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2023-08-21 12:35:19
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132
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
5e1380e7e83fc9ec185495578654737b55934163
|
13f836eb4770d3d2b0e4be27067411a9d71b8e0d
|
/__init__.py
|
f61e61e171dabbbe82865b96ec71b02b37e4a5a4
|
[
"ISC"
] |
permissive
|
willsion/push_api
|
b6f5395178543a6139bffa2406a8955b69c8b393
|
91b5ab8f15029a698216791365b2f589dc340d5c
|
refs/heads/master
| 2021-01-15T14:23:45.981417
| 2016-09-07T02:41:35
| 2016-09-07T02:41:35
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 390
|
py
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# =============================================================================
# FileName: __init__.py
# Desc: 2015-15/1/7:下午1:32
# Author: 苦咖啡
# Email: voilet@qq.com
# HomePage: http://blog.kukafei520.net
# History:
# =============================================================================
|
[
"voilet@voiletdeMacBook-Pro-2.local"
] |
voilet@voiletdeMacBook-Pro-2.local
|
1d5d22515ceb69a934cb6bae79eabbf50bc1f463
|
47744b621bd0bc03f2eb6c0fead3ad2347a70aac
|
/ud120-projects/k_means/k_means_3_features.py
|
54960b687f087c22669e3e9627fb3600a5022b27
|
[] |
no_license
|
shivam04/udacity-intro-to-machine-learning
|
55be33ab1c426d7578bac4cf6c23486feca52c0d
|
5e3a535bc31ec3d29088db832a0fa921a6b4b467
|
refs/heads/master
| 2020-04-06T04:20:40.663517
| 2017-06-24T07:46:43
| 2017-06-24T07:46:43
| 82,966,759
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,623
|
py
|
#!/usr/bin/python
"""
Skeleton code for k-means clustering mini-project.
"""
import pickle
import numpy
import matplotlib.pyplot as plt
import sys
sys.path.append("../tools/")
from feature_format import featureFormat, targetFeatureSplit
def Draw(pred, features, poi, mark_poi=False, name="image.png", f1_name="feature 1", f2_name="feature 2"):
""" some plotting code designed to help you visualize your clusters """
### plot each cluster with a different color--add more colors for
### drawing more than five clusters
colors = ["b", "c", "k", "m", "g"]
for ii, pp in enumerate(pred):
plt.scatter(features[ii][0], features[ii][1], color = colors[pred[ii]])
### if you like, place red stars over points that are POIs (just for funsies)
if mark_poi:
for ii, pp in enumerate(pred):
if poi[ii]:
plt.scatter(features[ii][0], features[ii][1], color="r", marker="*")
plt.xlabel(f1_name)
plt.ylabel(f2_name)
plt.savefig(name)
plt.show()
### load in the dict of dicts containing all the data on each person in the dataset
data_dict = pickle.load( open("../final_project/final_project_dataset.pkl", "r") )
### there's an outlier--remove it!
data_dict.pop("TOTAL", 0)
#print data_dict
### the input features we want to use
### can be any key in the person-level dictionary (salary, director_fees, etc.)
feature_1 = "salary"
feature_2 = "exercised_stock_options"
feature_3 = "total_payments"
poi = "poi"
features_list = [poi, feature_1, feature_2,feature_3]
data = featureFormat(data_dict, features_list )
poi, finance_features = targetFeatureSplit( data )
### in the "clustering with 3 features" part of the mini-project,
### you'll want to change this line to
### for f1, f2, _ in finance_features:
### (as it's currently written, the line below assumes 2 features)
for f1, f2 ,f3 in finance_features:
plt.scatter( f1, f2, f3 )
plt.show()
### cluster here; create predictions of the cluster labels
### for the data and store them to a list called pred
from sklearn.cluster import KMeans
data2 = featureFormat(data_dict, features_list )
poi, finance_features = targetFeatureSplit( data2 )
clf = KMeans(n_clusters=2, random_state=0)
pred = clf.fit_predict( finance_features )
### rename the "name" parameter when you change the number of features
### so that the figure gets saved to a different file
try:
Draw(pred, finance_features, poi, mark_poi=False, name="clusters3.pdf", f1_name=feature_1, f2_name=feature_2)
except NameError:
print "no predictions object named pred found, no clusters to plot"
|
[
"sinhahsivam04@gmail.com"
] |
sinhahsivam04@gmail.com
|
75ae57ff4ee114e75afc618e0e52b41489e7628d
|
f6e2744ba52b0655d82071edc741d36cb840e1ff
|
/Lab1/DataGenerator/CsvParser.py
|
50f2e1699047b5e143d5ee2e059879b9de1ecd62
|
[] |
no_license
|
PinarTurkyilmaz/SDM-Lab1
|
abb77192cf4c85b1751263e1939434cb2de8d3c2
|
0df7b8d2c47d588e15633a684c857ddda5ebefa7
|
refs/heads/master
| 2020-04-28T18:15:46.867738
| 2019-03-13T18:28:40
| 2019-03-13T18:28:40
| 175,473,072
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 444
|
py
|
import csv
with open('Populate.csv', 'r') as csv_file:
csv_reader = csv.DictReader(csv_file)
with open('Cititation.csv', 'w') as new_file:
fieldnames = ['title']
csv_writer = csv.DictWriter(new_file, fieldnames)
csv_writer.writeheader()
for line in csv_reader:
del line['author'] #remove this column
csv_writer.writerow(line)
print(line)
#upload title to another csv
|
[
"pinar.turkyilmaz@estudiant.upc.edu"
] |
pinar.turkyilmaz@estudiant.upc.edu
|
ec1ff974949d84acfe1277e786b564a0462c7d31
|
c20a7a651e63c1e7b1c5e6b5c65c8150898bbaf2
|
/OJ/LeetCode/74. Search a 2D Matrix.py
|
bafc00d5a9be337a73709ca26357f10eba16536e
|
[] |
no_license
|
Nobody0321/MyCodes
|
08dbc878ae1badf82afaf0c9fc608b70dfce5cea
|
b60e2b7a8f2ad604c7d28b21498991da60066dc3
|
refs/heads/master
| 2023-08-19T14:34:23.169792
| 2023-08-15T15:50:24
| 2023-08-15T15:50:24
| 175,770,050
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 712
|
py
|
# 剑指offer出现过
# 矩阵每一行都是左到右递增，每一列都是上到下递增，所以从左下角开始，类似二分查找
class Solution:
def searchMatrix(self, matrix, target):
if matrix == []:
return False
height, width = len(matrix), len(matrix[0])
i, j= height-1, 0
while 0<=i<=height-1 and 0<=j<=width-1:
if 0<=i<=height-1 and 0<=j<=width-1 and matrix[i][j] < target:
j+=1
elif 0<=i<=height-1 and 0<=j<=width-1 and matrix[i][j] > target:
i-=1
else:
return True
return False
if __name__ == "__main__":
print(Solution().searchMatrix([[1]], 2))
|
[
"cyk19951@gmail.com"
] |
cyk19951@gmail.com
|
7035acb8a40194eba9b97b8e70803602562936bc
|
a13ffbab0f24047e43f003131b06052c4a29adff
|
/Chapter_07/shop/admin.py
|
c416b49b87b43f83b8f9e5857d303c64c142eaee
|
[
"Unlicense"
] |
permissive
|
codingEzio/code_py_book_django2_by_example
|
58a02b7b8e6a549804834d28488412243df94ea2
|
d215d0c87a557685824286822186966b06fa8d59
|
refs/heads/master
| 2020-04-09T18:24:58.821192
| 2019-01-24T08:49:26
| 2019-01-24T08:49:26
| 160,511,430
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 964
|
py
|
from django.contrib import admin
from parler.admin import TranslatableAdmin
from .models import Category, Product
@admin.register(Category)
class CategoryAdmin(TranslatableAdmin):
"""
For the "translated_fields", you need to
use `get_prepopulated_fields` instead of `prepopulated_fields`
Since it provides the same functionality,
there's no difference actually, just a different way to get it :P
"""
list_display = ['name', 'slug']
def get_prepopulated_fields(self, request, obj=None):
return { 'slug': ('name',) }
@admin.register(Product)
class ProductAdmin(TranslatableAdmin):
list_display = ['name', 'slug', 'price',
'available', 'created', 'updated']
list_filter = ['available', 'created', 'updated']
list_editable = ['price', 'available']
def get_prepopulated_fields(self, request, obj=None):
return { 'slug': ('name',) }
|
[
"assassinste@gmail.com"
] |
assassinste@gmail.com
|
ea590224b5586f898dbc17f6cb755bd3676f56a1
|
ee01a1f16e63483ebfd304b838f015f9f2d168b7
|
/streamtools/web/main.py
|
0188e48a1b050926b6b4c97b32e5a60899ae5eef
|
[
"MIT"
] |
permissive
|
mariocesar/stream-tools
|
284aa494676d27204d71da3a0bdb9a196bcab861
|
384c10d364d8b40b9dfa15eeebed15da6f90ed31
|
refs/heads/master
| 2022-12-22T14:52:01.033784
| 2021-07-19T01:32:17
| 2021-07-19T01:32:17
| 250,092,686
| 1
| 1
|
MIT
| 2022-12-12T08:22:55
| 2020-03-25T21:14:04
|
Python
|
UTF-8
|
Python
| false
| false
| 867
|
py
|
import asyncio
from asyncio import Queue
from aiohttp import web
from streamtools.relay.main import fetch_events
routes = web.RouteTableDef()
@routes.get("/ws/")
async def websocket_handler(request):
ws = web.WebSocketResponse()
await ws.prepare(request)
task = asyncio.create_task(fetch_events(request.app.queue))
try:
while True:
message = await request.app.queue.get()
print(message)
await ws.send_json(message.asdata())
finally:
await ws.close()
task.cancel()
return ws
@routes.get("/")
async def landing(request):
return web.Response(text="Hello!")
def get_application():
app = web.Application()
app.queue = Queue()
app.queue.empty()
app.add_routes(routes)
return app
if __name__ == "__main__":
web.run_app(get_application(), port=3000)
|
[
"mariocesar.c50@gmail.com"
] |
mariocesar.c50@gmail.com
|
636e89e816adde63d47a7c4d4e3d83e62438d8d6
|
c3dc08fe8319c9d71f10473d80b055ac8132530e
|
/challenge-133/paulo-custodio/python/ch-1.py
|
0c9b9ec563b3fa36246755408c816a2874d78618
|
[] |
no_license
|
southpawgeek/perlweeklychallenge-club
|
d4b70d9d8e4314c4dfc4cf7a60ddf457bcaa7a1e
|
63fb76188e132564e50feefd2d9d5b8491568948
|
refs/heads/master
| 2023-01-08T19:43:56.982828
| 2022-12-26T07:13:05
| 2022-12-26T07:13:05
| 241,471,631
| 1
| 0
| null | 2020-02-18T21:30:34
| 2020-02-18T21:30:33
| null |
UTF-8
|
Python
| false
| false
| 760
|
py
|
#!/usr/bin/env python3
# Challenge 133
#
# TASK #1 > Integer Square Root
# Submitted by: Mohammad S Anwar
# You are given a positive integer $N.
#
# Write a script to calculate the integer square root of the given number.
#
# Please avoid using built-in function. Find out more about it here.
#
# Examples
# Input: $N = 10
# Output: 3
#
# Input: $N = 27
# Output: 5
#
# Input: $N = 85
# Output: 9
#
# Input: $N = 101
# Output: 10
# solution: https://en.wikipedia.org/wiki/Integer_square_root
import sys
def isqrt(n):
x0 = n >> 1 # initial estimate
if x0 == 0:
return n
# loop
x1 = int(x0 + n/x0) >> 1
while x1 < x0:
x0 = x1;
x1 = int(x0 + n/x0) >> 1
return x0
n = int(sys.argv[1])
print(isqrt(n))
|
[
"pauloscustodio@gmail.com"
] |
pauloscustodio@gmail.com
|
70f76bc9b439c416383973f9088f2be3a89488ca
|
cb9b861f5f3c0a36acfa2d0e1664216587b91f07
|
/svr_surrogate.py
|
df181b6f63917221a1b40cfcb1ae7a7835fb5914
|
[] |
no_license
|
rubinxin/SoTL
|
feae052dba5506b3750126b9f7180a02a01bd998
|
16e24371972aab2a5fa36f8febbe83ae4dacf352
|
refs/heads/master
| 2023-01-20T14:35:37.027939
| 2020-11-30T16:51:29
| 2020-11-30T16:51:29
| 307,888,874
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,080
|
py
|
# Our implementation of SVR-based learning curve extrapolation surrogate
# based on the description in B. Baker, O. Gupta, R. Raskar, and N. Naik,
# “Accelerating neural architecture search using performance prediction,” arXiv preprint arXiv:1705.10823, 2017.
import numpy as np
from sklearn.ensemble import RandomForestRegressor
from sklearn.linear_model import BayesianRidge
from sklearn.model_selection import cross_val_score, train_test_split
from sklearn.svm import NuSVR
import time
from scipy import stats
def loguniform(low=0, high=1, size=None):
return np.exp(np.random.uniform(np.log(low), np.log(high), size))
class LcSVR(object):
def __init__(self, VC_all_archs_list, HP_all_archs_list, AP_all_archs_list, test_acc_all_archs_list,
n_hypers=1000, n_train=200, seed=0, all_curve=True, model_name='svr'):
self.n_hypers = n_hypers
self.all_curve = all_curve
self.n_train = n_train
self.seed = seed
self.model_name = model_name
self.VC = np.vstack(VC_all_archs_list)
self.HP = np.vstack(HP_all_archs_list)
self.AP = np.vstack(AP_all_archs_list)
self.DVC = np.diff(self.VC, n=1, axis=1)
self.DDVC = np.diff(self.DVC, n=1, axis=1)
self.max_epoch = self.VC.shape[1]
self.test_acc_seed_all_arch = test_acc_all_archs_list
def learn_hyper(self, epoch):
n_epoch = int(epoch)
VC_sub = self.VC[:, :n_epoch]
DVC_sub = self.DVC[:, :n_epoch]
DDVC_sub = self.DDVC[:, :n_epoch]
mVC_sub = np.mean(VC_sub, axis=1)[:, None]
stdVC_sub = np.std(VC_sub, axis=1)[:, None]
mDVC_sub = np.mean(DVC_sub, axis=1)[:, None]
stdDVC_sub = np.std(DVC_sub, axis=1)[:, None]
mDDVC_sub = np.mean(DDVC_sub, axis=1)[:, None]
stdDDVC_sub = np.std(DDVC_sub, axis=1)[:, None]
if self.all_curve:
TS = np.hstack([VC_sub, DVC_sub, DDVC_sub, mVC_sub, stdVC_sub])
else:
TS = np.hstack([mVC_sub, stdVC_sub, mDVC_sub, stdDVC_sub, mDDVC_sub, stdDDVC_sub])
X = np.hstack([self.AP, self.HP, TS])
y_val_acc = self.VC[:, -1]
y_test_acc = np.array(self.test_acc_seed_all_arch)
y = np.vstack([y_val_acc, y_test_acc]).T
# split into train/test data sets
split = (X.shape[0] - self.n_train) / X.shape[0]
X_train, X_test, y_both_train, y_both_test = train_test_split(
X, y, test_size=split, random_state=self.seed)
y_train = y_both_train[:, 0] # all final validation acc
y_test = y_both_test[:, 1] # all final test acc
np.random.seed(self.seed)
# specify model parameters
if self.model_name == 'svr':
C = loguniform(1e-5, 10, self.n_hypers)
nu = np.random.uniform(0, 1, self.n_hypers)
gamma = loguniform(1e-5, 10, self.n_hypers)
hyper = np.vstack([C, nu, gamma]).T
else:
print('Not implemented')
print(f'start CV on {self.model_name}')
mean_score_list = []
t_start = time.time()
for i in range(self.n_hypers):
# define model
if self.model_name == 'svr':
model = NuSVR(C=hyper[i, 0], nu=hyper[i, 1], gamma=hyper[i, 2], kernel='rbf')
# model = SVR(C=hyper[i, 0], nu=hyper[i, 1], gamma= ,kernel='linear')
elif self.model_name == 'blr':
model = BayesianRidge(alpha_1=hyper[i, 0], alpha_2=hyper[i, 1],
lambda_1=hyper[i, 2], lambda_2=hyper[i, 3])
elif self.model_name == 'rf':
model = RandomForestRegressor(n_estimators=int(hyper[i, 0]), max_features=hyper[i, 1])
# perform cross validation to learn the best hyper value
scores = cross_val_score(model, X_train, y_train, cv=3)
mean_scores = np.mean(scores)
mean_score_list.append(mean_scores)
t_end = time.time()
best_hyper_idx = np.argmax(mean_score_list)
best_hyper = hyper[best_hyper_idx]
max_score = np.max(mean_score_list)
time_taken = t_end - t_start
print(f'{self.model_name} on {self.seed} n_train={self.n_train}: '
f'best_hyper={best_hyper}, score={max_score}, time={time_taken}')
self.epoch = epoch
self.best_hyper = best_hyper
self.X_train, self.X_test = X_train, X_test
self.y_train, self.y_test = y_train, y_test
return best_hyper, time_taken
def extrapolate(self):
if self.model_name == 'svr':
best_model = NuSVR(C=self.best_hyper[0], nu=self.best_hyper[1], gamma=self.best_hyper[2], kernel='rbf')
else:
print('Not implemented')
# train and fit model
best_model.fit(self.X_train, self.y_train)
y_pred = best_model.predict(self.X_test)
rank_corr, p = stats.spearmanr(self.y_test, y_pred)
print(f'{self.model_name} on n_train={self.n_train} e={self.epoch}: rank_corr={rank_corr}')
return rank_corr
|
[
"robin@robots.ox.ac.uk"
] |
robin@robots.ox.ac.uk
|
69fffa27f3895ac0ec76dfa70d08f3e0ab8e62f2
|
e76c8b127ae58c5d3b5d22c069719a0343ea8302
|
/tf_ex_5_linear_reg_with_eager_api.py
|
31dc0013a8602daf6ff29927b818a2c4785c48cd
|
[] |
no_license
|
janFrancoo/TensorFlow-Tutorials
|
18f3479fc647db3cbdb9fb9d5c0b9a67be804642
|
b34dbf903d2f5ff7bde6fb279fef6d7e2004a3bf
|
refs/heads/master
| 2020-07-23T02:01:14.940932
| 2019-10-26T08:41:23
| 2019-10-26T08:41:23
| 207,410,175
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,490
|
py
|
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
# Set Eager API
tf.enable_eager_execution()
tfe = tf.contrib.eager
# Parameters
num_steps = 1000
learning_rate = .01
# Training data
x_train = np.array([3.3, 4.4, 5.5, 6.71, 6.93, 4.168, 9.779, 6.182, 7.59, 2.167, 7.042, 10.791, 5.313,
7.997, 5.654, 9.27, 3.1])
y_train = np.array([1.7, 2.76, 2.09, 3.19, 1.694, 1.573, 3.366, 2.596, 2.53, 1.221, 2.827, 3.465, 1.65,
2.904, 2.42, 2.94, 1.3])
# Weights
w = tfe.Variable(np.random.randn())
b = tfe.Variable(np.random.randn())
# Construct a linear model
def linear_regression(inputs):
return (inputs * w) + b
# Define loss function
def mean_square_fn(model_fn, inputs, labels):
return tf.reduce_sum(((model_fn(inputs) - labels) ** 2) / (2 * len(x_train)))
# Define optimizer
optimizer = tf.train.GradientDescentOptimizer(learning_rate)
# Compute gradients
grad = tfe.implicit_gradients(mean_square_fn)
# Start training
for step in range(num_steps):
optimizer.apply_gradients(grad(linear_regression, x_train, y_train))
if (step + 1) % 50 == 0:
print("Epoch: {}, Loss: {}, W: {}, b: {}".format(step + 1, mean_square_fn(linear_regression, x_train, y_train),
w.numpy(), b.numpy()))
# Display
plt.plot(x_train, y_train, 'ro', label='Original data')
plt.plot(x_train, np.array(w * x_train + b), label='Fitted line')
plt.legend()
plt.show()
|
[
"noreply@github.com"
] |
janFrancoo.noreply@github.com
|
c094ca768a09f90b5ff71b83649c758e5347b11a
|
dbf34d933a288e6ebca568eaebaa53e5b98ba7c1
|
/src/rebecca/index/splitter.py
|
34d4aa005a6bca3c5d5273b7acd574142148f30d
|
[] |
no_license
|
rebeccaframework/rebecca.index
|
dc68dfa2c1b77fc273a12b3f934074722fb8300c
|
ab452c9b375227e84fab42496633dc026421a283
|
refs/heads/master
| 2021-01-10T21:11:53.567186
| 2013-05-05T18:53:58
| 2013-05-05T18:53:58
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 759
|
py
|
from zope.interface import implementer
from zope.index.text.interfaces import ISplitter
from persistent import Persistent
from igo.Tagger import Tagger
@implementer(ISplitter)
class IgoSplitter(Persistent):
def __init__(self, dictionary):
self.dictionary = dictionary
@property
def tagger(self):
if not hasattr(self, '_v_tagger'):
self._v_tagger = Tagger(self.dictionary)
return self._v_tagger
def process(self, terms):
results = []
for term in terms:
results.extend(self.tagger.wakati(term))
return results
def processGlob(self, terms):
results = []
for term in terms:
results.extend(self.tagger.wakati(term))
return results
|
[
"aodagx@gmail.com"
] |
aodagx@gmail.com
|
c361eca7aae2a04817c28fe837c042af887c9567
|
411e5de8629d6449ff9aad2eeb8bb1dbd5977768
|
/AlgoExpert/greedy/minimumWaitingTime.py
|
654f08d249d968d38d7b072c4abfa1fdfa5e8e37
|
[
"MIT"
] |
permissive
|
Muzque/Leetcode
|
cd22a8f5a17d9bdad48f8e2e4dba84051e2fb92b
|
2c37b4426b7e8bfc1cd2a807240b0afab2051d03
|
refs/heads/master
| 2022-06-01T20:40:28.019107
| 2022-04-01T15:38:16
| 2022-04-01T15:39:24
| 129,880,002
| 1
| 1
|
MIT
| 2022-04-01T15:39:25
| 2018-04-17T09:28:02
|
Python
|
UTF-8
|
Python
| false
| false
| 486
|
py
|
"""
"""
testcases = [
{
'input': [3, 2, 1, 2, 6],
'output': 17,
},
{
'input': [2],
'output': 0,
},
]
def minimumWaitingTime(queries):
queries.sort()
ret = 0
for i in range(len(queries)-1):
if i > 0:
queries[i] += queries[i-1]
ret += queries[i]
return ret
if __name__ == '__main__':
for tc in testcases:
ret = minimumWaitingTime(tc['input'])
assert(ret == tc['output'])
|
[
"zerosky1943@gmail.com"
] |
zerosky1943@gmail.com
|
3d90e1a3792eaec38062f7ea1dbe0cfdf9455b06
|
3fa4a77e75738d00835dcca1c47d4b99d371b2d8
|
/backend/pyrogram/raw/base/server_dh_inner_data.py
|
6813099ac6c9cffd446ad983b6da40d37ae93590
|
[
"Apache-2.0"
] |
permissive
|
appheap/social-media-analyzer
|
1711f415fcd094bff94ac4f009a7a8546f53196f
|
0f9da098bfb0b4f9eb38e0244aa3a168cf97d51c
|
refs/heads/master
| 2023-06-24T02:13:45.150791
| 2021-07-22T07:32:40
| 2021-07-22T07:32:40
| 287,000,778
| 5
| 3
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,903
|
py
|
# Pyrogram - Telegram MTProto API Client Library for Python
# Copyright (C) 2017-2021 Dan <https://github.com/delivrance>
#
# This file is part of Pyrogram.
#
# Pyrogram is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Pyrogram is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with Pyrogram. If not, see <http://www.gnu.org/licenses/>.
# # # # # # # # # # # # # # # # # # # # # # # #
# !!! WARNING !!! #
# This is a generated file! #
# All changes made in this file will be lost! #
# # # # # # # # # # # # # # # # # # # # # # # #
from typing import Union
from pyrogram import raw
from pyrogram.raw.core import TLObject
ServerDHInnerData = Union[raw.types.ServerDHInnerData]
# noinspection PyRedeclaration
class ServerDHInnerData: # type: ignore
"""This base type has 1 constructor available.
