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

cb781d9d988c44c11a77c73ac37e5299553ac34a

c74b29b68211a51d7283d57b24d7cf83422a8ceb

/classertest.py

ffa1e7ece13d8dbad8941e217e8ee1bf19fb8681

[]

no_license

proycon/nlpsandbox

63359e7cdd709dd81d66aed9bf1437f8ecf706a0

22e5f85852b7b2a658c6b94c3dedd425a5d6396f

refs/heads/master

2020-12-09T19:37:10.040962

2019-04-23T17:17:15

2,347,265

0

1

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Python

false

857

py

#!/usr/bin/env python #-*- coding:utf-8 -*- from pynlpl.statistics import FrequencyList from pynlpl.textprocessors import crude_tokenizer, Classer import sys import codecs import asizeof freqlist = FrequencyList() f = codecs.open(sys.argv[1], 'r','utf-8') for line in f: line = crude_tokenizer(line.strip()) freqlist.append(line) f.close() print "FREQLIST: " ,asizeof.asizeof(freqlist) classer = Classer(freqlist) print "CLASSER: " ,asizeof.asizeof(classer) classer2 = Classer(freqlist, False,True) print "CLASSER (ONLY DECODER): " ,asizeof.asizeof(classer2) freqlist2 = FrequencyList() f = codecs.open(sys.argv[1], 'r','utf-8') for line in f: line = crude_tokenizer(line.strip()) freqlist2.append(classer.encodeseq(line)) f.close() print "FREQLIST-AFTER-CLASSER: " ,asizeof.asizeof(freqlist2)

[ "proycon@anaproy.nl" ]

proycon@anaproy.nl

b152b59d05c3e3d5cdabcc403e4d35db597bceab

235fb362b5af1f7dbd90dc3819fe63f18e074e9d

/learn_pyqt/pyqt5-cv2-multithreaded-master/SharedImageBuffer.py

faf4fedcd3df098ddfccf082c84eb6906e8874fe

[]

no_license

cener-1999/learn_about_python

74c9b8c6a546224261d5577183a946a78ca7e84f

86cfc0a5621f86fc8a1885a39847d40b33137c49

refs/heads/master

2023-04-30T06:38:34.459506

2021-05-18T14:20:29

368,473,253

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from PyQt5.QtCore import QMutexLocker, QMutex, QWaitCondition class SharedImageBuffer(object): def __init__(self): # Initialize variables(s) self.nArrived = 0 self.doSync = False self.syncSet = set() self.wc = QWaitCondition() self.imageBufferDict = dict() self.mutex = QMutex() def add(self, deviceUrl, imageBuffer, sync=False): # Device stream is to be synchronized if sync: with QMutexLocker(self.mutex): self.syncSet.add(deviceUrl) # Add image buffer to map self.imageBufferDict[deviceUrl] = imageBuffer def getByDeviceUrl(self, deviceUrl): return self.imageBufferDict[deviceUrl] def removeByDeviceUrl(self, deviceUrl): # Remove buffer for device from imageBufferDict self.imageBufferDict.pop(deviceUrl) # Also remove from syncSet (if present) with QMutexLocker(self.mutex): if self.syncSet.__contains__(deviceUrl): self.syncSet.remove(deviceUrl) self.wc.wakeAll() def sync(self, deviceUrl): # Only perform sync if enabled for specified device/stream self.mutex.lock() if self.syncSet.__contains__(deviceUrl): # Increment arrived count self.nArrived += 1 # We are the last to arrive: wake all waiting threads if self.doSync and self.nArrived == len(self.syncSet): self.wc.wakeAll() # Still waiting for other streams to arrive: wait else: self.wc.wait(self.mutex) # Decrement arrived count self.nArrived -= 1 self.mutex.unlock() def wakeAll(self): with QMutexLocker(self.mutex): self.wc.wakeAll() def setSyncEnabled(self, enable): self.doSync = enable def isSyncEnabledForDeviceUrl(self, deviceUrl): return self.syncSet.__contains__(deviceUrl) def getSyncEnabled(self): return self.doSync def containsImageBufferForDeviceUrl(self, deviceUrl): return self.imageBufferDict.__contains__(deviceUrl)

[ "1065802928@qq.com" ]

1065802928@qq.com

18da7de4cc349c8c1d2580cadf1d38fed8ba6dfc

1800155dcdb48bf956fa423858a8cc20ed27e6cb

/two-sum-iii-data-structure-design.py

24185cd468ecda7dacfaaced0516ae3647362d6b

[]

no_license

gitprouser/LeetCode-3

1cc2d1dbbf439af4b3768da388dafd514cc5432b

530ea79f0377e1fc3fbfb5c5cfe7768159144e57

refs/heads/master

2021-06-06T16:30:14.795093

2016-08-22T21:40:01

null

0

null

UTF-8

Python

false

828

py

class TwoSum(object): def __init__(self): """ initialize your data structure here """ self.table = {} def add(self, number): """ Add the number to an internal data structure. :rtype: nothing """ self.table[number] = self.table.get(number, 0) + 1 def find(self, value): """ Find if there exists any pair of numbers which sum is equal to the value. :type value: int :rtype: bool """ for i in self.table.keys(): j = value - i if i == j and self.table[i] > 1 or i != j and j in self.table: return True return False # Your TwoSum object will be instantiated and called as such: # twoSum = TwoSum() # twoSum.add(number) # twoSum.find(value)

[ "tohaowu@gmail.com" ]

tohaowu@gmail.com

e35651f899532537e810f36a9aa113eb399a5eaa

382034646e9d3e32c8e63e8d83d2dd7da5be4ef3

/workery/shared_foundation/tests/models/test_opening_hours_specification.py

ee5abb18bc973e46a7b73620b7db5b912280e1f9

[ "BSD-3-Clause", "LicenseRef-scancode-unknown-license-reference" ]

permissive

wahello/workery-django

80c88ecb7968951719af6857711891ec3787cf46

289318b0333d830c089f4492716c38d409c365ed

refs/heads/master

2020-03-30T04:21:48.642659

2018-09-28T01:30:22

null

0

null

UTF-8

Python

false

1,728

py

# -*- coding: utf-8 -*- from django.core.management import call_command from starterkit.utils import get_unique_username_from_email from django_tenants.test.cases import TenantTestCase from django_tenants.test.client import TenantClient from django.urls import reverse from shared_foundation.models import * TEST_USER_EMAIL = "bart@workery.ca" TEST_USER_USERNAME = "bart@workery.ca" TEST_USER_PASSWORD = "123P@$$w0rd" TEST_USER_TEL_NUM = "123 123-1234" TEST_USER_TEL_EX_NUM = "" TEST_USER_CELL_NUM = "123 123-1234" class TestSharedOpeningHoursSpecification(TenantTestCase): """ Console: python manage.py test shared_foundation.tests.models.test_opening_hours_specification """ def setUp(self): super(TestSharedOpeningHoursSpecification, self).setUp() self.c = TenantClient(self.tenant) self.user = SharedUser.objects.create( first_name="Bart", last_name="Mika", email=TEST_USER_EMAIL, is_active=True, ) self.obj = SharedOpeningHoursSpecification.objects.create( owner=self.user, closes="9:00 PM", day_of_week="Monday", opens="8:00 AM" ) def tearDown(self): del self.c self.obj.delete() super(TestSharedOpeningHoursSpecification, self).tearDown() def test_str(self): self.assertIsNotNone(str(self.obj)) self.assertIn("9:00 PM", self.obj.closes) def test_delete_all(self): SharedOpeningHoursSpecification.objects.delete_all() try: obj = SharedOpeningHoursSpecification.objects.get() except SharedOpeningHoursSpecification.DoesNotExist: self.assertTrue(True)

[ "bart@mikasoftware.com" ]

bart@mikasoftware.com

27139caa2ff73ba9f0c5c0772b1633c315e9aa52

a939e018333a9ecd26ddc618f99835b7eb381686

/deploy/vertical_crawler_youtube/le_crawler/common/page_local_writer.py

3a63fce7ba2cc572e552cac20ddeef9e74c0b3e1

[]

no_license

cash2one/crawl_youtube

bff5ba254001c2f31f770e55a4aca39bc54e45ee

0dc40186a1d89da2b00f29d4f4edfdc5470eb4fc

refs/heads/master

2021-01-16T22:30:17.800282

2016-02-18T11:50:09

null

0

null

UTF-8

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#!/usr/bin/python # # Copyright 2014 LeTV Inc. All Rights Reserved. __author__ = 'guoxiaohe@letv.com' import time import os import Queue import threading from scrapy import log from scrapy.utils.project import get_project_settings from ..core.page_writer import PageWriterBase """ for json format data writer """ class PageLocalJsonWriter(PageWriterBase): def __init__(self, spider): PageWriterBase.__init__(self, spider) self._init( get_project_settings().getint('LOCAL_PAGE_WRITER_DATA_TIME_LIMIT', 86400), get_project_settings().getint('LOCAL_PAGE_WRITER_DATA_FLUSH_LIMIT', 20000), get_project_settings().get('LOCAL_PAGE_WRITER_DATA_DIR', '/letv/crawler_delta/') ) self.set_name('PageLocalJsonWriter') def _init(self, gen_max_time = 86400, file_max_nums = 2000, data_dir = ""): if not os.path.isdir(data_dir): raise Exception('%s is not dir' % (data_dir)) self.file_fp_ = None self.current_file_name_ = '' self.total_items_ = 0 self.current_nums_ = 0 self.gen_file_max_time_threshold_ = gen_max_time # 10min self.max_lines_per_file_ = file_max_nums self.last_flush_time_ = int(time.time()) self.data_dir_ = data_dir self.data_queue_ = Queue.LifoQueue(maxsize = 10240) thread = threading.Thread(target = self.file_writer_manger, args = ()) thread.start() def finalize(self): self.exit_ = True while not self.data_queue_.empty(): self.spider_.log('page page_local_writer que[%d]' % (self.data_queue_.qsize()), log.INFO) time.sleep(1) self.spider_.log('%s write items[%s]' % (self.name, self.total_items_), log.INFO) def process_item(self, item): self.add_item(item) def add_item(self, item): if not item: return while True: try: self.data_queue_.put(item, block = True, timeout = 5) return except Exception, e: self.spider_.log('try to put item into queu error %s, size %d' % (e, self.data_queue_.qsize())) continue def status(self): return 'total item wrote: %s' % (self.total_items_) def gen_filestr(self): return os.path.join(self.data_dir_, '%s_%d'%(time.strftime('%Y%m%d_%H%M%S', time.localtime()), os.getpid())) def gen_json_str(self, item): if not item: return None try: return item.to_json_str() except: self.spider_.log('Failed decoding [%s] with [%s]' %(dict['url'], dict['page_encoding']), log.WARNING) dict['page'] = 'error decoding' return None def _prepare_writer(self): if self.file_fp_: self._dump_file() self.current_file_name_ = self.gen_filestr() self.file_fp_ = open(self.current_file_name_ + '.tmp', 'w+') self.current_nums_ = 0 def _dump_file(self): try: if not self.file_fp_: return False self.file_fp_.close() self.last_flush_time_ = int(time.time()) self.file_fp_ = None if self.current_nums_ == 0: os.remove(self.current_file_name_ + '.tmp') else: os.rename(self.current_file_name_ + '.tmp', self.current_file_name_ + '.json') return True except Exception, e: print e self.spider_.log('Error while dump file:[%s]' % self.current_file_name_, log.ERROR) return False def file_writer_manger(self): while not self.exit_ or not self.data_queue_.empty(): item = None try: item = self.data_queue_.get(block = True, timeout = 10) except Exception, e: self.spider_.log('get item from queu timeout[%s]' %(e), log.DEBUG) item = None while not self.file_fp_: self._prepare_writer() self.spider_.log('prepare file ptr:[%s]' % self.current_file_name_, log.INFO) time.sleep(1) if item: line_str = self.gen_json_str(item) if line_str: try: #line_zip = zlib.compress(line_str, zlib.Z_BEST_COMPRESSION) self.file_fp_.write(line_str) self.file_fp_.write('\n') self.current_nums_ += 1 self.total_items_ += 1 if self.current_nums_ > 0 and self.current_nums_ % 1000 == 0: self.spider_.log('Flush result with [%d]' % (self.current_nums_), log.INFO) self.file_fp_.flush() except Exception, e: print time.localtime() print e self.spider_.log('Error while write to file[%s]' % (self.current_file_name_)) nows = int(time.time()) if self.current_nums_ >= self.max_lines_per_file_ or (self.current_nums_ > 0 and (nows - self.last_flush_time_) >= self.gen_file_max_time_threshold_): # flush file to disk if not self._dump_file(): self.spider_.log('flush file error:[%s]' % self.current_file_name_, log.ERROR) self.spider_.log('flush:[ %s ] with [%d]' %(self.current_file_name_, self.current_nums_), log.INFO) self.spider_.log('page_local_writer manager exit normal', log.INFO) self._dump_file()

[ "zjc0516@126.com" ]

zjc0516@126.com

21a34dcd8837c42f9ea42b7bc1e4e5db25cfe7a5

f485dff7fcb036868d6e4053a7a6ccd7f95214bf

/week09/employee_091.py

62e4238ccb5f78116cc7d56777ee671bba48bdc0

[]

no_license

jamesfallon99/CA117

aa4f851365aafe8a4888c85e1b8b2f571e2c9b2a

0055ccbbd710453c9574930b361c26fcde2b9036

refs/heads/master

2020-06-28T14:26:06.829418

2019-08-02T16:41:38

200,254,591

3

1

null

UTF-8

Python

false

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py

#!/usr/bin/env python3 class Employee(object): def __init__(self, name, number): self.name = name self.number = number def wages(self): return 0 def __str__(self): l = [] l.append("Name: {}".format(self.name)) l.append("Number: {}".format(self.number)) l.append("Wages: {:.2f}".format(self.wages())) return "\n".join(l) class Manager(Employee): def __init__(self, name, number, salary): super().__init__(name, number) self.salary = salary def wages(self): return self.salary / 52 class AssemblyWorker(Employee): def __init__(self, name, number, hourly_rate, hours): super().__init__(name, number) self.hourly_rate = hourly_rate self.hours = hours def wages(self): return self.hourly_rate * self.hours

[ "noreply@github.com" ]

jamesfallon99.noreply@github.com

52be7e9c34bece4e6db3c03156d40c378d72b6ca

a1684facd42cba1cd8af003ccffb530f56582e9a

/backend/pet/admin.py

94b98dc921d660340f7a676c08544c25cf98bd86

[]

no_license

dunderlabs/siteong7vidas

e13749863a8f5d64d469b735765044893cc38536

fb3c529025e05adcc9aab17e1eeada909a193e56

refs/heads/master

2021-04-26T21:47:58.638150

2018-10-30T15:37:19

124,160,847

6

1

null

2018-11-28T02:05:10

2018-03-07T01:28:12

Python

UTF-8

Python

false

464

py

from django.contrib import admin from .models import Pet, PetBreed, PetPelage class PetAdmin(admin.ModelAdmin): prepopulated_fields = {"slug": ("name",)} class PetBreedAdmin(admin.ModelAdmin): prepopulated_fields = {"slug": ("name",)} class PetPelageAdmin(admin.ModelAdmin): prepopulated_fields = {"slug": ("name",)} admin.site.register(Pet, PetAdmin) admin.site.register(PetBreed, PetBreedAdmin) admin.site.register(PetPelage, PetPelageAdmin)

[ "luizrodrigo46@hotmail.com" ]

luizrodrigo46@hotmail.com

c30f230f2e18f35e186cf375fa987efcef0c253c

3712a929d1124f514ea7af1ac0d4a1de03bb6773

/开班笔记/python数据分析机器学习部分/机器学习/day08/kpca.py

3ccd0a9d11baf3e0fd08e50a8ae07ade3578adfb

[]

no_license

jiyabing/learning

abd82aa3fd37310b4a98b11ea802c5b0e37b7ad9

6059006b0f86aee9a74cfc116d2284eb44173f41

refs/heads/master

2020-04-02T20:47:33.025331

2018-10-26T05:46:10

154,779,387

0

null

UTF-8

Python

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py

# -*- coding: utf-8 -*- from __future__ import unicode_literals import sklearn.datasets as sd import sklearn.decomposition as dc import matplotlib.pyplot as mp x, y = sd.make_circles(n_samples=500, factor=0.2, noise=0.04) model = dc.KernelPCA(kernel='rbf', fit_inverse_transform=True, gamma=10) kpca_x = model.fit_transform(x) mp.figure('Original', facecolor='lightgray') mp.title('Original', fontsize=20) mp.xlabel('x', fontsize=14) mp.ylabel('y', fontsize=14) mp.tick_params(labelsize=10) mp.grid(linestyle=':') mp.scatter(x[:, 0], x[:, 1], s=60, c=y, cmap='brg', alpha=0.5) mp.figure('KPCA', facecolor='lightgray') mp.title('KPCA', fontsize=20) mp.xlabel('x', fontsize=14) mp.ylabel('y', fontsize=14) mp.tick_params(labelsize=10) mp.grid(linestyle=':') mp.scatter(kpca_x[:, 0], kpca_x[:, 1], s=60, c=y, cmap='brg', alpha=0.5) mp.show()

[ "yabing_ji@163.com" ]

yabing_ji@163.com

82893714841e99045c7d0a2c1bbfa4dc32f9deac

3d1a8ccef4153b6154c0aa0232787b73f45137ba

/services/customer/server.py

02bd6b68c181a44732e11ad2a8e09a2eb503637c

[]

no_license

jan25/hotrod-python

a0527930b2afc33ca3589c1cf7ae07814148535a

dbce7df1bc2d764351dd2ba1122078fc525caed7

refs/heads/master

2020-06-03T14:59:35.627093

2019-06-22T16:52:19

191,616,546

6

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null

UTF-8

Python

false

845

py

from flask import Flask, request, jsonify from uwsgidecorators import postfork import services.common.middleware as middleware import services.config.settings as config import services.common.serializer as serializer from . import db app = Flask(__name__) @postfork def postfork(): middleware.init_tracer('customer') @app.before_request def before_request(): return middleware.before_request(request) @app.after_request def after_request(response): return middleware.after_request(response) @app.route('/customer') def get_customer(): customer_id = request.args.get('id') customer_obj = db.get_customer_by_id(customer_id) return jsonify(serializer.obj_to_json(customer_obj)) def start_server(debug): app.run(host='0.0.0.0', port=config.CUSTOMER_PORT, debug=debug) if __name__ == '__main__': start_server(True)

[ "abhilashgnan@gmail.com" ]

abhilashgnan@gmail.com

1552ae664ea965da697ab12f85e1cc327fb30124

6be8aa517e679b33b47d35f100e6590902a8a1db

/DP/Problem19.py

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[]

no_license

LeeJuhae/Algorithm-Python

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729947b4428205adfbac194a5527b0eeafe1c525

refs/heads/master

2023-04-24T01:02:36.430970

2021-05-23T07:17:25

null

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null

UTF-8

Python

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py

# https://www.acmicpc.net/problem/11049 import sys read = sys.stdin.readline n = int(read().strip()) arr = [tuple(map(int, read().strip().split())) for _ in range(n)] dp = [[-1 for _ in range(n)] for _ in range(n)] def mul(a, b): if dp[a][b] != -1: return dp[a][b] if a == b: return 0 ret = float('inf') for k in range(a, b): ret = min(ret, mul(a, k) + mul(k + 1, b) + arr[a][0] * arr[k][1] * arr[b][1]) dp[a][b] = ret return ret print(mul(0, n - 1))

[ "gusdn0657@gmail.com" ]

gusdn0657@gmail.com

f269f66869c2a17070ed2079a79139e33939efe5

377b908723f157ab30733fa5ff15db90c0be9693

/build/celex4/catkin_generated/pkg.installspace.context.pc.py

f861cb62d3e2dc6d77d7eb7eb7bef0ed002c193b

[]

no_license

eleboss/celex4_ros

af0b28ec0ba79016ae80e90e0cd3d270a8865fa1

28500367e8e28e6e5384036b6f9bd8981a7b932e

refs/heads/master

2020-04-30T14:03:43.823980

2019-03-21T05:59:05

176,877,974

1

0

null

UTF-8

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441

py

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "cv_bridge;dvs_msgs;image_transport;roscpp;roslib;sensor_msgs".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "celex4" PROJECT_SPACE_DIR = "/home/ubuntu/Documents/celex4_ros/install" PROJECT_VERSION = "0.0.0"

[ "you@example.com" ]

you@example.com

2eee67dfdbd5f09719f524851ce744a41a9b3f32

ce18877752c43eb66f03bdc169e3ef45a1720d15

/src/apps_common/mailerlite/__init__.py

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[]

no_license

ajlexgit/robin

26e8682ae09795acf0f3fc1297d20044285b83df

25ac1c3455838fc26656cfa16d05b2943d0cbba6

refs/heads/master

2021-07-13T22:49:09.177207

2017-10-13T07:44:42

103,655,240

1

0

null

UTF-8

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py

""" Модуль подписки на рассылку. Зависит от: premailer libs.associative_request libs.color_field libs.pipeline libs.templatetags Установка: # settings.py: INSTALLED_APPS = ( ... 'mailerlite', ... ) SUIT_CONFIG = { ... { 'app': 'mailerlite', 'icon': 'icon-envelope', 'models': ( 'Campaign', 'Subscriber', 'Group', 'MailerConfig', ) }, } MAILERLITE_APIKEY = '438b16c79cbd9acea354a1c1ad5eda08' # urls.py: ... url(r'^mailerlite/', include('mailerlite.urls', namespace='mailerlite')), ... # crontab */15 * * * * . $HOME/.profile; ~/aor.com/env/bin/python3 ~/aor.com/src/manage.py mailerlite -ig -es -ic -ec 10 * * * * . $HOME/.profile; ~/aor.com/env/bin/python3 ~/aor.com/src/manage.py mailerlite -ig -eg -es -is Использование: # views.py: from mailerlite import SubscribeForm class IndexView(View): def get(self, request, *args, **kwargs): ... return self.render_to_response({ subscribe_form': SubscribeForm(), ... }) # template.html: <form action="" method="post" id="subscribe-form"> {% render_form subscribe_form %} <input type="submit" value="Subscribe" class="btn"> </form> """ default_app_config = 'mailerlite.apps.Config'

[ "pix666@ya.ru" ]

pix666@ya.ru

ae241182ad08298d4046ba796efca16ca15a0257

54f352a242a8ad6ff5516703e91da61e08d9a9e6

/Source Codes/AtCoder/arc028/A/4640482.py

31948a2b01b51da02f93d6230fbd993758c38420

[]

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

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333

py

n,a,b = map(int,input().split()) turn = 1 while True: if turn == 1: if n > a: n -= a turn *= -1 else: print("Ant") exit() else: if n > b: n -= b turn *= -1 else: print("Bug") exit()

[ "kwnafi@yahoo.com" ]

kwnafi@yahoo.com

cf526d0998ec05ba8a704de0e3067c5e2d706869

89b45e528f3d495f1dd6f5bcdd1a38ff96870e25

/AutomateTheBoringStuffWithPython/chapter12/spreadsheet_to_text_files.py

40698e57cc6c206b11f50b49c18978d9f96df97b

[]

no_license

imatyukin/python

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#!/usr/bin/env python3 import openpyxl def main(): spreadsheet = "text_to_spreadsheet.xlsx" wb = openpyxl.load_workbook(spreadsheet) sheet = wb.active nrows = sheet.max_row ncols = sheet.max_column for col in range(1, ncols+1): text_file = "spreadsheet_" + str(col) + ".txt" with open(text_file, 'w') as f: for row in range(1, nrows+1): content = sheet.cell(row=row, column=col).value if content is None: continue f.write(str(content)) if __name__ == "__main__": main()

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i.matukin@gmail.com

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yattom/snaffle

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# coding: utf-8 import time import logging import webbrowser logger = logging.getLogger(__name__) handler = logging.StreamHandler() handler.setLevel(logging.DEBUG) logger.setLevel(logging.DEBUG) logger.addHandler(handler) import snaffle.ws_server class Snaffle: def __init__(self, start=True): if start: self.start() def start(self): snaffle.ws_server.start_server_tornado() webbrowser.open('http://localhost:9999/index') def shutdown(self): snaffle.ws_server.shutdown() def write_something(self, msg): snaffle.ws_server.write_something(msg) def send_script(self, script): msg = ''' {{ "type": "script", "content": "{0}" }} '''.format(script) self.write_something(msg)

