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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
14186262586 | import json
from sksurv.functions import StepFunction
from sksurv.linear_model import CoxPHSurvivalAnalysis
from sksurv.metrics import concordance_index_censored
from sksurv.nonparametric import nelson_aalen_estimator, kaplan_meier_estimator
from core.cox_wrapper import CoxFairBaseline
from core.drawing import draw_po... | DanilaEremenko/SurvBeX | main_run_synth_data_explainers.py | main_run_synth_data_explainers.py | py | 10,714 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "numpy.ndarray",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name": "core.cox_generator.CoxGenerator",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 26,
"usage_type": "call"
}... |
34197446896 | #!/bin/python
import sys
import os
import time
import datetime
import hashlib
from os import walk
import mysql.connector
from sys import argv
import json
import boto3
from botocore.exceptions import ClientError
import requests
from requests.exceptions import HTTPError
game_client = argv[1]
target_dir = argv[2]
backof... | vlad-solomai/viam_automation | automation_gambling/deploy_game_client/deploy_game_client.py | deploy_game_client.py | py | 8,482 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "sys.argv",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "sys.argv",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "sys.argv",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "sys.argv",
"line_number": 20,
"usa... |
40696737073 | import asyncio
import importlib
from abc import ABC, abstractmethod
from functools import partial
from typing import Any, Awaitable, Callable, Dict, List, Union
ParamValueT = Union[str, int, float, bool, List[Union[str, int, float, bool]]]
ExecutorFuncT = Callable[[Dict[str, ParamValueT]], Awaitable[Dict[str, Any]]]
... | magma/magma | orc8r/gateway/python/magma/magmad/generic_command/command_executor.py | command_executor.py | py | 2,311 | python | en | code | 1,605 | github-code | 6 | [
{
"api_name": "typing.Union",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number"... |
5759883314 | # -*- coding: utf-8 -*-
"""
Editor de Spyder
Este es un archivo temporal
"""
import numpy as np
import matplotlib.pyplot as plt
from sklearn import svm
#%%
np.random.seed(5)
X = np.r_[np.random.randn(20,2)-[2,2],np.random.randn(20,2)+[2,2]]
Y = [0]*20+[1]*20
plt.scatter(X[:,0],X[:,1],c=Y)
plt.show(... | OscarFlores-IFi/CDINP19 | code/p18.py | p18.py | py | 902 | python | es | code | 0 | github-code | 6 | [
{
"api_name": "numpy.random.seed",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "numpy.r_",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "numpy.random.randn"... |
8927043584 | from collections import OrderedDict
from concurrent import futures
import six
from nose import tools
from tornado import gen
from tornado import testing as tt
import tornado.concurrent
from flowz.artifacts import (ExtantArtifact, DerivedArtifact, ThreadedDerivedArtifact,
WrappedArtifact,... | ethanrowe/flowz | flowz/test/artifacts/artifacts_test.py | artifacts_test.py | py | 8,314 | python | en | code | 2 | github-code | 6 | [
{
"api_name": "tornado.testing.AsyncTestCase",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "tornado.testing",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "collections.OrderedDict",
"line_number": 25,
"usage_type": "call"
},
{
"api_na... |
37588584638 | from sqlalchemy import TypeDecorator
from sqlalchemy.types import VARCHAR
from sqlalchemy import dialects
from sqlalchemy.dialects import postgresql, mysql
import json
from typing import Union, Optional
DialectType = Union[postgresql.UUID, VARCHAR]
ValueType = Optional[Union[dict, str]]
class JSON(TypeDecorator):
... | infrascloudy/gandalf | gandalf/database/json_type.py | json_type.py | py | 1,390 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "typing.Union",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.dialects.postgresql.UUID",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "sqlalchemy.dialects.postgresql",
"line_number": 8,
"usage_type": "name"
},
{
... |
20600597111 | import functools
import os
import google.protobuf.json_format
from synthtool.protos.preconfig_pb2 import Preconfig
PRECONFIG_ENVIRONMENT_VARIABLE = "SYNTHTOOL_PRECONFIG_FILE"
PRECONFIG_HELP = """
A json file containing a description of prefetch sources that this synth.py may
us. See preconfig.proto for detail abou... | googleapis/google-cloud-java | owl-bot-postprocessor/synthtool/preconfig.py | preconfig.py | py | 777 | python | en | code | 1,781 | github-code | 6 | [
{
"api_name": "os.environ.get",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "synthtool.protos.preconfig_pb2.Preconfig",
"line_number": 25,
"usage_type": "call"
},
{
"api_name"... |
4369034891 | # coding: utf-8
import pandas as pd
import xgboost as xgb
from sklearn.preprocessing import LabelEncoder
import numpy as np
train_df = pd.read_csv('../data/train.csv')
test_df = pd.read_csv('../data/test.csv')
# ๅกซๅ
็ฉบๅผ๏ผ็จไธญไฝๆฐๅกซๅ
ๆฐๅผๅ็ฉบๅผ๏ผ็จไผๆฐๅกซๅ
ๅญ็ฌฆๅ็ฉบๅผ
from sklearn.base import TransformerMixin
class DataFrameIm... | Gczaizi/kaggle | Titanic/XGBoost/XGBoost.py | XGBoost.py | py | 1,786 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.base.TransformerMixin",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "pandas.... |