Constructors:
.. hlist::
:columns: 2
- :obj:`ServerDHInnerData <pyrogram.raw.types.ServerDHInnerData>`
"""
QUALNAME = "pyrogram.raw.base.ServerDHInnerData"
def __init__(self):
raise TypeError("Base types can only be used for type checking purposes: "
"you tried to use a base type instance as argument, "
"but you need to instantiate one of its constructors instead. "
"More info: https://docs.pyrogram.org/telegram/base/server-dh-inner-data")
|
[
"taleb.zarhesh@gmail.com"
] |
taleb.zarhesh@gmail.com
|
6927adb2877ed18131676f2f35fb65189fcc17a5
|
ca617409a3a992a2014eab34bf45ea5cd22021d7
|
/event_management/serializers/venue.py
|
c595ecb61bac9e3ec3a25c229f8cb80dabf5c790
|
[] |
no_license
|
Imam-Hossain-45/ticketing
|
89463b048db3c7b1bc92a4efc39b83c4f17d967f
|
65a124d579162a687b20dfbdba7fd85c110006c6
|
refs/heads/master
| 2022-04-14T22:36:23.152185
| 2020-03-07T11:52:38
| 2020-03-07T11:52:38
| 230,717,468
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 495
|
py
|
from rest_framework import serializers
from event_management.models import Venue
from settings.models import Address
class AddressCreateSerializer(serializers.ModelSerializer):
class Meta:
model = Address
fields = '__all__'
class VenueCreateSerializer(serializers.ModelSerializer):
venue_address = AddressCreateSerializer()
class Meta:
model = Venue
fields = ('name', 'amenities', 'capacity', 'contact_person', 'contact_mobile', 'venue_address')
|
[
"imamhossain1310@gmail.com"
] |
imamhossain1310@gmail.com
|
2ea30df6db951105fb4bc2b8f1eb8fdd7e346f4d
|
cbd60a20e88adb174b40832adc093d848c9ca240
|
/solutions/busnumbers/busnumbers.py
|
690a0be7996a788721974b7b20150d4091bcf299
|
[] |
no_license
|
maxoja/kattis-solution
|
377e05d468ba979a50697b62ce8efab5dcdddc63
|
b762bfa9bbf6ef691d3831c628d9d16255ec5e33
|
refs/heads/master
| 2018-10-09T04:53:31.579686
| 2018-07-19T12:39:09
| 2018-07-19T12:39:09
| 111,871,691
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 579
|
py
|
n = int(input())
seq = sorted(list(map(int, input().split())))
prevs = []
for i in range(len(seq)):
current = seq[i]
nxt = -1 if i == len(seq)-1 else seq[i+1]
if nxt == current+1:
prevs.append(current)
continue
else:
if prevs:
## print('enter' , prevs)
if len(prevs) >= 2:
print(str(prevs[0]) + '-' + str(current), end=' ')
else:
print(prevs[0], current, end=' ')
prevs = []
else:
print(current, end=' ')
|
[
"-"
] |
-
|
3bd03fe4d769ba382d80392cf0c083c66cb30acb
|
71501709864eff17c873abbb97ffabbeba4cb5e3
|
/llvm13.0.0/lldb/test/API/functionalities/thread/concurrent_events/TestConcurrentTwoBreakpointThreads.py
|
1f6832d9ecdb1b993193adf3655ceba218a19e06
|
[
"NCSA",
"Apache-2.0",
"LLVM-exception"
] |
permissive
|
LEA0317/LLVM-VideoCore4
|
d08ba6e6f26f7893709d3285bdbd67442b3e1651
|
7ae2304339760685e8b5556aacc7e9eee91de05c
|
refs/heads/master
| 2022-06-22T15:15:52.112867
| 2022-06-09T08:45:24
| 2022-06-09T08:45:24
| 189,765,789
| 1
| 0
|
NOASSERTION
| 2019-06-01T18:31:29
| 2019-06-01T18:31:29
| null |
UTF-8
|
Python
| false
| false
| 700
|
py
|
import unittest2
from lldbsuite.test.decorators import *
from lldbsuite.test.concurrent_base import ConcurrentEventsBase
from lldbsuite.test.lldbtest import TestBase
@skipIfWindows
class ConcurrentTwoBreakpointThreads(ConcurrentEventsBase):
mydir = ConcurrentEventsBase.compute_mydir(__file__)
# Atomic sequences are not supported yet for MIPS in LLDB.
@skipIf(triple='^mips')
@expectedFailureAll(archs=["aarch64"], oslist=["freebsd"],
bugnumber="llvm.org/pr49433")
def test(self):
"""Test two threads that trigger a breakpoint. """
self.build(dictionary=self.getBuildFlags())
self.do_thread_actions(num_breakpoint_threads=2)
|
[
"kontoshi0317@gmail.com"
] |
kontoshi0317@gmail.com
|
433be8a7d7781edf3a6c0b6fd7ea8ce7d790b2f2
|
ca7aa979e7059467e158830b76673f5b77a0f5a3
|
/Python_codes/p02803/s436740421.py
|
e18ddeaa284997e7a2fa19641dcbbc710be7f0af
|
[] |
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
| 1,057
|
py
|
from collections import deque
H, W = map(int, input().split())
field = ['#' * (W+2)] * (H+2)
for i in range(1, H+1):
field[i] = '#' + input() + '#'
di = [1, 0, -1, 0]
dj = [0, 1, 0, -1]
ans = 0
q = deque()
for si in range(1, H+1):
for sj in range(1, W+1):
if field[si][sj] == '#':
continue
q.clear()
q.append([si, sj])
dist = [[-1 for _ in range(W+2)] for _ in range(H+2)]
dist[si][sj] = 0
dist_max = 0
while len(q) != 0:
current = q.popleft()
ci = current[0]
cj = current[1]
for d in range(4):
next_i = ci + di[d]
next_j = cj + dj[d]
if field[next_i][next_j] == '#':
continue
if dist[next_i][next_j] != -1:
continue
q.append([next_i, next_j])
dist[next_i][next_j] = dist[ci][cj] + 1
dist_max = max(dist_max, dist[next_i][next_j])
ans = max(ans, dist_max)
print(ans)
|
[
"66529651+Aastha2104@users.noreply.github.com"
] |
66529651+Aastha2104@users.noreply.github.com
|
76f9cf3c70feb1745228287e760e543e56e9ce1d
|
900f3e5e0a5f9bbc28aa8673153046e725d66791
|
/less15/chat_v3/chat/chat/settings.py
|
e6a04b5f17f725ceee6cdb1c8879e9c0dbd6a011
|
[] |
no_license
|
atadm/python_oop
|
c234437faebe5d387503c2c7f930ae72c2ee8107
|
2ffbadab28a18c28c14d36ccb008c5b36a426bde
|
refs/heads/master
| 2021-01-23T04:40:10.092048
| 2017-05-30T12:22:53
| 2017-05-30T12:22:53
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,427
|
py
|
"""
Django settings for chat project.
Generated by 'django-admin startproject' using Django 1.11.1.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.11/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '692yjr^yr4$)m_4ud6j7^^!*gd%r+jcp!vn+nr@a4iuzy=m1js'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'chatApp.apps.ChatappConfig',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'chat.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')]
,
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'chat.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql_psycopg2',
'NAME': 'chatdb',
'USER': 'postgres',
'PASSWORD': 'Univer123',
'HOST': '', # Set to empty string for localhost.
'PORT': '5433', # Set to empty string for default.
}
}
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
|
[
"anna@3g.ua"
] |
anna@3g.ua
|
6b09c02200e9cd1e184bdbbc08dba0c6c89f9b8e
|
e8f6a0d45cc5b98747967169cea652f90d4d6489
|
/week2/day2/taco_project/taco_project/settings.py
|
0d5bc4a9d6be4b8a4afe7e0834b1445e8f8b528f
|
[] |
no_license
|
prowrestler215/python-2020-09-28
|
1371695c3b48bbd89a1c42d25aa8a5b626db1d19
|
d250ebd72e7f2a76f40ebbeb7fbb31ac36afd75f
|
refs/heads/master
| 2022-12-28T22:24:52.356588
| 2020-10-06T18:50:12
| 2020-10-06T18:50:12
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,128
|
py
|
"""
Django settings for taco_project project.
Generated by 'django-admin startproject' using Django 2.2.4.
For more information on this file, see
https://docs.djangoproject.com/en/2.2/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/2.2/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'kkc*+j-s50vfg_6s%p!rc^#5$pc2=okw94a6=r17z+lz1s&y@a'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'taco_stand_app',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'taco_project.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'taco_project.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.2/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/2.2/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.2/howto/static-files/
STATIC_URL = '/static/'
|
[
"CBaut@users.noreply.github.com"
] |
CBaut@users.noreply.github.com
|
d45bbc2ebc3e163699e0e18d6bf32523bccae91f
|
978248bf0f275ae688f194593aa32c267832b2b6
|
/xlsxwriter/test/worksheet/test_write_sheet_views8.py
|
16dd94be70b03ae21d672a359c7baa4a50a33d46
|
[
"BSD-2-Clause-Views"
] |
permissive
|
satish1337/XlsxWriter
|
b0c216b91be1b74d6cac017a152023aa1d581de2
|
0ab9bdded4f750246c41a439f6a6cecaf9179030
|
refs/heads/master
| 2021-01-22T02:35:13.158752
| 2015-03-31T20:32:28
| 2015-03-31T20:32:28
| 33,300,989
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,068
|
py
|
###############################################################################
#
# Tests for XlsxWriter.
#
# Copyright (c), 2013-2015, John McNamara, jmcnamara@cpan.org
#
import unittest
from ...compatibility import StringIO
from ...worksheet import Worksheet
class TestWriteSheetViews(unittest.TestCase):
"""
Test the Worksheet _write_sheet_views() method.
"""
def setUp(self):
self.fh = StringIO()
self.worksheet = Worksheet()
self.worksheet._set_filehandle(self.fh)
def test_write_sheet_views1(self):
"""Test the _write_sheet_views() method with split panes + selection"""
self.worksheet.select()
self.worksheet.set_selection('A2')
self.worksheet.split_panes(15, 0)
self.worksheet._write_sheet_views()
exp = '<sheetViews><sheetView tabSelected="1" workbookViewId="0"><pane ySplit="600" topLeftCell="A2" activePane="bottomLeft"/><selection pane="bottomLeft" activeCell="A2" sqref="A2"/></sheetView></sheetViews>'
got = self.fh.getvalue()
self.assertEqual(got, exp)
def test_write_sheet_views2(self):
"""Test the _write_sheet_views() method with split panes + selection"""
self.worksheet.select()
self.worksheet.set_selection('B1')
self.worksheet.split_panes(0, 8.43)
self.worksheet._write_sheet_views()
exp = '<sheetViews><sheetView tabSelected="1" workbookViewId="0"><pane xSplit="1350" topLeftCell="B1" activePane="topRight"/><selection pane="topRight" activeCell="B1" sqref="B1"/></sheetView></sheetViews>'
got = self.fh.getvalue()
self.assertEqual(got, exp)
def test_write_sheet_views3(self):
"""Test the _write_sheet_views() method with split panes + selection"""
self.worksheet.select()
self.worksheet.set_selection('G4')
self.worksheet.split_panes(45, 54.14)
self.worksheet._write_sheet_views()
exp = '<sheetViews><sheetView tabSelected="1" workbookViewId="0"><pane xSplit="6150" ySplit="1200" topLeftCell="G4" activePane="bottomRight"/><selection pane="topRight" activeCell="G1" sqref="G1"/><selection pane="bottomLeft" activeCell="A4" sqref="A4"/><selection pane="bottomRight" activeCell="G4" sqref="G4"/></sheetView></sheetViews>'
got = self.fh.getvalue()
self.assertEqual(got, exp)
def test_write_sheet_views4(self):
"""Test the _write_sheet_views() method with split panes + selection"""
self.worksheet.select()
self.worksheet.set_selection('I5')
self.worksheet.split_panes(45, 54.14)
self.worksheet._write_sheet_views()
exp = '<sheetViews><sheetView tabSelected="1" workbookViewId="0"><pane xSplit="6150" ySplit="1200" topLeftCell="G4" activePane="bottomRight"/><selection pane="topRight" activeCell="G1" sqref="G1"/><selection pane="bottomLeft" activeCell="A4" sqref="A4"/><selection pane="bottomRight" activeCell="I5" sqref="I5"/></sheetView></sheetViews>'
got = self.fh.getvalue()
self.assertEqual(got, exp)
|
[
"jmcnamara@cpan.org"
] |
jmcnamara@cpan.org
|
bd1244422c562b95b4abe609a6ecc9151d8cc0f3
|
2c5edd9a3c76f2a14c01c1bd879406850a12d96e
|
/config/default.py
|
37e61c16709d86117c0fa3d63970296d5b8742d2
|
[
"MIT"
] |
permissive
|
by46/coffee
|
e13f5e22a8ff50158b603f5115d127e07c2e322b
|
f12e1e95f12da7e322a432a6386a1147c5549c3b
|
refs/heads/master
| 2020-08-14T04:42:05.248138
| 2017-10-23T13:39:05
| 2017-10-23T13:39:05
| 73,526,501
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 486
|
py
|
HTTP_HOST = '0.0.0.0'
HTTP_PORT = 8080
DEBUG = False
SECRET_KEY = "\x02|\x86.\\\xea\xba\x89\xa3\xfc\r%s\x9e\x06\x9d\x01\x9c\x84\xa1b+uC"
# Flask-NegLog Settings
LOG_LEVEL = 'debug'
LOG_FILENAME = "logs/error.log"
LOG_BACKUP_COUNT = 10
LOG_MAX_BYTE = 1024 * 1024 * 10
LOG_FORMATTER = '%(asctime)s - %(levelname)s - %(message)s'
LOG_ENABLE_CONSOLE = True
# Flask-CORS Settings
CORS_ORIGINS = "*"
CORS_METHODS = "GET,POST,PUT"
CORS_ALLOW_HEADERS = "Content-Type,Host"
|
[
"ycs_ctbu_2010@126.com"
] |
ycs_ctbu_2010@126.com
|
e53bee84de0b19c27956646ed221e41449d3e3ae
|
0818a9020adc6e25b86060a8e84171d0b4958625
|
/tensorflow-piece/file_gene_scripts.py
|
840928b309ae60acdab8f757ab590e178999874f
|
[] |
no_license
|
wgwangang/mycodes
|
2107becb6c457ed88b46426974a8f1fa07ed37dd
|
9fa48ca071eacf480034d1f69d3c05171d8a97d2
|
refs/heads/master
| 2020-03-28T07:58:45.017910
| 2018-03-14T07:21:14
| 2018-03-14T07:21:14
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,196
|
py
|
import os
def generate_train_test_txt(data_root_dir, save_dir, rate=.1):
train_txt_file_path = os.path.join(save_dir, "train.txt")
test_txt_file_path = os.path.join(save_dir, "test.txt")
dirs = os.listdir(data_root_dir)
train_txt_file = open(train_txt_file_path, mode="w")
test_txt_file = open(test_txt_file_path, mode="w")
for i,level1 in enumerate(dirs):
path_to_level1 = os.path.join(data_root_dir, level1)
img_names = os.listdir(path_to_level1)
test_num = rate*len(img_names)
if test_num < 1:
test_num = 1
test_num = int(test_num)
for img in img_names[:-test_num]:
abs_path = os.path.join(level1, img)
item = abs_path+" "+str(i)+"\n"
train_txt_file.write(item)
for img in img_names[-test_num:]:
abs_path = os.path.join(level1, img)
item = abs_path + " " + str(i) + "\n"
test_txt_file.write(item)
print("people ", i, " Done!")
train_txt_file.close()
test_txt_file.close()
def main():
generate_train_test_txt("/home/dafu/PycharmProjects/data", save_dir="../data")
if __name__ == "__main__":
main()
|
[
"yinpenghhz@hotmail.com"
] |
yinpenghhz@hotmail.com
|
8e0277e0fae0c9499d3837975223b854aed5431e
|
6ba406a7c13d5c76934e36494c32c927bbda7ae7
|
/tests/trails_fhn.py
|
8ff814c29523973081000a55dda715750cf1dacf
|
[
"MIT"
] |
permissive
|
sowmyamanojna/neuronmd
|
50e5e4bd9a4340fda73e363133314118ea815360
|
3994d02214c3cc4996261324cfe9238e34e29f1c
|
refs/heads/main
| 2023-07-09T01:31:32.597268
| 2021-08-23T14:33:38
| 2021-08-23T14:33:38
| 398,491,112
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 315
|
py
|
import numpy as np
import matplotlib.pyplot as plt
from fitzhugh_nagumo import FHNNeuron
neuron = FHNNeuron()
tmax = 100
dt = 0.01
I = 1.75
t = np.arange(0, tmax, dt)
neuron.simulate(0.6, 0, t, 0.6)
neuron.plot(name="0.1")
current_list = np.arange(0.01, I, 0.01)
neuron.animate(t, current_list, ylim=[-0.45,1.5])
|
[
"sowmyamanojna@gmail.com"
] |
sowmyamanojna@gmail.com
|
8fe76f727f44429df1fc0876ce238e15960bc6ec
|
549d11c89ce5a361de51f1e1c862a69880079e3c
|
/python高级语法/线程/都任务版的UDP聊天器.py
|
9d751967f4b2eaba2e1846ea3f723ae9a52eca1e
|
[] |
no_license
|
BaldSuperman/workspace
|
f304845164b813b2088d565fe067d5cb1b7cc120
|
4835757937b700963fdbb37f75a5e6b09db97535
|
refs/heads/master
| 2020-08-01T15:32:02.593251
| 2019-09-26T08:04:50
| 2019-09-26T08:04:50
| 211,034,750
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 953
|
py
|
import socket
import threading
def recv_msg( udp_socket):
while True:
recv_data = udp_socket.recvfrom(1024)
print("收到的数据:{0}".format(recv_data))
def send_msg(udp_socket, dest_port,dest_ip):
'''发送数据'''
while True :
send_data = input("输入发送的数据： ")
udp_socket.sendto(send_data.encode('utf-8'), (dest_ip,dest_port))
def main():
#创建套接字
udp_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
#绑定本地信息
udp_socket.bind(("", 7890))
#获取对方ip
dest_ip = input("请输入对方IP： ")
dest_port = int(input("请输入对方port： "))
#接受数据
#创建线程执行接受发送功能
t_recv = threading.Thread(target=recv_msg, args=(udp_socket, ))
t_send = threading.Thread(target=send_msg, args=(udp_socket, dest_port,dest_ip))
t_recv.start()
t_send.start()
if __name__ == '__main__':
main()
|
[
"you@example.com"
] |
you@example.com
|
f2c68ec335f6a55681c06b381e461d9c65326cee
|
a316a0018bd1cb42c477423916669ed32e2c5d7c
|
/homie/node/property/property_boolean.py
|
49d8eb14cd18735035fe6c9f1f25173d63f9b69c
|
[
"MIT"
] |
permissive
|
mjcumming/HomieV3
|
a8b60ee9119059d546b69b31280cf15a7978e6fc
|
62278ec6e5f72071b2aaebe8e9f66b2071774ef7
|
refs/heads/master
| 2020-04-28T06:49:22.193682
| 2020-04-04T12:36:08
| 2020-04-04T12:36:08
| 175,072,550
| 5
| 7
|
MIT
| 2020-01-15T03:41:38
| 2019-03-11T19:44:17
|
Python
|
UTF-8
|
Python
| false
| false
| 624
|
py
|
from .property_base import Property_Base
class Property_Boolean(Property_Base):
def __init__(self, node, id, name, settable=True, retained=True, qos=1, unit=None, data_type='boolean', data_format=None, value=None, set_value=None):
super().__init__(node,id,name,settable,retained,qos,unit,'boolean',data_format,value,set_value)
def validate_value(self, value):
return True # tests below validate
def get_value_from_payload(self,payload):
if payload == 'true':
return True
elif payload == 'false':
return False
else:
return None
|
[
"mike@4831.com"
] |
mike@4831.com
|
6ee0b28d5d47fef3766ee9a9567b845b290892dd
|
3298ad5f82b30e855637e9351fe908665e5a681e
|
/Regression/Polynomial Regression/polynomial_regression.py
|
07f16298a93575a5156ff3fe4ef8b1102a78ad42
|
[] |
no_license
|
Pratyaksh7/Machine-learning
|
8ab5281aecd059405a86df4a3ade7bcb308f8120
|
74b7b045f17fe52bd02e99c0e25b8e0b4ac3f3a6
|
refs/heads/master
| 2022-12-21T14:05:28.882803
| 2020-09-28T17:03:55
| 2020-09-28T17:03:55
| 292,274,874
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,924
|
py
|
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
dataset = pd.read_csv('Position_Salaries.csv')
X = dataset.iloc[: , 1:-1].values
y = dataset.iloc[: , -1].values
# training the linear regression model on the whole dataset
from sklearn.linear_model import LinearRegression
lin_reg = LinearRegression()
lin_reg.fit(X, y)
# training the polynomial regression model on the whole dataset
from sklearn.preprocessing import PolynomialFeatures
poly_reg = PolynomialFeatures(degree=4)
X_poly = poly_reg.fit_transform(X)
lin_reg_2 = LinearRegression()
lin_reg_2.fit(X_poly,y)
# visualising the linear regression results
plt.scatter(X,y, color='red')
plt.plot(X, lin_reg.predict(X), color= 'blue') # plotting the linear regression line for the X values and the predicted Salary i.e., lin_reg
plt.title('Truth or Bluff (Linear Regression )')
plt.xlabel('Position Level')
plt.ylabel('Salary')
plt.show()
# visualising the polynomial regression results
plt.scatter(X,y, color='red')
plt.plot(X, lin_reg_2.predict(X_poly), color= 'blue') # plotting the linear regression line for the X values and the predicted Salary i.e., lin_reg
plt.title('Truth or Bluff (Polynomial Regression )')
plt.xlabel('Position Level')
plt.ylabel('Salary')
plt.show()
# visualising the polynomial regression results(for higher resolution and smoother curve)
X_grid = np.arange(min(X), max(X), 0.1) # choosing each point with a diff of 0.1
X_grid = X_grid.reshape((len(X_grid),1))
plt.scatter(X,y,color= 'red')
plt.plot(X_grid, lin_reg_2.predict(poly_reg.fit_transform(X_grid)),color='blue')
plt.title('Truth or Bluff (Polynomial Regression Smooth)')
plt.xlabel('Position Level')
plt.ylabel('Salary')
plt.show()
# predicting a new result with linear regression
print(lin_reg.predict([[6.5]]))
# predicting a new result with polynomial regression
print(lin_reg_2.predict(poly_reg.fit_transform([[6.5]])))
|
[
"pratyakshgupta7@gmail.com"
] |
pratyakshgupta7@gmail.com
|
079ded3be59ad28e3f6743e307ba309423d27dcd
|
87cfb3d137853d91faf4c1c5f6e34a4e4a5206d9
|
/src/zojax/cssregistry/tests.py
|
41aa3e1e8e541b96a69a0706d39bde5e7b101372
|
[
"ZPL-2.1"
] |
permissive
|
Zojax/zojax.cssregistry
|
cea24579ef73f7ea2cec9c8b95671a5eeec0ce8f
|
688f4ecb7556935997bbe4c09713bf57ef7be617
|
refs/heads/master
| 2021-01-10T21:06:12.664527
| 2011-12-16T07:15:04
| 2011-12-16T07:15:04
| 2,034,954
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,368
|
py
|
##############################################################################
#
# Copyright (c) 2009 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
""" zojax.cssregistry tests
$Id$
"""
__docformat__ = "reStructuredText"
import unittest, doctest
from zope import interface, schema
from zope.component import provideAdapter
from zope.app.testing import setup
from zope.traversing.namespace import view
from zope.traversing.interfaces import ITraversable
def setUp(test):
setup.placelessSetUp()
setup.setUpTraversal()
provideAdapter(view, (None, None), ITraversable, name="view")
def tearDown(test):
setup.placelessTearDown()
def test_suite():
return unittest.TestSuite((
doctest.DocFileSuite(
'README.txt',
setUp=setUp, tearDown=tearDown,
optionflags=doctest.NORMALIZE_WHITESPACE|doctest.ELLIPSIS),
))
|
[
"andrey.fedoseev@gmail.com"
] |
andrey.fedoseev@gmail.com
|
07f515eae1a86622a522fa62d427c819d880730d
|
c8efab9c9f5cc7d6a16d319f839e14b6e5d40c34
|
/source/All_Solutions/1116.打印零与奇偶数/1116-打印零与奇偶数.py
|
6ba403369346dcd95a2fdfe939a07dc70c003e60
|
[
"MIT"
] |
permissive
|
zhangwang0537/LeetCode-Notebook
|
73e4a4f2c90738dea4a8b77883b6f2c59e02e9c1
|
1dbd18114ed688ddeaa3ee83181d373dcc1429e5
|
refs/heads/master
| 2022-11-13T21:08:20.343562
| 2020-04-09T03:11:51
| 2020-04-09T03:11:51
| 277,572,643
| 0
| 0
|
MIT
| 2020-07-06T14:59:57
| 2020-07-06T14:59:56
| null |
UTF-8
|
Python
| false
| false
| 1,103
|
py
|
import threading
class ZeroEvenOdd:
def __init__(self, n):
self.n = n+1
self.Zero=threading.Semaphore(1)
self.Even=threading.Semaphore(0)
self.Odd=threading.Semaphore(0)