[ "tsutomu.yasui@gmail.com" ]

tsutomu.yasui@gmail.com

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permissive

GyxChen/AmusingPythonCodes

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# encoding: utf-8 import xml.etree.ElementTree as ETree import requests import re def dataset_xml_iterator(filename): """An iterator to convert xml-format dataset to more readable text format""" instances = ETree.parse(filename).getroot() for instance in instances: paragraph = instance.find('text').text questions = instance.findall('questions')[0] queries = [] for question in questions.findall('question'): tmp_dict = {'Text': question.get('text')} for answer in question.findall('answer'): tmp_dict[answer.get('correct')] = answer.get('text') queries.append(tmp_dict) yield paragraph, queries def read_nth_data(filename, n): """Read Nth paragraph and corresponding queries""" index = 0 for paragraph, queries in dataset_xml_iterator(filename): index += 1 if n == index: # para = paragraph # que = queries return paragraph, queries return None def extract_conceptnet(phrase): """Access ConceptNet API and read relational triples as well as their weight and simple example""" url_head = 'http://api.conceptnet.io/c/en/' # access ConceptNet API raw_json = requests.get(url_head + phrase).json() edges = raw_json['edges'] if not edges: # if edges is empty, which means ConceptNet doesn't contain such concept or node return None concepts = [] for edge in edges: triple = re.findall(r'/a/\[/r/(.*?)/.*?,/c/en/(.*?)/.*?,/c/en/(.*?)/.*?\]', edge['@id'])[0] # ERE triple surface_text = re.sub(r'[\[\]]', '', '' if edge['surfaceText'] is None else edge['surfaceText']) # example weight = edge['weight'] # weight concepts.append({'Triple': triple, 'weight': weight, 'example': surface_text}) return concepts

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open-mmlab/mmaction2

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_base_ = '../../../_base_/default_runtime.py' model = dict( type='Recognizer3D', backbone=dict( type='ResNet3dSlowOnly', in_channels=17, base_channels=32, num_stages=3, out_indices=(2, ), stage_blocks=(4, 6, 3), conv1_stride_s=1, pool1_stride_s=1, inflate=(0, 1, 1), spatial_strides=(2, 2, 2), temporal_strides=(1, 1, 1), dilations=(1, 1, 1)), cls_head=dict( type='I3DHead', in_channels=512, num_classes=60, dropout_ratio=0.5, average_clips='prob')) dataset_type = 'PoseDataset' ann_file = 'data/skeleton/ntu60_2d.pkl' left_kp = [1, 3, 5, 7, 9, 11, 13, 15] right_kp = [2, 4, 6, 8, 10, 12, 14, 16] train_pipeline = [ dict(type='UniformSampleFrames', clip_len=32), dict(type='PoseDecode'), dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True), dict(type='Resize', scale=(64, 64), keep_ratio=False), dict(type='RandomResizedCrop', area_range=(0.56, 1.0)), dict(type='Resize', scale=(56, 56), keep_ratio=False), dict(type='Flip', flip_ratio=0.5, left_kp=left_kp, right_kp=right_kp), dict(type='GeneratePoseTarget', with_kp=True, with_limb=False), dict(type='FormatShape', input_format='NCTHW_Heatmap'), dict(type='PackActionInputs') ] val_pipeline = [ dict(type='UniformSampleFrames', clip_len=32, num_clips=1, test_mode=True), dict(type='PoseDecode'), dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True), dict(type='Resize', scale=(64, 64), keep_ratio=False), dict(type='GeneratePoseTarget', with_kp=True, with_limb=False), dict(type='FormatShape', input_format='NCTHW_Heatmap'), dict(type='PackActionInputs') ] test_pipeline = [ dict( type='UniformSampleFrames', clip_len=32, num_clips=10, test_mode=True), dict(type='PoseDecode'), dict(type='PoseCompact', hw_ratio=1., allow_imgpad=True), dict(type='Resize', scale=(64, 64), keep_ratio=False), dict( type='GeneratePoseTarget', with_kp=True, with_limb=False, left_kp=left_kp, right_kp=right_kp), dict(type='FormatShape', input_format='NCTHW_Heatmap'), dict(type='PackActionInputs') ] train_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=True), dataset=dict( type='RepeatDataset', times=10, dataset=dict( type=dataset_type, ann_file=ann_file, split='xsub_train', pipeline=train_pipeline))) val_dataloader = dict( batch_size=16, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type=dataset_type, ann_file=ann_file, split='xsub_val', pipeline=val_pipeline, test_mode=True)) test_dataloader = dict( batch_size=1, num_workers=8, persistent_workers=True, sampler=dict(type='DefaultSampler', shuffle=False), dataset=dict( type=dataset_type, ann_file=ann_file, split='xsub_val', pipeline=test_pipeline, test_mode=True)) val_evaluator = [dict(type='AccMetric')] test_evaluator = val_evaluator train_cfg = dict( type='EpochBasedTrainLoop', max_epochs=18, val_begin=1, val_interval=1) val_cfg = dict(type='ValLoop') test_cfg = dict(type='TestLoop') param_scheduler = [ dict( type='CosineAnnealingLR', eta_min=0, T_max=18, by_epoch=True, convert_to_iter_based=True) ] optim_wrapper = dict( optimizer=dict(type='SGD', lr=0.2, momentum=0.9, weight_decay=0.0003), clip_grad=dict(max_norm=40, norm_type=2)) # Default setting for scaling LR automatically # - `enable` means enable scaling LR automatically # or not by default. # - `base_batch_size` = (8 GPUs) x (16 samples per GPU). auto_scale_lr = dict(enable=False, base_batch_size=128)

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/new_algs/Sequence+algorithms/Binary+search+algorithm/palindromes.py

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coolsnake/JupyterNotebook

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#!python """STARTER CODE FROM NEPTUNIUS""" import string import re # Hint: Use these string constants to ignore capitalization and/or punctuation # string.ascii_lowercase is 'abcdefghijklmnopqrstuvwxyz' # string.ascii_uppercase is 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' # string.ascii_letters is ascii_lowercase + ascii_uppercase def is_palindrome(text): """A string of characters is a palindrome if it reads the same forwards and backwards, ignoring punctuation, whitespace, and letter casing.""" # implement is_palindrome_iterative and is_palindrome_recursive below, then # change this to call your implementation to verify it passes all tests assert isinstance(text, str), 'input is not a string: {}'.format(text) return is_palindrome_recursive(text) # return is_palindrome_recursive(text) def is_palindrome_iterative(text): #implements the is_palindrome function iteratively here regex = re.compile('[^a-zA-Z]') text = regex.sub('', text) text = text.upper() thing_1 = 0 thing_2 = len(text)-1 while thing_1 < thing_2: if text[thing_1] != text[thing_2]: return False thing_1+=1 thing_2-=1 return True # once implemented, change is_palindrome to call is_palindrome_iterative # to verify that your iterative implementation passes all tests def is_palindrome_recursive(text, left=None, right=None): #implements the is_palindrome function recursively here if left is None: regex = re.compile('[^a-zA-Z]') text = regex.sub('', text) text = text.upper() left = 0 right = len(text)-1 if text == '': return True if text[left] != text[right]: return False if left < right: return is_palindrome_recursive(text, left=left+1, right=right-1) else: return True # once implemented, change is_palindrome to call is_palindrome_recursive # to verify that your iterative implementation passes all tests def main(): import sys args = sys.argv[1:] # Ignore script file name if len(args) > 0: for arg in args: is_pal = is_palindrome(arg) result = 'PASS' if is_pal else 'FAIL' is_str = 'is' if is_pal else 'is not' print('{}: {} {} a palindrome'.format(result, repr(arg), is_str)) else: print('Usage: {} string1 string2 ... stringN'.format(sys.argv[0])) print(' checks if each argument given is a palindrome') if __name__ == '__main__': #print(is_palindrome_iterative("talcat")) print(is_palindrome_recursive("TAC!!!Oc at", left=None, right=None)) print(is_palindrome_iterative("no, on!"))

[ "chenqh@uci.edu" ]

chenqh@uci.edu

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bopopescu/nova-24

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2022-11-20T00:48:53.224075

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#coding:utf-8 # Copyright 2013 OpenStack Foundation # 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. from oslo.config import cfg from nova.compute import task_states from nova.compute import vm_states imagecache_opts = [ cfg.IntOpt('image_cache_manager_interval', default=2400, help='Number of seconds to wait between runs of the image ' 'cache manager. Set to -1 to disable. ' 'Setting this to 0 will disable, but this will change in ' 'the K release to mean "run at the default rate".'), # TODO(gilliard): Clean the above message after the K release cfg.StrOpt('image_cache_subdirectory_name', default='_base', help='Where cached images are stored under $instances_path. ' 'This is NOT the full path - just a folder name. ' 'For per-compute-host cached images, set to _base_$my_ip'), cfg.BoolOpt('remove_unused_base_images', default=True, help='Should unused base images be removed?'), cfg.IntOpt('remove_unused_original_minimum_age_seconds', default=(24 * 3600), help='Unused unresized base images younger than this will not ' 'be removed'), ] CONF = cfg.CONF CONF.register_opts(imagecache_opts) CONF.import_opt('host', 'nova.netconf') class ImageCacheManager(object): """Base class for the image cache manager. This class will provide a generic interface to the image cache manager. """ def __init__(self): self.remove_unused_base_images = CONF.remove_unused_base_images self.resize_states = [task_states.RESIZE_PREP, task_states.RESIZE_MIGRATING, task_states.RESIZE_MIGRATED, task_states.RESIZE_FINISH] def _get_base(self): """Returns the base directory of the cached images.""" raise NotImplementedError() def _list_running_instances(self, context, all_instances): """List running instances (on all compute nodes). This method returns a dictionary with the following keys: - used_images - image_popularity - instance_names """ used_images = {} image_popularity = {} instance_names = set() for instance in all_instances: # NOTE(mikal): "instance name" here means "the name of a directory # which might contain an instance" and therefore needs to include # historical permutations as well as the current one. instance_names.add(instance.name) instance_names.add(instance.uuid) if (instance.task_state in self.resize_states or instance.vm_state == vm_states.RESIZED): instance_names.add(instance.name + '_resize') instance_names.add(instance.uuid + '_resize') for image_key in ['image_ref', 'kernel_id', 'ramdisk_id']: image_ref_str = getattr(instance, image_key) if image_ref_str is None: continue local, remote, insts = used_images.get(image_ref_str, (0, 0, [])) if instance.host == CONF.host: local += 1 else: remote += 1 insts.append(instance.name) used_images[image_ref_str] = (local, remote, insts) image_popularity.setdefault(image_ref_str, 0) image_popularity[image_ref_str] += 1 return {'used_images': used_images, 'image_popularity': image_popularity, 'instance_names': instance_names} def _list_base_images(self, base_dir): """Return a list of the images present in _base. This method returns a dictionary with the following keys: - unexplained_images - originals """ return {'unexplained_images': [], 'originals': []} def _age_and_verify_cached_images(self, context, all_instances, base_dir): """Ages and verifies cached images.""" raise NotImplementedError() def update(self, context, all_instances): """The cache manager. This will invoke the cache manager. This will update the cache according to the defined cache management scheme. The information populated in the cached stats will be used for the cache management. """ raise NotImplementedError()

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takin6/algorithm-practice

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# Definition for a binary tree node. class TreeNode: def __init__(self, x): self.val = x self.left = None self.right = None class Solution: def distributeCoins(self, root: TreeNode) -> int: self.res = 0 def dfs(root): if root is None: return 0 excess_from_left = dfs(root.left) excess_from_right = dfs(root.right) print(root.val, excess_from_left, excess_from_right) self.res += abs(excess_from_left) + abs(excess_from_right) return root.val + excess_from_left + excess_from_right - 1 dfs(root) return self.res # t = TreeNode(3) # t.left = TreeNode(0) # t.right = TreeNode(0) # print(Solution().distributeCoins(t)) # print("---------------") # t = TreeNode(0) # t.left = TreeNode(3) # t.right = TreeNode(0) # print(Solution().distributeCoins(t)) print("---------------") # [1,0,0,null,3] t = TreeNode(1) t.left = TreeNode(0) t.right = TreeNode(0) t.left.right = TreeNode(3) print(Solution().distributeCoins(t))

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Wang-Yann/LeetCodeMe

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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Author : Rock Wayne # @Created : 2020-05-07 08:00:00 # @Last Modified : 2020-05-07 08:00:00 # @Mail : lostlorder@gmail.com # @Version : alpha-1.0 """ # 给定一个非负整数数组，a1, a2, ..., an, 和一个目标数，S。现在你有两个符号 + 和 -。对于数组中的任意一个整数，你都可以从 + 或 -中选 # 择一个符号添加在前面。 # # 返回可以使最终数组和为目标数 S 的所有添加符号的方法数。 # # 示例 1: # # 输入: nums: [1, 1, 1, 1, 1], S: 3 # 输出: 5 # 解释: # # -1+1+1+1+1 = 3 # +1-1+1+1+1 = 3 # +1+1-1+1+1 = 3 # +1+1+1-1+1 = 3 # +1+1+1+1-1 = 3 # # 一共有5种方法让最终目标和为3。 # # # 注意: # # # 数组非空，且长度不会超过20。 # 初始的数组的和不会超过1000。 # 保证返回的最终结果能被32位整数存下。 # # Related Topics 深度优先搜索动态规划 """ import functools from typing import List import pytest # leetcode submit region begin(Prohibit modification and deletion) class Solution: def findTargetSumWays(self, nums: List[int], S: int) -> int: """ https://leetcode-cn.com/problems/target-sum/solution/0-1bei-bao-you-hua-jie-fa-by-sunrise-z/ sum(a)+sum(b)=sum(nums) sum(a)-sum(b)=S a代表所有非负数组，b代表所有非正数组，一正一负，正的和负的绝对值为总和，正的-负的为我们的目标S 那么可以求得sum(a) = (sum(nums)+S) /2 即在数组nums中取子集，满足子集的和为(sum(nums)+S) /2，看看这样的条件有多少种转化为　0-1 背包二维的话 dp[i][j] = x 表示，若只在前 i 个物品中选择，若当前背包的容量为 j，则最多有 x 种方法可以恰好装满背包 dp[i][j] = dp[i-1][j] + dp[i-1][j-nums[i-1]]; """ total = sum(nums) if total < S: return 0 tmp = total + S if tmp & 0b1: return 0 target = tmp // 2 dp = [0] * (target + 1) dp[0] = 1 for num in nums: for v in range(target, num - 1, -1): dp[v] += dp[v - num] return dp[target] # leetcode submit region end(Prohibit modification and deletion) class Solution1: def findTargetSumWays(self, nums: List[int], S: int) -> int: """ 初始版本　超时优化后可以过 """ N = len(nums) @functools.lru_cache(None) def dfs(i, cur_sum): ans = 0 if i == N: if cur_sum == S: return 1 else: ans += dfs(i + 1, cur_sum + nums[i]) + dfs(i + 1, cur_sum - nums[i]) return ans return dfs(0, 0) @pytest.mark.parametrize("kw,expected", [ [dict(nums=[1, 1, 1, 1, 1], S=3), 5], ]) def test_solutions(kw, expected): assert Solution().findTargetSumWays(**kw) == expected assert Solution1().findTargetSumWays(**kw) == expected if __name__ == '__main__': pytest.main(["-q", "--color=yes", "--capture=no", __file__])

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rock@get.com.mm

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# -*- coding: utf-8 -*- __author__ = 'caiqinxiong_cai' # 2019/9/3 14:35 import struct import json import os import sys import hashlib from core.server_auth import ServerAuth as sa from core.log import Log as log from conf import settings as ss class Common: '''公共类''' @staticmethod def mySend(conn, msgb, dic=False): '''发送数据时，解决粘包问题''' if dic: msgb = json.dumps(msgb).encode('utf-8') len_msg = len(msgb) pack_len = struct.pack('i', len_msg) conn.send(pack_len) conn.send(msgb) @staticmethod def myRecv(conn, dic=False): '''接收数据时，解决粘包问题''' pack_len = conn.recv(4) # struct机制，在发送数据前，加上固定长度4字节的头部 len_msg = struct.unpack('i', pack_len)[0] # 解包，得到元组。 msg_b = conn.recv(len_msg) if dic: msg_b = json.loads(msg_b.decode('utf-8')) return msg_b @staticmethod def processBar(num, total): '''打印进度条''' rate = num / total rate_num = int(rate * 100) bar = ('>' * rate_num, rate_num,) # 展示的进度条符号 r = '\r%s>%d%%\n' % bar if rate_num == 100 else '\r%s>%d%%' % bar sys.stdout.write(r) # 覆盖写入 return sys.stdout.flush # 实时刷新 @staticmethod def updateQuota(file, name, quota_new): '''更新磁盘配额''' with open(file, mode='r', encoding='utf-8') as f1, open(file + '.bak', mode='w', encoding='utf-8') as f2: for line in f1: if line.strip(): if name in line: usr, pwd, quota_old = line.split('|') line = usr + '|' + pwd + '|' + quota_new + '\n' f2.write(line) os.remove(file) os.rename(file + '.bak', file) @staticmethod def checkQuota(file, dic): '''检查磁盘配额''' for n, p, q in sa.readInfo(file): if dic['name'] == n: dic['msg'] = '用户%s当前磁盘配额剩余：%s字节\n上传文件大小为：%s字节' % (dic['name'], q, dic['filesize']) num = int(q) - int(dic['filesize']) dic['flag'] = False if num < 0 else True if not dic['flag']: dic['msg'] = '%s用户磁盘配额不足！\n' % dic['name'] + dic['msg'] dic['total'] = q dic['quota'] = str(num) return dic @classmethod def startTransfer(cls, conn, dic, kind, file, mode, b_size=1024000): '''开始传输，提取上传下载公共代码''' md5 = hashlib.md5() # 发送数据时，添加MD5校验，就不用再单独打开一次文件做校验了 if dic['exist_size']: log.debug('文件上次已经%s了%s字节，开始断点续传！' % (kind, dic['exist_size'])) with open(file, mode) as f: if kind == '下载': f.seek(dic['exist_size']) # 将指针移动到指定位置开始读 while dic['filesize'] > 0: if kind == '下载': line = f.read(b_size) conn.send(line) # 发生粘包也没有关系，反正最后把文件传完就行 elif kind == '上传': line = conn.recv(b_size) # 发生粘包也没有关系，反正最后把文件传完就行 f.write(line) dic['exist_size'] += len(line) # 累计发送文件大小，传输进度条用 dic['filesize'] -= len(line) # 退出循环用 cls.processBar(dic['exist_size'], dic['total_size']) md5.update(line) dic['server_md5'] = md5.hexdigest() # 自己发送数据的MD5值 dic['client_md5'] = cls.myRecv(conn).decode('utf-8') # 接收对方的MD5值 dic['msg'] = 'MD5校验OK，文件传输成功！' if dic['client_md5'] == dic['server_md5'] else 'MD5不一致，文件传输失败！' if not dic['msg'].find('成功') < 0 and kind == '上传': cls.updateQuota(ss.USER_FILE, dic['name'], dic['quota']) # 传输成功时更新磁盘配额 dic['msg'] = dic['msg'] + '\n文件上传位置：' + dic['upload_file'] + '\nMD5值为：' + dic['server_md5'] + '\n磁盘配额剩余：%s字节' % dic['quota'] elif not dic['msg'].find('成功') < 0 and kind == '下载': dic['msg'] = dic['msg'] + '\n文件下载位置：' + dic['download_file'] + '\nMD5值为：' + dic['server_md5'] log.readAndWrite(dic['msg']) cls.mySend(conn, dic, True) return dic @classmethod def startGetFile(cls, conn, dic): '''客户端从服务器下载文件''' return cls.startTransfer(conn, dic, kind='下载', file=dic['file_path'], mode='rb') @classmethod def startPutFile(cls, conn, dic): '''从客户端上传文件到服务器''' return cls.startTransfer(conn, dic, kind='上传', file=dic['upload_file'], mode='ab')

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/test/runtime/frontend_test/chainer_test/pow_var_var_test.py

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import chainer import numpy as np from test.util import generate_kernel_test_case from webdnn.frontend.chainer.converter import ChainerConverter def test(): vx1 = chainer.Variable(np.random.rand(2, 4, 6, 8).astype(np.float32)) vx2 = chainer.Variable(np.random.rand(2, 4, 6, 8).astype(np.float32)) vy = vx1 ** vx2 graph = ChainerConverter().convert([vx1, vx2], [vy]) x1 = graph.inputs[0] x2 = graph.inputs[1] y = graph.outputs[0] generate_kernel_test_case( description=f"[chainer] F.PowVarVar", graph=graph, inputs={ x1: vx1.data, x2: vx2.data }, expected={y: vy.data}, ) def test_itself(): vx = chainer.Variable(np.random.rand(2, 4, 6, 8)) vy = vx ** vx graph = ChainerConverter().convert([vx], [vy]) x = graph.inputs[0] y = graph.outputs[0] generate_kernel_test_case( description=f"[chainer] F.PowVarVar itself", graph=graph, inputs={x: vx.data}, expected={y: vy.data}, )

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y.kikura@gmail.com

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/QUANTTOOLS/QAStockETL/QASU/save_usstock_alpha.py

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[]

