seq_id stringlengths 4 11 | text stringlengths 113 2.92M | repo_name stringlengths 4 125 ⌀ | sub_path stringlengths 3 214 | file_name stringlengths 3 160 | file_ext stringclasses 18
values | file_size_in_byte int64 113 2.92M | program_lang stringclasses 1
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381786064 | import gym
import random
import numpy as np
from keras.layers import Dense, Flatten
from keras.models import Sequential
from rl.agents import SARSAAgent
from rl.policy import EpsGreedyQPolicy
env = gym.make('CartPole-v1')
states = env.observation_space.shape[0]
print('States', states)
actions = env.action_space.n
prin... | MaZeeT/MultiAgentRL | CartPole/sarsa/sarsa.py | sarsa.py | py | 1,909 | python | en | code | 0 | github-code | 90 |
18484934699 | #028_A
from fractions import gcd
N,M=map(int,input().split())
S=input()
T=input()
flg=True
g=gcd(N,M)
n,m=N//g,M//g
for k in range(0,g):
if S[k*n]!=T[k*m]:
flg=False
print(N*M//g if flg else -1) | Aasthaengg/IBMdataset | Python_codes/p03231/s294453782.py | s294453782.py | py | 210 | python | en | code | 0 | github-code | 90 |
33595576449 | import logging
from trpycore.thread.util import join
from trsvcscore.service.handler.service import ServiceHandler
from trschedulesvc.gen import TScheduleService
import settings
from scheduler import ChatScheduler
class ScheduleServiceHandler(TScheduleService.Iface, ServiceHandler):
def __init__(self, service):
... | techresidents/schedulesvc | schedulesvc/handler.py | handler.py | py | 1,359 | python | en | code | 1 | github-code | 90 |
34476209827 | '''
Created on 13/feb/2013
@author: sambarza@gmail.com
'''
from ywnThing import Thing
from pandac.PandaModules import BitMask32
class Box(Thing):
'''
classdocs
'''
def __init__(self, ywn):
'''
Constructor
'''
Thing.__init__(self, "Box", ywn)
self.... | sambarza/bo | world/things/box/Box.py | Box.py | py | 633 | python | en | code | 0 | github-code | 90 |
70194252776 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Georeferenciació de la demanda.
FORMULARIO 8:
Información relativa a generación conectada a sus redes de distribución
codigo empresa
cil
x
y
provincia
municipio
conexión
potencia instalada
energía activa
energía reactiva
"""
import sys
import os
import multiprocessing
... | gisce/georef | bin/georef_re.py | georef_re.py | py | 7,839 | python | en | code | 1 | github-code | 90 |
27501577894 | import os
import time
import argparse
import torch
from torch.nn.utils import clip_grad_norm_
from apex import amp
from tqdm import tqdm
from .model import Transformer
from .optim import Adam, RAdam, SGD
from .optim.lr_scheduler import InverseSquareRootScheduler
from .data import Dictionary, Seq2SeqDataset,... | liu-hz18/NaiveSeq | naiveseq/tasks/autoregressive.py | autoregressive.py | py | 14,125 | python | en | code | 1 | github-code | 90 |
16375923509 | import scrapy
import pandas as pd
from scrapy_selenium import SeleniumRequest
import json
import codecs
import requests
import re
import cssselect
from lxml.html import etree
import time
import random
# from selenium.webdriver.common.by import By
# from selenium.webdriver.support import expected_conditions as EC
clas... | HacoK/BookLibCrawler | BookLibCrawler/spiders/all_spider.py | all_spider.py | py | 7,574 | python | en | code | 1 | github-code | 90 |
30378688994 | import cv2
import numpy as np
def init_video_capture():
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FPS, int(60))
fps = cap.get(cv2.CAP_PROP_FPS)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 360)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
cap.set(cv2.CAP_PROP_BUFFERSIZE,0)
print("fps:",fps)
... | DecXlll/STARK_Tracking | mmtracking/demo/test.py | test.py | py | 1,381 | python | en | code | 0 | github-code | 90 |
11027786553 | def Show(arr,n):
max=arr[0]
for i in range(1,n):
if arr[i]>max:
max=arr[i]
return max
arr=[10,35,85,45,69,96]
n=len(arr)
f1=Show(arr,n)
print("List Of Array Is :",f1)
| nazim164/python_code | MaxArray.py | MaxArray.py | py | 204 | python | en | code | 0 | github-code | 90 |
12454274730 | """
Assumption :
1/01/0001 was Monday
Every month has 31 days
Every year has 365 days
"""
x = int(input("Enter day"))
y = int(input("Enter month"))
z = int(input("Enter year"))
r1 = x + (31 * (y-1))
r2 = (365 * (z-1)) - 1
result = (r1 + r2)%7
if result == 0:
print("Monday")
if result == 1:
print("Tuesday")
i... | SuyogAhuja/CodeCell_challenges | 2nd_challenge.py | 2nd_challenge.py | py | 519 | python | en | code | 0 | github-code | 90 |
18331827969 | from bisect import bisect_left
n = int(input())
l = sorted(list(map(int, input().split())))
#aを1番短い辺、bを2番めに短い辺とする
cnt = 0
for i in range(n-2):
for j in range(i+1, n-1):
c_i = bisect_left(l, l[i] + l[j])
cnt += c_i - (j+1)
print(cnt) | Aasthaengg/IBMdataset | Python_codes/p02888/s584975795.py | s584975795.py | py | 287 | python | en | code | 0 | github-code | 90 |
18037845939 | import sys
sys.setrecursionlimit(10 ** 7)
f_inf = float('inf')
mod = 10 ** 9 + 7
def resolve():
H, W = map(int, input().split())
C = []
for i in range(H):
c = input()
C.append(c)
C.append(c)
for c in C:
print(c)
if __name__ == '__main__':
resolve()
| Aasthaengg/IBMdataset | Python_codes/p03853/s389451136.py | s389451136.py | py | 307 | python | en | code | 0 | github-code | 90 |
18032721489 | from heapq import heappush,heappop,heapify
INF=10**30
def dijkstra(G,s,n):
que=[(0,s)]
dist=[INF]*n
last=[-1]*n
dist[s]=0
while que:
mincost,u=heappop(que)
if(mincost>dist[u]):
continue
for c,v in G[u]:
if(dist[u]+c<dist[v]):
dist[v]=d... | Aasthaengg/IBMdataset | Python_codes/p03837/s103959509.py | s103959509.py | py | 921 | python | en | code | 0 | github-code | 90 |
37115877304 | import nidaqmx
from nidaqmx.constants import AcquisitionType
sample_per_second = 10
with nidaqmx.Task() as task:
task.ai_channels.add_ai_voltage_chan("PCI6289/ai0", min_val=-0.1, max_val=0.1)
task.timing.cfg_samp_clk_timing(rate=sample_per_second, sample_mode=AcquisitionType.CONTINUOUS)
for n in r... | Kaige213/QuantumTransportExperiment | 仪器使用/PCI6289采集卡/program/pci6289_ai_test.py | pci6289_ai_test.py | py | 497 | python | en | code | 4 | github-code | 90 |
73516568298 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 3 21:37:50 2021
@author: aliuzun
"""
import sys
sys.path.append("../Work")
import csv, random
import os
from tkinter import Label
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from src.OpenFile import OpenFile
from src.My... | uzunali/III-V-Python-Scripts-V2.1 | src/Data_Analysis.py | Data_Analysis.py | py | 8,983 | python | en | code | 0 | github-code | 90 |
21939010290 | import argparse
from dstk.management.TweetManager import TweetManager
"""
Usage:
python manage_tweets.py EVENT RUMOR ACTION --options ...
