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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
40057143195 | #!/usr/bin/env python3
import scapy.all as scapy
import argparse
from datetime import datetime
import sys
def ip():
parse = argparse.ArgumentParser()
parse.add_argument("-ip", dest="ip", help="Needs IP range /24")
parse.add_argument("-i", dest="interface", help='Needs interface')
parse.add_... | WMDA/ctf | tools/python_scripts/network_scanner.py | network_scanner.py | py | 1,853 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "scapy.all.ARP",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "scapy.all",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "scapy.all.Ether",
... |
22568917957 | from .workspace import get_workspace_location, get_workspace_state, resolve_this
from .cache import Cache
from .config import Config
from .resolver import find_dependees
from .ui import warning, fatal, show_conflicts
from .cmd_git import has_package_path, get_head_branch
from .util import iteritems, yaml_dump
from pygi... | fkie/rosrepo | src/rosrepo/cmd_export.py | cmd_export.py | py | 3,924 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "pygit2.Repository",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "ui.warning",
"line_nu... |
40211358205 | #%% [markdown]
# ## Preliminaries
#%%
from pkg.utils import set_warnings
set_warnings()
import time
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from giskard.utils import get_random_seed
from myst_nb import glue as default_glue
from pkg.data import load_network_palette... | neurodata/bilateral-connectome | misc_scripts/perturbations_unmatched_deep_dive.py | perturbations_unmatched_deep_dive.py | py | 6,901 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "pkg.utils.set_warnings",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pkg.io.savefig",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.close",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "matplotl... |
6363206566 | from itertools import count
global_index = 1
global_bank_fee = 1
global_bank_win = 2
global_bank_lose = 3
class smartPlayer:
_ids = count(0)
def __init__(self, trustor_or_trustee, trust_coefficient, beta):
global global_bank_fee
global_bank_fee = beta
self.id = next(self._ids)
... | snirsh/TrustGame | SmartPlayer.py | SmartPlayer.py | py | 2,264 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "itertools.count",
"line_number": 10,
"usage_type": "call"
}
] |
7086566402 | from django.shortcuts import render,redirect
from adm.models import *
def ViewInicio(request):
listJogos = Jogo.objects.select_related('Vencedora','Perdedora').all()
context = {
"listJogos":listJogos,
}
return render(request,"inicio.html",context)
def ViewCadastro(request):
if request.me... | michel110299/Administrador_tranca | adm/views.py | views.py | py | 7,068 | python | pt | code | 0 | github-code | 36 | [
{
"api_name": "django.shortcuts.render",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.redirect",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "django.shortcuts.render",
"line_number": 45,
"usage_type": "call"
},
{
"api_nam... |
28891628391 | """Tests for traces.traces."""
import ast
import collections
import sys
import textwrap
from pytype import config
from pytype.pytd import pytd
from pytype.pytd import pytd_utils
from pytype.tests import test_utils
from pytype.tools.traces import traces
import unittest
_PYVER = sys.version_info[:2]
_BINMOD_OP = "BINA... | google/pytype | pytype/tools/traces/traces_test.py | traces_test.py | py | 11,794 | python | en | code | 4,405 | github-code | 36 | [
{
"api_name": "sys.version_info",
"line_number": 14,
"usage_type": "attribute"
},
{
"api_name": "pytype.tools.traces.traces.MatchAstVisitor",
"line_number": 22,
"usage_type": "attribute"
},
{
"api_name": "pytype.tools.traces.traces",
"line_number": 22,
"usage_type": "name... |
38801618139 | from transformers import pipeline
# classifier = pipeline('sentiment-analysis')
# res = classifier(
# 'We are not very happy to introduce pipeline to the transformers repository.')
pipe = pipeline('question-answering')
res = pipe({
'question': 'What is the name of the repository ?',
'context': 'Pipeline h... | taterboom/simple-tts | index.py | index.py | py | 397 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "transformers.pipeline",
"line_number": 7,
"usage_type": "call"
}
] |
39472235141 | import json
from flask import request, jsonify
from flask_restful import Resource
from werkzeug.exceptions import BadRequest
from managers.brand import BrandManager
from models import RoleType
from models.products import *
from schemas.request.brand import CreateBrandRequestSchema, EditBrandRequestSchema
from schemas... | a-angeliev/Shoecommerce | server/resources/brand.py | brand.py | py | 2,486 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "dotenv.load_dotenv",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "cloudinary.config",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "flask_restful.Resource",
"line_number": 28,
"usage_type": "name"
},
{
"api_name": "managers.... |
38672578742 | import shodan
import requests
from shodan import Shodan
'''
api = Shodan('Insert_your_Shodan_Api_Key')
print(api.search(query='product:nginx', facets='country,org'))
'''
SHODAN_API_KEY = "Insert_your_Shodan_Api_Key"
api = shodan.Shodan(SHODAN_API_KEY)
target = 'www.packtpub.com'
dnsResolve = 'https://api.shodan.io/... | MuhammadAli947/shodanCode | ShodanScans.py | ShodanScans.py | py | 1,526 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "shodan.Shodan",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 19,
"usage_type": "call"
}
] |
36211707503 | #file a transaction
#any changes to the users balanace should be reflected in the account file
import datetime
def transaction_options(accounts_path, line_number):
stay_logged_in = True
while stay_logged_in == True:
ask = input('Would you like to make a transaction, return to the homepage, or logout ... | 2105-may24-devops/fletcher-project0 | transaction_module.py | transaction_module.py | py | 3,661 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime.strptime",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "datetime.datetime",
"line_number": 57,
"usage_type": "attribute"
}
] |
11371604753 | import logging
from sklearn.metrics import accuracy_score
from pytorch_tabular import TabularModel
from pytorch_tabular.config import DataConfig, OptimizerConfig, TrainerConfig
from ml.solvers.base_solver import Solver
class PytorchTabularSolver(Solver):
def init_model(self):
super(PytorchTabularSolver,... | gregiberri/coupon | ml/solvers/pytorch_tabular_solver.py | pytorch_tabular_solver.py | py | 2,165 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "ml.solvers.base_solver.Solver",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "pytorch_tabular.config.DataConfig",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "pytorch_tabular.config.TrainerConfig",
"line_number": 20,
"usage_type": "... |
40587003321 | from django.contrib.auth.base_user import AbstractBaseUser
from django.contrib.auth.decorators import login_required
from django.http import (HttpRequest, HttpResponse, HttpResponseNotFound,
HttpResponseRedirect)
from django.shortcuts import redirect, render
from django.urls import reverse_lazy... | Xewus/Examiner | src/questions/views.py | views.py | py | 4,430 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "django.urls.reverse_lazy",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "django.urls.reverse_lazy",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "django.urls.reverse_lazy",
"line_number": 14,
"usage_type": "call"
},
{
"api_na... |
39479105306 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.core.management.base import BaseCommand, CommandError
from cards.search import searchservice
from cards.models import Card, BaseCard
from cards.models import PhysicalCard
import json
from django.utils import dateparse
import codecs
import s... | jcrickmer/mtgdbpy | cards/management/commands/reindex_es.py | reindex_es.py | py | 5,648 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.core.management.base.BaseCommand",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "cards.search.searchservice.search",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "cards.search.searchservice",
"line_number": 45,
"usage_type": "... |
26419037040 | import datetime
from functools import wraps
from django.http import HttpResponseRedirect
from django.urls import reverse
from django.utils import timezone
def authentication_required(function=None):
def decorator(view_func):
@wraps(view_func)
def _wrapped_view(request, *args, **kwargs):
... | qiuosier/Pisces | decorators.py | decorators.py | py | 1,068 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "datetime.datetime",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "django.utils.timezone.now",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "django.utils.timezone",
"line_number": 19,
"usage_type": "name"
},
{
"api_name":... |
73574130663 | import torch
import torch.nn as nn
import torch.nn.functional as F
from policy import discrete_policy_net
from critic import attention_critic
import numpy as np
from buffer import replay_buffer
from make_env import make_env
import os
import random
from gym.spaces.discrete import Discrete
from gym.spaces.box ... | deligentfool/MAAC_pytorch | model_mpe.py | model_mpe.py | py | 12,313 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "make_env.make_env",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "gym.spaces.discrete.Discrete",
"line_number": 34,
"usage_type": "argument"
},
{
"api_name": "critic.attention_critic",
"line_number": 38,
"usage_type": "call"
},
{
"api_na... |
38650316304 | #%%
import pyautogui, pyperclip
Y = 550 # 507
X = 800 # 740
pyperclip.copy("직")
pyautogui.moveTo(x=X, y=Y, duration=0.001)
pyautogui.click(clicks=1)
pyautogui.hotkey("ctrl", "v")
pyperclip.copy("업")
pyautogui.moveTo(x=X, y=Y, duration=1)
pyautogui.click(clicks=1)
pyautogui.hotkey("ctrl", "v")
pypercli... | shetshield/src | stitching_img/pymacro.py | pymacro.py | py | 1,353 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pyperclip.copy",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "pyautogui.moveTo",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "pyautogui.click",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "pyautogui.hotkey",
"... |
38313990919 | from flask import flash
from flask_app.config.mysqlconnection import connectToMySQL
from flask_app.models import user
from flask_app.models import message
class Event:
db = "plannendar_schema"
def __init__(self, data):
self.id = data['id']
self.event = data['event']
self.description =... | rchuu/plannendar | flask_app/models/event.py | event.py | py | 5,351 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask_app.config.mysqlconnection.connectToMySQL",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "flask_app.config.mysqlconnection.connectToMySQL",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "flask_app.config.mysqlconnection.connectToMySQL",... |
12410410025 | """
Update existing "embargo_approved_no_user" logs to link to registered project instead
of the registration.
