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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
44dae8bb6e4004e76a2b7c96a8b12ff2dd961b7f | Python | atrox3d/python-corey-schafer-tutorials | /03-python practical examples/07-advanced logging.py | UTF-8 | 5,791 | 3.234375 | 3 | [] | no_license | #
# https://youtu.be/jxmzY9soFXg
#
#########################################################################################################
# DEBUG: Detailed information, typically of interest only when diagnosing problems.
# INFO: Confirmation that things are working as expected.
# WARNING: An indication that somet... | true |
25e6a6637fb4c1c54d3365ff5a462e8dc1700a18 | Python | vilus/learning_telegram | /weather/tests/test_parser.py | UTF-8 | 779 | 2.5625 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import pytest
from ..demultiplexer import get_weather_location, check_params
def test_get_weather_location():
params = {'message': {'text': '/say Bangkok weather: {0}'}}
assert get_weather_location(params) == 'Bangkok'
def test_check_params():
params = {
'update_id': 1,
... | true |
8d4a2081d86027990d03a552bb37148d1cdb94bf | Python | kiramipt/dash_news | /app.py | UTF-8 | 10,442 | 2.625 | 3 | [] | no_license | import random
import dash
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
from plotly.colors import DEFAULT_PLOTLY_COLORS
import pandas as pd
from datetime import date
from dash.dependencies import Input, Output
external_stylesheets = ['https://codepen.io/chrid... | true |
0fb05d0fef20b2e794aec5c13ef29cfa0f7ffc04 | Python | beOk91/baekjoon2 | /baekjoon15726.py | UTF-8 | 84 | 2.546875 | 3 | [] | no_license | a,b,c=map(int,input().strip().split())
print(max(a/1000*b//c*1000,a/1000//b*c*1000)) | true |
cde950d1b0d8ab503b7060c3d1d27135bdbee5f7 | Python | jpramos123/Artigo-CC5661 | /accuracy.py | UTF-8 | 1,681 | 2.90625 | 3 | [] | no_license | import numpy as np
import math as math
class accuracy:
def __init__(self, clusters, lessons):
self.num_dim = np.shape(clusters)[1]
self.num_klus = np.shape(clusters)[0]
self.num_lessons = np.shape(lessons)[0]
self.seeds = clusters
self.lessons = lessons
#Euclidian Dis... | true |
8386cfa51473bcb8cb7ecf3c0132e655afa5f7db | Python | dodosman/PredictX_plane_flights | /calculations.py | UTF-8 | 1,299 | 3.21875 | 3 | [] | no_license | import geopy.distance
import pandas as pd
class FlightDistance:
def read_cvs(self):
df = pd.read_csv("Flight Distance Test.csv")
return df
def dep_coordinates_together(self):
df = self.read_cvs()
dep_coordin_together = list(zip(df['Departure_lat'], df['Departure_lon']))
return dep_coordin_... | true |
b85da377d3f362d7049f3c2d6571f35542042d03 | Python | CristianCuartas/Python-Course | /Bases Python/06-arreglos.py | UTF-8 | 633 | 4.03125 | 4 | [] | no_license | lenguajes = ['Python', 'Kotlin', 'Java', 'JavaScript']
print(lenguajes[3])
# Ordenar los elementos
lenguajes.sort()
print(lenguajes)
# Acceder un elemento dentro de un texto
aprendiendo = f'Estoy aprendiendo {lenguajes[3]}.'
print(aprendiendo)
# Modificando valores
lenguajes[2] = 'PHP'
# Agregar elementos
lenguaje... | true |
1b21ac1102e1c193579d5f37e6cd079c624ec3ef | Python | GilbertQ/Python | /Tarea_01.py | UTF-8 | 666 | 4.03125 | 4 | [] | no_license | #Calcular el sueldo líquido de una persona
# 100 100 100 => 275.34
nombre = input ("Ingrese el nombre del empleado : ")
puesto = input ("Ingrese el puesto de {}: ".format(nombre))
sueldob = input("Ingrese el sueldo base de {}: ".format(nombre))
bonificacion = input("Ingrese el valor de la bonificacion de {}: ".for... | true |
2290017b189a194f46dd15e31784015da5088e03 | Python | Aasthaengg/IBMdataset | /Python_codes/p02819/s996325275.py | UTF-8 | 285 | 2.9375 | 3 | [] | no_license | x = int(input())
eratostenes = [True] * 10**6
for i in range(2, len(eratostenes)):
if eratostenes[i]:
for j in range(i * 2, len(eratostenes), i):
eratostenes[j] = False
for i in range(x, len(eratostenes)):
if eratostenes[i]:
print(i)
exit() | true |
af192c72373736e32f4c064c34c327932f29532e | Python | shashankrnr32/WaveCLI | /plot/wave.py | UTF-8 | 1,372 | 2.78125 | 3 | [
"MIT",
"LicenseRef-scancode-proprietary-license"
] | permissive | #!/usr/bin/env python3
# =============================================================================
# Developer : Shashank Sharma(shashankrnr32@gmail.com)
# License : MIT License
# Year : 2019
# =============================================================================
# =========================================... | true |
80ba09381f6826f282683a285374f66d092ea13a | Python | codemedici/crypto | /vigenere_brute.py | UTF-8 | 762 | 3.0625 | 3 | [] | no_license | import itertools
import vigenereCipher, freqAnalysis
letters = ['A','B','C','D','E','F','G','H','I','J','K','L','M','N','O','P','Q','R','S','T','U','V','W','X','Y','Z']
dictionary = [ ''.join(c) for c in itertools.permutations(letters, 3) ]
ciphertext = "AZAXVHEFWVWOUWQCFEMHKARAZEJVNLCBFOVMMMBMSNHBAUGKZMBJGIEOWZWWWB... | true |
a87f5ff8bdac2294c20578adb954e73929e942e5 | Python | fiso1011/HydroBA | /Sandtrap.py | UTF-8 | 11,460 | 2.578125 | 3 | [] | no_license | import numpy as np
import RawMaterial as c_rm
class Sandtrap:
def __init__(self,input_data):
self.sandtrap_data=input_data.input_dict["sandtrap_data"] ["dict"]
self.sandtrap_material=input_data.input_dict["sandtrap_material"]["dict"]
self.total_sandtrap_cost
#import relevant Dicts
... | true |
5acdc62487cfd3cf7d70e85af139dceaaa2e8440 | Python | patinbsb/Main | /irc/twitch.py | UTF-8 | 3,946 | 2.96875 | 3 | [] | no_license | """This script attempts to use the activity of the chat room of a video stream to gauge and log
the interesting events which occur"""
import socket
import string
import time
from time import localtime, strftime
import urllib
import json
