blob_id stringlengths 40 40 | language stringclasses 1
value | repo_name stringlengths 5 133 | path stringlengths 2 333 | src_encoding stringclasses 30
values | length_bytes int64 18 5.47M | score float64 2.52 5.81 | int_score int64 3 5 | detected_licenses listlengths 0 67 | license_type stringclasses 2
values | text stringlengths 12 5.47M | download_success bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|---|
caad3fa7da38aa9bcc752eb320380ff56c15f7a9 | Python | hsinhoyeh/leecode | /kth-largest-element-in-an-array/solution.py | UTF-8 | 1,184 | 3.59375 | 4 | [] | no_license | class Solution(object):
def findKthLargest(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: int
"""
return self.find_k_th(nums, k)
def find_k_th(self, nums, k):
if len(nums) ==1:
return nums[0]
pivot = nums[-1] # use the... | true |
bbd82c13f1e7c81d1b0435b5ee32ec63ee0dcfbc | Python | tiffany70072/explainable-Seq2Seq | /src_March/utils.py | UTF-8 | 16,931 | 2.515625 | 3 | [] | no_license | import numpy as np
import tensorflow as tf
import keras.backend as K
import read_data
def write_results(results, output_file):
print('output filename =', output_file)
fout = open(output_file, 'w')
for i in range(len(results)):
fout.write(" ".join(results[i]))
fout.write("\n")
def masked_perplexity_loss(y_true... | true |
2ff777dcb8aef3600fb431e2a80b725b6f45eebc | Python | bpRsh/a4b_jedicolor_args | /myranges.py | UTF-8 | 537 | 2.828125 | 3 | [] | no_license | #!/usr/local/bin/env python3
# -*- coding: utf-8 -*-
#
# Author : Bhishan Poudel, Physics PhD Student, Ohio University
# Date : Jul 06, 2017 Thu
# Last update :
def main():
"""Main Module."""
# Imports
import numpy as np
import pandas as pd
import time
laml = np.linspace(2208,2764... | true |
e8434ddf36c7f479880eeb924591bff6a4d5b59c | Python | HDree/Python | /Stock price Predict.py | UTF-8 | 1,176 | 2.828125 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from google.colab import files
uploaded = files.upload()
#read the file
df = pd.read_csv('A2M.AX1.csv')
df = df.set_index(pd.DatetimeIndex(df['Date'].values))
#print the head
df
def EMA(data, period=20, column='Close'):
return data[column].ewm(... | true |
08336363fd81dfedb247a43ac0da0a3cbb589f8f | Python | Malikanhar/Pose-Detection | /src/run_webcam.py | UTF-8 | 4,525 | 2.515625 | 3 | [
"MIT"
] | permissive | import argparse
import logging
import time
from keras.models import load_model
from keras.layers import Activation
import cv2
import numpy as np
from estimator import TfPoseEstimator
from networks import get_graph_path, model_wh
logger = logging.getLogger('TfPoseEstimator-WebCam')
logger.setLevel(logging.DEBUG)
ch ... | true |
122caeb6cb85e6e5dc7b91eb83f5981a068b9b23 | Python | csadrian/wae | /utils.py | UTF-8 | 2,333 | 2.703125 | 3 | [
"BSD-3-Clause"
] | permissive | # Copyright 2017 Max Planck Society
# Distributed under the BSD-3 Software license,
# (See accompanying file ./LICENSE.txt or copy at
# https://opensource.org/licenses/BSD-3-Clause)
"""Various utilities.
"""
import tensorflow as tf
import os
import sys
import copy
import numpy as np
import logging
import matplotlib
m... | true |
8e9fe85c2ed5ac61190dba74e2c92d9dd9c1d0e5 | Python | rmlz/cqw2calibtool | /cqw2_calibrate/epiphyton_rates_constants.py | UTF-8 | 6,810 | 2.5625 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
"""
Created on Thu Sep 5 16:30:52 2019
@author: Ramon Barros
CE-QUAL-W2 Calibration Tool v0.0.1
MODEL EPIPHYTON GROUPS RATES & CONSTANTS
paramcontrol(name, calibrate, value, low, high, guess)
name = Parameter or setting name,
calibrate = boolean, True if the parameter must be calibrated (val... | true |
ac720d5c61ecaa14f0ce41d0128c46a64684853b | Python | codinghappiness-web/python-project | /dice game.py | UTF-8 | 264 | 3.640625 | 4 | [] | no_license | import random
min = 1
max = 6
roll_again = "y"
while roll_again is "y":
print("rolling the dices...")
print("the values are")
print(random.randint(min,max))
print(random.randint(1,6))
roll_again = input("roll the dices again? ")
| true |
50cd81f1741f6ee1e5ac520e89547f9317ed236c | Python | pochtalexa/netology_home_works | /data_fomats/data_formats.py | UTF-8 | 2,301 | 3.1875 | 3 | [] | no_license | import json
import jmespath
import pandas as pd
import xml.etree.ElementTree as ET
from pprint import pprint
# -------------------------------------------------------------------------------------------------------
def read_json(file_name):
with open(file_name, encoding='utf-8') as f:
data = json.load(f)... | true |
471d6c40a29b8c42f369aac1925dd78d1861e366 | Python | LifeBringer/LinearAlgebra | /line.py | UTF-8 | 4,935 | 3.234375 | 3 | [
"MIT"
] | permissive | from decimal import Decimal, getcontext
from vector import Vector
getcontext().prec = 30
class Line(object):
NO_NONZERO_ELTS_FOUND_MSG = 'No nonzero elements found'
def __init__(self, normal_vector=None, constant_term=None):
self.dimension = 2
if not normal_vector:
... | true |
c6f242972e92a8e144c472c2d312d36b1b31fa6b | Python | irfan87/python_tutorial | /dictionaries/favorite_languages.py | UTF-8 | 1,694 | 3.328125 | 3 | [] | no_license | favorite_languages = {
'jen': 'python',
'edward': 'ruby',
'phil': 'python',
'sarah': 'c',
'jamal': 'java',
'james': 'java',
'hassan': 'php'
}
print("\nProgrammer with their favorite language polls")
for programmer_name, favorite_language in favorite_languages.items():
if favorite_langua... | true |
d683175e48af3c3706acb8845ba97d979488bdc2 | Python | cloudtrends/harrychinese | /python/DbRowFactory/pyDbRowFactory.py | UTF-8 | 8,690 | 2.796875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
'''
#@summary: DbRowFactory is one common row factory for any database
module conformed to Python Database API Specification
v2.0. e.g. cx_Oracle, zxJDBC
#@note: DbRowFactory will create one row instance based on row class binding,
and try to assign all fie... | true |
9c7d45f954ac8edfeaff633435564b713afffc19 | Python | yuwtsri/tcga-script | /Plot/KM_plot.py | UTF-8 | 1,631 | 2.90625 | 3 | [] | no_license | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
#import seaborn as sns
from lifelines import KaplanMeierFitter
file = "X:\\Su Lab\\TCGA\\Data\\Matrix\\TCGA-BRCA-total-matrix.csv"
matrix = pd.read_csv(file, sep = '\t')
def is_number(s):
if pd.isnull(s):
return False
else:
try:... | true |
65bd101ce1315d1b8f768fdae0603767cf62ad39 | Python | arnold8968/lab1 | /Project1/Code/NYC_Parking/Question_d/mapper.py | UTF-8 | 716 | 2.921875 | 3 | [] | no_license | #!/usr/bin/python
# --*-- coding:utf-8 --*--
import re
import sys
for line in sys.stdin:
valueString = str(line) # input comes from STDIN(Standard input)
SingleParkingData = valueString.split(',') # split csv document into different columns
if len(SingleParkingData[34]) > 0: # cleaning the empty co... | true |
f5cfecee1481ce28ec64ef626a5282c9ff5a2fb6 | Python | a3r0d7n4m1k/YACS | /courses/encoder.py | UTF-8 | 5,531 | 2.53125 | 3 | [
"MIT"
] | permissive | """ Handles the encoding of model objects for templates.
