text stringlengths 0 1.05M | meta dict |
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from __future__ import absolute_import, division, print_function
import os
import sys
import subprocess
import uuid
import mmap
from tempfile import NamedTemporaryFile
from contextlib import closing
from functools import partial
from distutils.spawn import find_executable
import pandas as pd
from pandas.formats.form... | {
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"path": "odo/backends/sql_csv.py",
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"config_test"... |
from __future__ import absolute_import, division, print_function
import os
import sys
import subprocess
import uuid
import mmap
from contextlib import closing
from functools import partial
from distutils.spawn import find_executable
import sqlalchemy as sa
from sqlalchemy.ext.compiler import compiles
from sqlalchemy... | {
"repo_name": "cpcloud/odo",
"path": "odo/backends/sql_csv.py",
"copies": "1",
"size": "8019",
"license": "bsd-3-clause",
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from __future__ import absolute_import, division, print_function
import os
import sys
import subprocess
from setuptools import setup, find_packages
from codecs import open
from os import path
from huckle import package
from huckle import hutils
if sys.argv[-1] == 'publish':
branch = subprocess.check_output('git ... | {
"repo_name": "cometaj2/huckle",
"path": "setup.py",
"copies": "1",
"size": "2602",
"license": "mit",
"hash": 7998725660022406000,
"line_mean": 36.1714285714,
"line_max": 133,
"alpha_frac": 0.6299000769,
"autogenerated": false,
"ratio": 3.7874818049490537,
"config_test": false,
"has_no_keywor... |
from __future__ import absolute_import, division, print_function
import os
import sys
import tensorflow.compat.v1 as tfv1
from attrdict import AttrDict
from xdg import BaseDirectory as xdg
from src.flags import FLAGS
from .gpu import get_available_gpus
from .logging import log_error
from .text import Alphabet, UTF8A... | {
"repo_name": "googleinterns/deepspeech-reconstruction",
"path": "src/deepspeech_training/util/config.py",
"copies": "1",
"size": "5748",
"license": "apache-2.0",
"hash": 2776932445715784000,
"line_mean": 37.32,
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"alpha_frac": 0.6475295755,
"autogenerated": false,
"ratio": 3.80410... |
from __future__ import absolute_import, division, print_function
import os
import sys
import threading
import queue
import numpy as np
from util import text_processing
class BatchLoaderClevr:
def __init__(self, imdb, data_params):
self.imdb = imdb
self.data_params = data_params
self.voca... | {
"repo_name": "ronghanghu/n2nmn",
"path": "util/clevr_train/data_reader.py",
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"ratio": 3.7498532002348797,
"con... |
from __future__ import absolute_import, division, print_function
import os
import sys
import threading
import queue
import numpy as np
from util import text_processing
class BatchLoaderVqa:
def __init__(self, imdb, data_params):
self.imdb = imdb
self.data_params = data_params
self.vocab_... | {
"repo_name": "ronghanghu/n2nmn",
"path": "util/vqa_train/data_reader.py",
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"autogenerated": false,
"ratio": 3.807973664959766,
"config... |
from __future__ import absolute_import, division, print_function
import os
import sys
import time
import timeit
import math
import numpy as np
import PIL.Image as Image
from scipy.stats import spearmanr
from scipy.stats import pearsonr
from scipy.stats import kendalltau
from .utils import tile_raster_images, image_f... | {
"repo_name": "jongyookim/IQA_BIECON_release",
"path": "IQA_BIECON_release/trainer.py",
"copies": "1",
"size": "27661",
"license": "mit",
"hash": 5576336438958596000,
"line_mean": 41.4248466258,
"line_max": 79,
"alpha_frac": 0.4845811793,
"autogenerated": false,
"ratio": 3.6073291601460618,
"co... |
from __future__ import absolute_import, division, print_function
import os
import sys
import unittest
from pathlib import Path
import numpy as np
from sprocket.util.hdf5 import HDF5
dirpath = os.path.dirname(os.path.realpath(__file__))
listf = os.path.join(dirpath, '/data/test.h5')
class hdf5FunctionsTest(unittes... | {
"repo_name": "k2kobayashi/sprocket",
"path": "sprocket/util/tests/test_hdf5.py",
"copies": "1",
"size": "1977",
"license": "mit",
"hash": -9121286587846112000,
"line_mean": 27.652173913,
"line_max": 101,
"alpha_frac": 0.5700556399,
"autogenerated": false,
"ratio": 2.9729323308270676,
"config_t... |
from __future__ import absolute_import, division, print_function
import os
import sys
import unittest
import tempfile
from itertools import product as it_product
import blaze
from blaze.datadescriptor import dd_as_py
blaze.set_strategy('jit')
import numpy as np
from numpy.testing import assert_allclose
def _clean... | {
"repo_name": "zeeshanali/blaze",
"path": "blaze/tests/test_eval.py",
"copies": "2",
"size": "5802",
"license": "bsd-3-clause",
"hash": -3369850830092426000,
"line_mean": 26.7607655502,
"line_max": 75,
"alpha_frac": 0.5501551189,
"autogenerated": false,
"ratio": 3.1584104518236256,
"config_test... |
from __future__ import absolute_import, division, print_function
import os
import sys
from cffi import FFI
include_dirs = [os.path.join("extras", "libargon2", "include")]
use_system_argon2 = os.environ.get("ARGON2_CFFI_USE_SYSTEM", "0") == "1"
if use_system_argon2:
include_dirs = []
# Add vendored integer type... | {
"repo_name": "sserrot/champion_relationships",
"path": "venv/Lib/site-packages/argon2/_ffi_build.py",
"copies": "2",
"size": "5277",
"license": "mit",
"hash": -6346051924984462000,
"line_mean": 26.6282722513,
"line_max": 75,
"alpha_frac": 0.6109531931,
"autogenerated": false,
"ratio": 2.96127946... |
from __future__ import absolute_import, division, print_function
import os
import sys
from conda.base.context import context
from conda.cli.conda_argparse import ArgumentParser
from conda.cli.main import init_loggers
from conda.gateways.logging import initialize_logging
try:
from conda.exceptions import conda_ex... | {
"repo_name": "Microsoft/PTVS",
"path": "Python/Product/Miniconda/Miniconda3-x64/Lib/site-packages/conda_env/cli/main.py",
"copies": "1",
"size": "2566",
"license": "apache-2.0",
"hash": 527158863517042600,
"line_mean": 27.8314606742,
"line_max": 72,
"alpha_frac": 0.7116134061,
"autogenerated": fal... |
from __future__ import absolute_import, division, print_function
import os
import sys
from ginga import cmap as ginga_cmap
from qtpy import QtGui, QtWidgets
from glue.config import viewer_tool
from glue.viewers.common.qt.tool import CheckableTool, Tool
from glue.plugins.ginga_viewer.qt.utils import cmap2pixmap, ging... | {
"repo_name": "saimn/glue",
"path": "glue/plugins/ginga_viewer/qt/mouse_modes.py",
"copies": "1",
"size": "6049",
"license": "bsd-3-clause",
"hash": -4377492188591445000,
"line_mean": 23.8930041152,
"line_max": 80,
"alpha_frac": 0.639940486,
"autogenerated": false,
"ratio": 3.34383637368712,
"c... |
from __future__ import absolute_import, division, print_function
import os
import sys
from pudb.py3compat import PY3
if PY3:
from configparser import ConfigParser
else:
from ConfigParser import ConfigParser
# minor LGPL violation: stolen from python-xdg
_home = os.environ.get('HOME', None)
xdg_data_home = o... | {
"repo_name": "albfan/pudb",
"path": "pudb/settings.py",
"copies": "1",
"size": "16295",
"license": "mit",
"hash": 7966609117641069000,
"line_mean": 31.2673267327,
"line_max": 84,
"alpha_frac": 0.5655108929,
"autogenerated": false,
"ratio": 3.8179475164011247,
"config_test": true,
"has_no_key... |
from __future__ import absolute_import, division, print_function
import os
import sys
from setuptools import setup, Extension
try:
from Cython.Distutils import build_ext
from Cython.Build import cythonize
except ImportError:
print("Could not import Cython. Install `cython` and rerun.")