"""
from copy import deepcopy
import logging
import sys
from modularodm import Q
from framework.transactions.context import TokuTransaction
from website.models import Node, NodeLog
from website.app import i... | karenhanson/osf.io_rmap_integration_old | scripts/fix_embargo_approved_logs.py | fix_embargo_approved_logs.py | py | 1,458 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "website.models.NodeLog.find",
"line_number": 26,
"usage_type": "call"
},
{
"api_name": "website.models.NodeLog",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "... |
35217860162 | from itertools import product
import sys
from bs4 import BeautifulSoup
from selenium import webdriver
import time
import json
import random
sys.path.append('../..')
from lib import excelUtils
from lib import httpUtils
from lib import textUtil
from lib.htmlEleUtils import getNodeText
from lib.htmlEleUtils import getInn... | Just-Doing/python-caiji | src/work/20230205/parchem.py | parchem.py | py | 2,568 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "sys.path.append",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "selenium.webdriver.ChromeOptions",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "selenium... |
7416408824 | import pywt
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
plt.style.use("resources/figstyle.mplstyle")
FIG_WIDTH = 2.3 * 7.16
# Gaussian fitting utils
from scipy import optimize
def fit_generalized_gaussian(x):
μ0 = x.mean()
σ0 = x.std()
β0 = 2
res = optimize.minimiz... | mattbit/wavelet-wqn-acha | acha_scripts/02_figure_2__coeff_distributions.py | 02_figure_2__coeff_distributions.py | py | 4,260 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "matplotlib.pyplot.style.use",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.style",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot",
"line_number": 7,
"usage_type": "name"
},
{
"api_name"... |
10246834959 | import os
import argparse
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Some hyperparameters')
parser.add_argument('--epochs', type=int, default=200)
parser.add_argument('--frac', type=float, default=0.1)
... | jinwoolim8180/fl-sparse-masking | accuracy.py | accuracy.py | py | 3,163 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 67,
"usage_type": "call"
},
{
"api_name": "matplot... |
19074906476 | from collections import Iterator, Iterable
#global set_num
#set_num = 0
class Disjoint_set(Iterable):
def __init__(self, element=None):
self.head = element
self.tail = element
element.set = self
#global set_num
#set_num += 1
def add_element(self, element):
... | LouisYLWang/Algorithms | Clustering_algorithm/Disjoint_set.py | Disjoint_set.py | py | 2,199 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "collections.Iterable",
"line_number": 7,
"usage_type": "name"
}
] |
39804183733 | import os
from celery import Celery
# Set the default Django settings module for the 'celery' program.
# similar to the setup in asgi.py
# os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'prolube76site.settings')
app = Celery('prolube76site')
# Using a string here means the worker doesn't have to serialize
# the co... | zjgcainiao/new_place_at_76 | prolube76site/celery.py | celery.py | py | 952 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "celery.Celery",
"line_number": 9,
"usage_type": "call"
}
] |
31566863140 | import sys
import csv
# preprocessing
import gensim
from gensim.utils import simple_preprocess
import re
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
# lemmitization
from nltk.stem import WordNetLemmatizer
def pre_processor():
user_input = input('Please enter a dream... | connormeaton/dream_cluster | src/app/SampleTextPreprocessor.py | SampleTextPreprocessor.py | py | 1,906 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "re.sub",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 25,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "re.sub",
"line_number": 29,
"usage_type"... |
12185526029 | """Inference for 2D US Echocardiography EchoNet dataset."""
import os
import numpy as np
import torch
import torchvision.transforms as transforms
import torch.nn.functional as F
from PIL import Image
from torch.autograd import Variable
import matplotlib.pyplot as plt
from models.unet import UNet
from models.cenet impo... | SanoScience/TTTS_CV | src/inference.py | inference.py | py | 2,235 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "models.fpn.FPN",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "torch.load",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "torchvision.transforms.Compose",
"line_number": 32,
"usage_type": "call"
},
{
"api_name": "torchvision.... |
69997777065 | from re import split
from typing import Dict, Mapping
from elasticsearch import Elasticsearch
import cbor
import json
from trec_car.read_data import *
class IndexManagement:
def __init__(self):
self.es_cli = Elasticsearch(
timeout=200, max_retries=15, retry_on_timeout=True)
self.es_cli... | Hanifff/ConversationalAssistance | index_data.py | index_data.py | py | 3,917 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "elasticsearch.Elasticsearch",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"line_number": 46,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "json.dumps",
"l... |
19348729652 | from app import app
from flask import request, jsonify, make_response
from api_exception import ApiException
from data.internal_configurations.internal_configurations import InternalConfigurations
@app.errorhandler(ApiException)
def handle_invalid_service(error):
response = jsonify(error.to_dict())
response.s... | mbast100/st-joseph-backend-services | routes/internal_configurations.py | internal_configurations.py | py | 1,885 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "flask.jsonify",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "app.app.errorhandler",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "api_exception.ApiException",
"line_number": 7,
"usage_type": "argument"
},
{
"api_name": "app.ap... |
35609489128 | from math import sqrt
import torch
from torch import nn
class FSRCNN(nn.Module):
"""
Args:
upscale_factor (int): Image magnification factor.
"""
def __init__(self, upscale_factor: int) -> None:
super(FSRCNN, self).__init__()
# Feature extraction layer.
self.feature_ex... | gmlwns2000/sharkshark-4k | src/upscale/model/fsrcnn/model.py | model.py | py | 2,315 | python | en | code | 14 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "torch.nn.Sequential",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "torch.nn",
"line_... |
33532112483 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
A script to test if the associations.csv are good.