# printNumber(x) outputs "x", where x is an integer.
def zero(self, printNumber: 'Callable[[int], None]') -> None:
for i in range(1,self.n):
self.Zero.acquire()
printNumber(0)
if i%2==1:
self.Odd.release()
else:
self.Even.release()
def even(self, printNumber: 'Callable[[int], None]') -> None:
for i in range(1,self.n):
if i%2==0:
self.Even.acquire()
printNumber(i)
self.Zero.release()
def odd(self, printNumber: 'Callable[[int], None]') -> None:
for i in range(1,self.n):
if i%2==1:
self.Odd.acquire()
printNumber(i)
self.Zero.release()
|
[
"mzm@mail.dlut.edu.cn"
] |
mzm@mail.dlut.edu.cn
|
c8813dfc6bcc9f3e14517bbb631dad71176f78d9
|
32eeb97dff5b1bf18cf5be2926b70bb322e5c1bd
|
/benchmark/wikipedia/testcase/interestallcases/testcase6_011_1.py
|
f8d2461ccd955bd20d8bbd39508574f42faae36b
|
[] |
no_license
|
Prefest2018/Prefest
|
c374d0441d714fb90fca40226fe2875b41cf37fc
|
ac236987512889e822ea6686c5d2e5b66b295648
|
refs/heads/master
| 2021-12-09T19:36:24.554864
| 2021-12-06T12:46:14
| 2021-12-06T12:46:14
| 173,225,161
| 5
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 8,155
|
py
|
#coding=utf-8
import os
import subprocess
import time
import traceback
from appium import webdriver
from appium.webdriver.common.touch_action import TouchAction
from selenium.common.exceptions import NoSuchElementException, WebDriverException
desired_caps = {
'platformName' : 'Android',
'deviceName' : 'Android Emulator',
'platformVersion' : '4.4',
'appPackage' : 'org.wikipedia',
'appActivity' : 'org.wikipedia.main.MainActivity',
'resetKeyboard' : True,
'androidCoverage' : 'org.wikipedia/org.wikipedia.JacocoInstrumentation',
'noReset' : True
}
def command(cmd, timeout=5):
p = subprocess.Popen(cmd, stderr=subprocess.STDOUT, stdout=subprocess.PIPE, shell=True)
time.sleep(timeout)
p.terminate()
return
def getElememt(driver, str) :
for i in range(0, 5, 1):
try:
element = driver.find_element_by_android_uiautomator(str)
except NoSuchElementException:
time.sleep(1)
else:
return element
os.popen("adb shell input tap 50 50")
element = driver.find_element_by_android_uiautomator(str)
return element
def getElememtBack(driver, str1, str2) :
for i in range(0, 2, 1):
try:
element = driver.find_element_by_android_uiautomator(str1)
except NoSuchElementException:
time.sleep(1)
else:
return element
for i in range(0, 5, 1):
try:
element = driver.find_element_by_android_uiautomator(str2)
except NoSuchElementException:
time.sleep(1)
else:
return element
os.popen("adb shell input tap 50 50")
element = driver.find_element_by_android_uiautomator(str2)
return element
def swipe(driver, startxper, startyper, endxper, endyper) :
size = driver.get_window_size()
width = size["width"]
height = size["height"]
try:
driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper),
end_y=int(height * endyper), duration=2000)
except WebDriverException:
time.sleep(1)
driver.swipe(start_x=int(width * startxper), start_y=int(height * startyper), end_x=int(width * endxper),
end_y=int(height * endyper), duration=2000)
return
def scrollToFindElement(driver, str) :
for i in range(0, 5, 1):
try:
element = driver.find_element_by_android_uiautomator(str)
except NoSuchElementException:
swipe(driver, 0.5, 0.6, 0.5, 0.2)
else:
return element
return
def clickoncheckable(driver, str, value = "true") :
parents = driver.find_elements_by_class_name("android.widget.LinearLayout")
for parent in parents:
try :
parent.find_element_by_android_uiautomator(str)
lists = parent.find_elements_by_class_name("android.widget.LinearLayout")
if (len(lists) == 1) :
innere = parent.find_element_by_android_uiautomator("new UiSelector().checkable(true)")
nowvalue = innere.get_attribute("checked")
if (nowvalue != value) :
innere.click()
break
except NoSuchElementException:
continue
# preference setting and exit
try :
os.popen("adb shell svc data diable")
time.sleep(5)
starttime = time.time()
driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)
os.popen("adb shell am start -n org.wikipedia/org.wikipedia.settings.DeveloperSettingsActivity")
scrollToFindElement(driver, "new UiSelector().text(\"useRestbase_setManually\")").click()
clickoncheckable(driver, "new UiSelector().text(\"useRestbase_setManually\")", "false")
scrollToFindElement(driver, "new UiSelector().text(\"mediaWikiBaseUriSupportsLangCode\")").click()
clickoncheckable(driver, "new UiSelector().text(\"mediaWikiBaseUriSupportsLangCode\")", "true")
scrollToFindElement(driver, "new UiSelector().text(\"suppressNotificationPolling\")").click()
clickoncheckable(driver, "new UiSelector().text(\"suppressNotificationPolling\")", "true")
scrollToFindElement(driver, "new UiSelector().text(\"memoryLeakTest\")").click()
clickoncheckable(driver, "new UiSelector().text(\"memoryLeakTest\")", "true")
scrollToFindElement(driver, "new UiSelector().text(\"readingListsFirstTimeSync\")").click()
clickoncheckable(driver, "new UiSelector().text(\"readingListsFirstTimeSync\")", "false")
driver.press_keycode(4)
time.sleep(2)
os.popen("adb shell am start -n org.wikipedia/org.wikipedia.settings.SettingsActivity")
scrollToFindElement(driver, "new UiSelector().text(\"Download only over Wi-Fi\")").click()
clickoncheckable(driver, "new UiSelector().text(\"Download only over Wi-Fi\")", "true")
scrollToFindElement(driver, "new UiSelector().text(\"Show images\")").click()
clickoncheckable(driver, "new UiSelector().text(\"Show images\")", "false")
driver.press_keycode(4)
time.sleep(2)
except Exception, e:
print 'FAIL'
print 'str(e):\t\t', str(e)
print 'repr(e):\t', repr(e)
print traceback.format_exc()
finally :
endtime = time.time()
print 'consumed time:', str(endtime - starttime), 's'
command("adb shell am broadcast -a com.example.pkg.END_EMMA --es name \"6_011_pre\"")
jacocotime = time.time()
print 'jacoco time:', str(jacocotime - endtime), 's'
driver.quit()
# testcase011
try :
starttime = time.time()
driver = webdriver.Remote('http://localhost:4723/wd/hub', desired_caps)
element = getElememtBack(driver, "new UiSelector().text(\"Search Wikipedia\")", "new UiSelector().className(\"android.widget.TextView\")")
TouchAction(driver).tap(element).perform()
driver.press_keycode(82)
driver.press_keycode(82)
driver.press_keycode(82)
driver.press_keycode(82)
driver.press_keycode(82)
driver.press_keycode(82)
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/icon\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().className(\"android.widget.ImageButton\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/menu_overflow_button\").className(\"android.widget.TextView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/menu_overflow_button\").className(\"android.widget.TextView\")")
TouchAction(driver).long_press(element).release().perform()
swipe(driver, 0.5, 0.8, 0.5, 0.2)
element = getElememtBack(driver, "new UiSelector().text(\"Explore\")", "new UiSelector().className(\"android.widget.TextView\").instance(4)")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/menu_overflow_button\").className(\"android.widget.TextView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/icon\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/icon\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/icon\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/voice_search_button\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
element = getElememtBack(driver, "new UiSelector().text(\"Got it\")", "new UiSelector().className(\"android.widget.TextView\").instance(2)")
TouchAction(driver).tap(element).perform()
element = getElememt(driver, "new UiSelector().resourceId(\"org.wikipedia:id/icon\").className(\"android.widget.ImageView\")")
TouchAction(driver).tap(element).perform()
except Exception, e:
print 'FAIL'
print 'str(e):\t\t', str(e)
print 'repr(e):\t', repr(e)
print traceback.format_exc()
else:
print 'OK'
finally:
cpackage = driver.current_package
endtime = time.time()
print 'consumed time:', str(endtime - starttime), 's'
command("adb shell am broadcast -a com.example.pkg.END_EMMA --es name \"6_011\"")
jacocotime = time.time()
print 'jacoco time:', str(jacocotime - endtime), 's'
driver.quit()
if (cpackage != 'org.wikipedia'):
cpackage = "adb shell am force-stop " + cpackage
os.popen(cpackage)
os.popen("adb shell svc data enable")
|
[
"prefest2018@gmail.com"
] |
prefest2018@gmail.com
|
9cbf5b6cf37fb49f49e1452747be65c5d74a5e7b
|
05887f0f20f3a57c11370021b996d76a56596e5f
|
/cats/articles/urls.py
|
ec12a3e5441c566e5a600233b109c2dba9bbd2ea
|
[] |
no_license
|
kate-ka/cats_backend
|
11b5102f0e324713a30747d095291dbc9e194c3a
|
df19f7bfa4d94bf8effdd6f4866012a0a5302b71
|
refs/heads/master
| 2020-12-06T16:59:02.713830
| 2017-10-27T09:51:23
| 2017-10-27T09:51:23
| 73,502,091
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 340
|
py
|
from django.conf.urls import url
from rest_framework.urlpatterns import format_suffix_patterns
from . views import ArticleList, ArticleDetail
urlpatterns = [
url(r'^api-v1/articles/$', ArticleList.as_view()),
url(r'^api-v1/articles/(?P<pk>[0-9]+)/$', ArticleDetail.as_view()),
]
urlpatterns = format_suffix_patterns(urlpatterns)
|
[
"you@example.com"
] |
you@example.com
|
ea1bcc55cfd8b75317e22e14dd2204cfadba8760
|
413f7768f98f72cef8423c473424d67642f1228f
|
/examples/10_useful_functions/ex06_enumerate.py
|
909474c54cfdc5aacf3c864d87b7e09cc6e3b343
|
[] |
no_license
|
easypythoncode/PyNEng
|
a7bbf09c5424dcd81796f8836509be90c3b1a752
|
daaed1777cf5449d5494e5a8471396bbcb027de6
|
refs/heads/master
| 2023-03-22T01:21:47.250346
| 2022-08-29T18:25:13
| 2022-08-29T18:25:13
| 228,477,021
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 176
|
py
|
from pprint import pprint
with open("config_r1.txt") as f:
for num, line in enumerate(f, 1):
if line.startswith("interface"):
print(num, line, end="")
|
[
"58902135+easypythoncode@users.noreply.github.com"
] |
58902135+easypythoncode@users.noreply.github.com
|
7391bab13b498877c272f00e6690ce87243867f1
|
c85d43dc50c26ea0fa4f81b54fb37460ef6cca8d
|
/rms/urls.py
|
e59bd4b9b1b0e2b3f232d4b3be1bab71db14aab9
|
[] |
no_license
|
yorong/buzzz-web-dev
|
c48dbc165d0aa3abce07971a2dee0280f9bf1e92
|
0b74bd1b7cfc7a6a7d61672f930d0bde635b4398
|
refs/heads/master
| 2021-08-23T02:38:00.544503
| 2017-12-02T16:01:31
| 2017-12-02T16:01:31
| 112,854,877
| 0
| 0
| null | 2017-12-02T15:50:40
| 2017-12-02T15:50:39
| null |
UTF-8
|
Python
| false
| false
| 281
|
py
|
from django.conf.urls import url
# from django.views.generic.base import RedirectView
from rms.views import (
RMSHomeView,
RMSStartView,
)
urlpatterns = [
url(r'^$', RMSHomeView.as_view(), name='home'),
url(r'^start/$', RMSStartView.as_view(), name='start'),
]
|
[
"ppark9553@gmail.com"
] |
ppark9553@gmail.com
|
a0b89519a21414737b9664285aa3073dcc619318
|
9ab48ad4a8daf4cab1cdf592bac722b096edd004
|
/genutility/fingerprinting.py
|
b20ca97a8ec9dc1a95e9d6192a517f13f01cf58d
|
[
"ISC"
] |
permissive
|
Dobatymo/genutility
|
c902c9b2df8ca615b7b67681f505779a2667b794
|
857fad80f4235bda645e29abbc14f6e94072403b
|
refs/heads/master
| 2023-08-16T18:07:23.651000
| 2023-08-15T19:05:46
| 2023-08-15T19:05:46
| 202,296,877
| 4
| 1
|
ISC
| 2022-06-14T01:39:53
| 2019-08-14T07:22:23
|
Python
|
UTF-8
|
Python
| false
| false
| 4,528
|
py
|
import logging
import numpy as np
from PIL import Image, ImageFilter
# from .numba import opjit
from .numpy import rgb_to_hsi, rgb_to_ycbcr, unblock
# fingerprinting aka perceptual hashing
def phash_antijpeg(image: Image.Image) -> np.ndarray:
"""Source: An Anti-JPEG Compression Image Perceptual Hashing Algorithm
`image` is a RGB pillow image.
"""
raise NotImplementedError
def hu_moments(channels: np.ndarray) -> np.ndarray:
"""Calculates all Hu invariant image moments for all channels separately.
Input array must be of shape [width, height, channels]
Returns shape [moments, channels]
"""
# pre-calculate matrices
n, m, _ = channels.shape
coords_x, coords_y = np.meshgrid(np.arange(m), np.arange(n))
coords_x = np.expand_dims(coords_x, axis=-1) # for batch input, some change is needed here
coords_y = np.expand_dims(coords_y, axis=-1) # for batch input, some change is needed here
def M(p, q):
return np.sum(coords_x**p * coords_y**q * channels, axis=(-2, -3))
def mu(p, q, xb, yb):
return np.sum((coords_x - xb) ** p * (coords_y - yb) ** q * channels, axis=(-2, -3))
def eta(p, q, xb, yb, mu00):
gamma = (p + q) / 2 + 1
return mu(p, q, xb, yb) / mu00**gamma
def loop():
M00 = M(0, 0)
if not np.all(M00 > 0.0):
logging.error("M00: %s", M00)
raise ValueError("Failed to calculate moments. Single color pictures are not supported yet.")
M10 = M(1, 0)
M01 = M(0, 1)
xb = M10 / M00
yb = M01 / M00
mu00 = mu(0, 0, xb, yb)
eta20 = eta(2, 0, xb, yb, mu00)
eta02 = eta(0, 2, xb, yb, mu00)
eta11 = eta(1, 1, xb, yb, mu00)
eta30 = eta(3, 0, xb, yb, mu00)
eta12 = eta(1, 2, xb, yb, mu00)
eta21 = eta(2, 1, xb, yb, mu00)
eta03 = eta(0, 3, xb, yb, mu00)
phi1 = eta20 + eta02
phi2 = (eta20 - eta02) ** 2 + 4 * eta11**2
phi3 = (eta30 - 3 * eta12) ** 2 + (3 * eta21 - eta03) ** 2
phi4 = (eta30 + eta12) ** 2 + (eta21 + eta03) ** 2
phi5 = (eta30 - 3 * eta12) * (eta30 + eta12) * ((eta30 + eta12) ** 2 - 3 * (eta21 + eta03) ** 2) + (
3 * eta21 - eta03
) * (eta21 + eta03) * (3 * (eta30 + eta12) ** 2 - (eta21 + eta03) ** 2)
phi6 = (eta20 - eta02) * ((eta30 + eta12) ** 2 - (eta21 + eta03) ** 2) + 4 * eta11 * (eta30 + eta12) * (
eta21 + eta03
)
phi7 = (3 * eta21 - eta03) * (eta30 + eta12) * ((eta30 + eta12) ** 2 - 3 * (eta21 + eta03) ** 2) - (
eta30 - 3 * eta12
) * (eta21 + eta03) * (3 * (eta30 + eta12) ** 2 - (eta21 + eta03) ** 2)
return np.array([phi1, phi2, phi3, phi4, phi5, phi6, phi7])
return loop()
# @opjit() rgb_to_hsi and rgb_to_ycbcr not supported by numba
def phash_moments_array(arr: np.ndarray) -> np.ndarray:
arr = arr / 255.0
# convert colorspaces
hsi = rgb_to_hsi(arr)
ycbcr = rgb_to_ycbcr(arr) # .astype(np.uint8)
channels = np.concatenate([hsi, ycbcr], axis=-1)
return np.concatenate(hu_moments(channels).T)
def phash_moments(image: Image.Image) -> np.ndarray:
"""Source: Perceptual Hashing for Color Images Using Invariant Moments
`image` is a RGB pillow image. Results should be compared with L^2-Norm of difference vector.
"""
if image.mode != "RGB":
raise ValueError("Only RGB images are supported")
# preprocessing
image = image.resize((512, 512), Image.BICUBIC)
image = image.filter(ImageFilter.GaussianBlur(3))
image = np.array(image)
return phash_moments_array(image)
def phash_blockmean_array(arr: np.ndarray, bits: int = 256) -> np.ndarray:
"""If bits is not a multiple of 8,
the result will be zero padded from the right.
"""
if len(arr.shape) != 2:
raise ValueError("arr must be 2-dimensional")
n = int(np.sqrt(bits))
if n**2 != bits:
raise ValueError("bits must be a square number")
blocks = unblock(arr, n, n)
means = np.mean(blocks, axis=-1)
median = np.median(means)
bools = means >= median
return np.packbits(bools)
def phash_blockmean(image: Image.Image, bits: int = 256, x: int = 256) -> bytes:
"""Source: Block Mean Value Based Image Perceptual Hashing
Method: 1
Metric: 'Bit error rate' (normalized hamming distance)
"""
image = image.convert("L").resize((x, x))
image = np.array(image)
return phash_blockmean_array(image, bits).tobytes()
|
[
"dobatymo@users.noreply.github.com"
] |
dobatymo@users.noreply.github.com
|
550b55101c715dd350fa5cd27249306a0f72db95
|
aea7bbe854591f493f4a37919eb75dde7f2eb2ca
|
/startCamp/03_day/flask/intro/function.py
|
f11de57476cf04f3c28b5c8018c3382bdd7abb9c
|
[] |
no_license
|
GaYoung87/StartCamp
|
6e31a50d3037174b08a17114e467989520bb9a86
|
231b1fd0e245acb5d4570778aa41de79d6ad4b17
|
refs/heads/master
| 2020-06-17T11:52:38.256085
| 2019-07-12T01:14:47
| 2019-07-12T01:14:47
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 167
|
py
|
# sum이라는 함수를 정의
def sum(num1, num2): # 숫자 num1, num2라는 인자를 받는 함수
return num1 + num2
result = sum(5, 6)
print(result)
|
[
"gyyoon4u@naver.com"
] |
gyyoon4u@naver.com
|
5a2524a0bd81ae136a6c230538fb8c7985d95562
|
09e57dd1374713f06b70d7b37a580130d9bbab0d
|
/data/p3BR/R2/benchmark/startCirq330.py
|
74d7d9238c53332a3cb7ad0438bb8c452fc6d169
|
[
"BSD-3-Clause"
] |
permissive
|
UCLA-SEAL/QDiff
|
ad53650034897abb5941e74539e3aee8edb600ab
|
d968cbc47fe926b7f88b4adf10490f1edd6f8819
|
refs/heads/main
| 2023-08-05T04:52:24.961998
| 2021-09-19T02:56:16
| 2021-09-19T02:56:16
| 405,159,939
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,271
|
py
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 5/15/20 4:49 PM
# @File : grover.py
# qubit number=3
# total number=66
import cirq
import cirq.google as cg
from typing import Optional
import sys
from math import log2
import numpy as np
#thatsNoCode
from cirq.contrib.svg import SVGCircuit
# Symbols for the rotation angles in the QAOA circuit.
def make_circuit(n: int, input_qubit):
c = cirq.Circuit() # circuit begin
c.append(cirq.H.on(input_qubit[0])) # number=1
c.append(cirq.H.on(input_qubit[2])) # number=38
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=39
c.append(cirq.H.on(input_qubit[2])) # number=40
c.append(cirq.H.on(input_qubit[2])) # number=59
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=60
c.append(cirq.H.on(input_qubit[2])) # number=61
c.append(cirq.H.on(input_qubit[2])) # number=42
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=43
c.append(cirq.H.on(input_qubit[2])) # number=44
c.append(cirq.H.on(input_qubit[2])) # number=48
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=49
c.append(cirq.H.on(input_qubit[2])) # number=50
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=54
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=63
c.append(cirq.X.on(input_qubit[2])) # number=64
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=65
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=56
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=47
c.append(cirq.CNOT.on(input_qubit[0],input_qubit[2])) # number=37
c.append(cirq.H.on(input_qubit[2])) # number=51
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=52
c.append(cirq.H.on(input_qubit[2])) # number=53
c.append(cirq.H.on(input_qubit[2])) # number=25
c.append(cirq.CZ.on(input_qubit[0],input_qubit[2])) # number=26
c.append(cirq.H.on(input_qubit[2])) # number=27
c.append(cirq.H.on(input_qubit[1])) # number=7
c.append(cirq.CZ.on(input_qubit[2],input_qubit[1])) # number=8
c.append(cirq.rx(0.17592918860102857).on(input_qubit[2])) # number=34
c.append(cirq.rx(-0.3989822670059037).on(input_qubit[1])) # number=30
c.append(cirq.H.on(input_qubit[1])) # number=9
c.append(cirq.H.on(input_qubit[1])) # number=18
c.append(cirq.rx(2.3310617489636263).on(input_qubit[2])) # number=58
c.append(cirq.CZ.on(input_qubit[2],input_qubit[1])) # number=19
c.append(cirq.H.on(input_qubit[1])) # number=20
c.append(cirq.X.on(input_qubit[1])) # number=62
c.append(cirq.Y.on(input_qubit[1])) # number=14
c.append(cirq.H.on(input_qubit[1])) # number=22
c.append(cirq.CZ.on(input_qubit[2],input_qubit[1])) # number=23
c.append(cirq.rx(-0.9173450548482197).on(input_qubit[1])) # number=57
c.append(cirq.H.on(input_qubit[1])) # number=24
c.append(cirq.Z.on(input_qubit[2])) # number=3
c.append(cirq.Z.on(input_qubit[1])) # number=41
c.append(cirq.X.on(input_qubit[1])) # number=17
c.append(cirq.Y.on(input_qubit[2])) # number=5
c.append(cirq.X.on(input_qubit[2])) # number=21
c.append(cirq.CNOT.on(input_qubit[1],input_qubit[0])) # number=15
c.append(cirq.CNOT.on(input_qubit[1],input_qubit[0])) # number=16
c.append(cirq.X.on(input_qubit[2])) # number=28
c.append(cirq.X.on(input_qubit[2])) # number=29
# circuit end
c.append(cirq.measure(*input_qubit, key='result'))
return c
def bitstring(bits):
return ''.join(str(int(b)) for b in bits)
if __name__ == '__main__':
qubit_count = 4
input_qubits = [cirq.GridQubit(i, 0) for i in range(qubit_count)]
circuit = make_circuit(qubit_count,input_qubits)
circuit = cg.optimized_for_sycamore(circuit, optimizer_type='sqrt_iswap')
circuit_sample_count =2000
simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=circuit_sample_count)
frequencies = result.histogram(key='result', fold_func=bitstring)
writefile = open("../data/startCirq330.csv","w+")
print(format(frequencies),file=writefile)
print("results end", file=writefile)
print(circuit.__len__(), file=writefile)
print(circuit,file=writefile)
writefile.close()
|
[
"wangjiyuan123@yeah.net"
] |
wangjiyuan123@yeah.net
|
7354bef465760c7821f2382d875c71a979be9fd7
|
332cceb4210ff9a5d99d2f3a65a704147edd01a2
|
/justext/utils.py
|
42e5074ec56396d742d4234e9106a0655e9de958
|
[] |
permissive
|
miso-belica/jusText
|
16e5befcb449d3939ce62dc3460afbc768bd07cc
|
22a59079ea691d67e2383039cf5b40d490420115
|
refs/heads/main
| 2023-08-30T03:48:27.225553
| 2023-01-24T08:45:58
| 2023-01-24T08:45:58
| 8,121,947
| 527
| 70
|
BSD-2-Clause
| 2022-05-04T06:11:47
| 2013-02-10T11:42:20
|
Python
|
UTF-8
|
Python
| false
| false
| 1,965
|
py
|
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals
import re
import os
import sys
import pkgutil
MULTIPLE_WHITESPACE_PATTERN = re.compile(r"\s+", re.UNICODE)
def normalize_whitespace(text):
"""
Translates multiple whitespace into single space character.
If there is at least one new line character chunk is replaced
by single LF (Unix new line) character.
"""
return MULTIPLE_WHITESPACE_PATTERN.sub(_replace_whitespace, text)
def _replace_whitespace(match):
"""Normalize all spacing characters that aren't a newline to a space."""
text = match.group()
return "\n" if "\n" in text or "\r" in text else " "
def is_blank(string):
"""
Returns `True` if string contains only white-space characters
or is empty. Otherwise `False` is returned.
"""
return not string or string.isspace()
def get_stoplists():
"""Returns a collection of built-in stop-lists."""
path_to_stoplists = os.path.dirname(sys.modules["justext"].__file__)
path_to_stoplists = os.path.join(path_to_stoplists, "stoplists")
stoplist_names = []
for filename in os.listdir(path_to_stoplists):
name, extension = os.path.splitext(filename)
if extension == ".txt":
stoplist_names.append(name)
return frozenset(stoplist_names)
def get_stoplist(language):
"""Returns an built-in stop-list for the language as a set of words."""
file_path = os.path.join("stoplists", "%s.txt" % language)
try:
stopwords = pkgutil.get_data("justext", file_path)
except IOError:
raise ValueError(
"Stoplist for language '%s' is missing. "
"Please use function 'get_stoplists' for complete list of stoplists "
"and feel free to contribute by your own stoplist." % language
)
return frozenset(w.decode("utf8").lower() for w in stopwords.splitlines())
|
[
"miso.belica@gmail.com"
] |
miso.belica@gmail.com
|
e42abe3c8e78b1c9969be47b78657894ae274870
|
351fa4edb6e904ff1ac83c6a790deaa7676be452
|
/graphs/graphUtil/graphAdjMat.py
|
a8211d8ac10c6c16d87eb91ba14de7aa24570e2a
|
[
"MIT"
] |
permissive
|
shahbagdadi/py-algo-n-ds
|
42981a61631e1a9af7d5ac73bdc894ac0c2a1586
|
f3026631cd9f3c543250ef1e2cfdf2726e0526b8
|
refs/heads/master
| 2022-11-27T19:13:47.348893
| 2022-11-14T21:58:51
| 2022-11-14T21:58:51
| 246,944,662
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,664
|
py
|
from typing import List
from collections import deque
from collections import defaultdict
# A class to represent a graph. A graph
# is the list of the adjacency Matrix.
# Size of the array will be the no. of the
# vertices "V"
class Graph:
def __init__(self, vertices, directed=True):
self.V = vertices
self.adjMatrix = []
self.directed = directed
for i in range(self.V):
self.adjMatrix.append([0 for i in range(self.V)])
# Function to add an edge in an undirected graph
def add_edge(self, src, dest):
if src == dest:
print(f"Same vertex {src} and {dest}")
self.adjMatrix[src][dest] = 1
if not self.directed:
self.adjMatrix[dest][src] = 1
# Function to print the graph adj list
def print_adj_list(self):
for k in self.graph.keys():
print(f"Adjacency list of vertex {k}\n {k}", end="")
for n in self.graph[k]:
print(f" -> {n}", end="")
print(" \n")
def print_adj_mat(self):
print(self.adjMatrix)
# Breadth First Traversal of graph
def BFS(self, root):
q = deque([root])
visited = set([root])
while q:
node = q.pop()
print(f'{node} => ', end="")
for i, child in enumerate(self.adjMatrix[node]):
if child == 1 and i not in visited:
visited.add(i)
q.appendleft(i)
g = Graph(5, True)
g.add_edge(0, 1)
g.add_edge(0, 4)
g.add_edge(1, 4)
g.add_edge(1, 3)
g.add_edge(1, 2)
g.add_edge(2, 3)
g.print_adj_mat()
print('====== BFS =====')
g.BFS(0)
print('\n')
|
[
"email.shanu@gmail.com"
] |
email.shanu@gmail.com
|
1326a2e287de4aba98c8281869940dc914c7ec24
|
7db575150995965b0578f3b7c68567e07f5317b7
|
/tr2/models/transformer.py
|
f3799d94287770125fd19476f059cc6c49ce70a5
|
[] |
no_license
|
anhdhbn/thesis-tr2
|
b14049cc3de517cdd9205239e4cf3d225d168e85
|
7a74bb1228f5493b37934f38a8d3e1ab5328fc3c
|
refs/heads/master
| 2023-03-27T21:51:57.763495
| 2021-02-26T12:51:20
| 2021-02-26T12:51:20
| 338,924,981
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,876
|
py
|
import torch
import torch.nn as nn
from torch import Tensor
from tr2.models.encoder import TransformerEncoder, TransformerEncoderLayer
from tr2.models.decoder import TransformerDecoder, TransformerDecoderLayer
class Transformer(nn.Module):
def __init__(self,
hidden_dims=512,
num_heads = 8,
num_encoder_layer=6,
num_decoder_layer=6,
dim_feed_forward=2048,
dropout=.1
):
super().__init__()
encoder_layer = TransformerEncoderLayer(
hidden_dims=hidden_dims,
num_heads=num_heads,
dropout=dropout,
dim_feedforward=dim_feed_forward
)
self.encoder = TransformerEncoder(
encoder_layer=encoder_layer,
num_layers=num_encoder_layer
)
decoder_layer = TransformerDecoderLayer(
hidden_dims=hidden_dims,
num_heads=num_heads,
dropout=dropout,
dim_feedforward=dim_feed_forward
)
decoder_layer2 = TransformerDecoderLayer(
hidden_dims=hidden_dims,
num_heads=num_heads,
dropout=dropout,
dim_feedforward=dim_feed_forward
)
self.decoder = TransformerDecoder(decoder_layer=decoder_layer, num_layers=num_decoder_layer)
self.decoder2 = TransformerDecoder(decoder_layer=decoder_layer2, num_layers=num_decoder_layer)
def _reset_parameters(self):
for p in self.parameters():
if p.dim() > 1:
nn.init.xavier_uniform_(p)
def forward(self, template: Tensor, mask_template: Tensor, pos_template: Tensor,
search: Tensor, mask_search: Tensor, pos_search:Tensor) -> Tensor:
"""
:param src: tensor of shape [batchSize, hiddenDims, imageHeight // 32, imageWidth // 32]
:param mask: tensor of shape [batchSize, imageHeight // 32, imageWidth // 32]
Please refer to detr.py for more detailed description.
:param query: object queries, tensor of shape [numQuery, hiddenDims].
:param pos: positional encoding, the same shape as src.
