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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
41902703943 | import cv2
import numpy as np
img = cv2.imread('water_coins.jpg')
gr_img = cv2.cvtColor(img , cv2.COLOR_BGR2GRAY)
_ , thresh = cv2.threshold(gr_img , 0 , 255 , cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
#noise removal
kernel = np.ones((3 , 3) , np.uint8)
opening = cv2.morphologyEx(thresh , cv2.MORPH_OPEN , ker... | kumar6rishabh/counting_objects | counting_objects.py | counting_objects.py | py | 1,148 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.imread",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "cv2.threshold",
"lin... |
6753837772 | import numpy as np
from scipy import signal
# input:
# data(type:numpy array)(shape:time * 2)
# model(sklearn model or pytorch model)
# flatten(type: bool)(whether to flatten the input as 200 or use 100*2 as the model input)
# output:
# probanility_map(number of split, 12)
def stroke_probability_map(data, model, fl... | yzhao07/MLMA_EOG | Continuous CNN/stroke probability map/stroke_probability_map.py | stroke_probability_map.py | py | 881 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.zeros",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.sum",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.floor",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "scipy.signal.resample",
"line_n... |
10538619256 | from collections import deque
노드개수, 간선개수 = map(int, input().split())
result = 0
# 빈 그래프 그리기
graph = [ [] for i in range(노드개수+1) ]
for i in range(간선개수):
a, b = map(int, input().split())
graph[a].append(b)
graph[b].append(a)
visited = [False] * (노드개수 + 1)
def 너비우선탐색(graph, start, visited):
queue = deq... | 5pponent/opponent | dfs&bfs/연결 요소의 개수.py | 연결 요소의 개수.py | py | 768 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.deque",
"line_number": 16,
"usage_type": "call"
}
] |
5747062131 | from setuptools import setup
with open('README.md', 'r', encoding='utf-8') as f:
readme = f.read()
setup(
name='gearbest_api',
version='0.0.4',
description='Retrieve info from gearbest api.',
long_description=readme,
long_description_content_type='text/markdown',
url='https://github.com/ma... | matteobaldelli/python-gearbest-api | setup.py | setup.py | py | 716 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "setuptools.setup",
"line_number": 6,
"usage_type": "call"
}
] |
29767005499 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('qsource_user', '0005_auto_20151118_2237'),
]
operations = [
migrations.CreateModel(
name='QuestionsAnswered',
... | SamuelWenninger/QSource-app | qsource_user/migrations/0006_questionsanswered_questionsasked.py | 0006_questionsanswered_questionsasked.py | py | 971 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 14,
"usage_type": "call"
},
... |
35319730396 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Author: mcxiaoke
# @Date: 2016-01-04 11:18:06
import codecs
import os
import sys
import requests
import shutil
import time
HEADERS = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/46.0.1234.0 Safari/537.36',
'Refe... | mcxiaoke/python-labs | instagram/utils.py | utils.py | py | 2,838 | python | en | code | 7 | github-code | 36 | [
{
"api_name": "codecs.open",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 40,
"usage_type": "attribute"
},
{
"api_name": "codecs.open",
"line_numbe... |
40451981469 | """seed event types
Revision ID: 0311eb0fc2e6
Revises: 61043123657a
Create Date: 2021-02-04 14:27:03.847005
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.sql import table, column
from sqlalchemy import String, Integer, Boolean
# revision identifiers, used by Alembic.
revision = '0311eb0fc2e6'
do... | jcsumlin/secret-santa-discord-bot | alembic/versions/0311eb0fc2e6_seed_event_types.py | 0311eb0fc2e6_seed_event_types.py | py | 1,160 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sqlalchemy.sql.table",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.sql.column",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.Integer",
"line_number": 22,
"usage_type": "argument"
},
{
"api_name": "sql... |
70631838504 | import pandas as pd
import numpy as np
import string, re
import nltk
import time,random
import operator
#from tabulate import tabulate
from nltk.stem.snowball import SnowballStemmer
import os.path
stop_list = nltk.corpus.stopwords.words('english')
lemmatizer = nltk.stem.WordNetLemmatizer()
punctuation = list(string.p... | zaksoliman/twitter-sentiment-analysis | tweet_analysis/classifiers/process_chars.py | process_chars.py | py | 2,719 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "nltk.corpus",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "nltk.stem.WordNetLemmatizer",
"line_number": 13,
"usage_type": "call"
},
{
"api_name... |
74752031784 | import os
import requests
from requests.exceptions import ReadTimeout
from requests_oauthlib import OAuth1
from helpers.configHelpers import decryptEnvVar
from helpers.logHelpers import createLog
from helpers.errorHelpers import URLFetchError
logger = createLog('hathiCover')
class HathiCover():
"""Manager class ... | NYPL/sfr-ingest-pipeline | lambda/sfr-hathi-reader/lib/hathiCover.py | hathiCover.py | py | 5,653 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "helpers.logHelpers.createLog",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "helpers.c... |
25240483381 | import datetime
import json
import time
import numpy as np
from common.args import Runtime
from data.premetheus import DataManger
cpu_data_range = {}
def cpu_data_pretreatment():
y = datetime.datetime.now().year
m = datetime.datetime.now().month
d = datetime.datetime.now().day
dt = str(y) + '-' + st... | falcomlife/klog-ai | src/core/data/pretreatment.py | pretreatment.py | py | 2,476 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.now",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime.now",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "da... |
32352030938 | import logging
import glob
import collections
import os
import clang.cindex
from clang.cindex import CursorKind
from . import helpers
from . import enum_decl
from . import class_struct_decl
from . import function_decl
_LOGGER = logging.getLogger(__name__)
def _detect_library_file():
version = os.getenv("PYCODE... | blejdfist/pycodegen | pycodegen/frontend/frontend_cpp/parser_libclang.py | parser_libclang.py | py | 3,854 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "glob.glob",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"l... |
9815611814 | # author：Nicolo
# time：2017/7/23
# function:生成汉字字库并转换为图片
import codecs
import os
import pygame
start,end = (0x4E00, 0x9FA5)
with codecs.open("chinese.txt", "wb", encoding="utf-8") as f:
