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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
433628226 | import os
import pickle
import numpy as np
from PIL import Image
import torch
from torch.utils.data import Dataset
from torchvision import transforms
import h5py
import json
from transforms import Scale
from torch.utils.data import DataLoader
transform = transforms.Compose([
transforms.ToTensor(),
])
... | null | dataset.py | dataset.py | py | 4,110 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torchvision.transforms.Compose",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "torchvision.transforms.ToTensor",
"line_number": 17,
"usage_type": "call"
},
{
... |
354672268 | #!/usr/bin/python3
import sys
import re
import string
import ipdb
"""
Parse a bookmarks.html file by the provided tags
Group and structurize them together by common tags (order is important atm)
param arg: bookmark.html file
returns: BOOKMARKS.md file
"""
def add_to_nested_list_at_index(nested_list, index_list,... | null | Admin/Scripts/Utility/parse_bookmarks.py | parse_bookmarks.py | py | 3,811 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.argv",
"line_number": 70,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 73,
"usage_type": "attribute"
},
{
"api_name": "re.search",
"line_number": 86,
"usage_type": "call"
},
{
"api_name": "ipdb.set_trace",
"line_numb... |
482599548 | import json
import os
import requests
def main():
# url = "https://www.goodreads.com/search.xml?key={}&q=Ender%27s+Game".format(os.getenv('GOODREADS_KEY'))
url = "https://www.goodreads.com/owned_books/{}?format=xml".format(os.getenv('USER_ID'))
print (url)
params = {
'key': os.getenv('GOODREAD... | null | get_shelves.py | get_shelves.py | py | 525 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.getenv",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 16,
... |
49355515 | import argparse
from datetime import datetime
def valid_date(value):
try:
return datetime.strptime(value, "%Y-%m-%d")
except ValueError:
msg = "\033[91mERROR:\033[0m Fecha en formato no valido: '{0}'.".format(value)
raise argparse.ArgumentTypeError(msg)
def str2bool(value):
if v... | null | utilities/validation.py | validation.py | py | 584 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "argparse.ArgumentTypeError",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": ... |
586786480 | import bs4
def scrape(site):
soup = bs4.BeautifulSoup(site, 'html.parser')
html_header_list = soup.select('span.deck-price-paper')
for item in html_header_list:
if item.text != '\n':
print(item.text.strip('\n'))
if __name__ == "__main__":
with open('.\scraped_page.html') as f:
... | null | days/46-48-beautifulsoup4/pauper_meta/scrape_data.py | scrape_data.py | py | 360 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "bs4.BeautifulSoup",
"line_number": 4,
"usage_type": "call"
}
] |
52877629 | import os
import pickle
import click
import pandas as pd
@click.command("predict")
@click.option("--input-data-dir")
@click.option("--input-model-dir")
@click.option("--input-scaler-dir")
@click.option("--output-preds-dir")
def predict(input_data_dir: str, input_model_dir: str, input_scaler_dir: str, output_preds_di... | null | airflow_ml_dags/images/airflow-predict/predict.py | predict.py | py | 950 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_nu... |
63022187 | import requests
from bs4 import BeautifulSoup
# Load the webpage url
r = requests.get("https://mp.weixin.qq.com/s/tzFKo2e3FM-TEpPjGuhPaQ")
# Use beautifulSoup to parse the webpage
bs = BeautifulSoup(r.text,'lxml')
# Index number for output image name
i=1
# The assumption is to find all img tags in the webpage
# Of ... | null | yasige/jpg_dowload.py | jpg_dowload.py | py | 1,358 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.get",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 34,
"usage_type": "call"
}
] |
216479846 | import sys
import os
pathToLib = os.path.join(os.path.dirname(__file__), "../kickoff/") # NOQA
sys.path.append(pathToLib) # NOQA
import json
import ConfigParser
import StringIO
import urllib2
from collections import OrderedDict
from config import SUPPORTED_AURORA_LOCALES
from config import SUPPORTED_NIGHTLY_LOCALES
... | null | scripts/sync-and-check-l10n.py | sync-and-check-l10n.py | py | 2,894 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "sys.path.append",
"line_nu... |
213734778 | # importing necessary packages
import nltk
import io
import sys
import os
import pandas as pd
from nltk.corpus import stopwords... | null | FaqFinder/QuestionSearch.py | QuestionSearch.py | py | 6,551 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_excel",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.ExcelWriter",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics.pairwise.cosine_similarity",
"line_number": 48,
"usage_type": "call"
},
{
"a... |
49949751 | # Imports
import pygame
import math
import random
# Initialize game engine
pygame.init()
# Window
SIZE = (800, 600)
TITLE = "My Awesome Picture"
screen = pygame.display.set_mode(SIZE)
pygame.display.set_caption(TITLE)
# Timer
clock = pygame.time.Clock()
refresh_rate = 60
# Colors
RED = (255... | null | night_scene.py | night_scene.py | py | 5,431 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pygame.init",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_mode",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "pygame.display... |
266085282 | import logging
from typing import List
from fastapi import APIRouter, HTTPException
from pydantic import conint
from starlette.status import (
HTTP_201_CREATED, HTTP_500_INTERNAL_SERVER_ERROR, HTTP_404_NOT_FOUND, HTTP_200_OK
)
from niched.database.mongo import conn
from niched.database.user_utils import check_use... | null | niched/api/routers/user.py | user.py | py | 2,637 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "niched.database.mongo.conn.get_users_collection",
"line_number": 22,
"usage_type": "call"
},
{
... |
419765086 | import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms
from utils.get_audio_VF import GetAudio
class LibriSpeech300_train(Dataset):
def __init__(self, epoch_len=100):
super().__init__()
self.epoch_len = epoch_len
self.data_path = "/workspace/db/au... | null | dataloader/dataloader.py | dataloader.py | py | 2,023 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "utils.get_audio_VF.GetAudio",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms.ToTensor",
"line_number": 14,
"usage_type": "call"
},
{
... |
336247255 | import json
from datetime import date, datetime, timedelta
from dateutil.relativedelta import relativedelta
from babel.dates import format_date
from odoo import models,fields,api,_
from odoo.release import version
from odoo.tools import DEFAULT_SERVER_DATE_FORMAT as DF