Example:
python manage_tweets.py sydneysiege hadley generate_training -ss 80
This will generate a training sheet for the Hadley
rumor containing 80 tweets.
AVALI... | emCOMP/data_science_toolkit | package/manage_tweets.py | manage_tweets.py | py | 7,151 | python | en | code | 0 | github-code | 90 |
2797430356 | # BlackJack.py
from Deck import Card, Deck
class Hand:
"""
represents a player's hand in blackjack
"""
def __init__(self, card1, card2):
"""
initializes Hand object with two cards
"""
self.cards = [card1, card2]
# self.points = {'A': 1, 2: 2, 3: 3, 4: 4, 5: 5, 6:... | PdxCodeGuild/class_salmon | 1 Python/solutions/blackjack/Blackjack.py | Blackjack.py | py | 6,699 | python | en | code | 5 | github-code | 90 |
4547969382 |
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import sklearn as skl
from sklearn.cross_validation import train_test_split
from sklearn.metrics import confusion_matrix, accuracy_score, classification_report
from sklearn import linear_model
from sklearn.feature_select... | vikneke/cs5014_p2 | binaryML/binary.py | binary.py | py | 6,474 | python | en | code | 1 | github-code | 90 |
17997385490 | import sys
import pandas as pd
import numpy as np
import lightfm
from scipy import sparse
import tensorflow as tf
data = pd.read_csv(sys.argv[1])
data = data.loc[:, data.columns != 'Unnamed: 0']
data.shape
dt = np.array(data)
dt.shape
df_test = pd.read_csv('df_test.csv')
print('date loaded')
# LightFM model
norm ... | LiviReka/CamperRecommender | model_code/lightfm_model.py | lightfm_model.py | py | 1,490 | python | en | code | 0 | github-code | 90 |
72990653738 | from flask import Flask, render_template
from flask_restful import Resource, Api, reqparse, fields, marshal_with
from baby_names import baby_names_utilities
from imdb_scraper import imdb_scraper
import json
# Creat app and API
app = Flask(__name__)
api = Api(app)
# Arg parser
parser = reqparse.RequestParser(bundle_er... | brandonmburroughs/baby-names-and-movie-stars | app.py | app.py | py | 2,088 | python | en | code | 1 | github-code | 90 |
33527403783 | # -*- coding: utf-8 -*-
"""
Created on Tue Oct 24 15:45:00 2017
@author: dell
"""
import numpy as np
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import AdaBoostRegressor
from sklearn import datasets
from sklearn.metrics import mean_squared_error, explained_
variance_score
from sk... | bsrjy/Python-Machine-Learning | example.py | example.py | py | 3,737 | python | en | code | 0 | github-code | 90 |
7065965398 | # Chennai Curler v1
# Author: Gurjot Sidhu
# For: CPR Climate Team, New Delhi
# Description: This script pings the GCC server and saves the result in a CSV file. Data from 01.01.2010 to 31.12.2020 is downloaded by altering the date and gender fields in the request payload.
import time
import requests
from bs4 import B... | gsidhu/cpr-web-scraping | chennai-curler.py | chennai-curler.py | py | 3,851 | python | en | code | 0 | github-code | 90 |
18153819909 | n,k=map(int,input().split())
s=[]
s2=[]
mod=998244353
for i in range(k):
l,r=map(int,input().split())
s+=[i for i in range(l,r+1)]
s2.append([l,r])
s.sort()
dp=[0]*(n+1)
dpsum=[0]*(n+1)
dp[1]=1
dpsum[1]=1
for i in range(2,n+1):
for j in range(k):
if i-s2[j][0]>=0:
dp[i]+=(dpsum[i-s2... | Aasthaengg/IBMdataset | Python_codes/p02549/s016996778.py | s016996778.py | py | 432 | python | en | code | 0 | github-code | 90 |
4126613006 | import socket
import sys
c_socket = socket.socket()
host = '192.168.56.101'
port = 8889
print('waiting to connect..')