12998412388 | import uuid
from django.db import models
from django.conf import settings
User = settings.AUTH_USER_MODEL
# Create your models here.
class PlanCharge(models.Model):
id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
tier = models.IntegerField()
charge_id = models.CharField(max_len... | kapphire/99typos-server | plan/models.py | models.py | py | 585 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.conf.settings.AUTH_USER_MODEL",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "django.conf.settings",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "django.db.models.Model",
"line_number": 8,
"usage_type": "attribute"
},
... |
42124061830 | import requests
import os
from django.http import HttpResponse
from django.conf import settings
class ProductClient:
global host
def __init__(self):
global host
print("came inside product constructor")
if os.getenv("PRODUCT_HOST") != "":
host = os.getenv("PRODUCT_HOST")
... | Robinrrr10/storeorderui | client/productClient.py | productClient.py | py | 738 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "os.getenv",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.conf.settings.PRODUCT_HOST",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "django.con... |
29778129362 | from flask import Flask, render_template, request, url_for
import y_u_so_stupid as fle
import json
app = Flask(__name__)
correctAnswer = ''
score = 0
highscore = 0
@app.route('/')
def play():
global correctAnswer
q = json.loads(fle.getRandomQuestion())
question = q['question']
choices... | asav13/PRLA-Verk5 | part2/y_u_so_stupid_SERVER.py | y_u_so_stupid_SERVER.py | py | 1,208 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "y_u_so_stupid.getRandomQuestion",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "flask.render_te... |
49613121 | from collections import deque, defaultdict
import random
class RandomizedSet:
def __init__(self):
self.vec = deque()
self.hash_map = defaultdict(int)
def insert(self, val: int) -> bool:
if val in self.hash_map:
return False
self.vec.append(val)
s... | code-cp/leetcode | solutions/380/main.py | main.py | py | 1,102 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "collections.deque",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 35,
"usage_type": "call"
}
] |
3954866418 | # -*- coding: utf-8 -*-
"""view module prilog application
* view function, and run Flask
"""
from glob import glob
from flask import Flask, render_template, request, session, redirect, jsonify
import os
import re
import json
import urllib.parse
import subprocess
import time as tm
import analyze as al
import c... | Neilsaw/PriLog_web | app.py | app.py | py | 21,596 | python | en | code | 30 | github-code | 6 | [
{
"api_name": "configparser.ConfigParser",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "os.mkdir",
... |
75093396986 | from pubnub.callbacks import SubscribeCallback
from pubnub.enums import PNStatusCategory
from pubnub.pnconfiguration import PNConfiguration
from pubnub.pubnub import PubNub
from pprint import pprint
from dotenv import load_dotenv
import os
EVENT_UPLOADED_MESSAGE = "message_uploaded"
load_dotenv()
UUID = os.getenv("... | deibid/radio-azar | my_modules/PubNubClient.py | PubNubClient.py | py | 2,682 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pubnub.pnconfiguration.PNConfiguration",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "p... |
42572073330 | import abc
import collections
from typing import List, Callable, Optional, OrderedDict, Tuple
import pandas as pd
class PreProcessingBase:
def __init__(self,
df: pd.DataFrame,
actions: Optional[OrderedDict[Callable, Tuple]] = None):
self._df = df
self._actions = ... | gilcaspi/COVID-19-Vaccinations | data_processing/preprocessing/pre_processing_base.py | pre_processing_base.py | py | 791 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.DataFrame",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "typing.Optional",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.OrderedDict",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "typing.Calla... |
5500500071 | import time
import base64
from google.cloud import pubsub_v1
from google.oauth2 import service_account
project_id = "<gcp_project_id>"
topic_name = "<topic_name>"
credentials = service_account.Credentials.from_service_account_file("<gcp_Service_account_file_path>")
print(credentials)
publisher = pubsub_v1.PublisherC... | natsu1628/hackathons | ML/GCP-python-ML2/to_pubsub.py | to_pubsub.py | py | 1,772 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "google.oauth2.service_account.Credentials.from_service_account_file",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "google.oauth2.service_account.Credentials",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "google.oauth2.service_account",
... |
7807070088 | import logging
from copy import deepcopy
from itertools import permutations
import numpy as np
from scipy.special import softmax
from scipy.stats import entropy
def true_entropy(team_generator, batch_predict, num_items: int, num_selections: int):
P_A = np.zeros((num_selections, num_items)) # basically P(A^i_j)
... | nianticlabs/metagame-balance | src/metagame_balance/entropy_fns.py | entropy_fns.py | py | 3,539 | python | en | code | 3 | github-code | 6 | [
{
"api_name": "numpy.zeros",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "itertools.permutations",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "scipy.special.softmax",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.zeros"... |
28398915179 | import datetime
import termux
from sync.misc.Config import config
from sync.misc.Logger import logger
class Notification:
__instance__ = None
def __init__(self):
self.sync_all = {}
self.watchers = {}
self.global_status = "Active"
now_date = datetime.datetime.now()
se... | dpjl/termux-sync | sync/misc/Notification.py | Notification.py | py | 3,522 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "datetime.datetime.now",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime.now",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "da... |
11579230306 | import sklearn
import cv2
import pandas as pd
import numpy as np
import math
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_samples, silhouette_score
from collections import Counter
from scipy.spatial import distance_matrix
from scipy.sparse.csgraph import shortest_path
class ImageClassifie... | elraffray/pyImage | imageclassifier.py | imageclassifier.py | py | 6,442 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "cv2.COLOR_BGR2HSV",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "cv2.COLOR_BGR2LAB",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "cv2.COLOR_BGR2HLS",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "... |
24102936874 | from helpers import ReadLines
from typing import Tuple, List
class DayFive(ReadLines):
def __init__(
self, file_path="/home/jonathan/projects/2020-advent-of-code/five/input.txt"
):
super().__init__(file_input=file_path)
self.seat_ids = sorted(
[DayFive.identify_seat(seat_co... | jonodrew/2020-advent-of-code | five/five.py | five.py | py | 1,952 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "helpers.ReadLines",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Tuple",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Tuple",
"line_nu... |
70945120828 | # ํํ์ ๋ถ์
from konlpy.tag import Okt
from docutils.parsers.rst.directives import encoding
okt = Okt()
#result = okt.pos('๊ณ ์ถ ๋ฑ ๋งค์ด์์์ ์ค๋ซ๋์ ๋๋ฌด ๋ง์ด ๋จน์์ ๊ฒฝ์ฐ ์ธ์ง๋ฅ๋ ฅ๊ณผ ๊ธฐ์ต๋ ฅ์ ์ ํ์ํฌ ์ํ์ด ๋๋ค๋ ์ฐ๊ตฌ๊ฒฐ๊ณผ๊ฐ ๋์๋ค.')
#result = okt.morphs('๊ณ ์ถ ๋ฑ ๋งค์ด์์์ ์ค๋ซ๋์ ๋๋ฌด ๋ง์ด ๋จน์์ ๊ฒฝ์ฐ ์ธ์ง๋ฅ๋ ฅ๊ณผ ๊ธฐ์ต๋ ฅ์ ์ ํ์ํฌ ์ํ์ด ๋๋ค๋ ์ฐ๊ตฌ๊ฒฐ๊ณผ๊ฐ ๋์๋ค.')
#result = okt.nouns('๊ณ ์ถ ๋ฑ ๋งค์ด์์์ ์ค๋ซ๋์ ๋... | kangmihee/EX_python | py_morpheme/pack/morp1.py | morp1.py | py | 2,358 | python | ko | code | 0 | github-code | 6 | [
{
"api_name": "konlpy.tag.Okt",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "urllib.parse.quote",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "urllib.parse",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "urllib.request.urlopen"... |
27094908089 | import pandas as pd
import random
from tqdm.auto import tqdm
tqdm.pandas()
import re
from tqdm import tqdm
import numpy as np
import cv2
from albumentations import (
Compose, OneOf, Normalize, Resize, HorizontalFlip, VerticalFlip, Rotate, RandomRotate90, CenterCrop
)
from albumentations.pytorch import ToTensorV... | phelchegs/bms-molecular-translation | InChI/InChI_preprocessing.py | InChI_preprocessing.py | py | 7,948 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "tqdm.auto.tqdm.pandas",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "tqdm.auto.tqdm",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "re.compile",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_... |