for codepoint in range(int(start),int(end)):
f.write(chr(codepoint))
chinese_dir = 'chinese'
if not os.path.... | X-Nicolo/ChineseToImg | wordToImg.py | wordToImg.py | py | 824 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "codecs.open",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "os.mkdir",
"line_number": ... |
19354601917 | from __future__ import (absolute_import, print_function,
unicode_literals, division)
import time
import numpy as np
import pandas as pd
import requests
from bokeh import plotting
from bokeh.objects import ColumnDataSource
class QlogPlot:
def __init__(self, base, name, limit, ds):
self.nam... | jordens/qlog | qlog/plot.py | plot.py | py | 2,229 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "bokeh.plotting.line",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "bokeh.plotting",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "bokeh.plotting.circle... |
274283973 | import os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def boxplot(df, output_folder):
#simple version, only makes the 4 boxplots every dataset has in common
fig, (ax1, ax2, ax3, ax4) = plt.subplots(1, 4)
#fig.suptitle('Air Beam', fontsize=20)
dat = [df['Temperature'].dropna(... | bglowniak/Air-Quality-Analysis | src/main/python/vis_utils.py | vis_utils.py | py | 4,065 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "os.path.join... |
73156319784 | from flask import Flask,render_template,request,make_response
app=Flask(__name__)
@app.route('/')
def input():
return render_template('page2.html')
@app.route('/page3',methods=['POST','GET'])
def page3():
a=request.form.get('nos1',type=int)
b=request.form.get('nos2',type=int)
result=a+b
resp=make_... | adityatyagi1998/Flask-Calci | calculator.py | calculator.py | py | 722 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "flask.render_template",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "flask.request.form.get",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "flask.request.... |
74032441703 | import os
import json
import time
import numpy as np
from .FCNN_FA import FCNN_FA
class FCNN_KP(FCNN_FA):
'''
Description: Class to define a Fully Connected Neural Network (FCNN)
with the Kolen-Pollack (KP) algorithm as learning algorithm
'''
def __init__(self, sizes... | makrout/Deep-Learning-without-Weight-Transport | fcnn/FCNN_KP.py | FCNN_KP.py | py | 4,665 | python | en | code | 31 | github-code | 36 | [
{
"api_name": "FCNN_FA.FCNN_FA",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "time.time",
"line_number": 53,
"usage_type": "call"
},
{
"api_name": "numpy.mean",
"line_number": 74,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 77... |
25743739281 | __all__ = [
"EBCOTCodec"
]
from copy import deepcopy
from multiprocessing import Pool
import numpy as np
from fpeg.base import Codec
from fpeg.config import read_config
from fpeg.funcs import parse_marker, cat_arrays_2d
config = read_config()
D = config.get("jpeg2000", "D")
G = config.get("jpeg2000", "G")
QCD = co... | yetiansh/fpeg | fpeg/codec/EBCOT_codec.py | EBCOT_codec.py | py | 31,395 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "fpeg.config.read_config",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "fpeg.base.Codec",
"line_number": 24,
"usage_type": "name"
},
{
"api_name": "fpeg.funcs.parse_marker",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "multi... |
25066192842 | import torch
import torch.nn
import os,csv,datetime
import numpy as np
from cnn_structure import CNN
from torch.autograd import Variable
from sklearn.metrics import confusion_matrix
# MODEL_FOLDER = './model/'
MODEL_FOLDER = './'
DATA_FOLDER = './k1000_vec200/'
EMOTION = {'ne':0, 'ha':1, 'sa':2, 'an':3, 'di':4, 'su':5... | 1021546/test_pytorch | 學長 pytorch/2dCNNpredict/model_predict.py | model_predict.py | py | 2,030 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.listdir",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"... |
1488036241 | import os
import re
import json
import glob
import tempfile
import argparse
import ast
import pandas as pd
import sys
import shipyard_utils as shipyard
from google.cloud import bigquery
from google.oauth2 import service_account
from google.api_core.exceptions import NotFound
EXIT_CODE_UNKNOWN_ERROR = 3
EXIT_CODE_INVA... | shipyardapp/googlebigquery-blueprints | googlebigquery_blueprints/upload_file.py | upload_file.py | py | 9,540 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 82,
"usage_type": "call"
},
{
"api_name": "tempfile.mkstemp",
"line_number": 83,
"usage_type": "call"
},
{
"api_name": "os.fdopen",
"... |
73260920425 | import pymongo
cliente = pymongo.MongoClient("mongodb://localhost:27017/")
database = cliente["bancoDados"]
pessoas = database["pessoas"]
pessoa1 = {"nome":"Gustavo","peso": 58}
insert = pessoas.insert_one(pessoa1)
print(insert.inserted_id)
listaDBs = cliente.list_database_names()
print(listaDBs)
listaCollections = ... | Gustavo-Baumann/AprendendoSintaxePython | phyton/mongoDB/test.py | test.py | py | 376 | python | pt | code | 0 | github-code | 36 | [
{
"api_name": "pymongo.MongoClient",
"line_number": 3,
"usage_type": "call"
}
] |
6405350957 | """This module contains necessary function needed"""
# Import necessary modules
from imblearn.over_sampling import SMOTE, ADASYN
from imblearn.under_sampling import RandomUnderSampler, NearMiss
import numpy as np
import pandas as pd
import streamlit as st
import math
from sklearn.model_selection import cross_validate... | tobintobin16/Streamlit_CS498 | Parkinsons-Detector/web_functions.py | web_functions.py | py | 3,070 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "streamlit.cache_data",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "sklearn.model_selection.cross_validate",
"line_number": 38,
"usage_type": "call"
},
{
"... |
24629581794 | from Crypto.PublicKey import RSA
from django.contrib.auth.models import User
from rest_framework import serializers
from app.models import *
import uuid
class UserRelationField(serializers.RelatedField):
def to_representation(self, value):
return '{}'.format(value.user.username)
class AllOthersRelationFi... | bobbykemp/cryptoapp | cryptoapp/serializers.py | serializers.py | py | 4,528 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "rest_framework.serializers.RelatedField",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "rest_framework.serializers.PrimaryKeyRelatedField",
"line_number": 28,
... |
11504595660 | import numpy as np
import theano
import theano.tensor as T
from collections import OrderedDict
def simulate_dynamics(initial_pos, initial_vel, stepsize, n_steps, energy_fn):
"""
Return final (position, velocity) obtained after an `n_steps` leapfrog
updates, using Hamiltonian dynamics.
