seq_id string | text string | repo_name string | sub_path string | file_name string | file_ext string | file_size_in_byte int64 | program_lang string | lang string | doc_type string | stars int64 | dataset string | pt string | api list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
425850101 | import numpy as np
from sklearn.linear_model import LinearRegression
import pickle
# num_tuples = 36244344
data=np.loadtxt('ranges.txt')
# for i in range(num_tuples):
# X.append(i)
# X = np.array(X)
# X=X.reshape(-1,1)
n = data.size
X = []
for i in range(n):
X.append([])
X[i].append(data[i]**0.5)
X[i].append(d... | null | index_scan/vu_model_1/quadratic.py | quadratic.py | py | 604 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.loadtxt",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearR... |
160940927 | r"""Test `lmp.config.BaseConfig.__iter__`.
Usage:
python -m unittest test.lmp.config.test_iter
"""
# built-in modules
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import inspect
import unittest
from typing i... | null | test/lmp/config/test_iter.py | test_iter.py | py | 4,026 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "unittest.TestCase",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "inspect.signature",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "lmp.config.BaseConfig.__iter__",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_... |
455501056 | import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from sklearn.decomposition import PCA
import utils
df_wine = utils.read_csv('wine.data',
... | null | ml_05_02_LDA.py | ml_05_02_LDA.py | py | 3,291 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "utils.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train... |
631273001 | from django.conf import settings
from django.http import Http404
from django.shortcuts import get_object_or_404
from nepal.mail.models import MailAlias
def get_alias_or_404(request, alias_id):
alias = get_object_or_404(MailAlias, pk=alias_id)
if alias.domain.profile == request.user:
return alias
... | null | nepal/mail/shortcuts.py | shortcuts.py | py | 712 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.shortcuts.get_object_or_404",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "nepal.mail.models.MailAlias",
"line_number": 7,
"usage_type": "argument"
},
{
"api_name": "django.http.Http404",
"line_number": 12,
"usage_type": "call"
},
{
... |
8253301 | import numpy as np
from gym.envs.mujoco.ant_v3 import AntEnv
class Ant(AntEnv):
def __init__(self, get_reward=None, *args, **kwargs):
kwargs['exclude_current_positions_from_observation'] = False
super().__init__(*args, **kwargs)
if self._exclude_current_positions_from_observation == True:... | null | envs/ant.py | ant.py | py | 1,358 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "gym.envs.mujoco.ant_v3.AntEnv",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "numpy.testing.assert_almost_equal",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "numpy.testing",
"line_number": 43,
"usage_type": "attribute"
}
] |
319709123 | #!/usr/bin/python3
# (c) Bernhard Tittelbach, 2019
### this file replaces ssh-status-json.sh
### meant to be run via .ssh/authorized_keys as forced command=
import json
import sys
import os
import shutil
env_ssh_original_command_ = "SSH_ORIGINAL_COMMAND"
spaceapi_status_dst_filepath_="/dev/shm/www/spaceapi.json"
spa... | null | scripts/ssh-status-json.py | ssh-status-json.py | py | 1,575 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.dirname",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "os.path.exists",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_numbe... |
54947714 | import os
import itertools
from rpy2.robjects.packages import importr
class HarryPotterTextRDA(object):
def __init__(self, book_dir="data/temp", to_text=False):
self.book_dir = book_dir
self.book_name = [
"philosophers_stone",
"chamber_of_secrets",
"prisoner_of... | null | harry-old.py | harry-old.py | py | 2,988 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "rpy2.robjects.packages.importr",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "os.path.join... |
96695863 | import discord
import aiohttp
import re
import traceback
from bs4 import BeautifulSoup as b_soup
from datetime import datetime
from random import choice
from io import BytesIO
from urllib.parse import quote_plus
from discord.ext import commands
from .utils import checks, time
class Misc:
def __init__(self, bot):... | null | cogs/command_misc.py | command_misc.py | py | 5,921 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "random.choice",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "discord.Embed",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands.co... |
276071996 | from __future__ import print_function
import googleapiclient.discovery
import pickle
import os.path
import sys
import json
from google.oauth2 import service_account
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Requ... | null | add_delegate.py | add_delegate.py | py | 2,038 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "google.oauth2.service_account.Credentials.from_service_account_file",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "google.oauth2.service_account.Credentials",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "google.oauth2.service_account"... |
387982521 | import requests
import urllib.parse
from bs4 import BeautifulSoup
from db import *
find_card_with_id_query = 'select card_number from cards where card_number = {CARD_NUMBER}'.format(CARD_NUMBER='1')
def get_soup_for_card_info(card_url, card_name):
url = 'https://' + urllib.parse.quote(card_url.format(CARD_NAME=car... | null | scrapper_for_product_details.py | scrapper_for_product_details.py | py | 4,643 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urllib.parse.parse.quote",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "urllib.parse.parse",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "urllib.parse",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "request... |
45935797 | from __future__ import unicode_literals
from collections import OrderedDict
import importlib
import logging
import os
import sys
import unittest
def getTests(targets):