:return: tensor of shape [batchSize, num_decoder_layer * WH, hiddenDims]
"""
# flatten NxCxHxW to HWxNxC
bs, c, h, w = search.shape
template = template.flatten(2).permute(2, 0, 1) # HWxNxC
search = search.flatten(2).permute(2, 0, 1) # HWxNxC
mask_template = mask_template.flatten(1) # NxHW
mask_search = mask_search.flatten(1) # NxHW
pos_template = pos_template.flatten(2).permute(2, 0, 1) # HWxNxC
pos_search = pos_search.flatten(2).permute(2, 0, 1) # HWxNxC
memory = self.encoder(template, src_key_padding_mask=mask_template, pos=pos_template)
out = self.decoder(search, memory, memory_key_padding_mask=mask_template, pos_template=pos_template, pos_search=pos_search, tgt_key_padding_mask=mask_search) # num_decoder_layer x WH x N x C
out2 = self.decoder2(search, memory, memory_key_padding_mask=mask_template, pos_template=pos_template, pos_search=pos_search, tgt_key_padding_mask=mask_search) # num_decoder_layer x WH x N x C
return out.transpose(1, 2), out2.transpose(1, 2)
def init(self, template, mask_template, pos_template):
template = template.flatten(2).permute(2, 0, 1) # HWxNxC
mask_template = mask_template.flatten(1) # NxHW
pos_template = pos_template.flatten(2).permute(2, 0, 1) # HWxNxC
return self.encoder(template, src_key_padding_mask=mask_template, pos=pos_template)
def track(self, memory, mask_template, pos_template, search, mask_search, pos_search):
search = search.flatten(2).permute(2, 0, 1) # HWxNxC
mask_template = mask_template.flatten(1) # NxHW
mask_search = mask_search.flatten(1) # NxHW
pos_template = pos_template.flatten(2).permute(2, 0, 1) # HWxNxC
pos_search = pos_search.flatten(2).permute(2, 0, 1) # HWxNxC
out = self.decoder(search, memory, memory_key_padding_mask=mask_template, pos_template=pos_template, pos_search=pos_search, tgt_key_padding_mask=mask_search)
out2 = self.decoder2(search, memory, memory_key_padding_mask=mask_template, pos_template=pos_template, pos_search=pos_search, tgt_key_padding_mask=mask_search)
return out.transpose(1, 2), out2.transpose(1, 2)
def build_transformer(
hidden_dims=512,
num_heads = 8,
num_encoder_layer=6,
num_decoder_layer=6,
dim_feed_forward=2048,
dropout=.1
):
return Transformer(hidden_dims=hidden_dims,
num_heads = num_heads,
num_encoder_layer = num_encoder_layer,
num_decoder_layer = num_decoder_layer,
dim_feed_forward = dim_feed_forward,
dropout=dropout
)
|
[
"anhdhbn@gmail.com"
] |
anhdhbn@gmail.com
|
70b347db5fcd769831550b3fecad4822d3c19ea2
|
fe9573bad2f6452ad3e2e64539361b8bc92c1030
|
/Socket_programming/TLS_server.py
|
846eac13cb9e9873d922eb3e035275be919fb72a
|
[] |
no_license
|
OceanicSix/Python_program
|
e74c593e2e360ae22a52371af6514fcad0e8f41f
|
2716646ce02db00306b475bad97105b260b6cd75
|
refs/heads/master
| 2022-01-25T16:59:31.212507
| 2022-01-09T02:01:58
| 2022-01-09T02:01:58
| 149,686,276
| 1
| 2
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,090
|
py
|
#!/usr/bin/python3
import socket, ssl, pprint
html = """
HTTP/1.1 200 OK\r\nContent-Type: text/html\r\n\r\n
<!DOCTYPE html><html><body><h1>This is Bank32.com!</h1></body></html>
"""
SERVER_CERT = './certs/mycert.crt'
SERVER_PRIVATE = './certs/mycert.key'
# context = ssl.SSLContext(ssl.PROTOCOL_TLS_SERVER) # For Ubuntu 20.04 VM
context = ssl.SSLContext(ssl.PROTOCOL_TLSv1_2) # For Ubuntu 16.04 VM
context.load_cert_chain(SERVER_CERT, SERVER_PRIVATE)
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM, 0)
sock.bind(('0.0.0.0', 4433))
sock.listen(5)
while True:
newsock, fromaddr = sock.accept()
try:
ssock = context.wrap_socket(newsock, server_side=True)
print("TLS connection established")
data = ssock.recv(1024) # Read data over TLS
pprint.pprint("Request: {}".format(data))
ssock.sendall(html.encode('utf-8')) # Send data over TLS
ssock.shutdown(socket.SHUT_RDWR) # Close the TLS connection
ssock.close()
except Exception as e:
print("TLS connection fails")
print(e)
continue
|
[
"byan0007@student.monash.edu"
] |
byan0007@student.monash.edu
|
8f5307ec6a941ac8d84d56f251ad4dbd6cccadd2
|
d362a983e055984c588ee81c66ba17d536bae2f5
|
/backend/agent/migrations/0003_beautician.py
|
50fc77458670228cbb0dd38577ad9635cf06145d
|
[] |
no_license
|
prrraveen/Big-Stylist-CRM
|
1d770b5ad28f342dfc5d40002ddc3ee7cc6f840a
|
6cd84ce7b01a49a09b844c27ecc4575dcca54393
|
refs/heads/master
| 2021-01-10T04:37:43.414844
| 2015-12-15T10:47:21
| 2015-12-15T10:47:21
| 49,239,402
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,057
|
py
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('agent', '0002_service'),
]
operations = [
migrations.CreateModel(
name='Beautician',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('name', models.CharField(max_length=100)),
('gender', models.CharField(max_length=1, choices=[(b'M', b'Male'), (b'F', b'Female')])),
('marital_status', models.CharField(max_length=1, choices=[(b'M', b'married'), (b'S', b'Single')])),
('family_members', models.CharField(max_length=80, blank=True)),
('age', models.IntegerField(null=True, blank=True)),
('customer_rating', models.IntegerField(null=True, blank=True)),
('bs_rating', models.IntegerField(null=True, blank=True)),
('rating_by_service', models.IntegerField(null=True, blank=True)),
('phone_number', models.CharField(max_length=11)),
('alternate_number', models.CharField(max_length=11, blank=True)),
('address', models.CharField(max_length=1000, blank=True)),
('locality', models.CharField(max_length=100)),
('employment_status', models.CharField(blank=True, max_length=1, choices=[(b'0', b'Employed'), (b'1', b'Unemployed')])),
('availability', models.CharField(blank=True, max_length=2, choices=[(b'A', b'Available'), (b'NA', b'Single')])),
('Services', models.ManyToManyField(to='agent.Service', null=True, blank=True)),
('pincode', models.ForeignKey(related_name='beautician_pincode', blank=True, to='agent.Pincode', null=True)),
('serving_in', models.ManyToManyField(related_name='beautician_pincode_server_in', null=True, to='agent.Pincode', blank=True)),
],
),
]
|
[
"prrraveen@gmail.com"
] |
prrraveen@gmail.com
|
5c1167fe99ba3fb29255afa69fa05a2a94c03178
|
6c2d219dec81b75ac1aef7f96f4e072ed7562f81
|
/scenes/siteVogov.py
|
2501bf763ea4538e32f964cf4d904cf6f7aeb93f
|
[] |
no_license
|
SFTEAM/scrapers
|
7e2b0a159cb19907017216c16a976d630d883ba5
|
778f282bf1b6954aa06d265fdb6f2ecc2e3c8e47
|
refs/heads/main
| 2023-08-15T18:21:41.922378
| 2021-09-24T22:24:29
| 2021-09-24T22:24:29
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,781
|
py
|
import re
import scrapy
from tpdb.BaseSceneScraper import BaseSceneScraper
class VogovSpider(BaseSceneScraper):
name = 'Vogov'
network = 'Vogov'
parent = 'Vogov'
site = 'Vogov'
start_urls = [
'https://vogov.com'
]
selector_map = {
'title': '//meta[@property="og:title"]/@content',
'description': '//div[contains(@class,"info-video-description")]/p/text()',
'performers': '//div[contains(@class,"info-video-models")]/a/text()',
'date': '//li[contains(text(),"Release")]/span/text()',
'image': '//meta[@property="og:image"]/@content',
'tags': '//div[contains(@class,"info-video-category")]/a/text()',
'external_id': r'videos\/(.*)\/?',
'trailer': '//script[contains(text(),"video_url")]/text()',
'pagination': '/latest-videos/%s/'
}
def get_scenes(self, response):
scenes = response.xpath('//div[@class="video-post"]/div/a/@href').getall()
for scene in scenes:
yield scrapy.Request(url=self.format_link(response, scene), callback=self.parse_scene, meta={'site': 'Vogov'})
def get_trailer(self, response):
if 'trailer' in self.get_selector_map() and self.get_selector_map('trailer'):
trailer = self.process_xpath(
response, self.get_selector_map('trailer')).get()
trailer = re.search(r'video_url:\ .*?(https:\/\/.*?\.mp4)\/', trailer).group(1)
if trailer:
return trailer
return ''
def get_tags(self, response):
if self.get_selector_map('tags'):
tags = self.process_xpath(
response, self.get_selector_map('tags')).getall()
return list(map(lambda x: x.strip().title(), tags))
return []
|
[
"briadin@yahoo.com"
] |
briadin@yahoo.com
|
5e7f226554ea2fb5c3ea365c54d0f77bb1955e6d
|
180dc578d12fff056fce1ef8bd1ba5c227f82afc
|
/tensorflow_models/__init__.py
|
18eea8c6304e418deeb1b34e45a57fd437c81079
|
[
"Apache-2.0"
] |
permissive
|
jianzhnie/models
|
6cb96c873d7d251db17afac7144c4dbb84d4f1d6
|
d3507b550a3ade40cade60a79eb5b8978b56c7ae
|
refs/heads/master
| 2023-07-12T05:08:23.314636
| 2023-06-27T07:54:20
| 2023-06-27T07:54:20
| 281,858,258
| 2
| 0
|
Apache-2.0
| 2022-03-27T12:53:44
| 2020-07-23T05:22:33
|
Python
|
UTF-8
|
Python
| false
| false
| 909
|
py
|
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# 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 writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""TensorFlow Models Libraries."""
# pylint: disable=wildcard-import
from tensorflow_models import nlp
from tensorflow_models import vision
from official import core
from official.modeling import hyperparams
from official.modeling import optimization
from official.modeling import tf_utils as utils
|
[
"gardener@tensorflow.org"
] |
gardener@tensorflow.org
|
14bc7b551cf26a394151530e590ccdb32e250759
|
09e57dd1374713f06b70d7b37a580130d9bbab0d
|
/benchmark/startPyquil2701.py
|
b7aa787a468a8dbc6e74cfb46597078a617fc507
|
[
"BSD-3-Clause"
] |
permissive
|
UCLA-SEAL/QDiff
|
ad53650034897abb5941e74539e3aee8edb600ab
|
d968cbc47fe926b7f88b4adf10490f1edd6f8819
|
refs/heads/main
| 2023-08-05T04:52:24.961998
| 2021-09-19T02:56:16
| 2021-09-19T02:56:16
| 405,159,939
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,864
|
py
|
# qubit number=4
# total number=41
import pyquil
from pyquil.api import local_forest_runtime, QVMConnection
from pyquil import Program, get_qc
from pyquil.gates import *
import numpy as np
conn = QVMConnection()
def make_circuit()-> Program:
prog = Program() # circuit begin
prog += H(3) # number=32
prog += CZ(0,3) # number=33
prog += H(3) # number=34
prog += H(3) # number=26
prog += CZ(0,3) # number=27
prog += H(3) # number=28
prog += X(3) # number=24
prog += CNOT(0,3) # number=25
prog += CNOT(0,3) # number=12
prog += H(2) # number=29
prog += CZ(0,2) # number=30
prog += H(2) # number=31
prog += X(2) # number=21
prog += CNOT(0,2) # number=22
prog += H(1) # number=2
prog += H(2) # number=3
prog += H(3) # number=4
prog += H(0) # number=5
prog += Y(3) # number=36
prog += H(3) # number=16
prog += CZ(1,3) # number=17
prog += H(3) # number=18
prog += H(1) # number=6
prog += H(2) # number=37
prog += CNOT(1,0) # number=38
prog += Z(1) # number=39
prog += CNOT(1,0) # number=40
prog += H(2) # number=7
prog += H(3) # number=8
prog += H(0) # number=9
prog += CNOT(3,0) # number=13
prog += CNOT(3,0) # number=14
# circuit end
return prog
def summrise_results(bitstrings) -> dict:
d = {}
for l in bitstrings:
if d.get(l) is None:
d[l] = 1
else:
d[l] = d[l] + 1
return d
if __name__ == '__main__':
prog = make_circuit()
qvm = get_qc('4q-qvm')
results = qvm.run_and_measure(prog,1024)
bitstrings = np.vstack([results[i] for i in qvm.qubits()]).T
bitstrings = [''.join(map(str, l)) for l in bitstrings]
writefile = open("../data/startPyquil2701.csv","w")
print(summrise_results(bitstrings),file=writefile)
writefile.close()
|
[
"wangjiyuan123@yeah.net"
] |
wangjiyuan123@yeah.net
|
3811c8ded3c52d3c4297b523a72aef17f3e5b4ff
|
fe8bd31a416d7217c8b95d2ebf36158fdc0412de
|
/revscoring/languages/__init__.py
|
8076663b037c06ed1909940273411b71a9b88537
|
[
"MIT"
] |
permissive
|
nealmcb/revscoring
|
f0020a9009e584a0f59576adcdd16eadae21ee06
|
e5c889093c4f49443d12193a2da725065c87e6d6
|
refs/heads/master
| 2021-01-11T11:32:10.684223
| 2015-10-21T22:34:56
| 2015-10-21T22:34:56
| 44,418,672
| 0
| 0
| null | 2015-10-17T01:16:45
| 2015-10-17T01:16:45
| null |
UTF-8
|
Python
| false
| false
| 788
|
py
|
"""
This module implements a set of :class:`revscoring.Language`
-- collections of features that are language specific.
languages
+++++++++
.. automodule:: revscoring.languages.english
.. automodule:: revscoring.languages.french
.. automodule:: revscoring.languages.hebrew
.. automodule:: revscoring.languages.indonesian
.. automodule:: revscoring.languages.persian
.. automodule:: revscoring.languages.portuguese
.. automodule:: revscoring.languages.spanish
:members:
.. automodule:: revscoring.languages.turkish
:members:
.. automodule:: revscoring.languages.vietnamese
:members:
Base classes
++++++++++++
.. automodule:: revscoring.languages.language
.. automodule:: revscoring.languages.space_delimited
"""
from .language import Language
__all__ = [Language]
|
[
"aaron.halfaker@gmail.com"
] |
aaron.halfaker@gmail.com
|
7e3edaadd3fc130cc391da1bfd5cd75125fbd91d
|
78b7a0f04a92499d7c7479d22a6d6ed0494f51d4
|
/doc/future_bottumup.py
|
2f3208851514d1180279d9e67312187043ba02fe
|
[] |
no_license
|
duchesnay/pylearn-epac
|
5a6df8a68dc121ed6f87720250f24d927d553a04
|
70b0a85b7614b722ce40c506dfcb2e0c7dca8027
|
refs/heads/master
| 2021-01-21T00:16:09.693568
| 2013-07-23T10:21:56
| 2013-07-23T10:21:56
| 6,781,768
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 7,240
|
py
|
# -*- coding: utf-8 -*-
"""
Created on Thu May 23 15:21:35 2013
@author: ed203246
"""
from sklearn import datasets
from sklearn.svm import SVC
from sklearn.lda import LDA
from sklearn.feature_selection import SelectKBest
X, y = datasets.make_classification(n_samples=12, n_features=10,
n_informative=2)
from epac import Methods, Pipe
self = Methods(*[Pipe(SelectKBest(k=k), SVC(kernel=kernel, C=C)) for kernel in ("linear", "rbf") for C in [1, 10] for k in [1, 2]])
self = Methods(*[Pipe(SelectKBest(k=k), SVC(C=C)) for C in [1, 10] for k in [1, 2]])
import copy
self.fit_predict(X=X, y=y)
self.reduce()
[l.get_key() for l in svms.walk_nodes()]
[l.get_key(2) for l in svms.walk_nodes()] # intermediary key collisions: trig aggregation
"""
# Model selection using CV: CV + Grid
# -----------------------------------------
from epac import CVBestSearchRefit
# CV + Grid search of a simple classifier
wf = CVBestSearchRefit(*[SVC(C=C) for C in [1, 10]], n_folds=3)
wf.fit_predict(X=X, y=y)
wf.reduce()
"""
"""
import numpy as np
results_list = \
{'Methods/SelectKBest(k=1)/SVC(kernel=linear,C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=1)/SVC(kernel=linear,C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=1)/SVC(kernel=rbf,C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=1)/SVC(kernel=rbf,C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(kernel=linear,C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(kernel=linear,C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(kernel=rbf,C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(kernel=rbf,C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])}}
import numpy as np
run epac/utils.py
run epac/workflow/base.py
results_list=\
{'Methods/SelectKBest(k=1)/SVC(C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=1)/SVC(C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(C=1)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te': np.array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])},
'Methods/SelectKBest(k=2)/SVC(C=10)': {'pred_te': np.array([1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0]),
'score_te': 0.83333333333333337,
'score_tr': 0.83333333333333337,
'true_te':np. array([1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0])}}
"""
keys_splited = [key_split(key, eval_args=True) for key in results_list.keys()]
first = keys_splited[0]
arg_grids = list() # list of [depth_idx, arg_idx, arg_name, [arg_values]]
for i in xrange(len(first)):
if len(first[i]) > 1: # has arguments
for arg_idx in xrange(len(first[i][1])):
arg_grids.append([i, arg_idx, first[i][1][arg_idx][0],
[first[i][1][arg_idx][1]]])
# Check if Results can be stacked same depth, same node type a,d argument names
# An enumerate all possible arguments values
for other in keys_splited[1:]:
if len(first) != len(other):
print results_list.keys()
raise ValueError("Results cannot be stacked: different depth")
for i in xrange(len(first)):
if first[i][0] != other[i][0]:
print results_list.keys()
raise ValueError("Results cannot be stacked: nodes have different type")
if len(first[i]) > 1 and len(first[i][1]) != len(other[i][1]):
print results_list.keys()
raise ValueError("Results cannot be stacked: nodes have different length")
if len(first[i]) > 1: # has arguments
for arg_idx in xrange(len(first[i][1])):
if first[i][1][arg_idx][0] != other[i][1][arg_idx][0]:
print results_list.keys()
raise ValueError("Results cannot be stacked: nodes have"
"argument name")
values = [item for item in arg_grids if i==item[0] and \
arg_idx==item[1]][0][3]
values.append(other[i][1][arg_idx][1])
#values[i][1][arg_idx][1].append(other[i][1][arg_idx][1])
for grid in arg_grids:
grid[3] = set(grid[3])
arg_grids
@classmethod
def stack_results(list_of_dict, axis_name=None,
axis_values=[]):
"""Stack a list of Result(s)
Example
-------
>>> _list_of_dicts_2_dict_of_lists([dict(a=1, b=2), dict(a=10, b=20)])
{'a': [1, 10], 'b': [2, 20]}
"""
dict_of_list = dict()
for d in list_of_dict:
#self.children[child_idx].signature_args
#sub_aggregate = sub_aggregates[0]
for key2 in d.keys():
#key2 = sub_aggregate.keys()[0]
result = d[key2]
# result is a dictionary
if isinstance(result, dict):
if not key2 in dict_of_list.keys():
dict_of_list[key2] = dict()
for key3 in result.keys():
if not key3 in dict_of_list[key2].keys():
dict_of_list[key2][key3] = ListWithMetaInfo()
dict_of_list[key2][key3].axis_name = axis_name
dict_of_list[key2][key3].axis_values = axis_values
dict_of_list[key2][key3].append(result[key3])
else: # simply concatenate
if not key2 in dict_of_list.keys():
dict_of_list[key2] = ListWithMetaInfo()
dict_of_list[key2].axis_name = axis_name
dict_of_list[key2].axis_values = axis_values
dict_of_list[key2].append(result)
return dict_of_list
|
[
"edouard.duchesnay@gmail.com"
] |
edouard.duchesnay@gmail.com
|
2f6e31622147ccd5f16a2b68f420e3f8bf6471a0
|
c9c4536cebddfc3cc20f43084ccdb2ce1320b7e6
|
/experiments/utils.py
|
dfdf83bd5f97232f940217ba09e8103c9311d9a1
|
[
"MIT"
] |
permissive
|
jdc08161063/gym-miniworld
|
adaf03db39fc47b88dfc5faa4f3f9e926c7f25ca
|
4e96db30cb574c6e0eb5db33e83c68a979094a7f
|
refs/heads/master
| 2020-04-06T17:06:23.350527
| 2018-11-14T19:47:17
| 2018-11-14T19:47:17
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,863
|
py
|
from functools import reduce
import operator
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
class Print(nn.Module):
"""
Layer that prints the size of its input.
Used to debug nn.Sequential
"""
def __init__(self):
super(Print, self).__init__()
def forward(self, x):
print('layer input:', x.shape)
return x
class GradReverse(torch.autograd.Function):
"""
Gradient reversal layer
"""
def __init__(self, lambd=1):
self.lambd = lambd
def forward(self, x):
return x.view_as(x)
def backward(self, grad_output):
return (grad_output * -self.lambd)
def init_weights(m):
classname = m.__class__.__name__
if classname.startswith('Conv'):
nn.init.orthogonal_(m.weight.data)
m.bias.data.fill_(0)
elif classname.find('Linear') != -1:
nn.init.xavier_uniform_(m.weight)
m.bias.data.fill_(0)
elif classname.find('BatchNorm') != -1:
m.weight.data.normal_(1.0, 0.02)
m.bias.data.fill_(0)
def print_model_info(model):
modelSize = 0
for p in model.parameters():
pSize = reduce(operator.mul, p.size(), 1)
modelSize += pSize
print(str(model))
print('Total model size: %d' % modelSize)
def make_var(arr):
arr = np.ascontiguousarray(arr)
arr = torch.from_numpy(arr).float()
arr = Variable(arr)
if torch.cuda.is_available():
arr = arr.cuda()
return arr
def save_img(file_name, img):
from skimage import io
if isinstance(img, Variable):
img = img.data.numpy()
if len(img.shape) == 4:
img = img.squeeze(0)
img = img.astype(np.uint8)
io.imsave(file_name, img)
def load_img(file_name):
from skimage import io
# Drop the alpha channel
img = io.imread(file_name)
img = img[:,:,0:3] / 255
# Flip the image vertically
img = np.flip(img, 0)
# Transpose the rows and columns
img = img.transpose(2, 0, 1)
# Make it a batch of size 1
var = make_var(img)
var = var.unsqueeze(0)
return var
def gen_batch(gen_data_fn, batch_size=2):
"""
Returns a tuple of PyTorch Variable objects
gen_data is expected to produce a tuple
"""
assert batch_size > 0
data = []
for i in range(0, batch_size):
data.append(gen_data_fn())
# Create arrays of data elements for each variable
num_vars = len(data[0])
arrays = []
for idx in range(0, num_vars):
vals = []
for datum in data:
vals.append(datum[idx])
arrays.append(vals)
# Make a variable out of each element array
vars = []
for array in arrays:
var = make_var(np.stack(array))
vars.append(var)
return tuple(vars)
|
[
"maximechevalierb@gmail.com"
] |
maximechevalierb@gmail.com
|
127d350e935ff500677c170ab861f0343b28e635
|
e7b312b4cc3355f4ca98313ef2ac9f3b0d81f245
|
/abc/229/g/g.TLE.py
|
756dc1a784847d74805a2326514ab64db4f673f6
|
[] |
no_license
|
minus9d/programming_contest_archive
|
75466ab820e45ee0fcd829e6fac8ebc2accbbcff
|
0cb9e709f40460305635ae4d46c8ddec1e86455e
|
refs/heads/master
| 2023-02-16T18:08:42.579335
| 2023-02-11T14:10:49
| 2023-02-11T14:10:49
| 21,788,942
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,868
|
py
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
類題 https://tutorialspoint.com/program-to-find （YをN個連続させるのに必要な最小スワップ回数を求める）
を見つけたので、これを使って二分探索で解こうとしたが、TLE
類題のコードは理解していない
https://twitter.com/kyopro_friends/status/1464593018451750919
を参考にとき直すこと
"""
import array
from bisect import *
from collections import *
import fractions
import heapq
from itertools import *
import math
import random
import re
import string
import sys
sys.setrecursionlimit(10 ** 9)
# https://www.tutorialspoint.com/program-to-find-minimum-adjacent-swaps-for-k-consecutive-ones-in-python
def calc_swap_num(nums, k):
j = val = 0
ans = 10 ** 100
loc = []
for i, x in enumerate(nums):
if x:
loc.append(i)
m = (j + len(loc) - 1)//2
val += loc[-1] - loc[m] - (len(loc)-j)//2
if len(loc) - j > k:
m = (j + len(loc))//2
val -= loc[m] - loc[j] - (len(loc)-j)//2
j += 1
if len(loc)-j == k:
ans = min(ans, val)
return ans
def solve(S, K):
nums = []
for ch in S:
if ch == 'Y':
nums.append(1)
else:
nums.append(0)
max_ans = sum(nums)
# for i in range(1, max_ans + 1):
# print(i, calc_swap_num(nums, i))
if max_ans == 0:
return 0
tmp = calc_swap_num(nums, max_ans)
if tmp <= K:
return max_ans
lo = 1
hi = max_ans
while hi - lo > 1:
mid = (lo + hi) // 2
tmp = calc_swap_num(nums, mid)
if tmp <= K:
lo = mid
else:
hi = mid
return lo
S = input()
K = int(input())
print(solve(S, K))
|
[
"minus9d@gmail.com"
] |
minus9d@gmail.com
|
67d1f7cd8d7bbddc37fe4bfd3e34c2c84521cfa4
|
5a8f9d8d1cc47ae83546b0e11279b1d891798435
|
/enumerate_reversible.py
|
fcce362a8588dd9d6a470e2f099a5cfab00ea31f
|
[
"MIT"
] |
permissive
|
cjrh/enumerate_reversible
|
d81af841129adbad3a3d69a4955bfba202a174c7
|
d67044c78c1214c8749b60227d5c170d8c327770
|
refs/heads/master
| 2021-05-21T08:16:31.660568
| 2021-05-03T04:05:15
| 2021-05-03T04:05:15
| 252,613,686
| 0
| 0
|
MIT
| 2021-05-03T04:05:15
| 2020-04-03T02:27:01
|
Python
|
UTF-8
|
Python
| false
| false
| 438
|
py
|
original_enumerate = enumerate
def enumerate(iterable, start=0):
class Inner:
def __iter__(self):
yield from original_enumerate(iterable, start=start or 0)
def __reversed__(self):
stt = start or 0
rev = reversed(iterable) # First, for accurate exception msg
rng = range(len(iterable) - 1 + stt, -1 + stt, -1)
yield from zip(rng, rev)
return Inner()
|
[
"caleb.hattingh@gmail.com"
] |
caleb.hattingh@gmail.com
|
2b9e188a0d339e9e9ab6c6f43ca76d30a7100206
|
ca446c7e21cd1fb47a787a534fe308203196ef0d
|
/tests/graph/test_statement.py
|
4835355ef9be96cbb32485a349d98a91c0e3b83d
|
[
"MIT"
] |
permissive
|
critocrito/followthemoney
|
1a37c277408af504a5c799714e53e0f0bd709f68
|
bcad19aedc3b193862018a3013a66869e115edff
|
refs/heads/master
| 2020-06-12T09:56:13.867937
| 2019-06-28T08:23:54
| 2019-06-28T08:23:54
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,279
|
py
|
# from nose.tools import assert_raises
from unittest import TestCase
from followthemoney import model
from followthemoney.types import registry
from followthemoney.graph import Statement, Node
ENTITY = {
'id': 'test',
'schema': 'Person',
'properties': {
'name': 'Ralph Tester',
'birthDate': '1972-05-01',
'idNumber': ['9177171', '8e839023'],
'website': 'https://ralphtester.me',
'phone': '+12025557612',
'email': 'info@ralphtester.me',
'passport': 'passportEntityId'
}
}
class StatementTestCase(TestCase):
def test_base(self):
prop = model.get_qname('Thing:name')
node = Node(registry.entity, 'banana')
stmt = Statement(node, prop, "Theodore Böln")
assert stmt.subject == node
value = stmt.to_tuple()
other = stmt.from_tuple(model, value)
assert other == stmt, (stmt, other)
assert hash(other) == hash(stmt)
assert repr(other) == repr(stmt)
def test_invert(self):
prop = model.get_qname('Thing:name')
node = Node(registry.entity, 'banana')
stmt = Statement(node, prop, "Theodore")
assert not stmt.inverted
inv = stmt.invert()
assert inv.inverted
assert inv.rdf() is None
banana = Node(registry.entity, 'banana')
peach = Node(registry.entity, 'peach')
prop = model.get_qname('Thing:sameAs')
stmt = Statement(banana, prop, peach.value)
inv = stmt.invert()
assert inv.subject == peach
assert inv.value_node == banana
assert inv.prop == stmt.prop
def test_make_statements(self):
statements = list(model.get_proxy(ENTITY).statements)
assert len(statements) == 8, len(statements)
def test_rdf(self):
statements = list(model.get_proxy(ENTITY).statements)
triples = [l.rdf() for l in statements]
assert len(triples) == 8, len(triples)
for (s, p, o) in triples:
assert 'test' in s, s
if str(o) == 'Ralph Tester':
assert str(p) == 'http://www.w3.org/2004/02/skos/core#prefLabel' # noqa
if p == registry.phone:
assert str(o) == 'tel:+12025557612', o
# assert False, triples
|
[
"friedrich@pudo.org"
] |
friedrich@pudo.org
|
2d7d3d140684312694eeceace7b7556b9773c49c
|
2e22d14109f41ec84554a7994cd850619d73dc4d
|
/core/socketserver.py
|
acbb6e93f7ec0b453e50d8a8c82c25425d367983
|
[
"MIT"
] |
permissive
|
magus0219/clockwork
|
35cefeac77e68c1b5e12ab275b7fde18fd07edfc
|
78c08afdd14f226d7f5c13af633d41a2185ebb7f
|
refs/heads/master
| 2021-01-10T07:49:09.539766
| 2015-09-28T08:17:46
| 2015-09-28T08:17:46
| 43,036,160
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,035
|
py
|
# coding:utf-8
'''
Created on Feb 17, 2014
@author: magus0219
'''
import socket, logging, threading, pickle
from core.command import Command
def recv_until(socket, suffix):
'''
Receive message suffixed with specified char
@param socket:socket
@param suffix:suffix
'''
message = ''
while not message.endswith(suffix):
data = socket.recv(4096)
if not data:
raise EOFError('Socket closed before we see suffix.')
message += data
return message
class SocketServer(object):
'''
Socket Server
This socket server is started by clockwork server and only used to invoke methods
of JobManager
'''
def __init__(self, host, port, jobmanager):
'''
Constructor
'''
self.host = host
self.port = port
self.jobmanager = jobmanager
self.logger = logging.getLogger("Server.SocketThread")
def handleCommand(self, command):
'''
Handle one request command of client and return server's answer
@param command:Command to handle
This function return a Command object which contains result type and detail
information.