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chaopaoo12/QuantTools

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from QUANTAXIS.QAUtil import (DATABASE, QA_util_log_info,QA_util_to_json_from_pandas,QA_util_today_str) from QUANTTOOLS.QAStockETL.QAUtil import (QA_util_get_trade_range, QA_util_if_trade) from QUANTTOOLS.QAStockETL.QAFetch import QA_fetch_usstock_list from QUANTTOOLS.QAStockETL.QAFetch import (QA_fetch_get_usstock_alpha, QA_fetch_get_usstock_alpha101) import pymongo import gc def QA_SU_save_usstock_alpha_day(code = None, start_date = None, end_date = None, client=DATABASE, ui_log = None, ui_progress = None): ''' save stock_day 保存财报日历历史全部数据 :return: ''' if end_date is None: end_date = QA_util_today_str() if start_date is None: start_date = '2009-01-01' deal_date_list = QA_util_get_trade_range(start_date, end_date, 'us') if code is None: code = list(QA_fetch_usstock_list()['code']) stock_alpha = client.usstock_alpha stock_alpha.create_index([("code", pymongo.ASCENDING), ("date_stamp", pymongo.ASCENDING)], unique=True) err = [] def __saving_work(date, code): try: QA_util_log_info( '##JOB01 Now Saving USStock Alpha191==== {}'.format(str(date)), ui_log) data = QA_fetch_get_usstock_alpha(code, date) if data is not None: stock_alpha.insert_many(QA_util_to_json_from_pandas(data), ordered=False) gc.collect() except Exception as error0: print(error0) err.append(str(date)) for item in deal_date_list: QA_util_log_info('The {} of Total {}'.format ((deal_date_list.index(item) +1), len(deal_date_list))) strProgressToLog = 'DOWNLOAD PROGRESS {}'.format(str(float((deal_date_list.index(item) +1) / len(deal_date_list) * 100))[0:4] + '%', ui_log) intProgressToLog = int(float((deal_date_list.index(item) +1) / len(deal_date_list) * 100)) QA_util_log_info(strProgressToLog, ui_log= ui_log, ui_progress= ui_progress, ui_progress_int_value= intProgressToLog) if QA_util_if_trade(item) == True: __saving_work( item, code) if len(err) < 1: QA_util_log_info('SUCCESS save USStock Alpha191 ^_^', ui_log) else: QA_util_log_info(' ERROR CODE \n ', ui_log) QA_util_log_info(err, ui_log) def QA_SU_save_usstock_alpha_his(code = None, start_date = None, end_date = None, client=DATABASE, ui_log = None, ui_progress = None): ''' save stock_day 保存财报日历反向查询四个季度财报 :return: ''' if code is None: code = list(QA_fetch_usstock_list()['code']) if end_date is None: end_date = QA_util_today_str() if start_date is None: start_date = '2009-01-01' deal_date_list = QA_util_get_trade_range(start_date, end_date, 'us') stock_alpha = client.usstock_alpha stock_alpha.create_index([("code", pymongo.ASCENDING), ("date_stamp", pymongo.ASCENDING)], unique=True) err = [] def __saving_work(code, date): try: QA_util_log_info( '##JOB01 Now Saving USStock Alpha191==== {}'.format(str(date)), ui_log) data = QA_fetch_get_usstock_alpha(code, date) if data is not None: stock_alpha.insert_many(QA_util_to_json_from_pandas(data), ordered=False) except Exception as error0: print(error0) err.append(str(date)) for item in deal_date_list: QA_util_log_info('The {} of Total {}'.format ((deal_date_list.index(item) +1), len(deal_date_list))) strProgressToLog = 'DOWNLOAD PROGRESS {}'.format(str(float((deal_date_list.index(item) +1) / len(deal_date_list) * 100))[0:4] + '%', ui_log) intProgressToLog = int(float((deal_date_list.index(item) + 1)/ len(deal_date_list) * 100)) QA_util_log_info(strProgressToLog, ui_log= ui_log, ui_progress= ui_progress, ui_progress_int_value= intProgressToLog) if QA_util_if_trade(item) == True: __saving_work(code, item) if len(err) < 1: QA_util_log_info('SUCCESS save USStock Alpha191 ^_^', ui_log) else: QA_util_log_info(' ERROR CODE \n ', ui_log) QA_util_log_info(err, ui_log) def QA_SU_save_usstock_alpha101_day(code = None, start_date = None, end_date = None, client=DATABASE, ui_log = None, ui_progress = None): ''' save stock_day 保存财报日历历史全部数据 :return: ''' if end_date is None: end_date = QA_util_today_str() if start_date is None: start_date = '2009-01-01' codes = code if codes is None: codes = list(QA_fetch_usstock_list()['code']) stock_alpha = client.usstock_alpha101 stock_alpha.create_index([("code", pymongo.ASCENDING), ("date_stamp", pymongo.ASCENDING)], unique=True) err = [] def __saving_work(code,start,end): try: QA_util_log_info( '##JOB01 Now Saving USStock Alpha101==== {}'.format(str(code)), ui_log) data = QA_fetch_get_usstock_alpha101(code,start,end) if data is not None: stock_alpha.insert_many(QA_util_to_json_from_pandas(data), ordered=False) gc.collect() except Exception as error0: print(error0) err.append(str(code)) for code in codes: QA_util_log_info('The {} of Total {}'.format ((codes.index(code) +1), len(codes))) strProgressToLog = 'DOWNLOAD PROGRESS {}'.format(str(float((codes.index(code) +1) / len(codes) * 100))[0:4] + '%', ui_log) intProgressToLog = int(float((codes.index(code) +1) / len(codes) * 100)) QA_util_log_info(strProgressToLog, ui_log= ui_log, ui_progress= ui_progress, ui_progress_int_value= intProgressToLog) __saving_work(code,start_date,end_date) if len(err) < 1: QA_util_log_info('SUCCESS save USStock Alpha101 ^_^', ui_log) else: QA_util_log_info(' ERROR CODE \n ', ui_log) QA_util_log_info(err, ui_log) def QA_SU_save_usstock_alpha101_his(code = None, start_date = None, end_date = None, client=DATABASE, ui_log = None, ui_progress = None): ''' save stock_day 保存财报日历历史全部数据 :return: ''' if end_date is None: end_date = QA_util_today_str() if start_date is None: start_date = '2009-01-01' codes = code if codes is None: codes = list(QA_fetch_usstock_list()['code']) stock_alpha = client.usstock_alpha101 stock_alpha.create_index([("code", pymongo.ASCENDING), ("date_stamp", pymongo.ASCENDING)], unique=True) err = [] def __saving_work(code,start,end): try: QA_util_log_info( '##JOB01 Now Saving USStock Alpha101==== {}'.format(str(code)), ui_log) data = QA_fetch_get_usstock_alpha101(code,start,end) if data is not None: stock_alpha.insert_many(QA_util_to_json_from_pandas(data), ordered=False) gc.collect() except Exception as error0: print(error0) err.append(str(code)) for code in codes: QA_util_log_info('The {} of Total {}'.format ((codes.index(code) +1), len(codes))) strProgressToLog = 'DOWNLOAD PROGRESS {}'.format(str(float((codes.index(code) +1) / len(codes) * 100))[0:4] + '%', ui_log) intProgressToLog = int(float((codes.index(code) +1) / len(codes) * 100)) QA_util_log_info(strProgressToLog, ui_log= ui_log, ui_progress= ui_progress, ui_progress_int_value= intProgressToLog) __saving_work(code,start_date,end_date) if len(err) < 1: QA_util_log_info('SUCCESS save USStock Alpha101 ^_^', ui_log) else: QA_util_log_info(' ERROR CODE \n ', ui_log) QA_util_log_info(err, ui_log) if __name__ == '__main__': pass

[ "chaopaoo12@hotmail.com" ]

chaopaoo12@hotmail.com

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/test/mitmproxy/test_flow_export/locust_get.py

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from locust import HttpLocust, TaskSet, task class UserBehavior(TaskSet): def on_start(self): ''' on_start is called when a Locust start before any task is scheduled ''' self.path() @task() def path(self): url = self.locust.host + '/path' headers = { 'header': 'qvalue', 'content-length': '7', } self.response = self.client.request( method='GET', url=url, headers=headers, ) ### Additional tasks can go here ### class WebsiteUser(HttpLocust): task_set = UserBehavior min_wait = 1000 max_wait = 3000

[ "aldo@nullcube.com" ]

aldo@nullcube.com

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/shipments/migrations/0012_auto_20141029_1158.py

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('shipments', '0011_auto_20141023_1542'), ] operations = [ migrations.AlterField( model_name='location', name='latitude', field=models.DecimalField(null=True, max_digits=13, decimal_places=10), preserve_default=True, ), migrations.AlterField( model_name='location', name='longitude', field=models.DecimalField(null=True, max_digits=13, decimal_places=10), preserve_default=True, ), ]

[ "dpoirier@caktusgroup.com" ]

dpoirier@caktusgroup.com

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/full-stack-web-app/api/DjangoAPI/EmployeeApp/serializers.py

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Nourreddine1920/full-stack-web-app

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2023-06-29T21:38:57.416787

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from rest_framework import serializers from EmployeeApp.models import Departments,Employees class DepartmentSerializer(serializers.ModelSerializer): class Meta: model=Departments fields=('DepartmentId','DepartmentName') class EmployeeSerializer(serializers.ModelSerializer): class Meta: model=Employees fields=('EmployeeId','EmployeeName','Department','DateOfJoining','PhotoFileName')

[ "Vous@exemple.com" ]

Vous@exemple.com

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/03_Bigdata/02_Standardization_Analysis/2. Excel/7pandas_column_by_index.py

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SuHyeonJung/iot_python2019

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2020-06-14T22:18:27.503781

2019-11-08T05:50:41

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import sys import pandas as pd input_file = sys.argv[1] output_file = sys.argv[2] data_frame = pd.read_excel(input_file, 'january_2013', index_col=None) data_frame_column_by_index = data_frame.iloc[:, [1, 4]] writer = pd.ExcelWriter(output_file) data_frame_column_by_index.to_excel(writer, sheet_name='jan_13_output', index=False) writer.save()

[ "galma94815@naver.com" ]

galma94815@naver.com

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/18. 4Sum.py

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no_license

jiewu-stanford/leetcode

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refs/heads/master

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2022-05-18T05:16:22

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''' Title : 18. 4Sum Problem : https://leetcode.com/problems/4sum/ ''' ''' pair up to convert to the 2-sum problem ''' class Solution: def fourSum(self, nums: List[int], target: int) -> List[List[int]]: pair_nums = {} for i in range(len(nums)-1): for j in range(i+1, len(nums)): pair_num = nums[i] + nums[j] if pair_num in pair_nums: pair_nums[pair_num].append((i, j)) else: pair_nums[pair_num] = [(i, j)] quadruplets = set() for key, val in pair_nums.items(): dif = target - key if dif in pair_nums: pair1, pair2 = val, pair_nums[dif] for i, j in pair1: for k, l in pair2: quad = [i, j, k, l] if len(set(quad)) != len(quad): continue quadruplet = [nums[i], nums[j], nums[k], nums[l]] quadruplet.sort() quadruplets.add(tuple(quadruplet)) return list(quadruplets) ''' iterative solution, more comprehensible but much slower ''' class Solution: def fourSum(self, nums: List[int], target: int) -> List[List[int]]: nums.sort() quadruplets = [] L = len(nums) for i in range(L-3): if i > 0 and nums[i-1] == nums[i]: continue for j in range(i+1, L-2): if j > i + 1 and nums[j-1] == nums[j]: continue dif = target - nums[i] - nums[j] l, r = j+1, L-1 while l < r: if nums[l] + nums[r] == dif: quadruplets.append((nums[i], nums[j], nums[l], nums[r])) r -= 1 l += 1 while l < r and nums[l-1] == nums[l]: l += 1 while l < r and nums[r] == nums[r+1]: r -= 1 elif nums[l] + nums[r] > dif: r -= 1 else: l += 1 return quadruplets ''' combine the solution of 1. Two Sum and 15. 3Sum Reference: https://programmer.help/blogs/leetcode-2sum-3sum-4sum-python.html ''' class Solution: def fourSum(self, nums: List[int], target: int) -> List[List[int]]: if len(nums) < 4: return [] nums.sort() def threeSum(nums, target): # the 15. solution def twoSum(nums, target, num, triplets): # the 1. solution l, r, tgt = 0, len(nums)-1, target-num while l != r: if nums[l] + nums[r] < tgt: l += 1 elif nums[l] + nums[r] > tgt: r -= 1 else: triplet = [num, nums[l], nums[r]] l += 1 while l != r and nums[l-1] == nums[l]: l += 1 triplets.append(triplet) return triplets result = [] for i in range(len(nums)-2): if i > 0 and nums[i-1] == nums[i]: continue else: remnant = nums[i+1:] result = twoSum(remnant, target, nums[i], result) return result res = [] for i in range(len(nums)-3): if i > 0 and nums[i-1] == nums[i]: continue num = nums[i] trisum = target - num rem = nums[i+1:] triples = threeSum(rem, trisum) if len(triples) > 0: for triple in triples: triple.append(num) res.append(triple) return res

[ "bayernscience@hotmail.com" ]

bayernscience@hotmail.com

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/account_flujo_caja_it/__manifest__.py

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# -*- encoding: utf-8 -*- { 'name': 'Saldos Comprobantes Analisis IT Extended', 'category': 'account', 'author': 'ITGRUPO-COMPATIBLE-BO', 'depends': ['analisis_saldos_comprobantes_periodo_it','account_sheet_work','account_multipayment_invoices_it','account_multipayment_invoices_it_advance'], 'version': '1.0', 'description':""" Analisis de Saldos por Comprobantes version 2017 """, 'auto_install': False, 'demo': [], 'data': ['wizard/account_contable_period_view.xml'], 'installable': True }

[ "angel_afla@hotmail.com" ]

angel_afla@hotmail.com

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/autofill_users.py

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prateekchandan/pickup-server

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import requests import os import json loginURL = "http://pickup.prateekchandan.me/add_user" HTTPSession = requests.session() start_locations=['Larsen+Tourbo+Powai','IIT+Bombay+Hostel+9','Hiranandani+Hospital','Hiranandani','Kanjur+Marg+Station', 'Chandivali','Raheja+Vihar','Supreme+Powai','Galleria+Hiranandani','Powai+Plaza'] for i in range(100): postData = {'key':'9f83c32cf3c9d529e' ,'fbid':i ,'name':'person'+str(i) , 'email':'person'+str(i)+'@gmail.com' , 'device_id':i , 'gcm_id':i, 'mac_addr':i , 'gender':'male'} afterLoginPage = HTTPSession.post(loginURL, data = postData ) print afterLoginPage.content #afterLoginPage = HTTPSession.post(loginURL, data = postData ) #print afterLoginPage.content

[ "kalpeshk2011@gmail.com" ]

kalpeshk2011@gmail.com

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/hadoop-python/TopPopularLinksMapper.py

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atashi/LLL

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refs/heads/master

2021-05-17T10:11:28.946779

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#!/usr/bin/env python import sys from collections import Counter counter = Counter() for line in sys.stdin: line = line.strip() k, v = line.split('\t') try: v = int(v) except ValueError: continue counter.update({k: v}) counter_list = counter.items() sort_counter = sorted(counter_list, key=lambda x: x[1], reverse=True) for k, v in sort_counter[:10]: print("%s\t%d" % (k, v))

[ "rebornwwp@gmail.com" ]

rebornwwp@gmail.com

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/ch03/ex3-9.motorcycles.py

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[]

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gustavonvp/PYTHON-CRASH-COURSE

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refs/heads/master

2023-04-03T00:42:20.333183

2017-10-24T05:47:01

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py

# Appending Elements to the End of a List motorcycles = [] motorcycles.append('honda') motorcycles.append('yamaha') motorcycles.append('suzuki') print(motorcycles)

[ "freebz@hananet.net" ]

freebz@hananet.net

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/Python_Scripts/model_numbers.py

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permissive

ICB-DCM/solverstudy

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refs/heads/master

2023-01-19T17:36:08.394305

2020-11-23T22:53:03

307,409,328

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MIT

2020-11-23T22:53:05

2020-10-26T14:59:53

Python

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py

"""Extract some basic information on model numbers.""" import os import pandas as pd from C import DIR_MODELS df = pd.read_csv(os.path.join(DIR_MODELS, 'model_summary.tsv'), sep='\t') print("Column names", df.columns) print("Number of models:", df.shape[0]) print("Number of model groups:", len(df.short_id.unique())) print("Number of AMICI importable models:", sum(df.amici_import == 'OK')) print("Number of COPASI importable models:", sum(~pd.isnull(df.copasi_path))) df_imp = df[(df.amici_import == 'OK') & (~pd.isnull(df.copasi_path))] print("Number of importable models:", df_imp.shape[0]) print("Number of model groups:", len(df_imp.short_id.unique())) df_acc = df_imp[df_imp.accepted] print("Number of accepted models:", df_acc.shape[0]) print("Number of accepted model groups:", len(df_acc.short_id.unique()))

[ "noreply@github.com" ]

ICB-DCM.noreply@github.com

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d3afd01b844f314a25e231d49eb18419b38de40b

/NotMnist/make_datasets.py

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[]

no_license

nanigasi-san/Chainer_DL

35cb6f58ef05ce45f371990af5f7ebc675ee2472

ee8fb1faec9e5aad67a5d366681acc3979946c4b

refs/heads/master

2020-04-29T14:40:00.004462

2019-06-20T08:16:51

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from skimage import io import glob import numpy as np from chainer.datasets import TupleDataset from random import randint #Tuple_Datasetを作る def make_tupledata_set_train(size=100): alphabet_list = list("ABCDEFGHIJKLMNOPQRSTUVWXYZ") image_list = [] answer_list = [] def make_image_set(): image_path_list = glob.glob("F://notMnist_large/{0}/*".format(alphabet)) count = 0 _dataset = [] for image_path in image_path_list[:size+100]: try: _dataset.append(io.imread(image_path)/255) count += 1 except: continue if count == size: break return _dataset def make_answer_set(): return np.array( [alphabet_list.index(alphabet)] * size) for alphabet in alphabet_list[:10]: image_list.extend(make_image_set()) answer_list.extend(make_answer_set()) return TupleDataset(np.array(image_list,dtype=np.float32),np.array(answer_list)) def make_tupledata_set_test(size=10): alphabet_list = list("ABCDEFGHIJKLMNOPQRSTUVWXYZ") image_list = [] answer_list = [] def make_image_set(): image_path_list = glob.glob("F://notMnist_large/{0}/*".format(alphabet)) count = 0 _dataset = [] for i in range(size+50): try: _dataset.append(io.imread(image_path_list[randint(0,30000)])/255) count += 1 except: continue if count == size: break return _dataset def make_answer_set(): return np.array( [alphabet_list.index(alphabet)] * size) for alphabet in alphabet_list[:10]: image_list.extend(make_image_set()) answer_list.extend(make_answer_set()) return TupleDataset(np.array(image_list,dtype=np.float32),np.array(answer_list))

[ "nanigasi.py@gmail.com" ]

nanigasi.py@gmail.com

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/torchblocks/processor/sequence_labeling_processor.py

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permissive

topDreamer/TorchBlocks

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refs/heads/master

2022-12-29T15:13:42.779220

2020-10-18T02:18:11

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import logging from .base import DataProcessor from .utils import InputFeatures logger = logging.getLogger(__name__) class SequenceLabelingProcessor(DataProcessor): ''' special_token_label: [CLS]和[SEP]对应的标签, defalult: 'O' pad_label_id: padding对应的标签id, 默认使用'X',即default: 0 ''' def __init__(self, tokenizer, data_dir, prefix='', encode_mode='one', truncate_label=True, special_token_label='O', add_special_tokens=True, pad_to_max_length=True, pad_label_id=0): super().__init__(data_dir=data_dir, prefix=prefix, tokenizer=tokenizer, encode_mode=encode_mode, pad_to_max_length=pad_to_max_length, add_special_tokens=add_special_tokens, truncate_label=truncate_label) self.pad_label_id = pad_label_id self.special_token_label = special_token_label def convert_to_features(self, examples, label_list, max_seq_length, **kwargs): label_map = {label: i for i, label in enumerate(label_list)} features = [] for (ex_index, example) in enumerate(examples): if ex_index % 10000 == 0: logger.info("Writing example %d/%d" % (ex_index, len(examples))) texts = example.texts inputs = self.encode(texts=texts, max_seq_length=max_seq_length) label_ids = example.label_ids if label_ids is None or not isinstance(label_ids, list): raise ValueError("label_ids is not correct") special_toekns_num = 2 if self.add_special_tokens else 0 if len(label_ids) > max_seq_length - special_toekns_num: # [CLS] and [SEP] label_ids = label_ids[:(max_seq_length - special_toekns_num)] label_ids = [label_map[x] for x in label_ids] label_ids = [label_map[self.special_token_label]] + label_ids + [label_map[self.special_token_label]] label_ids += [self.pad_label_id] * (max_seq_length - len(label_ids)) # padding inputs['guid'] = example.guid inputs['label_ids'] = label_ids if ex_index < 5: self.print_examples(**inputs) features.append(InputFeatures(**inputs)) return features class SequenceLabelingSpanProcessor(DataProcessor): ''' span sequence labeling ''' def __init__(self, tokenizer, data_dir, prefix='', encode_mode='one', truncate_label=True, add_special_tokens=True, pad_to_max_length=True, pad_label_id=0): super().__init__(data_dir=data_dir, prefix=prefix, encode_mode=encode_mode, tokenizer=tokenizer, pad_to_max_length=pad_to_max_length, add_special_tokens=add_special_tokens, truncate_label=truncate_label) self.pad_label_id = pad_label_id def get_batch_keys(self): return ['input_ids', 'attention_mask', 'token_type_ids', 'start_positions', 'end_positions'] def convert_to_features(self, examples, label_list, max_seq_length): label2id = {label: i for i, label in enumerate(label_list)} features = [] for (ex_index, example) in enumerate(examples): if ex_index % 10000 == 0: logger.info("Writing example %d/%d" % (ex_index, len(examples))) texts = example.texts inputs = self.encode(texts=texts, max_seq_length=max_seq_length) start_positions = [self.pad_label_id] * max_seq_length end_positions = [self.pad_label_id] * max_seq_length for span in example.label_ids: label = span[0] if self.add_special_tokens: start = span[1] + 1 # cls end = span[2] + 1 # cls special_num = 2 else: start = span[1] end = span[2] special_num = 0 if start > max_seq_length - special_num: continue start_positions[start] = label2id[label] if end > max_seq_length - special_num: continue end_positions[end] = label2id[label] assert len(start_positions) == max_seq_length assert len(end_positions) == max_seq_length inputs['guid'] = example.guid inputs['start_positions'] = start_positions inputs['end_positions'] = end_positions if ex_index < 5: self.print_examples(**inputs) features.append(InputFeatures(**inputs)) return features

[ "1436496575@qq.com" ]

1436496575@qq.com

d3f68f0ea82a4d0dbaf2ae04832775a6e8124729

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/chap04_Classification/lecture_1x/step05_softmax_classifier.py

b2a0c2b0c34af50a17fb6d5bf97458f396355a39

[]

no_license

DominKim/Tensorflow_DNN_CNN_RNN_Basic

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1de11219800169b3bc0c95872d5952e76cbc3227

refs/heads/master

2022-11-09T11:16:06.576660

2020-06-30T05:50:04

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# -*- coding: utf-8 -*- """ step05_softmax_classifier - 활성함수 : Softmax(model) - 손실함수 : Cross Entropy """ import numpy as np import tensorflow.compat.v1 as tf tf.disable_v2_behavior() from sklearn.metrics import accuracy_score # 1. x, y 공급 data # [털, 날개] x_data = np.array([[0, 0], [1, 0], [1, 1], [0, 0], [0, 1], [1, 1]]) # [6, 2] # [기타, 포유류, 조류] : [6, 3] -> one hot encoding y_data = np.array([ [1, 0, 0], # 기타[0] [0, 1, 0], # 포유류[1] [0, 0, 1], # 조류[2] [1, 0, 0], [1, 0, 0], [0, 0, 1] ]) # 2. X, Y 변수 정의 X = tf.placeholder(dtype = tf.float32, shape = [None, 2]) # [관측치, 입력수] Y = tf.placeholder(dtype = tf.float32, shape = [None, 3]) # [관측치, 출력수] # 3. w, b w = tf.Variable(tf.random_normal([2,3])) # [입력수, 출력수] b = tf.Variable(tf.random_normal([3])) # [출력수] # 4. softmax 분류기 # 1) 회귀방정식 : 예측치 model = tf.matmul(X, w) + b # 회귀모델 # softmax(예측치) softmax = tf.nn.softmax(model) # 활성함수 적용(0 ~ 1) : y1 : 0.8, y2 : 0.1, y3 : 0.1 # (2) loss function : Entropy 이용 : -sum(Y * log(model)) loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(labels = Y, logits = model)) loss = -tf.reduce_mean(Y * tf.log(softmax) + (1 - Y) * tf.log(1 - softmax)) # 3) optimizer : 오차 최소화(w, b update) train = tf.train.AdamOptimizer(0.1).minimize(loss) # 오차 최소화 # 4) argmax() : encoding(2) -> decoding(10) y_pred = tf.argmax(softmax, axis = 1) y_true = tf.argmax(Y, axis = 1) # 5. with tf.Session() as sess: sess.run(tf.global_variables_initializer()) # 반복학습 : 500회 for step in range(500): _, loss_val = sess.run([train, loss], feed_dict = {X:x_data, Y: y_data}) if (step + 1) % 50 == 0: print(f"step = {step + 1}, loss = {loss_val}") # mode result print(sess.run(softmax, feed_dict = {X:x_data})) y_pred_re = sess.run(y_pred, feed_dict = {X:x_data}) # 예측치 y_true_re = sess.run(y_true, feed_dict = {Y:y_data}) # 정답 acc = accuracy_score(y_true_re, y_pred_re) print("y_pred =", y_pred_re) print("y_true =", y_true_re) print("accuracy =", acc) ''' y_pred = [0 1 1 0 0 1] y_true = [0 1 2 0 0 2] accuracy = 0.6666666666666666 '''

[ "hyungm3@gmail.com" ]

hyungm3@gmail.com

5dda0c6d02518f56ac74730f1e83e27e23506133

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/Exercices/6/Q Sauvegarde.py

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[]

no_license

rverschuren/Info

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c9aa0bdc1b026c8ba8134b878b5fae7d49d75e19

refs/heads/master

2020-04-16T07:29:49.847812

2019-01-14T14:50:18

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1

2

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2019-01-12T18:56:01

2019-01-12T13:12:46

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#Wiaux Bastien def save_data(filename, life, mana, position_x, position_y): with open(filename,"w") as fichier: fichier.write("{}\n{}\n{}\n{}".format(life, mana, position_x, position_y)) def load_data(filename): with open(filename,'r') as fichier: data = [int(i) for i in fichier.read().strip().split("\n")] return data[0],data[1],data[2],data[3]

[ "bastien.wiaux@gmail.com" ]

bastien.wiaux@gmail.com

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/home/context_processors.py

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[ "MIT" ]

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manushah17/Capstone_2019

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refs/heads/master

2022-12-16T21:08:29.385969

2019-09-07T15:08:42

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MIT

2022-12-08T01:22:56

2019-09-07T15:04:22

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from django.conf import settings def global_settings(request): return { 'GOOGLE_MAPS_API_KEY': settings.GOOGLE_MAPS_API_KEY }

[ "manushah@unomaha.edu" ]

manushah@unomaha.edu

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kaist-plrg/jstar

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1. If _Desc_ is *undefined*, return *undefined*. 1. Let _obj_ be ! OrdinaryObjectCreate(%Object.prototype%). 1. Assert: _obj_ is an extensible ordinary object with no own properties. 1. If _Desc_ has a [[Value]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"value"*, _Desc_.[[Value]]). 1. If _Desc_ has a [[Writable]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"writable"*, _Desc_.[[Writable]]). 1. If _Desc_ has a [[Get]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"get"*, _Desc_.[[Get]]). 1. If _Desc_ has a [[Set]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"set"*, _Desc_.[[Set]]). 1. If _Desc_ has an [[Enumerable]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"enumerable"*, _Desc_.[[Enumerable]]). 1. If _Desc_ has a [[Configurable]] field, then 1. Perform ! CreateDataPropertyOrThrow(_obj_, *"configurable"*, _Desc_.[[Configurable]]). 1. Return _obj_.