try:
c_socket.connect((host,port))
except socket.error as e:
print(str(e))
response = c_socket.recv(1024)
print(response.decode('utf-8'))
print("Choose a mathematical function\n1:log10,2:SquareRoot,... | llippie/itt440-lab6-client | 6.3.py | 6.3.py | py | 816 | python | en | code | 0 | github-code | 90 |
19641352252 | from tools import parsers, loader
from collections import deque
from math import lcm
from typing import NamedTuple
import numpy as np
class Point(NamedTuple):
row: int
col: int
def __add__(self, other):
return Point(row=self.row + other.row, col=self.col + other.col)
DIRECTIONS = {'>': Point(0,... | Nyaaa/advent-of-code | 2022/day 24/day24.py | day24.py | py | 3,172 | python | en | code | 0 | github-code | 90 |
22801147302 | from ..TransformerABC import Transformer as tabc
import pandas as pd
class NetworkDataMetricsAggregator(tabc):
def __init__(self, aggregated_asset_name:str, metrics:[str]=None):
self.aggregated_asset_name = aggregated_asset_name
self.metrics = metrics
def get_unique_metrics(self, columns:[str]... | 0x2b543c/0xv8l422 | modules/Transformers/Aggregators/NetworkDataMetricsAggregator.py | NetworkDataMetricsAggregator.py | py | 1,062 | python | en | code | 0 | github-code | 90 |
18373463789 | N, K = map(int,input().split())
AB = [list(map(int,input().split())) for _ in range (N-1)]
import sys
sys.setrecursionlimit(10**9)
edge = [[] for _ in range(N)]
for u,v in AB:
edge[u-1].append(v-1)
edge[v-1].append(u-1)
MOD = 10**9+7
mod = 10 ** 9 + 7
MAX = K+10
fac = [0] * MAX
finv = [0] * MAX
inv = [0] * MA... | Aasthaengg/IBMdataset | Python_codes/p02985/s142327132.py | s142327132.py | py | 1,201 | python | en | code | 0 | github-code | 90 |
14225819885 | import scipy.misc as misc
from matplotlib import image as mpimg
from matplotlib import pyplot as plt
import numpy as np
import cv2
num_white = 2
def _arrange_data(inData, visize):
img_ht, img_wd = visize
num_data = inData.shape[2] # data has shape [ht, wd, ch]
cell_wd = min(8, int(np.sqrt(num_data)))
... | jia2lin3yuan1/FilePreprocess | visualLayer.py | visualLayer.py | py | 1,957 | python | en | code | 1 | github-code | 90 |
70470772778 | import json
import boto3
from datetime import datetime
# Initialize DynamoDB client
dynamodb = boto3.resource('dynamodb')
TABLE_NAME = 'known_users' # Replace with your DynamoDB table name
SESSION_TABLE_NAME = 'rise_admins' # Replace with the session DynamoDB table name
def is_authorized(session_id):
try:
... | sqavi/RiseApp | admin/admin.py | admin.py | py | 4,728 | python | en | code | 0 | github-code | 90 |
30718425234 | #!/usr/bin/env python
# coding=utf8
import csv
import datetime
import os
import re
import sys
out = csv.writer(sys.stdout)
for line in file(os.path.expanduser('~/.birthdays')):
m = re.match(
'(?P<name>[^=]*)=(?P<day>\d+)/(?P<month>\d+)/(?P<year>\d+)\s*bd\s*',
line
)
if not m:
pri... | mbr/birthday.py | convert.py | convert.py | py | 640 | python | en | code | 1 | github-code | 90 |
21708178780 | import numpy as np
import cv2
def meanshift(particle,oldimg,newimg):
r,h,c,w = particle.y-5,10,particle.x-5,10 # simply hardcoded the values
track_window = (c,r,w,h)
# set up the ROI for tracking
roi = oldimg[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hs... | MemSadePeSade/particle-meanshift | meanshift.py | meanshift.py | py | 957 | python | en | code | 0 | github-code | 90 |
19533746785 | from flask import jsonify, make_response, request
from flask_restful import Api
from flask import Blueprint
from models import db, Garbage, Equipment
from utils import token_required
equipment_routes_blueprint = Blueprint('equipment_routes', __name__, )
api = Api(equipment_routes_blueprint)
# Create Equipment
@equipm... | PatriciaPaulo/ProjetoInformatico | API/routes/equipment_routes.py | equipment_routes.py | py | 1,469 | python | en | code | 0 | github-code | 90 |
73133607655 | import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split, cross_validate # 划分数据集函数
from sklearn.linear_model import LinearRegression
import matplotlib.pyplot as plt
data_df = pd.read_csv('./cwurData.csv') # 读入 csv 文件为 pandas 的 DataFrame
data_df = data_df.dropna() # 舍去包含 NaN 的 row
... | LHS1998/Machine-Learning-Project | ML02/source/nation.py | nation.py | py | 1,986 | python | en | code | 1 | github-code | 90 |
38304959530 |
# return a version of the given string, where for every star (*) in the string the star and the chars immediately to its left and right are gone
# so "ab*cd" yields "ad" and "ab**cd" also yields "ad"
def start_out(str):
s = ''
for x in range(len(str)):
if x == 0 and str[x] != '*':
s = s + ... | jemtca/CodingBat | Python/String-2/start_out.py | start_out.py | py | 596 | python | en | code | 0 | github-code | 90 |
35730933496 | import logging
import time
from config import Config, ConfigItem, ConfigurationError
from ticker_fetcher import AlphavantageTickerExtractor, PostgresqlTickerLoader, AlphavantageTickerTransformer
from ticker_fetcher.ticker_etl_runner import TickerETLRunner
logging.basicConfig(level=logging.DEBUG)
logger = logging.getL... | jshepp27/etl-alphaVantage | worker.py | worker.py | py | 1,308 | python | en | code | 0 | github-code | 90 |
14492740589 | """ Define a class for simulating a type of semi-Markov model. """
import numpy as np
import scipy.optimize as sciopt
from numba import njit
from typing import Sequence, Union, Optional
class SemiMarkov(object):
""" A semi-Markov model.
