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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6227495516 | #Dependencies
"""
!pip install -U sklearn
!pip install pmdarima
!pip install river
!pip install tslearn
!pip install arch
!pip install skorch
"""
#Imports
import json
import math
import calendar
from datetime import timedelta
from datetime import datetime as dt
import numpy as np
import pandas as pd
import warnings... | amarabuco/codrift | codrift3.py | codrift3.py | py | 60,743 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "warnings.simplefilter",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "seaborn.set_theme",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "logging.basicConfig",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "logging.W... |
35947650994 | # -*- coding: utf-8 -*-
import os
import csv
import ast
from itertools import islice
import matplotlib.pyplot as plt
from sklearn import preprocessing
import numpy
"""
This script is plotting all of bad sample data
"""
if __name__ == '__main__':
root=os.getcwd()
bsxs=["bs1","bs2","bs3","bs4","bs5","bs6","bs... | s-okugawa/HDNNP-tools | tools/bad-sample/plot-allbs.py | plot-allbs.py | py | 1,785 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.getcwd",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "csv.reader",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
... |
38069299722 | import os
import glob
import shutil
import re
import gi
gi.require_version('Limba', '1.0')
gi.require_version('AppStream', '1.0')
from gi.repository import Limba
from gi.repository import AppStream
from hashlib import sha256
from ..utils import build_cpt_path
from ..repository.models import *
from ..user import User
f... | limbahq/limba-hub | lihub/maintain/ipkimport.py | ipkimport.py | py | 6,824 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "gi.require_version",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "gi.require_version",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "gi.repository.AppStream.Metadata",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "... |
5310216277 | from collections import deque
from typing import List, Tuple
def shortest_distance(maze: List[List[int]], src: Tuple[int, int], dest: Tuple[int, int]) -> int:
row = len(maze)
col = len(maze[0])
visited = [[False for i in range(col)] for j in range(row)]
distance = [[float('inf') for i in range(col)] f... | Sourolio10/Leetcode-Practice | Graph/Shortest_distance/shortest_dist_in_matrix_using_djitras_queue.py | shortest_dist_in_matrix_using_djitras_queue.py | py | 1,376 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.List",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "typing.Tuple",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "collections.deque",
"line_number": 13,
"usage_type": "call"
}
] |
16954723069 | # Link For Problem: https://leetcode.com/problems/longest-increasing-path-in-a-matrix/
import functools
class Solution:
"""
DFS + Memoization Approach.
TC : O(n)
SC : O(n)
"""
def longestIncreasingPath(self, matrix: list[list[int]]) -> int:
R, C = len(matrix), len(matr... | loopclub2022/MonthLongChallenge | Anurag_19_CSE/Python/day19.py | day19.py | py | 857 | python | en | code | 9 | github-code | 1 | [
{
"api_name": "functools.lru_cache",
"line_number": 30,
"usage_type": "call"
}
] |
1585593679 | from typing import Optional
from decimal import Decimal
from validator_collection import validators
from highcharts_core import errors
from highcharts_core.metaclasses import HighchartsMeta
from highcharts_core.utility_classes.gradients import Gradient
from highcharts_core.utility_classes.patterns import Pattern
cl... | highcharts-for-python/highcharts-core | highcharts_core/options/axes/data_classes.py | data_classes.py | py | 3,874 | python | en | code | 40 | github-code | 1 | [
{
"api_name": "highcharts_core.metaclasses.HighchartsMeta",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "highcharts_core.utility_classes.gradients.Gradient",
"line_number": 27,
"usage... |
6584194716 | from typing import Dict, Optional, Tuple, TYPE_CHECKING
from UM.Logger import Logger
from UM.Version import Version
from cura.Backups.Backup import Backup
if TYPE_CHECKING:
from cura.CuraApplication import CuraApplication
class BackupsManager:
"""
The BackupsManager is responsible for managing the creat... | Ultimaker/Cura | cura/Backups/BackupsManager.py | BackupsManager.py | py | 3,130 | python | en | code | 5,387 | github-code | 1 | [
{
"api_name": "typing.TYPE_CHECKING",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "cura.Backups.Backup.Backup",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "typing.Tuple",
"line_number": 22,
"usage_type": "name"
},
{
"api_name": "typing.Op... |
30644851301 | from ..math_basics import is_RealIntervalFieldElement # type: ignore
from ..exceptions import InsufficientPrecisionError # type: ignore
from typing import Sequence
__all__ = ['floor_as_intergers', 'SpatialDict']
def floor_as_integers(x) -> Sequence[int]:
"""
Computes floor of a number or interval, returning ... | ekim1919/SnapPy | python/drilling/spatial_dict.py | spatial_dict.py | py | 3,952 | python | en | code | null | github-code | 1 | [
{
"api_name": "math_basics.is_RealIntervalFieldElement",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "exceptions.InsufficientPrecisionError",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "typing.Sequence",
"line_number": 8,
"usage_type": "name"
... |
20068242046 | from tkinter import Tk, Label, Button, Entry, Text, messagebox
from os import environ
from source.email import Email
from dotenv import load_dotenv
#se crea la ventana
venatana = Tk()
#se pone el titulo, color y tamaño de la ventana
venatana.title("Semana 12")
venatana.geometry("500x400")
venatana.config(bg="#5F6A6... | DanCastSV/S12 | S12/main.py | main.py | py | 1,511 | python | es | code | 0 | github-code | 1 | [
{
"api_name": "tkinter.Tk",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "tkinter.Label",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "tkinter.Label",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tkinter.Entry",
"line_numbe... |
73740570595 | # Face Recognition/Identification
import cv2 as cv
import face_recognition as fr
import os
# training data
knownFaces = [
{
"file": "JoeBiden.jpg",
"name": "Joe Biden",
"code": None,
},
{
"file": "FumioKishida.jpg",
"name": "Fumio Kishida",
"code": None,
... | smstong/ai | ai012.py | ai012.py | py | 2,130 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "face_recognition.load_image_file",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "face_recognition.face_locations",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "face_recognition.face_encodings",
"line_number": 35,
"usage_type": "call... |
33397514940 | import numpy as np
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import os
os.environ['KMP_DUPLICATE_LIB_OK'] = 'TRUE'
startPoint = 5
state1 = np.loadtxt('1.0_2.0_state')[:,0].reshape(1,201,1)
encoder_input1 = state1[:,:startPoint,:]
decoder_input1 = state1[:,startPoint:-1,:]
output1 = state1[:,s... | Bonbon-Tang/DL-for-dynamical-systems | MSSPartial/noiseFree/Train_RNNS2.py | Train_RNNS2.py | py | 5,234 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "numpy.loadtxt",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_... |
15103185485 | import calendar
import pandas as pd
import numpy as np
def remove_high_corr(df,target='Israelis_Count',threshold=0.5):
'''
return dataframe without corrlation that can be drop.
args:
df = dataframe
target = string of the target
threshold = default 0.5
'''
target_col = df.pop(target)
df.insert(len(... | LiavCohn/nature-reserves-paper | function.py | function.py | py | 11,566 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.triu",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.bool",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot.cla",
"li... |
39473584807 | import numpy as np
from keras.models import load_model
test_images = np.load("mnist_test_images.npy")
test_labels = np.load("mnist_test_labels.npy")
network = load_model("mnist_model.h5")
# Evaluate the model
print("Evaluating...")
