Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('personal', '0006_personal_imagen'), ] operations = [ migrations.AlterField( model_name='personal', name='condiciones_alta', field=models.CharField(default=b'', max_length=150, blank=True), preserve_default=True, ), migrations.AlterField( model_name='personal', name='cuip', field=models.CharField(max_length=30, blank=True), preserve_default=True, ), migrations.AlterField( model_name='personal', name='id_seguridad_social', field=models.CharField(max_length=20, blank=True), preserve_default=True, ), ]

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from django.contrib import admin from newspaper.models import * # Register your models here. @admin.register(News, Image) class PersonAdmin(admin.ModelAdmin): pass

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felchuck@yandex.ru

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/github.com/ceph/ceph-deploy/ceph_deploy/util/wrappers.py

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""" In a lot of places we need to make system calls, mainly through subprocess. Here we define them and reuse them with the added functionality of getting logging and remote execution. This allows us to only remote-execute the actual calls, not whole functions. """ from ceph_deploy.util.decorators import remote_compile from ceph_deploy.util import context def check_call(conn, logger, args, *a, **kw): """ Wraps ``subprocess.check_call`` for a remote call via ``pushy`` doing all the capturing and logging nicely upon failure/success The mangling of the traceback when an exception ocurrs, is because the caller gets eating up by not being executed in the actual function of a given module (e.g. ``centos/install.py``) but rather here, where the stack trace is no longer relevant. :param args: The args to be passed onto ``check_call`` """ command = ' '.join(args) patch = kw.pop('patch', True) # Always patch unless explicitly told to logger.info('Running command: %s' % command) def remote_call(args, *a, **kw): import subprocess subprocess.check_call( args, *a, **kw ) with context.remote(conn, logger, remote_call, mangle_exc=False, patch=patch) as call: try: return call(args, *a, **kw) except Exception as err: import inspect stack = inspect.getframeinfo(inspect.currentframe().f_back) if hasattr(err, 'remote_traceback'): logger.error('Traceback (most recent call last):') logger.error(' File "%s", line %s, in %s' % ( stack[0], stack[1], stack[2]) ) err.remote_traceback.pop(0) for line in err.remote_traceback: if line: logger.error(line) raise RuntimeError('Failed to execute command: %s' % ' '.join(args)) else: raise err

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roman.heinrich@gmail.com

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/makeDigikeyBOM.py

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BitKnitting/MakeDigikeyBOM

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2021-01-13T00:59:15.063713

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# # The main entry point to making a digikey Bom CSV file from the output of bom2csv # as discussed in the bitknitting blog post: https://bitknitting.wordpress.com/2016/03/05/from-kicad-to-digikey-generating-a-bom-based-on-esteem-overview/ # import logging logger = logging.getLogger(__name__) from replaceJellyBeanParts import replaceJellyBeanParts from makeDigikeyFile import makeDigikeyFile from getParts import getParts def makeDigikeyBOM(outputFrom_bom2csv,jellyBeanFile,outDir,numProcesses): modifiedBOM2csvFile = replaceJellyBeanParts(outputFrom_bom2csv=outputFrom_bom2csv,jellyBeanFile=jellyBeanFile) components_by_part_number = getParts(modifiedBOM2csvFile=modifiedBOM2csvFile) if not makeDigikeyFile(components_by_part_number,outDir): logger.error("Could not make the Digikey file. Check output from logger.")

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# coding: utf-8 """ Adobe Experience Manager OSGI config (AEM) API Swagger AEM OSGI is an OpenAPI specification for Adobe Experience Manager (AEM) OSGI Configurations API # noqa: E501 The version of the OpenAPI document: 1.0.0 Contact: opensource@shinesolutions.com Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import unittest import swaggeraemosgi from swaggeraemosgi.models.com_adobe_granite_repository_hc_impl_authorizable_node_name_health_check_properties import ComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties # noqa: E501 from swaggeraemosgi.rest import ApiException class TestComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties(unittest.TestCase): """ComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties unit test stubs""" def setUp(self): pass def tearDown(self): pass def testComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties(self): """Test ComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties""" # FIXME: construct object with mandatory attributes with example values # model = swaggeraemosgi.models.com_adobe_granite_repository_hc_impl_authorizable_node_name_health_check_properties.ComAdobeGraniteRepositoryHcImplAuthorizableNodeNameHealthCheckProperties() # noqa: E501 pass if __name__ == '__main__': unittest.main()

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# SPDX-FileCopyrightText: 2021 ladyada for Adafruit Industries # SPDX-License-Identifier: MIT import time import board import adafruit_pct2075 i2c = board.I2C() # uses board.SCL and board.SDA pct = adafruit_pct2075.PCT2075(i2c) pct.high_temperature_threshold = 35.5 pct.temperature_hysteresis = 30.0 pct.high_temp_active_high = False print("High temp alert active high? %s" % pct.high_temp_active_high) # Attach an LED with the Cathode to the INT pin and Anode to 3.3V with a current limiting resistor while True: print("Temperature: %.2f C" % pct.temperature) time.sleep(0.5)

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from urllib import urlopen from bs4 import BeautifulSoup html = urlopen("http://www.pythonscraping.com/pages/page3.html") bsObj = BeautifulSoup(html, "html.parser") for sibling in bsObj.find("table", {"id":"giftList"}).tr.next_siblings: print(sibling)

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import numpy.random import milk.unsupervised.pca import numpy as np def test_pca(): numpy.random.seed(123) X = numpy.random.rand(10,4) X[:,1] += numpy.random.rand(10)**2*X[:,0] X[:,1] += numpy.random.rand(10)**2*X[:,0] X[:,2] += numpy.random.rand(10)**2*X[:,0] Y,V = milk.unsupervised.pca(X) Xn = milk.unsupervised.normalise.zscore(X) assert X.shape == Y.shape assert ((np.dot(V[:4].T,Y[:,:4].T).T-Xn)**2).sum()/(Xn**2).sum() < .3

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/learning/20.BayesianNetwork/20.1.Iris_GaussianNB.py

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alenzhd/meachineLearning

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#!/usr/bin/python # -*- coding:utf-8 -*- import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib as mpl from sklearn.preprocessing import StandardScaler, MinMaxScaler, PolynomialFeatures from sklearn.naive_bayes import GaussianNB, MultinomialNB from sklearn.pipeline import Pipeline from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split from sklearn.neighbors import KNeighborsClassifier def iris_type(s): it = {'Iris-setosa': 0, 'Iris-versicolor': 1, 'Iris-virginica': 2} return it[s] if __name__ == "__main__": data = pd.read_csv('..\\8.Regression\\iris.data', header=None) x, y = data[np.arange(4)], data[4] y = pd.Categorical(values=y).codes feature_names = u'花萼长度', u'花萼宽度', u'花瓣长度', u'花瓣宽度' features = [0,1] x = x[features] x, x_test, y, y_test = train_test_split(x, y, train_size=0.7, random_state=0) priors = np.array((1,2,4), dtype=float) priors /= priors.sum() gnb = Pipeline([ ('sc', StandardScaler()), ('poly', PolynomialFeatures(degree=1)), ('clf', GaussianNB(priors=priors))]) # 由于鸢尾花数据是样本均衡的，其实不需要设置先验值 # gnb = KNeighborsClassifier(n_neighbors=3).fit(x, y.ravel()) gnb.fit(x, y.ravel()) y_hat = gnb.predict(x) print ('训练集准确度: %.2f%%' % (100 * accuracy_score(y, y_hat))) y_test_hat = gnb.predict(x_test) print ('测试集准确度：%.2f%%' % (100 * accuracy_score(y_test, y_test_hat))) # 画图 N, M = 500, 500 # 横纵各采样多少个值 x1_min, x2_min = x.min() x1_max, x2_max = x.max() t1 = np.linspace(x1_min, x1_max, N) t2 = np.linspace(x2_min, x2_max, M) x1, x2 = np.meshgrid(t1, t2) # 生成网格采样点 x_grid = np.stack((x1.flat, x2.flat), axis=1) # 测试点 mpl.rcParams['font.sans-serif'] = [u'simHei'] mpl.rcParams['axes.unicode_minus'] = False cm_light = mpl.colors.ListedColormap(['#77E0A0', '#FF8080', '#A0A0FF']) cm_dark = mpl.colors.ListedColormap(['g', 'r', 'b']) y_grid_hat = gnb.predict(x_grid) # 预测值 y_grid_hat = y_grid_hat.reshape(x1.shape) plt.figure(facecolor='w') plt.pcolormesh(x1, x2, y_grid_hat, cmap=cm_light) # 预测值的显示 plt.scatter(x[features[0]], x[features[1]], c=y, edgecolors='k', s=50, cmap=cm_dark) plt.scatter(x_test[features[0]], x_test[features[1]], c=y_test, marker='^', edgecolors='k', s=120, cmap=cm_dark) plt.xlabel(feature_names[features[0]], fontsize=13) plt.ylabel(feature_names[features[1]], fontsize=13) plt.xlim(x1_min, x1_max) plt.ylim(x2_min, x2_max) plt.title(u'GaussianNB对鸢尾花数据的分类结果', fontsize=18) plt.grid(True) plt.show()

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# -*- coding: utf-8 -*- ############################################################################### # # CreateInvite # Invites a user to become friends with authorized user. # # Python versions 2.6, 2.7, 3.x # # Copyright 2014, Temboo Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in 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 temboo.core.choreography import Choreography from temboo.core.choreography import InputSet from temboo.core.choreography import ResultSet from temboo.core.choreography import ChoreographyExecution import json class CreateInvite(Choreography): def __init__(self, temboo_session): """ Create a new instance of the CreateInvite Choreo. A TembooSession object, containing a valid set of Temboo credentials, must be supplied. """ super(CreateInvite, self).__init__(temboo_session, '/Library/Fitbit/Social/CreateInvite') def new_input_set(self): return CreateInviteInputSet() def _make_result_set(self, result, path): return CreateInviteResultSet(result, path) def _make_execution(self, session, exec_id, path): return CreateInviteChoreographyExecution(session, exec_id, path) class CreateInviteInputSet(InputSet): """ An InputSet with methods appropriate for specifying the inputs to the CreateInvite Choreo. The InputSet object is used to specify input parameters when executing this Choreo. """ def set_AccessTokenSecret(self, value): """ Set the value of the AccessTokenSecret input for this Choreo. ((required, string) The Access Token Secret retrieved during the OAuth process.) """ super(CreateInviteInputSet, self)._set_input('AccessTokenSecret', value) def set_AccessToken(self, value): """ Set the value of the AccessToken input for this Choreo. ((required, string) The Access Token retrieved during the OAuth process.) """ super(CreateInviteInputSet, self)._set_input('AccessToken', value) def set_ConsumerKey(self, value): """ Set the value of the ConsumerKey input for this Choreo. ((required, string) The Consumer Key provided by Fitbit.) """ super(CreateInviteInputSet, self)._set_input('ConsumerKey', value) def set_ConsumerSecret(self, value): """ Set the value of the ConsumerSecret input for this Choreo. ((required, string) The Consumer Secret provided by Fitbit.) """ super(CreateInviteInputSet, self)._set_input('ConsumerSecret', value) def set_InvitedUserEmail(self, value): """ Set the value of the InvitedUserEmail input for this Choreo. ((conditional, string) The email address of the user to invite; user can be a Fitbit member already. Required unless providing the InvitedUserID.) """ super(CreateInviteInputSet, self)._set_input('InvitedUserEmail', value) def set_InvitedUserID(self, value): """ Set the value of the InvitedUserID input for this Choreo. ((conditional, string) The Fitbit user id of the user to send an invite to. Required unless providing the InvitedUserEmail.) """ super(CreateInviteInputSet, self)._set_input('InvitedUserID', value) def set_ResponseFormat(self, value): """ Set the value of the ResponseFormat input for this Choreo. ((optional, string) The format that you want the response to be in: xml or json. Defaults to json.) """ super(CreateInviteInputSet, self)._set_input('ResponseFormat', value) def set_UserID(self, value): """ Set the value of the UserID input for this Choreo. ((optional, string) The user's encoded id. Defaults to "-" (dash) which will return data for the user associated with the token credentials provided.) """ super(CreateInviteInputSet, self)._set_input('UserID', value) class CreateInviteResultSet(ResultSet): """ A ResultSet with methods tailored to the values returned by the CreateInvite Choreo. The ResultSet object is used to retrieve the results of a Choreo execution. """ def getJSONFromString(self, str): return json.loads(str) def get_Response(self): """ Retrieve the value for the "Response" output from this Choreo execution. (The response from Fitbit.) """ return self._output.get('Response', None) class CreateInviteChoreographyExecution(ChoreographyExecution): def _make_result_set(self, response, path): return CreateInviteResultSet(response, path)

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#!/usr/bin/env python '''SSH''' import socket import threading import paramiko import sys # using the demo keys in the paramiko demo files host_key = paramiko.RSAKey(filename='test_rsa.key') #print host_key.get_base64() class Server(paramiko.ServerInterface): def __init__(self): self.event = threading.Event() def check_channel_request(self, kind, chanid): if kind == 'session': return paramiko.OPEN_SUCCEEDED return paramiko.OPEN_FAILED_ADMINISTRATIVELY_PROHIBITED def check_auth_password(self, username, password): if (username == 'joker') and (password == 'joker'): return paramiko.AUTH_SUCCESSFUL return paramiko.AUTH_FAILED def main(): '''Main''' server = sys.argv[1] ssh_port = int(sys.argv[2]) try: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) sock.bind((server, ssh_port)) sock.listen(100) print '[+] Listening for connection...' client, addr = sock.accept() except Exception, e: print '[-] Listen failed: ' + str(e) sys.exit(1) #print '[+] Got a connection to %s:%d!' % (addr[1], addr[2]) try: bh_session = paramiko.Transport(client) bh_session.add_server_key(host_key) server = Server() try: bh_session.start_server(server=server) except paramiko.SSHException, x: print '[-] SSH negotiation failed.' chan = bh_session.accept(20) print '[+] Authenticated!' print chan.recv(1024) chan.send('Welcome to bh_ssh') while True: try: command = raw_input("Enter command: ").strip('\n') if command != 'exit': chan.send(command) print chan.recv(1024) + '\n' else: chan.send('exit') print 'exiting' bh_session.close() raise Exception('exit') except KeyboardInterrupt: bh_session.close() except Exception, e: print '[-] Caught exception: ' + str(e) try: bh_session.close() except: pass sys.exit(1) main()

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# -*- coding: iso-8859-1 -*- """ crypto.keyedHash.pbkdf2 Password Based Key Derivation Function 2 References: RFC2898, B. Kaliski, September 2000, PKCS #5 This function is used for IEEE 802.11/WPA passphrase to key hashing Copyright © (c) 2002 by Paul A. Lambert Read LICENSE.txt for license information. """ from ..keyedHash.hmacHash import HMAC_SHA1 from ..common import xor from math import ceil from struct import pack def pbkdf2(password, salt, iterations, keySize, PRF=HMAC_SHA1): """ Create key of size keySize from password and salt """ if len(password)>63: raise 'Password too long for pbkdf2' #if len(password)<8 : raise 'Password too short for pbkdf2' if (keySize > 10000): # spec says >4294967295L*digestSize raise 'keySize too long for PBKDF2' prf = PRF(key=password) # HMAC_SHA1 numBlocks = int(ceil(1.*keySize/prf.digest_size)) # ceiling function key = '' for block in range(1,numBlocks+1): # Calculate F(P, salt, iterations, i) F = prf(salt+pack('>i',block)) # i is packed into 4 big-endian bytes U = prf(salt+pack('>i',block)) # i is packed into 4 big-endian bytes for count in range(2,iterations+1): U = prf(U) F = xor(F,U) key = key + F return key[:keySize] def dot11PassPhraseToPSK(passPhrase,ssid): """ The 802.11 TGi recommended pass-phrase-to-preshared-key mapping. This function simply uses pbkdf2 with interations=4096 and keySize=32 """ assert( 7<len(passPhrase)<64 ), 'Passphrase must be greater than 7 or less than 64 characters' return pbkdf2(passPhrase, ssid, iterations=4096, keySize=32)

[ "mrknow@interia.pl" ]

mrknow@interia.pl

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/Python Books/PythonTesting-BeginnersGuide/code/tests/test_chapter5/test_pid.py

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theGreenJedi/Path

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refs/heads/master

2023-07-27T14:23:37.694546

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from unittest import TestCase, main from mocker import Mocker import pid class test_pid_constructor(TestCase): def test_without_when(self): mocker = Mocker() mock_time = mocker.replace('time.time') mock_time() mocker.result(1.0) mocker.replay() controller = pid.PID(P = 0.5, I = 0.5, D = 0.5, setpoint = 0, initial = 12) mocker.restore() mocker.verify() self.assertEqual(controller.gains, (0.5, 0.5, 0.5)) self.assertAlmostEqual(controller.setpoint[0], 0.0) self.assertEqual(len(controller.setpoint), 1) self.assertAlmostEqual(controller.previous_time, 1.0) self.assertAlmostEqual(controller.previous_error, -12.0) self.assertAlmostEqual(controller.integrated_error, 0) def test_with_when(self): controller = pid.PID(P = 0.5, I = 0.5, D = 0.5, setpoint = 1, initial = 12, when = 43) self.assertEqual(controller.gains, (0.5, 0.5, 0.5)) self.assertAlmostEqual(controller.setpoint[0], 1.0) self.assertEqual(len(controller.setpoint), 1) self.assertAlmostEqual(controller.previous_time, 43.0) self.assertAlmostEqual(controller.previous_error, -11.0) self.assertAlmostEqual(controller.integrated_error, 0) class test_calculate_response(TestCase): def test_without_when(self): mocker = Mocker() mock_time = mocker.replace('time.time') mock_time() mocker.result(1.0) mock_time() mocker.result(2.0) mock_time() mocker.result(3.0) mock_time() mocker.result(4.0) mock_time() mocker.result(5.0) mocker.replay() controller = pid.PID(P = 0.5, I = 0.5, D = 0.5, setpoint = 0, initial = 12) self.assertEqual(controller.calculate_response(6), -3) self.assertEqual(controller.calculate_response(3), -4.5) self.assertEqual(controller.calculate_response(-1.5), -0.75) self.assertEqual(controller.calculate_response(-2.25), -1.125) mocker.restore() mocker.verify() def test_with_when(self): controller = pid.PID(P = 0.5, I = 0.5, D = 0.5, setpoint = 0, initial = 12, when = 1) self.assertEqual(controller.calculate_response(6, 2), -3) self.assertEqual(controller.calculate_response(3, 3), -4.5) self.assertEqual(controller.calculate_response(-1.5, 4), -0.75) self.assertEqual(controller.calculate_response(-2.25, 5), -1.125) if __name__ == '__main__': main()

[ "GreenJedi@protonmail.com" ]

GreenJedi@protonmail.com

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/mime_gen_both.py

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wwwlwscom/python

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refs/heads/master

2021-01-20T10:06:17.251976

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py

#!/usr/bin/env python from email.MIMEText import MIMEText from email.MIMEMultipart import MIMEMultipart from email.MIMEBase import MIMEBase from email import Utils, Encoders import mimetypes, sys def genpart(data, contenttype): maintype, subtype = contenttype.split('/') if maintype == 'text': retval = MIMEText(data, _subtype=subtype) else: retval = MIMEBase(maintype, subtype) retval.set_payload(data) Encoders.encode_base64(retval) return retval def attachment(filename): fd = open(filename, 'rb') mimetype, mimeencoding = mimetypes.guess_type(filename) if mimeencoding or (mimetype is None): mimetype = 'application/octet-stream' retval = genpart(fd.read(), mimetype) retval.add_header('Content-Disposition', 'attachment', filename = filename) fd.close() return retval message = """Hello, This is a test message from Rock. I hope you enjoy it! --Anonymous""" messagehtml = """Hello, This is a greattest message from Rock. I hope you enjoy it! --Anonymous""" msg = MIMEMultipart() msg['To'] = 'recipient@example.com' msg['From'] = 'Test Sender <sender@example.com>' msg['Subject'] = 'Test Message, Rock' msg['Date'] = Utils.formatdate(localtime = 1) msg['Message-ID'] = Utils.make_msgid() body = MIMEMultipart('alternative') body.attach(genpart(message, 'text/plain')) body.attach(genpart(messagehtml, 'text/html')) msg.attach(body) for filename in sys.argv[1:]: msg.attach(attachment(filename)) print msg.as_string()

[ "root@localhost.localdomain" ]

root@localhost.localdomain

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/gen.py

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[]

no_license

robert-giaquinto/baum-welch

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b57fb2bd64ed3fdfed1552a6ea5afd9c7c120cfc

refs/heads/master

2021-01-15T09:09:29.267399

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import random import numpy as np N_SEQ = 10 START = 0 BEFORE = 1 AFTER = 2 END = 3 def gen_seq(): seq = [] state = START while state != END: if state == START: state = BEFORE seq.append('S') if state == BEFORE: n, l, r = np.random.multinomial(1, [0.96, 0.036, 0.004]) if n: seq.append('N') elif l: seq.append('L') else: seq.append('R') state += np.random.binomial(1, 1/5000.) if state == AFTER: n, l, r = np.random.multinomial(1, [0.96, 0.004, 0.036]) if n: seq.append('N') elif l: seq.append('L') else: seq.append('R') state += np.random.binomial(1, 1/5000.) seq.append('E') return seq if __name__ == '__main__': random.seed(42) for i in xrange(N_SEQ): seq = gen_seq() print ''.join(seq)

[ "piotrek.kaleta@gmail.com" ]

piotrek.kaleta@gmail.com

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/configs/D2Det/D2Det_detection_r101_fpn_2x.py

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permissive

Randl/D2Det

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2022-09-25T13:52:21.141590

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# model settings model = dict( type='D2Det', pretrained='torchvision://resnet101', backbone=dict( type='ResNet', depth=101, num_stages=4, out_indices=(0, 1, 2, 3), frozen_stages=1, style='pytorch'), neck=dict( type='FPN', in_channels=[256, 512, 1024, 2048], out_channels=256, num_outs=5), rpn_head=dict( type='RPNHead', in_channels=256, feat_channels=256, anchor_scales=[8], anchor_ratios=[0.5, 1.0, 2.0], anchor_strides=[4, 8, 16, 32, 64], target_means=[.0, .0, .0, .0], target_stds=[1.0, 1.0, 1.0, 1.0], loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0)), bbox_roi_extractor=dict( type='SingleRoIExtractor', roi_layer=dict( type='DeformRoIPoolingPack', out_size=7, sample_per_part=1, out_channels=256, no_trans=False, group_size=1, trans_std=0.1), out_channels=256, featmap_strides=[4, 8, 16, 32]), bbox_head=dict( type='SharedFCBBoxHead', with_reg=False, num_fcs=2, in_channels=256, fc_out_channels=1024, roi_feat_size=7, num_classes=81, target_means=[0., 0., 0., 0.], target_stds=[0.1, 0.1, 0.2, 0.2], reg_class_agnostic=False, loss_cls=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=2.0)), reg_roi_extractor=dict( type='SingleRoIExtractor', roi_layer=dict(type='RoIAlign', out_size=14, sample_num=2), out_channels=256, featmap_strides=[4, 8, 16, 32]), D2Det_head=dict( type='D2DetHead', num_convs=8, in_channels=256, norm_cfg=dict(type='GN', num_groups=36), MASK_ON=False)) # model training and testing settings train_cfg = dict( rpn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.7, neg_iou_thr=0.3, min_pos_iou=0.3, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=256, pos_fraction=0.5, neg_pos_ub=-1, add_gt_as_proposals=False), allowed_border=0, pos_weight=-1, debug=False), rpn_proposal=dict( nms_across_levels=False, nms_pre=2000, nms_post=2000, max_num=2000, nms_thr=0.7, min_bbox_size=0), rcnn=dict( assigner=dict( type='MaxIoUAssigner', pos_iou_thr=0.5, neg_iou_thr=0.5, min_pos_iou=0.5, ignore_iof_thr=-1), sampler=dict( type='RandomSampler', num=512, pos_fraction=0.25, neg_pos_ub=-1, add_gt_as_proposals=True), pos_radius=1, pos_weight=-1, max_num_grid=192, debug=False)) test_cfg = dict( rpn=dict( nms_across_levels=False, nms_pre=1000, nms_post=1000, max_num=1000, nms_thr=0.7, min_bbox_size=0), rcnn=dict( score_thr=0.03, nms=dict(type='nms', iou_thr=0.5), max_per_img=125)) # dataset settings dataset_type = 'CocoDataset' data_root = 'data/coco/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict(type='Resize', img_scale=(1333, 800), keep_ratio=True), dict(type='RandomFlip', flip_ratio=0.5), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']), ] test_pipeline = [ dict(type='LoadImageFromFile'), dict( type='MultiScaleFlipAug', img_scale=(1333, 800), flip=False, transforms=[ dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', **img_norm_cfg), dict(type='Pad', size_divisor=32), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img']), ]) ] data = dict( imgs_per_gpu=2, workers_per_gpu=2, train=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_train2017.json', img_prefix=data_root + 'train2017/', pipeline=train_pipeline), val=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_val2017.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline), test=dict( type=dataset_type, ann_file=data_root + 'annotations/instances_val2017.json', img_prefix=data_root + 'val2017/', pipeline=test_pipeline)) evaluation = dict(interval=1, metric='bbox') # optimizer optimizer = dict(type='SGD', lr=0.02, momentum=0.9, weight_decay=0.0001) optimizer_config = dict(grad_clip=None) # learning policy lr_config = dict( policy='step', warmup='linear', warmup_iters=1000, warmup_ratio=1.0 / 80, step=[20, 23]) checkpoint_config = dict(interval=1) # yapf:disable log_config = dict( interval=50, hooks=[ dict(type='TextLoggerHook'), # dict(type='TensorboardLoggerHook') ]) # yapf:enable # runtime settings total_epochs = 24 dist_params = dict(backend='nccl') log_level = 'INFO' work_dir = './work_dirs/D2Det_detection_r101_fpn_2x' load_from = None resume_from = None workflow = [('train', 1)]

