testcase
from logger.logger import logger
import time
class test_planner(object):
'''
classdocs
'''
def __init__(self):
'''
Constructor
'''
self.list_tc = {}
self.lis... | 0.18159 | 0.102709 |
import subprocess
import argparse
import sys
import os
import shutil
import time
import friendlytoml as toml
config = toml.load(os.path.join(os.path.dirname(__file__), "publish_rust.toml"))
HOME = os.environ["HOME"]
PROJECT_FOLDER = os.path.join(HOME, os.path.join(*config["dir"]["rust"]))
USER = config["user"]
GITHUB... | publish_rust.py | import subprocess
import argparse
import sys
import os
import shutil
import time
import friendlytoml as toml
config = toml.load(os.path.join(os.path.dirname(__file__), "publish_rust.toml"))
HOME = os.environ["HOME"]
PROJECT_FOLDER = os.path.join(HOME, os.path.join(*config["dir"]["rust"]))
USER = config["user"]
GITHUB... | 0.275032 | 0.091139 |
from flask import Blueprint, flash, jsonify, request, redirect, render_template, session, url_for
from flask_login import login_required, current_user
from ims.common.ComboBoxUtil import getComCategoryList
from ims.common.Messages import Messages
from ims.common.RoleUtil import admin_required
from ims.contents.comCont... | ims/views/masterData.py | from flask import Blueprint, flash, jsonify, request, redirect, render_template, session, url_for
from flask_login import login_required, current_user
from ims.common.ComboBoxUtil import getComCategoryList
from ims.common.Messages import Messages
from ims.common.RoleUtil import admin_required
from ims.contents.comCont... | 0.380759 | 0.21211 |
# Python modules
from __future__ import absolute_import
import socket
# Third-party modules
import tornado.gen
import tornado.iostream
from tornado.concurrent import TracebackFuture
# NOC modules
from .base import CLI
from .telnet import TelnetIOStream
class BeefCLI(CLI):
name = "beef_cli"
default_port = 2... | core/script/cli/beef.py |
# Python modules
from __future__ import absolute_import
import socket
# Third-party modules
import tornado.gen
import tornado.iostream
from tornado.concurrent import TracebackFuture
# NOC modules
from .base import CLI
from .telnet import TelnetIOStream
class BeefCLI(CLI):
name = "beef_cli"
default_port = 2... | 0.614625 | 0.087097 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import unittest
import click
import click.testing
import mock
import treadmill
from treadmill import plugin_manager
from treadmill.admin import exc as admin_exceptions
... | lib/python/treadmill/tests/cli/admin/ldap/allocation_test.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import unittest
import click
import click.testing
import mock
import treadmill
from treadmill import plugin_manager
from treadmill.admin import exc as admin_exceptions
... | 0.700485 | 0.16398 |
import numpy as np
from astropy import units as u
import os
from uclahedp.tools import csv as csvtools
from uclahedp.tools import hdf as hdftools
from uclahedp.tools import util
import h5py
def hrrToRaw( run, probe, hdf_dir, csv_dir, dest, verbose=False, debug=False):
""" Retreives the appropriate metadata for ... | uclahedp/load/hrr.py | import numpy as np
from astropy import units as u
import os
from uclahedp.tools import csv as csvtools
from uclahedp.tools import hdf as hdftools
from uclahedp.tools import util
import h5py
def hrrToRaw( run, probe, hdf_dir, csv_dir, dest, verbose=False, debug=False):
""" Retreives the appropriate metadata for ... | 0.30965 | 0.389488 |
from unittest import TestCase
from daylio_parser.config import (
DEFAULT_COLOR_PALETTE,
DEFAULT_MOODS,
Mood,
MoodConfig,
MoodNotFound,
)
class TestConfig(TestCase):
def test_default_mood_list(self):
"""Test that the default config contains 5 moods with known boundaries."""
m... | tests/test_config.py |
from unittest import TestCase
from daylio_parser.config import (
DEFAULT_COLOR_PALETTE,
DEFAULT_MOODS,
Mood,
MoodConfig,
MoodNotFound,
)
class TestConfig(TestCase):
def test_default_mood_list(self):
"""Test that the default config contains 5 moods with known boundaries."""
