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

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/tests/inventory/test_macos_apps_views.py

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ChefAustin/zentral

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from datetime import datetime from django.urls import reverse from django.utils.http import urlencode from django.test import TestCase, override_settings from zentral.contrib.inventory.models import MachineSnapshotCommit from accounts.models import User @override_settings(STATICFILES_STORAGE='django.contrib.staticfiles.storage.StaticFilesStorage') class MacOSAppsViewsTestCase(TestCase): @classmethod def setUpTestData(cls): # user cls.pwd = "godzillapwd" cls.user = User.objects.create_user("godzilla", "godzilla@zentral.io", cls.pwd) # machine snapshot cls.computer_name = "yolozulu" source = {"module": "tests.zentral.io", "name": "Zentral Tests"} tree = { "source": source, "business_unit": {"name": "yo bu", "reference": "bu1", "source": source, "links": [{"anchor_text": "bu link", "url": "http://bu-link.de"}]}, "groups": [{"name": "yo grp", "reference": "grp1", "source": source, "links": [{"anchor_text": "group link", "url": "http://group-link.de"}]}], "serial_number": "0123456789", "system_info": {"computer_name": cls.computer_name}, "os_version": {'name': 'OS X', 'major': 10, 'minor': 11, 'patch': 1}, "osx_app_instances": [ {'app': {'bundle_id': 'io.zentral.baller', 'bundle_name': 'Baller.app', 'bundle_version': '123', 'bundle_version_str': '1.2.3'}, 'bundle_path': "/Applications/Baller.app", 'signed_by': { "common_name": "Developer ID Application: GODZILLA", "organization": "GOZILLA INC", "organizational_unit": "ATOM", "sha_1": 40 * "a", "sha_256": 64 * "a", "valid_from": datetime(2015, 1, 1), "valid_until": datetime(2026, 1, 1), "signed_by": { "common_name": "Developer ID Certification Authority", "organization": "Apple Inc.", "organizational_unit": "Apple Certification Authority", "sha_1": "3b166c3b7dc4b751c9fe2afab9135641e388e186", "sha_256": "7afc9d01a62f03a2de9637936d4afe68090d2de18d03f29c88cfb0b1ba63587f", "valid_from": datetime(2012, 12, 1), "valid_until": datetime(2027, 12, 1), "signed_by": { "common_name": "Apple Root CA", "organization": "Apple Inc.", "organizational_unit": "Apple Certification Authority", "sha_1": "611e5b662c593a08ff58d14ae22452d198df6c60", "sha_256": "b0b1730ecbc7ff4505142c49f1295e6eda6bcaed7e2c68c5be91b5a11001f024", "valid_from": datetime(2006, 4, 25), "valid_until": datetime(2035, 2, 9) } } }} ] } _, cls.ms = MachineSnapshotCommit.objects.commit_machine_snapshot_tree(tree) cls.osx_app_instance = cls.ms.osx_app_instances.all()[0] cls.osx_app = cls.osx_app_instance.app def log_user_in(self): self.client.post(reverse('login'), {'username': self.user.username, 'password': self.pwd}) def test_macos_apps(self): self.log_user_in() response = self.client.get(reverse("inventory:macos_apps")) self.assertContains(response, "1 macOS application") def test_macos_apps_sha_256_search(self): self.log_user_in() # cert signature response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"sha_256": "7afc9d01a62f03a2de9637936d4afe68090d2de18d03f29c88cfb0b1ba63587f"}) )) self.assertContains(response, "1 macOS application") # binary signature response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"sha_256": 64 * "a"}) )) self.assertContains(response, "1 macOS application") # bad sha 256 response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"sha_256": 64 * "z"}) )) self.assertFormError(response, "search_form", "sha_256", "Enter a valid sha256.") # another sha 256 response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"sha_256": 64 * "f"}) )) self.assertContains(response, "0 macOS applications") def test_macos_apps_source_search(self): self.log_user_in() response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"source": self.ms.source.id}) )) self.assertContains(response, "1 macOS application") def test_macos_apps_bundle_name(self): self.log_user_in() response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"bundle_name": "baller"}) )) self.assertContains(response, "1 macOS application") response = self.client.get("{}?{}".format( reverse("inventory:macos_apps"), urlencode({"bundle_name": "yolo"}) )) self.assertContains(response, "0 macOS applications") def test_macos_app(self): self.log_user_in() response = self.client.get(reverse("inventory:macos_app", args=(self.osx_app.id,))) self.assertContains(response, "Baller.app 1.2.3") self.assertContains(response, "1 application instance") self.assertContains(response, self.osx_app_instance.signed_by.sha_256) def test_macos_app_instance_machines(self): self.log_user_in() response = self.client.get(reverse("inventory:macos_app_instance_machines", args=(self.osx_app.id, self.osx_app_instance.id)), follow=True) self.assertContains(response, "Baller.app 1.2.3") self.assertContains(response, "1 Machine") self.assertContains(response, self.osx_app_instance.signed_by.sha_256) self.assertContains(response, self.computer_name)

[ "eric.falconnier@112hz.com" ]

eric.falconnier@112hz.com

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/source/res/scripts/client/gui/scaleform/daapi/view/lobby/header/BattleTypeSelectPopover.py

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[]

no_license

StranikS-Scan/WorldOfTanks-Decompiled

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d2fe9c195825ececc728e87a02983908b7ea9199

refs/heads/1.18

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# Python bytecode 2.7 (decompiled from Python 2.7) # Embedded file name: scripts/client/gui/Scaleform/daapi/view/lobby/header/BattleTypeSelectPopover.py from adisp import process from frameworks.wulf import WindowLayer from gui.Scaleform.daapi.settings.views import VIEW_ALIAS from gui.Scaleform.daapi.view.lobby.header import battle_selector_items from gui.Scaleform.daapi.view.meta.BattleTypeSelectPopoverMeta import BattleTypeSelectPopoverMeta from gui.Scaleform.framework.managers.containers import POP_UP_CRITERIA from gui.Scaleform.framework.managers.loaders import SFViewLoadParams from gui.Scaleform.genConsts.TOOLTIPS_CONSTANTS import TOOLTIPS_CONSTANTS from gui.Scaleform.locale.TOOLTIPS import TOOLTIPS from gui.prb_control.settings import PREBATTLE_ACTION_NAME from gui.shared import EVENT_BUS_SCOPE from gui.shared.events import LoadViewEvent from helpers import dependency from skeletons.gui.game_control import IRankedBattlesController from skeletons.gui.lobby_context import ILobbyContext class BattleTypeSelectPopover(BattleTypeSelectPopoverMeta): __rankedController = dependency.descriptor(IRankedBattlesController) __lobbyContext = dependency.descriptor(ILobbyContext) def __init__(self, _=None): super(BattleTypeSelectPopover, self).__init__() self._tooltip = None return def selectFight(self, actionName): self.__selectFight(actionName) def getTooltipData(self, itemData, itemIsDisabled): if itemData is None: return else: tooltip = '' isSpecial = False if itemData == PREBATTLE_ACTION_NAME.RANDOM: tooltip = TOOLTIPS.BATTLETYPES_STANDART elif itemData == PREBATTLE_ACTION_NAME.EPIC: tooltip, isSpecial = self.__getEpicAvailabilityData() elif itemData == PREBATTLE_ACTION_NAME.RANKED: tooltip, isSpecial = self.__getRankedAvailabilityData() elif itemData == PREBATTLE_ACTION_NAME.E_SPORT: tooltip = TOOLTIPS.BATTLETYPES_UNIT elif itemData == PREBATTLE_ACTION_NAME.STRONGHOLDS_BATTLES_LIST: if not itemIsDisabled: tooltip = TOOLTIPS.BATTLETYPES_STRONGHOLDS else: tooltip = TOOLTIPS.BATTLETYPES_STRONGHOLDS_DISABLED elif itemData == PREBATTLE_ACTION_NAME.TRAININGS_LIST: tooltip = TOOLTIPS.BATTLETYPES_TRAINING elif itemData == PREBATTLE_ACTION_NAME.EPIC_TRAINING_LIST: tooltip = TOOLTIPS.BATTLETYPES_EPIC_TRAINING elif itemData == PREBATTLE_ACTION_NAME.SPEC_BATTLES_LIST: tooltip = TOOLTIPS.BATTLETYPES_SPEC elif itemData == PREBATTLE_ACTION_NAME.BATTLE_TUTORIAL: tooltip = TOOLTIPS.BATTLETYPES_BATTLETUTORIAL elif itemData == PREBATTLE_ACTION_NAME.SANDBOX: isSpecial = True tooltip = TOOLTIPS_CONSTANTS.BATTLE_TRAINING elif itemData == PREBATTLE_ACTION_NAME.BATTLE_ROYALE: tooltip = TOOLTIPS_CONSTANTS.BATTLE_ROYALE_SELECTOR_INFO isSpecial = True elif itemData == PREBATTLE_ACTION_NAME.MAPBOX: tooltip = TOOLTIPS_CONSTANTS.MAPBOX_SELECTOR_INFO isSpecial = True elif itemData == PREBATTLE_ACTION_NAME.EVENT_BATTLE or itemData == PREBATTLE_ACTION_NAME.EVENT_SQUAD: isSpecial = True tooltip = TOOLTIPS_CONSTANTS.EVENT_BATTLES_SELECTOR_INFO result = {'isSpecial': isSpecial, 'tooltip': tooltip} self._tooltip = tooltip return result def demoClick(self): demonstratorWindow = self.app.containerManager.getView(WindowLayer.WINDOW, criteria={POP_UP_CRITERIA.VIEW_ALIAS: VIEW_ALIAS.DEMONSTRATOR_WINDOW}) if demonstratorWindow is not None: demonstratorWindow.onWindowClose() else: self.fireEvent(LoadViewEvent(SFViewLoadParams(VIEW_ALIAS.DEMONSTRATOR_WINDOW)), EVENT_BUS_SCOPE.LOBBY) return def update(self): if not self.isDisposed(): self.as_updateS(*battle_selector_items.getItems().getVOs()) def _populate(self): super(BattleTypeSelectPopover, self)._populate() self.update() def __getRankedAvailabilityData(self): return (TOOLTIPS_CONSTANTS.RANKED_SELECTOR_INFO, True) if self.__rankedController.isAvailable() else (TOOLTIPS_CONSTANTS.RANKED_UNAVAILABLE_INFO, True) def __getEpicAvailabilityData(self): return (TOOLTIPS_CONSTANTS.EPIC_BATTLE_SELECTOR_INFO, True) @process def __selectFight(self, actionName): navigationPossible = yield self.__lobbyContext.isHeaderNavigationPossible() if not navigationPossible: return battle_selector_items.getItems().select(actionName)

[ "StranikS_Scan@mail.ru" ]

StranikS_Scan@mail.ru

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/5S97Me79PDAefLEXv_17.py

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daniel-reich/ubiquitous-fiesta

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refs/heads/master

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def lambda_to_def(code): eq_index = code.index("=") sem_index = code.index(":") lambda_index = code.index("lambda") try: secound_sem = code.index(":",sem_index+1) except ValueError: secound_sem = None if secound_sem != None: if code[secound_sem+1] != "'": sem_index = secound_sem return "def "+code[:eq_index-1]+"("+code[lambda_index+7:sem_index]+"):\n\treturn"+code[sem_index+1:]

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

daniel.reich@danielreichs-MacBook-Pro.local

5f49a46cba72f2d75b3f06ab89300e953baf3963

b75a259624cd91c75d584b9f9548a2b7e179a81f

/models/LSTM_Classifier.py

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[]

no_license

lucaskingjade/Classification

911f73b8ec037d9f560065aa71116650c128d721

506c036c141df5eee69a5f84672f9635e0ad242b

refs/heads/master

2021-01-20T06:43:26.815927

2017-06-02T07:58:54

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#This is a simple implementation of LSTM from keras.layers import Input,Embedding,RepeatVector,Reshape,LSTM,merge,Dense from keras.models import Model from keras.optimizers import SGD,RMSprop def lstm_model(max_len=200,dof=70,embd_dim=2, hidden_dim_list=[100,20],activation_list=['tanh','tanh'], optimizer ='sgd',lr='0.01',momentum=0.0): input = Input(shape = (max_len,dof),name='input') label_input =Input(shape=(1,),name='label_input') embd_label = Embedding(input_dim=8,output_dim=embd_dim)(label_input) embd_label = Reshape(target_shape=(embd_dim,))(embd_label) embd_label = RepeatVector(max_len)(embd_label) encoded = merge([input, embd_label], mode='concat',concat_axis=2) for i, (dim, activation) in enumerate(zip(hidden_dim_list, activation_list)): if i ==len(hidden_dim_list)-1: encoded = LSTM(output_dim=dim, activation=activation, return_sequences=False)(encoded) else: encoded = LSTM(output_dim=dim, activation=activation, return_sequences=True)(encoded) encoded = Dense(output_dim=8, activation='sigmoid')(encoded) model = Model(input=[input, label_input], output = encoded, name='Encoder') if optimizer=='sgd': optimizer_model = SGD(lr=lr,momentum=momentum) elif optimizer=='rmsprop': optimizer_model = RMSprop(lr=lr) else: raise ValueError('No such kind optimizer') #compile model model.compile(optimizer=optimizer_model,loss='binary_crossentropy',metrics='accuracy') model.summary() return model