[ "connor@tju.edu.cn" ]

connor@tju.edu.cn

7d812592e10d2a0d003e3156aef68f26c0796648

601adbb343313e7cce71b9b8d06620f541f349e5

/tests/test_ci/test_runners/test_BaseRunner.py

4545078bf38683e3c939099329a8ad2f0d27d15f

[]

no_license

jgsogo/conan-sword-and-sorcery

f3ff2c9b739410a7fb6eb97c49470d585fd1ab4c

143f05d8b469a3afc9c807ec87fbe2dcbe63dab3

refs/heads/master

2021-04-06T06:23:40.584031

2018-08-15T16:50:43

124,441,534

1

0

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UTF-8

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py

# -*- coding: utf-8 -*- import os import unittest try: from unittest import mock except ImportError: import mock from conan_sword_and_sorcery.ci.runners import AppveyorRunner from conan_sword_and_sorcery.ci.runners.base_runner import SUCCESS, FAIL, DRY_RUN, BaseRunner from conan_sword_and_sorcery.parsers.settings import get_settings from conan_sword_and_sorcery.utils.environ import context_env from conan_sword_and_sorcery.parsers.profile import profile_for from tests.utils import TestCaseEnvClean class JobGeneratorClass4Testing: def __init__(self, *args, **kwargs): pass class BaseRunner4Testing(BaseRunner): job_generator_class = JobGeneratorClass4Testing class TestBaseRunnerStableBranch(TestCaseEnvClean): def setUp(self): self.settings = get_settings() # Dummy (but valid) conanfile me = os.path.dirname(__file__) self.conanfile = os.path.join(me, '..', '..', 'files', 'single', 'conanfile01.py') def test_enumerate_jobs(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows") with context_env(CONAN_VISUAL_VERSIONS="12", CONAN_VISUAL_RUNTIMES="MT"): self.assertTrue(len(list(runner.enumerate_jobs())) != 0) def test_is_pull_request(self): runner = BaseRunner4Testing(conanfile=self.conanfile, settings=self.settings, osys="Windows") with self.assertRaises(NotImplementedError): runner.is_pull_request() def test_get_branch_name(self): runner = BaseRunner4Testing(conanfile=self.conanfile, settings=self.settings, osys="Windows") with self.assertRaises(NotImplementedError): runner.get_branch_name() def test_dry_run(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows", dry_run=True) with context_env(CONAN_GCC_VERSIONS="6", CONAN_ARCHS='x86', CONAN_BUILD_PACKAGES='pckg1'): compiler, options = list(runner.enumerate_jobs())[0] with profile_for(compiler=compiler) as profile_file: runner.set_compiler(compiler) runner.set_profile(profile_file) r = runner.run(options={'shared': True}, username='test', channel='testing') self.assertEqual(r, DRY_RUN) def test_run_fail(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows") with context_env(CONAN_GCC_VERSIONS="6", CONAN_ARCHS='x86', CONAN_BUILD_PACKAGES='pckg1'): compiler, options = list(runner.enumerate_jobs())[0] with profile_for(compiler=compiler) as profile_file: runner.set_compiler(compiler) runner.set_profile(profile_file) with mock.patch('conan_sword_and_sorcery.ci.runners.base_runner.cmd', return_value=1) as mocked_cmd: r = runner.run(options={'shared': True}, username='test', channel='testing') self.assertEqual(r, FAIL) def test_run_success(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows") with context_env(CONAN_GCC_VERSIONS="6", CONAN_ARCHS='x86', CONAN_BUILD_PACKAGES='pckg1'): compiler, options = list(runner.enumerate_jobs())[0] with profile_for(compiler=compiler) as profile_file: runner.set_compiler(compiler) runner.set_profile(profile_file) with mock.patch('conan_sword_and_sorcery.ci.runners.base_runner.cmd', return_value=0) as mocked_cmd: r = runner.run(options={'shared': True}, username='test', channel='testing') self.assertEqual(r, SUCCESS) args, kwargs = mocked_cmd.call_args self.assertEqual(len(args), 0) # All arguments are passed with name self.assertEqual(kwargs['exception'], None) command = kwargs.get('command') self.assertIn('--build=pckg1', command) self.assertIn('--build=outdated', command) self.assertIn('--build={}'.format(runner.recipe.name), command) self.assertIn('--profile {}'.format(profile_file), command) self.assertIn('-o {}:shared=True'.format(runner.recipe.name), command) def test_is_upload_requested(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows") with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="True", APPVEYOR_REPO_BRANCH='non-stable-branch'): self.assertFalse(runner.is_stable_branch()) self.assertFalse(runner.is_upload_requested()) with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="False", APPVEYOR_REPO_BRANCH='non-stable-branch'): self.assertFalse(runner.is_stable_branch()) self.assertTrue(runner.is_upload_requested()) with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="False", APPVEYOR_REPO_BRANCH='stable/v1.2.3'): self.assertTrue(runner.is_stable_branch()) self.assertTrue(runner.is_upload_requested()) with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="True", APPVEYOR_REPO_BRANCH='stable/v1.2.3'): self.assertTrue(runner.is_stable_branch()) self.assertTrue(runner.is_upload_requested()) def test_upload(self): runner = AppveyorRunner(conanfile=self.conanfile, settings=self.settings, osys="Windows") with mock.patch('conan_sword_and_sorcery.ci.runners.base_runner.upload', return_value=0) as mocked_upload: with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="True", APPVEYOR_REPO_BRANCH='non-stable-branch'): runner.upload(username='test', channel='testing') with context_env(CONAN_UPLOAD_ONLY_WHEN_STABLE="False", APPVEYOR_REPO_BRANCH='non-stable-branch'): runner.upload(username='test', channel='testing') args, kwargs = mocked_upload.call_args self.assertEqual(kwargs['username'], 'test')

[ "jgsogo@gmail.com" ]

jgsogo@gmail.com

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/이진탐색/부품찾기.py

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[]

no_license

jjangsungwon/python-for-coding-test

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refs/heads/master

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def binary_search(target, start, end): if start > end: return None while start <= end: mid = (start + end) // 2 if array[mid] == target: # 일치 return "yes" elif array[mid] > target: # 중간값이 찾고자 하는 값보다 클 때 end = mid - 1 else: start = mid + 1 return None # 일치하는 값이 없을 때 if __name__ == "__main__": # 입력 N = int(input()) array = list(map(int, input().split())) M = int(input()) find = list(map(int, input().split())) # 이진 탐색을 하기 위해서 정렬 array.sort() # find에서 값을 하나씩 읽는다. for data in find: # 이진 탐색 result = binary_search(data, 0, N - 1) if result is not None: print('yes', end=" ") else: print('no', end=" ")

[ "dnjs2113@gmail.com" ]

dnjs2113@gmail.com

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/python/chapter-1/lab4-exec1.2.py

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no_license

clovery410/mycode

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refs/heads/master

2021-05-16T02:46:47.996748

2017-05-10T23:43:50

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def gcb_recur(a, b): smaller_para = min(a, b) larger_para = max(a, b) remainder = larger_para % smaller_para if smaller_para % remainder == 0: return remainder return gcb_recur(smaller_para, remainder) print(gcb_recur(50, 35)) def gcb_itera(a, b): smaller_para = min(a, b) larger_para = max(a, b) remainder = larger_para % smaller_para while not smaller_para % remainder == 0: smaller_para, remainder = remainder, smaller_para % remainder return remainder print(gcb_itera(50, 35))

[ "admin@admins-MacBook-Air.local" ]

admin@admins-MacBook-Air.local

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/graphgallery/gallery/nodeclas/tensorflow/__init__.py

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permissive

blindSpoter01/GraphGallery

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refs/heads/master

2023-06-17T11:42:27.169751

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from .gcn import GCN from .gat import GAT from .clustergcn import ClusterGCN from .sgc import SGC from .gwnn import GWNN from .robustgcn import RobustGCN from .graphsage import GraphSAGE from .fastgcn import FastGCN from .chebynet import ChebyNet from .densegcn import DenseGCN from .lgcn import LGCN from .BVAT.obvat import OBVAT from .BVAT.sbvat import SBVAT from .gmnn import GMNN from .dagnn import DAGNN from .mlp import MLP from .tagcn import TAGCN from .appnp import APPNP, PPNP from .ssgc import SSGC from .agnn import AGNN from .arma import ARMA # experimental model from .experimental.edgeconv import EdgeGCN from .experimental.s_obvat import SimplifiedOBVAT from .experimental.gcn_mix import GCN_MIX from .experimental.gcna import GCNA from .experimental.sat import SAT

[ "cnljt@outlook.com" ]

cnljt@outlook.com

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from .category import load_categories, load_category # noqa from .entry import load_entries # noqa from .notification import create_notification, load_notifications # noqa from .price import ( # noqa cheapest_price_by_category, load_price, prices_for_category, ) from .profile import ( # noqa add_balance, create_profile, del_balance, load_profile, save_profile, ) from .subscription import create_subscription, load_subscription # noqa from .user import create_user, save_password # noqa

[ "proofit404@gmail.com" ]

proofit404@gmail.com

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def wish(*names, message="Hi"): for n in names: print(message, n) wish("Bill", "Steve", message="Hello") wish("Bill", "Steve", "Mike")

[ "srikanthpragada@gmail.com" ]

srikanthpragada@gmail.com

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import logging import os import json import mlflow from io import StringIO from mlflow.pyfunc.scoring_server import infer_and_parse_json_input, predictions_to_json def init(): global model global input_schema # "model" is the path of the mlflow artifacts when the model was registered. For automl # models, this is generally "mlflow-model". model_path = os.path.join(os.getenv("AZUREML_MODEL_DIR"), "model") model = mlflow.pyfunc.load_model(model_path) input_schema = model.metadata.get_input_schema() def run(raw_data): json_data = json.loads(raw_data) if "input_data" not in json_data.keys(): raise Exception("Request must contain a top level key named 'input_data'") serving_input = json.dumps(json_data["input_data"]) data = infer_and_parse_json_input(serving_input, input_schema) predictions = model.predict(data) result = StringIO() predictions_to_json(predictions, result) return result.getvalue()

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#!/usr/bin/python # Copyright 2012 Steven Watanabe # Distributed under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or http://www.boost.org/LICENSE_1_0.txt) import BoostBuild t = BoostBuild.Tester(use_test_config=False) # Test a header loop that depends on (but does not contain) a generated header. t.write("test.cpp", '#include "header1.h"\n') t.write("header1.h", """\ #ifndef HEADER1_H #define HEADER1_H #include "header2.h" #endif """) t.write("header2.h", """\ #ifndef HEADER2_H #define HEADER2_H #include "header1.h" #include "header3.h" #endif """) t.write("header3.in", "/* empty file */\n") t.write("jamroot.jam", """\ import common ; make header3.h : header3.in : @common.copy ; obj test : test.cpp : <implicit-dependency>header3.h ; """) t.run_build_system(["-j2"]) t.expect_addition("bin/header3.h") t.expect_addition("bin/$toolset/debug*/test.obj") t.expect_nothing_more() t.rm(".") # Test a linear sequence of generated headers. t.write("test.cpp", '#include "header1.h"\n') t.write("header1.in", """\ #ifndef HEADER1_H #define HEADER1_H #include "header2.h" #endif """) t.write("header2.in", """\ #ifndef HEADER2_H #define HEADER2_H #include "header3.h" #endif """) t.write("header3.in", "/* empty file */\n") t.write("jamroot.jam", """\ import common ; make header1.h : header1.in : @common.copy ; make header2.h : header2.in : @common.copy ; make header3.h : header3.in : @common.copy ; obj test : test.cpp : <implicit-dependency>header1.h <implicit-dependency>header2.h <implicit-dependency>header3.h ; """) t.run_build_system(["-j2", "test"]) t.expect_addition("bin/header1.h") t.expect_addition("bin/header2.h") t.expect_addition("bin/header3.h") t.expect_addition("bin/$toolset/debug*/test.obj") t.expect_nothing_more() t.rm(".") # Test a loop in generated headers. t.write("test.cpp", '#include "header1.h"\n') t.write("header1.in", """\ #ifndef HEADER1_H #define HEADER1_H #include "header2.h" #endif """) t.write("header2.in", """\ #ifndef HEADER2_H #define HEADER2_H #include "header3.h" #endif """) t.write("header3.in", """\ #ifndef HEADER2_H #define HEADER2_H #include "header1.h" #endif """) t.write("jamroot.jam", """\ import common ; actions copy { sleep 1 cp $(>) $(<) } make header1.h : header1.in : @common.copy ; make header2.h : header2.in : @common.copy ; make header3.h : header3.in : @common.copy ; obj test : test.cpp : <implicit-dependency>header1.h <implicit-dependency>header2.h <implicit-dependency>header3.h ; """) t.run_build_system(["-j2", "test"]) t.expect_addition("bin/header1.h") t.expect_addition("bin/header2.h") t.expect_addition("bin/header3.h") t.expect_addition("bin/$toolset/debug*/test.obj") t.expect_nothing_more() t.rm(".") # Test that all the dependencies of a loop are updated before any of the # dependents. t.write("test1.cpp", '#include "header1.h"\n') t.write("test2.cpp", """\ #include "header2.h" int main() {} """) t.write("header1.h", """\ #ifndef HEADER1_H #define HEADER1_H #include "header2.h" #endif """) t.write("header2.h", """\ #ifndef HEADER2_H #define HEADER2_H #include "header1.h" #include "header3.h" #endif """) t.write("header3.in", "\n") t.write("sleep.bat", """\ ::@timeout /T %1 /NOBREAK >nul @ping 127.0.0.1 -n 2 -w 1000 >nul @ping 127.0.0.1 -n %1 -w 1000 >nul @exit /B 0 """) t.write("jamroot.jam", """\ import common ; import os ; if [ os.name ] = NT { SLEEP = call sleep.bat ; } else { SLEEP = sleep ; } rule copy { common.copy $(<) : $(>) ; } actions copy { $(SLEEP) 1 } make header3.h : header3.in : @copy ; exe test : test2.cpp test1.cpp : <implicit-dependency>header3.h ; """) t.run_build_system(["-j2", "test"]) t.expect_addition("bin/header3.h") t.expect_addition("bin/$toolset/debug*/test1.obj") t.expect_addition("bin/$toolset/debug*/test2.obj") t.expect_addition("bin/$toolset/debug*/test.exe") t.expect_nothing_more() t.touch("header3.in") t.run_build_system(["-j2", "test"]) t.expect_touch("bin/header3.h") t.expect_touch("bin/$toolset/debug*/test1.obj") t.expect_touch("bin/$toolset/debug*/test2.obj") t.expect_touch("bin/$toolset/debug*/test.exe") t.expect_nothing_more() t.rm(".") # Test a loop that includes a generated header t.write("test1.cpp", '#include "header1.h"\n') t.write("test2.cpp", """\ #include "header2.h" int main() {} """) t.write("header1.h", """\ #ifndef HEADER1_H #define HEADER1_H #include "header2.h" #endif """) t.write("header2.in", """\ #ifndef HEADER2_H #define HEADER2_H #include "header3.h" #endif """) t.write("header3.h", """\ #ifndef HEADER3_H #define HEADER3_H #include "header1.h" #endif """) t.write("sleep.bat", """\ ::@timeout /T %1 /NOBREAK >nul @ping 127.0.0.1 -n 2 -w 1000 >nul @ping 127.0.0.1 -n %1 -w 1000 >nul @exit /B 0 """) t.write("jamroot.jam", """\ import common ; import os ; if [ os.name ] = NT { SLEEP = call sleep.bat ; } else { SLEEP = sleep ; } rule copy { common.copy $(<) : $(>) ; } actions copy { $(SLEEP) 1 } make header2.h : header2.in : @copy ; exe test : test2.cpp test1.cpp : <implicit-dependency>header2.h <include>. ; """) t.run_build_system(["-j2", "test"]) t.expect_addition("bin/header2.h") t.expect_addition("bin/$toolset/debug*/test1.obj") t.expect_addition("bin/$toolset/debug*/test2.obj") t.expect_addition("bin/$toolset/debug*/test.exe") t.expect_nothing_more() t.cleanup()

[ "james.pack@stardog.com" ]

james.pack@stardog.com

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EnggQasim/PythonOpenCV

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import cv2 import numpy as np cap = cv2.VideoCapture(1) while True: _, frame = cap.read() hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) #hsv hue sat value lower_red = np.array([150,150,50]) upper_red = np.array([180, 255, 150]) mask = cv2.inRange(hsv, lower_red, upper_red) res = cv2.bitwise_and(frame, frame, mask=mask) cv2.imshow('Frame', frame) cv2.imshow('Mask', mask) cv2.imshow('Result', res) k = cv2.waitKey(5) & 0xFF if k == 27: break cv2.destroyAllWindows() cv2.release()

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m.qasim077@gmail.com

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# Generated by Django 2.1.7 on 2019-04-29 15:32 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('ebooks', '0006_auto_20190429_1727'), ] operations = [ migrations.AddField( model_name='chapter', name='description_en', field=models.TextField(null=True, verbose_name='description'), ), migrations.AddField( model_name='chapter', name='description_it', field=models.TextField(null=True, verbose_name='description'), ), migrations.AddField( model_name='chapter', name='slug_en', field=models.SlugField(null=True, unique=True, verbose_name='slug'), ), migrations.AddField( model_name='chapter', name='slug_it', field=models.SlugField(null=True, unique=True, verbose_name='slug'), ), migrations.AddField( model_name='chapter', name='title_en', field=models.CharField(max_length=50, null=True, verbose_name='title'), ), migrations.AddField( model_name='chapter', name='title_it', field=models.CharField(max_length=50, null=True, verbose_name='title'), ), ]

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flavius476@gmail.com

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""" This code was originally published by the following individuals for use with Scilab: Copyright (C) 2012 - 2013 - Michael Baudin Copyright (C) 2012 - Maria Christopoulou Copyright (C) 2010 - 2011 - INRIA - Michael Baudin Copyright (C) 2009 - Yann Collette Copyright (C) 2009 - CEA - Jean-Marc Martinez website: forge.scilab.org/index.php/p/scidoe/sourcetree/master/macros Much thanks goes to these individuals. It has been converted to Python by Abraham Lee. """ import numpy as np def grep(haystack, needle): start = 0 while True: start = haystack.find(needle, start) if start == -1: return yield start start += len(needle) def build_regression_matrix(H, model, build=None): """ Build a regression matrix using a DOE matrix and a list of monomials. Parameters ---------- H : 2d-array model : str build : bool-array Returns ------- R : 2d-array """ ListOfTokens = model.split(' ') if H.shape[1] == 1: size_index = len(str(H.shape[0])) else: size_index = len(str(H.shape[1])) if build is None: build = [True] * len(ListOfTokens) # Test if the vector has the wrong direction (lines instead of columns) if H.shape[0] == 1: H = H.T # Collect the list of monomials Monom_Index = [] for i in range(len(ListOfTokens)): if build[i]: Monom_Index += [grep(ListOfTokens, 'x' + str(0) * (size_index - \ len(str(i))) + str(i))] Monom_Index = -np.sort(-Monom_Index) Monom_Index = np.unique(Monom_Index) if H.shape[1] == 1: nb_var = H.shape[0] # vector "mode": the number of vars is equal to the number of lines of H VectorMode = True for i in range(nb_var): for j in range(ListOfTokens.shape[0]): ListOfTokens[j] = ListOfTokens[j].replace( 'x' + str(0) * (size_index - len(str(i))) + str(i), 'H(' + str(i) + ')') else: nb_var = H.shape[0] # matrix "mode": the number of vars is equal to the number of columns of H VectorMode = False for i in range(nb_var): for j in range(ListOfTokens.shape[0]): ListOfTokens[j] = ListOfTokens[j].replace( 'x' + str(0) * (size_index - len(str(i))) + str(i), 'H[i,' + str(i) + ')') # Now build the regression matrix if VectorMode: R = np.zeros((len(ListOfTokens), 1)) for j in range(len(ListOfTokens)): R[j, 0] = eval(ListOfTokens[j]) else: R = np.zeros((H.shape[0], len(ListOfTokens))) for i in range(H.shape[0]): for j in range(len(ListOfTokens)): R[i, j] = eval(ListOfTokens[j]) return R

[ "quanpan302@hotmail.com" ]

quanpan302@hotmail.com

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from getratings.models.ratings import Ratings class NA_Ornn_Top_Aatrox(Ratings): pass class NA_Ornn_Top_Ahri(Ratings): pass class NA_Ornn_Top_Akali(Ratings): pass class NA_Ornn_Top_Alistar(Ratings): pass class NA_Ornn_Top_Amumu(Ratings): pass class NA_Ornn_Top_Anivia(Ratings): pass class NA_Ornn_Top_Annie(Ratings): pass class NA_Ornn_Top_Ashe(Ratings): pass class NA_Ornn_Top_AurelionSol(Ratings): pass class NA_Ornn_Top_Azir(Ratings): pass class NA_Ornn_Top_Bard(Ratings): pass class NA_Ornn_Top_Blitzcrank(Ratings): pass class NA_Ornn_Top_Brand(Ratings): pass class NA_Ornn_Top_Braum(Ratings): pass class NA_Ornn_Top_Caitlyn(Ratings): pass class NA_Ornn_Top_Camille(Ratings): pass class NA_Ornn_Top_Cassiopeia(Ratings): pass class NA_Ornn_Top_Chogath(Ratings): pass class NA_Ornn_Top_Corki(Ratings): pass class NA_Ornn_Top_Darius(Ratings): pass class NA_Ornn_Top_Diana(Ratings): pass class NA_Ornn_Top_Draven(Ratings): pass class NA_Ornn_Top_DrMundo(Ratings): pass class NA_Ornn_Top_Ekko(Ratings): pass class NA_Ornn_Top_Elise(Ratings): pass class NA_Ornn_Top_Evelynn(Ratings): pass class NA_Ornn_Top_Ezreal(Ratings): pass class NA_Ornn_Top_Fiddlesticks(Ratings): pass class NA_Ornn_Top_Fiora(Ratings): pass class NA_Ornn_Top_Fizz(Ratings): pass class NA_Ornn_Top_Galio(Ratings): pass class NA_Ornn_Top_Gangplank(Ratings): pass class NA_Ornn_Top_Garen(Ratings): pass class NA_Ornn_Top_Gnar(Ratings): pass class NA_Ornn_Top_Gragas(Ratings): pass class NA_Ornn_Top_Graves(Ratings): pass class NA_Ornn_Top_Hecarim(Ratings): pass class NA_Ornn_Top_Heimerdinger(Ratings): pass class NA_Ornn_Top_Illaoi(Ratings): pass class NA_Ornn_Top_Irelia(Ratings): pass class NA_Ornn_Top_Ivern(Ratings): pass class NA_Ornn_Top_Janna(Ratings): pass class NA_Ornn_Top_JarvanIV(Ratings): pass class NA_Ornn_Top_Jax(Ratings): pass class NA_Ornn_Top_Jayce(Ratings): pass class NA_Ornn_Top_Jhin(Ratings): pass class NA_Ornn_Top_Jinx(Ratings): pass class NA_Ornn_Top_Kalista(Ratings): pass class NA_Ornn_Top_Karma(Ratings): pass class NA_Ornn_Top_Karthus(Ratings): pass class NA_Ornn_Top_Kassadin(Ratings): pass class NA_Ornn_Top_Katarina(Ratings): pass class NA_Ornn_Top_Kayle(Ratings): pass class NA_Ornn_Top_Kayn(Ratings): pass class NA_Ornn_Top_Kennen(Ratings): pass class NA_Ornn_Top_Khazix(Ratings): pass class NA_Ornn_Top_Kindred(Ratings): pass class NA_Ornn_Top_Kled(Ratings): pass class NA_Ornn_Top_KogMaw(Ratings): pass class NA_Ornn_Top_Leblanc(Ratings): pass class NA_Ornn_Top_LeeSin(Ratings): pass class NA_Ornn_Top_Leona(Ratings): pass class NA_Ornn_Top_Lissandra(Ratings): pass class NA_Ornn_Top_Lucian(Ratings): pass class NA_Ornn_Top_Lulu(Ratings): pass class NA_Ornn_Top_Lux(Ratings): pass class NA_Ornn_Top_Malphite(Ratings): pass class NA_Ornn_Top_Malzahar(Ratings): pass class NA_Ornn_Top_Maokai(Ratings): pass class NA_Ornn_Top_MasterYi(Ratings): pass class NA_Ornn_Top_MissFortune(Ratings): pass class NA_Ornn_Top_MonkeyKing(Ratings): pass class NA_Ornn_Top_Mordekaiser(Ratings): pass class NA_Ornn_Top_Morgana(Ratings): pass class NA_Ornn_Top_Nami(Ratings): pass class NA_Ornn_Top_Nasus(Ratings): pass class NA_Ornn_Top_Nautilus(Ratings): pass class NA_Ornn_Top_Nidalee(Ratings): pass class NA_Ornn_Top_Nocturne(Ratings): pass class NA_Ornn_Top_Nunu(Ratings): pass class NA_Ornn_Top_Olaf(Ratings): pass class NA_Ornn_Top_Orianna(Ratings): pass class NA_Ornn_Top_Ornn(Ratings): pass class NA_Ornn_Top_Pantheon(Ratings): pass class NA_Ornn_Top_Poppy(Ratings): pass class NA_Ornn_Top_Quinn(Ratings): pass class NA_Ornn_Top_Rakan(Ratings): pass class NA_Ornn_Top_Rammus(Ratings): pass class NA_Ornn_Top_RekSai(Ratings): pass class NA_Ornn_Top_Renekton(Ratings): pass class NA_Ornn_Top_Rengar(Ratings): pass class NA_Ornn_Top_Riven(Ratings): pass class NA_Ornn_Top_Rumble(Ratings): pass class NA_Ornn_Top_Ryze(Ratings): pass class NA_Ornn_Top_Sejuani(Ratings): pass class NA_Ornn_Top_Shaco(Ratings): pass class NA_Ornn_Top_Shen(Ratings): pass class NA_Ornn_Top_Shyvana(Ratings): pass class NA_Ornn_Top_Singed(Ratings): pass class NA_Ornn_Top_Sion(Ratings): pass class NA_Ornn_Top_Sivir(Ratings): pass class NA_Ornn_Top_Skarner(Ratings): pass class NA_Ornn_Top_Sona(Ratings): pass class NA_Ornn_Top_Soraka(Ratings): pass class NA_Ornn_Top_Swain(Ratings): pass class NA_Ornn_Top_Syndra(Ratings): pass class NA_Ornn_Top_TahmKench(Ratings): pass class NA_Ornn_Top_Taliyah(Ratings): pass class NA_Ornn_Top_Talon(Ratings): pass class NA_Ornn_Top_Taric(Ratings): pass class NA_Ornn_Top_Teemo(Ratings): pass class NA_Ornn_Top_Thresh(Ratings): pass class NA_Ornn_Top_Tristana(Ratings): pass class NA_Ornn_Top_Trundle(Ratings): pass class NA_Ornn_Top_Tryndamere(Ratings): pass class NA_Ornn_Top_TwistedFate(Ratings): pass class NA_Ornn_Top_Twitch(Ratings): pass class NA_Ornn_Top_Udyr(Ratings): pass class NA_Ornn_Top_Urgot(Ratings): pass class NA_Ornn_Top_Varus(Ratings): pass class NA_Ornn_Top_Vayne(Ratings): pass class NA_Ornn_Top_Veigar(Ratings): pass class NA_Ornn_Top_Velkoz(Ratings): pass class NA_Ornn_Top_Vi(Ratings): pass class NA_Ornn_Top_Viktor(Ratings): pass class NA_Ornn_Top_Vladimir(Ratings): pass class NA_Ornn_Top_Volibear(Ratings): pass class NA_Ornn_Top_Warwick(Ratings): pass class NA_Ornn_Top_Xayah(Ratings): pass class NA_Ornn_Top_Xerath(Ratings): pass class NA_Ornn_Top_XinZhao(Ratings): pass class NA_Ornn_Top_Yasuo(Ratings): pass class NA_Ornn_Top_Yorick(Ratings): pass class NA_Ornn_Top_Zac(Ratings): pass class NA_Ornn_Top_Zed(Ratings): pass class NA_Ornn_Top_Ziggs(Ratings): pass class NA_Ornn_Top_Zilean(Ratings): pass class NA_Ornn_Top_Zyra(Ratings): pass