import datetime
time.clock()
'''Setting up info for irc connection'''
# IRC conne... | true |
eb2c144e3b573df18d8d46b72476d4d3ef648621 | Python | elifoster/Miscellaneous | /other/dice.py | UTF-8 | 806 | 3.6875 | 4 | [] | no_license | import random
import time
import sys
import gc
def loop():
lo = input("Would you like to roll again? (0 for yes, 1 for no)\n")
while True:
if lo == str(0):
run()
elif lo == str(1):
print("Done")
sys.exit()
def run():
number = input("How many sides would ... | true |
4fc05debb26b0849812235774023e165a5e7f8ba | Python | towithyou/master-agent-rpc | /master/agent.py | UTF-8 | 750 | 2.75 | 3 | [] | no_license |
import datetime
from common.state import *
class Agent:
'''客户端注册的信息需要封装， 提供一个信息存储的类， 数据存储在类的实例中'''
def __init__(self, id, hostname, ip):
self.id = id
self.hostname = hostname
self.ip = ip
self.regtime = datetime.datetime.now() # 服务器生出注册时间
self.state = WAITING # 可以在注册的时... | true |
109cbfd693fa0cb6a468b3ab3a805a94c42f449c | Python | JaeWorld/PS_everyday | /BOJ/11779.py | UTF-8 | 1,121 | 3.25 | 3 | [] | no_license | # BOJ 11779 최소비용 구하기 2
# 다익스트라 알고리즘
import sys
import heapq
input = sys.stdin.readline
INF = 987654321
def djikstra(start, graph, n, parent):
dist = [INF]*(n+1)
dist[start] = 0
queue = []
heapq.heappush(queue, [0, start])
while queue:
d, v = heapq.heappop(queue)
for a, w in gra... | true |
1c48f1c8934a1cfe8ff018172b601bf50933a4e3 | Python | IINemo/isanlp | /src/isanlp/processor_spacy.py | UTF-8 | 7,013 | 2.9375 | 3 | [
"MIT",
"Python-2.0"
] | permissive | import spacy
from . import annotation as ann
class ProcessorSpaCy:
""" Wrapper around spaCy - The NLP library for multiple languages.
Performs:
1. Tokenization, sentence splitting.
2. POS-Tagging, morphological analysis, lemmatizing.
3. Dependency parsing.
4. Named entity recognition.
US... | true |
429642deb2400f4b2ab53aeab6173f4e8ea9fca7 | Python | surim-wang/kidney | /source/2020-07-11_imageTOtext.py | UTF-8 | 13,046 | 2.859375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Sat Jul 11 21:11:18 2020
@author: SURIMWANG
"""
#%% 이미지 txt로 가져와서 한줄씩 들어온 데이터 전처리하기
import numpy as np
import pandas as pd
import os
os.chdir('D:/MNIST/source')
from PIL import Image
import pytesseract
#test_kor= pytesseract.image_to_string(Image.open('../image/test_img3.png'... | true |
05651b9197f064ed95edae3eb9a4d5f00803cf17 | Python | apple/coremltools | /coremltools/converters/mil/mil/types/get_type_info.py | UTF-8 | 2,123 | 2.734375 | 3 | [
"MIT",
"BSD-3-Clause"
] | permissive | # Copyright (c) 2020, Apple Inc. All rights reserved.
#
# Use of this source code is governed by a BSD-3-clause license that can be
# found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
from .type_spec import FunctionType, Type
from .type_void import void
def get_python_method_type(py... | true |
a37ca072ab79b25b0522b18d403bc6faaf4c3ad3 | Python | 44Schwarz/resume-storage | /api/tests.py | UTF-8 | 557 | 2.84375 | 3 | [] | no_license | import unittest
from django.test import TestCase
# Create your tests here.
class TestParseText(unittest.TestCase):
def test_regex(self):
import re
from .tasks import RE_PATTERN
test_string = 'A-B Company (2015-01-11 - 2018-07-26; laboris nisi ut aliquipc,fdmf2f ea commodo conse).'
... | true |
2adb753aa9c81c01d80142e68746034dda8a2907 | Python | mrulle/python_course_solutions | /06-conditional_statements/random_sentence.py | UTF-8 | 2,481 | 3.5 | 4 | [] | no_license | # adjectives from: http://www.enchantedlearning.com/wordlist/adjectives.shtml
# nouns from: http://www.talkenglish.com/vocabulary/top-1500-nouns.aspx
# verbs from: http://www.linguasorb.com/english/verbs/most-common-verbs/
import random
'''
adjectives are 1 word per line
nouns has a line format of 'word frequency type... | true |
57697da5b3d4a87938f0234655647b6643763560 | Python | abigail-Moore/GBS-analysis | /new_subj_rtd.py | UTF-8 | 1,185 | 2.828125 | 3 | [] | no_license | #! /usr/bin/env python
InFileName = "rtd.mIDs"
OutFileName = "rtd_0001of0001_subj.fa"
SubjectSeqs = [ ]
SplitLine = [ ]
AllUniqued = 0
UniqSubjects = 0
WrittenSeqs = 0
InFile = open(InFileName, 'rU')
for Line in InFile:
Line = Line.strip('\n').strip('\r').split()
AllUniqued += 1
if len(Line) > 2:
NewSeq = Line[... | true |
0991f5edbb67b88d2913c2b99dc1bc490a77233c | Python | bwang8482/LeetCode | /Google/305_Number_of_Islands_II.py | UTF-8 | 2,840 | 4.15625 | 4 | [] | no_license | """
A 2d grid map of m rows and n columns is initially filled with water. We may perform an addLand operation which turns the water at position (row, col) into a land. Given a list of positions to operate, count the number of islands after each addLand operation. An island is surrounded by water and is formed by connec... | true |
2acb1d381ba428603bebdf81074e1b505da81b0d | Python | xingyunsishen/Python_CZ | /tom.py | UTF-8 | 846 | 3.875 | 4 | [] | no_license | #-*- coding:utf-8 -*-
class Cat(object):
def __init__(self, new_name, new_age):
print('\033[0;31;42m ======哈哈哈=======\033[0m')
self.name = new_name
self.age = new_age
def __str__(self):
return '\033[0;33;43m %s 的年龄:%d\033[0m'%(self.name, self.age)
def eat(self):
... | true |
326e91c1f7f0289b9878730a4d9d973a181dc49e | Python | jiadaizhao/LeetCode | /1201-1300/1252-Cells with Odd Values in a Matrix/1252-Cells with Odd Values in a Matrix.py | UTF-8 | 432 | 2.90625 | 3 | [
"MIT"
] | permissive | class Solution:
def oddCells(self, n: int, m: int, indices: List[List[int]]) -> int:
rows = [False] * n
cols = [False] * m
countRow = countCol = 0
for r, c in indices:
rows[r] ^= True
cols[c] ^= True
countRow += 1 if rows[r] else -1
cou... | true |
a8513dba9129ce3622e1fb262936da74dbf40937 | Python | barryntklc/pysqlite | /pysqlite_manager/Objects/NodeList.py | UTF-8 | 2,589 | 3.15625 | 3 | [] | no_license | import pysqlite_manager