[ "wangqi531@hotmail.com" ]

wangqi531@hotmail.com

eaf7a34c14cd4e1b28388a48ae0963692d9f010e

afebbb07b2b4eada17a5853c1ce63b4075d280df

/marketsim/gen/_out/orderbook/_VolumeLevels.py

b906b3b76b1fa1729242c7a4bbcd934491c3730f

[]

no_license

peter1000/marketsimulator

8c0a55fc6408b880311d3ad49defc55e9af57824

1b677200a9d5323f2970c83f076c2b83d39d4fe6

refs/heads/master

2021-01-18T01:39:04.869755

2015-03-29T17:47:24

null

0

null

UTF-8

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# generated with class generator.python.intrinsic_observable$Import from marketsim import registry from marketsim.gen._out._observable._observableivolumelevels import ObservableIVolumeLevels from marketsim.gen._out._ivolumelevels import IVolumeLevels from marketsim.gen._intrinsic.orderbook.volume_levels import VolumeLevels_Impl from marketsim.gen._out._iorderqueue import IOrderQueue @registry.expose(["Asset", "VolumeLevels"]) class VolumeLevels_IOrderQueueFloatInt(ObservableIVolumeLevels,VolumeLevels_Impl): """ **Returns arrays of levels for given volumes [i*volumeDelta for i in range(0, volumeCount)]** Level of volume V is a price at which cumulative volume of better orders is V Parameters are: **queue** **volumeDelta** distance between two volumes **volumeCount** number of volume levels to track """ def __init__(self, queue = None, volumeDelta = None, volumeCount = None): from marketsim.gen._out._ivolumelevels import IVolumeLevels from marketsim.gen._out._observable._observableivolumelevels import ObservableIVolumeLevels from marketsim.gen._out.orderbook._asks import Asks_IOrderBook as _orderbook_Asks_IOrderBook from marketsim import deref_opt ObservableIVolumeLevels.__init__(self) self.queue = queue if queue is not None else deref_opt(_orderbook_Asks_IOrderBook()) self.volumeDelta = volumeDelta if volumeDelta is not None else 30.0 self.volumeCount = volumeCount if volumeCount is not None else 10 VolumeLevels_Impl.__init__(self) @property def label(self): return repr(self) _properties = { 'queue' : IOrderQueue, 'volumeDelta' : float, 'volumeCount' : int } def __repr__(self): return "VolumeLevels(%(queue)s)" % dict([ (name, getattr(self, name)) for name in self._properties.iterkeys() ]) def bind_ex(self, ctx): if self.__dict__.get('_bound_ex', False): return self.__dict__['_bound_ex'] = True if self.__dict__.get('_processing_ex', False): raise Exception('cycle detected') self.__dict__['_processing_ex'] = True self.__dict__['_ctx_ex'] = ctx.updatedFrom(self) if hasattr(self, '_internals'): for t in self._internals: v = getattr(self, t) if type(v) in [list, set]: for w in v: w.bind_ex(self.__dict__['_ctx_ex']) else: v.bind_ex(self.__dict__['_ctx_ex']) self.queue.bind_ex(self._ctx_ex) self.bind_impl(self.__dict__['_ctx_ex']) if hasattr(self, '_subscriptions'): for s in self._subscriptions: s.bind_ex(self.__dict__['_ctx_ex']) self.__dict__['_processing_ex'] = False def reset_ex(self, generation): if self.__dict__.get('_reset_generation_ex', -1) == generation: return self.__dict__['_reset_generation_ex'] = generation if self.__dict__.get('_processing_ex', False): raise Exception('cycle detected') self.__dict__['_processing_ex'] = True if hasattr(self, '_internals'): for t in self._internals: v = getattr(self, t) if type(v) in [list, set]: for w in v: w.reset_ex(generation) else: v.reset_ex(generation) self.queue.reset_ex(generation) self.reset() if hasattr(self, '_subscriptions'): for s in self._subscriptions: s.reset_ex(generation) self.__dict__['_processing_ex'] = False def typecheck(self): from marketsim import rtti from marketsim.gen._out._iorderqueue import IOrderQueue rtti.typecheck(IOrderQueue, self.queue) rtti.typecheck(float, self.volumeDelta) rtti.typecheck(int, self.volumeCount) def registerIn(self, registry): if self.__dict__.get('_id', False): return self.__dict__['_id'] = True if self.__dict__.get('_processing_ex', False): raise Exception('cycle detected') self.__dict__['_processing_ex'] = True registry.insert(self) self.queue.registerIn(registry) if hasattr(self, '_subscriptions'): for s in self._subscriptions: s.registerIn(registry) if hasattr(self, '_internals'): for t in self._internals: v = getattr(self, t) if type(v) in [list, set]: for w in v: w.registerIn(registry) else: v.registerIn(registry) self.__dict__['_processing_ex'] = False def bind_impl(self, ctx): VolumeLevels_Impl.bind_impl(self, ctx) def reset(self): VolumeLevels_Impl.reset(self) def VolumeLevels(queue = None,volumeDelta = None,volumeCount = None): from marketsim.gen._out._iorderqueue import IOrderQueue from marketsim import rtti if queue is None or rtti.can_be_casted(queue, IOrderQueue): if volumeDelta is None or rtti.can_be_casted(volumeDelta, float): if volumeCount is None or rtti.can_be_casted(volumeCount, int): return VolumeLevels_IOrderQueueFloatInt(queue,volumeDelta,volumeCount) raise Exception('Cannot find suitable overload for VolumeLevels('+str(queue) +':'+ str(type(queue))+','+str(volumeDelta) +':'+ str(type(volumeDelta))+','+str(volumeCount) +':'+ str(type(volumeCount))+')')

[ "anton.kolotaev@gmail.com" ]

anton.kolotaev@gmail.com

3e99befc5438312e713a1e78d14e1bc4f6d79697

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/md_rahaman/python/full_stack_django/dojo_secret/apps/dojo_secret_app/migrations/0001_initial.py

8a6981c5b5c67aeb2eb76efcddae0dfeca2b27b1

[]

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RibRibble/python_april_2017

162e543f97afc77d44fcc858106e4730d3f7f760

3cc4240d371a8bad8da2ea085e3675272cca2de3

refs/heads/master

2021-01-19T01:12:34.667828

2017-04-27T22:11:53

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# -*- coding: utf-8 -*- # Generated by Django 1.10 on 2017-04-20 21:41 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Secret', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('secret', models.TextField()), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now=True)), ], ), migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('first_name', models.CharField(max_length=255)), ('last_name', models.CharField(max_length=255)), ('email', models.CharField(max_length=255)), ('password', models.CharField(max_length=255)), ('created_at', models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now=True)), ], ), migrations.AddField( model_name='secret', name='likes', field=models.ManyToManyField(related_name='secrets_liked', to='dojo_secret_app.User'), ), migrations.AddField( model_name='secret', name='user', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='secrets', to='dojo_secret_app.User'), ), ]

[ "soikatesc@gmail.com" ]

soikatesc@gmail.com

b6b21288b2195932f2a24c5efb924383b55353da

f0d713996eb095bcdc701f3fab0a8110b8541cbb

/2iQhC3t4SDZ6LGMWw_20.py

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[]

no_license

daniel-reich/turbo-robot

feda6c0523bb83ab8954b6d06302bfec5b16ebdf

a7a25c63097674c0a81675eed7e6b763785f1c41

refs/heads/main

2023-03-26T01:55:14.210264

2021-03-23T16:08:01

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0

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""" Given a list of 2D points `[x, y]`, create a function that returns `True` if those points can be on the _bounds_ of a rectangle, `False` otherwise. ![](https://edabit-challenges.s3.amazonaws.com/fhh2XNW.png) ### Examples on_rectangle_bounds([[0, 1], [1, 0], [1, 1], [0, 0]]) ➞ True on_rectangle_bounds([[0, 1], [1, 0], [1, 1], [0.5, 0.5]]) ➞ False on_rectangle_bounds([[0, 1], [10, 0], [10, 1]]) ➞ True on_rectangle_bounds([[0, 1]]) ➞ True ### Notes Only rectangles with sides parallel to _x-axis_ and _y-axis_ will be considered. """ def on_rectangle_bounds(dots): bounds = [[min(axis), max(axis)] for axis in zip(*dots)] return all(map(lambda dot: dot[0] in bounds[0] or dot[1] in bounds[1], dots))

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

daniel.reich@danielreichs-MacBook-Pro.local

4397382269e0dec61503218124ea7997ba367489

0bcab6ea00eeb88516c218604d96c9cfc9ea5642

/cs212-docp/07-18.py

1a3dfb413c3c95e0814933cab7a4d0d8af72b932

[]

no_license

alexchonglian/udacity

c11ffbbdbf19aa4247ec917ec51d3baab1411fa4

cc3d990542fd1d14574ca42b64ebdd2d31f99d93

refs/heads/master

2022-08-28T17:17:10.428118

2020-09-10T02:12:40

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2022-07-29T23:11:54

2019-05-18T04:04:07

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# -------------- # User Instructions # # Fill out the function match(pattern, text), so that # remainders is properly assigned. def match(pattern, text): "Match pattern against start of text; return longest match found or None." remainders = pattern(text) if remainders: shortest = min(remainders, key=len) return text[:len(text)-len(shortest)] def lit(s): return lambda t: set([t[len(s):]]) if t.startswith(s) else null def seq(x, y): return lambda t: set().union(*map(y, x(t))) def alt(x, y): return lambda t: x(t) | y(t) def oneof(chars): return lambda t: set([t[1:]]) if (t and t[0] in chars) else null dot = lambda t: set([t[1:]]) if t else null eol = lambda t: set(['']) if t == '' else null def star(x): return lambda t: (set([t]) | set(t2 for t1 in x(t) if t1 != t for t2 in star(x)(t1))) null = frozenset([]) def test(): assert match(star(lit('a')), 'aaaaabbbaa') == 'aaaaa' assert match(lit('hello'), 'hello how are you?') == 'hello' assert match(lit('x'), 'hello how are you?') == None assert match(oneof('xyz'), 'x**2 + y**2 = r**2') == 'x' assert match(oneof('xyz'), ' x is here!') == None return 'tests pass'

[ "alexchonglian@gmail.com" ]

alexchonglian@gmail.com

f6449926a5b1dd8b1dc863a3cf3df671d50dc093

f47863b3a595cbe7ec1c02040e7214481e4f078a

/plugins/scan/discuz/449.py

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[]

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gobiggo/0bscan

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281cf7c5c2181907e6863adde27bd3977b4a3474

refs/heads/master

2020-04-10T20:33:55.008835

2018-11-17T10:05:41

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0

null

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py

#!/usr/bin/env python # -*- coding: utf-8 -*- #__author__ = 'darkkid' # Name:Discuz! X3 tools def assign(service, arg): if service == "discuz": return True, arg def audit(arg): payload = 'source/plugin/tools/tools.php' verify_url = arg + payload code, head, res, errcode, _ = curl.curl(verify_url) if code == 200 and "Discuz" in res: security_warning(verify_url + ' Discuz! X3 tools') if __name__ == '__main__': audit(assign('discuz', 'http://www.example.com/')[1])

[ "zer0i3@aliyun.com" ]

zer0i3@aliyun.com

3ec05c59ff77a33bf89d81b92c7d0dac1f34f4f0

22da4a564696d905bed0e4f21a1cb724fcadbbcf

/frappe/commands/scheduler.py

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permissive

ektai/erp2Dodock

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refs/heads/master

2023-01-02T14:00:12.701247

2020-10-28T07:18:45

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from __future__ import unicode_literals, absolute_import, print_function import click import sys import frappe from frappe.utils import cint from frappe.commands import pass_context, get_site def _is_scheduler_enabled(): enable_scheduler = False try: frappe.connect() enable_scheduler = cint(frappe.db.get_single_value("System Settings", "enable_scheduler")) and True or False except: pass finally: frappe.db.close() return enable_scheduler @click.command('trigger-scheduler-event') @click.argument('event') @pass_context def trigger_scheduler_event(context, event): "Trigger a scheduler event" import frappe.utils.scheduler for site in context.sites: try: frappe.init(site=site) frappe.connect() frappe.utils.scheduler.trigger(site, event, now=True) finally: frappe.destroy() if not context.sites: raise SiteNotSpecifiedError @click.command('enable-scheduler') @pass_context def enable_scheduler(context): "Enable scheduler" import frappe.utils.scheduler for site in context.sites: try: frappe.init(site=site) frappe.connect() frappe.utils.scheduler.enable_scheduler() frappe.db.commit() print("Enabled for", site) finally: frappe.destroy() if not context.sites: raise SiteNotSpecifiedError @click.command('disable-scheduler') @pass_context def disable_scheduler(context): "Disable scheduler" import frappe.utils.scheduler for site in context.sites: try: frappe.init(site=site) frappe.connect() frappe.utils.scheduler.disable_scheduler() frappe.db.commit() print("Disabled for", site) finally: frappe.destroy() if not context.sites: raise SiteNotSpecifiedError @click.command('scheduler') @click.option('--site', help='site name') @click.argument('state', type=click.Choice(['pause', 'resume', 'disable', 'enable'])) @pass_context def scheduler(context, state, site=None): from frappe.installer import update_site_config import frappe.utils.scheduler if not site: site = get_site(context) try: frappe.init(site=site) if state == 'pause': update_site_config('pause_scheduler', 1) elif state == 'resume': update_site_config('pause_scheduler', 0) elif state == 'disable': frappe.connect() frappe.utils.scheduler.disable_scheduler() frappe.db.commit() elif state == 'enable': frappe.connect() frappe.utils.scheduler.enable_scheduler() frappe.db.commit() print('Scheduler {0}d for site {1}'.format(state, site)) finally: frappe.destroy() @click.command('set-maintenance-mode') @click.option('--site', help='site name') @click.argument('state', type=click.Choice(['on', 'off'])) @pass_context def set_maintenance_mode(context, state, site=None): from frappe.installer import update_site_config if not site: site = get_site(context) try: frappe.init(site=site) update_site_config('maintenance_mode', 1 if (state == 'on') else 0) finally: frappe.destroy() @click.command('doctor') #Passing context always gets a site and if there is no use site it breaks @click.option('--site', help='site name') @pass_context def doctor(context, site=None): "Get diagnostic info about background workers" from frappe.utils.doctor import doctor as _doctor if not site: site = get_site(context, raise_err=False) return _doctor(site=site) @click.command('show-pending-jobs') @click.option('--site', help='site name') @pass_context def show_pending_jobs(context, site=None): "Get diagnostic info about background jobs" from frappe.utils.doctor import pending_jobs as _pending_jobs if not site: site = get_site(context) with frappe.init_site(site): pending_jobs = _pending_jobs(site=site) return pending_jobs @click.command('purge-jobs') @click.option('--site', help='site name') @click.option('--queue', default=None, help='one of "low", "default", "high') @click.option('--event', default=None, help='one of "all", "weekly", "monthly", "hourly", "daily", "weekly_long", "daily_long"') def purge_jobs(site=None, queue=None, event=None): "Purge any pending periodic tasks, if event option is not given, it will purge everything for the site" from frappe.utils.doctor import purge_pending_jobs frappe.init(site or '') count = purge_pending_jobs(event=event, site=site, queue=queue) print("Purged {} jobs".format(count)) @click.command('schedule') def start_scheduler(): from frappe.utils.scheduler import start_scheduler start_scheduler() @click.command('worker') @click.option('--queue', type=str) @click.option('--quiet', is_flag = True, default = False, help = 'Hide Log Outputs') def start_worker(queue, quiet = False): from frappe.utils.background_jobs import start_worker start_worker(queue, quiet = quiet) @click.command('ready-for-migration') @click.option('--site', help='site name') @pass_context def ready_for_migration(context, site=None): from frappe.utils.doctor import get_pending_jobs if not site: site = get_site(context) try: frappe.init(site=site) pending_jobs = get_pending_jobs(site=site) if pending_jobs: print('NOT READY for migration: site {0} has pending background jobs'.format(site)) sys.exit(1) else: print('READY for migration: site {0} does not have any background jobs'.format(site)) return 0 finally: frappe.destroy() commands = [ disable_scheduler, doctor, enable_scheduler, purge_jobs, ready_for_migration, scheduler, set_maintenance_mode, show_pending_jobs, start_scheduler, start_worker, trigger_scheduler_event, ]

[ "63931935+ektai@users.noreply.github.com" ]

63931935+ektai@users.noreply.github.com

b21593202db3ec2c9fca713de182051eab520cf7

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/Notes/Sprint1/MaxMinInt.py

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[ "MIT" ]

permissive

mark-morelos/CS_Notes

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339c47ae5d7e678b7ac98d6d78857d016c611e38

refs/heads/main

2023-03-10T11:56:52.691282

2021-03-02T15:09:31

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""" Challenge #10: Given a string of space separated integers, write a function that returns the maximum and minimum integers. Example: - max_and_min("1 2 3 4 5") -> "5 1" - max_and_min("1 2 -3 4 5") -> "5 -3" - max_and_min("1 9 3 4 -5") -> "9 -5" Notes: - All inputs are valid integers. - There will always be at least one number in the input string. - The return string must be two numbers separated by a single space, and the maximum number is first. """ # def max_and_min(input_str): # Your code here def csAntyhingButFive(start, end): rangeNum = range(start, end) return rangeNum csAntyhingButFive(2, 5)

