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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8660980424 | import numpy as np
from ctypes import * # c 类型库
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from astropy.io import ascii
from astropy.table import Table, vstack
import os
from scipy.stats import *
import time
z4figpre = '../z4/figs/'
z4datapre = '../z4/data/'
z5figpre = '../z5/figs/'
z5data... | lovetomatoes/BHMF | PYmodule/__init__.py | __init__.py | py | 8,267 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.get_cmap",
"line_number": 61,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 61,
"usage_type": "name"
},
{
"api_name": "numpy.min"... |
2628647448 | import os
import cv2
import glob
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
import random
from ipdb import set_trace as bp
size_h, size_w = 600, 600
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=False, dtype='uint8')
ob... | nguyenvantui/mnist-object-detection | mnist_gen.py | mnist_gen.py | py | 8,145 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "tensorflow.examples.tutorials.mnist.input_data.read_data_sets",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "tensorflow.examples.tutorials.mnist.input_data",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "os.path.exists",
"line_number": ... |
39076799665 | from string import ascii_lowercase
class Node:
def __init__(self, val, parents = []):
self.val = val
self.parents = parents
def __str__(self):
return self.val
from collections import deque
from string import ascii_lowercase
class Solution:
def findLadders(self, beginWord: str, endWor... | YuxiLiuAsana/LeetCodeSolution | q0126.py | q0126.py | py | 2,196 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.deque",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "string.ascii_lowercase",
"line_number": 36,
"usage_type": "name"
}
] |
74274579943 | import pytest
import ruleset
import util
import os
def get_testdata(rulesets):
"""
In order to do test-level parametrization (is this a word?), we have to
bundle the test data from rulesets into tuples so py.test can understand
how to run tests across the whole suite of rulesets
"""
testdata = ... | fastly/ftw | ftw/pytest_plugin.py | pytest_plugin.py | py | 3,940 | python | en | code | 263 | github-code | 36 | [
{
"api_name": "ruleset.tests",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "ruleset.Test",
"line_number": 25,
"usage_type": "attribute"
},
{
"api_name": "pytest.fixture",
"line_number": 33,
"usage_type": "attribute"
},
{
"api_name": "pytest.fixtu... |
18701687808 | import numpy as np
from numpy import linalg as LA
from keras.applications.vgg16 import VGG16
from keras.preprocessing import image
from keras.applications.vgg16 import preprocess_input
from PIL import Image
from cv2 import imread,resize,cvtColor,COLOR_BGR2RGB,INTER_AREA,imshow
'''
VGG16模型,权重由ImageNet训练而来
使用vgg16模型提取特... | 935048000/ImageSearch | core/feature_extraction.py | feature_extraction.py | py | 1,808 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "keras.applications.vgg16.VGG16",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "cv2.imread",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "cv2.resize",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "cv2.INTER_AREA",... |
43135278080 |
# Mnemonic: em.py
# Abstract: Run em (Expectation Maximisation)
#
# Author: E. Scott Danies
# Date: 06 March 2019
#
# Acknowledgements:
# This code is based in part on information gleaned from, or
# code examples from the following URLs:
# https://github.com/minmingzhao?... | ScottDaniels/gtcs7641 | a3/em.py | em.py | py | 4,623 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tools.printf",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "tools.str_flag",
"line_number": 46,
"usage_type": "name"
},
{
"api_name": "tools.bool_flag",
"line_number": 47,
"usage_type": "name"
},
{
"api_name": "tools.int_flag",
"lin... |
1054566885 | # -*- coding = utf-8 -*-
# @Time : 2021/5/5 18:25
# @Author : 水神与月神
# @File : 灰度转彩色.py
# @Software : PyCharm
import cv2 as cv
import numpy as np
import os
import mypackage.dip_function as df
# demo
# path = r"C:\Users\dell\Desktop\8.png"
#
# image = cv.imread(path, cv.IMREAD_UNCHANGED)
#
# image1 = image[:, :, 0]
# ... | mdwalu/previous | 数字图像处理/灰度转彩色.py | 灰度转彩色.py | py | 2,065 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "os.listdir",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number"... |
3572388059 | ##
# @file mathlib.py
# @package mathlib
# @brief Module with functions to convert and evaluate expression using expression tree
import treeClass
import logging
# """Priorities of operators"""
priority = {
'!' : 3,
'^' : 2,
'*' : 1,
'/' : 1,
'%' : 1,
'+' : 0,
'-' : 0,
}
# """Associativit... | Hedgezi/jenna_calcutega | src/mathlib.py | mathlib.py | py | 4,055 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "treeClass.Stack",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 100,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"line_number": 117,
"usage_type": "call"
},
{
"api_name": "logging.debug",
"li... |
70167417064 | from mongoengine import Q
from django_pds.conf import settings
from django_pds.core.managers import UserReadableDataManager, GenericReadManager, UserRoleMapsManager
from django_pds.core.rest.response import error_response, success_response_with_total_records
from django_pds.core.utils import get_fields, get_document, ... | knroy/django-pds | django_pds/core/pds/generic/read.py | read.py | py | 6,463 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "django_pds.conf.settings.SELECT_NOT_ALLOWED_ENTITIES",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "django_pds.conf.settings",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "django_pds.conf.settings.SECURITY_ATTRIBUTES",
"line_numbe... |
20145639624 | """
Cobweb plot function
"""
import numpy as np
import matplotlib.pyplot as plt
__all__ = [
'cobweb'
]
def cobweb(func, initial_conditon, nsteps, limits, args=(), ax=None):
"""
Plot cobweb diagram for onedimensional iterated functions
``x[n+1] = func(x[n])``.
Parameters
----------
func ... | antonior92/dynamic-system-plot | dynplt/cobweb.py | cobweb.py | py | 1,586 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "matplotlib.pyplot.subplots",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "numpy.linspace",
"line_number": 40,
"usage_type": "call"
}
] |
5765246532 | import pyautogui
import schedule
import time
import datetime
import random
pyautogui.FAILSAFE = False
screenWidth, screenHeight = pyautogui.size() # Get the size of the primary monitor.
currentMouseX, currentMouseY = pyautogui.position() # Get the XY position of the mouse.