"""
from django.db.models import Model
from courses import models
def get_fields(model):
return model._meta.fields
def get_fk_fields(model):
return [f for f in get_fields(model) if f.rel]
def get_normal_fields(model):
return [f for f in get_fie... | true |
0923f6d9b46b9d358584edbdc32bc7d2ccea0b25 | Python | ttund21/LearningPython | /Extras/Faculdade/Prova/questao2.py | UTF-8 | 711 | 3.703125 | 4 | [] | no_license | def notaAbaixo(notas):
reg = []
for i in notas:
if i < 7:
reg.append(str(i))
print(f"\nNotas Abaixo de 7: {' ,'.join(reg)}")
def parImpar(notas):
impar = []
par = []
for i in notas:
if i%2 == 0:
par.append(str(i))
else:
impar.append(st... | true |
8a9b430f031c001168b9642ef511d74efcca5840 | Python | TheCyberAtom/LeetCode_Python | /How Many Numbers Are Smaller Than the Current Number.py | UTF-8 | 305 | 3.046875 | 3 | [] | no_license | class Solution:
def smallerNumbersThanCurrent(self, nums: List[int]) -> List[int]:
lst = sorted(nums)
res = []
for i in nums:
for j in range(len(lst)):
if i == lst[j]:
res.append(j)
break
return res
| true |
8417a9c14e62f54bfb5336eb132084eec5b38da5 | Python | HSIYJND/Hyperspectral-Image-Learning | /HSI Classification/Using SOM/SOM_v1.py | UTF-8 | 1,719 | 2.625 | 3 | [] | no_license | #Import the library
import SimpSOM as sps
import os
from spectral import *
import scipy.io as sio
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
script_dir = os.path.dirname(__file__) #<-- absolute dir the script is in
rel_path = "data/92AV3C.lan"
abs_file_path = os.path.join(sc... | true |
b1d11cddd9daa50dc768516446a56d4a9d5b1307 | Python | Kungbib/ocrqc | /ocrqtapp.py | UTF-8 | 1,729 | 2.53125 | 3 | [
"Apache-2.0"
] | permissive | # -*- coding: utf-8 -*-
from __future__ import print_function
from flask import Flask, request, session, g, redirect, url_for, abort, render_template, flash
import editdistance
import diff_match_patch as dmp_module
app = Flask(__name__)
app.config.from_object(__name__)
@app.route("/", methods=['POST', 'GET'])
def in... | true |
308fe8b2cea8d964b4e418b48b1f0e5d4c2c3406 | Python | a87150/learnpy | /coroutine_selectors.py | UTF-8 | 1,475 | 2.796875 | 3 | [] | no_license | import socket
import sys
import time
from selectors import DefaultSelector, EVENT_READ, EVENT_WRITE
sel = DefaultSelector()
times = 10
class Furture():
def __init__(self):
self.coro = None
def add_coro(self, coro):
self.coro = coro
def resume(self):
global times
try:
... | true |
ec551fbfad0269d4ac59940bec9d35ea401e3505 | Python | rafaelaraujobsb/URI-CodeForces | /Python/round3B.py | UTF-8 | 215 | 3.703125 | 4 | [] | no_license | while True:
n = int(input())
if n == 0:
break
i=1
p=1
for t in range(1,n+1):
if t == 1:
print("1", end="")
i += 2
p += i
if p > n:
break
else:
print(" {}".format(p), end="")
print("")
| true |
685d117dcc5fe65cf8128f6615e3e4677e57ee46 | Python | OnyiegoAyub/SENDIT-API | /app/api/v1/models/parcel_order_models.py | UTF-8 | 949 | 2.90625 | 3 | [] | no_license | class Parcel:
parcels = []
users = []
def create(self, origin, destination, weight, status):
parcel = {
"parcel_id": len(Parcel.parcels) + 1,
"user_id": len(Parcel.parcels) + 1,
"origin": origin,
"destination": destination,
"weight": weight,
"status": s... | true |
c40b0b751294a4e1f99ad1a8018bc5ec9f91a001 | Python | ravisrhyme/CTCI | /chapter9/staircase.py | UTF-8 | 628 | 3.90625 | 4 | [] | no_license | """
A child is running up in a staircase with n steps, and can hop either 1 step,
2steps or 3 steps at a time. Implement a method to count how many possible ways
the child can run up the stairs
Time Complexity = O(n)
space Complexity = O(n)
"""
__author__ = "Ravi Kiran Chadalawada"
__email__ = "rchadala@usc.edu"
... | true |
9cd94eaa5e7b48b9ab6da9476fa85d92efac4b95 | Python | danpianji/python3.7 | /lgp/highlevel/8JSON.py | UTF-8 | 895 | 4 | 4 | [] | no_license | # -*- coding: UTF-8 -*-
import json
print "你好"
"""
json.dumps 将 Python 对象编码成 JSON 字符串
json.loads 将已编码的 JSON 字符串解码为 Python 对象
python 原始类型向 json 类型的转化对照表：
Python JSON
dict object
list, tuple array
str, unicode string
int, long, float number
True true
False false
None null
json 类型转换到 python 的类型对照表：
JSON Pyt... | true |
cd4f21aecc1e84f63d4d05b1b8df7ac74f7a0285 | Python | vegadodo/project-euler-python | /p001.py | UTF-8 | 293 | 4.03125 | 4 | [
"MIT"
] | permissive | """
Problem 1.