[ "makoimorelos@gmail.com" ]

makoimorelos@gmail.com

e48e2e127a3980f24a9bca937240644815c580b0

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/cXfcK7iXpuZ67taSh_6.py

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[]

no_license

daniel-reich/turbo-robot

feda6c0523bb83ab8954b6d06302bfec5b16ebdf

a7a25c63097674c0a81675eed7e6b763785f1c41

refs/heads/main

2023-03-26T01:55:14.210264

2021-03-23T16:08:01

350,773,815

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""" This is a **reverse coding challenge**. Normally you're given explicit directions with how to create a function. Here, you must generate your own function to satisfy the relationship between the inputs and outputs. Your task is to create a function that, when fed the inputs below, produce the sample outputs shown. ### Examples "A4B5C2" ➞ "AAAABBBBBCC" "C2F1E5" ➞ "CCFEEEEE" "T4S2V2" ➞ "TTTTSSVV" "A1B2C3D4" ➞ "ABBCCCDDDD" ### Notes If you get stuck, check the **Comments** for help. """ def mystery_func(txt): letters = txt[::2] nums = txt[1::2] final = [] for i in zip(letters, nums): final.append(i[0]*int(i[1])) return ''.join(final)

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

daniel.reich@danielreichs-MacBook-Pro.local

db7e523a58f687eac59bf3abe458af25e9ee7bb6

06f0ae3ecaaf47b1c23e231838afa524d8446f5e

/contest/migrations/0005_auto_20160321_2239.py

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[]

no_license

nakamotohideyoshi/draftboard-web

c20a2a978add93268617b4547654b89eda11abfd

4796fa9d88b56f80def011e2b043ce595bfce8c4

refs/heads/master

2022-12-15T06:18:24.926893

2017-09-17T12:40:03

224,877,650

0

null

2022-12-08T00:02:57

2019-11-29T15:20:17

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py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('prize', '0006_auto_20160209_2241'), ('draftgroup', '0018_draftgroup_fantasy_points_finalized'), ('sports', '0001_squashed_0008_auto_20160119_2124'), ('contest', '0004_auto_20160321_2142'), ] operations = [ migrations.CreateModel( name='ContestPool', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created', models.DateTimeField(auto_now_add=True)), ('cid', models.CharField(editable=False, blank=True, max_length=6, help_text='unique, randomly chosen when Contest is created', default='')), ('name', models.CharField(default='', max_length=64, help_text='The front-end name of the Contest', verbose_name='Public Name')), ('start', models.DateTimeField(help_text='the start should coincide with the start of a real-life game.', verbose_name='Start Time')), ('end', models.DateTimeField(blank=True, help_text='forces the end time of the contest (will override "Ends tonight" checkbox!!', verbose_name='Cutoff Time')), ('max_entries', models.PositiveIntegerField(default=1, help_text='USER entry limit')), ('entries', models.PositiveIntegerField(default=2, help_text='CONTEST limit')), ('current_entries', models.PositiveIntegerField(default=0, help_text='The current # of entries in the contest')), ('gpp', models.BooleanField(default=False, help_text='a gpp Contest will not be cancelled if it does not fill')), ('respawn', models.BooleanField(default=False, help_text='indicates whether a new identical Contest should be created when this one fills up')), ('doubleup', models.BooleanField(default=False, help_text='whether this contest has a double-up style prize structure')), ('status', models.CharField(choices=[('Scheduled', (('scheduled', 'Scheduled'),)), ('Created', (('created', 'Created'),))], default='scheduled', max_length=32)), ('draft_group', models.ForeignKey(blank=True, to='draftgroup.DraftGroup', help_text='the pool of draftable players and their salaries, for the games this contest includes.', null=True, verbose_name='DraftGroup')), ('prize_structure', models.ForeignKey(to='prize.PrizeStructure')), ('site_sport', models.ForeignKey(to='sports.SiteSport', related_name='contest_contestpool_site_sport')), ], options={ 'abstract': False, 'verbose_name_plural': 'Contest Pools', 'verbose_name': 'Contest Pools', }, ), migrations.RemoveField( model_name='pool', name='draft_group', ), migrations.RemoveField( model_name='pool', name='prize_structure', ), migrations.RemoveField( model_name='pool', name='site_sport', ), migrations.DeleteModel( name='Pool', ), migrations.CreateModel( name='CurrentContestPool', fields=[ ], options={ 'proxy': True, }, bases=('contest.contestpool',), ), ]

[ "cbanister@coderden.com" ]

cbanister@coderden.com

48d33bfa29646585b6db9ca254362c02f141d4cc

e02405f3db787275545f87a23bf7eb3510ddd2f4

/test_main.py

4e68d61ebcec6bfcbe8da0934a8fedd93d0a5e41

[]

no_license

kevlab/flasktaskr_project

a51ca6d62b080fb1fdbe0fb34ad5d7cff36ba329

3a3ba1dfbe2571deb7958970d52437abb03b03e7

refs/heads/master

2021-01-17T17:07:33.064404

2015-06-07T14:38:25

33,480,265

0

null

2015-04-06T13:25:34

2015-04-06T12:10:55

Python

UTF-8

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false

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py

import os import unittest from project import app, db from config import basedir from project.models import User, Task TEST_DB = 'test.db' class Alltests(unittest.TestCase): def setUp(self): app.config['TESTING'] = True app.config['WTF_CSRF_ENABLED'] = False app.config['DEBUG'] = False app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///' + \ os.path.join(basedir, TEST_DB) self.app = app.test_client() db.create_all() def tearDown(self): db.drop_all() def login(self, name, password): return self.app.post('users/', data=dict(name=name, password=password), follow_redirects=True) def test_404_error(self): response = self.app.get('/not-actually-a-route/') self.assertEqual(response.status_code, 404) self.assertIn('Sorry. There\'s nothing here.', response.data) #def test_500_error(self): #bad_user = User(name='baduser', #email='baduser@gmail.com', #password='django') #db.session.add(bad_user) #db.session.commit() #response = self.login('baduser', 'django') #self.assertEqual(response.status_code, 500) #self.assertIn('Something went terribly wrong.', response.data) #self.assertNotIn('ValueError: Invalid salt', response.data) def test_index(self): """ Ensure flask was set up properly """ response = self.app.get('/', content_type='html/text') self.assertEqual(response.status_code, 302) if __name__ == "__main__": unittest.main()

[ "greenleaf1348@gmail.com" ]

greenleaf1348@gmail.com

ed9bd818265cb5b56fa0412338d0e74acfdcfc60

fd390bfa1f471d09cafb72ad85e5143214abf32d

/shakecast/app/orm/migrations.py

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[ "LicenseRef-scancode-warranty-disclaimer", "LicenseRef-scancode-public-domain-disclaimer" ]

permissive

usgs/shakecast

0ac6ac955aaff3029b133c4ce9264adc90004d86

e287d697d93467e5e25c99d27b70754a0a5e6e39

refs/heads/master

2023-05-13T09:22:13.001195

2022-03-08T03:26:18

52,902,913

9

24

NOASSERTION

2023-05-01T22:45:23

2016-03-01T19:15:42

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UTF-8

Python

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from sqlalchemy import Column, Integer, String, Float, PrimaryKeyConstraint ############### DB Migrations ################ def migrate_1to2(engine): ''' Add updated and updated_by columns to keep track of which users are updating inventory ''' updated = Column('updated', Integer) updated_by = Column('updated_by', String) try: add_column(engine, 'user', updated) except Exception: pass try: add_column(engine, 'user', updated_by) except Exception: pass try: add_column(engine, 'group', updated) except Exception: pass try: add_column(engine, 'group', updated_by) except Exception: pass try: add_column(engine, 'facility', updated) except Exception: pass try: add_column(engine, 'facility', updated_by) except Exception: pass return engine def migrate_2to3(engine): ''' Add updated and updated_by columns to keep track of which users are updating inventory ''' mms = Column('mms', String(255)) try: add_column(engine, 'user', mms) except Exception: pass return engine def migrate_3to4(engine): ''' Add updated and updated_by columns to keep track of which users are updating inventory ''' aebm = Column('aebm', String(50)) try: add_column(engine, 'facility_shaking', aebm) except Exception: pass return engine def migrate_4to5(engine): sent_timestamp = Column('sent_timestamp', Float) try: add_column(engine, 'notification', sent_timestamp) except Exception: pass return engine def migrate_5to6(engine): type_ = Column('type', String(64)) try: add_column(engine, 'shakemap', type_) except Exception: pass try: add_column(engine, 'event', type_) except Exception: pass return engine def migrate_6to7(engine): epicentral_distance = Column('epicentral_distance', String(64)) try: add_column(engine, 'facility_shaking', epicentral_distance) except Exception: pass return engine def migrate_7to8(engine): override_directory = Column('override_directory', String(255)) try: add_column(engine, 'shakemap', override_directory) except Exception: pass try: add_column(engine, 'event', override_directory) except Exception: pass return engine def migrate_8to9(engine): product_string = Column('product_string', String(255)) try: add_column(engine, 'group', product_string) except Exception: pass return engine def migrate_9to10(engine): generated_timestamp = Column('generated_timestamp', Float) try: add_column(engine, 'notification', generated_timestamp) except Exception: pass return engine def migrate_10to11(engine): file_name = Column('file_name', String) try: add_column(engine, 'local_product_types', file_name) except Exception: pass name = Column('name', String) try: add_column(engine, 'local_product_types', name) except Exception: pass try: engine.execute('drop table local_product_types') except Exception: pass begin_timestamp = Column('begin_timestamp', Float) try: add_column(engine, 'local_products', begin_timestamp) except Exception: pass finish_timestamp = Column('finish_timestamp', Float, default=0) try: add_column(engine, 'local_products', finish_timestamp) except Exception: pass error = Column('error', String(255)) try: add_column(engine, 'notification', error) except Exception: pass return engine def migrate_11to12(engine): update = Column('updated', Integer) try: add_column(engine, 'event', update) except Exception: pass return engine def migrate_12to13(engine): dependencies = Column('dependencies', String) tries = Column('tries', Integer, default=0) try: add_column(engine, 'local_product_types', dependencies) except Exception: pass try: add_column(engine, 'local_products', tries) except Exception: pass return engine def add_column(engine, table_name, column): ''' Add a column to an existing table ''' column_name = column.compile(dialect=engine.dialect) column_type = column.type.compile(engine.dialect) if 'sqlite' in str(engine): engine.execute('ALTER TABLE "%s" ADD COLUMN %s %s' % (table_name, column_name, column_type)) elif 'mysql' in str(engine): engine.execute('ALTER TABLE `%s` ADD COLUMN %s %s' % (table_name, column_name, column_type)) ####################################################################### # List of database migrations for export migrations = [migrate_1to2, migrate_2to3, migrate_3to4, migrate_4to5, migrate_5to6, migrate_6to7, migrate_7to8, migrate_8to9, migrate_9to10, migrate_10to11, migrate_11to12, migrate_12to13] def migrate(engine): ''' Run all database migrations ''' for migration in migrations: engine = migration(engine) return engine

[ "dslosky@usgs.gov" ]

dslosky@usgs.gov

5a3513f9f209d1ef28d755df10e6aa2cfc4607aa

6f2d5600b65b062151bab88c592796b878de7465

/InterfaceTest/common/do_mysql.py

5eac443a50281fb43beeeb98044f8353bb135ad0

[]

no_license

zhouyanmeng/python_api_test

1e6549321c20ee9a71beffac2533c917b5ecc157

7303352c9b5baacba5296b088f89ba4c702fb485

refs/heads/master

2022-12-17T14:34:26.351566

2019-03-01T13:02:06

185,185,856

0

null

2022-12-08T01:45:15

2019-05-06T11:45:55

Python

UTF-8

Python

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py

import pymysql class DoMysql: #完成与sql数据库的交互 def __init__(self):###实例化对象的时候就建立连接 #def connect(self): host="test.lemonban.com" user="test" password="test" port=3306 self.mysql=pymysql.connect(host=host,user=user,password=password,port=3306) #self.cursor = self.mysql.cursor() self.cursor=self.mysql.cursor(pymysql.cursors.DictCursor)###设置返回字典游标 def fetch_one(self,sql): self.cursor.execute(sql) self.mysql.commit() return self.cursor.fetchone() def fetch_all(self,sql): self.cursor.executee(sql) return self.cursor.fetchall() def close(self): self.cursor.close()##关闭游标，查询 self.mysql.close()#关闭链接 if __name__ == '__main__': mysql=DoMysql()###实例化，建立连接 # mysql.connect() result=mysql.fetch_one('select max(mobilephone) from future.member')##输入查询语句 print(result) mysql.close()

[ "2440269710@qq.com" ]

2440269710@qq.com

6deb89e092b5b74f23029184b835d8e808de678a

3b81dfbacf97918d36fb5accbcef0b610378e1a8

/data-struct/probelm/02-second-try.py

3a304359cfc1762c450a8f2640ca20afd38eef61

[]

no_license

XiaoFei-97/the-way-to-python

11706f0845f56246ba8ea0df8ff34e622bbdad2d

3667a24f4f4238998e9c6ed42cdc49c68881a529

refs/heads/master

2020-03-21T06:46:36.939073

2018-06-23T03:51:11

138,241,410

0

null

UTF-8

Python

false

845

py

#如果a+b+c=1000,且a^2+b^2=c^2（a,b,c为自然数），求出abc所以可能的组合 #运行时间1秒 # #a = 0 #b = 0 #c = 0 # import time # #start_time = time.time() #for a in range(1000): # for b in range(1000): # for c in range(1000): # if a+b+c == 1000 and a**2 +b**2 == c**2: # print("a=%d,b=%d,c=%d"%(a,b,c)) #end_time = time.time() # #print("times:%d"%(end_time-start_time)) #T=1000 * 1000 * 1000 * 2(此处细化是10步) #时间复杂度T(n) = n^3 * 2 #大O表示法：g(n)=n^3 start_time = time.time() for a in range(1001): for b in range(1001-a): c = 1000-a-b if a**2 +b**2 == c**2: print("a=%d,b=%d,c=%d"%(a,b,c)) #T= 1000 * 1000 * 3 #时间复杂度T(n) = n^2 *3 #大O表示法：g(n)=n^2 end_time = time.time() print("times:%d"%(end_time-start_time))

[ "jack_970124@163.com" ]

jack_970124@163.com

f41ff08bfd79dc9007fd2de6edc00cb85adf391a

c46754b9600a12df4f9d7a6320dfc19aa96b1e1d

/src/transformers/models/clipseg/__init__.py

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# Copyright 2022 The HuggingFace Team. 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 typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _import_structure = { "configuration_clipseg": [ "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP", "CLIPSegConfig", "CLIPSegTextConfig", "CLIPSegVisionConfig", ], "processing_clipseg": ["CLIPSegProcessor"], } try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_clipseg"] = [ "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST", "CLIPSegModel", "CLIPSegPreTrainedModel", "CLIPSegTextModel", "CLIPSegVisionModel", "CLIPSegForImageSegmentation", ] if TYPE_CHECKING: from .configuration_clipseg import ( CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP, CLIPSegConfig, CLIPSegTextConfig, CLIPSegVisionConfig, ) from .processing_clipseg import CLIPSegProcessor try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_clipseg import ( CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST, CLIPSegForImageSegmentation, CLIPSegModel, CLIPSegPreTrainedModel, CLIPSegTextModel, CLIPSegVisionModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

