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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
617433100 | # coding: utf-8
import os
import random
import numpy as np
import pickle as pkl
import networkx as nx
import scipy.sparse as sp
from utils import loadWord2Vec, clean_str
from math import log
from sklearn import svm
from nltk.corpus import wordnet as wn
from sklearn.feature_extraction.text import TfidfVectorizer
import... | null | graph_builder.py | graph_builder.py | py | 16,986 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "random.seed",
"line_number": 77,
"usage_type": "call"
},
{
"api_name": "random.shuffle",
"line_number": 78,
"usage_type": "call"
},
{
"api_name": "random.shuffle",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "scipy.sparse.csr_matrix",
... |
235209546 | # --------------------------------------------------------
# Deep Iterative Matching Network
# Licensed under The Apache-2.0 License [see LICENSE for details]
# Written by Gu Wang, Yi Li
# --------------------------------------------------------
from __future__ import print_function, division
import numpy as np
import... | null | toolkit/ModelNet_4_gen_rendered_and_pair_set.py | ModelNet_4_gen_rendered_and_pair_set.py | py | 5,904 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.dirname",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.path.insert",
"l... |
189897464 | __package__ = 'keras_retinanet.utils'
from .transform import random_transform
from .image import apply_transform, TransformParameters, adjust_transform_for_image
import cv2
image = cv2.imread('test.jpg')
cv2.imshow('image', image)
cv2.waitKey(0)
m1 = random_transform(flip_x_chance=1)
print(m1)
transform_parameters = T... | null | keras_retinanet/utils/test_transform.py | test_transform.py | py | 518 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.imread",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "transform.random_transform",
"line... |
545320224 | from trac.core import *
from trac.web.chrome import ITemplateProvider, add_stylesheet
#from trac.wiki.api import IWikiMacroProvider
from trac.web.main import IRequestHandler
from trac.util import escape
from genshi.core import Markup
from trac.wiki.macros import WikiMacroBase
import re
__all__ = ['ShellExample']
####... | null | shellexamplemacro/0.12/tags/0.12.1/shellexample/module.py | module.py | py | 6,729 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "re.compile",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "re.M",
"line_number": 45,
"usage_type": "attribute"
},
{
"api_name": "re.S",
"line_number": 45,
"us... |
468362484 | from typing import overload, NamedTuple
from abc import ABCMeta
from pyraknet.bitstream import Serializable, c_uint8, c_uint16, c_uint32
from enums import PACKET_IDS, PACKET_NAMES
class CString(Serializable):
def __init__(self, data, allocated_length=None, length_type=None):
self.data = data
self.a... | null | server/structs.py | structs.py | py | 2,122 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pyraknet.bitstream.Serializable",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "pyraknet.bitstream.Serializable",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "typing.overload",
"line_number": 21,
"usage_type": "name"
},
{
"ap... |
159528591 | import sqlite3
from sqlite3 import Error
def create_connection(db_file):
""" create a database connection to the SQLite database
specified by the db_file
:param db_file: database file
:return: Connection object or None
"""
conn = None
try:
conn = sqlite3.connect(db_... | null | MAMEly/sqlitetest.py | sqlitetest.py | py | 2,560 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlite3.connect",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sqlite3.Error",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "sqlite3.Error",
"line_number": 28,
"usage_type": "name"
}
] |
545266574 | import os
import subprocess
import sys
import textwrap
import yaml
from datetime import date
from importlib import import_module
import connexion
from cloudmesh.common.Shell import Shell
from cloudmesh.common.console import Console
from cloudmesh.common.debug import VERBOSE
from cloudmesh.common.util import path_expan... | null | cloudmesh/openapi3/function/server.py | server.py | py | 9,017 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.fork",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "os._exit",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.EX_OK",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "importlib.import_module",
"line_nu... |
271843764 |
import os, sys, math, random, itertools
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import datasets, transforms, models
from torch.optim.lr_scheduler import MultiStepLR
from models import TrainableModel
from utils import *
class ConvBlock(nn.Module):
d... | null | modules/resnet.py | resnet.py | py | 2,174 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.nn.Module",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
350690072 | from collections import namedtuple
import pytest
from solax import inverter
XHYBRID_DE01_RESPONSE = {
'method': 'uploadsn',
'version': 'Solax_SI_CH_2nd_20160912_DE02',
'type': 'AL_SE',
'SN': 'XXXXXXX',
'Data': [0, 1, 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
... | null | tests/fixtures.py | fixtures.py | py | 5,249 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pytest.fixture",
"line_number": 130,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 140,
"usage_type": "call"
},
{
"api_name": "solax.inverter.XHybrid",
"line_number": 151,
"usage_type": "attribute"
},
{
"api_name": "... |
628044039 | from shapely.geometry import Point
from shapely.geometry import Polygon
from shapely.geometry import box
from BFS import bfs
from DFS import dfs
from AS import astar
inputf = open('input.txt','r')
IP = [line.rstrip('\n') for line in inputf]
inputf.close()
# SP = Starting point
# FP = Goal point
# POLY ... | null | python_scripts/CS180_MP_Khim/Main.py | Main.py | py | 992 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "shapely.geometry.Point",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "shapely.geometry.Point",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "shapely.geometry.Polygon",
"line_number": 32,
"usage_type": "call"
},
{
"api_name":... |
430007972 | #!/usr/bin/env python3
""" This module contains a class for converting a TOMES Excel 2007+ (.xlsx) entity dictionary
file to a Python generator where each item is a dict with headers as keys and row data as
values. """