36040675316 | import typing
from datetime import datetime, timedelta
import arrow
from ParadoxTrading.Utils.DataStruct import DataStruct
DATETIME_TYPE = typing.Union[str, datetime]
class SplitAbstract:
def __init__(self):
self.cur_bar: DataStruct = None
self.cur_bar_begin_time: DATETIME_TYPE = None
s... | ppaanngggg/ParadoxTrading | ParadoxTrading/Utils/Split.py | Split.py | py | 9,614 | python | en | code | 51 | github-code | 6 | [
{
"api_name": "typing.Union",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "datetime.datetime",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "ParadoxTrading.Utils.DataStruct.DataStruct",
"line_number": 13,
"usage_type": "name"
},
{
"api_... |
70488593467 | import csv
import functools
import json
import math
import random
def cycle_call_parametrized(string_q: int, left_b: int, right_b: int):
def cycle_call(func):
# print(f'LALA')
def wrapper_(*args, **kwargs):
# creating a csv-file:
generate_csv(string_q, left_b, right_b)
... | LocusLontrime/Python | Dive_into_python/HomeWork9/Decorators.py | Decorators.py | py | 1,807 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "csv.reader",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "json.dump",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "csv.writer",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "csv.QUOTE_MINIMAL",
"line_number"... |
39426129134 | ''' Strategy to be backtested. '''
import backtrader as bt
# Create a Stratey
class TestStrategy(bt.Strategy):
''' Base class to be subclassed for user defined strategies. '''
# Moving average parameters
params = (('pfast',2),('pslow',184),)
def __init__(self):
self.dataclose = self.datas[0... | Kyle-sn/PaperStreet | python/backtest/strategy.py | strategy.py | py | 2,714 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "backtrader.Strategy",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "backtrader.indicators.MovingAverageSimple",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "backtrader.indicators",
"line_number": 22,
"usage_type": "attribute"
... |
37612660256 | from django.shortcuts import render
from .models import *
import cv2
import numpy as np
from pytesseract import *
pytesseract.tesseract_cmd="C:/Program Files/Tesseract-OCR/tesseract.exe"
def main(request):
return render(request,'main.html')
def maintest(request):
return render(request,'maintest.html')... | YounngR/Graduation-work | DB/views.py | views.py | py | 1,680 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pytesseract.tesseract_cmd",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "django.shortcuts.render",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 17,
"usage_type": "call"
},
{
"api... |
37585700958 | import tkinter as tk
from tkinter import *
from tkinter import ttk
from tkinter.messagebox import showinfo
import tkinter.font as tkFont
import sqlite3, time, datetime, random
name_of_db = 'inventory_master.db'
my_conn = sqlite3.connect(name_of_db)
cdb = my_conn.cursor()
def create_table():
cdb.exec... | InfoSoftBD/Python | CustomerUpdate.py | CustomerUpdate.py | py | 9,946 | python | en | code | 2 | github-code | 6 | [
{
"api_name": "sqlite3.connect",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "tkinter.Tk",
"line_number": ... |
24829002801 | import pygame
pygame.init()
pygame.display.set_caption("WannabePong")
size = 800, 600
screen = pygame.display.set_mode(size)
width, height = size
speed = [1, 1]
bgc = 255, 255, 255
fontControls = pygame.font.SysFont("monospace", 16)
font = pygame.font.SysFont("monospace", 26)
fontCount = pygame.font.SysFont("monospa... | vsanjorge/localMultiplayerPong | main.py | main.py | py | 3,327 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pygame.init",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "pygame.display.set_caption",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "pygame.display",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "pygame.displa... |
27923745620 | from sklearn.model_selection import train_test_split
from tensorflow.keras.layers import Dense
from keras.utils import np_utils
from tensorflow.keras.models import Sequential
import matplotlib.pyplot as plt
from scipy.io import loadmat
import numpy as np
def display(i):
img = X[i]
plt.title('Example'... | ankitlohiya212/basic-ml-problems | Basic ML problems/Mnist.py | Mnist.py | py | 2,107 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "matplotlib.pyplot.title",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.imshow",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "ma... |
26057428953 | import re
import requests
from bs4 import BeautifulSoup
URL = "https://sourcesup.renater.fr/scm/viewvc.php/rec/2019-CONVECS/REC/"
page = requests.get(URL)
soup = BeautifulSoup(page.content, "html.parser")
for link in soup.find_all('a', href=True):
print(link['href'])
if 'name' in link:
print(link['nam... | philzook58/egglog-rec | scraper.py | scraper.py | py | 711 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "requests.get",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "re.search",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_numbe... |
9224589864 | from prediction.M2I.predictor import M2IPredictor
import numpy as np
import math
import logging
import copy
import random
import time
import interactive_sim.envs.util as utils
import plan.helper as plan_helper
import agents.car as car
S0 = 2
T = 0.25 #1.5 # reaction time when following
DELTA = 4 # the power term in... | Tsinghua-MARS-Lab/InterSim | simulator/plan/env_planner.py | env_planner.py | py | 107,809 | python | en | code | 119 | github-code | 6 | [
{
"api_name": "math.atan2",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "math.sqrt",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "math.atan2",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 56,
... |
14839954104 | from PyQt5 import QtCore, QtGui, QtWidgets, uic
import sys
from AssignmentCategoryDict import AssignmentCategoryDict
from Assignment import Assignment
import uuid
class EditCategories(object):
def __init__(self, course, reload_gradesheet):
col_headers = ['Category Name', 'Drop Count']
self.ECate... | meeksjt/SuperTeacherGradebook499 | src/EditCategories.py | EditCategories.py | py | 5,236 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "PyQt5.QtWidgets.QDialog",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtWidgets",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "PyQt5.uic.loadUi",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "PyQt5.uic",
... |
40327690661 | from pyecharts import options as opts
from typing import Any,Optional
from pyecharts.charts import Radar
import os
import sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from easy_pyechart import constants,baseParams,radar_base_config,round_radar_base_config
class eRadar():
def... | jayz2017/easy_pyechart.py | easy_pyechart/easy_radar.py | easy_radar.py | py | 1,470 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "sys.path.append",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number... |
23775563757 | import flask
import grpc
import search_pb2_grpc as pb2_grpc
import search_pb2 as pb2
import redis
import json
from google.protobuf.json_format import MessageToJson
from flask import request, jsonify
app = flask.Flask(__name__)
app.config["DEBUG"] = True
class SearchClient(object):
"""
Client for... | manfruta/Sistemas-Tarea1 | cliente_app.py | cliente_app.py | py | 1,587 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "flask.Flask",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "grpc.insecure_channel",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "search_pb2_grpc.SearchStub",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "search_p... |
44407917630 | '''
Created on 16/ago/2011
@author: Marco
'''
from reportlab.pdfgen import canvas
from reportlab.lib.units import cm
from math import sqrt
import ModelsCache
import Configuration
class PdfStructure(object):
'''
classdocs
'''
__markerList = []
__modelsCache = ModelsCache.ModelsCache()
@... | mziccard/RuneTagDrawer | PdfStructure.py | PdfStructure.py | py | 3,883 | python | en | code | 3 | github-code | 6 | [
{
"api_name": "ModelsCache.ModelsCache",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "reportlab.pdfgen.canvas.Canvas",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "reportlab.pdfgen.canvas",
"line_number": 32,
"usage_type": "name"
},
{
"ap... |
32802770666 | from elasticsearch import Elasticsearch, helpers
import csv
import json
import time
mvar = "clara"
matching_query = { "query_string": {
"query": mvar
}
}