Multiples of 3 and 5
https://projecteuler.net/problem=1
"""
# Pretty self-exlanatory code.
# Check if given number is dividable by 3 or 5.
# Rinse and repeat for 1 to 1000.
answer = 0
for i in range(1000):
if i % 3 == 0 or i % 5 == 0:
answer += i
print(answer)
| true |
bb41fc74c02f92080ace7b1ec9c81783b7e94c8d | Python | jinglinzhao/Python_codes | /0404-ksiboo/Calendar-BJD.py | UTF-8 | 327 | 2.546875 | 3 | [] | no_license | # run with python2.7
import numpy as np
from DateTime import DateTime
Date = np.genfromtxt('ksiboo_date_sqrt_p.dat', dtype = None)
Date_new = [ Date[i][0] + ' ' + Date[i][1] for i in range(len(Date))]
BJD = [DateTime(Date_new[i]).timeTime()/(24.*3600) for i in range(len(Date))]
np.savetxt('ksiboo_BJD_sqrt_p.dat... | true |
c0a9c198ca1ed20a4e61919b81bac10327b7a6ea | Python | suvoganguli/DeepLearning | /Part6_ReinforcedLearning/Project-Quadcopter/2018-07-06/main.py | UTF-8 | 2,521 | 2.828125 | 3 | [] | no_license | import numpy as np
import agents.agent as agent
from task import Task
import matplotlib.pyplot as plt
import sys
# Task: take-off and hover
init_pose = [0.0, 0.0, 100.0, 0.0, 0.0, 0.0]
init_velocities = [0.0, 0.0, 0.0]
init_angle_velocities = [0.0, 0.0, 0.0]
run_time = 10
target_pos = [0.0, 0.0, 100.0]
num_episodes =... | true |
da15e3c94c211fc6b6e3c28072f02008b952a74c | Python | jlinkemeyer/MLinPractice | /code/preprocessing/stemmer.py | UTF-8 | 1,426 | 3.40625 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Create the word stems of the individual words of the tweet.
Created on Wed Oct 6 16:32:45 2021
@author: laura
"""
from code.preprocessing.preprocessor import Preprocessor
from code.util import TOKEN_DELIMITER
from nltk.stem import PorterStemmer
class Stemmer(Prepr... | true |
0663695a4af4d05cbd49542519b7569da069a22d | Python | spotty-cloud/spotty | /spotty/providers/aws/resources/snapshot.py | UTF-8 | 1,585 | 2.6875 | 3 | [
"MIT"
] | permissive | import time
class Snapshot(object):
def __init__(self, ec2, snapshot_info):
self._ec2 = ec2
self._snapshot_info = snapshot_info
@staticmethod
def get_by_name(ec2, snapshot_name: str):
"""Returns a snapshot by its name."""
res = ec2.describe_snapshots(Filters=[
... | true |
34a05755ce62d5ef71570834f02779b7aef16601 | Python | slopezv2/CompetitiveProgramming | /talkingp.py | UTF-8 | 231 | 3.328125 | 3 | [] | no_license | vowels = ["a", "e", "i", "o", "u"]
cases = int(input())
phrases = []
newPhrases = []
for i in range(cases):
phrases.append(input())
for p in phrases:
for v in vowels:
p = p.replace(v, v + "p" + v)
print(p)
| true |
56de67e1446f4c8da009ef12aa9920555da41c0f | Python | jlandy99/TrafficSignClassification | /run.py | UTF-8 | 1,582 | 2.8125 | 3 | [] | no_license | from preprocess import preprocess, rebalance
from Net import Net, printModel
from TrafficSignDataset import TrafficSignDataset, dataLoader
from train import train_model
from plot import plot
import torch
from helper import cal_accuracy
# Use this function if using GPU to run code
def setupGPU():
"""Make sure we ... | true |
f246b6e69e7e3455011f0dbb669c2b86cdc2cfdb | Python | TillSchlemmermeier/l3d-controller-software | /generators/g_cube.py | UTF-8 | 1,453 | 3.0625 | 3 | [] | no_license | # modules
import numpy as np
class g_cube():
'''
Generator: cube
a cube in the cube
Parameters:
- size
- sides y/n : just the edges or also the sides of the cube?
'''
def __init__(self):
self.size = 4
self.sides = False
def control(self, size, sides, blub1):
... | true |
49d70733fbd6a4e45768cbf7fee8cec3b4bf6762 | Python | greyshell/ds_algorithm | /heap/k_largest_elements_array.py | UTF-8 | 667 | 3.59375 | 4 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# author: greyshell
from snowowl import Heap, HeapType
def get_k_largest_elements_array(array: list, k: int) -> list:
"""
time complexity: O(n*log(k))
space complexity: O(k)
"""
min_heap = Heap([])
for num in array:
min_heap.insert(num)
if len(min_heap... | true |
c060ea614666b3ffeeddaa5eb880c0c6a7e90642 | Python | Kunal352000/python_adv | /21_datatime1.py | UTF-8 | 110 | 2.71875 | 3 | [] | no_license | import datetime
x=datetime.datetime.now()
print(x)
"""
output:
-------
2021-07-21 16:53:56.507188
"""
| true |
cec6a0575b81086a708af27e4c7bac6b6f9878c7 | Python | ecwolf/Programming | /Python/MSoumen_reverse.py | UTF-8 | 283 | 3.796875 | 4 | [] | no_license | from func import get_digits
def reverse(num:int):
s=""
for i in map(str, get_digits(num)):
s += i
return int(s)
# Main Starts from here
a_number = int(input("Enter Your Number : "))
print("Reversed :", reverse(a_number))
print("Happy Programming.") | true |
497a4c2a676f38d3010bebb4bdcc4588efb3da93 | Python | slyt/KitChat | /kitchat_client.py | UTF-8 | 5,952 | 2.578125 | 3 | [] | no_license | # KitChat client
import socket
import sys
import select
import time
try:
import pygame
except ImportError:
print "\n\n-------------------------------------------------------------------"
print 'For sounds, please install pygame with "sudo apt-get install python-pygame"'
print "if you\'re Kit and love... | true |
a960a3a8d9e7afea6fcfdbd0e0d1c72bb72d7395 | Python | skypanther/robovision | /tests/test_robovision.py | UTF-8 | 1,494 | 2.734375 | 3 | [
"MIT"
] | permissive | """
pylint tests, run from main robovision directory with `pytest`
"""
import cv2
import numpy as np
import sys
from os import path
from unittest.mock import MagicMock
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
from robovision import robovision as rv
kitten = cv2.imread('tests/kitten.jpg')
h, ... | true |