One way to describe a pure Markov model is to say that the system sta... | ttesileanu/bio-time-series | bioslds/markov.py | markov.py | py | 13,174 | python | en | code | 1 | github-code | 90 |
18018566709 | from sys import exit
N,M = map(int,input().split())
if 2*N>=M:
print(M//2)
exit()
ans = 0
ans += N
M -= 2*N
ans += M//4
print(ans) | Aasthaengg/IBMdataset | Python_codes/p03797/s553876094.py | s553876094.py | py | 135 | python | en | code | 0 | github-code | 90 |
3756722017 | import sys, os
dir_path = os.path.dirname(os.path.realpath(__file__)).split("/")
root_path = ""
for i in dir_path:
root_path += i + "/"
if i == "stock_trading":
break
sys.path.insert(0, root_path)
import yfinance as yf
from datetime import datetime as dt
import pandas as pd
import numpy as np
import mu... | dangalea/stock_trading | scripts/walk_forward_analysis/Trend Following B/new_wfa.py | new_wfa.py | py | 13,326 | python | en | code | 0 | github-code | 90 |
15766342612 | from queue import Queue
class Node:
def __init__(self, value):
self.value = value
self.left = None
self.right = None
class BinarySearchTree:
def __init__(self, root_value):
self.root = Node(root_value)
def insert(self, node, value):
if value <= node.value:
... | bhavani-Zemoso/python | module3/binarySearchTrees/isBSTSatisfied.py | isBSTSatisfied.py | py | 1,696 | python | en | code | 0 | github-code | 90 |
11039845752 | class Solution(object):
def minDeletionSize(self, A):
"""
:type A: List[str]
:rtype: int
"""
res = 0
for col in zip(*A):
if all(col[i]<=col[i+1] for i in range(len(col)-1)):
continue
else:
res +=1
return ... | liangliannie/LeetCode | 944. Delete Columns to Make sorted.py | 944. Delete Columns to Make sorted.py | py | 323 | python | en | code | 0 | github-code | 90 |
9788635447 | #!/usr/bin/python
from math import *
from scipy import *
# from matplotlib import pyplot
# from scipy import linalg
import main
# ----( commands )-------------------------------------------------------------
@main.command
def project_unif(X=3, Y=2):
"projects dJ matrix via inclusion-exclusion, WRT J metric"
... | fritzo/kazoo | test/map_optimizer.py | map_optimizer.py | py | 3,779 | python | en | code | 5 | github-code | 90 |
33969747379 | from flask import Flask, redirect, url_for, render_template, request
from time import sleep
app = Flask(__name__)
@app.route('/',methods=['POST','GET'])
def home():
if request.method == 'POST':
di=request.form["dicta"]
return redirect(url_for("rikrol",dict=di))
return render_template('index... | tuanlt1328/RR | server.py | server.py | py | 494 | python | en | code | 0 | github-code | 90 |
29256246067 | import numpy as np
import pickle
import matplotlib.pyplot as plt
def plot_features():
with open('../../results/RNN_features', 'rb') as f:
feature_selection = pickle.load(f)
# n = feature_selection["count"]
n = 30
feature_mean_errors = []
for featureNo in range(n):
mean_error = np.... | dzitkowskik/StockPredictionRNN | src/nyse-rnn/plotting.py | plotting.py | py | 1,799 | python | en | code | 643 | github-code | 90 |
14343924411 | from fabric.api import run
from fabric.contrib.files import exists
from utils import cat
_key = None
def setup():
global _key
if not exists("~/.ssh/id_rsa"):
run("ssh-keygen -t rsa -b 4096 -f ~/.ssh/id_rsa -N ''")
_key = None
def key():
global _key
if _key == None:
_key = cat("~/.ssh/id_rsa.pub")
return _... | conradz/system | ssh.py | ssh.py | py | 325 | python | en | code | 0 | github-code | 90 |
23048850418 | from collections import defaultdict
from copy import deepcopy
with open("day7_input.txt") as file:
reqs = defaultdict(list)
for line in file.readlines():
reqs[line.split()[7]].append(line.split()[1])
def ans1(reqs):
order = ""
while len(order) != ord(max(reqs.keys())) - ord("A")+1:
fo... | jmjac/advent_of_code_2018 | day7.py | day7.py | py | 1,880 | python | en | code | 0 | github-code | 90 |
1991912551 | import configs
import loading_win
import validations
from search_options import Options
from dialog_win import DialogWin
# desc: displays trade info in gui
class ViewTrade:
# fintracker will be needed to update the table after edit
def __init__(self, dpg, fintracker, trade_id, is_option, row_tag):
sel... | gnikkoch96/Fintracker-GUI | view_trade.py | view_trade.py | py | 23,203 | python | en | code | 2 | github-code | 90 |
35420808704 | import pandas as pd
import numpy as np
arr = np.array(
[
[12,23,34,45,56,67,78],
[22,34,65,55,89,54,33],
[45,56,67,78,78,78,99]
]
)
# print(arr)
df = pd.DataFrame(arr)
# print(df)
arr1 = np.array(
[
['hibernate','education','global','english',1450,200],
['sweet ben... | gauravkamble74/PythonClass | DATA-SCIENCE/PANDAS/01PandasCreate.py | 01PandasCreate.py | py | 1,269 | python | en | code | 0 | github-code | 90 |
19413737742 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 27 09:29:25 2020
@author: pavankunchala
"""
import cv2
import dlib
import matplotlib.pyplot as plt
def show_img_with_matplotlib(color_img,title,pos):
img_RGB = color_img[:,:,::-1]
ax = plt.subplot(1,2,pos)
plt.imshow(img... | Pavankunchala/Deep-Learning | Face-Detection-All Models/Face_detection_dlib/Face_detection_dlib_hog.py | Face_detection_dlib_hog.py | py | 1,398 | python | en | code | 31 | github-code | 90 |
69982927018 | class Image:
def __init__(self, file_path):
file = open(file_path, 'rb')
self.image_data = file.read()
file.close()
self.file_size = self.get_bytes_to_int(2, 4)
self.pixel_data_offset = self.get_bytes_to_int(10, 4)
self.header_size = self.get_bytes_to_int(14, 4)
... | anguslmm/Pyground | images/image.py | image.py | py | 2,511 | python | en | code | 0 | github-code | 90 |