[ "h2oche22@gmail.com" ]

h2oche22@gmail.com

cefbf59aba6168247c1a7dd09e5d28cd50a6b679

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/Web網頁框架/框架(Django)/200502_cookie&session/mysite/app01/views.py

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narru888/PythonWork-py37-

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2022-12-09T04:58:06.068302

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from django.shortcuts import render, redirect def login(request): print('COOKIES', request.COOKIES) print('SESSION', request.session) if request.method == 'POST': name = request.POST.get('user') pwd = request.POST.get('pwd') if name == 'sb' and pwd == '123': # 純COOKIE(不安全) # ret = redirect('/index/') # # set_cookie(key, values, 有效存在時間(s)) # ret.set_cookie('data', {'user': name, 'pwd': pwd}, max_age=5) # cookie加入信息 # return ret # COOKIE & SESSION request.session['is_login'] = True request.session['user'] = name # request.session.set_expiry(value) # 如果value是個整數，session會在些秒數後失效。 # 如果value是個datatime或timedelta，session就會在這個時間後失效。 # 如果value是0, 用戶關閉瀏覽器session就會失效。 # 如果value是None, session會依賴全局session失效策略。 request.session.set_expiry(10) return redirect('/index/') return render(request, 'login.html') def index(request): # 純COOKIE(不安全) # if request.COOKIES.get('data', None): # 沒有抓到回傳None # user = request.COOKIES.get('data') # return render(request, 'index.html', locals()) # COOKIE & SESSION if request.session.get('is_login', None): user = request.session.get('user') return render(request, 'index.html', locals()) else: return redirect('/login/')

[ "as124122323@gmail.com" ]

as124122323@gmail.com

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koyo922/leetcode

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#!/usr/bin/env python # -*- coding: utf-8 -*- # vim: tabstop=4 shiftwidth=4 expandtab number """ 给定一个包含 n 个整数的数组 nums，判断 nums 中是否存在三个元素 a，b，c ，使得 a + b + c = 0 ？找出所有满足条件且不重复的三元组。注意：答案中不可以包含重复的三元组。例如, 给定数组 nums = [-1, 0, 1, 2, -1, -4]，满足要求的三元组集合为： [ [-1, 0, 1], [-1, -1, 2] ] 来源：力扣（LeetCode）链接：https://leetcode-cn.com/problems/3sum 著作权归领扣网络所有。商业转载请联系官方授权，非商业转载请注明出处。 Authors: qianweishuo<qzy922@gmail.com> Date: 2019/7/4 上午8:46 """ class Solution(object): def bruteforce(self, nums): res = set() nums.sort() # 有利于减少重复，减轻判重压力 for i, x in enumerate(nums): for j, y in enumerate(nums[i + 1:], start=i + 1): # 注意start for z in nums[j + 1:]: if x + y + z == 0: res.add((x, y, z)) return list(res) def using_set(self, nums): if len(nums) < 3: # 边界条件 return [] res = set() nums.sort() # 先排序，减轻判重压力 for i, v in enumerate(nums[:-2]): if i - 1 >= 0 and nums[i - 1] == v: # 如果跟左边值相等，避免重复解 continue trap = set() # 类似two-sum，不过返回的是值而非下标；所以能用set代替dict for x in nums[i + 1:]: if x in trap: res.add((v, -v - x, x)) else: trap.add(-v - x) return res def using_pinch(self, nums): res = set() nums.sort() for i, v in enumerate(nums[:-2]): if i - 1 >= 0 and nums[i - 1] == v: # 重复值跳过 continue l, r = i + 1, len(nums) - 1 # 开始就地两边夹逼，避免了额外空间 while l < r: s = v + nums[l] + nums[r] if s < 0: l += 1 elif s > 0: r -= 1 else: res.add((v, nums[l], nums[r])) # 如果res是list，则此处要手动去重 while l<r and nums[l+1]==nums[l]: l+=1 l += 1 r -= 1 return res def threeSum(self, nums): # return self.bruteforce(nums) # return self.using_set(nums) return self.using_pinch(nums) if __name__ == '__main__': print(Solution().threeSum([-1, 0, 1, 2, -1, -4]))

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# !/usr/bin/python3 # -*- coding: utf-8 -*- # @Author：AI悦创 @DateTime ：2020/2/16 16:02 @Function ：功能 Development_tool ：PyCharm # code is far away from bugs with the god animal protecting # I love animals. They taste delicious. from sqlalchemy import create_engine from sqlalchemy import Table,Column,String,Integer,MetaData from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base Base = declarative_base() # 创建基类 engine = create_engine( "mysql+pymysql://root:123456@127.0.0.1:3306/test", max_overflow = 5, # 超过连接池大小之后，外最多可以创建的链接 pool_size = 10, # 连接池大小 echo = True, # 调试信息展示 ) metadata = MetaData() class Host(Base): # 表名为 host __tablename__ = 'host' # 表结构 # primary_key 等于主键 # unique 唯一 # nullable 可为空的 id = Column(Integer, primary_key=True, autoincrement=True) hostname = Column(String(64), unique=True, nullable=False) ip_addr = Column(String(128),unique=True, nullable=False) port = Column(Integer, default=22) # @classmethod # def filter(cls, param): # pass # Base.metadata.create_all(engine) # 创建表 # res = sess.query(Host).filter_by(id=1).all() if __name__ == '__main__': Session = sessionmaker(bind = engine) sess = Session() res = sess.query(Host).filter(Host.id==1) for r in res: print(r) print(r.hostname) print(r.ip_addr) sess.commit() h = Host(hostname='test1', ip_addr='127.0.0.1') h2 = Host(hostname='test2', ip_addr='192.168.0.1', port=8080) h3 = Host(hostname='test3', ip_addr='192.170.1.0', port=3030) # sess.query(Host).filter(Host.id==1).update({'port':9999}) # sess.commit() # 循环加入多个数据 # if __name__ == '__main__': # Session = sessionmaker(bind = engine) # sess = Session() # data_list = ['AI悦创', 'aiyc', 12, 1314.520, '黄'] # for index, data in enumerate(data_list): # h = Host(hostname=data,ip_addr=index) # # h = Host(hostname='{}'.format(data), ip_addr='{}'.format(index)) # sess.add(h) # sess.commit() # user = Table('mybank', metadata, # Column('id', Integer, primary_key=True, autoincrement=True), # Column('name', String(10)) # ) # connect = engine.connect() # connect.execute(user.delete().where(user.c.id==1)) # connect.close() # # res = connect.execute(select([user.c.name,])) # # # res = connect.execute(select([user.c.id==1,user.c.id==2])) # # print(res.fetchall()) # # connect.close() # # metadata.create_all(engine) # # conn = engine.connect() # # conn.execute(user.update().where(user.c.id==1).values(name='Python')) # # conn.close() # # res = engine.execute('select * from user2020') # # print(res) # # for i in res: # # print(i) # # print(i[0]) # # print(i[1]) # # print(type(i)) # # engine.execute("insert into user2020 (City, name) values ('AIYC', 'huang')") # # 同时添加多个数据，字段名称的位置可以不按数据库表中的来写 # # # engine.execute("update user2020 set id=5, name='Python' where id=1") # # engine.execute("update user2020 set name='Python',id=10 where id=5") # # # # # engine.execute('update 操作对象(表) set （更新数据操作）所要修改的数据在哪里(where)') # # # engine.execute("insert into user2020 (name) values ('AIYC')") # # # metadata = MetaData() # 取得元数据，介绍数据库 # # data = Table('user', metadata, # # Column('id', Integer, primary_key = True, autoincrement=True), # # Column('name', String(10)), # # Column('City', String(255)) # # ) # # # metadata.create_all(engine) # # connect = engine.connect() # # # connect.execute(data.update(data.c.id==1).values(City="Beijing",name="AI悦创")) # # # connect.execute(select([])) # # connect.close() # from sqlalchemy import create_engine,MetaData,Table,engine # from sqlalchemy import Column,String,Integer # # # engine = create_engine( # "mysql+pymysql://root:123456@127.0.0.1:3306/test",# （里面的 root 要填写你的密码）,注意：mysql+pymysql 之间不要加空格 # # "mysql + pymysql://root:root@localhost/test", # max_overflow = 5, # 超过连接池大小之后，外最多可以创建的链接 # pool_size = 10, # 连接池大小 # echo = True, # 调试信息展示 # ) # # metadata = MetaData() # 获得元数据，介绍数据库 # # # 定义表 # user_table = Table('user_table', metadata, # Column("id", Integer, primary_key=True,autoincrement=True), # Column("教学表",String(10))) # metadata.create_all(engine) # 创建表 # # # 修改表中数据 # conn = engine.connect() # 获取一个连接 # # 增加数据 # conn.execute(user_table.insert(),{"教学表":"hjb_two"}) # # # 更新数据-更新全部数据 # conn.execute(user_table.update(),{"教学表":"AI悦创"}) # # # 更新指定数据 # conn.execute(user_table.update().where(user_table.c.id==1).values(id=1000)) # conn.execute(user_table.update().where(user_table.c.id==2).values(教学表='AIYC')) # # # where(user.c.id==2) 查找的位置,或者说要修改的位置 # conn.close() # # from sqlalchemy import create_engine,MetaData,Table,engine # from sqlalchemy import Column,String,Integer # # # engine = create_engine( # "mysql+pymysql://root:123456@127.0.0.1:3306/test", # max_overflow = 5, # 超过连接池大小之后，外最多可以创建的链接 # pool_size = 10, # 连接池大小 # echo = True, # 调试信息展示 # ) # # metadata = MetaData() # 获得元数据，介绍数据库 # # # 定义表 # user = Table('mybank', metadata, # Column("id", Integer, primary_key=True,autoincrement=True), # Column("教学表",String(10))) # metadata.create_all(engine) # 创建表 # # ----------------------------插入数据---------------------------------- # # 修改表中数据 # conn = engine.connect() # 获取一个连接 # # 增加数据 # conn.execute(user.insert(),{"教学表":"hjb_two"}) # conn.close() # # ----------------------------更新数据---------------------------------- # # # 更新数据-更新全部数据 # conn.execute(user.update(),{"教学表":"AI悦创"}) # # # 更新指定数据 # conn.execute(user.update().where(user.c.id==1).values(id=1000)) # conn.execute(user.update().where(user.c.id==2).values(教学表='AIYC')) # # 同时更新多个数据 # conn.execute(user.update().where(user.c.id==1).values(City="Beijing",name="AI悦创")) # # # where(user.c.id==2) 查找的位置,或者说要修改的位置 # conn.close() # # ----------------------------查询数据---------------------------------- # # 需要导入：select # from sqlalchemy import select # conn = engine.execute() # res = conn.execute(select([user.c.name,])) # # res = conn.execute(select([user.c.id==1, user.c.id==2])) # print(res.fetchall()) # conn.close() # # ----------------------------删除数据---------------------------------- # conn = engine.execute() # conn.execute(user.delete().where(user.c.id==1)) # conn.close()

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registry = {} class Data: def __repr__(self): return str(self.val) def __init__(self,V): # lookup for existant object if V in registry: self = registry[V] else: self.val = V registry[V] = self # register created object print registry,Data(0) print registry,Data(0) print registry,Data(1) print registry,Data(1)

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abandonsea/Revisiting-Feature-Fusion-for-RGB-T-Salient-Object-Detection

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import cv2 import numpy as np import T_train import os import sys import tensorflow as tf import time import vgg16 import math os.environ["CUDA_VISIBLE_DEVICES"] = "2" #img_t_mean=[101.515, 78.315, 140.606] #img_t_mean=[85.971, 56.608, 151.944] #img_t_mean=[127.493, 126.314, 127.453] #small def load_img_list(dataset): if dataset == 'MSRA-B': path = 'dataset/MSRA-B/image' elif dataset == 'DUT-OMRON': path = 'dataset/DUT-OMRON/DUT-OMRON-image' imgs = os.listdir(path) return path, imgs def image_entropy(input): tmp = [] for i in range(256): tmp.append(0) val = 0 k = 0 res = 0 #image = input.convert('L') img = np.array(input) for i in range(len(img)): for j in range(len(img[i])): val = img[i][j] tmp[val] = float(tmp[val] + 1) k = float(k + 1) for i in range(len(tmp)): tmp[i] = float(tmp[i] / k) for i in range(len(tmp)): if(tmp[i] == 0): res = res else: res = float(res - tmp[i] * (math.log(tmp[i]) / math.log(2.0))) res_ = res / 8.0 return res_ if __name__ == "__main__": model = T_train.Model() model.build_model() sess = tf.Session() sess.run(tf.global_variables_initializer()) img_size = T_train.img_size label_size = T_train.label_size ckpt = tf.train.get_checkpoint_state('Model-thermal/') saver = tf.train.Saver() saver.restore(sess, 'Model-thermal/model.ckpt-14') datasets = ['MSRA-B', 'DUT-OMRON'] if not os.path.exists('Result'): os.mkdir('Result') #for dataset in datasets: #path, imgs = load_img_list(dataset) #save_dir = 'Result/' + dataset #if not os.path.exists(save_dir): #os.mkdir(save_dir) #save_dir = 'Result/' + dataset + '/NLDF_' #if not os.path.exists(save_dir): #os.mkdir(save_dir) imgs_r = os.listdir('DATA/thermal-test') for f_img_r in imgs_r: img_r = cv2.imread(os.path.join('DATA/thermal-test', f_img_r)) img_name, ext = os.path.splitext(f_img_r) if img_r is not None: #ori_img = img.copy() img_shape = img_r.shape img_r = cv2.resize(img_r, (img_size, img_size)) #- R_train.img_r_mean img_r = img_r.astype(np.float32) / 255. img_r = img_r.reshape((1, img_size, img_size, 3)) start_time = time.time() result = sess.run(model.Prob, feed_dict={model.input_holder_t: img_r}) print("--- %s seconds ---" % (time.time() - start_time)) result = np.reshape(result, (label_size, label_size, 2)) result = result[:, :, 0] result = cv2.resize(np.squeeze(result), (img_shape[1], img_shape[0])) save_name = os.path.join('Result', img_name+'.png') cv2.imwrite(save_name, (result*255).astype(np.uint8)) sess.close()

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#!/usr/bin/env python ''' driver.py ''' # **************************************** # ############# # IMPORTS # ############# # standard python packages import inspect, itertools, logging, os, sqlite3, string, sys, time # ------------------------------------------------------ # # import sibling packages HERE!!! if not os.path.abspath( __file__ + "/../../../lib/iapyx/src" ) in sys.path : sys.path.append( os.path.abspath( __file__ + "/../../../lib/iapyx/src" ) ) from dedt import dedt, dedalusParser from utils import parseCommandLineInput, tools from evaluators import c4_evaluator # **************************************** # #################### # CLASS # ####################

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''' Understanding confidence intervals In this exercise, you'll develop your intuition for how various parameter values impact confidence intervals. Specifically, you will explore through the get_ci() function how changes widen or tighten the confidence interval. This is the function signature, where cl is the confidence level and sd is the standard deviation. ''' import pandas as pd import scipy.stats as sci def get_ci(value, cl, sd): loc = sci.norm.ppf(1 - cl/2) rng_val = sci.norm.cdf(loc - value/sd) lwr_bnd = value - rng_val upr_bnd = value + rng_val return_val = (lwr_bnd, upr_bnd) return(return_val) ''' INSTRUCTIONS 1/3 * Find the confidence interval with a value of 1, a confidence level of 0.975 and a standard deviation of 0.5. ''' # Compute and print the confidence interval confidence_interval = get_ci(1, 0.975, 0.5) print(confidence_interval) ''' INSTRUCTIONS 2/3 * Repeat the calculation, updating the confidence level to 0.95 and the standard deviation to 2. Leave the value as 1 ''' # Compute and print the confidence interval confidence_interval = get_ci(1, 0.95, 2) print(confidence_interval) ''' INSTRUCTIONS 3/3 * Finally, update your code such that the standard deviation is 0.001 while leaving the confidence level and value the same as the previous exercise part. Compare the three confidence intervals outputted. How do they seem to relate to the parameters used? ''' # Compute and print the confidence interval confidence_interval = get_ci(1, 0.95, 0.001) print(confidence_interval) ''' (0.9755040421682947, 1.0244959578317054) (0.6690506448818785, 1.3309493551181215) (1.0, 1.0) As our standard deviation decreases so too does the width of our confidence interval. Great work! '''

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import torch from torch.autograd import gradcheck from scipy.spatial import cKDTree from torch_flexconv import FlexMaxPool, flex_maxpool def test_flexmaxpool(): B = 16 p = torch.rand(B, 3, 1000) p_np = p.squeeze().numpy() idx_nn = [] for i in range(B): idx = cKDTree(p_np[i].T).query(p_np[i].T, k=12)[1] idx = torch.IntTensor(idx.T) idx_nn.append(idx) idx_nn = torch.stack(idx_nn, dim=0) net = torch.rand(B, 32, 1000) model = FlexMaxPool() out1 = model(net, idx_nn) net = net.cuda() idx_nn = idx_nn.cuda() model = model.cuda() out2 = model(net, idx_nn).cpu() print(((out1 - out2).abs()/out1.abs()).mean()) def test_flexmaxpool_grads(): B = 16 in_channels = 8 n_points = 20 p = torch.rand(B, 3, n_points) p_np = p.squeeze().numpy() idx_nn = [] for i in range(B): idx = cKDTree(p_np[i].T).query(p_np[i].T, k=3)[1] idx = torch.IntTensor(idx.T) idx_nn.append(idx) idx_nn = torch.stack(idx_nn, dim=0) feat = torch.rand(B, in_channels, n_points) # idx_nn = idx_nn.cuda() # feat = feat.cuda() feat = feat.to(torch.float64) p = p.to(torch.float64) feat.requires_grad_() gradcheck( flex_maxpool, [feat, idx_nn]) test_flexmaxpool() test_flexmaxpool_grads()

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import numpy as np import random import math #TODO documentation def apply2prefs(k_fun, p1, p2): (x1p, y1p), (x1n, y1n) = p1 (x2p, y2p), (x2n, y2n) = p2 res = 0. if y1p == y2p: res += k_fun(x1p, x2p) if y1n == y2n: res += k_fun(x1n, x2n) if y1p == y2n: res -= k_fun(x1p, x2n) if y1n == y2p: res -= k_fun(x1n, x2p) return res class GenK: def __init__(self): pass def get_random_kernel(self): pass def get_pref_kernel_function(self): pass def get_kernel_function(self): pass class GenKList(GenK): def __init__(self, k_list): self.kernel_list = k_list def __repr__(self): return "GenKList(n_kernel=%d)" %len(self.kernel_list) def get_random_kernel(self): return random.randint(0, len(self.kernel_list)-1) def get_pref_kernel_function(self, d): return lambda p1, p2: apply2prefs(self.get_kernel_function(d), p1, p2) def get_kernel_function(self, d): return self.kernel_list[d] class GenHPK(GenK): def __init__(self, min_deg=2, max_deg=2): self.min_deg = min_deg self.max_deg = max(max_deg, min_deg) def __repr__(self): return "GenHPK(dmin=%d, dmax=%d)" %(self.min_deg, self.max_deg) def get_random_kernel(self): return random.randint(self.min_deg, self.max_deg) def get_pref_kernel_function(self, degree): return lambda p1, p2: apply2prefs(self.get_kernel_function(degree), p1, p2) def get_kernel_function(self, degree): return lambda x,z: np.dot(x,z)**degree class GenRBFK(GenKList): def __init__(self, gamma_range): self.gamma_range = gamma_range def __repr__(self): return "GenRBFK(gamma_range=%s)" %(self.gamma_range) def get_random_kernel(self): return random.choice(self.gamma_range) def get_pref_kernel_function(self, gamma): return lambda p1, p2: apply2prefs(self.get_kernel_function(gamma), p1, p2) def get_kernel_function(self, gamma): return lambda x,z: math.exp(-gamma * np.linalg.norm(x-z)**2) #return lambda x,z: math.exp(-gamma * np.sum((x-z)**2))

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#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2018-6-14 17:02 # @Author : Jerry Wang # @Site : # @File : audit_shell.py # @Software: PyCharm import sys,os if __name__ == '__main__': os.environ.setdefault("DJANGO_SETTINGS_MODULE", "LuffyAudit.settings") import django django.setup() # 手动注册django所有的APP from audit.backend import user_interactive obj = user_interactive.UserShell(sys.argv) obj.start()

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from django.contrib import admin from .models import Profile, Question, Comment, Session, Record, Doctor, Inpatient # Register your models here. admin.site.register(Inpatient) admin.site.register(Profile) admin.site.register(Comment) admin.site.register(Question) admin.site.register(Session) admin.site.register(Record) admin.site.register(Doctor)

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# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from collections import namedtuple import grpc class _ClientInterceptorAsync( grpc.aio.UnaryUnaryClientInterceptor, grpc.aio.UnaryStreamClientInterceptor, grpc.aio.StreamUnaryClientInterceptor, grpc.aio.StreamStreamClientInterceptor ): def __init__(self, interceptor_async_function): self._fn = interceptor_async_function async def intercept_unary_unary(self, continuation, client_call_details, request): new_details, new_request_iterator, postprocess = await \ self._fn(client_call_details, iter((request,)), False, False) response = await continuation(new_details, next(new_request_iterator)) return (await postprocess(response)) if postprocess else response async def intercept_unary_stream(self, continuation, client_call_details, request): new_details, new_request_iterator, postprocess = await \ self._fn(client_call_details, iter((request,)), False, True) response_it = await continuation(new_details, next(new_request_iterator)) return (await postprocess(response_it)) if postprocess else response_it async def intercept_stream_unary(self, continuation, client_call_details, request_iterator): new_details, new_request_iterator, postprocess = await \ self._fn(client_call_details, request_iterator, True, False) response = await continuation(new_details, new_request_iterator) return (await postprocess(response)) if postprocess else response async def intercept_stream_stream(self, continuation, client_call_details, request_iterator): new_details, new_request_iterator, postprocess = await \ self._fn(client_call_details, request_iterator, True, True) response_it = await continuation(new_details, new_request_iterator) return (await postprocess(response_it)) if postprocess else response_it def create(intercept_async_call): return _ClientInterceptorAsync(intercept_async_call) ClientCallDetails = namedtuple('ClientCallDetails', ('method', 'timeout', 'metadata', 'credentials')) def header_adder_interceptor_async(header, value): async def intercept_async_call(client_call_details, request_iterator, request_streaming, response_streaming): metadata = list(client_call_details.metadata or ()) metadata.append((header, value)) client_call_details = ClientCallDetails( client_call_details.method, client_call_details.timeout, metadata, client_call_details.credentials, ) return client_call_details, request_iterator, None return create(intercept_async_call)