def main():
#sundesh
es = Elasticsearch(host = "localhost", port = 9200)
#anagn... | d4g10ur0s/InformationRetrieval_21_22 | save_books.py | save_books.py | py | 627 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "csv.DictReader",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "elasticsearch.helpers.bulk",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": ... |
21546390354 | import re
from collections import Counter, defaultdict
from itertools import combinations
from typing import Dict, List, Tuple, Set
import numpy as np
from helper import load_input
def create_input():
'''Extract puzzle input and transform'''
# creates pattern for extracting replcements
pattern = r"(\w+)... | rick-62/advent-of-code | advent_of_code_2015/solutions/day19.py | day19.py | py | 2,647 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "helper.load_input",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "re.findall",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "collections.defaultdict",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "typing.List",
... |
38649682103 | import http
import requests
import telegram
from flask import Blueprint, Response, request
from sqlalchemy_utils import create_database, database_exists
from config import BUILD_NUMBER, DATABASE_URL, REBASE_URL, VERSION
from .bot import dispatcher
from .db import db, test_db
from .utils import log
routes = Blueprin... | andrewscwei/python-telegram-bot-starter-kit | app/routes.py | routes.py | py | 1,370 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "flask.Blueprint",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sqlalchemy_utils.database_exists",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "config.DATABASE_URL",
"line_number": 19,
"usage_type": "argument"
},
{
"api_name... |
16098965612 | from django.urls import path
from card import views
urlpatterns = [
path('create/', views.CreateFlashCardView.as_view(), name="create-flash-card"),
path('update/<id>/', views.UpdateFlashCardView.as_view(), name="update-flash-card"),
path('dalete/<id>/', views.DeleteFlashCardView.as_view(), name="delete-fl... | leonardo0231/flash-card | card/urls.py | urls.py | py | 428 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.urls.path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "card.views.CreateFlashCardView.as_view",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "card.views.CreateFlashCardView",
"line_number": 6,
"usage_type": "attribute"
},
... |
39697340199 | import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits import mplot3d
# plots intensity time series for MDRE model
def plotIntensity ():
# index boundaries for time 3D plot
nStart = 0
nEnd = 10000
with open("time_series.txt", "r") as file:
lines = file.readlines()
time = []
int... | sir-aak/microscopically-derived-rate-equations | plotscripts/mdre_plotscript_intensity_inversion.py | mdre_plotscript_intensity_inversion.py | py | 3,810 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "numpy.array",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": ... |
17324365412 | from motor import motor_asyncio
from .model import Guild
import os
class Database:
def __init__(self, *, letty):
self.letty = letty
self.connection = motor_asyncio.AsyncIOMotorClient(os.environ['DB_URL'])
self.db = db = self.connection[os.environ['DB_NAME']]
self.guild = db.guilds
... | WhyNoLetty/Letty | database/base.py | base.py | py | 890 | python | en | code | 7 | github-code | 6 | [
{
"api_name": "motor.motor_asyncio.AsyncIOMotorClient",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "motor.motor_asyncio",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "os.environ",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name"... |
15152787587 | # -*- coding: utf-8 -*
#่ฏฅ็จๅบ็จไบๆจกๅๆต่ฏ
import os
import torch
import numpy as np
import torch.nn as nn
from evaluation import HKOEvaluation
from ium_data.bj_iterator import BJIterator
if __name__ == "__main__":
#ๆไฝณ็ๆจกๅ
test_model = torch.load('./checkpoints/trained_model_12000.pkl' )
test_model.eval()
... | LiangHe77/UNet_v1 | test.py | test.py | py | 1,817 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "torch.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "ium_data.bj_iterator.BJIterator",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.from_numpy",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.cat... |
29821357591 | import docker
class MicroDockerClient:
def __init__(self, micro_configuration):
self.client = docker.from_env()
self.config = micro_configuration
def pull(self):
self.client.images.pull(self.config.image_name)
def run(self):
self.client.containers.run(
self.confi... | alichamouda/micro-cd | micro_docker_client.py | micro_docker_client.py | py | 713 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "docker.from_env",
"line_number": 5,
"usage_type": "call"
}
] |
13020029275 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import ensemble
def data_accuracy(predictions, real):
"""
Check the accuracy of the estimated prices
"""
# This will be a list, the ith element of this list will be abs(prediction[i] - real[i])/rea... | V1K1NGbg/House-Price-Prediction-Project | testing.py | testing.py | py | 2,216 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "numpy.percentile",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.average",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "sklearn.ensemble.GradientBoostingRegressor",
"line_number": 29,
"usage_type": "call"
},
{
"api_nam... |
34652323206 | # Subgroup enumeration for cyclic, dicyclic, and tricyclic integer groups.
# PM Larsen, 2019
#
# The theory implemented here is described for two-dimensional groups in:
# Representing and counting the subgroups of the group Z_m x Z_n
# Mario Hampejs, Nicki Holighaus, Lรกszlรณ Tรณth, and Christoph Wiesmeyr
# Jo... | pmla/evgraf | evgraf/subgroup_enumeration.py | subgroup_enumeration.py | py | 6,050 | python | en | code | 13 | github-code | 6 | [
{
"api_name": "numpy.diag",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "numpy.arange",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "numpy.prod",
"line_number": 3... |
33225197622 | # -*- coding: utf-8 -*-
""" #+begin_org
* *[Summary]* :: A =CmndLib= for providing currents configuration to CS-s.
#+end_org """
####+BEGIN: b:py3:cs:file/dblockControls :classification "cs-u"
""" #+begin_org
* [[elisp:(org-cycle)][| /Control Parameters Of This File/ |]] :: dblk ctrls classifications=cs-u
#+BEGIN_SRC... | bisos-pip/currents | py3/bisos/currents/currentsConfig.py | currentsConfig.py | py | 33,875 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "typing.Dict",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "typing.Any",
"line_number": 41,
"usage_type": "attribute"
},
{
"api_name": "bisos.b.subProc.WOpW",
"line_number": 116,
"usage_type": "call"
},
{
"api_name": "bisos.b.subPro... |
28153506484 | import json
import numpy as np
def load_json(file_path : str) -> dict:
"""
Loads .json file types.
Use json python library to load a .json file.
Parameters
----------
file_path : string
Path to file.
Returns
-------
json file : dictionary
.json dictionary file.
... | jm1261/PeakFinder | src/fileIO.py | fileIO.py | py | 4,274 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "json.load",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "numpy.genfromtxt",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "numpy.genfromtxt",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "numpy.generic",
"line... |
12858137004 | """
We are given a directed graph. We are given also a set of pairs of vertices.
Find the shortest distance between each pair of vertices or -1 if there is no path connecting them.
On the first line, you will get N, the number of vertices in the graph.
On the second line, you will get P, the number of pairs between whi... | dandr94/Algorithms-with-Python | 04. Minimum-spanning-tree-and-Shortest-path-in-Graph/02. Exercise/01. distance_between_vertices.py | 01. distance_between_vertices.py | py | 2,005 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "typing.Dict",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": ... |
73952557948 | import os
today = '02-06-19_'
import numpy as np
import treecorr
def parse_args():
import argparse
parser = argparse.ArgumentParser(description='Produce Tau correlations, i.e correlation among galaxies and reserved stars')
parser.add_argument('--metacal_cat',
#default='/home2/d... | des-science/Y3_shearcat_tests | alpha-beta-eta-test/code/essentials/taus.py | taus.py | py | 7,792 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path.append",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 55,
"usage_type": "attribute"