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# model settings norm_cfg = dict(type='SyncBN', requires_grad=True) model = dict( type='EncoderDecoder', pretrained='open-mmlab://resnet50_v1c', backbone=dict( type='ResNetV1c', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), dilations=(1, 1, 2, 4), strides=(1, 2, 1, 1), norm_cfg=norm_cfg, norm_eval=False, style='pytorch', contract_dilation=True), decode_head=dict( type='DepthwiseSeparableASPPHead', in_channels=2048, in_index=3, channels=512, dilations=(1, 12, 24, 36), c1_in_channels=0, c1_channels=0, dropout_ratio=0.1, num_classes=19, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), auxiliary_head=dict( type='FCNHead', in_channels=1024, in_index=2, channels=256, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=19, norm_cfg=norm_cfg, align_corners=False, loss_decode=dict( type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4))) # model training and testing settings train_cfg = dict() test_cfg = dict(mode='whole')

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yhyuan@pku.edu.cn

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alexogch1/SistemaOperaciones

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from django.http import HttpResponse, HttpResponseRedirect from django.shortcuts import render from django.urls import reverse_lazy from django.contrib.auth.mixins import LoginRequiredMixin from django.contrib.messages.views import SuccessMessageMixin #from .filters import NominaFiltro from dateutil.parser import parse from django.views import generic from generales.views import SinPrivilegios from .form import NominaEncForm, NominaDetForm, DetalleNominaFormSet from .models import NominaEnc, NominaDet class NominaCompletaList(generic.ListView): template_name='nomina/nomina_completa.html' context_object_name='nomina' queryset = NominaEnc.objects.all() def get_context_data(self, **kwargs): context = super(NominaCompletaList, self).get_context_data(**kwargs) context['detalles'] = NominaDet.objects.all() context['encabezado'] = self.queryset return context class NominaList( generic.ListView): model=NominaEnc template_name='nomina/nomina_list.html' context_object_name='nomina' """ def get_context_data(self, **kwargs): context = super(NominaList, self).get_context_data(**kwargs) initial_date = self.request.GET.get('fecha_inicial') final_date = self.request.GET.get('fecha_final') if not initial_date or not final_date: context ['nomina'] = NominaEnc.objects.order_by('fecha_nomina') else: initial_date = parse(initial_date) final_date = parse(final_date) context['nomina'] = NominaEnc.objects.filter(fecha_nomina__gte=initial_date, fecha_nomina__lte=final_date ) return context """ #def get_context_data(self, **kwargs): #context = super().get_context_data(**kwargs) #context['filter']=NominaFiltro(self.request.GET, queryset=self.get_queryset()) #return context class NominaNew(SinPrivilegios, generic.CreateView): permission_required='nomina.add_nominaenc' model=NominaEnc login_url='generales:home' template_name='nomina/nomina_form.html' form_class=NominaEncForm success_url=reverse_lazy('nomina:nomina_list') def get(self, request, *args, **kwargs): self.object=None form_class=self.get_form_class() form=self.get_form(form_class) detalle_nomina_formset=DetalleNominaFormSet() return self.render_to_response( self.get_context_data( form=form, detalle_nomina = detalle_nomina_formset ) ) def post(self, request, *args, **kwargs): form_class=self.get_form_class() form=self.get_form(form_class) detalle_nomina=DetalleNominaFormSet(request.POST) if form.is_valid() and detalle_nomina.is_valid(): return self.form_valid(form, detalle_nomina) else: return self.form_invalid(form, detalle_nomina) def form_valid(self, form, detalle_nomina): self.object=form.save() detalle_nomina.instance=self.object detalle_nomina.save() return HttpResponseRedirect(self.success_url) def form_invalid(self, form, detalle_nomina): return self.render_to_response( self.get_context_data( form=form, detalle_nomina=detalle_nomina ) ) class NominaEdit(SinPrivilegios,generic.UpdateView): permission_required='nomina.change_nominaenc' model=NominaEnc login_url='generales:home' template_name='nomina/nomina_form.html' form_class=NominaEncForm success_url=reverse_lazy('nomina:nomina_list') def get_success_url(self): from django.urls import reverse return reverse ('nomina:nomina_edit', kwargs={'pk':self.get_object().id}) def get (self, request, *args, **kwargs): self.object = self.get_object() form_class = self.get_form_class() form = self.get_form(form_class) detalles =NominaDet.objects.filter(nomina=self.object).order_by('pk') detalles_data = [] for detalle in detalles: d={ 'concepto':detalle.concepto, 'cantidad':detalle.cantidad } detalles_data.append(d) detalle_nomina = DetalleNominaFormSet(initial=detalles_data) detalle_nomina.extra += len(detalles_data) return self.render_to_response( self.get_context_data( form=form, detalle_nomina = detalle_nomina ) ) def post(self,request, *args, **kwargs): self.object = self.get_object() form_class = self.get_form_class() form=self.get_form(form_class) detalle_nomina = DetalleNominaFormSet(request.POST) if form.is_valid() and detalle_nomina.is_valid(): return self.form_valid(form, detalle_nomina) else: return self.form_valid(form, detalle_nomina) def form_valid(self, form, detalle_nomina): self.object = form.save() detalle_nomina.instance =self.object NominaDet.objects.filter(nomina=self.object).delete() detalle_nomina.save() return HttpResponseRedirect(self.get_success_url()) def form_invalid(self, form, detalle_nomina): return self.render_to_response( self.get_context_data( form=form, detalle_nomina=detalle_nomina ) ) class NominaDel(SinPrivilegios,generic.DeleteView): permission_required='nomina:delete_nominaenc' model= NominaEnc template_name = 'nomina/nomina_del.html' context_object_name='obj' success_url=reverse_lazy('nomina:nomina_list')

[ "alexogch@hotmail.com" ]

alexogch@hotmail.com

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/addons/todo_user/__manifest__.py

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gitstalker/docker_odoo

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{ 'name':'Multiuser To-Do', 'description': 'Extend the To-Do app to multiuser.', 'depends': ['website'], 'data':['views/templates.xml'], 'author': 'hdwolf' }

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spacegoing@gmail.com

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/sdk/rdbms/azure-mgmt-rdbms/azure/mgmt/rdbms/mysql/aio/operations/_replicas_operations.py

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Azure/azure-sdk-for-python

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# pylint: disable=too-many-lines # coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import Any, AsyncIterable, Callable, Dict, Optional, TypeVar from azure.core.async_paging import AsyncItemPaged, AsyncList from azure.core.exceptions import ( ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, ResourceNotModifiedError, map_error, ) from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse from azure.core.rest import HttpRequest from azure.core.tracing.decorator import distributed_trace from azure.core.utils import case_insensitive_dict from azure.mgmt.core.exceptions import ARMErrorFormat from ... import models as _models from ..._vendor import _convert_request from ...operations._replicas_operations import build_list_by_server_request from .._vendor import MySQLManagementClientMixinABC T = TypeVar("T") ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] class ReplicasOperations: """ .. warning:: **DO NOT** instantiate this class directly. Instead, you should access the following operations through :class:`~azure.mgmt.rdbms.mysql.aio.MySQLManagementClient`'s :attr:`replicas` attribute. """ models = _models def __init__(self, *args, **kwargs) -> None: input_args = list(args) self._client = input_args.pop(0) if input_args else kwargs.pop("client") self._config = input_args.pop(0) if input_args else kwargs.pop("config") self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer") self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer") @distributed_trace def list_by_server( self, resource_group_name: str, server_name: str, **kwargs: Any ) -> AsyncIterable["_models.Server"]: """List all the replicas for a given server. :param resource_group_name: The name of the resource group. The name is case insensitive. Required. :type resource_group_name: str :param server_name: The name of the server. Required. :type server_name: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either Server or the result of cls(response) :rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.rdbms.mysql.models.Server] :raises ~azure.core.exceptions.HttpResponseError: """ _headers = kwargs.pop("headers", {}) or {} _params = case_insensitive_dict(kwargs.pop("params", {}) or {}) api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2017-12-01")) cls: ClsType[_models.ServerListResult] = kwargs.pop("cls", None) error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError, 304: ResourceNotModifiedError, } error_map.update(kwargs.pop("error_map", {}) or {}) def prepare_request(next_link=None): if not next_link: request = build_list_by_server_request( resource_group_name=resource_group_name, server_name=server_name, subscription_id=self._config.subscription_id, api_version=api_version, template_url=self.list_by_server.metadata["url"], headers=_headers, params=_params, ) request = _convert_request(request) request.url = self._client.format_url(request.url) else: request = HttpRequest("GET", next_link) request = _convert_request(request) request.url = self._client.format_url(request.url) request.method = "GET" return request async def extract_data(pipeline_response): deserialized = self._deserialize("ServerListResult", pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) # type: ignore return None, AsyncList(list_of_elem) async def get_next(next_link=None): request = prepare_request(next_link) _stream = False pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access request, stream=_stream, **kwargs ) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, error_format=ARMErrorFormat) return pipeline_response return AsyncItemPaged(get_next, extract_data) list_by_server.metadata = { "url": "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.DBforMySQL/servers/{serverName}/replicas" }

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tonyonifo/anytime

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from __future__ import absolute_import from __future__ import division from __future__ import print_function from .cityscapes import Cityscapes as cityscapes

[ "email@email.com" ]

email@email.com

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Leahxuliu/Data-Structure-And-Algorithm

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''' 5. Longest Palindromic Substring 注意题目的return是什么 ''' def longestPalindrome(self, s: str) -> str: if s == '': return '' n = len(s) dp = [[False] * n for _ in range(n)] max_len = 1 start = 0 for i in range(n - 1, -1, -1): for j in range(i, n): if i == j: dp[i][j] = True elif j - i == 1: if s[i] == s[j]: dp[i][j] = True if max_len < 2: max_len = 2 start = i else: if s[i] == s[j] and dp[i + 1][j - 1] == True: dp[i][j] = True if max_len < j - i + 1: max_len = j - i + 1 start = i return s[start:start + max_len]

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leahxuliu@gmail.com

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iKintosh/dagster

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import os import pandas as pd from dagster import AssetIn, Definitions, IOManager, asset, io_manager from .asset_input_managers import ( load_numpy_array, load_pandas_dataframe, store_pandas_dataframe, ) # start_numpy_example class PandasAssetIOManager(IOManager): def handle_output(self, context, obj): file_path = self._get_path(context) store_pandas_dataframe(name=file_path, table=obj) def _get_path(self, context): return os.path.join( "storage", f"{context.asset_key.path[-1]}.csv", ) def load_input(self, context): file_path = self._get_path(context) return load_pandas_dataframe(name=file_path) @io_manager def pandas_asset_io_manager(): return PandasAssetIOManager() class NumpyAssetIOManager(PandasAssetIOManager): def load_input(self, context): file_path = self._get_path(context) return load_numpy_array(name=file_path) @io_manager def numpy_asset_io_manager(): return NumpyAssetIOManager() @asset(io_manager_key="pandas_manager") def upstream_asset(): return pd.DataFrame([1, 2, 3]) @asset( ins={"upstream": AssetIn(key_prefix="public", input_manager_key="numpy_manager")} ) def downstream_asset(upstream): return upstream.shape defs = Definitions( assets=[upstream_asset, downstream_asset], resources={ "pandas_manager": pandas_asset_io_manager, "numpy_manager": numpy_asset_io_manager, }, ) # end_numpy_example

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pritamSarkar123/Compitative20_21

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#problem description #https://www.youtube.com/watch?v=xbpUHSKoALg&t=784s # algorithm: # #create intermediate nodes # p=head # q=NULL # while p!=NULL: # q=p # p=p->next # t=copy(q) # q->next=t # t->next=p # #connecting new linked list # p=head # q=NULL # while p!=NULL: # q=p # p=p->next->next # q->next->random=q->random->next # q=q->next # if p!=NULL: # q->next=p->next # else: # q->next=NULLa # #changing head pointer # head=head->next class Node: def __init__(self,value): self.value=value self.next=None self.random=None self.message="Original" class LinkedList: def __init__(self): self.head=Node(1) temp=self.head temp.next=Node(2) temp=temp.next temp.next=Node(3) temp=temp.next temp=self.head temp.random=temp.next.next #1->3 temp=temp.next temp.random=self.head #2->1 temp=temp.next temp.random=temp #3->3 def show_list(self): temp=self.head while temp: print(temp.value,temp.message,temp.random.value) temp=temp.next def copy_list(self): #create intermediate nodes p=self.head q=None while p: q=p p=p.next temp=Node(q.value);temp.message="Coppied" q.next=temp temp.next=p #connecting new linked list p=self.head q=None while p: q=p p=p.next.next q.next.random=q.random.next q=q.next if p: q.next=p.next else: q.next=None #changing head pointer self.head=self.head.next self.show_list() if __name__=="__main__": myList=LinkedList() myList.show_list() myList.copy_list()

[ "pritamsarkar84208220@gmail.com" ]

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sendurr/spring-grading

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# Alexis Thompson-Klemish # q = [['a', 'b', 'c'], ['d', 'e', 'f'], ['g', 'h']] # print the letter a print q[0][0] # print the list ['d', 'e', 'f'] print q[1] # print the last element h print q[-1][-1] #print the d element print q[1][0] #explain why q[-1][-2] has the value g print "negative indexes count from the right, not the left so q[-1] produces the rightmost list and q[-1][-2] produces the second to last element in the last list"

[ "sendurr@hotmail.com" ]

sendurr@hotmail.com

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rohe/oidc-oob-federation

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import logging import cherrypy from cryptojwt import as_bytes from oidcmsg.oauth2 import is_error_message from oidcmsg.oauth2 import AuthorizationRequest from oidcendpoint.sdb import AuthnEvent logger = logging.getLogger(__name__) class OpenIDProvider(object): def __init__(self, config, endpoint_context): self.config = config self.endpoint_context = endpoint_context def do_response(self, endpoint, req_args, **args): info = endpoint.do_response(request=req_args, **args) for key, value in info['http_headers']: cherrypy.response.headers[key] = value try: _response_placement = info['response_placement'] except KeyError: _response_placement = endpoint.response_placement if _response_placement == 'body': logger.info('Response: {}'.format(info['response'])) return as_bytes(info['response']) elif _response_placement == 'url': logger.info('Redirect to: {}'.format(info['response'])) raise cherrypy.HTTPRedirect(info['response']) @cherrypy.expose def service_endpoint(self, name, **kwargs): logger.info(kwargs) logger.info('At the {} endpoint'.format(name)) endpoint = self.endpoint_context.endpoint[name] try: authn = cherrypy.request.headers['Authorization'] except KeyError: pr_args = {} else: pr_args = {'auth': authn} if endpoint.request_placement == 'body': if cherrypy.request.process_request_body is True: _request = cherrypy.request.body.read() else: raise cherrypy.HTTPError(400, 'Missing HTTP body') if not _request: _request = kwargs req_args = endpoint.parse_request(_request, **pr_args) else: req_args = endpoint.parse_request(kwargs, **pr_args) logger.info('request: {}'.format(req_args)) if is_error_message(req_args): return as_bytes(req_args.to_json()) args = endpoint.process_request(req_args) return self.do_response(endpoint, req_args, **args) @cherrypy.expose def authn_verify(self, url_endpoint, **kwargs): """ Authentication verification :param authn_method: Which authn method that was used :param kwargs: response arguments :return: HTTP redirect """ authn_method = self.endpoint_context.endpoint_to_authn_method[url_endpoint] username = authn_method.verify(**kwargs) if not username: cherrypy.HTTPError(403, message='Authentication failed') auth_args = authn_method.unpack_token(kwargs['token']) request = AuthorizationRequest().from_urlencoded(auth_args['query']) # uid, salt, valid=3600, authn_info=None, time_stamp=0, authn_time=None, # valid_until=None authn_event = AuthnEvent(username, 'salt', authn_info=auth_args['authn_class_ref'], authn_time=auth_args['iat']) endpoint = self.endpoint_context.endpoint['authorization'] args = endpoint.post_authentication(request, user=username, authn_event=authn_event) return self.do_response(endpoint, request, **args) def _cp_dispatch(self, vpath): # Only get here if vpath != None ent = cherrypy.request.remote.ip logger.info('ent:{}, vpath: {}'.format(ent, vpath)) if len(vpath) == 2 and vpath[0] == 'verify': a = vpath.pop(0) b = vpath.pop(0) cherrypy.request.params['url_endpoint'] = '/'.join(['', a, b]) return self.authn_verify for name, instance in self.endpoint_context.endpoint.items(): if vpath == instance.vpath: cherrypy.request.params['name'] = name for n in range(len(vpath)): vpath.pop() return self.service_endpoint return self

[ "roland@catalogix.se" ]

roland@catalogix.se

1e5810523ea93878d26b6ef00317399d8e25aa25

1005a4290bca16dcf4c6b3415662e134044305bd

/python/Sources/gensource_Z2Jets_muhad_cfi.py

1d71fe0e0d4998bc6ab78e9176740d7f2eb3bcf3

[]

no_license

cms-analysis/TauAnalysis-GenSimTools

2652bb713107bb1d459882581237662d229d3906

b787b784ee3598c4428c4883c04cdc525eb54eb6

refs/heads/master

2020-12-24T15:58:14.392883

2013-06-28T20:10:42

null

0

null

UTF-8

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1,238

py

import FWCore.ParameterSet.Config as cms # The Alpgen Source. It reads unweighted alpgen files source = cms.Source("AlpgenSource", # use an input file name without extension unw fileNames = cms.untracked.vstring( 'file:/home/cbernet/ALPGEN/v213/zjetwork/z2j' ) ) # The Alpgen Producer. from GeneratorInterface.AlpgenInterface.generator_cfi import * generator.comEnergy = 14000.0 generator.pythiaHepMCVerbosity = False generator.maxEventsToPrint = 0 # Set the jet matching parameters as you see fit. generator.jetMatching.applyMatching = True generator.jetMatching.exclusive = True generator.jetMatching.etMin = 20.0 generator.jetMatching.drMin = 0.5 # for every process including tau should be use TAUOLA from GeneratorInterface.ExternalDecays.TauolaSettings_cff import * generator.ExternalDecays = cms.PSet( Tauola = cms.untracked.PSet( TauolaPolar, InputCards = cms.PSet( pjak1 = cms.int32(0), pjak2 = cms.int32(0), #mdtau = cms.int32(116) #mdtau = 0 all decays mdtau = cms.int32(116) #mdtau = 116 - ONE mu+-, other taus -> all channels ) ), parameterSets = cms.vstring('Tauola') ) ProductionFilterSequence = cms.Sequence(generator)

[ "sha1-5c72da6f595cce9b6b48aff6d56f01e9beb4aad1@cern.ch" ]

sha1-5c72da6f595cce9b6b48aff6d56f01e9beb4aad1@cern.ch

f50fbf295e7c63db3184c8adcae01d3500afaf12

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/tools/grit/grit/format/policy_templates/writers/ios_plist_writer_unittest.py

0fdecb1d1ef33336fc052bf6c32b3b97d6f1800a

[ "BSD-3-Clause", "LGPL-2.0-or-later", "LicenseRef-scancode-unknown-license-reference", "GPL-2.0-only", "Apache-2.0", "LicenseRef-scancode-unknown", "MIT" ]

permissive

metux/chromium-suckless

efd087ba4f4070a6caac5bfbfb0f7a4e2f3c438a

72a05af97787001756bae2511b7985e61498c965

refs/heads/orig

2022-12-04T23:53:58.681218

2017-04-30T10:59:06

2017-04-30T23:35:58

89,884,931

5

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BSD-3-Clause

2022-11-23T20:52:53

2017-05-01T00:09:08

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UTF-8

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py

#!/usr/bin/env python # Copyright (c) 2014 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. '''Unit tests for grit.format.policy_templates.writers.ios_plist_writer''' import base64 import functools import os import plistlib import sys if __name__ == '__main__': sys.path.append(os.path.join(os.path.dirname(__file__), '../../../..')) import unittest try: import Cocoa except: Cocoa = None from grit.format.policy_templates.writers import writer_unittest_common class IOSPListWriterUnittest(writer_unittest_common.WriterUnittestCommon): '''Unit tests for IOSPListWriter.''' def _ParseWithPython(self, decode, text): '''Parses a serialized Plist, using Python's plistlib. If |decode| is true then |text| is decoded as Base64 before being deserialized as a Plist.''' if decode: text = base64.b64decode(text) return plistlib.readPlistFromString(text) def _ParseWithCocoa(self, decode, text): '''Parses a serialized Plist, using Cocoa's python bindings. If |decode| is true then |text| is decoded as Base64 before being deserialized as a Plist.''' if decode: data = Cocoa.NSData.alloc().initWithBase64EncodedString_options_(text, 0) else: data = Cocoa.NSData.alloc().initWithBytes_length_(text, len(text)) result = Cocoa.NSPropertyListSerialization. \ propertyListFromData_mutabilityOption_format_errorDescription_( data, Cocoa.NSPropertyListImmutable, None, None) return result[0] def _VerifyGeneratedOutputWithParsers(self, templates, expected_output, parse, decode_and_parse): _defines = { '_chromium': '1', 'mac_bundle_id': 'com.example.Test', 'version': '39.0.0.0' } # Generate the grit output for |templates|. output = self.GetOutput( self.PrepareTest(templates), 'fr', _defines, 'ios_plist', 'en') # Parse it as a Plist. plist = parse(output) self.assertEquals(len(plist), 2) self.assertTrue('ChromePolicy' in plist) self.assertTrue('EncodedChromePolicy' in plist) # Get the 2 expected fields. chrome_policy = plist['ChromePolicy'] encoded_chrome_policy = plist['EncodedChromePolicy'] # Verify the ChromePolicy. self.assertEquals(chrome_policy, expected_output) # Decode the EncodedChromePolicy and verify it. decoded_chrome_policy = decode_and_parse(encoded_chrome_policy) self.assertEquals(decoded_chrome_policy, expected_output) def _VerifyGeneratedOutput(self, templates, expected): # plistlib is available on all Python platforms. parse = functools.partial(self._ParseWithPython, False) decode_and_parse = functools.partial(self._ParseWithPython, True) self._VerifyGeneratedOutputWithParsers( templates, expected, parse, decode_and_parse) # The Cocoa bindings are available on Mac OS X only. if Cocoa: parse = functools.partial(self._ParseWithCocoa, False) decode_and_parse = functools.partial(self._ParseWithCocoa, True) self._VerifyGeneratedOutputWithParsers( templates, expected, parse, decode_and_parse) def _MakeTemplate(self, name, type, example, extra=''): return ''' { 'policy_definitions': [ { 'name': '%s', 'type': '%s', 'desc': '', 'caption': '', 'supported_on': ['ios:35-'], 'example_value': %s, %s }, ], 'placeholders': [], 'messages': {}, } ''' % (name, type, example, extra) def testEmpty(self): templates = ''' { 'policy_definitions': [], 'placeholders': [], 'messages': {}, } ''' expected = {} self._VerifyGeneratedOutput(templates, expected) def testEmptyVersion(self): templates = ''' { 'policy_definitions': [], 'placeholders': [], 'messages': {}, } ''' expected = {} self._VerifyGeneratedOutput(templates, expected) def testBoolean(self): templates = self._MakeTemplate('BooleanPolicy', 'main', 'True') expected = { 'BooleanPolicy': True, } self._VerifyGeneratedOutput(templates, expected) def testString(self): templates = self._MakeTemplate('StringPolicy', 'string', '"Foo"') expected = { 'StringPolicy': 'Foo', } self._VerifyGeneratedOutput(templates, expected) def testStringEnum(self): templates = self._MakeTemplate( 'StringEnumPolicy', 'string-enum', '"Foo"', ''' 'items': [ { 'name': 'Foo', 'value': 'Foo', 'caption': '' }, { 'name': 'Bar', 'value': 'Bar', 'caption': '' }, ], ''') expected = { 'StringEnumPolicy': 'Foo', } self._VerifyGeneratedOutput(templates, expected) def testInt(self): templates = self._MakeTemplate('IntPolicy', 'int', '42') expected = { 'IntPolicy': 42, } self._VerifyGeneratedOutput(templates, expected) def testIntEnum(self): templates = self._MakeTemplate( 'IntEnumPolicy', 'int-enum', '42', ''' 'items': [ { 'name': 'Foo', 'value': 100, 'caption': '' }, { 'name': 'Bar', 'value': 42, 'caption': '' }, ], ''') expected = { 'IntEnumPolicy': 42, } self._VerifyGeneratedOutput(templates, expected) def testStringList(self): templates = self._MakeTemplate('StringListPolicy', 'list', '["a", "b"]') expected = { 'StringListPolicy': [ "a", "b" ], } self._VerifyGeneratedOutput(templates, expected) def testStringEnumList(self): templates = self._MakeTemplate('StringEnumListPolicy', 'string-enum-list', '["a", "b"]', ''' 'items': [ { 'name': 'Foo', 'value': 'a', 'caption': '' }, { 'name': 'Bar', 'value': 'b', 'caption': '' }, ], ''') expected = { 'StringEnumListPolicy': [ "a", "b" ], } self._VerifyGeneratedOutput(templates, expected) def testListOfDictionary(self): templates = self._MakeTemplate( 'ManagedBookmarks', 'dict', ''' [ { "name": "Google Search", "url": "www.google.com", }, { "name": "Youtube", "url": "www.youtube.com", } ] ''') expected = { 'ManagedBookmarks': [ { "name": "Google Search", "url": "www.google.com" }, { "name": "Youtube", "url": "www.youtube.com" }, ], } self._VerifyGeneratedOutput(templates, expected) if __name__ == '__main__': unittest.main()