from _winapi import NULL
from .Node import Node
# NodeList
# Stores the connection information for a bunch of Nodes.
#
class NodeList(object):
Nodes = []
def __init__(self):
self.Nodes = []
# print("Nodelist created.")
# Add
# Adds a Node to the NodeList if does... | true |
9260f4791bb789c7ef8035858c277bb0a1b8bd3e | Python | furuolan/Chest-X-ray-Disease-Diagnosis-using-Faster-R-CNN | /Code/src/image_to_array.py | UTF-8 | 732 | 2.875 | 3 | [] | no_license | import time
import cv2
import numpy as np
import pandas as pd
def convert_images_to_arrays(file_path, df):
lst_images = [l for l in df['Image_Index']]
return np.array([np.array(cv2.imread(file_path + img, cv2.IMREAD_GRAYSCALE)) for img in lst_images])
def save_to_array(arr_name, arr_object):
return ... | true |
3eb8c92b8597176ec6615434f13d786ddc4cbd60 | Python | AnnMertens/Project_Boontje | /boontje/htmltags_to_corpus.py | UTF-8 | 8,144 | 3.375 | 3 | [] | no_license | """ html corpora opdelen in zinnen en woorden en deze zinnen in een lijst teruggeven als corpus"""
import nltk.data
import make_corpus
import filefunctions
from nltk.tokenize import word_tokenize
import tagging
import glob
# variabele tagger maken
#tagger_conll = tagging.tagger_conll2002('b')
tagger_alpino = tagging.t... | true |
feac20b4d18b6d91546c7028c878c372cdd4a1ac | Python | ratalex/pyNastran | /pyNastran/bdf/utils.py | UTF-8 | 17,745 | 2.8125 | 3 | [] | no_license | """
Defines various utilities including:
- parse_patran_syntax
- parse_patran_syntax_dict
- Position
- PositionWRT
- TransformLoadWRT
"""
from __future__ import print_function, unicode_literals
from copy import deepcopy
from typing import List, Union, Dict, Tuple, Optional
import numpy as np # type: ignore
from ... | true |
3752f06271de1f722d94bfaee78b2bd9a4623ca0 | Python | ksons/ln.py | /ln/triangle.py | UTF-8 | 2,685 | 2.75 | 3 | [
"MIT"
] | permissive | from pyrr import Vector3
from .hit import Hit, NoHit
from .box import Box
from .ray import Ray
from .path import Paths
from .util import vector_min, vector_max
EPS = 1e-9
class Triangle:
def __init__(self, v1=None, v2=None, v3=None):
self.v1 = Vector3() if v1 is None else Vector3(v1)
self.v2 = ... | true |
ea5bb1314fe7d97aba14114cfcd1d3964cd3608e | Python | purusoth-lw/my-work | /36.multiple Inheritance.py | UTF-8 | 1,253 | 3.859375 | 4 | [] | no_license | """
Multiple Inheritance:
=====================
many parent class
But only one child class
syntax:
=======
class Class1:
statements
class Class2:
statements
class Class3(Class1,class2):
statements
class Father:
cash1=50000
def show1(self):
print("Father cash :",self... | true |
3b90a8f957de622c93c40d604ddf3a0029eff406 | Python | francoisleroux16/MRN_Final | /testdata.py | UTF-8 | 27,016 | 2.90625 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
"""
Created on Tue Sep 22 18:36:26 2020
@author: Francois le Roux
This script is regarding everything relating to the test data
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy import interpolate
import importing
def cubic(x,val1,val2):
tck = interpolate.splre... | true |
67a941b7ff7fe9c9786de722aeb5d7305739c608 | Python | lawiet019/foodie | /foodieProject/users/utils.py | UTF-8 | 7,115 | 2.859375 | 3 | [] | no_license | import random
from PIL import Image, ImageDraw, ImageFont, ImageFilter
from string import ascii_letters,digits
from .models import UserProfile
from django.core.mail import send_mail
from django.conf import settings
import configparser
from datetime import datetime
from .models import EmailVerifyRecord
import jwt
from d... | true |
0e0888d583a11f2bb48108675c7f1dcf40ca6835 | Python | Lodewic/DuPont-hackathon | /src/enzyme_hackathon/utils.py | UTF-8 | 5,358 | 2.9375 | 3 | [] | no_license | import numpy as np
import tensorflow as tf
import pandas as pd
from keras import backend as K
from keras import Model
from keras.layers import Input, Dense, Flatten, Dropout, BatchNormalization
from keras.optimizers import Adam
from keras.regularizers import l2
from sklearn.preprocessing import LabelEncoder, OneHotEnco... | true |
370f3d6f2dec1fb1d4ff280930b831930b079b1e | Python | nileshmahale03/Python | /Python/5 Tuples.py | UTF-8 | 1,084 | 4.3125 | 4 | [
"MIT"
] | permissive |
#Tuple
#ordered
#indexed
#Immutable
#Faster than list
t = ("Monday", "Tuesday", "Wednesday", "Thursday", "Friday")
print(t)
print(type(t))
#t.append(20) AttributeError: 'tuple' object has no attribute 'append'
print(t[2])
print(t[-1])
print(t[1:3])
print(len(t))
print(t.count("Monday"))
print(t.index("Friday")... | true |
88f0c96ae54c8810920b11236cc288b05059c353 | Python | dantin/daylight | /dcp/002/solution.py | UTF-8 | 1,594 | 3.96875 | 4 | [
"BSD-3-Clause"
] | permissive | # -*- coding: utf-8 -*-
class Solution():
"""Algorithm:
1. Construct `left`, with `left[i]` contains product of all elements on `left` of `nums[i]` excluding
`nums[i]`
2. Construct `right`, with `right[i]` contains product of all elements on `right` of `nums[i]`
excluding `nums[i]`
3. re... | true |
43e9e072be0561a97cd91948a3b4430e95d25ed9 | Python | starbt/pic_link | /pic_link.py | UTF-8 | 2,593 | 2.71875 | 3 | [] | no_license | from __future__ import division
from PIL import Image
import numpy
import numexpr
import os
import os.path
import random
path = r'/home/xcv/learning_python/scrapy/picture'
bigPhoto = r'/home/xcv/learning_python/scrapy/big.jpg'
aval = []
W_num = 25
H_num = 25
W_size = 360
H_size = 640
alpha = 0.3
#获得所有照片信息
def getA... | true |
520cc3699a1fc2f9f7252fa0728c936382f90cf5 | Python | zsmountain/lintcode | /python/stack_queue_hash_heap/545_top_k_largest_numbers_ii.py | UTF-8 | 2,502 | 4.25 | 4 | [] | no_license | '''
Implement a data structure, provide two interfaces:
add(number). Add a new number in the data structure.
topk(). Return the top k largest numbers in this data structure. k is given when we create the data structure.