test_loss, test_acc = network.evaluate(test_images, test_labels)
print()
print("Test ... | byelipk/deep-mnist | mnist_eval.py | mnist_eval.py | py | 373 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.load",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.load",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "keras.models.load_model",
"line_number": 7,
"usage_type": "call"
}
] |
15143059359 | #!/usr/bin/env python
# coding: utf-8
# # COURSE: Master statistics and machine learning: Intuition, Math, code
# ##### COURSE URL: udemy.com/course/statsml_x/?couponCode=202006
# ## SECTION: The t-test family
# ### VIDEO: Mann-Whitney U test
# #### TEACHER: Mike X Cohen, sincxpress.com
# In[ ]:
# import libraries... | mikexcohen/Statistics_course | Python/ttest/stats_ttest_MannWhitneyU.py | stats_ttest_MannWhitneyU.py | py | 900 | python | en | code | 18 | github-code | 1 | [
{
"api_name": "numpy.random.poisson",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 28,
"usage_type": "attribute"
},
{
"api_name": "numpy.random.poisson",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.ran... |
70599120354 | from dask.distributed import Client
import dask.dataframe as dd
from fastapi import FastAPI
client = Client()
app = FastAPI()
# Import data
opioids_data = dd.read_csv(
"/Users/lorna/Documents/MIDS 2022/First Semester/720 Practicing Data Science/dask/arcos_2011_2012.tsv",
sep="\t",
usecols=["BUYER_STATE","... | lornamariak/dask-api | app/main.py | main.py | py | 2,589 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "dask.distributed.Client",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "fastapi.FastAPI",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "dask.dataframe.read_csv",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "dask.dat... |
19752788443 | import tempfile
import os
import torch
from kaner.common import save_text, save_json
from kaner.adapter.tokenizer.char import CharTokenizer
def test_chartokenizer():
"""Test the class `CharTokenizer`."""
tokens = ["[UNK]", "[PAD]", "南", "京", "市", "长", "江", "大", "桥"]
token_embeddings = [
[0.0, 0.0]... | knowledgeresearch/kaner | tests/adapter/tokenizer/test_char.py | test_char.py | py | 1,483 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "tempfile.TemporaryDirectory",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "kaner.common.save_text",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "torch.save",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "torch.t... |
1041291189 | import logging.config
import logging.handlers
def set_logging(project_name, logging_path='mylog.log'):
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(project_name)
logger.setLevel(logging.DEBUG)
filehandler = logging.handlers.TimedRot... | Maxsparrow/StatMouse2 | statmouse/logger.py | logger.py | py | 700 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.config.Formatter",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "logging.config",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "logging.config.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "logging... |
35911465282 | import torch
from torch.nn.utils.rnn import pad_sequence
class Translator:
def __init__(self, model, dataset):
self.model = model
self.dataset = dataset
def translate(self, src_strs, device="cuda"):
src_field, trg_field = self.dataset.src, self.dataset.trg
src_v... | r-gould/transformer | src/translator.py | translator.py | py | 2,422 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "torch.tensor",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "torch.int64",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "torch.nn.utils.rnn.pad_sequence",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "torch.o... |
27783022168 | import pandas as pd
from pathlib import Path
from configs import Config, configs
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelEncoder
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.utils import to_categorical
from typing import Unio... | ClementJu/kaggle-novozymes-enzyme-stability-prediction | src/data_preparation/dataset.py | dataset.py | py | 5,745 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "typing.Union",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_numbe... |
20275942333 | import openpyxl
wb = openpyxl.load_workbook('NUMBER_PLATE_LIST (Autosaved)1.xlsx')
ws=wb.active
count=0
i=0
first=ws['C']
second=ws['D']
a=[]
for(cell,cell_1) in zip(first,second):
if str(cell.value) == str(cell_1.value).split()[-1]:
count=count+1
if str(cell.value) != str(cell_1.value).split()[-1]:
... | drishtiramesh/Python_Scripts | Extract_Wrong_Detections.py | Extract_Wrong_Detections.py | py | 647 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "openpyxl.load_workbook",
"line_number": 2,
"usage_type": "call"
}
] |
1498623289 | #!/usr/bin/env python3
# dpw@Darryls-iMac.localdomain
# 2023-03-10 21:45:37
#
# @see https://schedule.readthedocs.io/
import threading
import time
import schedule
# no input args; with args, use functools.partial to define
def job():
print(
f"working at {time.time()} on thread {threading.current_thread... | darrylwest/python-play | concurrency/run-at.py | run-at.py | py | 588 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "time.time",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "threading.current_thread",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "threading.Thread",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "schedule.every",
... |
25015396838 | from typing import Optional, List, Dict
from src.db_models import LabelGroup, LabelFormat, FieldScope, CalculatedField, Driver, DriverChange
from src.data_models import LabelFormatApi, LabelFormatApiList
from src.data_models import CalculatedFieldApi, CalculatedFieldApiList
from src.data_models import DriverApi, Drive... | krezac/tesla-race-analyzer | src/backup.py | backup.py | py | 6,723 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "typing.Optional",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "src.db_models.FieldScope",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "src.db_models.FieldScope.query.filter_by",
"line_number": 13,
"usage_type": "call"
},
{
... |
10541671700 | from collections import deque
# 각 노드가 연결된 정보를 표현(2차원 리스트)
n, m = map(int, input().split(' '))
graph = [[] for _ in range(n+1)]
for i in range(m):
a,b = map(int,input().split(' '))
graph[a].append(b) # 서로 마주하기 때문에 해당 인덱스의 리스트에 값을 추가한다.
