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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
18809920603 | # -*- coding: utf-8 -*-
"""
Your task is to use the iterative parsing to process the map file and
find out not only what tags are there, but also how many, to get the
feeling on how much of which data you can expect to have in the map.
Fill out the count_tags function. It should return a dictionary with the
tag name ... | sarinograsso-zz/udacity-data-analyst-nanodegree | p3-wrangle-openstreetmap-data/code/mapparser.py | mapparser.py | py | 1,739 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "xml.etree.cElementTree.parse",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "xml.etree.cElementTree",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "operator.itemgetter",
"line_number": 60,
"usage_type": "call"
},
{
"api_name"... |
344749226 | import subprocess
import os
from tqdm import tqdm
base_dir = "voicedatabase"
target_dir = "voicedatabase_wav"
os.makedirs(target_dir, exist_ok=True)
for name in tqdm(os.listdir(base_dir)):
file_path = os.path.join(base_dir, name)
new_file_path = file_path.replace(base_dir, target_dir)
new_file_path = ne... | chronos123/video_recognition | seetaFace6Python-master_w/turn_mp3_2wav.py | turn_mp3_2wav.py | py | 502 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "os.makedirs",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 11,... |
1789139276 | from PyQt5.QtWidgets import (QGroupBox, QLineEdit, QPushButton, QTabWidget, QCheckBox, QComboBox,
QVBoxLayout, QWidget, QDoubleSpinBox, QFormLayout)
from PyQt5.QtCore import QLocale
class widget(QWidget):
"""Base class for GUI widgets."""
def __init__(self, title='Control window')... | nvladimus/daoSPIM | microscope_control/src/widget.py | widget.py | py | 9,327 | python | en | code | 10 | github-code | 6 | [
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QVBoxLayout",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QGroupBox",
"line_number": 29,
"usage_type": "call"
},
{
"api_... |
18847610254 | import pytest
import yatest.common as common
from cloud.blockstore.tests.python.lib.test_base import run_test
DEFAULT_MON_PORT = 8766
TESTS = [
[
"myt1-ct5-13",
"cloud/blockstore/tests/loadtest/remote/remote-myt1-ct5-13.txt",
"myt1-ct5-13.cloud.yandex.net",
9766,
DEFAULT_M... | ydb-platform/nbs | cloud/blockstore/tests/loadtest/remote/test.py | test.py | py | 1,777 | python | en | code | 32 | github-code | 6 | [
{
"api_name": "cloud.blockstore.tests.python.lib.test_base.run_test",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "yatest.common.get_param",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "yatest.common",
"line_number": 52,
"usage_type": "name"
},... |
7105569271 | import sys
assert sys.version_info >= (3, 5) # make sure we have Python 3.5+
from pyspark.sql import SparkSession, functions, types #type:ignore
# add more functions as necessary
def main(inputs, output):
observation_schema = types.StructType([
types.StructField('station', types.StringType()),
... | brendanartley/Programming-for-Big-Data-Coursework | week_6/temp_range_sql.py | temp_range_sql.py | py | 2,263 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sys.version_info",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "pyspark.sql.types.StructType",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.types",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "p... |
1002914150 | import time
import random
import sys
import numpy as np
import scipy.sparse as spa
from sklearn.linear_model import SGDClassifier
from sklearn.svm import LinearSVC
from sklearn.metrics import classification_report
from sklearn.model_selection import KFold
from utils import readDataset, Processor, Sequencer, test, ... | Refefer/Dagger | baseline.py | baseline.py | py | 2,450 | python | en | code | 29 | github-code | 6 | [
{
"api_name": "scipy.sparse.vstack",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "scipy.sparse",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "numpy.vstack",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.SG... |
40005355955 | from functools import partial
import pytest
from xdlang.parser import parse_text
def parse_stmt(text):
return parse_text(program_text=text, start="statement")
@pytest.mark.parametrize(
"text,value",
[
("return 42;", "42"),
("return 0.0;", "0.0"),
("return false;", "false"),
... | mbednarski/xdlang | tests/parser/test_parser_return.py | test_parser_return.py | py | 586 | python | en | code | 3 | github-code | 6 | [
{
"api_name": "xdlang.parser.parse_text",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pytest.mark.parametrize",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pytest.mark",
"line_number": 12,
"usage_type": "attribute"
}
] |
31981290467 | from pymongo import MongoClient
from dotenv import dotenv_values as env
import dns.resolver
dns.resolver.default_resolver=dns.resolver.Resolver(configure=False)
dns.resolver.default_resolver.nameservers=['8.8.8.8']
class Connection:
url =env(".env")["DATABASE_STRING"]
@classmethod
def connect(cls):
try:
clie... | Crown003/Portfolio | Databases/Database.py | Database.py | py | 535 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "dns.resolver.resolver",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "dns.resolver",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "dns.resolver.resolver.Resolver",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "d... |
27759270841 | from ast import arg
from rdflib import Graph, RDFS, RDF, URIRef, Namespace, Literal, XSD
from owlrl import DeductiveClosure, RDFS_Semantics
import random, sys
import sys
import os
import pandas as pd
from string import Template
import networkx as nx
import networkx.algorithms.community as nxcom
from scipy import rand
... | GabHoo/The-Game-of-Thrones-Automyth | generator.py | generator.py | py | 10,160 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "rdflib.URIRef",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "random.choice",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "rdflib.Literal",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "rdflib.XSD.boolean",
"... |
650440827 | #! /usr/bin/python
import os
import sys
import json
from concurrent import futures
import luigi
import numpy as np
import cluster_tools.utils.volume_utils as vu
import cluster_tools.utils.function_utils as fu
from cluster_tools.cluster_tasks import SlurmTask, LocalTask, LSFTask
#
# Find Labeling Tasks
#
class Fin... | constantinpape/cluster_tools | cluster_tools/relabel/find_labeling.py | find_labeling.py | py | 4,185 | python | en | code | 32 | github-code | 6 | [
{
"api_name": "luigi.Task",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "luigi.Parameter",
"l... |
4831701553 | from builtins import next
from builtins import str
from builtins import range
from builtins import object
import numpy as np
from sosdb import Sos
from sosdb.DataSet import DataSet
from numsos import Inputer
import datetime as dt
import time
import os
import sys
class DataSource(object):
DEF_LIMIT = 1024 * 10... | nick-enoent/numsos | numsos/DataSource.py | DataSource.py | py | 40,844 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "builtins.object",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "builtins.str",
"line_number": 75,
"usage_type": "name"
},
{
"api_name": "sosdb.Sos.ColSpec",
"line_number": 77,
"usage_type": "call"
},
{
"api_name": "sosdb.Sos",
"line_... |
29589756771 | # License AGPL-3.0 or later (https://www.gnu.org/licenses/agpl).