# import modules.
import hashlib
import itertools
import logging
import os
from openpyxl import lo... | null | tomes_entities/lib/xlsx_to_entities.py | xlsx_to_entities.py | py | 13,117 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "logging.NullHandler",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "hashlib.sha256",
"line_number": 61,
"usage_type": "call"
},
{
"api_name": "itertools.produc... |
57328911 |
import argparse
import collections
import json
import os
import sys
from vocab import Dictionary
from eval_util import *
from dstore_util import *
from dataset_util import *
import numpy as np
import torch
from tqdm import tqdm
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKCYAN = '\033[96m'
... | null | offline_eval_hunt.py | offline_eval_hunt.py | py | 8,129 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.full_like",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "numpy.bool",
"line_number": 45,
"usage_type": "attribute"
},
{
"api_name": "tqdm.tqdm",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "numpy.isin",
"line_numb... |
553610731 | from django import template
from oscar.core.loading import get_model
register = template.Library()
Line = get_model('wishlists', 'Line')
Product = get_model('catalogue', 'Product')
@register.simple_tag
def get_product_parent(product):
if product and product.is_child:
return product.parent
return pr... | null | app/catalogue/templatetags/find_parent_tags.py | find_parent_tags.py | py | 751 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.template.Library",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.template",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "oscar.core.loading.get_model",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "osc... |
391598952 | import itertools
import six
class ProxyDictPostWrite(dict):
""" Dictionary wrapper that updates an arguments instance on any item set in the dictionary """
def __init__(self, update_obj, update_func, *args, **kwargs):
super(ProxyDictPostWrite, self).__init__(*args, **kwargs)
self._update_obj... | null | trains/utilities/proxy_object.py | proxy_object.py | py | 5,025 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "six.string_types",
"line_number": 83,
"usage_type": "attribute"
},
{
"api_name": "six.string_types",
"line_number": 86,
"usage_type": "attribute"
},
{
"api_name": "six.string_types",
"line_number": 100,
"usage_type": "attribute"
},
{
"api_name": "si... |
362933787 | import numpy as np
from scipy import linalg
from random import randint
from sys import argv
from matplotlib import pyplot as plt
# companion pencil
def comPencil(P):
# degree and size
m = len(P) - 1
n = len(P[0])
# matrix A
A0 = -P[0]
for j in range(1,m):
A0 = np.concatenate((A0,-P[j]),... | null | Python/pellet.py | pellet.py | py | 3,249 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.concatenate",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.concatenate",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.eye",
"line... |
343000379 | from cryptography.fernet import Fernet as fernet
from tkinter import messagebox
def decryptFromUserInput():
userInputToken = entry2.get()
userInputFile = entry1.get()
try:
decdet=getDecryptionDetails(userInputFile)
decrypted = decryptFile(userInputToken,decdet['encryptedContents'])
m... | null | encryption.py | encryption.py | py | 2,419 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tkinter.messagebox.showinfo",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "tkinter.messagebox",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "tkinter.messagebox.showinfo",
"line_number": 12,
"usage_type": "call"
},
{
"api_name... |
139685208 | import os
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
mc_experiments = [e for e in os.listdir('results') if e.startswith('mc_')]
os.makedirs('figures', exist_ok=True)
fig = plt.figure(figsize=... | null | tests/plot_mc_results.py | plot_mc_results.py | py | 1,254 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.use",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "matplotlib.rcParams.update",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.rcParams",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "os.listdir... |
151986377 | import pandas as pd
import numpy as np
train = pd.read_csv('train.csv')
test = pd.read_csv('test.csv')
import matplotlib.pyplot as plt
plt.style.use(style='ggplot')
plt.rcParams['figure.figsize'] = (10, 6)
#plot a histogram of SalePrice
print ("Skew is:", train.SalePrice.skew())
plt.hist(train.SalePrice, col... | null | houseprice decision tree.py | houseprice decision tree.py | py | 5,214 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "matplotlib.p... |
334523592 | import pandas as pd
import numpy as np
import datetime as dt
from datetime import date , time
class dataassertionreport:
# '''
# Function does Sanitcy Check on the dataframe to look for data consistency and accuracy
# '''
def __init__(self, dataframe, primarykey_list, main_date_key):
... | null | Mortgage_Loan_Segment_Project/data_assertion.py | data_assertion.py | py | 1,447 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.DataFrame",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "numpy.select",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "datetime.date.today",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "datetime.date",
... |
451963833 | from django.shortcuts import render, redirect, HttpResponse
import requests
import json
import time
# Create your views here.
def main(req):
return render(req, 'main/container.html')
def get_stats(req):
if req.method == 'GET':
return render(req,'main/__stats__.html')
def getChartData(ticker, gr... | null | apps/main/views.py | views.py | py | 1,669 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.shortcuts.render",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.request",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "djang... |
328472557 | import io
import os.path
from cStringIO import StringIO
from django.utils.translation import ugettext_lazy as _
from django.utils import translation
from submissions.models import Submission
SUBMIT_CONFIRMATION = [
(_('Film'), [
'title', 'title_en', 'country', 'language', 'genre',
'section', 'sy... | null | submissions/pdf.py | pdf.py | py | 3,939 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.utils.translation.ugettext_lazy",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.utils.translation.ugettext_lazy",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.utils.translation.ugettext_lazy",
"line_number": 19,
... |
535276217 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
CHAVE-Sim: The simulator for research based in clouds architecture
CHAVE: Consolidation with High Availability on virtualyzed environments
"""
from shelve import DbfilenameShelf, Shelf
import shelve
from copy import deepcopy
import random
from math import sqrt
from ... | null | misc/tests/database/MetricDB_shelve.py | MetricDB_shelve.py | py | 5,180 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "shelve.open",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "collections.OrderedDict",
"line_number": 130,
"usage_type": "call"
}
] |
53004994 | from selenium import webdriver
from selenium.webdriver.chrome.options import Options
class WeatherCrawler():
def __init__(self, url="https://www.cwb.gov.tw/V8/C/W/Town/Town.html?TID=6400600"):
self.url = url
# ---------------------------------------------------------------------------------... | null | Models/WeatherCrawler.py | WeatherCrawler.py | py | 1,760 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "selenium.webdriver.chrome.options.Options",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 24,
"usage_type": "name"
}
] |
12382334 | from docx import Document
import os
def combine_word_documents(files):
merged_document = Document()
for index, file in enumerate(files):
sub_doc = Document(file)
if index < len(files)-1:
sub_doc.add_page_break()
for element in sub_doc.element.body:
merged_docu... | null | ocr_niilakantha_jiivana_daasa/merge_docs.py | merge_docs.py | py | 547 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "docx.Document",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "docx.Document",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number"... |
626924623 |
from sklearn.neighbors import KNeighborsClassifier as KNC
from MLalgorithms._Classification import Classification
class KNeighborsClassifier(Classification):
def fit(self, X, y):
return self.model.fit(X=X,
y=y)
def predict(self, X):
return self.model.predict(X=X)