sys.exit(1)
e... | {
"repo_name": "filonik/clibs",
"path": "setup.py",
"copies": "1",
"size": "3025",
"license": "mit",
"hash": 4576642634832667600,
"line_mean": 35.4578313253,
"line_max": 109,
"alpha_frac": 0.6476033058,
"autogenerated": false,
"ratio": 2.91988416988417,
"config_test": false,
"has_no_keywords":... |
from __future__ import absolute_import, division, print_function
import os
import sys
from virtualenv.builders.legacy import LegacyBuilder
from virtualenv.builders.venv import VenvBuilder
from virtualenv.flavors.posix import PosixFlavor
from virtualenv.flavors.windows import WindowsFlavor
def select_flavor():
#... | {
"repo_name": "ionelmc/virtualenv",
"path": "virtualenv/core.py",
"copies": "1",
"size": "1845",
"license": "mit",
"hash": 3673681554003491000,
"line_mean": 33.8113207547,
"line_max": 87,
"alpha_frac": 0.718699187,
"autogenerated": false,
"ratio": 4.392857142857143,
"config_test": false,
"has... |
from __future__ import (absolute_import, division, print_function)
import os
import sys
import netCDF4
import ruamel.yaml as yaml
from six import raise_from
from docopt import docopt
__all__ = [
'main',
'build'
]
__doc__ = """
Generate ncml based on a yaml file.
Usage:
yaml2ncml INFILE [--output=O... | {
"repo_name": "ocefpaf/yaml2ncml",
"path": "yaml2ncml/yaml2ncml.py",
"copies": "1",
"size": "8605",
"license": "mit",
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"line_mean": 31.8435114504,
"line_max": 99,
"alpha_frac": 0.5764090645,
"autogenerated": false,
"ratio": 3.469758064516129,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), '..'))
import decatur
from decatur import config, utils
###########################... | {
"repo_name": "jlurie/decatur",
"path": "tests/paper.py",
"copies": "1",
"size": "9876",
"license": "mit",
"hash": 3658238776590735400,
"line_mean": 39.1463414634,
"line_max": 84,
"alpha_frac": 0.3828473066,
"autogenerated": false,
"ratio": 4.660689004247287,
"config_test": false,
"has_no_key... |
from __future__ import absolute_import, division, print_function
import os
import sys
try:
import sphinx_rtd_theme
except ImportError:
sphinx_rtd_theme = None
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative... | {
"repo_name": "grigouze/symantecssl",
"path": "docs/conf.py",
"copies": "5",
"size": "3873",
"license": "apache-2.0",
"hash": -2321553010709284400,
"line_mean": 28.3409090909,
"line_max": 79,
"alpha_frac": 0.6493674154,
"autogenerated": false,
"ratio": 3.8614157527417747,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import os
import tempfile
import unittest
import warnings
import blaze
from blaze.datadescriptor import dd_as_py
# A CSV toy example
csv_buf = u"""k1,v1,1,False
k2,v2,2,True
k3,v3,3,False
"""
csv_schema = "{ f0: string; f1: string; f2: int16; f3: bool... | {
"repo_name": "aburan28/blaze",
"path": "blaze/tests/test_array_opening.py",
"copies": "7",
"size": "3020",
"license": "bsd-3-clause",
"hash": -7763266689859111000,
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"alpha_frac": 0.5887417219,
"autogenerated": false,
"ratio": 2.814538676607642,
"confi... |
from __future__ import absolute_import, division, print_function
import os
import tempfile
import unittest
import blaze
from blaze.datadescriptor import dd_as_py
# A CSV toy example
csv_buf = u"""k1,v1,1,False
k2,v2,2,True
k3,v3,3,False
"""
csv_schema = "{ f0: string, f1: string, f2: int16, f3: bool }"
csv_ldict = ... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/tests/test_array_opening.py",
"copies": "1",
"size": "3037",
"license": "bsd-3-clause",
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"autogenerated": false,
"ratio": 2.8016605166051662,
"config... |
from __future__ import absolute_import, division, print_function
import os
import tempfile
from functools import partial
import pytest
from bag8.project import Project
from bag8.utils import check_call as base_check_call
from bag8.utils import inspect
check_call = partial(base_check_call, exit=False)
@pytest.ma... | {
"repo_name": "novafloss/bag8",
"path": "bag8/tests/test_cli.py",
"copies": "1",
"size": "10623",
"license": "mit",
"hash": 6714268961105525000,
"line_mean": 30.0614035088,
"line_max": 96,
"alpha_frac": 0.5532335498,
"autogenerated": false,
"ratio": 3.2666051660516606,
"config_test": true,
"h... |
from __future__ import absolute_import, division, print_function
import os
import types
import warnings
from itertools import count
import numpy as np
from sunpy.extern import six
from sunpy.extern.six.moves import map, zip
__all__ = ['to_signed', 'unique', 'print_table',
'replacement_filename', 'merge',... | {
"repo_name": "Alex-Ian-Hamilton/sunpy",
"path": "sunpy/util/util.py",
"copies": "1",
"size": "8079",
"license": "bsd-2-clause",
"hash": 2408865092647867400,
"line_mean": 25.145631068,
"line_max": 86,
"alpha_frac": 0.5391756405,
"autogenerated": false,
"ratio": 4.23205866946045,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import os
import unittest
import dask.array as da
import numpy as np
from netCDF4 import Dataset
from odvc import ocean_s_coordinate_g1
from odvc.utils import (
get_formula_terms,
get_formula_terms_dims,
get_formula_terms_variables,
pre... | {
"repo_name": "pyoceans/odvc",
"path": "tests/test_ocean_s_coordinate_g1.py",
"copies": "3",
"size": "2760",
"license": "mit",
"hash": 4291468013574247000,
"line_mean": 28.0526315789,
"line_max": 72,
"alpha_frac": 0.5141304348,
"autogenerated": false,
"ratio": 3.4074074074074074,
"config_test":... |
from __future__ import absolute_import, division, print_function
import os
import warnings
from collections import OrderedDict
from glue.core.data import Component, Data
from glue.config import data_factory
__all__ = ['is_hdf5', 'hdf5_reader']
def extract_hdf5_datasets(handle):
'''
Recursive function that... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/core/data_factories/hdf5.py",
"copies": "4",
"size": "3091",
"license": "bsd-3-clause",
"hash": -452199982591098240,
"line_mean": 29.3039215686,
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"alpha_frac": 0.5949530896,
"autogenerated": false,
"ratio": 3.8831658291457285,
"... |
from __future__ import absolute_import, division, print_function
import os
import warnings
from qtpy import QtCore, QtGui, QtWidgets
from qtpy.QtCore import Qt
from glue.external import six
from glue.core.callback_property import add_callback
from glue.viewers.common.qt.tool import CheckableTool
from glue.icons.qt i... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/viewers/common/qt/toolbar.py",
"copies": "3",
"size": "4898",
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"hash": 8000714395341098000,
"line_mean": 29.0490797546,
"line_max": 89,
"alpha_frac": 0.5624744794,
"autogenerated": false,
"ratio": 4.292725679228747,
"... |
from __future__ import absolute_import, division, print_function
import os
from appr.commands.command_base import CommandBase
from appr.pack import ApprPackage
class PullCmd(CommandBase):
name = 'pull'
help_message = "download a package"
def __init__(self, options):
super(PullCmd, self).__init_... | {
"repo_name": "app-registry/appr",
"path": "appr/commands/pull.py",
"copies": "2",
"size": "2329",
"license": "apache-2.0",
"hash": -6064321086907732000,
"line_mean": 37.1803278689,
"line_max": 95,
"alpha_frac": 0.6161442679,
"autogenerated": false,
"ratio": 3.881666666666667,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import os
from appr.formats.utils import kub_factory
from appr.commands.command_base import CommandBase, LoadVariables
class DeployCmd(CommandBase):
name = 'deploy'
help_message = "deploy a package on kubernetes"
default_media_type = "kpm"... | {
"repo_name": "app-registry/appr",
"path": "appr/commands/deploy.py",
"copies": "2",
"size": "2784",
"license": "apache-2.0",
"hash": -9176044098071153000,
"line_mean": 39.9411764706,
"line_max": 93,
"alpha_frac": 0.6041666667,
"autogenerated": false,
"ratio": 4.211800302571861,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import os
from bag8.project import Project
from bag8.yaml import Yaml
CURR_DIR = os.path.realpath('.')