graph[b].append(a)
#print(graph)
def bfs(start) :
#... | Lee-han-seok/Solving_Algorithm_SQL | 백준/Silver/1389. 케빈 베이컨의 6단계 법칙/케빈 베이컨의 6단계 법칙.py | 케빈 베이컨의 6단계 법칙.py | py | 1,220 | python | ko | code | 0 | github-code | 1 | [
{
"api_name": "collections.deque",
"line_number": 16,
"usage_type": "call"
}
] |
25015394148 | from flask import url_for, flash, Markup, redirect, Response
from flask_admin import expose
from flask_jwt_extended import create_access_token
import pendulum
from src.admin.admin_forms import TestLabelFormatForm, TestCalculatedFieldForm, DriverChangeForm, \
ConfigRestoreForm, ConfigBackupForm, GenerateJwtTokenFor... | krezac/tesla-race-analyzer | src/admin/admin_views.py | admin_views.py | py | 13,674 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "src.parent_views.MyRoleRequiredCustomView",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "src.admin.admin_forms.TestCalculatedFieldForm",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "src.db_models.FieldScope.query.all",
"line_number": 2... |
32894121704 | import os
from PyQt5.QtCore import QObject,pyqtSignal,pyqtSlot
import pyautogui
from time import sleep
class Worker(QObject):
'Object managing the simulation'
finished = pyqtSignal()
sbMessage = pyqtSignal(list)
def __init__(self):
super(Worker, self).__init__()
def control(self,acti... | konexis/Automate | worker.py | worker.py | py | 8,191 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "PyQt5.QtCore.QObject",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "PyQt5.QtCore.pyqtSignal",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "py... |
39309134173 | import tornado.ioloop
import tornado.web
import requests
import argparse
class MainHandler(tornado.web.RequestHandler):
def get(self, slug):
url = "http://osu.ppy.sh/api/{}?".format(slug)
# Build URL with all get params
for i in self.request.arguments:
url += "{}={}&".format(i, self.get_argument(i))
# Re... | osuripple/osuapiproxy | osuapiproxy.py | osuapiproxy.py | py | 1,617 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "tornado.ioloop.web",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "tornado.ioloop",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "tornado.ioloop.web"... |
5812455236 | '''
Bitwise operations done on the files
'''
import cv2
import numpy as np
img1 = np.zeros((250, 500, 3),np.uint8)
img1 = cv2.rectangle(img1, (200,0), (300, 100), (255,255,255), -1)
img2 = np.zeros((250, 500, 3),np.uint8)
img2 = cv2.rectangle(img2, (0, 0), (250, 250), (255,255,255), -1)
cv2.imshow('image... | Utkichaps/opencv-tutorial-practice | g.bitwise_ops.py | g.bitwise_ops.py | py | 598 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.zeros",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "cv2.rectangle",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "numpy.zeros",
"line_numbe... |
8765523962 | #!/usr/bin/env python
__author__ = 'MidnightInAPythonWorld'
# Check for Python3
import sys
if sys.version_info[0] != 3:
print("[-] This script requires Python 3")
print("[-] Exiting script")
exit()
# stdlib
import json,os,requests,argparse
# Check for Pandas
try:
import pandas as pd
except:
print... | MidnightInAPythonWorld/API-GreyNoise | api_grey_noise_gnql.py | api_grey_noise_gnql.py | py | 2,808 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.version_info",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "requests.get",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 56,
"usage_type": "call"
},
{
"api_name": "os.path.isfile",
... |
13430467993 | """ Usage:
Start the flask server by running:
$ python tests/test_map_flask.py
And then head to http://127.0.0.1:5000/ in your browser to see the map displayed
"""
import base64
from flask import Flask
import folium
from folium import IFrame
from mongoengine import connect
from PhotoManagement.db ... | ydethe/photomanagement | tests/test_map_flask.py | test_map_flask.py | py | 2,130 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "PhotoManagement.db.Address.objects",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "PhotoManagement.db.Address",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "base64.b64encode",
"line_number": 50,
"usage_type": "call"
},
{
"ap... |
15592539446 | #!/usr/bin/env python
import sys
import string
import xml.dom.minidom
class NamedElement:
def __init__(self, xml_element):
name_element = xml_element.getElementsByTagName('name')[0]
self.name = name_element.firstChild.data.strip()
class DocumentedElement:
def __init__(self, xml_element):
doc_element = xml_ele... | niahoo/exmms2 | priv/genipc/genipc.py | genipc.py | py | 5,278 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "xml.dom.minidom.dom.minidom.parse",
"line_number": 171,
"usage_type": "call"
},
{
"api_name": "xml.dom.minidom.dom",
"line_number": 171,
"usage_type": "attribute"
},
{
"api_name": "xml.dom.minidom",
"line_number": 171,
"usage_type": "name"
}
] |
12476247076 | from keras.models import load_model
import keras
import numpy as np
from keras import backend as K
from sklearn.metrics import accuracy_score
import sys
import tensorflow as tf
tf.compat.v1.disable_eager_execution()
def cal_adversis_epsilon(data,gradient,epsilon):
adversaries=data + epsilon * np.sign(g... | Suraj-Jha1508/Deep_Learning_CS677 | assignment_10/test.py | test.py | py | 1,919 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "tensorflow.compat.v1.disable_eager_execution",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "tensorflow.compat",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "numpy.sign",
"line_number": 13,
"usage_type": "call"
},
{
"api_... |
23003384613 | #!/usr/bin/python
# -*- coding: utf-8 -*-
'''
Created on Feb 20, 2013
@author: Maribel Acosta
@author: Fabian Floeck
@author: Michael Ruster
'''
from mw.xml_dump import Iterator as mwIterator
from mw.xml_dump.functions import EXTENSIONS as mwExtensions
from mw.xml_dump.functions import open_file
from functions.print... | 0nse/WikiWho | WikiWho.py | WikiWho.py | py | 5,085 | python | en | code | null | github-code | 1 | [
{
"api_name": "os.path.isdir",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "os.listdir",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "mw.xml_dump.functions.EXTENSION... |
22817131703 | # -*- coding: utf-8 -*-
# @Author: Jeremiah
# @Date: 2017-05-26 23:27:33
# @Last Modified by: jemarks
# @Last Modified time: 2017-05-31 20:13:15
#This file exists in order to provider some basic objects for SRs, SPs, Stores, and backstop reports.
import datetime
import os
import pandas
import collections
from p... | jeremiahmarks/vcde | backstop_automation/backstop_objects.py | backstop_objects.py | py | 3,841 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "collections.namedtuple",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.strptime",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 58,
"usage_type": "attribute"
},
{
"api_name... |
12889471327 | import numpy as np
import torch
from torch.utils.data.dataloader import DataLoader
from torchvision import transforms
from functions import*
import os
'''
bbvi without Rao_Blackwellization and Control Variates
'''
num_epochs=1
batchSize=500
num_S=5#训练的采样数量
dim=1000000+1
eta=0.05#步长
num_St=100#测试的采样数量
interval=20
#读取数据... | allenzhangzju/Black_Box_Variational_Inference | bbvi_criteo4000000/bbvi_basic.py | bbvi_basic.py | py | 2,620 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "numpy.linspace",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torch.utils.data.dataloader.DataLoader",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "torch.zeros",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "tor... |
40365228173 | #encoding=utf-8
import sktensor
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import sys
import os
import scipy.io as scio
import numpy as np
np.seterr(divide='ignore', invalid='ignore')
from random import random
from scipy.sparse import rand as sprand
from compt_methods import *
from road_sim... | qiushye/ITS_217 | tensor_cpt.py | tensor_cpt.py | py | 21,683 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "matplotlib.use",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "numpy.seterr",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "scipy.io.loadmat",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "scipy.io",
"line_numb... |
3415780911 | import os
from reportlab.pdfgen import canvas
from reportlab.lib.utils import ImageReader
def img2pdf(filepath):
name = filepath + '.pdf'
raw_file = os.listdir(filepath)
''' get img file'''
img_list = []
for i in raw_file:
end = i.split('.')[-1]
if end in ['jpg','jpeg','pn... | ll104567/image2pdf | image2pdf.py | image2pdf.py | py | 792 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.listdir",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "reportlab.pdfgen.canvas.Canvas",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "reportlab.pdfgen.canvas",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "repo... |
73742107553 | # detect jolly jumpers
import sys
from functools import reduce
def is_jolly(nums):
if len(nums) == 1:
return True
# else check the diffs
mask = [False for x in range(len(nums))]
mask[0] = True # the zero diff does not count
i = 0
j = 1
while j < len(nums):
diff = abs(nums[j... | DylanMeeus/CompetitiveProgramming3 | UVa/chapter2/10038.py | 10038.py | py | 863 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "functools.reduce",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_number": 28,
"usage_type": "attribute"
}
] |
75205683873 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
files_to_database.py
Create a database with all files in selected directory
"""
import os
import sys
import sqlite3
from pathlib import Path
import hashlib
class Database:
def __init__(self, name):
self.conn = sqlite3.connect(name)
self.cur = self.... | thejoltjoker/python | files/files_to_database.py | files_to_database.py | py | 1,842 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sqlite3.connect",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "hashlib.md5",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number"... |
32738209475 | import argparse
from colorama import init
from .common import Fore, Messages, Path
from .. import Havok
def parse_args():
parser = argparse.ArgumentParser(
description="Compare Havok packfiles.\nAlso works between Wii U and Switch packfiles."