datetime.datetime.now()
print(datetime.date... | jbernax/autoclicktimer | autoclick.py | autoclick.py | py | 5,721 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pyautogui.FAILSAFE",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "pyautogui.size",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pyautogui.position",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "datetime.datet... |
73313388265 | # %%
import csv
import sys
import numpy as np
import pandas as pd
import os
from matplotlib import pyplot as plt
# plt.rcParams['font.sans-serif'] = ['Times New Roman']
# 找到全局最优 10 20 41
# 不断找到最优 15 34
filename1 = "results/Cifar10-center/LeNet/record_sgd weight.csv"
filename2 = "results/Cifar10-center/LeNet/recor... | zhengLabs/FedLSC | painting/painting_weight_change.py | painting_weight_change.py | py | 1,279 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.clf",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "matplotlib.pypl... |
35584359150 | from zipfile import ZipFile
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn import datasets, linear_model
from sklearn.metrics import mean_squared_error, r2_score
from sklearn.model_selection import train_test_split, cross_val_score
from sklearn.preprocessing import StandardScaler
i... | Kamkas/Bike-Sharing-Data-Analysis | lr.py | lr.py | py | 2,416 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model.LinearRegression",
"line_number": 62,
"usage_type": "call"
},
{
"api_name": "sklearn.linear_model",
"line_number": 62,
"usage_type": "name"
},
{
"api_na... |
11370165603 | import numpy as np
import torch
import torch.nn as nn
from ml.modules.backbones import Backbone
from ml.modules.bottoms import Bottom
from ml.modules.heads import Head
from ml.modules.layers.bifpn import BiFpn
from ml.modules.tops import Top
class BaseModel(nn.Module):
def __init__(self, config):
super()... | gregiberri/DepthPrediction | ml/models/base_model.py | base_model.py | py | 4,058 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "ml.modules.bottoms.Bottom",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "ml.modules.ba... |
44575910113 | from dbmanager import DatabaseManager
from tgbot import Bot
from market import Market
from plot_provider import PlotProvider
import threading
import sys
import logging
import logging.handlers
import queue
from apscheduler.schedulers.background import BackgroundScheduler
class MarketManager:
def __init__(self, pa... | hype-ecosystem/predictions_bot | market_manager.py | market_manager.py | py | 3,531 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "logging.ERROR",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "logging.handlers.SysLogHandler",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "l... |
73895256743 | import numpy as np
import torch
from torch.utils.data import Dataset
import pickle as pkl
def valence_map(elements: list, valences: list):
"""
## Given a list of elements and their corresponding valences, create a dictionary mapping each element to its valence.
### Args:
- elements: a list of ele... | Airscker/DeepMuon | DeepMuon/dataset/XASData.py | XASData.py | py | 4,337 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "pickle.load",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"l... |
43069956711 | import csv
import io
from Crypto.Signature import pkcs1_15
from Crypto.PublicKey import RSA
from Crypto.Hash import SHA256, SHA
gSigner = "signer@stem_app"
def loadVoters(fname):
try:
voters = {s['studNr']: s for s in csv.DictReader(
loadFile(fname), delimiter=';')}
return voters
... | Tataturk/stem_app | audit.py | audit.py | py | 2,468 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "csv.DictReader",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "csv.DictReader",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "io.StringIO",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "Crypto.PublicKey.RSA.i... |
71910544423 | from collections import OrderedDict
from Models.Utils.FRRN_utils import *
class FRRNet(nn.Module):
"""
implementation table A of Full-Resolution Residual Networks
"""
def __init__(self, in_channels=3, out_channels=21, layer_blocks=(3, 4, 2, 2)):
super(FRRNet, self).__init__()
# 5×5
... | akshatgarg99/FRR-Net | Models/FRRN.py | FRRN.py | py | 2,658 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.OrderedDict",
"line_number": 15,
"usage_type": "call"
}
] |
37664896770 | from page.E_confirm_order_page import ConfirmOrderPage
class MyOrderPage(ConfirmOrderPage):
"""我的订单页面"""
order_sn_loc = ('id', 'com.tpshop.malls:id/order_sn_tv') # 订单编号
to_be_received_loc = ('id','com.tpshop.malls:id/status_receive_tv') # 待收货
back_loc = ('id','com.tpshop.malls:id/title_back_img') # ... | 15008477526/- | APP_aaaaaaaa/page/F_my_order.py | F_my_order.py | py | 2,633 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "page.E_confirm_order_page.ConfirmOrderPage",
"line_number": 4,
"usage_type": "name"
},
{
"api_name": "common.base_app.open_app",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "page.E_confirm_order_page.ConfirmOrderPage",
"line_number": 43,
"usage... |
18482251122 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, inplanes, planes, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(inplanes, inplanes, 1, stride, bias=False)
self.bn1 = nn.... | TWSFar/DSSD | model/decoder.py | decoder.py | py | 3,824 | python | en | code | 8 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "torch.nn.Conv2d",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
33078013582 | # pylint: disable=W0102
# pylint: disable=W0212
# pylint: disable=W0221
# pylint: disable=W0231
# pylint: disable=W0640
# pylint: disable=C0103
"""Module for representing UDS corpora."""
import os
import json
import requests
from pkg_resources import resource_filename
from os.path import basename, splitext
from loggi... | decompositional-semantics-initiative/decomp | decomp/semantics/uds/corpus.py | corpus.py | py | 26,248 | python | en | code | 56 | github-code | 36 | [
{
"api_name": "typing.Union",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "typing.TextIO",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "predpatt.PredPattCorpus",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": "pkg_resources.reso... |
30629658909 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import json, urllib
import plotly.graph_objects as go
import pandas as pd
import numpy as np
# In[2]:
asi_measures = pd.read_csv('final-data.csv')
asi_measures.head()
# In[4]:
all_nodes = asi_measures.Category.values.tolist() + asi_measures.ASI.values.tolist()
s... | nikolamedi/sankey-diagram | Sankey diagram with plotly.py | Sankey diagram with plotly.py | py | 912 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "plotly.graph_objects.Figure",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "plotly.graph_objects",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "plot... |
34091963292 | from loader import dp, bot
from aiogram.types import ContentType, Message
from pathlib import Path
# kelgan hujjatlar (rasm/video/audio...) downloads/categories papkasiga tushadi
download_path = Path().joinpath("downloads","categories")
download_path.mkdir(parents=True, exist_ok=True)
@dp.message_handler()
async def ... | BakhtiyarTayir/mukammal-bot | handlers/users/docs_handlers.py | docs_handlers.py | py | 1,536 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pathlib.Path",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "aiogram.types.Message",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "loader.dp.message_handler",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "loader.dp"... |
35896409907 | from typing import NamedTuple, Optional, List, Dict, Any, Union
from enum import Enum, auto
import pysam
def _build_filter(rec: pysam.VariantRecord) -> List[Union[str, int]]:
return [f for f in rec.filter]
def _build_info(rec: pysam.VariantRecord) -> Dict[str, Any]:
info = dict()
for key, value in rec.... | EUCANCan/variant-extractor | src/variant_extractor/variants.py | variants.py | py | 8,031 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "pysam.VariantRecord",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "typing.List",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 7,
"usage_type": "name"
},
{
"api_name": "pysam.VariantRecord",
... |
25046698571 | #!/usr/bin/python
import json
import re
import os
import sys
# Get data.json from Twitter for
# Followers: https://oauth-playground.glitch.me/?id=usersIdFollowers¶ms=%28%27user.fields%21%27description%27%29_
# Followings: https://oauth-playground.glitch.me/?id=usersIdFollowing¶ms=%28%27user.fields%21%27descr... | tjosten/twitter-mastodon-finder | finder.py | finder.py | py | 983 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "sys.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "json.load",
"line_number"... |
4197719073 | """Utilities for plotting the results of the experiments."""