def test_data():
# normal
project = Project('busybox')
assert Yaml(project).data == {
'busybox': {
'dockerfile': ... | {
"repo_name": "novafloss/bag8",
"path": "bag8/tests/test_yaml.py",
"copies": "1",
"size": "4636",
"license": "mit",
"hash": 437238647660886600,
"line_mean": 27.6172839506,
"line_max": 73,
"alpha_frac": 0.4109145815,
"autogenerated": false,
"ratio": 3.9828178694158076,
"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import os
from ...external.qt.QtGui import (
QMainWindow, QMessageBox, QWidget)
from ...external.qt.QtCore import Qt
from ...core.application_base import ViewerBase
from ..decorators import set_cursor
from ..layer_artist_model import QtLayerArtis... | {
"repo_name": "JudoWill/glue",
"path": "glue/qt/widgets/data_viewer.py",
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"hash": 6262726998563272000,
"line_mean": 29.2248995984,
"line_max": 90,
"alpha_frac": 0.5721498804,
"autogenerated": false,
"ratio": 4.12609649122807,
"config_test... |
from __future__ import absolute_import, division, print_function
import os
from flask import Flask, request
from flask_cors import CORS
from appr.api.config import DevelopmentConfig, ProductionConfig
from appr.exception import InvalidUsage
def getvalues():
jsonbody = request.get_json(force=True, silent=True)
... | {
"repo_name": "app-registry/appr",
"path": "appr/api/app.py",
"copies": "2",
"size": "1307",
"license": "apache-2.0",
"hash": -2522829662725542400,
"line_mean": 26.2291666667,
"line_max": 85,
"alpha_frac": 0.6679418516,
"autogenerated": false,
"ratio": 3.580821917808219,
"config_test": true,
... |
from __future__ import absolute_import, division, print_function
import os
from functools import partial
from collections import Counter
import numpy as np
from glue.core import Coordinates
from qtpy import QtCore, QtWidgets
from glue.utils.qt import load_ui
from glue.utils.qt.widget_properties import (TextProperty... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/common/qt/data_slice_widget.py",
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"c... |
from __future__ import absolute_import, division, print_function
import os
from glue.core.data_factories.helpers import has_extension
from glue.core.data_factories.pandas import panda_process
from glue.config import data_factory
__all__ = []
@data_factory(label="Excel", identifier=has_extension('xls xlsx'))
def p... | {
"repo_name": "saimn/glue",
"path": "glue/core/data_factories/excel.py",
"copies": "5",
"size": "1367",
"license": "bsd-3-clause",
"hash": 3723305937751760400,
"line_mean": 26.34,
"line_max": 68,
"alpha_frac": 0.6488661302,
"autogenerated": false,
"ratio": 3.6356382978723403,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import os
from glue.core import Subset
from glue.config import data_exporter
__all__ = []
def data_to_astropy_table(data):
if isinstance(data, Subset):
mask = data.to_mask()
data = data.data
else:
mask = None
fro... | {
"repo_name": "saimn/glue",
"path": "glue/core/data_exporters/astropy_table.py",
"copies": "2",
"size": "1396",
"license": "bsd-3-clause",
"hash": -912792003874775000,
"line_mean": 24.3818181818,
"line_max": 72,
"alpha_frac": 0.6303724928,
"autogenerated": false,
"ratio": 3.7628032345013476,
"c... |
from __future__ import absolute_import, division, print_function
import os
from glue.core.subset import Subset
from qtpy import QtWidgets
from glue.utils.qt import load_ui
from glue.external.echo.qt import autoconnect_callbacks_to_qt
class VolumeLayerStyleWidget(QtWidgets.QWidget):
def __init__(self, layer_a... | {
"repo_name": "PennyQ/glue-3d-viewer",
"path": "glue_vispy_viewers/volume/layer_style_widget.py",
"copies": "1",
"size": "2060",
"license": "bsd-2-clause",
"hash": 8303252644797740000,
"line_mean": 35.1403508772,
"line_max": 82,
"alpha_frac": 0.6359223301,
"autogenerated": false,
"ratio": 3.75912... |
from __future__ import absolute_import, division, print_function
import os
from glue.external.modest_image import imshow
from qtpy.QtCore import Qt
from qtpy import QtCore, QtWidgets, QtGui
from glue.core.callback_property import add_callback, delay_callback
from glue import core
from glue.config import viewer_tool
f... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/image/qt/viewer_widget.py",
"copies": "1",
"size": "19555",
"license": "bsd-3-clause",
"hash": -8239916408426576000,
"line_mean": 35.4832089552,
"line_max": 121,
"alpha_frac": 0.6049603682,
"autogenerated": false,
"ratio": 3.9489095315024234,
"c... |
from __future__ import absolute_import, division, print_function
import os
from idaskins import UI_DIR
from PyQt5 import uic
from PyQt5.Qt import qApp
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QCursor, QFont, QKeySequence
from PyQt5.QtWidgets import QShortcut, QWidget
Ui_ObjectInspector, ObjectInspectorBas... | {
"repo_name": "zyantific/IDASkins",
"path": "plugins/idaskins/objectinspector.py",
"copies": "1",
"size": "2576",
"license": "mit",
"hash": 2552390391094649300,
"line_mean": 31.6075949367,
"line_max": 76,
"alpha_frac": 0.6129658385,
"autogenerated": false,
"ratio": 4.031298904538341,
"config_te... |
from __future__ import absolute_import, division, print_function
import os
from odo.backends.hdfstore import discover
from contextlib import contextmanager
from odo.utils import tmpfile
from odo.chunks import chunks
from odo import into, append, convert, resource, discover, odo
import datashape
import pandas as pd
fr... | {
"repo_name": "cowlicks/odo",
"path": "odo/backends/tests/test_hdfstore.py",
"copies": "4",
"size": "4599",
"license": "bsd-3-clause",
"hash": 7903338533433737000,
"line_mean": 25.4310344828,
"line_max": 83,
"alpha_frac": 0.5475103283,
"autogenerated": false,
"ratio": 3.2524752475247523,
"confi... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtCore, QtWidgets
from glue.utils.qt import get_qapp
from glue.utils.qt import load_ui, connect_color
from glue.utils.qt.widget_properties import CurrentComboProperty, ValueProperty, connect_value, connect_current_combo
from g... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/scatter/qt/layer_style_widget.py",
"copies": "2",
"size": "1941",
"license": "bsd-3-clause",
"hash": 6604689418227823000,
"line_mean": 34.2909090909,
"line_max": 117,
"alpha_frac": 0.6640906749,
"autogenerated": false,
"ratio": 3.607806691449814,
... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtCore, QtWidgets
from glue.utils.qt import load_ui
from glue.utils import nonpartial
class ComponentSelector(QtWidgets.QWidget):
""" An interface to view the components and data of a DataCollection
Components can b... | {
"repo_name": "saimn/glue",
"path": "glue/dialogs/common/qt/component_selector.py",
"copies": "1",
"size": "4412",
"license": "bsd-3-clause",
"hash": -1965189886523367700,
"line_mean": 27.8366013072,
"line_max": 72,
"alpha_frac": 0.5947416138,
"autogenerated": false,
"ratio": 3.8838028169014085,
... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtCore, QtWidgets
from qtpy.QtCore import Qt
from glue.utils.qt import load_ui
from glue.utils import nonpartial
class ComponentSelector(QtWidgets.QWidget):
""" An interface to view the components and data of a DataColle... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/dialogs/common/qt/component_selector.py",
"copies": "3",
"size": "5850",
"license": "bsd-3-clause",
"hash": -4024027942271601000,