)
parser.add_argument(
"hkFiles", type=Path, ... | krenyy/botw_havok | botw_havok/cli/hk_compare.py | hk_compare.py | py | 1,257 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "common.Path",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "colorama.init",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "common.Messages.loa... |
29783814673 | #!/usr/bin/env python
from StringIO import StringIO
import pycurl
# The BeautifulSoup module
from bs4 import BeautifulSoup
import lxml
import argparse
url = 'http://kotaku.com/'
storage = StringIO()
storage = StringIO()
c = pycurl.Curl()
c.setopt(c.URL, url)
c.setopt(c.WRITEFUNCTION, storage.write)
# again setting hea... | jmgamboa/Scrapers | ScrapeStringio.py | ScrapeStringio.py | py | 791 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "StringIO.StringIO",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "StringIO.StringIO",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pycurl.Curl",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
... |
42776218853 | import numpy as np
import plotly.graph_objs as go
alpha = 0.01
length = 1 # length of the kernel
a = 1
t = 1 # time for modeling
h = 1e-2 # x-axis step of the mesh
tau = 1e-2 # time step of the mesh
M = int(length / h) + 1 # amount of x-axis nodes of the mesh : 11 now
y = np.array([]) # array with y(n, i) values... | lehakofficial/HARD_KERNEL | Gauss_method.py | Gauss_method.py | py | 2,789 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.array",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.linspace",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.append",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "numpy.vstack",
"line_numb... |
18544973064 | #!/usr/bin/env python3
import os
import secrets
import sqlite3
from flask import Flask
from flask import Response
from flask import jsonify
from flask import redirect
from flask import render_template
from flask import request
from flask import url_for
app = Flask(__name__)
app.config["API_URL"] = os.environ.get("AP... | Varbin/historisch-gewachsen.de | app.py | app.py | py | 2,185 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.environ.get",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "sqlite3.connect",
"lin... |
33622872466 | # coding:utf-8
import requests
from lxml import html
import os
import datetime
from multiprocessing.dummy import Pool as ThreadPool
import multiprocessing
import re
from multiprocessing import Pool
def header(referer):
headers = {
'Host': 'i.meizitu.net',
'Pragma': 'no-cache',
'Accept-Enco... | liuyongliu/liuyong_code | 妹子图爬取.py | 妹子图爬取.py | py | 3,570 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "lxml.html.fromstring",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "lxml.html",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "lxml.html.fromstring",
... |
40759539134 | import json
import pickle
import random
from os.path import join, dirname
import nltk
from random import shuffle
from string import punctuation
from sklearn.feature_extraction import DictVectorizer
from sklearn.pipeline import Pipeline
from sklearn.svm import LinearSVC
from JarbasModelZoo.features import extract_word... | OpenJarbas/ModelZoo | train/postag/sklearn_macmorpho_udep_svm.py | sklearn_macmorpho_udep_svm.py | py | 3,791 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "nltk.download",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "string.punctuation",
"line_number": 86,
"usage_type": "name"
},
{
"api_name": "nltk.corpus.mac_morpho.tagged_sents",
"line_number": 90,
"usage_type": "call"
},
{
"api_name": "... |
20255221258 | import os
from collections import namedtuple
from pathlib import Path
import string
import random
from PIL import Image
from PIL.ImageFile import ImageFile
from werkzeug.utils import secure_filename
from configuration import SoccerConfig
Chunk = namedtuple("Chunk", "path url")
STORAGE_PATH = Path(SoccerConfig.STORA... | IsnandaZain/bola-app | soccer/libs/file.py | file.py | py | 2,953 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "collections.namedtuple",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "configuration.SoccerConfig.STORAGE_PATH",
"line_number": 15,
"usage_type": "attribute"
},
{
"... |
29489219323 | import math
from typing import Callable
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
def GetInterval(start:int,end:int,step:float, fn:Callable[[float],float]) -> dict[str,list[int]]:
x = np.linspace(start,end,math.ceil((end-start)/step))
my_dict = {"X":[],"Y":[]}
for i in x:
... | Grinduim/Bosch-2022.2 | Bosch/Revisão Python - Queila/Arquivos Prova/untitled1.py | untitled1.py | py | 806 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "typing.Callable",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "numpy.linspace",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "math.ceil",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.subplots",
... |
15651178657 | # -*- coding: utf-8 -*-
import multiprocessing
import os
def do_this(what):
whoami(what)
def whoami(what):
print("进程 %s 说： %s" % (os.getpid(), what))
if __name__ == '__main__':
whoami('我是主程序')
for n in range(4):
p = multiprocessing.Process(target=do_this, args=("我是 #%s 进程" % n,))
... | ivix-me/note-introducing-python | ch10/1003/100302/mp.py | mp.py | py | 357 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.getpid",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "multiprocessing.Process",
"line_number": 19,
"usage_type": "call"
}
] |
33764436406 | '''
using :keyword:`with` statement
'''
from easyprocess import EasyProcess
from pyvirtualdisplay.smartdisplay import SmartDisplay
if __name__ == "__main__":
with SmartDisplay(visible=0, bgcolor='black') as disp:
with EasyProcess('xmessage hello'):
img = disp.waitgrab()
img.show()... | tawfiqul-islam/RM_DeepRL | venv/lib/python3.6/site-packages/pyvirtualdisplay/examples/screenshot3.py | screenshot3.py | py | 321 | python | en | code | 12 | github-code | 1 | [
{
"api_name": "pyvirtualdisplay.smartdisplay.SmartDisplay",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "easyprocess.EasyProcess",
"line_number": 9,
"usage_type": "call"
}
] |
42233449488 | from http import HTTPStatus
from django.test import TestCase
from konekt.forms import CandidateForm, EducationFormset, ExperienceFormset, SkillsFormset
class TestForms(TestCase):
def test_candidate_form(self):
form = CandidateForm({
'name': 'Pierre Dupont',
'job': 'DevOps',
... | sebabert/Konekt-pub | konekt/konekt/tests.py | tests.py | py | 2,701 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.test.TestCase",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "konekt.forms.CandidateForm",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "konekt.forms.EducationFormset",
"line_number": 43,
"usage_type": "argument"