import os
import json
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use("pdf")
# Avoid trouble when generating pdf's on a distant server
# matplotlib.use("TkAgg") # Be able to import matplotlib in ipython
import matplotlib.pyplot as plt
... | RobinVogel/Weighted-Empirical-Risk-Minimization | plot_utils.py | plot_utils.py | py | 10,788 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyp... |
9896960203 | #!/usr/bin/env python3
#-*- coding: utf-8 -*-
import os
import sys
import rospy
import numpy as np
import cv2
from sensor_msgs.msg import Image, CompressedImage
from cv_bridge import CvBridge, CvBridgeError
from darknet_ros_msgs.msg import BoundingBoxes, ObjectCount
class Bridge(object):
"""압축된 이미지를 센서 메세지 형태로 ... | Taemin0707/minibot_control | pedestrian_tracking/src/visualizing.py | visualizing.py | py | 2,884 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv_bridge.CvBridge",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "darknet_ros_msgs.msg.BoundingBoxes",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "rospy.Publisher",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": ... |
39154979229 | from typing import Callable
def format_number(number: int) -> str:
num = float(f"{number:.3g}")
magnitude = 0
format_human: Callable[[float], str] = lambda x: f"{x:f}".rstrip("0").rstrip(".")
while abs(num) >= 1000:
magnitude += 1
num /= 1000.0
return f"{format_human(num)}{['', ... | SkyLissh/skylet-discord | app/utils/format_number.py | format_number.py | py | 358 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.Callable",
"line_number": 8,
"usage_type": "name"
}
] |
12685785417 | import itertools
from itertools import izip, cycle
import os
import string
import glob
from moduleBaseClass import ModuleBaseClass
class XorStuff:
def __init__(self, filepath=None):
"""Constructor : set xored file (optional)
"""
self.file_type = None
self.list_types = self.load_f... | tengwar/xorstuff | xorstuff.py | xorstuff.py | py | 4,032 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "glob.glob",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "os.path.splitext",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "moduleBaseClass.ModuleBaseCla... |
8036114944 | from django.shortcuts import render, get_object_or_404
from django.http import HttpResponseRedirect
from django.urls import reverse
from django.views import generic
#from django.template import loader # no longer needed b/c of render shortcut
from .models import Question, Choice
# Create your views here.
class Index... | Alex-Bishka/Languages | Django/mysite/polls/views.py | views.py | py | 3,562 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.views.generic.ListView",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "django.views.generic",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "models.Question.objects.order_by",
"line_number": 18,
"usage_type": "call"
},
... |
11473243619 | import os
import zipfile
from abc import ABCMeta
from pathlib import Path
from typing import Optional, Union
from urllib.request import urlretrieve
class BaseDownloader(metaclass=ABCMeta):
"""Base downloader for all Movielens datasets."""
DOWNLOAD_URL: str
DEFAULT_PATH: str
def __init__(self, zip_pa... | smartnews/rsdiv | src/rsdiv/dataset/base.py | base.py | py | 876 | python | en | code | 7 | github-code | 36 | [
{
"api_name": "abc.ABCMeta",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "typing.Union",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_numb... |
16539248084 | import markovify
import sys
import argparse
import configparser
import twitter
model_depth_default = 2
model_depth = model_depth_default
def main():
arg_parser = argparse.ArgumentParser(description="Generate text with Markov chains based on a source corpus.")
subparser = arg_parser.add_subparsers(dest="subparser_na... | nanovad/poorlytrained | poorlytrained.py | poorlytrained.py | py | 2,216 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "configparser.ConfigParser",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "sys.stderr.write",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "sy... |
33066511083 | """
enums.py
Contains the different types of objects for the application.
"""
# Import modules and libraries
from enum import Enum
class UserType(Enum):
"""
Represents the different types of users in the application.
"""
admin = "admin"
manager = "manager"
inspector = "inspector"
maintenan... | Xata/cis4050-spring2023-prototipo | backend/app/enums.py | enums.py | py | 1,280 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "enum.Enum",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "enum.Enum",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "enum.Enum",
"line_number": 33,
"usage_type": "name"
},
{
"api_name": "enum.Enum",
"line_number": 44,
"... |
28555182089 | # This is a sample Python script.
# Press ⌃R to execute it or replace it with your code.
# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.
import sys
import asyncio
import datetime
import time
import collections
import json
# function to execute aws cli 'iam' command
async... | SeungwookE/InvalidAccessKeyDetector | main.py | main.py | py | 3,645 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "asyncio.create_subprocess_shell",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "asyncio.subprocess",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "asyncio.subprocess",
"line_number": 19,
"usage_type": "attribute"
},
{
"a... |
10663941067 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 21 16:38:00 2016
@author: Neo
Oct 25, 2016: updated by Niu.
"""
import numpy as np
import matplotlib.pyplot as plt
res_dir = '../results/'
dat_fil = ['OVrot.dat', 'GRrot.dat']
#glide for the three special catalog
w3 = np.loadtxt(res_dir + 'Speci... | Niu-Liu/thesis-materials | sou-selection/progs/RotationPlot.py | RotationPlot.py | py | 5,084 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.loadtxt",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.loadtxt",
"line_n... |
15193997907 | from enum import Enum
from dynsimf.models.helpers.ConfigValidator import ConfigValidator
from dynsimf.models.components.conditions.Condition import Condition
__author__ = "Mathijs Maijer"
__email__ = "m.f.maijer@gmail.com"
class UpdateType(Enum):
'''
An Enum to specify the type of the update
'''
STAT... | Tensaiz/DyNSimF | dynsimf/models/components/Update.py | Update.py | py | 4,795 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "enum.Enum",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "dynsimf.models.helpers.ConfigValidator.ConfigValidator.validate",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "dynsimf.models.helpers.ConfigValidator.ConfigValidator",
"line_numbe... |
73550814184 | #-*- coding: utf-8 -*-
'''
1. 添加系：adddepartment
2. 添加班级：addclass
3. 删除系：deldepartment
4. 删除班级：delclass
5. 编辑系：editdepartment
6. 编辑班级：editclass
'''
from django.shortcuts import render_to_response
from django.template import RequestContext, Template, Context
from classes.models import Class, Department
from teachers.mo... | Luokun2016/QuickSort | classes/views.py | views.py | py | 7,941 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "django.http.HttpResponseRedirect",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "classes.models.Department.objects.order_by",
"line_number": 24,
"usage_type": "call"
... |
21662366530 | #!/usr/bin/env python3
# -*- coding:utf-8 -*-
# @Time: 2020/4/5 21:14
# @Author: qyh
import matplotlib.pyplot as plt
import numpy.random as rdm
import networkx as nx
node_num = 100
probability = 0.01
er_graph = nx.erdos_renyi_graph(node_num, probability)
susceptible = 'S'
infected = 'I'
recovered = 'R'
... | QCloudHao/COVID19 | development.py | development.py | py | 2,014 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "networkx.erdos_renyi_graph",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "numpy.random.random",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "numpy.random",
"line_number": 27,
"usage_type": "name"
},
{
"api_name": "numpy.ran... |
5741967370 | import os
import pandas as pd
from sklearn.model_selection import KFold, train_test_split
root_path = os.path.dirname(__file__)
asset_path = os.path.join(root_path, '../assets')
# load the full titanic example data
data = pd.read_csv(os.path.join(root_path, '../data/train.csv'))
# train / test split
train_data, tes... | Esadruhn/owkin_elixir_hackathon | substra_materials/titanic_example/titanic/scripts/generate_data_samples.py | generate_data_samples.py | py | 1,475 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "os.path.dirname",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 7... |
39642904721 | """ CONTROLLER.PY
The site controller controlls the production of the response
for requests to the website. The controller creates and interacts
with both, the SiteModel and the SiteViews. A call to the controller
calls start_response and returns the contents of the response.