from odoo.exceptions import ValidationError,UserE... | null | rd_tool/models/dashboard_graph.py | dashboard_graph.py | py | 7,726 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "odoo.models.AbstractModel",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "odoo.fields.Selection",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "odoo... |
454395869 | from django.conf.urls import patterns, include, url
from .views import DBView, Files, Books
from django.views.decorators.cache import cache_page
urlpatterns = patterns(
'',
url(r'^$', DBView.as_view(), name="main"),
url(r'^films/', include('db.films.urls', namespace='films')),
url(r'^books$', Books.as_... | null | src/db/urls.py | urls.py | py | 660 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.conf.urls.patterns",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.conf.urls.url",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "views.DBView.as_view",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "view... |
198518688 | # Sierpiński Carpet
import numpy as np
from PIL import Image
import imageio
w, h = 729, 729 # easy powers of three
carpet_color = [157, 130, 232] # default-grey = [235, 238, 242]
carpet = np.asarray([[carpet_color for i in range(w)] for j in range(h)], dtype=np.uint8)
carpet_files = []
image_initial = Image.froma... | null | scripts/carpet.py | carpet.py | py | 1,407 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.asarray",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "PIL.Image.fromarray",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"lin... |
38186946 | import numpy as np
import pandas as pd
import multiprocessing
import os
import sys
from functools import reduce
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.preprocessing import OneHotEncoder
# Turning off the pandas chained assignment warning
pd.options.mode.chained_assignment = None
c... | null | python/tools/preprocessing.py | preprocessing.py | py | 7,129 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.options",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "pandas.read_parquet",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "pandas.read_parquet",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pandas.re... |
102342820 | import os
import random
import numpy as np
from python_speech_features import mfcc
import scipy.io.wavfile as wav
from imutils import paths
from sklearn.preprocessing import OneHotEncoder
from sklearn.preprocessing import LabelEncoder
from keras.utils import to_categorical
class Audio:
#trainsfer the labels to one-ho... | null | Audio.py | Audio.py | py | 5,365 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.listdir",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.LabelEncoder",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.OneHotEncoder",
"line_number": 22,
"usage_type": "call"
},
{
... |
123106043 | import sys
import re
import os
import requests
import pandas as pd
from collections import defaultdict
from openpyxl import Workbook
# path = sys.argv[1]
path = 'C:\\Users\\jbwang\\Desktop\\tq\\target\\demo'
with open(os.path.join(path, 'folders.txt')) as fg:
groupvs_list = [i.strip() for i in fg]
wi... | null | codefile/kegg.py | kegg.py | py | 4,751 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_nu... |
226961083 | # -*- coding: UTF-8 -*-
#!/usr/bin/python
"""
Convert parsing result to conll format for TWEET
@Author Yi Zhu
Upated 01/30/2017
"""
#************************************************************
# Imported Libraries
#************************************************************
import argparse
#***********************... | null | scripts/tweet_conll_converter.py | tweet_conll_converter.py | py | 2,544 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 65,
"usage_type": "call"
}
] |
386401855 | from PyQt5.QtGui import QColor
from PyQt5.QtWidgets import QMdiSubWindow, QWidget, QFormLayout, QHBoxLayout, \
QLabel, QLineEdit, QComboBox, QRadioButton, QPushButton, QButtonGroup, \
QSpacerItem, QSizePolicy
from db.msql_db import MysqlDB
class InsertDvd(QMdiSubWindow):
def __init__(self):
supe... | null | model/insert_dvd.py | insert_dvd.py | py | 5,753 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "PyQt5.QtWidgets.QMdiSubWindow",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QFormLayout",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QLabel",
"line_number": 16,
"usage_type": "call"
},
{
"a... |
89317862 | #pip install opencv-python==3.4.3.18
#pip install azureml.core
#pip install onnxruntime
from __future__ import print_function
import cv2 as cv
import cv2 as cv2
import numpy as np
import argparse
from azureml.core.model import Model
import onnxruntime
from object_detection import ObjectDetection
from PIL import Image, ... | null | ONNXObjectDetection/cascade_classifier/objectDetection.py | objectDetection.py | py | 3,205 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "azureml.core.model.Model.get_model_path",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "azureml.core.model.Model",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "onnxruntime.InferenceSession",
"line_number": 28,
"usage_type": "call"
... |
141441774 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on 2018.11.9
@author: wrj
"""
'''
双分支 + 特征map32 + 交叉熵损失函数 + 参数共享 + 上支路差值求绝对值
'''
import numpy as np
import math
import time
import model_d_map32_diff_res_pro as model
import read_data
import tensorflow as tf
import os
from datetime import da... | null | train_nature_map32_diff_res_pro.py | train_nature_map32_diff_res_pro.py | py | 16,244 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "logging.basicConfig",
"... |
76498103 | #!/usr/bin/python3
import requests
import json
import sys
import pandas as pd
import time
import random
from sqlalchemy import *
import sqlalchemy
import sqlalchemy.schema
import io
from IPython.display import *
from pandas.io.json import *
from sqlalchemy.types import *
# https://stackoverflow.com/questions/24518944/... | null | sreality/scraping_data/sreality_a.py | sreality_a.py | py | 18,222 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.argv",
"line_number": 36,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "time.time",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 9... |
267728712 | import math, numpy
import matplotlib.pyplot as plt
data = numpy.loadtxt("testSet.txt")
split_data = numpy.split(data, [2], axis=1)
data_x = split_data[0]
data_y = split_data[1]
data_x = numpy.insert(data_x, 0, 1, axis=1)
theta = numpy.zeros((3,1))
alpha = 0.001
def sigmoid(data_x, theta):
theta_x = nump... | null | mlia_logistic1.py | mlia_logistic1.py | py | 2,194 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.loadtxt",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.split",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.insert",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": ... |
393612860 | """
Here I keep all settings about adaptation.
How we adapt, what to adapt and what to do.