[ "enrico.weigelt@gr13.net" ]

enrico.weigelt@gr13.net

17182f5cae79f76332304a2abd4a7f9acf5a1442

d41d18d3ea6edd2ec478b500386375a8693f1392

/plotly/validators/layout/ternary/aaxis/_showticksuffix.py

2a1b061ea73eecf6d8c074e3d8662b7cb67f3748

[ "MIT" ]

permissive

miladrux/plotly.py

38921dd6618650d03be9891d6078e771ffccc99a

dbb79e43e2cc6c5762251537d24bad1dab930fff

refs/heads/master

2020-03-27T01:46:57.497871

2018-08-20T22:37:38

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1

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MIT

2018-08-22T17:37:07

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UTF-8

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py

import _plotly_utils.basevalidators class ShowticksuffixValidator( _plotly_utils.basevalidators.EnumeratedValidator ): def __init__( self, plotly_name='showticksuffix', parent_name='layout.ternary.aaxis', **kwargs ): super(ShowticksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type='plot', role='style', values=['all', 'first', 'last', 'none'], **kwargs )

[ "adam.kulidjian@gmail.com" ]

adam.kulidjian@gmail.com

9bf714a6abbcdb0385038e4cdee96b601cece13d

06a7dc7cc93d019e4a9cbcf672b23a0bbacf8e8b

/2013_adni/MMSE-AD-CTL/01_build_dataset.py

f9049d7b28f1fc1da3d70f12b740317ca04ad28d

[]

no_license

neurospin/scripts

6c06cd218a5f32de9c3c2b7d1d8bda3f3d107458

f14a2c9cf2cd7f5fbea767b017c3faf36d170bdb

refs/heads/master

2021-07-11T22:55:46.567791

2021-07-02T13:08:02

10,549,286

2

null

UTF-8

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py

# -*- coding: utf-8 -*- """ @author: edouard.Duchesnay@cea.fr Compute mask, concatenate masked non-smoothed images for all the subjects. Build X, y, and mask INPUT: - subject_list.txt: - population.csv OUTPUT: - mask.nii.gz - y.npy - X.npy = intercept + Age + Gender + Voxel """ import os import numpy as np import glob import pandas as pd import nibabel import brainomics.image_atlas import shutil #import proj_classif_config GENDER_MAP = {'Female': 0, 'Male': 1} BASE_PATH = "/neurospin/brainomics/2013_adni" #INPUT_CLINIC_FILENAME = os.path.join(BASE_PATH, "clinic", "adnimerge_baseline.csv") INPUT_SUBJECTS_LIST_FILENAME = os.path.join(BASE_PATH, "templates", "template_FinalQC", "subject_list.txt") INPUT_IMAGEFILE_FORMAT = os.path.join(BASE_PATH, "templates", "template_FinalQC", "registered_images", "mw{PTID}*_Nat_dartel_greyProba.nii") INPUT_CSV = os.path.join(BASE_PATH, "MMSE-AD-CTL", "population.csv") OUTPUT = os.path.join(BASE_PATH, "MMSE-AD-CTL") OUTPUT_CS = os.path.join(BASE_PATH, "MMSE-AD-CTL_cs") #OUTPUT_ATLAS = os.path.join(BASE_PATH, "MMSE-AD-CTL_gtvenet") #OUTPUT_CS_ATLAS = os.path.join(BASE_PATH, "MMSE-AD-CTL_cs_gtvenet") if not os.path.exists(OUTPUT): os.makedirs(OUTPUT) if not os.path.exists(OUTPUT_CS): os.makedirs(OUTPUT_CS) #os.makedirs(OUTPUT_ATLAS) #os.makedirs(OUTPUT_CS_ATLAS) # Read input subjects input_subjects = pd.read_table(INPUT_SUBJECTS_LIST_FILENAME, sep=" ", header=None) input_subjects = [x[:10] for x in input_subjects[1]] # Read pop csv pop = pd.read_csv(INPUT_CSV) pop['PTGENDER.num'] = pop["PTGENDER"].map(GENDER_MAP) ############################################################################# # Read images n = len(pop) assert n == 242 Z = np.zeros((n, 3)) # Intercept + Age + Gender Z[:, 0] = 1 # Intercept y = np.zeros((n, 1)) # DX images = list() for i, PTID in enumerate(pop['PTID']): cur = pop[pop.PTID == PTID] print cur imagefile_pattern = INPUT_IMAGEFILE_FORMAT.format(PTID=PTID) imagefile_name = glob.glob(imagefile_pattern) if len(imagefile_name) != 1: raise ValueError("Found %i files" % len(imagefile_name)) babel_image = nibabel.load(imagefile_name[0]) images.append(babel_image.get_data().ravel()) Z[i, 1:] = np.asarray(cur[["AGE", "PTGENDER.num"]]).ravel() y[i, 0] = cur["MMSE"] shape = babel_image.get_data().shape ############################################################################# # Compute mask # Implicit Masking involves assuming that a lower than a givent threshold # at some voxel, in any of the images, indicates an unknown and is # excluded from the analysis. Xtot = np.vstack(images) mask = (np.min(Xtot, axis=0) > 0.01) & (np.std(Xtot, axis=0) > 1e-6) mask = mask.reshape(shape) assert mask.sum() == 313734 ############################################################################# # Compute atlas mask babel_mask_atlas = brainomics.image_atlas.resample_atlas_harvard_oxford( ref=imagefile_name[0], output=os.path.join("/tmp", "mask.nii.gz")) mask_atlas = babel_mask_atlas.get_data() assert np.sum(mask_atlas != 0) == 638715 mask_atlas[np.logical_not(mask)] = 0 # apply implicit mask # smooth mask_atlas = brainomics.image_atlas.smooth_labels(mask_atlas, size=(3, 3, 3)) assert np.sum(mask_atlas != 0) == 285983 out_im = nibabel.Nifti1Image(mask_atlas, affine=babel_image.get_affine()) out_im.to_filename(os.path.join("/tmp", "mask.nii.gz")) im = nibabel.load(os.path.join("/tmp", "mask.nii.gz")) assert np.all(mask_atlas == im.get_data()) #shutil.copyfile(os.path.join(OUTPUT_ATLAS, "mask.nii.gz"), os.path.join(OUTPUT_CS_ATLAS, "mask.nii.gz")) ############################################################################# # Compute mask with atlas but binarized (not group tv) mask_bool = mask_atlas != 0 assert mask_bool.sum() == 285983 out_im = nibabel.Nifti1Image(mask_bool.astype("int16"), affine=babel_image.get_affine()) out_im.to_filename(os.path.join(OUTPUT, "mask.nii.gz")) babel_mask = nibabel.load(os.path.join(OUTPUT, "mask.nii.gz")) assert np.all(mask_bool == (babel_mask.get_data() != 0)) shutil.copyfile(os.path.join(OUTPUT, "mask.nii.gz"), os.path.join(OUTPUT_CS, "mask.nii.gz")) ############################################################################# # X X = Xtot[:, mask_bool.ravel()] X = np.hstack([Z, X]) assert X.shape == (242, 285986) n, p = X.shape np.save(os.path.join(OUTPUT, "X.npy"), X) fh = open(os.path.join(OUTPUT, "X.npy").replace("npy", "txt"), "w") fh.write('shape = (%i, %i): Intercept + Age + Gender + %i voxels' % \ (n, p, mask_bool.sum())) fh.close() # Xcs X = Xtot[:, mask_bool.ravel()] X = np.hstack([Z[:, 1:], X]) assert X.shape == (242, 285985) X -= X.mean(axis=0) X /= X.std(axis=0) n, p = X.shape np.save(os.path.join(OUTPUT_CS, "X.npy"), X) fh = open(os.path.join(OUTPUT_CS, "X.npy").replace("npy", "txt"), "w") fh.write('Centered and scaled data. Shape = (%i, %i): Age + Gender + %i voxels' % \ (n, p, mask_bool.sum())) fh.close() ## atlas #X = Xtot[:, (mask_atlas.ravel() != 0)] #X = np.hstack([Z, X]) #assert X.shape == (242, 285986) #n, p = X.shape #np.save(os.path.join(OUTPUT_ATLAS, "X.npy"), X) #fh = open(os.path.join(OUTPUT_ATLAS, "X.npy").replace("npy", "txt"), "w") #fh.write('shape = (%i, %i): Intercept + Age + Gender + %i voxels' % \ # (n, p, (mask_atlas.ravel() != 0).sum())) #fh.close() # ## atlas cs #X = Xtot[:, (mask_atlas.ravel() != 0)] #X = np.hstack([Z[:, 1:], X]) #assert X.shape == (242, 285985) #X -= X.mean(axis=0) #X /= X.std(axis=0) #n, p = X.shape #np.save(os.path.join(OUTPUT_CS_ATLAS, "X.npy"), X) #fh = open(os.path.join(OUTPUT_CS_ATLAS, "X.npy").replace("npy", "txt"), "w") #fh.write('Centered and scaled data. Shape = (%i, %i): Age + Gender + %i voxels' % \ # (n, p, (mask_atlas.ravel() != 0).sum())) #fh.close() np.save(os.path.join(OUTPUT, "y.npy"), y) y -= y.mean() y /= y.std() np.save(os.path.join(OUTPUT_CS, "y.npy"), y) #np.save(os.path.join(OUTPUT_ATLAS, "y.npy"), y) #np.save(os.path.join(OUTPUT_CS_ATLAS, "y.npy"), y)

[ "edouard.duchesnay@gmail.com" ]

edouard.duchesnay@gmail.com

2bb5e9136817920f0a118765a28bf286b13b41be

c86277d74266b90b64774bc924b041009d697b2e

/source/nextdoor/wsgi.py

2ae744a10344445edcd3ffe9adf052710f84605a

[]

no_license

rakeshsukla53/facebook-for-neighbours

dcd0c564530404e5415fa08b184398d10b1170ba

3d6c1430ab4f7ac8f668626c82705552da9f6566

refs/heads/master

2021-01-10T04:54:00.962831

2015-12-25T17:32:45

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2

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py

""" WSGI config for nextdoor project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/1.8/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "nextdoor.settings") application = get_wsgi_application()

[ "rakesh.sukla53@gmail.com" ]

rakesh.sukla53@gmail.com

7a78bab1a7c668a9b26dfe834a4c903b5273b3e3

d833e1643f799d8979ae385992be9f3012af23a5

/examples/c60_find_submit.py

848dd0dd9378059f4770fd68b09de99329f047ff

[ "BSD-3-Clause" ]

permissive

ZhouHUB/simdb

05906505d549cbf584dcdcc91c9cebe95c2d349b

33fa21ddcc683e1618dfb337f5f928363c902a1e

refs/heads/master

2020-04-01T22:32:36.665260

2016-04-15T19:20:46

36,950,426

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2018-07-24T19:56:44

2015-06-05T19:06:15

Python

UTF-8

Python

false

1,051

py

__author__ = 'christopher' import ase from simdb.insert import * from simdb.search import * from pyiid.utils import build_sphere_np from copy import deepcopy as dc target_config, = find_atomic_config_document(name='C60 DFT') parent_atoms = target_config.file_payload[-1] # find the combined Potential Energy Surface (PES) pes, = find_pes_document(name='C60 PDF Spring') # find the simulation parameters params, = find_simulation_parameter_document(name='T=1, iter=100, accept=.65') rattles = [.05, .07, .08, .1] for rattle in rattles: # find starting_config try: start_config, = find_atomic_config_document(name='C60' + str(rattle)) except ValueError: starting_atoms = dc(parent_atoms) starting_atoms.rattle(rattle, 42) # Add the atoms to the DB start_config = insert_atom_document('C60 ' + str(rattle), starting_atoms) # Finally create the simulation sim = insert_simulation('C60 rattle->DFT ' + str(rattle), params, start_config, pes) print 'simulation added, number ', sim.id

[ "cjwright4242@gmail.com" ]

cjwright4242@gmail.com

e2886ddba4caf4503f5d0cf9cf97f91e5c76cd44

3d0bb8d94a69237bf3c6ba6b2ccfdd0bc9cc162c

/addons/asterisk/agi-bin/states/get_fast_dial_destination_from_ibs.py

4521e2804bce47ffccda4b3c9723ff47c347a06f

[]

no_license

ha8sh/IBSng

69727a7c5476ecb8efa45b7393ffe51de37a8a10

596aa468f8264ab0129431e3ede6cc1282b1ebbd

refs/heads/main

2023-08-25T18:21:28.081153

2021-10-02T05:03:52

412,687,955

1

0

null

UTF-8

Python

false

791

py

import xmlrpclib import ibs_agi from lib import request from lib.error import * def init(): ibs_agi.getStateMachine().registerState("GET_FAST_DIAL_DESTINATION_FROM_IBS",getFastDialIndexFromIBS) def getFastDialIndexFromIBS(_index): """ get fast dial index destination from ibs may raise an IBSException """ _index=int(_index) req=request.Request() try: destination=req.send("getFastDialDestination",True,index=_index) except xmlrpclib.Fault,e: logException() ibs_agi.getSelectedLanguage().sayPrompt("unknown_problem") raise IBSException(e.faultString) else: if ibs_agi.getConfig().getValue("debug"): toLog("getFastDialIndexFromIBS: %s"%destination) return destination

[ "hassanshaikhi@gmail.com" ]

hassanshaikhi@gmail.com

73c1cb0d4aa4a86afefeb3fd74e8241edec6456a

7620893c7d253a4d8c6f5aef2cfda6c72b777d49

/src/Camera/DisplayImage.py

8d1b1ee14891406071b40da9d5bf7f304a4aa7ad

[]

no_license

garridoH/cameraGUI

cacc549a9da0bcb6c3b9be04ef9783c653300118

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refs/heads/master

2021-01-17T22:38:53.398306

2012-06-12T20:41:44

null

0

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''' Adapted from online sources, including http://www.blog.pythonlibrary.org/2010/03/26/creating-a-simple-photo-viewer-with-wxpython/ ''' import wx class displayImage(wx.App): def __init__(self, redirect=False): wx.App.__init__(self, redirect) self.frame = wx.Frame(None, title='Prosilica Viewer', pos=(100,300), size=(1360,1024)) self.panel = wx.Panel(self.frame) self.Image = wx.StaticBitmap(self.frame, bitmap=wx.EmptyBitmap(1360,1024)) #self.panel.Layout() self.frame.Show() def showImage(self, bmpImg): h=bmpImg.GetHeight() w=bmpImg.GetWidth() print "Image is " + str(h) + " x " + str(w) self.Image.SetBitmap(bmpImg) self.Image.Refresh() def OnClose(self, event): self.Destroy()

[ "raedwards@gmail.com" ]

raedwards@gmail.com

0c3d842557c9376a3e85eb48319735d211b4170d

487ce91881032c1de16e35ed8bc187d6034205f7

/codes/CodeJamCrawler/16_0_1/Naca/main.py

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[]

no_license

DaHuO/Supergraph

9cd26d8c5a081803015d93cf5f2674009e92ef7e

c88059dc66297af577ad2b8afa4e0ac0ad622915

refs/heads/master

2021-06-14T16:07:52.405091

2016-08-21T13:39:13

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2021-03-19T21:55:46

2016-01-17T18:23:00

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T = int(input()); data = []; for i in range(T) : data.append(int(input())); for i in range(T) : if (data[i] == 0) : print("Case #" + str(i + 1) + ": INSOMNIA"); else : digits = []; sumN = data[i]; while (len(digits) < 10) : tmp = sumN; while (tmp > 0) : if (tmp % 10 not in digits) : digits.append(tmp % 10); tmp //= 10; sumN += data[i]; print("Case #" + str(i + 1) + ": " + str(sumN - data[i]));

[ "[dhuo@tcd.ie]" ]

[dhuo@tcd.ie]

5c373349176db66ba2f7617dfca9fa2c18ee4d78

94724578994ab1438dcefb51b7ef4d8570da5d4c

/calibre/draveness.recipe

361ce64106650ddf8643557d49369ebfec882386

[]

no_license

PegasusWang/collection_python

6648d83203634abf44fd42c0b37b0bf7cc406d8f

9ef019a737a0817860d3184924c67a0833bd1252

refs/heads/master

2023-09-01T23:15:39.813635

2023-08-24T06:46:12

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2015-10-05T15:28:15

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recipe

#!/usr/bin/python # encoding: utf-8 from calibre.web.feeds.recipes import BasicNewsRecipe # 引入 Recipe 基础类 """ 教程： - https://bookfere.com/tools#calibre - https://www.jianshu.com/p/0bcb92509309 - https://snowdreams1006.github.io/myGitbook/advance/export.html 命令： ebook-convert draveness.recipe draveness.mobi --output-profile=kindle """ class DravenessBlog(BasicNewsRecipe): # 继承 BasicNewsRecipe 类的新类名 # /////////////////// # 设置电子书元数据 # /////////////////// title = "draveness" # 电子书名 description = u"draveness的博客" # 电子书简介 # cover_url = '' # 电子书封面 # masthead_url = '' # 页头图片 __author__ = "draveness" # 作者 language = "zh" # 语言 encoding = "utf-8" # 编码 # /////////////////// # 抓取页面内容设置 # /////////////////// # keep_only_tags = [{ 'class': 'example' }] # 仅保留指定选择器包含的内容 no_stylesheets = True # 去除 CSS 样式 remove_javascript = True # 去除 JavaScript 脚本 auto_cleanup = True # 自动清理 HTML 代码 delay = 5 # 抓取页面间隔秒数 max_articles_per_feed = 100 # 抓取文章数量 timeout = 10 # /////////////////// # 页面内容解析方法 # /////////////////// def parse_index(self): site = "https://draveness.me/whys-the-design/" soup = self.index_to_soup(site) # 解析列表页返回 BeautifulSoup 对象 articles = [] # 定义空文章资源数组 ultag = soup.findAll("ul")[6] urls = ultag.findAll("li") urls.reverse() for link in urls: title = link.a.contents[0].strip() # 提取文章标题 url = link.a.get("href") # 提取文章链接 print(title, url) articles.append({"title": title, "url": url}) ans = [(self.title, articles)] # 组成最终的数据结构 return ans # 返回可供 Calibre 转换的数据结构

[ "291374108@qq.com" ]

291374108@qq.com

eec8efa198fdd6ce3ad3070fc8265762caf05d1c

58141d7fc37854efad4ad64c74891a12908192ed

/tests/test_storage2.py

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[]

no_license

stanleylio/fishie

b028a93b2093f59a8ceee4f78b55a91bb1f69506

0685045c07e4105934d713a0fd58c4bc28821ed6

refs/heads/master

2022-08-14T13:08:55.548830

2022-07-29T01:32:28

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8

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import unittest,sys from os.path import expanduser sys.path.append(expanduser('~')) from node.storage.storage2 import storage class TestStorage2(unittest.TestCase): def test_read_latest_non_null(self): s = storage() self.assertTrue(s.read_latest_non_null('node-008', 'ReceptionTime', 'idx')) #self.assertTrue(parse_SeaFET(m) is not None) def test_read_last_N_minutes(self): s = storage() self.assertTrue(s.read_last_N_minutes('node-007', 'ReceptionTime', 1, 'T_280')) if __name__ == '__main__': unittest.main()

[ "stanleylio@gmail.com" ]

stanleylio@gmail.com

7f06aa3882b4fc1e0e5f3f8bc66e51bcb16b8038

5730e8d500a65992bb21094ffed26e21ccc7c0fd

/augment_dnase_pipeline_outputs/metadata/aggregate_ataqc.py

2963e434753969d97146b33d89c1eb86a8843a62

[]

no_license

kundajelab/atlas_resources

35f1df4c09356d7256a6667700b88020396d5642

89bcde11921526b9956be48bf367617db4974d31

refs/heads/master

2021-10-25T07:01:30.127405

2021-10-25T00:55:25

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py

import argparse import collections import json import pdb def parse_args(): parser=argparse.ArgumentParser(description="aggregate ataqc metrics for all samples in a single report") parser.add_argument("--ataqc_files",default="/oak/stanford/groups/akundaje/projects/atlas/dnase_processed/aggregate_outputs/qc.json.txt") parser.add_argument("--outf",default="atlas.metadata.report.txt") parser.add_argument("--mitra_prefix",default="http://mitra.stanford.edu/kundaje/projects/atlas/") parser.add_argument("--prefix_to_drop_for_oak",default="/oak/stanford/groups/akundaje/projects/atlas/") parser.add_argument("--hash_to_id",default="/oak/stanford/groups/akundaje/projects/atlas/dnase_processed/processed_all.txt") parser.add_argument("--fname_hash_index",type=int,default=9) return parser.parse_args() def flatten(d, parent_key='', sep='.'): items = [] for k, v in d.items(): new_key = parent_key + sep + k if parent_key else k if isinstance(v, collections.MutableMapping): items.extend(flatten(v, new_key, sep=sep).items()) else: items.append((new_key, v)) return dict(items) def iterate_json(data,val_dict,all_keys,cur_id): flat_data=flatten(data) for key in flat_data: if key not in all_keys: all_keys.add(key) val_dict[cur_id][key]=flat_data[key] return val_dict,all_keys def main(): args=parse_args() ataqc_files=open(args.ataqc_files,'r').read().strip().split('\n') val_dict=dict() all_keys=set([]) outf=open(args.outf,'w') hash_to_id=open(args.hash_to_id,'r').read().strip().split('\n') hash_to_id_dict=dict() for line in hash_to_id: tokens=line.split('\t') cur_hash=tokens[0] cur_id=tokens[1] hash_to_id_dict[cur_hash]=cur_id for fname in ataqc_files: with open(fname,'r') as cur_f: data=json.load(cur_f) #get the report title report_title=fname.replace(args.prefix_to_drop_for_oak,args.mitra_prefix).replace(".json",".html") #get the hash cur_hash=fname.split('/')[args.fname_hash_index] cur_id=hash_to_id_dict[cur_hash] print(cur_id+" : "+report_title) val_dict[cur_id]=dict() val_dict[cur_id]['path']=report_title all_keys.add('path') #iterate through the json file recursively val_dict,all_keys=iterate_json(data,val_dict,all_keys,cur_id) outf.write('Dataset') all_keys=list(all_keys) for key in all_keys: outf.write('\t'+key) outf.write('\n') for dataset in val_dict: outf.write(dataset) for key in all_keys: if key in val_dict[dataset]: outf.write('\t'+str(val_dict[dataset][key])) else: outf.write('\tNA') outf.write('\n') outf.close() if __name__=="__main__": main()