# If a string was passed in, put it into a list.
if type(targets) != list:
targets = [targets]
# Make sure there are no duplicate... | null | green/loader.py | loader.py | py | 4,387 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "collections.OrderedDict",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "unittest.TestLoad... |
611902143 | # --------------------------------------------------------
# DaSiamRPN
# Licensed under The MIT License
# Written by Qiang Wang (wangqiang2015 at ia.ac.cn)
# --------------------------------------------------------
import torch.nn as nn
import torch.nn.functional as F
import torch
import numpy as np
class SiamRPN(nn.... | null | code/net.py | net.py | py | 5,200 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.nn.Module",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"lin... |
380129970 | from typing import Any, Dict
from azure.storage.blob import BlobClient, BlobServiceClient
from ..config import local_config
from .base import Source
class AzureBlobStorage(Source):
"""
A class for pulling data from the Azure Blob Storage
(do not confuse with Azure Data Lake Gen1 and Azure Data Lake Gen2... | null | viadot/sources/azure_blob_storage.py | azure_blob_storage.py | py | 3,085 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "base.Source",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "config.local_config.get",
"line... |
453684984 | import re
import json
from collections import Counter
file = open("all_reviews_texts_318352.txt", encoding='UTF8')
reg = []
massiv = []
massivCat2 = []
goda = []
for line in file:
res = re.search(r'\d\d.\d\d.\d{4}', line)
if res:
reg.append(res.group()[6:])
pik = json.loads(line)
if... | null | week1.py | week1.py | py | 1,069 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "re.search",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"l... |
153155237 | import random
import matplotlib.pyplot as plt
from matplotlib import style
style.use('fivethirtyeight')
fig = plt.figure()
def create_plots():
xs = [i+1 for i in range(10)]
ys = [random.randrange(1, 11, 1) for _ in range(10)]
return xs, ys
if __name__ == "__main__":
ax1 = plt.subplot2grid((6,... | null | p5_subplots.py | p5_subplots.py | py | 784 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "matplotlib.style.use",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "matplotlib.style",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "matplotli... |
41222607 |
# -*- coding: utf-8 -*-
import logging
import Artus.Utility.logger as logger
log = logging.getLogger(__name__)
import array
import fcntl
import re
import termios
def flattenList(listOfLists):
"""
flatten 2D list
return [1, 2, 3, 4, ...] for input [[1, 2], [3, 4, ...], ...]
"""
return [item for subList in list... | null | Utility/python/tools.py | tools.py | py | 1,887 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "array.array",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "fcntl.ioctl",
"line_number... |
639231642 | from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner import load_checkpoint, force_fp32
from torch import nn as nn
import torch
from mmdet.models import BACKBONES
@BACKBONES.register_module()
class SECONDMASK(nn.Module):
"""Backbone network for SECOND/PointPillars/PartA2/MVXNet.
Args:
... | null | mmdet3d/models/backbones/second_mask.py | second_mask.py | py | 6,081 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "torch.nn.Module",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "mmcv.cnn.build_conv_layer",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "mmcv.cnn.buil... |
469944025 | #Q2
import pylab as g
import pandasql as s
import pandas as p
position_d = p.read_excel(r"C:\Users\Hp\Documents\Data Science Project\data\Football Data New Excel Format.xlsx","Position")
wage_d = p.read_excel(r"C:\Users\Hp\Documents\Data Science Project\data\Football Data New Excel Format.xlsx","Wage")
df = p.concat(... | null | Analysis/Post Visualization/Position/Q2.py | Q2.py | py | 636 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pandas.read_excel",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pandas.concat",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandasql.sqldf",
"... |
546869069 | import argparse
import sys
from .._main import (
categorize_urls,
find_files,
find_urls,
is_allowed,
print_to_screen,
read_config,
)
try:
from importlib import metadata
except ImportError:
# Python 3.7 and earlier
pass
def check(argv=None):
# Parse command line arguments.
... | null | src/deadlink/_cli/check.py | check.py | py | 4,368 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "_main.find_files",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "_main.read_config",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "_main.is_allowed",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "_main.find_urls",... |
433427436 | '''
SI 618: HW 2
Uniqname: gracfu
'''
import urllib2, re, json, time, pydot, itertools
from collections import OrderedDict
from bs4 import BeautifulSoup
#step 1: fetch IMDB top 100 and save in 'step1.html'
url = urllib2.urlopen('http://www.imdb.com/search/title?at=0&sort=num_votes&count=100')
movie = unicode(url.read(... | null | imdb_costars.py | imdb_costars.py | py | 1,839 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "urllib2.urlopen",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "urllib2.urlopen",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"l... |
303913227 | import random
import argparse
import json
import os
import torch
from torch import optim
import torch.nn as nn
from torch.nn.utils import clip_grad_norm_
import params
from utils import init_model, save_models, \
build_vocab_music, load_data, get_data_loader, Vocabulary
from model import Encoder, KnowledgeEncoder, ... | null | train.py | train.py | py | 9,645 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.backends",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "torch.backends",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "argpa... |
320344868 | # coding: utf-8
# Create your views here.
from django.http import HttpResponse
from blog.models import Post,Tag,Category
from django.shortcuts import render,get_object_or_404
import markdown
'''
def index(request):
return render(request,'static/index.html',context={
'title':'我的博客首页',
'welcome':'... | null | Django_ch/myblog/blog/views.py | views.py | py | 983 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "blog.models.Post.objects.all",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "blog.models.Post.objects",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "blog.models.Post",
"line_number": 23,
"usage_type": "name"
},
{
"api_n... |
566089895 | # Matej Badin | UHP | 2019 |
# -------------------------------------------------------------------- |
# Packages needed : numpy, re, os, pandas, Camelot, OpenCV |
# pdfminer.six -- requirement already for Camelot |
# ----------------------... | null | CRZ_klasifikacia_zmluv/03_extract_tables.py | 03_extract_tables.py | py | 4,061 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.getcwd",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pdfminer.pdfparser.PDFParser",
... |
371941526 | #!/usr/bin/env python
from setuptools import setup, Extension
liboio = Extension('oio-streams',
sources=[],
libraries=['oio-streams'])
setup(name='pyostreams',
version = '0.0.3',
description = 'Python interface to ciostreams .',
author = 'Angelo Frangione',
author_e... | null | pypi_install_script/pyostreams-0.0.3.tar/setup.py | setup.py | py | 494 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "setuptools.Extension",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "setuptools.setup",
"line_number": 11,
"usage_type": "call"
}
] |
357557741 | import os
import json
import time
import logging
from hpbandster.core.result import logged_results_to_HBS_result
from autoPyTorch.pipeline.base.pipeline_node import PipelineNode
class SaveResults(PipelineNode):
def fit(self, result_dir, fit_duration, test_score, fit_result, autonet, task_id):
if (task_id... | null | autoPyTorch/utils/benchmarking/benchmark_pipeline/save_results.py | save_results.py | py | 1,115 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "autoPyTorch.pipeline.base.pipeline_node.PipelineNode",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "time.sleep",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"... |
162965801 | from common import *
from matplotlib.lines import Line2D
import matplotlib.ticker as ticker
import os
from matplotlib import container
from common import *
from collections import OrderedDict
import pandas
from matplotlib.markers import MarkerStyle
import traceback
series = ["loadvslat-kthmorning-cx5/RSS" , "loadvsla... | null | loadvslat/plotvslat.py | plotvslat.py | py | 6,393 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.path.dirname",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "os.sep",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "os.path.basename",
"line... |
55875103 | from android import activity
from able.android.jni import PythonBluetooth
from able.dispatcher import BluetoothDispatcherBase
from jnius import autoclass
Activity = autoclass('android.app.Activity')
BLE = autoclass('org.able.BLE')
BluetoothGattDescriptor = autoclass(
'android.bluetooth.BluetoothGattDescriptor')
... | null | able/android/dispatcher.py | dispatcher.py | py | 1,535 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "jnius.autoclass",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "jnius.autoclass",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "jnius.autoclass",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "able.dispatcher.Bluetoo... |
412871986 | """
Create database example with Peewee ORM, sqlite and Python
"""
import logging
import customer_model as cm
logging.basicConfig(level=logging.INFO)
LOGGER = logging.getLogger(__name__)
LOGGER.info('Creating a database using the customer model')
cm.database.create_tables([cm.Customer])
cm.database.close()
| null | students/Shirin_A/lesson03/assignment/src/create_database.py | create_database.py | py | 316 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.basicConfig",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "customer_model.d... |
243499487 | import warnings
import sys
import numpy as np
import pandas as pd
from pandas import Series
from statsmodels.tsa.arima_model import ARIMA
from sklearn.metrics import mean_squared_error
def mean_absolute_percentage_error(y_true, y_pred):
rng = len(y_true)
diff = []
for i in range(0,rng):
diff.append(y_true[i] - ... | null | System_Evaluation_Part/Arima-Evaluate.py | Arima-Evaluate.py | py | 1,899 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.abs",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.mean",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "statsmodels.tsa.arima_model.ARIMA",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "pandas.read_cs... |
535027771 | """
0420011 Отчетность об операциях с денежными средствами
некредитных финансовых организаций.