Upgrade to multi-s... | berthoud/webfitsviewer | webfitsviewer/src/controller.py | controller.py | py | 16,483 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "configobj.ConfigObj",
"line_number": 80,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 88,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 88,
"usage_type": "attribute"
},
{
"api_name": "logging.config.basicCon... |
6671044786 | from sense_hat import SenseHat
from PIL import Image
from random import randint
import time
sense = SenseHat()
amount_of_pics = 3
while True:
pic_nr = str(randint(1, amount_of_pics))
img = Image.open('pic'+pic_nr+'.png')
byteList = list(img.getdata())
pixels = []
for index, byte in enumerate(byte... | gdmgent-IoT-1920/labo-2-sensehat-hansvertriest | avatar_animated.py | avatar_animated.py | py | 425 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sense_hat.SenseHat",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "PIL.Image.open",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "PIL.Image",
"line... |
74518602024 | #import os
from typing import Union
import torch
import numpy as np
from . import torch_knn
gpu_available = torch_knn.check_for_gpu()
if not gpu_available:
print("The library was not successfully compiled using CUDA. Only the CPU version will be available.")
_transl_torch_device = {"cpu": "CPU", "cuda": "GPU"}
c... | thomgrand/torch_kdtree | torch_kdtree/nn_distance.py | nn_distance.py | py | 7,259 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "torch.Tensor",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "torch.device",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "torch.float32",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "torch.from_num... |
9135106371 | #!/usr/bin/env python3
import sqlite3
def nice_print(sql_table):
""" used to show information in a slightly more readable fashion"""
for row in sql_table:
row_string = map(str,row)
pretty_row = '\t\t'.join(list(row_string))
print(pretty_row)
conn = sqlite3.connect('northwind.sqlite3'... | Tclack88/Lambda | DS-3-2-SQL-and-Databases/sc/northwind.py | northwind.py | py | 2,024 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sqlite3.connect",
"line_number": 13,
"usage_type": "call"
}
] |
7413102812 | """Sorts duplicate photos/files and places all copies in their own folder."""
import click
import halo
from hashlib import sha256
from pathlib import Path
from shutil import copyfile, move
""" Return the SHA256 sum of the provided file name.
:param file_name - Name of the file to check
:return Hexdigst of SHA sum
"... | poiriermike/sort_dup_photos | sort_dupes.py | sort_dupes.py | py | 1,698 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "hashlib.sha256",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "click.echo",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "pathlib.Path",
"line_numbe... |
40066321475 | import pandas as pd
from decouple import config
import numpy as np
import os
import nilearn.image as img
from nilearn.glm.second_level import non_parametric_inference
import nibabel
import argparse
def options() -> dict:
'''
Function to accept accept command line flags.
Needs -t for task name and -p for n... | WMDA/socio-emotion-cognition | task_fmri/modelling/nilearn_notebooks/second_level_group_differences_nilearn.py | second_level_group_differences_nilearn.py | py | 5,119 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "decouple.config",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "os.path",
"l... |
21811338637 | from elasticsearch import Elasticsearch
from services.caption_processor import split_captions
es = Elasticsearch()
def index_captions(captions, video_id):
for ctime, ctext in split_captions(captions):
doc = {
'time': ctime,
'text': ctext,
'video': video_id
}
... | veotani/youtube-caption-search | server/services/caption_indexator.py | caption_indexator.py | py | 696 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "services.caption_processor.split_captions",
"line_number": 8,
"usage_type": "call"
}
] |
31061471225 |
from ..utils import Object
class GetLanguagePackStrings(Object):
"""
Returns strings from a language pack in the current localization target by their keys. Can be called before authorization
Attributes:
ID (:obj:`str`): ``GetLanguagePackStrings``
Args:
language_pack_id (:obj:`str`... | iTeam-co/pytglib | pytglib/api/functions/get_language_pack_strings.py | get_language_pack_strings.py | py | 1,077 | python | en | code | 20 | github-code | 36 | [
{
"api_name": "utils.Object",
"line_number": 6,
"usage_type": "name"
}
] |
27912151130 | import boto3
import pg8000
import datetime
import json
import time
# Create an S3 client
s3 = boto3.client('s3')
# Create a CloudWatch client
cloudwatch = boto3.client('cloudwatch')
def ingest_database_to_s3(bucket_name):
# Retrieve the database connection details from AWS Secrets Manager
secretsmanager = bo... | vasilecondrea/lake-cabin-project | extract/src/extract.py | extract.py | py | 4,151 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "boto3.client",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "boto3.client",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number":... |
17122612080 | # import the packages
import matplotlib.pyplot as plt
import networkx as nx
# Define the data structures of vertices and edges
vertices = range(1, 10)
edges = [(7, 2), (2, 3), (7, 4), (4, 5), (7, 3), (7, 5),
(1, 6), (1, 7), (2, 8), (2, 9)]
# Let's first instantiate the graph
G = nx.Graph()
# let's draw the gr... | amrmabdelazeem/40-Algorithms-to-Know | Fraud Analytics.py | Fraud Analytics.py | py | 1,258 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "networkx.Graph",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "networkx.spring_layout",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "networkx.draw_networkx_nodes",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "ne... |
2760395481 | import os
from datetime import datetime, timedelta
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
from google.oauth2.credentials import Credentials
import googleapiclient.discovery
import googleapiclient.errors
import httplib2.error
import youtube_dl
import log... | vachau/youtube-restreamer | utils/apis.py | apis.py | py | 12,777 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "os.path.exists",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 47,
"usage_type": "attribute"
},
{
"api_name": "google.oauth2.credentials.Credentials.from_authorized_user_file",
"line_number": 49,
"usage_type": "call"
}... |
3984159879 | from django.http import HttpResponse
from django.shortcuts import render
from .models import *
def home_view(request):
names = ['Jitendra', 'Rimaljit', 'Mohit', 'Deepak']
address = ['Chandigarh', 'Ludhiana', 'Ludhiana', 'Ludhian']
info = zip(names, address)
data = {
'info': info
}... | jitendra5581/cms-training | studentapp/views.py | views.py | py | 1,601 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.shortcuts.render",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 61,
"usage_type": "call"
}
] |
19112292097 |
import torch as T
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
class DeepQNetwork(nn.Module):
def __init__(self, lr, input_dims, fc1_dims, fc2_dims, n_actions):
super(DeepQNetwork, self).__init__()
self.input_dims = input_dims
self.fc... | miczed/learny-mc-learnface | DQN/Examples/DQN_Lunar_MLwithPhil.py | DQN_Lunar_MLwithPhil.py | py | 5,392 | python | en | code | 0 | github-code | 36 | [
{
"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.Linear",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_numb... |
15083780449 | import ray
import numpy as np
import gym
import tensorflow as tf
import tensorflow.contrib.slim as slim
import time
import sys
sys.path.insert(0, "/home/ubuntu/pong_py")
from pongjsenv import PongJSEnv
ray.init(num_workers=0)
n_obs = 8 # dimensionality of observations