m... | 0.834036 | 0.514705 |
import numpy as np # linear algebra
np.set_printoptions(threshold=np.nan)
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directo... | kaggle-ml/quora/kernel.py |
import numpy as np # linear algebra
np.set_printoptions(threshold=np.nan)
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
# Input data files are available in the "../input/" directory.
# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directo... | 0.55447 | 0.245384 |
from typing import List
# MONAD = "Reader"
MONAD = "State"
PARAM = MONAD[0]
def generic(i: int) -> str:
return chr(i + ord("A"))
def arg(i: int) -> str:
return chr(i + ord("a"))
def arg2(i: int) -> str:
return arg(i) + "2"
def generics(i: int) -> List[str]:
return [generic(i) for i in range(0, ... | GenCode.py | from typing import List
# MONAD = "Reader"
MONAD = "State"
PARAM = MONAD[0]
def generic(i: int) -> str:
return chr(i + ord("A"))
def arg(i: int) -> str:
return chr(i + ord("a"))
def arg2(i: int) -> str:
return arg(i) + "2"
def generics(i: int) -> List[str]:
return [generic(i) for i in range(0, ... | 0.629888 | 0.536738 |
__author__ = "<NAME>"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__copyright__ = "Copyright (C) 2020, Nokia"
__license__ = "BSD-3"
from pybgl.automaton import Automaton, alphabet, add_vertex, add_edge, delta, set_final
from pybgl.nfa import Nfa, initials, is_final, sigma
def moore_deter... | pybgl/moore_determination.py |
__author__ = "<NAME>"
__maintainer__ = "<NAME>"
__email__ = "<EMAIL>"
__copyright__ = "Copyright (C) 2020, Nokia"
__license__ = "BSD-3"
from pybgl.automaton import Automaton, alphabet, add_vertex, add_edge, delta, set_final
from pybgl.nfa import Nfa, initials, is_final, sigma
def moore_deter... | 0.790732 | 0.353847 |
import ctypes
import io
import os
import struct
import sys
from contextlib import contextmanager
from . import mcclient_const as const
from . import mcclient_types as types
if 'sphinx' in sys.modules:
client = None
else:
client = types.load_library()
if client is None:
raise ImportError("ERROR: ... | bindings/mcclient/mcclient.py | import ctypes
import io
import os
import struct
import sys
from contextlib import contextmanager
from . import mcclient_const as const
from . import mcclient_types as types
if 'sphinx' in sys.modules:
client = None
else:
client = types.load_library()
if client is None:
raise ImportError("ERROR: ... | 0.617513 | 0.201892 |
import logging as log
import numpy as np
import random
log.basicConfig(format="%(message)s", level=log.INFO)
def load_data(file_path):
"""加载数据
源数据格式为多行，每行为两个浮点数，分别表示 (x,y)
"""
data = []
with open(file_path, 'r', encoding='utf-8') as fr:
for line in fr.read().splitlines():
... | _codes/machine_learning/KMeans/kmeans.py | import logging as log
import numpy as np
import random
log.basicConfig(format="%(message)s", level=log.INFO)
def load_data(file_path):
"""加载数据
源数据格式为多行，每行为两个浮点数，分别表示 (x,y)
"""
data = []
with open(file_path, 'r', encoding='utf-8') as fr:
for line in fr.read().splitlines():
... | 0.242564 | 0.370738 |
import os
from typing import Optional, Sequence, Dict, List
from csr.exceptions import ReaderException
from sources2csr.ngs import AnalysisType, NGS, LibraryStrategy
class NgsReader:
"""Reader that reads NGS data files.
"""
def __init__(self, input_dir: str, library_strategy: LibraryStrategy):
se... | sources2csr/ngs_reader.py | import os
from typing import Optional, Sequence, Dict, List
from csr.exceptions import ReaderException
from sources2csr.ngs import AnalysisType, NGS, LibraryStrategy
class NgsReader:
"""Reader that reads NGS data files.
"""
def __init__(self, input_dir: str, library_strategy: LibraryStrategy):
se... | 0.825836 | 0.331471 |
from pyhunt.deploy import WMIEXEC
from pyhunt.deploy_smb import CMDEXEC
from multiprocessing import Process, Pool
from time import sleep
class HuntScan:
def __init__(self, usr, pwd, domain, hashes=''):
self.targets = []
self.__currentpath = ''
self.surveyfile = "survey/survey.ps1"
s... | scan.py | from pyhunt.deploy import WMIEXEC
from pyhunt.deploy_smb import CMDEXEC
from multiprocessing import Process, Pool
from time import sleep
class HuntScan:
def __init__(self, usr, pwd, domain, hashes=''):
self.targets = []
self.__currentpath = ''
self.surveyfile = "survey/survey.ps1"
s... | 0.240329 | 0.070624 |
import os
import geopandas as gpd
import numpy as np
import pandas as pd
from prereise.gather.demanddata.bldg_electrification import const
def aggregate_puma_df(
puma_states, tract_puma_mapping, tract_gbs_area, tract_degday_normals, tract_pop
):
"""Scale census tract data up to puma areas.
:param panda... | prereise/gather/demanddata/bldg_electrification/puma_data_agg.py | import os
import geopandas as gpd
import numpy as np
import pandas as pd
from prereise.gather.demanddata.bldg_electrification import const
def aggregate_puma_df(
puma_states, tract_puma_mapping, tract_gbs_area, tract_degday_normals, tract_pop
):
"""Scale census tract data up to puma areas.
:param panda... | 0.764892 | 0.402744 |