Have you met this question in a real interview?
Example
s = new Solution(3);
>> create a new data... | true |
493ed3820055157e7531dfba8d6fbcf537f812dc | Python | cRAN-cg/Competitive | /code/python/basic/a_very_big_sum.py | UTF-8 | 141 | 3.09375 | 3 | [] | no_license | #!/usr/bin/python3 env
import sys
n = int(input().strip())
arr = [int(arr_vals) for arr_vals in input().strip().split(" ")]
print(sum(arr)) | true |
817a54ec999d608bc04b607a1f00ff58db3dc290 | Python | ylashin/deep-learning-workshop | /Sample10/TrainLocalModel.py | UTF-8 | 916 | 3.09375 | 3 | [] | no_license | import pickle
import os
import pandas
import numpy as np
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
# create the outputs folder
os.makedirs('./outputs', exist_ok=True)
# load input dataset from a DataPrep package as a pandas DataFrame
inputDf = pandas.read_csv('data.csv')
# load... | true |
c0694a38e64600b75757cebec9d79df815fdaf7b | Python | deggs7/py-practice | /sweet/attr_pass.py | UTF-8 | 807 | 3.1875 | 3 | [
"Unlicense"
] | permissive |
class Test(object):
name = 'origin'
t = Test()
all = [ 'a',
1,
t,
['a', 'b', 'c'],
('x', 'y', 'z'),
{
'name': 'abc',
'desc': 'xyc'
}
]
def change(n):
print id(n)
if type(n) == str:
n = 'b'
elif type(n) == int:
n =... | true |
86c4b48c5cc516f538a3b442bfdba6df5f3e64ac | Python | kennethnym/covid19-alarm | /server/routes/alarms/daily_brief.py | UTF-8 | 2,582 | 3.25 | 3 | [
"MIT"
] | permissive | """
This module handles daily brief processing.
"""
import logging
import datetime
from typing import Dict, Any
import pyttsx3
from server.api.weather import fetch_weather
from server.api.news import fetch_news_headlines
from server.api.covid import fetch_covid_data
__speech_engine = pyttsx3.init()
def daily_brie... | true |
c62cfb446a03c57dc1235e36000b298661b6ed1c | Python | DanishKhan14/DumbCoder | /Python/strings/shortestPalind.py | UTF-8 | 697 | 4.15625 | 4 | [] | no_license | """
Given a string S, you are allowed to convert it to a palindrome by adding characters in front of it.
Find and return the shortest palindrome you can find by performing this transformation
"""
# [TLE] Method 1: Brute Force. Keep adding one char at a time in rev order
class Solution(object):
def shortestPalind... | true |
8ba4095cd60eeb07d9b9db3a925250dede5a5f0b | Python | ad54/aws_rest_api | /rest_lambda_function.py | UTF-8 | 2,925 | 3.234375 | 3 | [] | no_license | """This is the lambda function for rest api , which will provide data from dynamo db.
You need to pass the name of the sport and team. It will provide recent reords of the team.
If the searched sport is not availble, it will list all the available, the same for the searched team.
"""
import boto3
import json
from boto... | true |
19044ffe2c5b2cc6f609dd9f3ea48962e9ff7562 | Python | ace12358/100knock | /test65_2.py | UTF-8 | 526 | 2.609375 | 3 | [] | no_license | #coding:utf-8
import sys,os
noun100 = []
for line in open(sys.argv[1]):
noun100.append(line.strip().split()[0])
files = os.listdir('/Users/kitagawayoshiaki/Dropbox/100knock/my100knock/work_dir_n') #指定したパスのディレクトリ内のファイルをリストとして返す
for file in files:
for line in open("work_dir_n/"+file):
list = line.strip().split("\t... | true |
f08faf6b04c2fcc85178bf2161cb32b523d83b73 | Python | fzero17/college_wish | /src/test.py | UTF-8 | 523 | 2.75 | 3 | [] | no_license | import sqlite3
db_file = './utils/database/de/2016.db'
conn = sqlite3.connect(db_file)
conn.text_factory = str
c = conn.cursor()
res = c.execute("select name from sqlite_master where type='table' order by name;")
table_list = res.fetchall()
COUNT = 0
for table_name in table_list:
cursor = c.execute("SELECT c... | true |
68aa779993c14e0f654c0fbf458bb7e0bc39a8d2 | Python | wangyf/AH-RJMCMC | /make_AH_IL_comparison.py | UTF-8 | 4,216 | 2.6875 | 3 | [
"MIT"
] | permissive | # Script to make a comparison plot from the RJ-MCMC output
# of the AH and IL methods.
# The script assumes that the current directory contains the AH-output, and the directory with the IL-output is specified.