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''' UniCEUB - Ciência da Computação - Prof. Barbosa Atalho de teclado: ctlr <d>, duplica linha. ctrl <y>, apaga linha. ctrl </>, comenta linha Sintaxe: POO em Python com gets e sets class NomeClasse (object): def __init__ (self, p_1, p_2, ...): # Método construtor self.nome_atributo1 = p_1 # Atributos self.nome_atributo2 = p_2 ... def get_nome_atributo1 (self): # Modelo do método get (retorna valor do atributo) return self.nome_atributo1 def set_nome_atributo1 (self, valor): # Modelo do método set (altera valor do atributo) self.nome_atributo1 = valor def outro_metodo (self): # Outros métodos da classe (métodos fundionais) ... [return ...] if __name__ == '__main__': # mai <tab> nome_objeto1 = NomeClasse(a_1, a_2, ...) # Cria (instancia) o primeiro objeto da classe nome_objeto2 = NomeClasse(a_1, a_2, ...) # Cria (instancia) o segundo objeto da classe . . . r = nome_objeto1.get_nome_atributo1() # Consulta um atributo print(r) nome_objeto1.set_nome_atributo1(novo_valor) # Altera um atributo ------------------------------- Com base no modelo acima, implemente estes itens: 1- Crie a classe Aluno. - Crie o construtor da classe com os atributos: nome, mensalidade, idade - Crie os métodos gets e sets - No main, crie pelo menos dois objetos da classe Aluno. Teste 5- Use os métodos gets e sets para os objetos criados - Crie o método mostra_dados. Mostra os dados (atrigutos) dentro do método. Teste. - Refaça o anterior sem usar o nome do atributo, crie o método mostra_dados_2. Teste - Crie o método retorna_dados, retorne todos os dados (atributos) concatenados.Teste - Crie o método aumento_mensalidade_valor, ele recebe o valor do aumento. Teste 10- Crie o método aumento_mensalidade_porcentagem (Recebe: 10%, 15% etc.). Teste --- 11- Altere o construtor com estes valor default: Mensalidade = 1000 e idade = 0. - No main, crie o objeto aluno3 da classe Aluno passando apenas o nome. Teste - No main, crie o objeto aluno4 da classe Aluno passando o nome e a mensalidade. Teste 14- No main, crie o objeto aluno5 da classe Aluno passando somente o nome e a idade. não passe o argumento mensalidade. Teste ----- ''' class Aluno(object): # class Aluno: def __init__(self, nome, mensalidade=1000, idade=0): # Método construtor com valores default # def __init__(self, nome, mensalidade, idade): # Método construtor self.nome = nome # Atributos self.mensalidade = mensalidade self.idade = idade def get_nome(self): # Métodos gets e sets return self.nome def set_nome(self, nome): self.nome = nome def get_mensalidade(self): return self.mensalidade def set_mensalidade(self, valor): self.mensalidade = valor def get_idade(self): return self.idade def set_idade(self, idade): self.idade = idade def mostra_dados (self): # Metodos funcionais print('Nome: ', self.nome) print('Mensalidade: ', self.mensalidade) print('Idade: ', self.idade) def mostra_dados_2(self): print('Nome: ', self.get_nome()) print('Mensalidade: ', self.get_mensalidade()) print('Idade: ', self.get_idade()) def retorna_dados(self): dados = self.nome + ' - ' + str(self.mensalidade) + ' - ' + str(self.idade) # dados = self.get_nome() + ' - ' + str(self.get_mensalidade()) + ' - ' + str(self.get_idade()) return dados def aumento_mensalidade_valor(self, valor): self.mensalidade += valor # self.mensalidade = self. mensalidade + valor def aumento_mensalidade_porcentagem(self, pct): self.mensalidade += self.mensalidade * pct / 100 # self.mensalidade=self.mensalidade + self.mensalidade * pct/100 if __name__ == '__main__': # Atalho: main <tab> aluno1 = Aluno('Paulo', 1000, 21) # Chamando o construtor __init__ aluno2 = Aluno('Carla', 900, 20) print("Aluno 1:") print("Nome: ", aluno1.get_nome()) # print(nome_objeto.nome_metodo()) print("Mensalidade: ", aluno1.get_mensalidade()) print("Idade: ", aluno1.get_idade()) print("Aluno 2:") print("Nome: ", aluno2.get_nome()) # print(nome_objeto.nome_metodo()) print("Mensalidade: ", aluno2.get_mensalidade()) print("Idade: ", aluno2.get_idade()) novo_nome = input("Novo nome: ") # Solução 1 aluno1.set_nome(novo_nome) # nome_objeto.nome_metodo() aluno2.set_nome("João") # Solução 2 aluno1.mostra_dados() aluno2.mostra_dados() aluno1.mostra_dados_2() aluno2.mostra_dados_2() print('Dados concatenados: ', aluno1.retorna_dados()) print('Dados concatenados: ', aluno2.retorna_dados()) aluno1.aumento_mensalidade_valor(110) print('Nova mensalidade', aluno1.get_mensalidade()) aluno1.mostra_dados_2() aluno2.aumento_mensalidade_porcentagem(10) aluno2.mostra_dados_2() print('Nova mensalidade', aluno2.get_mensalidade()) aluno3 = Aluno('Ailton') aluno3.mostra_dados() aluno4 = Aluno('Ana', 800) aluno4.mostra_dados() aluno5 = Aluno('Rogério', idade = 31) # Sem passar mensalidade aluno5.mostra_dados() aluno6 = Aluno( idade = 30, nome= 'Vinicius') # Fora da sequência aluno6.mostra_dados()

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import numpy as np import scipy.stats import pandas as pd np.random.binomial(100, 0.5, 20) np.random.binomial(10, 0.3, 3) scipy.stats.binom.pmf(20, 100, 0.5) scipy.stats.binom.pmf(50, 100, 0.5) dd = scipy.stats.binom.pmf(np.arange(0, 21, 1), 100, 0.5) dd.sum() scipy.stats.binom.cdf(20, 100, 0.5) HSRet300 = pd.read_csv('return300.csv') ret = HSRet300.iloc[:, 1] print(ret.head(3)) p = len(ret[ret>0])/len(ret) print(p) prob = scipy.stats.binom.pmf(6, 10, p) print(prob)

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- import scipy.signal import numpy as np import matplotlib.pyplot as plt # The imput signal x x = np.zeros(100) x[30:60] = 1. # ... y = np.ones(30) xc = scipy.signal.convolve(x, y) plt.plot(x) plt.plot(xc / 30.) plt.show()

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import math def inserttree(idx): global cnt if idx <= V: inserttree(2*idx) tree[idx] = cnt cnt += 1 inserttree(2*idx+1) for tc in range(1,int(input())+1): V = int(input().rstrip()) tree = [[] for _ in range(V+1)] cnt = 1 inserttree(1) print(f'#{tc}', tree[1], tree[V//2])

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import functools import typing import string import random import pytest ## Lösung Teil 1. def mysum(zs: list) -> int: return sum(xs) ## Lösung Teil 2. (Tests) def test_2(): assert mysum([1, 2, 3]) == 6 ###################################################################### ## hidden tests pytest.main (["-v", "--assert=plain", "-p", "no:cacheprovider"]) from inspect import getfullargspec mysumargs = getfullargspec(mysum).args class TestName: def test_mysum (self): assert mysum assert 'xs' in mysumargs class TestGrades: def test_docstring_present(self): assert False def test_typing_present(self): assert True def test_coverage(self): assert False def sum_oracle(self, xs:list)->int: return sum(xs) def check_sum (self,xs): assert mysum (xs) == self.sum_oracle (xs) def test_correctness(self): for i in range (100): l = random.randrange (6) xs = [ random.randrange (10) for z in range(l) ] self.check_sum (xs)

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#!/usr/bin/env python # ----------------------------------------------------------------------------- # # P A G E B O T # # Copyright (c) 2016+ Buro Petr van Blokland + Claudia Mens & Font Bureau # www.pagebot.io # Licensed under MIT conditions # # Supporting usage of DrawBot, www.drawbot.com # Supporting usage of Flat, https://github.com/xxyxyz/flat # ----------------------------------------------------------------------------- # from random import random from pagebot.contexts import defaultContext as c for p in range(20): c.newPage(1000, 1000) for n in range(50): c.fill(random(), 0, random(), 0.5 + random()*0.2) ch = random() x = 20 + random()*800 y = 20 + random()*800 if ch < 0.2: c.oval(x, y, 80, 80 ) elif ch < 0.4: c.rect(x, y, 80, 80 ) else: fs = c.newString('Hello world on %d,%d' % (x, y), style=dict(fontSize=24)) c.text(fs, (x, y)) c.saveImage('_export/OurNiceDrawing.pdf')

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def distance(strand1, strand2): dist = 0 for i in range(len(strand1)): if strand1[i] != strand2[i]: dist += 1 return dist

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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = [ 'GetAlertRuleResult', 'AwaitableGetAlertRuleResult', 'get_alert_rule', ] @pulumi.output_type class GetAlertRuleResult: """ The alert rule resource. """ def __init__(__self__, actions=None, condition=None, description=None, is_enabled=None, last_updated_time=None, location=None, name=None, tags=None, type=None): if actions and not isinstance(actions, list): raise TypeError("Expected argument 'actions' to be a list") pulumi.set(__self__, "actions", actions) if condition and not isinstance(condition, dict): raise TypeError("Expected argument 'condition' to be a dict") pulumi.set(__self__, "condition", condition) if description and not isinstance(description, str): raise TypeError("Expected argument 'description' to be a str") pulumi.set(__self__, "description", description) if is_enabled and not isinstance(is_enabled, bool): raise TypeError("Expected argument 'is_enabled' to be a bool") pulumi.set(__self__, "is_enabled", is_enabled) if last_updated_time and not isinstance(last_updated_time, str): raise TypeError("Expected argument 'last_updated_time' to be a str") pulumi.set(__self__, "last_updated_time", last_updated_time) if location and not isinstance(location, str): raise TypeError("Expected argument 'location' to be a str") pulumi.set(__self__, "location", location) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if tags and not isinstance(tags, dict): raise TypeError("Expected argument 'tags' to be a dict") pulumi.set(__self__, "tags", tags) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) @property @pulumi.getter def actions(self) -> Optional[Sequence[Any]]: """ the array of actions that are performed when the alert rule becomes active, and when an alert condition is resolved. """ return pulumi.get(self, "actions") @property @pulumi.getter def condition(self) -> Any: """ the condition that results in the alert rule being activated. """ return pulumi.get(self, "condition") @property @pulumi.getter def description(self) -> Optional[str]: """ the description of the alert rule that will be included in the alert email. """ return pulumi.get(self, "description") @property @pulumi.getter(name="isEnabled") def is_enabled(self) -> bool: """ the flag that indicates whether the alert rule is enabled. """ return pulumi.get(self, "is_enabled") @property @pulumi.getter(name="lastUpdatedTime") def last_updated_time(self) -> str: """ Last time the rule was updated in ISO8601 format. """ return pulumi.get(self, "last_updated_time") @property @pulumi.getter def location(self) -> str: """ Resource location """ return pulumi.get(self, "location") @property @pulumi.getter def name(self) -> str: """ Azure resource name """ return pulumi.get(self, "name") @property @pulumi.getter def tags(self) -> Optional[Mapping[str, str]]: """ Resource tags """ return pulumi.get(self, "tags") @property @pulumi.getter def type(self) -> str: """ Azure resource type """ return pulumi.get(self, "type") class AwaitableGetAlertRuleResult(GetAlertRuleResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetAlertRuleResult( actions=self.actions, condition=self.condition, description=self.description, is_enabled=self.is_enabled, last_updated_time=self.last_updated_time, location=self.location, name=self.name, tags=self.tags, type=self.type) def get_alert_rule(resource_group_name: Optional[str] = None, rule_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetAlertRuleResult: """ Use this data source to access information about an existing resource. :param str resource_group_name: The name of the resource group. :param str rule_name: The name of the rule. """ __args__ = dict() __args__['resourceGroupName'] = resource_group_name __args__['ruleName'] = rule_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-nextgen:insights/v20160301:getAlertRule', __args__, opts=opts, typ=GetAlertRuleResult).value return AwaitableGetAlertRuleResult( actions=__ret__.actions, condition=__ret__.condition, description=__ret__.description, is_enabled=__ret__.is_enabled, last_updated_time=__ret__.last_updated_time, location=__ret__.location, name=__ret__.name, tags=__ret__.tags, type=__ret__.type)

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from test.test_support import findfile, TestFailed, TestSkipped, import_module sunaudiodev = import_module('sunaudiodev', deprecated=True) import os try: audiodev = os.environ["AUDIODEV"] except KeyError: audiodev = "/dev/audio" if not os.path.exists(audiodev): raise TestSkipped("no audio device found!") def play_sound_file(path): fp = open(path, 'r') data = fp.read() fp.close() try: a = sunaudiodev.open('w') except sunaudiodev.error, msg: raise TestFailed, msg else: a.write(data) a.close() def test_main(): play_sound_file(findfile('audiotest.au')) if __name__ == '__main__': test_main()

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# Generated by Django 3.0 on 2020-06-18 16:05 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Product', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('short_code', models.CharField(max_length=20)), ('updated', models.DateTimeField(auto_now=True)), ('created', models.DateTimeField(auto_now_add=True)), ], ), ]

[ "inbox.dipayan@gmail.com" ]

inbox.dipayan@gmail.com

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fb9371054b6ce236c6b202cc51c6bc98a3483060

/python_20190615/Python网络爬虫与信息提取/BaiduStocks/BaiduStocks/spiders/stocks.py

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skymoonfp/python_learning

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refs/heads/master

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# -*- coding: utf-8 -*- import random import re import scrapy class StocksSpider(scrapy.Spider): name = 'stocks' allowed_domains = ['baidu.com'] start_urls = ['http://quote.eastmoney.com/stock_list.html'] user_agent_list = [ "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1" "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6", "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1", "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5", "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3", "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3", "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24", "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24" ] def parse(self, response): for href in response.css('a::attr(href)').extract(): try: stock = re.findall(r"[s][hz]\d{6}", href)[0] url = "https://gupiao.baidu.com/stock/" + stock + ".html" ua = random.choice(self.user_agent_list) # 随机抽取User-Agent headers = { 'Accept-Encoding': 'gzip, deflate, sdch, br', 'Accept-Language': 'zh-CN,zh;q=0.8', 'Connection': 'keep-alive', 'Referer': 'https://gupiao.baidu.com/', 'User-Agent': ua } yield scrapy.Request(url, callback=self.parse_stock, headers=headers) except: continue def parse_stock(self, response): infoDict = dict() stockInfo = response.css(".stock-bets") name = stockInfo.css(".bets-name").extract()[0] keyList = stockInfo.css("dt").extract() valueList = stockInfo.css("dd").extract() for i in range(len(keyList)): key = re.findall(r'>.*</dt>', keyList[i])[0][1:-5] try: val = re.findall(r'\d+\.?.*</dd>', valueList[i])[0][0:-5] except: val = "--" infoDict[key] = val infoDict.update( {"股票名称": re.findall('\s.*\(', name)[0].split()[0] + re.findall('\>.*\<', name)[0][1:-1]} ) yield infoDict