Typically you would run this file from a command line like this:
ipython3.exe -i -- /deploy/cbmcfs3_runner/scripts/check_associations.py
"""
# Built-in modules #
# Third party modules #
import pandas
from tqd... | xapple/cbmcfs3_runner | scripts/associations/check_associations.py | check_associations.py | py | 4,628 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "autopaths.auto_paths.AutoPaths",
"line_number": 44,
"usage_type": "call"
},
{
"api_name": "plumbing.databases.access_database.AccessDatabase",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "plumbing.cache.property_cached",
"line_number": 46,
"usa... |
16721355609 | import torch
import torch.nn.functional as F
from torch.distributions import Normal
from torch.utils.data.sampler import BatchSampler, SubsetRandomSampler
from torch.nn.utils import clip_grad_norm_
from PPO_Continuous.version2.Network import Actor, Critic
class PPO(object):
def __init__(self,
st... | zhihangmuzi/deep-reinforcement-learning-with-pytorch | PPO_Continuous/version2/Agent.py | Agent.py | py | 3,981 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PPO_Continuous.version2.Network.Actor",
"line_number": 38,
"usage_type": "call"
},
{
"api_name": "torch.optim.Adam",
"line_number": 39,
"usage_type": "call"
},
{
"api_name": "torch.optim",
"line_number": 39,
"usage_type": "attribute"
},
{
"api_name"... |
12259799552 | from PySide2 import QtWidgets
import ui.devicesDialog_ui
import input.audio
class form(QtWidgets.QDialog, ui.devicesDialog_ui.Ui_Dialog):
def __init__(self):
super(form, self).__init__()
self.setupUi(self) #setup user interface
self.currentDevice = 0 #set default device
self.butto... | HamerKits/RoscoeQRSSViewer | devicesDialog.py | devicesDialog.py | py | 948 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "PySide2.QtWidgets.QDialog",
"line_number": 5,
"usage_type": "attribute"
},
{
"api_name": "PySide2.QtWidgets",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "ui.devicesDialog_ui.devicesDialog_ui",
"line_number": 5,
"usage_type": "attribute"
},
... |
3270527178 | """
Model implementation.
"""
from helper import cache_func, INIT_METHODS
import tensorflow as tf
class CNNModel:
"""
CNN model implementation. Covers the implementations for both the large and the
compact network.
"""
def __init__(self, data, target, model_params, data_params):
self.data ... | Oguzhanka/face_attractiveness | models/cnn_model.py | cnn_model.py | py | 13,191 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tensorflow.compat.v1.get_variable",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "tensorflow.compat",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "helper.INIT_METHODS",
"line_number": 31,
"usage_type": "name"
},
{
"api_... |
31635729829 | import os
import torch
import torchvision
import random
import pandas as pd
import numpy as np
import torch.nn as nn
import matplotlib.pyplot as plt
from PIL import Image
import cv2
import torch.nn.functional as F
import torchvision.transforms as transforms
import torchvision.models as models
from torc... | a20815579/cat_face_detection | cat_CNN.py | cat_CNN.py | py | 13,278 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "cv2.resize",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "cv2.copyMakeBorder",
"line_number": 47,
"usage_type": "call"
},
{
"api_name": "cv2.BORDER_CONSTANT",
"line_number": 47,
"usage_type": "attribute"
},
{
"api_name": "torch.utils.da... |
21848108182 | import numpy as np
from sklearn.externals.joblib import Parallel, delayed
from multiprocessing import cpu_count
def apply_parallel_joblib(func, data, *args, chunk=None, overlap=10,
n_jobs=None, **kwargs):
"""
Apply a function in parallel to overlapping chunks of an array
Parameters
----------
... | emmanuelle/skimage-sprint | chunk_joblib.py | chunk_joblib.py | py | 1,921 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "multiprocessing.cpu_count",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "sklearn.externals.joblib.Parallel",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "sklearn.externals.joblib.delayed",
"line_number": 57,
"usage_type": "call"
... |
24396409804 | import logging
logger = logging.getLogger(__name__)
def do_something():
logger.debug(
'Detailed information, typically of interest only when diagnosing problems.')
logger.info('Confirmation that things are working as expected.')
logger.warning(
'An indication that something unexpected hap... | jmhart/python-template | src/stuff/thing.py | thing.py | py | 656 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 3,
"usage_type": "call"
}
] |
2986896269 | import os
import h5py
import numpy as np
class bcolors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKCYAN = '\033[96m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
if 'KAGGLE_BASE_URL' in os.environ:
challen... | felix-20/gravitational_oceans | src/helper/utils.py | utils.py | py | 5,376 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "os.environ",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_nu... |
12803394908 | import urllib2
import json
headers = {'Content-Type': 'application/json; charset=utf-8'}
XXX_HOST = "http://xxx.xxx.com/xxx-app/"
# post请求，json格式数据
def post_json(url, header, request_data):
req = urllib2.Request(url, request_data, header)
page = urllib2.urlopen(req)
res = page.read()
page.close()
... | AldrichYang/HelloPython2 | src/http/http_helper.py | http_helper.py | py | 690 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "urllib2.Request",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "urllib2.urlopen",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "urllib2.Request",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "urllib2.urlopen",
... |
13425691279 | ### Unzip the Dataset
# importing the zipfile module
from zipfile import ZipFile
import pandas as pd
import random
# loading the temp.zip and creating a zip object
with ZipFile("./resources/Sentences_from_Stormfront_dataset.zip", 'r') as zip_oject:
# Extracting all the members of the zip
# into a specific loc... | Speymanhs/SemEval_2023_Task_11_Lonea | reading_dataset_stormfront.py | reading_dataset_stormfront.py | py | 1,887 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "zipfile.ZipFile",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "pandas.read_csv",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "random.randint",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "random.randint",
"l... |
71578985703 | #!/usr/bin/env python
import vtk
def main():
pd_fn, scene_fn = get_program_parameters()
colors = vtk.vtkNamedColors()
polyData = ReadPolyData(pd_fn)
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputData(polyData)
actor = vtk.vtkActor()
actor.SetMapper(mapper)
actor.GetProperty().Set... | lorensen/VTKExamples | src/Python/Utilities/SaveSceneToFile.py | SaveSceneToFile.py | py | 5,409 | python | en | code | 319 | github-code | 36 | [
{
"api_name": "vtk.vtkNamedColors",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "vtk.vtkPolyDataMapper",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "vtk.vtkActor",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "vtk.vtkRenderer"... |
3479784873 | # This is the model definition of retrieval model.
from typing import List, Dict, Tuple, Text
import os
import tensorflow as tf
import tensorflow_recommenders as tfrs
import numpy as np
from . import dataset as ds, params
# Get unique query and candidate and timestamp.
unique_user_ids, unique_therapist_ids = ds.get_u... | thomiaditya/theia | theia/config/recommender/retrieval_definition.py | retrieval_definition.py | py | 6,028 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "tensorflow.keras",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "tensorflow.keras.Sequential",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "tensorflow.keras",
"line_number": 24,
"usage_type": "attribute"
},
{
"api_name"... |
37248697117 | # Importing libraries and modules
from tkinter import *
from PIL import ImageTk, Image
import time
from tkinter import messagebox
from tkinter.filedialog import askopenfilename
# Start of GUI
root = Tk()
root.title("A-Star Grid World")
# Grid Initialization
# Ask the user if he wants to load a pre-deined world map
... | abhianshi/DynamicPathPlanning | src/AStarGUI.py | AStarGUI.py | py | 8,336 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "tkinter.messagebox.showinfo",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "tkinter.messagebox",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "tkinter.filedialog.askopenfilename",
"line_number": 17,
"usage_type": "call"
},
{
... |
33532139383 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
A script to convert the column names from CamelCase to snake_case.