Parameters
-... | rueberger/MJHMC | mjhmc/fast/hmc.py | hmc.py | py | 14,473 | python | en | code | 24 | github-code | 36 | [
{
"api_name": "theano.tensor.grad",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "theano.tensor",
"line_number": 57,
"usage_type": "name"
},
{
"api_name": "theano.tensor.grad",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "theano.tensor",
... |
17457985140 | """
Tests for specific issues and pull requests
"""
import os
import tempfile
import difflib
from textwrap import dedent
import gffutils
from gffutils import feature
from gffutils import merge_criteria as mc
from nose.tools import assert_raises
def test_issue_79():
gtf = gffutils.example_filename("keep-order-te... | hpatterton/gffutils | gffutils/test/test_issues.py | test_issues.py | py | 13,843 | python | en | code | null | github-code | 36 | [
{
"api_name": "gffutils.example_filename",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "gffutils.create_db",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "difflib.ndiff",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "gffutils.f... |
17455031519 | #!/usr/bin/env python
#
# Author: Greg Hellings - <ghelling@redhat.com> or <greg.hellings@gmail.com>
#
# Module to configure users in Jenkins authorized to use CLI
import xml.etree.ElementTree as ET
import os
from ansible.module_utils.basic import AnsibleModule
DOCUMENTATION = """
---
version_added: "2.1"
module: jen... | devroles/ansible_collection_system | plugins/modules/jenkins_cli_user.py | jenkins_cli_user.py | py | 3,843 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 44,
"usage_type": "attribute"
},
{
"api_name": "xml.etree.ElementTree.parse",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "xml.etree.Eleme... |
23614214391 | import wqpy.read
import aiohttp
import asyncio
import io
async def _basic_aquery(service_url, service_params):
async with aiohttp.ClientSession() as session:
async with session.get(service_url, params = service_params) as r:
return(await r.text())
def multi_query(service_url, service_param_list, parse = T... | mkoohafkan/wqpy-clone | wqpy/aquery.py | aquery.py | py | 675 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "aiohttp.ClientSession",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "asyncio.get_event_loop",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "asyncio.gather",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "wqpy.read.... |
37749884465 | from elegy.module import Module
import typing as tp
import haiku as hk
import jax.numpy as jnp
import numpy as np
from elegy import types
def _infer_shape(output_shape, dimensions):
"""
Replaces the -1 wildcard in the output shape vector.
This function infers the correct output shape given the input d... | anvelezec/elegy | elegy/nn/flatten.py | flatten.py | py | 4,093 | python | en | code | null | github-code | 36 | [
{
"api_name": "numpy.prod",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.prod",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "elegy.module.Module",
"line_num... |
8445132228 | import numpy as _numpy
import cupy as _cupy
from cupy_backends.cuda.libs import cublas as _cublas
from cupy.cuda import device as _device
def gesv(a, b):
"""Solve a linear matrix equation using cusolverDn<t>getr[fs]().
Computes the solution to a system of linear equation ``ax = b``.
Args:
a (cu... | cupy/cupy | cupyx/lapack.py | lapack.py | py | 12,437 | python | en | code | 7,341 | github-code | 36 | [
{
"api_name": "cupy_backends.cuda.libs.cusolver",
"line_number": 48,
"usage_type": "argument"
},
{
"api_name": "cupy_backends.cuda.libs.cusolver",
"line_number": 49,
"usage_type": "argument"
},
{
"api_name": "cupy_backends.cuda.libs.cusolver",
"line_number": 50,
"usage_ty... |
74050641704 | from typing import Any, Dict, List, Optional, Union
from parlai.agents.rag.retrieve_api import (
SearchEngineRetriever,
SearchEngineRetrieverMock,
)
from parlai.agents.rag.retrievers import Document
from parlai.core.agents import Agent
from parlai.core.opt import Opt
from parlai.core.params import ParlaiParser... | facebookresearch/ParlAI | projects/bb3/agents/search_agent.py | search_agent.py | py | 3,676 | python | en | code | 10,365 | github-code | 36 | [
{
"api_name": "parlai.core.agents.Agent",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "parlai.core.params.ParlaiParser",
"line_number": 23,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 23,
"usage_type": "name"
},
{
"api_name... |
70050076903 | """
Simple runner that can parse template and run all Sources to write in the Sinks
"""
import sys
from typing import Optional
from pipereport.base.templateregistry import BaseTemplateRegistry
from pipereport.template.template import Template
from pipereport.template.registry import GitFSTemplateRegistry
class Pip... | enchantner/pipereport | pipereport/runner/runner.py | runner.py | py | 2,078 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.Optional",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "pipereport.base.templateregistry.BaseTemplateRegistry",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "pipereport.template.registry.GitFSTemplateRegistry",
"line_number": 22,... |
22778778238 | #!/usr/bin/python
# encoding: utf-8
import random
import six
import numpy as np
from skimage.transform import resize as imresize
import chainer
import os
import skimage.io as skio
class resizeNormalize(object):
def __init__(self, size):
self.size = size
def __call__(self, img):
# image shap... | Swall0w/chainer-crnn | dataset.py | dataset.py | py | 2,600 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "numpy.newaxis",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "numpy.transpose",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "skimage.transform.resize",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "numpy.flo... |
12485964052 | from pathlib import Path
import numpy as np
import pandas as pd
ROOT_DIRECTORY = Path("/code_execution")
DATA_DIRECTORY = Path("/data")
OUTPUT_FILE = ROOT_DIRECTORY / "submission" / "subset_matches.csv"
def generate_matches(query_video_ids) -> pd.DataFrame:
raise NotImplementedError(
"This script is jus... | drivendataorg/meta-vsc-matching-runtime | submission_src/main.py | main.py | py | 786 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "pandas.read_csv",
"... |
8880207451 | import math
from typing import Callable
import numpy as np
from nm.typing import NDArrayOrFloat
def relative_error(
curr_approx: NDArrayOrFloat, prev_approx: NDArrayOrFloat
) -> NDArrayOrFloat:
"""Given current and previous iteration/approximation value returns the
relative error (does not return percen... | abzrg/nmpy | nm/error.py | error.py | py | 2,102 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "nm.typing.NDArrayOrFloat",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "nm.typing.NDArrayOrFloat",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "nm.... |
4204565119 | import argparse
import itertools
import random
import sys
import gym
import numpy as np
from gym.wrappers import TimeLimit
from tqdm import trange
import sen.envs
from sen.agents import LimitActionsRandomAgent, RandomAgent
from sen.envs.block_pushing import render_cubes, rot90_action
from sen.utils import save_h5
d... | jypark0/sen | sen/data/gen_cubes.py | gen_cubes.py | py | 3,917 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "sen.envs.block_pushing.render_cubes",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "gym.logger.set_level",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "gym.logger",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name... |
71513904425 | from flask import request, jsonify
from os.path import isfile
from sklearn import svm
import pickle
MODEL_FILE = 'model.p'
class Model(object):
__model_loaded = False
def __init__(self):
self.__model = svm.SVC()
if isfile(MODEL_FILE):
self.__load_model()
def __load... | ColinShaw/python-sklearn-flask-deployment-example | src/model.py | model.py | py | 1,593 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sklearn.svm.SVC",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sklearn.svm",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "os.path.isfile",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_nu... |
75311890665 | import json
import os
import shutil
import torch
from efficientnet_pytorch import EfficientNet
from tensorboardX import SummaryWriter
from torch.nn import CrossEntropyLoss
from torch.optim.lr_scheduler import ExponentialLR, CosineAnnealingLR
from torch.utils.data import DataLoader
from torchsummary import summary
from... | Danil328/ID_RND_V2 | src/shuffleMetrics.py | shuffleMetrics.py | py | 3,370 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "json.load",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.device",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line... |
38190199809 | #!/usr/bin/python
import sys
import logging
from rdsConfig import getDbConfig
import json
import config
from responseIO import returnResponse, errString
from keyCheck import verifyPublisher, verifyUsers