n_h = 256 # number of h... | robertnishihara/ray-tutorial-docker | rl_exercises/pong_py_no_git/pong_py/parallel_train.py | parallel_train.py | py | 4,946 | python | en | code | 8 | github-code | 36 | [
{
"api_name": "sys.path.insert",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "ray.init",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "tensorflow.contrib.slim.fully_co... |
14489788093 | # Lab 24 - Rain Data
import datetime
import matplotlib.pyplot as plt
def open_file():
"""opens the file and returns its contents as a list separated by each row"""
with open('lab24_ankeny_rain.txt', 'r') as data:
return data.read().split("\n")
def get_dates(data):
"""accepts data and returns a list of just... | mjhcodes/pdxcodeguild | python/lab24.py | lab24.py | py | 2,881 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.pyplot.plot",
"line_number": 68,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 68,
"usage_type": "name"
},
{
"api_name": "matplotlib.pyplot.ylabel",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "mat... |
23777096489 | import re
import sys
from random import randrange, randint, choices, shuffle
from typing import List, Dict, Tuple
import numpy as np
import pandas as pd
from pepfrag import ModSite, IonType, pepfrag
from pyteomics.mass import calculate_mass
from src.fragment_matching import write_matched_fragments
from src.model.frag... | Eugleo/dibby | src/generate_data.py | generate_data.py | py | 18,105 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "src.model.peptide.Peptide",
"line_number": 37,
"usage_type": "name"
},
{
"api_name": "typing.List",
"line_number": 42,
"usage_type": "name"
},
{
"api_name": "typing.Dict",
"... |
21195656811 | import os
from setuptools import setup
def read(fname):
return open(os.path.join(os.path.dirname(__file__), fname)).read()
setup(
name='snmpdesk',
version='0.0.91',
description='Scripts for easy get snmp data',
author='Svintsov Dmitry',
author_email='spam@19216801.ru',
url='http://github.c... | uralbash/snmpdesk | setup.py | setup.py | py | 927 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "os.path.dirname",
"line_number": 5,
"usage_type": "call"
},
{
"api_name": "setuptools.setup",
"line_n... |
29432851011 | from asyncore import read
#JMP:xkalou03
__author__ = 'xkalou03'
import sys
import argparse
import re
import reader
import table
def checkParameters():
parser = argparse.ArgumentParser(description = 'Projekt do IPP.', add_help = False)
parser.add_argument('--help', action = "count", default = 0, help = 'P... | Strihtrs/IPP_Projects | JMP/jmp.py | jmp.py | py | 4,768 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "sys.stderr",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "sys.argv",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "sys.stderr",
... |
16128248265 | import functools
from importlib import import_module
from pyws.public import InvalidPath
def route(path):
def wrapper(func):
@functools.wraps(func)
def _wrapper(*args, **kwargs):
return func(*args, **kwargs)
_wrapper.__route__ = path
return _wrapper
return wrapp... | czasg/ScrapyLearning | czaSpider/dump/bootstrap_test/blogs_v1/pyws/route.py | route.py | py | 1,042 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "functools.wraps",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "importlib.import_module",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "importlib.import_module",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "pyws.... |
22450428766 | """
Team 46
Haoyue Xie 1003068 @Melbourne
Jiayu Li 713551 @Melbourne
Ruqi Li 1008342 @Melbourne
Yi Zhang 1032768 @Melbourne
Zimeng Jia 978322 @Hebei, China
"""
import json
path = "E:/Unimelb/2020semester1/COPM90024 Cluster and Cloud Computing/assignment2/code/"
filename = path + 'SA4_2016_AUST.json'
with open(file... | yzzhan4/COMP90024-AuzLife | Create City_GeoJSON file/coordinates for cities.py | coordinates for cities.py | py | 19,866 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "json.load",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "json.JSONEncoder",
"line_number": 516,
"usage_type": "call"
}
] |
27521291277 | from pyspark.sql import SparkSession
from pyspark.sql import functions as fs
spark= SparkSession.builder.appName("word_count").getOrCreate()
data= spark.read.text("book.txt")
pro_data= data.select(fs.explode(fs.split(data.value,"\\W+")).alias("words"))
pro_data.filter(pro_data.words !="")
a=pro_data.select("words")... | AmanSolanki007/Pyspark_problems | word_count_dataframe.py | word_count_dataframe.py | py | 353 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pyspark.sql.SparkSession.builder.appName",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "pyspark.sql.SparkSession.builder",
"line_number": 4,
"usage_type": "attribute"
},
{
"api_name": "pyspark.sql.SparkSession",
"line_number": 4,
"usage_type": "... |
15783422482 | # -*- coding: utf-8 -*-
"""
Created on Sat May 8 12:16:46 2021
@author: tamon
"""
import csv
import numpy as np
from scipy.interpolate import griddata
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
radius = []
angles = []
points = []
result = []
with open('angrad.csv', new... | Maselko/individual-project | Angrad.py | Angrad.py | py | 4,228 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "csv.reader",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "numpy.float64",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "numpy.mgrid",
"line_number": 35,
"usage_type": "attribute"
},
{
"api_name": "scipy.interpolate.griddata"... |
74120455144 | import pygame
from constantes import *
from auxiliar import Auxiliar
class Background:
'''
Clase para representar un fondo en un juego utilizando Pygame.
Attributes:
x (int): La coordenada x de la esquina superior izquierda del fondo.
y (int): La coordenada y de la esquina superior izquier... | valverdecristian/cristian_valverde_tp_pygame | background.py | background.py | py | 1,080 | python | es | code | 0 | github-code | 36 | [
{
"api_name": "pygame.image.load",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "pygame.image",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "pygame.transform.scale",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pygame.tra... |
39055642818 | #!/usr/bin/env python
from __future__ import print_function
import os, sys, json
import numpy as np
from ase.build import bulk, surface
from ase.units import Rydberg, Bohr
from ase.io import read
from ase.visualize import view
from ase.spacegroup import crystal
from ase.calculators.espresso import Espresso
infile... | marshallmcdonnell/sno2_ase_espresso | surfaces/surfaces_sno2.py | surfaces_sno2.py | py | 2,092 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sys.argv",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "json.loads",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "os.getcwd",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "ase.spacegroup.crystal",
"line... |
34450828117 | import pytest
from PyQt6.QtTest import QTest
from PyQt6.QtWidgets import QLineEdit
from pytestqt import qtbot
from main import OLXWork, OLXSettings
from PyQt6 import QtCore
def test_olxwork_button_stop_clicked(qtbot):
parent = OLXSettings()
widget = OLXWork(parent= parent)
widget.show()
qtbot.addWidg... | Kandel269/OLXroom | test_main.py | test_main.py | py | 3,676 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "main.OLXSettings",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "main.OLXWork",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "pytestqt.qtbot.addWidget",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pytestqt.qtbot... |
22353260658 | import torch
from .logger_utils import get_logger
import matplotlib.pyplot as plt
import numpy as np
import itertools
logger = get_logger()
def prediction(*, test_data, model, device):
"""Predict on test data and generate confusion matrix.