Раздел 1. Операции, совершенные с использованием банковских счетов
некредитной финансовой организации
1.1. Виды и суммы операций, совершенных по банковским счетам
некредитной финансовой организации Обороты
http://www.cbr.ru/... | null | module/forms_maker/sr_0420001_ods_r1_p1_p1_oboroty.py | sr_0420001_ods_r1_p1_p1_oboroty.py | py | 7,989 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "openpyxl.utils.column_index_from_string",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "module.functions.razdel_name_row",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "openpyxl.utils.column_index_from_string",
"line_number": 59,
"us... |
64040877 | from helpers.base_helper import TrainTestHelper, transform_train, transform_test
from utils import get_channels_axis,save_roc_pr_curve_data, show_roc_pr_curve_data
from models.ae_backbone import CAE_backbone, AE_backbone
from keras2pytorch_dataset import trainset_pytorch
import torch.utils.data as data
import torch
im... | null | helpers/rdae_helper.py | rdae_helper.py | py | 5,710 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "helpers.base_helper.TrainTestHelper",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "models.ae_backbone.CAE_backbone",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "models.ae_backbone.AE_backbone",
"line_number": 29,
"usage_type": "ca... |
273266927 | from PIL import Image
import os
from resizeimage import resizeimage
for filename in os.listdir(f"{os.path.dirname(__file__)}/../assets/items_female"):
if filename.endswith(".jpg"):
im = Image.open(f"{os.path.dirname(__file__)}/../assets/items_female/{filename}")
if im.size[1] != 470:
r... | null | _src/female_img_resizer.py | female_img_resizer.py | py | 538 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "os.listdir",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.open",
"line_numbe... |
487852188 | # -*- encoding:utf-8 -*-
# Copyright (c) Alibaba, Inc. and its affiliates.
import json
import logging
import os
import tensorflow as tf
from tensorflow.python.lib.io import file_io
from easy_rec.python.main import _train_and_evaluate_impl
from easy_rec.python.utils import config_util
from easy_rec.python.utils import... | null | easy_rec/python/train_eval.py | train_eval.py | py | 4,873 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tensorflow.__version__",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.compat",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "logging.basicConfig",
"line_number": 18,
"usage_type": "call"
},
{
"api_name":... |
588560226 | import os, sys
import numpy as np
from skimage import io,transform
img_folder_path = sys.argv[1]
target_img = sys.argv[2]
if(img_folder_path[0] == '/'):
img_folder_path = img_folder_path[1:len(img_folder_path)]
# read image & construct X
for image_no in range(0,415):
img = io.imread(img_folder_path + '/' + str(ima... | null | hw6/pca.py | pca.py | py | 1,096 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.argv",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "skimage.io.imread",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "skimage.io",
"line_nu... |
142366334 | from django.db import DatabaseError
from user_office.models import ICO_Info
from blockchain.ico.contracts import CrowdsaleContract
from ico_portal.utils.service_object import ServiceObject, service_call
class SyncICOInfo(ServiceObject):
def get_total_supply(self, context):
try:
total_supply =... | null | blockchain/ico/services/sync_ico_info.py | sync_ico_info.py | py | 1,043 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "ico_portal.utils.service_object.ServiceObject",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "blockchain.ico.contracts.CrowdsaleContract",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "user_office.models.ICO_Info",
"line_number": 18,
... |
291919786 | from sklearn import linear_model
import os
import random
FEATURESMAP = {
1: ['weight0', 'height0', 'waistline0', 'checkinCount1'],
2: ['weight1', 'height0', 'waistline1', 'checkinCount2'],
3: ['weight2', 'height0', 'waistline2', 'checkinCount3'],
4: ['weight3', 'height0', 'waistline3', 'checkinCount4'... | null | git/NeuralNet_predict_weight/min_max_t1/t1/predict_oneStep3.py | predict_oneStep3.py | py | 9,164 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "random.uniform",
"line_number": 169,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LogisticRegression",
"line_number": 321,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model",
"line_number": 321,
"usage_type": "name"
}
] |
531643697 | import numpy as np
import random
def est_entropy(probs):
res = 0
nbz = 0
for prob in probs:
if prob == 0:
nbz += 1
else:
res = res - prob * np.log2(prob)
return res, nbz
def count_value(listvalue, value):
return np.sum(np.array(listvalue) == value)
def get_probs(x):
minrange = int(np.min(x))
... | null | range_coding.py | range_coding.py | py | 17,153 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.log2",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.sum",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.min",
"line_number": 18,
... |
501615788 | #! /usr/bin/env python
#
# Copyright (C) 2016 Basho Technologies, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | null | riak_mesos/config.py | config.py | py | 9,205 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "json.load",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 51,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 97,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 131,
... |
431316177 | # 멀티 프로세싱을 통한 웹 스크래핑 1
import requests
from bs4 import BeautifulSoup as bs
import time
from multiprocessing import Pool
def get_link():
url = 'https://beomi.github.io/beomi.github.io_old/'
data = requests.get(url).text
soup = bs(data, 'html.parser')
print(soup)
my_title = soup.select('h3 > ... | null | pypro2/net/multi_scrap1.py | multi_scrap1.py | py | 881 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"... |