def __init__(self, n_neig... | null | Code/Implement and design a machine learning hierarchy wrapper for SimpleML/MLalgorithms/Classification/_KNeighborsClassifier.py | _KNeighborsClassifier.py | py | 914 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "MLalgorithms._Classification.Classification",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "sklearn.neighbors.KNeighborsClassifier",
"line_number": 24,
"usage_type": "call"
}
] |
51256673 | from __future__ import print_function
import sqlite3
def get_name(database_file, person_id):
query = "SELECT personal || ' ' || family FROM Person WHERE id=?;"
connection = sqlite3.connect(database_file)
cursor = connection.cursor()
cursor.execute(query, [person_id])
results = cursor.fetchall()
... | null | DataFest-2018/Multiple-Approaches-to-Combining-Data/scripts/better_query.py | better_query.py | py | 447 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlite3.connect",
"line_number": 7,
"usage_type": "call"
}
] |
413722799 | from django.urls import path
from . import views
app_name = 'shirts'
urlpatterns = [
path('', views.shirts, name='shirts'),
path('detail/<slug:slug>/<str:color>/', views.shirts_card, name='shirts_card'),
path('create/', views.add_shirt, name='add_shirt'),
] | null | shirts/urls.py | urls.py | py | 273 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.urls.path",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 11,
"usage_type": "call"
}
] |
73130147 | from rest_framework import serializers
from project.models import Project
from placed_user.serializers import PlacedUserSerializer
from skill.models import Skill
from project_platform.models import ProjectPlatform
from project_data.models import ProjectData
from project_target_device.models import ProjectTargetDevice
... | null | django-apps/placed_backend/project/serializers.py | serializers.py | py | 2,163 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "rest_framework.serializers.ModelSerializer",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "placed_user.serializers.PlacedUserSerializer",
"line_number": 11,
... |
496501141 | #!/usr/bin/python
from datetime import datetime, timedelta
from typing import IO
from dateutil.relativedelta import relativedelta
import grequests
import requests
import json
import sys
import os
import parse
import zendesk as zd
import slackhandler as slack
import util
user = ''
domain = ''
view = ''
channel = ''
m... | null | python/bot.py | bot.py | py | 7,838 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "datetime.datetime.today",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 56,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.now",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "datet... |
498687752 | from datetime import date
import matplotlib.pyplot as plt
import seaborn as sns
import requests
import json
import numpy as np
def get_data():
"""Retrieve the data we will be working with."""
response = requests.get(
"http://earthquake.usgs.gov/fdsnws/event/1/query.geojson",
params={
... | null | plot_earthquakes.py | plot_earthquakes.py | py | 4,344 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.get",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "datetime.date.fromtimestamp",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "datetime.date",
... |
258132722 | from __future__ import unicode_literals
from django.conf.urls import url
from .views import NamespaceDetailView, NamespaceListView, SettingEditView
urlpatterns = [
url(
regex=r'^namespaces/$', view=NamespaceListView.as_view(),
name='namespace_list'
),
url(
regex=r'^namespaces/(?P<... | null | mayan/apps/smart_settings/urls.py | urls.py | py | 577 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.conf.urls.url",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "views.NamespaceListView.as_view",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "views.NamespaceListView",
"line_number": 9,
"usage_type": "name"
},
{
"api_nam... |
170006835 | import cv2
import numpy as np
import random
# load grayscale image
img = cv2.imread("data/image/rose.jpg", 0)
# thresholding
min_value = 200
max_value = 255
thresh_type = cv2.THRESH_BINARY
_, img_thresh = cv2.threshold(img, min_value, max_value, thresh_type)
# connected components analysis
_, labels = cv2.connectedC... | null | src/basic/segmentation/connectedComponentAnalysis.py | connectedComponentAnalysis.py | py | 1,287 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.imread",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.THRESH_BINARY",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "cv2.threshold",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.connectedComponent... |
304253323 | import os.path, sys
import numpy as np
import pandas as pd
from scipy import linalg
from scipy.sparse import csr_matrix
from sklearn.preprocessing import OneHotEncoder
import Bio.PDB, warnings
pdb_list = Bio.PDB.PDBList()
pdb_parser = Bio.PDB.PDBParser()
from scipy.spatial import distance_matrix
from Bio import Biopy... | null | furano_periwal_prot/run_edist_family.py | run_edist_family.py | py | 12,269 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "Bio.PDB.PDB.PDBList",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "Bio.PDB.PDB",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "Bio.PDB",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "Bio.PDB.PDB.PDBParser",
... |
263979975 | #!/usr/bin/env python
"""test_cam.py: open external USB cam (address 1) to check if it's working.
"""
__author__ = "Vinicius Guimaraes Goecks"
__copyright__ = "TBD"
__credits__ = ["TBD", "TBD"]
__license__ = "TBD"
__version__ = "0.0.0"
__maintainer__ = "Vinicius Guimaraes Goecks"
__email__ = "viniciusguigo@gmail.com"
... | null | test/test_cam/test_cam.py | test_cam.py | py | 1,246 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "cv2.namedWindow",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "cv2.WINDOW_NORMAL",
"line_number": 36,
"usage_type": "attribute"
},
{
"api_name": "cv2.imshow",
... |
175178490 | import os
import sys
import csv
import pandas as pd
import getopt
import matplotlib.pyplot as plt
import math
import subprocess
def show_total_data(ifile, timeRefrush):
plt.style.use("fivethirtyeight")
df = pd.read_csv(ifile)
rowCnt = df.shape[0]
lname = df.columns.values[2:].tolist()
i = 1
pl... | null | memory/showTotalMem.py | showTotalMem.py | py | 2,035 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 12,
"usage_type": "name"
},
{
"api_na... |
230653743 | import random
from typing import Dict, Mapping, Iterable
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
from torch.utils.data.sampler import SubsetRandomSampler
from torch.utils.data import DataLoader
from torch.utils.tensorbo... | null | tuto/pytorch/solution.py | solution.py | py | 7,463 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.nn.Module",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
129098895 | import numpy as np
from keras import backend as K
from plotting import lossplot, roc, prcurve
from performance import ACC, MCC
from load_data import load_data
from model import build_model,compileModel,build_model_CNN
K.set_image_data_format('channels_last')
import os
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" # ... | null | main.py | main.py | py | 1,958 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "keras.backend.set_image_data_format",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "keras.backend",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "os.environ",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.en... |
337593346 | import json
import time
import logging
from builder import errors
from builder.metrics import MetricsLogger
public_log = logging.getLogger('public')
private_log = logging.getLogger('private')
metrics = MetricsLogger()
def handle_progress(push_line):
details = push_line.get('progressDetail')
return "{} Pushi... | null | stage/builder/registry.py | registry.py | py | 3,299 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "builder.metrics.MetricsLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "json.... |
649446085 | import torch
import matplotlib.pyplot as plt
import os
import torch.nn as nn
m1 = torch.load("mnist_1/initial_state_dict_lt.pth.tar", map_location="cpu").state_dict()
def train(model, train_loader, optimizer, criterion):
EPS = 1e-6
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model... | null | analysis.py | analysis.py | py | 6,276 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.load",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_n... |
119333925 | """Hamiltonian Monte Carlo MCMC sampler classes."""