'''
cmd = command.cmd
try:
if cmd == Command.JOB_ADD:
jobid = int(command.data)
self.jobmanager.addJob(jobid)
return Command(Command.RESULT_SUCCESS, "Successful!")
elif cmd == Command.JOB_REMOVE:
jobid = int(command.data)
self.jobmanager.removeJob(jobid)
return Command(Command.RESULT_SUCCESS, "Successful!")
elif cmd == Command.JOB_RELOAD:
jobid = int(command.data)
self.jobmanager.reloadJob(jobid)
return Command(Command.RESULT_SUCCESS, "Successful!")
elif cmd == Command.TASK_RUN_IMMEDIATELY:
jobid, params = command.data
jobid = int(jobid)
task = self.jobmanager.spawnImmediateTask(jobid=jobid, params=params)
return Command(Command.RESULT_SUCCESS, "Successful!", task.get_taskid())
elif cmd == Command.TASK_CANCEL:
taskid = command.data
self.jobmanager.cancelTask(taskid)
return Command(Command.RESULT_SUCCESS, "Successful!")
elif cmd == Command.STATUS:
return Command(Command.RESULT_SUCCESS, self.jobmanager.getServerStatus())
except ValueError, e:
self.logger.exception(e)
return Command(Command.RESULT_FAIL, str(e))
def process(self, conn, address):
'''
Thread entry where new socket created
'''
self.logger.info("Accepted a connection from %s" % str(address))
self.logger.info("Socket connects %s and %s" % (conn.getsockname(), conn.getpeername()))
cmd = pickle.loads(recv_until(conn, '.'))
self.logger.info("Recieve Command:[%s]" % str(cmd))
while cmd.cmd != Command.EXIT:
conn.sendall(pickle.dumps(self.handleCommand(cmd)))
cmd = pickle.loads(recv_until(conn, '.'))
self.logger.info("Recieve Command:[%s]" % str(cmd))
self.logger.info("Socket is Over")
def start(self):
'''
Start the socket server and enter the main loop
'''
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
s.bind((self.host, self.port))
s.listen(10)
self.logger.info("SocketThread is Listening at %s:%s" % (self.host, str(self.port)))
while True:
conn, address = s.accept()
thread = threading.Thread(target=self.process, args=(conn, address))
thread.daemon = True
thread.start()
if __name__ == '__main__':
server = SocketServer("0.0.0.0", 3993)
server.start()
|
[
"magus0219@gmail.com"
] |
magus0219@gmail.com
|
d3c54bcbc564892dfd88c419f85921faa603d6a6
|
a6610e191090e216b0e0f23018cecc5181400a7a
|
/robotframework-ls/tests/robotframework_ls_tests/test_code_analysis.py
|
dd34aae67913ad1d119eaee83156b557a906088b
|
[
"Apache-2.0"
] |
permissive
|
JohanMabille/robotframework-lsp
|
d7c4c00157dd7c12ab15b7125691f7052f77427c
|
610f0257fdcd79b8c38107a0ecf600f60160bc1f
|
refs/heads/master
| 2023-01-19T10:29:48.982578
| 2020-11-25T13:46:22
| 2020-11-25T13:46:22
| 296,245,093
| 0
| 0
|
NOASSERTION
| 2020-09-17T06:58:54
| 2020-09-17T06:58:53
| null |
UTF-8
|
Python
| false
| false
| 5,420
|
py
|
def _collect_errors(workspace, doc, data_regression, basename=None, config=None):
from robotframework_ls.impl.completion_context import CompletionContext
from robotframework_ls.impl.code_analysis import collect_analysis_errors
completion_context = CompletionContext(doc, workspace=workspace.ws, config=config)
errors = [
error.to_lsp_diagnostic()
for error in collect_analysis_errors(completion_context)
]
data_regression.check(errors, basename=basename)
def test_keywords_analyzed(workspace, libspec_manager, data_regression):
workspace.set_root("case1", libspec_manager=libspec_manager)
doc = workspace.get_doc("case1.robot")
doc.source = doc.source + (
"\n This keyword does not exist" "\n [Teardown] Also not there"
)
_collect_errors(workspace, doc, data_regression)
def test_keywords_analyzed_templates(workspace, libspec_manager, data_regression):
workspace.set_root("case1", libspec_manager=libspec_manager)
doc = workspace.get_doc("case1.robot")
doc.source = """*** Settings ***
Test Template this is not there"""
_collect_errors(workspace, doc, data_regression)
def test_keywords_with_vars_no_error(workspace, libspec_manager, data_regression):
workspace.set_root("case1", libspec_manager=libspec_manager)
doc = workspace.get_doc("case1.robot")
doc.source = (
doc.source
+ """
I check ls
I execute "ls" rara "-lh"
*** Keywords ***
I check ${cmd}
Log ${cmd}
I execute "${cmd}" rara "${opts}"
Log ${cmd} ${opts}
"""
)
_collect_errors(workspace, doc, data_regression)
def test_keywords_with_prefix_no_error(workspace, libspec_manager, data_regression):
workspace.set_root("case1", libspec_manager=libspec_manager)
doc = workspace.get_doc("case1.robot")
# Ignore bdd-related prefixes (see: robotframework_ls.impl.robot_constants.BDD_PREFIXES)
doc.source = (
doc.source
+ """
given I check ls
then I execute
*** Keywords ***
I check ${cmd}
Log ${cmd}
I execute
Log foo
"""
)
_collect_errors(workspace, doc, data_regression, basename="no_error")
def test_keywords_prefixed_by_library(workspace, libspec_manager, data_regression):
workspace.set_root("case4", libspec_manager=libspec_manager)
doc = workspace.get_doc("case4.robot")
doc.source = """*** Settings ***
Library String
Library Collections
Resource case4resource.txt
*** Test Cases ***
Test
BuiltIn.Log Logging
case4resource3.Yet Another Equal Redefined
String.Should Be Titlecase Hello World
${list}= BuiltIn.Create List 1 2
Collections.Append To List ${list} 3"""
_collect_errors(workspace, doc, data_regression, basename="no_error")
def test_keywords_prefixed_with_alias(workspace, libspec_manager, data_regression):
workspace.set_root("case4", libspec_manager=libspec_manager)
doc = workspace.get_doc("case4.robot")
doc.source = """*** Settings ***
Library Collections WITH NAME Col1
*** Test Cases ***
Test
Col1.Append To List ${list} 3"""
_collect_errors(workspace, doc, data_regression, basename="no_error")
def test_keywords_name_matches(workspace, libspec_manager, data_regression):
workspace.set_root("case4", libspec_manager=libspec_manager)
doc = workspace.get_doc("case4.robot")
doc.source = """*** Settings ***
Library Collections
*** Test Cases ***
Test
AppendToList ${list} 3"""
_collect_errors(workspace, doc, data_regression, basename="no_error")
def test_resource_does_not_exist(workspace, libspec_manager, data_regression):
workspace.set_root("case4", libspec_manager=libspec_manager)
doc = workspace.get_doc("case4.robot")
doc.source = """*** Settings ***
Library DoesNotExist
Library .
Library ..
Library ../
Resource does_not_exist.txt
Resource ${foo}/does_not_exist.txt
Resource ../does_not_exist.txt
Resource .
Resource ..
Resource ../
Resource ../../does_not_exist.txt
Resource case4resource.txt
*** Test Cases ***
Test
case4resource3.Yet Another Equal Redefined"""
from robotframework_ls.robot_config import RobotConfig
config = RobotConfig()
# Note: we don't give errors if we can't resolve a resource.
_collect_errors(workspace, doc, data_regression, basename="no_error", config=config)
def test_casing_on_filename(workspace, libspec_manager, data_regression):
from robocorp_ls_core.protocols import IDocument
from pathlib import Path
# i.e.: Importing a python library with capital letters fails #143
workspace.set_root("case4", libspec_manager=libspec_manager)
doc: IDocument = workspace.get_doc("case4.robot")
p = Path(doc.path)
(p.parent / "myPythonKeywords.py").write_text(
"""
class myPythonKeywords(object):
ROBOT_LIBRARY_VERSION = 1.0
def __init__(self):
pass
def Uppercase_Keyword (self):
return "Uppercase does not work"
"""
)
doc.source = """*** Settings ***
Library myPythonKeywords.py
*** Test Cases ***
Test
Uppercase Keyword"""
from robotframework_ls.robot_config import RobotConfig
config = RobotConfig()
# Note: we don't give errors if we can't resolve a resource.
_collect_errors(workspace, doc, data_regression, basename="no_error", config=config)
|
[
"fabiofz@gmail.com"
] |
fabiofz@gmail.com
|
9ddff1fa09a2a5c49b82729b44d4140b40e1fa55
|
cbdbb05b91a4463639deefd44169d564773cd1fb
|
/djangoproj/pos/invoices/migrations/0011_auto_20150718_0908.py
|
d24848402c8400bd25b51f8bef05d5d93aff8b99
|
[] |
no_license
|
blazprog/py3
|
e26ef36a485809334b1d5a1688777b12730ebf39
|
e15659e5d5a8ced617283f096e82135dc32a8df1
|
refs/heads/master
| 2020-03-19T20:55:22.304074
| 2018-06-11T12:25:18
| 2018-06-11T12:25:18
| 136,922,662
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 684
|
py
|
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('invoices', '0010_artikel_davek'),
]
operations = [
migrations.AddField(
model_name='racunpozicija',
name='txtNazivArtikla',
field=models.CharField(max_length=25, default='naziv'),
preserve_default=False,
),
migrations.AddField(
model_name='racunpozicija',
name='txtSifraArtikla',
field=models.CharField(max_length=5, default='sifra'),
preserve_default=False,
),
]
|
[
"blaz.korosec@mentis.si"
] |
blaz.korosec@mentis.si
|
5416209788d81dbbb8263cbf9614f1608d323758
|
03bf031efc1f171f0bb3cf8a565d7199ff073f96
|
/utils/admin.py
|
ad5b99e1ae02e5c6358ca6949bc8b89a84e33e2a
|
[
"MIT"
] |
permissive
|
emilps/onlineweb4
|
a213175678ac76b1fbede9b0897c538c435a97e2
|
6f4aca2a4522698366ecdc6ab63c807ce5df2a96
|
refs/heads/develop
| 2020-03-30T01:11:46.941170
| 2019-05-10T19:49:21
| 2019-05-10T19:49:21
| 150,564,330
| 0
| 0
|
MIT
| 2019-05-10T19:49:22
| 2018-09-27T09:43:32
|
Python
|
UTF-8
|
Python
| false
| false
| 802
|
py
|
from django.contrib import admin
class DepositWithdrawalFilter(admin.SimpleListFilter):
"""
A simple filter to select deposits, withdrawals or empty transactions
"""
title = 'Transaction type'
parameter_name = 'amount'
def lookups(self, request, model_admin):
"""
Tuples with values for url and display term
"""
return (
('positive', 'Deposit'),
('negative', 'Withdrawal'),
('empty', 'Empty')
)
def queryset(self, request, queryset):
if self.value() == 'positive':
return queryset.filter(amount__gt=0)
if self.value() == 'negative':
return queryset.filter(amount__lt=0)
if self.value() == 'empty':
return queryset.filter(amount=0)
|
[
"hlsolbjorg@gmail.com"
] |
hlsolbjorg@gmail.com
|
12ada9555cc15be06cd931a4408c0bd361b6eb02
|
caf8cbcafd448a301997770165b323438d119f5e
|
/.history/chapter01/python_05_if_condition_20201128214052.py
|
9ee4357bc39e5526dabfbdaecafa8175ebd0349b
|
[
"MIT"
] |
permissive
|
KustomApe/nerdape
|
03e0691f675f13ce2aefa46ee230111247e90c72
|
aef6fb2d1f8c364b26d91bf8570b4487a24de69a
|
refs/heads/main
| 2023-01-23T10:13:26.584386
| 2020-11-28T22:29:49
| 2020-11-28T22:29:49
| 309,897,105
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 977
|
py
|
"""[if文について]
もし〜だったら、こうして
"""
# if 条件:
# 実行するブロック
# 条件によって処理を適応したい場合
# 3000kmごとにオイル交換しないといけない
distance = 3403
# if distance > 3000:
# print('オイル交換時期です')
total = 123200
average = total / 3
print(average)
if average > 3000:
print('オイル交換時期ですよ！')
# 文字列を比較する/リストを比較する
# if 'abc' == "ABC":
# print('同類です')
# if 'CDE' == 'CDE':
# print('同類です')
# if 'あいうえお' == 'あいうえお':
# print('同類です')
# 文字列を検索する/リストの要素を検索する
# if 'abc' in "ABC":
# print('ヒットしました！')
# if 'ドリフト' in '僕はドリフトが好きです':
# print('ヒットしました！')
# if 'japan' in 'japanese domestic market vehicle':
# print('ヒットしました！')
# else文
# elif文
|
[
"kustomape@gmail.com"
] |
kustomape@gmail.com
|
e68d1c40e9032cb0617ca2a03de48c33736f012f
|
9bd1daa53a7e5d65d4f7a3558f11d06006ecb000
|
/conditioner/tests/actions/factories.py
|
f744f19bb34a5f1c829d51e2f8696013d030116f
|
[
"MIT"
] |
permissive
|
pombredanne/django-conditioner
|
55b01ac8e42a8e2c73025934c39aa72ee478c333
|
d5d2ad1f016bc3e6b34c74ff68cd024e8fad5125
|
refs/heads/master
| 2020-09-25T21:16:29.274170
| 2017-03-17T08:34:00
| 2017-03-17T08:34:00
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 988
|
py
|
"""
Conditioner module actions related factories
"""
import random
import factory
from faker import Factory as FakerFactory
from conditioner.actions import LoggerAction, SendTemplatedEmailAction
from conditioner.tests.factories import BaseActionFactory
faker = FakerFactory.create()
class LoggerActionFactory(BaseActionFactory):
"""
Factory for `conditioner.actions.misc.LoggerAction` model
"""
level = random.choice(LoggerAction.LEVEL_CHOICES)[0]
message = factory.LazyAttribute(lambda n: faker.paragraph())
class Meta:
model = LoggerAction
class SendTemplatedEmailActionFactory(BaseActionFactory):
"""
Factory for `conditioner.actions.common.SendTemplatedEmailAction` model
"""
email = factory.LazyAttribute(lambda n: faker.email())
subject = factory.LazyAttribute(lambda n: faker.sentence())
template = factory.LazyAttribute(lambda n: faker.uri_path() + '.txt')
class Meta:
model = SendTemplatedEmailAction
|
[
"pawel.ad@gmail.com"
] |
pawel.ad@gmail.com
|
1129328bacebf961f72d0c0b6cf180bcc0d9483c
|
ee6fb9095faef4c88848f5f769b296f672d37cd0
|
/photomosaic/imgutils.py
|
791cb03f378176e1dbb5c88b361c085704f9beeb
|
[] |
no_license
|
cosmozhang1995/photo-mosaic
|
76ca2846db0eefd6d7ded117fec1b2ac06e823ea
|
f5c57a9765887aeeb65804c5597727646b945814
|
refs/heads/master
| 2022-07-10T14:13:10.605884
| 2020-02-14T08:51:08
| 2020-02-14T08:51:08
| 240,463,724
| 0
| 0
| null | 2022-06-22T01:05:54
| 2020-02-14T08:41:38
|
Python
|
UTF-8
|
Python
| false
| false
| 600
|
py
|
import cv2
import numpy as np
def resize_cut(srcimg, dstsize):
dstheight, dstwidth = dstsize
img = srcimg
imgheight, imgwidth = img.shape[:2]
sc = max(dstheight/imgheight, dstwidth/imgwidth)
imgsize = (int(np.ceil(imgheight*sc)), int(np.ceil(imgwidth*sc)))
img = cv2.resize(img, (imgsize[1], imgsize[0]))
imgheight, imgwidth = img.shape[:2]
imgcut = (int((imgheight-dstheight)/2), int((imgwidth-dstwidth)/2))
imgcuttop, imgcutleft = imgcut
imgcutbottom, imgcutright = (imgcuttop + dstheight, imgcutleft + dstwidth)
img = img[imgcuttop:imgcutbottom, imgcutleft:imgcutright, :]
return img
|
[
"cosmozhang1995@gmail.com"
] |
cosmozhang1995@gmail.com
|
b4ffb6e7aa7720bf94408c4205e0d631a33ccac7
|
c7d7bafdff29a9e0f91bec25e88b8db1b6694643
|
/firebot/modules/mf.py
|
37002a949a6c8212931fce04e72ad19042a64323
|
[
"MIT"
] |
permissive
|
ultra-noob/Vivek-UserBot
|
ebedb80d98ca72fe1167211c14e32c017fcdf903
|
6c371a4aaa0c05397efa36237e9a2118deeb0d91
|
refs/heads/main
| 2023-07-11T16:52:37.696359
| 2021-08-11T03:38:15
| 2021-08-11T03:38:15
| 394,882,145
| 0
| 1
| null | 2021-08-11T06:11:45
| 2021-08-11T06:11:45
| null |
UTF-8
|
Python
| false
| false
| 2,724
|
py
|
import sys
from telethon import __version__, functions
from firebot import CMD_HELP
from firebot.utils import fire_on_cmd
@fire.on(fire_on_cmd(pattern="mf ?(.*)", allow_sudo=True)) # pylint:disable=E0602
async def _(event):
if event.fwd_from:
return
splugin_name = event.pattern_match.group(1)
if splugin_name in borg._modules:
s_help_string = borg._modules[splugin_name].__doc__
else:
s_help_string = ""
help_string = """
......................................../´¯/)
......................................,/¯../
...................................../..../
..................................../´.¯/
..................................../´¯/
..................................,/¯../
................................../..../
................................./´¯./
................................/´¯./
..............................,/¯../
............................./..../
............................/´¯/
........................../´¯./
........................,/¯../
......................./..../
....................../´¯/
....................,/¯../
.................../..../
............./´¯/'...'/´¯¯`·¸
........../'/.../..../......./¨¯\
........('(...´...´.... ¯~/'...')
.........\.................'...../
..........''...\.......... _.·´
............\..............(
..............\.............\...
""".format(
sys.version, __version__
)
tgbotusername = Config.TG_BOT_USER_NAME_BF_HER # pylint:disable=E0602
if tgbotusername is not None:
results = await borg.inline_query( # pylint:disable=E0602
tgbotusername, help_string + "\n\n" + s_help_string
)
await results[0].click(
event.chat_id, reply_to=event.reply_to_msg_id, hide_via=True
)
await event.delete()
else:
await event.reply(help_string + "\n\n" + s_help_string)
await event.delete()
@fire.on(fire_on_cmd(pattern="dc")) # pylint:disable=E0602
async def _(event):
if event.fwd_from:
return
result = await borg(functions.help.GetNearestDcRequest()) # pylint:disable=E0602
await event.edit(result.stringify())
@fire.on(fire_on_cmd(pattern="config")) # pylint:disable=E0602
async def _(event):
if event.fwd_from:
return
result = await borg(functions.help.GetConfigRequest()) # pylint:disable=E0602
result = result.stringify()
logger.info(result) # pylint:disable=E0602
await event.edit("""Telethon UserBot powered by @UniBorg""")
CMD_HELP.update(
{
"mf": "**Mf**\
\n\n**Syntax : **`.mf`\
\n**Usage :** funny plugin.\
\n\n**Syntax : **`.dc`\
\n**Usage :** shows nearest Dc."
}
)
|
[
"noreply@github.com"
] |
ultra-noob.noreply@github.com
|
98ad144923dfcbae14b423be115a14fbb1c611c4
|
150464efa69db3abf328ef8cd912e8e248c633e6
|
/_4.python/__code/Pythoneer-master/Jumbled Word/Jumbled(withouttkinter).py
|
7211039e1c6397134008308e8017b3165e1a9494
|
[] |
no_license
|
bunshue/vcs
|
2d194906b7e8c077f813b02f2edc70c4b197ab2b
|
d9a994e3afbb9ea84cc01284934c39860fea1061
|
refs/heads/master
| 2023-08-23T22:53:08.303457
| 2023-08-23T13:02:34
| 2023-08-23T13:02:34
| 127,182,360
| 6
| 3
| null | 2023-05-22T21:33:09
| 2018-03-28T18:33:23
|
C#
|
UTF-8
|
Python
| false
| false
| 1,397
|
py
|
import os
import sys
from collections import defaultdict
print " ";
print "................................Jumbled ......................................";
print "NOTE : Please make sure, you enter all the letters necessary to make the word!";
print " ";
print " ";
word = input("Enter the word: ")
print " ";
#word = sys.argv[1]
word1 = word
#print word1
leng=len(word)
no = leng
chek=''
dict = defaultdict(list)
#word = input("Enter the : ")
word = word.lower()
word = sorted(word)
word = ''.join(word)
word = "\n"+word
word = word.replace(" ", "")
file = open("C:\Python27\Jumbled\Dictionary.txt", "r")
line = file.readline()
print " "
count = 0;
while line:
if(line!=None):
line = file.readline()
j = line
line = sorted(line)
line = ''.join(line)
j = ''.join(j)
k = sorted(j)
k = ''.join(k)
k = k.lower()
if (word==k):
if(count<1):
print "Solution : "+j+"\n",
count=count+1;
if(count>1):
print "Another Combnation : "+j
if(j=="mazahir"):
print "'Mazahir' here! :), Hope you liked my program :D"
#dict[word].append(k)
file.close()
fo = open("C:/Mazahir/now.txt", "w")
line = fo.write( j )
fo.close()
file = open("C:/Mazahir/now1.txt", "w")
file.write( str(no) )
file.close()
|
[
"david@insighteyes.com"
] |
david@insighteyes.com
|
7e6c1f50001acdca960cd972aca451db26803155
|
68ea05d0d276441cb2d1e39c620d5991e0211b94
|
/1940.py
|
a6e8f345cdc993bcae8b3a828ab9b0865b506f3b
|
[] |
no_license
|
mcavalca/uri-python
|
286bc43aa157d3a6880dc222e0136c80cf079565
|
e22875d2609fe7e215f9f3ed3ca73a1bc2cf67be
|
refs/heads/master
| 2021-11-23T08:35:17.614443
| 2021-10-05T13:26:03
| 2021-10-05T13:26:03
| 131,339,175
| 50
| 27
| null | 2021-11-22T12:21:59
| 2018-04-27T19:54:09
|
Python
|
UTF-8
|
Python
| false
| false
| 236
|
py
|
j, r = [int(x) for x in input().split()]
entrada = list(map(int, input().split()))
pontos = [0] * j
for k in range(j):
pontos[k] = sum(entrada[k::j])
pontos = pontos[::-1]
vencedor = j - pontos.index(max(pontos))
print(vencedor)
|
[
"m.cavalca@hotmail.com"
] |
m.cavalca@hotmail.com
|
6a26301089da81a8e292227e32da92a3e05f82e2
|
f7d343efc7b48818cac4cf9b98423b77345a0067
|
/training/Permutations.py
|
10acfdf1568289dd3b55bcf473e76239ead669a4
|
[] |
no_license
|
vijaymaddukuri/python_repo
|
70e0e24d0554c9fac50c5bdd85da3e15c6f64e65
|
93dd6d14ae4b0856aa7c6f059904cc1f13800e5f
|
refs/heads/master
| 2023-06-06T02:55:10.393125
| 2021-06-25T16:41:52
| 2021-06-25T16:41:52
| 151,547,280
| 0
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 845
|
py
|
def permutations1(string):
def factorial(n):
fact=1
for i in range(1,n+1):
fact=fact*i
return fact
repeat=len(string)-len(''.join(set(string)))
n=factorial(len(string))
k=factorial(repeat)
loop=n/(k**repeat)
final=[]
j=0
for i in range(loop):
if i>=2:
j=0
else:
j+=1
new = string[j-1:] + string[j-1:]
final.append(new)
string=new
return final
return loop
def permutations(string):
result = set(string)
if len(string) == 2:
result.add(string[1] + string[0])
elif len(string) > 2:
for i, c in enumerate(string):
for s in permutations(string[:i] + string[i + 1:]):
result.add(c + s)
return list(result)
a='abc'
per=permutations(a)
print(per)
|
[
"Vijay.Maddukuri@virtustream.com"
] |
Vijay.Maddukuri@virtustream.com
|
e48b80cea00aad77f599556a86f3688235cc9a93
|
6cfa568e2012dde5c86265226b0dd3a49849c7f7
|
/website_sale_booking/__openerp__.py
|
6573e2e4ae8e491f0af198340e85248ca9f2cfc3
|
[] |
no_license
|
arinno/odoo-website-sale-booking
|
c48771ee30dc8791656a7a9d75efa14fe07f88bc
|
dd2e45873e64ad0f5bdd24a23d905b70702cd85a
|
refs/heads/master
| 2021-01-09T06:23:01.904899
| 2017-02-05T07:10:21
| 2017-02-05T07:10:21
| 80,975,669
| 0
| 0
| null | 2017-02-05T07:06:24
| 2017-02-05T07:06:24
| null |
UTF-8
|
Python
| false
| false
| 425
|
py
|
{
'name': 'Website Booking System',
'category': 'sale',
'description':"""
OpenERP Website Booking System view.