126262760 | # -*- coding: utf-8 -*-
# =============================================================================
# Step 1 Import Libraries.
# =============================================================================
import numpy as np
import matplotlib.pyplot as plt
from keras.models import Model, Sequential, load_model
f... | null | imageClassifierUseCNN.py | imageClassifierUseCNN.py | py | 4,933 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "keras.models.Sequential",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "keras.layers.Convolution2D",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "keras.layers.Activation",
"line_number": 29,
"usage_type": "call"
},
{
"api_na... |
539751250 | #The aim is to put any size of glasses on any size of frontal face image. The code has already been developing,
#and for future, I want to help people choose their glasses by just looking a front facing camera at the end of the work.
import cv2
import numpy as np
face_cascade = cv2.CascadeClassifier('Haarcas... | null | Put a glass on a face.py | Put a glass on a face.py | py | 3,103 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.CascadeClassifier",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.CascadeClassifier",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
... |
558364945 | from PIL import Image
import cv2
import numpy as np
class ChineseCharacter:
def __init__(self, font: str, value: str, image: Image.Image, source: Image.Image =None, location: list =None):
self.font = font
self.value = value if value != '' and value != '.' and value != '\\' and value != '\/' else ... | null | Character.py | Character.py | py | 1,301 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "PIL.Image.Image",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "PIL.Image.Image",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image",
"li... |
30846261 | from django.conf import settings
from django.contrib.auth.models import User
from django.core.mail import send_mail
from django.utils import timezone
from apps.core.models import ServiceMap, UserProfile, EmailAuthToken, ResetPWToken
from apps.core.forms import UserForm, UserProfileForm
from secrets import token_hex
fro... | null | apps/core/backends.py | backends.py | py | 10,031 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.models.User.objects.filter",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.models.User.objects",
"line_number": 31,
"usage_type... |
430465777 | import os
import errno
import uuid as _uuid
import logging
class AgentID:
"""An identifier for an agent or a topic."""
def __init__(self, name, is_topic=False):
self.name = name
if is_topic:
self.is_topic = True
else:
self.is_topic = False
class Performative:... | null | src/main/python/fjagepy/org_arl_fjage/__init__.py | __init__.py | py | 3,282 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "uuid.uuid4",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 74,
"usage_type": "attribute"
},
{
"api_name": "os.path.exists",
... |
291369013 | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.transforms.processing import TestTimeAug
from mmengine.dataset.sampler import DefaultSampler
from mmengine.visualization.vis_backend import LocalVisBackend
from mmdet3d.datasets.semantickitti_dataset import SemanticKittiDataset
from mmdet3d.datasets.transforms.... | null | mmdet3d/configs/_base_/datasets/semantickitti.py | semantickitti.py | py | 8,373 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "mmdet3d.datasets.transforms.loading.LoadPointsFromFile",
"line_number": 87,
"usage_type": "name"
},
{
"api_name": "mmdet3d.datasets.transforms.loading.LoadAnnotations3D",
"line_number": 93,
"usage_type": "name"
},
{
"api_name": "mmdet3d.datasets.transforms.loading.... |
517236678 | from django.urls import path
from store.views import (
GroupListView,
ProductDetailView,
GroupDetailView,
CartView,
AddToCartView,
DeleteFromCartView,
ChangeQTYView,
MakeOrderView,
ProductSearchView,
ProductListView,
EmailView,
)
urlpatterns = [
path('', GroupListView.a... | null | store/urls.py | urls.py | py | 1,111 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.urls.path",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "store.views.GroupListView.as_view",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "store.views.GroupListView",
"line_number": 18,
"usage_type": "name"
},
{
"api_... |
441732611 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import collections
import logging
import matplotlib.pyplot as plt
def defaultPlotStruct(subplot_size, title=None, figsize=None,
subplot_space=0.03, borderwidth=1, xlabel=None,
xticklabel_positions=None, xticklabel_values=None,
... | null | mestrado/plotModels.py | plotModels.py | py | 12,285 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.debug",
"line_number": 70,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 73,
"usage_type": "name"
},
{
"api_name": "collection... |
458288094 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('catalog', '0003_auto_20150525_1419'),
]
operations = [
migrations.CreateModel(
name='Order',
fields=... | null | catalog/migrations/0004_auto_20150525_2211.py | 0004_auto_20150525_2211.py | py | 1,084 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 14,
"usage_type": "call"
},
... |
348549713 | from collections import OrderedDict
from pprint import pprint
from collections import defaultdict
print('############################### 5.1234')
from zoo import hours as info
#import zoo
info()
print('############################### 5.56')
plain = dict (
a = 1,
b = 2,
c =... | null | ex5.py | ex5.py | py | 668 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "zoo.hours",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "collections.defaultdic... |
246616154 | # Disable warnings
import warnings
warnings.filterwarnings("ignore")
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import itertools
from sklearn.model_selection import train_test_split
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import MinMaxScal... | null | explore.py | explore.py | py | 7,731 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "sklearn.prep... |
444838679 | def bookSearch(book,page):
import requests
from bs4 import BeautifulSoup
import time
import random
d = {}
for i in range(page):
url = 'https://search.books.com.tw/search/query/cat/all/key/{}/sort/1/page/{}/v/0/'.format(book,i)
res = requests.get(url)
soup = BeautifulSoup(... | null | 博客來書籍搜尋.py | 博客來書籍搜尋.py | py | 1,415 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "requests.get",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_n... |
269136302 | from django.http import HttpResponseRedirect
from django.conf import settings
from re import compile
from django.contrib import auth
from django.contrib.auth.middleware import RemoteUserMiddleware
from django.contrib.auth.backends import RemoteUserBackend
from django.contrib.auth import load_backend, BACKEND_SESSION_KE... | null | files/project/middleware.py | middleware.py | py | 1,565 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.contrib.auth.middleware.RemoteUserMiddleware",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "django.contrib.auth.load_backend",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.contrib.auth.BACKEND_SESSION_KEY",
"line_number": ... |