import logging
import numpy as np
import hmc
from hmc.states import HamiltonianState
from hmc.utils import LogRepFloat
from hmc.errors import (
IntegratorError, NonReversibleStepError, ConvergenceError)
try:
import tqdm.auto as tqdm
TQDM_AVAILABLE = True
... | null | hmc/samplers.py | samplers.py | py | 30,947 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.empty",
"line_number": 85,
"usage_type": "call"
},
{
"api_name": "numpy.float64",
"line_number": 85,
"usage_type": "attribute"
},
{
"api_name": "numpy.empty",
"l... |
538259771 | # -*- coding: utf-8 -*-
from quicky import tenancy
from django.contrib.auth import authenticate, login as request_login
from django.shortcuts import redirect
from . import menu
import importlib
import json
from django.views.decorators.http import require_http_methods
from django.views.decorators.csrf import csrf_exempt... | null | apps/hrm/views.py | views.py | py | 5,438 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "quicky.applications.get_app_by_file",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "quicky.applications",
"line_number": 20,
"usage_type": "attribute"
},
{
"ap... |
515970234 | # Canny edge detector implementation
# See https://towardsdatascience.com/canny-edge-detection-step-by-step-in-python-computer-vision-b49c3a2d8123
from utils.timeit import time_it
from scipy import ndimage
from scipy.ndimage.filters import convolve
import numpy as np
class CannyEdgeDetector:
def __init__(
... | null | order-processing-app/processing/canny_edge_detector.py | canny_edge_detector.py | py | 5,117 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.zeros",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "numpy.int32",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "utils.timeit.time_it",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "numpy.mgrid",
"... |
325521718 | #!/usr/bin/env python3
'''
Library + demonstration tool for parsing the metadata contained in a `btrfs
send` stream, as printed by `btrfs receive --dump`.
Usage:
btrfs send --no-data SUBVOL/ | btrfs receive --dump | parse_dump.py
The `--no-data` flag is optional, but should speed up the send & receive
considerably... | null | infra_macros/macro_lib/convert/container_image/btrfs_diff/parse_dump.py | parse_dump.py | py | 15,136 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "collections.OrderedDict",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "re.escape",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "compiler.enriched_namedt... |
242228917 | from tkinter import *
import sqlite3
class Sistema():
def __init__(self, master=None):
self.cria_db
# Define os containers
self.container_01 = Frame(master)
self.container_01["pady"] = 10
self.container_01.pack()
self.container_02 = Frame(master)
self.contai... | null | Tkinter/gerenciamento_estoque/Gerenciador de produtos.py | Gerenciador de produtos.py | py | 7,449 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlite3.connect",
"line_number": 102,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 127,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 169,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
... |
531403138 | # uncompyle6 version 3.7.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: build/bdist.linux-x86_64/egg/snmpsim_control_plane/management/exporters/renderer.py
# Compiled at: 2020-01-01 13:42:52
import os, stat, tempfile, jinja2
def ren... | null | pycfiles/snmpsim_control_plane-0.0.2-py2.7/renderer.py | renderer.py | py | 1,151 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.exists",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.unlink",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number... |
268245867 | # coding: utf-8
# Copyright 2016 Mirantis, 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 | nailgun/nailgun/test/unit/test_downgrade_fuel_9_0_2.py | test_downgrade_fuel_9_0_2.py | py | 2,117 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "nailgun.db.dropdb",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "alembic.command.upgrade",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "nailgun.db.migration.ALEMBIC_CONFIG",
"line_number": 32,
"usage_type": "argument"
},
{
... |
176343728 | # import sqlite3
# conn = sqlite3.connect("new.db")
# cursor = conn.cursor()
# try:
# cursor.execute("""INSERT INTO population VALUES
# ("Alexandria", "Alex", 5000000)""")
# cursor.execute("""INSERT INTO population VALUES
# ("Mahalla", "MHL", "mama")""")
# cursor.execute("""SELECT * FROM population WHERE k... | null | sql/sqltest.py | sqltest.py | py | 697 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlite3.connect",
"line_number": 20,
"usage_type": "call"
}
] |
545385795 | import requests
import json
def barkCheck(messageText):
headers = {
'Content-Type': 'application/json; charset=utf-8',
'X-Token-Auth': 'rn4t4uzMufZYNtteRDS9hvZK',
}
data = "{ \"message\": \"" + messageText + "\" }"
return requests.post('https://partner.bark.us/api/v1/messages', header... | null | cbBarkUsi.py | cbBarkUsi.py | py | 428 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "requests.post",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 15,
"usage_type": "call"
}
] |
164425082 | import curses
from time import sleep
def main(stdscr):
# clear screen
stdscr.clear()
# This raises ZeroDivisionError when i == 10
stdscr.addstr(0, 0, 'Enter something:')
for i in range(0, 10):
v = i - 10
key = stdscr.getkey()
stdscr.addstr(0, 0, f' ')
stdscr.a... | null | Meet my pyppy/wrapper_curses.py | wrapper_curses.py | py | 666 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "time.sleep",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "curses.newwin",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "curses.wrapper",
"line_number": 33,
"usage_type": "call"
}
] |
431843300 | """
Player for the competition
"""
from players.AbstractPlayer import AbstractPlayer
import utils
from SearchAlgos import AlphaBeta
import time
import numpy as np
import networkx as nx
# TODO: TO DELETE
# TODO: This is probably not legal though we'll check
import copy
import matplotlib.pyplot as plt
class Player(Abst... | null | players/CompetePlayer.py | CompetePlayer.py | py | 15,343 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "players.AbstractPlayer.AbstractPlayer",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "players.AbstractPlayer.AbstractPlayer.__init__",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "players.AbstractPlayer.AbstractPlayer",