[ "954918@qq.com" ]

954918@qq.com

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5963c12367490ffc01c9905c028d1d5480078dec

/tests/components/tado/test_config_flow.py

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[ "Apache-2.0" ]

permissive

BenWoodford/home-assistant

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refs/heads/dev

2023-03-05T06:13:30.354545

2021-07-18T09:51:53

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"""Test the Tado config flow.""" from unittest.mock import MagicMock, patch import requests from homeassistant import config_entries, setup from homeassistant.components.tado.const import DOMAIN from homeassistant.const import CONF_PASSWORD, CONF_USERNAME from tests.common import MockConfigEntry def _get_mock_tado_api(getMe=None): mock_tado = MagicMock() if isinstance(getMe, Exception): type(mock_tado).getMe = MagicMock(side_effect=getMe) else: type(mock_tado).getMe = MagicMock(return_value=getMe) return mock_tado async def test_form(hass): """Test we can setup though the user path.""" await setup.async_setup_component(hass, "persistent_notification", {}) result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) assert result["type"] == "form" assert result["errors"] == {} mock_tado_api = _get_mock_tado_api(getMe={"homes": [{"id": 1, "name": "myhome"}]}) with patch( "homeassistant.components.tado.config_flow.Tado", return_value=mock_tado_api, ), patch( "homeassistant.components.tado.async_setup_entry", return_value=True, ) as mock_setup_entry: result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {"username": "test-username", "password": "test-password"}, ) await hass.async_block_till_done() assert result2["type"] == "create_entry" assert result2["title"] == "myhome" assert result2["data"] == { "username": "test-username", "password": "test-password", } assert len(mock_setup_entry.mock_calls) == 1 async def test_form_invalid_auth(hass): """Test we handle invalid auth.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) response_mock = MagicMock() type(response_mock).status_code = 401 mock_tado_api = _get_mock_tado_api(getMe=requests.HTTPError(response=response_mock)) with patch( "homeassistant.components.tado.config_flow.Tado", return_value=mock_tado_api, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {"username": "test-username", "password": "test-password"}, ) assert result2["type"] == "form" assert result2["errors"] == {"base": "invalid_auth"} async def test_form_cannot_connect(hass): """Test we handle cannot connect error.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) response_mock = MagicMock() type(response_mock).status_code = 500 mock_tado_api = _get_mock_tado_api(getMe=requests.HTTPError(response=response_mock)) with patch( "homeassistant.components.tado.config_flow.Tado", return_value=mock_tado_api, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {"username": "test-username", "password": "test-password"}, ) assert result2["type"] == "form" assert result2["errors"] == {"base": "cannot_connect"} async def test_no_homes(hass): """Test we handle no homes error.""" result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_USER} ) mock_tado_api = _get_mock_tado_api(getMe={"homes": []}) with patch( "homeassistant.components.tado.config_flow.Tado", return_value=mock_tado_api, ): result2 = await hass.config_entries.flow.async_configure( result["flow_id"], {"username": "test-username", "password": "test-password"}, ) assert result2["type"] == "form" assert result2["errors"] == {"base": "no_homes"} async def test_form_homekit(hass): """Test that we abort from homekit if tado is already setup.""" await setup.async_setup_component(hass, "persistent_notification", {}) result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_HOMEKIT}, data={"properties": {"id": "AA:BB:CC:DD:EE:FF"}}, ) assert result["type"] == "form" assert result["errors"] == {} flow = next( flow for flow in hass.config_entries.flow.async_progress() if flow["flow_id"] == result["flow_id"] ) assert flow["context"]["unique_id"] == "AA:BB:CC:DD:EE:FF" entry = MockConfigEntry( domain=DOMAIN, data={CONF_USERNAME: "mock", CONF_PASSWORD: "mock"} ) entry.add_to_hass(hass) result = await hass.config_entries.flow.async_init( DOMAIN, context={"source": config_entries.SOURCE_HOMEKIT}, data={"properties": {"id": "AA:BB:CC:DD:EE:FF"}}, ) assert result["type"] == "abort"

[ "noreply@github.com" ]

BenWoodford.noreply@github.com

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/std_modules/plistlib/.readPlist()

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[]

no_license

kilirobbs/python-fiddle

8d6417ebff9d6530e713b6724f8416da86c24c65

9c2f320bd2391433288cd4971c2993f1dd5ff464

refs/heads/master

2016-09-11T03:56:39.808358

2013-03-19T19:26:19

null

0

null

UTF-8

Python

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423

#!/usr/bin/env python from os.path import expanduser from plistlib import readPlist plist="~/Library/LaunchAgents/org.lighttpd.plist" path=expanduser(plist) pl = readPlist(path) print pl.__class__,pl print pl.keys() print pl.Label print "Label" in pl print "KeepAlive" in pl if "Program" in pl: print pl.Program if "ProgramArguments" in pl: print pl.ProgramArguments # print pl.programarguments # AttributeError

[ "cancerhermit@gmail.com" ]

cancerhermit@gmail.com

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cc13092b652113221a877db2bf907c050dc30aaa

/kws_streaming/models/tc_resnet.py

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[ "Apache-2.0" ]

permissive

Th-Fo/google-research

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refs/heads/master

2020-12-27T17:30:43.916109

2020-05-25T17:06:20

237,989,659

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3

Apache-2.0

2020-05-25T17:06:22

2020-02-03T14:52:08

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UTF-8

Python

false

6,116

py

# coding=utf-8 # Copyright 2020 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Model based on combination of n by 1 convolutions with residual blocks.""" from kws_streaming.layers import speech_features from kws_streaming.layers.compat import tf from kws_streaming.models.utils import parse def model_parameters(parser_nn): """Temporal Convolution Resnet model parameters. In more details parameters are described at: https://arxiv.org/pdf/1904.03814.pdf We converted model to Keras and made it compatible with TF V2 https://github.com/hyperconnect/TC-ResNet Args: parser_nn: global command line args parser Returns: parser with updated arguments """ parser_nn.add_argument( '--channels', type=str, default='24, 36, 36, 48, 48, 72, 72', help='Number of channels per convolutional block (including first conv)', ) parser_nn.add_argument( '--debug_2d', type=int, default=0, help='if 0 conv_kernel will be [3, 3], else conv_kernel [3, 1]', ) parser_nn.add_argument( '--pool_size', type=str, default='', help="pool size for example '4,4'", ) parser_nn.add_argument( '--pool_stride', type=int, default=0, help='pool stride, for example 4', ) parser_nn.add_argument( '--bn_momentum', type=float, default=0.997, help='Momentum for the moving average', ) parser_nn.add_argument( '--bn_center', type=int, default=1, help='If True, add offset of beta to normalized tensor.' 'If False, beta is ignored', ) parser_nn.add_argument( '--bn_scale', type=int, default=1, help='If True, multiply by gamma. If False, gamma is not used. ' 'When the next layer is linear (also e.g. nn.relu), this can be disabled' 'since the scaling will be done by the next layer.', ) parser_nn.add_argument( '--bn_renorm', type=int, default=0, help='Whether to use Batch Renormalization', ) parser_nn.add_argument( '--dropout', type=float, default=0.2, help='Percentage of data dropped', ) def model(flags): """Temporal Convolution ResNet model. It is based on paper: Temporal Convolution for Real-time Keyword Spotting on Mobile Devices https://arxiv.org/pdf/1904.03814.pdf Args: flags: data/model parameters Returns: Keras model for training """ input_audio = tf.keras.layers.Input( shape=(flags.desired_samples,), batch_size=flags.batch_size) net = speech_features.SpeechFeatures( speech_features.SpeechFeatures.get_params(flags))( input_audio) time_size, feature_size = net.shape[1:3] channels = parse(flags.channels) net = tf.keras.backend.expand_dims(net) if flags.debug_2d: conv_kernel = first_conv_kernel = (3, 3) else: net = tf.reshape( net, [-1, time_size, 1, feature_size]) # [batch, time, 1, feature] first_conv_kernel = (3, 1) conv_kernel = (9, 1) net = tf.keras.layers.Conv2D( filters=channels[0], kernel_size=first_conv_kernel, strides=1, padding='same', activation='linear')( net) net = tf.keras.layers.BatchNormalization( momentum=flags.bn_momentum, center=flags.bn_center, scale=flags.bn_scale, renorm=flags.bn_renorm)( net) net = tf.keras.layers.Activation('relu')(net) if parse(flags.pool_size): net = tf.keras.layers.AveragePooling2D( pool_size=parse(flags.pool_size), strides=flags.pool_stride)( net) channels = channels[1:] # residual blocks for n in channels: if n != net.shape[-1]: stride = 2 layer_in = tf.keras.layers.Conv2D( filters=n, kernel_size=1, strides=stride, padding='same', activation='linear')( net) layer_in = tf.keras.layers.BatchNormalization( momentum=flags.bn_momentum, center=flags.bn_center, scale=flags.bn_scale, renorm=flags.bn_renorm)( layer_in) layer_in = tf.keras.layers.Activation('relu')(layer_in) else: layer_in = net stride = 1 net = tf.keras.layers.Conv2D( filters=n, kernel_size=conv_kernel, strides=stride, padding='same', activation='linear')( net) net = tf.keras.layers.BatchNormalization( momentum=flags.bn_momentum, center=flags.bn_center, scale=flags.bn_scale, renorm=flags.bn_renorm)( net) net = tf.keras.layers.Activation('relu')(net) net = tf.keras.layers.Conv2D( filters=n, kernel_size=conv_kernel, strides=1, padding='same', activation='linear')( net) net = tf.keras.layers.BatchNormalization( momentum=flags.bn_momentum, center=flags.bn_center, scale=flags.bn_scale, renorm=flags.bn_renorm)( net) # residual connection net = tf.keras.layers.Add()([net, layer_in]) net = tf.keras.layers.Activation('relu')(net) net = tf.keras.layers.AveragePooling2D( pool_size=net.shape[1:3], strides=1)( net) net = tf.keras.layers.Dropout(rate=flags.dropout)(net) # fully connected layer net = tf.keras.layers.Conv2D( filters=flags.label_count, kernel_size=1, strides=1, padding='same', activation='linear')( net) net = tf.reshape(net, shape=(-1, net.shape[3])) return tf.keras.Model(input_audio, net)

[ "copybara-worker@google.com" ]

copybara-worker@google.com

03e25ec68fa24203aeca5c8b73e78b1da4d5005b

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/BalancedSmileys/py2/bs.py

ae9c513dbea5334261132bb501da379f9a70fc60

[]

no_license

StevenDunn/CodeEval

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refs/heads/master

2021-01-15T15:33:53.155975

2018-04-01T13:54:16

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# balanced smileys soln in py2 for code eval by steven a dunn import sys def is_balanced(line): if line == "": return "YES" line = line.replace(":)", "}").replace(":(", "{") min_val = 0 max_val = 0 for i in range(0, len(line)): c = line[i] if c == '(': min_val += 1 max_val += 1 elif c == ')': min_val -= 1 max_val -= 1 if max_val < 0: return "NO" elif c == '{': max_val += 1 elif c == '}': min_val -= 1 if min_val <= 0 and 0 <= max_val: return "YES" return "NO" f = open(sys.argv[1], 'r') for line in f: print is_balanced(line) f.close()

[ "stevendunn@gmail.com" ]

stevendunn@gmail.com

d2fb1ee1dc5bf60a4b7ed477b3f0d3dd9283e44f

ac5e52a3fc52dde58d208746cddabef2e378119e

/exps-gsn-edf.0/gsn-edf_ut=3.5_rd=0.5_rw=0.06_rn=4_u=0.075-0.325_p=harmonic-2/sched=RUN_trial=66/params.py

d68d8385fdd6a0806cc34b1f280849c3602ecd11

[]

no_license

ricardobtxr/experiment-scripts

1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1

7bcebff7ac2f2822423f211f1162cd017a18babb

refs/heads/master

2023-04-09T02:37:41.466794

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{'cpus': 4, 'duration': 30, 'final_util': '3.527214', 'max_util': '3.5', 'periods': 'harmonic-2', 'release_master': False, 'res_distr': '0.5', 'res_nmb': '4', 'res_weight': '0.06', 'scheduler': 'GSN-EDF', 'trial': 66, 'utils': 'uni-medium-3'}

[ "ricardo.btxr@gmail.com" ]

ricardo.btxr@gmail.com

be8e93fb9885fd8b2e99c287d74219d031f769ab

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/archimedes/archimedesquestion/urls.py

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[]

no_license

cvelas11/mmobious

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refs/heads/master

2021-07-09T06:01:59.712677

2021-04-05T15:26:30

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"""archimedes URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/2.2/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: path('', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.urls import include, path 2. Add a URL to urlpatterns: path('blog/', include('blog.urls')) """ from django.contrib import admin from django.urls import path from django.conf.urls import url from django.conf.urls import include from archimedesquestion import views from django.views.generic import TemplateView app_name= 'archimedesquestion' urlpatterns = [ url("^register", views.register, name = 'register'), url("^ingresar", views.ingresar, name = 'ingresar'), url("^logout", views.logout_func, name = 'logout'), url("^practicar", views.practicar, name = 'practicar'), url("^recursos", views.recursos, name = 'recursos'), url("^questions", views.questions, name = 'questions'), url("^iniciar", views.iniciar, name = 'iniciar'), url("^proyecto", views.proyecto, name = 'proyecto'), url("^dashboard", views.dashboard, name = 'dashboard'), # path('practicar', TemplateView.as_view(template_name='archimedesquestion/practicar.html')), # <-- #path('accounts/', include('allauth.urls')) ]

[ "(none)" ]

(none)

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/ABC/ABC151-200/ABC196/B.py

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[]

no_license

k-harada/AtCoder

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refs/heads/master

2023-08-21T18:55:53.644331

2023-08-05T14:21:25

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9

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null

2023-05-22T16:29:18

2019-05-04T14:24:18

Python

UTF-8

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py

def solve(xs): if "." in xs: return int(xs[:xs.index(".")]) else: return int(xs) def main(): xs = input() res = solve(xs) print(res) def test(): assert solve("5.90") == 5 assert solve("0") == 0 assert solve("84939825309432908832902189.9092309409809091329") == 84939825309432908832902189 if __name__ == "__main__": test() main()

[ "cashfeg@gmail.com" ]

cashfeg@gmail.com

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/mysite/baseItems/models.py

aa8e62fe30b17d1bf2c62081b129658066edc4bb

[]

no_license

LKingJ23/Gymkana-formacion-Django

5a5daf27abdd100ee8f9e0e61af5eb010899928a

63d49b7ed81e8a3d0c5ed9c9765801680fb51ef7

refs/heads/master

2021-04-15T19:03:33.830028

2018-04-09T16:29:59

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0

null

2018-04-09T16:30:00

2018-03-23T09:05:57

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UTF-8

Python

false

1,023

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models from django.db.models.signals import post_delete from django.dispatch import receiver import os class BaseItems(models.Model): title = models.CharField(max_length=200, blank=False, null=False) subtitle = models.CharField(max_length=200, blank=False, null=False) body = models.TextField() class Meta: abstract = True def __str__(self): return self.title class New(BaseItems): publish_date = models.DateField(auto_now_add=True) image = models.ImageField(upload_to="img", default='/img/periodico.jpg') class Event(BaseItems): start_date = models.DateField(blank=False, null=False) end_date = models.DateField(blank=False, null=False) @receiver(post_delete, sender=New) def delete_img(sender, **kwargs): try: image = kwargs.get('instance').image if image.name != "/img/periodico.jpg": os.remove(image.path) except OSError: pass