from odoo import api, fields, models, _
from odoo.exceptions import Warning as UserError
import logging
_logger = logging.getLogger(__name__)
class ExternalSource(models.Model):
_name = 'external.source'
_description = 'External Source'
n... | OdooNodrizaTech/external_odoo | external_odoo_base/models/external_source.py | external_source.py | py | 9,478 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "odoo.models.Model",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "odoo.fields.Char"... |
31282904597 | #!/usr/bin/env python
from __future__ import print_function
import sys
sys.path.append("..")
import json
import urllib2
import time
import cig_codes
GITHUB_API_URL = "https://api.github.com"
HOOKS_URL = GITHUB_API_URL + "/repos/geodynamics/%s/hooks"
TEST_PUSH_HOOK_URL = GITHUB_API_URL + "/repos/geodynamics/%s/hooks/... | geodynamics/cig_backend | git/setup_github.py | setup_github.py | py | 3,364 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "sys.path.append",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "urllib2.Request",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "urllib2.urlopen",
"li... |
28420080170 | """モジュールのインポート"""
import numpy as np
from scipy import signal
from sklearn.cluster import KMeans
import pickle
from src.visualize_data import (
show_signals, show_peaks, show_amp_means, show_sses,
show_amp_clusters, show_signals_with_cluster
) # 自作モジュール
"""データの読み込み"""
n_data = 50 # データ数
n_samples = 2... | T-S1/PracticeVibrationAnalysis | kmeans_ampmean.py | kmeans_ampmean.py | py | 2,483 | python | ja | code | 0 | github-code | 6 | [
{
"api_name": "numpy.zeros",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "src.visualize_data.show_signals... |
43270763213 | import json
import os
import boto3
import time
sqs_client = boto3.client('sqs', region_name='us-west-2')
kinesis_client = boto3.client('firehose', region_name='us-west-2')
cloudwatch_client = boto3.client('cloudwatch', region_name='us-west-2')
def handler(event, context):
try:
lambda_end = time.time() + ... | uw-it-aca/sqs-to-kinesis-worker | index.py | index.py | py | 2,438 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "boto3.client",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 13... |
650456967 | import os
import luigi
from ..cluster_tasks import WorkflowBase
from ..utils import volume_utils as vu
from ..morphology import MorphologyWorkflow
from . import skeletonize as skeleton_tasks
class SkeletonWorkflow(WorkflowBase):
input_path = luigi.Parameter()
input_key = luigi.Parameter()
output_path = l... | constantinpape/cluster_tools | cluster_tools/skeletons/skeleton_workflow.py | skeleton_workflow.py | py | 2,984 | python | en | code | 32 | github-code | 6 | [
{
"api_name": "cluster_tasks.WorkflowBase",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "luigi.Parameter",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "luigi.Parameter",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "luigi.Para... |
16008764419 | # This file is part of botwtools.
#
# botwtools is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# botwtools is distributed in the hop... | RenaKunisaki/botwtools | codec/sarc/reader/sarc.py | sarc.py | py | 2,458 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "header.Header",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "sfatheader.SFATHeader",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "sfatnode.SFATNo... |
37411695618 | from bs4 import BeautifulSoup
from bs4.element import Tag
from requests import get
from . import schema
from .db import create_constituencies, create_results, create_summary
from .settings import get_settings
def scrape():
settings = get_settings()
doc = get(settings.election_all_constituency_url).text
... | carneddau/senedd-election | src/senedd_election/scrape.py | scrape.py | py | 2,890 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "settings.get_settings",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "settings.election_all_constituency_url",
"line_number": 13,
"usage_type": "attribute"
},
{
"ap... |
73696096509 | import configparser
import logging
import os
from collections import defaultdict
__all__ = [
'ConfigurationError',
'ConfigBuilder'
]
class ConfigurationError(Exception):
pass
class BlueSkyKMLConfigParser(configparser.ConfigParser):
"""Custom config parser class whose sole contribution is to
trans... | pnwairfire/blueskykml | blueskykml/configuration.py | configuration.py | py | 12,841 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "collections.defaultdict",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "... |
4785990380 | from collections import defaultdict
n = int(input())
l = []
for i in range(1,n+1):
tmp = list(input())
cnt = 0
for j in range(n):
if tmp[j] == "o":
cnt += 1
l.append((cnt,i))
d = defaultdict(list)
for i,v in l:
d[i].append(v)
for i in d:
d[i].sort()
ans = []
for i in range(n... | K5h1n0/compe_prog_new | abc323/b/main.py | main.py | py | 421 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "collections.defaultdict",
"line_number": 12,
"usage_type": "call"
}
] |
6131237751 | """
Tests for pyhap.accessory_driver
"""
import os
import tempfile
from unittest.mock import patch, Mock
import pytest
from pyhap.accessory import (Accessory,
Bridge,
STANDALONE_AID)
from pyhap.accessory_driver import AccessoryDriver
@patch("pyhap.accessory_d... | bdrydyk/homecontroller | tests/test_accessory_driver.py | test_accessory_driver.py | py | 1,737 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pyhap.accessory.Accessory",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pyhap.accessory_driver.AccessoryDriver",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pyhap.accessory.STANDALONE_AID",
"line_number": 20,
"usage_type": "name"... |
74525065146 | from itertools import chain
import torch
import numpy as np
class Visualizer():
def __init__(self, env='cysb'):
import visdom
self.vis = visdom.Visdom()
self.index={}
self.env=env
def plot(self,name,y):
x = self.index.get(name,0)
self.vis.line(Y=np.array([y]),X=np... | jimmyyfeng/Tianchi-1 | Tianchi_tensorflow/util.py | util.py | py | 1,654 | python | en | code | 5 | github-code | 6 | [
{
"api_name": "visdom.Visdom",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 12,
"usage_type": "call"
}
] |
1210248705 | # measure the latency of each operation performed when computing the fft with
# redis and also the total latency, then save the results to a .csv file
import time
from statistics import mean
import numpy as np
import pandas as pd
import redis
import redisai as rai
con = rai.Client(host='localhost', port=6379)
r = re... | xolotl18/ML_monitoring | redis_vis/dev/time_metrics.py | time_metrics.py | py | 2,542 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "redisai.Client",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "redis.Redis",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "time.time",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.frombuffer",
"line_num... |
35021380521 | """Book crawl spider"""
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from book_scraper.book_loader import BookLoader
from book_scraper.items import Book
class BookCrawlSpider(CrawlSpider):
"""Book crawl spider class"""
name = 'book_crawl_spider'
allowed_d... | OsnovaDT/book_scraper | book_scraper/spiders/book_crawl_spider.py | book_crawl_spider.py | py | 1,545 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "scrapy.spiders.CrawlSpider",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "scrapy.spiders.Rule",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "scrapy.linkextractors.LinkExtractor",
"line_number": 22,
"usage_type": "call"
},
{
... |
72746063868 | # -*- coding:utf-8 -*-
__author__ = 'shichao'
import os
import tensorflow as tf
from PIL import Image
import cv2
import matplotlib.pyplot as plt
def encode_TFRecord(root_dir,filename,classes):
'''
encode images and their labels into the TF Record
:param cwd:
:param filename:
:param classes:
:r... | csrunner/utils | TFRecord_IO.py | TFRecord_IO.py | py | 3,412 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "tensorflow.python_io.TFRecordWriter",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "tensorflow.python_io",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 20,
"usage_type": "call"
},
{
"api_na... |
74063454268 | import numpy as np
##imports
from bokeh.io import output_file
from bokeh.plotting import figure,show
#My word count
days = np.linspace(1,10,10)
words = [200,300,400,400,200,500,100,800,200,100]
cum = np.cumsum(words)
#output file
output_file("legend_added.html",title = "With Legends")
#create figure
fig = figure... | dipanwita2019/Bokeh_plots | 02_firstglyph.py | 02_firstglyph.py | py | 790 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "numpy.linspace",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "numpy.cumsum",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "bokeh.io.output_file",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "bokeh.plotting.figure... |
3403292676 | from tkinter import *
import tkinter.font
from tkinter.colorchooser import *
from tkinter import simpledialog
from PIL import Image, ImageDraw, ImageTk
from tkinter.messagebox import askyesno
import os
import tkinter.filedialog
root = Tk()
root.geometry("800x600")
root.title("Paint App")
root.configure(background='whi... | trav382/paint_app | paintapp.py | paintapp.py | py | 15,679 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "PIL.Image.new",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line_number": 38,
"usage_type": "name"
},
{
"api_name": "PIL.ImageDraw.Draw",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "PIL.ImageDraw",
"line_... |
37273677215 | '''open.ai gym environment wrapper.