# We also assume that the comparison is direct - i.e. that all parameters and data are shared between the two... | true |
6ef05fc6e8bd533d8b3689911a62f31f4db98d49 | Python | destroyer7/puf_iot | /Protocol1Full/DriverOnlineServer.py | UTF-8 | 3,993 | 2.703125 | 3 | [] | no_license | #---------------------- DriverOnlineServer.py----------------------
import sys
from OnlineServerSocket import ServerSocket # For Server-Client communication using TCP sockets
from OnlineServerCrypto import ServerCrypto # For Cryptographic Functions
from IOTDatabase import database_server # For the Database
def device... | true |
cd6b5e62eee818e61ea77c07b725244655e5727b | Python | miaofa/PythonScriptsForWork | /bin2bin/uifor2019.py | UTF-8 | 5,000 | 2.578125 | 3 | [] | no_license | # -*- coding: utf-8 -*-
# 全部UI设计
# 默认的输出目录是桌面，针对Linux的还没有添加（最好是home目录）
import tkinter as tk
from tkinter.filedialog import askdirectory, askopenfilename
from tkinter import scrolledtext
import os
import conversion
class UI(object):
def __init__(self, master):
self.master = master
... | true |
bfe2f246e4e30aac57c0f9542e9a10723a8579c1 | Python | asolberg/CJ-2012-Prelim | /B - Dancing with the Googlers/dancing.py | UTF-8 | 4,630 | 3.671875 | 4 | [] | no_license | # Problem
#
# You're watching a show where Googlers (employees of Google) dance, and then each dancer is
# given a triplet of scores by three judges. Each triplet of scores consists of three
# integer scores from 0 to 10 inclusive. The judges have very similar standards, so it's
# surprising if a triplet of scores con... | true |
691404d715a2931e22d99e1caf0a19d98d70f0e8 | Python | LadyM2019/Python-Fundamentals-Softuni | /05. Dictionaries - Exercises/05. Social Media Posts.py | UTF-8 | 1,070 | 3.5 | 4 | [
"MIT"
] | permissive | def Post(postName):
socialMedia.__setitem__(postName,list([0,0]))
def Like(postName):
socialMedia[postName][0] += 1
def Dislike(postName):
socialMedia[postName][1] += 1
def Comment(postName,commentator,content):
socialMedia[postName].append(f"* {commentator}: {content}")
socialMedia = dict()
while... | true |
9afcbfcc8d83b5715ef9353de3c385cfac902871 | Python | Sladge17/linear_regression | /teacher.py | UTF-8 | 1,867 | 2.796875 | 3 | [] | no_license | import sys
import numpy as np
def check_argv(argv):
argv_len = len(argv)
if not argv_len:
return 'data.csv'
if argv_len != 1:
print("\033[31mNeed only one dataset\033[37m")
exit()
return argv[0]
def read_data(source):
try:
data = np.genfromtxt(source, dtype=np.uint32, delimiter=',')[1:]
except:
print(... | true |
48795a26e884322189b14aa425dc3a7670f650a2 | Python | ww35133634/chenxusheng | /ITcoach/xlrd_xlwt处理数据/第9章 Python函数技术/9.7 递归函数写法及应用/9.7.1.py | UTF-8 | 242 | 3.390625 | 3 | [
"AFL-3.0"
] | permissive | # def fact(x):
# if x==1:
# return 1
# else:
# return x+fact(x-1)
#
# print(fact(5))
def con(l):
if len(l)==0:
return ''
else:
return con(l[:len(l)-1])+'-'+l[-1]
print(con(['a','b','c','d']))
| true |
ca7d6bbd4e41c591d6e280b481e7e3227cddca8e | Python | tedchou12/connect-pm-server | /src/pm_server/modules/security.py | UTF-8 | 1,560 | 2.546875 | 3 | [] | no_license | from flask import make_response, request, session
from datetime import date, datetime, timedelta
from .db import db
import time
import random
import string
class security :
def __init__(self):
self.table = 'security'
self.valid_duration = 60 * 10
def get_hash(self) :
obj_database = db(... | true |
a2d6a9d2a033aa5ad5d1cc057f40b400855b8c6f | Python | ElTrackiras/KeyboardTrainer | /main.py | UTF-8 | 7,406 | 3.40625 | 3 | [] | no_license | import pygame
import random
pygame.init()
class LetterBoxes:
monster_img = pygame.image.load('Assets/Monster.png')
all_boxes = list()
box_font = pygame.font.SysFont("monospace", 30)
def __init__(self, x, y, letter):
self.image = LetterBoxes.monster_img
self.x = x
self.y = y
... | true |
f00c2fedad62050629a90f32b1d9472f0b4154a7 | Python | siberowl/AI_CP365 | /src/Adaline/Adaline.py | UTF-8 | 1,234 | 2.734375 | 3 | [] | no_license | import numpy as np
import pandas as pd
class Adaline:
def __init__(self):
return None
def fit(self, data, labels):
self.data = data
self.labels = labels
self.nexamples = data.shape[0]
self.nfeatures = data.shape[1]
ws = np.ones((self.nfeatures,1))
lr = 0.... | true |
bf557469d6acda997412d01f02bc55663b4a2c30 | Python | zkroliko/Abyssal-Destructor | /abyssaldestrucion/client/Client.py | UTF-8 | 5,912 | 2.53125 | 3 | [] | no_license | import paho.mqtt.client as mqtt
import sys
import random
from ControllerUtil import ControllerUtil
from Topics import Topics, main_topic
from SerialStub import *
from threading import Thread
import Message
import thread
import time
import serial
class Client:
def on_message(self, client, obj, msg):
# if ... | true |
53d67df26ea5e4b491f0c8951eab0025e94c03b7 | Python | dbconfession78/interview_prep | /leetcode/14_longest_common_prefix.py | UTF-8 | 1,568 | 3.78125 | 4 | [] | no_license | """
Write a function to find the longest common prefix string amongst an array of strings.
If there is no common prefix, return an empty string "".
Example 1:
Input: ["flower","flow","flight"]
Output: "fl"
Example 2:
Input: ["dog","racecar","car"]
Output: ""
Explanation: There is no common prefix among the input st... | true |
fec4aaaa79a96677673c14ec804a11439ca637a6 | Python | yehudit96/coreferrability | /classifiers/significance_test/create_data_for_AP_significance_test.py | UTF-8 | 2,262 | 2.8125 | 3 | [] | no_license | import os
import sys
import random
import argparse
import _pickle as cPickle
from random import choices
from tqdm import tqdm
random.seed(1)
from svm_classifier import *
parser = argparse.ArgumentParser(description='Creating data for statistical significance tests')
parser.add_argument('--rules_path', type=str,
... | true |
c88f845952f56e96430ad1829f1f19a7f522e973 | Python | YifanXu1999/AI-Learning | /Trust Region Policy Optimization/TRPO Project/CartPole A2C/agent.py | UTF-8 | 2,296 | 2.609375 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 28 20:12:19 2020
@author: yifanxu
"""
from model import Actor
from model import Critic
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import hp
import torch.distributions as distributions
import gym
... | true |