"""
import os
from django.conf import settings
STATIC_CMS_ROOT = os.path.join(settings.BASE_DIR, 'adaptation', 'plugins', '{package}', 'static')
TEMPLATES_ROOT = os.path.join(STATIC_CMS_ROOT, 'tpl')
JS_SCRIPT = os.path.join(s... | null | adaptation/settings.py | settings.py | py | 3,508 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.join",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings.BASE_DIR",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "django.c... |
83260386 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
import os,sys,re,time,urllib.parse,ntpath,zipfile,gzip,subprocess
from urllib.request import Request, urlopen, urlretrieve
help = '''
Entre com um emulador suportado:
Windows :
Snes9K
Snes9x
zsnesw
Kega_F... | null | libs/default/GamesRetro.py | GamesRetro.py | py | 15,488 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.getcwd",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "urllib.request.Request",
"line_number": 135,
"usage_type": "call"
},
{
"api_name": "urllib.request.urlopen",
"line_number": 143,
"usage_type": "call"
},
{
"api_name": "time.sleep"... |
182399014 | from __future__ import print_function, division
import os
import torch
import pandas as pd
from skimage import io, transform
import numpy as np
import matplotlib.pyplot as plt
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils, VOCDetection
class FaceLandmarksDataset(Dataset):
... | null | pytorch_blitz/prepare_dataset.py | prepare_dataset.py | py | 1,637 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "pandas.read_json",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "skimage.transform",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "os.path.j... |
128326369 | from wikidataStuff.WikidataStuff import WikidataStuff as WDS
import pywikibot
import importer_utils as utils
from os import path
MAPPING_DIR = "mappings"
PROPS = utils.load_json(path.join(MAPPING_DIR, "props_general.json"))
class Uploader(object):
TEST_ITEM = "Q4115189"
def make_labels(self):
label... | null | importer/Uploader.py | Uploader.py | py | 11,968 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "importer_utils.load_json",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "pywikibot.Site",
"line... |
97556783 | # -*- coding: utf-8 -*-
import itertools
from django import forms
from django.forms import models as model_forms
from django.db.models import get_model
from django.utils.datastructures import SortedDict
from models import get_parent_field
from django.utils.encoding import smart_str
def create_internal_m2m_form_facto... | null | synergy/contrib/records/forms.py | forms.py | py | 12,415 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.forms.ModelForm",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "django.forms",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "django.forms.widgets.HiddenInput",
"line_number": 22,
"usage_type": "call"
},
{
"api_nam... |
78109702 | import matplotlib.pyplot as plt
import numpy as np
import math
def sigmoid(x):
return 1 / (1+math.exp(-x))
x = np.linspace(-5,5,100)
y = np.zeros_like(x)
for i in range(len(x)):
y[i] = sigmoid(x[i])
plt.figure(figsize=(10,5))
plt.plot(x,y)
plt.ylabel('g(z)')
plt.xlabel('z')
plt.savefig('Logistic_function.pn... | null | notes/scripts/logistic.py | logistic.py | py | 335 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "math.exp",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.linspace",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.zeros_like",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
... |
540808985 | import datetime
from pyiem.observation import Observation
import pytz
import os
import sys
import mesonet
import psycopg2
IEM = psycopg2.connect("host=iemdb dbname=iem user=mesonet")
icursor = IEM.cursor()
now = datetime.datetime.now()
fp = "/mesonet/ARCHIVE/data/%s/text/ot/ot0007.dat" % (now.strftime("%Y/%m/%d"),)
... | null | scripts/ingestors/parse0007.py | parse0007.py | py | 1,111 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "psycopg2.connect",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.path.... |
359960742 | """Unit tests for //compilers/clsmith/cl_launcher.py."""
import pytest
import sys
from absl import app
from absl import flags
from compilers.clsmith import cl_launcher
from gpu.cldrive import driver
from gpu.cldrive import env
FLAGS = flags.FLAGS
# A bare-bones CLSmith program.
CLSMITH_EXAMPLE_SRC = """
// -g 1,1,1... | null | compilers/clsmith/cl_launcher_test.py | cl_launcher_test.py | py | 2,952 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "absl.flags.FLAGS",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "absl.flags",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "gpu.cldrive.env.OclgrindOpenCLEnvironment",
"line_number": 77,
"usage_type": "call"
},
{
"api_na... |
461735855 | import os
from PIL import Image
import numpy as np
import cv2
path = "./pix2pix/inputs/"
dirs = os.listdir(path)
def black_remove(src):
src = np.array(src)
# src = ~src
gray = cv2.cvtColor(src, cv2.COLOR_GRAY2BGR)
# bg_index = np.where(np.less(gray, 255))
# gray[bg_index] = 0
return gray
f... | null | util/image_prep.py | image_prep.py | py | 692 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.listdir",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_GRAY2BGR",
"line_num... |
285479424 | import nltk
from nltk.corpus import stopwords
import glob
import math
from string import punctuation
from collections import Counter
def cleaningTXTFile(text, f):
with open(f) as file:
text = file.read()
text = text.split(' ')
stop_words = set(stopwords.words('english'))
text ... | null | optimized.py | optimized.py | py | 3,325 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "glob.glob",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "glob.glob... |
46883849 | __author__ = 'Max'
import ArtieEditorGUI.aestartgui as GUI
import wx
def run_artie_editor(parent):
"""
Runs ArtieEditor
:rtype: void
:return: void
"""
app = wx.App()
GUI.ArtieEditorStartScreen(parent)
app.MainLoop()
if __name__ == '__main__':
run_artie_editor(None) | null | ArtieEditor/aemain.py | aemain.py | py | 305 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "wx.App",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "ArtieEditorGUI.aestartgui.ArtieEditorStartScreen",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "ArtieEditorGUI.aestartgui",
"line_number": 14,
"usage_type": "name"
}
] |
545358857 | import os
import pandas as pd
import requests
from flask import Flask, json, Response
from Resources.Trainer_utilities import model_trainer
app = Flask(__name__)
app.config["DEBUG"] = True
@app.route('/training-cp/<model>', methods=['POST'])
def train_models(model):
db_api = os.environ['TRAIN_DB_API']
r = r... | null | Assignment 1/Trainer/.ipynb_checkpoints/Forest_Trainer-checkpoint.py | Forest_Trainer-checkpoint.py | py | 900 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.Flask",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "requests.get",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame.from_dict",
... |
472350959 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Xiang Wang @ 2016-05-30 09:40:39
from testmodels.models import *
from django.utils.crypto import get_random_string
from django.db.models import Q
from django.contrib.auth.models import *
import random, time
user = User.objects.first()
def main():
Text.objects.bul... | null | test.py | test.py | py | 1,728 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.utils.crypto.get_random_string",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.db.models.Q",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.db.models.Q",
"line_number": 24,
"usage_type": "call"
},
{
"api_n... |
134971510 | """
Common DBus utilities.
"""
__all__ = ['DBusProperties', 'DBusProxy']
from dbus import Interface
from dbus.exceptions import DBusException
class DBusProperties(object):
"""
Dbus property map abstraction.
Properties of the object can be accessed as attributes.