"line_mean": 31.1428571429,
"line_max": 87,
"alpha_frac": 0.592991453,
"autogenerated": false,
"ratio": 3.979591836... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtGui, compat
from glue.viewers.common.qt.tool import Tool, CheckableTool
from glue.config import viewer_tool
from ..extern.vispy import app, io
RECORD_START_ICON = os.path.join(os.path.dirname(__file__), 'glue_record_start... | {
"repo_name": "PennyQ/glue-3d-viewer",
"path": "glue_vispy_viewers/common/tools.py",
"copies": "1",
"size": "3759",
"license": "bsd-2-clause",
"hash": 7443118557678038000,
"line_mean": 29.314516129,
"line_max": 90,
"alpha_frac": 0.5746209098,
"autogenerated": false,
"ratio": 3.831804281345566,
... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtGui, compat
try:
from glue.viewers.common.tool import Tool, CheckableTool
except ImportError: # glue-core <0.15
from glue.viewers.common.qt.tool import Tool, CheckableTool
from glue.config import viewer_tool
from... | {
"repo_name": "astrofrog/glue-3d-viewer",
"path": "glue_vispy_viewers/common/tools.py",
"copies": "2",
"size": "3840",
"license": "bsd-2-clause",
"hash": -2273169019433526800,
"line_mean": 29.4761904762,
"line_max": 91,
"alpha_frac": 0.5859375,
"autogenerated": false,
"ratio": 3.8057482656095143,... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from glue import core
from glue.plugins.dendro_viewer.client import DendroClient
from glue.viewers.common.qt.mpl_toolbar import MatplotlibViewerToolbar
from glue.viewers.common.qt.mouse_mode import PickMode
from glue... | {
"repo_name": "saimn/glue",
"path": "glue/plugins/dendro_viewer/qt/viewer_widget.py",
"copies": "1",
"size": "4872",
"license": "bsd-3-clause",
"hash": 1916025047225315800,
"line_mean": 32.1428571429,
"line_max": 87,
"alpha_frac": 0.6063218391,
"autogenerated": false,
"ratio": 4.076987447698745,
... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from glue import core
from glue.utils import nonpartial
from glue.utils.qt import load_ui
__all__ = ['LinkEditor']
class LinkEditor(QtWidgets.QDialog):
def __init__(self, collection, functions=None, parent=No... | {
"repo_name": "saimn/glue",
"path": "glue/dialogs/link_editor/qt/link_editor.py",
"copies": "1",
"size": "4149",
"license": "bsd-3-clause",
"hash": -2959285724988993500,
"line_mean": 29.0652173913,
"line_max": 95,
"alpha_frac": 0.6080983369,
"autogenerated": false,
"ratio": 3.899436090225564,
"... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from qtpy.QtCore import Qt
from glue import core
from glue.utils import nonpartial
from glue.utils.qt import load_ui, HtmlItemDelegate
__all__ = ['LinkEditor']
class LinkEditor(QtWidgets.QDialog):
def __init... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/dialogs/link_editor/qt/link_editor.py",
"copies": "3",
"size": "4366",
"license": "bsd-3-clause",
"hash": -8995892236241781000,
"line_mean": 29.3194444444,
"line_max": 88,
"alpha_frac": 0.6142922584,
"autogenerated": false,
"ratio": 3.9016979445... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from glue.external.echo.qt import autoconnect_callbacks_to_qt
from glue.utils.qt import load_ui, fix_tab_widget_fontsize
from glue.viewers.image.qt.slice_widget import MultiSliceWidgetHelper
__all__ = ['ImageOption... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/viewers/image/qt/options_widget.py",
"copies": "1",
"size": "1267",
"license": "bsd-3-clause",
"hash": 1050973563412401700,
"line_mean": 33.2432432432,
"line_max": 82,
"alpha_frac": 0.6756116811,
"autogenerated": false,
"ratio": 3.74852071005917... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from glue.utils import nonpartial
from glue.utils.qt import load_ui
from glue.external.echo.qt import autoconnect_callbacks_to_qt
class ScatterLayerStyleWidget(QtWidgets.QWidget):
def __init__(self, layer_art... | {
"repo_name": "PennyQ/glue-3d-viewer",
"path": "glue_vispy_viewers/scatter/layer_style_widget.py",
"copies": "1",
"size": "1997",
"license": "bsd-2-clause",
"hash": 7740161033935505000,
"line_mean": 31.737704918,
"line_max": 86,
"alpha_frac": 0.6014021032,
"autogenerated": false,
"ratio": 3.51584... |
from __future__ import absolute_import, division, print_function
import os
from qtpy import QtWidgets
from glue.utils.qt import load_ui
from glue.external.echo.qt import autoconnect_callbacks_to_qt
from glue_vispy_viewers.utils import fix_tab_widget_fontsize
class ScatterLayerStyleWidget(QtWidgets.QWidget):
... | {
"repo_name": "astrofrog/glue-3d-viewer",
"path": "glue_vispy_viewers/scatter/layer_style_widget.py",
"copies": "2",
"size": "2088",
"license": "bsd-2-clause",
"hash": 2725176566554368000,
"line_mean": 31.625,
"line_max": 92,
"alpha_frac": 0.6039272031,
"autogenerated": false,
"ratio": 3.47420965... |
from __future__ import absolute_import, division, print_function
import os
from qtpy.QtCore import Qt
from qtpy import QtCore, QtWidgets
from glue.core.application_base import ViewerBase
from glue.core.qt.layer_artist_model import QtLayerArtistContainer, LayerArtistWidget
from glue.utils.qt import get_qapp
from glue.... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/viewers/common/qt/data_viewer.py",
"copies": "1",
"size": "9978",
"license": "bsd-3-clause",
"hash": -2858473583310382600,
"line_mean": 30.2789968652,
"line_max": 94,
"alpha_frac": 0.5850871918,
"autogenerated": false,
"ratio": 4.129966887417218... |
from __future__ import absolute_import, division, print_function
import os
from qtpy.QtCore import Qt
from qtpy import QtWidgets
from glue import core
from glue.viewers.scatter.client import ScatterClient
from glue.viewers.common.qt.mpl_toolbar import MatplotlibViewerToolbar
from glue.viewers.common.qt.mouse_mode imp... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/scatter/qt/viewer_widget.py",
"copies": "1",
"size": "9914",
"license": "bsd-3-clause",
"hash": -574948424469269800,
"line_mean": 34.28113879,
"line_max": 101,
"alpha_frac": 0.6210409522,
"autogenerated": false,
"ratio": 3.8817541111981204,
"con... |
from __future__ import absolute_import, division, print_function
import os
from qtpy.QtCore import Qt
from qtpy import QtWidgets
from glue.utils.qt import set_cursor_cm
__all__ = ['data_wizard', 'GlueDataDialog']
def data_wizard():
""" QT Dialog to load a file into a new data object
Returns:
A list... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/dialogs/data_wizard/qt/data_wizard_dialog.py",
"copies": "2",
"size": "4394",
"license": "bsd-3-clause",
"hash": 1343342467754434800,
"line_mean": 33.328125,
"line_max": 90,
"alpha_frac": 0.5464269458,
"autogenerated": false,
"ratio": 4.40722166... |
from __future__ import absolute_import, division, print_function
import os
from setuptools import setup
import versioneer
rootpath = os.path.abspath(os.path.dirname(__file__))
def read(*parts):
return open(os.path.join(rootpath, *parts), "r").read()
long_description = "{}\n{}".format(read("README.rst"), rea... | {
"repo_name": "ocefpaf/odvc",
"path": "setup.py",
"copies": "3",
"size": "1658",
"license": "bsd-3-clause",
"hash": 286826740314771330,
"line_mean": 27.1016949153,
"line_max": 75,
"alpha_frac": 0.646562123,
"autogenerated": false,
"ratio": 3.751131221719457,
"config_test": false,
"has_no_keyw... |
from __future__ import absolute_import, division, print_function
import os
# gpi, future
import gpi
from bart.gpi.borg import IFilePath, OFilePath, Command