reference: https://github.com/openai/gym/tree/master/gym/wrappers'''
import gym
import numpy as np
import cv2
import config
class NoopResetEnv(gym.Wrapper):
def __init__(self, env, noop_max=30):
"""start the game with no-op actions to provide random starting positions
... | ZiyuanMa/R2D2 | environment.py | environment.py | py | 2,139 | python | en | code | 31 | github-code | 6 | [
{
"api_name": "gym.Wrapper",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "gym.Wrapper.__init__",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "gym.Wrapper",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "numpy.random.ra... |
35416595248 | import logging
import battle.boss
import battle.main
import memory.main
import menu
import pathing
import save_sphere
import screen
import vars
import xbox
import random
from paths import (
MacalaniaTempleApproach,
MacalaniaTempleEscape,
MacalaniaTempleFoyer,
MacalaniaTempleTrials,
MacalaniaUnderTe... | coderwilson/FFX_TAS_Python | area/mac_temple.py | mac_temple.py | py | 14,899 | python | en | code | 14 | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "vars.vars_handle",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "xbox.controller_handle",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "memory.main... |
27572670921 | from django.core.management.base import BaseCommand
from django.utils import timezone
import string
import requests
from bs4 import BeautifulSoup
import re
from jobapp.models import JobModel
class Command(BaseCommand):
help = 'Get new jobs'
def handle(self, *args, **kwargs):
url = 'https://www.myjob... | Afeez1131/JobScraperWeb | jobapp/management/commands/jobmag.py | jobmag.py | py | 1,633 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": ... |
19347557565 | """
This code is used to download the data used to train and test our model
"""
import os
from six.moves import urllib
import zipfile
raw_dir = os.path.join(os.getcwd(), 'data')
def download_url(url, folder, filename):
r"""Downloads the content of an URL to a specific folder.
Args:
url (string): The... | hadarser/ProvablyPowerfulGraphNetworks_torch | utils/get_data.py | get_data.py | py | 1,616 | python | en | code | 39 | github-code | 6 | [
{
"api_name": "os.path.join",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.getcwd",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.makedirs",
"line_number": 22,... |
73558889468 | import json
import plotly
import pandas as pd
import sys
from nltk.stem import WordNetLemmatizer
from nltk.tokenize import word_tokenize
from flask import Flask
from flask import render_template, request, jsonify
from plotly.graph_objs import Bar
from sklearn.externals import joblib
from sqlalchemy import create_engi... | austin047/udacity-datascience-disaster-res-pipeline | app/run.py | run.py | py | 3,666 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sys.path.append",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "flask.Flask",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "nltk.tokenize.word_tokenize... |
1742266102 | import pytest
import random
import numpy as np
from scipy.stats import unitary_group
import piquasso as pq
@pytest.mark.monkey
@pytest.mark.parametrize("d", [2, 3, 4, 5])
def test_random_gaussianstate(d):
with pq.Program() as prepare_random_program:
for i in range(d):
r = np.random.normal()
... | Budapest-Quantum-Computing-Group/piquasso | tests/backends/gaussian/test_monkey.py | test_monkey.py | py | 716 | python | en | code | 19 | github-code | 6 | [
{
"api_name": "piquasso.Program",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.random.normal",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "random.uniform... |
3588875710 | import json
import sublime
import sublime_plugin
import os
import re
from .jinja2 import Environment
class PluginMixin():
def get_selection(self):
selections = []
for region in self.view.sel():
if not region.empty():
selections.append(region)
if len(selections) ... | mattmc3/subl-codegen | plugin.py | plugin.py | py | 2,885 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sublime.Region",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sublime.Region",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_nu... |
34201802013 | import pygame
from pygame.math import Vector2
from pygame import Rect
class Block:
"""
Base class for square or rectangular object
"""
def __init__(self, position, width, height, color):
# Create a rectangle centered around the x and y
self.position = position
self.rectangle =... | NandoTheessen/Sprint-Challenge--Python-1 | src/block.py | block.py | py | 3,621 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pygame.Rect",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pygame.draw.rect",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "pygame.draw",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "pygame.Rect",