[ "annashcherbina@gmail.com" ]

annashcherbina@gmail.com

58950f55ea5a2b7fae6b323bfc181434c02aaaee

305d25e1d2084761e889057077706b1ba3f9122d

/nmigen_boards/arty_z7.py

ba432b642cc9588c44c7e5037b12b600668f5a6b

[ "LicenseRef-scancode-unknown-license-reference", "BSD-2-Clause" ]

permissive

nicolas-robin/nmigen-boards

d7d8fe29d788f8b1fdcf8da0cf7202a1f0fa741a

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refs/heads/master

2020-12-10T15:43:43.358008

2020-01-17T21:54:48

233,314,458

0

NOASSERTION

2020-01-12T00:01:57

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import os import subprocess from nmigen.build import * from nmigen.vendor.xilinx_7series import * from .resources import * __all__ = ["ArtyZ720Platform"] class ArtyZ720Platform(Xilinx7SeriesPlatform): device = "xc7z020" package = "clg400" speed = "1" default_clk = "clk125" resources = [ Resource("clk125", 0, Pins("H16", dir="i"), Clock(125e6), Attrs(IOSTANDARD="LVCMOS33")), *SwitchResources( pins="M20 M19", attrs=Attrs(IOSTANDARD="LVCMOS33")), RGBLEDResource(0, r="N15", g="G17", b="L15", # LD4 attrs=Attrs(IOSTANDARD="LVCMOS33")), RGBLEDResource(1, # LD5 r="M15", g="L14", b="G14", attrs=Attrs(IOSTANDARD="LVCMOS33")), *LEDResources( pins="R14 P14 N16 M14", attrs=Attrs(IOSTANDARD="LVCMOS33")), *ButtonResources( pins="D19 D20 L20 L19", attrs=Attrs(IOSTANDARD="LVCMOS33")), Resource("audio", 0, Subsignal("pwm", Pins("R18", dir="o")), Subsignal("sd", PinsN("T17", dir="o")), Attrs(IOSTANDARD="LVCMOS33")), Resource("crypto_sda", 0, # ATSHA204A Pins("J15", dir="io"), Attrs(IOSTANDARD="LVCMOS33")), Resource("hdmi_rx", 0, # J10 Subsignal("cec", Pins("H17", dir="io")), Subsignal("clk", DiffPairs("N18", "P19", dir="i"), Attrs(IO_TYPE="TMDS_33")), Subsignal("d", DiffPairs("V20 T20 N20", "W20 U20 P20", dir="i"), Attrs(IO_TYPE="TMDS_33")), Subsignal("hpd", Pins("T19", dir="o")), Subsignal("scl", Pins("U14", dir="io")), Subsignal("sda", Pins("U15", dir="io")), Attrs(IOSTANDARD="LVCMOS33")), Resource("hdmi_tx", 0, # J11 Subsignal("cec", Pins("G15", dir="io")), Subsignal("clk", DiffPairs("L16", "L17", dir="o"), Attrs(IO_TYPE="TMDS_33")), Subsignal("d", DiffPairs("K17 K19 J18", "K18 J19 H18", dir="o"), Attrs(IO_TYPE="TMDS_33")), Subsignal("hpd", PinsN("R19", dir="i")), Subsignal("scl", Pins("M17", dir="io")), Subsignal("sda", Pins("M18", dir="io")), Attrs(IOSTANDARD="LVCMOS33")) ] connectors = [ Connector("pmod", 0, "Y18 Y19 Y16 Y17 - - U18 U19 W18 W19 - -"), # JA Connector("pmod", 1, "Y14 W14 T10 T11 - - W16 V16 W13 V12 - -"), # JB Connector("ck_io", 0, { # Outer Digital Header "io0": "T14", "io1": "U12", "io2": "U13", "io3": "V13", "io4": "V15", "io5": "T15", "io6": "R16", "io7": "U17", "io8": "V17", "io9": "V18", "io10": "T16", "io11": "R17", "io12": "P18", "io13": "N17", # Inner Digital Header "io26": "U5", "io27": "V5", "io28": "V6", "io29": "U7", "io30": "V7", "io31": "U8", "io32": "V8", "io33": "V10", "io34": "W10", "io35": "W6", "io36": "Y6", "io37": "Y7", "io38": "W8", "io39": "Y8", "io40": "W9", "io41": "Y9", # Outer Analog Header as Digital IO "a0": "Y11", "a1": "Y12", "a2": "W11", "a3": "V11", "a4": "T5", "a5": "U10", # Inner Analog Header as Digital IO "a6": "F19", "a7": "F20", "a8": "C20", "a9": "B20", "a10": "B19", "a11": "A20", # Misc. "a": "Y13" }), Connector("ck_spi", 0, { "miso": "W15", "mosi": "T12", "sck": "H15", "ss": "F16" }), Connector("ck_i2c", 0, { "scl": "P16", "sda": "P15" }), Connector("xadc", 0, { # Outer Analog Header "vaux1_n": "D18", "vaux1_p": "E17", "vaux9_n": "E19", "vaux9_p": "E18", "vaux6_n": "J14", "vaux6_p": "K14", "vaux15_n": "J16", "vaux15_p": "K16", "vaux5_n": "H20", "vaux5_p": "J20", "vaux13_n": "G20", "vaux13_p": "G19", # Inner Analog Header "vaux12_n": "F20", "vaux12_p": "F19", "vaux0_n": "B20", "vaux0_p": "C20", "vaux8_n": "A20", "vaux8_p": "B19" }) ] def toolchain_program(self, products, name, **kwargs): xc3sprog = os.environ.get("XC3SPROG", "xc3sprog") with products.extract("{}.bit".format(name)) as bitstream_filename: subprocess.run([xc3sprog, "-c", "jtaghs1_fast", "-p", "1", bitstream_filename], check=True) if __name__ == "__main__": from .test.blinky import * ArtyZ720Platform().build(Blinky(), do_program=True)

[ "whitequark@whitequark.org" ]

whitequark@whitequark.org

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/book/apress/Beginning.Python.Visualization.Crafting.Visual.Transformation.Scripts/Chapter04/src/read_ini.py

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xenron/sandbox-da-python

0814159da9a91923e4b66c5e40057e381f765e96

ab8f1c0d57fdc6006355f613012b84165068c315

refs/heads/master

2020-04-12T05:41:33.182110

2016-12-14T22:57:33

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# read an INI (config) file import ConfigParser read_opts=ConfigParser.ConfigParser() read_opts.read('../data/options.ini') # print parameters and values for section in read_opts.sections(): print "[%s]" % section for param in read_opts.items(section): print param

[ "xenron@outlook.com" ]

xenron@outlook.com

db3596b8480850b3718c2c9d08671fd49db81831

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/main_app/migrations/0018_profile.py

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[]

no_license

tanveerahmad1517/Treasuregram

134853f298628c161ebe741864cdb581ce80db8f

797e0ff1460eb50d90aa385f6fb25990ed7766fa

refs/heads/master

2020-03-10T13:58:43.912795

2018-04-13T14:32:31

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py

# -*- coding: utf-8 -*- # Generated by Django 1.10 on 2018-02-13 13:10 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main_app', '0017_remove_treasure_date'), ] operations = [ migrations.CreateModel( name='Profile', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(db_column='first_name', max_length=50)), ('last_name', models.CharField(db_column='last_name', max_length=50)), ], ), ]

[ "tanveerobjects@gmail.com" ]

tanveerobjects@gmail.com

53171e07178a012d3d4820a34f4a4926dbf039f9

909afe0216a37bdc19683d81e533fa6c094329c1

/python/fluent_python/17-futures/flags_threadpool.py

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[]

no_license

wxnacy/study

af7fdcd9915d668be73c6db81bdc961247e24c73

7bca9dc8ec211be15c12f89bffbb680d639f87bf

refs/heads/master

2023-04-08T17:57:40.801687

2023-03-29T08:02:20

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null

2022-12-16T03:11:43

2018-01-19T07:14:02

HTML

UTF-8

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#!/usr/bin/env python # -*- coding:utf-8 -*- # Author: wxnacy(wxnacy@gmail.com) # Description: 使用多线程下载 from concurrent.futures import ThreadPoolExecutor from flags import download_one, main MAX_WORKERS = 20 def download_many(suffixs): workers = min(MAX_WORKERS, len(suffixs)) with ThreadPoolExecutor(workers) as executor: res = executor.map(download_one, suffixs) return len(list(res)) if __name__ == "__main__": main(download_many)

[ "371032668@qq.com" ]

371032668@qq.com

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/portrait/deeplab/model_test.py

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[ "Apache-2.0" ]

permissive

hiepgaf/portrait

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refs/heads/master

2020-03-19T00:14:06.916160

2018-05-14T05:57:29

null

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null

UTF-8

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py

"""Tests for encoder""" import numpy as np import tensorflow as tf from model import deeplab_v3_plus_model def create_test_inputs(batch, height, width, channels): """Create mock Images """ if None in [batch, height, width, channels]: return tf.placeholder(tf.float32, (batch, height, width, channels)) else: return tf.to_float( np.tile(np.reshape( np.reshape(np.arange(height), [height, 1]) + np.reshape(np.arange(width), [1, width]), [1, height, width, 1]), [batch, 1, 1, channels])) class DeepLabV3PlusTest(tf.test.TestCase): def testBuildDeepLabV3Plus(self): """"Encoder Constructor Test""" images = create_test_inputs(2, 224, 224, 3) encoded_features, _ = deeplab_v3_plus_model( images=images) self.assertListEqual( encoded_features.get_shape().as_list(), [2, 28, 28, 256]) if __name__ == '__main__': tf.test.main()

[ "tdat.nguyen93@gmail.com" ]

tdat.nguyen93@gmail.com

3091099fee02328c00c32ce85434caa6c2918a00

d2fdd6b10b0467913971d1408a9a4053f0be9ffb

/datahub/investment/project/migrations/0033_add_investment_document_permission.py

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[]

no_license

jakub-kozlowski/data-hub-leeloo

fc5ecebb5e4d885c824fc7c85acad8837fcc5c76

7f033fcbcfb2f7c1c0e10bec51620742d3d929df

refs/heads/master

2020-05-18T13:29:14.145251

2019-04-30T12:12:50

null

0

null

UTF-8

Python

false

728

py

# Generated by Django 2.0.1 on 2018-01-09 16:32 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('investment', '0032_investmentproject_comments'), ] operations = [ migrations.AlterModelOptions( name='investmentproject', options={'default_permissions': ('add', 'change_all', 'delete'), 'permissions': (('read_all_investmentproject', 'Can read all investment project'), ('read_associated_investmentproject', 'Can read associated investment project'), ('change_associated_investmentproject', 'Can change associated investment project'), ('read_investmentproject_document', 'Can read investment project document'))}, ), ]

[ "reupen@users.noreply.github.com" ]

reupen@users.noreply.github.com

3e5b76060a8d08eb9c454a93b5bf91d108e6268c

e2e08d7c97398a42e6554f913ee27340226994d9

/pyautoTest-master（ICF-7.5.0）/test_case/scg_old/scg_obj_shell_2nd/test_c40343.py

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[]

no_license

lizhuoya1111/Automated_testing_practice

88e7be512e831d279324ad710946232377fb4c01

b3a532d33ddeb8d01fff315bcd59b451befdef23

refs/heads/master

2022-12-04T08:19:29.806445

2020-08-14T03:51:20

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null

UTF-8

Python

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import pytest import time import sys from page_obj.scg.scg_def import * from page_obj.scg.scg_def_obj import * from page_obj.scg.scg_def_log import * from page_obj.common.rail import * from os.path import dirname, abspath sys.path.insert(0, dirname(dirname(abspath(__file__)))) test_id = 40343 # 修改以subnet方式添加的一条addr obj,查看log def test_change_obj_wxw(browser): try: login_web(browser, url="10.2.2.81") # 先添加再修改 add_obj_address_wxw(browser, name='obj_add_343', desc='zhe是yi个描述1', subnetip='11.11.11.1', subnetmask='24') # 欲修改哪个参数可直接编辑 change_obj_address_wxw(browser, name='obj_add_343', desc='zhe是yi个描述2', subnetip='11.11.11.2', subnetmask='32') time.sleep(2) # 切换到默认frame browser.switch_to.default_content() get_log(browser, 管理日志) browser.switch_to.default_content() # 切换到左侧frame browser.switch_to.frame("content") loginfo = browser.find_element_by_xpath('//*[@id="namearea0"]').text try: assert "配置地址对象成功，修改内部对象 [obj_add_343]" in loginfo rail_pass(test_run_id, test_id) except: rail_fail(test_run_id, test_id) assert "配置地址对象成功，修改内部对象 [obj_add_343]" in loginfo except Exception as err: # 如果上面的步骤有报错，重新设备，恢复配置 reload(hostip="10.2.2.81") print(err) rail_fail(test_run_id, test_id) time.sleep(70) assert False if __name__ == '__main__': pytest.main(["-v", "-s", "test_c40343.py"])

[ "15501866985@163.com" ]

15501866985@163.com

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/mah/divide and conquer/[BOJ]1920_수 찾기.py

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[]

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hongsungheejin/Algo-Study

f1c521d01147a6f74320dbc8efe3c1037e970e73

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refs/heads/main

2023-07-06T10:58:27.258128

2021-07-29T02:11:13

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N = int(input()) nums = list(map(int, input().split())) nums.sort() M = int(input()) tars = list(map(int, input().split())) def binary_serach(tar): l, r = 0, len(nums) - 1 while l<=r: m = (l+r)//2 if nums[m] == tar: return 1 elif nums[m] < tar: l=m+1 else: r=m-1 return 0 for tar in tars: print(binary_serach(tar))

[ "mai.hong0924@gmail.com" ]

mai.hong0924@gmail.com

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205be8d429df36e27cdfc048bfca9212c5a62a87

/icu/urls.py

ed2cf073014ebef72cfb33b59762ed1241b9df93

[]

no_license

KennyChrisUmurundi/HOsto

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refs/heads/master

2022-04-01T02:42:39.146227

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from django.urls import path from django.contrib.auth import views as auth_views from . import views as icu_views from django.conf.urls.static import static from django.conf import settings app_name = 'icu' urlpatterns = [ path('Medical Update/',icu_views.update_list,name="add-medical"), path('scan/',icu_views.ScanCode,name="ScanCode"), path('patient/<slug:code>',icu_views.patient,name="patient"), path('feedback/<slug:code>/<int:id>',icu_views.feedback,name="feedback"), ]

[ "ndayikennysmuusic@gmail.com" ]

ndayikennysmuusic@gmail.com

13daadc403ee347a1877bef70ef64461737e38cc

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/coinlibbitfinex/coinlibbitfinex/streamapi.py

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[]

no_license

tetocode/coinliball

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41ebbac13c1fbba98aedaa766b9a505cb157f374

refs/heads/master

2022-09-28T21:58:08.130006

2020-06-04T03:00:56

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import json import logging from typing import Hashable, Dict from websocket import WebSocket from coinlib.datatypes.streamdata import StreamData from coinlib.trade.websocketstreamapi import WebSocketStreamApi logger = logging.getLogger(__name__) class StreamApi(WebSocketStreamApi): URL = 'wss://api.bitfinex.com/ws' def __init__(self, **kwargs): super().__init__(**kwargs) self._subscriptions = {} self._channel_id_map: Dict[int, Hashable] = {} def _process_subscription_q(self, ws: WebSocket): # process one if len(self._subscription_q): op, (key, params) = self._subscription_q.popleft() if op == 'subscribe': self._subscriptions[key] = params self._subscribe_channel(params) logger.debug(f'subscribe {key} {params}') elif op == 'unsubscribe': params = self._subscriptions.pop(key, None) if params is not None: for channel_id, v in self._channel_id_map.items(): if v == key: self._unsubscribe_channel(channel_id) logger.debug(f'unsubscribe {key} {params} {channel_id}') break else: assert False, f'unknown operation={op}' def _subscribe_channel(self, params: dict): request = dict(event='subscribe') request.update(params) self.send_message(request) def _unsubscribe_channel(self, channel_id: int): self.send_message({ 'event': 'unsubscribe', 'chanId': channel_id, }) def on_message(self, message_data: str): message = json.loads(message_data) if isinstance(message, dict): event = message.get('event') if event == 'info': logger.debug(f'event info {message}') return elif event == 'subscribed': self.on_subscribed(message) return elif event == 'unsubscribed': self.on_unsubscribed(message) return elif event == 'error': self.on_error(message) return else: logger.warning(f'event unsupported {message}') return if isinstance(message, list): self.on_channel_data(message) return logger.warning(f'unknown message {message}') def on_subscribed(self, message: dict): channel_name = message['channel'] for key, params in self._subscriptions.items(): if channel_name == params.get('channel'): if channel_name == 'book': # TODO: distinguish between order_book and raw_order_book if message['pair'].upper() != params.get('pair', '').upper(): continue channel_id = int(message['chanId']) self._channel_id_map[channel_id] = key logger.debug(f'event subscribed {message}') return logger.warning('unknown event subscribe {message}') def on_unsubscribed(self, message: dict): _ = self logger.debug(f'event unsubscribed {message}') def on_error(self, message: dict): _ = self logger.error(f'event error {message}') def on_channel_data(self, data: list): channel_id = data[0] key = self._channel_id_map.get(channel_id) if key: self.on_raw_data(StreamData(key, data))

[ "_" ]

_

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/djthia/core/views.py

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permissive

carthage-college/django-djthia

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refs/heads/master

2023-03-04T08:22:03.055448

2023-02-24T18:33:12

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MIT

2023-02-24T18:33:56

2020-03-25T13:43:24

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# -*- coding: utf-8 -*- import json import requests from datetime import datetime from django.conf import settings from django.core.cache import cache from django.http import HttpResponse from django.shortcuts import render from django.urls import reverse_lazy from django.utils.safestring import mark_safe from django.views.decorators.csrf import csrf_exempt from djauth.decorators import portal_auth_required from djthia.core.decorators import eligibility @portal_auth_required( session_var='DJTHIA_AUTH', redirect_url=reverse_lazy('access_denied'), ) @eligibility def home(request): """Application home.""" return render(request, 'home.html', {'year': datetime.now().year}) @csrf_exempt @portal_auth_required( session_var='DJTHIA_AUTH', redirect_url=reverse_lazy('access_denied'), ) def clear_cache(request, ctype='blurbs'): """Clear the cache for API content.""" cid = request.POST.get('cid') request_type = 'post' if not cid: cid = request.GET.get('cid') request_type = 'get' if cid: key = 'livewhale_{0}_{1}'.format(ctype, cid) cache.delete(key) timestamp = datetime.timestamp(datetime.now()) earl = '{0}/live/{1}/{2}@JSON?cache={3}'.format( settings.LIVEWHALE_API_URL, ctype, cid, timestamp, ) try: response = requests.get(earl, headers={'Cache-Control': 'no-cache'}) text = json.loads(response.text) cache.set(key, text) api_data = mark_safe(text['body']) except ValueError: api_data = "Cache was not cleared." if request_type == 'post': content_type = 'text/plain; charset=utf-8' else: content_type = 'text/html; charset=utf-8' else: api_data = "Requires a content ID" return HttpResponse(api_data, content_type=content_type)

[ "plungerman@gmail.com" ]

plungerman@gmail.com

15964455a90498f40c1b5832baba1979f60603a1

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/codes/CodeJamCrawler/16_0_3_neat/16_0_3_stanm_coin-jam.py

d03fbeb3caa801b73d052e9fa018ecc9ef309635

[]

no_license

DaHuO/Supergraph

9cd26d8c5a081803015d93cf5f2674009e92ef7e

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refs/heads/master

2021-06-14T16:07:52.405091

2016-08-21T13:39:13

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py

#! /usr/bin/python import sys def rinp(): one = input() _ = input().split(' ') N = int(_[0]) J = int(_[1]) return (N, J) def get_binary(num): return "{0:b}".format(num) def in_base(stng, base): return int(stng, base) def get_div(x): for d in range(2, x): if d * d > x: return 1 if x % d == 0: return d def check_num(x): bnry = get_binary(x) divs = [] for base in range(2, 11): t = in_base(bnry, base) div = get_div(t) if div == 1: return 0 divs.append(div) print (bnry, " ".join([str(d) for d in divs])) return 1 def main(): (N, J) = rinp() start = 2 ** (N - 1) + 1 end = 2 ** N - 1 print ("Case #1:") count = 0 for x in range(end, start, -2): get_binary(x) count += check_num(x) if count == J: break if __name__ == '__main__': main()

[ "[dhuo@tcd.ie]" ]

[dhuo@tcd.ie]

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/aefingar_forritun/daemi21-while.py

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[]

no_license

danielthorr18/forritun_git

c3647e1e6dd35cd55287bb2d51066d8ab55ea931

b544371664a15dd0660aef83cdf474e506e1b412

refs/heads/master

2020-03-28T00:04:50.700712

2018-11-15T15:26:42

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py

turns = int(input("Sláðu inn tölu: ")) counter = 0 while counter < turns: pick = int(input("Sláðu inn tölu: ")) if pick % 2 == 1: print("þú valdir", pick) counter += 1

[ "danielr18@ru.is" ]

danielr18@ru.is

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/alf/networks/action_encoder.py

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permissive

HorizonRobotics/alf

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2023-08-21T18:51:41.370566

2023-08-16T00:07:22

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Apache-2.0

2023-09-14T20:40:20

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# Copyright (c) 2019 Horizon Robotics. 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. """A simple parameterless action encoder.""" import numpy as np import torch import torch.nn.functional as F import alf from .network import Network class SimpleActionEncoder(Network): """A simple encoder for action. It encodes discrete action to one hot representation and use the original continous actions. The output is the concat of all of them after flattening. """ def __init__(self, action_spec): """ Args: action_spec (nested BoundedTensorSpec): spec for actions """ def check_supported_spec(spec): if spec.is_discrete: assert np.min(spec.minimum) == np.max(spec.minimum) == 0 assert np.min(spec.maximum) == np.max(spec.maximum) alf.nest.map_structure(check_supported_spec, action_spec) self._action_spec = action_spec super().__init__(input_tensor_spec=action_spec, name="ActionEncoder") def forward(self, inputs, state=()): """Generate encoded actions. Args: inputs (nested Tensor): action tensors. Returns: nested Tensor with the same structure as inputs. """ alf.nest.assert_same_structure(inputs, self._action_spec) actions = inputs outer_rank = alf.nest.utils.get_outer_rank(inputs, self._action_spec) def _encode_one_action(action, spec): if spec.is_discrete: num_actions = spec.maximum - spec.minimum + 1 if num_actions.ndim == 0: num_actions = int(num_actions) else: num_actions = int(num_actins[0]) a = F.one_hot(action, num_actions).to(torch.float32) else: a = action if outer_rank > 0: return a.reshape(*a.shape[:outer_rank], -1) else: return a.reshape(-1) actions = alf.nest.map_structure(_encode_one_action, actions, self._action_spec) return torch.cat(alf.nest.flatten(actions), dim=-1), ()

[ "noreply@github.com" ]

HorizonRobotics.noreply@github.com

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/tensorflow_federated/python/research/optimization/emnist_ae/dataset_test.py

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permissive

matech96/federated

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refs/heads/master

2022-11-12T10:20:34.483506

2020-06-11T21:13:02

2020-06-11T21:13:30

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Apache-2.0

2020-06-11T21:31:51

2020-06-11T21:31:50

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# Copyright 2019, The TensorFlow Federated 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. import tensorflow as tf from tensorflow_federated.python.research.optimization.emnist_ae import dataset TEST_BATCH_SIZE = dataset.TEST_BATCH_SIZE class DatasetTest(tf.test.TestCase): def test_emnist_dataset_structure(self): emnist_train, emnist_test = dataset.get_emnist_datasets( client_batch_size=10, client_epochs_per_round=1, only_digits=True) self.assertEqual(len(emnist_train.client_ids), 3383) sample_train_ds = emnist_train.create_tf_dataset_for_client( emnist_train.client_ids[0]) train_batch = next(iter(sample_train_ds)) train_batch_shape = train_batch[0].shape test_batch = next(iter(emnist_test)) test_batch_shape = test_batch[0].shape self.assertEqual(train_batch_shape.as_list(), [10, 28*28]) self.assertEqual(test_batch_shape.as_list(), [TEST_BATCH_SIZE, 28*28]) def test_global_emnist_dataset_structure(self): global_train, global_test = dataset.get_centralized_emnist_datasets( batch_size=32, only_digits=False) train_batch = next(iter(global_train)) train_batch_shape = train_batch[0].shape test_batch = next(iter(global_test)) test_batch_shape = test_batch[0].shape self.assertEqual(train_batch_shape.as_list(), [32, 28*28]) self.assertEqual(test_batch_shape.as_list(), [TEST_BATCH_SIZE, 28*28]) if __name__ == '__main__': tf.test.main()

[ "tensorflow.copybara@gmail.com" ]

tensorflow.copybara@gmail.com

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/src/Socket_Control/coordinate_collation_interface.py

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SamKaiYang/2019_Hiwin_Shaking