"line_number": 1... |
229655718 | # using scaled time so each data point is 1 time unit
# there is a lot of potential for underflow because of the x^3 term, so many
# runs may be needed
import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt
import math
import time
import argparse
import torch
import torch.nn as nn
import torc... | null | experiments/silverbox/silverbox_anode.py | silverbox_anode.py | py | 6,441 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "numpy.asarray",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "numpy.transpose... |
458010033 | import ssn_multi_probes
from util import find_params_to_sigmoid
import jax.numpy as np
# import scipy.io as sio
import json
import sys
ind_in = int(sys.argv[1])
with open("talapas-full-sweep.json", "r") as read_file:
parameters = json.load(read_file)
Jee = parameters['Jee'][ind_in]
Jei = parameters['Jei'][ind_i... | null | jax_caleb/par_sweep_talapas.py | par_sweep_talapas.py | py | 2,258 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sys.argv",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "jax.numpy.array",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "jax.numpy",
"line_number":... |
127354123 | from functools import lru_cache
with open("input.txt", mode="r") as f:
jolts = [ int(x.strip()) for x in f.readlines() ]
jolts.sort()
jolts = [0] + jolts + [ jolts[-1] + 3]
@lru_cache
def counts(j):
global jolts
if j == 0:
return 1
c1, c2, c3 = 0, 0, 0
return (counts(j - 3) if (j - 3) i... | null | 2020/10/part2_cache.py | part2_cache.py | py | 478 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "functools.lru_cache",
"line_number": 11,
"usage_type": "name"
}
] |
383015348 | import pyspark
from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()
from pyspark.sql.functions import unix_timestamp
from pyspark.sql import SQLContext
CUSTOMER = spark.read.option('delimiter',"|").csv(r"C:\Users\pooja\Desktop\DBS\Customer.txt")
CUSTOMER_EXTN = spark.read.... | null | DBS_HackTron_2019_28.py | DBS_HackTron_2019_28.py | py | 3,588 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pyspark.sql.SparkSession.builder.getOrCreate",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 5,
"usage_type... |
580297243 | # Final Project
#
# Author : Rajarshi Biswas
# Sayam Ganguly
import pandas as pd
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer
import string
import _pickle as pickle
def strip_data(data):
data = data[['TITLE','CATEGORY']]
return data
... | null | Final Project/Preprocessing.py | Preprocessing.py | py | 3,363 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "nltk.tokenize.word_tokenize",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "nltk.stem.PorterStemmer",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 28,
"usage_type": "call"
},
{
"a... |
58522932 | # -*- coding: utf-8 -*-
"""The api module.
"""
from .datetime import Zulu
from .timedelta import Delta
now = Zulu.now
parse = Zulu.parse
range = Zulu.range
span_range = Zulu.span_range
delta = Delta.parse
def create(*args, **kargs):
"""Factory function to create a new :class:`.Zulu` datetime using the same
... | null | zulu/api.py | api.py | py | 385 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "datetime.Zulu.now",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "datetime.Zulu",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "datetime.Zulu.parse",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "datetime.... |
628601682 | #!/usr/bin/env python
import rospy
import yaml
import rospkg
config_file_location = "log_config.yaml"
class topic_monitor:
works = []
def __init__(self, topic_type, topic, min_freq):
self.topic_type = topic_type
self.msg_count = 0
self.count_list = []
self.working = True... | null | catkin_ws/src/Backup files/rqt_freq_monitor/src/rqt_freq_monitor/frequency_monitor.py | frequency_monitor.py | py | 2,381 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "rospy.Subscriber",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "rospy.AnyMsg",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "rospy.Timer",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "rospy.Duration",
"... |
154171154 | import module.feature_engineering as fe
import module.utility_es as es
from gensim.models import Word2Vec, KeyedVectors
import pickle
from nltk.tokenize import word_tokenize
import pandas as pd
import numpy as np
def get_entities(tokens, tags):
entities_dict = {
"NAME": [],
"TYPE": [],
... | null | server/module/answer_ext.py | answer_ext.py | py | 2,557 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "nltk.tokenize.word_tokenize",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "module.feature_engineering.clean",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "module.feature_engineering",
"line_number": 37,
"usage_type": "name"
},
... |
207277496 | from sklearn.feature_extraction.text import TfidfVectorizer
dataset = ["Load up on guns, bring your friends",
"It's fun to lose and to pretend",
"She's over-bored and self-assured",
"Oh no, I know a dirty word",
"Hello"]
vectorizer = TfidfVectorizer()
weighted_matrix = vect... | null | Key Terms Extraction/Key Terms Extraction/task/tfidf_score.py | tfidf_score.py | py | 429 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sklearn.feature_extraction.text.TfidfVectorizer",
"line_number": 9,
"usage_type": "call"
}
] |
278674684 | import cv2
import numpy as np
from matplotlib import pyplot as plt
img = cv2.imread('building2.jpg',0)
sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=1)
sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=1)
dst= np.hstack((sobelx,sobely))
cv2.imshow('dsti1',img)
cv2.waitKey(0)
cv2.imshow('dst',dst)
cv2.waitKey(0)
| null | Common/OpenCV/Day3/Set1/16sobel.py | 16sobel.py | py | 312 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.imread",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.Sobel",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "cv2.CV_64F",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "cv2.Sobel",
"line_number": 6,
... |
338652690 | import abc
import logging
__all__ = ['ResolutionError',
'Resolvable',
'Promise',
'Referentiable',
'Reference']
log = logging.getLogger(__name__)
class ResolutionError(RuntimeError):
"""Object could not be resolved."""