Args:
test_data (torch.utils.data.Dataset): Test dataset.
... | abhijitramesh/hpc-demo | utils/prediction_utils.py | prediction_utils.py | py | 1,910 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logger_utils.get_logger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "torch.zeros",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "torch.no_grad",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "torch.tensor",
"... |
11130997604 | import csv
import os
from flask import Blueprint, redirect, render_template, request
import sqlalchemy
from forms.addTeacherForm import AddTeacherForm
from models import GroupOfTeacher, Teacher, TeacherInGroup, db
from forms.editForm import EditTeacherForm
ROWS_PER_PAGE = 5
teachers_blueprint = Blueprint("teachers_b... | IngNoN/School_App | controllers/teachers.py | teachers.py | py | 4,762 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Blueprint",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "flask.request.args.get",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "flask.request.args",
"line_number": 17,
"usage_type": "attribute"
},
{
"api_name": "flask.... |
16154091028 | from django.contrib import admin
from .models import InstrumentItem
# Register your models here.
class InstrumentItemAdmin(admin.ModelAdmin):
search_fields = ['definition']
list_filter = ['instrument']
list_display = ['definition','instrument','discrimination','difficulty','guessing','upper_asymptote']
ad... | langcog/web-cdi | webcdi/cdi_forms/cat_forms/admin.py | admin.py | py | 375 | python | en | code | 7 | github-code | 36 | [
{
"api_name": "django.contrib.admin.ModelAdmin",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "django.contrib.admin",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "django.contrib.admin.site.register",
"line_number": 10,
"usage_type": "call"
},... |
15065246438 | import asyncio
import base64
import collections
import json
import struct
import sys
import aiohttp
import pytest
import six
from pytest_httpserver import RequestHandler
import consul
import consul.aio
Check = consul.Check
@pytest.fixture
def local_server(httpserver):
from pytest_httpserver import RequestHandl... | poppyred/python-consul2 | tests/test_aio.py | test_aio.py | py | 10,482 | python | en | code | 125 | github-code | 36 | [
{
"api_name": "consul.Check",
"line_number": 16,
"usage_type": "attribute"
},
{
"api_name": "pytest_httpserver.RequestHandler",
"line_number": 24,
"usage_type": "argument"
},
{
"api_name": "json.dumps",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "col... |
30055311792 | from collections import defaultdict
import os
import pandas as pd
path = '/home/djf/djf/POI/CDRF/data/Foursquare_NYC.txt'
dic = defaultdict(int)
f = open(path, 'r')
lines = f.readlines()
for line in lines:
user, t, lat, lon, POI = line.strip().split('\t')
dic[int(POI)] += 1
counts = [item[1] for item in... | Mediocre250/CTMR | long_tail.py | long_tail.py | py | 462 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.defaultdict",
"line_number": 8,
"usage_type": "call"
}
] |
6410410688 | import random
import os
import argparse
from typing import DefaultDict
# from paper "Learning Unknown from Correlations:
# Graph Neural Network for Inter-novel-protein Interaction Prediction"
standard_acids = [
('A', 1), ('C', 6), ('D', 5), ('E', 7), ('F', 2),
('G', 1), ('H', 4), ('I', 2), ('K', 5), ... | LtECoD/PPITrans | data/dscript/builddataset.py | builddataset.py | py | 5,962 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "typing.DefaultDict",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 79,
"usage_type": "call"
},
{
"api_name": "os.path",
... |
10423506179 | # coding: utf-8
import xlrd
def getProgramList(filepath):
program_list = dict()
program_list[u'网络剧'] = []
program_list[u'网络电影'] = []
program_list[u'网络综艺'] = []
data = xlrd.open_workbook(filepath)
table = data.sheet_by_name(u'网络剧')
nrows = table.nrows
ncols = table.ncols
for i in range(2, nrows):
one_p... | LayneIns/CrawlerProject | crawl2/dataHelper/fetchProgram.py | fetchProgram.py | py | 1,465 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "xlrd.open_workbook",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "xlrd.open_workbook",
"line_number": 45,
"usage_type": "call"
}
] |
37213151621 | #!/usr/bin/env python3
import argparse
from pprint import pprint
import json
import hlib
def check_temp(cl, device_id):
device_name = None
# first, try and find the device as a device
url = f"/clip/v2/resource/device/{device_id}"
resp = cl.get(url)
if resp.status_code == 200:
... | parlaynu/hue-utilities | bin/check-temp.py | check-temp.py | py | 2,946 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 54,
"usage_type": "call"
},
{
"api_name": "hlib.find_bridge",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "hlib.load_config",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "hlib.new_cl... |
41366597699 | import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import os
def MyPlotSO(CompMethod,trials,MaxFuncEvals,method,problem):
##% Plot
figcount=0
Convergence = np.zeros((int(CompMethod.shape[0]/trials), MaxFuncEvals))
count=-1
for i in range(0,int(Co... | KZervoudakis/Mayfly-Optimization-Algorithm-Python | plotting.py | plotting.py | py | 5,858 | python | en | code | 4 | github-code | 36 | [
{
"api_name": "numpy.zeros",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.array",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot",
"line_num... |
15130917408 | # %%
from pprint import pprint
from datasets import load_dataset
test_file = "../data/ekonspacing/test_small.txt"
val_file = "../data/ekonspacing/val_small.txt"
train_file = "../data/ekonspacing/train_small.txt"
# %%
dataset = load_dataset(
"ekonspacing.py",
name="small",
data_files={"train": str(train_f... | entelecheia/transformer-datasets | datasets/ekonspacing/ekonspacing_test.py | ekonspacing_test.py | py | 500 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datasets.load_dataset",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "pprint.pprint",
"line_number": 20,
"usage_type": "call"
}
] |
17079442964 | import logging
from .html import extract_html_text
from .pdf import extract_pdf_text
logger = logging.getLogger(__name__)
def extract_text(file_path: str) -> str:
"""Extract text from any kind of file as long as it's html or pdf"""
try:
if file_path.endswith('.html'):
return extract_htm... | amy-langley/tracking-trans-hate-bills | lib/util/misc.py | misc.py | py | 691 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "html.extract_html_text",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pdf.extract_pdf_text",
"line_number": 17,
"usage_type": "call"
}
] |
71038521063 | import numpy as np
try:
import mc
except Exception:
pass
import cv2
import os
from PIL import Image
import torch
from torch.utils.data import Dataset
import torchvision.transforms as transforms
import utils
from . import reader
class PartialCompDataset(Dataset):
def __init__(self, config, phase):
... | XiaohangZhan/deocclusion | datasets/partial_comp_dataset.py | partial_comp_dataset.py | py | 6,088 | python | en | code | 764 | github-code | 36 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 18,
"usage_type": "name"
},
{
"api_name": "torchvision.transforms.Compose",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms",
"line_number": 31,
"usage_type": "name"
},
{
"ap... |
23751441892 | import os
import argparse
import matplotlib.pyplot as plt
from matplotlib import cm
import torch
import numpy as np
import statistics as st
import csv
import seaborn as sns
from timeseries import EchoCard
from quality_classification import predict_single as predict_acq
from quality_classification import CardioNet