# bart
import bart
base_path = bart.__path__[0] # library base for executables
import bart.python.cfl as cfl
class ExternalNode(gpi.NodeAPI):
"""Usage: cdf9... | {
"repo_name": "nckz/bart",
"path": "gpi/cdf97_GPI.py",
"copies": "1",
"size": "1988",
"license": "bsd-3-clause",
"hash": -7054664795357644000,
"line_mean": 24.164556962,
"line_max": 75,
"alpha_frac": 0.5533199195,
"autogenerated": false,
"ratio": 3.960159362549801,
"config_test": false,
"has_... |
from __future__ import absolute_import, division, print_function
import os
import datashape
from datashape import DataShape, Record, to_numpy, to_numpy_dtype, discover
from datashape.predicates import isrecord
from datashape.dispatch import dispatch
import h5py
import numpy as np
from toolz import keyfilter
from ..a... | {
"repo_name": "mrocklin/into",
"path": "into/backends/h5py.py",
"copies": "1",
"size": "7768",
"license": "bsd-3-clause",
"hash": -331208715482822600,
"line_mean": 29.1085271318,
"line_max": 89,
"alpha_frac": 0.5742790937,
"autogenerated": false,
"ratio": 3.3642269380684278,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import os
import datashape
from .data_descriptor import DDesc
from .. import py2help
from dynd import nd
from .dynd_data_descriptor import DyND_DDesc, Capabilities
def json_descriptor_iter(array):
for row in array:
yield DyND_DDesc(row)
... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/datadescriptor/json_data_descriptor.py",
"copies": "3",
"size": "2737",
"license": "bsd-3-clause",
"hash": -2306633751572151000,
"line_mean": 28.1170212766,
"line_max": 72,
"alpha_frac": 0.5999269273,
"autogenerated": false,
"ratio": 4.140695915279... |
from __future__ import absolute_import, division, print_function
import os
import datashape
from .data_descriptor import IDataDescriptor
from .. import py2help
from dynd import nd
from .dynd_data_descriptor import DyNDDataDescriptor, Capabilities
def json_descriptor_iter(array):
for row in array:
yield... | {
"repo_name": "XinSong/blaze",
"path": "blaze/datadescriptor/json_data_descriptor.py",
"copies": "7",
"size": "2681",
"license": "bsd-3-clause",
"hash": -5404987424908856000,
"line_mean": 29.1235955056,
"line_max": 72,
"alpha_frac": 0.6161879896,
"autogenerated": false,
"ratio": 4.269108280254777... |
from __future__ import absolute_import, division, print_function
import os
import idaapi
from idaskins import IDA_DIR, THEMES_DIR, VERSION
from idaskins.idafontconfig import IdaFontConfig
from idaskins.objectinspector import ObjectInspector
from idaskins.settings import Settings
from idaskins.thememanifest import The... | {
"repo_name": "zyantific/IDASkins",
"path": "plugins/idaskins/plugin.py",
"copies": "1",
"size": "6051",
"license": "mit",
"hash": -7239864608497623000,
"line_mean": 35.0178571429,
"line_max": 92,
"alpha_frac": 0.604858701,
"autogenerated": false,
"ratio": 3.8104534005037785,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import os
import invoke
import fabric.api
import fabric.contrib.files
from .utils import cd, ssh_host
SALT_MASTER = "192.168.5.1"
@invoke.task(name="sync-changes")
def sync_changes():
# Push our changes to GitHub
# TODO: Determine what orig... | {
"repo_name": "python/psf-salt",
"path": "tasks/salt.py",
"copies": "1",
"size": "4528",
"license": "mit",
"hash": -6890022229323660000,
"line_mean": 36.1147540984,
"line_max": 149,
"alpha_frac": 0.6274293286,
"autogenerated": false,
"ratio": 3.559748427672956,
"config_test": false,
"has_no_k... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
from matplotlib.colors import ColorConverter
from qtpy import QtWidgets
from glue.core.message import SettingsChangeMessage
from glue.utils import nonpartial
from glue.utils.qt import load_ui, ColorProperty
from glue.utils.... | {
"repo_name": "saimn/glue",
"path": "glue/app/qt/preferences.py",
"copies": "2",
"size": "4299",
"license": "bsd-3-clause",
"hash": -3868479306875037000,
"line_mean": 33.6693548387,
"line_max": 102,
"alpha_frac": 0.6327052803,
"autogenerated": false,
"ratio": 3.797703180212014,
"config_test": f... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import pandas as pd
import xarray as xr
from . import randint, randn, requires_dask
try:
import dask
import dask.multiprocessing
except ImportError:
pass
os.environ['HDF5_USE_FILE_LOCKING'] = 'FALSE'
class... | {
"repo_name": "shoyer/xray",
"path": "asv_bench/benchmarks/dataset_io.py",
"copies": "1",
"size": "16435",
"license": "apache-2.0",
"hash": 7250270921864721000,
"line_mean": 35.6852678571,
"line_max": 78,
"alpha_frac": 0.526194098,
"autogenerated": false,
"ratio": 3.927120669056153,
"config_tes... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import seaborn as sns
import tensorflow as tf
from matplotlib import pyplot as plt
from scipy import stats
from sklearn.mixture import GaussianMixture
from tensorflow.python.keras import Sequential
from odin import visual a... | {
"repo_name": "imito/odin",
"path": "tests/test_mixture_density_network.py",
"copies": "1",
"size": "1885",
"license": "mit",
"hash": 4191435767940286500,
"line_mean": 25.1805555556,
"line_max": 70,
"alpha_frac": 0.6376657825,
"autogenerated": false,
"ratio": 2.8517397881996973,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import tensorflow as tf
from tensorflow_probability.python.distributions import (Bernoulli, Independent,
NegativeBinomial,
... | {
"repo_name": "imito/odin",
"path": "tests/test_stack_distributions.py",
"copies": "1",
"size": "4308",
"license": "mit",
"hash": 7284793420709947000,
"line_mean": 38.5229357798,
"line_max": 80,
"alpha_frac": 0.6511142061,
"autogenerated": false,
"ratio": 3.545679012345679,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import tensorflow as tf
import torch
from tensorflow.python.keras.layers import Dense
from odin import networks_torch as nt
from odin.networks import (TimeDelay, TimeDelayConv, TimeDelayConvTied,
... | {
"repo_name": "imito/odin",
"path": "tests/test_time_delay_networks.py",
"copies": "1",
"size": "1445",
"license": "mit",
"hash": 6688619488873689000,
"line_mean": 20.8939393939,
"line_max": 71,
"alpha_frac": 0.644982699,
"autogenerated": false,
"ratio": 2.768199233716475,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import tensorflow as tf
import torch
from odin.bay.distributions import NegativeBinomialDisp, ZeroInflated
from odin.stats import describe
from scvi.models.log_likelihood import log_nb_positive, log_zinb_positive
os.enviro... | {
"repo_name": "imito/odin",
"path": "tests/test_negative_binomial_disp.py",
"copies": "1",
"size": "2797",
"license": "mit",
"hash": -1093659561195446000,
"line_mean": 31.9058823529,
"line_max": 73,
"alpha_frac": 0.6503396496,
"autogenerated": false,
"ratio": 2.86577868852459,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import tensorflow as tf
import torch
from odin import backend as K
from odin import networks as net # tensorflow networks
from odin import networks_torch as nt # pytorch networks
tf.random.set_seed(8)
torch.manual_seed(8... | {
"repo_name": "imito/odin",
"path": "tests/test_keras_torch.py",
"copies": "1",
"size": "2654",
"license": "mit",
"hash": -7446849769077663000,
"line_mean": 26.9368421053,
"line_max": 77,
"alpha_frac": 0.5346646571,
"autogenerated": false,
"ratio": 2.9820224719101125,
"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import os
import numpy as np