import datetime
from modules.post import post
from dbCommons import createModuleIssue
## Creating a lamb... | misternaks/allmoduleissues | allModuleIssues.py | allModuleIssues.py | py | 2,027 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "config.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "rdsConfig.getDbConfig",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "responseIO.returnResponse",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "json... |
13076725712 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import os
# directory where the FWHM file is located
directory = '//fs03/LTH_Neutimag/hkromer/02_Simulations/06_COMSOL/\
03_BeamOptics/01_OldTarget/IGUN_geometry/2018-09-18_comsolGeometry/\
02.define_release_time/particle... | kromerh/phd_python | 03_COMSOL/03_BeamOptics/01_particlePosition/2018-09-28_compareFWHMs_oldTarget.py | 2018-09-28_compareFWHMs_oldTarget.py | py | 1,802 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "matplotl... |
14836136357 | import torch.multiprocessing as mp
from torch.nn.parallel import DistributedDataParallel as DDP
from utils.Manager import Manager
from models.XFormer import XFormer
def main(rank, manager):
""" train/dev/test/tune the model (in distributed)
Args:
rank: current process id
world_size: total gpu... | tyh666/News-Recommendation-MIND | xformer.py | xformer.py | py | 1,123 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "models.XFormer.XFormer",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "torch.nn.parallel.DistributedDataParallel",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "utils.Manager.Manager",
"line_number": 36,
"usage_type": "call"
},
{... |
7731571907 | # Pickhacks 2023
# Safer Caver
# This is inspired by https://github.com/UP-RS-ESP/PointCloudWorkshop-May2022/blob/main/2_Alignment/ICP_Registration_ALS_UAV.ipynb
import copy
from pathlib import Path
import numpy as np
import open3d as o3d
import laspy
import distinctipy as colorpy
from scipy.spatial import cKDTree... | cubrink/pickhacks-2023 | safercaver/src/aligner.py | aligner.py | py | 8,767 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "open3d.visualization.draw_geometries",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "open3d.visualization",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "distinctipy.get_colors",
"line_number": 25,
"usage_type": "call"
},
{
... |
21325729011 | import csv
from elasticsearch import Elasticsearch
from elasticsearch import helpers
es = Elasticsearch([{'host': 'localhost', 'port': 9200}])
#es.indices.delete(index='movies', ignore=[400, 404])
print(es.ping())
def convert(filename,indexname,type):
with open(filename, encoding="utf8") as file:
... | gdimitropoulos/information-retrieval | part1b/reader.py | reader.py | py | 1,044 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "csv.DictReader",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "elasticsearch.helpers.bulk",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "... |
1941680628 | # SHOW CARD LIST
#
import os
import re
import json
import sublime
import sublime_plugin
import subprocess
class UmbertoGetRecipCardLinkCommand(sublime_plugin.TextCommand, sublime_plugin.WindowCommand):
def run(self, edit):
settings = sublime.load_settings('Umberto.sublime-settings'... | tgparton/Umberto | get_recip_card_link.py | get_recip_card_link.py | py | 4,350 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sublime_plugin.TextCommand",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "sublime_plugin.WindowCommand",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "sublime.load_settings",
"line_number": 19,
"usage_type": "call"
},
... |
34358986297 | import SECRETS
import os
import openai
openai.organization = "org-0iQE6DR7AuGXyEw1kD4poyIg"
openai.api_key = SECRETS.open_ai_api_key
from sms.logger import json_logger
def send_init_roast_bot_primer_prompt():
completion = openai.Completion.create(
model = "text-davinci-003",
# prompt="Tell me a joke abo... | Brandon-Valley/tik_live_host | src/open_ai_api_handler.py | open_ai_api_handler.py | py | 1,813 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "openai.organization",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "openai.api_key",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "SECRETS.open_ai_api_key",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name":... |
5213207430 | from unittest import TestCase
from typing import List, Set, Tuple
"""
You are given a m x n 2D grid initialized with these three possible values.
-1 - A wall or an obstacle.
0 - A gate.
INF - Infinity means an empty room. We use the value 231 - 1 = 2147483647 to represent INF as you may assume that the
distance to a... | tugloo1/leetcode | problem_286.py | problem_286.py | py | 3,246 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.Tuple",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typing.Tuple",
"line_number": 43,
"usage_type": "name"
},
{
"api_name": "unittest.TestCase",
"line_n... |
71806898343 |
import pandas as pd
from splinter import Browser
from bs4 import BeautifulSoup as bs
from webdriver_manager.chrome import ChromeDriverManager
import time
def scrape():
# Latest Mars News
# Set up Splinter
executable_path = {'executable_path': ChromeDriverManager().install()}
browser = Browser('c... | NZeinali/Web_Scraping_Challenge | scrape_mars.py | scrape_mars.py | py | 2,652 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "webdriver_manager.chrome.ChromeDriverManager",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "splinter.Browser",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 20,
"usage_type": "call"
},
{
"api_name... |
10076939934 | from langchain.document_loaders import PyPDFLoader
from langchain.document_loaders.csv_loader import CSVLoader
from langchain.text_splitter import MarkdownHeaderTextSplitter,RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.l... | Utsav-ace/LLMGpt | src/mylib/upload.py | upload.py | py | 3,755 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "fastapi.UploadFile",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "os.getcwd",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line... |
14559612423 | #!/usr/bin/env python3
from time import time
from datetime import timedelta
import json
import decimal
import os
import sys
import traceback
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import logging
logging.getLogger("tensorflow").setLevel(logging.WARNING)
import tensorflow as tf
from recipes.baskt_rs_recipes import Ba... | Stepka/baskt-recommendation-system | prediction_flask_server.py | prediction_flask_server.py | py | 10,049 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logging.WARNING",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "flask.Flask",
... |
37360585045 | # 工具类函数
import colorsys
import functools
import glob
import json
import re
from loguru import logger
def parse_range(page_range: str, page_count: int, is_multi_range: bool = False, is_reverse: bool = False, is_unique: bool = True):
# e.g.: "1-3,5-6,7-10", "1,4-5", "3-N", "even", "odd"
page_range = page_range... | kevin2li/PDF-Guru | thirdparty/utils.py | utils.py | py | 7,425 | python | en | code | 941 | github-code | 36 | [
{
"api_name": "re.match",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 93,
"usage_type": "call"
},
{
"api_name": "colorsys.rgb_to_hsv",
"line_number": ... |
13183244334 | from math import sqrt
from itertools import product
import pandas as pd
import torch
from torch.autograd import Function
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
def make_vgg():
layers = []
in_channels = 3
cfg = [64, 64, 'M', 128, 128, 'M', 256, 256,
... | jsw6872/DataScience_ML-DL | DL/lecture/detection_segmentation/SSD/model.py | model.py | py | 17,905 | python | ko | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn.MaxPool2d",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "torch.nn.MaxPool2d",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_n... |
74698899304 | from fastapi import APIRouter
from db import db
from models import Wct
router = APIRouter()
@router.patch("/{syncId}/wct")
async def update_wct(syncId: int, wct: Wct):
await db.update_user_wct(syncId, wct)
return {
'status': 'OK'
}
| NIDILLIN/Kathrin | Microservices/Users(1406)/routers/patch.py | patch.py | py | 258 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "models.Wct",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "db.db.update_user_wct",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "db.db",
"line_n... |
12979955656 | import sys
from reward_abc import RewardFunctionAbc
# from skimage.measure import approximate_polygon, find_contours
# from skimage.draw import polygon_perimeter, line
from skimage.transform import hough_line, probabilistic_hough_line
# from skimage.transform import hough_line_peaks
import torch
from skimage.draw impor... | kreshuklab/rewardchecking | lines_reward.py | lines_reward.py | py | 9,442 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.tight_layout",
"line_number": 39,
"usage_type": "call"