fro... | HelmholtzAI-Consultants-Munich/Echo2Pheno | Module I/run4single.py | run4single.py | py | 25,479 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "matplotlib.colors.cnames",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.colors",
"line_number": 30,
"usage_type": "name"
},
{
"api_name": "colorsys.rgb_to_hls",
"line_number": 33,
"usage_type": "call"
},
{
"api_name": "m... |
14940809637 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import sys
try:
import petsclinter as pl
except ModuleNotFoundError as mnfe:
try:
petsc_dir = os.environ['PETSC_DIR']
except KeyError as ke:
raise RuntimeError('Must set PETSC_DIR environment variable') from ke
sys.path.insert(0, os.path.join(pets... | firedrakeproject/slepc | lib/slepc/bin/maint/slepcClangLinter.py | slepcClangLinter.py | py | 3,156 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "sys.path.insert",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line... |
41896395893 | import cv2
import numpy as np
import csv
import math
img = cv2.imread(".//new_dataset//250.jpg")
img = cv2.GaussianBlur(img , (5 , 5) , 0)
n = 64
div = 256//n #n is the number of bins, here n = 64
rgb = cv2.split(img)
q = []
for ch in rgb:
vf = np.vectorize(lambda x, div: int(x//div)*div)
quanti... | kumar6rishabh/cbir-search-engine | ccv_searcher.py | ccv_searcher.py | py | 1,968 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.imread",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "cv2.GaussianBlur",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "cv2.split",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "numpy.vectorize",
"line_numbe... |
71534616424 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
from icalendar import Calendar, Event
from datetime import *
from dateutil.parser import parse
from pytz import UTC # timezone
cal_file = '/Users/gyyoon/Desktop/pentaa.ics'
MEETING_STR = '[회의]'
TEATIME_STR = '[Tea-Time]'
WORK_STR = '[업무]'
NONWORK_STR = '[비업무]'
LUNCH_ST... | Dry8r3aD/ics_parser | run.py | run.py | py | 8,555 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "icalendar.Calendar.from_ical",
"line_number": 245,
"usage_type": "call"
},
{
"api_name": "icalendar.Calendar",
"line_number": 245,
"usage_type": "name"
}
] |
22706853086 | import code
import gym
import torch
from tqdm import trange
import numpy as np
import components.prioritized_memory
import components.memory
from components.filesys_manager import ExperimentPath
class BaseTrainer:
def __init__(self, args):
# init experiment hyper-parameters
self.args = args
... | APM150/Continuous_Envs_Experiments | mujoco/trainers/base_trainer.py | base_trainer.py | py | 10,727 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "components.filesys_manager.ExperimentPath",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "gym.make",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "gym.make",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "component... |
22926496902 | import cv2
import math
# Source: https://richardpricejones.medium.com/drawing-a-rectangle-with-a-angle-using-opencv-c9284eae3380
# Made slight adjustments to color
def draw_angled_rec(x0, y0, width, height, angle, img, color):
_angle = angle * math.pi / 180.0
b = math.cos(_angle) * 0.5
a = math.sin(_angl... | MatanPazi/opt_fabric_layout | minAreaRect_Test.py | minAreaRect_Test.py | py | 2,974 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "math.pi",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "math.cos",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "math.sin",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "cv2.line",
"line_number": 20,
"... |
15733506905 | __docformat__ = "reStructuredText"
__author__ = "davidh"
import logging
import os
import re
import sys
from collections import namedtuple
from datetime import datetime, timedelta
from glob import glob
LOG = logging.getLogger(__name__)
FILENAME_RE = r"HS_H08_(?P<date>\d{8})_(?P<time>\d{4})_(?P<band>B\d{2})_FLDK_(?P<r... | ssec/sift | uwsift/project/organize_data_topics.py | organize_data_topics.py | py | 6,413 | python | en | code | 45 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "re.compile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "collections.namedtuple",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "datetime.datetime... |
29290663147 | from django.db import models
from wagtail.admin.edit_handlers import MultiFieldPanel, RichTextFieldPanel, StreamFieldPanel
from wagtail.core.fields import RichTextField, StreamField
from wagtail.snippets.models import register_snippet
from ..modules import text_processing
from .. import configurations
from ..blogs.blo... | VahediRepositories/AllDota | dotahub/home/blogs/models.py | models.py | py | 1,626 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.db.models.Model",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "django.db.models",
"line_number": 12,
"usage_type": "name"
},
{
"api_name": "wagtail.core.fields.RichTextField",
"line_number": 13,
"usage_type": "call"
},
{
"ap... |
7182836122 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# @Author: José Sánchez-Gallego (gallegoj@uw.edu)
# @Date: 2023-01-19
# @Filename: test_callback.py
# @License: BSD 3-clause (http://www.opensource.org/licenses/BSD-3-Clause)
import unittest.mock
import click
from click.testing import CliRunner
from unclick.core import... | albireox/unclick | tests/test_callback.py | test_callback.py | py | 1,732 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "click.command",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "click.argument",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "click.argument",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "click.option",
"line_... |
27549684390 | """
Query builder examples.
NOTES:
# Infix notation (natural to humans)
NOT ((FROM='11' OR TO="22" OR TEXT="33") AND CC="44" AND BCC="55")
# Prefix notation (Polish notation, IMAP version)
NOT (((OR OR FROM "11" TO "22" TEXT "33") CC "44" BCC "55"))
# Python query builder
NOT(AND(OR(from_='11', to='22', t... | ikvk/imap_tools | examples/search.py | search.py | py | 2,613 | python | en | code | 608 | github-code | 36 | [
{
"api_name": "imap_tools.OR",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "datetime.date",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "imap_tools.NOT",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "imap_tools.OR",
"line_... |
15857685473 | # -*- coding: utf-8 -*-
import os
import sys
import webbrowser
from invoke import task
docs_dir = 'docs'
build_dir = os.path.join(docs_dir, '_build')
@task
def readme(ctx, browse=False):
ctx.run("rst2html.py README.rst > README.html")
if browse:
webbrowser.open_new_tab('README.html')
def build_doc... | CenterForOpenScience/COSDev | tasks.py | tasks.py | py | 1,383 | python | en | code | 6 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "webbrowser.open_new_tab",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "invoke.task",
"li... |
74160129703 | '''
Algorithm: just count how many characters(frequency more than one regard it as one)
'''
#!/bin/python3
import sys
from collections import Counter
def stringConstruction(s):
# Complete this function
return len(Counter(s).values())
if __name__ == "__main__":
q = int(input().strip())
for a0 in range(... | CodingProgrammer/HackerRank_Python | (Strings)String_Construction(Counter_FK1).py | (Strings)String_Construction(Counter_FK1).py | py | 413 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.Counter",
"line_number": 10,
"usage_type": "call"
}
] |
33531980673 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Written by Lucas Sinclair and Paul Rougieux
JRC biomass Project.