import torch
from six import string_types
from torch import nn
from odin.backend import concatenate, expand_dims, parse_reduction, squeeze
from odin.networks_torch.keras_torch import Conv1D, Dense, Layer
from odin.utils imp... | {
"repo_name": "imito/odin",
"path": "odin/networks_torch/time_delay.py",
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from __future__ import absolute_import, division, print_function
import os
import numpy as np
from qtpy import QtCore, QtWidgets
from glue.utils.qt import load_ui
from glue.utils import nonpartial
from glue.icons.qt import get_icon
from glue.core.state_objects import State, CallbackProperty
from glue.external.echo.q... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/viewers/common/qt/data_slice_widget.py",
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"autogenerated": false,
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from __future__ import absolute_import, division, print_function
import os
import numpy as np
from toolz import first
from .dispatch import dispatch
import datashape
import shutil
from blaze.utils import tmpfile
from odo import resource
try:
import tables as tb
from tables import Table
except ImportError:... | {
"repo_name": "mrocklin/blaze",
"path": "blaze/pytables.py",
"copies": "1",
"size": "3639",
"license": "bsd-3-clause",
"hash": -7819087954397837000,
"line_mean": 26.7786259542,
"line_max": 83,
"alpha_frac": 0.5622423743,
"autogenerated": false,
"ratio": 3.5502439024390244,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import os
import pytest
import numpy as np
from numpy.testing import assert_array_equal
from glue.tests.helpers import make_file
from glue.core.data_factories.helpers import find_factory
from glue.core import data_factories as df
from glue.tests.helpe... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/plugins/dendro_viewer/tests/test_data_factory.py",
"copies": "2",
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"hash": 7593548819647206000,
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"autogenerated": false,
"ratio": 2.... |
from __future__ import absolute_import, division, print_function
import os
import pytest
@pytest.mark.filterwarnings("default")
def test_yield_tests_deprecation(testdir):
testdir.makepyfile(
"""
def func1(arg, arg2):
assert arg == arg2
def test_gen():
yield "m1", ... | {
"repo_name": "davidszotten/pytest",
"path": "testing/deprecated_test.py",
"copies": "1",
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"alpha_frac": 0.6139008621,
"autogenerated": false,
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from __future__ import absolute_import, division, print_function
import os
import stripe
from flask import Flask, request, redirect
stripe.api_key = os.environ.get("STRIPE_SECRET_KEY")
stripe.client_id = os.environ.get("STRIPE_CLIENT_ID")
app = Flask(__name__)
@app.route("/")
def index():
return '<a href="/a... | {
"repo_name": "stripe/stripe-python",
"path": "examples/oauth.py",
"copies": "1",
"size": "1527",
"license": "mit",
"hash": 9106938337279194000,
"line_mean": 24.45,
"line_max": 77,
"alpha_frac": 0.6516044532,
"autogenerated": false,
"ratio": 3.1290983606557377,
"config_test": false,
"has_no_k... |
from __future__ import absolute_import, division, print_function
import os
# Stripe Python bindings
# API docs at http://stripe.com/docs/api
# Authors:
# Patrick Collison <patrick@stripe.com>
# Greg Brockman <gdb@stripe.com>
# Andrew Metcalf <andrew@stripe.com>
# Configuration variables
api_key = None
client_id = N... | {
"repo_name": "stripe/stripe-python",
"path": "stripe/__init__.py",
"copies": "1",
"size": "1399",
"license": "mit",
"hash": -7784308622320020000,
"line_mean": 24.4363636364,
"line_max": 77,
"alpha_frac": 0.7105075054,
"autogenerated": false,
"ratio": 3.2995283018867925,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import os
try:
from inspect import getfullargspec
except ImportError: # Python 2.7
from inspect import getargspec as getfullargspec
from qtpy import QtWidgets
from qtpy import PYSIDE
from glue import core
from glue.config import link_function,... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/dialogs/link_editor/qt/link_equation.py",
"copies": "1",
"size": "10524",
"license": "bsd-3-clause",
"hash": 5079556409656396000,
"line_mean": 32.4095238095,
"line_max": 131,
"alpha_frac": 0.6222919042,
"autogenerated": false,
"ratio": 4.1173708... |
from __future__ import absolute_import, division, print_function
import os
try:
import sphinx_rtd_theme
except ImportError:
sphinx_rtd_theme = None
base_dir = os.path.join(os.path.dirname(__file__), os.pardir)
about = {}
with open(os.path.join(base_dir, "virtualenv", "__about__.py")) as f:
exec(f.read()... | {
"repo_name": "ionelmc/virtualenv",
"path": "docs/conf.py",
"copies": "1",
"size": "2665",
"license": "mit",
"hash": -7539529149794524000,
"line_mean": 26.7604166667,
"line_max": 79,
"alpha_frac": 0.6600375235,
"autogenerated": false,
"ratio": 3.9191176470588234,
"config_test": false,
"has_no... |
from __future__ import absolute_import, division, print_function
import os.path as op
import keras
from .due import due, Doi # noqa
# Use duecredit (duecredit.org) to provide a citation to relevant work to
# be cited. This does nothing, unless the user has duecredit installed,
# And calls this with duecredit (as in... | {
"repo_name": "uw-biomedical-ml/keratin",
"path": "keratin/keratin.py",
"copies": "1",
"size": "1984",
"license": "mit",
"hash": 5516094152929797000,
"line_mean": 37.1538461538,
"line_max": 77,
"alpha_frac": 0.5483870968,
"autogenerated": false,
"ratio": 3.273927392739274,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import os.path
from glob import glob
from io import BytesIO
from numbers import Number
import numpy as np
from .. import Dataset, backends, conventions
from ..core import indexing
from ..core.combine import auto_combine
from ..core.pycompat import base... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/backends/api.py",
"copies": "1",
"size": "35346",
"license": "apache-2.0",
"hash": 8544805690203871000,
"line_mean": 41.381294964,
"line_max": 80,
"alpha_frac": 0.6264923895,
"autogenerated": false,
"ratio": 4.4555653598890705,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import os.path
import datetime
from warnings import warn
import copy
import csv
import sqlite3
import numpy as np
from astropy.io import fits
import pandas
from sunpy.time import parse_time
from sunpy import config
from sunpy.util.net import check_down... | {
"repo_name": "Alex-Ian-Hamilton/sunpy",
"path": "sunpy/instr/lyra.py",
"copies": "1",
"size": "30619",
"license": "bsd-2-clause",
"hash": 8336615997560095000,
"line_mean": 40.4891598916,
"line_max": 93,
"alpha_frac": 0.6130833796,
"autogenerated": false,
"ratio": 4.093449197860963,
"config_tes... |
from __future__ import absolute_import, division, print_function
import os.path
import sys
from Cython.Build import cythonize
from Cython.Distutils import extension
from echomesh.base import Path
from echomesh.base import Platform
_DEBUG_FLAG = '--debug'
DEBUG = _DEBUG_FLAG in sys.argv
if DEBUG:
sys.argv.remov... | {
"repo_name": "rec/echomesh",
"path": "code/python/echomesh/build/BuildConfig.py",
"copies": "1",
"size": "2875",
"license": "mit",
"hash": 1014947364197734700,
"line_mean": 29.585106383,
"line_max": 79,