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# 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, Callable, Dict, Generic, Optional, TypeVar, Union import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod from azure.mgmt.core.exceptions import ARMErrorFormat from azure.mgmt.core.polling.async_arm_polling import AsyncARMPolling from ... import models as _models T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]] class ExchangeOperations: """ExchangeOperations async operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.reservations.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer) -> None: self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config async def _post_initial( self, body: "_models.ExchangeRequest", **kwargs ) -> Optional["_models.ExchangeOperationResultResponse"]: cls = kwargs.pop('cls', None) # type: ClsType[Optional["_models.ExchangeOperationResultResponse"]] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2020-10-01-preview" content_type = kwargs.pop("content_type", "application/json") accept = "application/json" # Construct URL url = self._post_initial.metadata['url'] # type: ignore # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Content-Type'] = self._serialize.header("content_type", content_type, 'str') header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') body_content_kwargs = {} # type: Dict[str, Any] body_content = self._serialize.body(body, 'ExchangeRequest') body_content_kwargs['content'] = body_content request = self._client.post(url, query_parameters, header_parameters, **body_content_kwargs) pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200, 202]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize(_models.Error, response) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) response_headers = {} deserialized = None if response.status_code == 200: deserialized = self._deserialize('ExchangeOperationResultResponse', pipeline_response) if response.status_code == 202: response_headers['Location']=self._deserialize('str', response.headers.get('Location')) response_headers['Retry-After']=self._deserialize('int', response.headers.get('Retry-After')) if cls: return cls(pipeline_response, deserialized, response_headers) return deserialized _post_initial.metadata = {'url': '/providers/Microsoft.Capacity/exchange'} # type: ignore async def begin_post( self, body: "_models.ExchangeRequest", **kwargs ) -> AsyncLROPoller["_models.ExchangeOperationResultResponse"]: """Exchange Reservation(s). Returns one or more ``Reservations`` in exchange for one or more ``Reservation`` purchases. :param body: Request containing the refunds and purchases that need to be executed. :type body: ~azure.mgmt.reservations.models.ExchangeRequest :keyword callable cls: A custom type or function that will be passed the direct response :keyword str continuation_token: A continuation token to restart a poller from a saved state. :keyword polling: True for ARMPolling, False for no polling, or a polling object for personal polling strategy :paramtype polling: bool or ~azure.core.polling.AsyncPollingMethod :keyword int polling_interval: Default waiting time between two polls for LRO operations if no Retry-After header is present. :return: An instance of AsyncLROPoller that returns either ExchangeOperationResultResponse or the result of cls(response) :rtype: ~azure.core.polling.AsyncLROPoller[~azure.mgmt.reservations.models.ExchangeOperationResultResponse] :raises ~azure.core.exceptions.HttpResponseError: """ polling = kwargs.pop('polling', True) # type: Union[bool, AsyncPollingMethod] cls = kwargs.pop('cls', None) # type: ClsType["_models.ExchangeOperationResultResponse"] lro_delay = kwargs.pop( 'polling_interval', self._config.polling_interval ) cont_token = kwargs.pop('continuation_token', None) # type: Optional[str] if cont_token is None: raw_result = await self._post_initial( body=body, cls=lambda x,y,z: x, **kwargs ) kwargs.pop('error_map', None) kwargs.pop('content_type', None) def get_long_running_output(pipeline_response): deserialized = self._deserialize('ExchangeOperationResultResponse', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized if polling is True: polling_method = AsyncARMPolling(lro_delay, lro_options={'final-state-via': 'location'}, **kwargs) elif polling is False: polling_method = AsyncNoPolling() else: polling_method = polling if cont_token: return AsyncLROPoller.from_continuation_token( polling_method=polling_method, continuation_token=cont_token, client=self._client, deserialization_callback=get_long_running_output ) else: return AsyncLROPoller(self._client, raw_result, get_long_running_output, polling_method) begin_post.metadata = {'url': '/providers/Microsoft.Capacity/exchange'} # type: ignore

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""" Distributed under the terms of the BSD 3-Clause License. The full license is in the file LICENSE, distributed with this software. Author: Jun Zhu <jun.zhu@xfel.eu> Copyright (C) European X-Ray Free-Electron Laser Facility GmbH. All rights reserved. """ from PyQt5.QtCore import pyqtSignal from PyQt5.QtWidgets import QFrame, QHBoxLayout, QPushButton class ScanButtonSet(QFrame): scan_toggled_sgn = pyqtSignal(bool) reset_sgn = pyqtSignal() def __init__(self, parent=None): super().__init__(parent=parent) self._scan_btn = QPushButton("Scan") self._pause_btn = QPushButton("Pause") self._pause_btn.setEnabled(False) self._reset_btn = QPushButton("Reset") self.initUI() self.initConnections() def initUI(self): layout = QHBoxLayout() layout.addWidget(self._scan_btn) layout.addWidget(self._pause_btn) layout.addWidget(self._reset_btn) self.setLayout(layout) def initConnections(self): self._scan_btn.clicked.connect(self._onStartScan) self._pause_btn.clicked.connect(self._onStopScan) self._reset_btn.clicked.connect(self.reset_sgn) def _onStartScan(self): self._scan_btn.setEnabled(False) self._pause_btn.setEnabled(True) self.scan_toggled_sgn.emit(True) def _onStopScan(self): self._pause_btn.setEnabled(False) self._scan_btn.setEnabled(True) self.scan_toggled_sgn.emit(False)

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#!/usr/bin/env python # -*- coding:utf-8 -*- __author__ = 'MFC' __time__ = '18/12/4 09:14' from datetime import timedelta from celery.schedules import crontab # broker_url消息中间件 BROKER_URL = 'amqp://guest:guestpwd@localhost:port/vhost_name' # with passwd, e.g. guestpwd is your password # BROKER_URL = 'redis://127.0.0.1:6379/1' # without passwd # BROKER_URL = 'redis://:xxx@127.0.0.1:6379/1' # with redis auth, e.g. xxx is your password # backend_url主要用于存储任务执行结果 CELERY_RESULT_BACKEND = 'redis://:xxx@127.0.0.1:6379/4' # localhost redis-server /usr/local/redis-4.0.1/etc/redis.conf CELERY_TIMEZONE = 'Asia/Shanghai' # 忽略返回任务结果 CELERY_IGNORE_RESULT = False # UTC # 导入指定的任务模块 CELERY_IMPORTS = ( 'celery_app.task1', 'celery_app.task2', 'celery_app.task_send_email', ) CELERYD_MAX_TASKS_PER_CHILD = 40 # 设置定时任务 task1 每10s执行一次， task2 每天17:30执行 CELERYBEAT_SCHEDULE = { 'task1': { 'task': 'celery_app.task1.add', 'schedule': timedelta(seconds=7), 'args': (2, 8) }, 'task2': { 'task': 'celery_app.task2.multiply', # 'schedule': crontab(hour=17, minute=21), 'schedule': timedelta(seconds=3), 'args': (4, 5) }, 'task3': { 'task': 'celery_app.task_send_email.send_email', # 'schedule': crontab(hour=17, minute=21), 'schedule': timedelta(seconds=5), }, } ## Run in terminal: celery beat -A celery_app -l INFO

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ GtkBox manager. """ import gi gi.require_version('Gtk', '3.0') import gi.repository.Gtk from ...util import log_func # from ...util import spc_func # from ...util import id_func from . import base_manager __version__ = (0, 0, 0, 1) class iqGtkBoxManager(base_manager.iqBaseManager): """ GtkBox manager. """ def clearGtkBox(self, box=None): """ Clear GtkBox. :param box: GtkBox object. :return: True/False. """ assert issubclass(box.__class__, gi.repository.Gtk.Box), u'GtkBox manager type error' try: for child in box.get_children(): box.remove(child) child.destroy() return True except: log_func.fatal(u'Error clear box <%s>' % box.get_name()) return False

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import torch class LSTM(torch.nn.quantizable.LSTM): r"""A quantized long short-term memory (LSTM). For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` Attributes: layers : instances of the `_LSTMLayer` .. note:: To access the weights and biases, you need to access them per layer. See examples in :class:`~torch.nn.quantizable.LSTM` Examples:: >>> custom_module_config = { ... 'float_to_observed_custom_module_class': { ... nn.LSTM: nn.quantizable.LSTM, ... }, ... 'observed_to_quantized_custom_module_class': { ... nn.quantizable.LSTM: nn.quantized.LSTM, ... } ... } >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) >>> tq.convert(model, convert_custom_module_class=custom_module_config) """ _FLOAT_MODULE = torch.nn.quantizable.LSTM def _get_name(self): return 'QuantizedLSTM' @classmethod def from_float(cls, *args, **kwargs): # The whole flow is float -> observed -> quantized # This class does observed -> quantized only raise NotImplementedError("It looks like you are trying to convert a " "non-observed LSTM module. Please, see " "the examples on quantizable LSTMs.") @classmethod def from_observed(cls, other): assert type(other) == cls._FLOAT_MODULE converted = torch.ao.quantization.convert(other, inplace=False, remove_qconfig=True) converted.__class__ = cls return converted

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''' -**make snake longer when eaten - FIGURE OUT HOW TO KNOW WHERE TO ADD THE NEXT BLOCK (MOVE LAST LOCATION TO BACK) -fix player_location lists, so that the list only has the location of the current snake location, not infinite list (done) - fix apple so disappers when you go over it (done) ''' import arcade import random # Set how many rows and columns we will have ROW_COUNT = 29 COLUMN_COUNT = 51 # This sets the WIDTH and HEIGHT of each grid location WIDTH = 20 HEIGHT = 20 # This sets the margin between each cell # and on the edges of the screen. MARGIN = 5 # Do the math to figure out our screen dimensions SCREEN_WIDTH = (WIDTH + MARGIN) * COLUMN_COUNT + MARGIN SCREEN_HEIGHT = (HEIGHT + MARGIN) * ROW_COUNT + MARGIN up = False down = False left = False right = False player_x_column = 5 player_y_row = 5 snake_body = [] apple_x = random.randint(0, COLUMN_COUNT) apple_y = random.randint(0, ROW_COUNT) apple_display = True grid_texture = arcade.load_texture("29x51_grid.jpg") def on_update(delta_time): snake_move() def on_draw(): arcade.start_render() grid_background() snake() apple() def grid_background(): arcade.draw_texture_rectangle(SCREEN_WIDTH//2, SCREEN_HEIGHT//2, grid_texture.width, grid_texture.height, grid_texture, 0) def snake_move(): global player_x, player_y, player_x_column, player_y_row if (0 <= player_x_column < COLUMN_COUNT) and (0 <= player_y_row < ROW_COUNT): if up: player_y_row += 1 elif down: player_y_row -= 1 elif right: player_x_column += 1 elif left: player_x_column -= 1 # for i in range (1): # player_loaction_x = player_loaction_x(player_x_column) # player_loaction_y.append(player_y_row) else: restart() # Player coordinates player_x = (MARGIN + WIDTH) * player_x_column + MARGIN + WIDTH // 2 player_y = (MARGIN + HEIGHT) * player_y_row + MARGIN + HEIGHT // 2 def restart(): global player_x_column, player_y_row global up, down, left, right player_x_column = 5 player_y_row = 5 snake_len = [] body = 1 up = False down = False left = False right = False print ("You died") def snake(): global player_x_column, player_y_row, apple_x, apple_y, snake_len, snake_body, snake_head arcade.draw_rectangle_filled(player_x , player_y, WIDTH, HEIGHT, arcade.color.BLUE) snake_head = [player_x_column, player_y_row] snake_len = [snake_head] # if (len(snake_body) > 1): # for num in range (1, len(snake_body): # snake_len[i]= snake_len[i-1] print("body", body) # for index in range (body - 1, 0, -1): # player_x_column = snake_len[index - 1][0] # player_y_row = snake_len[index - 1][1] # snake_len[index] for i in range (body): arcade.draw_rectangle_filled( (MARGIN + WIDTH) * snake_len[i][0] + MARGIN + WIDTH // 2, (MARGIN + HEIGHT) * snake_len[i][1] + MARGIN + HEIGHT // 2 , WIDTH, HEIGHT, arcade.color.BLUE) def apple(): global apple_x, apple_y, apple_x_coordinate, apple_y_coordinate, snake_body, snake_len global SPEED apple_x_coordinate = (MARGIN + WIDTH) * apple_x + MARGIN + WIDTH // 2 apple_y_coordinate = (MARGIN + HEIGHT) * apple_y + MARGIN + HEIGHT // 2 if (player_x_column == apple_x) and (player_y_row == apple_y): apple_display = False snake_body.append([10 + num, 10]) snake_head.append(snake_body) print ("hit") else: apple_display = True print (snake_len) if apple_display is True: arcade.draw_rectangle_filled(apple_x_coordinate, apple_y_coordinate, WIDTH, HEIGHT, arcade.color.RED) elif apple_display is False: apple_x = random.randint(0, COLUMN_COUNT) apple_y = random.randint(0, ROW_COUNT) apple_x_coordinate = (MARGIN + WIDTH) * apple_x + MARGIN + WIDTH // 2 apple_y_coordinate = (MARGIN + HEIGHT) * apple_y + MARGIN + HEIGHT // 2 apple_display == True def on_key_press(key, modifiers): global up, down, left, right if key == arcade.key.W: up = True down = False right = False left = False elif key == arcade.key.S: down = True up = False right = False left = False elif key == arcade.key.A: left = True up = False down = False right = False elif key == arcade.key.D: right = True up = False down = False left = False def on_key_release(key, modifiers): pass def on_mouse_press(x, y, button, modifiers): pass def setup(): global grid # global player_x_column, apple_x, player_y_row, apple_y, SPEED # SPEED = 10 # if (player_x_column == apple_x) and (player_y_row == apple_y): # SPEED += 5 arcade.open_window(SCREEN_WIDTH, SCREEN_HEIGHT, "snake") arcade.set_background_color(arcade.color.BLACK) arcade.schedule(on_update, 1/10) # Override arcade window methods window = arcade.get_window() window.on_draw = on_draw window.on_key_press = on_key_press window.on_key_release = on_key_release window.on_mouse_press = on_mouse_press arcade.run() if __name__ == '__main__': setup()

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clementina1023@gmail.com

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/bc19-scaffold/bots/34.TacticsImprovedBot/pilgrims.py

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import constants import utility import pilgrims_utility import movement import check def pilgrim(robot): if robot.pilgrim_mine_ownership == None: robot.steps_to_mine += 1 # communications.self_communicate_loop(robot) # robot.log("Pilgrims current move destination is " + robot.current_move_destination) carry_karb = robot.me.karbonite carry_fuel = robot.me.fuel # The pilgrim is on a mine and wants to deposit resources if carry_fuel > 80 or carry_karb > 18: # robot.log("Nearing capacity") return pilgrim_full(robot) # The pilgrim checks if it has a mine on it's current position pilgrim_is_mining = pilgrim_mine(robot) if pilgrim_is_mining !=0 and robot.fuel > 1 and robot.actual_round_number != None: if robot.actual_round_number >= 6: if robot.piligrim_did_i_shout_my_x_cord == False: robot.castle_talk(robot.me.x + 64) robot.piligrim_did_i_shout_my_x_cord = True else: if robot.piligrim_did_i_shout_my_y_cord == False: robot.castle_talk(robot.me.y + 64) robot.piligrim_did_i_shout_my_y_cord = True return pilgrim_is_mining # Receive signal from castle on which mine to go to if robot.step == 0: pilgrims_utility.receive_initial_signal(robot) # Move Section pilgrim_is_moving = pilgrim_move(robot) if pilgrim_is_moving !=0 and robot.fuel > 30: # robot.log(pilgrim_is_moving) return pilgrim_is_moving def pilgrim_move(robot): # Emergency case, allows pilgrims to mine if robot.fuel <= 2: return 0 pos_x = robot.me.x pos_y = robot.me.y passable_map, occupied_map, karb_map, fuel_map = utility.get_all_maps(robot) random_directions = utility.random_cells_around() # May change for impossible resources # pilgrims_utility.did_pilgrim_burn_out(robot) # Capture and start mining any resource if more than 50 turns since creation and no mine # TODO - Improve this code snippet to mine, if in visible region and empty # if robot.me.turn > constants.pilgrim_will_scavenge_closeby_mines_after_turns: #and robot.me.turn < constants.pilgrim_will_scavenge_closeby_mines_before_turns: # for direction in random_directions: # if (not utility.is_cell_occupied(occupied_map, pos_x + direction[1], pos_y + direction[0])) and utility.is_cell_resourceful(karb_map, fuel_map, pos_x + direction[1], pos_y + direction[0]): # robot.current_move_destination = None # utility.default_movement_variables(robot) # return robot.move(direction[1], direction[0]) # TODO - Make into scout if too old, which will scout enemy bases # If the mine is already occupied # pilgrims_utility.is_pilgrim_scavenging(robot) # Just move if not movement.is_completely_surrounded(robot): if robot.current_move_destination == None and robot.pilgrim_mine_ownership != None: robot.current_move_destination = robot.pilgrim_mine_ownership move_command = movement.move_to_destination(robot) if move_command != None: return move_command # Random Movement when not enough time # for direction in random_directions: # if not utility.is_cell_occupied(occupied_map, pos_x + direction[1], pos_y + direction[0]) and passable_map[pos_y + direction[0]][pos_x + direction[1]] == 1: # robot.mov_path_between_location_and_destination = None # return robot.move(direction[1], direction[0]) return 0 def pilgrim_mine(robot): pos_x = robot.me.x pos_y = robot.me.y karb_map = robot.get_karbonite_map() fuel_map = robot.get_fuel_map() if utility.is_cell_resourceful(karb_map, fuel_map, pos_x, pos_y): robot.signal(0, 0) if utility.is_cell_fuel(fuel_map, pos_x, pos_y): robot.karb_miner = False robot.fuel_miner = True robot.castle_talk(6) elif utility.is_cell_karbonite(karb_map, pos_x, pos_y): robot.karb_miner = True robot.fuel_miner = False robot.castle_talk(7) # TRAVIS CHECK MINE 1 robot.pilgrim_mine_ownership = (pos_x, pos_y) return check.mine_check(robot, 1) else: return 0 def pilgrim_full(robot): # If we have adjacent castle/church or haven't reached the convoy age end pilgrim_give_or_convoy = pilgrims_utility.give_or_mine(robot) if pilgrim_give_or_convoy != 0 and robot.fuel > 4: return pilgrim_give_or_convoy # FIXME - Make churches not be built if castle/other church is in reasonable travel range if robot.karbonite > 50 and robot.fuel > 200: return pilgrims_utility.make_church(robot) return None

[ "f2015845@hyderabad.bits-pilani.ac.in" ]

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#!/usr/bin/env python import ROOT as r import optparse import tool r.gROOT.SetBatch(True) # to suppress canvas pop-outs def KSTest(ifile, ofile, name): f = r.TFile(ifile) testTree = f.Get("TestTree") trainTree = f.Get("TrainTree") nBins = 20 nBins2 = 100000 xMin = -1.0 xMax = 1.0 BDT_Sig_Train = r.TH1F('BDT_Sig_Train', 'BDT_Sig_Train', nBins, xMin, xMax) BDT_Sig_Test = r.TH1F('BDT_Sig_Test', 'Overtraining Check (%s)' %name[:name.find('_')], nBins, xMin, xMax) BDT_Bkg_Train = r.TH1F('BDT_Bkg_Train', 'BDT_Bkg_Train', nBins, xMin, xMax) BDT_Bkg_Test = r.TH1F('BDT_Bkg_Test', 'BDT_Bkg_Test', nBins, xMin, xMax) BDT_Sig_Train_4KS = r.TH1F('BDT_Sig_Train_4KS', 'BDT_Sig_Train_4KS', nBins2, xMin, xMax) BDT_Sig_Test_4KS = r.TH1F('BDT_Sig_Test_4KS', 'BDT_Sig_Test_4KS', nBins2, xMin, xMax) BDT_Bkg_Train_4KS = r.TH1F('BDT_Bkg_Train_4KS', 'BDT_Bkg_Train_4KS', nBins2, xMin, xMax) BDT_Bkg_Test_4KS = r.TH1F('BDT_Bkg_Test_4KS', 'BDT_Bkg_Test_4KS', nBins2, xMin, xMax) totalTest = testTree.GetEntries() for i in range(totalTest): testTree.GetEntry(i) if testTree.className == "Signal": BDT_Sig_Test.Fill(testTree.BDT, testTree.weight) BDT_Sig_Test_4KS.Fill(testTree.BDT, testTree.weight) else: BDT_Bkg_Test.Fill(testTree.BDT, testTree.weight) BDT_Bkg_Test_4KS.Fill(testTree.BDT, testTree.weight) totalTrain = trainTree.GetEntries() for i in range(totalTrain): trainTree.GetEntry(i) if trainTree.className == "Signal": BDT_Sig_Train.Fill(trainTree.BDT, trainTree.weight) BDT_Sig_Train_4KS.Fill(trainTree.BDT, trainTree.weight) else: BDT_Bkg_Train.Fill(trainTree.BDT, trainTree.weight) BDT_Bkg_Train_4KS.Fill(trainTree.BDT, trainTree.weight) BDT_Bkg_Train.Sumw2() BDT_Sig_Train.Sumw2() sigKS = BDT_Sig_Test_4KS.KolmogorovTest(BDT_Sig_Train_4KS) bkgKS = BDT_Bkg_Test_4KS.KolmogorovTest(BDT_Bkg_Train_4KS) print 'signal: %.4f' %sigKS print 'background: %.4f' %bkgKS BDT_Bkg_Train.Scale(1/BDT_Bkg_Train.Integral()) BDT_Bkg_Train.SetMarkerColor(r.kRed) BDT_Bkg_Train.SetMarkerStyle(21) BDT_Bkg_Test.SetLineColor(r.kRed) BDT_Bkg_Test.SetFillColor(r.kRed) BDT_Bkg_Test.SetFillStyle(3354) BDT_Bkg_Test.Scale(1/BDT_Bkg_Test.Integral()) BDT_Sig_Train.Scale(1/BDT_Sig_Train.Integral()) BDT_Sig_Train.SetMarkerColor(r.kBlue) BDT_Sig_Train.SetMarkerStyle(21) BDT_Sig_Test.SetLineColor(r.kBlue) BDT_Sig_Test.SetFillColor(r.kBlue) BDT_Sig_Test.SetFillStyle(3001) BDT_Sig_Test.Scale(1/BDT_Sig_Test.Integral()) legendHistos1 = [] legendHistos1.append((BDT_Bkg_Test, 'bkg test')) legendHistos1.append((BDT_Bkg_Train, 'bkg train')) # legendHistos1.append((BDT_Bkg_Train, 'KS: %0.3f' %bkgKS)) legendHistos2 = [] legendHistos2.append((BDT_Sig_Test, 'sig test')) legendHistos2.append((BDT_Sig_Train, 'sig train')) # legendHistos2.append((BDT_Sig_Train, 'KS: %0.3f' %sigKS)) l1 = tool.setMyLegend(lPosition=(0.2, 0.67, 0.5, 0.82), lHistList=legendHistos1) l2 = tool.setMyLegend(lPosition=(0.6, 0.67, 0.9, 0.82), lHistList=legendHistos2) r.gStyle.SetOptStat(0) c = r.TCanvas("c","Test", 800, 600) BDT_Sig_Test.Draw() BDT_Sig_Test.GetXaxis().SetTitle("BDT") BDT_Sig_Test.SetMaximum(0.5) BDT_Sig_Train.Draw('sameE1P') BDT_Bkg_Test.Draw('same') BDT_Bkg_Train.Draw('sameE1P') l1.Draw('same') l2.Draw('same') c.Print('%s.pdf' %ofile) massPoints = ['260','270','280','290','300','310','320','330','340','350'] # massPoints = ['260','300','350'] nTreesList = ['150'] for nTrees in nTreesList: for iMass in massPoints: postFix = '_7_n%s_mJJ' %nTrees KSTest('/nfs_scratch/zmao/TMVA/TMVA%s%s.root' %(iMass,postFix), '/nfs_scratch/zmao/TMVA/pdf/TMVA%s%s' %(iMass,postFix), 'H2hh%s_n%s' %(iMass, nTrees))

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zaixing.mao@cern.ch

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dlunch/uotp

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refs/heads/master

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2017-12-23T11:21:42

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from struct import unpack from .base import Packet, Opcode class TimeRequest(Packet): OPCODE = Opcode.Time SIMPLE = True @classmethod def _encode_payload(cls, data: dict) -> bytes: return b'' @classmethod def _decode_payload(cls, payload: bytes) -> dict: time, = unpack("!I", payload) return { 'time': time }

[ "devunt@gmail.com" ]

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/src/filingcabinet/migrations/0019_auto_20210323_1404.py

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okfde/django-filingcabinet

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# Generated by Django 3.1.6 on 2021-03-23 13:04 import uuid import django.db.models.deletion from django.conf import settings from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.FILINGCABINET_DOCUMENT_MODEL), ("filingcabinet", "0018_auto_20200622_1302"), ] operations = [ migrations.AddField( model_name="document", name="listed", field=models.BooleanField(default=True), ), migrations.AddField( model_name="documentcollection", name="listed", field=models.BooleanField(default=True), ), migrations.AddField( model_name="documentcollection", name="uid", field=models.UUIDField(default=uuid.uuid4, editable=False), ), migrations.AlterField( model_name="page", name="document", field=models.ForeignKey( on_delete=django.db.models.deletion.CASCADE, related_name="pages", to=settings.FILINGCABINET_DOCUMENT_MODEL, ), ), ]

[ "mail@stefanwehrmeyer.com" ]

mail@stefanwehrmeyer.com

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/visualization_data.py

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[]

no_license

Tulin2010/LSTM_GoogleClusterTraceData

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refs/heads/master

2023-03-17T13:06:17.392797

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import pandas as pd import matplotlib.pyplot as plt from pandas import read_csv dataset = read_csv('/home/nguyen/learnRNNs/international-airline-passengers.csv', usecols=[1], engine='python', skipfooter=3) plt.plot(dataset) plt.show() # print a