6288111551 | values = []
filename = 'values-1'
with open(filename, 'r') as f:
for line in f:
line = line.split(',')
print(len(line))
print(line)
loss, acc, i = [], [], 0
for value in line:
if i % 2 == 0:
loss.append(value)
else:
if len(value) > 4:
acc_val = value[:4]
l... | hamsterz0/GAN-Stabilization | fix.py | fix.py | py | 600 | python | en | code | 1 | github-code | 90 |
40458651618 | class Hall:
def __init__(self, name, phone, addr, date, cost, owner):
self.name = name
self.phone = phone
self.addr = addr
self.date = date
self.cost = cost
self.owner = owner
def __eq__(self, obj):
# fill your code
return self.name == obj.name an... | praveen-kumars/Python-OOP | CLASSANDOBJECT/IP1/Hall.py | Hall.py | py | 598 | python | en | code | 0 | github-code | 90 |
7855622972 | """
Supervisory Control under Local Mean Payoff Constraints
Weighted Finite-state Automaton
"""
import random
from string import ascii_lowercase
import itertools
from itertools import combinations
from transitions_gui import WebMachine
import time
# from transitions.extensions import GraphMachine as Machine
# naive ... | zhiqich/Supervisory-Control-under-Local-Mean-Payoff-Constraints-Implementation | automaton.py | automaton.py | py | 19,158 | python | en | code | 0 | github-code | 90 |
1973916366 | import sys
from collections import Counter
n=int(sys.stdin.readline())
arr=[] #입력값으로 배열 채우기
for _ in range(n):
arr.append(int(sys.stdin.readline()))
#산술평균
print(round(sum(arr)/n))#소숫점 출력
#중앙값
arr.sort()
print(arr[(n-1)//2])
#최빈값
cnt=Counter(arr).most_common(2)
if len(arr)>1:
if cnt[0][1]==cnt[1][1]:
... | seminss/algorithm-study | solvedac/수학/2108 통계학.py3 | 2108 통계학.py3 | py3 | 481 | python | zh | code | 0 | github-code | 90 |
38512799770 | import tempfile
from http import HTTPStatus
from django.test import TestCase, Client
from blog.models import Article
class BlogURLTest(TestCase):
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.article = Article.objects.create(
title='Привет',
content='',
... | PyChenka/wStore | windstore/blog/tests/test_urls.py | test_urls.py | py | 1,377 | python | en | code | 0 | github-code | 90 |
18336516639 | import sys
input = lambda : sys.stdin.readline().rstrip()
sys.setrecursionlimit(max(1000, 10**9))
write = lambda x: sys.stdout.write(x+"\n")
a,b = list(map(int, input().split()))
def factor(n, m=None):
# mを与えると、高々その素因数まで見て、残りは分解せずにそのまま出力する
arr = {}
temp = n
M = int(-(-n**0.5//1))+1
if m is not Non... | Aasthaengg/IBMdataset | Python_codes/p02900/s345329926.py | s345329926.py | py | 833 | python | en | code | 0 | github-code | 90 |
34868721250 | def digitCount(val):
ret = 1
while(val>0):
remainder = val%10
ret = ret*10
val = val//10
# print('remainder=',remainder,'ret=',ret,'val',val)
return ret
l=[1,21,3,4,5]
num = 0
for i in l:
num = num*digitCount(i) + i
print(num)
# print(digitCount(21))
| manojdon777/Python_Programs | digitsConcat.py | digitsConcat.py | py | 299 | python | en | code | 0 | github-code | 90 |
18067110449 | s = input()
n = len(s)
ans = ''
for i in range(n):
s1 = s[i]
if s1 == '0':
ans += '0'
elif s1 == '1':
ans += '1'
else:
ans = ans[:-1]
print(ans)
| Aasthaengg/IBMdataset | Python_codes/p04030/s686042021.py | s686042021.py | py | 188 | python | en | code | 0 | github-code | 90 |
36084558286 | def primeno(a):
x=0
for i in range(0,a):
c=0
for j in range(1,a):
if i%j==0:
c=c+1
if c==2:
x=x+1
return x
n=int(input("enter the number"))
print(primeno(n))
| ruchikamehra/cyber | Assignment3/cyber3python9.py | cyber3python9.py | py | 240 | python | en | code | 0 | github-code | 90 |
8413386397 | import requests, funcoes, comandos
# Armazenando token do bot (@progredes_dummy_bot) e endereço da
# API do Telegram
API_TOKEN = "6844908109:AAEvwS1L9ToLwN_gsLPAdlKtIxO6ffVkzEc"
TELEGRAM_API = f"https://api.telegram.org/bot{API_TOKEN}"
# Função para salvar a última atualização
def salvar_update_id(update_id: in... | sidneypepo/ifrn | 2023.2/programacao_para_redes/11_bot_telegram/requisicoes.py | requisicoes.py | py | 6,011 | python | pt | code | 2 | github-code | 90 |
14179361049 | import os
import shutil
import cv2
import numpy as np
def load_img_float(path):
"""
return [0, 1]
"""
img = cv2.imread(path, -1)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
return img/255
def save_img_float(path, img):
"""
input [0, 1]
"""
img = (img*255).astype(np.uint8)
... | ZFhuang/MLAA-python | utils.py | utils.py | py | 1,445 | python | en | code | 4 | github-code | 90 |
73640684456 | from args import build_parser
import logging
import os
import wandb
import sys
import time
from chat_classifier import LLamaChatClassifier, ChatGPTChatClassifier
from config import LOGGING_FORMAT, LOGGING_DATE_FORMAT, RESULTS_DIR, LOG_DIR, WANDB_DIR, WANDB_API_KEY_PATH, \
WANDB_USER_NAME_PATH
from utils ... | pauli31/czech-sentiment-prompting | main.py | main.py | py | 2,772 | python | en | code | 0 | github-code | 90 |
661774642 | from oslo_log import log as logging
from jacket.db import extend as db
from jacket import exception
from jacket.objects import base
from jacket.objects import extend as objects
from jacket.objects import fields
LOG = logging.getLogger(__name__)
@base.JacketObjectRegistry.register
class ImageSync(base.JacketPersiste... | HybridF5/jacket | jacket/objects/extend/image_sync.py | image_sync.py | py | 2,542 | python | en | code | 0 | github-code | 90 |
70640474856 | import streamlit as st
from Get_Details.Create_URL import CreateURL
from Get_Details.Fetch_Details import GetData, StoreData
from Web_App import Create_App
class DisplayDetails:
"""