},
{
"api_n... |
571034080 | ## BMO CHATBOT CLASS DEFINITION
# Author: Milk + Github Copilot (WOW!)
# Last modified: 2022-10-05
import random
from pathlib import Path
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
class BMO():
def __init__(self,debug=False):
#set debug mode
self.DEBUG = debug
... | MasterMilkX/BMO_chatbot_prototype | Python/bmo.py | bmo.py | py | 10,867 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "nltk.tokenize.word_tokenize",
"line_number": 229,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 230,
"usage_type": "call"
},
{
"api_name":... |
36947653909 | from __future__ import print_function
__revision__ = "src/engine/SCons/Tool/MSCommon/common.py bee7caf9defd6e108fc2998a2520ddb36a967691 2019-12-17 02:07:09 bdeegan"
import copy
import json
import os
import re
import subprocess
import sys
import SCons.Util
# SCONS_MSCOMMON_DEBUG is internal-use so undocumented:
# se... | mongodb/mongo | src/third_party/scons-3.1.2/scons-local-3.1.2/SCons/Tool/MSCommon/common.py | common.py | py | 9,322 | python | en | code | 24,670 | github-code | 36 | [
{
"api_name": "os.environ.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "logging.basicConfig",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
... |
73495508264 | from django.shortcuts import render, redirect
from django.http import HttpResponse, HttpResponseNotFound
from django.views import View
from django.conf import settings
import json
import itertools
import random
from datetime import datetime
JSON_DATA = settings.NEWS_JSON_PATH
def get_json_data():
with open(JSON_... | Vladpetr/NewsPortal | HyperNews Portal/task/news/views.py | views.py | py | 2,754 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.conf.settings.NEWS_JSON_PATH",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "json.load",
"line_number": 15,
"usage_type": "call"
},
{
"api_name"... |
31091913885 | from django.shortcuts import render
from parse.forms import ParseForm
from parse.tasks import task_parse
def ozon_parse(request):
if request.method == 'POST':
form = ParseForm(request.POST)
if form.is_valid():
id_user = form.cleaned_data.get('id_user')
api_key = form.clean... | jurawlew/ozon_parse | parse/views.py | views.py | py | 500 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "parse.forms.ParseForm",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "parse.tasks.task_parse.delay",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "parse.tasks.task_parse",
"line_number": 13,
"usage_type": "name"
},
{
"api_name... |
70806938343 | import sys
from collections import deque
sys.stdin = open('input.txt')
def bellmanford():
for n in range(N):
for i in range(N):
for weight, node in linked[i]:
if distance[i] != -1e10 and distance[node] < weight + distance[i]:
distance[node] = distance[i] + w... | unho-lee/TIL | CodeTest/Python/BaekJoon/1738.py | 1738.py | py | 888 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sys.stdin",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "sys.stdin.readline",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "sys.stdin.readline",
... |
20460415252 | import time
import matplotlib.pyplot as plt
import numpy as np
import numpy.random as rnd
import sorting.merge_sort as merge
import sorting.quick_sort as quick
MAX_SIZE = 1000
STEP = 1
NUM_ITERATIONS = 10
def timer(task):
start = time.clock()
task()
end = time.clock()
return end - start
def test_... | Apophany/coding-exercises | python/performance/perf_test.py | perf_test.py | py | 1,160 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "time.clock",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "time.clock",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.random.randint",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_n... |
74053950505 | from urllib.request import urlopen
from bs4 import BeautifulSoup
import ssl
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
url = input("Enter URL - ")
############################################### Comment this for first question ##############################
pos = in... | maleeha045/python-for-everybody | 3_using_python_to_access_web_data/scrapUrl.py | scrapUrl.py | py | 634 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "ssl.create_default_context",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "ssl.CERT_NONE",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "urllib.request.urlopen",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "bs... |
38985345142 | from functools import partial
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.datasets import fetch_openml
from sklearn.metrics import mean_tweedie_deviance
from sklearn.metrics import mean_absolute_error
from sklearn.metrics import mean_squared_error
def load_mtpl2(n_samples=100... | christopher-parrish/sas_viya | python/tweedie_regressor_python/pure_premium_python_example.py | pure_premium_python_example.py | py | 10,361 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "sklearn.datasets.fetch_openml",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "sklearn.datasets.fetch_openml",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics.mean_absolute_error",
"line_number": 112,
"usage_type": "name... |
11412632632 | import logging
import time
from typing import List
from spaceone.inventory.connector.aws_kinesis_data_stream_connector.schema.data import (
StreamDescription,
Consumers,
)
from spaceone.inventory.connector.aws_kinesis_data_stream_connector.schema.resource import (
StreamResource,
KDSResponse,
)
from sp... | 100sun/plugin-aws-cloud-services | src/spaceone/inventory/connector/aws_kinesis_data_stream_connector/connector.py | connector.py | py | 6,632 | python | en | code | null | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "spaceone.inventory.libs.connector.SchematicAWSConnector",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "time.time",
"line_number": 27,
"usage_type": "call"
},
{
... |
24026596766 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Python version: 3.6
from tqdm import tqdm
import matplotlib.pyplot as plt
import os
import datetime
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from utils import get_dataset
from options import args_parser
from update ... | LiruichenSpace/FedFusion | src/baseline_main.py | baseline_main.py | py | 4,708 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "options.args_parser",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 37,
"usage_type": "attribute"
},
{
"api_name": "torch.device",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_availa... |
4693523565 | from bs4 import BeautifulSoup
import requests as google
from nltk import word_tokenize, FreqDist
import string
from nltk.corpus import stopwords
import matplotlib.pyplot as plt
import re
from sklearn.feature_extraction.text import TfidfVectorizer
import gensim
from nltk.tokenize import word_tokenize
stopwords_list... | ethirajsrinivasan/LSIWebScrap | search_engine_interface.py | search_engine_interface.py | py | 3,042 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "bs4.Be... |
33553726731 | '''
单个模型的pipeline
比如多层意图 只能对某一层意图进行infer