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thangbk2209@gmail.com

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[ "oscar.salvador@pharmadus.com" ]

oscar.salvador@pharmadus.com

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MIT

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# 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 .sub_resource_py3 import SubResource class ApplicationGatewayUrlPathMap(SubResource): """UrlPathMaps give a url path to the backend mapping information for PathBasedRouting. :param id: Resource ID. :type id: str :param default_backend_address_pool: Default backend address pool resource of URL path map. :type default_backend_address_pool: ~azure.mgmt.network.v2017_06_01.models.SubResource :param default_backend_http_settings: Default backend http settings resource of URL path map. :type default_backend_http_settings: ~azure.mgmt.network.v2017_06_01.models.SubResource :param default_redirect_configuration: Default redirect configuration resource of URL path map. :type default_redirect_configuration: ~azure.mgmt.network.v2017_06_01.models.SubResource :param path_rules: Path rule of URL path map resource. :type path_rules: list[~azure.mgmt.network.v2017_06_01.models.ApplicationGatewayPathRule] :param provisioning_state: Provisioning state of the backend http settings resource. Possible values are: 'Updating', 'Deleting', and 'Failed'. :type provisioning_state: str :param name: Name of the resource that is unique within a resource group. This name can be used to access the resource. :type name: str :param etag: A unique read-only string that changes whenever the resource is updated. :type etag: str :param type: Type of the resource. :type type: str """ _attribute_map = { 'id': {'key': 'id', 'type': 'str'}, 'default_backend_address_pool': {'key': 'properties.defaultBackendAddressPool', 'type': 'SubResource'}, 'default_backend_http_settings': {'key': 'properties.defaultBackendHttpSettings', 'type': 'SubResource'}, 'default_redirect_configuration': {'key': 'properties.defaultRedirectConfiguration', 'type': 'SubResource'}, 'path_rules': {'key': 'properties.pathRules', 'type': '[ApplicationGatewayPathRule]'}, 'provisioning_state': {'key': 'properties.provisioningState', 'type': 'str'}, 'name': {'key': 'name', 'type': 'str'}, 'etag': {'key': 'etag', 'type': 'str'}, 'type': {'key': 'type', 'type': 'str'}, } def __init__(self, *, id: str=None, default_backend_address_pool=None, default_backend_http_settings=None, default_redirect_configuration=None, path_rules=None, provisioning_state: str=None, name: str=None, etag: str=None, type: str=None, **kwargs) -> None: super(ApplicationGatewayUrlPathMap, self).__init__(id=id, **kwargs) self.default_backend_address_pool = default_backend_address_pool self.default_backend_http_settings = default_backend_http_settings self.default_redirect_configuration = default_redirect_configuration self.path_rules = path_rules self.provisioning_state = provisioning_state self.name = name self.etag = etag self.type = type

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/functional/Components/Clients/Clients_POST/test_TC_43120_Clients_POST_Height_Gt.py

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[]

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muktabehera/QE

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refs/heads/master

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py

# -*- coding: UTF-8 -*- """PFE Component Tests - Clients. * TC-43120 - Clients POST: Verify that user is able to add source constraint rule with specific rule for parameter 'Height>GT(Greater Than) using request POST '/clients/'. Equivalent test CURL command: curl -H "Host: <client_host>" -H "Authorization: Bearer <valid_token>" -X POST -d @<JSON_data_file> -H "Content-Type: application/json" "<PF_host>://<client_host>/clients" Same, with test data: curl -H "Host: <client_host>" -H "Authorization: Bearer <valid_token>" -X POST -d @<JSON_data_file> -H "Content-Type: application/json" "<PF_host>://<client_host>/clients" JSON data sent to PathFinder in this test: {'id': 'sourceRuleHeightGT', 'matchingRule': {'groups': [], 'operator': 'ALL', 'rules': []}, 'name': 'POST: Client with Source Rule Height GT', 'sourceSelectionRule': [{'groups': [], 'operator': 'ALL', 'rules': [{'contextField': 'heightPx', 'contextFieldKey': None, 'contextFieldType': 'String', 'expressionType': 'Single', 'matchValue': 1000, 'operator': 'GT'}]}]} """ import pytest from qe_common import * logger = init_logger() @pytest.mark.components @pytest.allure.story('Clients') @pytest.allure.feature('POST') class Test_PFE_Components(object): """PFE Clients test cases.""" @pytest.allure.link('https://jira.qumu.com/browse/TC-43120') @pytest.mark.Clients @pytest.mark.POST def test_TC_43120_POST_Clients_Height_Gt(self, context): """TC-43120 - Clients-POST Verify that user is able to add source constraint rule with specific rule for parameter 'Height>GT(Greater Than) using request POST '/clients/'.""" # Define a test step with pytest.allure.step("""Verify that user is able to add source constraint rule with specific rule for parameter 'Height>GT(Greater Than) using request POST '/clients/'."""): # Test case configuration clientDetails = context.sc.ClientDetails( id='sourceRuleHeightGT', matchingRule={'operator': 'ALL', 'rules': [], 'groups': []}, name='POST: Client with Source Rule Height GT', sourceSelectionRule=[{ 'operator': 'ALL', 'rules': [{ 'expressionType': 'Single', 'contextField': 'heightPx', 'operator': 'GT', 'contextFieldType': 'String', 'matchValue': 1000, 'contextFieldKey': None }], 'groups': [] }]) # createEntity the Clients. # The `check` call validates return code # and some of the swagger schema. # Most schema checks are disabled. response = check( context.cl.Clients.createEntity( body=clientDetails ) )

[ "mbehera@qumu.com" ]

mbehera@qumu.com

1ab116b1625ef9856f2198a6637bb253a87c266b

25f4e894beced05eb15708ac2314d72e679fa069

/google/google/spiders/GoogleSpider.py

7358c7cbfd2aefd2703b5e751cd026ebcac532c8

[]

no_license

pyscrape/web-scraping-projects

4e6059daaa2f1092e2c8f1ee4a4ad1e422b21096

f1e77b151de256e1a5e83099859635edc2f5826a

refs/heads/master

2021-06-01T15:02:42.548264

2016-08-24T07:27:11

null

0

null

UTF-8

Python

false

2,883

py

import scrapy from scrapy.contrib.spiders import CrawlSpider, Rule from scrapy.contrib.linkextractors.lxmlhtml import LxmlLinkExtractor from google.items import GoogleItem from scrapy.conf import settings def parsing_rating(line): if len(line)>0: return line[0][line[0].find("alt"):] else: return "" class GoogleSpider(CrawlSpider): name = 'google' allowed_domains = ['google.com'] # rules = (Rule(LxmlLinkExtractor(allow=(r'\/([A-Z])([A-Z0-9]{9})'),deny=('')),callback='parse_item'),Rule(LxmlLinkExtractor(allow=(''))),),) # rules = (Rule(LxmlLinkExtractor(allow=(r'https://www.tripadvisor.com/Attraction_Review.*')),callback='parse_trip', process_links='process_links'),) rules = (Rule(LxmlLinkExtractor(allow=(r'https://www.google.com/.*')),callback='parse_search'),Rule(LxmlLinkExtractor(allow=(''))),follow=False) def __init__(self,*args, **kwargs): super(TripadvisorSpider, self).__init__(*args, **kwargs) start_url='https://www.tripadvisor.com/Attractions-g187337-Activities-Frankfurt_Hesse.html' # start_url='https://www.tripadvisor.com/' self.start_urls = [start_url] def parse_trip(self,response): item = GoogleItem() print "\n\n---------------------START-----------------------" print response.url # print response.xpath('//a/@href').extract() # try: item['name'] = response.xpath('//*[@id="HEADING"]/text()').extract()[0].encode('ascii','ignore') # item['rating'] = parsing_rating(response.xpath('//*[@id="HEADING_GROUP"]/div/div[2]/div[1]/div/span/img').extract()) # item['neighborhood'] = response.xpath('//*[@id="MAP_AND_LISTING"]/div[2]/div/div[2]/div/div[1]/div/address/span/span').extract() # item['classification'] = response.xpath('//*[@id="HEADING_GROUP"]/div/div[3]/div[2]/div').extract() item['url'] = response.url # item['price'] = response.xpath('//*[@id="ABOVE_THE_FOLD"]/div[2]/div[1]/div/div[2]/div/div[1]/div/div[2]/div[1]/text()').extract() # item['hours'] = response.xpath('//*[@id="MAP_AND_LISTING"]/div[2]/div/div[2]/div/div[4]/div/div[2]/div').extract() # item['desc'] = response.xpath('//*[@id="OVERLAY_CONTENTS"]/div/p/text()').extract() # item['desc'] = [desc.encode('ascii','ignore') for desc in response.xpath('//*[@id="feature-bullets"]/ul/li/span/text()').extract() ] # usernames = response.xpath('//*[@class="username mo"]').extract() # reviews = response.xpath('//*[@class="partial_entry"]/text()').extract() # item['reviews'] = zip(usernames,reviews) print "\n\n---------------------------------------------------" print(item) # except: # print('Not a product!') # item = None yield item def process_links(self,links): print "\n LINKS" links_list = [] for i in links: if "https://www.tripadvisor.com/Attraction_Review" in i.url: links_list.append(i) print i.url return links_list def dummy(self,response): print(str(response.url))

[ "mymamyma@gmail.com" ]

mymamyma@gmail.com

9e15da608c57204097c2be6bfac95cf84b72f297

8b71fdd80be5f22659cfb135019f5fd968a3cb77

/supervised_learning/0x01-classification/19-deep_neural_network.py

5e9cf4bd693450e09c970d9f96ab70baf7c24890

[]

no_license

KamalTaleb/holbertonschool-machine_learning

357e1c6bfcffa6672e12a3d518846b2a96747148

242b449b3a7a4051270ca32a22866a884754d141

refs/heads/master

2023-03-29T07:24:44.113412

2021-04-08T15:45:16

320,596,666

0

null

2020-12-11T14:41:48

2020-12-11T14:29:03

Python

UTF-8

Python

false

3,177

py

#!/usr/bin/env python3 """Contains the DeepNeuralNetwork class""" import numpy as np class DeepNeuralNetwork: """ DeepNeuralNetwork class defines a deep neural network performing binary classification: """ def __init__(self, nx, layers): """ Class constructor :param nx: the number of input features :param layers: list representing the number of nodes in each layer of the network """ if not isinstance(nx, int): raise TypeError("nx must be an integer") if nx < 1: raise ValueError("nx must be a positive integer") if not isinstance(layers, list): raise TypeError("layers must be a list of positive integers") if len(layers) == 0: raise TypeError('layers must be a list of positive integers') self.nx = nx self.layers = layers self.__L = len(layers) self.__cache = {} self.__weights = {} for i in range(self.L): if not isinstance(layers[i], int) or layers[i] < 1: raise TypeError("layers must be a list of positive integers") W_key = "W{}".format(i + 1) b_key = "b{}".format(i + 1) self.weights[b_key] = np.zeros((layers[i], 1)) if i == 0: f = np.sqrt(2 / nx) self.__weights['W1'] = np.random.randn(layers[i], nx) * f else: f = np.sqrt(2 / layers[i - 1]) h = np.random.randn(layers[i], layers[i - 1]) * f self.__weights[W_key] = h @property def L(self): """property to retrieve L""" return self.__L @property def cache(self): """property to retrieve b1""" return self.__cache @property def weights(self): """property to retrieve A1""" return self.__weights def forward_prop(self, X): """ Calculates the forward propagation of the neural network :param X: a numpy.ndarray with shape (nx, m) that contains the input data :return: the output of the neural network and the cache, respectively """ self.__cache['A0'] = X for l in range(self.__L): W_key = "W{}".format(l + 1) b_key = "b{}".format(l + 1) A_key_prev = "A{}".format(l) A_key_forw = "A{}".format(l + 1) Z = np.matmul(self.__weights[W_key], self.__cache[A_key_prev]) \ + self.__weights[b_key] self.__cache[A_key_forw] = 1 / (1 + np.exp(-Z)) return self.__cache[A_key_forw], self.__cache def cost(self, Y, A): """ Calculates the cost of the model using logistic regression :param Y: numpy.ndarray with shape (1, m) that contains the correct labels for the input data :param A: numpy.ndarray with shape (1, m) containing the activated output of the neuron for each example :return: the cost """ cost = -np.sum((Y * np.log(A)) + ((1 - Y) * np.log(1.0000001 - A))) / Y.shape[1] return cost

[ "kamal.talebb@gmail.com" ]

kamal.talebb@gmail.com

b94058827cb1372d534468bbbd322a04a99f959b

ebc7607785e8bcd6825df9e8daccd38adc26ba7b

/python/leetcode/dfs/dfs.py

73df417ba9abc9d12885a4e0fbd4b12e54d6ba30

[]

no_license

galid1/Algorithm

18d1b72b0d5225f99b193e8892d8b513a853d53a

5bd69e73332f4dd61656ccdecd59c40a2fedb4b2

refs/heads/master

2022-02-12T07:38:14.032073

2022-02-05T08:34:46

179,923,655

3

0

null

2019-06-14T07:18:14

2019-04-07T05:49:06

Python

UTF-8

Python

false

920

py

import sys # stack을 이용한 구현 # def dfs(g, start): # for key in g.keys(): # g[key] = sorted(g[key], reverse=True) # stack = [] # stack.append(start) # # visited = set() # while stack: # cur = stack.pop() # if cur in visited: # continue # # 방문 처리 및 출력 # print(cur) # visited.add(cur) # # for link in g[cur]: # stack.append(link) def dfs(g, vertex, visited): print(vertex, end=' ') visited.add(vertex) for next_vertex in g[vertex]: if next_vertex not in visited: dfs(g, next_vertex, visited) n, m, s = map(int, sys.stdin.readline().strip().split(" ")) g = {i: [] for i in range(1, n+1)} for _ in range(m): k, v = map(int, sys.stdin.readline().strip().split(" ")) g[k].append(v) g[v].append(k) for key in g.keys(): g[key].sort() dfs(g, s, set())

[ "galid1@naver.com" ]

galid1@naver.com

d508c9134e55dfefde90ff6147e63c22f1ef4da6

817c58b0d73d20638ea410512aa61b6b8837cf62

/backend/backend/api_urls.py

9a86a93b978ca7dfe66526f69f4c88b62bccf19d

[ "MIT" ]

permissive

ProjetoALES/ales-website

d64eaef437ba6da1df7d810b8f495ad141d41464

9dc5b460f5e780a1221d0ed5071043f088082395

refs/heads/master

2022-01-25T04:15:59.302899

2020-02-25T05:15:10

242,913,529

0

MIT

2022-01-06T22:42:46

2020-02-25T04:57:07

Vue

UTF-8

Python

false

403

py

from django.urls import include, path from .views import CurrentUserViewset from student import api_urls as student_urls from .router import base_router base_router.register("me", CurrentUserViewset, basename="me") app_name = "api" urlpatterns = [ path( "", include((student_urls.urlpatterns, student_urls.app_name), namespace="student"), ) ] urlpatterns += base_router.urls

[ "gustavomaronato@gmail.com" ]

gustavomaronato@gmail.com

95293ca379d2cc6ee06bbdf758e30368f3d7f4e6

6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4

/zDei9LFWkX9d7wXyb_17.py

4d91f8876a0ba580b6c2e2347c216c95b10964bd

[]

no_license

daniel-reich/ubiquitous-fiesta

26e80f0082f8589e51d359ce7953117a3da7d38c

9af2700dbe59284f5697e612491499841a6c126f

refs/heads/master

2023-04-05T06:40:37.328213

2021-04-06T20:17:44

355,318,759

0

null

UTF-8

Python

false

197

py

def malthusian(food_growth, pop_mult): year=0 pop=100 food_prod = 100 while True: food_prod+=food_growth pop*=pop_mult year+=1 if pop>food_prod: break return year

[ "daniel.reich@danielreichs-MacBook-Pro.local" ]

daniel.reich@danielreichs-MacBook-Pro.local

15dc7407da6affbb37c0dd12b9349f1ca91bba81

b2edef9270dfe69986c1f268d4bad7c4b1a54315

/329.longest-increasing-path-in-a-matrix.py

cf326f9a2ae3e6f0ab5d2ed9fd1dbb47b1428f78

[]

no_license

mrgrant/LeetCode

9167f29462a072df4932201834073043cba99366

82132065ae1b4964a1e0ef913912f382471f4eb5

refs/heads/master

2021-12-03T00:16:42.070167

2021-11-30T15:02:29

143,361,502

0

null

UTF-8

Python

false

2,240

py

# # @lc app=leetcode id=329 lang=python # # [329] Longest Increasing Path in a Matrix # # @lc code=start import collections class Solution(object): def longestIncreasingPath(self, matrix): """ :type matrix: List[List[int]] :rtype: int """ # dfs solution # m = len(matrix) # n = len(matrix[0]) # dp = [[0 for _ in range(n)] for _ in range(m)] # def dfs(i, j): # if not dp[i][j]: # val = matrix[i][j] # dp[i][j] = 1 + max( # dfs(i-1,j) if i > 0 and matrix[i-1][j] < val else 0, # dfs(i+1,j) if i < m - 1 and matrix[i+1][j] < val else 0, # dfs(i,j-1) if j > 0 and matrix[i][j-1] < val else 0, # dfs(i,j+1) if j < n - 1 and matrix[i][j+1] < val else 0, # ) # return dp[i][j] # for i in range(m): # for j in range(n): # dfs(i, j) # return max(dp[i][j] for i in range(m) for j in range(n)) # bfs with topological sort solution m = len(matrix) n = len(matrix[0]) dir = [(1, 0), (-1, 0), (0, 1), (0, -1)] indeg = {} q = collections.deque() for i in range(m): for j in range(n): cnt = 0 for dx, dy in dir: mx = i + dx my = j + dy if 0 <= mx < m and 0 <= my < n and matrix[mx][my] < matrix[i][j]: cnt += 1 indeg[(i, j)] = cnt if cnt == 0: q.append((i, j)) step = 0 while q: size = len(q) for _ in range(size): x, y = q.popleft() for dx, dy in dir: mx = x + dx my = y + dy if 0 <= mx < m and 0 <= my < n and matrix[mx][my] > matrix[x][y] and (mx, my) in indeg: indeg[(mx, my)] -= 1 if indeg[(mx, my)] == 0: q.append((mx, my)) step += 1 return step # @lc code=end

[ "mrgrantcy@gmail.com" ]

mrgrantcy@gmail.com

fc65a1a0c364aa804a4aa0ff883d6b6e9a1b0133

2279568acd5c7182ea4d287d20cd208b10c945a2

/django/django_intro/form_submission/POST_form_submission/views.py

6e7bdc0b8c7af63776f3aafbe8e7e54a0eb7dcd8

[]

no_license

quangnguyen17/Python

fbc5cec0eb51e48c964022e1bd45fb585d2b60ec

1920f757c5381480fc42f90946651aa0363fcaff

refs/heads/master

2020-12-27T08:58:51.058504

2020-02-10T21:42:45

2020-02-10T21:43:12

237,815,684

1

0

null

UTF-8

Python

false

367

py

from django.shortcuts import render, redirect # Create your views here. def index(request): return render(request, "index.html") def create_user(request): request.session['name'] = request.POST['name'] request.session['email'] = request.POST['email'] return redirect("/success") def success(request): return render(request, "success.html")

[ "wan15112001@gmail.com" ]

wan15112001@gmail.com

3fa906d66b83757fe642d3e423f6b479a7ee5ff3

796344a0ecccb0c979348baef8b80a5146ba5ddd

/mysite/settings.py

bf17080ab7a8e8652cc8a877fd0148fa785c140d

[]

no_license

emantovanelli/my-first-blog

d5f2d2af6373196172acbefbbf090f80296b5d99

6c87da8db54576111976dc57109ca096fd694363

refs/heads/master

2021-01-10T12:36:48.237270

2016-01-04T13:52:34

48,194,425

1

0

null

UTF-8

Python

false

2,711

py

""" Django settings for mysite project. Generated by 'django-admin startproject' using Django 1.8.5. For more information on this file, see https://docs.djangoproject.com/en/1.8/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.8/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.8/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'u_&c4%-u=vm)^hsyx-30-hf9z#oa_@db=s89od@1_t^5c=x)1e' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = ( 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'blog', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'django.middleware.security.SecurityMiddleware', ) ROOT_URLCONF = 'mysite.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'mysite.wsgi.application' # Database # https://docs.djangoproject.com/en/1.8/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Internationalization # https://docs.djangoproject.com/en/1.8/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'America/Sao_Paulo' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.8/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = os.path.join(BASE_DIR, 'static')

[ "you@example.com" ]

you@example.com

e21df57f20a42deffed822307c1bf7b5614cf75f

0274f2c465f110598456624581f569331221068b

/impl/gps/gps_operations.py

64a7a924c36f2bd4394f6ff191375c071b57d962

[]

no_license

bluecube/thesis

63e745076c86a3122e9c3d7ff42ff22e32921860

588db206e64de9b681372fea9a70d3fa2aa598df

refs/heads/master

2016-09-06T00:01:03.840006

2013-05-27T09:36:51

1,376,241

2

0

null

UTF-8

Python

false

6,060

py

from __future__ import unicode_literals import collections import logging from . import sirf from . import sirf_messages if bytes == str: # This branch is here for python 2.x and to avoid # the cost of calls to sirf.bytes_to_message_id # This whole business is a little ugly :-) _message_id_filter = chr else: _message_id_filter = lambda(x): x assert _message_id_filter(97) == b'a'[0] class GpsOperations(collections.Iterator): """ Operations common to both real gps and recording. """ def __init__(self): self._logger = logging.getLogger('localization.gps') def _read_binary_sirf_msg(self): """ Return bytes with a single valid message read from the port (the message payload). """ raise NotImplemented() def set_message_rate(self, msg_type, rate): """ Set how often a message gets sent by the SIRF chip. Rate is integer, meaning number of seconds, 0 means disabled. This is a no-op unless we are on a real gps. """ pass def try_read_message(self): """ Try to read one SIRF message from the gps. Raises UnrecognizedMessageException. """ return sirf.from_bytes(self._read_binary_sirf_msg()) def read_message(self): """ Read one recognized SIRF message from the gps. """ while True: try: return sirf.from_bytes(self._read_binary_sirf_msg()) except sirf.UnrecognizedMessageException: pass def read_specific_message(self, msg_type): """ Discards messages until one of given type is received. May block for a long time, careful with this. """ if not issubclass(msg_type, sirf_messages._SirfReceivedMessageBase): raise TypeError("msg_type must be a message type.") msg = None while not isinstance(msg, msg_type): msg = self.read_message() #print(msg) return msg def filtered_messages(self, msg_type_set): """ Returns iterator of messages of types in msg_type_set. Faster than filtering using isinstance. """ ids = {msg_type.get_message_id() for msg_type in msg_type_set} while True: data = self._read_binary_sirf_msg() if sirf.bytes_to_message_id(data) in ids: yield sirf.from_bytes(data) def split_to_cycles(self, msg_type_filter = None, separation = 0.5): """ Returns iterator of messages grouped by the measurement cycles and optionally filtered only to message types contained in msg_type_filter. """ ids = {msg_type.get_message_id() for msg_type in msg_type_filter} if not len(ids): class _Everything: def __contains__(self, x): return True ids = _Everything() out = [] last_msg_time = float("nan") while True: data = self._read_binary_sirf_msg() if sirf.bytes_to_message_id(data) in ids: out.append(sirf.from_bytes(data)) if self.last_msg_time - last_msg_time > separation: yield out out = [] last_msg_time = self.last_msg_time def loop(self, observers, cycle_end_callback = None, cycle_end_threshold = 0.3, log_status = 600): """ Read messages in infinite loop and notify observers. observers: Iterable of observers that will be notified as messages are received cycle_end_callback: Callable that will be called after the measurement cycle ends, or None. Block end callback will only be called when a message arrives with time distance larger than block end threshold, not immediately after the time runs out! cycle_end_threshold: How long a pause between two messages must be to be taken as a start of new measurement cycle. log_status: After how many cycles should the status be logged. If this is false, then no logging is performed. """ observers = list(observers) message_ids = {} for observer in observers: for message_type in observer.observed_message_types(): filtered_id = _message_id_filter(message_type.get_message_id()) message_ids.setdefault(filtered_id, []).append(observer) if log_status: status_id = _message_id_filter(sirf_messages.GeodeticNavigationData.get_message_id()) else: status_id = None status_remaining = 0 last_msg_time = float("nan") while True: try: binary = self._read_binary_sirf_msg() except StopIteration: return if cycle_end_callback is not None and self.last_msg_time - last_msg_time > cycle_end_threshold: cycle_end_callback() last_msg_time = self.last_msg_time message_id = binary[0] if status_remaining <= 0 and message_id == status_id: message = sirf.from_bytes(binary) self._logger.info(message.status_line()) status_remaining = log_status if message_id not in message_ids: continue else: if message_id == status_id: status_remaining -= 1 if message_id not in message_ids: continue else: message = sirf.from_bytes(binary) for observer in message_ids[message_id]: observer(message) def __next__(self): """ We want to support iterator protocol. """ return self.read_message() def next(self): """ Iterator protocol for python 2.x """ return self.read_message()