},
{
"api_name": "os.path.expandus... |
23525022654 | from matplotlib import pyplot as plt
import numpy as np
import collections
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
# Get cpu or gpu device for training.
device = "cuda" if torch.cuda.is_a... | lewiis252/machine_learning | cifar10_nn.py | cifar10_nn.py | py | 7,791 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "torch.cuda.is_available",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "torchvision.datasets.CIFAR10",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "... |
23048935694 | from sqlalchemy.orm import Session
from .. import models, schemas
from fastapi.encoders import jsonable_encoder
def get_score(db: Session):
score = db.query(models.Score).first()
if not score:
new_score = create_score()
db.add(new_score)
db.commit()
db.refresh(new_score)
... | hooglander/fastapi-get-and-post | app/repository/score.py | score.py | py | 873 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "sqlalchemy.orm.Session",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "fastapi.encoders.jsonable_encoder",
"line_number": 25,
"usage_type": "call"
}
] |
71968698427 | import torch.nn as nn
from collections import OrderedDict
from graph_ter_seg.tools import utils
class EdgeConvolution(nn.Module):
def __init__(self, k, in_features, out_features):
super(EdgeConvolution, self).__init__()
self.k = k
self.conv = nn.Conv2d(
in_features * 2, out_f... | gyshgx868/graph-ter | graph_ter_seg/models/layers.py | layers.py | py | 2,158 | python | en | code | 56 | github-code | 6 | [
{
"api_name": "torch.nn.Module",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
12805757281 | import os
import cv2
import matplotlib.pyplot as plt
import numpy as np
import random
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
Datadirectory = "train\\"
Classes = ["0", "1", "2", "3", "4", "5", "6"]
img_size = 224
training_data = []
counter = 0
def createtrainingset()... | Mudaferkaymak/Detecting-Faces-and-Analyzing-Them-with-Computer-Vision | Detecting-Faces-and-Analyzing-Them-with-Computer-Vision/training_themodel.py | training_themodel.py | py | 1,867 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "os.path.join",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": ... |
21840251334 | """Order views module"""
from django_filters.rest_framework import DjangoFilterBackend
from rest_framework import filters
from rest_framework import status as st
from rest_framework import generics
from rest_framework.renderers import JSONRenderer, BrowsableAPIRenderer
from rest_framework.parsers import JSONParser
from... | GunGalla/order-flow-test | orders/views.py | views.py | py | 2,855 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "rest_framework.generics.ListCreateAPIView",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.generics",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "order_flow.settings.DEBUG",
"line_number": 22,
"usage_type": "name... |
15047866942 | # from __future__ import absolute_import
import torch
import torch.nn as nn
import onnx
from typing import List, Dict, Union, Optional, Tuple, Sequence
import copy
from .util import*
from torch.autograd import Variable
class onnxTorchModel(nn.Module):
def __init__(self,onnx_model: onnx.ModelProto,cfg:dict):
... | diamour/onnxQuanter | onnx_torch_engine/converter.py | converter.py | py | 16,899 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "torch.nn.Module",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "onnx.ModelProto",
"line_number": 11,
"usage_type": "attribute"
}
] |
75188719226 | # ์ด๊ธฐ ๊ฑฐ๋ฆฌ๋ฅผ 1๋ก ์ง์
# ๊ฐ๊น์ด ๊ณณ๋ถํฐ ์ํํ๋ bfs์ด๊ธฐ์ ์ด๋ฏธ ์ต๋จ๊ฑฐ๋ฆฌ๊ฐ ๊ธฐ๋ก๋ ๊ฒฝ์ฐ์๋ ๊ฑฐ๋ฆฌ๊ฐ ๊ฐฑ์ ๋์ง ์๋๋ก ์ค์
from collections import deque
def bfs(x, y):
# ํ ๊ตฌํ์ ์ํด deque ๋ผ์ด๋ธ๋ฌ๋ฆฌ ์ฌ์ฉ
queue = deque()
# ์ด๊ธฐ ์ขํ ์ค์
queue.append((x, y))
# ํ๊ฐ ๋น ๋๊น์ง ๋ฐ๋ณต
while queue:
x, y = queue.popleft()
# ํ์ฌ ์์น์์ 4๊ฐ์ง ๋ฐฉํฅ์ผ๋ก ์์น ํ์ธ
... | zacinthepark/Problem-Solving-Notes | na/02/DFS-BFS/๋ฏธ๋กํ์ถ.py | ๋ฏธ๋กํ์ถ.py | py | 1,348 | python | ko | code | 0 | github-code | 6 | [
{
"api_name": "collections.deque",
"line_number": 8,
"usage_type": "call"
}
] |
41152326339 | from tkinter import *
from datetime import datetime, timedelta
import tkinter as tk
from tkinter import Entry, Label, StringVar, ttk, Checkbutton, Button, messagebox
import numpy as np
import pandas as pd
def generarCodigo(texto):
sumar = 0
codigo = texto[:3]
if texto[len(texto) // 2] == " ":
suma... | Moisesmp75/TkinterForms | Trabajo2/Biblioteca.py | Biblioteca.py | py | 23,516 | python | es | code | 0 | github-code | 6 | [
{
"api_name": "tkinter.ttk.Frame",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "tkinter.ttk",
"line_number": 44,
"usage_type": "name"
},
{
"api_name": "tkinter.Entry",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "tkinter.Entry",
"line... |
15362206849 | from generator import Generator
from discriminator import Discriminator
from speaker_encoder import SPEncoder
import torch
import torch.nn.functional as F
import os
from os.path import join, basename, exists
import time
import datetime
import numpy as np
from tqdm import tqdm
import numpy as np
import copy
class Solve... | Mortyzhou-Shef-BIT/DYGANVC | solver.py | solver.py | py | 12,824 | python | en | code | null | github-code | 6 | [
{
"api_name": "torch.device",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "torch.cuda.is_available",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "torch.cuda",
"line_number": 52,
"usage_type": "attribute"
},
{
"api_name": "torch.optim.Adam... |
17536523132 | import pystan
import stan_utility
import matplotlib
import matplotlib.pyplot as plot
##################################################
##### Simulate data and write to file
##################################################
model = stan_utility.compile_model('gen_data.stan')
fit = model.sampling(seed=194838, algorit... | MiyainNYC/Rose | stan/wimlds/1/lin_regr.py | lin_regr.py | py | 3,574 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "stan_utility.compile_model",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pystan.stan_rdump",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pystan.read_rdump",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "stan_u... |
16351053586 | from bs4 import BeautifulSoup as bs
import requests
from cardBeta import CardBeta
from cardWitj import CardWitj
urls = {
'beta':
'https://beta.gouv.fr/recrutement/developpement?',
'witj':
'https://www.welcometothejungle.com/fr/companies/communaute-beta-gouv/jobs'
}
divs = {'beta': 'fr-card__body', 'wi... | apimobi/witj-beta-replit | crawler.py | crawler.py | py | 1,963 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "requests.get",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "cardWitj.CardWitj",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "cardBeta.CardBeta",
... |
25070502975 | import pydoc
import logging
from typing import Generic, Type, Optional, Union, TypeVar, Any, NamedTuple
from django.db import models
from django.conf import settings
from django.forms.models import model_to_dict
from rest_framework import serializers
logger = logging.getLogger(__name__)
T = TypeVar("T")
class Abstra... | danh91/purplship | server/modules/core/purplship/server/serializers/abstract.py | abstract.py | py | 8,956 | python | en | code | null | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "typing.TypeVar",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "typing.NamedTuple",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"l... |
5769042811 | import hashlib
import json
import os
import pathlib
import shutil
import subprocess
from typing import Mapping, Any, List
class RunException(Exception):
pass
class ExecuteException(Exception):
pass
class style:
reset = 0
bold = 1
dim = 2
italic = 3
underline = 4
blink = 5
rblink =... | Abdullahjavednesar/lpython | compiler_tester/tester.py | tester.py | py | 9,744 | python | en | code | null | github-code | 6 | [
{
"api_name": "hashlib.sha224",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "os.path.basename",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 52,
"usage_type": "attribute"
},
{
"api_name": "os.path.splitext",
"... |
14956977226 | import argparse
import os
from scipy.interpolate import griddata
import numpy as np
from tqdm import tqdm
import cv2
import scipy.ndimage as sp
import matplotlib.pyplot as plt
from matplotlib import cm, patches
# Argument Parser
parser = argparse.ArgumentParser(description="Time-series Heatmap Generator")
parser.add_a... | raghavauppuluri13/robot-palpation | rpal/scripts/visualize_heatmap.py | visualize_heatmap.py | py | 2,568 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "numpy.loadtxt",
... |
26113397145 | __authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "08/09/2017"
import weakref
from silx.gui import qt
from silx.gui.icons import getQIcon
from .. import actions
class ViewpointToolButton(qt.QToolButton):
"""A toolbutton with a drop-down list of ways to reset the viewpoint.