},
{
"... |
23030254845 | from django.db import models
from django.contrib.auth.models import AbstractUser
from django.utils.translation import gettext_lazy as _
# Create your models here.
def user_avatar_path(user, filename: str):
return 'avatar/user_{0}/{1}'.format(user.username, filename)
def user_thumbnail_path(user, filename: str):... | blueglasses1995/VideoRecomApp | users/models.py | models.py | py | 1,341 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "django.contrib.auth.models.AbstractUser",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "django.db.models.EmailField",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "django.db.models",
"line_number": 16,
"usage_type": "name"
},
{
... |
9919923837 | import logging
import json
from flask import request, jsonify;
from codeitsuisse import app;
logger = logging.getLogger(__name__)
@app.route('/encryption', methods=['POST'])
def encrypt():
data = request.get_json();
logging.info("data sent for evaluation {}".format(data))
result = []
f... | hlx1024/pythondemo25th | codeitsuisse/routes/secret_message.py | secret_message.py | py | 1,023 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "logging.getLogger",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "flask.request",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "logging.info",
... |
72919674913 | from django.urls import path, include
from . import views
urlpatterns = [
path('', views.IndexView.as_view()),
path('alumno/', views.AlumnoView.as_view(),name='alumnos'),
path('alumno/<int:alumno_id>', views.AlumnoDetailView.as_view()),
path('alumno_horario/', views.Alumno_HorarioView.as_view()), # Co... | aaronbarra040998/avanve-proy03 | Avance API ALumnos/lab13/api/urls.py | urls.py | py | 434 | python | en | code | 0 | github-code | 1 | [
{
"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",
... |
73799501155 | #Data analaysis using Instagram
from IPython.display import Image
from IPython.display import display
from InstagramAPI import InstagramAPI
username="krisha_mehta"
InstagramAPI = InstagramAPI(username,"prideandprejudice")
InstagramAPI.login()
InstagramAPI.getProfileData()
result = InstagramAPI.LastJson
#print(result)... | krishamehta/InstagramAnalysis | instagram.py | instagram.py | py | 1,145 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "InstagramAPI.InstagramAPI",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "InstagramAPI.InstagramAPI.login",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "InstagramAPI.InstagramAPI",
"line_number": 8,
"usage_type": "name"
},
{
"... |
29710262008 | from datetime import datetime
from db import db
class BookCopieModel(db.Model):
__tablename__ = 'book_copie'
id = db.Column(db.Integer, primary_key=True)
contribution_date = db.Column(
db.DateTime(timezone=True), default=datetime.utcnow)
book_id = contributor_user_id = db.Column(db.Integer,... | rezid/api-rest | models/book_copie.py | book_copie.py | py | 1,339 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "db.db.Model",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "db.db",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "db.db.Column",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "db.db",
"line_number": 8,
"u... |
8077731236 | import json
def get_historique_user(user):
# Load existing user data from the file (if any)
try:
with open('users.json', 'r') as f:
users = json.load(f)
except FileNotFoundError:
users = []
# Search for the user in the list
for u in users:
if u['user... | RadouaneElarfaoui/BankSystem | get_history.py | get_history.py | py | 724 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "json.load",
"line_number": 7,
"usage_type": "call"
}
] |
18558221401 | """
Implementation of a language predictor based on a transformer architecture
by the wonderful OpenNMT team at Harvard.
SOURCE: OpenNMT: Open-Source Toolkit for Neural Machine Translation
AUTHORS: Guillaume Klein
Yoon Kim
Yuntian Deng
Jean Senellart
Alexander M. Rush
EDITORS: Lu... | nonas-hunter/adventure-generator | transformer.py | transformer.py | py | 23,533 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "torch.nn.Module",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "torch.tensor",
"line_number": 103,
"usage_type": "call"
},
{
"api_name": "torch.tensor",
"line_... |
26465804587 | ##### Sales Prediction with Linear Regression
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
pd.set_option("display.float_format", lambda x: "%.2f" % x)
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_absolute_error, mean_squared_error
... | seymagkts/machine_learning | Module_4/linear_reg_exercises.py | linear_reg_exercises.py | py | 5,376 | python | tr | code | 0 | github-code | 1 | [
{
"api_name": "pandas.set_option",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 27,
"usage_type": "call"
},
{
"api_name":... |
9348809940 | from flask import Flask, request, jsonify, make_response
from functools import lru_cache
import json
app = Flask(__name__)
"""
comma_separtaed_params_to_list splits string when comma occurs and append splitted tokens to a list
input_str: input string
Returns: a list of tokens separated by commas
"""
def comma_separ... | johnlgtmchung/flask_api_practice | app.py | app.py | py | 3,142 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "flask.make_response",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "flask.jsonify",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_nu... |
2957910804 | #!/usr/bin/python3
import sys
from q import run, run_text
if len(sys.argv) == 1:
while True:
text = input('> ')
if text == 'exit': break
print(run_text(text))
elif len(sys.argv) == 2:
run(sys.argv[1])
else:
print('Usage: q [file]') | nirvanasupermind/qlang | build/lib/cli.py | cli.py | py | 277 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.argv",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "q.run_text",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "q.run",
"line_number": 13,
... |
6055001780 | import glob
import os
import json
import re
import tqdm
import pickle
import pandas as pd
import arguments as args
files = glob.glob(os.path.join(args.scopes_dir, '*.scopes.json'))
os.makedirs(args.cooc_dir, exist_ok=True)
def str_normalize(value):
return re.sub(r'\s+', ' ', value).lower()
def get_item_string_by... | ewoij/cooccurrences-graph | 02_build_cooccurrences.py | 02_build_cooccurrences.py | py | 2,271 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "glob.glob",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "arguments.scopes_dir",
"line_... |
12826388315 | import numpy as np
import h5py as hp
import sys
first = sys.argv[1]
second = sys.argv[2]
third= sys.argv[3]
fourth = sys.argv[4]
process = sys.argv[5]
grid = (2048,2048,2048)
def get_mass(path):
try:
f=hp.File(path,'r')
except IOError:
print('files not found')
return ... | calvinosinga/HIColor | previous_versions/combine_fields.py | combine_fields.py | py | 1,200 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.argv",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": ... |
10856186589 | from collections import Counter
def MostPopularNumbers(array, size):
c = Counter(array)
values = c.most_common(size)
return min(values)
a = [1, 1, 2, 2, 3, 4, 5, 6]
MostPopularNumbers(a, a.count)
| luizvictorPa/intro-to-computer-science-with-python | testes_extras/ex3.py | ex3.py | py | 213 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "collections.Counter",
"line_number": 4,
"usage_type": "call"
}
] |
40057309346 | from __future__ import print_function
import os,sys,inspect
from termcolor import colored
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(currentdir)
sys.path.insert(0,parentdir)
import models as Models
import global_vars as Global
from utils.args imp... | ashafaei/OD-test | setup/model_setup.py | model_setup.py | py | 3,061 | python | en | code | 61 | github-code | 1 | [
{