==========================
""",
'version': '1.0',
'js': [
],
'css': [
],
'author': 'Vertel AB',
'website': 'http://www.vertel.se',
'depends': ['website', 'product', 'hr_contract', 'resource'],
'data': ['view/website_sale_booking.xml'],
'installable': True,
}
|
[
"apollo_zhj@msn.com"
] |
apollo_zhj@msn.com
|
883364571d231534b05121da2095291109c936e8
|
9743d5fd24822f79c156ad112229e25adb9ed6f6
|
/xai/brain/wordbase/adjectives/_handpicked.py
|
d8b02e24092556f8401358860df23874bd852d2b
|
[
"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
| 448
|
py
|
#calss header
class _HANDPICKED():
def __init__(self,):
self.name = "HANDPICKED"
self.definitions = [u'Someone who is handpicked has been carefully chosen for a special job or purpose: ']
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.specie = 'adjectives'
def run(self, obj1, obj2):
self.jsondata[obj2] = {}
self.jsondata[obj2]['properties'] = self.name.lower()
return self.jsondata
|
[
"xingwang1991@gmail.com"
] |
xingwang1991@gmail.com
|
e7694b0db2814d86d4fe4e4c05b90604614b2138
|
91f30c829664ff409177e83776c9f4e2e98d9fc4
|
/apps/events/migrations/0002_auto_20180607_0411.py
|
0436f1e6422da2a9e882d0161aa9c56529c7231f
|
[] |
no_license
|
TotalityHacks/madras
|
3ac92dc6caf989efcb02590f6474ab333d1f93fa
|
2395a703eed1a87cca3cdd6c0fb9162b69e8df27
|
refs/heads/master
| 2021-08-17T15:29:41.055074
| 2018-07-18T23:05:29
| 2018-07-18T23:05:29
| 105,232,414
| 4
| 5
| null | 2021-03-31T18:58:56
| 2017-09-29T05:13:41
|
Python
|
UTF-8
|
Python
| false
| false
| 581
|
py
|
# -*- coding: utf-8 -*-
# Generated by Django 1.11.5 on 2018-06-07 04:11
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('events', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='event',
name='description',
field=models.TextField(),
),
migrations.AlterField(
model_name='event',
name='title',
field=models.CharField(max_length=40),
),
]
|
[
"ezwang1@gmail.com"
] |
ezwang1@gmail.com
|
d4cb34b70a91e2240a08ad427a015525c61d1b39
|
7f8db5b974a747632729d16c431de7aca007af00
|
/0x11-python-network_1/8-json_api.py
|
482167a08bb420f6d28ad7b10c9d98d4c2ec9cbe
|
[] |
no_license
|
thomasmontoya123/holbertonschool-higher_level_programming
|
6f5ceb636167efba1e36ed2dee7bf83b458f6751
|
48b7c9dccac77ccb0f57da1dc1d150f356612b13
|
refs/heads/master
| 2020-07-22T22:31:13.744490
| 2020-02-13T22:54:17
| 2020-02-13T22:54:17
| 207,351,235
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 594
|
py
|
#!/usr/bin/python3
'''sends a POST request with the letter as a parameter.'''
if __name__ == "__main__":
import requests
from sys import argv
url = 'http://0.0.0.0:5000/search_user'
if len(argv) == 2:
values = {'q': argv[1]}
result = requests.post(url, data=values)
try:
json = result.json()
if json:
print("[{}] {}".format(json.get("id"), json.get("name")))
else:
print("No result")
except Exception:
print("Not a valid JSON")
else:
print("No result")
|
[
"tomasmontoya123@gmail.com"
] |
tomasmontoya123@gmail.com
|
43f78419297092954ae2d68c3e9a6c3cdeb59b73
|
8bb2842aa73676d68a13732b78e3601e1305c4b2
|
/1920.py
|
5ce8ca2d8ffeda7120bfef402770ca16c94a7353
|
[] |
no_license
|
Avani18/LeetCode
|
239fff9c42d2d5703c8c95a0efdc70879ba21b7d
|
8cd61c4b8159136fb0ade96a1e90bc19b4bd302d
|
refs/heads/master
| 2023-08-24T22:25:39.946426
| 2021-10-10T20:36:07
| 2021-10-10T20:36:07
| 264,523,162
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 277
|
py
|
# Build Array from Permutation
class Solution(object):
def buildArray(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
ans = []
for i in range(len(nums)):
ans.append(nums[nums[i]])
return ans
|
[
"noreply@github.com"
] |
Avani18.noreply@github.com
|
3323c4ec71a8a7d1a3ac28964a61aeacbeb33fd6
|
196eb2f5e3366987d7285bf980ac64254c4aec16
|
/supervised/util.py
|
4dbf6da6ffafcd128d865320bca7ad87e38b8408
|
[
"MIT"
] |
permissive
|
mfouda/codenames
|
f54e0c4366edbf65251aadefddef1fda6cd7de9d
|
ccd0bd7578b3deedeec60d0849ec4ebca48b6426
|
refs/heads/master
| 2022-01-07T02:03:42.529978
| 2018-12-21T13:16:27
| 2018-12-21T13:16:27
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 595
|
py
|
import time
import matplotlib.pyplot as plt
plt.switch_backend('agg')
import matplotlib.ticker as ticker # noqa: E402
def as_minutes(s):
m = s // 60
s -= m * 60
return '%dm %ds' % (m, s)
def time_since(since, percent):
now = time.time()
s = now - since
es = s / percent
rs = es - s
return '%s (- %s)' % (as_minutes(s), as_minutes(rs))
def show_plot(points):
plt.figure()
fig, ax = plt.subplots()
# this locator puts ticks at regular intervals
loc = ticker.MultipleLocator(base=0.2)
ax.yaxis.set_major_locator(loc)
plt.plot(points)
|
[
"lukas.jendele@gmail.com"
] |
lukas.jendele@gmail.com
|
7b80ef96fa22fd633d5e959b647de4b9f16faedc
|
c7f98de17088cb4df6c171f1e76614beb1f4e0f7
|
/modules/vulnerability-analysis/w3af.py
|
73cb1fc29cbd307d7038d2d133f512666a097029
|
[] |
no_license
|
fryjustinc/ptf
|
6262ca5b94a43a51e984d3eee1649a16584b597b
|
ba85f9e867b65b4aa4f06b6232207aadac9782c9
|
refs/heads/master
| 2020-03-31T09:43:44.474563
| 2018-10-08T18:39:03
| 2018-10-08T18:39:03
| 152,107,950
| 0
| 0
| null | 2018-10-08T16:00:37
| 2018-10-08T16:00:37
| null |
UTF-8
|
Python
| false
| false
| 244
|
py
|
#!/usr/bin/env python
#####################################
# Installation module for w3af
#####################################
AUTHOR="Justin Fry"
INSTALL_TYPE="GIT"
REPOSITORY_LOCATION="https://github.com/andresriancho/w3af"
LAUNCHER="w3af"
|
[
"fryjustinc@gmail.com"
] |
fryjustinc@gmail.com
|
47bcf163541fb59722252c3f339c87df5bc27d1b
|
a8a5772674e62beaa4f5b1f115d280103fd03749
|
/metstationdistance.py
|
06718ded3fcc86dd7af918765369d469f2ed4e6b
|
[] |
no_license
|
tahentx/pv_workbook
|
c6fb3309d9acde5302dd3ea06a34ad2aee0de4b7
|
08912b0ef36a5226d23fa0430216a3f277aca33b
|
refs/heads/master
| 2022-12-12T20:39:35.688510
| 2021-03-30T03:20:54
| 2021-03-30T03:20:54
| 172,827,250
| 0
| 1
| null | 2022-12-08T16:47:39
| 2019-02-27T02:25:24
|
Python
|
UTF-8
|
Python
| false
| false
| 591
|
py
|
import csv
from haversine import haversine
with open('tucson.csv') as file:
has_header = csv.Sniffer().has_header(file.read(1024))
file.seek(0)
met = csv.reader(file)
if has_header:
next(met)
met_list = list(met)
coords = []
for x in met_list:
coords.append(x[1:])
print(coords)
#
# def find_backup_metstation(coordinates: list) -> list:
# backup_mets = []
# for i in range(len(coordinates)-1):
# backup_mets.append(haversine(coordinates[i], coordinates[i + 1],unit='mi'))
# print(type(coordinates[i]))
#
# find_backup_metstation(coords)
|
[
"hendricks.ta@gmail.com"
] |
hendricks.ta@gmail.com
|
ce1d4c9f9dae392dbcd0c9e6cec095469f9b8092
|
0fccee4c738449f5e0a8f52ea5acabf51db0e910
|
/genfragments/ThirteenTeV/BulkGraviton/BulkGraviton_VBF_WW_inclu_narrow_M4000_13TeV-madgraph_cff.py
|
2bcf409e757355e8832799dc74ad7539b4678a06
|
[] |
no_license
|
cms-sw/genproductions
|
f308ffaf3586c19b29853db40e6d662e937940ff
|
dd3d3a3826343d4f75ec36b4662b6e9ff1f270f4
|
refs/heads/master
| 2023-08-30T17:26:02.581596
| 2023-08-29T14:53:43
| 2023-08-29T14:53:43
| 11,424,867
| 69
| 987
| null | 2023-09-14T12:41:28
| 2013-07-15T14:18:33
|
Python
|
UTF-8
|
Python
| false
| false
| 797
|
py
|
import FWCore.ParameterSet.Config as cms
# link to cards:
# https://github.com/cms-sw/genproductions/tree/91ab3ea30e3c2280e4c31fdd7072a47eb2e5bdaa/bin/MadGraph5_aMCatNLO/cards/production/13TeV/exo_diboson/Spin-2/BulkGraviton_VBF_WW_inclu/BulkGraviton_VBF_WW_inclu_narrow_M4000
externalLHEProducer = cms.EDProducer("ExternalLHEProducer",
args = cms.vstring('/cvmfs/cms.cern.ch/phys_generator/gridpacks/slc6_amd64_gcc481/13TeV/madgraph/V5_2.2.2/exo_diboson/Spin-2/BulkGraviton_VBF_WW_inclu/narrow/v1/BulkGraviton_VBF_WW_inclu_narrow_M4000_tarball.tar.xz'),
nEvents = cms.untracked.uint32(5000),
numberOfParameters = cms.uint32(1),
outputFile = cms.string('cmsgrid_final.lhe'),
scriptName = cms.FileInPath('GeneratorInterface/LHEInterface/data/run_generic_tarball_cvmfs.sh')
)
|
[
"sheffield@physics.rutgers.edu"
] |
sheffield@physics.rutgers.edu
|
c441b84ad77af9e2410f70a7eb69c516673a72a5
|
8e67d8618b9be7c777597b650876fa20082a6ebb
|
/14501.py
|
74d650e562528e9b9e0e32bd3b717523cf2ba523
|
[] |
no_license
|
ljm9748/practice_codingtest
|
c5a2cc315c1ccd8f48a9424d13d2097c9fed0efc
|
367710238976c1a2f8b42bfc3fc2936c47b195c5
|
refs/heads/master
| 2023-01-14T12:29:32.530648
| 2020-11-18T17:49:50
| 2020-11-18T17:49:50
| 282,162,451
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 284
|
py
|
n=int(input())
myinp=[]
for _ in range(n):
myinp.append(list(map(int, input().split())))
dp=[0]*(n)
for i in range(n):
day=myinp[i][0]
val=myinp[i][1]
if i+day-1<=(n-1):
for j in range(i+day-1, n):
dp[j]=max(dp[j], dp[i+day-2]+val)
print(dp[n-1])
|
[
"ljm9748@naver.com"
] |
ljm9748@naver.com
|
2855a822a742a7fbeb6e50814966d36d5e36be0c
|
61a856d931688a49435b3caab4e9d674ca2a32aa
|
/tests/test_zeroDS.py
|
27f6636792c8ed111a8de6cd4169b2281cecf6d1
|
[
"Apache-2.0"
] |
permissive
|
kvt0012/NeMo
|
3c9803be76c7a2ef8d5cab6995ff1ef058144ffe
|
6ad05b45c46edb5d44366bd0703915075f72b4fc
|
refs/heads/master
| 2020-08-14T16:59:18.702254
| 2019-10-14T22:46:48
| 2019-10-14T22:46:48
| 215,203,912
| 1
| 0
|
Apache-2.0
| 2019-10-15T04:05:37
| 2019-10-15T04:05:34
| null |
UTF-8
|
Python
| false
| false
| 4,613
|
py
|
import unittest
import os
import tarfile
import torch
from ruamel.yaml import YAML
from nemo.core.neural_types import *
from .context import nemo, nemo_asr
from .common_setup import NeMoUnitTest
class TestZeroDL(NeMoUnitTest):
labels = ["'", "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", " "]
manifest_filepath = "tests/data/asr/an4_train.json"
yaml = YAML(typ="safe")
def setUp(self) -> None:
super().setUp()
data_folder = "tests/data/"
print("Looking up for test ASR data")
if not os.path.exists(data_folder + "nemo_asr"):
print(f"Extracting ASR data to: {data_folder + 'nemo_asr'}")
tar = tarfile.open("tests/data/asr.tar.gz", "r:gz")
tar.extractall(path=data_folder)
tar.close()
else:
print("ASR data found in: {0}".format(data_folder + "asr"))
def test_simple_train(self):
print("Simplest train test with ZeroDL")
neural_factory = nemo.core.neural_factory.NeuralModuleFactory(
backend=nemo.core.Backend.PyTorch, create_tb_writer=False)
trainable_module = nemo.backends.pytorch.tutorials.TaylorNet(dim=4)
data_source = nemo.backends.pytorch.common.ZerosDataLayer(
size=10000,
dtype=torch.FloatTensor,
batch_size=128,
output_ports={
"x": NeuralType({
0: AxisType(BatchTag),
1: AxisType(ChannelTag, dim=1)}),
"y": NeuralType({
0: AxisType(BatchTag),
1: AxisType(ChannelTag, dim=1)})})
loss = nemo.backends.pytorch.tutorials.MSELoss()
x, y = data_source()
y_pred = trainable_module(x=x)
loss_tensor = loss(predictions=y_pred, target=y)
callback = nemo.core.SimpleLossLoggerCallback(
tensors=[loss_tensor],
print_func=lambda x: print(f'Train Loss: {str(x[0].item())}'))
neural_factory.train(
[loss_tensor], callbacks=[callback],
optimization_params={"num_epochs": 3, "lr": 0.0003},
optimizer="sgd")
def test_asr_with_zero_ds(self):
print("Testing ASR NMs with ZeroDS and without pre-processing")
with open("tests/data/jasper_smaller.yaml") as file:
jasper_model_definition = self.yaml.load(file)
dl = nemo.backends.pytorch.common.ZerosDataLayer(
size=100, dtype=torch.FloatTensor,
batch_size=4,
output_ports={
"processed_signal": NeuralType(
{0: AxisType(BatchTag),
1: AxisType(SpectrogramSignalTag, dim=64),
2: AxisType(ProcessedTimeTag, dim=64)}),
"processed_length": NeuralType(
{0: AxisType(BatchTag)}),
"transcript": NeuralType({0: AxisType(BatchTag),
1: AxisType(TimeTag, dim=64)}),
"transcript_length": NeuralType({0: AxisType(BatchTag)})
})
jasper_encoder = nemo_asr.JasperEncoder(
feat_in=jasper_model_definition['AudioPreprocessing']['features'],
**jasper_model_definition["JasperEncoder"])
jasper_decoder = nemo_asr.JasperDecoderForCTC(
feat_in=1024,
num_classes=len(self.labels)
)
ctc_loss = nemo_asr.CTCLossNM(num_classes=len(self.labels))
# DAG
processed_signal, p_length, transcript, transcript_len = dl()
encoded, encoded_len = jasper_encoder(audio_signal=processed_signal,
length=p_length)
# print(jasper_encoder)
log_probs = jasper_decoder(encoder_output=encoded)
loss = ctc_loss(log_probs=log_probs,
targets=transcript,
input_length=encoded_len,
target_length=transcript_len)
callback = nemo.core.SimpleLossLoggerCallback(
tensors=[loss],
print_func=lambda x: print(f'Train Loss: {str(x[0].item())}'))
# Instantiate an optimizer to perform `train` action
neural_factory = nemo.core.NeuralModuleFactory(
backend=nemo.core.Backend.PyTorch, local_rank=None,
create_tb_writer=False)
neural_factory.train(
[loss], callbacks=[callback],
optimization_params={"num_epochs": 2, "lr": 0.0003},
optimizer="sgd")
|
[
"okuchaiev@nvidia.com"
] |
okuchaiev@nvidia.com
|
eaebb4666a97d396903989fc5c9df6e3c92ebdc2
|
e13091c137650cd31c8d9778087b369033d0cf96
|
/src/main/python/algo_expert/Algorithm Implementation /Sort/selection_sort.py
|
db348f63325d79466c26d8e70fdde8fcced1ec7b
|
[] |
no_license
|
jwoojun/CodingTest
|
634e2cfe707b74c080ddbe5f32f58c1e6d849968
|
d62479d168085f13e73dfc1697c5438a97632d29
|
refs/heads/master
| 2023-08-22T09:03:32.392293
| 2021-10-31T01:00:33
| 2021-10-31T01:00:33
| 300,534,767
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 253
|
py
|
# selection_sort
def selection_sort(lst) :
for i in range(len(lst)-1) :
min_ = i
for j in range(i+1, len(lst)) :
if lst[min_] > lst[j] :
min_ = j
lst[i], lst[min_] = lst[min_], lst[i]
return lst
|
[
"jjwjun10@gmail.com"
] |
jjwjun10@gmail.com
|
6aff8bc6b2649dd67495d446bfea943bd810d87e
|
24e7e0dfaaeaca8f911b40fcc2937342a0f278fd
|
/venv/Lib/site-packages/pygments/plugin.py
|
76e8f6cb61c2c456a487266d8ae4197c7a0293af
|
[
"MIT"
] |
permissive
|
BimiLevi/Covid19
|
90e234c639192d62bb87364ef96d6a46d8268fa0
|
5f07a9a4609383c02597373d76d6b6485d47936e
|
refs/heads/master
| 2023-08-04T13:13:44.480700
| 2023-08-01T08:36:36
| 2023-08-01T08:36:36
| 288,455,446
| 1
| 0
|
MIT
| 2021-01-22T19:36:26
| 2020-08-18T12:53:43
|
HTML
|
UTF-8
|
Python
| false
| false
| 1,734
|
py
|
# -*- coding: utf-8 -*-
"""
pygments.plugin
~~~~~~~~~~~~~~~
Pygments setuptools plugin interface. The methods defined
here also work if setuptools isn't installed but they just
return nothing.
lexer plugins::
[pygments.lexers]
yourlexer = yourmodule:YourLexer
formatter plugins::
[pygments.formatters]
yourformatter = yourformatter:YourFormatter
/.ext = yourformatter:YourFormatter
As you can see, you can define extensions for the formatter
with a leading slash.
syntax plugins::
[pygments.styles]
yourstyle = yourstyle:YourStyle
filter plugin::
[pygments.filter]
yourfilter = yourfilter:YourFilter
:copyright: Copyright 2006-2020 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
LEXER_ENTRY_POINT = 'pygments.lexers'
FORMATTER_ENTRY_POINT = 'pygments.formatters'
STYLE_ENTRY_POINT = 'pygments.styles'
FILTER_ENTRY_POINT = 'pygments.filters'
def iter_entry_points(group_name):
try:
import pkg_resources
except (ImportError, IOError):
return []
return pkg_resources.iter_entry_points(group_name)
def find_plugin_lexers():
for entrypoint in iter_entry_points(LEXER_ENTRY_POINT):
yield entrypoint.load()
def find_plugin_formatters():
for entrypoint in iter_entry_points(FORMATTER_ENTRY_POINT):
yield entrypoint.name, entrypoint.load()
def find_plugin_styles():
for entrypoint in iter_entry_points(STYLE_ENTRY_POINT):
yield entrypoint.name, entrypoint.load()
def find_plugin_filters():
for entrypoint in iter_entry_points(FILTER_ENTRY_POINT):
yield entrypoint.name, entrypoint.load()
|
[
"50989568+BimiLevi@users.noreply.github.com"
] |
50989568+BimiLevi@users.noreply.github.com
|
964d74884c5d4fe523268950f181853cad302a7e
|
f77028577e88d228e9ce8252cc8e294505f7a61b
|
/web_backend/nvlserver/module/hw_module/specification/get_hw_module_specification.py
|
2c708377f8fa3bf925fcbfc53584e58eb50737ec
|
[] |
no_license
|
Sud-26/Arkally
|
e82cebb7f907a3869443b714de43a1948d42519e
|
edf519067d0ac4c204c12450b6f19a446afc327e
|
refs/heads/master
| 2023-07-07T02:14:28.012545
| 2021-08-06T10:29:42
| 2021-08-06T10:29:42
| 392,945,826
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,170
|
py
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__version__ = '1.0.1'
get_hw_module_list_query = """
SELECT hwm.id AS id,
hwm.name AS name,
COALESCE(hwm.module_id::VARCHAR, '') AS module_id,
hwm.user_id AS user_id,
coalesce(usr.fullname, '') AS user_name,
hwm.traceable_object_id AS traceable_object_id,
coalesce(tob.name, '') AS traceable_object_name,
hwm.meta_information::json AS meta_information,
hwm.show_on_map AS show_on_map,
hwm.gprs_active AS gprs_active,
hwm.active AS active,
hwm.deleted AS deleted,
hwm.created_on AS created_on,
hwm.updated_on AS updated_on
FROM public.hw_module AS hwm
LEFT OUTER JOIN public.user AS usr ON usr.id = hwm.user_id
LEFT OUTER JOIN public.traceable_object AS tob on hwm.traceable_object_id = tob.id
WHERE hwm.deleted is FALSE
AND ($1::BIGINT = 0 OR hwm.user_id = $1::BIGINT)
AND (
$2::VARCHAR is NULL OR
hwm.name ILIKE $2::VARCHAR || '%' OR
hwm.name ILIKE '%' || $2::VARCHAR || '%' OR
hwm.name ILIKE $2::VARCHAR || '%')
"""
get_hw_module_list_user_id_hw_module_id_list_query = """
SELECT hwm.id AS id
FROM public.hw_module AS hwm
WHERE hwm.deleted is FALSE AND hwm.active is TRUE
AND hwm.show_on_map IS TRUE
AND ($1::BIGINT IS NULL OR hwm.user_id = $1::BIGINT)
AND (array_length($2::int[], 1) IS NULL OR hwm.traceable_object_id = any ($2::int[]))
"""
get_hw_module_list_dropdown_query = """
SELECT hwm.id AS id,
hwm.name AS name
FROM public.hw_module AS hwm
WHERE hwm.deleted is FALSE AND hwm.active is TRUE
AND ($1::BIGINT IS NULL OR hwm.user_id = $1::BIGINT)
AND (
$2::VARCHAR is NULL OR
hwm.name ILIKE $2::VARCHAR || '%' OR
hwm.name ILIKE '%' || $2::VARCHAR || '%' OR
hwm.name ILIKE $2::VARCHAR || '%')
"""
get_hw_module_list_count_query = """
SELECT count(*) AS hw_module_count
FROM public.hw_module AS hwm
LEFT OUTER JOIN public.user AS usr ON usr.id = hwm.user_id
WHERE hwm.deleted is FALSE
AND ($1::BIGINT = 0 OR hwm.user_id = $1::BIGINT)
AND (
$2::VARCHAR is NULL OR
hwm.name ILIKE $2::VARCHAR || '%' OR
hwm.name ILIKE '%' || $2::VARCHAR || '%' OR
hwm.name ILIKE $2::VARCHAR || '%')
"""
get_hw_module_element_query = """
SELECT hwm.id AS id,
hwm.name AS name,
COALESCE(hwm.module_id::VARCHAR, '') AS module_id,
hwm.user_id AS user_id,
coalesce(usr.fullname, '') AS user_name,
hwm.traceable_object_id AS traceable_object_id,
coalesce(tob.name, '') AS traceable_object_name,
hwm.meta_information::json AS meta_information,
hwm.show_on_map AS show_on_map,
hwm.gprs_active AS gprs_active,
hwm.active AS active,
hwm.deleted AS deleted,
hwm.created_on AS created_on,
hwm.updated_on AS updated_on
FROM public.hw_module AS hwm
LEFT OUTER JOIN public.user AS usr ON usr.id = hwm.user_id
LEFT OUTER JOIN public.traceable_object AS tob on hwm.traceable_object_id = tob.id
WHERE hwm.deleted is FALSE
AND hwm.id = $1;
"""
get_hw_module_element_by_traceable_object_id_query = """
SELECT hwm.id AS id,
hwm.name AS name,
COALESCE(hwm.module_id::VARCHAR, '') AS module_id,
hwm.user_id AS user_id,
coalesce(usr.fullname, '') AS user_name,
hwm.traceable_object_id AS traceable_object_id,
coalesce(tob.name, '') AS traceable_object_name,
hwm.meta_information::json AS meta_information,
hwm.gprs_active AS gprs_active,
hwm.show_on_map AS show_on_map,
hwm.active AS active,
hwm.deleted AS deleted,
hwm.created_on AS created_on,
hwm.updated_on AS updated_on
FROM public.hw_module AS hwm
LEFT OUTER JOIN public.user AS usr ON usr.id = hwm.user_id
LEFT OUTER JOIN public.traceable_object AS tob on hwm.traceable_object_id = tob.id
WHERE hwm.deleted is FALSE
AND ($1::BIGINT is NULL OR hwm.user_id = $1::BIGINT)
AND hwm.traceable_object_id = $2;
"""
get_hw_module_element_by_name_query = """
SELECT hwm.id AS id,
hwm.name AS name,
COALESCE(hwm.module_id::VARCHAR, '') AS module_id,
hwm.user_id AS user_id,
coalesce(usr.fullname, '') AS user_name,
hwm.traceable_object_id AS traceable_object_id,
coalesce(tob.name, '') AS traceable_object_name,
hwm.meta_information::json AS meta_information,
hwm.gprs_active AS gprs_active,
hwm.show_on_map AS show_on_map,
hwm.active AS active,
hwm.deleted AS deleted,
hwm.created_on AS created_on,
hwm.updated_on AS updated_on
FROM public.hw_module AS hwm
LEFT OUTER JOIN public.user AS usr ON usr.id = hwm.user_id
LEFT OUTER JOIN public.traceable_object AS tob on hwm.traceable_object_id = tob.id
WHERE hwm.deleted is FALSE
AND (
$1::VARCHAR is NULL OR
hwm.name ILIKE $1::VARCHAR || '%' OR
hwm.name ILIKE '%' || $1::VARCHAR || '%' OR
hwm.name ILIKE $1::VARCHAR || '%')
LIMIT 1;
"""
|
[
"sudhakar@satmatgroup.com"
] |
sudhakar@satmatgroup.com
|
42d1ab3ce84114a87a59d9c3f9a7720ae4e57ece
|
bffe3ed7c76d488a685f1a586f08270d5a6a847b
|
/side_service/utils/importer.py
|
a6ea97b8f8a7a02c6df5fb58ea6838cd08c9642a
|
[] |
no_license
|
ganggas95/side-service
|
86a863d7b8d164e05584938aa63e56aa1ed8f793
|
c58ee47d1145cb704c4268006f135a141efc0667
|
refs/heads/nizar_dev
| 2021-06-21T11:37:54.771478
| 2019-10-14T23:45:39
| 2019-10-14T23:45:39
| 213,881,364
| 0
| 1
| null | 2021-05-06T19:55:47
| 2019-10-09T09:52:06
|
Python
|
UTF-8
|
Python
| false
| false
| 2,443
|
py
|
import os
from numpy import int64
import pandas as pd
from flask import current_app as app
from side_service.models.prov import Provinsi
from side_service.models.kab import Kabupaten
from side_service.models.kec import Kecamatan
from side_service.models.desa import Desa
class FileImporter:
temps = []
def __init__(self, filename):
if filename:
self.df = pd.read_csv(os.path.join(
app.config["FILE_IMPORT_FOLDER"],
filename), header=None)
class ImportProvinceFile(FileImporter):
def read_data(self):
for row in range(0, len(self.df.index)):
kode_prov = str(self.df[0][self.df.index[row]])
name = self.df[1][self.df.index[row]]
prov = Provinsi(kode_prov, name)
prov.save()
print("Import Province is success")
class ImportRegenciesFile(FileImporter):
@property
def provs(self):
return Provinsi.all()
def read_data(self):
for prov in self.provs:
df_prov = self.df.loc[self.df[1] == int64(prov.kode_prov)]
for row in range(0, len(df_prov.index)):
kode_kab = str(df_prov[0][df_prov.index[row]])
name = df_prov[2][df_prov.index[row]]
kab = Kabupaten(kode_kab, name, prov.kode_prov)
kab.save()
print("Import Kabupaten is success")
class ImportDistrictFile(FileImporter):
@property
def kabs(self):
return Kabupaten.all()
def read_data(self):
for kab in self.kabs:
df_kab = self.df.loc[self.df[1] == int64(kab.kode_kab)]
for row in range(0, len(df_kab.index)):
kode_kec = str(df_kab[0][df_kab.index[row]])
name = df_kab[2][df_kab.index[row]]
kec = Kecamatan(kode_kec, name, kab.kode_kab)
kec.save()
print("Import District Success")
class ImportVillagesFile(FileImporter):
@property
def kecs(self):
return Kecamatan.all()
def read_data(self):
for kec in self.kecs:
df_desa = self.df.loc[self.df[1] == int64(kec.kode_kec)]
for row in range(0, len(df_desa.index)):
kode_desa = str(df_desa[0][df_desa.index[row]])
name = df_desa[2][df_desa.index[row]]
desa = Desa(kode_desa, name, kec.kode_kec)
desa.save()
print("Import Villages Success")
|
[
"subhannizar25@gmail.com"
] |
subhannizar25@gmail.com
|
b637325039f49ef3a68474942e03ff5f45a15a45
|
6455c57f85289fae2195e15b9de126ef1f6bf366
|
/project/job/models.py
|
d76497cb302d53dfa50245b326202b283d94f849
|
[] |
no_license
|
muhamed-mustafa/django-job-board
|
8fcb76e8543509d233cb7697ced67c96f5d81fbc
|
6b3fa1d7126d9c400c1c6cf3ccb4c8061db8692b
|
refs/heads/master
| 2022-12-15T00:53:15.202174
| 2020-09-17T21:43:48
| 2020-09-17T21:43:48
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,523
|
py
|
from django.db import models
from django.utils.translation import ugettext as _
from django.utils.text import slugify
from django.contrib.auth.models import User
def image_upload(instance, filename):
imagename, extension = filename.split(".")