[ "lkingj23@gmail.com" ]

lkingj23@gmail.com

e61ef3bc74137cb2c14a765724f0967c90ad8dfc

48e124e97cc776feb0ad6d17b9ef1dfa24e2e474

/sdk/python/pulumi_azure_native/apimanagement/v20210801/get_policy.py

f723b56f81345494660930c00c7d052abe191863

[ "BSD-3-Clause", "Apache-2.0" ]

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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities __all__ = [ 'GetPolicyResult', 'AwaitableGetPolicyResult', 'get_policy', 'get_policy_output', ] @pulumi.output_type class GetPolicyResult: """ Policy Contract details. """ def __init__(__self__, format=None, id=None, name=None, type=None, value=None): if format and not isinstance(format, str): raise TypeError("Expected argument 'format' to be a str") pulumi.set(__self__, "format", format) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) if value and not isinstance(value, str): raise TypeError("Expected argument 'value' to be a str") pulumi.set(__self__, "value", value) @property @pulumi.getter def format(self) -> Optional[str]: """ Format of the policyContent. """ return pulumi.get(self, "format") @property @pulumi.getter def id(self) -> str: """ Fully qualified resource ID for the resource. Ex - /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/{resourceProviderNamespace}/{resourceType}/{resourceName} """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ The name of the resource """ return pulumi.get(self, "name") @property @pulumi.getter def type(self) -> str: """ The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts" """ return pulumi.get(self, "type") @property @pulumi.getter def value(self) -> str: """ Contents of the Policy as defined by the format. """ return pulumi.get(self, "value") class AwaitableGetPolicyResult(GetPolicyResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetPolicyResult( format=self.format, id=self.id, name=self.name, type=self.type, value=self.value) def get_policy(format: Optional[str] = None, policy_id: Optional[str] = None, resource_group_name: Optional[str] = None, service_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetPolicyResult: """ Policy Contract details. :param str format: Policy Export Format. :param str policy_id: The identifier of the Policy. :param str resource_group_name: The name of the resource group. :param str service_name: The name of the API Management service. """ __args__ = dict() __args__['format'] = format __args__['policyId'] = policy_id __args__['resourceGroupName'] = resource_group_name __args__['serviceName'] = service_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:apimanagement/v20210801:getPolicy', __args__, opts=opts, typ=GetPolicyResult).value return AwaitableGetPolicyResult( format=__ret__.format, id=__ret__.id, name=__ret__.name, type=__ret__.type, value=__ret__.value) @_utilities.lift_output_func(get_policy) def get_policy_output(format: Optional[pulumi.Input[Optional[str]]] = None, policy_id: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, service_name: Optional[pulumi.Input[str]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetPolicyResult]: """ Policy Contract details. :param str format: Policy Export Format. :param str policy_id: The identifier of the Policy. :param str resource_group_name: The name of the resource group. :param str service_name: The name of the API Management service. """ ...

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# 조이스틱 : https://programmers.co.kr/learn/courses/30/lessons/42860 def solution(name): def go_next_idx(): nonlocal answer, current_idx diff_min = 100 next_idx = 0 for i in range(length): if name[i] == current_string[i]: continue diff = min(abs(i - current_idx), length - abs(i - current_idx)) if diff_min > diff: diff_min = diff next_idx = i current_idx = next_idx answer += diff_min def change_char(): nonlocal answer, current_string to_change = name[current_idx] current_string[current_idx] = to_change cost = min(abs(ord(to_change) - ord('A')),\ (ord('Z') - ord('A') + 1) - abs(ord(to_change) - ord('A'))) answer += cost answer = 0 length = len(name) current_string = ['A' for _ in range(length)] current_idx = 0 while True: if ''.join(current_string) == name: break go_next_idx() change_char() return answer

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import frappe from frappe.modules.import_file import import_file_by_path from frappe.utils import get_bench_path import os from os.path import join def after_migrate(**args): supplier_rfq_create_custom_fields(**args) make_property_setter() def make_property_setter(): supplier_rfq_app_folder_path='/apps/supplier_rfq/supplier_rfq/import_records' if(not frappe.db.exists('Property Setter','Request for Quotation-main-title_field')): fname="property_setter.json" import_folder_path="{bench_path}/{app_folder_path}".format(bench_path=get_bench_path(),app_folder_path=supplier_rfq_app_folder_path) make_records(import_folder_path,fname) def make_records(path, fname): if os.path.isdir(path): import_file_by_path("{path}/{fname}".format(path=path, fname=fname)) def supplier_rfq_create_custom_fields(**args): from frappe.custom.doctype.custom_field.custom_field import create_custom_fields custom_fields = { 'Request for Quotation':[ dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Request for Quotation', fetch_if_empty= 0, fieldname= 'project_cf', fieldtype= 'Link', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'vendor', label= 'Project', length= 0, name= 'Request for Quotation-project_cf', no_copy= 0, options= 'Project', permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ), dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Request for Quotation', fetch_if_empty= 0, fieldname= 'supplier_comparison_section', fieldtype= 'Section Break', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'items', label= 'Supplier Comparison', length= 0, name= 'Request for Quotation-supplier_comparison_section', no_copy= 0, permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ), dict( allow_in_quick_entry= 0, allow_on_submit= 1, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Request for Quotation', fetch_if_empty= 0, fieldname= 'supplier_quotation_comparisons', fieldtype= 'Table', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'supplier_comparison_section', label= '', length= 0, name= 'Request for Quotation-supplier_quotation_comparisons', no_copy= 0, options= 'Supplier Quotation Comparison CT', permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ) ], 'Supplier Quotation Item':[ dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Supplier Quotation Item', fetch_if_empty= 0, fieldname= 'schedule_date', fieldtype= 'Date', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 1, in_standard_filter= 0, insert_after= 'item_name', label= 'Required Date', length= 0, name= 'Supplier Quotation Item-schedule_date', no_copy= 0, permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ) ], 'Supplier Quotation':[ dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Supplier Quotation', fetch_if_empty= 0, fieldname= 'supplier_uploaded_attachment_cf', fieldtype= 'Attach', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'supplier_name', label= 'Supplier Uploaded Attachment', length= 0, name= 'Supplier Quotation-supplier_uploaded_attachment_cf', no_copy= 0, permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0, ), dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Supplier Quotation', fetch_if_empty= 0, fieldname= 'supplier_comparison', fieldtype= 'Section Break', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'amended_from', label= 'Supplier Comparison', length= 0, name= 'Supplier Quotation-supplier_comparison', no_copy= 0, permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ), dict( allow_in_quick_entry= 0, allow_on_submit= 1, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Supplier Quotation', fetch_if_empty= 0, fieldname= 'supplier_quotation_comparisons', fieldtype= 'Table', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'supplier_comparison', label= '', length= 0, name= 'Supplier Quotation-supplier_quotation_comparisons', no_copy= 0, options= 'Supplier Quotation Comparison CT', permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 1, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ), dict( allow_in_quick_entry= 0, allow_on_submit= 0, bold= 0, collapsible= 0, columns= 0, docstatus= 0, doctype= 'Custom Field', dt= 'Supplier Quotation', fetch_if_empty= 0, fieldname= 'supplier_notes', fieldtype= 'Text', hidden= 0, ignore_user_permissions= 0, ignore_xss_filter= 0, in_global_search= 0, in_list_view= 0, in_standard_filter= 0, insert_after= 'terms', label= 'Supplier Notes', length= 0, name= 'Supplier Quotation-supplier_notes', no_copy= 0, permlevel= 0, print_hide= 0, print_hide_if_no_value= 0, read_only= 0, report_hide= 0, reqd= 0, search_index= 0, translatable= 0, unique= 0 ) ] } create_custom_fields(custom_fields) frappe.db.commit() # to avoid implicit-commit errors

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Erich6917/python_littlespider

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# -*- coding: utf-8 -*- # @Time : 2018/2/2 # @Author : LIYUAN134 # @File : aa.py # @Commment: # urls = [] urls = None if urls: print 'loops' else: print 'empty'

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# -*- coding: utf-8 -*- # Copyright 2014 Spanish National Research Council (CSIC) # # 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. """Module containing the APEL SSM Messenger.""" import json import typing import warnings # We are not parsing XML so this is safe import xml.etree.ElementTree as ETree # nosec import dirq.QueueSimple from oslo_config import cfg from oslo_log import log import caso.exception import caso.messenger import caso.record from caso import utils LOG = log.getLogger(__name__) opts = [ cfg.StrOpt( "output_path", default="/var/spool/apel/outgoing/openstack", help="Directory to put the generated SSM records.", ), cfg.IntOpt( "max_size", default=100, help="Maximum number of records to send per message" ), ] CONF = cfg.CONF CONF.register_opts(opts, group="ssm") __all__ = ["SSMMessenger", "SSMMessengerV04"] class SSMMessenger(caso.messenger.BaseMessenger): """SSM Messenger that pushes formatted messages to a dirq instance.""" version_cloud = "0.4" version_ip = "0.2" version_accelerator = "0.1" version_storage = None # FIXME: this cannot have a none version def __init__(self): """Initialize the SSM messenger with configured values.""" try: utils.makedirs(CONF.ssm.output_path) except Exception as err: LOG.error(f"Failed to create path {CONF.ssm.output_path} because {err}") raise err self.queue = dirq.QueueSimple.QueueSimple(CONF.ssm.output_path) def _push_message_cloud(self, entries: typing.List[str]): """Push a compute message, formatted following the CloudRecord.""" message = f"APEL-cloud-message: v{self.version_cloud}\n" aux = "\n%%\n".join(entries) message += f"{aux}\n" self.queue.add(message.encode("utf-8")) def _push_message_json( self, entries: typing.List[str], msg_type: str, version: str, ): """Push a JSON message with a UsageRecords list.""" message = { "Type": msg_type, "Version": version, "UsageRecords": [json.loads(r) for r in entries], } self.queue.add(json.dumps(message)) def _push_message_ip(self, entries: typing.List[str]): """Push an IP message.""" self._push_message_json(entries, "APEL Public IP message", self.version_ip) def _push_message_accelerator(self, entries: typing.List[str]): """Push an accelerator message.""" self._push_message_json( entries, "APEL-accelerator-message", self.version_accelerator ) def _push_message_storage(self, entries): """Push a storage message.""" ETree.register_namespace( "sr", "http://eu-emi.eu/namespaces/2011/02/storagerecord" ) root = ETree.Element("sr:StorageUsageRecords") for record in entries: # We are not parsing XML so this is safe sr = ETree.fromstring(record) # nosec root.append(sr) self.queue.add(ETree.tostring(root)) def _push(self, entries_cloud, entries_ip, entries_accelerator, entries_storage): """Push all messages, dividing them into smaller chunks. This method gets lists of messages to be pushed in smaller chucks as per GGUS ticket 143436: https://ggus.eu/index.php?mode=ticket_info&ticket_id=143436 """ for i in range(0, len(entries_cloud), CONF.ssm.max_size): entries = entries_cloud[i : i + CONF.ssm.max_size] # noqa(E203) self._push_message_cloud(entries) for i in range(0, len(entries_ip), CONF.ssm.max_size): entries = entries_ip[i : i + CONF.ssm.max_size] # noqa(E203) self._push_message_ip(entries) for i in range(0, len(entries_accelerator), CONF.ssm.max_size): entries = entries_accelerator[i : i + CONF.ssm.max_size] # noqa(E203) self._push_message_accelerator(entries) for i in range(0, len(entries_storage), CONF.ssm.max_size): entries = entries_storage[i : i + CONF.ssm.max_size] # noqa(E203) self._push_message_storage(entries) def push(self, records): """Push all records to SSM. This includes pushing the following records: - Cloud records - IP records - Accelerator records - Storage records This method will iterate over all the records, transforming them into the correct messages, then pushing it. """ if not records: return entries_cloud = [] entries_ip = [] entries_accelerator = [] entries_storage = [] for record in records: if isinstance(record, caso.record.CloudRecord): entries_cloud.append(record.ssm_message()) elif isinstance(record, caso.record.IPRecord): entries_ip.append(record.ssm_message()) elif isinstance(record, caso.record.AcceleratorRecord): entries_accelerator.append(record.ssm_message()) elif isinstance(record, caso.record.StorageRecord): entries_storage.append(record.ssm_message()) else: raise caso.exception.CasoError("Unexpected record format!") self._push(entries_cloud, entries_ip, entries_accelerator, entries_storage) class SSMMessengerV04(SSMMessenger): """Deprecated versioned SSM Messenger.""" def __init__(self): """Initialize the SSM V04 messenger. Deprecated not to be used, please stop using SSM versioned messengers. """ msg = ( "Using an versioned SSM messenger is deprecated, please use " "'ssm' as messenger instead in order to use the latest " "version." ) warnings.warn(msg, DeprecationWarning) super(SSMMessengerV04, self).__init__()

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def solution(clothes): answer = 1 closet = {} for cloth in clothes: closet[cloth[1]] = closet.get(cloth[1], 0) + 1 for k, v in closet.items(): answer *= v + 1 return answer - 1 clothes = [['yellow_hat', 'headgear'], ['blue_sunglasses', 'eyewear'], ['green_turban', 'headgear']] print(solution(clothes))