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refs/heads/master

2020-07-22T13:25:21.063822

2019-09-09T03:29:11

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#!/usr/bin/env python3 # license removed for brevity #encoding:utf-8 import tkinter as tk import shake_strategy_trigger as shake_trig import shake_strategy_content as shake_cont # interface for collation # ======================================================================= # =23/07/2019:add above pos_collation = # ======================================================================= collate_speed=15 def LeftCollate(): shake_cont.InitData(shake_cont.delt_z) # shake_cont.Left(shake_cont.Animation_Action) shake_cont.Left(shake_trig.Hiwin_Solo_Action) shake_cont.InitData(-shake_cont.delt_z) def RightCollate(): shake_cont.InitData(shake_cont.delt_z) # shake_cont.Right(shake_cont.Animation_Action) shake_cont.Right(shake_trig.Hiwin_Solo_Action) shake_cont.InitData(-shake_cont.delt_z) def ArmTestAct(): shake_cont.InitData(shake_cont.delt_z) # shake_cont.ArmTest(shake_cont.Animation_Action) shake_cont.ArmTest(shake_trig.Hiwin_Action) shake_cont.InitData(-shake_cont.delt_z) def CupCollate(): global collate_speed shake_cont.InitData(shake_cont.delt_z) # Action=shake_cont.Animation_Action Action=shake_trig.Hiwin_Solo_Action shake_cont.SpeedModeToggle(1) Action.ArmMove(shake_cont.Above_Shake_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯上方') Action.ArmMove(shake_cont.Pre_Grip_Pos,collate_speed,shake_cont.gp_stop,'轉動') Action.ArmMove(shake_cont.Grip_Shake_For_Pour_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯') tk.messagebox.showinfo(message='Shake OK?') Action.GripCtrl(shake_cont.Grip_Shake_For_Pour_Pos,collate_speed,shake_cont.gp_tight_catch,'移動至雪克杯','夾住雪克杯') tk.messagebox.showinfo(message='Shake OK?') Action.ArmMove(shake_cont.Lift_Up_Full_Shake_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯空位上方') Action.ArmMove(shake_cont.Pour_Product_Ready_Pos,collate_speed,shake_cont.gp_stop,'準備倒飲料至手搖杯') Action.ArmMove(shake_cont.Pour_Product_Pour_Pos,collate_speed,shake_cont.gp_stop,'倒飲料至手搖杯') Action.ArmMove(shake_cont.Pour_Product_Down_Pos,collate_speed,shake_cont.gp_stop,'向下移動') tk.messagebox.showinfo(message='Cup OK?') Action.ArmMove(shake_cont.Pour_Product_Pour_Pos,collate_speed,shake_cont.gp_stop,'向上移動') Action.ArmMove(shake_cont.Pour_Product_Ready_Pos,collate_speed,shake_cont.gp_stop,'倒飲料至手搖杯結束') Action.ArmMove(shake_cont.Lift_Up_Full_Shake_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯空位上方') Action.GripCtrl(shake_cont.Grip_Shake_For_Pour_Pos,collate_speed,shake_cont.gp_open,'放下雪克杯','鬆開雪克杯') tk.messagebox.showinfo(message='Cup OK?') Action.ArmMove(shake_cont.Pre_Grip_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯上方') Action.ArmMove(shake_cont.Above_Shake_Pos,collate_speed,shake_cont.gp_stop,'轉動') tk.messagebox.showinfo(message='Collation Finished!') Action.ArmMove(shake_cont.Home_Pos,collate_speed,shake_cont.gp_stop,'移動至原位') shake_cont.InitData(-shake_cont.delt_z) def LidCollate(): shake_cont.InitData(shake_cont.delt_z) # Action=shake_cont.Animation_Action Action=shake_trig.Hiwin_Solo_Action shake_cont.SpeedModeToggle(1) Action.LimitArmMove(shake_cont.Above_Lid_Pos,collate_speed,5,shake_cont.gp_stop,'移動至雪克杯蓋上方') Action.GripCtrl(shake_cont.Lid_Pos,collate_speed,shake_cont.gp_tight_catch,'移動至雪克杯蓋','夾住雪克杯蓋') tk.messagebox.showinfo(message='Lid OK?') Action.ArmMove(shake_cont.Above_Lid_Pos,collate_speed,shake_cont.gp_stop,'拿起雪克杯蓋') Action.ArmMove(shake_cont.Above_Shake_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯上方') Action.LimitArmMove(shake_cont.Collate_Lid_Pos,collate_speed,5,shake_cont.gp_stop,'蓋杯蓋') tk.messagebox.showinfo(message='Lid OK?') Action.ArmMove(shake_cont.Above_Shake_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯上方') Action.ArmMove(shake_cont.Above_Lid_Pos,collate_speed,shake_cont.gp_stop,'移動至雪克杯蓋上方') Action.GripCtrl(shake_cont.Lid_Pos,collate_speed//2,shake_cont.gp_open,'放下雪克杯蓋','鬆開雪克杯蓋') tk.messagebox.showinfo(message='Collation Finished!') Action.ArmMove(shake_cont.Home_Pos,collate_speed,shake_cont.gp_stop,'移動至原位') shake_cont.InitData(-shake_cont.delt_z) def PosCollate(): shake_cont.InitData(shake_cont.delt_z) pos_list = [shake_cont.Home_Pos,shake_cont.Full_Ice_Pos,shake_cont.Above_Ice_Pos, shake_cont.Above_Duo_Duo_Pos,shake_cont.Duo_Duo_Pos,shake_cont.Above_Duo_Duo_Pos, shake_cont.Above_Dong_Gua_T_Pos,shake_cont.Dong_Gua_T_Pos,shake_cont.Above_Dong_Gua_T_Pos, shake_cont.Above_Blace_T_Pos,shake_cont.Blace_T_Pos,shake_cont.Above_Blace_T_Pos, shake_cont.Above_Green_T_Pos,shake_cont.Green_T_Pos,shake_cont.Above_Green_T_Pos, shake_cont.Above_Lid_Pos,shake_cont.Back_Sugar_Pos,shake_cont.Above_Sugar_Unspined_Pos, shake_cont.Above_Sugar_Unspined_Pos,shake_cont.Back_Sugar_Pos] pause_list=[1,4,7,10,13,18] shake_cont.SpeedModeToggle(1) for i in range(len(pos_list)): shake_trig.Hiwin_Action.ArmMove(pos_list[i],collate_speed,0,'test point({}/{})'.format(i+1,len(pos_list))) # shake_cont.Animation_Action.ArmMove(pos_list[i],20,0,'test point({}/{})'.format(i+1,len(pos_list))) if i in pause_list: tk.messagebox.showinfo(message='Next Point?') tk.messagebox.showinfo(message='Collation Finished!') # shake_cont.Home(shake_cont.Animation_Action) shake_cont.Home(shake_trig.Hiwin_Action) shake_cont.InitData(-shake_cont.delt_z) def Collation(): collate = tk.Toplevel() collate.title('Coordinate Collation') collate.geometry('620x355') collate.wm_attributes("-topmost",1) def CollateOK(): collate.destroy() # shake_cont.Home(shake_cont.Animation_Action) shake_cont.Home(shake_trig.Hiwin_Solo_Action) arm_test = tk.Button(collate,text='Arm Test',font=('Arial', 15),width=45,height=2,command=ArmTestAct) arm_test.place(x=50,y=35) left_collate = tk.Button(collate,text='Left',font=('Arial', 15),width=19,height=2,command=LeftCollate) left_collate.place(x=50,y=110) right_collate = tk.Button(collate,text='Right',font=('Arial', 15),width=19,height=2,command=RightCollate) right_collate.place(x=335,y=110) pos_collate = tk.Button(collate,text='Pos',font=('Arial', 15),width=12,height=2,command=PosCollate) pos_collate.place(x=50,y=185) cup_collate = tk.Button(collate,text='Cup',font=('Arial', 15),width=12,height=2,command=CupCollate) cup_collate.place(x=230,y=185) lid_collate = tk.Button(collate,text='Lid',font=('Arial', 15),width=12,height=2,command=LidCollate) lid_collate.place(x=410,y=185) collate_ok = tk.Button(collate,text='OK',font=('Arial', 15),width=45,height=2,command=CollateOK) collate_ok.place(x=50,y=260) def BackHome(): collate.destroy() # shake_cont.Home(shake_cont.Animation_Action) shake_cont.Home(shake_trig.Hiwin_Solo_Action) collate.protocol('WM_DELETE_WINDOW', BackHome) collate.mainloop()

[ "tt00621212@gmail.com" ]

tt00621212@gmail.com

7f824ee40e811bbb0b10b06bebe9de412a97a178

65e07d1e35598e5686e743e9bdefcdd5e1269a0d

/archiveit_redirect.py

51440f3afb3374425033df8ef6d544f7754a5e5a

[]

no_license

ale-gaeta/bentley_scripts

94dbf3e120c218ec0af8ed235bc304ca45b3518e

2ad4b986212715a495036697d78952dc53dad74c

refs/heads/master

2023-03-15T14:12:12.595590

2016-06-30T19:02:55

null

0

null

UTF-8

Python

false

6,501

py

import os from os.path import join import requests from lxml import etree import csv import re import HTMLParser def get_redirect_metadata(redirect_dict, collection_id, redirect_dir): skip = ['createdDate','lastUpdatedDate','active','public','note','url'] starting_seeds = {} for seed in redirect_dict: starting_seeds[seed] = '' with requests.Session() as s: collection_feed = s.get('https://partner.archive-it.org/seam/resource/collectionFeed?accountId=934&collectionId=' + collection_id) collection_metadata = etree.fromstring(collection_feed.text.encode('utf-8')) tree = etree.ElementTree(collection_metadata) seeds = tree.xpath('//seed') for seed in seeds: url = seed.xpath('./url')[0].text if url in starting_seeds: starting_seeds[url] = tree.getpath(seed) redirect_metadata = [] add_deactivate = {} redirect_investigate = {} entity_parser = HTMLParser.HTMLParser() for seed in starting_seeds: if len(starting_seeds[seed]) > 0: new_seed = redirect_dict[seed] add_deactivate[seed] = new_seed seed_metadata = {} seed_path = starting_seeds[seed] seed_element = tree.xpath(seed_path)[0] for elem in seed_element.xpath('.//*'): if elem.text is not None and not elem.tag in skip and not 'name' in elem.attrib: elem_name = elem.tag elem_text = entity_parser.unescape(elem.text.replace('“','"').replace('”','"').replace('’',"'")) if elem_name not in seed_metadata: seed_metadata[elem_name] = [] seed_metadata[elem_name].append(elem_text.encode('utf-8')) elif 'name' in elem.attrib: if elem.attrib['name'] not in skip: elem_name = elem.attrib['name'] elem_text = entity_parser.unescape(elem.text.replace('“','"').replace('”','"').replace('’',"'")) if elem_name not in seed_metadata: seed_metadata[elem_name] = [] seed_metadata[elem_name].append(elem_text.encode('utf-8')) seed_metadata['url'] = [] seed_metadata['url'].append(new_seed) seed_metadata['Note'] = [] seed_metadata['Note'].append("QA NOTE: This seed was created as a result of the previous seed URL redirecting to this URL. Previous captures under seed URL " + seed) redirect_metadata.append(seed_metadata) else: redirect_investigate[seed] = redirect_dict[seed] with open(join(redirect_dir,'add_and_deactivate.csv'),'ab') as add_deactivate_csv: writer = csv.writer(add_deactivate_csv) writer.writerow(['Add','Deactivate','Deactivation Note']) for seed, new_seed in add_deactivate.items(): writer.writerow([new_seed, seed, 'QA NOTE: Seed deactivated. Seed URL redirects to ' + new_seed + '. A new seed with the redirected seed URL has been added.']) if len(redirect_investigate) > 0: with open(join(redirect_dir,'redirect_investigate.csv'),'ab') as investigate_csv: writer = csv.writer(investigate_csv) writer.writerow(['Seed URL','Redirect URL']) for seed, new_seed in redirect_investigate.items(): writer.writerow([seed, new_seed]) header_order = ['url','Title','Subject','Personal Creator','Corporate Creator','Coverage','Description','Publisher','Note'] redirect_csv = join(redirect_dir,'redirect_metadata.csv') header_counts = {} for seed in redirect_metadata: for element in seed: count = len(seed[element]) elem_lower = element.lower() if element not in header_counts: header_counts[element] = count elif count > header_counts[element]: header_counts[element] = count for element in header_order: elem_lower = element.lower() if element not in header_counts and elem_lower not in header_counts: header_counts[element] = 1 for seed in redirect_metadata: for element in header_counts: if element not in seed: seed[element] = [] for element in seed: current_count = len(seed[element]) header_count = header_counts[element] difference = header_count - current_count if difference > 0: seed[element].extend([''] * difference) header_row = [] header_counts_lower = {k.lower():v for k,v in header_counts.items()} for element in header_order: elem_lower = element.lower() header_row.extend([element] * header_counts_lower[elem_lower]) with open(redirect_csv,'ab') as csvfile: writer = csv.writer(csvfile) writer.writerow(header_row) for seed in redirect_metadata: row = [] for element in header_order: elem_lower = element.lower() if element in seed: row.extend([item for item in seed[element]]) elif elem_lower in seed: row.extend([item for item in seed[elem_lower]]) with open(redirect_csv,'ab') as csvfile: writer = csv.writer(csvfile) writer.writerow(row) def main(): job_numbers = raw_input('Enter a comma separated list of job numbers: ') base_dir = raw_input('Enter the directory in which job files are saved (e.g., U:/web_archives/jobs): ') jobs = [job.strip() for job in job_numbers.split(',')] for job in jobs: redirect_dict = {} job_dir = join(base_dir,job) with open(join(job_dir,'seedstatus.csv'),'rb') as csvfile: reader = csv.reader(csvfile) first_row = reader.next() collection_string = first_row[0] collection_id = re.findall(r'(\d+)\t',collection_string)[0] redirect_dir = join(job_dir,'redirects') redirect_csv = join(redirect_dir,'redirect_information.csv') with open(redirect_csv,'rb') as redirect_csv: reader = csv.reader(redirect_csv) next(reader,None) for row in reader: seed = row[0].strip() redirect = row[1].strip() redirect_dict[seed] = redirect get_redirect_metadata(redirect_dict,collection_id,redirect_dir) main()

[ "djpillen@umich.edu" ]

djpillen@umich.edu

310c8ae150190d6740b6121ace9773d0a661e430

54f352a242a8ad6ff5516703e91da61e08d9a9e6

/Source Codes/CodeJamData/11/32/13.py

c3ba2816bd0c1116751668d1ffb42f0e53b1d0e5

[]

no_license

Kawser-nerd/CLCDSA

5cbd8a4c3f65173e4e8e0d7ed845574c4770c3eb

aee32551795763b54acb26856ab239370cac4e75

refs/heads/master

2022-02-09T11:08:56.588303

2022-01-26T18:53:40

211,783,197

23

9

null

UTF-8

Python

false

2,460

py

filename = "B-large.in" outputname = filename + "out.txt" inFile = open(filename, 'r') outFile = open(outputname, 'w') numCases = int(inFile.readline()) def getTime(fullGapList, ttb, numStations): currTime = 0 counter = 0 while currTime < ttb and counter < len(fullGapList): currTime += fullGapList[counter]*2 counter += 1 if counter == len(fullGapList): return sum(fullGapList)*2 newGapList = fullGapList[counter:] if currTime != ttb: newGapList += [(currTime - ttb)/2] newGapList.sort() newGapList.reverse() stations = newGapList[0:numStations] return sum(fullGapList)*2 - sum(stations) for i in range(numCases): print i nextLine = inFile.readline().split() numStations = int(nextLine[0]) timeToBuild = int(nextLine[1]) numStars = int(nextLine[2]) numGaps = int(nextLine[3]) gapList = [] for j in range(numGaps): gapList += [int(nextLine[4+j])] fullGapList = [] while len(fullGapList) < numStars: fullGapList += gapList fullGapList = fullGapList[0:numStars] answer = getTime(fullGapList, timeToBuild, numStations) outFile.write("Case #" + str(i+1) + ": " + str(answer) + "\n") inFile.close() outFile.close() def oneStation(fullGapList, pos, ttb): priorTime = sum(fullGapList[0:pos])*2 afterTime = sum(fullGapList[pos+1:])*2 if priorTime > ttb: return priorTime + fullGapList[pos] + afterTime elif priorTime + 2*fullGapList[pos] < ttb: return priorTime + 2*fullGapList[pos] + afterTime else: return priorTime + (ttb-priorTime)/2 + fullGapList[pos] + afterTime def twoStation(fullGapList, pos1, pos2, ttb): priorTime = sum(fullGapList[0:pos1])*2 if priorTime > ttb: afterBoost = priorTime + fullGapList[pos1] elif priorTime + 2*fullGapList[pos1] < ttb: afterBoost = priorTime + 2*fullGapList[pos1] else: afterBoost = priorTime + (ttb-priorTime)/2 + fullGapList[pos1] priorTime = afterBoost + sum(fullGapList[pos1+1:pos2])*2 if priorTime > ttb: afterBoost = priorTime + fullGapList[pos2] elif priorTime + 2*fullGapList[pos2] < ttb: afterBoost = priorTime + 2*fullGapList[pos2] else: afterBoost = priorTime + (ttb-priorTime)/2 + fullGapList[pos2] return afterBoost + sum(fullGapList[pos2+1:])*2

[ "kwnafi@yahoo.com" ]

kwnafi@yahoo.com

d521724116b490a6181f5b3f286c4bc901268838

93ff3a214354128910c5c77824c64678d78e556d

/downloads/views.py

cd885baeb2cf1ca88ff849bf9cbe45dc2e079bad

[ "LicenseRef-scancode-public-domain", "MIT" ]

permissive

samoKrajci/roots

1fc2c7f205ba9dc0d9026026253c7349c3a551aa

9c6bf6ed30e8e6ff9099e9dca6d56a2df2ef10b0

refs/heads/master

2021-09-23T02:20:17.927687

2017-01-01T19:05:22

2017-01-01T19:05:38

null

0

null

UTF-8

Python

false

1,090

py

from sendfile import sendfile from django.conf import settings from django.core.exceptions import PermissionDenied from django.contrib.auth.decorators import login_required @login_required def download_protected_file(request, model_class, path_prefix, path): """ This view allows download of the file at the specified path, if the user is allowed to. This is checked by calling the model's can_access_files method. """ # filepath is the absolute path, mediapath is relative to media folder filepath = settings.SENDFILE_ROOT + path_prefix + path filepath_mediapath = path_prefix + path if request.user.is_authenticated(): # Superusers can access all files if request.user.is_superuser: return sendfile(request, filepath) else: # We need to check can_access_files on particular instance obj = model_class.get_by_filepath(filepath_mediapath) if obj is not None and obj.can_access_files(request.user): return sendfile(request, filepath) raise PermissionDenied

[ "tomasbabej@gmail.com" ]

tomasbabej@gmail.com

2578e88ce408cf417424eda2136335cf2eb1c5d0

a851830dbfd27d850e887d1cbc56c906512585d2

/AS0/ps0-4-code.py

7c37625f2438b193a9384e90e5fc0fc757b603e6

[]

no_license

AlexisDrch/Computer-Vision

d6861f1e11401b6c0b131026bc22a76433b74025

dc2687d53af73dd4e973bf969c48ae9f343bd49d

refs/heads/master

2021-01-25T11:55:47.316194

2018-04-06T06:15:49

123,440,935

8

1

null

UTF-8

Python

false

2,549

py

# ### 4. Arithmetic and Geometric operations from scipy import misc from scipy import ndimage import numpy as np import matplotlib.pyplot as plt import matplotlib.image as mpimg # ### a. # input 2 pictures as numpy ndarray picture_1 = misc.imread('./pictures/ps0-1-a-1.jpg') picture_2 = misc.imread('./pictures/ps0-1-a-2.jpg') # set red and blue channel to value 0 mono_g_picture = picture_1.copy() mono_g_picture[:,:,0] = mono_g_picture[:,:,2] = 0 # In[40]: green_mg1_values = mono_g_picture[:,:,1].copy() min_g1_value = np.min(green_mg1_values) max_g1_value = np.max(green_mg1_values) mean_g1_value = np.mean(green_mg1_values) std_g1_value = np.std(green_mg1_values) print('From the MG1 pixel values : min = {} | max = {} | mean = {} | stand dev = {} ' .format(min_g1_value, max_g1_value, mean_g1_value, std_g1_value)) print('\n') print('To compute these values, it is necessary to consider the pixel values as a unique array,' + 'here : the green pixel value of all the instances in the picture (green channel). ' + 'Then, basic mathematic ops can be applied.') # #### b. Operations on mg1 # In[41]: # substracting the mean green_mg1_values = green_mg1_values - mean_g1_value # diving by the std green_mg1_values = green_mg1_values / std_g1_value # multiply by 10 green_mg1_values = green_mg1_values * 10 # add mean green_mg1_values = green_mg1_values + mean_g1_value # plot (for notebook) and output the resulting picture mono_g_picture_flat = mono_g_picture.copy() mono_g_picture_flat[:,:,1] = green_mg1_values #plt.imshow(mono_g_picture_flat) #plt.title('Flat M1g') #plt.show() mpimg.imsave('./output/ps0-4-b-1.jpg', mono_g_picture_flat) # #### c. Shift M1g # In[42]: shifted_mg1 = mono_g_picture.copy() #shift two pixels to the left, except two last columns for i in range(512): for j in range(510): shifted_mg1[i,j] = shifted_mg1[i, j+2] # plot (for notebook) and output resulting picture #plt.imshow(shifted_mg1) #plt.show() mpimg.imsave('./output/ps0-4-c-1.jpg', shifted_mg1) # #### d. M1g - shiftedM1g # In[47]: sub_m1g = mono_g_picture - shifted_mg1 # verif that green chanel has valid values (not < 0) verif_array = np.where(sub_m1g < 0) print(verif_array) # plot (for notebook) and output resulting picture #plt.imshow(sub_m1g) #plt.show() mpimg.imsave('./output/ps0-4-d-1.jpg', sub_m1g) # The value of a pixel represent its light intensity. Since negative light intensity doesn't exist, negative value for a pixel is a bug, and does not represent a physical quantity. exit()

[ "aleksi.durocher@wanadoo.fr" ]

aleksi.durocher@wanadoo.fr

3bb95ced81396f906f7822e77e1d040cd8901b31

d33b2ce08591d23b06ab466f5dd6e302e3d4af2f

/fgcz_biobeamer.py.bak

36ca192e64d75ab8a4deb5d3140b2ca66875ef94

[]

no_license

Python3pkg/BioBeamer

8b5fceb94664dbe7ce15603276f9628bbe6d25ca

61dc1299fb47ece91ff9a7d333149cb2bfd500f3

refs/heads/master

2021-01-21T09:28:49.967511

2017-05-18T06:10:05

91,655,529

0

null

2017-05-18T06:10:03

null

UTF-8

Python

false

1,595

bak

#!/usr/bin/python # -*- coding: latin1 -*- """ Copyright 2006-2015 Functional Genomics Center Zurich This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program 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 General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. Author / Maintainer: Christian Panse <cp@fgcz.ethz.ch>, Witold E. Wolski <wew@fgcz.ethz.ch> """ # pip install PyFGCZ import biobeamer import sys import socket import time configuration_url = "http://fgcz-s-021.uzh.ch/config/" if __name__ == "__main__": print( "hostname is {0}.".format(socket.gethostname())) bio_beamer = biobeamer.Robocopy() biobeamer_xsd = "{0}/BioBeamer.xsd".format(configuration_url) biobeamer_xml = "{0}/BioBeamer.xml".format(configuration_url) bio_beamer.para_from_url(xsd=biobeamer_xsd, xml=biobeamer_xml) bio_beamer.run() time.sleep(5) BBChecker = biobeamer.Checker() BBChecker.para_from_url(xsd=biobeamer_xsd, xml=biobeamer_xml) BBChecker.run() sys.stdout.write("done. exit 0\n") time.sleep(5) sys.exit(0)

[ "raliclo@gmail.com" ]

raliclo@gmail.com

7a024d0157cfc178d4f1771c56c94ee8a96ad515

fd41984178ffba0846fa7ab1f67c1a0843a5e3ff

/自动化办公与鼠标键盘模拟/2.读取PDF文件/读取PDF文件.py

f2f9dc6056b35277a8a88b16d765a546092ed2d4

[]

no_license

LasterSmithKim/Python-Base

23f17472ee80f7224e96a4185775c9cd05ac7a98

27756126d999ddabf53b6bdc7114903a297464a0

refs/heads/master

2020-03-28T08:00:11.156911

2018-11-28T09:54:51

147,939,778

0

null

UTF-8

Python

false

2,066

py

import sys import importlib importlib.reload(sys) from pdfminer.pdfparser import PDFParser,PDFDocument from pdfminer.pdfinterp import PDFResourceManager,PDFPageInterpreter from pdfminer.converter import PDFPageAggregator from pdfminer.layout import LTTextBoxHorizontal,LAParams from pdfminer.pdfinterp import PDFTextExtractionNotAllowed def readPDF(path,toPath): #以二进制形式打开PDF文件 f = open(path,"rb") #创建管理器-pdf文档分析器 parser = PDFParser(f) #创建一个pdf文档 pdfFile = PDFDocument() #链接分析器与文档对象(分析器和文件双向链接） parser.set_document(pdfFile) pdfFile.set_parser(parser) #提供初始化密码 pdfFile.initialize() #检测文档是否提供txt转换 if not pdfFile.is_extractable: raise PDFTextExtractionNotAllowed else: #解析数据 #数据管理器 manager = PDFResourceManager() #创建一个PDF设备的对象 laparams = LAParams() device = PDFPageAggregator(manager,laparams=laparams) #创建解释器对象 interpreter = PDFPageInterpreter(manager,device) #开始循环处理，每次处理一页 for page in pdfFile.get_pages(): interpreter.process_page(page) #创建涂层，循环处理涂层 layout = device.get_result() for x in layout: #判断 x 是否是 LTTextBoxHorizontal类型的数据 if(isinstance(x,LTTextBoxHorizontal)): with open(toPath,"a") as f: str = x.get_text() #print(str) f.write(str+"\n") path = r"/Users/jinpeihua/PycharmProjects/Python语言基础视频课程/入门教程一/自动化办公与鼠标键盘模拟/2.读取PDF文件/LegalNotices.pdf" toPath = r"/Users/jinpeihua/PycharmProjects/Python语言基础视频课程/入门教程一/自动化办公与鼠标键盘模拟/2.读取PDF文件/a.txt" readPDF(path,toPath)