Class to initialize value and represent it
"""
def __init__(self, temperature, humidity, forecast):
self.tempera... | siddheshshankar/Weather_API | Web_App/run_app.py | run_app.py | py | 1,063 | python | en | code | 0 | github-code | 90 |
41458376518 | import sys
from collections import UserDict, namedtuple
from pathlib import Path
from string import ascii_lowercase
import numpy as np
import pytest
from icecream import ic
# a number longer than any path we'll be making
NOT_REACHED = 1_000_000
# --> Puzzle solution
def parse(input_text):
all_lines = []
f... | j-carson/advent_2022 | days/12/wip.py | wip.py | py | 4,534 | python | en | code | 0 | github-code | 90 |
39166448249 | class Painting:
def __init__(self,paintingID,painterName,paintingPrice,paintingType):
self.paintingID = paintingID
self.painterName = painterName
self.paintingPrice = paintingPrice
self.paintingType = paintingType
class ShowRoom:
def __init__(self,paintings):
se... | 07shikhar/Python-Codes | Painting.py | Painting.py | py | 1,634 | python | en | code | 0 | github-code | 90 |
37462131498 | import argparse
from planner.planner import Planner
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("map_name", type=str, help="Name of the map")
parser.add_argument('source', type=str, help='Name of source node')
parser.add_argument('destination', type=str, help='Nam... | anenriquez/mrta_planner | get_path.py | get_path.py | py | 673 | python | en | code | 1 | github-code | 90 |
7633442264 | # uses an arx model structure to learn a dynamic systems output probability density function
# this example is for a very simple no input single output feedback system
# what is interesting is that it can learn different pdfs: gaussian, cauchy, bimodal gaussian
import torch
import matplotlib.pyplot as plt
import torch... | jnh277/ebm_arx | scalar_example.py | scalar_example.py | py | 7,757 | python | en | code | 3 | github-code | 90 |
34697083187 | from scipy.io import loadmat
from scipy.spatial import distance
import os, math
import numpy as np
def get_splits(splits_path='/home/wpc/master-thesis-master/srnn-copy/data/JHMDB/splits', ind_split = 1, JHMDB=True):
train = np.array([],dtype=str)
test = np.array([],dtype=str)
ind_split = str(ind_split) +... | Keysmis/Action-Recognition-based-on-Structural-RNN-tensorflow | read_data_submit.py | read_data_submit.py | py | 20,387 | python | en | code | 5 | github-code | 90 |
37972483681 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2022/3/6 12:01
# @Author : v_bkaiwang
# @File : assert_pkg.py
# @Software: win10 Tensorflow1.13.1 python3.6.3
from typing import Iterable
# from .log_message import LogMessage, LOG_ERROR, LOG_INFO
from Lib.CommonLib.BaseLib.log_message import LogMessage, LO... | Wangkaiof21/M1 | Lib/CommonLib/BaseLib/assert_pkg.py | assert_pkg.py | py | 4,152 | python | en | code | 0 | github-code | 90 |
29042372235 | import pandas as pd
import os
import tensorflow as tf
import numpy as np
paths = {
'Data' : os.path.join(os.getcwd(),'Data'),
'Notebooks' : os.path.join(os.getcwd(),'notebooks'),
'models' : os.path.join(os.getcwd(),'models')
}
df = pd.read_csv(os.path.join(paths['Data'],'amazon_co_ecommerce_sample.csv'))
... | alihkousha/Task1 | mainn.py | mainn.py | py | 1,042 | python | en | code | 2 | github-code | 90 |
4949462640 | import argparse
from pathlib import Path
import numpy as np
import torch
from torchvision.utils import make_grid, save_image
from tqdm import tqdm
import util
def main():
"""
Load trained generator model and save generated sampels.
<n_row> x <n_row> grid image is saved into <output_dir>
"""
par... | raahii/infogan-pytorch | src/infer.py | infer.py | py | 1,603 | python | en | code | 14 | github-code | 90 |
44848250026 | # Advent of Code 2020 Day 8
import AOC
CMD = 0
VAL = 1
def get_code() -> []:
lines = AOC.get_input_lines(8, AOC.format_strip)
code = []
for line in lines:
line.replace("+","")
split = line.split(" ")
code.append(split)
return code
def run_code(code : [] , log_errors = False... | drantscript/AdventOfCode2020 | Day8.py | Day8.py | py | 1,548 | python | en | code | 0 | github-code | 90 |
41601161783 | import os
'''
Faça uma lista de compras com listas
O usuário deve ter a possiblidade de inserir,
apagar e listar valores da sua lista
Não permita que o programa quebre com erros
de índices inexistentes na lista
'''
lista = []
produto = ''
indice = ''
while True:
print("\n")
try:
print(5*'=', 'Minha L... | Dhaxx/PYTHON | EXERCICIOS/lista_de_compras.py | lista_de_compras.py | py | 2,032 | python | pt | code | 1 | github-code | 90 |
72143536938 | # -*- coding: utf-8 -*-
"""Define the top-level function for the ``sync-npm`` cli.
"""
from __future__ import absolute_import, division, print_function, unicode_literals
import time
from aspen import log
from gratipay import wireup
from gratipay.sync_npm import consume_change_stream, get_last_seq, production_change_... | gratipay/gratipay.com | gratipay/cli/sync_npm.py | sync_npm.py | py | 1,160 | python | en | code | 1,121 | github-code | 90 |
39284628014 | modern_family = ['CLaiRe_DunPhY', 'PHiL_dUnpHY', 'GLoRiA_PriTCheTt', 'CaMErOn_TuCKEr',
'StELLa']
indices = list()
characters = list()
for i, name in enumerate(modern_family):
indices.append(i)
characters.append(name.lower().replace('_', '-'))
print(indices)
print(characters)
[0, 1, 2... | gajjoshi/task1 | task1.py | task1.py | py | 1,181 | python | en | code | 0 | github-code | 90 |
16492526863 | try:
from fuzzywuzzy import fuzz
except:
import os
inp = input('The fuzzywuzzy package is not installed. Do you want to install? Press y.')