"""
def __init__(self, dbus_objec... | null | udiskie/common.py | common.py | py | 2,421 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "dbus.Interface",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "dbus.exceptions.DBusException",
"line_number": 35,
"usage_type": "name"
},
{
"api_name": "dbus.Interface",
"line_number": 38,
"usage_type": "call"
}
] |
616853859 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
from django.conf import settings
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.Create... | null | mapstory/apps/initiatives/migrations/0001_initial.py | 0001_initial.py | py | 2,808 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.swappable_dependency",
"line_number": 11,
"usage_type": "call... |
397708190 | import collections
from pykka.exceptions import ActorDeadError
__all__ = [
'ActorProxy',
]
class ActorProxy(object):
"""
An :class:`ActorProxy` wraps an :class:`ActorRef <pykka.ActorRef>`
instance. The proxy allows the referenced actor to be used through regular
method calls and field access.
... | null | pykka/proxy.py | proxy.py | py | 7,454 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pykka.exceptions.ActorDeadError",
"line_number": 98,
"usage_type": "call"
},
{
"api_name": "collections.Callable",
"line_number": 132,
"usage_type": "attribute"
}
] |
167385820 | #!/usr/bin/env python3
# coding: utf-8
import numpy as np
from keras.datasets import boston_housing
from keras import models
from keras import layers
from keras import optimizers
import matplotlib.pyplot as plt
from keras.utils.np_utils import to_categorical
def vectorize_sequences(sequences, dimension=10000):
#... | null | 2019Fall/SWE248P/m3/house_prices/run.py | run.py | py | 4,655 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.zeros",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "keras.models.Sequential",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "keras.models",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "keras.layers.Dense",... |
553980301 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import _thread
from django.core.mail import EmailMultiAlternatives
from DjangoKMS import settings
__author__ = "xuzhao"
__email__ = "contact@xuzhao.xin"
__file__ = "email.py"
__description__ = ""
__created_time__ = "2018/9/1 23:33"
def send_email(mail_to, title, content):
... | null | apps/utils/email.py | email.py | py | 653 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.core.mail.EmailMultiAlternatives",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "DjangoKMS.settings.DEFAULT_FROM_EMAIL",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "DjangoKMS.settings",
"line_number": 24,
"usage_type": ... |
318485118 | from .getter import app
from .setter import Setter
from .pool import ProxyPool
from .detector import Detector
from .settings import SETTER_CYCLE, DETECTOR_CYCLE
from .settings import FLASK_HOST, FLASK_PORT
from .settings import SETTER_ENABLE, DETECTOR_ENABLE, FLASK_ENABLE
import time
from multiprocessing import Process... | null | proxypool/scheduler.py | scheduler.py | py | 1,226 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "settings.SETTER_CYCLE",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "setter.Setter",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "setter.run",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line... |
85410574 | import glob
import logging
import warnings
import pytest
import os
from _pytest.outcomes import Failed
from .broker_pact import BrokerPact, BrokerPacts, PactBrokerConfig
from .result import log, PytestResult
def pytest_addoption(parser):
group = parser.getgroup("pact specific options (pactman)")
group.addop... | null | pactman/verifier/pytest_plugin.py | pytest_plugin.py | py | 6,443 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ.get",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 49,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "logging.basicConfig"... |
48575997 | from setuptools import setup, find_packages
import os
import sys
# Version
BASE_DIR = os.path.dirname(os.path.realpath(__file__))
VERSION_FILE = os.path.join(BASE_DIR, 'pynetdicom3', '_version.py')
with open(VERSION_FILE) as fp:
exec(fp.read())
setup(
name = "pynetdicom3",
packages = find_packages(),
... | null | setup.py | setup.py | py | 1,233 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.path.realpath",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_n... |
243172886 | import datetime
import json
import sys
import discord
import emoji
import mysql
from discord.ext import commands
from gssp_experiments.client_tools import ClientTools
from gssp_experiments.database import cnx, cursor
from gssp_experiments.database.database_tools import DatabaseTools, insert_users, insert_s... | null | bot.py | bot.py | py | 7,596 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "discord.ext.commands.Bot",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "discord.ext.commands",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "gssp_experiments.settings.config.config",
"line_number": 16,
"usage_type": "name"
},
{
... |
579620085 | import sys, pickle #, cPickle
print(sys.executable)
import sklearn.preprocessing as pre, scipy, numpy as np, matplotlib.pyplot as plt, glob, pyemma as py, sys, os
import pandas as pd, seaborn as sns, argparse
from sklearn.model_selection import train_test_split
#os.environ["CUDA_DEVICE_ORDER"]="PCI_BUS_ID"
#os.environ... | null | SRV_runs/run_SRV_permute.py | run_SRV_permute.py | py | 4,566 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.executable",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "sys.path.append",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "sys.path",
"line... |
36336290 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
# (c) Copyright 2007-2012 by Joseph Reagle
# Licensed under the GPLv3, see <http://www.gnu.org/licenses/gpl-3.0.html>
'''Build a PDF (article or book) based on markdown source using pandoc.