"alpha_frac": 0.5648695652,
"autogenerated": false,
"ratio": 3.4307875894988067,
"config_te... |
from __future__ import absolute_import, division, print_function
import os.path
import sys
import yaml
__all__ = ['ManifestChart']
MANIFEST_FILES = ["Chart.yaml", "Chart.yml"]
class ManifestChart(dict):
def __init__(self, package=None, values=None):
def __init__(self):
super(ManifestChart,... | {
"repo_name": "app-registry/appr",
"path": "appr/formats/helm/manifest_chart.py",
"copies": "2",
"size": "1983",
"license": "apache-2.0",
"hash": -3774338324030189600,
"line_mean": 23.4814814815,
"line_max": 95,
"alpha_frac": 0.5511850731,
"autogenerated": false,
"ratio": 4.006060606060606,
"co... |
from __future__ import absolute_import, division, print_function
import os.path
import yaml
from appr.formats.appr.manifest import ManifestBase
from appr.pack import all_files
from appr.render_jsonnet import RenderJsonnet, yaml_to_jsonnet
__all__ = ['ManifestJsonnet']
MANIFEST_FILES = ['manifest.jsonnet', 'manifes... | {
"repo_name": "cn-app-registry/cnr-server",
"path": "appr/formats/appr/manifest_jsonnet.py",
"copies": "2",
"size": "2349",
"license": "apache-2.0",
"hash": -1232279893608426800,
"line_mean": 33.0434782609,
"line_max": 94,
"alpha_frac": 0.5917411665,
"autogenerated": false,
"ratio": 3.72857142857... |
from __future__ import absolute_import, division, print_function
import os, sys, argparse
import urllib
import tflearn
from tflearn.data_utils import *
parser = argparse.ArgumentParser(description=
'Pass a text file to generate LSTM output')
parser.add_argument('filename')
parser.add_argument('-t','--temp', hel... | {
"repo_name": "hashware/tflearn-learn",
"path": "examples/nlp/lstm_generator_textfile.py",
"copies": "2",
"size": "2983",
"license": "mit",
"hash": 7709433194300414000,
"line_mean": 37.7402597403,
"line_max": 92,
"alpha_frac": 0.6473348978,
"autogenerated": false,
"ratio": 3.4208715596330275,
"... |
from __future__ import absolute_import, division, print_function
import pandas as pd
from ..expr import (Expr, Symbol, Field, Arithmetic, Math,
Date, Time, DateTime, Millisecond, Microsecond, broadcast,
sin, cos, Map, UTCFromTimestamp, DateTimeTruncate, symbol,
... | {
"repo_name": "dwillmer/blaze",
"path": "blaze/compute/pyfunc.py",
"copies": "3",
"size": "6148",
"license": "bsd-3-clause",
"hash": 4429572772047655000,
"line_mean": 29.8944723618,
"line_max": 100,
"alpha_frac": 0.6107677293,
"autogenerated": false,
"ratio": 3.2615384615384615,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import pandas as pd
from ..expr import (Expr, Symbol, Field, Arithmetic, UnaryMath, BinaryMath,
Date, Time, DateTime, Millisecond, Microsecond, broadcast,
sin, cos, Map, UTCFromTimestamp, DateTimeTruncate, symbol,
... | {
"repo_name": "ContinuumIO/blaze",
"path": "blaze/compute/pyfunc.py",
"copies": "5",
"size": "7748",
"license": "bsd-3-clause",
"hash": -5583132074411088000,
"line_mean": 28.572519084,
"line_max": 100,
"alpha_frac": 0.6143520909,
"autogenerated": false,
"ratio": 3.213604313562837,
"config_test"... |
from __future__ import absolute_import, division, print_function
import pandas as pd
from toolz import partial
from dask.base import compute
def _categorize_block(df, categories):
""" Categorize a dataframe with given categories
df: DataFrame
categories: dict mapping column name to iterable of categori... | {
"repo_name": "cowlicks/dask",
"path": "dask/dataframe/categorical.py",
"copies": "2",
"size": "3559",
"license": "bsd-3-clause",
"hash": -985202191573583100,
"line_mean": 28.4132231405,
"line_max": 85,
"alpha_frac": 0.5465018264,
"autogenerated": false,
"ratio": 3.790202342917998,
"config_test... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import nfldb
from nfldb.update import log
from nfldbproj.names import name_to_id
from nfldbproj import update
def from_dataframe(db, df, metadata, single_week_only=False, season_totals=False,
fp_projection=True, s... | {
"repo_name": "hsharrison/nfldb-projections",
"path": "nfldbproj/import_.py",
"copies": "1",
"size": "4785",
"license": "bsd-2-clause",
"hash": -5380721281696894000,
"line_mean": 33.6739130435,
"line_max": 117,
"alpha_frac": 0.5740856844,
"autogenerated": false,
"ratio": 3.353188507358094,
"con... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import numpy as np
from ..core import tokenize, DataFrame
from .io import from_delayed
from ...delayed import delayed
from ...utils import random_state_data
__all__ = ['make_timeseries']
def make_float(n, rstate):
return rstat... | {
"repo_name": "cpcloud/dask",
"path": "dask/dataframe/io/demo.py",
"copies": "1",
"size": "7953",
"license": "bsd-3-clause",
"hash": -8599157415794791000,
"line_mean": 38.1773399015,
"line_max": 88,
"alpha_frac": 0.5743744499,
"autogenerated": false,
"ratio": 3.4683820322721326,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import numpy as np
from .core import tokenize, DataFrame
from ..utils import different_seeds
__all__ = ['make_timeseries']
def make_float(n, rstate):
return rstate.rand(n) * 2 - 1
def make_int(n, rstate):
return rstate.po... | {
"repo_name": "mikegraham/dask",
"path": "dask/dataframe/demo.py",
"copies": "1",
"size": "3180",
"license": "bsd-3-clause",
"hash": -5252871372486875000,
"line_mean": 34.3333333333,
"line_max": 82,
"alpha_frac": 0.593081761,
"autogenerated": false,
"ratio": 3.3263598326359833,
"config_test": f... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import numpy as np
from ..core import tokenize, DataFrame
from ...utils import random_state_data
__all__ = ['make_timeseries']
def make_float(n, rstate):
return rstate.rand(n) * 2 - 1
def make_int(n, rstate):
return rsta... | {
"repo_name": "jeffery-do/Vizdoombot",
"path": "doom/lib/python3.5/site-packages/dask/dataframe/io/demo.py",
"copies": "1",
"size": "3187",
"license": "mit",
"hash": -1467380368623516000,
"line_mean": 34.4111111111,
"line_max": 82,
"alpha_frac": 0.5917791026,
"autogenerated": false,
"ratio": 3.31... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import re
import ast
log_pattern = re.compile("^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d+ - \w+ - .*$")
def _is_legal_log_line(line):
return log_pattern.match(line) is not None
def _hublog_read_scan_line(line):
""" Parses a... | {
"repo_name": "HumanDynamics/openbadge-analysis",
"path": "openbadge_analysis/preprocessing/hublog.py",
"copies": "1",
"size": "7539",
"license": "mit",
"hash": -2815039506591023000,
"line_mean": 26.5182481752,
"line_max": 104,
"alpha_frac": 0.5370738825,
"autogenerated": false,
"ratio": 3.890092... |
from __future__ import absolute_import, division, print_function
import pandas as pd
from .alignment import deep_align
from .pycompat import OrderedDict, basestring
from .utils import Frozen
from .variable import as_variable, assert_unique_multiindex_level_names
PANDAS_TYPES = (pd.Series, pd.DataFrame, pd.Panel)
_V... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/merge.py",
"copies": "1",
"size": "19661",
"license": "apache-2.0",
"hash": -4577991834176582000,
"line_mean": 33.6754850088,
"line_max": 79,
"alpha_frac": 0.6252988149,
"autogenerated": false,
"ratio": 4.524971231300345,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import pandas as pd
from .core import Series, map_partitions, partial
class Accessor(object):
"""
Base class for pandas Accessor objects cat, dt, and str.