return 'jobs/%s.%s' % (instance.id, extension)
class Job(models.Model):
objects = None
JOB_TYPE = (
('Full Time', 'Full Time'),
('Part Time', 'Part Time')
)
owner = models.ForeignKey(User, related_name='job_owner', on_delete=models.CASCADE)
like = models.ManyToManyField(User,blank=True)
location = models.CharField(max_length=20)
title = models.CharField(max_length=100)
job_type = models.CharField(max_length=100, choices=JOB_TYPE)
description = models.TextField(max_length=1000)
published_at = models.DateTimeField(auto_now=True)
vacancy = models.IntegerField(default=1)
salary = models.IntegerField(default=0)
experience = models.IntegerField(default=1)
category = models.ForeignKey('Category', on_delete=models.CASCADE)
image = models.ImageField(upload_to=image_upload, null=True, blank=True)
slug = models.SlugField(null=True, blank=True)
facebook = models.CharField(max_length=500,null=True,blank=True)
instagram = models.CharField(max_length=500,null=True,blank=True)
google = models.CharField(max_length=500,null=True,blank=True)
twitter = models.CharField(max_length=500,null=True,blank=True)
def save(self, *args, **kwargs):
if not self.slug:
self.slug = slugify(self.title)
super(Job, self).save(*args, **kwargs)
class meta:
verbose_name = _('Job')
verbose_name_plural = _('Jobs')
def __str__(self):
return self.title
class Category(models.Model):
name = models.CharField(max_length=25)
class meta:
verbose_name = _('Category')
verbose_name_plural = _('Categories')
def __str__(self):
return self.name
class Apply(models.Model):
job = models.ForeignKey(Job, related_name='apply_job', on_delete=models.CASCADE)
name = models.CharField(max_length=50)
email = models.EmailField(max_length=100)
website = models.URLField()
cv = models.FileField(upload_to='apply/')
cover_letter = models.TextField(max_length=1000)
created_at = models.DateTimeField(auto_now=True,null=True,blank=True)
class Meta:
verbose_name = _('Apply')
verbose_name_plural = _('Applies')
def __str__(self):
return self.name
|
[
"muuhamed14mustafa@gmail.com"
] |
muuhamed14mustafa@gmail.com
|
3d07fac9d2bb63738f35e626530cf62382648804
|
127e99fbdc4e04f90c0afc6f4d076cc3d7fdce06
|
/2021_하반기 코테연습/boj16937.py
|
6d06ddfaf0afe6fb35157d542a1476f2a0119f6a
|
[] |
no_license
|
holim0/Algo_Study
|
54a6f10239368c6cf230b9f1273fe42caa97401c
|
ce734dcde091fa7f29b66dd3fb86d7a6109e8d9c
|
refs/heads/master
| 2023-08-25T14:07:56.420288
| 2021-10-25T12:28:23
| 2021-10-25T12:28:23
| 276,076,057
| 3
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 999
|
py
|
from itertools import combinations
h, w = map(int, input().split())
n = int(input())
sti = []
for _ in range(n):
r, c = map(int, input().split())
if (r<=h and c<=w) or (r<=w and c<=h):
sti.append((r, c))
answer = -1
johab = list(combinations(sti, 2))
for cur in johab:
r1,c1, r2, c2 = cur[0][0], cur[0][1], cur[1][0], cur[1][1]
rest_r, rest_c = h-r1, w-c1
rest_r2, rest_c2 = h-c1, w-r1
if rest_r>=0 and rest_c>=0:
if (r2<=rest_r and c2<=w) or (r2<=h and c2<=rest_c):
answer = max(answer, r1*c1+r2*c2)
elif (c2<=rest_r and r2<=w) or (c2<=h and r2<=rest_c):
answer = max(answer, r1*c1+r2*c2)
if rest_r2>=0 and rest_c2>=0:
if (r2<=rest_r2 and c2<=w) or (r2<=h and c2<=rest_c2):
answer = max(answer, r1*c1+r2*c2)
elif (c2<=rest_r2 and r2<=w) or (c2<=h and r2<=rest_c2):
answer = max(answer, r1*c1+r2*c2)
if answer == -1:
print(0)
else:
print(answer)
|
[
"holim1226@gmail.com"
] |
holim1226@gmail.com
|
66249f846adc240a436f156b941e6d0a01b7be95
|
4bed9030031fc99f6ea3d5267bd9e773f54320f8
|
/sparse/repos/katyhon/hello-world.git/setup.py
|
9910a87c354430aea7dbbdccc76c28a3264a91f0
|
[
"BSD-3-Clause"
] |
permissive
|
yuvipanda/mybinder.org-analytics
|
c5f4b939541d29727bc8d3c023b4d140de756f69
|
7b654e3e21dea790505c626d688aa15640ea5808
|
refs/heads/master
| 2021-06-13T05:49:12.447172
| 2018-12-22T21:48:12
| 2018-12-22T21:48:12
| 162,839,358
| 1
| 1
|
BSD-3-Clause
| 2021-06-10T21:05:50
| 2018-12-22T20:01:52
|
Jupyter Notebook
|
UTF-8
|
Python
| false
| false
| 1,133
|
py
|
# -*- coding: utf-8 -*-
# @Author: Zebedee Nicholls
# @Date: 2017-04-10 13:42:11
# @Last Modified by: Chris Smith
# @Last Modified time: 2018-01-11 19:17:00
from setuptools import setup
from setuptools import find_packages
import versioneer
# README #
def readme():
with open('README.rst') as f:
return f.read()
setup(name='fair',
version=versioneer.get_version(),
cmdclass=versioneer.get_cmdclass(),
description='Python package to perform calculations with the FAIR simple climate model',
long_description=readme(),
keywords='simple climate model temperature response carbon cycle emissions forcing',
url='https://github.com/OMS-NetZero/FAIR',
author='OMS-NetZero, Chris Smith, Richard Millar, Zebedee Nicholls, Myles Allen',
author_email='c.j.smith1@leeds.ac.uk, richard.millar@physics.ox.ac.uk',
license='Apache 2.0',
packages=find_packages(exclude=['tests*','docs*']),
package_data={'': ['*.csv']},
include_package_data=True,
install_requires=[
'numpy>=1.11.3',
'scipy>=0.19.0',
],
zip_safe=False,
)
|
[
"yuvipanda@gmail.com"
] |
yuvipanda@gmail.com
|
757fdd5ec99459542dde88e360700156603c2846
|
ee8c4c954b7c1711899b6d2527bdb12b5c79c9be
|
/assessment2/amazon/run/core/controllers/vivacious.py
|
6023c96df4e75d647fba458235af9ef85c64b4ef
|
[] |
no_license
|
sqlconsult/byte
|
02ac9899aebea4475614969b594bfe2992ffe29a
|
548f6cb5038e927b54adca29caf02c981fdcecfc
|
refs/heads/master
| 2021-01-25T14:45:42.120220
| 2018-08-11T23:45:31
| 2018-08-11T23:45:31
| 117,135,069
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 372
|
py
|
#!/usr/bin/env python3
from flask import Blueprint, Flask, render_template, request, url_for
controller = Blueprint('vivacious', __name__, url_prefix='/vivacious')
# @controller.route('/<string:title>', methods=['GET'])
# def lookup(title):
# if title == 'Republic': # TODO 2
# return render_template('republic.html') # TODO 2
# else:
# pass
|
[
"sqlconsult@hotmail.com"
] |
sqlconsult@hotmail.com
|
0743fab55b7760c26dc13b3922aea2a97eec77c6
|
50008b3b7fb7e14f793e92f5b27bf302112a3cb4
|
/recipes/Python/580763_Context_Manager_Arbitrary_Number_Files/recipe-580763.py
|
150135fb1201d2a97d2a7f356d35cb1f5cb58577
|
[
"MIT"
] |
permissive
|
betty29/code-1
|
db56807e19ac9cfe711b41d475a322c168cfdca6
|
d097ca0ad6a6aee2180d32dce6a3322621f655fd
|
refs/heads/master
| 2023-03-14T08:15:47.492844
| 2021-02-24T15:39:59
| 2021-02-24T15:39:59
| 341,878,663
| 0
| 0
|
MIT
| 2021-02-24T15:40:00
| 2021-02-24T11:31:15
|
Python
|
UTF-8
|
Python
| false
| false
| 416
|
py
|
class Files(tuple):
def __new__(cls, *filePaths):
files = []
try:
for filePath in filePaths:
files.append(open(filePath))
files[-1].__enter__()
except:
for file in files:
file.close()
raise
else:
return super(Files, cls).__new__(cls, files)
def __enter__(self):
return self
def __exit__(self, *args):
for file in self:
file.close()
|
[
"betty@qburst.com"
] |
betty@qburst.com
|
8bc30b4ffffdd2a9e6c67b806b72324ac9bcf8c5
|
699c7f26a91106a2fc79bb15299ce0cee532a2dd
|
/test/pivottest.py
|
a875542be8d7a661c68859711f9c108434bede2c
|
[] |
no_license
|
samconnolly/astro
|
70581a4d3f2086716aace3b5db65b74aaaa5df95
|
3731be313592c13dbb8af898e9734b98d83c0cc2
|
refs/heads/master
| 2020-04-06T03:40:27.454279
| 2014-03-12T14:36:34
| 2014-03-12T14:36:34
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,709
|
py
|
# Programme to test how a pivoting spectral component, plus a
# constant soft component changes the shape of the flux-flux diagram
import numpy as np
from pylab import *
# parameters
epivot = 2.0 # KeV pivot energy
pivmin = 2.0
pivmax = 10.0
cindex = 2.0 # index of constant component
nsteps = 10.0
# constants
h = 6.63 # planck
e = 1.6e-19 # electron charge
# energy axis
energy = np.arange(0.5,10.0,0.01) # energy range of spectrum in KeV
logenergy = np.log(energy) # log of energy
freq = (energy*e*1000.0)/h # frequency range in Hz
stepsize = (pivmax-pivmin)/nsteps
pivnorm = ( ((epivot*e*1000.0)/h)**pivmin)
fluxflux = [[],[],[]]
# plotting the log spectrum components
# constant component
cflux = freq**(-cindex) # constant flux component
logcflux = np.log10(cflux) # log of constant flux
logvflux = []
# varying component
for piv in np.arange(pivmin,pivmax,stepsize):
currvflux = (freq**(-piv))
pnorm = (((epivot*e*1000.0)/h)**piv)
currvflux = (currvflux/pnorm)*pivnorm
logcurrvflux = np.log10(currvflux) # log thereof
logvflux.append(logcurrvflux)
# soft/hard delineaters
low = [np.log(0.5),np.log10(0.5)]
div = [np.log(2.0),np.log10(2.0)]
high = [np.log(10.0),np.log10(10.0)]
yrange = [logcflux[-1],logvflux[-1][0]]
subplot(1,2,1) # log spectrum plot
#plot(logenergy,logcflux,color="red")
plot(logenergy,logvflux[0],color="blue")
plot(logenergy,logvflux[len(logvflux)/2],color="blue")
plot(logenergy,logvflux[-1],color="blue")
#plot(low,yrange)
#plot(div,yrange)
#plot(high,yrange)
# total spectrum
subplot(1,2,2)
for x in [0,len(logvflux)/2,-1]:
logtotal = logvflux[x] + logcflux
plot(logenergy,logtotal)
show()
|
[
"sdc1g08@soton.ac.uk"
] |
sdc1g08@soton.ac.uk
|
cbb97a71e43ba0aeae79c64781b1c2a7c1f09cb8
|
8fb4f83ac4e13c4c6de7f412f68c280d86ddea15
|
/eon/tests/unit/deployer/network/ovsvapp/test_vapp_util.py
|
6e5508948b41971f8773c56807dceeb902078137
|
[
"Apache-2.0"
] |
permissive
|
ArdanaCLM/hpe-eon
|
cbd61afa0473bbd9c6953e5067dbe5a7ff42c084
|
48a4086d2ccc5ccac60385b183f0d43f247c0b97
|
refs/heads/master
| 2021-07-25T18:55:30.176284
| 2017-10-24T08:49:42
| 2017-10-24T08:49:42
| 103,971,673
| 0
| 1
| null | 2017-11-07T15:47:45
| 2017-09-18T17:43:45
|
Python
|
UTF-8
|
Python
| false
| false
| 6,225
|
py
|
#
# (c) Copyright 2015-2017 Hewlett Packard Enterprise Development Company LP
#
# 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 writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
import contextlib
from mock import patch
from pyVmomi import vim
from eon.deployer.network.ovsvapp.util.vapp_util import OVSvAppUtil
from eon.deployer.util import VMwareUtils
from eon.tests.unit import tests
from eon.tests.unit.deployer import fake_inputs
# TODO: Put all the helper classes in one location
class PrepFolder:
name = 'fake_folder'
childEntity = False
class MoveInto_Task:
def __init__(self, val):
self.val = val
class Destroy_Task:
pass
class MOB:
class content():
def rootFolder(self):
pass
def propertyCollector(self):
pass
class VM:
class Vm:
class config:
annotation = 'hp-ovsvapp'
class runtime:
powerState = 'poweredOn'
class PowerOff:
pass
class Destroy:
pass
vm = [Vm]
class Cluster:
@staticmethod
def ReconfigureComputeResource_Task(cluster_spec_ex, modify):
pass
class TestOVSvAppUtil(tests.BaseTestCase):
def setUp(self):
super(TestOVSvAppUtil, self).setUp()
self.ovs_vapp_util = OVSvAppUtil()
vc_info = fake_inputs.data.get('vcenter_configuration')
self.cluster = {'obj': Cluster(),
'name': vc_info.get('cluster'),
'configuration.dasConfig.enabled': True,
'configuration.drsConfig.enabled': True}
def test_get_ovsvapps(self):
fake_vms = [{'name': 'ovsvapp_fake_vm',
'config.annotation': 'hp-ovsvapp',
'runtime.host': 'host-1'}]
content = None
vm_folder = None
with contextlib.nested(
patch.object(VMwareUtils, 'get_view_ref'),
patch.object(VMwareUtils, 'collect_properties',
return_value=fake_vms))as (
mock_get_view_ref, mock_collect_properties):
output = self.ovs_vapp_util.get_ovsvapps(content, vm_folder,
fake_inputs.fake_clusters)
self.assertEqual(fake_vms[0], output['host-1'])
self.assertTrue(mock_get_view_ref.called)
self.assertTrue(mock_collect_properties.called)
def test_get_active_hosts(self):
host = {'obj': 'host1', 'name': 'fake_host'}
with patch.object(VMwareUtils, 'get_all_hosts',
return_value=[host]) as mock_get_all_hosts:
self.ovs_vapp_util.get_active_hosts(MOB, 'vm_folder',
['host1'], 'cluster')
self.assertTrue(mock_get_all_hosts.called)
def test_exec_multiprocessing(self):
pass
def test_get_folder(self):
pass
def test_create_host_folder(self):
with patch.object(OVSvAppUtil, '_get_folder',
return_value='fake_folder') as mock_get_folder:
self.ovs_vapp_util.create_host_folder(
'content', [{'cluster': {'name': self.cluster.get('name')}}],
'host_folder')
self.assertTrue(mock_get_folder.called)
def test_move_hosts_in_to_folder(self):
pass
def test_enter_maintenance_mode(self):
pass
def test_destroy_failed_commissioned_vapps(self):
host = {'obj': VM, 'name': 'fake_host'}
with patch.object(VMwareUtils, 'wait_for_task') as mock_wait_for_task:
self.ovs_vapp_util.destroy_failed_commissioned_vapps(host, MOB)
self.assertTrue(mock_wait_for_task.called)
def test_move_host_back_to_cluster(self):
host = {'obj': 'host', 'name': 'fake_host'}
cluster = {'obj': PrepFolder, 'name': 'fake_cluster'}
with contextlib.nested(
patch.object(OVSvAppUtil, 'destroy_failed_commissioned_vapps'),
patch.object(OVSvAppUtil, 'enter_maintenance_mode'),
patch.object(VMwareUtils, 'wait_for_task')) as (
mock_destroy, mock_enter_maintenance_mode,
mock_wait_for_task):
self.ovs_vapp_util.move_host_back_to_cluster(MOB, host, cluster,
PrepFolder, 'err')
self.assertTrue(mock_destroy.called)
self.assertTrue(mock_enter_maintenance_mode.called)
self.assertTrue(mock_wait_for_task.called)
def test_get_host_parent(self):
pass
def test_get_cluster_inventory_path(self):
pass
def test_get_eon_env(self):
pass
def test_exec_subprocess(self):
pass
def test_disable_ha_on_ovsvapp(self):
with contextlib.nested(
patch.object(vim.VirtualMachine, '__init__',
return_value=None),
patch.object(vim.HostSystem, '__init__', return_value=None),
patch.object(VMwareUtils, 'wait_for_task')) as (
mock_vm, mock_host, mock_wait_for_task):
vim.VirtualMachine.name = 'fake-vm'
self.vm_obj = vim.VirtualMachine()
self.host_obj = vim.HostSystem()
host = {'obj': self.host_obj,
'name': 'fake_host'}
self.ovs_vapp_util.disable_ha_on_ovsvapp(fake_inputs.session['si'],
self.vm_obj, self.cluster,
host)
self.assertTrue(mock_vm.called)
self.assertTrue(mock_host.called)
self.assertTrue(mock_wait_for_task.called)
|
[
"srivastava.abhishek@hp.com"
] |
srivastava.abhishek@hp.com
|
e646bb93cc2e371f15aec3b80cb3f8c0380cccc1
|
51a37b7108f2f69a1377d98f714711af3c32d0df
|
/src/leetcode/P292.py
|
5c48dc1f6e7885796ce6210fadce7d6c63219433
|
[] |
no_license
|
stupidchen/leetcode
|
1dd2683ba4b1c0382e9263547d6c623e4979a806
|
72d172ea25777980a49439042dbc39448fcad73d
|
refs/heads/master
| 2022-03-14T21:15:47.263954
| 2022-02-27T15:33:15
| 2022-02-27T15:33:15
| 55,680,865
| 7
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 136
|
py
|
class Solution:
def canWinNim(self, n):
"""
:type n: int
:rtype: bool
"""
return n % 4 != 0
|
[
"stupidchen@foxmail.com"
] |
stupidchen@foxmail.com
|
9af39db942c3e1dde49345526d12a0c37972f44a
|
739e41d4f24f79c772d266cded0de9b759c6e953
|
/venv/lib/python3.6/site-packages/datasets/__init__.py
|
eb40f7f2cfc457e3e42b84454b398c6c73b9dd70
|
[
"MIT"
] |
permissive
|
MachineLearningBCAM/Minimax-risk-classifiers-NeurIPS-2020
|
24b7bbdecf459292f8b58be286feab3b9aa341ba
|
82586c632268c103de269bcbffa5f7849b174a29
|
refs/heads/main
| 2023-05-18T15:41:13.495286
| 2021-06-11T18:21:35
| 2021-06-11T18:21:35
| 304,268,819
| 3
| 2
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,246
|
py
|
# flake8: noqa
# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# 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 writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__version__ = "1.0.2"
import pyarrow
from pyarrow import total_allocated_bytes
from . import datasets
from .arrow_dataset import Dataset, concatenate_datasets
from .arrow_reader import ArrowReader, ReadInstruction
from .arrow_writer import ArrowWriter
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .dataset_dict import DatasetDict
from .features import (
Array2D,
Array3D,
Array4D,
Array5D,
ClassLabel,
Features,
Sequence,
Translation,
TranslationVariableLanguages,
Value,
)
from .info import DatasetInfo, MetricInfo
from .inspect import inspect_dataset, inspect_metric, list_datasets, list_metrics
from .load import import_main_class, load_dataset, load_from_disk, load_metric, prepare_module
from .metric import Metric
from .splits import NamedSplit, Split, SplitBase, SplitDict, SplitGenerator, SplitInfo, SubSplitInfo, percent
from .utils import *
from .utils.tqdm_utils import disable_progress_bar
if int(pyarrow.__version__.split(".")[1]) < 16 and int(pyarrow.__version__.split(".")[0]) == 0:
raise ImportWarning(
"To use `datasets`, the module `pyarrow>=0.16.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"
"If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."
)
SCRIPTS_VERIONS = __version__
|
[
"adiaz@bcamath.org"
] |
adiaz@bcamath.org
|
b21cdd6b34ce845121a1bedbe1cbd7d5fcb287c1
|
2834f98b53d78bafc9f765344ded24cf41ffebb0
|
/weblayer/renderer/DEPS
|
e83c233386cd4f75dd17543c345adb86342e4984
|
[
"BSD-3-Clause"
] |
permissive
|
cea56/chromium
|
81bffdf706df8b356c2e821c1a299f9d4bd4c620
|
013d244f2a747275da76758d2e6240f88c0165dd
|
refs/heads/master
| 2023-01-11T05:44:41.185820
| 2019-12-09T04:14:16
| 2019-12-09T04:14:16
| 226,785,888
| 1
| 0
|
BSD-3-Clause
| 2019-12-09T04:40:07
| 2019-12-09T04:40:07
| null |
UTF-8
|
Python
| false
| false
| 784
|
include_rules = [
# This is needed for error page strings/resources.
# TODO(1024326): If WebLayer stays with WebView's error pages implementation
# long-term, componentize these strings/resources as part of componentizing
# that implementation and remove the need for this dependency.
"+android_webview/grit",
"+components/safe_browsing/common",
"+components/safe_browsing/renderer",
"+components/security_interstitials/content/renderer",
"+components/security_interstitials/core/common",
"+components/spellcheck/renderer",
"+content/public/renderer",
# needed for safebrowsing
"+mojo/public/cpp/bindings",
"+net/base",
"+services/service_manager/public/cpp",
"+third_party/blink/public/common",
"+third_party/blink/public/platform",
"+ui/base",
]
|
[
"commit-bot@chromium.org"
] |
commit-bot@chromium.org
|
|
352bab04b5f300ec488b2c2277b3fcce8aa5430d
|
0fd92b7d882a1edb5542f6600bb177dcad67ed50
|
/powerful104/2476.py
|
59884bdebe88950cc45e5841b1b8de057f17569f
|
[] |
no_license
|
alpha-kwhn/Baekjun
|
bce71fdfbbc8302ec254db5901109087168801ed
|
f8b4136130995dab78f34e84dfa18736e95c8b55
|
refs/heads/main
| 2023-08-02T11:11:19.482020
| 2021-03-09T05:34:01
| 2021-03-09T05:34:01
| 358,347,708
| 0
| 0
| null | 2021-04-15T17:56:14
| 2021-04-15T17:56:13
| null |
UTF-8
|
Python
| false
| false
| 317
|
py
|
ans=0
for _ in range(int(input())):
a, b, c= map(int, input().split())
prize=0
if a==b==c:
prize=10000+a*1000
elif a==b or a==c:
prize=1000+a*100
elif b==c:
prize=1000+b*100
else:
prize=max(a,b,c)*100
if ans<prize:
ans=prize
print(ans)
|
[
"noreply@github.com"
] |
alpha-kwhn.noreply@github.com
|
b3a89023ea3508c3e11a114dd212533d8cafa3d2
|
c7f43c4cc0ee84a5fe246b67f51e30b8d726ebd5
|
/ml/m30_pca2_5_diabetes_RF.py
|
cf6c7c7cf6d4e1510dfd2fa544ccd37999038961
|
[] |
no_license
|
89Mansions/AI_STUDY
|
d9f8bdf206f14ba41845a082e731ea844d3d9007
|
d87c93355c949c462f96e85e8d0e186b0ce49c76
|
refs/heads/master
| 2023-07-21T19:11:23.539693
| 2021-08-30T08:18:59
| 2021-08-30T08:18:59
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,082
|
py
|
# PCA : 차원축소, 컬럼 재구성
# RandomForest로 모델링
import numpy as np
from sklearn.datasets import load_diabetes
from sklearn.decomposition import PCA
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.metrics import r2_score
from sklearn.pipeline import Pipeline
from xgboost import XGBRegressor
#1. DATA
datasets = load_diabetes()
x = datasets.data
y = datasets.target
# print(x.shape, y.shape) # (442, 10) (442,)
pca = PCA(n_components=8)
x2 = pca.fit_transform(x) # fit_transform : 전처리 fit과 transform 한꺼번에 한다.
x_train, x_test, y_train, y_test = train_test_split(x2, y, train_size=0.8, shuffle=True, random_state=46)
print(x_train.shape) # (353, 8) >> 컬럼을 압축시켰다. 컬럼 재구성됨
print(x_test.shape) # (89, 8) >> 컬럼을 압축시켰다. 컬럼 재구성됨
# pca = PCA()
# pca.fit(x)
# cumsum = np.cumsum(pca.explained_variance_ratio_)
# print("cumsum : ", cumsum) # cumsum 누적 합을 계산
# cumsum : [0.40242142 0.55165324 0.67224947 0.76779711 0.83401567 0.89428759
# 0.94794364 0.99131196 0.99914395 1. ]
# d = np.argmax(cumsum >= 0.95)+1
# print("cumsum >= 0.95", cumsum > 0.95)
# print("d : ", d)
# cumsum >= 0.95 [False False False False False False False True True True]
# d : 8
# import matplotlib.pyplot as plt
# plt.plot(cumsum)
# plt.grid()
# plt.show()
#2. Modeling
model = Pipeline([("scaler", MinMaxScaler()),("model",RandomForestRegressor())])
model = Pipeline([("scaler", MinMaxScaler()),("model",XGBRegressor())])
#3. Train
model.fit(x_train, y_train)
#4. Score, Predict
result = model.score(x_test, y_test)
print("model.score : ", result)
y_pred = model.predict(x_test)
score = r2_score(y_pred, y_test)
print("r2_score : ", score)
# RandomForestRegressor
# model.score : 0.43512635590690074
# r2_score : -0.5421970924222612
# XGBoost
# model.score : 0.3449642489091771
# r2_score : -0.3388132027144872
|
[
"hwangkei0212@gmail.com"
] |
hwangkei0212@gmail.com
|
9db9821260783c8ab2205fe0109af946caaa20e8
|
3806db5b4bb7a638f30c818a29ccaf2b0ddb2836
|
/test_141.py
|
47edc016610b2369996717a30fdc8799c917f569
|
[] |
no_license
|
EomAA/fenics-qa
|
d0a687a7b84c51417e96eeeef9855c0d4ba27dea
|
c37a36a14450d0e7f6432c4726c5d96e0d6c4e96
|
refs/heads/master
| 2021-12-15T12:07:10.316478
| 2017-08-18T09:16:01
| 2017-08-18T09:16:01
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 634
|
py
|
import dolfin
mesh = dolfin.UnitSquareMesh(1,1)
dX = dolfin.dx(mesh)
fe = dolfin.FiniteElement(
family="Quadrature",
cell=mesh.ufl_cell(),
degree=1,
quad_scheme="default")
cppExprCode='''
namespace dolfin
{
class CppExpr : public Expression
{
public:
CppExpr(): Expression(0)
{
}
void eval(Array<double>& values, const Array<double>& position) const
{
std::cout << "position = " << position << std::endl;
values[0] = 1.;
std::cout << "values = " << values << std::endl;
}
};
}'''
cppExpr = dolfin.Expression(cppExprCode, element=fe)
dolfin.assemble(cppExpr * dX)
|
[
"miroslav.kuchta@gmail.com"
] |
miroslav.kuchta@gmail.com
|
e358e020b0dd01cb1f401a59c6dc293c3929cbad
|
6ea69f9a4431837a36b04ab926ac9c565b8a5eb6
|
/pydemic_ui/i18n.py
|
53f5ca158c862fef6e82e4716ab8fbbb4df02fcd
|
[
"MIT"
] |
permissive
|
WillAllmeida/pydemic-ui
|
e9fad4845c428f3e2f0e7a65913391c3216083b3
|
f7c05d97489918736b0c7b1da4b0992bd77ed9a1
|
refs/heads/master
| 2023-01-24T13:49:27.219863
| 2020-10-07T18:11:02
| 2020-10-07T18:11:02
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 945
|
py
|
from gettext import gettext
from pathlib import Path
import sidekick as sk
LOCALEDIR = Path(__file__).parent / "locale"
def set_i18n(lang, language=None):
"""
Set locale and translations.