46b24c38c760ebad267d81f82c14929bd28ab235 | Python | pzmrzy/LeetCode | /python/reverse_integer.py | UTF-8 | 403 | 3.0625 | 3 | [] | no_license | class Solution(object):
def reverse(self, x):
"""
:type x: int
:rtype: int
"""
flag = 1
if (x < 0):
x = -1 * x
flag = -1
result = 0
while (x > 0):
result *= 10
result += x % 10
x /= 10
... | true |
bd71839e7eb8b1c6840fe8f23ce4bd1edcb50918 | Python | LuminousCL/Iris_kmeans | /Iris_kmeans_decisiontree.py | UTF-8 | 804 | 3.234375 | 3 | [] | no_license | #############鸢尾花数据集的决策树分析#############
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn import metrics
from sklearn.datasets import load_iris
import matplotlib.pyplot as plt
iris = load_iris()
x_train,x_test,y_train,y_test = train_test_split(iris.data,i... | true |
52f37705e21ffa6dd7e6a2513743e5bfd7df4101 | Python | Marist-CMPT120-FA19/-Jim-Moehringer--Project-3 | /tree.py | UTF-8 | 233 | 3.6875 | 4 | [] | no_license | def main():
height=int(input("Enter the height of the tree: "))
h= height
hashtag= 1
while h >0:
print(' ' * (h-1) + "#" * (hashtag))
h -=1
hashtag +=2
print(" " * (height-1) + "#")
main()
| true |
1f4663b8540a7d1ebe098eb1cfa7c1b7b9c0ca3e | Python | LeytonYu/python_algorithm | /sword art online/图/广度优先遍历.py | UTF-8 | 399 | 3.515625 | 4 | [] | no_license | def bfs(graph,start):
explored,queue=[],[start]
explored.append(start)
while queue:
v=queue.pop(0)
for i in graph[v]:
if i not in explored:
explored.append(i)
queue.append(i)
return explored
G = {'0': ['1', '2'],
'1': ['2', '3'],
'2'... | true |
920de34e0d208ffe4c83b3dfb75a93004efb5119 | Python | ehdusjenny/music | /music/data/musicnet.py | UTF-8 | 9,398 | 2.59375 | 3 | [] | no_license | #import config
import numpy as np
from tqdm import tqdm
import torch
import os
import csv
import pickle
from intervaltree import IntervalTree
import scipy
from scipy.io import wavfile
import pretty_midi
class Memoize(object):
def __init__(self, file_name, func):
self.file_name = file_name
self.func... | true |
bcbbf956b590b9d4b50444cd6e1103fcfd46d9e5 | Python | ygperez/CIS-024C-HW | /helperfunctions.py | UTF-8 | 270 | 3.71875 | 4 | [] | no_license | import math
import sys
def add(x,y):
print "Add = ", x+y
def diff(x,y):
print "Subtract = ", x-y
def product(x,y):
print "Product = ", x*y
def greatest(x,y):
if x>y:
print "x is greater than y"
if y>x:
print "y is greater than x" | true |
8285fb7c6412df9a64a5c43f5aefa4dc8dfb5f7f | Python | Arcprm4/HelloGit | /ABC121/C.py | UTF-8 | 294 | 2.8125 | 3 | [] | no_license | def MAP(): return list(map(int,input().split()))
n,m = MAP()
lst = [MAP() for _ in range(n)]
lst = sorted(lst,key = lambda x:x[0])
q = 0
ans = 0
for i in lst:
if q+i[1]<m:
q+=i[1]
ans+=i[0]*i[1]
else:
ans += (m-q)*i[0]
break
print(ans) | true |
af9059fa3577c707612c39263d59fdfddfda65e6 | Python | enesgrahovac/kaggle | /nlp_tutorial/first.py | UTF-8 | 1,132 | 3.5 | 4 | [] | no_license | import spacy
nlp = spacy.load('en')
doc = nlp("Yo! My name is Enes, hello computer! How're you doing today?")
for token in doc:
print(token)
print(f"Token \t\tLemma \t\tStopword".format('Token', 'Lemma', 'Stopword'))
print("-"*40)
for token in doc:
print(f"{str(token)}\t\t{token.lemma_}\t\t{token.is_stop}")... | true |
01f31dbdd5584992d6359773a976bf7f5726fe62 | Python | yabirgb/hashcode | /2018/main.py | UTF-8 | 1,543 | 3.28125 | 3 | [
"MIT"
] | permissive | import sys
from car import Car
from plan import *
from ride import Ride
def get_info(filename):
"""
Function that gets the input
Return:
params: A tuple with the input params
rides: A list with all the rides info
"""
with open(filename) as f:
#get the first line of the inpu... | true |
b692bd7714ffeb2d415bab7c184af949ffb5ea9b | Python | leosamuel64/MPSI | /IPT/1-Python/TP2/ex11.py | UTF-8 | 297 | 3.578125 | 4 | [] | no_license | def sentenceToWords(sentence):
liste = []
word = ""
for i in range (0,len(sentence)):
if sentence[i] != " ":
word += sentence[i]
else :
liste.append(word)
word = ""
liste.append(word)
return liste
print(sentenceToWords("Arthur le glomorphe à rayure marche à vive allure"))
| true |
a3508b93ffe2d46d5af3ba5a259f3c411ac48319 | Python | daniloBlera/ProjetoPSD-RSI | /StreamProcessing/post_structure_processing.py | UTF-8 | 2,488 | 2.53125 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
from datetime import datetime
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.mqtt import MQTTUtils
import pika
sc = SparkContext("local[5]", "Jesus Christ that's Jason Bourne")
ssc = StreamingContext(sc, 1)
ssc.checkpoint("/tmp/spark-str... | true |
3944e7245529b6dc0f22ff555bc6894795f19f42 | Python | jenjouhung/DHD_Classifier | /train.py | UTF-8 | 3,739 | 2.734375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import numpy as np
import pickle
from keras.utils import to_categorical
from keras.callbacks import EarlyStopping
import dataload
import param
from model import birnn
#from model import att_birnn
WORD2IDX_FILE = param.WORD_BASED_WORD2IDX_FILE if param.USE_WORD_DATA else param.CHAR_BASED_WORD2... | true |
bf41f22545e55b76fbed7dbfe7d5f91ff392bab7 | Python | JackRogersMacro/ABM_Macro | /SimpleMacro3.py | UTF-8 | 17,602 | 2.671875 | 3 | [] | no_license | """
Simple Macroeconomic Model with Satisficing Behaviour
Authors: Hyun Chang Yi and Sarunas Girdenas
LastModified: 04/06/2014
"""
# from datetime import datetime # import this to calculate script execution time
# startTime=datetime.now()
from random import randrange, choice, randint
from random import uniform as unif... | true |
f57092e40334c6d4ea4fb7ca2a785a85e8ff667a | Python | jackyjsy/SGGAN | /data_loader.py | UTF-8 | 4,733 | 2.75 | 3 | [
"MIT"
] | permissive | import torch
import os
import random
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision.datasets import ImageFolder
from PIL import Image
import numpy as np
def to_categorical(y, num_classes):
""" 1-hot encodes a tensor """
# print(y... | true |
e9d4d9ec84a2625c650510033e980fa4cb6de437 | Python | vancun/nifi_factory | /sandbox/explore_jinja2/basic_jinja.py | UTF-8 | 1,356 | 3.328125 | 3 | [] | no_license |
"""
>>> from jinja2 import Template
>>> tpl = Template(u'Greetings, {{ name }}! I am from {{ location }}.')
>>> tpl.render(name='Mr. Arda', location='Amsterdam')
'Greetings, Mr. Arda! I am from Amsterdam.'
Template variables could also be passed as a dictionary.