[ "kingone@yeah.net" ]

kingone@yeah.net

7b684337197c473ca2fbb5bd628978519553e9fb

2f07911e75ded21b80cae89ded82ce38f03a7931

/example.py

95c0f6863c126d023a70847fc9d9b552a45d593c

[]

no_license

benmaier/radial-distance-layout

2b1571c34dd167301bfb8ea9750a177ac420cda9

9be12e2906138e239e72eeb6082ebcd3d569b3dc

refs/heads/master

2022-02-23T08:09:58.174365

2022-02-12T21:44:41

50,359,905

3

2

null

UTF-8

Python

false

806

py

from radial_distance_layout import radial_distance_layout import matplotlib.pyplot as pl import networkx as nx paths = [ [ 'a','b','c'] ] paths += [ [ 'a','b','d'] ] paths += [ [ 'a','e','f','g'] ] paths += [ [ 'a','e','f','h'] ] paths += [ [ 'a','e','i'] ] paths += [ [ 'a','j','k'] ] paths += [ [ 'a','j','l'] ] dists = {'a': 0, 'b':1.1, 'e': 1.2, 'j': 1.4, 'c':2.1, 'd': 2.2, 'f': 2.1, 'i': 2.34, 'k':3.8, 'l':2.5, 'g': 3.9, 'h': 3.8} T = nx.DiGraph() for p in paths: T.add_path(p) keystr = 'dist' nx.set_node_attributes(T,keystr,dists) fig,ax = pl.subplots(1,2,figsize=(15,8)) pos = radial_distance_layout(T,keystr,mode='soph') nx.draw_networkx(T,pos,ax=ax[0]) pos = radial_distance_layout(T,keystr,mode='normal') nx.draw_networkx(T,pos,ax=ax[1]) pl.show()

[ "benjaminfrankmaier@gmail.com" ]

benjaminfrankmaier@gmail.com

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/nexus_auth/models/ping.py

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hreeder/nexus-auth

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refs/heads/master

2021-01-10T10:08:37.190558

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from nexus_auth import db from nexus_auth.models.groups import Group TYPE_SERVER = 0 TYPE_GROUP = 1 class PingServer(db.Model): id = db.Column(db.Integer, primary_key=True) servers = db.Column(db.Text) display_name = db.Column(db.String(64)) class PingTarget(db.Model): id = db.Column(db.Integer, primary_key=True) parent_group_id = db.Column(db.Integer, db.ForeignKey('group.id')) type = db.Column(db.SmallInteger) target = db.Column(db.Integer) def get_target_representation(self): if self.type == TYPE_SERVER: server = PingServer.query.filter_by(id=self.target).first() return "Server: " + server.display_name elif self.type == TYPE_GROUP: group = Group.query.filter_by(id=self.target).first() return "Group: " + group.name def get_target_name(self): if self.type == TYPE_SERVER: server = PingServer.query.filter_by(id=self.target).first() return server.display_name elif self.type == TYPE_GROUP: group = Group.query.filter_by(id=self.target).first() return group.name def get_group(self): return Group.query.filter_by(id=self.parent_group_id).first()

[ "harry@harryreeder.co.uk" ]

harry@harryreeder.co.uk

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/hr_payroll_account/models/hr_payroll_account.py

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[]

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tamam001/ALWAFI_P1

a3a9268081b9befc668a5f51c29ce5119434cc21

402ea8687c607fbcb5ba762c2020ebc4ee98e705

refs/heads/master

2020-05-18T08:16:50.583264

2019-04-30T14:43:46

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#-*- coding:utf-8 -*- # Part of ALWAFI. See LICENSE file for full copyright and licensing details. from odoo import api, fields, models, _ from odoo.exceptions import UserError from odoo.tools import float_compare, float_is_zero class HrPayslipLine(models.Model): _inherit = 'hr.payslip.line' def _get_partner_id(self, credit_account): """ Get partner_id of slip line to use in account_move_line """ # use partner of salary rule or fallback on employee's address register_partner_id = self.salary_rule_id.register_id.partner_id partner_id = register_partner_id.id or self.slip_id.employee_id.address_home_id.id if credit_account: if register_partner_id or self.salary_rule_id.account_credit.internal_type in ('receivable', 'payable'): return partner_id else: if register_partner_id or self.salary_rule_id.account_debit.internal_type in ('receivable', 'payable'): return partner_id return False class HrPayslip(models.Model): _inherit = 'hr.payslip' date = fields.Date('Date Account', states={'draft': [('readonly', False)]}, readonly=True, help="Keep empty to use the period of the validation(Payslip) date.") journal_id = fields.Many2one('account.journal', 'Salary Journal', readonly=True, required=True, states={'draft': [('readonly', False)]}, default=lambda self: self.env['account.journal'].search([('type', '=', 'general')], limit=1)) move_id = fields.Many2one('account.move', 'Accounting Entry', readonly=True, copy=False) @api.model def create(self, vals): if 'journal_id' in self.env.context: vals['journal_id'] = self.env.context.get('journal_id') return super(HrPayslip, self).create(vals) @api.onchange('contract_id') def onchange_contract(self): super(HrPayslip, self).onchange_contract() self.journal_id = self.contract_id.journal_id.id or (not self.contract_id and self.default_get(['journal_id'])['journal_id']) @api.multi def action_payslip_cancel(self): moves = self.mapped('move_id') moves.filtered(lambda x: x.state == 'posted').button_cancel() moves.unlink() return super(HrPayslip, self).action_payslip_cancel() @api.multi def action_payslip_done(self): res = super(HrPayslip, self).action_payslip_done() for slip in self: line_ids = [] debit_sum = 0.0 credit_sum = 0.0 date = slip.date or slip.date_to currency = slip.company_id.currency_id name = _('Payslip of %s') % (slip.employee_id.name) move_dict = { 'narration': name, 'ref': slip.number, 'journal_id': slip.journal_id.id, 'date': date, } for line in slip.details_by_salary_rule_category: amount = currency.round(slip.credit_note and -line.total or line.total) if currency.is_zero(amount): continue debit_account_id = line.salary_rule_id.account_debit.id credit_account_id = line.salary_rule_id.account_credit.id if debit_account_id: debit_line = (0, 0, { 'name': line.name, 'partner_id': line._get_partner_id(credit_account=False), 'account_id': debit_account_id, 'journal_id': slip.journal_id.id, 'date': date, 'debit': amount > 0.0 and amount or 0.0, 'credit': amount < 0.0 and -amount or 0.0, 'analytic_account_id': line.salary_rule_id.analytic_account_id.id, 'tax_line_id': line.salary_rule_id.account_tax_id.id, }) line_ids.append(debit_line) debit_sum += debit_line[2]['debit'] - debit_line[2]['credit'] if credit_account_id: credit_line = (0, 0, { 'name': line.name, 'partner_id': line._get_partner_id(credit_account=True), 'account_id': credit_account_id, 'journal_id': slip.journal_id.id, 'date': date, 'debit': amount < 0.0 and -amount or 0.0, 'credit': amount > 0.0 and amount or 0.0, 'analytic_account_id': line.salary_rule_id.analytic_account_id.id, 'tax_line_id': line.salary_rule_id.account_tax_id.id, }) line_ids.append(credit_line) credit_sum += credit_line[2]['credit'] - credit_line[2]['debit'] if currency.compare_amounts(credit_sum, debit_sum) == -1: acc_id = slip.journal_id.default_credit_account_id.id if not acc_id: raise UserError(_('The Expense Journal "%s" has not properly configured the Credit Account!') % (slip.journal_id.name)) adjust_credit = (0, 0, { 'name': _('Adjustment Entry'), 'partner_id': False, 'account_id': acc_id, 'journal_id': slip.journal_id.id, 'date': date, 'debit': 0.0, 'credit': currency.round(debit_sum - credit_sum), }) line_ids.append(adjust_credit) elif currency.compare_amounts(debit_sum, credit_sum) == -1: acc_id = slip.journal_id.default_debit_account_id.id if not acc_id: raise UserError(_('The Expense Journal "%s" has not properly configured the Debit Account!') % (slip.journal_id.name)) adjust_debit = (0, 0, { 'name': _('Adjustment Entry'), 'partner_id': False, 'account_id': acc_id, 'journal_id': slip.journal_id.id, 'date': date, 'debit': currency.round(credit_sum - debit_sum), 'credit': 0.0, }) line_ids.append(adjust_debit) move_dict['line_ids'] = line_ids move = self.env['account.move'].create(move_dict) slip.write({'move_id': move.id, 'date': date}) move.post() return res class HrSalaryRule(models.Model): _inherit = 'hr.salary.rule' analytic_account_id = fields.Many2one('account.analytic.account', 'Analytic Account') account_tax_id = fields.Many2one('account.tax', 'Tax') account_debit = fields.Many2one('account.account', 'Debit Account', domain=[('deprecated', '=', False)]) account_credit = fields.Many2one('account.account', 'Credit Account', domain=[('deprecated', '=', False)]) class HrContract(models.Model): _inherit = 'hr.contract' _description = 'Employee Contract' analytic_account_id = fields.Many2one('account.analytic.account', 'Analytic Account') journal_id = fields.Many2one('account.journal', 'Salary Journal') class HrPayslipRun(models.Model): _inherit = 'hr.payslip.run' journal_id = fields.Many2one('account.journal', 'Salary Journal', states={'draft': [('readonly', False)]}, readonly=True, required=True, default=lambda self: self.env['account.journal'].search([('type', '=', 'general')], limit=1))

[ "50145400+gilbertp7@users.noreply.github.com" ]

50145400+gilbertp7@users.noreply.github.com

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/examples/Redfish/ex09_find_ilo_mac_address.py

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[ "Apache-2.0" ]

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injan0913/python-ilorest-library

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refs/heads/master

2020-12-24T22:20:13.135325

2016-06-23T18:26:33

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# Copyright 2016 Hewlett Packard Enterprise Development 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 sys from redfishobject import RedfishObject from ilorest.rest.v1_helper import ServerDownOrUnreachableError def ex9_find_ilo_mac_address(redfishobj): sys.stdout.write("\nEXAMPLE 9: Find iLO's MAC Addresses\n") instances = redfishobj.search_for_type("Manager.") for instance in instances: tmp = redfishobj.redfish_get(instance["@odata.id"]) response = redfishobj.redfish_get(tmp.dict["EthernetInterfaces"]\ ["@odata.id"]) for entry in response.dict["Members"]: ethernet = redfishobj.redfish_get(entry["@odata.id"]) if "MACAddress" not in ethernet.dict: sys.stderr.write("\tNIC resource does not contain " \ "'MACAddress' property\n") else: sys.stdout.write("\t" + ethernet.dict["Name"] + " = " + \ ethernet.dict["MACAddress"] + "\t(" + \ ethernet.dict["Status"]["State"] + ")\n") if __name__ == "__main__": # When running on the server locally use the following commented values # iLO_host = "blobstore://." # iLO_account = "None" # iLO_password = "None" # When running remotely connect using the iLO address, iLO account name, # and password to send https requests iLO_host = "https://10.0.0.100" iLO_account = "admin" iLO_password = "password" # Create a REDFISH object try: REDFISH_OBJ = RedfishObject(iLO_host, iLO_account, iLO_password) except ServerDownOrUnreachableError, excp: sys.stderr.write("ERROR: server not reachable or doesn't support " \ "RedFish.\n") sys.exit() except Exception, excp: raise excp ex9_find_ilo_mac_address(REDFISH_OBJ)

[ "jackgarcia77@gmail.com" ]

jackgarcia77@gmail.com

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/activity/migrations/0009_auto_20190305_1508.py

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[]

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qoutland/docent

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2022-12-15T00:13:24.940849

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# Generated by Django 2.1.3 on 2019-03-05 23:08 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('activity', '0008_auto_20190305_1507'), ] operations = [ migrations.AlterField( model_name='activity', name='pic_url', field=models.URLField(blank=True), ), ]

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=

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/planemo-de/xenv/lib/python3.7/site-packages/galaxy/__init__.py

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[]

no_license

Slugger70/galaxy-metabolomics

e1ef083316394ace66c1f69c313db0a0fc8c3dec

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refs/heads/master

2020-09-19T21:51:16.177730

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2019-11-26T23:45:53

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# -*- coding: utf-8 -*- __version__ = '19.5.2' PROJECT_NAME = "galaxy-lib" PROJECT_OWNER = PROJECT_USERAME = "galaxyproject" PROJECT_URL = "https://github.com/galaxyproject/galaxy-lib" PROJECT_AUTHOR = 'Galaxy Project and Community' PROJECT_EMAIL = 'jmchilton@gmail.com' RAW_CONTENT_URL = "https://raw.github.com/%s/%s/master/" % ( PROJECT_USERAME, PROJECT_NAME )

[ "ma.bioinformatics@gmail.com" ]

ma.bioinformatics@gmail.com

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/dask/dataframe/shuffle.py

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JDWarner/dask

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2021-01-18T21:02:18.344193

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from itertools import count from collections import Iterator from math import ceil from toolz import merge, accumulate, merge_sorted import toolz from operator import getitem, setitem import pandas as pd import numpy as np from .. import threaded from ..optimize import cull from .core import DataFrame, Series, get, _Frame, tokens from ..compatibility import unicode from ..utils import ignoring from .utils import (strip_categories, unique, shard_df_on_index, _categorize, get_categories) def set_index(df, index, npartitions=None, compute=True, **kwargs): """ Set DataFrame index to new column Sorts index and realigns Dataframe to new sorted order. This shuffles and repartitions your data. """ npartitions = npartitions or df.npartitions if not isinstance(index, Series): index2 = df[index] else: index2 = index divisions = (index2 .quantiles(np.linspace(0, 100, npartitions+1)) .compute()).tolist() return df.set_partition(index, divisions, compute=compute, **kwargs) def new_categories(categories, index): """ Flop around index for '.index' """ if index in categories: categories = categories.copy() categories['.index'] = categories.pop(index) return categories def set_partition(df, index, divisions, compute=False, **kwargs): """ Group DataFrame by index Sets a new index and partitions data along that index according to divisions. Divisions are often found by computing approximate quantiles. The function ``set_index`` will do both of these steps. Parameters ---------- df: DataFrame/Series Data that we want to re-partition index: string or Series Column to become the new index divisions: list Values to form new divisions between partitions See Also -------- set_index shuffle partd """ if isinstance(index, _Frame): assert df.divisions == index.divisions import partd p = ('zpartd' + next(tokens),) # Get Categories token = next(tokens) catname = 'set-partition--get-categories-old' + token catname_new = 'set-partition--get-categories-new' + token dsk1 = {catname: (get_categories, df._keys()[0]), p: (partd.PandasBlocks, (partd.Buffer, (partd.Dict,), (partd.File,))), catname_new: (new_categories, catname, index.name if isinstance(index, Series) else index)} # Partition data on disk name = 'set-partition--partition' + next(tokens) if isinstance(index, _Frame): dsk2 = dict(((name, i), (_set_partition, part, ind, divisions, p)) for i, (part, ind) in enumerate(zip(df._keys(), index._keys()))) else: dsk2 = dict(((name, i), (_set_partition, part, index, divisions, p)) for i, part in enumerate(df._keys())) # Barrier barrier_token = 'barrier' + next(tokens) dsk3 = {barrier_token: (barrier, list(dsk2))} if compute: dsk = merge(df.dask, dsk1, dsk2, dsk3) if isinstance(index, _Frame): dsk.update(index.dask) p, barrier_token = get(dsk, [p, barrier_token], **kwargs) # Collect groups name = 'set-partition--collect' + next(tokens) dsk4 = dict(((name, i), (_categorize, catname_new, (_set_collect, i, p, barrier_token))) for i in range(len(divisions) - 1)) dsk = merge(df.dask, dsk1, dsk2, dsk3, dsk4) if isinstance(index, _Frame): dsk.update(index.dask) if compute: dsk = cull(dsk, list(dsk4.keys())) return DataFrame(dsk, name, df.columns, divisions) def barrier(args): list(args) return 0 def _set_partition(df, index, divisions, p): """ Shard partition and dump into partd """ df = df.set_index(index) df = strip_categories(df) divisions = list(divisions) shards = shard_df_on_index(df, divisions[1:-1]) p.append(dict(enumerate(shards))) def _set_collect(group, p, barrier_token): """ Get new partition dataframe from partd """ try: return p.get(group) except ValueError: return pd.DataFrame() def shuffle(df, index, npartitions=None): """ Group DataFrame by index Hash grouping of elements. After this operation all elements that have the same index will be in the same partition. Note that this requires full dataset read, serialization and shuffle. This is expensive. If possible you should avoid shuffles. This does not preserve a meaningful index/partitioning scheme. See Also -------- set_index set_partition partd """ if isinstance(index, _Frame): assert df.divisions == index.divisions if npartitions is None: npartitions = df.npartitions import partd p = ('zpartd' + next(tokens),) dsk1 = {p: (partd.PandasBlocks, (partd.Buffer, (partd.Dict,), (partd.File,)))} # Partition data on disk name = 'shuffle-partition' + next(tokens) if isinstance(index, _Frame): dsk2 = dict(((name, i), (partition, part, ind, npartitions, p)) for i, (part, ind) in enumerate(zip(df._keys(), index._keys()))) else: dsk2 = dict(((name, i), (partition, part, index, npartitions, p)) for i, part in enumerate(df._keys())) # Barrier barrier_token = 'barrier' + next(tokens) dsk3 = {barrier_token: (barrier, list(dsk2))} # Collect groups name = 'shuffle-collect' + next(tokens) dsk4 = dict(((name, i), (collect, i, p, barrier_token)) for i in range(npartitions)) divisions = [None] * (npartitions + 1) dsk = merge(df.dask, dsk1, dsk2, dsk3, dsk4) if isinstance(index, _Frame): dsk.update(index.dask) return DataFrame(dsk, name, df.columns, divisions) def partition(df, index, npartitions, p): """ Partition a dataframe along a grouper, store partitions to partd """ rng = pd.Series(np.arange(len(df))) if isinstance(index, Iterator): index = list(index) if not isinstance(index, (pd.Index, pd.core.generic.NDFrame)): index = df[index] if isinstance(index, pd.Index): groups = rng.groupby([abs(hash(x)) % npartitions for x in index]) if isinstance(index, pd.Series): groups = rng.groupby(index.map(lambda x: abs(hash(x)) % npartitions).values) elif isinstance(index, pd.DataFrame): groups = rng.groupby(index.apply( lambda row: abs(hash(tuple(row))) % npartitions, axis=1).values) d = dict((i, df.iloc[groups.groups[i]]) for i in range(npartitions) if i in groups.groups) p.append(d) def collect(group, p, barrier_token): """ Collect partitions from partd, yield dataframes """ return p.get(group)

[ "mrocklin@gmail.com" ]

mrocklin@gmail.com

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lovesh/abhiabhi-web-scrapper

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import downloader import dom import urllib2 import re import time import math import pymongo from collections import defaultdict import datetime siteurl='http://www.infibeam.com' category_browser='http://www.infibeam.com/Books/BrowseCategories.action' subcategory_browser='http://www.infibeam.com/Books/BrowseCategories.action' books=[] book_urls=defaultdict(list) logfile=open('infibeam_books_log.txt','w') dl=downloader.Downloader() dl.addHeaders({'Origin':siteurl,'Referer':siteurl}) shipping_pattern = re.compile('in (\d+) business days', re.I) def getCategoryUrls(): category_page=dom.DOM(url=category_browser) category_path='//div[@id="allcategories"]//h3/a' category_urls=dict((link[0],'http://www.infibeam.com'+link[1]) for link in category_page.getLinksWithXpath(category_path)) return category_urls def getSubCategoryUrls(): category_page=dom.DOM(url=subcategory_browser) subcategory_path='//div[@id="allcategories"]//ul/li/a' subcategory_urls=set('http://www.infibeam.com'+link[1] for link in category_page.getLinksWithXpath(subcategory_path)) return subcategory_urls def getBookUrlsFromPage(html): book_url_path='//ul[@class="search_result"]//span[@class="title"]/h2/a' page_dom=dom.DOM(string=html) links=set(l[1] for l in page_dom.getLinksWithXpath(book_url_path)) return links def getBookUrlsOfCategory(cat,category_url): page=urllib2.urlopen(category_url) html=page.read() page.close() page=dom.DOM(string=html) urls=getBookUrlsFromPage(html) #get book urls from first page count_path='//div[@id="search_result"]/div/b[2]' count=int(page.getNodesWithXpath(count_path)[0].text.replace(',','')) print count if count>20: num_pages=int(math.ceil(count/20.0)) page_urls=set(category_url+'/search?page='+str(page) for page in xrange(2,num_pages)) print page_urls dl.putUrls(page_urls) result=dl.download() for r in result: status=result[r][0] html=result[r][1] if status > 199 and status < 400: urls.update(getBookUrlsFromPage(html)) url_dict={} for url in urls: url_dict[url]=cat return url_dict def getAllBookUrls(): global book_urls category_urls=getCategoryUrls() start=time.time() for cat in category_urls: print('Getting book urls of category %s\n\n'%cat) urls=getBookUrlsOfCategory(cat,category_urls[cat]) print('Witring book urls of category %s\n\n'%cat) logfile.write('Witring book urls of category %s\n\n'%cat) for url in urls: logfile.write(url+'\n') book_urls[url].append(urls[url]) logfile.write('\n\n\n\n') finish=time.time() print "All book urls(%s) fetched in %s\n\n",(len(book_urls),str(finish-start)) logfile.write("All book urls fetched in %s\n\n"%str(finish-start)) logfile.flush() return book_urls def parseBookPage(url=None,string=None): book={} print url if url: try: doc=dom.DOM(url=url) except urllib2.HTTPError: return False else: doc=dom.DOM(string=string) addBox=doc.getNodesWithXpath('//input[@class="buyimg "]') if url: book['url']=url if addBox: #availability check book['availability']=1 # availability 1 signals "in stock" m = shipping_pattern.search(doc.html) if m: book['shipping']=(int(m.group(1)), ) else: book['availability']=0 price_path = '//span[@class="infiPrice amount price"]' price = doc.getNodesWithXpath(price_path) if len(price) > 0: book['price']=int(price[0].text.replace(',', '')) img_path="//img[@id='imgMain']" book['img_url']=doc.getImgUrlWithXpath(img_path) tbody_path='//div[@id="ib_products"]/table/tbody' if len(doc.getNodesWithXpath(tbody_path)) == 0: tbody_path='//div[@id="ib_products"]/table' if len(doc.getNodesWithXpath(tbody_path)) == 0: tbody_path='//table[@style="color:#333; font:verdana,Arial,sans-serif;"]' data=doc.parseTBody(tbody_path) if data: if 'author' in data: data['author']=data['author'].split(',') if 'publish date' in data: m=re.search('(\d+)-(\d+)-(\d+)',data['publish date']) if m: data['pubdate']=datetime.date(int(m.group(1)),int(m.group(2)),int(m.group(3))) book.update(data) book['scraped_datetime']=datetime.datetime.now() book['last_modified_datetime']=datetime.datetime.now() book['site']='infibeam' product_history={} if 'price' in book: product_history['price']=book['price'] if 'shipping' in book: product_history['shipping']=book['shipping'] product_history['availability']=book['availability'] product_history['datetime']=book['last_modified_datetime'] book['product_history']=[product_history,] return book def go(): global books urls=getAllBookUrls() dl.putUrls(urls,10) start=time start=time.time() result=dl.download() finish=time.time() logfile.write("All books(%s) downloaded in %s"%(len(books),str(finish-start))) start=time.time() for r in result: status=result[r][0] html=result[r][1] if status > 199 and status < 400: book=parseBookPage(string=html) book['url']=r if r.find('/Books/') == -1: book['type']='ebook' else: book['type']='book' books.append(book) finish=time.time() logfile.write("All books parsed in %s"%str(finish-start)) return books def prepareXMLFeed(): books=go() root=dom.XMLNode('books') start=time.time() for book in books: child=root.createChildNode('book') child.createChildNodes(book) f=open('infibeam_books.xml','w') f.write(root.nodeToString()) f.close() finish=time.time() logfile.write("XML file created in %s"%str(finish-start))

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#!/Users/ashutoshjha/Desktop/flask_blog/venv/bin/python3 # -*- coding: utf-8 -*- import re import sys from isort.main import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

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def tidy(n): a = list(str(n)) if len(a)>=2: for i in range(len(a)-1): if a[i]>a[i+1]: a[i] = str(int(a[i])-1) for j in range(i+1, len(a)): a[j] = '9' a = ''.join(a) out = int(a) return out def check_tidy(n): a = tidy(n) b = list(str(a)) b.sort() b = ''.join(b) b = int(b) if a == b: return a else: return check_tidy(a) in_f = open("i.in", 'r') ou_f = open("o.out", 'w') T = int(in_f.readline()) for i in range(T): s = in_f.readline().strip() k = int(s) out = check_tidy(k) j = "Case #" + str(i+1) +": " + str(out) + "\n" ou_f.write(j) in_f.close() ou_f.close()