'''
from pre_data_deal import Pre_Data_Deal
from NameEntityRec import NameEntityRec
import random
from IntentConfig import Config
from collections import OrderedDict
from model.dl_model.model_lstm_mask.lstm_mask import LstmMask
from model.dl_model.model_lstm_mask.pipeline_lstm_m... | markWJJ/Intent_Detection | pipeline_tool.py | pipeline_tool.py | py | 10,671 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "logging.basicConfig",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pre_data_deal... |
4023788958 | import os
import sys
import json
import struct
import logging
from capstone.arm import *
from collections import Counter
from argxtract.common import paths as common_paths
from argxtract.core import utils
from argxtract.core import consts
from argxtract.common import objects as common_objs
from argxtract.core.disasse... | projectbtle/argXtract | argxtract/resources/vendor/nordic_ant/chipset_analyser.py | chipset_analyser.py | py | 8,728 | python | en | code | 25 | github-code | 36 | [
{
"api_name": "logging.info",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.stat",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "argxtract.common.paths.path_to_fw",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "argxtract... |
26478313784 | from django.db import models
from django.contrib.auth.models import User
from django.db import IntegrityError
import uuid
class Procedure(models.Model):
title = models.CharField(max_length=255, blank=True)
author = models.CharField(max_length=255, blank=True)
uuid = models.UUIDField(default=uuid.uuid4, ed... | protocolbuilder/sana.protocol_builder | src-django/api/models.py | models.py | py | 4,416 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.db.models.Model",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "django.db.models.CharField",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "... |
23063743554 | import sys
from dataclasses import dataclass
import numpy as np
import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import OneHotEncoder, StandardScaler
from sklearn.pipeline import Pipeline
from src.exception import CustomException
from ... | AnshulDubey1/Music-Recommendation | src/components/data_transformation.py | data_transformation.py | py | 3,195 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "dataclasses.dataclass",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "sklearn.pipeline.Pipe... |
2526327823 | # This script scraps Kenyan startups from https://startuplist.africa/
# Import required libraries
import pandas as pd
import numpy as np
from bs4 import BeautifulSoup as soup
from urllib.request import Request, urlopen
from selenium import webdriver
# URLs
url = "https://startuplist.africa/startups-in-kenya"
# Dri... | CharlesIvia/startups_in_kenya | scrapper/companies_scrapper.py | companies_scrapper.py | py | 1,120 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "pandas.read_html",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "pandas.... |
33207354162 | import Bio
from Bio.Blast import NCBIWWW,NCBIXML
from Bio.Seq import Seq
from Bio import SeqIO
def find_stop_codon(seq, start, stop_codons):
"""Find the next stop codon in the given sequence."""
for i in range(start, len(seq), 3):
codon = seq[i:i+3]
if codon in stop_codons:
return i... | jkjkciog/transcripomics | Chat GPT model improvements (non functional).py | Chat GPT model improvements (non functional).py | py | 2,540 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "Bio.SeqIO.parse",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "Bio.SeqIO",
"line_number": 55,
"usage_type": "name"
}
] |
29836727610 | import logging
import requests
import datetime
from aiogram import Bot, Dispatcher, executor, types
from tg_info import info
from bs4 import BeautifulSoup
weather_token = "6e8d79779a0c362f14c60a1c7f363e29"
API_TOKEN = "5158040057:AAEtt8ByoaJdYMy09MpupqpNAxiCAQnGj-0"
# Configure logging
logging.basicConfig(... | sivtv/telegrambot | main.py | main.py | py | 4,353 | python | uk | code | 0 | github-code | 36 | [
{
"api_name": "logging.basicConfig",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "aiogram.Bot",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "aiogram.Dispatcher"... |
71929861545 | from torch import nn
import torch.nn.functional as F
class PeriodDiscriminator(nn.Module):
def __init__(self, period):
super(PeriodDiscriminator, self).__init__()
layer = []
self.period = period
inp = 1
for l in range(4):
out = int(2 ** (5 + l + 1))
... | cuongnguyengit/hifigan | model/period_discriminator.py | period_discriminator.py | py | 1,062 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "torch.nn.utils.weight_norm",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.nn.utils... |
8290510873 |
import os
import json
import errno
import itertools
import numpy as np
import pandas as pd
def export_labels(root_dir: str):
"""Transforms `Balloon` dataset into Faster R-CNN standard format"""
labels_dir = os.path.join(root_dir, "labels")
if not os.path.exists(labels_dir):
try:
... | AndreasKaratzas/faster-rcnn | lib/balloon.py | balloon.py | py | 2,836 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "os.path.exists",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number":... |
34408858736 | from django.conf.urls import include, url
from teacherMan import views as tech
app_name = 'teacher'
urlpatterns = [
url(r'main', tech.main, name='teacher'),
url(r'data', tech.getData),
url(r'edit', tech.editTech),
url(r'delTechInfo', tech.delTech),
url(r'addTechInfo', tech.addTech),
#url(r'fi... | A11en0/InfoManageSystem | teacherMan/urls.py | urls.py | py | 349 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "django.conf.urls.url",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "teacherMan.views.main",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "teacherMan.views",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.... |
27954967699 | import time
import os
import pandas as pd
import requests as re
import numpy as np
import asyncio
from aiohttp import ClientSession
from loguru import logger
url_general = 'https://www.fundamentus.com.br/resultado.php'
url_paper = 'https://www.fundamentus.com.br/detalhes.php?papel='
data_to_save = list()
... | Muriloozol/InvestCode | scrapper/scrapper.py | scrapper.py | py | 4,364 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pandas.read_html",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "aiohttp.ClientSes... |
25625656419 | import logging
import random
import json
import string
import threading
import urllib.request
import spacy
from datetime import datetime
from tinydb import TinyDB, Query
from tinydb.operations import add
from urllib.parse import quote
from urllib.error import HTTPError
import pymorphy2
from operator import... | alkurmtl/playnamegame | run.py | run.py | py | 29,693 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "logging.basicConfig",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "telegram.ext.Updater",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "pymorphy2.... |
7292695784 | #!/usr/bin/python3
"""