"line... |
12700438398 | from django.http import HttpResponse
from django.shortcuts import render
from .models import add,place,blog
# Create your views here.
def create(request):
var=add.objects.all()
return render(request,"index.html",{'gives':var})
def fun(request):
var=add.objects.all()
make=blog.objects.all()
obj=pla... | sanjanapy/travelvlog | travelapp/views.py | views.py | py | 611 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "models.add.objects.all",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "models.add.objects",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "models.add",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.shortcu... |
31632163434 | import os
import sys
import numpy as np
import tables as tb
import pandas as pd
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.colors as clrs
import matplotlib.cm as cm
from matplotlib.colors import Normalize
from invisible_cities.... | paolafer/next_analysis | plotting/plot2D_voxels_beersheba.py | plot2D_voxels_beersheba.py | py | 3,205 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "matplotlib.use",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.cm.get_cmap",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.cm",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": ... |
31180681839 | import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from tweepy import Stream
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
import json
import datetime
ckey='MRblXfNQmvHssuz5zLydkUjuP'
csecret='RE2htDqLQfXMu44abXXCC5chWYBfHpkGmnvSsCfKxDdpJeAdX0'
atoken='904991952... | ravirajsingh-knit/real-time-twitter-sentiment-analysis | tw_data.py | tw_data.py | py | 1,802 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "nltk.sentiment.vader.SentimentIntensityAnalyzer",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "tweepy.streaming.StreamListener",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "datetime.datetime.now",
"line_number": 48,
"usage_type": ... |
37051109253 | #!/usr/bin/env python
# coding: utf-8
# # Search for elements with given classes and attributes
# In[2]:
import requests as req
from bs4 import BeautifulSoup
# In[3]:
URL = 'https://pt.wikipedia.org/wiki/Ariquemes'
r = req.get(URL)
soup = BeautifulSoup(r.content)
# In[4]:
links = soup.find_all("a") # findin... | ROHIT-1112/Creation-of-Web-Scraper-in-python | Mod-3.py | Mod-3.py | py | 885 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "requests.get",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 18,
"usage_type": "call"
}
] |
73993765949 | import re
import shutil
import subprocess
import tempfile
import pytest
import requests
import requests.auth
import klaus
from .utils import *
def test_make_app_using_list():
app = klaus.make_app(REPOS, TEST_SITE_NAME)
with serve_app(app):
response = requests.get(UNAUTH_TEST_SERVER).text
as... | jonashaag/klaus | tests/test_make_app.py | test_make_app.py | py | 5,924 | python | en | code | 659 | github-code | 6 | [
{
"api_name": "klaus.make_app",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pytest.raises",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "klaus.make_app",
"line_... |
17371141816 | from decimal import Decimal
from django.contrib.auth import get_user_model
from django.contrib.auth.tokens import default_token_generator
from django.core.mail import send_mail
from rest_framework import viewsets, status
from rest_framework.decorators import action
from rest_framework.generics import get_object_or_404... | vavsar/freelance_t | users/views.py | views.py | py | 3,549 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "django.contrib.auth.get_user_model",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "rest_framework.viewsets.ModelViewSet",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.viewsets",
"line_number": 19,
"usage_type": "... |
50554619 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 27 12:29:45 2023
@author: victor
"""
import numpy as np
import pandas as pd
import iminuit
import copy
import efficiency_fit as acc
#remember to have the correct path for this part
#currently accessing toy data
data = pd.read_csv('cleaned_total_dataset.csv')
bin_ranges... | georgesuhk/TBPS_7 | fitting/fitting_functions.py | fitting_functions.py | py | 16,941 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "pandas.read_csv",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "efficiency_fit.n6_polynomial",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "efficiency_fit.popt_costhetak_ls",
"line_number": 50,
"usage_type": "attribute"
},
{
... |
28573784122 | from sklearn.datasets import load_iris
from sklearn.neural_network import MLPClassifier
from sklearn import tree
import numpy as np
import warnings
warnings.filterwarnings("ignore")
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import datasets
from sklearn.decomposition i... | dixitomkar1809/MultipleModels | Main.py | Main.py | py | 19,925 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "sklearn.neural_network... |
30138175095 | # !/usr/local/python/bin/python
# -*- coding: utf-8 -*-
# (C) Wu Dong, 2020
# All rights reserved
# @Author: 'Wu Dong <wudong@eastwu.cn>'
# @Time: '2020-04-13 10:52'
""" 演示 pre-request 框架验证字符串任意包含测试
"""
from flask import Flask
from pre_request import pre, Rule
app = Flask(__name__)
app.config["TESTING"] = True
client... | Eastwu5788/pre-request | examples/example_filter/example_contains_any.py | example_contains_any.py | py | 903 | python | en | code | 55 | github-code | 6 | [
{
"api_name": "flask.Flask",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pre_request.Rule",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pre_request.pre.catch",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "pre_request.pre",
... |
17542699256 | # *** Important Note: This part should be executed only after executing 'part1.4.py' ***
from Cryptodome.Cipher import AES
from Cryptodome.Util.Padding import unpad
if __name__ == '__main__':
cipherFile = open('cipherText.txt', 'rb') # Opening the file containing the cipher text for read
cipherText = cipherFil... | Abdullah-00/cryptography-in-python | part1/part1.5.py | part1.5.py | py | 970 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "Cryptodome.Cipher.AES.new",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "Cryptodome.Cipher.AES",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "Cryptodome.Cipher.AES.MODE_CBC",
"line_number": 11,
"usage_type": "attribute"
},
{
... |
1522094914 | import torch
from thesis import metrics
TARGETS = [
torch.tensor([[0, 0, 1, 1], [1, 0, 2, 1], [1, 1, 2, 2]], dtype=torch.float),
torch.tensor([[1, 1, 2, 2], [3, 1, 4, 2], [5, 1, 6, 2], [7, 1, 8, 2]], dtype=torch.float),
torch.tensor([[0, 0, 5, 5], [5, 5, 10, 10]], dtype=torch.float),
]
PREDICTIONS = [
... | laitalaj/cvpce | test/metrics_test.py | metrics_test.py | py | 5,150 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "torch.tensor",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "torch.float",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.tensor",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "torch.float",
"line_numbe... |
21052452549 | import os
import time
import openai
from colorama import Fore
from pprint import pprint
openai.api_key = os.getenv("OPENAI_API_KEY")
openai.api_base = 'http://47.251.11.225:8080/v1'
# Overly simple abstraction until we create something better
# simple retry mechanism when getting a rate error or a bad gateway
def ... | cttmayi/pylib | pylib/ai/reader/llm.py | llm.py | py | 1,395 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "openai.api_key",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "os.getenv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "openai.api_base",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "openai.ChatCompletio... |
18797452563 | import socket
import os
import ocr
import boto3
from flask import Flask, flash, request, redirect, url_for
from werkzeug.utils import secure_filename
dynamodb_resource = boto3.resource('dynamodb', region_name='us-east-1')
dynamodb_client = boto3.client('dynamodb', region_name='us-east-1')
s3_client = boto3.client('s... | Zut2020/szakdolgozat | docker/ocr/server.py | server.py | py | 1,227 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "boto3.resource",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "flask.Flask",
"line_numbe... |
3986885530 | import asyncio
from asyncio import Event
from datetime import datetime
import logging
import uvicorn
from bareasgi import Application, text_writer, HttpResponse
logging.basicConfig(level=logging.DEBUG)
LOGGER = logging.getLogger('background_tasks')
async def time_ticker(info, shutdown_event):
"""
This is t... | rob-blackbourn/bareASGI | docs/examples/background_tasks_nt.py | background_tasks_nt.py | py | 2,394 | python | en | code | 26 | github-code | 6 | [
{
"api_name": "logging.basicConfig",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "logging.getLogger",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "datetime.datet... |
30969605726 | import numpy as np
import pandas as pd
import joblib
#######
## Get the model trained in the notebook
# `../nbs/1.0-asl-train_model.ipynb`
#######
model = joblib.load('models/LinSVR.joblib')
def preprocess(data):
"""
Returns the features entered by the user in the web form.