96642081 | import sys
import os.path
sys.path.append(os.path.dirname(sys.path[0]))
import json
from data_retrieval.get_speedlimits import SpeedLimitDataRetrieval
class MockResponse:
def __init__(self):
self.json_data = json.dumps({})
self.status_code = 400
def good_speedlimit_response(self):
... | null | routemodel/tests/test_speedlimit_data_retrieval.py | test_speedlimit_data_retrieval.py | py | 1,265 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "os.path.path.dirname",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "os.path.path",
"l... |
584630010 | import logging
import pytest
from logger import sum_even_numbers
def test_sum_numbers_function_works(caplog):
assert sum_even_numbers([2, 9, 4, 11, 6]) == 12
def test_sum_numbers_logging(caplog):
caplog.set_level(logging.INFO, logger="app")
sum_even_numbers(list(range(1, 11)))
assert len(caplog.re... | null | 125_algorithms/_examples/_algorithms_challenges/pybites/intermediate/315/test_logger.py | test_logger.py | py | 1,116 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logger.sum_even_numbers",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "logger.sum_even_numbers",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "logg... |
464937976 | from sinesp_client import SinespClient
from flask import Flask, jsonify, request
import os, json
app = Flask(__name__)
@app.route('/', methods=['GET'])
def video():
if request.args.get('placa'):
placa = request.args.get('placa')
sc = SinespClient()
resultado = sc.search(placa)
re... | null | app.py | app.py | py | 506 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.request.args.get",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.request.args",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "flask.request... |
374014832 | import re
from datetime import datetime
from typing import Dict, Generator, Optional
from urllib.parse import quote
from torrent_domains import abstract
from torrent_domains.abstract import Domain, SearchParameter
def parse_row(item: str, i: int, parse_tracker: bool) -> Dict:
torrent = {}
# name
try:
... | null | torrent_domains/btdb.py | btdb.py | py | 3,037 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "re.finditer",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torrent_domains.abstract.log_missing_keys",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torr... |
310949787 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
########## Collect count files ##########
# Author: Huitian (Yolanda) Diao
# Apr 30, 2019
# Dependencies:
# - HTseq-count output count files
########## Import ##########
import os
import csv
import glob
from astropy.io import ascii
########## Self defined functions ####... | null | codes_locol/z_old/2_1_collect_count_files.py | 2_1_collect_count_files.py | py | 5,499 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "csv.reader",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.walk",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 41,
... |
244006145 | from __future__ import print_function
import json
from string import Template
import requests
from frinx_rest import odl_url_base, odl_headers, odl_credentials, parse_response
odl_url_cli_mount = odl_url_base + "/config/network-topology:network-topology/topology/cli/node/"
odl_url_cli_oper = odl_url_base + "/operat... | null | microservices/netinfra_utils/workers/cli_worker.py | cli_worker.py | py | 11,835 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "frinx_rest.odl_url_base",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "frinx_rest.odl_url_base",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "frinx_rest.odl_url_base",
"line_number": 12,
"usage_type": "name"
},
{
"api_name"... |
26707363 | import pygame
from game.base_monster import BaseMonster
class LargeMonster(BaseMonster):
monster_id = "large"
def __init__(self, monster_path, image_dictionary, monster_type_dict, all_monster_sprites, screen_offset,
collision_grid, splat_loader, ui_manager, *groups):
image = image_di... | null | game/large_monster.py | large_monster.py | py | 797 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "game.base_monster.BaseMonster",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "pygame.Color",
"line_number": 14,
"usage_type": "call"
}
] |
575109379 | #! /usr/bin/env python
from obspy import read
import numpy as np
from glob import glob
from obspy.core import Trace, Stream, Stats
import matplotlib.pyplot as plt
from obspy.signal.filter import bandpass, highpass, lowpass
from scipy.signal import fftconvolve, hanning
from problem_setup import *
from scipy.signal impo... | null | SYNTHETIC/MULTIPLE/proc.py | proc.py | py | 11,832 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "obspy.core.Stream",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "glob.glob",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "obspy.read",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.random.uniform",
"li... |
197743814 | import numpy as np
import tensorflow as tf
from keras import backend, losses
from keras.utils.generic_utils import register_keras_serializable
from keras.utils.losses_utils import ReductionV2 as Reduction
@register_keras_serializable(package='SegMe')
class SobelEdgeLoss(losses.LossFunctionWrapper):
""" Proposed i... | null | segme/loss/sobel_edge.py | sobel_edge.py | py | 2,272 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "keras.losses.LossFunctionWrapper",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "keras.losses",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "keras.utils.losses_utils.ReductionV2.AUTO",
"line_number": 18,
"usage_type": "attribute"... |
566338668 | from flask import redirect, render_template, request, url_for, Blueprint, flash
from project.users.models import User, TeamUsers
from project.teams.models import Team
from project.users.views import ensure_correct_user
from project.teams.forms import TeamForm
from flask_login import current_user, login_required
from pr... | null | project/teams/views.py | views.py | py | 5,067 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Blueprint",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "flask.request.method",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "project.teams.... |
369960636 | import os
import csv
import sys
import json
import matplotlib.pyplot as plt
import pandas as pd
import csv
class TweetFilter:
"""
tweetsDirectory: contains previously collected (unfiltered) tweets
expandedDirectory: contains results of expanded URLs that match known fake news domains
domainJson: he... | null | postExpandUrl/FakeTweet.py | FakeTweet.py | py | 7,814 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.platform",
"line_number": 31,
"usage_type": "attribute"
},
{
"api_name": "sys.argv.append",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "sys.argv.append",
... |
65176461 | from django.conf.urls import url, include
from rest_framework.routers import DefaultRouter
from apps._messages.views import MessagesViewSet, AboutPatientViewSet, MessagesMetaView
router = DefaultRouter()
router.register('about', AboutPatientViewSet)
router.register('', MessagesViewSet)
urlpatterns = [
url('meta... | null | lifeline-backend-master/apps/_messages/urls.py | urls.py | py | 430 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "rest_framework.routers.DefaultRouter",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "apps._messages.views.AboutPatientViewSet",