[ "blue.cube@seznam.cz" ]

blue.cube@seznam.cz

7c38e135fbe87c2b8a76e963211c110dcae4f12e

9bac4cd580ecd3152b828d3bb421e648f2156361

/_admin_panel/apuzzles/forms.py

c6fc0066f8a3ab00f8123e3fdbbcb435b61c62ae

[]

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sharingsimplethoughts/mygame2

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refs/heads/master

2023-05-29T04:01:04.104641

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from django import forms from puzzles.models import * class PuzzlesAddEditForm(forms.Form): def clean(self): les_name = self.data['les_name'] les_cat = self.data['les_cat'] les_desc = self.data['les_desc'] les_hint = self.data['les_hint'] les_exp = self.data['les_exp'] les_learn = self.data['les_learn'] if not les_name or les_name=="": raise forms.ValidationError('Please provide puzzle name') if not les_cat or les_cat=="": raise forms.ValidationError('Please choose puzzle category') if les_cat: obj = PuzzleCategory.objects.filter(id=les_cat).first() if not obj: raise forms.ValidationError('Please choose valid puzzle category') if not les_desc or les_desc=="": raise forms.ValidationError('Please provide puzzle description') if not les_hint or les_hint=="": raise forms.ValidationError('Please provide puzzle hint') if not les_exp or les_exp=="": raise forms.ValidationError('Please provide puzzle explanation') if not les_learn or les_learn=="": raise forms.ValidationError('Please provide puzzle learning text') class PuzzleCategoriesAddForm(forms.Form): def clean(self): cr_name=self.data['cr_name'] cr_list=self.data['cr_list'] if not cr_name or cr_name=="": raise forms.ValidationError('Please provide category name') # if not cr_list or cr_list=="," or cr_list=="": # raise forms.ValidationError('Please select puzzles') lcr = PuzzleCategory.objects.filter(name=cr_name).first() if lcr: raise forms.ValidationError('This category name already exists') class PuzzleCategoriesEditForm(forms.Form): # def __init__(self,*args, **kwargs): # self.cr_id=kwargs.pop('cr_id',None) # super(PuzzleCategoriesEditForm,self).__init__(*args,**kwargs) def clean(self): cr_id=self.data['cr_id'] cr_name=self.data['cr_name'] cr_list=self.data['cr_list'] if not cr_name or cr_name=="": raise forms.ValidationError('Please provide category name') # if not cr_list or cr_list=="," or cr_list=="": # raise forms.ValidationError('Please select puzzles') lcobj = PuzzleCategory.objects.filter(id=cr_id).first() if lcobj.name!=cr_name: lcr = PuzzleCategory.objects.filter(name=cr_name).first() if lcr: raise forms.ValidationError('This category name already taken')

[ "sukamal.sinha@fluper.in" ]

sukamal.sinha@fluper.in

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/largestRectangleHistogram/main.py

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no_license

publicbull/leetcode

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refs/heads/master

2020-12-24T15:22:12.457530

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''' Created on May 15, 2013 @author: Administrator ''' def largestRectangle(data): def _largestRectangle(left, right, maxRect): if left > right: return currMin = data[left] currMinPos = left for i in range(left, right + 1): if currMin > data[i]: currMin = data[i] currMinPos = i maxRect[0] = currMin * (right - left + 1) maxRect[1], maxRect[2] = left, right max1 = [-1, 0, 0] _largestRectangle(left, currMinPos - 1, max1) if maxRect[0] < max1[0]: maxRect[0], maxRect[1], maxRect[2] = max1[0], max1[1], max1[2] max2 = [-1, 0, 0] _largestRectangle(currMinPos + 1, right, max2) if maxRect[0] < max2[0]: maxRect[0], maxRect[1], maxRect[2] = max2[0], max2[1], max2[2] size = len(data) maxRect = [-1, 0, 0] _largestRectangle(0, size - 1, maxRect) return maxRect if __name__ == '__main__': data = [2, 1, 5, 6, 2, 3] print(largestRectangle(data))

[ "baiyubin@gmail.com" ]

baiyubin@gmail.com

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0x0400/LeetCode

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2023-02-24T20:13:11.345873

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# https://leetcode.com/problems/next-permutation/ class Solution(object): def nextPermutation(self, nums): """ :type nums: List[int] :rtype: void Do not return anything, modify nums in-place instead. """ idx = len(nums) - 2 while idx >= 0: if nums[idx] >= nums[idx+1]: idx -= 1 continue minIdx = len(nums) -1 while minIdx > idx: if nums[minIdx] <= nums[idx]: minIdx -= 1 continue break nums[idx], nums[minIdx] = nums[minIdx], nums[idx] break idx += 1 lastIdx = len(nums) - 1 i = 0 while idx + i < lastIdx - i: nums[idx+i], nums[lastIdx-i] = nums[lastIdx-i], nums[idx+i] i += 1

[ "0x0400@users.noreply.github.com" ]

0x0400@users.noreply.github.com

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/python/batch_uninstall.py

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[]

no_license

cet4meiguo/AndroidTestPyScripts

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refs/heads/master

2021-06-18T03:24:24.750998

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#!/usr/bin/env python # -*- coding: utf-8 -*- import os #批量卸载设备上的第三方应用 def uninstall(): os.popen("adb wait-for-device") print "start uninstall..." for packages in os.popen("adb shell pm list packages -3").readlines(): packageName = packages.split(":")[-1].splitlines()[0] os.popen("adb uninstall %s" %packageName) print "remove %s successes." %packageName if __name__ == "__main__": uninstall() print " " print "All the third-party applications uninstall successes."

[ "jayzhen_testing@163.com" ]

jayzhen_testing@163.com

eb86ed1da548c5ada25cc1aa23969fe16b9b6d66

cc7ad1a2aa5d691c15ff7838d1e5126ab2c2bee0

/basic_ranking/urls.py

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[]

no_license

demirantay/lingooapp

9632be8a7d3dd00e7a4ac13618f32975da389729

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refs/heads/master

2023-03-14T08:00:37.681334

2021-01-09T09:36:48

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from django.urls import path from . import views urlpatterns = [ # Ranking Overview path( "ranking/overview/<int:page>/", views.ranking_overview, name="ranking_overview" ), # Category Ranking Page path( "ranking/<str:language>/<int:page>/", views.category_ranking, name="category_ranking" ), ]

[ "demir99antay@gmail.com" ]

demir99antay@gmail.com

43edad709ef0ed6de4ca2dcc842527c0a49c651b

db4c1703bee4e79e0a275434b7491c6dfe7a8602

/backend/rush_19600/wsgi.py

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[]

no_license

crowdbotics-apps/rush-19600

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refs/heads/master

2022-12-01T09:00:15.372702

2020-08-18T05:48:32

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""" WSGI config for rush_19600 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/2.2/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "rush_19600.settings") application = get_wsgi_application()

[ "team@crowdbotics.com" ]

team@crowdbotics.com

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c3e75ab16954f7dffdf68983237df98fae832b43

/conf_matrix.py

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[]

no_license

satojkovic/ml-algorithms-simple

713c6f57c23030a79db7500dff32f30858ebeee6

a2bd09544b82a96dcf41b5a650fee4fe21b99934

refs/heads/master

2021-06-04T15:22:06.421941

2021-05-11T12:50:51

3,835,836

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#!/usr/bin/env python # -*- coding: utf-8 -*- from sklearn.datasets import load_digits from sklearn.cross_validation import train_test_split from sklearn.multiclass import OneVsRestClassifier from sklearn.svm import SVC from sklearn.metrics import confusion_matrix from sklearn.metrics import accuracy_score def main(): digits = load_digits() X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target) estimator = SVC(C=1.0, kernel='rbf', gamma=0.01) clf = OneVsRestClassifier(estimator) clf.fit(X_train, y_train) pred = clf.predict(X_test) cm = confusion_matrix(y_test, pred) print cm print accuracy_score(y_test, pred) if __name__ == '__main__': main()

[ "satojkovic@gmail.com" ]

satojkovic@gmail.com

9a79938a1d99004ccdaf6accc35ec65df0ca6e7c

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/machine_program/data_ready.py

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[]

no_license

sunxhap/machine_learning

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refs/heads/master

2022-05-01T15:22:07.314221

2017-11-12T09:12:30

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null

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# -*- coding: utf-8 -*- """ @Time: 2017/11/8 11:24 @Author: sunxiang """ import numpy as np filename = "data.csv" def data_ready(): """ 数据读入已有分类标签 """ data = [] labels = [] with open("data.txt") as ifile: for line in ifile: try: tokens = line.strip().split(' ') data.append([float(tk) for tk in tokens[:-1]]) labels.append(tokens[-1]) except: print line x = np.array(data) labels = np.array(labels) y = np.zeros(labels.shape) ''''' 标签转换为0/1 ''' y[labels == 'A'] = 1 return x, y def data_ready_notype(): """ 数据读入已有分类标签返回列表 """ data = [] labels = [] with open(filename) as ifile: for line in ifile: try: tokens = line.strip().split(' ') data.append([tk for tk in tokens]) labels.append(tokens[-1]) except: print line # x = np.array(data) # labels = np.array(labels) # y = np.zeros(labels.shape) # # ''''' 标签转换为0/1 ''' # y[labels == 'A'] = 1 return data # def createDataSet(): # """ # 创建数据集 # :return: # """ # return data_ready_notype() # # dataSet = [[1, 1, 'yes'], # # [1, 1, 'yes'], # # [1, 0, 'no'], # # [0, 1, 'no'], # # [0, 1, 'no']] # # labels = ['no surfacing', 'flippers'] # # return dataSet, labels def createDataSet(): """ 创建数据集 :return: """ return np.loadtxt(filename, dtype=str, delimiter=",").tolist()

[ "1925453680@qq.com" ]

1925453680@qq.com

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/src/matches/utils.py

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EdwardBetts/matchmaker

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refs/heads/master

2020-12-11T01:50:10.773983

2016-01-26T16:53:29

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from decimal import Decimal def get_match(user_a, user_b): a = user_a.useranswer_set.all().values_list("question") b = user_b.useranswer_set.all().values_list("question") matches_b = user_b.useranswer_set.filter(question=a).order_by("question") matches_a = user_a.useranswer_set.filter(question=b).order_by("question") questions_match_num = matches_b.count() if questions_match_num: a_points = 0 b_points = 0 a_total_points = 0 b_total_points = 0 for question_a, question_b in zip(matches_a, matches_b): if question_b.their_answer == question_a.my_answer: a_points += question_b.their_points a_total_points += question_b.their_points if question_a.their_answer == question_b.my_answer: b_points += question_a.their_points b_total_points += question_a.their_points if a_total_points == 0: a_decimal = 0.000001 else: a_decimal = a_points / Decimal(a_total_points) if b_total_points == 0: b_decimal = 0.000001 else: b_decimal = b_points / Decimal(b_total_points) match_percentage = (Decimal(a_decimal) * Decimal(b_decimal)) ** (1/Decimal(questions_match_num)) return match_percentage, questions_match_num else: return None, False

[ "eddie.valv@gmail.com" ]

eddie.valv@gmail.com

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binglinchengxiash/txtai

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refs/heads/master

2023-04-03T18:59:35.845281

2021-04-05T22:05:15

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""" Translation module """ import fasttext from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer, MarianMTModel, MarianTokenizer from transformers.file_utils import cached_path from transformers.hf_api import HfApi from .hfmodel import HFModel class Translation(HFModel): """ Translates text from source language into target language. """ # Default language detection model DEFAULT_LANG_DETECT = "https://dl.fbaipublicfiles.com/fasttext/supervised-models/lid.176.ftz" def __init__(self, path="facebook/m2m100_418M", quantize=False, gpu=True, batch=64, langdetect=DEFAULT_LANG_DETECT): """ Constructs a new language translation pipeline. Args: path: optional path to model, accepts Hugging Face model hub id or local path, uses default model for task if not provided quantize: if model should be quantized, defaults to False gpu: True/False if GPU should be enabled, also supports a GPU device id batch: batch size used to incrementally process content langdetect: path to language detection model, uses a default path if not provided """ # Call parent constructor super().__init__(path, quantize, gpu, batch) # Language detection self.detector = None self.langdetect = langdetect # Language models self.models = {} self.ids = self.available() def __call__(self, texts, target="en", source=None): """ Translates text from source language into target language. This method supports texts as a string or a list. If the input is a string, the return type is string. If text is a list, the return type is a list. Args: texts: text|list target: target language code, defaults to "en" source: source language code, detects language if not provided Returns: list of translated text """ values = [texts] if not isinstance(texts, list) else texts # Detect source languages languages = self.detect(values) if not source else [source] * len(values) unique = set(languages) # Build list of (index, language, text) values = [(x, lang, values[x]) for x, lang in enumerate(languages)] results = {} for language in unique: # Get all text values for language inputs = [(x, text) for x, lang, text in values if lang == language] # Translate text in batches outputs = [] for chunk in self.batch([text for _, text in inputs], self.batchsize): outputs.extend(self.translate(chunk, language, target)) # Store output value for y, (x, _) in enumerate(inputs): results[x] = outputs[y] # Return results in same order as input results = [results[x] for x in sorted(results)] return results[0] if isinstance(texts, str) else results def available(self): """ Runs a query to get a list of available language models from the Hugging Face API. Returns: list of available language name ids """ return set(x.modelId for x in HfApi().model_list() if x.modelId.startswith("Helsinki-NLP")) def detect(self, texts): """ Detects the language for each element in texts. Args: texts: list of text Returns: list of languages """ if not self.detector: # Suppress unnecessary warning fasttext.FastText.eprint = lambda x: None # Load language detection model path = cached_path(self.langdetect) self.detector = fasttext.load_model(path) # Transform texts to format expected by language detection model texts = [x.lower() for x in texts] return [x[0].split("__")[-1] for x in self.detector.predict(texts)[0]] def translate(self, texts, source, target): """ Translates text from source to target language. Args: texts: list of text source: source language code target: target language code Returns: list of translated text """ # Return original if already in target language if source == target: return texts # Load model and tokenizer model, tokenizer = self.lookup(source, target) model.to(self.device) indices = None with self.context(): if isinstance(model, M2M100ForConditionalGeneration): source = self.langid(tokenizer.lang_code_to_id, source) target = self.langid(tokenizer.lang_code_to_id, target) tokenizer.src_lang = source tokens, indices = self.tokenize(tokenizer, texts) translated = model.generate(**tokens, forced_bos_token_id=tokenizer.lang_code_to_id[target]) else: tokens, indices = self.tokenize(tokenizer, texts) translated = model.generate(**tokens) # Decode translations translated = tokenizer.batch_decode(translated, skip_special_tokens=True) # Combine translations - handle splits on large text from tokenizer results, last = [], -1 for x, i in enumerate(indices): if i == last: results[-1] += translated[x] else: results.append(translated[x]) last = i return results def lookup(self, source, target): """ Retrieves a translation model for source->target language. This method caches each model loaded. Args: source: source language code target: target language code Returns: (model, tokenizer) """ # Determine best translation model to use, load if necessary and return path = self.modelpath(source, target) if path not in self.models: self.models[path] = self.load(path) return self.models[path] def modelpath(self, source, target): """ Derives a translation model path given source and target languages. Args: source: source language code target: target language code Returns: model path """ # First try direct model template = "Helsinki-NLP/opus-mt-%s-%s" path = template % (source, target) if path in self.ids: return path # Use multi-language - english model if target == "en": return template % ("mul", target) # Default model if no suitable model found return self.path def load(self, path): """ Loads a model specified by path. Args: path: model path Returns: (model, tokenizer) """ if path.startswith("Helsinki-NLP"): model = MarianMTModel.from_pretrained(path) tokenizer = MarianTokenizer.from_pretrained(path) else: model = M2M100ForConditionalGeneration.from_pretrained(path) tokenizer = M2M100Tokenizer.from_pretrained(path) # Apply model initialization routines model = self.prepare(model) return (model, tokenizer) def langid(self, languages, target): """ Searches a list of languages for a prefix match on target. Args: languages: list of languages target: target language code Returns: best match or None if no match found """ for lang in languages: if lang.startswith(target): return lang return None

[ "561939+davidmezzetti@users.noreply.github.com" ]

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/test8.py

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[]

no_license

bcrafton/weight-mirror

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d2e35e7378fc261de397c54a6db76b3f8a1e0281

refs/heads/master

2020-05-15T18:45:57.488229

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import numpy as np import argparse import keras import matplotlib.pyplot as plt from whiten import whiten ####################################### parser = argparse.ArgumentParser() parser.add_argument('--epochs', type=int, default=100) parser.add_argument('--lr', type=float, default=1e-2) parser.add_argument('--l2', type=float, default=1e-3) args = parser.parse_args() LAYER1 = 1024 * 3 LAYER2 = 1000 LAYER3 = 1000 LAYER4 = 10 TRAIN_EXAMPLES = 50000 TEST_EXAMPLES = 10000 ####################################### def softmax(x): e_x = np.exp(x - np.max(x, axis=1, keepdims=True)) return e_x / np.sum(e_x, axis=1, keepdims=True) def sigmoid(x): return 1. / (1. + np.exp(-x)) def dsigmoid(x): return x * (1. - x) def relu(x): return x * (x > 0) def drelu(x): # USE A NOT Z return 1.0 * (x > 0) def tanh(x): return np.tanh(x) def dtanh(x): # USE A NOT Z return (1. - (x ** 2)) ####################################### def unit_vector(vector): return vector / np.linalg.norm(vector) def angle_between(v1, v2): v1_u = unit_vector(v1) v2_u = unit_vector(v2) return np.arccos(np.clip(np.dot(v1_u, v2_u), -1.0, 1.0)) def zca_approx(data, ksize, ssize): N, H, W, C = np.shape(data) KX, KY, KZ = ksize SX, SY, SZ = ssize for sx in range(0, KX, SX): for sy in range(0, KY, SY): for sz in range(0, KZ, SZ): for x in range(sx, H+sx, KX): for y in range(sy, W+sy, KY): for z in range(sz, C+sz, KZ): x1 = x x2 = x + KX y1 = y y2 = y + KY z1 = z z2 = z + KZ if (x2 > H or y2 > W or z2 > C): continue print (x, y, z) white = whiten(X=data[:, x1:x2, y1:y2, z1:z2], method='zca') white = np.reshape(white, (N, x2-x1, y2-y1, z2-z1)) data[:, x1:x2, y1:y2, z1:z2] = white return data ####################################### (x_train, y_train), (x_test, y_test) = keras.datasets.cifar10.load_data() assert(np.shape(x_train) == (50000, 32, 32, 3)) assert(np.shape(x_test) == (10000, 32, 32, 3)) y_train = keras.utils.to_categorical(y_train, 10) x_train = x_train.astype('float32') y_test = keras.utils.to_categorical(y_test, 10) x_test = x_test.astype('float32') mean = np.mean(x_train, axis=0, keepdims=True) std = np.std(x_train, axis=0, ddof=1, keepdims=True) scale = std x_train = x_train - mean x_train = x_train / scale x_train = x_train.reshape(TRAIN_EXAMPLES, 32, 32, 3) # x_train = whiten(x_train) x_train = zca_approx(x_train, (8, 8, 3), (8, 8, 3)) x_train = x_train.reshape(TRAIN_EXAMPLES, 1024 * 3) ####################################### high = 1. / np.sqrt(LAYER1) weights1 = np.random.uniform(low=-high, high=high, size=(LAYER1, LAYER2)) bias1 = np.zeros(shape=LAYER2) high = 1. / np.sqrt(LAYER2) weights2 = np.random.uniform(low=-high, high=high, size=(LAYER2, LAYER3)) bias2 = np.zeros(shape=LAYER3) high = 1. / np.sqrt(LAYER3) weights3 = np.random.uniform(low=-high, high=high, size=(LAYER3, LAYER4)) bias3 = np.zeros(shape=LAYER4) high = 1. / np.sqrt(LAYER2) # b2 = np.random.uniform(low=-high, high=high, size=(LAYER2, LAYER3)) b2 = np.zeros(shape=(LAYER2, LAYER3)) ######## xx1 = 0. xx2 = 0. batch_size = 100 for idx in range(0, 10000, batch_size): print (idx) start = idx end = idx + batch_size x1 = np.reshape(x_train[start:end], (batch_size, LAYER1)) @ weights1 x2 = np.random.uniform(low=-1., high=1., size=(batch_size, LAYER1)) @ weights1 y1 = x1 @ weights2 y2 = x2 @ weights2 xx1 += x1.T @ y1 xx2 += x2.T @ y2 xx1 = xx1 / np.max(xx1) xx2 = xx2 / np.max(xx2) weights2 = weights2 / np.max(weights2) print (np.shape(xx1), np.shape(xx2), np.shape(weights2)) loss1 = np.sum((weights2 - xx1) ** 2) loss2 = np.sum((weights2 - xx2) ** 2) angle1 = angle_between(np.reshape(xx1, -1), np.reshape(weights2, -1)) * (180.0 / 3.14) angle2 = angle_between(np.reshape(xx2, -1), np.reshape(weights2, -1)) * (180.0 / 3.14) print (loss1, loss2, loss1 / loss2) print (angle1, angle2)

[ "crafton.b@husky.neu.edu" ]

crafton.b@husky.neu.edu

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OriHoch/knesset-data-k8s

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refs/heads/master

2023-08-17T12:28:05.208947

2023-08-14T18:04:57

116,827,286

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2018-03-28T10:58:49

2018-01-09T14:35:09

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#!/usr/bin/env python3 import json import subprocess ALLOWED_IPS=""" 212.80.204.81 5.100.254.253 194.36.91.251 212.199.115.150 212.80.204.206 194.36.91.165 5.100.248.220 195.28.181.207 212.115.111.44 212.115.111.199 83.229.74.79 83.229.74.80 194.36.90.155 """ def main(): allowed_ips = [ip.strip() for ip in ALLOWED_IPS.split() if ip.strip()] node_ip_names = {} for node in json.loads(subprocess.check_output(['kubectl', 'get', 'node', '-o', 'json']))['items']: node_ip_names[node['metadata']['annotations']['rke.cattle.io/external-ip']] = node['metadata']['name'] for ip in allowed_ips: node_name = node_ip_names.get(ip) if node_name: subprocess.check_call(['kubectl', 'label', 'node', node_name, 'oknesset-allowed-ip=true', '--overwrite']) if __name__ == '__main__': main()

[ "ori@uumpa.com" ]

ori@uumpa.com

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/Algorithm 190902/N-Queen.py

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vxda7/pycharm

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refs/heads/master

2020-07-03T11:27:27.807096

2019-11-15T08:50:32

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def find(N): stack = [] stack.append([0,0]) # place.append([0,0]) cnt = 0 res = 0 ok = False next = 0 while stack != []: get = stack.pop() col, row = get[0], get[1] for i in stack: # 확인하는 곳 if i[0] != col and i[1] != row and i[0]+i[1] != col+row and i[0]-i[1] != col-row: ok = True cnt += 1 if cnt == N: res += 1 cnt = 0 if ok: # 위치가 관계없다면 추가 if 0 <= col + 1 < N and 0 <= row + next < N: stack.append([col+1, row+2]) return res t = int(input()) for tc in range(1, t+1): N = int(input()) print("#{} {}".format(tc, find(N)))

[ "vxda77@gmail.com" ]

vxda77@gmail.com

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/pbrx/cmd/main.py

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emonty/shiny-octo-computing-machine