>>> tpl.render({'name': 'Arthur', 'location':'Stockholm... | true |
258cbf2c0b477c80736d41cf3c03066b0809f198 | Python | finiteautomata/tp-aa | /helpers.py | UTF-8 | 1,014 | 2.984375 | 3 | [] | no_license | #! coding: utf-8
"""Auxiliares varios."""
from sklearn.metrics import precision_score, accuracy_score, f1_score, recall_score, roc_auc_score
import pandas as pd
from data_builder import load_test_data
scores = [
precision_score,
accuracy_score,
f1_score,
recall_score,
roc_auc_score
]
def add_pre... | true |
5eab3b4632de0ee5968842ebba1c87f3345b4173 | Python | AnasTaherGit/Electronic | /Arduino/PySerial/ReadValue.py | UTF-8 | 1,101 | 2.9375 | 3 | [] | no_license | import serial
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib import style
def Voltage(x, in_min=0, in_max=1023, out_min=0, out_max=5):
return (x - in_min) * (out_max - out_min) / (in_max - in_min) + out_min
Arduino = serial.Serial('COM7', 9600)
fig = plt.figure()
ax1 =... | true |
6af269448984ee21b98f31ef3a9f32ac11939bc8 | Python | sklx2016/Repeat-Buyers-Prediction | /split_date.py | UTF-8 | 2,340 | 2.78125 | 3 | [
"MIT"
] | permissive | #-*-coding:utf-8-*-
'''
将usr_log按用户、商户和类别拆分为多个文件
'''
import csv
import os
'''
#记录已存在的date.csv
date_dictionary = {}
#将words写入date.csv文件最后一行，文件打开采用'a'模式，即在原文件后添加（add）
def writeByDate(date,words):
file_name = date+".csv"
os.chdir('../data/date/')
if not date_dictionary.has_key(date):
date_diction... | true |
bf4fc48a86c1dbffb1fab7ba4c6724eeb0f57429 | Python | mal2/Project-Simulation | /fusim16/PCA/pca.py | UTF-8 | 10,183 | 3.34375 | 3 | [] | no_license | import numpy as np
import scipy.spatial.distance as dst
import tempfile # For memory mapped class attributes
class PCA:
""" Apply principal component on a given data set
for the plain purpose of dimensionality reduction.
Attributes
----------
data: 2D numpy.ndarray
Data matrix of dime... | true |
daa5a3fe740eaf2a40689d9d94ea23c1f21059ed | Python | mendrugory/monkey-note-bot | /app/telegram/api.py | UTF-8 | 768 | 2.84375 | 3 | [
"MIT"
] | permissive | import json
import requests
from app.settings import TOKEN
TELEGRAM_URL_API = 'https://api.telegram.org/bot'
def __build_url(method):
url = '{}{}/{}'.format(TELEGRAM_URL_API, TOKEN, method)
return url
def __post(url, body, params=dict()):
"""
Internal post
:param url:
:param body:
:pa... | true |
630fa1acec386f39345d4d0213a3b18de4da65aa | Python | edwardsemisotov/homework | /snowfall.py | UTF-8 | 1,162 | 2.875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import random
import simple_draw as sd
snowflake_list = []
def sd_spawn_snowflake():
x_point = random.randint(10, sd.resolution[0] - 10)
snowflake_len = random.randint(10, 40)
speed = snowflake_len / 5
return [x_point, sd.resolution[1], snowflake_len, speed]
de... | true |
f20d19c45124aa335b2d78c22e19efd1cbb6e4ca | Python | countessellis/pythonpractice | /practicepython_ex7.py | UTF-8 | 100 | 2.984375 | 3 | [] | no_license | #!/usr/bin/python
a = [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
print [ b for b in a if b % 2 == 0 ]
| true |
3dcc5654fd78d2980a40052edb5a69ad2738b39f | Python | williamjameshandley/williamjameshandley.github.io | /assets/students/timeline.py | UTF-8 | 2,495 | 2.703125 | 3 | [] | no_license | #!/usr/bin/env python
from collections import Counter
from students import students
import matplotlib.pyplot as plt
import os
import datetime
import numpy as np
grey = '#bbbbbb'
plt.rcParams['axes.edgecolor'] = grey
plt.rcParams['xtick.color'] = grey
plt.rcParams['ytick.color'] = grey
plt.rcParams['ytick.color'] = grey... | true |
835fb1084c7db85515eae6ce36c7bb31c2e5f5a0 | Python | rickgithacker/pythonclass | /quicktest.py | UTF-8 | 117 | 3 | 3 | [] | no_license | fruit='banana'
fl = len(fruit)
index = 0
while index < fl:
print index, fruit[index]
index = index +1
| true |
d9b765539ae1871986158ca9aedbcb180ab8c37f | Python | Tanvir-Aunjum-Sunny/gltf-blender-importer | /addons/io_scene_gltf/mesh.py | UTF-8 | 9,298 | 2.984375 | 3 | [
"MIT"
] | permissive | import bmesh
import bpy
def convert_coordinates(v):
"""Convert glTF coordinate system to Blender."""
return [v[0], -v[2], v[1]]
def primitive_to_mesh(op, primitive, name, layers, material_index):
"""Create a Blender mesh for a glTF primitive."""