:param parent: See :cl... | silx-kit/silx | src/silx/gui/plot3d/tools/ViewpointTools.py | ViewpointTools.py | py | 1,903 | python | en | code | 106 | github-code | 6 | [
{
"api_name": "silx.gui.qt.QToolButton",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "silx.gui.qt",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "silx.gui.qt.QMenu",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "silx.gui.q... |
31108358568 | import tushare as ts
import pandas as pd
#ๅฝๅๅคชๅคๆถ๏ผๆพ็คบไธๆข่ก
pd.set_option('expand_frame_repr',False)
#ๆพ็คบๆๆ็ๅ
pd.set_option('display.max_columns', None)
'''
Created on 2020ๅนด12ๆ24ๆฅ
@author: My
'''
ts.set_token('b869861b624139897d87db589b6782ca0313e0e9378b2dd73a4baff5')
pro=ts.pro_api()
#data = pro.stock_basic(exchange=''... | geekzhp/zhpLiangHua | tmp/tushareStudy.py | tushareStudy.py | py | 1,356 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.set_option",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pandas.set_option",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "tushare.set_token",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tushare.pro_api",... |
41969655941 | import cv2 as cv
src = cv.imread("./img_input/266679.png") #่ฏปๅๅพ็
# ๆฐๅปบไธไธช็ชๅฃๅนถๅฑ็คบ
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)
cv.waitKey(0)
cv.destroyAllWindows()
print("hello") | RMVision/study-opencv | chapter01/test.py | test.py | py | 237 | python | zh | code | 1 | github-code | 6 | [
{
"api_name": "cv2.imread",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "cv2.namedWindow",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.WINDOW_AUTOSIZE",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "cv2.imshow",
"li... |
3709328599 | import os
from cloudservice import add_file, add_dir, get_dir_subs, get_root_dir_id
from pathlib import Path
import pandas as pd
def test():
uploadfile(os.path.join('ๆๆไปถๅคน', 'test1.docx'), dirid=39, projid=36)
print()
def create_dir_test():
add_dir('addsub', 39, 36)
def uploadfile(fpath, dirid, projid)... | pengyang486868/PY-read-Document | batch_upload.py | batch_upload.py | py | 3,549 | python | en | code | 0 | 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": "cloudservice.add_dir",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.path.split",
"lin... |
75226774588 | import logging
from kiteconnect import KiteConnect
import datetime
import pymongo
instrument_token = "738561"
from_date = "2021-04-01"
to_date = "2021-06-30"
interval = '5minute'
logging.basicConfig(level=logging.DEBUG)
api_key = "kpgos7e4vbsaam5x"
api_secret = "t9092opsldr1huxk1bgopmitovurftto"
reque... | prashanth470/trading | source/sample.py | sample.py | py | 1,284 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "logging.basicConfig",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "kiteconnect.KiteConnect",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "pymong... |
10958770997 | import os
import csv
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from torch.utils.data import Dataset, DataLoader
from torchvision.io import read_image
import torchvision.datasets as datasets
import torchvision.transforms as transforms
from torchvision.io import rea... | K-kiron/animal-detect | Helpers/AWA2_Dataloader.py | AWA2_Dataloader.py | py | 7,864 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "numpy.random.seed",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line... |
23850509915 | from datasets import load_dataset,load_metric
from transformers import AutoTokenizer,AutoModelForSeq2SeqLM,Seq2SeqTrainingArguments,DataCollatorForSeq2Seq,Seq2SeqTrainer
import numpy as np
metric=load_metric("BLEU.py")
max_input_length = 64
max_target_length = 64
src_lang = "zh"
tag_lang = "en"
model_path = "... | Scpjoker/NLP-Course-Homework-2022 | translate.py | translate.py | py | 2,866 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "datasets.load_metric",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "numpy.where",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "numpy.count_nonzero",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "numpy.mean",
... |
20463208050 | from collections import defaultdict
d = defaultdict(int)
n = int(input())
for _ in range(n):
d[input()] += 1
allwords = list(d)
allwords_str = d.values()
listofx = []
for x in allwords_str:
listofx.append(str(x))
print(len(allwords))
print(" ".join(listofx))
# This line is the same as the above block > print(... | Ronen-EDH/Code-exercises | Python/Hackerrank/Hackrank_wordorder.py | Hackrank_wordorder.py | py | 361 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "collections.defaultdict",
"line_number": 2,
"usage_type": "call"
}
] |
24150027900 | from fastapi import FastAPI, APIRouter,status, Request
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates
from fastapi.responses import HTMLResponse
from services.connectionHobolink import Connection
from routers import login
app=FastAPI(title="WeatherStation")
#routers
app.inc... | AlvaroCoder/WeatherStation | main.py | main.py | py | 1,214 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "routers.login.router",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "routers.login",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "fastapi.static... |
73400221629 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/... | PolarisXQ/Polaris-NoteBook | source/conf.py | conf.py | py | 1,924 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "recommonmark.parser.CommonMarkParser",
"line_number": 62,
"usage_type": "name"
}
] |
34572128931 | import random,server,time,istatistik,settings
import sqlite3 as sql
server_list=server.Server()
patlayan_power=6.5;kartopu_power=7;oyuk_power=2
_35power=10;_25power=9;_15power=5
def randomplayer():
global first,two
while True:
first=random.choice(server_list)
two=random.choice(server_li... | zeminkat/Game | savas.py | savas.py | py | 11,157 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "server.Server",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "random.choice",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "random.choice",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_n... |
40070373372 | import boto3
import json
from tqdm import tqdm
dynamodb = boto3.resource('dynamodb',region_name='us-east-2')
table = dynamodb.Table('FSBP_tree')
print(table.creation_date_time)
'''
with open('/hdd/c3s/data/aws_data/breach_compilation-pw_tree_1000000.json') as f:
data = json.load(f)
with table.batch_writer() as bat... | lucy7li/compromised-credential-checking | perfomance_simulations/fsbp/save_amazon.py | save_amazon.py | py | 793 | python | en | code | 6 | github-code | 6 | [
{
"api_name": "boto3.resource",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 22,
"usage_type": "call"
}
] |
33381013184 | from django.contrib import admin
from django.contrib.staticfiles.urls import staticfiles_urlpatterns
from django.urls import path, include
from django.contrib.auth import views as auth_views
from polls.views import (
RegistrationView,
CreateBoardView,
BoardDetailView,
BoardDeleteView,
CreateList... | destinymalone/projectmanagement-capstone | mysite/urls.py | urls.py | py | 1,486 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.urls.path",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.contrib.admin.site",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "... |
2665829226 | from heatSink import HeatSink
from waterPipes import WaterPipes
from solarPanel import SolarPanel
from system import System
import matplotlib.pyplot as plt
flow_rates = [0.00025, 0.0005, 0.001, 0.002, 0.003, 0.005]
panel_temp = []
no_pipes = []
inlet_temp = 30
for f in flow_rates:
temps = []
pipes = []