0f9e669a1a84869711a8043f888dea444445f3cd | Python | artemetr-study/iut-cs | /lab-1/socket/server.py | UTF-8 | 961 | 2.703125 | 3 | [] | no_license | import re
import socket
HOST = '127.0.0.1'
PORT = 65432
if __name__ == '__main__':
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
s.bind((HOST, PORT))
s.listen(1)
while True:
conn, addr = s.accept()
with conn:
while True:
... | true |
df394e2acf07b931b5eb590285f6b399f22a05b7 | Python | h4m24/vault-download-cert | /run.py | UTF-8 | 5,997 | 2.515625 | 3 | [] | no_license | import argparse
import os
import logging
import hvac
import requests
import datetime
def vault_is_up(address, cafile):
logging.info("checking Health of vault: " + address)
vault_url = address + "/v1/sys/health"
try:
status = requests.get(vault_url, verify=cafile)
except Exception as e:
... | true |
5428744be13b8532294cb973fe3af0ec7c73fd9c | Python | Frank3000fr/FOA | /FOA.py | UTF-8 | 141 | 3.09375 | 3 | [] | no_license |
name = input('請輸入姓名: ')
print('Hi', name)
print('Hi', name)
print('Hi', name)
print('Hi', name)
| true |
686d9de4362f306f284fac005586bcfec261ad26 | Python | lyse0000/Leecode2021 | /62.63.64.980. Unique Paths I II III.py | UTF-8 | 3,207 | 3.34375 | 3 | [] | no_license | # 62. Unique Paths
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
dp = [1]*n
for i in range(1, m):
for j in range(1, n):
dp[j] += dp[j-1]
return dp[n-1]
# ===================================================================================... | true |
2378afae87cd75657a78dc1d9c193fe9d31203cc | Python | ricoping/keras | /neural.py | UTF-8 | 3,010 | 2.78125 | 3 | [] | no_license | import numpy as np
from keras import models
from keras import layers
import matplotlib.pyplot as plt
from keras.datasets import reuters
from keras.utils.np_utils import to_categorical
class Neural():
def __init__(self, epochs=20, batch_size=512, verbose=1, validation_size=1000):
self.epochs = epochs
s... | true |
3c351a5edee7acdd99fb7926bac6af63bb8cdd59 | Python | 98mcveigh/Mc_Labor_RD | /McLaborScraper/Excel.py | UTF-8 | 3,367 | 2.78125 | 3 | [] | no_license | import xlsxwriter
import McLaborScraper.Scraper as Scraper
import time
from datetime import date
def formatNewWorkbook(workbook,worksheet,query):
sheet = {"workbook":workbook,"worksheet":worksheet,"badSites":[],"index":3,"statusIndex":1,
"dateCol":0,"compNameCol":1,"locCol":2,"townCol":3,"stateCol":4,"zipCol":... | true |
0ad7b98c455d8205178587951ac3729ec3cfd3e8 | Python | hoangphand/UU691-Project | /clustering/clustering_product_categories_find_best_k.py | UTF-8 | 4,749 | 2.59375 | 3 | [] | no_license | from __future__ import print_function
from __future__ import division
import sys
from pyspark.sql import Row
from pyspark.sql import SparkSession
from pyspark.sql.functions import udf
import random
import copy
import math
# from random import *
random_seed = 1992
# random_seed = randint(1, 10000)
random.seed(random_se... | true |
1b4a9ef66d623b73ce332660c6cb27f97ebc7176 | Python | jfmam/algorithm | /taeho/baekjoon/python/1920.py | UTF-8 | 373 | 2.59375 | 3 | [] | no_license | # N, arr1, M, arr2 = (int(input()), input().split(), int(input()), input().split())
# arr1 = set(arr1)
# for i in arr2:
# if i in arr1:
# print(1)
# else:
# print(0)
N, arr1, M, arr2 = (int(input()), {i: 1 for i in map(int, input().split())}, int(input()), input().split())
for i in l... | true |
003a31990921313fdbeb97e91f42783287638265 | Python | heonmono/JustDoIT | /Programming/Algorithm/FastCampus/Recursive Call.py | UTF-8 | 1,773 | 4.125 | 4 | [] | no_license | # 재귀 호출
''' 고급 정렬에서 사용하므로, 미리 익히기
1. 재귀 용법 - 함소 안에서 동일 함수 호출, 익해져야함
2. 재귀 용법 이해'''
# 예제 1. factorial
a = 5
def factorial(n) :
if n == 1 :
return 1
return n * factorial(n-1)
def factorial(num) :
if num > 1 :
return num * factorial(num-1)
else :
return num
fa... | true |
6d390ec433e7fdd38a149df6ce8c3283da16e1d1 | Python | APietrzak99/IT_412_apietrza | /week1assignments/week1modularizingassignment/classesassignment/classes/person.py | UTF-8 | 332 | 2.71875 | 3 | [] | no_license | college_records = []
class Person():
"""a simple class meant to represent a person"""
def __init__(self,passed_id,passed_name,passed_email):
"""initialize name, email, id variables and attributes """
self.passed_id = passed_id
self.passed_name = passed_name
self.passed_email = p... | true |
f4e4734032b47bf51927f7f9ef6b92538b9ce3a4 | Python | lauren0914/baekjoon | /국영수.py | UTF-8 | 427 | 3.65625 | 4 | [] | no_license | '''
1. 국어 점수 내림차순
2. 영어 점수 오름차순
3. 수학 점수 내림차순
4. 이름 오름차순
'''
import sys
N = int(sys.stdin.readline())
score = []
for _ in range(N):
name, kor, eng, math = map(str, sys.stdin.readline().split())
score.append([name, int(kor), int(eng), int(math)])
score.sort(key=lambda x: (-x[1], x[2], -x[3], x[0]))
# x[1]이 같다면... | true |
d47872709cf1418026bb4adac47cff62b28ffcd3 | Python | zgcgreat/2017-cvr-tencent | /2017-cvr-tencent-final/src/data_analysis/test_analysis.py | UTF-8 | 993 | 2.78125 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
data_path = '../../data/'
out_path = '../../output/data_analysis/'
cnt = []
for i in range(24):
cnt.append(0)
fi_te = open(data_path + 'test.csv', 'r')
next(fi_te)
for line in fi_te:
s = line.replace('\n', '').split(',')
label = s[0]
date = int(s[1]... | true |
31d09a3b4450aaefe92460a9ca0fa8684acdc6c5 | Python | oknashar/interview-preparation | /top75LeetCode/Arrays/53.maxSubArray.py | UTF-8 | 1,053 | 3.609375 | 4 | [] | no_license | '''
Given an integer array nums, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.