"line_number": 7,
"usage_type": "argument"
},
{
"api_name": "apps._messages.views.MessagesViewSet",
"line_number": 8,
... |
353720106 | import datetime
import logging
date = datetime.datetime.now()
class Logger:
def __init__(self, path,logName='__name__'):
self._logger = logging.getLogger(logName)
handler = logging.FileHandler(path + "\\"+date.strftime('%Y%m%d%H%M%S%f') + '.log', mode='w')
formatter = logging.Formatter(
... | null | Utils/logger.py | logger.py | py | 824 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "datetime.datetime.now",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.F... |
288163773 | #vajab veel natuke tuunimist, igaks juhuks varvid veel uhe korra ule vaadata, eelisjarjekorras pall
#aared praegu ainult valged
import numpy as np
import cv2
print(cv2.__version__)
cap = cv2.VideoCapture(0)
img = np.zeros((480, 640, 3), np.uint8) # tuhi must pilt , selle peale joonistatakse kontuurid
kernel = np.one... | null | backup2.py | backup2.py | py | 5,833 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cv2.__version__",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"li... |
378367546 | import numpy as np
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix,classification_report,accuracy_score
import pickle
#same results for same model, makes it deterministic
np.random.seed(1234)
#reading data
input = np.load("../datasets_nav_strategic/Coopnav_50ti... | null | KNearest/knearest_train_nav.py | knearest_train_nav.py | py | 848 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.random.seed",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "numpy.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"lin... |
308100158 | """
Extract the location
"""
import nltk
from nltk.corpus import stopwords
import pymongo
import re
import distance
try:
import xml.etree.cElementTree as ET
except ImportError:
import xml.etree.ElementTree as ET
# Used for title standardization
stand_title = ["Others", "Introduction and Background", "Material... | null | 3_location_extract.py | 3_location_extract.py | py | 6,803 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "xml.etree.ElementTree.ElementTree",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "xml.etree.ElementTree.ElementTree",
"line_number": 61,
"usage_type": "call"
},
... |
117326964 | #!/usr/bin/env python3
import argparse
import copy
import datetime
import json
import numpy as np
from collections import OrderedDict
from pprint import pprint
from pymongo import MongoClient
from gdash.config import config
from gdash.queryexecutor import QueryExecutor
from gdash.logtools import set_logger
from gdash... | null | gdash/pingstats.py | pingstats.py | py | 6,984 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "gdash.mongo_tools.get_mongo_uri",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 105,
"usage_type": "call"
},
{
"api_... |
557332180 | # Copyright 2017 Catalyst IT Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | null | qinling/utils/etcd_util.py | etcd_util.py | py | 1,748 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "oslo_config.cfg.CONF",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "oslo_config.cfg",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "etcd3gw.client",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "oslo_utils.u... |
472251537 | from elegy import types
import typing as tp
import jax.numpy as jnp
from elegy import utils
from elegy.losses.loss import Loss, Reduction
def mean_percentage_absolute_error(
y_true: jnp.ndarray, y_pred: jnp.ndarray
) -> jnp.ndarray:
"""
Computes the mean absolute percentage error (MAPE) between labels and... | null | elegy/losses/mean_absolute_percentage_error.py | mean_absolute_percentage_error.py | py | 5,915 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "jax.numpy.ndarray",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "jax.numpy",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "jax.numpy.abs",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "jax.numpy",
"line_nu... |
59995532 | # assembler_word.py
r'''The defining word for all assembler words.
Use this to write functions in assembler.
'''
import itertools
from ucc.database import assembler, ast, crud
from ucclib.built_in import declaration
class assembler_word(declaration.word):
def parse_file(self, parser, debug = 0):
inst... | null | ucclib/built_in/assembler_word.py | assembler_word.py | py | 5,089 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "ucclib.built_in.declaration.word",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "ucclib.built_in.declaration",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "ucc.database.assembler.block",
"line_number": 20,
"usage_type": "call"
... |
171293463 | import theano
from theano import tensor as T
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
import numpy as np
from theano.tensor.nnet.conv import conv2d
from theano.tensor.signal.downsample import max_pool_2d
import load_cifar
# from ionmf.factorization.onmf import onmf
import roc_auc as auc
imp... | null | cnnet_separated_cifar.py | cnnet_separated_cifar.py | py | 8,277 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "theano.sandbox.rng_mrg.MRG_RandomStreams",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "theano.config",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_nam... |
458593131 | # -*- coding: utf-8 -*-
from Acquisition import aq_parent
from brasil.gov.agenda.interfaces import IAgendaDiaria
from five import grok
from Products.CMFCore.utils import getToolByName
from zope.component import getMultiAdapter
grok.templatedir('templates')
class AgendaDiariaView (grok.View):
''' Visao padrao da ... | null | src/brasil/gov/agenda/browser/agendadiaria.py | agendadiaria.py | py | 3,652 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "five.grok.templatedir",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "five.grok",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "five.grok.View",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "five.grok",
"li... |
63371501 | import logging
from sklearn.feature_extraction.text import CountVectorizer
from opendeep.log.logger import config_root_logger
from datasets.util import FileParser
from opendeep.data.memory_matrix import MemoryMatrix
from opendeep.models.multi_layer.generative_stochastic_network import GSN
log = logging.getLogger(__n... | null | test_gsn_bow.py | test_gsn_bow.py | py | 2,527 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "opendeep.log.logger.config_root_logger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "datasets.util.FileParser",
"line_number": 19,
"usage_type": "call"
},
{
... |
415294446 | from django.contrib.auth import authenticate
from django.core.checks import messages
from django.shortcuts import render, render_to_response
from django.http import Http404, HttpResponseRedirect, HttpResponse
from django.http import HttpResponse, HttpResponseRedirect, Http404
from django.contrib import messages
from Sc... | null | Homepage/views.py | views.py | py | 23,357 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "models.StudentProfile",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "models.StudentProfile",
"line_number": 94,
"usage_type": "call"