class Resolvable(abc.ABC):
"""An object that ... | null | virtualenv/lib/python3.8/site-packages/plum/resolvable.py | resolvable.py | py | 2,250 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "abc.ABC",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "abc.abstractmethod",
"line_number": 19,
"usage_type": "attribute"
}
] |
575803586 | # uncompyle6 version 3.7.4
# Python bytecode 2.7 (62211)
# Decompiled from: Python 3.6.9 (default, Apr 18 2020, 01:56:04)
# [GCC 8.4.0]
# Embedded file name: build/bdist.macosx-10.13-x86_64/egg/max/run.py
# Compiled at: 2019-04-27 23:02:52
import subprocess, sys, yaml, argparse, os
from monkey.getbasic import GetBasic... | null | pycfiles/maxauto-1.0.1-py2.7/run.py | run.py | py | 2,926 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "os.path.exists",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "os.makedirs",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "monkey.getbasic.GetBasic",
... |
257006151 | import xmltodict
import numpy as np
import pandas as pd
from functools import lru_cache
from collections import Counter, defaultdict
from tqdm.auto import tqdm
from nlp import morph_parse, word2pos, tokenize, morphAnalyzer
def normalize(v, epsilon=1e-10):
return v / (sum(v**2)**0.5 + epsilon)
class BaseSenten... | null | code/dale/my_knn.py | my_knn.py | py | 13,092 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "nlp.tokenize",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "functools.lru_cache",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "nlp.word2pos",
"line... |
425593383 | import random
import sqlite3
class saltClass():
def __init__(self, database=None, insults=None):
self.conn = sqlite3.connect(database)
self.c = self.conn.cursor()
with open(insults, "r") as f:
self.insults = [l.strip() for l in f.readlines()]
def insult(self, name):
... | null | bokasafn/salty.py | salty.py | py | 1,237 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "sqlite3.connect",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 14,
"usage_type": "call"
}
] |
178541395 | import pandas as pd
import math
import re
import json
# TableD = ''
zhibiao_path = './zhibiao.json'
zhibiao = ''
# 读取csv文件
def read_file(path):
return pd.read_csv(path, header=0, encoding='gbk')
# 将A表中的数据按户进行划分
def spliteFamily(TableA,TableD):
# 按照sid区分每一户
# 先取sid，去掉重复值
sid_array = TableA["SID"].drop... | null | src/process/test/test.py | test.py | py | 10,081 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 123,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 147,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 154... |
366423117 | #!/usr/bin/env python
import freshair, os, glob, sys, npr_utils
import calendar, numpy, datetime, matplotlib
from matplotlib.patches import Rectangle
from mutagen.easymp4 import EasyMP4
from PyQt4.QtGui import QColor
from optparse import OptionParser
matplotlib.use('Agg')
import pylab
_default_inputdir = '/mnt/media... | null | freshair_by_year.py | freshair_by_year.py | py | 9,917 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.use",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "calendar.monthcalendar",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"... |
348944063 | #!/usr/bin/python
import os
import sys
import logging
import numpy as np
import time
from home_platform.env import BasicEnvironment
from home_platform.utils import Viewer
from home_platform.suncg import loadModel, SunCgSceneLoader
from home_platform.acoustics import EvertAcoustics, CipicHRTF, FilterBank, \
Materi... | null | slam_ws/acoustic.py | acoustic.py | py | 3,800 | python | en | code | null | code-starcoder2 | 66 | [
{
"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.dirname",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "os.path.realpath",
"lin... |
411410325 | # -*- coding: utf-8 -*-
"""
Created on Fri Dec 8 14:15:30 2017
analysing projector data on Taobao.com
@author: talen
"""
import os,jieba,itertools
import pandas as pd
import collections as cc
jieba.load_userdict('C:/WinPython-64bit-3.6.1.0Qt5/python-3.6.1.amd64/Lib/site-packages/jieba/projectornames.txt')
os... | null | sales analysis.py | sales analysis.py | py | 4,452 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "jieba.load_userdict",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pandas.Series",
"l... |
575573102 | #!/usr/bin/env python
import argparse
import bz2
import csv
import hashlib
import os
import shlex
import sqlite3
import subprocess
import tempfile
from pathlib import Path
def parseArgs():
parser = argparse.ArgumentParser()
parser.add_argument('csv_file', type=str,
help='File containi... | null | src/gpu/DNNMark/generate_cachefiles.py | generate_cachefiles.py | py | 4,289 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "sqlite3.connect",
... |
100639889 | #！usr/bin/env python
'''
变换函数：cv2.warpAffine ，cv2.warpPerspective
cv2.warpAffine 接受2*3的变换矩阵
cv2.warpPerspective 接受3*3的变换矩阵
平移就是将对象换一个位置。如果你要沿（x，y）方向移动，
移动的距离 是（tx，ty），你可以以下面的方式构建移动矩阵：
M= [1 0 tx]
[0 1 ty]
使用 Numpy 数组构建这个矩阵（数据类型是 np.float32），
然 后把它传给函数 cv2.warpAffine()。
：函数 cv2.warpAffine() 的第三个参数的是输出图像的大小，
它的格式 应该是图像的（宽，... | null | Image Processing/Transformations/Translation.py | Translation.py | py | 925 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "cv2.warpAffine",
"line_... |
190937214 | import logging
import os
from django.conf import settings
from django.core.files.storage import get_storage_class
from django.db import models
from django.utils.timezone import now
from django.utils.functional import cached_property
from django import template
register = template.Library()
User = settings.AUTH_USER_MO... | null | codalab/apps/teams/models.py | models.py | py | 7,651 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.template.Library",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "django.template",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "django.conf.settings.AUTH_USER_MODEL",
"line_number": 11,
"usage_type": "attribute"
},
{
... |
494315738 | import json
from django.http import HttpResponseRedirect
from django.http import HttpResponse
from django.shortcuts import get_object_or_404
from django.urls import reverse
from django.contrib import messages
from django.views import View
from django.views.generic import FormView
from django.views.generic import ListV... | null | Library/views.py | views.py | py | 10,427 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.views.View",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "json.loads",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "django.http.HttpResponse",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "json.dumps",
... |
140384265 | import numpy as np
import os
import matplotlib.pyplot as plt
from scipy import stats
from scipy import optimize
import LAMMPSTool as LT
def Proportional(xData, m,c):
return m*xData+c
def IncreasingOnly(inArray, inTimes):
arrMax = 0
lstValues = []
lstTimes = []
for i in range(len(inArray)):
... | null | ActivationEnergyPlot.py | ActivationEnergyPlot.py | py | 5,228 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "numpy.array",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_numbe... |
445635864 | import pandas as pd
import xlsxwriter
from matplotlib import pyplot as plt
from scipy.stats import probplot, shapiro, ttest_ind
import seaborn as sns
import statsmodels.api as sm
from statsmodels.formula.api import ols
from scipy.stats import f_oneway
import sys
from PyQt5 import QtWidgets
from PyQt5.QtWidg... | null | report.py | report.py | py | 7,118 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "PyQt5.QtWidgets.QDialog",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "PyQt5.uic.loadUi",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QFileDialog.getOpenFileName",
"line_number": 23,
"usage_type": "call"
},
{
... |
157515461 | """
simple sample to start/stop EC2 instance
"""
import os, botocore
import config as cfg
from boto3 import client
from flask import Flask, render_template, redirect
# create EC2 service client
client = client('ec2',
aws_access_key_id = cfg.AWS_ACCESS_ID,
aws_secret_access_key=cfg.AWS... | null | py-ec2.py | py-ec2.py | py | 1,539 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "boto3.client",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "config.AWS_ACCESS_ID",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "config.AWS_ACCESS_KEY",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "con... |