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# Python import unittest from unittest.mock import Mock # ATS from ats.topology import Device # Genie from genie.metaparser.util.exceptions import SchemaEmptyParserError from genie.libs.parser.iosxe.show_crypto import ShowCryptoPkiCertificates # ==================================================== # Unit test for 'show crypto pki certificates <WORD>' # ==================================================== class test_show_crypto_pki_certificate(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output_c3850 = { "trustpoints": { "CISCO_IDEVID_SUDI": { "associated_trustpoints":{ "certificate": { "status": "Available", "serial_number_in_hex": "793B572700000003750B", "subject": { "name": "WS-C3850-24P-0057D21BC800", "pid": "WS-C3850-24P", "cn": "WS-C3850-24P-0057D21BC800", "serial_number": "FCW1947C0GF" }, "issuer": { "cn": "Cisco Manufacturing CA SHA2", "o": "Cisco" }, "crl_distribution_points": "http://www.cisco.com/security/pki/crl/cmca2.crl", "usage": "General Purpose", "validity_date": { "start_date": "00:34:52 UTC Nov 20 2015", "end_date": "00:44:52 UTC Nov 20 2025" } }, "ca_certificate": { "status": "Available", "serial_number_in_hex": "02", "subject": { "cn": "Cisco Manufacturing CA SHA2", "o": "Cisco" }, "issuer": { "cn": "Cisco Root CA M2", "o": "Cisco" }, "crl_distribution_points": "http://www.cisco.com/security/pki/crl/crcam2.crl", "usage": "Signature", "validity_date": { "start_date": "13:50:58 UTC Nov 12 2012", "end_date": "13:00:17 UTC Nov 12 2037" } } } } } } golden_output_c3850 = {'execute.return_value': ''' Certificate Status: Available Certificate Serial Number (hex): 793B572700000003750B Certificate Usage: General Purpose Issuer: cn=Cisco Manufacturing CA SHA2 o=Cisco Subject: Name: WS-C3850-24P-0057D21BC800 Serial Number: PID:WS-C3850-24P SN:FCW1947C0GF cn=WS-C3850-24P-0057D21BC800 serialNumber=PID:WS-C3850-24P SN:FCW1947C0GF CRL Distribution Points: http://www.cisco.com/security/pki/crl/cmca2.crl Validity Date: start date: 00:34:52 UTC Nov 20 2015 end date: 00:44:52 UTC Nov 20 2025 Associated Trustpoints: CISCO_IDEVID_SUDI CA Certificate Status: Available Certificate Serial Number (hex): 02 Certificate Usage: Signature Issuer: cn=Cisco Root CA M2 o=Cisco Subject: cn=Cisco Manufacturing CA SHA2 o=Cisco CRL Distribution Points: http://www.cisco.com/security/pki/crl/crcam2.crl Validity Date: start date: 13:50:58 UTC Nov 12 2012 end date: 13:00:17 UTC Nov 12 2037 Associated Trustpoints: CISCO_IDEVID_SUDI Trustpool '''} golden_parsed_output_csr1000 = { 'trustpoints': {'TP-self-signed-4146203551': {'associated_trustpoints': {'router_self_signed_certificate': {'issuer': {'cn': 'IOS-Self-Signed-Certificate-4146203551'}, 'serial_number_in_hex': '01', 'status': 'Available', 'storage': 'nvram:IOS-Self-Sig#1.cer', 'subject': {'cn': 'IOS-Self-Signed-Certificate-4146203551', 'name': 'IOS-Self-Signed-Certificate-4146203551'}, 'usage': 'General Purpose', 'validity_date': {'end_date': '00:00:00 UTC Jan 1 2020', 'start_date': '21:37:27 UTC Apr 23 2018'}}}}}} golden_output_csr1000 = {'execute.return_value': ''' Router Self-Signed Certificate Status: Available Certificate Serial Number (hex): 01 Certificate Usage: General Purpose Issuer: cn=IOS-Self-Signed-Certificate-4146203551 Subject: Name: IOS-Self-Signed-Certificate-4146203551 cn=IOS-Self-Signed-Certificate-4146203551 Validity Date: start date: 21:37:27 UTC Apr 23 2018 end date: 00:00:00 UTC Jan 1 2020 Associated Trustpoints: TP-self-signed-4146203551 Storage: nvram:IOS-Self-Sig#1.cer '''} def test_empty(self): self.device = Mock(**self.empty_output) obj = ShowCryptoPkiCertificates(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() def test_c3850(self): self.maxDiff = None self.device = Mock(**self.golden_output_c3850) obj = ShowCryptoPkiCertificates(device=self.device) parsed_output = obj.parse(trustpoint_name='CISCO_IDEVID_SUDI') self.assertEqual(parsed_output, self.golden_parsed_output_c3850) def test_csr1000(self): self.maxDiff = None self.device = Mock(**self.golden_output_csr1000) obj = ShowCryptoPkiCertificates(device=self.device) parsed_output = obj.parse(trustpoint_name='TP-self-signed-4146203551') self.assertEqual(parsed_output, self.golden_parsed_output_csr1000) if __name__ == '__main__': unittest.main()

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jeaubin@cisco.com

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/deployment_validation/csv_to_yaml_convertor/csv_to_yaml_convertor.py

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from os.path import dirname, abspath, join from robot.api import logger from shutil import copyfile import csv import re import sys import yaml current_dir = dirname(dirname(abspath(__file__))) class CsvToYamlConvertor: """ Take the CSV input and covert it into yaml format. """ def __init__(self, service, base_yaml_file_path, csv_file_path, dir_to_store_yaml, filename=None): """ :param service: TAS or Middlewware or worker or deployment :param yaml_file_path: Base YAML file name along with the location :param csv_file_path: CSV file name with the location """ self.yaml_file_path = base_yaml_file_path self.dir_to_store_yaml = dir_to_store_yaml self.file_name = filename # Open our data file in read-mode. self.csvfile = open(csv_file_path, 'r') # Save a CSV Reader object. self.datareader = csv.reader(self.csvfile, delimiter=',', quotechar='"') # Service name self.service = service # Empty array for data headings, which we will fill with the first row from our CSV. self.data_headings = [] def load_yaml_file(self, filename): """ load YAML file In case of any error, this function calls sys.exit(1) :param filename: YAML filename along with the location :return: YAML as dict """ try: with open(filename, 'r') as stream: try: return yaml.safe_load(stream) except yaml.YAMLError as exc: logger.error(exc) sys.exit(1) except IOError as e: logger.error(e) sys.exit(1) def update_yaml_data(self, myYaml, key, value, append_mode=False): """ Set or add a key to given YAML data. Call itself recursively. :param myYaml: YAML data to be modified :param key: key as array of key tokens :param value: value of any data type :param append_mode default is False :return: modified YAML data """ if len(key) == 1: if not append_mode or not key[0] in myYaml: myYaml[key[0]] = value else: if type(myYaml[key[0]]) is not list: myYaml[key[0]] = [myYaml[key[0]]] myYaml[key[0]].append(value) else: if not key[0] in myYaml or type(myYaml[key[0]]) is not dict: myYaml[key[0]] = {} myYaml[key[0]] = self.update_yaml_data(myYaml[key[0]], key[1:], value, append_mode) return myYaml def rm_yaml_data(self, myYaml, key): """ Remove a key and it's value from given YAML data structure. No error or such thrown if the key doesn't exist. :param myYaml: YAML data to be modified :param key: key as array of key tokens :return: modified YAML data """ if len(key) == 1 and key[0] in myYaml: del myYaml[key[0]] elif key[0] in myYaml: myYaml[key[0]] = self.rm_yaml_data(myYaml[key[0]], key[1:]) return myYaml def save_yaml(self, data, yaml_file): """ Saves given YAML data to file and upload yaml file to remote machine :param data: YAML data :param yaml_file: Location to save the yaml file """ try: with open(yaml_file, 'w') as outfile: yaml.dump(data, outfile, default_flow_style=False) except IOError as e: logger.error(e) sys.exit(1) def convert_csv_to_yaml(self): """ Update the yaml file and save it """ # Loop through each row... for row_index, row in enumerate(self.datareader): # If this is the first row, populate our data_headings variable. if row_index == 0: data_headings = row # Othrwise, create a YAML file from the data in this row... else: # Create a new config.yaml with filename based on index number (Tenant ID) of our current row # and service if self.file_name is None: file_name = str(row[0]) + '_' + self.service.lower() + '_config' + '.yaml' else: file_name = self.file_name + '_' + 'config' + '.yaml' updated_yaml_file_path = join(self.dir_to_store_yaml, file_name) copyfile(self.yaml_file_path, updated_yaml_file_path) readyamldata = self.load_yaml_file(updated_yaml_file_path) # Empty string that we will fill with YAML formatted text based on data extracted from our CSV. yaml_text = "" # Loop through each cell in this row... for cell_index, cell in enumerate(row): # Compile a line of YAML text from our headings list and the text of the current cell, # followed by a linebreak. # Heading text is converted to lowercase. Spaces are converted to underscores and hyphens # are removed. # In the cell text, line endings are replaced with commas. cell_heading = data_headings[cell_index].replace(" ", "_").replace("-", "") # Create the list of keys cell_items = cell_heading.split('.') if len(cell_items) == 1: cell_keys = [cell_heading] else: cell_keys = cell_items # Get the cell value cell_value = cell.replace("\n", ", ") # Update the data in yaml format set_value = self.update_yaml_data(readyamldata, cell_keys, cell_value) # Save the yaml data into a file self.save_yaml(set_value, updated_yaml_file_path) # Open the above yaml file to update the list formatted data f = open(updated_yaml_file_path, 'r') f = f.read() # Convert the data into list format using regex final = (re.sub(r'(\'[0-9]\'\:\s+)', '- ', str(f))) # Save the file with open(updated_yaml_file_path, 'w') as f: f.write(final) # Close the CSV self.csvfile.close() # Sample Execution # yamlObj = CsvToYamlConvertor('tas', r'C:\Users\config.yaml', r'C:\Users\Downloads\inputfile.csv') # yamlObj.convert_csv_to_yaml()

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n, m = [int(i) for i in input().split()] xyz = [[int(i) for i in input().split()] for _ in range(n)] ans = 0 a = [0]*3 for a[0] in range(-1, 2, 2): for a[1] in range(-1, 2, 2): for a[2] in range(-1, 2, 2): d = list(map(lambda x: sum([i * j for i, j in zip(a, x)]), xyz)) d.sort(reverse=1) ans = max(ans, sum(d[:m])) print(ans)

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import os import arrow import logging import argparse import numpy as np import torch import torch as th import torch.nn as nn from pathlib import Path from leibniz.unet.base import UNet from leibniz.unet.complex_hyperbolic import CmplxHyperBottleneck from leibniz.unet.hyperbolic import HyperBottleneck from leibniz.unet.senet import SEBottleneck from leibniz.nn.activation import CappingRelu from blks.direct import DirectBlocks from blks.am import AMBlocks from dataset.chaos_parabola import ChaosParabolaDataSet parser = argparse.ArgumentParser() parser.add_argument("-g", "--gpu", type=str, default='0', help="index of gpu") parser.add_argument("-c", "--n_cpu", type=int, default=64, help="number of cpu threads to use during batch generation") parser.add_argument("-b", "--batch_size", type=int, default=64, help="size of the batches") parser.add_argument("-e", "--epoch", type=int, default=0, help="current epoch to start training from") parser.add_argument("-n", "--n_epochs", type=int, default=500, help="number of epochs of training") parser.add_argument("-m", "--model", type=str, default='', help="metrological model to load") parser.add_argument("-k", "--check", type=str, default='', help="checkpoint file to load") opt = parser.parse_args() os.environ['CUDA_VISIBLE_DEVICES'] = opt.gpu print('cudnn:', th.backends.cudnn.version()) np.core.arrayprint._line_width = 150 np.set_printoptions(linewidth=np.inf) name = opt.model time_str = arrow.now().format('YYYYMMDD_HHmmss') model_path = Path(f'./_log-{time_str}') model_path.mkdir(exist_ok=True) log_file = model_path / Path('train.log') logging.basicConfig(level=logging.INFO, filename=log_file, filemode='w') logger = logging.getLogger() logger.setLevel(logging.INFO) logger.info(str(opt)) root = './data' if not os.path.exists(root): os.mkdir(root) train_set = ChaosParabolaDataSet(length=800) test_set = ChaosParabolaDataSet(length=200) batch_size = opt.batch_size train_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, shuffle=True) test_loader = torch.utils.data.DataLoader( dataset=test_set, batch_size=batch_size, shuffle=False) mean_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, shuffle=True) total_sum = 0.0 total_cnt = 0.0 for step, sample in enumerate(mean_loader): input, target = sample input, target = input.float(), target.float() data = th.cat((input, target), dim=1) total_sum += data.sum().item() total_cnt += np.prod(data.size()) mean = total_sum / total_cnt print(mean) std_loader = torch.utils.data.DataLoader( dataset=train_set, batch_size=batch_size, shuffle=True) total_std = 0.0 total_cnt = 0.0 for step, sample in enumerate(mean_loader): input, target = sample input, target = input.float(), target.float() data = th.cat((input, target), dim=1) total_std += ((data - mean) * (data - mean)).sum().item() total_cnt += np.prod(data.size()) std = total_std / total_cnt print(std) class LearningModel(nn.Module): def __init__(self): super().__init__() self.unet = UNet(2, 10, normalizor='batch', spatial=(32, 32), layers=5, ratio=0, vblks=[2, 2, 2, 2, 2], hblks=[2, 2, 2, 2, 2], scales=[-1, -1, -1, -1, -1], factors=[1, 1, 1, 1, 1], block=AMBlocks, relu=CappingRelu(), final_normalized=True) def forward(self, input): input = (input - mean) / std output = self.unet(input) output = output * std + mean return output class PerfectModel(nn.Module): def __init__(self): super().__init__() self.dummy = th.zeros(1) def forward(self, input): result = [] z = input[:, 1:2] for ix in range(10): z = 1 - 2 * z * z result.append(z) return th.cat(result, dim=1) mdl = LearningModel() pfc = PerfectModel() mse = nn.MSELoss() optimizer = th.optim.Adam(mdl.parameters()) def train(epoch): train_size = 0 loss_per_epoch = 0.0 mdl.train() for step, sample in enumerate(train_loader): input, target = sample input, target = input.float(), target.float() if th.cuda.is_available(): input = input.cuda() target = target.cuda() mdl.cuda() result = mdl(input) loss = mse(result, target) optimizer.zero_grad() loss.backward() optimizer.step() batch = result.size()[0] logger.info(f'Epoch: {epoch + 1:03d} | Step: {step + 1:03d} | Loss: {loss.item()}') loss_per_epoch += loss.item() * batch train_size += batch logger.info(f'Epoch: {epoch + 1:03d} | Train Loss: {loss_per_epoch / train_size}') def test(epoch): mdl.eval() test_size = 0 loss_per_epoch = 0.0 for step, sample in enumerate(test_loader): input, target = sample input, target = input.float(), target.float() if th.cuda.is_available(): input = input.cuda() target = target.cuda() mdl.cuda() with th.no_grad(): result = mdl(input) loss = mse(result, target) batch = result.size()[0] logger.info(f'Epoch: {epoch + 1:03d} | Step: {step + 1:03d} | Loss: {loss.item()}') loss_per_epoch += loss.item() * batch test_size += batch logger.info(f'Epoch: {epoch + 1:03d} | Test Loss: {loss_per_epoch / test_size}') def baseline(epoch): test_size = 0 loss_per_epoch = 0.0 for step, sample in enumerate(test_loader): input, target = sample input, target = input.float(), target.float() if th.cuda.is_available(): input = input.cuda() target = target.cuda() pfc.cuda() with th.no_grad(): result = pfc(input) loss = mse(result, target) batch = result.size()[0] logger.info(f'Epoch: {epoch + 1:03d} | Step: {step + 1:03d} | Loss: {loss.item()}') loss_per_epoch += loss.item() * batch test_size += batch logger.info(f'Epoch: {epoch + 1:03d} | Baseline: {loss_per_epoch / test_size}') if __name__ == '__main__': for epoch in range(opt.n_epochs): try: train(epoch) test(epoch) baseline(epoch) except Exception as e: logger.exception(e) break