Typically you would run this file from a command line like this:
ipython3.exe -i -- /deploy/cbmcfs3_runner/scripts/orig/convert_column_case.py
"""
# Built-in modules #
import os
# Third party ... | xapple/cbmcfs3_runner | scripts/orig/convert_column_case.py | convert_column_case.py | py | 7,647 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "os.environ.get",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 30,
"usage_type": "attribute"
},
{
"api_name": "autopaths.auto_paths.AutoPaths",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "pandas.... |
36872129562 | #! /usr/bin/python3
# -*- coding:utf-8 -*-
from flask import Flask, request, render_template, redirect
import json
import os
app = Flask(__name__)
@app.route('/')
def accueil():
if os.path.exists("db")==False:
os.mkdir("db")
return render_template('index.html')
@app.route('/formule')
def repon... | yahyalazaar/audit_project | __init__.py | __init__.py | py | 7,848 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "os.path.exists",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "os.mkdir",
"line_number": ... |
40988144291 | from pathlib import Path
from typing import Any, Dict
import json
MockData = Dict[str, Any]
class Mock:
"""
A class that holds the `mock.json` file contents
"""
mock: MockData = {}
@staticmethod
def populate(mock_path: Path) -> None:
if not mock_path.exists():
raise Exce... | viscript/Ox4Shell | lib/mock.py | mock.py | py | 490 | python | en | code | null | github-code | 36 | [
{
"api_name": "typing.Dict",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "typing.Any",
"line_number": 5,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "json.load",
"line_number": 21,
... |
72640625383 | """
Project: SSITH CyberPhysical Demonstrator
health.py
Author: Ethan Lew <elew@galois.com>
Date: 08/23/2021
Python 3.8.3
O/S: Windows 10
Component Health Monitoring Objects and Components
"""
import threading
import abc
import collections
import re
import requests
import typing
import struct
import socket
import time... | GaloisInc/BESSPIN-Tool-Suite | besspin/cyberPhys/cyberphyslib/cyberphyslib/demonstrator/healthmonitor.py | healthmonitor.py | py | 11,624 | python | en | code | 5 | github-code | 36 | [
{
"api_name": "socket.inet_aton",
"line_number": 35,
"usage_type": "call"
},
{
"api_name": "struct.unpack",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "abc.ABC",
"line_number": 38,
"usage_type": "attribute"
},
{
"api_name": "abc.abstractmethod",
... |
16589607570 | import random
import requests
import codecs
import json
import re
import queue
import time
from threading import Thread
requests.packages.urllib3.disable_warnings()
proxy = '127.0.0.1:8888'
def sec():
while True:
headers = {
'Referer': 'https://www.achievemint.com/signup?referral=1&utm_campaign=YOaBLXQNLBg%3D%0... | breitingerchris/public_code | Python/Achievemint/anker.py | anker.py | py | 1,509 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.packages.urllib3.disable_warnings",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "requests.packages",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "random.randint",
"line_number": 21,
"usage_type": "call"
},
{
"... |
4828779456 | import torch
from torch import nn
import pickle
from model import WideResNet
from autoattack import AutoAttack
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from torchvision import datasets, transforms, models
class ImageDataset(Dataset):
def __init__(self, file):
super().__i... | AmadeusloveIris/AutoAdversarialTraining | test.py | test.py | py | 2,316 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "torch.utils.data.Dataset",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "pickle.load",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "torch.Tensor",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "torchvision.transfo... |
19915052730 | """
Write a function that takes directory path, a file extension and an optional tokenizer.
It will count lines in all files with that extension if there are no tokenizer.
If a the tokenizer is not none, it will count tokens.
For dir with two files from hw1.py:
#>>> universal_file_counter(test_dir, "txt")
6
#>>> univer... | Abbath90/python_epam | homework9/task3/file_counter.py | file_counter.py | py | 1,333 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.TextIO",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "typing.Callable",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "pathlib.Path",
"lin... |
20604733756 | from sklearn import preprocessing
from pandas import read_csv
from sklearn.model_selection import train_test_split
from keras.layers import Dense
from keras.models import Sequential
from keras.optimizers import Adam
from sklearn.metrics import r2_score
from matplotlib import pyplot as plt
df = read_csv("C:\Code\RNASeq... | taytay191/RNAseqAnalysis | RNAseqFinal/model.py | model.py | py | 1,905 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.read_csv",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing.StandardScaler",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "sklearn.preprocessing",
"line_number": 14,
"usage_type": "name"
},
{
"api_na... |
2063569811 | from functools import cache
from . import get_track_data, get_countries_charts
import pandas as pd
@cache
def get_basic_track_features():
tracks = get_track_data()
isrc_cols = tracks.columns[tracks.columns.str.contains("isrc")].tolist()
album_cols = tracks.columns[tracks.columns.str.contains("album")].tol... | Sejmou/exploring-spotify-charts | data-collection-and-exploration/helpers/model.py | model.py | py | 3,256 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "functools.cache",
"line_number": 6,
"usage_type": "name"
},
{
"api_name": "pandas.merge",
"line_number": 36,
"usage_type": "call"
},
{
"api_name": "functools.cache",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "pandas.merge",
"line_... |
938934612 | import os
import json
class Settings:
def __init__(self, settings_directory, settings_default):
self.settings_directory = settings_directory
self.settings_default = settings_default
self.settings_file = os.path.join(self.settings_directory, "settings.json")
# Make sure a settings ... | ChimeraOS/chimera | chimera_app/settings.py | settings.py | py | 2,180 | python | en | code | 189 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 10,
"usage_type": "attribute"
},
{
"api_name": "os.path.isdir",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": ... |
12487564602 | import filecmp
import subprocess
import pytest
from typer.testing import CliRunner
import erdantic as erd
from erdantic.cli import app, import_object_from_name
import erdantic.examples.dataclasses as examples_dataclasses
import erdantic.examples.pydantic as examples_pydantic
from erdantic.examples.pydantic import Par... | drivendataorg/erdantic | tests/test_cli.py | test_cli.py | py | 6,182 | python | en | code | 205 | github-code | 36 | [
{
"api_name": "typer.testing.CliRunner",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "erdantic.cli.import_object_from_name",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "erdantic.examples.pydantic.Party",
"line_number": 20,
"usage_type": "name"
... |
10208120572 | import socket
import threading
from collections import deque
from concurrent.futures import ThreadPoolExecutor
from jsock.protocol import Protocol
from jsock.message import MessageHeader, Message
from jsock.errors import Errors
from jsock.client import Client
from jsock.config import Config
PORT = 1337
LISTEN_NUM = 50... | jacobggman/python_black_jack_server | jsock/server.py | server.py | py | 7,368 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "jsock.config.Config",
"line_number": 54,
"usage_type": "name"
},
{
"api_name": "jsock.protocol.Protocol",
"line_number": 54,
"usage_type": "name"
},
{
"api_name": "socket.socket",
"line_number": 57,
"usage_type": "call"
},
{
"api_name": "socket.AF_I... |
37989832631 | """
Steps to run:
python python policy_list_report_scraper.py
Program written in Python 3
Program Output:
1 file:
Exported_data.csv - csv file that contains the policy list report data
Program Description:
Progam first fetches the ASP login page paramters - __VIEWSTATE, __VIEWSTATEGENERATOR,
etc and then inputs the... | tebbythomas/Freelance_Projects | Web_Data_Extraction_Projects/J11_Finance_Pro_Policy_List_Report_Generator/Policy_List_Report/policy_list_report_scraper.py | policy_list_report_scraper.py | py | 7,187 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "requests.Session",
"line_number": 40,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 43,
"usage_type": "call"
},
{
"api_name": "requests.post",
"line_number": 60,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
... |
26290834166 | """Tests for common_utils.py."""