if inp =='y':
os.system(
'pip install fuzzywuzzy')
from fuzzywuzzy import fuzz
try:
import networkx as nx
except:
import os
inp = in... | snorre87/wordtools | string_matching.py | string_matching.py | py | 3,278 | python | en | code | 0 | github-code | 90 |
350573927 | from get_url_from_firstpage import Get_Url_From_FirstPage
import requests
from bs4 import BeautifulSoup
import urllib
import threading
import json
import pandasdmx
import time
import os
import sys
from selenium.common.exceptions import NoSuchElementException
def get_datacode():
urlsclass = Get_Url_From_FirstPage()
... | bluesky49/OECD_scraping | src/csv_download.py | csv_download.py | py | 7,549 | python | en | code | 1 | github-code | 90 |
37538740007 | import os.path
from teplo500.core import *
from teplo500.salus import salus_connect
EMUL_DEVICES_ONLINE_FILE = "/local/fakes/devices_online.html"
EMUL_DEVICES_OFFLINE_FILE = "/local/fakes/devices_offline.html"
## args:
## return:
## true=success or false=failed
def emul_load_devices():
file_path = get_app().home... | MaxBazarov/teplo500py | lib/Teplo500/salus/salus_emul.py | salus_emul.py | py | 777 | python | en | code | 0 | github-code | 90 |
18638183918 | import pygame
import pyray
WIDTH = 512
HEIGHT = 384
FPS = 60
display = pygame.display.set_mode((WIDTH, HEIGHT), pyray.flags)
clock = pygame.time.Clock()
colors = [(255, 0, 0),
(0, 255, 0)]
map = [[1,1,1,1,1,1,1],
[1,0,0,0,0,0,1],
[1,0,0,0,0,0,1],
[1,0,0,2,0,0,1],
[1,0,0,0,0,0,1... | lewisc64/pyray | examples/basic.py | basic.py | py | 899 | python | en | code | 0 | github-code | 90 |
12652231753 | import pickle
import numpy as np
import streamlit as st
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
MODEL_PKL_FILE = "model.pkl"
IRIS_PKL_FILE = "iris.pkl"
def main():
"""This function runs/ orchestrates the Machine Learning App Registry"""
st.markdown(
"""
# Machine ... | 7125messi/streamlit-web-ml | 010-streamlit-ml-predict.py | 010-streamlit-ml-predict.py | py | 3,324 | python | en | code | 1 | github-code | 90 |
15807359727 | # -*- coding: utf-8 -*-
#
# CTCを学習します．
#
# Pytorchを用いた処理に必要なモジュールをインポート
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torch import optim
# 作成したDatasetクラスをインポート
from my_dataset import SequenceDataset
# 数値演算用モジュール(numpy)をインポート
import numpy as np
# プロッ... | ry-takashima/python_asr | 05ctc/02_train_ctc.py | 02_train_ctc.py | py | 24,814 | python | ja | code | 75 | github-code | 90 |
11697120354 | from userdata import User, DatabaseEntry
from wordgame import InputWord
def register():
fname = input("Enter your first name: ")
sname = input("Enter your surname: ")
uname = input("Enter a username of your choice: ")
# To-CODE
# If username already present, do not create
database = DatabaseEnt... | raunakpalit/WGame | WordGame/userask.py | userask.py | py | 2,709 | python | en | code | 0 | github-code | 90 |
5304257418 | """Cache manager of traced repos.
"""
import os
import shutil
import tarfile
from pathlib import Path
from loguru import logger
from filelock import FileLock
from dataclasses import dataclass, field
from typing import Optional, Tuple, Generator
from ..utils import (
execute,
url_exists,
get_repo_info,
... | lean-dojo/LeanDojo | src/lean_dojo/data_extraction/cache.py | cache.py | py | 3,574 | python | en | code | 338 | github-code | 90 |
27932187794 | from __future__ import (division as _py3_division,
print_function as _py3_print,
absolute_import as _py3_abs_import)
from players import Human, Computer
from icon import IconO, IconX
class GameMode(object):
def restart(self):
self.player1.moves = []
... | Sergio2409/curemetrix-python-challengue | tic-tac-toe/game_mode.py | game_mode.py | py | 1,274 | python | en | code | 0 | github-code | 90 |
42440751061 | from skyfield.api import load, wgs84
import json
stations_url = 'http://celestrak.com/NORAD/elements/stations.txt'
satellites = load.tle_file(stations_url)
by_name = {sat.name: sat for sat in satellites}
satellite = by_name['ISS (ZARYA)']
n = 25544
url = 'https://celestrak.com/satcat/tle.php?CATNR={}'.format(n)
fil... | gonetoplaid74/SpaceRadar24 | iss1.py | iss1.py | py | 2,144 | python | en | code | 0 | github-code | 90 |
70760737256 | import pandas as pd
from sklearn.linear_model import LinearRegression
data = pd.read_csv(r"C:\Users\aarus\coding\kaggle\Udacity_SVM\data.csv")
X = data[['YearsExperience']]
y = data.Salary
model = LinearRegression()
model.fit(X,y)
print(model.predict(8.5))
| aaru4/SVM_emails | model.py | model.py | py | 264 | python | en | code | 0 | github-code | 90 |
14495062056 | from panda3d.core import VirtualFileSystem, ConfigVariableList, Filename
import sys
sys.path = [
'']
vfs = VirtualFileSystem.getGlobalPtr()
mounts = ConfigVariableList('vfs-mount')
for mount in mounts:
mountFile, mountPoint = (mount.split(' ', 2) + [None, None, None])[:2]
vfs.mount(Filename(mountFile), Filenam... | TTOFFLINE-LEAK/ttoffline | v1.0.0.test/toontown/launcher/TTOffQuickStartLauncher.py | TTOffQuickStartLauncher.py | py | 505 | python | en | code | 3 | github-code | 90 |
18395072559 | N = int(input())
cnt = dict()
nodes = [set() for _ in range(N+1)]
for _ in range(N-1):
a, b = [int(x) for x in input().split()]
cnt[a-1] = cnt.get(a-1,0) + 1
cnt[b-1] = cnt.get(b-1,0) + 1