"api_name": "os.path.dirname",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "os.path.abspath",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "inspect.getfile",
"line... |
36270372978 | # -*- coding: utf-8 -*-
'''从自己选出的优质股中，读取excel值，查看每个股票的K图，和证券公司的研报，筛选出好的股票存入excel'''
import time
import pandas as pd
from selenium import webdriver
from openpyxl import load_workbook
class ShowK:
def __init__(self):
self.share_list0 = []
self.share_list1 = []
def read_from_excel(self):
... | zhouxiongaaa/myproject | my_stock/check_k.py | check_k.py | py | 2,757 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "openpyxl.load_workbook",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "openpyxl.load_workbook",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 45,
"usage_type": "call"
},
{
"api_name"... |
35730064961 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 2 09:47:56 2021
@author: ebbek
"""
import pandas as pd
import numpy as np
from inflhist import inflhist
import scipy.stats as sp
from infl_concat import infl_concat
from inflhist import inflhist
from figure_formatting import figure_formatting
from AUcolor import AUcolor
... | ebbekyhl/Future-operation-of-hydropower-in-Europe | scripts/model_evaluation.py | model_evaluation.py | py | 13,813 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "warnings.filterwarnings",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "AUcolor.AUcolor",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "matplotlib.font_manager.FontProperties",
"line_number": 25,
"usage_type": "call"
},
{
"ap... |
38206554377 | from flask_app import app
from flask import render_template, redirect, request, session
from flask_app.models.dojo import Dojo
from flask_app.models.ninja import Ninja
@app.route('/create_dojo', methods=['POST'])
def create_user():
data={
'name':request.form['name'],
}
Dojo.create_dojo(data)
... | megikapo18/dojo_ninjas | flask_app/controllers/dojos.py | dojos.py | py | 620 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.request.form",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "flask.request",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "flask_app.models.dojo.Dojo.create_dojo",
"line_number": 14,
"usage_type": "call"
},
{
"api_... |
413332120 | from pathlib import Path
from copy import deepcopy
from typing import Callable, Optional, Any, \
Union, Generator, TextIO
import numpy as np
from dae.utils.variant_utils import get_interval_locus_ploidy
from dae.variants_loaders.raw.flexible_variant_loader import \
flexible_variant_loader
from dae.variants.... | iossifovlab/gpf | dae/dae/variants_loaders/cnv/flexible_cnv_loader.py | flexible_cnv_loader.py | py | 13,075 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "typing.Any",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"line_number":... |
31383412316 | from lingpy import *
from collections import defaultdict
from sinopy import sinopy
import re
csv1 = csv2list('2017-02-18-Behr-1-197-draft-2-western.csv', strip_lines=False)
csv2 = csv2list('2017-02-18-Behr-1-197-draft-2-eastern.csv', strip_lines=False)
chars = defaultdict(list)
for i, line in enumerate(csv2[1:]+csv1... | digling/rhymes | datasets/Behr2008/raw/helper-2017-01-03.py | helper-2017-01-03.py | py | 1,929 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "collections.defaultdict",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sinopy.sinopy.character_from_structure",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "sinopy.sinopy",
"line_number": 25,
"usage_type": "name"
},
{
"api_n... |
30337427434 | #import libraries
import os
import string
import glob
import subprocess
from subprocess import Popen
import shutil
import time
import datetime
from datetime import datetime
import pandas as pd
import requests
import tkinter as tk
from tkinter import *
from tkinter import ttk
from tkinter import messagebox
from PIL imp... | simremy/versadb_tk | packages/ginfo.py | ginfo.py | py | 29,035 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "packages.tool_path.get_current_path",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "packages.tool_path",
"line_number": 28,
"usage_type": "name"
},
{
"api_name":... |
9333482415 | #!/usr/bin/env python3
"""
Tests for the `pre_commit.git` submodule.
"""
from os import path
from tempfile import TemporaryDirectory
from unittest import (
main,
TestCase
)
from pre_commit.git import (
ForbiddenCharacterError,
GitHandle,
RepositoryError
)
from tests.util import BasicRepo
class T... | spreemohealth/style | tests/test_git.py | test_git.py | py | 5,403 | python | en | code | 2 | github-code | 1 | [
{
"api_name": "unittest.TestCase",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "tests.util.BasicRepo",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "pre_commit.git.GitHandle",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.pa... |
22388472051 | from flask import Flask, jsonify, request
app = Flask(__name__)
accounts = [
{"name":"Billy", 'balance':457.74},
{"name":"Renesmee", 'balance':-150.0},
{"name":"Edward", 'balance':4156.9},
{"name":"Marla", 'balance':321.31},
{"name":"Andrew", 'balance':-120.1},
{"name":"Roxane", 'balance':-10.... | Kroha1999/3KURS | Univer/REST +/lab 2/get.py | get.py | py | 2,190 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "flask.jsonify",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "flask.jsonify",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "flask.jsonify",
"line_numb... |
3203865574 | import fire,os,sys
import numpy as np
from tqdm import tqdm
from skimage import io,morphology
from keras.utils import to_categorical
import cv2
from ulitities.base_functions import get_file,send_message_callback,load_label
def post_process_segment(inf,outf,Flag_cv=True, minsize=10, area_threshold=1000):
# pass
... | scrssys/SCRS_RS_AI | mask_process/remove_small_object.py | remove_small_object.py | py | 2,935 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "ulitities.base_functions.load_label",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.unique",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "numpy.o... |
38736890564 | import numpy as np
from matplotlib import pyplot as plt
import matplotlib.colors
import random as rand
class Board:
def __init__(self,dim,targetTerrain): #set default values for a board
self.board = np.zeros((dim,dim), dtype= float)
self.target = (rand.randint(0,dim-1),rand.randint(0,dim-1))
... | akaashp/ProbabilisticHunting | Board.py | Board.py | py | 1,315 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "numpy.zeros",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "random.choices",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_nu... |
38777068404 | """
Aprenda a manipular datas
Realizar conversao de texto para data e vice-versa
realizar soma e subtracao em datas
- Como recuperar a data atual(DATE)
- Como trabalhar com a data, alterando sua formatação
- Como gerar um horário(TIME)
- Retornar data e hora atual(DATETIME)
- Alterar formação do DATETIME
- Realizar som... | Ademilson12/Aulas_Digital | Basico/aula10.py | aula10.py | py | 1,756 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "datetime.date.today",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "datetime.time",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now... |
32886110882 | from nltk.corpus import stopwords
from settings.common import word_tf_df
from preprocessing_pipeline.NextGen import NextGen
from preprocessing_pipeline import (Preprocess, RemovePunctuation, Capitalization, RemoveStopWords,
RemoveShortWords, TwitterCleaner, RemoveUrls)
def load_fl... | GU-DataLab/topic-modeling-textPrep | process_dataset.py | process_dataset.py | py | 2,946 | python | en | code | 5 | github-code | 1 | [
{
"api_name": "nltk.corpus.stopwords.words",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "nltk.corpus.stopwords",
"line_number": 34,
"usage_type": "name"
},
{
"api_name": "preprocessing_pipeline.Preprocess",
"line_number": 37,