import common_utils
import pytest
class TestCommonUtils:
def testGetFilePathShouldRaiseError(self):
common_utils.input = lambda _: 'foo'
with pytest.raises(FileNotFoundError):
common_utils.get_file_path()
common_utils.input = input
def testGetFilePathShouldNotR... | thompsond/PyAVMisc | com/AVMisc/common_utils_test.py | common_utils_test.py | py | 687 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "common_utils.input",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "pytest.raises",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "common_utils.get_file_path",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "common... |
477236470 | import io, os
from .comment_parser import CommentParser
from .create_parser import CreateParser
from .insert_parser import InsertParser
class Reader:
def __init__(self):
self._tables = {}
self._rows = {}
self._global_errors = []
self._global_warnings = []
self._parsing_error... | cmancone/mygrations | mygrations/formats/mysql/file_reader/reader.py | reader.py | py | 5,702 | python | en | code | 10 | github-code | 36 | [
{
"api_name": "io.IOBase",
"line_number": 128,
"usage_type": "attribute"
},
{
"api_name": "os.path.isfile",
"line_number": 135,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 135,
"usage_type": "attribute"
},
{
"api_name": "comment_parser.CommentP... |
12234497572 | import datetime
from typing import List
from sqlalchemy.orm import make_transient
from data_access.entities.person import Person
from data_access.entities.policy import Policy
from data_access.entities.policy_offer_template import PolicyOfferTemplate
from data_access.entities.policy_risk import PolicyRisk
from data_a... | bastyje/policyapp | python/src/services/policy_service.py | policy_service.py | py | 8,189 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "data_access.repositories.person_repository.PersonRepository",
"line_number": 25,
"usage_type": "name"
},
{
"api_name": "data_access.repositories.policy_repository.PolicyRepository",
"line_number": 26,
"usage_type": "name"
},
{
"api_name": "data_access.repositories.... |
6296104681 | import requests
import urllib.parse
from models import PlayByPlay
from constants import headers
from db_utils import insert_many
class PlayByPlayRequester:
url = 'https://stats.nba.com/stats/playbyplayv2'
def __init__(self, settings):
self.settings = settings
self.settings.db.bind([PlayByPl... | Promise-Igbo/nba-sql | stats/play_by_play.py | play_by_play.py | py | 3,273 | python | en | code | null | github-code | 36 | [
{
"api_name": "models.PlayByPlay",
"line_number": 15,
"usage_type": "name"
},
{
"api_name": "models.PlayByPlay",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "urllib.parse.parse.urlencode",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "urll... |
21704376256 | #
# @lc app=leetcode.cn id=40 lang=python3
#
# [40] 组合总和 II
#
from typing import List
# @lc code=start
class Solution:
def combinationSum2(self, candidates: List[int], target: int) -> List[List[int]]:
ans = []
current = []
def dfs(i, target):
if target == 0:
ans.append(current[:])
... | LinkTsang/.leetcode | solutions/40.组合总和-ii.py | 40.组合总和-ii.py | py | 780 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.List",
"line_number": 11,
"usage_type": "name"
}
] |
69812436265 | import numpy as np
import cv2
from PIL import Image
#В этом скрипте делаем маску
#С помощью манипуляций с opencv создаем два файла
#первый - с контрастными крышами, второй - с выделенными дорогами
#затем - используя второй файл, убираем дороги с первого
image = "ZRYNEEUSVQ213QTY.png"
input = cv2.imread(image)
_, th =... | kekartem/BuildingDefine | RunFirst.py | RunFirst.py | py | 1,512 | python | ru | code | 0 | github-code | 36 | [
{
"api_name": "cv2.imread",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "cv2.threshold",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "cv2.THRESH_TOZERO",
"line_number": 12,
"usage_type": "attribute"
},
{
"api_name": "cv2.imwrite",
"li... |
18913603323 | from collections import defaultdict
class Solution:
def valid_tree(self, n: int, edges: list[list[int]]) -> bool:
seen: set[int] = set()
children: dict[int, list[int]] = defaultdict(list)
for x, y in edges:
children[x].append(y)
children[y].append(x)
def d... | lancelote/leetcode | src/graph_valid_tree.py | graph_valid_tree.py | py | 689 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "collections.defaultdict",
"line_number": 7,
"usage_type": "call"
}
] |
11571428709 | from django.utils.module_loading import import_string
from django.urls import (RegexURLResolver, RegexURLPattern)
from CRM import settings
from collections import OrderedDict
def recursion_urls(pre_namespace, pre_url, urlpatterns, url_ordered_dict):
# None, '/', urlpatterns, url_ordered_dict
'''
第一次递归：
... | heyhito/CRM | rbac/server/routes.py | routes.py | py | 2,278 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.urls.RegexURLResolver",
"line_number": 16,
"usage_type": "argument"
},
{
"api_name": "collections.OrderedDict",
"line_number": 45,
"usage_type": "call"
},
{
"api_name": "django.utils.module_loading.import_string",
"line_number": 47,
"usage_type": "ca... |
71399122025 |
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.common.exceptions import NoSuchElementException
import time
driver = webdriver.Firefox()
driver.get('https://github.com/Vidoosh/Image-colorizer')
time.sleep(2)
code = driver.find_element(By.CSS_SELECTOR, '#re... | sravanithummapudi/st | download_button.py | download_button.py | py | 901 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "selenium.webdriver.Firefox",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "selenium.webdriver",
"line_number": 10,
"usage_type": "name"
},
{
"api_name": "time.sleep",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "selenium.web... |
71666166824 | # The following code was adapted from Week 3 Programming Assignment 2 in the Convolutional Neural Networks course by DeepLearning.AI offered on Coursera
# https://www.coursera.org/learn/convolutional-neural-networks/home/week/3
import tensorflow as tf
import numpy as np
from tensorflow.keras.layers import Input
fro... | AndrewZhang126/Neural-Networks | U-Net.py | U-Net.py | py | 6,154 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "os.path.join",
"line_number": 27,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 27,
"usage_type": "attribute"
},
{
"api_name": "os.path.join",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 2... |
33377706423 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
eps = 1e-7
class SCELoss(nn.Module):
def __init__(self, num_classes=10, a=1, b=1):
super(SCELoss, self).__init__()
self.num_classes = num_classes
self.a = a
self.b = b
self.cross_entropy ... | hitcszx/lnl_sr | losses.py | losses.py | py | 10,369 | python | en | code | 42 | github-code | 36 | [
{
"api_name": "torch.nn.Module",
"line_number": 9,
"usage_type": "attribute"
},
{
"api_name": "torch.nn",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "torch.nn.CrossEntropyLoss",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "torch.nn",
... |
39209701807 | # Create your views here.
from django.shortcuts import render
from team.models import Player
from django.shortcuts import render, get_object_or_404, redirect, render_to_response
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
def home(request):
context = {'message': 'Here is a message!'}
... | carolinp/Project-1 | team/views.py | views.py | py | 890 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "django.shortcuts.render",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "team.models.Player.objects.all",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "team.models.Player.objects",
"line_number": 12,
"usage_type": "attribute"
},
{
... |
34141195826 | import numpy as np
import torch
from snownlp import SnowNLP
from common_utils import *
from preprocessing.clean_data import batchify
def get_overlap(list1, list2):
"""
Returns a list of words that occur in both list1 and list2.