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# Copyright (c) 2020-2021 Manfred Moitzi # License: MIT License from pathlib import Path import math import ezdxf from ezdxf import zoom from ezdxf.math import UCS DIR = Path("~/Desktop/Outbox").expanduser() p = [ (0, 0, 0), (1, 0, 0), (1, 1, 0), (0, 1, 0), (0, 0, 1), (1, 0, 1), (1, 1, 1), (0, 1, 1), ] doc = ezdxf.new() msp = doc.modelspace() block = doc.blocks.new("block_4m3") cube = block.add_mesh() with cube.edit_data() as mesh_data: mesh_data.add_face([p[0], p[1], p[2], p[3]]) mesh_data.add_face([p[4], p[5], p[6], p[7]]) mesh_data.add_face([p[0], p[1], p[5], p[4]]) mesh_data.add_face([p[1], p[2], p[6], p[5]]) mesh_data.add_face([p[3], p[2], p[6], p[7]]) mesh_data.add_face([p[0], p[3], p[7], p[4]]) mesh_data.optimize() # Place untransformed cube, don't use the rotation # attribute unless you really need it, just # transform the UCS. blockref = msp.add_blockref(name="block_4m3", insert=(0, 0, 0)) # First rotation about the local x-axis ucs = UCS().rotate_local_x(angle=math.radians(45)) # same as a rotation around the WCS x-axis: # ucs = UCS().rotate(axis=(1, 0, 0), angle=math.radians(45)) # Second rotation about the WCS z-axis ucs = ucs.rotate(axis=(0, 0, 1), angle=math.radians(45)) # Last step transform block reference from UCS to WCS blockref.transform(ucs.matrix) zoom.extents(msp) doc.saveas(DIR / "cube.dxf")

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me@mozman.at

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arr = input().split() new_arr = list(map(int, arr)) result = [] line = input() while line != "end": value = line.split() command = value[0] if command == "swap": index_1 = int(value[1]) index_2 = int(value[2]) new_arr[index_1], new_arr[index_2] = new_arr[index_2], new_arr[index_1] elif command == "multiply": index_1 = int(value[1]) index_2 = int(value[2]) multiplied = new_arr[index_1] * new_arr[index_2] new_arr[index_1] = multiplied elif command == "decrease": for val in new_arr: val -= 1 result.append(val) line = input() print(", ".join(list(map(str, result)))) # print(', '.join([str(x) for x in last]))

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fadiga/mstock

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refs/heads/master

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#!/usr/bin/env python # -*- coding: utf8 -*- # vim: ai ts=4 sts=4 et sw=4 nu # maintainer: Fad from __future__ import ( unicode_literals, absolute_import, division, print_function) from PyQt4.QtGui import QIcon from PyQt4.QtCore import Qt from Common.ui.common import FMainWindow, QToolBadgeButton from ui.menutoolbar import MenuToolBar from ui.menubar import MenuBar from Common.ui.statusbar import GStatusBar from ui.dashboard import DashbordViewWidget from configuration import Config class MainWindow(FMainWindow): def __init__(self): FMainWindow.__init__(self) self.setWindowIcon(QIcon.fromTheme( 'logo', QIcon(u"{}".format(Config.APP_LOGO)))) self.menubar = MenuBar(self) self.setMenuBar(self.menubar) self.toolbar = MenuToolBar(self) self.addToolBar(Qt.LeftToolBarArea, self.toolbar) self.statusbar = GStatusBar(self) self.setStatusBar(self.statusbar) self.page = DashbordViewWidget self.change_context(self.page) def page_width(self): return self.width() - 100 def add_badge(self, msg, count): b = QToolBadgeButton(self) b.setText(msg) b.setCounter(count) self.toolbar.addWidget(b) def exit(self): self.logout() self.close() def active_menu(self): self.menubar = MenuBar(self) self.setMenuBar(self.menubar)

[ "ibfadiga@gmail.com" ]

ibfadiga@gmail.com

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YuanGongND/Deep_Speech_Visualization

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# -*- coding: utf-8 -*- """ Created on Sat Aug 26 21:03:04 2017 Conduct erxperiment on IEMOCAP, three labels: 96001: emotion(0-4, 5 = other emotions) 96002: speaker(0-9) 96003: gender(male=0, female=1) @author: Kyle """ import os from sys import argv _, newFolderName, gpuI = argv os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = str(gpuI) import sys sys.path.append("../../model/") import soundNet import waveCNN sys.path.append("../") import expUtil import numpy as np from keras import backend as K import matplotlib.pyplot as plt import shutil #%% creat folder to save model, the code, and model configuration while os.path.isdir( newFolderName ): newFolderName = newFolderName + '_1' print( 'exist' ) os.mkdir( newFolderName ) shutil.copy( os.path.basename(__file__), newFolderName ) # copy this file to the new folder shutil.copy( '../../model/soundNet.py', newFolderName ) shutil.copy( '../../model/waveCNN.py', newFolderName ) shutil.copy( '../expUtil.py', newFolderName ) # put all configuratation here thisTask = 'gender' dataType = 'toyWaveform' # define the model model = soundNet.soundNet # define the model #model = waveCNN.waveCNN # according to the configuaration, change the coresponding setting #if thisTask == 'emotion': # trainNewFolderName = newFolderName # load data trainFeature, trainLabel, testFeature, testLabel = expUtil.loadData( testFolder = 4, testTask = thisTask, precision = 'original', sampleRate = 16000, dataType = dataType ) #%% grid search #batch_sizeList = [ 32, 24, 16 ] #learningRateList = [ 1e-3, 5e-4, 1e-4, 5e-5, 1e-5 ] #initList = [ 'RandomUniform', 'lecun_normal', 'lecun_uniform', 'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform' ] batch_sizeList = [ 32 ] learningRateList = [ 1e-4 ] initList = [ 'glorot_normal' ] for batch_size in batch_sizeList: resultList = [ ] for learningRate in learningRateList: for init in initList: tempFolderName = newFolderName + '/' + str( learningRate ) + '_' + str( batch_size ) + '_' + init os.mkdir( tempFolderName ) # train the model resultOnTrain, resultOnTest = expUtil.train( testFeature, testLabel, trainFeature, trainLabel, iteration_num = 100, \ lr_decay = 0.1, batch_size = batch_size, learningRate = learningRate, iterationNum = 100, \ modelT = model, newFolderName = tempFolderName, init = keras.initializers.Constant(value=0.01), saveSign = True, denseUnitNum = 64, \ dataType = dataType ) resultList.append( resultOnTest[ -1 ] ) np.savetxt( newFolderName + '\_' + str( batch_size ) +'_gridSearch.csv', resultList, delimiter = ',' ) resultList = np.array( resultList ) resultList.resize( [ len( learningRateList ), len( initList ) ] ) np.savetxt( newFolderName + '\_' + str( batch_size ) +'_gridSearch.csv', resultList, delimiter = ',' ) #%% start test testSamples = testFeature.shape[ 0 ] trainSamples = trainFeature.shape[ 0 ] log = 'testSample_num = ' + str( testSamples ) + '\n trainSample_num = ' + str( trainSamples ) with open( newFolderName + '/log.txt' , "w") as text_file: text_file.write( log )

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ygong1@nd.edu

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rafaelperazzo/programacao-web

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from __future__ import division #INICIE SEU CDIGO AQUI n=float(input('Digite n')) n1=int(n) n2=n-int print('%.2f'%n1) print('%.2f'%n2)

[ "rafael.mota@ufca.edu.br" ]

rafael.mota@ufca.edu.br

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2023-05-14T16:38:52.408066

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.contrib import admin # from .models import Invoice # class InvoiceAdmin(admin.ModelAdmin): # list_display = ('__unicode__', 'user', 'release_date', 'is_discharged', 'payment_status') # readonly_fields = ('release_date', ) # search_fields = ('release_date', 'payu_reference_code') # admin.site.register(Invoice, InvoiceAdmin)

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# Definition for singly-linked list. class ListNode: def __init__(self, val=0, next=None): self.val = val self.next = next class Solution: def oddEvenList(self, head: ListNode) -> ListNode: if not head or head.next == None: return head odd, even, second = head, head.next, head.next while odd and odd.next and even and even.next: odd.next = odd.next.next even.next = even.next.next odd = odd.next even = even.next odd.next = second return head node = ListNode(1, ListNode(2, ListNode(3, ListNode(4)))) Solution().oddEvenList(node)

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blossomyyh@163.com

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#!/usr/bin/env python3 """ Module to execute function """ def matrix_shape(matrix): """Function that calculates the shape of a matrix""" shape = [] shape.append(len(matrix)) while type(matrix[0]) == list: matrix = matrix[0] shape.append(len(matrix)) return shape

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def f1(*a): pass def f2(**a): pass def f3(a, *b): pass def f4(a, **b): pass ## arg with default after *args is valid python3, not python2 def f5(*a, b=1): pass def f6(*a, b=1, **c): pass def f7(x=1, *a, b=1, **c): pass def f8(#asd *a): pass

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import os from collections import OrderedDict import pandas as pd from engine.cons import * from engine.utils import get_calendar from feature.time import TimeRange from mongoapi.get_data import get_day_trade_data from redis_cache.rediscache import cache_it_pickle class pricing_data_loader: def __init__(self, load_path=PRICING_DATA_PATH): self.load_path = load_path def load_data(self, instruments, feature, start_time, end_time): pass # # @cache_it_pickle() # def load_single_data(self, instrument, start_time, end_time, feature='close'): # df = pd.read_csv(os.path.join(self.load_path, instrument + '.csv'))[['date', feature, 'rate']] # df = df.rename(columns={feature: PRICE}) # # df[PRICE]=df[PRICE]/df['rate'] # del df['rate'] # carlender = get_calendar() # # df = df.set_index('date') # df_full = df.reindex(carlender).fillna(method='ffill') # # pricing_data = df_full[(df_full.index >= start_time) & (df_full.index <= end_time)].to_dict()[PRICE] # df = df.reindex(df_full.index) # on_trading = (~df[(df.index >= start_time) & (df.index <= end_time)].isnull()).astype(int).to_dict()[PRICE] # return OrderedDict(pricing_data), OrderedDict(on_trading) @cache_it_pickle() def load_single_data(self, instrument, start_time, end_time, feature='close'): trade_calendar = get_calendar(start_time, end_time) data = get_day_trade_data([instrument], start_time, end_time, [feature], return_df=True)[['date',feature]].set_index('date') data=data.reindex(trade_calendar) pricing_data = data.fillna(method='ffill').to_dict()[feature] on_trading = (~data.isnull()).astype(int).to_dict()[feature] return OrderedDict(pricing_data), OrderedDict(on_trading)

[ "zhangzc@pku.edu.cn" ]

zhangzc@pku.edu.cn

7c38dda3f18562b3df7eecb78e86f2712b212369

b5d72e68c3976766a7adfd1fa33f778a5268c84a

/Regex/ex1.py

35628e29ded201a4fa05a049420dc39525ee29d4

[]

no_license

LizinczykKarolina/Python

4a2fb0e7fb130c86239b2666fb346bf35a8e655b

7f4a3a9cba15fd2b4c7a104667461b3c49f8b757

refs/heads/master

2021-06-18T21:43:52.983557

2017-06-17T21:24:01

null

0

null

UTF-8

Python

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328

py

#1. Write a Python program to check that a string contains only a certain set of characters (in this case a-z, A-Z and 0-9). import re email_address = 'wieczorek.karolina1@o2.pl' searchObj = re.search(r'[a-zA-Z0-9.]', email_address, re.M | re.I) if searchObj: print True else: print False "sxdupa1" -match '^sx|1$'

[ "wieczorek.karolina1@o2.pl" ]

wieczorek.karolina1@o2.pl

f3ae22f885b78d753d9dbc851fea38a065e80d88

9fc768c541145c1996f2bdb8a5d62d523f24215f

/code/HomeWork/ch5/H_5_4.py

a92df699ef2667ea9bcb8c973b7297b29db61309

[]

no_license

jumbokh/pyclass

3b624101a8e43361458130047b87865852f72734

bf2d5bcca4fff87cb695c8cec17fa2b1bbdf2ce5

refs/heads/master

2022-12-25T12:15:38.262468

2020-09-26T09:08:46

283,708,159

0

null

UTF-8

Python

false

722

py

# H_5_4.py 功能:輸入數字後判斷是否為11的倍數 num_even = 0 # 儲存偶數位數字暫存 num_odd = 0 # 儲存奇數位數字暫存 number = str(input('請輸入數字 : ')) l = len(number) # 判斷輸入數字之長度 x = int(number) # 轉換成數值型態 for n in range(l,0,-1): y = x//(10**(n-1)) # 計算奇偶位數字 x = x - (y*(10**(n-1))) if n%2 == 0: # 判斷若是偶數位數字則儲存在偶數位暫存，反之存奇數位暫存 num_even = num_even + y else: num_odd = num_odd + y # 判斷是否為11的倍數 if abs(num_even - num_odd) == 0 or (abs(num_even - num_odd))%11 == 0: print('此數為11的倍數') else: print('此數不是11的倍數')

[ "jumbokh@gmail.com" ]

jumbokh@gmail.com

6eeb30afedb9faf5956630200d67199cef30815d

2a4a17a67b9069c19396c0f8eabc8b7c4b6ff703

/BGP3D/Chapter11/WorldClass_00.py

2cd366287c64b1790280d87dd425c04951cc0271

[]

no_license

kaz101/panda-book

0fa273cc2df5849507ecc949b4dde626241ffa5e

859a759c769d9c2db0d11140b0d04506611c2b7b

refs/heads/master

2022-12-19T09:36:05.794731

2020-09-16T19:04:10

295,784,057

0

null

UTF-8

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2,569

py

''' World Class This class is the launching point for the game. This is the file that needs to run to start the game, and this class creates all the pieces of the game. ''' import direct.directbase.DirectStart from direct.filter.CommonFilters import CommonFilters from HUDClass_00 import HUD from RaceClass_00 import Race from InputManagerClass_00 import InputManager from MenuClass_00 import Menu class World: def __init__(self): base.disableMouse() # Turns off the default mouse-camera controls in Panda3D. base.setBackgroundColor(0, 0, 0) # Sets the background to black. self.inputManager = InputManager() # Creates an InputManager to handle all of the user input in the game. #taskMgr.doMethodLater(10, self.debugTask, "Debug Task") # Tells the debugTask to run once every ten seconds. The debug task is a good # place to put various data print outs about the game to help with debugging. self.filters = CommonFilters(base.win, base.cam) filterok = self.filters.setBloom(blend=(0,0,0,1), desat=-0.5, intensity=3.0, size=2) render.setShaderAuto() # Turns on Panda3D's automatic shader generation. self.menuGraphics = loader.loadModel( "../Models/MenuGraphics.egg") # Loads the egg that contains all the menu graphics. self.fonts = { "silver" : loader.loadFont("../Fonts/LuconSilver.egg"), "blue" : loader.loadFont("../Fonts/LuconBlue.egg"), "orange" : loader.loadFont("../Fonts/LuconOrange.egg")} # Loads the three custom fonts our game will use. hud = HUD(self.fonts) # Creates the HUD. self.race = Race(self.inputManager, hud) self.race.createDemoRace() # creates an instance of the race class and tells it to # start a demo race. self.createStartMenu() # creates the start menu. def createStartMenu(self): menu = Menu(self.menuGraphics, self.fonts, self.inputManager) menu.initMenu([0,None, ["New Game", "Quit Game"], [[self.race.createRace, self.createReadyDialogue], [base.userExit]], [[None,None],[None]]]) def createReadyDialogue(self): menu = Menu(self.menuGraphics, self.fonts, self.inputManager) menu.initMenu([3,"Are you ready?", ["Yes","Exit"], [[self.race.startRace],[self.race.createDemoRace]], [[3],[None]]]) def debugTask(self, task): print(taskMgr) # prints all of the tasks in the task manager. return task.again # debugTask: Runs once every ten seconds to print out reports on the games status. w = World() run()

[ "kaz101130@gmail.com" ]

kaz101130@gmail.com

93770b04b06cc4bee60b772d822f418ad8a272c9

faca8866b3c8aca30a915d8cb2748766557ed808

/object_detection_updata/metrics/tf_example_parser.py

510e6917fa9838e9282ec6f561e50cb77a7b5ff9

[]

no_license

yongqis/proposal_joint_retireval

6899d80f8fb94569c7b60764f6e7de74bcfa9cc8

97b086c62473ab1a5baf45743535fce70c3f8c20

refs/heads/master

2020-05-25T19:07:22.946008

2019-06-03T07:09:04

2019-06-03T07:09:09

187,943,867

0

null

UTF-8

Python

false

6,294

py

# Copyright 2017 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 Example proto parser for data loading. A parser to decode data containing serialized tensorflow.Example protos into materialized tensors (numpy arrays). """ import numpy as np from object_detection_updata.core import data_parser from object_detection_updata.core import standard_fields as fields class FloatParser(data_parser.DataToNumpyParser): """Tensorflow Example float parser.""" def __init__(self, field_name): self.field_name = field_name def parse(self, tf_example): return np.array( tf_example.features.feature[self.field_name].float_list.value, dtype=np.float).transpose() if tf_example.features.feature[ self.field_name].HasField("float_list") else None class StringParser(data_parser.DataToNumpyParser): """Tensorflow Example string parser.""" def __init__(self, field_name): self.field_name = field_name def parse(self, tf_example): return "".join(tf_example.features.feature[self.field_name] .bytes_list.value) if tf_example.features.feature[ self.field_name].HasField("bytes_list") else None class Int64Parser(data_parser.DataToNumpyParser): """Tensorflow Example int64 parser.""" def __init__(self, field_name): self.field_name = field_name def parse(self, tf_example): return np.array( tf_example.features.feature[self.field_name].int64_list.value, dtype=np.int64).transpose() if tf_example.features.feature[ self.field_name].HasField("int64_list") else None class BoundingBoxParser(data_parser.DataToNumpyParser): """Tensorflow Example bounding box parser.""" def __init__(self, xmin_field_name, ymin_field_name, xmax_field_name, ymax_field_name): self.field_names = [ ymin_field_name, xmin_field_name, ymax_field_name, xmax_field_name ] def parse(self, tf_example): result = [] parsed = True for field_name in self.field_names: result.append(tf_example.features.feature[field_name].float_list.value) parsed &= ( tf_example.features.feature[field_name].HasField("float_list")) return np.array(result).transpose() if parsed else None class TfExampleDetectionAndGTParser(data_parser.DataToNumpyParser): """Tensorflow Example proto parser.""" def __init__(self): self.items_to_handlers = { fields.DetectionResultFields.key: StringParser(fields.TfExampleFields.source_id), # Object ground truth boxes and classes. fields.InputDataFields.groundtruth_boxes: (BoundingBoxParser( fields.TfExampleFields.object_bbox_xmin, fields.TfExampleFields.object_bbox_ymin, fields.TfExampleFields.object_bbox_xmax, fields.TfExampleFields.object_bbox_ymax)), fields.InputDataFields.groundtruth_classes: ( Int64Parser(fields.TfExampleFields.object_class_label)), # Object detections. fields.DetectionResultFields.detection_boxes: (BoundingBoxParser( fields.TfExampleFields.detection_bbox_xmin, fields.TfExampleFields.detection_bbox_ymin, fields.TfExampleFields.detection_bbox_xmax, fields.TfExampleFields.detection_bbox_ymax)), fields.DetectionResultFields.detection_classes: ( Int64Parser(fields.TfExampleFields.detection_class_label)), fields.DetectionResultFields.detection_scores: ( FloatParser(fields.TfExampleFields.detection_score)), } self.optional_items_to_handlers = { fields.InputDataFields.groundtruth_difficult: Int64Parser(fields.TfExampleFields.object_difficult), fields.InputDataFields.groundtruth_group_of: Int64Parser(fields.TfExampleFields.object_group_of), fields.InputDataFields.groundtruth_image_classes: Int64Parser(fields.TfExampleFields.image_class_label), } def parse(self, tf_example): """Parses tensorflow example and returns a tensor dictionary. Args: tf_example: a tf.Example object. Returns: A dictionary of the following numpy arrays: fields.DetectionResultFields.source_id - string containing original image id. fields.InputDataFields.groundtruth_boxes - a numpy array containing groundtruth boxes. fields.InputDataFields.groundtruth_classes - a numpy array containing groundtruth classes. fields.InputDataFields.groundtruth_group_of - a numpy array containing groundtruth group of flag (optional, None if not specified). fields.InputDataFields.groundtruth_difficult - a numpy array containing groundtruth difficult flag (optional, None if not specified). fields.InputDataFields.groundtruth_image_classes - a numpy array containing groundtruth image-level labels. fields.DetectionResultFields.detection_boxes - a numpy array containing detection boxes. fields.DetectionResultFields.detection_classes - a numpy array containing detection class labels. fields.DetectionResultFields.detection_scores - a numpy array containing detection scores. Returns None if tf.Example was not parsed or non-optional fields were not found. """ results_dict = {} parsed = True for key, parser in self.items_to_handlers.items(): results_dict[key] = parser.parse(tf_example) parsed &= (results_dict[key] is not None) for key, parser in self.optional_items_to_handlers.items(): results_dict[key] = parser.parse(tf_example) return results_dict if parsed else None

[ "syq132@live.com" ]

syq132@live.com

d83ff9d35756aa203096778316d1f1840a266b4c

d9f6f439300d298246c37ccfb881e8e8af4fda22

/cfp/migrations/0021_profile_name.py

814cb2ed2021c677ece96c65e1671b44cb2a0824

[ "MIT" ]

permissive

ajlozier/speakers

e62b8d346a58a034998860d1b42a38b00cbdbd23

d7d87c99b1cfa5f9df5455f737385115d9d5279c

refs/heads/master

2021-09-08T19:33:08.894305

2018-03-12T00:54:10

122,101,157

0

null

2018-02-19T18:08:18

null

UTF-8

Python

false

444

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('cfp', '0020_auto_20150218_0802'), ] operations = [ migrations.AddField( model_name='profile', name='name', field=models.CharField(max_length=300, default=''), preserve_default=False, ), ]

[ "kyle@kyleconroy.com" ]

kyle@kyleconroy.com

e5d51b840f9d3e61bbf612efe4cb4e6c26e84ce6

9743d5fd24822f79c156ad112229e25adb9ed6f6

/xai/brain/wordbase/nouns/_actor.py

04e32c50a329bba627e107500de9e8bd1c6b493f

[ "MIT" ]

permissive

cash2one/xai

de7adad1758f50dd6786bf0111e71a903f039b64

e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6

refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

null

0

null

UTF-8

Python

false

386

py

#calss header class _ACTOR(): def __init__(self,): self.name = "ACTOR" self.definitions = [u'someone who pretends to be someone else while performing in a film, play, or television or radio programme: '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

75af3c206ddd4f8e25574cabd71067f19214176c

4170ed62059b6898cc8914e7f23744234fc2f637

/CD zum Buch "Einstieg in Python"/Programmbeispiele/GUI/gui_check.py

5f2ffb98025c0f74ac7ab1c38d5a0295e3aeec43

[]

no_license

Kirchenprogrammierer/Cheats

9633debd31ab1df78dc639d1aef90d3ac4c1f069

0b71c150f48ad1f16d7b47a8532b1f94d26e148e

refs/heads/master

2021-05-08T10:42:39.927811

2018-02-01T17:29:11

119,858,392

0

null

UTF-8

Python

false

817

py

import tkinter def ende(): main.destroy() def anzeigen(): lb["text"] = "Zimmer " + du.get() + " " + mb.get() main = tkinter.Tk() # Anzeigelabel lb = tkinter.Label(main, text = "Zimmer ", width=40) lb.pack() # Widget-Variablen du = tkinter.StringVar() du.set("ohne Dusche") mb = tkinter.StringVar() mb.set("ohne Minibar") # Zwei Checkbuttons cb1 = tkinter.Checkbutton(main, text="Dusche", variable=du, onvalue="mit Dusche", offvalue="ohne Dusche", command=anzeigen) cb1.pack() cb2 = tkinter.Checkbutton(main, text="Minibar", variable=mb, onvalue="mit Minibar", offvalue="ohne Minibar", command=anzeigen) cb2.pack() bende = tkinter.Button(main, text = "Ende", command = ende) bende.pack() main.mainloop()

[ "noreply@github.com" ]

Kirchenprogrammierer.noreply@github.com

8f95dcb9c22025b63932cb30e24ae18203a9dc38

ce48d74eb28ec153573cd42fe58d39adc784c85c

/jdcloud_sdk/services/xdata/models/DwDatabaseInfo.py

bedf36eee3a80637f1aaf4c87b6493744b5f6c2c

[ "Apache-2.0" ]

permissive

oulinbao/jdcloud-sdk-python

4c886cb5b851707d98232ca9d76a85d54c8ff8a8

660e48ec3bc8125da1dbd576f7868ea61ea21c1d

refs/heads/master

2020-03-16T22:22:15.922184

2018-05-11T10:45:34

null

0

null

UTF-8

Python

false

1,049

py

# coding=utf8 # Copyright 2018-2025 JDCLOUD.COM # # 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. # # NOTE: This class is auto generated by the jdcloud code generator program. class DwDatabaseInfo(object): def __init__(self, owner=None, comments=None, databaseName=None): """ :param owner: (Optional) 所有者 :param comments: (Optional) 描述信息 :param databaseName: (Optional) 数据库名称 """ self.owner = owner self.comments = comments self.databaseName = databaseName

[ "oulinbao@jd.com" ]

oulinbao@jd.com