455080678 | from typing import Deque
from collections import deque
# Definition for a binary tree node.
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def sum(self, root: TreeNode) -> int:
_sum: int = 0
if not root:
... | null | leetcode_563/solution.py | solution.py | py | 1,113 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "typing.Deque",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "collections.deque",
"line_number": 18,
"usage_type": "call"
}
] |
464302176 | from estruturas.Ponto import Ponto
from estruturas.Vizinhanca import Vizinhanca
from estruturas.Local import Local
from estruturas.CasoInfeccao import CasoInfeccao
from estruturas.Controle import Controle
from estruturas.TipoTrajeto import TipoTrajeto
from estruturas.ControlePonto import ControlePonto
from estruturas.R... | null | banco/ConsultasBanco.py | ConsultasBanco.py | py | 14,126 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "psycopg2.connect",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "psycopg2.extras",
"line_number": 71,
"usage_type": "attribute"
},
{
"api_name": "estruturas.Ponto.Ponto",
"line_number": 101,
"usage_type": "call"
},
{
"api_name": "estrutu... |
85836329 | import argparse
import os
import glob
import shutil
import random
def die(string):
print(string)
exit(1)
class Options:
def __init__(self):
self.initialized=False
def initialize(self,parser):
parser.add_argument("--input_data_folder", type=str, required=True, help="ex)./data/original"... | null | divide_into_trainvaltest.py | divide_into_trainvaltest.py | py | 5,234 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentDefaultsHelpFormatter",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "os.mkdir",
"line_number": 67,
"usage_type": "call"
},
{
"api_... |
45757234 | #!/usr/bin/python
# -*- coding: latin-1 -*-
'''
This libraries contained the graphical functions useful for the CRN analysis
'''
import sys, os # Standard library
import matplotlib as mpl
mpl.use('Agg')
import numpy as np
import random as ran
from matplotlib import rc
import matplotlib.mlab as mlab
import matplotlib.... | null | _analysis/pythonTools/lib/visual/graphics.py | graphics.py | py | 7,765 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "matplotlib.use",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.rc",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplo... |
391804949 | """This module contains the termite tracking functionalities."""
import sys
import random
import cv2
import data
class Termite:
"""Termite under study abstraction."""
def __init__(self, identity, starting_point, box_size=20):
"""Initializer.
Args:
identity (int): termite identit... | null | trackingtermites/tracking.py | tracking.py | py | 5,996 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "random.randint",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "data.DataHandler",
"line_number": 62,
"usage_type": "call"
},
{
"api_name": "cv2.VideoCapture",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line... |
605903009 | # coding:utf-8
import tornado.testing
import tornado.web
import motor.motor_tornado
from app import *
import os
class TestSample(tornado.testing.AsyncHTTPTestCase):
def setUp(self):
super(TestSample,self).setUp()
def get_app(self):
db = motor.motor_tornado.MotorClient().prototest_db
return tornado.web.Ap... | null | test_app.py | test_app.py | py | 2,046 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tornado.testing.testing",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "tornado.testing",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "motor.motor_tornado.motor_tornado.MotorClient",
"line_number": 15,
"usage_type": "call"
},... |
400394739 | import pytest
import random
import numpy as np
from kaggle_environments import make
from hungry_geese.agents import QValueAgent, QValueSafeAgent, QValueSafeMultiAgent
from hungry_geese.utils import ACTIONS, opposite_action
from hungry_geese.model import N_ACTIONS
random.seed(7)
np.random.seed(7)
class FakeModelUnifo... | null | tests/agents/test_q_value.py | test_q_value.py | py | 4,658 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "random.seed",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.random.seed",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "numpy.ones",
"lin... |
103693657 | from html import escape
from aiogram import Dispatcher
from telethon.tl.types import Channel
from telethon.errors import ChannelPrivateError, RPCError
from database import Database
from broadcaster import Broadcaster
from globals import client, bot, DIR_PATH
from filters import *
from utils import get_entity, answer, ... | null | handlers.py | handlers.py | py | 7,626 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "aiogram.Dispatcher",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "globals.bot",
"line_number": 13,
"usage_type": "argument"
},
{
"api_name": "database.Database",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "globals.DIR_PATH... |
494403573 | from flask import Flask
from database import db
from sqlalchemy_utils import create_database, database_exists
from routes.routes import blue_print
from flask_jwt_extended import JWTManager, jwt_manager
import datetime
import os
app = Flask(__name__)
#Valriables SQL
db_usuario = os.environ.get('DB_USUARIO')
db_clave =... | null | app/app.py | app.py | py | 1,051 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.environ.get",
"line_... |
576647085 | """mypoll URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.10/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-bas... | null | poll/urls.py | urls.py | py | 2,301 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.conf.urls.url",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "poll.views.IndexView",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "poll.views",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "django.conf... |
49190242 | #! coding: utf-8
from django import template
register = template.Library()
#http://stackoverflow.com/questions/4356329/creating-a-python-dictionary-from-a-line-of-text/4356415#4356415
def pairwise(iterable):
#s -> (s0,s1), (s2,s3), (s4, s5), ...