'''
import codecs
from glob import glob
import locale
import logging
import md2bib
i... | null | bd.py | bd.py | py | 11,555 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "logging.basicConfig",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "logging.critical",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "logging.info",
... |
196340836 | # -*- coding: utf-8 -*-
"""
Created on Fri Feb 19 14:28:36 2021
@author: GeonHo
"""
import requests
import pandas as pd
import numpy as np
import re
from bs4 import BeautifulSoup
import time
import copy
from html_table_parser import parser_functions as parser
from io import BytesIO
from zipfile import... | null | crawling_dart_module.py | crawling_dart_module.py | py | 19,719 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.DataFrame",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_numb... |
219457192 | from zipfile import ZipFile
import tempfile
import logging
import os.path as op
import os
import sys
from pbcore.io import FastqRecord
from pbcommand.testkit import PbIntegrationBase
import pbtestdata
from test_file_utils import (make_mock_laa_inputs,
make_fastq_inputs)
log = logging.ge... | null | tests/unit/test_tasks_laa.py | test_tasks_laa.py | py | 2,803 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pbtestdata.get_file",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pbcommand.testkit.PbIntegrationBase",
"line_number": 21,
"usage_type": "name"
},
{
"api_nam... |
418386429 | import pyglet
from pyglet.image.codecs.png import PNGImageDecoder
#Farben definieren und in Variablen ablegen
BACKGROUND_COLOR = (0.9, 0.9, 0.9, 1)
DRAWING_COLOR_1 = (1, 0, 0)
DRAWING_COLOR_2 = (0,0.5,0.5)
#Fenster und seine Eigenschaften definieren
window = pyglet.window.Window(width=400,height=400,resizable=True,ca... | null | aufgabe_3/Utils/loadPNGImage.py | loadPNGImage.py | py | 1,204 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pyglet.window.Window",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pyglet.window",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "pyglet.image.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pyglet.imag... |
595299138 | from django.contrib import admin
#from django.contrib.admin import ModelAdmin, register
from .models import (
Doador,
Operador,
Entregador,
Endereco,
Telefone,
Email,
PessoaFisica,
PessoaJuridica,
Pessoa,
Cobranca,
)
#admin.site.register(Pessoa)
@admin.register(Pessoa)
c... | null | apv/apps/admin.py | admin.py | py | 2,083 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.register",
"line_number": 20,
"usage_type": "call"
},
... |
496343997 | '''
Created on Mar 31, 2010
@author: Drew Roos
'''
from django.shortcuts import get_object_or_404
from django.http import HttpResponse
from rapidsms.utils import render_to_response
from circumcision.apps.circumcision.models import Registration, SentNotif
from circumcision.apps.circumcision.app import split_contact_ti... | null | circumcision/apps/circumcision/views.py | views.py | py | 7,540 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "circumcision.apps.circumcision.models.Registration.objects.get",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "circumcision.apps.circumcision.models.Registration.objects",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "circumcision.apps.... |
281193660 | #!/usr/local/bin/python3
'''
# 3.x script to download EventLogFiles, original by @atorman (https://github.com/atorman/elfPy)
# Refactored from Python 2.7.9 by richard.krieg@gmail.com using 2to3
# Modified by @krieg to use command-line args in lieu of interactive prompts
'''
import argparse
import base64
import getpass... | null | elf.py | elf.py | py | 5,014 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "urllib.request.parse.urlencode",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "urllib.request.parse",
"line_number": 33,
"usage_type": "attribute"
},
{
"... |
107334322 | """
Given a list of numbers, return whether any two sums to k.
For example, given [10, 15, 3, 7] and k of 17, return true since 10 + 7 is 17.
Bonus: Can you do this in one pass?
"""
from utils import get_input_array
def check_if_pair_sums(array, sum):
table = {}
for num in array:
if table.get(num):
... | null | problems/dcp0001.py | dcp0001.py | py | 685 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "utils.get_input_array",
"line_number": 19,
"usage_type": "call"
}
] |
519856106 | import torch
import torch.nn as nn
import torch.nn.functional as F
"""
Architecture based on InfoGAN paper.
"""
class Generator(nn.Module):
def __init__(self, z_dim, channel_dim, c_dim=0):
super().__init__()
self.latent_dim = z_dim + c_dim
self.z_dim = z_dim
self.model = nn.Sequent... | null | models/rope_model.py | rope_model.py | py | 2,732 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_... |
215206016 | import collections
import json
import sqlite3
global para
global assetcash
global c
c = sqlite3.connect('../dubi/sl.db').cursor()
def init():
global para
global assetcash
global c
para=collections.OrderedDict()
single={'prcadj': 1, 'posadj': 1,'lvg':0.1}
assetcash=dict()
... | null | project/gubi_llp/dubi/para.py | para.py | py | 3,568 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "json.d... |
314083183 | """
This file demonstrates writing tests using the unittest module. These will pass
when you run "manage.py test".
Replace this with more appropriate tests for your application.
"""
from django.test import TestCase
from inventory.models import *
import test_utils as test_utils
class SimpleTest(TestCase):
def tes... | null | jerseytrade/inventory/tests/test_models.py | test_models.py | py | 1,186 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "django.test.TestCase",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "django.test.TestCase",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "test_utils.create_brand",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "tes... |
32401787 | __author__ = "Travis Williams"
# University of South Carolina
# Jason Hattrick-Simpers group
# Starting Date: June, 2016
import matplotlib.pyplot as plt
import numpy as np
from scripts.figure_plotters import ternary
def plt_ternary_save(data, tertitle='', labelNames=('Species A','Species B','Species C'), scale=1... | null | scripts/figure_plotters/plotTernary_small.py | plotTernary_small.py | py | 6,018 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 72,
"usage_type": "name"
},
{
"api_name": "scripts.figure_plotters.ternary.figure",
"line_number": 76,
"usage_type": "call"
},
{
... |
93265884 | """
This is homework 8 of SSW810
author: Mingyao Xiong
"""
import datetime, os
from prettytable import PrettyTable
def date_arithmetic():
""" This method is an example of using datetime."""
three_days_after_20000227 = datetime.datetime(2000, 2, 27) + datetime.timedelta(days=3)
three_days_after_20170227 = ... | null | HW08_Mingyao_Xiong.py | HW08_Mingyao_Xiong.py | py | 3,161 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "datetime.datetime",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.timedelta",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.timed... |
427770267 | import xml.etree.ElementTree as ET
import lxml.etree as LE
import pymysql
import sys
import re
"""
WORKING
conn = pymysql.connect(host='localhost', port=3306, user='root', passwd='1234', db='book_manager', charset='utf8mb4', autocommit=True)
str = "select * from books"
cur=conn.cursor()
cur.execute(str)
for i in range... | null | python/integrate_simple.py | integrate_simple.py | py | 2,308 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "xml.etree.ElementTree.parse",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 36,
"usage_type": "name"
},
{
"api_name": "lxml.etree.parse",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "lx... |
8504690 | import requests
from bs4 import BeautifulSoup
import time
import progressbar
def scrape_insolvency_court():
"""
Returns all selectable regions and courts from homepage www.insolvenzbekanntmachungen.de in a dictionary.