To simplify, we set a bun... | PeterLiessem/ML-oblig2 | boxoffice/app/predict.py | predict.py | py | 4,893 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "joblib.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 118,
"usage_type": "call"
}
] |
1379619171 | import flask, json
from flask import request, jsonify
from datetime import datetime, timedelta
import db
from tools import *
app = flask.Flask(__name__)
api_url = "/api/v1/"
# Show Graphs
@app.route('/<controller>', methods=['GET'])
def graph(controller):
to_time = datetime.now()
from_time = to_time + timede... | Thorium0/Sensor-api-project | api/app.py | app.py | py | 1,650 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "flask.Flask",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "datetime.timedelta... |
423251546 | import glob
import os
import tensorflow as tf
from PIL import Image
import numpy as np
AUTOTUNE = tf.data.experimental.AUTOTUNE
def image_scaling(img, label):
"""
Randomly scales the images between 0.5 to 2.0 times the original size.
Args:
img: Training image to scale.
label: Segmentation ma... | AfvanMoopen/cv-leap | segmentation/cityscape_reader.py | cityscape_reader.py | py | 7,052 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "tensorflow.data",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.random.uniform",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "tensorflow.random",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "... |
7804684058 | import networkx as nx
import constants
import geom
import osmnx as ox
from data_source import OpenStreetMap
from .util import approx_trail
class TrailNetwork(object):
"""TrailNetwork
"""
def __init__(
self,
trail_code,
trail_section=None,
trail_alternates=... | nst-guide/data | code/trail/network.py | network.py | py | 3,892 | python | en | code | 6 | github-code | 6 | [
{
"api_name": "constants.TRAIL_EPSG_XW",
"line_number": 38,
"usage_type": "attribute"
},
{
"api_name": "util.approx_trail",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "data_source.OpenStreetMap",
"line_number": 53,
"usage_type": "call"
},
{
"api_name... |
8651590324 | import asyncio
import base64
import binascii
import json
import logging
import socket
import time
from time import sleep
from websockets.server import serve
from websockets import exceptions as ws_exceptions
from .. import ami_conn, ami_parser, node_configs, node_db, ws_broadcaster
__BUILD_ID = "@@HEAD-DEVELOP@@"
log... | AllStarLink/Allmon3 | src/asl_allmon/allmon3_ws_status/__init__.py | __init__.py | py | 6,509 | python | en | code | 7 | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "asyncio.IncompleteReadError",
"line_number": 43,
"usage_type": "attribute"
},
{
"api_name": "websockets.exceptions.ConnectionClosedError",
"line_number": 46,
"usage_type": "attrib... |
19851190008 | from django.shortcuts import render
from django.http import HttpResponse, Http404
from .models import Tweet, Target
# Create your views here.
def index(request):
target_user_list = Target.objects.order_by('-target_name')[:5]
context = {'target_user_list': target_user_list}
return render(request, 'showoff/inde... | RedSquirrelious/nosycolors-v1-command-line | showoff/views.py | views.py | py | 991 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "models.Target.objects.order_by",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "models.Target.objects",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "models.Target",
"line_number": 13,
"usage_type": "name"
},
{
"api_name"... |
20908674803 | #!/usr/bin/python3
import sys
import os
import time
import multiprocessing
import argparse
from datetime import datetime
from datetime import date
from datetime import timedelta
from python_generic_modules import se_docker
from python_hadoop_modules import kafka
from python_hadoop_modules import zookeeper
from python_h... | karthikmahesh2611/docker_hadoop | startup_script.py | startup_script.py | py | 1,926 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "python_hadoop_modules.zookeeper.launch_zookeeper",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "python_hadoop_modules.zookeeper",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "python_hadoop_modules.kafka.launch_kafka",
"line_number": 21... |
70746226748 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# --------------------------------------
# @Time : 2020/11/01
# @Author : Oscar Chen
# @Email : 530824679@qq.com
# @File : test.py
# @Description : test demo for lanenet
# @IDE: PyCharm Community Edition
# --------------------------------------
import os
import t... | 530824679/LaneNet | test.py | test.py | py | 2,488 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "os.path.exists",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "cv2.imread",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_COLOR",
"line_n... |
842017177 | from datetime import date, datetime
import numpy as np
import pandas as pd
import ring
from ....common.client import Client
from ....common.constants import FUTURES
STOCK_CURRENCIES = [
{
"Currency": "EUR",
"RICSuffix": "AS",
},
{
"Currency": "EUR",
"RICSuffix": "BR",
... | webclinic017/data-server | services/backend/app/fetchers/factors/nav/models/forex.py | forex.py | py | 3,078 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "common.client.Client",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "ring.lru",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "common.constants.FUTURES",
"line_number": 58,
"usage_type": "name"
},
{
"api_name": "numpy.NaN",
... |
1705162928 | from pyspark.sql import SparkSession
from pyspark.sql.functions import col, expr,split
# Define a filter_input_data function
def filter_input_data(initial_data):
df_with_split_height = df.withColumn("height", split(col("height"), "-"))
df_with_split_height = df_with_split_height.withColumn("feet", df_wit... | saimanoj1234/sparkoptimization | per_unpre.py | per_unpre.py | py | 1,662 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pyspark.sql.functions.split",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.functions.col",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.functions.col",
"line_number": 11,
"usage_type": "call"
},
{
"api... |
71402508987 | import csv
import datetime
import os
import board
import busio
import adafruit_bme280
import adafruit_ina219
# get timestamp
# will need clock for non network connected device
now = datetime.datetime.now().isoformat()
# get data from BME280
try:
i2c = busio.I2C(board.SCL, board.SDA)
bme280 = adafruit_bme280... | jetolan/weather | get_data.py | get_data.py | py | 1,412 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "datetime.datetime.now",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "busio.I2C",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "board.SCL",
... |
14335858804 | import argparse
import logging
import sys
import vsc
from importlib import import_module
from pygen_src.riscv_instr_pkg import (mtvec_mode_t, f_rounding_mode_t,
riscv_reg_t, privileged_mode_t,
riscv_instr_group_t, data_pattern_t)
@vsc.rando... | merledu/azadi-soc | lowrisc_ibex/vendor/google_riscv-dv/pygen/pygen_src/riscv_instr_gen_config.py | riscv_instr_gen_config.py | py | 24,213 | python | en | code | 16 | github-code | 6 | [
{
"api_name": "vsc.rand_enum_t",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pygen_src.riscv_instr_pkg.data_pattern_t",
"line_number": 20,
"usage_type": "argument"
},
{
"api_name": "importlib.import_module",
"line_number": 25,
"usage_type": "call"
},
{
... |
39145718042 | import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import PretrainedConfig, PreTrainedModel
from flash_attn.modules.mha import MHA
import math
import numpy as np
# globals
num_features = 5
num_periods = 9
num_classes = 64
class CausalConvolution(nn.Module):
def __init__(sel... | mtanghu/Transformer-Trader | trader_models.py | trader_models.py | py | 8,185 | python | en | code | 2 | github-code | 6 | [
{
"api_name": "torch.nn.Module",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 20,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv1d",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_nu... |
41360693627 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sbn
# In[2]:
dataframe= pd.read_excel("merc.xlsx")
# In[3]:
dataframe
# In[4]:
dataframe.describe()
# In[7]:
dataframe.isnull().sum()#NULL OLAN VERİLER KONTROL EDİLM... | mucahitrtn/Python | PythonBtk/CarPriceAnalysis.py | CarPriceAnalysis.py | py | 2,824 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.read_excel",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "seaborn.distplot",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "seaborn.countplot",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "seaborn.scatterp... |