# This file is part of the Pop Icon Theme and is free software; you can
# redistribute it and/or modify it under the terms of the GNU Lesser General
# Public License as published by the Free Software Foundation; version 3.
#
# This file is part of the Pop Icon Theme and is distributed in the h... | pop-os/icon-theme | master-render.py | master-render.py | py | 7,234 | python | en | code | 189 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.chdir",
"line_number": 47,... |
74430643303 | import datetime
import json
from flask_restful import Resource
from flask import request
from init import app, db
from Models.player import Player
from Models.playerRequest import PlayerRequest
from decorators import json_required
import random
class RPlayerPost(Resource):
def post(self, **kwargs):
""" ... | Apolliner/Field-Mini-Game | testOnline/ApiServer/API/player.py | player.py | py | 3,174 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask_restful.Resource",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "random.randrange",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "Models.player.Player",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "init.db.... |
7046181493 | import logging
import json
from invokust.aws_lambda import LambdaLoadTest, results_aggregator
logging.basicConfig(level=logging.INFO)
###
# SETTINGS
###
# How long should the test run for in minutes?
# Note that Lambda invokations that are started cannot be stopped.
# Test times will actually be run in intervals of ... | cds-snc/gc_forms_load_testing | locust_swarm.py | locust_swarm.py | py | 4,479 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.basicConfig",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "invokust.aws_lambda.results_aggregator",
"line_number": 36,
"usage_type": "call"
},
{
"api_na... |
15266305014 | import json
from django.db.models import Q
from django.http import HttpResponse
from django.views import View
from mymodels.models import Posts, CustomUser
from mypackage.MixinClasses import GetUserMixin, SlicerMixin, ExcludeDelPostsMixin
import datetime
from django.utils import timezone
class PostsList(View, Slice... | untiwe/citrom_test | mypackage/posts_manager/posts_list.py | posts_list.py | py | 5,721 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "django.views.View",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "mypackage.MixinClasses.SlicerMixin",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "mypackage.MixinClasses.GetUserMixin",
"line_number": 13,
"usage_type": "name"
},
... |
35425129977 |
# coding: utf-8
# # 보스톤 집 값 예측하기
#
# * 보스턴 주택 데이터는 여러 개의 측정지표들을 포함한, 보스톤 인근의 주택가 중앙값
#
# * Variable in order:
# - CRIM : 마을별 1인당 범죄율
# - ZN : 25,000 평방미터를 초과하는 거주지역의 비율
# - INDUS : 비소매 상업지역이 점유하고 있는 토지의 비율
# - CHAS : 찰스 강에 대한 더미변수(강의 경계에 위치한 경우는 1, 아니면 0
# - NOX : 10ppm 당 농축 일산화질소
# - RM : 주책 1가구당 평균 방... | ALVHA/DeepLearning | 20190722/Boston+House.py | Boston+House.py | py | 2,276 | python | ko | code | 0 | github-code | 36 | [
{
"api_name": "numpy.random.seed",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.set_random_seed",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "pandas... |
39095320319 |
# coding: utf-8
# In[12]:
import nltk, re, string
from sklearn.preprocessing import normalize
from nltk.corpus import stopwords
# numpy is the package for matrix cacluation
import numpy as np
# for lemma
from nltk.stem import WordNetLemmatizer
from nltk.corpus import wordnet
wordnet_lemmatizer = WordNetLemmatizer... | vigneshsriram/Python-Tutorials | Multinomial Naive Bayes/Assignment5 (3).py | Assignment5 (3).py | py | 8,988 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "nltk.stem.WordNetLemmatizer",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_extraction.text.TfidfVectorizer",
"line_number": 42,
"usage_type": "call"
},
{... |
32274445958 | #!/opt/csw/bin/python
# coding=utf-8
from time import time
from ircbot import SingleServerIRCBot, Channel
from irclib import nm_to_n, is_channel, parse_channel_modes
from datetime import datetime
import conf.config as config
import logging
import sys
import traceback
import threading
import pluginloader
from logger im... | sviik/marju | marjubot.py | marjubot.py | py | 11,353 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "conf.config.NICK",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "conf.config",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "conf.config.PASSWORD",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "conf.conf... |
72223824745 | import requests
url = input("Enter the website URL: ")
# SQL injection test payload
payload = "' OR '1'='1"
# XSS test payload
xss_payload = "<script>alert('XSS')</script>"
# Add payload to the login form
data = {"username": "admin", "password": payload}
# Send the request
r = requests.post(url, data=data)
# Chec... | TheSyrox/SYVulnScan | VULNSCAN.py | VULNSCAN.py | py | 958 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.post",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 27,
"usage_type": "call"
}
] |
7554777199 | import torch
import torch.nn as nn
import torch.nn.init as init
class Fire(nn.Module):
def __init__(self, inplanes, squeeze_planes, expand1x1_planes, expand3x3_planes):
super(Fire, self).__init__()
self.inplanes = inplanes
self.squeeze = nn.Conv2d(inplanes, squeeze_planes, kernel_size=1)
... | gaungalif/cifar10.pytorch | cifar/models/squeeze.py | squeeze.py | py | 2,764 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numbe... |
6656532235 | # -*- coding: utf-8 -*-
"""
Created on 2023-11-28 (Tue) 15:03:39
Planar Maximally Filtered Graph implementation in python
@author: I.Azuma
"""
import numpy as np
import pandas as pd
import time
import networkx as nx
from networkx.algorithms.planarity import check_planarity
from tqdm import tqdm
import matplotlib.pypl... | groovy-phazuma/ImmunSocialNetwork | network_models/pmfg/pmfg.py | pmfg.py | py | 13,712 | python | en | code | null | github-code | 36 | [
{
"api_name": "numpy.array",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "networkx.Graph",
"line_number": 81,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
... |
889446688 | from numpy.lib import average
import pandas as pd
import numpy as np
import re
import nltk
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split,learning_curve,GridSearchCV
from nltk.stem.snowball import SnowballStemmer
from nltk.corpus import stopwords
from sklearn.feature_extraction.tex... | saarthakbabuta1/loan-agreement | machine_learning.py | machine_learning.py | py | 10,438 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "nlt... |
72027853863 |
# -*- coding: utf-8 -*-
# WindowでGroupByの区間を区切る
import apache_beam as beam
# Dataflowの基本設定
# ジョブ名、プロジェクト名、一時ファイルの置き場を指定します。
options = beam.options.pipeline_options.PipelineOptions()
gcloud_options = options.view_as(
beam.options.pipeline_options.GoogleCloudOptions)
gcloud_options.job_name = 'dataflow-tutorial7'
... | hayatoy/dataflow-tutorial | tutorial7.py | tutorial7.py | py | 2,908 | python | ja | code | 25 | github-code | 36 | [
{
"api_name": "apache_beam.options.pipeline_options.PipelineOptions",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "apache_beam.options",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "apache_beam.options",
"line_number": 11,
"usage_type": "attri... |
22344125415 | import logging
import re
from investments.models import RealEstate
from .utils import (check_skip, create_investment, extract_data, get_id,
get_interest_range, normalize_meta, normalize_number,
parse_markup_in_url, price_range, scrape_page)
logger = logging.getLogger(__name__)... | Constrictiongithub/constriction_website | importer/management/commands/scrapers/caseinpiemonte.py | caseinpiemonte.py | py | 3,395 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "investments.models.RealEstate",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "re... |