"usage_type": "call"
},
{
... |
21024956783 | import os
from music21 import humdrum
from music21 import converter
import chant21
class MultipleSpinesException(Exception):
"""An exception raised when encountering multiple spines
while expecting only 1"""
pass
def extract_phrases_from_spine(spine):
"""Enxtract the phrases as music21 streams from k... | bacor/cosine-contours | src/phrases.py | phrases.py | py | 2,919 | python | en | code | 4 | github-code | 1 | [
{
"api_name": "music21.humdrum.spineParser.KernSpine",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "music21.humdrum.spineParser",
"line_number": 29,
"usage_type": "attribute"
},
{
"api_name": "music21.humdrum",
"line_number": 29,
"usage_type": "name"
},
{... |
36279239216 | import os
import time
import threading
from dotenv import load_dotenv
import pyttsx3
import data_handler
from datetime import datetime
from datetime import timedelta
from task import Task
class AssistantApp:
def __init__(self):
# Initialize text to speech
self.engine = pyttsx3.init()
# Ini... | johku/Assistant | assistant.py | assistant.py | py | 5,966 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pyttsx3.init",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "data_handler.DataHandler",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "time.split",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
... |
39926577938 | from datetime import datetime
import requests
from flask import Flask, render_template
app = Flask(__name__)
year = datetime.now().year
# print(year)
response = requests.get('https://api.npoint.io/362a61befce3d173e925')
blog_posts = response.json()
# print(blog_posts)
@app.route('/')
def home():
... | vytautasmatukynas/Python-Random-Learning-Testing | WEB_DEV/flask/flask_1st_templates_forms/flask_project_3_blog_sample/server.py | server.py | py | 714 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "requests.get",
"... |
38317304274 | # Importing Required Libraries
import cv2
# define a class called ImageReader
class ImageReader:
def __init__(self, filename):
self.filename = filename
def read_image(self):
try:
img = cv2.imread(self.filename)
if img is None:
raise Exception("Err... | dsvijayvenkat/Computer_Vision_-_OpenCV | 1.Reading_an_Image.py | 1.Reading_an_Image.py | py | 1,890 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "cv2.imread",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "cv2.imshow",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "cv2.waitKey",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "cv2.destroyAllWindows",
"line_n... |
3260640635 | from collections import deque
import sys
input = lambda: sys.stdin.readline().rstrip()
def bfs(x, y):
q = deque()
q.append((x, y))
field[x][y] = 0
while (q):
a, b = q.popleft()
for i in range(8):
nx = a + dx[i]
ny = b + dy[i]
if 0 <= nx <... | zinnnn37/BaekJoon | 백준/Silver/4963. 섬의 개수/섬의 개수.py | 섬의 개수.py | py | 913 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.stdin.readline",
"line_number": 3,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_number": 3,
"usage_type": "attribute"
},
{
"api_name": "collections.deque",
"line_number": 6,
"usage_type": "call"
}
] |
74246591074 | import tweepy
import json
import time
import datetime
import ConfigParser
import tweepy
from tweepy.streaming import StreamListener
'''
Get API keys from Configurations document
'''
config = ConfigParser.ConfigParser()
config.readfp(open(r'./configurations.txt'))
consumerKey=config.get('API Keys', 'consumerKey')
con... | kevinjye/EverTweet | tweet_listener.py | tweet_listener.py | py | 1,336 | python | en | code | 1 | github-code | 1 | [
{
"api_name": "ConfigParser.ConfigParser",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "tweepy.AppAuthHandler",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "tweepy.API",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "time.mktim... |
18022219984 | import cv2
import numpy as np
import os
os.environ["OPENCV_IO_ENABLE_OPENEXR"]="1"
from PIL import Image
from utils.metrics_nocs import align, prepare_data_posefitting, draw_detections
from datasets.datasets import exr_loader,load_meta
syn_depth_path = '/data/sensor/data/real_data/test_0/0000_gt_depth.exr'
nocs_path =... | PKU-EPIC/DREDS | CatePoseEstimation/align.py | align.py | py | 3,904 | python | en | code | 89 | github-code | 1 | [
{
"api_name": "os.environ",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "numpy.zeros",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "cv2.IMREAD_ANYCOLOR",
"line... |
72107723554 | import json
import time
import datetime
import os.path
import GlobalConstants
import GlobalEnums
import Tools
from os import path
class ChatManager:
"""
Chat Manager
"""
def __init__(self):
#self.chatChannelGlobal = {}
self.createChannel(GlobalEnums.ChatChannel.CHAT_CHANNEL_GLOBAL)
def createChannel(self, ... | RottenVisions/ouroboros-prototyping | prototyping/Chat.py | Chat.py | py | 2,536 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "GlobalEnums.ChatChannel",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "GlobalEnums.ChatChannel",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "Tools.getDate",
"line_number": 28,
"usage_type": "call"
},
{
"api_name"... |
31281558255 | import torch
import pandas as pd
import numpy as np
import torch.nn as nn
import statistics
from DLDUlib import device, train, optimize_ols, center, normalize, r_squared, cross_validate_train
import copy
names = ['SalePrice','1st_Flr_SF','2nd_Flr_SF','Lot_Area','Overall_Qual',
'Overall_Cond','Year_Built','Year_Rem... | cpsiff/DLDU-Projects | 2_nonlinear/my_imp_nonlinear_crossv_train.py | my_imp_nonlinear_crossv_train.py | py | 2,166 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pandas.read_csv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.float",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "torch.FloatTensor",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "DLDUlib.center",
... |
13953011427 | ## Code to make a PCR reaction using a pre-mixed master-mix, distribute it between wells
## of a 96-well plate, add primers and add a given number of template samples.
###INPUT### PCR variables
num_replicates = 8
num_templates = 4
total_PCR_volume = 20
master_mix_volume = 8
template_volume = 1
primer_volume = 2.5
#... | Arne444/PCR_premixedMM | PCR_premixedMM.py | PCR_premixedMM.py | py | 3,516 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "opentrons.containers.load",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "opentrons.containers",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "opentrons.containers.load",
"line_number": 19,
"usage_type": "call"
},
{
"api_name... |
7087899911 | from utils.terminal import clear
from utils.Database import Database
import requests
from utils.OpenApi import OpenApi
class Dialogue:
def __init__(self):
self.database = Database()
self.main_menu()
self.open_api = OpenApi()
def main_menu(self) -> None:
"""
This funct... | adrien914/P5_Utilisez_les_donnees_publiques_de_OpenFoodFacts | utils/Dialogue.py | Dialogue.py | py | 11,416 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "utils.Database.Database",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "utils.OpenApi.OpenApi",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "utils.terminal.clear",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "ut... |
1323528673 | import pathlib
import tarfile
import datetime
import argparse
import json
class ConfigParser():
"""Configuration file parser."""
def __init__(self, config_file_name: str):
"""Intialization."""
self._config_file = config_file_name
self._config = dict()
def parse(self) -> bool:
... | sandeepbhat/home-made-backup | hmb.py | hmb.py | py | 3,031 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "pathlib.Path",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "json.load",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
... |
31584008482 | """
Class for weather data.