14585784078 | def getFile():
from PySide import QtGui
filters = "Esri ASC (*.asc);;CSV (*.csv);;All files (*.*)"
return QtGui.QFileDialog.getOpenFileName(None, "Open DEM,","",filters)[0]
def openEsri(filename):
grid_space = 1
file = open(filename, "r")
templist = [line.split() for line in file.readlines()]
... | JavierBrana/PVPlant | Utils/importDEM.py | importDEM.py | py | 2,990 | python | en | code | 3 | github-code | 6 | [
{
"api_name": "PySide.QtGui.QFileDialog.getOpenFileName",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "PySide.QtGui.QFileDialog",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "PySide.QtGui",
"line_number": 4,
"usage_type": "name"
},
{
"... |
35864117166 | import dash
from dash.dependencies import Output, Input
import dash_core_components as dcc
import dash_html_components as html
import plotly
import random
import plotly.graph_objs as go
# from collections import deque
import sqlite3
import pandas as pd
app = dash.Dash(__name__)
app.layout = html.Div(
[ html.... | Chris-Valenzuela/Twitter_Sentiment | 10_TwitterInput.py | 10_TwitterInput.py | py | 3,220 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "dash.Dash",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "dash_html_components.Div",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "dash_html_components.H2",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "dash_core_... |
30192270929 | #导入相应的包
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score as accu
train_size = 0.5 #训练集比例
#sigmoid函数
def sigmoid(x):
return 1.0/(1.0+np.exp(-x))
#预测结果函数
def y_hat(x,theta):
r... | TJPU-ML/Homework-for-the-fall-semester-of-2018 | iris classification/李书豪/李书豪.py | 李书豪.py | py | 3,591 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "numpy.exp",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.dot",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.log",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.log",
"line_number": 21,
... |
43897186086 | import pandas as pd
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
df = pd.read_csv("/home/anish/PycharmProjects/asdrp/data/final_data.csv", low_memory=False)
x = df[['Gender', 'Age', 'Ethnicity', 'Location']]
y = df['Income']
poly_fit = PolynomialFeatures(degr... | anishcherukuthota/COVID-Research-ML_Models | ML Models/polynomial_regression.py | polynomial_regression.py | py | 607 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.read_csv",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.PolynomialFeatures",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 13,
"usage_type": "call"
... |
20214506906 | import uuid
from flask import jsonify,request, abort
from .models import Question
from .errors import error400, error404, error422
def get_question(id):
data = Question.query.get(id)
if not data: return abort(404, description='resource not found')
return data
def create_question():
data = request.get... | Ismat27/quiz_learn | flaskr/question.py | question.py | py | 3,036 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "models.Question.query.get",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "models.Question.query",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "models.Question",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "fla... |
8996687733 | """code for generating post-decision biases for demonstration purposes
"""
import os
import sys
import pickle
import numpy as np
from scipy.interpolate import interp1d
sys.path.append('../..')
from src import utils
from src.utils import par
from src.model_ddm.model import DynamicBiasModel
utils.download_dataset("data/... | hyunwoogu/dynamic_bias | src/model_ddm/post_decision_bias.py | post_decision_bias.py | py | 4,045 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sys.path.append",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "src.utils.download_dataset",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "src.utils",
... |
16809364914 | # /usr/local/bin/python
# -*- coding: utf-8 -*-
import json
import logging
import os
import time
from typing import Tuple
import requests
from retry import retry
class CulilException(Exception):
pass
class CulilModule():
def __init__(self, sleep=3):
self.app_key = os.environ["CULIL_API_KEY"]
self.URL_... | sarcastic555/library_reservation | tools/tool_culil.py | tool_culil.py | py | 2,716 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "os.environ",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "time.sleep",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number... |
40776823861 | """
Script to make plots and tables for paper:
1. Comparing results from a single run for four solutions:
numerical, leading-order quasi-static, first-order quasi-static and composite
- Voltages
- Space-dependent variables:
- concentration
... | tinosulzer/faster-lead-acid | plots_for_paper.py | plots_for_paper.py | py | 20,080 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "numpy.where",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "numpy.where",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "src.numerical.Numerical",
"line_number": 52,
"usage_type": "name"
},
{
"api_name": "src.numerical.Numeric... |
39607763203 | import logging
from django.core.management.base import BaseCommand
from core.management.commands import configure_logging
from core import solr_index
configure_logging("index_titles_logging.config", "index_titles.log")
_logger = logging.getLogger(__name__)
class Command(BaseCommand):
help = """
Reindex... | open-oni/open-oni | core/management/commands/index_titles.py | index_titles.py | py | 659 | python | en | code | 43 | github-code | 6 | [
{
"api_name": "core.management.commands.configure_logging",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 12,
"usage_type": "n... |
21417022983 | from django.urls import path, include
from . import views
urlpatterns = [
path('', views.home),
path('home/', views.home),
path('resources/', views.resources),
path('manage/', views.manage),
path('manage/scoreboard/', views.download_scoreboard),
path('manage/firstblood/', views.firstblood, name='firstbl... | asadse7en/fypCTF | home/urls.py | urls.py | py | 587 | python | en | code | 16 | github-code | 6 | [
{
"api_name": "django.urls.path",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
15560680356 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('carte', '0018_auto_20161104_1446'),
]
operations = [
migrations.AddField(
model_name='rate_review',
... | Shashankagarwal181996/carte | carte/migrations/0019_rate_review_user_profile.py | 0019_rate_review_user_profile.py | py | 426 | python | en | code | 1 | github-code | 6 | [
{
"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.AddField",
"line_number": 14,
"usage_type": "call"
},
{
... |
19631530060 | import os
import itertools
import random
import src.utils as foo
from src.graph import Graph
from random import randrange
#lista de entradas en formato .txt para evaluar (se puede ver en la carpeta input)
lista = ["input_1.txt","input_2.txt","input_3.txt","input_4.txt","input_5.txt"]
#variable aleatorea para agarrar ... | CesarJardines/Complejidad- | P02/TSP.py | TSP.py | py | 1,974 | python | es | code | 0 | github-code | 6 | [
{
"api_name": "random.randrange",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "src.utils.creaGrafica",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "src.utils",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "src.utils.get_mst",
... |
20963459348 | from http.client import BAD_REQUEST, OK
from src.core.classes.authentication import AuthenticationBase
from src.core.database.authentication import Authentication
from src.core.database.user_info import UserInfo
class SignOut(AuthenticationBase):
def __init__(self, admin: bool = False):
super().__init__... | ParinovYT/TechnicalSupportCenterProject | src/core/user/authentication/sign_out.py | sign_out.py | py | 1,336 | python | en | code | 2 | github-code | 6 | [
{
"api_name": "src.core.classes.authentication.AuthenticationBase",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "src.core.database.user_info.UserInfo",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "http.client.OK",
"line_number": 28,
"usage_type": ... |
35307499675 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import re
import sys
from typing import Optional, Tuple
import typer
from pydantic import ValidationError
from rich import print
from typing_extensions import Annotated
sys.path.append('..')