attributes = primitive['attributes']
me = bpy.da... | true |
ffa95541a193ce440badc3adcc084d78bee6e954 | Python | svmldon/IE_507_Modelling_lab | /LAB 05/lab05ex2b.py | UTF-8 | 974 | 3.234375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 23 17:45:21 2017
@author: svmldon
"""
import random
from math import floor, ceil
a=[]*12
rand = float(0)
q = 0
while q < 5000:
q = q + 1
rand = ceil(12*(random.random()))
if rand == 1:
a[0]+= 1
elif rand == 2:
a[1... | true |
bc1daf18bf1227cc083715724ad8099d47417d31 | Python | Roman43407/Sem-1 | /Lab 11/zad3.py | UTF-8 | 160 | 3.6875 | 4 | [] | no_license | import math
a = input("Podaj kąt")
sin = math.sin(int(a))
cos = math.cos(int(a))
tg = math.tan(int(a))
ctg = 1/tg
print(sin)
print(cos)
print(tg)
print(ctg) | true |
47d646ec13e426d6fca2afe6b920c7a0f33ba8c4 | Python | ride80/scrappy-functions | /Scrappy2.1.py | UTF-8 | 1,290 | 2.625 | 3 | [] | no_license | import bs4
from urllib2 import urlopen as uReq
from bs4 import BeautifulSoup as soup
my_url = 'https://www.newegg.com/global/se/Product/ProductList.aspx?Submit=ENE&N=100829626&IsNodeId=1&bop=And&PageSize=96&order=BESTMATCH'
#my_url_2 = 'https://www.newegg.com/Desktop-Graphics-Cards/SubCategory/ID-48/Page-2?Tid=7709&Pa... | true |
01532951d2fba32b33a520778920d74e04b4ff6e | Python | JMGONB/Mirepositorio | /mi_proyecto_agosto/src/api/server.py | UTF-8 | 1,840 | 2.828125 | 3 | [] | no_license |
import os,sys
import json
import pandas as pd
from flask import Flask,render_template,redirect,request,jsonify
# ----------------------
# $$$$$$$ SERVER $$$$$$$$
app = Flask(__name__) #Inicializa el servidor
@app.route("/")
def default():
return "<h1>soy la ruta por defecto</h1>.<p>Añadir get_json?id= para ob... | true |
97f15bdeafc4d5900af5ec59f112b7a5525fc847 | Python | Dimen61/leetcode | /python_solution/DepthFirstSearch/98_ValidateBinarySearchTree.py | UTF-8 | 1,234 | 3.328125 | 3 | [] | no_license | # Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution(object):
def isValidBST(self, root):
"""
:type root: TreeNode
:rtype: bool
"""
# traversal... | true |
841735d89a2018ccfe55d7414963f3c08cca0c49 | Python | colinclement/varibayes | /varibayes/opt/adadelta.py | UTF-8 | 2,471 | 3.28125 | 3 | [
"MIT"
] | permissive | """
adadelta.py
author: Colin Clement
date: 2017-10-18
This is an implementation of the ADADELTA adaptic learning rate stochastic
gradient descent optimizer as described in https://arxiv.org/abs/1212.5701
"""
import numpy as np
class Adadelta(object):
def __init__(self, obj_grad_obj, rho=0.9, eps=1e-6):
... | true |
ed6f2f054f13e094e2d57c45e24d2a0624a8ffd7 | Python | adamb70/RomUtilityScripts | /RomUtilityScripts/WorldGen/Environment/GenerateEnvironementFiles.py | UTF-8 | 1,381 | 2.5625 | 3 | [] | no_license | from .DataImporter import ProceduralItemGroupSheetHandler, GrowableItemGroupSheetHandler
def generate_item_groups(outfile='Output/ItemGroups.sbc', handler=None):
ss = ProceduralItemGroupSheetHandler() if not handler else handler
ss.write_item_groups(ss.get_item_group_dict(), outfile)
return outfile
def ... | true |
6b6759c8ad5f925f54d9bd605978f455ec070fc1 | Python | kariulele/epita-image | /cours/2020/ing2/bigdata/lesson7 Graphics/dash_fertility.py | UTF-8 | 8,510 | 2.609375 | 3 | [] | no_license | import dash
import dash_core_components as dcc
import dash_html_components as html
import pandas as pd
import numpy as np
import plotly.graph_objs as go
START = 'Start'
STOP = 'Stop'
def get_data():
incomes = pd.read_excel('data/GDPpercapitaconstant2000US.xlsx', index_col=0).round()
children = pd.read_excel(... | true |
e47403b0d88387c91b54a94ab35c3df1081891af | Python | daniele-salerno/Gender-Classifier-CV | /3_image_gender_classifier.py | UTF-8 | 1,660 | 3.5 | 4 | [] | no_license | ###############################
"""
Part 3 of 4
Script used for testing the model previus saved with some random images from internet
"""
###############################
import cv2
from tensorflow.keras.models import load_model
SCALE = (200, 200)
model = load_model('model.h5')
face_cascade = cv2.CascadeClassifier(... | true |
be289912a071b4931c29b00287db4c1a31a9a053 | Python | cladren123/study | /AlgorithmStudy/백준/4 N과 M 시리즈/N 과 M (1).py | UTF-8 | 1,132 | 3.78125 | 4 | [] | no_license |
"""
2 브루트포스 문제 대비, N과 M은 확실하게 마스터 하자.
"""
n, m = map(int, input().split())
used = [0] * m
visited = [0] * n
card = []
"""
n 은 가짓수
m 은 하나씩 뽑는다.
입력 3 1
3개 중에서 하나 고르기
n 개 중에서 m 개 고르기
즉 n과 m은 n개 중에서 m개 고르기. 모든 경우의 수를 고르기.
used 는 m개 고를걸 담는다
visited 는 n개, 즉 전체에 방문하는 것을 통해 모든 경우의 수를 확인
card는 이제 뼈대가 들어오면 생기는 몸?... | true |
8812283ed58bc7521743af51e10698018191b911 | Python | rhutuja3010/function | /given 2 no. find max number.py | UTF-8 | 237 | 3.53125 | 4 | [] | no_license | # def max(a,b):
# if a > b:
# return a
# else:
# return b
# print("max number =",max(30,40))
def hello(name,mgs = "how are you"):
print("hello",name,mgs)
hello ("friend",",have a nice day")
hello("friend")
| true |
67de6e18a5add7320d21c26f2fd8812c24139290 | Python | passionzhan/design_pattern | /adapter.py | UTF-8 | 799 | 2.71875 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-#
#-------------------------------------------------------------------------------
# PROJECT_NAME: design_pattern
# Name: adapter.py
# Author: 9824373
# Date: 2020-08-19 15:24
# Contact: 9824373@qq.com
# Version: V1.... | true |
a3c2a5c4a88204757168015eaf9188da7a2eb02c | Python | ethanluckett/csci531-conniption | /play_test.py | UTF-8 | 2,720 | 3.3125 | 3 | [] | no_license | #!/usr/bin/env python
from board_class import BoardState
from expand import breadth
from search import alpha_beta_search
from cevaluate.evaluate import evaluate_full
#from evaluate import Evaluator
import functools
import random
import sys
#eval = Evaluator()
def human_move(state):
print('P1 flips:', state.p1_fl... | true |
f472ab4b199045a469d184065a3e838750a3903b | Python | skuxy/Advent-Of-Code-codes | /2017/day7.py | UTF-8 | 1,936 | 3.46875 | 3 | [] | no_license | #! /usr/bin/env python3
class node:
def __init__(self, name, value):
self.name = name
self.value = value
self.parent = None
self.children = []
def assign_parent(self, parent):
self.parent = parent
def assign_child(self, child):
self.children.append(child)
... | true |
bb9d35ce9ac87ee6f00b982d0375794c0c7e4a35 | Python | hyfgreg/leetcode | /118.yanghuiTriangle.py | UTF-8 | 925 | 3.640625 | 4 | [] | no_license | # -*- coding: utf-8 -*-
"""
给定一个非负整数 numRows，生成杨辉三角的前 numRows 行。
在杨辉三角中，每个数是它左上方和右上方的数的和。
示例:
输入: 5
输出:
[
[1],
[1,1],
[1,2,1],
[1,3,3,1],
[1,4,6,4,1]
]
"""
# 动态规划, 每一行的数字都和上一行的数字有关
from typing import List
class Solution:
def generate(self, numRows: int) -> List[List[int]... | true |