Also returns total number of words in list1 and in list2 (can be used
to ... | JasmineZhangxyz/ewb-ml-censorship | similarity/metrics/list_metrics.py | list_metrics.py | py | 4,969 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "snownlp.SnowNLP",
"line_number": 29,
"usage_type": "call"
},
{
"api_name": "snownlp.SnowNLP",
"line_number": 30,
"usage_type": "call"
},
{
"api_name": "torch.load",
"line_number": 64,
"usage_type": "call"
},
{
"api_name": "preprocessing.clean_data.b... |
7784263631 | import twitter
class pytwitter_forecast(NebriOS):
listens_to = ['forecast_date']
def check(self):
return True
def action(self):
auth = twitter.OAuth(shared.ttoken, shared.ttoken_secret, shared.tconsumer_key, shared.tconsumer_secret)
t = twitter.Twitter(auth=auth)... | bandono/nebri | tweet_rain/pytwitter_forecast.py | pytwitter_forecast.py | py | 874 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "twitter.OAuth",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "twitter.Twitter",
"line_number": 13,
"usage_type": "call"
}
] |
32316213655 | import time
import threading
import logging
import traceback
import datetime
import os
import sys
import re
import robotparser as rp
import numpy as np
import random
import util
import decide
import queries
from conn import connect
class Crawler:
'''
Abstract class for crawling a news source.
'''
###... | bentruitt/TopicStory | topicstory/crawler/crawler.py | crawler.py | py | 8,339 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "util.robots_url",
"line_number": 74,
"usage_type": "call"
},
{
"api_name": "robotparser.RobotFileParser",
"line_number": 75,
"usage_type": "call"
},
{
"api_name": "queries.insert_url",
"line_number": 97,
"usage_type": "call"
},
{
"api_name": "decide... |
18482541642 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .utils import weight_reduce_loss
class FocalLoss(nn.Module):
def __init__(self,
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
reduction='mean',
loss_weight=1.0):
... | TWSFar/FCOS | models/losses/focal_loss.py | focal_loss.py | py | 1,798 | python | en | code | 1 | 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.zeros",
"line_number": 31,
"usage_type": "call"
},
{
"api_name": "torch.long",
"line_number... |
39184736012 | ####################### IMPORT LIBRARIES ####################################
from pandas import ExcelFile, read_excel
from pandas import datetime
from sklearn.metrics import mean_squared_error
from math import sqrt
import matplotlib.pyplot as plt
import warnings
from hmmlearn.hmm import GaussianHMM
import numpy as np
... | srihari1212/bloqq | HMM/Docstring_HMM_test.py | Docstring_HMM_test.py | py | 4,173 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "pandas.ExcelFile",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "pandas.datetime.strptime",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "pandas.datetime",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "pandas.date... |
10567641757 | import time
from datetime import datetime, timedelta
from pydantic import BaseModel
from fastapi import FastAPI, Depends, File, UploadFile, HTTPException, Request, status
from fastapi.responses import HTMLResponse, JSONResponse, FileResponse
import uvicorn
import os
from pytube import YouTube
from pytube import Playlis... | uponex/YoutubeAPI | main.py | main.py | py | 7,761 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fastapi.FastAPI",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "pydantic.BaseModel",
"line_number": 16,
"usage_type": "name"
},
{
"api_name": "pytube.YouTube",
"line_number": 34,
"usage_type": "call"
},
{
"api_name": "fastapi.responses.J... |
23313577208 | import argparse
import gym
import random
import tensorflow as tf
import numpy as np
from tqdm import trange
from tensorflow import keras
from network import SharedModel
from subproc_env import EnvActor, SubProcessEnv
# Some parameters taken from OpenAI
# baselines implementation, since
# they're not mentioned in the... | james-sorrell/reinforcement_learning | atari/ppo/main.py | main.py | py | 4,674 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "gym.make",
"line_number": 37,
"usage_type": "call"
},
{
"api_name": "network.SharedModel",
"line_number": 42,
"usage_type": "call"
},
{
"api_name": "subproc_env.EnvActor",
"line_number": 49,
"usage_type": "call"
},
{
"api_name": "subproc_env.SubProc... |
16828444501 | from flask import Flask,request
import sqlite3
app = Flask(__name__)
connection = sqlite3.connect('sms.db')
curser = connection.cursor()
curser.execute('create table if not exists students (sid integer primary key,name text,age integer,address text)')
connection.close()
@app.route('/student_details')
def details():... | mubarakdalvi/mubarakdalvi | studnt_management.py | studnt_management.py | py | 868 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 4,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 7,
"usage_type": "call"
},
{
"api_name": "sqlite3.connect",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "flask.request.get_json",
... |
11876743553 | # 数据预处理 阴影过滤
#yangzhen
#2020.4.13
#translate from matlab
"""get the shadow proportion from images
of remote sensing"""
import numpy as np
import cv2
import os
import json
from shutil import copyfile
import argparse
def cv_imread(file_path):
cv_img=cv2.imdecode(np.fromfile(file_path,dtype=np.uint8),1)
retur... | jansona/GeoScripts | shadow_filter/shadowfilter.py | shadowfilter.py | py | 4,966 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.imdecode",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.fromfile",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "numpy.uint8",
"line_number": 15,
"usage_type": "attribute"
},
{
"api_name": "cv2.imencode",
"line... |
40083862973 | #!/usr/bin/env python3
import argparse
import random
import json
import re
import importlib.util
import os.path
import sys
import types
import inspect
import pandas as pd
import numpy as np
MAX_SLOT=8
SMART_COMMENT="\\s*#+\\s*(fastscore|odg)\\.(\\S*)\\s*:\\s*(\\S*)\\s*$"
def is_input_slot(s):
return s % 2 == 0
##... | modelop/modelop.github.io | Product Manuals/Model Launchers/Python Launcher/lh.py | lh.py | py | 9,190 | python | en | code | 1 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "re.match",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "re.split",
"line_number": 59,
"usage_type": "call"
},
{
"api_name": "sys.exit",
"line_number... |
24788697819 | """
N×M 크기의 공간에 아기 상어 여러 마리가 있다. 공간은 1×1 크기의 정사각형 칸으로 나누어져 있다. 한 칸에는 아기 상어가 최대 1마리 존재한다.
어떤 칸의 안전 거리는 그 칸과 가장 거리가 가까운 아기 상어와의 거리이다. 두 칸의 거리는 하나의 칸에서 다른 칸으로 가기 위해서 지나야 하는 칸의 수이고, 이동은 인접한 8방향(대각선 포함)이 가능하다.
안전 거리가 가장 큰 칸을 구해보자.