from httpfpt.common.yaml_handler import read_yaml
from httpfpt.schemas.case_dat... | wu-clan/httpfpt | httpfpt/cli.py | cli.py | py | 8,939 | python | zh | code | 21 | github-code | 6 | [
{
"api_name": "sys.path.append",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "typer.Typer",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_numbe... |
74918985146 | from collections import defaultdict
import networkx as nx
orbits = defaultdict(lambda: list())
def orbit_count(key):
n_orbits = 0
n_orbits += len(orbits[key])
for subkey in orbits[key]:
if subkey in orbits.keys():
n_orbits += orbit_count(subkey)
return n_orbits
def main():
... | aarroyoc/advent-of-code-2019 | day6/day6.py | day6.py | py | 829 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "collections.defaultdict",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "networkx.from_dict_of_lists",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "networkx.shortest_path_length",
"line_number": 32,
"usage_type": "call"
}
] |
34600648305 | from nltk.corpus import words
import pandas as pd
import numpy as np
# from ..section1.dates import date_sorter
correct_spellings = words.words()
spelling_series = pd.Series(correct_spellings)
def jaccard(entries, grams):
"""
:parameter
:param entries:the words to be corrected
:param grams:the d... | anantsrivastava30/TextMining | section2/spellchecker.py | spellchecker.py | py | 2,757 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "nltk.corpus.words.words",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.words",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "pandas.Series",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
... |
70483524669 | from PyQt5.QtCore import QSize
from PyQt5.QtWidgets import QWidget, QPushButton, QSizePolicy, QVBoxLayout, \
QHBoxLayout, QGridLayout, QLabel, QButtonGroup, QScrollArea
from PyQt5.QtGui import QIcon, QPixmap
class RightWindow(QWidget):
status = False
__width = 300
layout = QVBoxLayout()
qss = "QP... | LeoWei1997/SE_project | UI/RightWindow.py | RightWindow.py | py | 7,006 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtWidgets.QVBoxLayout",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets.QWidget",
"line_number": 33,
"usage_type": "argument"
},
{
"ap... |
40982692140 | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 29 17:15:26 2021
@author: BM109X32G-10GPU-02
"""
# Native imports
from subprocess import Popen
from subprocess import PIPE
from os import remove
import pandas as pd
# rdkit imports
from rdkit import Chem
from rdkit.Chem import Descriptors
def rdkit_descriptors(mol):
""... | JinYSun/DeepDonor | screen/basic.py | basic.py | py | 5,607 | python | en | code | 5 | github-code | 6 | [
{
"api_name": "rdkit.Chem.Descriptors.descList",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "rdkit.Chem.Descriptors",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "rdkit.Chem.MolToSmiles",
"line_number": 58,
"usage_type": "call"
},
{
... |
40188060759 | from random import random
import bcrypt
from django.http import JsonResponse
from django.views.decorators.csrf import csrf_exempt
import json
from rest_api.models import Equipos, Jugadoras, Clasificacion, Usuario
@csrf_exempt
def register(request):
if request.method != 'POST':
return JsonResponse({'erro... | CeciaVarela/trabajo-fin-ciclo | rest/futfem/rest_api/endpoints.py | endpoints.py | py | 5,355 | python | es | code | 0 | github-code | 6 | [
{
"api_name": "django.http.JsonResponse",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "django.http.JsonResponse",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.h... |
29857462838 | from django.shortcuts import render, redirect
from django.http import JsonResponse
from .models import User, File
import datetime, random, _thread, time, copy
import csv,io
import pandas as pd
from .ddqn import wrapper
from .DDPG.baselines import DDPGgive_results
def homepage(request) :
if not request.session.session_... | geekpradd/Reinforcement-Learning-Stock-Trader | WebPortal/StockApp/views.py | views.py | py | 3,764 | python | en | code | 26 | github-code | 6 | [
{
"api_name": "django.shortcuts.render",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "copy.deepcopy",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "DDPG.baselines.... |
28969528737 | import argparse
import logging
import json
import shutil
import time
import os
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
DATA_DIR = os.path.join(os.path.dirname(__file__), 'data')
DEVICES_FILE = os.path.join(DATA_DIR, 'things.json')
def parse_args():
... | wizzdev-pl/embedding_terraform_demo | aws_architecture/manage_thing.py | manage_thing.py | py | 5,119 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "logging.basicConfig",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging.INFO",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_... |
36163645980 | #!/usr/bin/env python
from __future__ import division
from __future__ import print_function
import datetime
import monthdelta
def parse_date(date_str):
return datetime.datetime.strptime(date_str, "%Y-%m-%d")
def unparse_date(date_obj):
return date_obj.strftime("%Y-%m-%d")
class Company(object):
def __ini... | zulip/finbot | money.py | money.py | py | 7,809 | python | en | code | 9 | github-code | 6 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "monthdelta.MonthDelta",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": ... |
20551372866 | from django.shortcuts import render
from django.http import *
from picture.forms import *
from picture.models import Picture
from django.contrib.auth.decorators import login_required
import os
from django.urls import reverse
import time
from urllib.parse import quote
# Create your views here.
@login_require... | Wlhang/document-manage | picture_manage/picture/views.py | views.py | py | 4,881 | python | en | code | 7 | github-code | 6 | [
{
"api_name": "picture.models.Picture.objects.filter",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "picture.models.Picture.objects",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "picture.models.Picture",
"line_number": 17,
"usage_type": "name... |
30545088756 | import pprint, pickle
from sklearn.metrics import mean_squared_error
from math import sqrt
pkl_file = open('/home/bc/Pictures/multi-step-prediction/neuron=10/data.pkl','rb')
data1 = pickle.load(pkl_file)
pprint.pprint(data1)
data2 = pickle.load(pkl_file)
pprint.pprint(data2)
print('rmse:',sqrt(mean_squared_error(dat... | limingwu8/ML | RNN/time_series_prediction/read_pickle.py | read_pickle.py | py | 349 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "pickle.load",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pickle.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number"... |
23245787205 | """
Funcion principal que recibe los datos en un diccionario en Json lo reenvia a la funcion genera_resultado y devuelve
el dataframe para pintar.