Example:
Input: [-2,1,-3,4,-1,2,1,-5,4],
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.
Follow up:
If you have figured out the O(n) solution, try coding a... | true |
737a1185d9a8a7a6fab54c08be211da0fab4bb84 | Python | xingjiepan/ss_generator | /ss_generator/BetaSheetSkeleton.py | UTF-8 | 13,131 | 2.984375 | 3 | [
"BSD-3-Clause"
] | permissive | import numpy as np
from . import geometry
from . import basic
from . import beta_sheet
def f_equal(f1, f2, cut_off=0.001):
'''Return true if two float values are equal.'''
return np.absolute(f1 - f2) < cut_off
def angle_2d(p1, p2, p3):
'''Return the angle rotating the vector p2p1 to p2p3.
The points... | true |
779755631289b77d8b3e9671501b378fefdbb8b0 | Python | aravindsairam/PolishCoinDetection | /main.py | UTF-8 | 6,585 | 3.015625 | 3 | [] | no_license | """
Importing all necessary packages
"""
import os
import cv2
import glob
import argparse
import numpy as np
import tensorflow as tf
from sklearn.model_selection import train_test_split
from data_processing import preprocess, mask_image, hist_eq, edge
def load_data(img, size):
"""
Return the image in grayscal... | true |
ec0b3c8bb65ecb205e104be302676e88418ceb17 | Python | KosteRico/fractal-analysis-labs | /lab1/main.py | UTF-8 | 1,048 | 2.5625 | 3 | [] | no_license | from os import listdir
import cv2
import numpy as np
from skimage.filters import threshold_otsu
def boxcount(bin_img, k):
S = np.add.reduceat(
np.add.reduceat(bin_img, np.arange(0, bin_img.shape[0], k), axis=0),
np.arange(0, bin_img.shape[1], k), axis=1)
return len(np.where((S > 0) & (S < k ... | true |
c3ffdabf2d86a81249097402dd8675ebea79e033 | Python | mayankj1995/Sentiment_Analysis | /preprocessing/get_articles.py | UTF-8 | 2,371 | 3.140625 | 3 | [] | no_license | import requests
from math import ceil
from time import sleep
import csv
import pandas as pd
from itertools import chain
def get_nyt_articles(api_key, query, begin_date, end_date, page):
"""
Make a basic call to the NYT articles API
`begin_date` and `end_date` are in YYYYMMDD format
returns a... | true |
51613408fecce78595edc87d36924efedda52a89 | Python | dvs-shashank/Testing_repository | /cspp1-practice/m22/assignment3/tokenize.py | UTF-8 | 623 | 4.25 | 4 | [] | no_license | '''
Write a function to tokenize a given string and return a dictionary with the frequency of
each word
'''
def tokenize(string):
'''
tokenise method
'''
token_dict = {}
string_list = string.split(" ")
#print(string_list)
for each_val in string_list:
if each_val not in token_dict:
... | true |
325a39b60ff8dd7cd8cecbd3eeb34c0a95e0a554 | Python | JulienDavat/sage-backends-experiments | /scripts/query_sage.py | UTF-8 | 2,851 | 2.609375 | 3 | [] | no_license | #!/usr/bin/python3
import logging
import coloredlogs
import click
import requests
from time import time
from json import dumps
from statistics import mean
from utils import list_files, basename
coloredlogs.install(level='INFO', fmt='%(asctime)s - %(levelname)s %(message)s')
logger = logging.getLogger(__name__)
@cl... | true |
81110d3ae2b6e680af1465b1a20ee7f49b52f2e0 | Python | swapnilvishwakarma/100_Days_of_Coding_Challenge | /42.Reorder_List.py | UTF-8 | 869 | 3.921875 | 4 | [] | no_license | # Given a singly linked list L: L0→L1→…→Ln-1→Ln,
# reorder it to: L0→Ln→L1→Ln-1→L2→Ln-2→…
# You may not modify the values in the list's nodes, only nodes itself may be changed.
# Definition for singly-linked list.
class ListNode:
def __init__(self, val=0, next=None):
self.val = val
self.next = next... | true |
da46e31be70615b91652554ec076cc8a8ea5025e | Python | sayakbanerjee1999/TARP-Pesticide-Segregator | /model.py | UTF-8 | 4,021 | 2.734375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Tue Apr 6 20:56:22 2021
@author: Sayak, Ritayan, Itsav
"""
# res_map = {'Potato___Early_blight': 0, 'Potato___Late_blight': 1, 'Potato___healthy': 2}
# Importing the required keraas library and Viz Libraries
from keras.models import Sequential
from keras.layers ... | true |
dfdb7e9092d9dce4b5513c76747b749ec8cd53a5 | Python | chunjiw/leetcode | /solve.py | UTF-8 | 2,314 | 3.9375 | 4 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# 130. Surrounded Regions
# Given a 2D board containing 'X' and 'O' (the letter O), capture all regions surrounded by 'X'.
# A region is captured by flipping all 'O's into 'X's in that surrounded region.
# Example:
# X X X X
# X O O X
# X X O X
# X O X X
# After runnin... | true |
6392b62e2883064e059e5ebc2eeb2dc06566ad24 | Python | Vlad12344/RoboDKToPulsePostprocessor | /postprocessor/converter/programParser.py | UTF-8 | 1,938 | 3.046875 | 3 | [
"MIT"
] | permissive | import re
def read_file(file_path):
"""Read initial program"""
with open(file_path, 'r') as program:
program = open(file_path, "r")
program = str(program.read())
return program.split('\n')
def find_numbers(data: str):
"""Finds all numbers in single line"""
diction = re.findall(... | true |
11d2a6b1de4c8d52b89ba66f79e90e0e4505f8d1 | Python | kimjieun6307/itwill | /itwill/Python_1/chap04_RegExText/exams/exam01.py | UTF-8 | 1,038 | 4.03125 | 4 | [] | no_license | '''
문1) 다음 emp '입사년도이름급여'순으로 사원의 정보가 기록된 데이터 있다.
이 벡터 데이터를 이용하여 사원의 이름만 추출하시오.