f... | southwelljake/HeatSinkModelling | src/comparePipes.py | comparePipes.py | py | 1,260 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "heatSink.HeatSink",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "solarPanel.SolarPanel",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "waterPipes.WaterPipes",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "system.... |
12483812629 | import numpy as np
import matplotlib.pyplot as plt
from scipy.constants import degree
from FallingCat import FallingCat
JI = 0.25
alpha = 30*degree
plt.figure(figsize=(5,7))
c = FallingCat(JI, alpha)
t = c.theta/degree
psi = c.lean()/degree
gamma = c.bend()/degree
phi = c.twist()/degree
print(phi[-1])
print((c.alpha... | tt-nakamura/cat | fig2.py | fig2.py | py | 660 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "scipy.constants.degree",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "Fallin... |
26664284885 | import json
import logging
import os
from http.client import HTTPConnection
from pathlib import Path
from typing import Dict, Any
from mmcc_framework import DictCallback, Framework
from mmcc_framework.nlu_adapters import NluAdapter
from tuning.mmcc_config.callbacks import my_callbacks
from tuning.types import Pipelin... | DEIB-GECO/DSBot | DSBot/tuning/mmcc_integration.py | mmcc_integration.py | py | 4,842 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pathlib.Path",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_nu... |
1904177195 | from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
import json, os
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=['*'],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get('/contents/{page_id}/{content_id}')
a... | tetla/knowledge-reader | backend/offdemy-api.py | offdemy-api.py | py | 1,203 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "fastapi.middleware.cors.CORSMiddleware",
"line_number": 8,
"usage_type": "argument"
},
{
"api_name": "os.path.exists",
"line_number": 20,
"usage_type": "call"
},
{
"api_name"... |
25814131906 | import errno
from flask import current_app, request, render_template
from flask.views import MethodView
from werkzeug.exceptions import Forbidden, NotFound
from ..constants import COMPLETE, FILENAME, LOCKED, TYPE
from ..utils.date_funcs import delete_if_lifetime_over
from ..utils.http import redirect_next_referrer
fr... | bepasty/bepasty-server | src/bepasty/views/modify.py | modify.py | py | 1,929 | python | en | code | 162 | github-code | 6 | [
{
"api_name": "flask.views.MethodView",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "flask.render_template",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "constants.FILENAME",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "utils... |
40155982512 | # -*- coding: utf-8 -*-
"""
This module contains functions for losses of various types: soiling, mismatch,
snow cover, etc.
"""
import numpy as np
import pandas as pd
from pvlib.tools import cosd
def soiling_hsu(rainfall, cleaning_threshold, tilt, pm2_5, pm10,
depo_veloc={'2_5': 0.004, '10': 0.0009},... | Samuel-psa/pvlib-python | pvlib/losses.py | losses.py | py | 2,997 | python | en | code | null | github-code | 6 | [
{
"api_name": "pandas.Timedelta",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "numpy.maximum",
"line_number": 73,
"usage_type": "call"
},
{
"api_name": "pvlib.tools.cosd",
"line_number": 74,
"usage_type": "call"
},
{
"api_name": "numpy.cumsum",
"l... |
34248836732 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
plt.style.use("bmh")
def exact(r1, r2, w):
return 2 * np.sqrt(w/np.pi) * np.exp(- w * (r1 * r1 + r2 * r2))
def fmt(x, pos):
a, b = '{:.1e}'.format(x).split('e')
b = int(b)
return r'${} \times 10^{{{}}}$'.format(... | evenmn/Master-thesis | scripts/plot_exact_tb.py | plot_exact_tb.py | py | 1,391 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 5,
"usage_type": "name"
},
{
"api_name"... |
70398650747 | """utilities for generation of CTRMs
Author: Keisuke Okumura
Affiliation: TokyoTech & OSX
"""
from __future__ import annotations
import numpy as np
from numba import f8, jit
from ..environment import Instance
from ..roadmap import TimedNode, TimedRoadmap
from ..roadmap.utils import valid_move
@jit(f8[:](f8[:, :], ... | omron-sinicx/ctrm | src/ctrm/roadmap_learned/utils.py | utils.py | py | 5,210 | python | en | code | 21 | github-code | 6 | [
{
"api_name": "numpy.ndarray",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "numpy.sum",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numba.jit",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numba.f8",
"line_number": ... |
28663549378 | # Please develop your ingestion service in Python. You may select the delivery format (e.g., Jupyter
# Notebook, containerized microservice). For this exercise, you may assume that a scheduling service
# to regularly invoke your ingestion is provided.
# Where and how you process the data is at your discretion.
import ... | madelinepet/take_home_assignment | assignment.py | assignment.py | py | 7,586 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "os.mkdir",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "os.mkdir",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "mappings.event_root_codes",
"line_number": 34,
"usage_type": "argument"
},
{
"api_name": "mappings.event_base_c... |
24168209609 | #!/usr/bin/env python
'''
summarise slurm job details
Usage: summarise.py --files slurm-*.log > summary.tsv
Time is in hours.
Memory is in GB.
'''
#(venv_somatic_2) spartan-login1 18:48:20 msi-evaluation$ sacct -j 18860471 --format="JobName,CPUTime,MaxRSS,Elapsed,MaxVMSize,Timelimit"
# JobName CPUTime ... | supernifty/slurm_util | summarise.py | summarise.py | py | 2,901 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "logging.warn",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "logging.info",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "sys.stdout.write",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "sys.stdout",
"line_num... |
22682272557 | # -*- coding: utf-8 -*-
"""
Created on Wed May 12 04:34:12 2021
@author: Zakaria
"""
import pandas as pd
data = pd.read_csv('prediction_de_fraud_2.csv')
caracteristiques = data.drop('isFraud', axis=1).values
cible = data['isFraud'].values
from sklearn.preprocessing import LabelEncoder
LabEncdr_X... | Baxx95/6-10-Programmes-Data-Science-SL-Random_Forest_Classifier | Random_Forest_Classifier.py | Random_Forest_Classifier.py | py | 961 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.LabelEncoder",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "sklearn.model_selection.train_test_split",
"line_number": 26,
"usage_type": "call"
}... |
29186498876 | import numpy
import multiprocessing as mp
import scipy.fftpack as fft
import scipy.signal as signal
import h5py
from .utilities import working_dir
from .stationbandpass import lofar_station_subband_bandpass
def fir_filter_coefficients(num_chan, num_taps, cal_factor=1./50.0):
'''
Compute FIR filter coefficient... | brentjens/software-correlator | softwarecorrelator/stationprocessing.py | stationprocessing.py | py | 11,844 | python | en | code | 4 | github-code | 6 | [
{
"api_name": "scipy.signal.firwin",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "scipy.signal",
"line_number": 39,
"usage_type": "name"
},
{
"api_name": "numpy.arange",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line... |
7796988085 | import xml.dom.minidom
import string;
import logging;
def LoadSession(system, FileName):
Logger = logging.getLogger("PPLT");
Logger.debug("Try to load Session from %s"%FileName);
doc = xml.dom.minidom.parse(FileName);
dev_tag = doc.getElementsByTagName("Devices")[0];