"""
import json
from flask import Flask, jsonify, request
import genera_resultado
app = Flask(__name__)
@app.route('/api/', methods=['POST'])
def recibe_datos():
dat... | Morraja/TheBridge-PT-SD-Sept2021 | Bloque 4 - Desarrollo y Storytelling/Ejercicios/Completo ETL/api_datos.py | api_datos.py | py | 463 | python | es | code | 0 | github-code | 6 | [
{
"api_name": "flask.Flask",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "flask.request",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "genera_resultado.rec... |
12719338270 | import collections
Person = collections.namedtuple('Person', ('name', 'age', 'gender'))
ben = Person(name='Ben', age=8, gender='boy')
harper = Person('Harper', age=6, gender='girl')
friends_list = (ben,harper)
for f in friends_list:
print(f.name, "is a", f.age, "year old", f.gender, ".")
KeyPress = collectio... | MGlaab/CP_Access_Key-Mouse | spare_parts/collections_example.py | collections_example.py | py | 939 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "collections.namedtuple",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "p... |
27009247728 | from sklearn.feature_selection import f_classif, chi2, f_regression, SelectKBest
def run(x, y, score_func, k):
if type(k) is str:
if k != 'all':
k = int(k)
estimated = SelectKBest(score_func=get_score_func(score_func), k=k)
x_new = estimated.fit_transform(x, y)
return {"scores_": e... | lisunshine1234/mlp-algorithm-python | feature_engineering/feature_selection/SelectKBest/run.py | run.py | py | 589 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sklearn.feature_selection.SelectKBest",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sklearn.feature_selection.f_classif",
"line_number": 18,
"usage_type": "argument"
},
{
"api_name": "sklearn.feature_selection.f_classif",
"line_number": 15,
"us... |
17940246401 | from keras.models import Sequential
from keras.layers import Dense, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras.optimizers import SGD
from keras.utils import to_categorical
import numpy as np
def cnn_model(train_feature_dir, train_label_dir, test_feature_dir, test_label_dir):
train_feature = ... | jingmouren/antifraud | antifraud/methods/CNN_max.py | CNN_max.py | py | 1,519 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "numpy.load",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.load",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "keras.utils.to_categorical",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.load",
"li... |
31440121652 | from django.contrib import admin
from django.urls import path,include
from . import views
urlpatterns = [
path('',views.Dashboard,name='Dashboard'),
path('Search/',views.Search,name='Search'),
path('DigitalPersonalLoan/',views.Digitalploan,name='Digitalploan'),
path('DigitalBusinessLoan/',views.Digital... | HIRAPARANAYAN/verni-by-s | adminDashboard/urls.py | urls.py | py | 2,580 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "django.urls.path",
... |
37045947084 | """Contains the JobViewSet class with handles post and get http request"""
from django.shortcuts import get_object_or_404
from rest_framework import viewsets
from rest_framework.decorators import api_view
from rest_framework.response import Response
from rest_framework import status
from job_scheduler.models import ... | DKMDebugin/incident-reporting-service | job_scheduler/views/job_view_set.py | job_view_set.py | py | 2,236 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "job_scheduler.models.Job.objects.all",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "job_scheduler.models.Job.objects",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "job_scheduler.models.Job",
"line_number": 33,
"usage_type": "n... |
10543443002 | import json
import os
import sys
from pathlib import Path
from typing import Iterator, List, Optional, Tuple
import numpy as np
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(BASE_DIR)
from benchmark.dataset_config import DatasetConfig
from dataset_reader.base_reader import Bas... | myscale/vector-db-benchmark | dataset_reader/json_reader.py | json_reader.py | py | 3,592 | python | en | code | 13 | github-code | 6 | [
{
"api_name": "os.path.dirname",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path.append",
"line... |
4197601189 | import spacy
import re
import spacy_stanza
from negspacy.termsets import termset
from negspacy.negation import Negex
nlp = spacy.load("en_biobert_ner_symptom")
nlp_sz = spacy_stanza.load_pipeline("en", package="mimic", processors={"ner": "i2b2"})
ts = termset("en_clinical")
ts.add_patterns({
'preceding_negations... | PratikMaitra/Sym_chk | model.py | model.py | py | 1,572 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "spacy.load",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "spacy_stanza.load_pipeline",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "negspacy.termsets.termset",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "re.sub... |
38400052797 | """The Dash app which will display a real-time graph of sentiment scores from
the Reddit comments. It updates live sentiment scores by fetching data from AWS RDS.
"""
import dash
import pandas as pd
import plotly
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
fr... | jeremythai01/Reddit-Sentiment-Analysis-Pipeline | src/services/data_vis/app.py | app.py | py | 1,677 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "utils.warehouse_connection.WarehouseConnection.getInstance",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "utils.warehouse_connection.WarehouseConnection",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "dash.Dash",
"line_number": 19,
... |
35854099541 | import sqlite3,datetime
def sql_start():
try:
global connection,cursor
connection = sqlite3.connect('autopay.db')
cursor = connection.cursor()
response = cursor.execute('''
SELECT * FROM price
''').fetchall()
print(response)
connection.commit()
... | Adelich27/autopay_bot | work_with_db/select.py | select.py | py | 804 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sqlite3.connect",
"line_number": 6,
"usage_type": "call"
}
] |
39628277203 | import copy
import os
import torch
import time
from torch.autograd import Variable
import torch.nn as nn
import torch.optim as optim
import torch.utils.data as data
from tensorboardX import SummaryWriter
import sklearn.metrics
import numpy as np
import torch.backends.cudnn as cudnn
import argparse
import sys
sys.path.... | jleesdev/meshdnns | train_meshnet.py | train_meshnet.py | py | 6,498 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "sys.path.insert",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "sys.path.insert",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_nu... |
23313534857 | import bpy
def drawMenu(self, context):
if context.space_data.tree_type != "SFX_NodeTree": return
layout = self.layout
layout.operator_context = "INVOKE_DEFAULT"
layout.operator('sfx.clock_in', text = 'Clock', icon = "CURVE_NCIRCLE" )
layout.menu("SFX_MT_sensors_menu", text= "Sensors", icon = "I... | wiredworks/wiredworks_winches | ui/SFX_node_menu.py | SFX_node_menu.py | py | 3,300 | python | en | code | 12 | github-code | 6 | [
{
"api_name": "bpy.types",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "bpy.types",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "bpy.types",
"line_number": 34,
"usage_type": "attribute"
},
{
"api_name": "bpy.types",
"line_nu... |
5156623921 | import yaml
DIR = "/config/www/floorplan"
def invert_percent(str, offset = 0):
return "{}%".format(100 - float(str.strip('%')) + offset)
def rotate(element):
if element["type"] == "icon":
element["tap_action"]["navigation_path"] = element["tap_action"]["navigation_path"].replace("180", "90")
... | ericmatte/HomeAutomation | www/floorplan/rotate-floorplan.py | rotate-floorplan.py | py | 1,417 | python | en | code | 7 | github-code | 6 | [
{
"api_name": "yaml.safe_load",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "yaml.dump",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "yaml.dump",
"line_number": 45,
"usage_type": "call"
}
] |
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