"""
import sys
from collections import deque
N, M = list(map(int, sys.stdin.readline().stri... | inhyeokJeon/AALGGO | Python/baekjoon/17086_baby_shark_2.py | 17086_baby_shark_2.py | py | 1,975 | python | ko | code | 0 | github-code | 36 | [
{
"api_name": "sys.stdin.readline",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
"line_number": 11,
"usage_type": "attribute"
},
{
"api_name": "sys.stdin.readline",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "sys.stdin",
... |
23269856572 | # import os
import sys
import csv
from matplotlib.patches import Ellipse
import matplotlib.transforms as transforms
# import pandas as pd
# from pandas.plotting import lag_plot
from PyQt5.QtWidgets import *
from PyQt5.QtCore import *
from PyQt5.QtGui import *
import random
import matplotlib.pyplot as plt
import numpy... | lukascao/GUI_vorlesung | GUI_example.py | GUI_example.py | py | 54,545 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.Optional",
"line_number": 40,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 41,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
"line_number": 42,
"usage_type": "name"
},
{
"api_name": "typing.Optional",
... |
74649269864 | # -*- coding: utf-8 -*-
# @Project : selenium_event
# @File : test_alert.py
# @Software: PyCharm
# @Author : Lizhipeng
# @Email : 1907878011@qq.com
# @Time : 2021/9/26 17:16
from selenium.webdriver import ActionChains
from seleium_study.selenium_js.base import Base
class TestAlert(Base):
def test_alert(... | iospeng/python | pycharm_demo/selenium_event/seleium_study/selenium_file_alert/test_alert.py | test_alert.py | py | 1,036 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "seleium_study.selenium_js.base.Base",
"line_number": 13,
"usage_type": "name"
},
{
"api_name": "selenium.webdriver.ActionChains",
"line_number": 21,
"usage_type": "call"
}
] |
40586478771 | from fastapi import APIRouter, Depends, status
from sqlalchemy.ext.asyncio import AsyncSession
from src.authentication import AuthModel, get_token_user
from src.core.exceptions import UnprocessableEntityException
from src.db.postgres import get_db
from .dependencies import get_token_parent
from .parents.crud import pa... | Xewus/KidEdVisor | backend/src/parents/router.py | router.py | py | 1,626 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "fastapi.APIRouter",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "parents.models.ParentModel",
"line_number": 21,
"usage_type": "name"
},
{
"api_name": "fastapi.Depends",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "dependen... |
35183490035 | import asyncio
import os
import oneai
from oneai import Input, Output
oneai.api_key = os.getenv("ONEAI_KEY")
async def split(filepath):
pipeline = oneai.Pipeline(
steps=[
oneai.skills.SplitByTopic(),
]
)
with open(filepath, 'r') as file_input:
output = await pipeline.... | clande/demo | oneai_splitbytopic_repro.py | oneai_splitbytopic_repro.py | py | 808 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "oneai.api_key",
"line_number": 6,
"usage_type": "attribute"
},
{
"api_name": "os.getenv",
"line_number": 6,
"usage_type": "call"
},
{
"api_name": "oneai.Pipeline",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "oneai.skills.SplitByTopic",... |
17579968573 | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from numpy import *
import sys
file_name = sys.argv[1]
data1 = loadtxt("./" + file_name)
NUM=data1[:,0] #
TIME=data1[:,1] #
fig = plt.figure() #
top = fig.add_subplot(111) # 1 riga, 1 colonna, figura 1
top.set_title('BRUTE FORCE')
top.grid... | UnProgrammatore/CCQ | altre_cose/fattorizzazione_mpi_banale_print/plot.py | plot.py | py | 480 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "matplotlib.use",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.argv",
"line_number": 7,
"usage_type": "attribute"
},
{
"api_name": "matplotlib.pyplot.figure",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "matplotlib.pyplot... |
12676975577 | import mlflow
import dvc.api
import pandas as pd
def yield_artifacts(run_id, path=None):
"""Yield all artifacts in the specified run"""
client = mlflow.tracking.MlflowClient()
for item in client.list_artifacts(run_id, path):
if item.is_dir:
yield from yield_artifacts(run_id, item.path)... | robert-min/bike_share_mlflow | model/utils.py | utils.py | py | 1,317 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "mlflow.tracking.MlflowClient",
"line_number": 8,
"usage_type": "call"
},
{
"api_name": "mlflow.tracking",
"line_number": 8,
"usage_type": "attribute"
},
{
"api_name": "mlflow.tracking.MlflowClient",
"line_number": 18,
"usage_type": "call"
},
{
"api_... |
27770003302 | import numpy as np
import pandas as pd
import matplotlib
import metrics
import sklearn
import xgboost
from sklearn import metrics
from decimal import *
import graphviz
'''
新細明體：PMingLiU
細明體：MingLiU
標楷體：DFKai-SB
黑体：SimHei
宋体：SimSun
新宋体：NSimSun
仿宋：FangSong
楷体：KaiTi
仿宋_GB2312：FangSong_GB2312
楷体_GB2312：KaiTi_GB2312
微軟正黑體... | kshsky/PycharmProjects | machinelearning/tools/mlTools.py | mlTools.py | py | 8,384 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "sklearn.metrics.confusion_matrix",
"line_number": 55,
"usage_type": "call"
},
{
"api_name": "sklearn.metrics",
"line_number": 55,
"usage_type": "name"
},
{
"api_name": "sklearn.metrics.accuracy_score",
"line_number": 57,
"usage_type": "call"
},
{
"a... |
37986696093 | """
This script is written to do analysis on GA study
"""
# import libraries
import re
import tsfresh
import numpy as np
import pandas as pd
from pandas import ExcelWriter
from sklearn.preprocessing import LabelBinarizer
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style("darkgrid")
... | emilymacq/Project-Clear-Lungs | Parkinsons_ML/main/Study_Ga.py | Study_Ga.py | py | 12,820 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "seaborn.set_style",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 65,
"usage_type": "call"
},
{
"api_name": "pandas.DataFrame",
"line_number": 69,
"usage_type": "call"
},
{
"api_name": "numpy.nan",
"... |
34366380953 | from scripts.hackerrank.isLeapYear import is_leap, is_leap2, is_leap3, is_leap4
class Test:
test_cases = [
[2004, True],
[2008, True],
[2012, True],
[2016, True],
[2005, False],
[2009, False],
[2013, False],
[2017, False],
]
testable_fun... | TrellixVulnTeam/learning_to_test_code_BL81 | tests/hackerrank/test_isLeapYear.py | test_isLeapYear.py | py | 560 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "scripts.hackerrank.isLeapYear.is_leap",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "scripts.hackerrank.isLeapYear.is_leap2",
"line_number": 17,
"usage_type": "name"
},
{
"api_name": "scripts.hackerrank.isLeapYear.is_leap3",
"line_number": 17,
... |
43314571963 | import requests
def getweather(city):
api = "96e3cd3e19571466a39662b984eec5f1"
server = "https://api.openweathermap.org/data/2.5/weather"
request = f"{server}?q={city}&appid={api}"
output = requests.get(request)
if output.status_code == 200:
weather_data = output.json()
weather = w... | XBOPb/Projects | API_Weather_App/weatherAPI.py | weatherAPI.py | py | 821 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "requests.get",
"line_number": 8,
"usage_type": "call"
}
] |
19530926102 | """
Projeto Marinha do Brasil
Autor: Pedro Henrique Braga Lisboa (pedro.lisboa@lps.ufrj.br)
Laboratorio de Processamento de Sinais - UFRJ
Laboratorio de de Tecnologia Sonar - UFRJ/Marinha do Brasil
"""
from __future__ import print_function, division
import os
import h5py
import warnings
import numpy a... | pedrolisboa/poseidon | poseidon/io/offline.py | offline.py | py | 6,116 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "os.listdir",
"line_number": 58,
"usage_type": "call"
},
{
"api_name": "os.listdir",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "os.path.join",
"line_number": 63,
"usage_type": "call"
},
{
"api_name": "os.path",
"line_number": 63,
... |
3118375238 | import torch.optim as optim
ADADELTA_LEARNING_RATE = 0.05
ADADELTA_MOMENTUM = 0.9
ADADELTA_WEIGHT_DECAY = 0.005
def get_adadelta_halnet(halnet,
momentum=ADADELTA_MOMENTUM,
weight_decay=ADADELTA_WEIGHT_DECAY,
learning_rate=ADADELTA_LEARNING_RATE):... | pauloabelha/muellerICCV2017 | optimizers.py | optimizers.py | py | 520 | python | pt | code | 2 | github-code | 36 | [
{
"api_name": "torch.optim.Adadelta",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "torch.optim",
"line_number": 11,
"usage_type": "name"
}
] |
28436305539 | import socket
import subprocess
import json
import os
import base64
import sys
import shutil
import time
import requests
from termcolor import colored
from mss import mss
def reliable_send(data):
json_data=json.dumps(data)
sock.send(json_data.encode('utf-8'))
def reliable_recv():
data=''
while True:
... | sharshith1312/reverse_shell | rstest1.py | rstest1.py | py | 5,215 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "json.dumps",
"line_number": 15,
"usage_type": "call"
},
{
"api_name": "json.loads",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 28,
"usage_type": "call"
},
{
"api_name": "mss.mss",
"line_number": 33,
... |
15386994551 | #!/usr/bin/env python3
"""게임과 론처를 묶어서 새 앱 프로토콜 버전을 서명한 뒤 패키지로 생성한다."""