72570992424 | # turns out there's a better website for records than the one this scraper uses
# scraper to query AZ SOS website for possible matches for each retailer
import urllib.request
import urllib.parse
import bs4 as bs
import re
import pandas as pd
import os
import numpy as np
from selenium import webdriver
from selenium.webd... | Luke-Patterson/state_scrap | AZ/old/AZ_1_crawler_old.py | AZ_1_crawler_old.py | py | 4,561 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "time.sleep",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "time.sleep",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number"... |
2317107691 |
import os
import numpy as np
import keras
from keras import models, layers
from PIL import Image
from numpy import asarray
from cv2 import cv2
from keras.models import load_model
from os.path import join, dirname, realpath
from flask import Flask,render_template,request
import skimage
from skimage.transform import res... | Roboramv2/Image-compression | 1_autoencoder/flask/app.py | app.py | py | 2,824 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "os.path.dirname",
"line_number... |
3289841382 | import copy
import abc
import logging
import weakref
import math
from collections import defaultdict
try:
from collections import OrderedDict
except ImportError: #pragma:nocover
from ordereddict import OrderedDict
from pyomo.core.kernel.component_interface import \
(IActiveObject,
... | igorsowa9/vpp | venv/lib/python3.6/site-packages/pyomo/core/kernel/component_block.py | component_block.py | py | 59,127 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "pyomo.core.kernel.component_interface.IComponent",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": "pyomo.core.kernel.component_interface.IComponentContainer",
"line_number":... |
75128039145 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.graph_objs as go
df=pd.read_csv(r'pax_all_agreements_data.csv',sep=',')
df['Dat_Y'],df['Dat_M'],df['Dat_D']=df['Dat'].str.split('-').str
fecha_inicio=min(df['Dat_Y'])
fecha_final=max(df['Dat_Y'])
df_grupo_region_fecha=df.groupb... | AlejandroUPC/data_vis_uoc | data_exploring.py | data_exploring.py | py | 3,063 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.to_numeric",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.to_numeric",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "pandas.crosstab",
... |
70569498345 | from fastapi import status, HTTPException, Depends, APIRouter
from sqlalchemy.orm import Session
from .. import models, schemas, utils, oauth2
from ..database import get_db
from sqlalchemy import func, case
router = APIRouter(
prefix="/users",
tags=['Users']
)
@router.post("/", status_code=status.HTTP_201_CRE... | charl1ecloud/notebank-webapp | backend/app/routers/user.py | user.py | py | 2,505 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "fastapi.Depends",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "database.get_... |
3799851771 | import os
import json
import requests
import logging
from urllib.parse import urlencode
from types import SimpleNamespace
MTYPES = dict(xbox=1, playstation=2, steam=3, blizzard=4, stadia=5, epic=6, bungie=254)
MLEVELS = dict(beginner=1, member=2, admin=3, actingfounder=4, founder=5) # Just like with Halo - Bungie nev... | xant-tv/ecumene | src/bnet/client.py | client.py | py | 12,445 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "types.SimpleNamespace",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "types.SimpleNamespace",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.gete... |
1486053711 | #! /usr/bin/env python
import rospy
import actionlib
import behavior_common.msg
import time
from std_msgs.msg import Float64
from sensor_msgs.msg import JointState
from geometry_msgs.msg import Twist
from math import radians, degrees
import tf
import os, thread
# for talking
# import actionlib
import actionlib.action... | shinselrobots/tb2s | tb2s_behaviors/follow_behavior/scripts/behavior_service.py | behavior_service.py | py | 21,227 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "rospy.Publisher",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "std_msgs.msg.Float64",
"line_number": 38,
"usage_type": "argument"
},
{
"api_name": "rospy.Publisher",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "std_msgs.msg... |
26558715293 | #!/usr/bin/env python3
import sys
import os
import argparse
import pandas as pd
import vcf
def main():
parser = argparse.ArgumentParser(description="Build reference set consisting of a selection of samples per pangolin lineage.")
parser.add_argument('--vcf', required=True, type=str, nargs='+', help="vcf file... | baymlab/wastewater_analysis | manuscript/select_samples_v1.py | select_samples_v1.py | py | 7,931 | python | en | code | 14 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.mkdir",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",... |
34140743906 | import cv2
import numpy as np
from model import *
from scipy.spatial.distance import cosine
def read_pairs(path):
files = []
with open(path) as f:
files = f.readlines()
files = [afile[:-1].split(' ') for afile in files]
files = [[afile[0], afile[1], afile[2]=='1'] for afile in files]
... | Jasmineysj/Face-verification-system | test.py | test.py | py | 2,930 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.zeros",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 2... |
29380151380 | import scrapy
from bs4 import BeautifulSoup
class CNGlobalStock(scrapy.Spider):
# modeled after: https://wallstreetcn.com/articles/3499602
name = "wallstreetcn"
start_urls = ["https://wallstreetcn.com/articles/3499602"]
def parse(self, response):
article_body = response.css("div.rich-... | mattfeng/bluefire | scrapers/wallstreetcn/old/wallstreetcn_scraper.py | wallstreetcn_scraper.py | py | 796 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "scrapy.Spider",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 11,
"usage_type": "call"
}
] |
36892858608 | from lxml import html
import requests
import csv
from os.path import exists
import time
import sys
# function printing additional info about request
def my_http_get(url):
print('')
print('REQUEST ' + url)
time.sleep(3) # added to avoid being blocked by fbref server
start = time.time()
result = req... | kornasm/GIS | scrapers/SeasonSquadScraper.py | SeasonSquadScraper.py | py | 3,520 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "time.sleep",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 15,
... |
32058498206 | from tkinter import *
import matplotlib
import os
from pandas import DataFrame
import numpy as np
import pandas as pd
from tkinter import ttk
matplotlib.use('TkAgg')
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.figure import Figure
from Functions import... | patidarrahul/PlotIT | extra_python files/boxplot.py | boxplot.py | py | 25,877 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.use",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "tkinter.ttk.Combobox",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "tkinter.ttk",
"... |
70474642983 |
import torch
import torch.nn.functional as F
from .modules import Module, ModuleList, ModuleDict
from pytorch_transformers import BertModel, BertConfig,BertTokenizer
from .modules.prediction import registry as prediction
from .modules.prediction import Prediction_Bert,Prediction_Bert_GAT
from .modules.GCNS import *
i... | XuChen0427/Syntactic-Informed-Graph-Networks-for-Sentence-Matching | hetesrc/network.py | network.py | py | 7,773 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"lin... |
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