a = iter(iterable)
return zip(a, a)
@register.inclusion_t... | null | breadcrumbs/templatetags/breadcrumb_tags.py | breadcrumb_tags.py | py | 4,110 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "django.template.Library",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "django.template",
"line_number": 4,
"usage_type": "name"
}
] |
154625776 | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... | null | Keras_tensorflow_nightly/source2.7/tensorflow/contrib/framework/python/framework/checkpoint_utils.py | checkpoint_utils.py | py | 11,621 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tensorflow.python.platform.gfile.IsDirectory",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "tensorflow.python.platform.gfile",
"line_number": 42,
"usage_type": "name"
},
{
"api_name": "tensorflow.python.training.saver.latest_checkpoint",
"line_numb... |
184021691 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 5 23:49:45 2019
@author: MAGESHWARAN
"""
import pandas as pd
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
iris = pd.read_csv("Iris.data.csv", sep =... | null | My_algorithms/k_nearest_neighbors/k_nearest_neighbors_scikit.py | k_nearest_neighbors_scikit.py | py | 949 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_... |
456765730 | import json
import os
import numpy
import paramiko
deployment_output = json.load(open("deployment_output.json"))
copy_done_vm = {}
key_path = "/home/violetadmin1/.ssh/id_rsa"
copy_file = "jar/"
fog_to_privateip = {}
privateip_to_fog = {}
edgeip_to_vm = {}
fogno_to_globalpublicip ={}
vm_copy_status = {}
for key in ... | null | deployment/custom/copy_to_edge.py | copy_to_edge.py | py | 1,845 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "json.load",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "paramiko.RSAKey.from_private_key_file",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "paramiko.RSAKey",
"line_number": 48,
"usage_type": "attribute"
},
{
"api_name": "p... |
2083959 | from common.lib.servers.Pulser2.pulse_sequences.pulse_sequence import pulse_sequence
from sub_sequences.DopplerCooling import doppler_cooling
from sub_sequences.ProbeLaser import probe_laser
from sub_sequences.PhotonTimeTags import photon_timetags
from labrad.units import WithUnit
class probe_line_scan(pulse_sequenc... | null | lib/scripts/pulse_sequences/ProbeLineScan.py | ProbeLineScan.py | py | 1,027 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "common.lib.servers.Pulser2.pulse_sequences.pulse_sequence.pulse_sequence",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "sub_sequences.DopplerCooling.doppler_cooling.all_required_parameters",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sub_... |
68078092 | import cv2
from .abstract_image import AbstractImage
from flax_baseline.common.flax_log import flax_log
from flax_baseline.common.flax_debug import flax_debug
# from flax_baseline.common.flax_config import flax_config
from flax_baseline.components.factory.denoise_factory import DenoiseFactory
from flax_baseline.compone... | null | flax_baseline/components/img_process/base/base_image.py | base_image.py | py | 3,709 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "abstract_image.AbstractImage",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "flax_baseline.common.flax_log.flax_log",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "flax_baseline.common.flax_debug.flax_debug",
"line_number": 29,
"usag... |
219721255 | import boto3
import os
import cv2
import time
def grabar():#splitvideo2
video = cv2.VideoCapture(0)
nframes = 0
hora_inicio = time.time()
print(hora_inicio)
try:
if not os.path.exists('data'):
os.makedirs('data')
except OSError:
print('Error: Creati... | null | Proyect/combination.py | combination.py | py | 2,682 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number":... |
612740918 | #!/usr/bin/env python3
# Report Tool to quesy news database and present it in a text
import psycopg2
DBNAME = "news"
def get_most_popular_articles():
"""Return most popular articles from the 'database', most viewed first."""
db = psycopg2.connect(database=DBNAME)
c = db.cursor()
c.execute("SELECT ar... | null | report.py | report.py | py | 2,068 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "psycopg2.connect",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "psycopg2.connect",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "psycopg2.connect",
"line_number": 35,
"usage_type": "call"
}
] |
323292539 | import os
import numpy as np
import pandas as pd
from sklearn.tree import DecisionTreeRegressor
from sklearn.metrics import mean_squared_error
import base_methods as base
def decision_tree():
prefix = 'Data/'
# ------------------------------- Learning ------------------------------- #
# Load training dat... | null | Models/dt.py | dt.py | py | 1,169 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "pandas.read_csv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "base_methods.load_from_csv",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
... |
636402898 | # -*- coding: utf-8 -*-
"""
Created on Sat Nov 21 17:21:44 2020
@author: lenovoz
"""
import pickle
import socket
import struct
import cv2
HOST = '192.168.1.63'
PORT = 8089
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print('Socket created')
s.bind((HOST, PORT))
print('Socket bind comp... | null | VideoSend/ServerVideo.py | ServerVideo.py | py | 1,236 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "socket.socket",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "socket.AF_INET",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "socket.SOCK_STREAM",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "struct.calc... |
452540884 | #!/usr/bin/python3
import cgi
import subprocess
print("content-type: text/html")
print()
mydata = cgi.FieldStorage()
imagename = mydata.getvalue("x")
cmd = "sudo docker rm -f {}".format(imagename)
output = subprocess.getoutput(cmd)
print(output)
| null | removeContainer.py | removeContainer.py | py | 253 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "cgi.FieldStorage",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "subprocess.getoutput",
"line_number": 15,
"usage_type": "call"
}
] |
418762418 | import os
import re
import tempfile
from abc import ABC
from typing import Dict, Text
import boto3
import tensorflow as tf
import tensorflow_io as tfio
import tensorflow_recommenders as tfrs
import urllib3
from recommender_system.recsys_core.recsys_utils import print_with_date
# from tqdm.keras import TqdmCallback
... | null | recsys_tfrs_model.py | recsys_tfrs_model.py | py | 12,527 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "tensorflow.distribute.MultiWorkerMirroredStrategy",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "tensorflow.distribute",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "tensorflow_recommenders.Model",
"line_number": 31,
"usage_ty... |
172657702 | import json
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import SGDClassifier
f=open('training.json', 'r')
N=int(f.readline())
i=0
train_ans=[]
train=[]
topic_list=[]
for line in f:
j = json.loads(line)
topic = (j['topic'])
if topic in topic_list:
topicN = t... | null | Stack Exchange Question Classifier.py | Stack Exchange Question Classifier.py | py | 1,006 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "json.loads",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_extraction.text.TfidfVectorizer",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": ... |
85459612 | """
Adversarial Attacks in Pytorch
Written by Harry Kim
Licensed under the MIT License
WARNING :: All images should be scaled to [0, 1] with transform[to.Tensor()] before used in attacks.
WARNING :: All models should return ONLY ONE vector of `(N, C)` where `C = number of classes`.
"""
import torch
import torch.nn ... | null | torchattacks/torchattacks.py | torchattacks.py | py | 14,359 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "torch.device",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "torch.max",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "torch.uint8",
"line_number": 64,
"usage_type": "attribute"
},
{
"api_name": "torch.cat",
"line_number"... |
31838145 | #This sets up the entire application, which reads the default configuration and initialize the UI
#Last updated on 04/15/2019 by Y. Xiang
#This code is written in Python 3.6.6 64-bit
from PyQt5 import QtGui, QtWidgets, QtCore
import broadening
import gmm
import configparser
import generate_report
import graph_3D_surfac... | null | source/main.py | main.py | py | 7,333 | python | en | code | null | code-starcoder2 | 66 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QApplication",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets",
"line_number": 25,
"usage_type": "name"
},
{
"api_name":... |
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