import argparse
import os
import os.path
import logging
import shutil
import tarfile
import tempfile
import zipfile
from zipfile import ZIP_DEFLATED
parser = argparse.ArgumentParser(description=__doc__.replace('\n', ' '))
parser.add_argument('out_... | FioX0/PandoraReborn | tools/pack/pack.py | pack.py | py | 3,340 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "argparse.ArgumentParser",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "logging.DEBUG",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "logging.INFO",
"line_number": 21,
"usage_type": "attribute"
},
{
"api_name": "logging.... |
31982185532 | import requests
from bs4 import BeautifulSoup
from datetime import datetime
import os.path
import csv
import threading
from queue import Queue
# Proxies for BURP - update requests if you want to use this proxy
proxies = {"http": "http://127.0.0.1:8080", "https": "http://127.0.0.1:8080"}
playersFile = 'sample_corrected... | zcrosman/PDGAscrape | PDGAscrape.py | PDGAscrape.py | py | 9,296 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "queue.Queue",
"line_number": 12,
"usage_type": "call"
},
{
"api_name": "requests.get",
"line_number": 23,
"usage_type": "call"
},
{
"api_name": "bs4.BeautifulSoup",
"line_number": 24,
"usage_type": "call"
},
{
"api_name": "datetime.datetime.now",
... |
40144939486 | from flask import request
from werkzeug.utils import secure_filename
from db import db
from models import Img
def upload_images(pic_list, private, user_id):
#import pdb; pdb.set_trace()
for pic in pic_list:
filename = secure_filename(pic.filename)
mimetype = pic.mimetype
if not filen... | elmanreasat/imagipy | controllers/upload.py | upload.py | py | 573 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "werkzeug.utils.secure_filename",
"line_number": 11,
"usage_type": "call"
},
{
"api_name": "models.Img",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "db.db.session.add",
"line_number": 18,
"usage_type": "call"
},
{
"api_name": "db.db.ses... |
12087004714 | from sklearn.feature_extraction.text import TfidfVectorizer
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
import spacy,os
import argparse
import re
from tqdm import tqdm
from collections import OrderedDict
import string
import numpy as np
from spacy.lang.en import En... | Law-AI/summarization | extractive/MMR/MMR.py | MMR.py | py | 4,098 | python | en | code | 139 | github-code | 36 | [
{
"api_name": "spacy.lang.en.English",
"line_number": 14,
"usage_type": "call"
},
{
"api_name": "string.punctuation",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "string.whitespace",
"line_number": 32,
"usage_type": "attribute"
},
{
"api_name": "... |
11936036688 | from typing import Any, Optional, TYPE_CHECKING
import logging
from ..common.utils import deepmerge
from .execution_method import ExecutionMethod
from .aws_settings import INFRASTRUCTURE_TYPE_AWS, AwsSettings
if TYPE_CHECKING:
from ..models import (
Task,
TaskExecution
)
logger = logging.getLog... | CloudReactor/task_manager | server/processes/execution_methods/aws_base_execution_method.py | aws_base_execution_method.py | py | 3,685 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "typing.TYPE_CHECKING",
"line_number": 9,
"usage_type": "name"
},
{
"api_name": "logging.getLogger",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "execution_method.ExecutionMethod",
"line_number": 19,
"usage_type": "name"
},
{
"api_name":... |
3219242168 | import sys
sys.path.append('../VQ-VAE')
from auto_encoder2 import VQ_CVAE
import argparse
from torch import optim
from torchvision import transforms
import fpa_dataset
parser = argparse.ArgumentParser(description='Train an autoencoder for hand depth image reconstruction')
parser.add_argument('-r', dest='dataset_root_f... | pauloabelha/handy | train_autoencoder.py | train_autoencoder.py | py | 2,275 | python | en | code | 2 | github-code | 36 | [
{
"api_name": "sys.path.append",
"line_number": 2,
"usage_type": "call"
},
{
"api_name": "sys.path",
"line_number": 2,
"usage_type": "attribute"
},
{
"api_name": "argparse.ArgumentParser",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "torchvision.transf... |
8755383285 | # -*- coding: utf-8 -*-
import json
import logging
from datetime import datetime, date, timedelta
from odoo import api, fields, models
from odoo.addons.muk_dms.models import dms_base
logger = logging.getLogger('FOLLOW-UP')
AVAILABLE_PRIORITIES = [
('0', u'Normale'),
('1', u'Basse'),
('2', u'Haute'),
... | odof/openfire | of_followup/models/of_followup.py | of_followup.py | py | 70,070 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "logging.getLogger",
"line_number": 9,
"usage_type": "call"
},
{
"api_name": "odoo.models.Model",
"line_number": 19,
"usage_type": "attribute"
},
{
"api_name": "odoo.models",
"line_number": 19,
"usage_type": "name"
},
{
"api_name": "odoo.api.model",
... |
2391690633 | from threading import Thread
from flask import Flask, request, redirect, session, render_template, send_file, Response, flash
from flask_session import Session
import os, json
from bs4 import BeautifulSoup, SoupStrainer
import requests, lxml, cchardet
app = Flask('')
app.config["SESSION_PERMANENT"] = False
app.confi... | CoolCoderSJ/DataPak | main.py | main.py | py | 17,220 | python | en | code | 3 | github-code | 36 | [
{
"api_name": "flask.Flask",
"line_number": 10,
"usage_type": "call"
},
{
"api_name": "flask_session.Session",
"line_number": 13,
"usage_type": "call"
},
{
"api_name": "os.environ",
"line_number": 23,
"usage_type": "attribute"
},
{
"api_name": "os.environ",
"l... |
33171162837 | import matplotlib.pyplot as plt
import cv2
import numpy as np
# from pyradar.classifiers.isodata import isodata_classification
from isodataclassifier import isodata_classification
def equalize_histogram(img, histogram, cfs):
"""
Equalize pixel values to [0:255].
"""
total_pixels = img.size
N, M = i... | sauravkarn541/morphological_operators | isodata.py | isodata.py | py | 2,932 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "numpy.zeros_like",
"line_number": 16,
"usage_type": "call"
},
{
"api_name": "numpy.zeros_like",
"line_number": 17,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"line_number": 19,
"usage_type": "call"
},
{
"api_name": "numpy.float32",
"... |
3715520265 | import cv2
import numpy as np
def get_crops(img, annotations, padding=0):
crops = []
new_img = img.copy() # Prevent drawing on original image
for a in annotations:
c = a['coordinates']
y1, y2 = int(c['y'] - c['height'] / 2 - padding), int(c['y'] + c['height'] / 2 + padding)
x1, x2 = int(c['x'] - c['width'] /... | mattzh72/sframe-visualizer | tools/utils/segment.py | segment.py | py | 1,936 | python | en | code | 0 | github-code | 36 | [
{
"api_name": "cv2.cvtColor",
"line_number": 20,
"usage_type": "call"
},
{
"api_name": "cv2.COLOR_BGR2GRAY",
"line_number": 20,
"usage_type": "attribute"
},
{
"api_name": "cv2.threshold",
"line_number": 21,
"usage_type": "call"
},
{
"api_name": "cv2.THRESH_BINARY_... |
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