Properties
----------
_meta_attributes : set
set of strings indict... | {
"repo_name": "jeffery-do/Vizdoombot",
"path": "doom/lib/python3.5/site-packages/dask/dataframe/accessor.py",
"copies": "3",
"size": "5164",
"license": "mit",
"hash": 4052590670606854000,
"line_mean": 28.3409090909,
"line_max": 77,
"alpha_frac": 0.5807513555,
"autogenerated": false,
"ratio": 4.14... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import datashape
from datashape import discover
from ..append import append
from ..convert import convert, ooc_types
from ..chunks import chunks, Chunks
from ..resource import resource
HDFDataset = (pd.io.pytables.AppendableFrameTa... | {
"repo_name": "mrocklin/into",
"path": "into/backends/hdfstore.py",
"copies": "1",
"size": "3041",
"license": "bsd-3-clause",
"hash": -3648227019648136700,
"line_mean": 30.3505154639,
"line_max": 87,
"alpha_frac": 0.6797106215,
"autogenerated": false,
"ratio": 3.420697412823397,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import pandas as pd
import xarray as xr
from . import randn, requires_dask
try:
import dask # noqa
except ImportError:
pass
def make_bench_data(shape, frac_nan, chunks):
vals = randn(shape, frac_nan)
coords = {'time': pd.date_range(... | {
"repo_name": "shoyer/xray",
"path": "asv_bench/benchmarks/dataarray_missing.py",
"copies": "3",
"size": "1938",
"license": "apache-2.0",
"hash": -6081267601055488000,
"line_mean": 26.2957746479,
"line_max": 73,
"alpha_frac": 0.5521155831,
"autogenerated": false,
"ratio": 3.3241852487135506,
"c... |
from __future__ import absolute_import, division, print_function
import pandas
import os
from toolz import curry, concat, map
import pandas as pd
import numpy as np
from collections import Iterator, Iterable
from odo import into
from odo.chunks import chunks, Chunks
from odo.backends.csv import CSV, csv_to_DataFrame
f... | {
"repo_name": "mrocklin/blaze",
"path": "blaze/compute/csv.py",
"copies": "1",
"size": "2625",
"license": "bsd-3-clause",
"hash": -498708794102937200,
"line_mean": 29.523255814,
"line_max": 80,
"alpha_frac": 0.6933333333,
"autogenerated": false,
"ratio": 3.5377358490566038,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import pandas
import os
from toolz import curry, concat
import pandas as pd
import numpy as np
from collections import Iterator, Iterable
from odo import into
from odo.chunks import chunks
from odo.backends.csv import CSV
from multipledispatch import MDN... | {
"repo_name": "LiaoPan/blaze",
"path": "blaze/compute/csv.py",
"copies": "11",
"size": "2667",
"license": "bsd-3-clause",
"hash": -4761388397392479000,
"line_mean": 28.9662921348,
"line_max": 80,
"alpha_frac": 0.6902887139,
"autogenerated": false,
"ratio": 3.532450331125828,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import paramiko
from contextlib import contextmanager
from toolz import keyfilter, memoize, take, curry
from datashape import discover
import re
import uuid
from ..directory import Directory
from ..utils import keywords, tmpfile, sample, ignoring, copyd... | {
"repo_name": "Dannnno/odo",
"path": "odo/backends/ssh.py",
"copies": "9",
"size": "7008",
"license": "bsd-3-clause",
"hash": 1505857868421652700,
"line_mean": 28.6949152542,
"line_max": 103,
"alpha_frac": 0.6245719178,
"autogenerated": false,
"ratio": 3.421875,
"config_test": false,
"has_no_... |
from __future__ import absolute_import, division, print_function
import paramiko
from contextlib import contextmanager
from toolz import keyfilter, memoize, take
from datashape import discover
import re
from ..directory import _Directory, Directory
from ..utils import keywords, tmpfile, sample
from ..resource import ... | {
"repo_name": "mrocklin/into",
"path": "into/backends/ssh.py",
"copies": "1",
"size": "4636",
"license": "bsd-3-clause",
"hash": 8174014660481400000,
"line_mean": 25.7976878613,
"line_max": 103,
"alpha_frac": 0.6147540984,
"autogenerated": false,
"ratio": 3.520121488230828,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import pickle
from collections import OrderedDict
import numpy as np
import theano.tensor as T
from functools import reduce
from .. import optimizer
from ..layers import layers
class ModelBasis(object):
"""
Arguments
model_config: mod... | {
"repo_name": "jongyookim/IQA_BIECON_release",
"path": "IQA_BIECON_release/models/model_basis.py",
"copies": "1",
"size": "12088",
"license": "mit",
"hash": -2358152926982187000,
"line_mean": 34.8694362018,
"line_max": 79,
"alpha_frac": 0.524652548,
"autogenerated": false,
"ratio": 3.841118525579... |
from __future__ import absolute_import, division, print_function
import pickle
from distutils.version import LooseVersion
from textwrap import dedent
import numpy as np
import pandas as pd
import pytest
import xarray as xr
import xarray.ufuncs as xu
from xarray import DataArray, Dataset, Variable
from xarray.core.py... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/tests/test_dask.py",
"copies": "1",
"size": "32253",
"license": "apache-2.0",
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"config_test":... |
from __future__ import absolute_import, division, print_function
import pickle
import random
from collections import namedtuple
import pandas as pd
from caar.cleanthermostat import _sort_meta_in_col_order, dict_from_file
from future import standard_library
standard_library.install_aliases()
Cycle = namedtuple('Cy... | {
"repo_name": "nickpowersys/CaaR",
"path": "caar/history.py",
"copies": "1",
"size": "12592",
"license": "bsd-3-clause",
"hash": -2693026809062823000,
"line_mean": 42.8745644599,
"line_max": 172,
"alpha_frac": 0.6194409149,
"autogenerated": false,
"ratio": 3.9923906150919466,
"config_test": fal... |
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