},
{
"api_name": "d... |
609557972 | #############################################################
## ASSIGNMENT 2 CODE SKELETON
## RELEASED: 1/17/2018
## DUE: 1/24/2018
## DESCRIPTION: In this assignment, you will explore the
## text classification problem of identifying complex words.
## We have provided the following skeleton for your code,
## with sev... | null | HW2/hw2.py | hw2.py | py | 26,564 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "collections.defaultdict",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "nltk.stem.WordNetLemmatizer",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "nltk.stem",
"line_number": 40,
"usage_type": "attribute"
},
{
"api_name": "nl... |
608978210 | """
Tests for salt.modules.zfs on Solaris
"""
import pytest
import salt.loader
import salt.modules.zfs as zfs
import salt.utils.zfs
from tests.support.mock import MagicMock, patch
from tests.support.zfs import ZFSMockData
@pytest.fixture
def utils_patch():
return ZFSMockData().get_patched_utils()
@pytest.fixt... | null | tests/pytests/unit/modules/test_zfs_solaris10.py | test_zfs_solaris10.py | py | 1,698 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "tests.support.zfs.ZFSMockData",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pytest.fixture",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "salt.loader.loader.utils",
"line_number": 21,
"usage_type": "call"
},
{
"api_na... |
285553881 | from json import loads as json2py
from json import dumps as py2json
class ArffJsonDocument(object):
def __init__(self, jsonObject):
rawData = jsonObject[1]
self.data = []
if type(rawData) is list:
self.storageType = ArffJsonDocument.dense
self.data... | null | src/classification/arff_json/ArffJsonDocument.py | ArffJsonDocument.py | py | 1,711 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "json.dumps",
"line_number": 50,
"usage_type": "call"
}
] |
528460044 | # coding=UTF-8
from MyModel import Model
from time import time
import numpy as np
from sklearn import metrics
from sklearn.model_selection import cross_val_score, KFold
from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
class Evaluator(Model):
def __init__(self, X, y):
super(Evaluator, s... | null | CCF_sentiment_analysis/Evaluate.py | Evaluate.py | py | 3,099 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "MyModel.Model",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "sklearn.model_selection.KFold",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.cross_val_score",
"line_number": 19,
"usage_type": "call"
},
{
... |
255062875 | """ Cgroups read engine to read the cgroups data periodically
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import glob
import logging
import os
import threading
import time
from treadmill import appenv
from tr... | null | lib/python/treadmill/metrics/engine.py | engine.py | py | 4,711 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "glob.glob",
"line... |
46937231 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# 测试说明 会建立新的数据库连接。。
import web
urls = ("/.*", "hello")
app = web.application(urls, globals())
def getconfig():
""" 通过配置文件获取配置"""
import os, ConfigParser
config = ConfigParser.ConfigParser()
config.read(os.path.dirname(os.path.abspath(__file__))+'/config.c... | null | notes/nginx/webpy.py | webpy.py | py | 1,445 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "web.application",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "ConfigParser.ConfigParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
... |
337977245 | import cdsapi
def download(year, month):
c = cdsapi.Client()
c.retrieve(
'reanalysis-era5-single-levels-monthly-means',
{
'format':'netcdf',
'product_type':'reanalysis-monthly-means-of-daily-means',
'variable':[
'10m_u_component_of_wind',
... | null | ERA-I_downloads/ERA5_monthly.py | ERA5_monthly.py | py | 1,278 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "cdsapi.Client",
"line_number": 4,
"usage_type": "call"
}
] |
537392954 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
PyTTa
Object Oriented Python in Technical Acoustics
__init__
@Autores:
- Matheus Lazarin Alberto, mtslazarin@gmail.com
@Última modificação: 16/10/18
EM EDIÇÃO!!! TENTANDO REMOVER CRIAÇÃO DO SWEEP DO FRFMEASURE
E CRIAR ... | null | OOPyTTa.py | OOPyTTa.py | py | 6,837 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "numpy.array",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.size",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.linspace",
"line_number... |
535649423 | from scrapy import Spider, Item, Field, Selector, Request
class Channel(Item):
title = Field()
video_url = Field()
page_url = Field()
img_url = Field()
class TVSpider(Spider):
name, start_urls = 'ip_spider', ['http://iranproud.com/livetv']
def parse_channel(self, response):
hxs = Se... | null | TVSpider.py | TVSpider.py | py | 1,036 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "scrapy.Item",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "scrapy.Field",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "scrapy.Field",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "scrapy.Field",
"line_number": ... |
355491707 | from datetime import datetime
from datetime import timedelta
from django.test import TestCase
from django.contrib.auth.models import User
from django.db import IntegrityError
from django.core.exceptions import ValidationError
from devilry.project.develop.testhelpers.corebuilder import SubjectBuilder, PeriodBuilder
fr... | null | devilry/apps/core/tests/test_period.py | test_period.py | py | 9,635 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.test.TestCase",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "devilry.project.develop.testhelpers.corebuilder.SubjectBuilder.quickadd_ducku_duck1010",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "devilry.project.develop.testhelpers.c... |
582400954 | from django.conf.urls import url
from . import views
app_name = 'stockart'
urlpatterns = [
url(r'^$', views.index, name='index'),
url(r'recargar/', views.recargar, name='recargar'),
url(r'busart/', views.busart, name='busart'),
url(r'report/', views.report, name='report'),
] | null | principal/Proyectofinal/stockart/urls.py | urls.py | py | 303 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "django.conf.urls.url",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.co... |
632854111 | # Copyright (C) 2020-2021 Intel Corporation
#
# SPDX-License-Identifier: MIT
from functools import partial
from glob import glob
from typing import Iterable
import inspect
import logging as log
import os
import os.path as osp
from datumaro.components.cli_plugin import CliPlugin, plugin_types
from datumaro.util.os_uti... | null | datumaro/components/environment.py | environment.py | py | 7,953 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "typing.Iterable",
"line_number": 46,
"usage_type": "name"
},
{
"api_name": "datumaro.components.cli_plugin.CliPlugin._get_name",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "datumaro.components.cli_plugin.CliPlugin",
"line_number": 50,
"usage_t... |
256013204 | #imports