:return (dict): keys - regions
value - courts
"""
URL = 'h... | null | Insolvency Scraper/helpers.py | helpers.py | py | 18,388 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "requests.Session",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "requests.Session",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup... |
540788827 | #!/usr/bin/env python
"""
Copyright 2015 Brocade Communications Systems, 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 required by appl... | null | pynos/utilities.py | utilities.py | py | 3,831 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "xml.etree.ElementTree.Element",
"line_number": 48,
"usage_type": "attribute"
},
{
"api_name": "xml.etree.ElementTree",
"line_number": 48,
"usage_type": "name"
},
{
"api_name": "xml.etree.ElementTree.fromstring",
"line_number": 51,
"usage_type": "call"
},
... |
335188516 | from utils import _Template, Field
from typing import List
class TaskTemplate(_Template):
LEVELS = ["task"]
OPTIONAL: List[str] = []
# Task level fields
LABEL_TASK_BOUNDARIES = Field(
name="label_task_boundaries", types=[bool], reqs=None
)
LEARNER_CONFIGURATION = Field(
nam... | null | experiments/config_templates/task_template.py | task_template.py | py | 1,056 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "utils._Template",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "utils.Field",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "utils.Field",
"line_number"... |
223848176 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 10 12:21:10 2016
Clean wind data and output csv
@author: mhong
"""
import pandas as pd
import numpy as np
option = 8
# 1. 股权激励
if option == 1:
filename = '../../wind_data/source_data/20160721Patch/guquanjili.xlsx'
df = pd.read_excel(filename)
df_new = df.cop... | null | event/wind_data_cleaner.py | wind_data_cleaner.py | py | 7,731 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_excel",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
... |
472078364 | from scholarly import scholarly
import urllib.request, json
import jellyfish
import pandas as pd
import sys
class ImpactFactor:
def __init__(self, file_name):
self.df = pd.read_csv(file_name, delimiter=";")
self.df["impact-factor"] = self.df["Cites / Doc. (2years)"]
def stats(self, journal):
... | null | utils/impact_factor.py | impact_factor.py | py | 1,075 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "jellyfish.jaro_winkler_similarity",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "jellyfish.jaro_winkler_similarity",
"line_number": 27,
"usage_type": "call"
}
] |
207172017 | # Copyright (c) 2014 Scopely, Inc.
# Copyright (c) 2015 Mitch Garnaat
# Copyright (c) 2019 Christophe Morio
# Copyright (c) 2020 Jerome Guibert
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
#... | null | skew/resources/aws/cloudsearch.py | cloudsearch.py | py | 1,145 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "skew.resources.aws.AWSResource",
"line_number": 24,
"usage_type": "name"
}
] |
405894464 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from .manta48 import spotsv
def heatmap48(values=None, title=None, vert=False, figsize=(14, 4), ax=None,
skip_ch=None, **kwargs):
if values is None:
values = np.arange(48)
values = np.asfarray(values)
if value... | null | multispot_utils/heatmap.py | heatmap.py | py | 1,622 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.arange",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.asfarray",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
... |
509702765 | import glob
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import time
from scipy.stats import norm
SSD_GRAPH_FILE = 'frozen_models/frozen_sim_mobile/frozen_inference_graph.pb'
tl = {'1': 'Green', '2': 'Red', '3': 'Yellow' , '4' : 'OFF' }
class inference():
def ... | null | tf_model/infer2.py | infer2.py | py | 3,923 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "tensorflow.Graph",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "tensorflow.GraphDef",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "tensorflow.gfile.GFile",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "tensorflo... |
526155722 | from urllib.request import urlopen
from bs4 import BeautifulSoup
import mysql.connector
def checkNoneTypePrice(arg):
if(arg is not None):
return arg.getText().replace("R$", "").strip()
else:
return None
def checkNoneTypeLink(arg):
if(arg is not None):
return arg
else:
r... | null | PcxOlxScraping.py | PcxOlxScraping.py | py | 2,537 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "mysql.connector.connector",
"line_number": 52,
"usage_type": "attribute"
},
{
"api_name": "mysql.connector",
"line_number": 52,
"usage_type": "name"
},
{
"api_name": "urllib.request.urlopen",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": ... |
24570417 | from SQL_Server_Connector import SQL_Server_Connection
from Queries import Queries
from Indexes import Indexes
from Functions import *
from API_BBG import *
from datetime import datetime
import sys
import pandas as pd
import numpy as np
# Main
################## Rotinas para cuidar de precos ausentes ###############... | null | Check_Prices_Repeat.py | Check_Prices_Repeat.py | py | 3,948 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "Queries.Queries",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "SQL_Server_Connector.SQL_Server_Connection",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "sys.argv",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name... |
230143944 | import webapp2
import jinja2
import os
jinja_environment = jinja2.Environment(autoescape=True,
loader=jinja2.FileSystemLoader(os.path.join(os.path.dirname(__file__), 'templates')))
class StartPage(webapp2.RequestHandler):
def get(self):
template = jinja_environment.get_template('start_page.html')
... | null | polygonlabs.py | polygonlabs.py | py | 444 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "jinja2.Environment",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "jinja2.FileSystemLoader",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"l... |
520302678 | import os
from slack import WebClient
class Slack:
def __init__(self, event_type, event_user, event_text, event_ts, event_channel, event_event_ts,
event_reaction=None):
# Create a SlackClient for your bot to use for Web API requests
slack_bot_token = os.environ["SLACK_BOT_TOKEN"]
... | null | lib/slack/slack.py | slack.py | py | 1,445 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "os.environ",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "slack.WebClient",
"line_number": 10,
"usage_type": "call"
}
] |
290978366 | import os
import glob
import sys
import tensorflow as tf
from tqdm import tqdm_notebook as tqdm
import logging
from scipy import misc
import numpy as np
from tensorflow.contrib.keras.python import keras
from tensorflow.contrib.keras.python.keras import layers, models
from tensorflow import image
from utils import sc... | null | code/aux_function.py | aux_function.py | py | 8,373 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "utils.separable_conv2d.SeparableConv2DKeras",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "tensorflow.contrib.keras.python.keras.layers.BatchNormalization",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "tensorflow.contrib.keras.python.keras... |
632383064 | #!/usr/bin/env python
from sploitego.maltego.message import IPv4Address, UIMessage
from sploitego.framework import configure
from common.reversegeo import getlocbymac
__author__ = 'Nadeem Douba'
__copyright__ = 'Copyright 2012, Sploitego Project'
__credits__ = ['Nadeem Douba']
__license__ = 'GPL'
__version__ = '0.1... | null | src/sploitego/transforms/findlocbymac.py | findlocbymac.py | py | 1,011 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sploitego.maltego.message.UIMessage",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "common.reversegeo.getlocbymac",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "sploitego.framework.configure",
"line_number": 24,
"usage_type": "call"... |
422561979 | import collections
import motor
import tornado
import tornado.web
import pymongo
import wrds
import multiprocessing
import multiprocessing.pool
import numpy as np
import time
from aBlackFireCapitalClass.ClassStocksMarketData.ClassStocksMarketDataInfos import StocksMarketDataInfos
# from bBlackFireCapitalData.Countrie... | null | zBlackFireCapitalImportantFunctions/SetClobalsEnvironment.py | SetClobalsEnvironment.py | py | 11,277 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "multiprocessing.Process",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": "multiprocessing.pool",
"line_number": 46,
"usage_type": "attribute"
},
{
"api_name": "collections.namedtuple",
"line_number": 50,
"usage_type": "call"
},
{
"api... |
111533048 |
"""
Canonical structures
"""
import os
import sys
import json
import pickle
import numpy as np
import bcr_models as igm
try:
FileNotFoundError
except NameError:
FileNotFoundError = IOError
class CsDatabase(object):
"""
Database interface for canonical structures.