# <출력 결과>
names = ['홍길동', '이순신', '유관순']
'''
from re import findall
# <Vector data>
emp = ["2014홍길동220", "2002이순신300", "2010유관순260"]
# print(findall('[가-힣]{3,}',emp)) --- error
year = [findall(r'^\d{2,}', i)[0] for i in emp]
prin... | true |
0068a09e23162b4dcd2520ffab23eb96794dad93 | Python | mjsmyth/abiquo-wiki-scripts | /release/getConfluencePageContentRestRelease.py | UTF-8 | 7,074 | 2.71875 | 3 | [] | no_license | # Python script: getConfluencePageContent
# ---------------------------------------
# Friendly warning: This script is provided "as is" and without any guarantees.
# I developed it to solve a specific problem.
# I'm sharing it because I hope it will be useful to others too.
# If you have any improvements to share, plea... | true |
6ac270e92232a05764b4edcb739c4f1f9265be62 | Python | nvieira-mcgill/rad-transient | /line_scattering.py | UTF-8 | 1,763 | 3.421875 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 11 23:13:04 2020
@author: Nicholas Vieira
@line_scattering.py
Scatter a photon packet on a known atomic line. A crude model for an atomic
line which invokes the Sobolev approximation. Based on the work of:
--> Kasen et al. 2006, ApJ 651, 366-380
"... | true |
0c3f82ff58068142f6695d8877cc01759412b78d | Python | LiveAlone/pythonDemo | /2.7-libs/multiple_process/process_map_run.py | UTF-8 | 883 | 2.765625 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'yaoqijun'
__mail__ = 'yaoqijunmail@foxmail.com'
'''
description: 通过线程池方式， 进行任务分配， 多任务的执行方式, 通过阻塞队列方式， 进行多任务的分发操作。
'''
import os
from multiprocessing import Pool
from multiprocessing import Queue
import time
import random
from collections import Iterable, ... | true |
5af36178573f7027fea7ca7fb821a478fb98e69e | Python | natarajan1993/Text-Classification | /Category Classifier.py | UTF-8 | 14,549 | 3.09375 | 3 | [] | no_license | """This was a machine learning project for text analytics and classification. The objective was to find the most important keywords
associated with whether a protection agreement was sold to the customer or not during the sale of appliances. The data is chats between
sales representatives and customers online. I achi... | true |
50cf56fba5dbfadae9e3ddd5810643e6d321e835 | Python | ToqYang/holbertonschool-higher_level_programming | /0x0C-python-almost_a_circle/models/rectangle.py | UTF-8 | 4,962 | 3.875 | 4 | [] | no_license | #!/usr/bin/python3
""" Module that Use the class base for make a Rectangle """
from models.base import Base
class Rectangle(Base):
""" Make the base class of a Rectangle """
def __init__(self, width, height, x=0, y=0, id=None):
""" __init__ Constructor of the class Rectangle
Args:
... | true |
b8899e6e16f2c6dbab3c5ce50d99be5484f413f2 | Python | wj1224/algorithm_solve | /programmers/python/programmers_hash_2.py | UTF-8 | 163 | 2.921875 | 3 | [] | no_license | def solution(phone_book):
answer = True
phone_book.sort()
for i, v in enumerate(phone_book[:-1]):
if v in phone_book[i + 1]:
answer = False
return answer
| true |
4a3cafa34d964bef959a531723c2c7ac233d5c92 | Python | gbrown9/Week-Nine-Assignment | /index.py | UTF-8 | 311 | 2.90625 | 3 | [
"MIT"
] | permissive | #CIS 125
#Gabe Brown and Daniel McMurray
sortedWords = ""
myWords = []
quiz = open("quizwords.txt", "r")
wordList = open("wordLists.txt", "r")
myQuiz = quiz.read()
quiz = quiz.replace(",", "")
myWords = myQuiz.split()
myWords = list(myWords)
def sortedWord(myWords):
def main()
quiz.close()
wordList.clo... | true |
87ced915670d0703bd9db149df74bbb863fa7bc1 | Python | g-morishita/intro-ML-python | /ch4/one_hot/binning.py | UTF-8 | 1,015 | 2.90625 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
from sklearn.tree import DecisionTreeRegressor
from sklearn.preprocessing import OneHotEncoder
from mglearn.datasets import make_wave
X, y = make_wave(n_samples=100)
line = np.linspace(-3, 3, 1000, ... | true |
e584671a0594904020f78c7a3fd8238a67a02b43 | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_199/2806.py | UTF-8 | 804 | 3.265625 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import sys
def pancake(s, k):
count = 0
for i in range(len(s) - k + 1):
if s[i] == "-":
count += 1
s = swap(s, i, k)
if '-' in s:
return "IMPOSSIBLE"
else:
return count
def swap(s, i, k):
# print("swa... | true |
56c0cc55d4d1e5c3dddc60356a14f1d33d916005 | Python | bopopescu/Py_projects | /BreakingPoint/RestApi/Python/RestApi_v2/SampleScripts/createSuperFlowStrikeList.py | UTF-8 | 3,650 | 2.578125 | 3 | [
"MIT"
] | permissive | """
createSuperFlowStrikeList.py
Description:
Create a Test Model from scratch.
What this script does:
- Login to BPS box
- Create a new superflow from scratch
- Add flow and actions to the new created superflow
- Save the superflow
- Edit parameters inside an action
- Remove action
- Create a... | true |
7ce08fa9c2cee801d5e7e9aa35dde64c2a844db7 | Python | Yashvir-Rana/dailyvscode | /tricks/kidsprojects/hexspiral.py | UTF-8 | 224 | 3.625 | 4 | [] | no_license | import turtle as tur
colors = ['red', 'purple', 'blue', 'green', 'yellow', 'orange']
t = tur.Pen()
tur.bgcolor('black')
for x in range(90):
t.pencolor(colors[x%6])
t.width(x/100+1)
t.forward(x)
t.left(59)
| true |
736e77087a8e83e830ce9e8f41c26368b7b7056d | Python | e2innovation/rul-wrs | /src/test/util/row.py | UTF-8 | 332 | 2.984375 | 3 | [] | no_license | """
Esta clase nos sirve para mockear el resultado de pyodbc.row
"""
class Row(object):
def __init__(self, dict):
self.__dict__ = dict
def __iter__(self): # iterate over all keys
for value in self.__dict__.values():
yield value
def __len__(self):
return len(self.__dict... | true |
b84db1082296a15e2a2b06fa485ddfe645ec71ed | Python | Caioseal/Python | /Exercícios/ex81.py | UTF-8 | 519 | 4.125 | 4 | [] | no_license | lista = []
while True:
lista.append(int(input('Digite um valor: ')))
print('Valor adicionado com sucesso')
resposta = str(input('Quer continuar: [S/N] ')).strip()
if resposta in 'Nn':
break
print('-=' * 30)
print(f'Foram digitados {len(lista)} números.')