Unit D1 Bioeconomy.
"""
# Built-in modules #
# Third party modules #
# First party modules #
import autopaths
from autopaths import Path
from autopaths.auto_paths import AutoPaths
from aut... | xapple/cbmcfs3_runner | cbmcfs3_runner/scenarios/base_scen.py | base_scen.py | py | 4,131 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "autopaths.Path",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "autopaths.auto_paths.AutoPaths",
"line_number": 52,
"usage_type": "call"
},
{
"api_name": "tqdm.tqdm",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "cbmcfs3_runne... |
22330605569 | import asyncio
import logging
import os
import re
import warnings
from asyncio import Future
from functools import wraps
from inspect import signature
from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union
from tqdm.auto import tqdm
from rubrix._constants import (
DATASET_NAME_REGEX_PATTER... | Skumarh89/rubrix | src/rubrix/client/api.py | api.py | py | 24,714 | python | en | code | null | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 66,
"usage_type": "call"
},
{
"api_name": "rubrix.utils.setup_loop_in_thread",
"line_number": 72,
"usage_type": "call"
},
{
"api_name": "asyncio.run_coroutine_threadsafe",
"line_number": 87,
"usage_type": "call"
},
{
... |
947951498 | #!/home/shailja/.virtualenv/my_env/bin/python3
import requests
import bs4
import sys
content = sys.argv[1]
def display_actual_text(text,para_no):
text = text[para_no]
[s.extract() for s in text(['style', 'script', '[document]', 'head', 'title'])]
visible_text = text.getText()
print(visible_text)
w... | SKT27182/web_scaping | wiki_search.py | wiki_search.py | py | 1,728 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sys.argv",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "requests.get",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 19,
"usage_type": "call"
}
] |
9866560419 | from mlagents_envs.environment import UnityEnvironment
from mlagents_envs.environment import ActionTuple
from mlagents_envs.side_channel.engine_configuration_channel import EngineConfigurationChannel
import numpy as np
import mlagents.trainers
from collections import namedtuple
obs = namedtuple(
'obs',
... | chagmgang/baselines | baselines/env/simple_drone.py | simple_drone.py | py | 3,699 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "collections.namedtuple",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "mlagents_envs.side_channel.engine_configuration_channel.EngineConfigurationChannel",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "mlagents.trainers.trainers",
"line_... |
15006294998 | import pandas as pd
from bs4 import BeautifulSoup as bs
#Criando objeto BS
def get_file(file_name):
content = []
with open(file_name, 'r') as file:
content = file.readlines()
content = ''.join(content)
soup = bs(content,'xml')
return soup
#Buscando parents
def get_parents(soup):
... | jonesamandajones/powercenter | create_excel.py | create_excel.py | py | 3,991 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "bs4.BeautifulSoup",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 41,
"usage_type": "call"
},
{
"api_name": "pandas.read_excel",
"line_number": 50,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame... |
71592171944 | #!/bin/python3
import math
import os
import random
import re
import sys
from collections import deque
# Complete the bfs function below.
def bfs(n, m, edges, s):
#Create adjacency list empty on array
neighbors = [[] for i in range(n) for j in range(1)]
#Include neighbors of each vertex, with index minus 1... | Gabospa/computer_science | bfs.py | bfs.py | py | 1,506 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.deque",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 46,
"usage_type": "attribute"
}
] |
521538009 | #imports
import numpy as np
import matplotlib.pyplot as plt
import scipy.constants as const
from scipy.special import iv as I0
from scipy.special import kv as K0
#Define Global Variables
L_geo = 55.6e-9
Z0 = 50.0
F0_base = 0.95e9 #At lowest Temp
squares= 27223
c_couple = 1.5e-14
TC = 1.5
Delta_0 = (3.5*const.Bo... | Ashleyyyt/Characterizing-KIDs | Simulate KID.py | Simulate KID.py | py | 7,177 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "scipy.constants.Boltzmann",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "scipy.constants",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "numpy.pi",
"line_number": 18,
"usage_type": "attribute"
},
{
"api_name": "scipy.co... |
28886388336 | # from urllib import request
from django.shortcuts import render, redirect
from .models import Post, Comment
from .forms import CommentForm, PostUpdateForm
# from django.http import HttpResponseRedirect
from django.contrib.auth.decorators import login_required
# LoginRequiredMixin is simply the class based version fo... | MSKose/django-blog-app | blog/views.py | views.py | py | 6,019 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "models.Post.objects.all",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "models.Post.objects",
"line_number": 26,
"usage_type": "attribute"
},
{
"api_name": "models.Post",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "django.s... |
74090977062 | import math
from datetime import datetime
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
from firebase_admin import firestore
import parseIntervalFiles as pif
import parseActivityFiles as paf
hervdir = "C:\\Users\\Ju\\GDrive\\Projects\\HeRV\\"
## Firestore co... | jucc/HeRV_analysis | pipeline/convert_csv_firestore.py | convert_csv_firestore.py | py | 3,459 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "datetime.datetime",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "firebase_admin.db.collection",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "fire... |
1693307394 | import numpy as np
import math
import cv2
center_points = {}
objects_bbs_ids = []
id_count = 0
vechical_count = 0
count = 0
person_id = 0
camera = cv2.VideoCapture("video.mp4")
object_detector = cv2.createBackgroundSubtractorMOG2(history = None, varThreshold = None)
kernelOp = np.ones((3,3), np.uint8)
kernelC1 = n... | Computer4062/Python-Projects | Road Tracker/counter.py | counter.py | py | 2,880 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.VideoCapture",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "cv2.createBackgroundSubtractorMOG2",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.ones",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.... |
19199461708 | from torch.utils.data import Dataset
import numpy as np
from pathlib import Path
import pandas as pd
import torch
from dpipe.io import load_numpy
class BraTSDataset(Dataset):
def __init__(self, meta: pd.DataFrame, source_folder: [str, Path], nonzero_mask=False, transform=None):
if isinstance(source_folder... | kurmukovai/hse_projects | 2020/Anvar/data_loader.py | data_loader.py | py | 1,392 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "pandas.DataFrame",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "pathlib.Path",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "pathlib.Pa... |
27194927025 | import logging
import numpy as np
from sklearn.model_selection import train_test_split, StratifiedKFold
from utils import logging as lg
from heatmap_tutorial import utils as ht_utils
lg.set_logging()
def get_mnist(dataset, dir_path='./data/mnist'):
if dataset == 'train':
prefix = 'train'
elif dat... | p16i/thesis-designing-recurrent-neural-networks-for-explainability | src/utils/data_provider.py | data_provider.py | py | 17,506 | python | en | code | 14 | github-code | 36 | [
{
"api_name": "utils.logging.set_logging",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "utils.logging",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "logging.debug",
"line_number": 22,
"usage_type": "call"
},
{
"api_name": "numpy.fromfile"... |
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