nodes[a-1].add(b-1)
nodes[b-1].add(a-1)
C = [int(x) for x in input().split()]
C = sorted(C, reverse=True)
Z... | Aasthaengg/IBMdataset | Python_codes/p03026/s977034787.py | s977034787.py | py | 692 | python | en | code | 0 | github-code | 90 |
12207660989 | import paho.mqtt.client as paho
import time
import matplotlib.pyplot as plt
import numpy as np
import serial
mqttc = paho.Client()
# XBee setting
serdev = '/dev/ttyUSB0'
s = serial.Serial(serdev, 9600)
s.write("+++".encode())
char = s.read(2)
s.write("ATMY <0x140>\r\n".encode())
char = s.read(3)
s.write("ATDL <0x240>... | Shelley1214/EE240500_Embedded_System | final_project/publish.py | publish.py | py | 1,617 | python | en | code | 0 | github-code | 90 |
377608578 | import tensorflow as tf
from instancesegmentation.loss.distancemetric import (
DistanceMetric,
ManhattanDistanceMetric,
)
from instancesegmentation.loss.errormetric import (
ErrorMetric,
SquaredErrorMetric,
)
# It is okay to use these as defaults, as they have no internal state
_default_distance_metri... | fuchspa/instancesegmentation | instancesegmentation/loss/metricloss.py | metricloss.py | py | 6,025 | python | en | code | 1 | github-code | 90 |
32012815422 | import datetime
import pytz
import base64
from datetime import timedelta, datetime
IST = pytz.timezone('Asia/kolkata')
def dictfetchall(cursor):
columns = [col[0] for col in cursor.description]
return [
dict(zip(columns, row))
for row in cursor.fetchall()
]
def write_A... | suhasnidgundi7/SCNJ_Tech | utils.py | utils.py | py | 3,778 | python | en | code | 0 | github-code | 90 |
28508571407 | import random
from Words import hangmanWords
import string
def get_valid_word(hangmanWords):
print("This is a set", set())
randomWord = random.choice(hangmanWords) # random word from this list
while '-' in randomWord or ' ' in randomWord:
randomWord = random.choice(hangmanWords)
return random... | Yxniv/PersonalProjects | Hangman.py | Hangman.py | py | 1,754 | python | en | code | 0 | github-code | 90 |
70087175018 | #!/usr/bin/env python
###################################################################
# #
# Setup file for compiling and installing the python wrapper #
# for dasslc #
# ... | asanet/dasslc2py | setup.py | setup.py | py | 1,477 | python | en | code | 13 | github-code | 90 |
73211779818 | #
# @lc app=leetcode id=877 lang=python
#
# [877] Stone Game
#
# @lc code=start
class Solution(object):
def stoneGame(self, piles):
"""
:type piles: List[int]
:rtype: bool
"""
# Both Alice and Bob can see the array
# Easy approach
# If sum is always ... | ashshekhar/leetcode-problems-solutions | 877.stone-game.py | 877.stone-game.py | py | 1,747 | python | en | code | 0 | github-code | 90 |
23092008774 | import random
rock = '''
_______
---' ____)
(_____)
(_____)
(____)
---.__(___)
'''
paper = '''
_______
---' ____)____
______)
_______)
_______)
---.__________)
'''
scissors = '''
_______
---' ____)____
______)
__________)
(____)
-... | fatiholgunoz/rock_paper_scissors | main.py | main.py | py | 1,137 | python | en | code | 0 | github-code | 90 |
72207855658 | '''
给定一个包含 [0, n] 中 n 个数的数组 nums ，找出 [0, n] 这个范围内没有出现在数组中的那个数。
进阶：
你能否实现线性时间复杂度、仅使用额外常数空间的算法解决此问题?
示例 1：
输入：nums = [3,0,1]
输出：2
解释：n = 3，因为有 3 个数字，所以所有的数字都在范围 [0,3] 内。2 是丢失的数字，因为它没有出现在 nums 中。
示例 2：
输入：nums = [0,1]
输出：2
解释：n = 2，因为有 2 个数字，所以所有的数字都在范围 [0,2] 内。2 是丢失的数字，因为它没有出现在 nums 中。
示例 3：
输入：nums = [9,6,4,2... | Asunqingwen/LeetCode | Cookbook/Array/丢失的数字.py | 丢失的数字.py | py | 1,448 | python | zh | code | 0 | github-code | 90 |
28300580455 | from observer.observers.DisplayElement import DisplayElement
from observer.observers.Observer import Observer
from observer.observables.WeatherData import WeatherData
class ForecastDisplay(Observer, DisplayElement):
def __init__(self, weather_data: WeatherData):
self.pressure = 1025 # hPa
... | gsegon/design_patterns | observer/observers/ForecastDisplay.py | ForecastDisplay.py | py | 934 | python | en | code | 0 | github-code | 90 |
43502101477 | from os import path
def remove_comments(input_file: str, output_file: str):
"""
Functie om de comments van een python file te verwijderen.
Als een lijn begint met een "#" dan is het een comment en
kan alles daarna verwijderd worden.
:param input_file: str, pad naar het bestand
:param output_f... | Thom2503/basecamp | arch3/week10/problems/commentremover.py | commentremover.py | py | 1,214 | python | nl | code | 0 | github-code | 90 |
40297402179 | # encoding: utf-8
class Solution:
def findDiagonalOrder(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: List[int]
"""
if (not matrix) or (not matrix[0]): return []
r, c = len(matrix), len(matrix[0])
if r == 1: return matrix[0]
res = []
... | 3367472/Python_20180421 | LeetCode/498.3.py | 498.3.py | py | 1,345 | python | en | code | 0 | github-code | 90 |
74639751015 | import os
from bot.bot import DiscordBot
if __name__ == '__main__':
bot = DiscordBot()
if not os.path.exists('{0}\{1}'.format(os.getcwd(), 'config.ini')):
print('Creating base configuration file...')
bot.create_config()
else:
bot.get_token()
bot.run() | Lanilor53/weeble | main.py | main.py | py | 295 | python | en | code | 0 | github-code | 90 |
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