lista.sort(reverse=True) #revers... | true |
a0699c7e17999182d3814f1573c71c21f0a0cd07 | Python | sforrester23/python_prime_numbers | /functions.py | UTF-8 | 1,677 | 4.28125 | 4 | [] | no_license | # function for determining if the argument parsed number is prime or not
def is_prime_number(number):
# make it an integer
number = int(number)
# start the count
index = 1
# make an empty list of the number's factors
list_of_factors = []
# for the whole time the count is below or equal to th... | true |
c49fc0445003ca88c479334ede88be107a98b1d5 | Python | CaptCorpMURICA/TrainingClasses | /Udemy/TimBuchalka/CompletePythonMasterclass/FileIO/writingTextFiles.py | UTF-8 | 1,056 | 3.671875 | 4 | [] | no_license | """
Author: CaptCorpMURICA
File: writingTextFiles.py
Creation Date: 10/5/2018, 11:08 AM
Description: Writing Text Files
"""
cities = ["Adelaide", "Alice Springs", "Darwin", "Melbourne", "Sydney"]
with open("cities.txt", 'w') as city_file:
for city in cities:
print(cit... | true |
14088870c4b943b4fade96151798e46d91fe2993 | Python | Zebralt/carambar | /carambar/termset.py | UTF-8 | 2,149 | 3.109375 | 3 | [] | no_license | import os
from contextlib import contextmanager
from functools import partial
from typing import Optional, Union, Callable, TextIO
from . import seq
"""
Compilation of terminal operations.
"""
def hide_cursor(file: TextIO):
"""Hide terminal cursor."""
file.write(seq.Cursor.HIDE)
def show_cursor(file: Tex... | true |
46e7cba6ee6f4bf3205b271ee5b2de425d7bad3b | Python | daumhch/bit_seoul_project | /test/test5.py | UTF-8 | 1,228 | 2.75 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
test_wav_filename = np.load('./test/data/test_wav_filename.npy')
test_wav_data = np.load('./test/data/test_wav_data.npy')
test_wav_target = np.load('./test/data/test_wav_target.npy')
print("test_wav_data.shape:", test_wav_data.shape)
print("test_wav_target.shape:", t... | true |
4205ccc8ab4faf75c2d0278b50b548f2dbc4dafa | Python | ilyashusterman/GmailClassifier | /tagger_machine/server.py | UTF-8 | 1,068 | 2.515625 | 3 | [] | no_license | import os
import tornado.ioloop
import tornado.web
CLIENT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__),
'web_client'))
CLIENT_STATIC = os.path.abspath(os.path.join(os.path.dirname(__file__),
'web_client/static_file... | true |
a946243156f69d83b48a89c6bb621881face5dd9 | Python | redclazz2/LogicaDeProgramacion | /Talleres/Taller30Abril/Punto29.py | UTF-8 | 96 | 3.546875 | 4 | [] | no_license | numero = float(input("Ingrese el número: "))
print("El número decimal es: {0}".format(numero)) | true |
c20de440f28e06ab66e858c2c52ba06a1e4f542e | Python | tamycova/Week-Projects | /Zombies/threads/helicoptero.py | UTF-8 | 3,458 | 2.59375 | 3 | [] | no_license | from PyQt4 import QtCore, QtGui
from random import randint
from math import sqrt
import time
class Helicoptero(QtCore.QThread):
trigger = QtCore.pyqtSignal(object)
def __init__(self, arena, main):
super().__init__()
self.trigger.connect(self.insertar_regalitos)
self.pausa = False
... | true |
f39a843fbd13fdf5db46996555ef6408795c5f35 | Python | init-13/codevita | /codevita2020/mock2020/A.py | UTF-8 | 93 | 2.921875 | 3 | [] | no_license | import math
for _ in range(int(input())):
print(math.ceil(math.log2(int(input())+1)))
| true |
06bcc8b57b84c54345d00365b571ccb0e3c190c3 | Python | Python-Programming-Boot-Camp/JonathanKarr | /Week 1/hello_variable.py | UTF-8 | 40 | 2.875 | 3 | [] | no_license | name = "Jonathan"
print("Hello " + name) | true |
574eef63e6632ba399c29b012b096b0d9d439745 | Python | Resolt/ML_Bootcamp | /DataVisualization/PandasBuiltInVisulizationExercises.py | UTF-8 | 675 | 2.890625 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
dir = 'Bootcamp/DataVisualization/'
df3 = pd.read_csv(dir + 'df3')
print(df3.info())
print(df3.head())
sns.set_style('darkgrid')
df3.plot.scatter(x='a', y='b', s=3, color='red', figsize=(12, 3), xlim=(-.2, 1.2), ylim=(-.2,1... | true |
c2845761d15d5b163fe415129b491eb56c3db772 | Python | Abuelodelanada/calidad | /Abc.py | UTF-8 | 2,405 | 3.1875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import csv
import json
from operator import itemgetter
class Abc():
TOTALES_ABC = {}
TOTALES_ABC_ACUM_JSON = []
TOTALES = ''
TOTAL = 0
grupos = {}
codigo_monto = {}
def __init__(self, ):
"""
"""
self.TOTALES_ABC = {}
def __exit__(self... | true |
1c42879379726c4c92f89dba541cf8906bae060e | Python | bchow1/Utils | /examples/StackOverflow/Csv_c2r.py | UTF-8 | 209 | 2.984375 | 3 | [] | no_license | import csv
x = []
y = []
with (open('E:\\TEMP\\xy.csv','r')) as egFile:
plots=csv.reader(egFile,delimiter=',')
for row in plots:
x.append(int(row[0]))
y.append(int(row[1]))
print x
print y
| true |
61abf819fa0aea5cb5ece21699f1abc3723fda14 | Python | tanc7/UdemyClassResources | /egghunters/old/kstetPOC3.py | UTF-8 | 1,852 | 2.671875 | 3 | [] | no_license | # Author: Uday Mittal
# Company: Yaksas CSC
# Contact: csc@yaksas.in | twitter.com/yaksas443
import sys
import socket
#Aa0Aa1Aa2Aa3Aa4Aa5Aa6Aa7Aa8Aa9Ab0Ab1Ab2Ab3Ab4Ab5Ab6Ab7Ab8Ab9Ac0Ac1Ac2Ac3Ac4Ac5Ac6Ac7Ac8Ac9Ad0Ad1Ad2Ad3Ad4Ad5Ad6Ad7Ad8Ad9Ae0Ae1Ae2Ae3Ae4Ae5Ae6Ae7Ae8Ae9Af0Af1Af2Af3Af4Af5Af6Af7Af8Af9Ag0Ag1Ag2Ag3Ag4Ag5A... | true |
011afc4eb7f06543a0eefe92e367b49279f16eb5 | Python | guidooswaldDB/DatabricksGitIntegration | /secondNotebook.py | UTF-8 | 568 | 2.515625 | 3 | [] | no_license | # Databricks notebook source
path = "/databricks-datasets/nyctaxi/tripdata/yellow/yellow_tripdata_2009-01.csv.gz"
logDF = (spark
.read
.option("header", True)
.csv(path)
)
display(logDF)
# COMMAND ----------
# MAGIC %scala
# MAGIC val path = "/databricks-datasets/nyctaxi/tripdata/yellow/yellow_tripdata_2009-0... | true |
7e65b8389a34a0a930c625f793f64c329091207f | Python | dpaneda/code | /jams/euler/53.py | UTF-8 | 267 | 3.546875 | 4 | [] | no_license | #!/usr/bin/env python3
from math import factorial
def combinations(n, r):
return factorial(n) / (factorial(r) * factorial(n-r))
exceeds = 0
for n in range(1, 101):
for r in range(1, n):
if combinations(n, r) > 1000000:
exceeds += 1
print(exceeds)
| true |
5379bd0c0172f8934e8081ae13524e3d602136ef | Python | mstryjek/VAEs | /window.py | UTF-8 | 3,252 | 3.234375 | 3 | [] | no_license | """
VAE visualization app definition utilizing tkinter.