sym_tag = doc.getElementsByTag... | BackupTheBerlios/pplt-svn | PPLT/PPLT/LoadSession.py | LoadSession.py | py | 2,939 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "logging.getLogger",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "xml.dom.minidom.dom.minidom.parse",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "xml.dom.minidom.dom",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_nam... |
13610828545 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import taggit.managers
class Migration(migrations.Migration):
dependencies = [
('taggit', '0001_initial'),
('learn', '0003_project_photo'),
]
operations = [
migrations.Create... | klebercode/sofia | sofia/apps/learn/migrations/0004_auto_20141215_1723.py | 0004_auto_20141215_1723.py | py | 1,769 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "django.db.migrations.Migration",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "django.db.migrations",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "django.db.migrations.CreateModel",
"line_number": 16,
"usage_type": "call"
},
... |
38474579179 | import argparse
import regex as re
from pathlib import Path
from textwrap import dedent
import yaml
from .validator import run_sigma_validator
from clint.textui import colored, puts
import logging
STANDARD_YAML_PATH = Path(__file__).resolve().parent.parent / Path('CCCS_SIGMA.yml')
SIGMA_FILENAME_REGEX = r'(\.yaml|\.ym... | CybercentreCanada/pysigma | pysigma/validator_cli.py | validator_cli.py | py | 13,374 | python | en | code | 7 | github-code | 6 | [
{
"api_name": "pathlib.Path",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "regex.compile",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "logging.getLogger",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser"... |
8677677831 | import xarray as xr
import xesmf as xe
import pandas as pd
import datetime
import os
first_date = '2021-01-01'
last_date = '2022-12-31'
lonmin,lonmax = 360-90,360-69
latmin,latmax = -40,-15
variables = [
'surf_el',
'water_temp',
'salinity',
'water_u',
'water_v']
renamedict = {'surf_el':'zos',
... | lucasglasner/DOWNLOADSCRIPTS | HYCOM/download_hycom_hindcast.py | download_hycom_hindcast.py | py | 2,754 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "xarray.open_dataset",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "pandas.Timedelta",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "pandas.to_datetime",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "pandas.date_r... |
21645750883 | #Tutorial de Umbral OpenCV
import cv2
import numpy as np
img = cv2.imread('Pagina.jpg')
#Imagen a escala de grises
grayscaled = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
#Umbral de 10
retval, threshold = cv2.threshold(img, 12, 255, cv2.THRESH_BINARY)
#Umbral en escala de grises
retval, threshold2 = cv2.threshold(grayscale... | Deniry/Practicas_OpenCV | Practica5.py | Practica5.py | py | 666 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "cv2.imread",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.cvtColor",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "cv2.threshold",
"lin... |
38785952057 | import cv2 as cv
import sys
img = cv.imread("Photos/cat_large.jpg")
print(img.shape)
cv.imshow("Cat", img)
def rescale(frame, scale=0.75):
width = frame.shape[1] * scale
height = frame.shape[0] * scale
dimensions = (int(width), int(height))
new_frame = cv.resize(frame, dimensions, interpolation=cv.... | adamferencz/opencv-course-ghb | rescale.py | rescale.py | py | 446 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "cv2.imread",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.resize",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "cv2.INTER_AREA",
"line_number": 15... |
1922022592 | from sklearn import preprocessing
import pandas as pd
import numpy as np
import pickle
data_path = './data/STT.csv'
window = 15
def normalize(df):
min_max_scaler = preprocessing.MinMaxScaler()
df['open'] = min_max_scaler.fit_transform(df.open.values.reshape(-1, 1))
df['close'] = min_max_scaler.fit_transf... | sinlin0908/ML_course | hw4/prepro.py | prepro.py | py | 1,925 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "sklearn.preprocessing.MinMaxScaler",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "numpy.array",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "... |
41584679238 | # ์๋์ฐ์์๋ ํ๊ธ ์ธ์ฝ๋ฉ ์ค๋ฅ๊ฐ ๋ฐ์ํ ์ ์์ต๋๋ค.
# ํ๊ธ ์ธ์ฝ๋ฉ ์ค๋ฅ๊ฐ ๋ฐ์ํ๋ค๋ฉด
# Message.log(message_type="info", msg="๋ฐ์ดํฐ๋ฅผ ์ ์ฅํ์ต๋๋ค.")
# ์์ ์ฝ๋ ๋ถ๋ถ์ msg๋ฅผ ์์ด๋ก ์์ ํด์ ์ฌ์ฉํด์ฃผ์ธ์.
import json
import sys
from eliot import Message, start_action, to_file, write_traceback
import requests
# ๋ก๊ทธ ์ถ๋ ฅ์ ํ์ค ์ถ๋ ฅ์ผ๋ก ์ค์ (ํฐ๋ฏธ๋์ ์ถ๋ ฅํ๊ธฐ)
to_file(sys.stdout)
# ํฌ๋กค๋ง ๋์... | JSJeong-me/2021-K-Digital-Training | Web_Crawling/python-crawler/chapter_5/sample_eliot.py | sample_eliot.py | py | 1,833 | python | ko | code | 7 | github-code | 6 | [
{
"api_name": "eliot.to_file",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "sys.stdout",
"line_number": 13,
"usage_type": "attribute"
},
{
"api_name": "eliot.start_action",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "eliot.start_action",... |
23748260373 | import os
import sys
from functools import partial
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
from toolBar import ToolBar
from Canvas.canvas import Canvas
import cv2
import numpy as np
from grab_cut import Grab_cut
from choiceDiaGen import ChoiceDiaGen
from choiceDiaStyle imp... | kisstherain8677/Image_generate | app.py | app.py | py | 19,181 | python | en | code | 3 | github-code | 6 | [
{
"api_name": "toolBar.ToolBar",
"line_number": 48,
"usage_type": "call"
},
{
"api_name": "zoomWidget.ZoomWidget",
"line_number": 137,
"usage_type": "call"
},
{
"api_name": "Canvas.canvas.Canvas",
"line_number": 139,
"usage_type": "call"
},
{
"api_name": "functool... |
24916898593 | import time
from datetime import datetime
from bluepy.btle import BTLEDisconnectError
from miband import miband
from ibmcloudant.cloudant_v1 import CloudantV1
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
from ibmcloudant.cloudant_v1 import CloudantV1, Document
import os
from dotenv import load_dotenv
... | Rushour0/MSIT-The-New-Normal-Submission | WebVersions/web_v1/cloudant-module.py | cloudant-module.py | py | 2,911 | python | en | code | 1 | github-code | 6 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.getenv",
"line_number":... |
19218028573 | from rest_framework import serializers
from api.v1.auth.schemas import LanguageChoiceField, TimeZoneNameChoiceField
from users.models import User
class CurrentUserOutputSchema(serializers.ModelSerializer):
language_code = LanguageChoiceField()
time_zone = TimeZoneNameChoiceField()
class Meta:
mo... | plathanus-tech/django_boilerplate | src/api/v1/users/schemas.py | schemas.py | py | 591 | python | en | code | 2 | github-code | 6 | [
{
"api_name": "rest_framework.serializers.ModelSerializer",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "rest_framework.serializers",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "api.v1.auth.schemas.LanguageChoiceField",
"line_number": 8,
"usa... |
42156059489 | import pytest
import responses
from repositories.app import APP
@pytest.fixture
def client():
with APP.test_client() as client:
APP.extensions["cache"].clear()
yield client
@responses.activate
def test_get_repo(client):
url = f"https://api.github.com/repos/owner/repo"
response = {
... | lukaszmenc/get-repository-data | tests/test_app.py | test_app.py | py | 1,667 | python | en | code | 0 | github-code | 6 | [
{
"api_name": "repositories.app.APP.test_client",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "repositories.app.APP",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "repositories.app.APP.extensions",
"line_number": 10,
"usage_type": "attribute"
},
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.