"""
def get(self, ig_ch... | null | bcr_models/canonical_structures.py | canonical_structures.py | py | 4,958 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "json.load",
"line_number": 76,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 88,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 88,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_numbe... |
63385965 | import sys, os
sys.path.extend([os.path.join(root, name) for root, dirs, _ in os.walk("../") for name in dirs])
from module import Model
import tensorflow as tf
import tensorflow_tools as tf_tools
from block import cnn_block
class CNN(Model):
def __init__(self, scope_name, channel_min, width, height, channel_rate... | null | TF_Build/TF_Build/unet/cnn_rgb.py | cnn_rgb.py | py | 6,619 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sys.path.extend",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": ... |
588438925 | # Copyright (c) 2018 UAVCAN Consortium
# This software is distributed under the terms of the MIT License.
# Author: Pavel Kirienko <pavel@uavcan.org>
import os
import typing
import logging
from . import _serializable
from . import _expression
from . import _error
from . import _dsdl_definition
from . import _parser
fr... | null | pydsdl/_data_type_builder.py | _data_type_builder.py | py | 17,142 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "typing.Iterable",
"line_number": 48,
"usage_type": "attribute"
},
{
"api_name": "typing.Callable",
"line_number": 49,
"usage_type": "attribute"
},
{
"api_name": "typing.Op... |
326034138 | '''
87. 単語の類似度
85で得た単語の意味ベクトルを読み込み，"United States"と"U.S."のコサイン類似度を計算せよ．
ただし，"U.S."は内部的に"U.S"と表現されていることに注意せよ．
'''
import pickle
import scipy.io as sio
from numpy.linalg import norm
from scipy import sparse
def load(file_name):
with open(f"./pickles/{file_name}.pkl", 'rb') as f_in:
data = pickle.load(f_in)
... | null | kiyuna/chapter09/knock87.py | knock87.py | py | 796 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pickle.load",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.linalg.norm",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "scipy.io.loadmat",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "scipy.io",
"line_n... |
42955053 | ##############################################################################
# Institute for the Design of Advanced Energy Systems Process Systems
# Engineering Framework (IDAES PSE Framework) Copyright (c) 2018-2019, by the
# software owners: The Regents of the University of California, through
# Lawrence Berkeley N... | null | idaes/dmf/util.py | util.py | py | 8,169 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "importlib.import_module",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 82,
"usage_type": "call"
},
{
"api_name": "tempfile.mkdtemp",... |
493368223 | #-*-coding:utf-8-*-
__author__ = 'AeenPython'
"""
由于淘宝的清单页的加密暂时无法破解，换个方式使用，直接抓取所有商品的列表
清单加密方式已经破解，接续尝试
"""
import asyncio
import json
import os
import random
import re
import time
from datetime import datetime
import pandas as pd
from pyppeteer import errors
from pyppeteer import launch
from retrying import retry
c... | null | Pyppete/taobao_store_classdown.py | taobao_store_classdown.py | py | 11,832 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pyppeteer.launch",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 134,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number... |
558634418 | from __future__ import absolute_import
import logging
import os
import re
import shutil
import subprocess
import sys
from io import open
from typing import (Dict, List, Text, MutableMapping, Any)
from .errors import WorkflowException
from .job import ContainerCommandLineJob
from .pathmapper import PathMapper, ensure... | null | cwltool/singularity.py | singularity.py | py | 8,056 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "job.ContainerCommandLineJob",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "re.search",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "re.sub",
... |
555781287 | from FT.weighted_tracts import load_ft, nodes_labels_mega, nodes_by_index_mega
import matplotlib.pyplot as plt
from FT.all_subj import all_subj_names
from dipy.tracking import utils
import numpy as np
from dipy.tracking.streamline import values_from_volume
import nibabel as nib
import os
index_to_text_file = r'C:\User... | null | non_norm_hist.py | non_norm_hist.py | py | 2,465 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "FT.all_subj.all_subj_names",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "FT.weighted_tracts.load_ft",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.p... |
356006672 | import speech_recognition as sr
r = sr.Recognizer()
file = sr.AudioFile('test2.wav')
with file as source:
r.adjust_for_ambient_noise(source)
audio = r.record(source)
result = r.recognize_google(audio, language='fr')
print(result) | null | voice_to_text.py | voice_to_text.py | py | 238 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "speech_recognition.Recognizer",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "speech_recognition.AudioFile",
"line_number": 5,
"usage_type": "call"
}
] |
524095328 | import json
import os
import argparse
import abeja
from abeja.datasets import APIClient
from abejacli.config import (
ABEJA_PLATFORM_USER_ID, ABEJA_PLATFORM_TOKEN
)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Annotation Data Importer: Text Classification')
parser.add_argument... | null | scripts/text_classification.py | text_classification.py | py | 2,582 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "abejacli.config.ABEJA_PLATFORM_USER_ID",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "abejacli.config.ABEJA_PLATFORM_TOKEN",
"line_number": 22,
"usage_type": "n... |
604620417 | import vk_api
from pymongo import MongoClient
client = MongoClient('localhost', 27017)
collection = client.test.coll2
def get_pool(vk_session, comm_id, wall, dbname="test", collname="coll"):
global collection
collection = client.get_database(dbname).get_collection(collname)
get_pool_comments(vk_session, ... | null | api_funcs.py | api_funcs.py | py | 5,597 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "vk_api.VkRequestsPool",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "vk_api.VkRequestsPool",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "vk_api... |
599842981 | from sklearn.ensemble import RandomForestClassifier
import math
class Domain:
def __init__(self, name, label=None):
self.name = name.strip()
self.length = len(name)
if label:
self.label = label.strip()
else:
self.label = None
self.entropy = Domain.cal... | null | test.py | test.py | py | 1,754 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "math.log2",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "sklearn.ensemble.RandomForestClassifier",
"line_number": 57,
"usage_type": "call"
}
] |
415726096 | import numpy as np
import matplotlib.pyplot as plt
incomes = np.random.normal(27000, 15000, 10000) # center of 27000, std 15000, 10000 data points
np.mean(incomes)
np.median(incomes)
plt.hist(incomes, 50) # create a histogram broken into 50 buckets
plt.show()
incomes = np.append(incomes, [1000000000])
| null | basic_stats.py | basic_stats.py | py | 314 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "numpy.random.normal",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "numpy.mean",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.median",