import socket,select,logging
from ev3.ev3dev import NoSuchMotorError,Motor,NoSuchSensorError,LegoSensor
from ev3.lego import TouchSensor,InfraredSensor,ColorSensor
import os
#Main class
class Brick():
def __init__(self):
#everything for the interal logger
self._logger = logging.getLogger('B... | null | brick/main.py | main.py | py | 15,099 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "logging.WARNING",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "logging.StreamHandler",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logging.... |
338637359 | import pandas as pd
import numpy as np
from sklearn.model_selection import KFold
from sklearn.preprocessing import LabelEncoder
import gc
import os
from datetime import datetime
t1=datetime.now()
ad_feature=pd.read_csv("../data/adFeature.csv")
user_feature=pd.read_csv("../data/userFeature.csv")
train=pd... | null | qk/one_hot_statis_feature_5_fold.py | one_hot_statis_feature_5_fold.py | py | 2,424 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "datetime.datetime.now",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv... |
350917253 | from PIL import Image
image = Image.open("hw0_data/westbrook.jpg")
pixel = image.load()
width, heigh = image.size
result = Image.new("RGB", (width, heigh))
for i in range(width):
for j in range(heigh):
r, g, b = pixel[i, j]
result.putpixel((i, j), (r // 2, g // 2, b // 2))
result.save("Q2.jpg", "... | null | 0_load_data/Q2.py | Q2.py | py | 326 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "PIL.Image.open",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 3,
"usage_type": "name"
},
{
"api_name": "PIL.Image.new",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 7,... |
321871422 | # constants
import enum
'''
The order of political parties in Constants.PARTIES tuple is predefined and cannot be changed
Constants.PARTIES[0] = 'PiS'
Constants.PARTIES[1] = 'KO'
Constants.PARTIES[2] = 'SLD'
Constants.PARTIES[3] = 'PSL'
Constants.PARTIES[4] = 'Konf'
Constants.PARTIES[5] = 'BS'
Constants.PARTIES[6] =... | null | Constants.py | Constants.py | py | 3,836 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "enum.Enum",
"line_number": 71,
"usage_type": "attribute"
}
] |
348786890 | import news.db
import news.preprocess
from bs4 import BeautifulSoup
from tqdm import tqdm
if __name__ == '__main__':
dset = news.db.read.AllRecords(db_name='ftv.db')
res = []
for i, n in enumerate(tqdm(dset)):
try:
# if '120940/5544528' in n.url:
if n.company == '民視':
... | null | test_parsing.py | test_parsing.py | py | 1,475 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "news.db.db.read.AllRecords",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "news.db.db",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "news.db",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "tqdm.tqdm",
"line... |
48675266 | from selenium import webdriver
import math
import time
def calc(x):
return str(math.log(abs(12*math.sin(int(x)))))
try:
browser = webdriver.Chrome()
browser.get("http://suninjuly.github.io/alert_accept.html")
# Нажимаем на кнопку
button = browser.find_element_by_tag_name("button")
button.cl... | null | section_2/lesson3_step4.py | lesson3_step4.py | py | 922 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "math.log",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "math.sin",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"l... |
256407901 | import pygame#import pygame
from time import sleep#import the time module
pygame.init()#start pygame
screen = pygame.display.set_mode((700, 400))#make the window
movie = pygame.movie.Movie("filename.mpg")#setting the file to play
pygame.mixer.quit()#stops the mixer from playing random audio
movie.play()#play the movie... | null | video_player.py | video_player.py | py | 634 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "pygame.init",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pygame.movie.Mov... |
124991463 | # -*- coding: utf-8 -*-
"""
Created on Thu Aug 9 13:01:55 2018
@author: eiahsid
"""
import nltk,os,sys
import re
import pickle
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
sys.path.append('...')
from backend.issuetype_classify import TypeClassificationUtils as utils
from config import pa... | null | backend/issuetype_classify/predict.py | predict.py | py | 2,032 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "sys.path.append",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "config.path_init.base_dir",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "config.p... |
591032126 | from typing import List
import regex
_RE_PUNC = regex.compile(r"^\p{p}$")
_EM_DASH = "-"
# note for grading TA:
# I couldn't import regex module, but I have activated conda and installed regex using pip The
# terminal gives me this when I tried to install regex again using pip: regex in
# /opt/anaconda3/lib/python3.... | null | cosi114_hw0_rachel_peng/hw0.py | hw0.py | py | 2,321 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "regex.compile",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "typing.List",
"line_number": 21,
"usage_type": "name"
}
] |
50792177 | from flask_restful import Resource
from sqlalchemy import and_
from sqlalchemy.exc import SQLAlchemyError
from webargs.flaskparser import use_kwargs
from webargs import fields
from models.ResponseCodes import ResponseCodes
from models.ResponseCodes import ResponseDescriptions
from api.models.models import db_session, T... | null | foundations/api/resources/Graph/transaction_size.py | transaction_size.py | py | 4,418 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "api.models.models.TransactionSize",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "flask_restful.Resource",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "webargs.fields.Date",
"line_number": 25,
"usage_type": "call"
},
{
"api_... |
239838624 | from flask import Blueprint, jsonify, abort
from marshmallow_jsonschema import JSONSchema
from emannotationschemas.errors import UnknownAnnotationTypeException
from emannotationschemas import get_schema, get_types
bp = Blueprint("schema", __name__, url_prefix="/schema")
@bp.route("")
def get_schemas():
return js... | null | annotationengine/schemas.py | schemas.py | py | 622 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "flask.Blueprint",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "flask.jsonify",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "emannotationschemas.get_types",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "emannotati... |
410860004 | import os
import unittest
from e2e_tests.connector_facade import E2EConnectorFacade
from infoblox_client.objects import ARecord, DNSZone, AAAARecord
class TestObjectsE2E(unittest.TestCase):
def setUp(self):
opts = {
'host': os.environ['WAPI_HOST'],
'username': os.environ['WAPI_USE... | null | e2e_tests/test_objects.py | test_objects.py | py | 2,676 | python | en | code | null | code-starcoder2 | 76 | [
{
"api_name": "unittest.TestCase",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
... |
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