"""
import numpy as np
from PIL import ImageTk
from PIL import Image as Img ## conflict with tkinter.Image class
from tkinter import *
class VAE_window():
"""
Simple class for visualizing the working of a Variational Autodecoder. \\
Params: \\
... | true |
bb1333b602293d05782d8fadb3adc33222846d92 | Python | sombriyo/Leetcode-_questions | /random/Maximum Product Difference Between Two Pairs.py | UTF-8 | 331 | 3.40625 | 3 | [] | no_license | '''
Find the maximum difference of the product
Runtime: 156 ms, faster than 97.41% of Python3
Memory : 15.4 MB, less than 53.06% of Python3
TC: O(nlogn)
SC : O(n)
'''
def maxProductDifference(self, nums: List[int]) -> int:
nums.sort()
diff = nums[len(nums)-1] * nums[len(nums)-2] - nums[0]*nums[1]
r... | true |
0e9a81d61dde221ab17a54b4fa1ebad9986af5d1 | Python | qzsiniong/python-life | /DateUtils.py | UTF-8 | 1,335 | 3.296875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
#
import time
import datetime
def timestamp_datetime(value):
format = '%Y-%m-%d %H:%M:%S'
# value为传入的值为时间戳(整形)，如：1332888820
value = time.localtime(value)
## 经过localtime转换后变成
## time.struct_time(tm_year=2012, tm_mon=3, tm_mday=28, tm_hour=6, tm_min=5... | true |
83fe430be752dd0063593f4149712ba6da0ee6d6 | Python | supab/Game | /main.py | UTF-8 | 4,440 | 2.921875 | 3 | [] | no_license | import pygame
from pygame.locals import *
from gamelib import SimpleGame
from elements import Player, Meteor, Bullet, Life,EnemyBullet
import random
class MeteorGame(SimpleGame):
BLACK = pygame.Color('black')
WHITE = pygame.Color('white')
COLOR = [pygame.Color('red'), pygame.Color('green'), pygame.Color('blue'), py... | true |
c2d1a1ec62e34eece9054956be38417db6489752 | Python | CatarinaBrendel/Lernen | /curso_em_video/Module 2/exer049.py | UTF-8 | 268 | 3.953125 | 4 | [] | no_license | print "{:-^45}".format(' \033[31mTabuada\033[m ')
num = int(raw_input("Digite aqui um numero inteiro a ser multiplicado: > "))
num2 = int(raw_input("Digite aqui o valor da tabuada: > "))
for n in range(1, num2+1):
print "{:3} x {:3} = {:3}".format(num, n, num * n) | true |
b3cd1c56baedb7696594fb0f0f625e88e99df8d8 | Python | agnosticdev/AutomationScripts | /latency_test.py | UTF-8 | 4,005 | 3.546875 | 4 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# The purpose of this script is to simply make anonymous GET requests to test latency
# These requests do not contain authentication or headers
# The only things that are asked from the user is the URL and the times they wish to run the URL
#
from __future__ import print_... | true |
98d374667a0422a8501f5be9790f8c22db721afe | Python | kovrichard/tweetshot | /tweetshot/take_screenshot.py | UTF-8 | 8,277 | 2.765625 | 3 | [
"MIT"
] | permissive | from pathlib import Path
from PIL import Image
from io import BytesIO
import base64
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from tweetshot.webdrivers.set_webdriver import get_driver
class Twee... | true |
bc257eb2361d9528c9d5b08765df2822aca3b46e | Python | Alex-Boiko/Vacanator2k | /sandbox.py | UTF-8 | 335 | 3.09375 | 3 | [] | no_license | from datetime import date
def diff_month(d1, d2):
return (d1.year - d2.year)*12 + d1.month - d2.month
print abs(diff_month(date(2010,10,1), date(2011,3,1)))
assert diff_month(date(2010,10,1), date(2009,10,1)) == 12
assert diff_month(date(2010,10,1), date(2009,11,1)) == 11
assert diff_month(date(2010,10,1), date(2... | true |
a3ccee7ac2a1806558d5f355f9f1525466e79701 | Python | shawnLeeZX/solution_to_intro_to_datascience_UW_coursera | /assignment1/tweet_sentiment.py | UTF-8 | 1,347 | 3.21875 | 3 | [] | no_license | # encoding: utf-8
import sys
import json
def main():
sent_file = open(sys.argv[1])
tweet_file = open(sys.argv[2])
# Get sentiment dictionary for words.
sent_dict = {}
for line in sent_file:
term, sent_score = line.split('\t')
sent_score = int(sent_score)
sent_dict[term] = ... | true |
6d53e7117bf8082eb7d0267d229ef94467548dea | Python | hellodevopsgit/PDS | /CSV-HORUS.py | UTF-8 | 771 | 2.578125 | 3 | [] | no_license | import pandas as pd
sInputFileName='C:/VKHCG/01-Vermeulen/00-RawData/Country_Code.csv'
InputData=pd.read_csv(sInputFileName,encoding="latin-1")
print(InputData)
ProcessData=InputData
ProcessData.drop('ISO-2-CODE', axis=1,inplace=True)
ProcessData.drop('ISO-3-Code', axis=1,inplace=True)
ProcessData.rename(columns... | true |
b40595364a95969e4964cefa12f9d400e89cc84f | Python | sandykrishdaswani/sandy2 | /18.py | UTF-8 | 197 | 2.9375 | 3 | [] | no_license | number=int(input())
sandy=0
aa=[]
bb=['a','a','b','i','k','l']
for i in range(0,number):
aa.append(list(input()))
for i in aa:
s=sorted(i)
if(bb==s):
sandy=sandy+1
print(sandy)
| true |