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refs/heads/master

2020-03-08T12:21:51.197849

2018-04-04T19:52:12

2018-04-27T21:17:33

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# Copyright 2018 Red Hat, 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. import argparse import json import logging import logging.config import os import sys try: import yaml except ImportError: yaml = None from pbrx import containers from pbrx import siblings import pbr.version log = logging.getLogger("pbrx") def _read_logging_config_file(filename): if not os.path.exists(filename): raise ValueError("Unable to read logging config file at %s", filename) ext = os.path.splitext(filename)[1] if ext in (".yml", ".yaml"): if not yaml: raise ValueError( "PyYAML not installed but a yaml logging config was provided." " Install PyYAML, or convert the config to JSON." ) return yaml.safe_load(open(filename, "r")) elif ext == ".json": return json.load(open(filename, "r")) return filename def setup_logging(log_config, debug): if log_config: config = _read_logging_config_file(log_config) if isinstance(config, dict): logging.config.dictConfig(config) else: logging.config.fileConfig(config) else: log.addHandler(logging.StreamHandler()) log.setLevel(logging.DEBUG if debug else logging.INFO) def main(): parser = argparse.ArgumentParser( description="pbrx: Utilities for projects using pbr" ) parser.add_argument( "--version", action="version", version=str(pbr.version.VersionInfo("pbrx")), ) parser.add_argument( "--debug", help="Emit debug output", action="store_true" ) parser.add_argument( "--log-config", help="Path to a logging config file. Takes precedence over --debug", ) subparsers = parser.add_subparsers( title="commands", description="valid commands", help="additional help" ) cmd_siblings = subparsers.add_parser( "install-siblings", help="install sibling packages" ) cmd_siblings.set_defaults(func=siblings.main) cmd_siblings.add_argument( "-c,--constraints", dest="constraints", help="Path to constraints file", required=False, ) cmd_siblings.add_argument( "projects", nargs="*", help="List of project src dirs to process" ) cmd_containers = subparsers.add_parser( "build-containers", help="build per-process container images" ) cmd_containers.set_defaults(func=containers.build) cmd_containers.add_argument( "--prefix", help="Organization prefix containers will be published to" ) args = parser.parse_args() setup_logging(args.log_config, args.debug) try: return args.func(args) except Exception as e: log.exception(str(e)) return 1 return 0 if __name__ == "__main__": sys.exit(main())

[ "mordred@inaugust.com" ]

mordred@inaugust.com

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/hog_von_mises.py

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[]

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bbbales2/faehrmann_hogs

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622ec582501041ff5e6dd50526d0e3d91de29f53

refs/heads/master

2020-02-26T13:39:05.916838

2016-06-23T23:20:30

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#%% import pystan import matplotlib.pyplot as plt import numpy import os import itertools import math import scipy.integrate import mahotas import collections import skimage.measure, skimage.io, skimage.feature, skimage.util, skimage.filters import seaborn import random # #,, # '/home/bbales2/microhog/rafting_rotated_2d/2na/9/signalx.png', # '/home/bbales2/microhog/rafting_rotated_2d/ah/9/signalx.png''/home/bbales2/web/hog/static/images/renen5strain02.png', # '/home/bbales2/web/hog/static/images/renen5strain22.png' # ims2 = [] for path in ['/home/bbales2/web/hog/static/images/molybdenum0.png', '/home/bbales2/web/hog/static/images/molybdenum1.png']: im = skimage.io.imread(path, as_grey = True).astype('float') im = skimage.transform.rescale(im, 0.25) im -= im.mean() im /= im.std() stats = [] for i in range(im.shape[0]): for j in range(im.shape[1]): if i == 0: dy = im[i + 1, j] - im[i, j] elif i == im.shape[0] - 1: dy = im[i, j] - im[i - 1, j] else: dy = (im[i + 1, j] - im[i - 1, j]) / 2.0 if j == 0: dx = im[i, j + 1] - im[i, j] elif j == im.shape[1] - 1: dx = im[i, j] - im[i, j - 1] else: dx = (im[i, j + 1] - im[i, j - 1]) / 2.0 angle = (numpy.arctan2(dy, dx) + numpy.pi)# / (2.0 * numpy.pi) mag = numpy.sqrt(dy**2 + dx**2) stats.append((angle, mag)) stats = numpy.array(stats) plt.imshow(im) plt.show() 1/0 hog = microstructure.features.hog2(im, bins = 20, stride = 1, sigma = 1.0) #%% stats[:, 0] = stats[:, 0] - stats[:, 0].min() #%% idxs = range(len(stats)) random.shuffle(idxs) seaborn.distplot(stats[idxs[:10000], 0]) plt.show() seaborn.distplot(stats[idxs[:10000], 1]) plt.show() idxs = numpy.argsort(stats[:, 1])[-2000:] seaborn.distplot(stats[idxs, 0]) plt.show() #%% model_code = """ data { int<lower=1> K; //Number of Von Mises distributions to fit int<lower=1> N; real<lower=0.0, upper=2.0 * pi()> y[N]; } parameters { real<lower=0.0, upper=2.0 * pi()> mu[K]; simplex[K + 1] theta; real<lower=0.0> kappa[K]; } model { real ps[K + 1]; for (k in 1:K) { kappa[k] ~ normal(5.0, 10.0); } for (n in 1:N) { for (k in 1:K) { ps[k] <- log(theta[k]) + von_mises_log(y[n], mu[k], kappa[k]); } ps[K + 1] <- log(theta[K + 1]) + uniform_log(y[n], 0.0, 2.0 * pi()); increment_log_prob(log_sum_exp(ps)); } } generated quantities { real out; { int k; k <- categorical_rng(theta); if (k <= K) { out <- von_mises_rng(mu[k], kappa[k]); } else { out <- uniform_rng(0.0, 2.0 * pi()); } } } """ sm = pystan.StanModel(model_code = model_code) #%% N = 100 idxs2 = range(len(idxs)) random.shuffle(idxs2) seaborn.distplot(stats[idxs[idxs2[:N]], 0], bins = 20) plt.show() samples = stats[idxs[idxs2[:N]], 0] #%% fit = sm.sampling(data = { 'K' : 4, 'N' : N, 'y' : samples }) #%% print fit plt.hist(fit.extract()['out'][2000:] % (2.0 * numpy.pi), normed = True, alpha = 0.5) plt.hist(samples, normed = True, alpha = 0.5) plt.show()

[ "bbbales2@gmail.com" ]

bbbales2@gmail.com

c22f182daa3f1e38aa9cc338dd18a375ab6e398c

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/medium/longest_palindromic_substring.py

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[]

no_license

mwong33/leet-code-practice

b21f277d73b30df9e681499733baad07979480a1

9c0e6294bf3b3614b185f0760906abad60f8d9b6

refs/heads/main

2023-03-29T20:35:43.841662

2021-03-31T22:05:44

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class Solution: # O(n^2) time O(1) space def longestPalindrome(self, s: str) -> str: if len(s) <= 1: return s[0] start = 0 end = 0 for i in range(len(s)): length_1 = self.middleOut(s, i, i) length_2 = self.middleOut(s, i, i+1) max_length = max(length_1, length_2) if max_length > (end - start + 1): start = i - ((max_length-1)//2) end = i + (max_length//2) return s[start:end+1] def middleOut(self, s, start, end): while start >= 0 and end < len(s) and s[start] == s[end]: start -= 1 end += 1 return end - start - 1

[ "noreply@github.com" ]

mwong33.noreply@github.com

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/src/airflow-stubs/contrib/task_runner/cgroup_task_runner.pyi

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viewthespace/mypy-stubs

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refs/heads/master

2023-06-07T18:52:46.739560

2023-06-01T22:05:27

2023-06-01T22:05:45

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MIT

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from airflow.task.task_runner.base_task_runner import BaseTaskRunner as BaseTaskRunner from airflow.utils.helpers import reap_process_group as reap_process_group from airflow.utils.operator_resources import Resources as Resources from typing import Any class CgroupTaskRunner(BaseTaskRunner): process: Any def __init__(self, local_task_job) -> None: ... mem_cgroup_name: Any cpu_cgroup_name: Any def start(self) -> None: ... def return_code(self): ... def terminate(self) -> None: ... def on_finish(self) -> None: ...

[ "andrew.marshall@vts.com" ]

andrew.marshall@vts.com

507ee908ce5b75fda95f6fe95550269860a2ecbb

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/shops/models.py

8789cd51b1e8525aad8d6eec6c3013595214bf11

[]

no_license

eyobofficial/clothing-shop-app

38d48ae12fb24265aac7ecbad650c41c785daf1c

5bfc35f765b4ebf6916c306341597d217be60a1d

refs/heads/master

2020-03-18T01:15:46.482548

2018-05-20T09:02:14

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from django.db import models from django.contrib.auth.models import AbstractUser from django.contrib.auth import get_user_model from django.conf import settings from django.urls import reverse def get_deleted_user(): return get_user_model().objects.get_or_create(username='Deleted')[0] class CustomUser(AbstractUser): pass class Base(models.Model): """ Base abstract model for all other models to inherit from """ created_at = models.DateTimeField( 'Created date', auto_now_add=True, help_text='Record created date and time.' ) updated_at = models.DateTimeField( 'Modified date', auto_now=True, help_text='Record last modified date and time' ) class Meta: abstract = True class Shop(Base): """ Models a virtual shop """ name = models.CharField(max_length=100) slug = models.SlugField() logo = models.ImageField( upload_to='shops/logo/', null=True, blank=True ) description = models.TextField('Short description', blank=True) class Meta: get_latest_by = ['updated_at', ] def __str__(self): return self.name def get_absolute_url(self, *args, **kwargs): return reverse('shops:shop-detail', args=[str(self.pk)]) class Catagory(Base): """ Models Product Catagory Example: Dress, Shoes, Leather etc... """ name = models.CharField(max_length=100) slug = models.SlugField() description = models.TextField('Short description', blank=True) class Meta: get_latest_by = ['-updated_at', ] def __str__(self): self.name def get_absolute_url(self, *args, **kwargs): return reverse('shops:catagory-detail', args=[str(self.pk)]) class Tag(Base): """ Models a product Tag Example: leather, oldies, modern, jano etc... """ name = models.CharField(max_length=30) def __str__(self): return self.name class Product(Base): """ Models a Product """ GENDER_OPTIONS = ( ('M', 'Male'), ('F', 'Female'), ) AGE_OPTIONS = ( ('A', 'Adults'), ('K', 'Kids'), ) shop = models.ForeignKey( Shop, related_name='products', on_delete=models.CASCADE, ) catagory = models.ForeignKey( Catagory, related_name='products', on_delete=models.CASCADE, ) name = models.CharField(max_length=100) slug = models.SlugField() description = models.TextField(blank=True) tags = models.ManyToManyField( Tag, blank=True, related_name='products', ) gender = models.CharField(max_length=1, choices=GENDER_OPTIONS) age = models.CharField(max_length=1, choices=AGE_OPTIONS) price = models.DecimalField(max_digits=10, decimal_places=2) is_on_sale = models.BooleanField('On sale', default=False) is_featured = models.BooleanField('Featured', default=False) thumbnail = models.ImageField(upload_to='shops/products/') publish = models.BooleanField( default=True, help_text='Publish product to the public' ) class Meta: order_with_respect_to = 'shop' get_latest_by = ['-updated_at', ] def __str__(self): return self.name def get_absolute_url(self, *args, **kwargs): return reverse('shops:product-detail', args=[str(self.pk)]) class ProductPicture(Base): product = models.ForeignKey( Product, related_name='pictures', on_delete=models.CASCADE ) picture = models.ImageField( upload_to='shops/products/pictures', blank=True, null=True, ) class Meta: get_latest_by = ['-updated_at', ] order_with_respect_to = 'product' def __str__(self): return '{} product pic #{}'.format(self.product, self.pk) class Inventory(Base): """ Models the product inventory data """ product = models.ForeignKey( Product, related_name='inventory', on_delete=models.CASCADE ) color = models.CharField(max_length=100, blank=True) size = models.CharField(max_length=100, blank=True) stock = models.PositiveIntegerField('Available in stock') class Meta: order_with_respect_to = 'product' def __str__(self): return 'Inventory for {}'.format(self.product) def get_absolute_url(self, *args, **kwargs): return reverse('shops:inventory-detail', args=[str(self.pk)]) class DeliveryMethod(Base): """ Models a product delivery method type """ name = models.CharField(max_length=100) icon = models.CharField(max_length=100, blank=True) description = models.TextField(blank=True) price = models.DecimalField(max_digits=6, decimal_places=2) class Meta: get_latest_by = ['updated_at', ] def __str__(self): return self.name class PaymentMethod(Base): """ Models a payment method type """ name = models.CharField(max_length=100) icon = models.CharField(max_length=100, blank=True) description = models.TextField(blank=True) class Meta: get_latest_by = ['updated_at', ] def __str__(self): return self.name class Order(Base): cutomer = models.ForeignKey( settings.AUTH_USER_MODEL, related_name='orders', on_delete=models.SET(get_deleted_user) ) delivery_method = models.ForeignKey( DeliveryMethod, related_name='orders', null=True, on_delete=models.SET_NULL, ) order_date = models.DateTimeField() is_delivered = models.BooleanField('Delivery status', default=False) class Meta: get_latest_by = ['-order_date', ] ordering = ['-order_date', 'is_delivered', ] def __str__(self): return 'Order No. {}'.format(self.pk) def get_absolute_url(self, *args, **kwargs): return reverse('shops:order-detail', args=[str(self.pk)]) class OrderList(Base): """ Models the an ordered product with respect to an Order object """ order = models.ForeignKey( Order, related_name='ordered_lists', on_delete=models.CASCADE ) product = models.ForeignKey( Product, related_name='ordered_lists', null=True, on_delete=models.SET_NULL ) qty = models.PositiveIntegerField('Quantity', default=1) amount = models.DecimalField(max_digits=8, decimal_places=2) class Meta: order_with_respect_to = 'order' get_latest_by = ['-updated_at', ] def __str__(self): return '{} of {}'.format(self.product, self.order) class Payment(Base): """ Models a payment made for an order """ order = models.ForeignKey( Order, related_name='payments', null=True, on_delete=models.SET_NULL, ) payment_method = models.ForeignKey( PaymentMethod, related_name='payments', null=True, on_delete=models.SET_NULL ) subtotal = models.DecimalField(max_digits=8, decimal_places=2) delivery_amount = models.DecimalField(max_digits=6, decimal_places=2) tax = models.DecimalField(max_digits=6, decimal_places=2) payment_date = models.DateTimeField() is_payment_completed = models.BooleanField(default=False) class Meta: get_latest_by = ['-updated_at', ] ordering = ['is_payment_completed', '-updated_at'] def __str__(self): return 'Payment for {}'.format(self.order) def get_absolute_url(self, *args, **kwargs): return reverse('shops:payment-detail', args=[str(self.pk)])

[ "eyobtariku@gmail.com" ]

eyobtariku@gmail.com

91231887766eacf8e685b57bd6b7f460b361dead

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/solutions_python/Problem_155/798.py

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[]

no_license

dr-dos-ok/Code_Jam_Webscraper

c06fd59870842664cd79c41eb460a09553e1c80a

26a35bf114a3aa30fc4c677ef069d95f41665cc0

refs/heads/master

2020-04-06T08:17:40.938460

2018-10-14T10:12:47

null

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null

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py

import sys def read_case(l): au = l.strip().split()[1] return [int(x) for x in au] def cant(c): inv = [i - sum(c[:i]) for i in range(len(c))] return max(0, max(inv)) def rint(): return int(rline()) def rline(): global linenr linenr += 1 return stdin[linenr - 1] global stdin global linenr stdin = sys.stdin.readlines() linenr = 0 cases = rint() case = 1 while linenr < len(stdin): c = read_case(rline()) print 'Case #{0}: {1}'.format(case, cant(c)) case += 1

[ "miliar1732@gmail.com" ]

miliar1732@gmail.com

e745c490084e729003b83b40f597a6e997348317

bc2df7e370e70aa3ccdab80bcecd5379d8ca222c

/bin/base/stuydy_recover.py

257f038f1c7b201773df4497d9b1f00ca1704412

[]

no_license

windyStreet/el-OAMP

092fe39e938ff2bf499ea5790e3914e359ec2069

9a986629daab6b24722a7e18ea0e6593a77d451d

refs/heads/master

2023-05-05T06:27:49.595082

2019-10-15T03:46:53

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#!/usr/bin/env python # !-*- coding:utf-8 -*- from bin.base.tool import RabbitMQ from pymongo import MongoClient from bin import init if __name__ == '__main__': conn = MongoClient('211.154.149.99', 27017) db = conn.BBT_TrainRecord record_set = db.processRecord ds = { "toolUser": "longrise", # "toolPassword": "longrise", # "toolHost": "192.168.7.219", "toolPort": 5672, "toolName": "", 'toolHost': '211.154.149.99', 'toolPassword': 'uCSXBwi7KJfKIx4x', } init.CONF_INFO = { 'study_recover': ds } RM = RabbitMQ.getInstance(ds='study_recover') start = 0 end = 5000000 limit = 1000 n = 0 while (True): offset = start + limit * n if offset >= end: break for re_dict in record_set.find({"studyend": {"$gt": "2019-06-13 10:00:00.000", '$lt': "2019-06-14 10:00:00"}, "isvideopass": "1"}).sort('createtime').skip(offset).limit(limit): re = { 'id': re_dict.get("recordid"), 'cwid': re_dict.get('cwid'), 'cardno': re_dict.get('cardno'), 'studentno': re_dict.get('studentno'), 'effecttime': '1', 'stuclientip': re_dict.get('ip'), 'stuclientmacinfo': "BBAPP_MQ_" + re_dict.get('comfrom2'), } RM.sendMsg(queue='APP_onlineUpdate', msg=re) print(offset) n = n + 1

[ "yq904276384@foxmail.com" ]

yq904276384@foxmail.com

1c4dc3f363cf67370ac7a4c684739dccada90fdc

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/W5/geolocation/migrations/0005_auto_20201207_1442.py

687464ec4b4eab5b7af85f1f1b57254ccd0985cc

[]

no_license

NFEL/DjangoPaeez99

d573cc8e36500f08bc104d76f7a2628062d86c2f

621636bfb47d71f2a4f45037b7264dd5ebc7cdd7

refs/heads/main

2023-01-27T22:05:57.788049

2020-12-08T10:08:28

304,553,353

1

2

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2020-10-16T07:33:04

2020-10-16T07:33:03

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# Generated by Django 3.1.2 on 2020-12-07 14:42 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('geolocation', '0004_address_lo'), ] operations = [ migrations.RenameField( model_name='address', old_name='lo', new_name='service_area', ), migrations.AddField( model_name='address', name='service_radius', field=models.DecimalField(decimal_places=3, max_digits=5, null=True, verbose_name='شعاع فعالیت'), ), ]

[ "nfilsaraee@gmail.com" ]

nfilsaraee@gmail.com

f86ee34060570d42f42a0bd9f70543ce71859a55

5fd658211a0951e287742973618012b7d9f89e43

/tennisblock/webapp/management/commands/local_host_entries.py

e9a7e7ac422add274661f5b80c3b0b1c2b7e0986

[]

no_license

sharpertool/tennisblock

6d14000d3d709ec339124e893ffc8a7cdfe73d8d

82bec4179a5c487a588ff10d910c6c7a9c1014d6

refs/heads/master

2022-03-05T13:03:43.728596

2021-02-15T06:37:53

148,848,726

1

0

null

2022-02-10T14:00:37

2018-09-14T22:43:16

JavaScript

UTF-8

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py

from os.path import exists import re from shutil import copy from django.core.management.base import BaseCommand from wagtail.core.models import Site class Command(BaseCommand): help = 'Generate output to be added to /etc/hosts file' def add_arguments(self, parser): parser.add_argument('--env', help=''' Point this to your .env.local file and it will update the allowed host entries ''') def handle(self, *args, **options): allowed_hosts = list( Site.objects.values_list('hostname', flat=True).all()) etc_hosts = [f"127.0.0.1 {x}" for x in allowed_hosts] hosts_lines = "\n".join(etc_hosts) etc_data = "# tennisblock.local begin\n" + hosts_lines + "\n# tennisblock.local end\n" print("Insert the following lines into your /etc/hosts file:") print(etc_data) envfile = options.get('env', None) if envfile and exists(envfile): copy(envfile, envfile + '.bak') with open(envfile, 'r') as fp: original = fp.readlines() with open(envfile, 'w') as fp: for line in original: if re.search(r'^DJANGO_ALLOWED_HOSTS', line): line = f"DJANGO_ALLOWED_HOSTS={','.join(allowed_hosts)}" fp.write(line)

[ "ed@sharpertool.com" ]

ed@sharpertool.com

b5478f5ad21fcd76d7703d0c8a466721f17e07d0

52b5773617a1b972a905de4d692540d26ff74926

/.history/stringReduction_20200722190200.py

ef338e3e8ae2885556338eaa1ee2321358b4f04a

[]

no_license

MaryanneNjeri/pythonModules

56f54bf098ae58ea069bf33f11ae94fa8eedcabc

f4e56b1e4dda2349267af634a46f6b9df6686020

refs/heads/master

2022-12-16T02:59:19.896129

2020-09-11T12:05:22

null

0

null

UTF-8

Python

false

707

py

def string(str): st = list(str) count = 0 while count < 20: for i in range(0,len(st)-1,2): pair = st[i] + st[i+1] if pair == 'ab' or pair == 'ba': st.pop(i) st.pop(i) st.insert(i,'c') break if pair == 'bc' or pair == 'cb': st.pop(i) st.pop(i) st.insert(i,'a') break if pair == 'ac' or pair == 'ca': st.pop(i) st.pop(i) st.insert(i,'b') break print(st) count +=1 print(len(st) // 2 ) string("abcabc")

[ "mary.jereh@gmail.com" ]

mary.jereh@gmail.com

f55287dd1de797ed3a0460fd54cdcb062360a5f4

99a4817f852115f2f14d50cc6a99abbdb62c4218

/Modulos/Modulo 02 - Deep Learning Frameworks/03 - Passoa a Passo/tensorcode08.py

7071ad1ac1236324ed48246ed099bb9c60c6f37b

[]

no_license

eduardodimperio/formacao-inteligencia-artificial

cac290e1385a9770a7b492ef3e695124b0ac5499

c5b50bad4908e8423fe384d90929a772f01787c3

refs/heads/master

2023-07-03T21:02:17.107564

2021-08-07T13:33:34

null

0

null

UTF-8

Python

false

1,052

py

# Criando Tensores import tensorflow as tf import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' print("\n") # Criando um tensor preenchido com zeros. tensor = tf.zeros(shape = [3, 4], dtype = tf.int32) print(('Tensor preenchido com zeros como int32, 3 linhas e 4 colunas:\n{0}').format(tensor.numpy())) print("\n") # Criando um tensor preenchido com valor 1 e tipo de dados float32. tensor = tf.ones(shape = [5, 3], dtype = tf.float32) print(('\nTensor preenchido com valor 1 e float32, 5 linhas e 3 colunas:\n{0}').format(tensor.numpy())) print("\n") # Criando um tensor preenchido com valor 100 e tipo de dados float64. tensor = tf.constant(100, shape = [4, 4], dtype = tf.float64) print(('\nTensor preenchido com valor 100 e float64, 4 linhas e 4 colunas:\n{0}').format(tensor.numpy())) print("\n") # Criando um tensor preenchido Rank 2 preenchido com zeros tensor = tf.Variable(tf.zeros([1, 2])) print(tensor) print("\n") # Atribuindo valores ao tensor criado no item anterior tensor.assign_add([[100, 200]]) print(tensor) print("\n")

[ "angelicogfa@gmail.com" ]

angelicogfa@gmail.com

97aba7f61ee1a790a8f6bc2b427fe23430b50d04

f40cc44ebfc337326577c91cd88d0c1dd845b098

/LuminarPythonPrograms/PythonToDatabase/SelectFromDBS.py

abfd684fd180b6d5bd3d4b9d24f0cf1e4182d452

[]

no_license

Aswin2289/LuminarPython

6e07d6f9bf6c8727b59f38f97f5779a33b2fab0d

ba633a276dd79bbf214cfceac2413c894eaa1875

refs/heads/master

2023-01-01T07:52:41.598110

2020-10-13T04:34:49

290,109,547

0

null

UTF-8

Python

false

447

py

import mysql.connector db=mysql.connector.connect( host="localhost", port=3307, user="root", password="Password@123", database="luminarpython" , auth_plugin='mysql_native_password' ) cursor=db.cursor() try: sql="SELECT * FROM EMPLOYEE" cursor.execute(sql) myresult=cursor.fetchall() for x in myresult: print(x) except Exception as e: db.rollback() print(e.args) finally: db.close()

[ "aswinabraham4@gmail.com" ]

aswinabraham4@gmail.com