Examples:
set_i18n('pt_BR.UTF-8') -> set locale to pt_BR.UTF-8 and language to pt_BR.
"""
import gettext
import locale
import warnings
import os
try:
locale.setlocale(locale.LC_ALL, lang)
locale.setlocale(locale.LC_MESSAGES, language or lang)
os.environ["LANG"] = lang
os.environ["LANGUAGE"] = language or lang.split(".")[0]
except locale.Error:
warnings.warn(f"locale is not supported: {lang}")
gettext.bindtextdomain("messages", localedir=LOCALEDIR)
def run():
import os
lang = os.environ.get("PYDEMIC_LANG") or os.environ.get("LANG")
set_i18n(lang)
def gettext_lazy(st):
return sk.deferred(gettext, st)
_ = gettext
__ = gettext_lazy
|
[
"fabiomacedomendes@gmail.com"
] |
fabiomacedomendes@gmail.com
|
a344bfbfba2175a962b94b0450d79418dd1cd225
|
8246e9fbdecdb37651e0d09497fd9428e434f33c
|
/ServiceCatagory/urls.py
|
e17e6184bb33e3ef9d66c52d6ec20aae7d197828
|
[] |
no_license
|
rajeev1234/Landing-Page
|
479995026ab01fc504a1e9502e7763dc04266009
|
4bfd22a6a1776907ba78b3dc9037064c820b049e
|
refs/heads/master
| 2020-03-08T13:37:20.253252
| 2018-04-05T06:33:26
| 2018-04-05T06:33:26
| 128,162,519
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 863
|
py
|
from django.urls import path
from . import views
urlpatterns = [
# Path to list view of ServiceCatagory : ServiceCatagory_list
path('', views.ServiceCatagoryListView.as_view(), name='ServiceCatagory_list'),
# Path to create new ServiceCatagory : ServiceCatagory_new
path('new/', views.ServiceCatagoryCreateView.as_view(), name='ServiceCatagory_new'),
# Path to edit ServiceCatagory : edit_list
path('<int:pk>/edit', views.ServiceCatagoryUpdateView.as_view(), name='ServiceCatagory_update'),
# Path to delete ServiceCatagory : ServiceCatagory_delete
path('<int:pk>/delete', views.ServiceCatagoryDeleteView.as_view(), name='ServiceCatagory_delete'),
# Path to detail view of ServiceCatagory : ServiceCatagory_details
path('<int:pk>', views.ServiceCatagoryDetailView.as_view(), name='ServiceCatagory_details')
]
|
[
"ccrcian.rajeev1@gmail.com"
] |
ccrcian.rajeev1@gmail.com
|
0e535165547e2b25ce06072821dc32d3a608475f
|
c9ddbdb5678ba6e1c5c7e64adf2802ca16df778c
|
/cases/pa3/benchmarks/sieve-244.py
|
29dca34d6015fcd1da12c7a36d7a12abcdf185e5
|
[] |
no_license
|
Virtlink/ccbench-chocopy
|
c3f7f6af6349aff6503196f727ef89f210a1eac8
|
c7efae43bf32696ee2b2ee781bdfe4f7730dec3f
|
refs/heads/main
| 2023-04-07T15:07:12.464038
| 2022-02-03T15:42:39
| 2022-02-03T15:42:39
| 451,969,776
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,581
|
py
|
# A resizable list of integers
class Vector(object):
items: [int] = None
size: int = 0
def __init__(self:"Vector"):
self.items = [0]
# Returns current capacity
def capacity(self:"Vector") -> int:
return len(self.items)
# Increases capacity of vector by one element
def increase_capacity(self:"Vector") -> int:
self.items = self.items + [0]
return self.capacity()
# Appends one item to end of vector
def append(self:"Vector", item: int) -> object:
if self.size == self.capacity():
self.increase_capacity()
self.items[self.size] = item
self.size = self.size + 1
# Appends many items to end of vector
def append_all(self:"Vector", new_items: [int]) -> object:
item:int = 0
for item in $ID:
self.append(item)
# Removes an item from the middle of vector
def remove_at(self:"Vector", idx: int) -> object:
if idx < 0:
return
while idx < self.size - 1:
self.items[idx] = self.items[idx + 1]
idx = idx + 1
self.size = self.size - 1
# Retrieves an item at a given index
def get(self:"Vector", idx: int) -> int:
return self.items[idx]
# Retrieves the current size of the vector
def length(self:"Vector") -> int:
return self.size
# A faster (but more memory-consuming) implementation of vector
class DoublingVector(Vector):
doubling_limit:int = 1000
# Overriding to do fewer resizes
def increase_capacity(self:"DoublingVector") -> int:
if (self.capacity() <= self.doubling_limit // 2):
self.items = self.items + self.items
else:
# If doubling limit has been reached, fall back to
# standard capacity increases
self.items = self.items + [0]
return self.capacity()
# Makes a vector in the range [i, j)
def vrange(i:int, j:int) -> Vector:
v:Vector = None
v = DoublingVector()
while i < j:
v.append(i)
i = i + 1
return v
# Sieve of Eratosthenes (not really)
def sieve(v:Vector) -> object:
i:int = 0
j:int = 0
k:int = 0
while i < v.length():
k = v.get(i)
j = i + 1
while j < v.length():
if v.get(j) % k == 0:
v.remove_at(j)
else:
j = j + 1
i = i + 1
# Input parameter
n:int = 50
# Data
v:Vector = None
i:int = 0
# Crunch
v = vrange(2, n)
sieve(v)
# Print
while i < v.length():
print(v.get(i))
i = i + 1
|
[
"647530+Virtlink@users.noreply.github.com"
] |
647530+Virtlink@users.noreply.github.com
|
836f316ea7373f660f670c441dd647f0fbff730c
|
6eb9078ce34bed9c895b821aae30f97bcc50ea7d
|
/前端第二课：Django/muggle/blog/admin.py
|
1eb06d37c9dd952bfd268205ff4916ceb34a5fa1
|
[] |
no_license
|
yinsendemogui/Atomspace
|
e7b9e24f8e541f57bdbae2e4d935a3b67133bc69
|
1053d7e3e71365f6acca99431c2d4295243d3df1
|
refs/heads/master
| 2020-06-11T19:24:53.123006
| 2016-12-19T16:53:51
| 2016-12-19T16:53:51
| 75,628,559
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 922
|
py
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
from django.contrib import admin
from blog.models import UserProfile, Topic, Question, Answer, Comment,Ticket
from django.contrib.auth.admin import UserAdmin as BaseUserAdmin
from django.contrib.auth.models import User
# Register your models here.
class UserProfileInline(admin.StackedInline):
model = UserProfile
can_delete = False
verbose_name_plural = 'UserProfile'
class TicketInline(admin.StackedInline):
model = Ticket
can_delete = False
verbose_name_plural = 'Ticket'
class UserAdmin(BaseUserAdmin):
inlines = (UserProfileInline,TicketInline )
admin.site.unregister(User)
admin.site.register(User, UserAdmin)
admin.site.register(UserProfile)
admin.site.register(Topic)
admin.site.register(Question)
admin.site.register(Answer)
admin.site.register(Comment)
admin.site.register(Ticket)
# 超级管理员账号密码: Admin/Admin123456
|
[
"215379068@qq.com"
] |
215379068@qq.com
|
de9fb2ae97800642eda88142b72a772c8c9c47c5
|
2b14ef0b8c086a2dd047f6fab6f565f27c3634c6
|
/BOJ/브루트포스/호석이두마리치킨.py
|
48feda541fda601099cc09a058365b61117ed8f8
|
[] |
no_license
|
psj8532/problem_solving
|
055475bbdc8902ed4d19fd242d95dff461cc9608
|
8ae06fc935c3d0a3c5ec537f13677b0534869df3
|
refs/heads/master
| 2023-06-09T10:16:01.248293
| 2021-05-07T03:09:38
| 2021-05-07T03:09:38
| 240,618,744
| 1
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,312
|
py
|
from itertools import combinations
from _collections import deque
def bfs(here, depth, chicken_house):
if here in chicken_house: return 0
deq = deque([[here, depth]])
visited = [False] * (N + 1)
visited[here] = True
while deq:
h, d = deq.popleft()
if h in chicken_house:
return 2 * d
for next in adj[h]:
if not visited[next]:
visited[next] = True
deq.append([next, d + 1])
CHICKEN_CNT = 2
answer = [0,0,9876543210]
N, M = map(int,input().split())
adj = {i:[] for i in range(N+1)}
for _ in range(M):
start, end = map(int,input().split())
adj[start].append(end)
adj[end].append(start)
perm = list(map(list, combinations(range(1, N + 1), CHICKEN_CNT)))
for chicken_list in perm:
chicken_house = sorted(chicken_list)
distance = 0
for house in range(1, N + 1):
distance += bfs(house, 0 , chicken_house)
if distance == answer[2] and chicken_house[0] <= answer[0]:
if (chicken_house[0] == answer[0] and chicken_house[1] < answer[1]) or (chicken_house[0] < answer[0]):
answer[0], answer[1] = chicken_house[0], chicken_house[1]
elif distance < answer[2]:
answer[0], answer[1], answer[2] = chicken_house[0], chicken_house[1], distance
print(*answer)
|
[
"psj8532@naver.com"
] |
psj8532@naver.com
|
e719c824c41b673746fdbfe99ee5d27001eb7e45
|
5f92dd6164c41e5756842da0a053b207005be252
|
/tests/models/test_dagcode.py
|
6f3c5d64cdf66aa29dc7df109dcd370d4f0fa3d5
|
[
"BSD-3-Clause",
"MIT",
"Apache-2.0"
] |
permissive
|
mans2singh/airflow
|
24d17446457ebfbf17850d336722f79e46b06404
|
de9633f93a366ebc0a46d1ec4df2c4aa9a18357d
|
refs/heads/main
| 2023-03-20T17:56:18.506101
| 2022-10-22T19:41:57
| 2022-10-22T19:41:57
| 168,956,212
| 0
| 0
|
Apache-2.0
| 2019-02-03T14:51:24
| 2019-02-03T14:51:23
| null |
UTF-8
|
Python
| false
| false
| 6,409
|
py
|
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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 writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
from datetime import timedelta
from unittest.mock import patch
import pytest
from airflow import AirflowException, example_dags as example_dags_module
from airflow.models import DagBag
from airflow.models.dagcode import DagCode
# To move it to a shared module.
from airflow.utils.file import open_maybe_zipped
from airflow.utils.session import create_session
from tests.test_utils.db import clear_db_dag_code
def make_example_dags(module):
"""Loads DAGs from a module for test."""
dagbag = DagBag(module.__path__[0])
return dagbag.dags
class TestDagCode:
"""Unit tests for DagCode."""
def setup_method(self):
clear_db_dag_code()
def teardown_method(self):
clear_db_dag_code()
def _write_two_example_dags(self):
example_dags = make_example_dags(example_dags_module)
bash_dag = example_dags['example_bash_operator']
DagCode(bash_dag.fileloc).sync_to_db()
xcom_dag = example_dags['example_xcom']
DagCode(xcom_dag.fileloc).sync_to_db()
return [bash_dag, xcom_dag]
def _write_example_dags(self):
example_dags = make_example_dags(example_dags_module)
for dag in example_dags.values():
dag.sync_to_db()
return example_dags
def test_sync_to_db(self):
"""Dg code can be written into database."""
example_dags = self._write_example_dags()
self._compare_example_dags(example_dags)
def test_bulk_sync_to_db(self):
"""Dg code can be bulk written into database."""
example_dags = make_example_dags(example_dags_module)
files = [dag.fileloc for dag in example_dags.values()]
with create_session() as session:
DagCode.bulk_sync_to_db(files, session=session)
session.commit()
self._compare_example_dags(example_dags)
def test_bulk_sync_to_db_half_files(self):
"""Dg code can be bulk written into database."""
example_dags = make_example_dags(example_dags_module)
files = [dag.fileloc for dag in example_dags.values()]
half_files = files[: int(len(files) / 2)]
with create_session() as session:
DagCode.bulk_sync_to_db(half_files, session=session)
session.commit()
with create_session() as session:
DagCode.bulk_sync_to_db(files, session=session)
session.commit()
self._compare_example_dags(example_dags)
@patch.object(DagCode, 'dag_fileloc_hash')
def test_detecting_duplicate_key(self, mock_hash):
"""Dag code detects duplicate key."""
mock_hash.return_value = 0
with pytest.raises(AirflowException):
self._write_two_example_dags()
def _compare_example_dags(self, example_dags):
with create_session() as session:
for dag in example_dags.values():
if dag.is_subdag:
dag.fileloc = dag.parent_dag.fileloc
assert DagCode.has_dag(dag.fileloc)
dag_fileloc_hash = DagCode.dag_fileloc_hash(dag.fileloc)
result = (
session.query(DagCode.fileloc, DagCode.fileloc_hash, DagCode.source_code)
.filter(DagCode.fileloc == dag.fileloc)
.filter(DagCode.fileloc_hash == dag_fileloc_hash)
.one()
)
assert result.fileloc == dag.fileloc
with open_maybe_zipped(dag.fileloc, 'r') as source:
source_code = source.read()
assert result.source_code == source_code
def test_code_can_be_read_when_no_access_to_file(self):
"""
Test that code can be retrieved from DB when you do not have access to Code file.
Source Code should at least exist in one of DB or File.
"""
example_dag = make_example_dags(example_dags_module).get('example_bash_operator')
example_dag.sync_to_db()
# Mock that there is no access to the Dag File
with patch('airflow.models.dagcode.open_maybe_zipped') as mock_open:
mock_open.side_effect = FileNotFoundError
dag_code = DagCode.get_code_by_fileloc(example_dag.fileloc)
for test_string in ['example_bash_operator', 'also_run_this', 'run_this_last']:
assert test_string in dag_code
def test_db_code_updated_on_dag_file_change(self):
"""Test if DagCode is updated in DB when DAG file is changed"""
example_dag = make_example_dags(example_dags_module).get('example_bash_operator')
example_dag.sync_to_db()
with create_session() as session:
result = session.query(DagCode).filter(DagCode.fileloc == example_dag.fileloc).one()
assert result.fileloc == example_dag.fileloc
assert result.source_code is not None
with patch('airflow.models.dagcode.os.path.getmtime') as mock_mtime:
mock_mtime.return_value = (result.last_updated + timedelta(seconds=1)).timestamp()
with patch('airflow.models.dagcode.DagCode._get_code_from_file') as mock_code:
mock_code.return_value = "# dummy code"
example_dag.sync_to_db()
with create_session() as session:
new_result = session.query(DagCode).filter(DagCode.fileloc == example_dag.fileloc).one()
assert new_result.fileloc == example_dag.fileloc
assert new_result.source_code == "# dummy code"
assert new_result.last_updated > result.last_updated
|
[
"noreply@github.com"
] |
mans2singh.noreply@github.com
|
2f3246645ae2b648b8a03a0fbdc252ec71da5335
|
119646d6e1f13582c577fd7b87c9654839a0b806
|
/hubspot/cms/domains/api/__init__.py
|
b4e60c2edbcb4bf654f47d3f798df161efd090c9
|
[] |
permissive
|
HubSpot/hubspot-api-python
|
446daaceeb3a6ce27edcd0414603c6d4bc07e327
|
d51a64c413461c0b82d8a41743e752d878747ca1
|
refs/heads/master
| 2023-08-31T09:52:56.583803
| 2023-08-07T11:00:27
| 2023-08-07T11:00:27
| 248,865,684
| 227
| 98
|
Apache-2.0
| 2023-09-14T15:25:19
| 2020-03-20T22:41:24
|
Python
|
UTF-8
|
Python
| false
| false
| 146
|
py
|
from __future__ import absolute_import
# flake8: noqa
# import apis into api package
from hubspot.cms.domains.api.domains_api import DomainsApi
|
[
"atanasiuk@hubspot.com"
] |
atanasiuk@hubspot.com
|
d09be6ac32398bbd0397467b2ebf8504d775e116
|
356740062993a5967717098a7a3ee78ac6c6cf3f
|
/chapter15/projects/brute_force_pdf/pdf_password_breaker.py
|
814c051fc597e336a223e62a06f1d762f59c9ba6
|
[] |
no_license
|
xerifeazeitona/autbor
|
79588302f14c0c09b1f9f57fcb973e656ee1da5c
|
c37ccbfa87c1ac260e728a3a91a8f2be97978f04
|
refs/heads/main
| 2023-04-03T18:01:34.588984
| 2021-04-07T17:59:26
| 2021-04-07T17:59:26
| 348,749,618
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,528
|
py
|
"""
Brute-Force PDF Password Breaker
Say you have an encrypted PDF that you have forgotten the password to,
but you remember it was a single English word. Trying to guess your
forgotten password is quite a boring task.
Instead you can write a program that will decrypt the PDF by trying
every possible English word until it finds one that works.
The text file dictionary.txt contains over 44,000 English words. Using
the file-reading skills you learned in Chapter 9, create a list of word
strings by reading this file.
Then loop over each word in this list, passing it to the decrypt()
method.
If this method returns the integer 0, the password was wrong and your
program should continue to the next password.
If decrypt() returns 1, then your program should break out of the loop
and print the hacked password.
You should try both the uppercase and lowercase form of each word.
"""
import sys
import PyPDF2
# Open PDF file
pdf_reader = PyPDF2.PdfFileReader(open('encrypted.pdf', 'rb'))
# Read dictionary words from text file
with open('dictionary.txt') as file_object:
wordlist = file_object.read().split('\n')
# try to brute-force the password
total_words = len(wordlist)
for i, word in enumerate(wordlist):
print(f'\r{i} / {total_words}', end='')
if pdf_reader.decrypt(word) == 1:
print(f'\nPassword found: "{word}"')
sys.exit()
if pdf_reader.decrypt(word.lower()) == 1:
print(f'\nPassword found: "{word.lower()}"')
sys.exit()
print('\nCould not find a valid password.')
|
[
"juliano.amaral@gmail.com"
] |
juliano.amaral@gmail.com
|
b9f7406f059d850f23f3e542f6e85d3ad59ee508
|
cd555725b300579d44c0bd3f6fc8f6a968912dfb
|
/UF2/Practica 25/Ejercicio4/main.py
|
b5ab8a5b60b80fa92c11bf55fc828788bc6704fe
|
[] |
no_license
|
aleexnl/aws-python
|
2da5d8a416927f381618f1d6076d98d5e35b3b5e
|
03fce7744b443b2b59a02c261067ecae46ecc3d9
|
refs/heads/master
| 2022-11-24T08:58:24.686651
| 2020-04-18T15:58:32
| 2020-04-18T15:58:32
| 221,772,677
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 158
|
py
|
from module import functions as fc # Llamamos al modulo que contiene las funciones
print(fc.mcd(30, 3)) # Llamamos a la funcion y le pasamos dos parametros
|
[
"alex.nieto0027@gmail.com"
] |
alex.nieto0027@gmail.com
|
a7bf7e1b684f8cbdcd574f13eed72023cf50bd3d
|
1bfad01139237049eded6c42981ee9b4c09bb6de
|
/RestPy/ixnetwork_restpy/testplatform/sessions/ixnetwork/statistics/view/formulacatalog/formulacatalog.py
|
b878626afcde61247e92d719fe488330d5646617
|
[
"MIT"
] |
permissive
|
kakkotetsu/IxNetwork
|
3a395c2b4de1488994a0cfe51bca36d21e4368a5
|
f9fb614b51bb8988af035967991ad36702933274
|
refs/heads/master
| 2020-04-22T09:46:37.408010
| 2019-02-07T18:12:20
| 2019-02-07T18:12:20
| 170,284,084
| 0
| 0
|
MIT
| 2019-02-12T08:51:02
| 2019-02-12T08:51:01
| null |
UTF-8
|
Python
| false
| false
| 2,267
|
py
|
# Copyright 1997 - 2018 by IXIA Keysight
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
from ixnetwork_restpy.base import Base
from ixnetwork_restpy.files import Files
class FormulaCatalog(Base):
"""The FormulaCatalog class encapsulates a required formulaCatalog node in the ixnetwork hierarchy.
An instance of the class can be obtained by accessing the FormulaCatalog property from a parent instance.
The internal properties list will contain one and only one set of properties which is populated when the property is accessed.
"""
_SDM_NAME = 'formulaCatalog'
def __init__(self, parent):
super(FormulaCatalog, self).__init__(parent)
@property
def FormulaColumn(self):
"""An instance of the FormulaColumn class.
Returns:
obj(ixnetwork_restpy.testplatform.sessions.ixnetwork.statistics.view.formulacatalog.formulacolumn.formulacolumn.FormulaColumn)
Raises:
NotFoundError: The requested resource does not exist on the server
ServerError: The server has encountered an uncategorized error condition
"""
from ixnetwork_restpy.testplatform.sessions.ixnetwork.statistics.view.formulacatalog.formulacolumn.formulacolumn import FormulaColumn
return FormulaColumn(self)
|
[
"hubert.gee@keysight.com"
] |
hubert.gee@keysight.com
|
3629c99cabd1fa8d37fb6433b4c595dcf55e3483
|
6c816f19d7f4a3d89abbb00eeaf43dd818ecc34f
|
/venv/Scripts/easy_install-3.6-script.py
|
a95d3aabec1724ba66e9a38d3cbc071eb631e331
|
[] |
no_license
|
reo-dev/bolt
|
29ee6aa7cfc96bd50fa7a7dae07fbaafc2125e54
|
d1a7859dd1ebe2f5b0e6e295047b620f5afdb92e
|
refs/heads/master
| 2023-07-13T04:05:57.856278
| 2021-08-27T09:07:03
| 2021-08-27T09:07:03
| 382,195,547
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 491
|
py
|
#!C:\Users\kwongibin.DESKTOP-KIC4V0D\PycharmProjects\bolttnut\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'setuptools==39.1.0','console_scripts','easy_install-3.6'
__requires__ = 'setuptools==39.1.0'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('setuptools==39.1.0', 'console_scripts', 'easy_install-3.6')()
)
|
[
"75593016+reo-dev@users.noreply.github.com"
] |
75593016+reo-dev@users.noreply.github.com
|
4e775386203f7562b4f2575de0d1b52520df4054
|
eb677df036fb922c36be3ac309a6b51137161343
|
/bin/alpha
|
fd242e28ca7f18e5ca9be924643804c1d152bc05
|
[] |
no_license
|
kmyk/dotfiles
|
f1be5f1732a22a44605faca92a003de7a40968fa
|
33fbd461135fa6bc4b954c403402d4433cc45abd
|
refs/heads/master
| 2021-07-02T03:17:12.814548
| 2020-09-20T05:56:52
| 2020-09-20T05:56:52
| 11,720,259
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 663
|
#!/usr/bin/env python
import sys
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-u', '--upper', action='store_true')
parser.add_argument('-l', '--lower', action='store_false', dest='upper')
parser.add_argument('-d', '--delimiter', type=str, default=' ')
parser.add_argument('-1', action='store_const', const="\n", dest='delimiter')
parser.add_argument('-0', action='store_const', const='', dest='delimiter')
parser.add_argument('-n', action='store_const', default="\n", const='')
args = parser.parse_args()
sys.stdout.write(args.delimiter.join(list("ABCDEFGHIJKLMNOPQRSTUVWXYZ" if args.upper else "abcdefghijklmnopqrstuvwxyz"))+args.n)
|
[
"kimiyuki95@gmail.com"
] |
kimiyuki95@gmail.com
|
|
bde40d296203cf014d6fa9584b60e567c306d60d
|
781e2692049e87a4256320c76e82a19be257a05d
|
/all_data/exercism_data/python/rna-transcription/64f6942fedc844af848cc19de6e53748.py
|
bc316926c867570f3906523b44066297c83447b6
|
[] |
no_license
|
itsolutionscorp/AutoStyle-Clustering
|
54bde86fe6dbad35b568b38cfcb14c5ffaab51b0
|
be0e2f635a7558f56c61bc0b36c6146b01d1e6e6
|
refs/heads/master
| 2020-12-11T07:27:19.291038
| 2016-03-16T03:18:00
| 2016-03-16T03:18:42
| 59,454,921
| 4
| 0
| null | 2016-05-23T05:40:56
| 2016-05-23T05:40:56
| null |
UTF-8
|
Python
| false
| false
| 239
|
py
|
#didnt work out with replace method
#so i used the translate method with a map
#Is translate deprecated in Python3.4?
def to_rna(what):
mapper = what.maketrans('GCTA','CGAU')
what = what.translate(mapper)
return what
|
[
"rrc@berkeley.edu"
] |
rrc@berkeley.edu
|
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