"""
from json import loads
from requests import get
from .location import Location
class Weather:
"""Class for weather data."""
def __init__(self, measure, location: Location, apikey=None):
self.apikey = apikey
self.measure = measure
self.location = locatio... | PiSmartTV/PiTV | PiTV/weather.py | weather.py | py | 1,454 | python | en | code | 14 | github-code | 1 | [
{
"api_name": "location.Location",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "requests.get",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_nu... |
15162365309 | import numpy as np
import pygplates
from scipy import spatial
def marsaglias_method(N):
## Marsaglia's method
dim = 3
norm = np.random.normal
normal_deviates = norm(size=(dim, N))
radius = np.sqrt((normal_deviates**2).sum(axis=0))
points = normal_deviates/radius
return points
... | atom-model/ATOM | reconstruction/sphere_tools.py | sphere_tools.py | py | 2,408 | python | en | code | 13 | github-code | 1 | [
{
"api_name": "numpy.random",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "numpy.sqrt",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pygplates.PointOnSphere",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "numpy.array",
... |
4200238882 | import itertools
import json
import math
import random
import statistics
from collections import defaultdict
from html.parser import HTMLParser
import boto3
import requests
from rating import RatingSystem, ContestType
old_sponsored_contests = {
"code-festival-2014-exhibition",
"code-festival-2014-final",
... | kenkoooo/AtCoderProblems | lambda-functions/time-estimator/function.py | function.py | py | 20,781 | python | en | code | 1,291 | github-code | 1 | [
{
"api_name": "html.parser.HTMLParser",
"line_number": 68,
"usage_type": "name"
},
{
"api_name": "html.parser",
"line_number": 79,
"usage_type": "argument"
},
{
"api_name": "math.log",
"line_number": 98,
"usage_type": "call"
},
{
"api_name": "math.exp",
"line_... |
15685183129 | import csv
from selenium import webdriver
import pandas
from pandas import DataFrame
import requests
test_url = "https://downtowndallas.com/experience/stay/"
chrome_driver_path = "E:\softwares/chromedriver.exe"
driver = webdriver.Chrome(executable_path=chrome_driver_path)
driver.get(test_url)
driver.... | PRANJALI1901/assesment | main.py | main.py | py | 1,349 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "selenium.webdriver.Chrome",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 11,
"usage_type": "name"
},
{
"api_name": "pandas.DataFrame",
"line_number": 51,
"usage_type": "call"
}
] |
27587876211 | from typing import Dict,List,Tuple,Union,NamedTuple,Optional
from typing_extensions import Literal
import json,re
import daa_luigi
from common_functions import ExecutionFolder,raise_exception,as_inputs
from copy import copy
import pandas as pd
from pathlib import Path
import sissopp
from sissopp.py_interface import get... | MilenaOehlers/cluster-based-SISSO | cluster_based_sisso/__init__.py | __init__.py | py | 21,087 | python | en | code | 5 | github-code | 1 | [
{
"api_name": "typing.Dict",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "typing_extensions.Literal",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.NamedTuple",... |
32509486669 | from ftplib import FTP
import ftplib
import os
import xml.etree.ElementTree as EleTree
import VAPublishUtil as VAUtil
import shutil
import EchoItemXML
__author__ = 'Jiao Zhongxiao'
# 选择的功能分支
FEATURE_BRANCH = None
# 确认的版本号
VERSION_NUM = None
ASSET_EXT = ".json,.jpg,.png,.swf,.xml,.mp3,.wdp,.xcom"
IGNORE_EXT = ".xc... | jiaox99/publishTools | pythonScripts/VACommonPublishTool.py | VACommonPublishTool.py | py | 8,536 | python | en | code | 3 | github-code | 1 | [
{
"api_name": "VAPublishUtil.parse_publish_config",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "VAPublishUtil.publish_dir",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "EchoItemXML.scan_dir",
"line_number": 39,
"usage_type": "call"
},
{
... |
15662447246 | import json
import os
from flask import (
Flask,
jsonify,
render_template,
request,
send_from_directory,
redirect,
session,
url_for,
)
import oci
from oci.ai_anomaly_detection.models import DetectAnomaliesDetails
import postgrest
from supabase import create_client, Client
from io import... | Salomon-mtz/oxxogas.github.io | app.py | app.py | py | 24,643 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "flask.Flask",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "os.urandom",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "oci.config.from_file",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "oci.config",
"line_nu... |
30989959642 | # from locale import setlocale, LC_ALL
from calendar import month_name, mdays
from functools import reduce
# setlocale(LC_ALL, 'pt_BR')
Lista_meses = filter(lambda x: mdays[x] == 31, range(1, 13))
nome_meses = map(lambda x: month_name[x], Lista_meses)
juntar = reduce(lambda todos, nome_mes: f'{todos}\n {nome_mes}',
... | higorsantana-omega/Programacao_funcional_Python | imutabilidade_v1.py | imutabilidade_v1.py | py | 381 | python | pt | code | 0 | github-code | 1 | [
{
"api_name": "calendar.mdays",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "calendar.month_name",
"line_number": 8,
"usage_type": "name"
},
{
"api_name": "functools.reduce",
"line_number": 9,
"usage_type": "call"
}
] |
16692902771 | #!/usr/bin/env python
import cv2
from lib import tracker
BLUE = (255, 50, 50)
GREEN = (50, 255, 50)
RED = (50, 50, 255)
WHITE = (255, 255, 255)
def main():
markers = tracker.find_markers(img)
for m_id, marker in markers.iteritems():
cv2.drawContours(img, [marker.contour], -1, GREEN, 2)
cv2.... | antoneri/rover-follow-target | examples/track_all_markers.py | track_all_markers.py | py | 1,174 | python | en | code | 13 | github-code | 1 | [
{
"api_name": "lib.tracker.find_markers",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "lib.tracker",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "cv2.drawContours",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "cv2.line",
... |
20521636348 | from turtle import Turtle
from paddle import Paddle
from scoreboard import Scoreboard
from random import randint
from time import sleep
BALL_RADIUS = 12 # supposedly 10
BALL_SPEED = 9
WINDOW_WIDTH = 960
WINDOW_HEIGHT = 640
class Ball(Turtle):
def __init__(self) -> None:
super().__init__()
... | LetSleepingFoxesLie/100DaysOfCode_py | 22_Pong/ball.py | ball.py | py | 2,597 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "turtle.Turtle",
"line_number": 14,
"usage_type": "name"
},
{
"api_name": "random.randint",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "random.randint",
"lin... |
2090654629 | import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
import urllib.request
import os
def to_image_name(user_info):
return f'{user_info["name"]}_({user_info["updatedAt"]}).jpg'
def get_local_user_from_image_name(image_name):
image_name_without_ext = os.path.spli... | huuquyen2606/FID | fast_api.py | fast_api.py | py | 1,610 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "os.path.splitext",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "firebase_admin.credentials.Certificate",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "... |
2144866290 | import requests
import re
from bs4 import BeautifulSoup
from headers import HEADERS
from csvImporter import CsvImporter
class InfoFinder:
def __init__(self, url_tuple_set, file_name):
self.url_tuple = url_tuple_set
self.has_contact_set = set()
self.no_contact_set = set()
self.impor... | redvox27/innovatiespotter | omleidingsSites/infoFinderController.py | infoFinderController.py | py | 4,517 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "csvImporter.CsvImporter",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "headers.HEADERS",
"line_number": 20,
"usage_type": "argument"
},
{
"api_name": "bs4.Beautifu... |
38730450704 | # raw_to_evoked
# simple utility to plot_joint from file name
import sys
raw_file=sys.argv[1]
event_id=1
import mne
Raw=mne.io.read_raw_fif(raw_file)
Events=mne.find_events(Raw)
reject = dict(grad=4e-10, mag=4e-12, eog=150e-6)
Epochs=mne.Epochs(Raw, Events, event_id=event_id, tmin=-0.1, tmax=0.8,
baseline=(... | smonto/cibr-meg | raw2plot_joint.py | raw2plot_joint.py | py | 400 | python | en | code | 0 | github-code | 1 | [
{
"api_name": "sys.argv",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "mne.io.read_raw_fif",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "mne.io",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "mne.find_events",
"l... |
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