"lin... |
243377501 | import time
import urllib
import httplib2
import simplejson
import datetime
from twitter.utils import OAuthSettings
from twitter.models import TwitterToken, Notification
from freshbooks.models import UserProfile
import simpleoauth
import settings
uri = 'http://api.twitter.com/1/statuses/update.json'
def get_status(... | null | twitter/api.py | api.py | py | 1,447 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "twitter.models.TwitterToken.objects.get",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "twitter.models.TwitterToken.objects",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "twitter.models.TwitterToken",
"line_number": 28,
"usage_... |
237623300 | #import rospy
import rclpy
from heartbeat_profiler_msgs.msg import HeartbeatProfiling
from std_msgs.msg import String
import datetime
from zoro_utils import time as zorotime
class FunctionProfiler:
def __init__(self, node, func_name):
# Internal data
self.node = node
self.runtime_accumulate... | null | spin_camera/src/octopus-dependency/src/heartbeat_sender/heartbeat_sender/heartbeat_profiler.py | heartbeat_profiler.py | py | 2,688 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "heartbeat_profiler_msgs.msg.HeartbeatProfiling",
"line_number": 27,
"usage_type": "argument"
},
{
"api_name": "zoro_utils.time.Time.now",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "zoro_utils.time.Time",
"line_number": 47,
"usage_type": "attr... |
219162453 | import xlrd
from xlutils.copy import copy
class ExcelUtil():
def __init__(self,excel_path = '',index = None):
if excel_path == '':
excel_path = 'D:\workspace\python\config\case_data.xls'
if index == None:
index = 0
self.excel_path = excel_path
self.index = ind... | null | util/excel_util.py | excel_util.py | py | 1,376 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "xlrd.open_workbook",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "xlutils.copy.copy",
"line_number": 45,
"usage_type": "call"
}
] |
424757544 | # -*- coding: utf-8 -*-
"""
Created on Wed Apr 1 22:05:02 2020
@author: einar
"""
import ast
from collections import Counter
from scipy.sparse import csr_matrix
import numpy as np
def clean_url(x):
x = x.replace('http://','').replace('https://','').replace('www.','')
string = x.split('/')
return string[... | null | EinarTest/FinalEinar/functions.py | functions.py | py | 847 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "ast.literal_eval",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "collections.Counter",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "scipy.sparse.csr_matrix",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.in... |
578848044 | # coding: utf-8
from itertools import zip_longest
from logging import getLogger
from math import degrees
from random import randrange
import bpy
import mathutils
from .icr2model.flavor import *
from .icr2model.flavor.flavor import *
from .icr2model.flavor.value.unit import to_papy_degree
from .icr2model.flavor.value.v... | null | io_scene_3do/export_3do.py | export_3do.py | py | 25,101 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "bpy.data",
"line_number": 74,
"usage_type": "attribute"
},
{
"api_name": "random.randrange",
"line_number": 145,
"usage_type": "call"
},
{
"api_name": "random.randrange",
... |
34337631 |
import sqlite3
conn = sqlite3.connect("services/chinook.db")
try:
pass
crs = conn.cursor()
cmd1 = "select CustomerId, FirstName, LastName from customers"
crs.execute(cmd1)
for customer_row in crs:
# print(customer_row)
cust_id = customer_row[0]
num_track... | null | In Class Code/2-16-19/in_class_190226/preparation/rest_example/basic_report.py | basic_report.py | py | 1,474 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "sqlite3.connect",
"line_number": 5,
"usage_type": "call"
}
] |
183915148 | from PIL import Image
import PIL
import sys, os
import shutil
from pathlib import Path
def copyAndCompress(fromDirectory, compressDirectory):
shutil.rmtree(compressDirectory)
print(fromDirectory)
shutil.copytree(fromDirectory, compressDirectory)
print(compressDirectory)
print(os)
print(os.c... | null | carouselImageCompressor.py | carouselImageCompressor.py | py | 1,002 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "shutil.rmtree",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "shutil.copytree",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 1... |
107744066 | from flask import Flask, Blueprint, redirect, url_for, request, session, render_template, flash, g, current_app
import uuid
import msal
import json
config = current_app.config
auth = Blueprint('auth', __name__, url_prefix=config.get('AUTH_ENDPOINTS_PREFIX'), static_folder='static')
msal_instance = msal.ConfidentialC... | null | auth_endpoints.py | auth_endpoints.py | py | 5,183 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "flask.current_app.config",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "flask.current_app",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "flask.Blueprint",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "msal.Con... |
444395460 | import os
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.Alphabet import IUPAC
from Bio.SeqRecord import SeqRecord
from Bio.Alphabet import generic_dna
from Bio import SeqFeature as SF
from Bio.SeqFeature import FeatureLocation
from Bio.SeqFeature import SeqFeature
def export_dna_record(gene_seq, gene_id, gen... | null | MetaCHIP_Temp/prodigal_parser.py | prodigal_parser.py | py | 5,554 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "Bio.Seq.Seq",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "Bio.Alphabet.IUPAC.unambiguous_dna",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "Bio.Alphabet.IUPAC",
"line_number": 13,
"usage_type": "name"
},
{
"api_name":... |
352572929 | # This file is part of Checkbox.
#
# Copyright 2013 Canonical Ltd.
# Written by:
# Zygmunt Krynicki <zygmunt.krynicki@canonical.com>
# Daniel Manrique <roadmr@ubuntu.com>
#
# Checkbox is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 3,
# as publi... | null | python3/dist-packages/plainbox/impl/transport.py | transport.py | py | 10,443 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "logging.getLogger",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "plainbox.abc.ISessionStateTransport",
"line_number": 57,
"usage_type": "name"
},
{
"api_name": "plainbox.i18n.gettext",
"line_number": 98,
"usage_type": "call"
},
{
"api_n... |
69862015 | import os
from django.db import models
from django.http import HttpResponse
from django.shortcuts import render
from gunicorn.http.wsgi import FileWrapper
from pyconbalkan.conference.models import Conference, CountDown, MissionStatement
from pyconbalkan.settings import BASE_DIR
from pyconbalkan.speaker.models import ... | null | pyconbalkan/core/views.py | views.py | py | 2,309 | python | en | code | null | code-starcoder2 | 83 | [
{
"api_name": "models.Person",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pyconbalkan.conference.models.CountDown.objects.filter",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "pyconbalkan.conference.models.CountDown.objects",
"line_number": 30,
... |
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