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########################################################################## # # Copyright (c) 2012, Image Engine Design Inc. All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above # copyright notice, this list of conditions and the following # disclaimer. # # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following # disclaimer in the documentation and/or other materials provided with # the distribution. # # * Neither the name of John Haddon nor the names of # any other contributors to this software may be used to endorse or # promote products derived from this software without specific prior # written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS # IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR # PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF # LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING # NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ########################################################################## import threading import traceback import weakref import IECore import Gaffer ## The OpMatcher class provides a means of searching for Ops suitable to # act upon a given input value. # # The following Op userData entries are supported : # # ["OpMatcher"]["ignore"] - when this BoolData is True, the Op is not # considered by the matcher. # # The following Parameter usedData entries are supported : # # ["OpMatcher"]["ignore"] - when this BoolData is True, the Parameter is not # considered by the matcher. class OpMatcher() : def __init__( self, classLoader, classNamesMatchString = "*", reportErrors=True ) : # these are filled with tuples of the form ( opClass, parameter, parameterPath ) self.__ops = [] for className in classLoader.classNames( classNamesMatchString ) : try : opClass = classLoader.load( className ) opInstance = opClass() except Exception, m : if reportErrors : IECore.msg( IECore.Msg.Level.Error, "Gaffer.OpMatcher", "Error loading op \"%s\" : %s" % ( className, traceback.format_exc() ) ) continue ignore = False with IECore.IgnoredExceptions( KeyError ) : # backwards compatibility with something proprietary ignore = opInstance.userData()["UI"]["OpMatcher"]["ignore"].value with IECore.IgnoredExceptions( KeyError ) : ignore = opInstance.userData()["OpMatcher"]["ignore"].value if ignore : continue parameters = [] self.__findParameters( opInstance.parameters(), parameters ) if len( parameters ) : self.__ops.append( ( opClass, parameters ) ) ## Returns a list of ( op, parameter ) tuples. Each op will be an Op instance # where the corresponding parameter has already been set with parameterValue. def matches( self, parameterValue ) : processedValues = [] if isinstance( parameterValue, ( Gaffer.FileSystemPath, Gaffer.SequencePath ) ) : # we might be able to match a single file processedValues.append( IECore.StringData( str( parameterValue ) ) ) # or provide a single file input to an op which accepts multiple files processedValues.append( IECore.StringVectorData( [ str( parameterValue ) ] ) ) elif isinstance( parameterValue, list ) : processedValue = IECore.StringVectorData() for value in parameterValue : assert( isinstance( value, ( Gaffer.FileSystemPath, Gaffer.SequencePath ) ) ) processedValue.append( str( value ) ) elif isinstance( parameterValue, IECore.Object ) : processedValue = parameterValue if not processedValues : return [] result = [] for opClass, parameters in self.__ops : for testParameter, parameterPath in parameters : for processedValue in processedValues : if testParameter.valueValid( processedValue )[0] : op = opClass() parameter = op.parameters() for name in parameterPath : parameter = parameter[name] parameter.setValue( processedValue ) result.append( ( op, parameter ) ) return result __defaultInstances = weakref.WeakKeyDictionary() __defaultInstancesMutex = threading.Lock() ## Returns an OpMatcher suitable for sharing by everyone - initialising one # takes considerable time so it's preferable to reuse one if one has been created # for the classLoader in question already. If classLoader is not specified then # it defaults to IECore.ClassLoader.defaultOpLoader(). @classmethod def defaultInstance( cls, classLoader=None ) : if classLoader is None : classLoader = IECore.ClassLoader.defaultOpLoader() with cls.__defaultInstancesMutex : result = cls.__defaultInstances.get( classLoader, None ) if result is None : result = OpMatcher( classLoader ) cls.__defaultInstances[classLoader] = result return result def __findParameters( self, parameter, result, path = None ) : if path is None : path = [] for child in parameter.values() : ignore = False with IECore.IgnoredExceptions( KeyError ) : # backwards compatibility with something proprietary ignore = child.userData()["UI"]["OpMatcher"]["ignore"].value with IECore.IgnoredExceptions( KeyError ) : # backwards compatibility with something proprietary ignore = child.userData()["OpMatcher"]["ignore"].value if ignore : continue childPath = path + [ child.name ] if isinstance( child, IECore.CompoundParameter ) : self.__findParameters( child, result, childPath ) elif isinstance( child, ( IECore.PathParameter, IECore.PathVectorParameter ) ) : if child.mustExist : result.append( ( child, childPath ) )

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def check(): print("模拟的扩展功能") def outter(func): def inner(name): check() func(name) return inner # 在函数的上方加上@符号,@符号加上一个装饰器名,表示将该名字对应的装饰器应用在该函数上 # 本质: 相当于执行了 func1 = outter(func1) 跟函数名同名的一个装饰后的函数名 = 装饰器名(函数名) @outter def func1(name): print("基础功能1") print("名字是:%s"%(name)) # def func2(): # print("基础功能2") func1("金三胖胖")

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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 azure.identity import DefaultAzureCredential from azure.mgmt.network import NetworkManagementClient """ # PREREQUISITES pip install azure-identity pip install azure-mgmt-network # USAGE python virtual_network_create_subnet_with_address_prefixes.py Before run the sample, please set the values of the client ID, tenant ID and client secret of the AAD application as environment variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET. For more info about how to get the value, please see: https://docs.microsoft.com/azure/active-directory/develop/howto-create-service-principal-portal """ def main(): client = NetworkManagementClient( credential=DefaultAzureCredential(), subscription_id="subid", ) response = client.virtual_networks.begin_create_or_update( resource_group_name="rg1", virtual_network_name="test-vnet", parameters={ "location": "eastus", "properties": { "addressSpace": {"addressPrefixes": ["10.0.0.0/16"]}, "subnets": [{"name": "test-2", "properties": {"addressPrefixes": ["10.0.0.0/28", "10.0.1.0/28"]}}], }, }, ).result() print(response) # x-ms-original-file: specification/network/resource-manager/Microsoft.Network/stable/2023-04-01/examples/VirtualNetworkCreateSubnetWithAddressPrefixes.json if __name__ == "__main__": main()

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# Given a array of strings ,we need to find the longest common prefix in them. # this function take the input array as a parameter and return the longest common prefix . def longest_common_prefix(input_array): min_length = 999999999999999 # min_length to store the length of the string with minimum size among all other strings min_index = -1 # min_index to store the index of the minimum length string n = len(input_array) # n store the length of the input array prefix = '' # traversing the input_array for i in range(0,n): length = len(input_array[i]) # length store the length the ith string in the array if length < min_length : min_length = length min_index = i min_word = input_array[min_index] # min_word is the string with minimum length for i in range(0,min_length): # traversing the min_word cur_alphabet = min_word[i] count = 0 for j in range(0,n): # traversing the array if input_array[j][i] == cur_alphabet : count += 1 else: break if count == n : prefix += cur_alphabet else: break return prefix # test case input_array = ['abcdef','abcdf'] answer = longest_common_prefix(input_array) print(answer)

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import torch from mmseg.models.decode_heads import NLHead from .utils import to_cuda def test_nl_head(): head = NLHead(in_channels=32, channels=16, num_classes=19) assert len(head.convs) == 2 assert hasattr(head, 'nl_block') inputs = [torch.randn(1, 32, 45, 45)] if torch.cuda.is_available(): head, inputs = to_cuda(head, inputs) outputs = head(inputs) assert outputs.shape == (1, head.num_classes, 45, 45)

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'''Escreva uma função não recursiva que receba como parâmetro uma lista de inteiros e retorne como resposta a soma de todos os elementos da lista''' lista = [10,20,30] def soma_elementos(lista): soma = 0 for elemento in lista: soma += int(elemento) print("A soma dos elementos é", soma) soma = soma_elementos(lista)

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import time import argparse import numpy as np import torch import torch.nn.functional as F import torch.optim as optim from utils import sgc_precompute, set_seed, stack_feat, load_donuts from models import get_model from metrics import accuracy import pickle as pkl from args import get_syn_args from time import perf_counter from noise import zero_idx, gaussian from train import train_regression, test_regression,\ train_gcn, test_gcn,\ train_kgcn, test_kgcn # Arguments args = get_syn_args() # setting random seeds set_seed(args.seed, args.cuda) adj, features, labels, idx_train,\ idx_val, idx_test, mesh_pack = load_donuts(args.gen_num_samples, args.gen_noise, args.gen_factor, args.gen_test_size, args.gen_num_neigh, args.normalization, args.cuda, args.invlap_alpha, args.gen_mesh, args.gen_mesh_step) ### NOISE TO FEATURES ONLY USE ZERO HERE if args.noise != "None": features = features.numpy() if args.noise == "gaussian": features = gaussian(features, mean=args.gaussian_opt[0], std=args.gaussian_opt[1]) if args.noise == "zero_test": idx_test = idx_test.numpy() features = zero_idx(features, idx_test) idx_test = torch.LongTensor(idx_test) if args.cuda: idx_test = idx_test.cuda() if args.noise != "None": features = torch.FloatTensor(features).float() if args.cuda: features = features.cuda() ### END NOISE TO FEATURES # Monkey patch for Stacked Logistic Regression if args.model == "SLG": nfeat = features.size(1) * args.degree else: nfeat = features.size(1) model = get_model(model_opt=args.model, nfeat=nfeat, nclass=labels.max().item()+1, nhid=args.hidden, dropout=args.dropout, cuda=args.cuda, degree=args.degree) if args.model == "SGC" or args.model == "gfnn": features, precompute_time = sgc_precompute(features, adj, args.degree) print("{:.4f}s".format(precompute_time)) model, acc_val, train_time = train_regression(model, features[idx_train], labels[idx_train], features[idx_val], labels[idx_val], args.epochs, args.weight_decay, args.lr, args.dropout) acc_test = test_regression(model, features[idx_test], labels[idx_test]) print("Validation Accuracy: {:.4f} Test Accuracy: {:.4f}".format(acc_val,\ acc_test)) print("Pre-compute time: {:.4f}s, train time: {:.4f}s, total: {:.4f}s".format(precompute_time, train_time, precompute_time+train_time)) if args.model == "SLG": features, precompute_time = stack_feat(features, adj, args.degree) features = torch.FloatTensor(features).float() if args.cuda: features = features.cuda() print("{:.4f}s".format(precompute_time)) model, acc_val, train_time = train_regression(model, features[idx_train], labels[idx_train], features[idx_val], labels[idx_val], args.epochs, args.weight_decay, args.lr, args.dropout) acc_test = test_regression(model, features[idx_test], labels[idx_test]) print("Validation Accuracy: {:.4f} Test Accuracy: {:.4f}".format(acc_val,\ acc_test)) print("Pre-compute time: {:.4f}s, train time: {:.4f}s, total: {:.4f}s".format(precompute_time, train_time, precompute_time+train_time)) if args.model == "GCN": model, acc_val, train_time = train_gcn(model, adj, features, labels, idx_train, idx_val, args.epochs, args.weight_decay, args.lr, args.dropout) acc_test = test_gcn(model, adj, features, labels, idx_test) print("Validation Accuracy: {:.4f} Test Accuracy: {:.4f}".format(acc_val,\ acc_test)) precompute_time = 0 print("Pre-compute time: {:.4f}s, train time: {:.4f}s, total: {:.4f}s".format(precompute_time, train_time, precompute_time+train_time)) if args.model == "KGCN": model, acc_val, train_time = train_kgcn(model, adj, features, labels, idx_train, idx_val, args.epochs, args.weight_decay, args.lr, args.dropout) acc_test = test_kgcn(model, adj, features, labels, idx_test) precompute_time = 0 print("Validation Accuracy: {:.4f} Test Accuracy: {:.4f}".format(acc_val,\ acc_test)) print("Pre-compute time: {:.4f}s, train time: {:.4f}s, total: {:.4f}s".format(precompute_time, train_time, precompute_time+train_time))

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import datetime from common.models.pay.PayOrder import PayOrder from application import app,db from common.libs.pay.PayService import PayService ''' python manager.py runjob -m pay/index ''' class JobTask(): def __init__(self): pass def run(self): now = datetime.datetime.now() date_before_30min = now + datetime.timedelta(minutes=-30) list = PayOrder.query.filter_by(status=-8)\ .filter(PayOrder.created_time <= date_before_30min.strftime('%Y-%m-%d %H:%M:%S')).all() if not list: return pay_target = PayService() for item in list: pay_target.closeOrder(pay_order_id= item.id)

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"""배열 array의 i번째 숫자부터 j번째 숫자까지 자르고 정렬했을 때, k번째에 있는 수를 구하려 합니다. 예를 들어 array가 [1, 5, 2, 6, 3, 7, 4], i = 2, j = 5, k = 3이라면 array의 2번째부터 5번째까지 자르면 [5, 2, 6, 3]입니다. 1에서 나온 배열을 정렬하면 [2, 3, 5, 6]입니다. 2에서 나온 배열의 3번째 숫자는 5입니다. 배열 array, [i, j, k]를 원소로 가진 2차원 배열 commands가 매개변수로 주어질 때, commands의 모든 원소에 대해 앞서 설명한 연산을 적용했을 때 나온 결과를 배열에 담아 return 하도록 solution 함수를 작성해주세요.""" array = [1, 5, 2, 6, 3, 7, 4] commands = [[2, 5, 3], [4, 4, 1], [1, 7, 3]] # 예상 답 : [5, 6, 3] def solutioned(array, commands): answer = [] div_arr = [] for i in range(len(commands)): for j in range(len(commands[i])): div_arr.append(commands[i][j]) print(f'index : {i}, {j} => {commands[i][j]}') if (j % 2) == 0: lst = array[div_arr[0] - 1:div_arr[1]] print(lst) lst.sort() answer.append(lst[div_arr[2] - 1]) print(f'sorted:{lst}') print(div_arr) div_arr.clear() print(answer) return answer # solutioned(array,commands) def solution(array, commands): answer = [] div_arr = [] for i in range(len(commands)): for j in range(len(commands[i])): div_arr.append(commands[i][j]) if (j % 2) == 0: lst = array[div_arr[0] - 1:div_arr[1]] lst.sort() answer.append(lst[div_arr[2] - 1]) div_arr.clear() return answer solutioned(array, commands)

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from flask_restplus import Namespace from app.api.securities.resources.bond import BondListResource, BondResource from app.api.securities.resources.bond_status import BondStatusResource from app.api.securities.resources.bond_type import BondTypeResource from app.api.securities.resources.bond_document import BondDocumentListResource from app.api.securities.resources.reclamation_invoice import ReclamationInvoiceListResource, ReclamationInvoiceResource from app.api.securities.resources.reclamation_invoice_document import ReclamationInvoiceDocumentListResource api = Namespace('securities', description='Securities operations') # Bonds api.add_resource(BondListResource, '/bonds') api.add_resource(BondResource, '/bonds/<bond_guid>') api.add_resource(BondStatusResource, '/bonds/status-codes') api.add_resource(BondTypeResource, '/bonds/type-codes') api.add_resource(BondDocumentListResource, '/<string:mine_guid>/bonds/documents') # Reclamation Invoices api.add_resource(ReclamationInvoiceListResource, '/reclamation-invoices') api.add_resource(ReclamationInvoiceResource, '/reclamation-invoices/<reclamation_invoice_guid>') api.add_resource(ReclamationInvoiceDocumentListResource, '/<string:mine_guid>/reclamation-invoices/documents')

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''' some Mac code from the internet // Path to resource files in Mac bundle wxString m_resourceDir; // container of locally activated font ATSFontContainerRef m_fontContainer; FSSpec spec; wxMacFilename2FSSpec(m_resourceDir + _T("Bank Gothic Light.ttf"), &spec); OSStatus status = ATSFontActivateFromFileSpecification(&spec, kATSFontContextLocal, kATSFontFormatUnspecified, NULL, kATSOptionFlagsDefault, &m_fontContainer); wxASSERT_MSG(status == noErr, _T("font activation failed")); and then anywhere in the app this works fine: wxFont(9, wxFONTFAMILY_DEFAULT, wxFONTSTYLE_NORMAL | wxFONTFLAG_ANTIALIASED, wxFONTWEIGHT_NORMAL, false, _T("Bank Gothic Light")); ''' import gui.native def loadfont(fontpath, private = True, enumerable = False): gui.native.notImplemented() return False def unloadfont(fontpath): gui.native.notImplemented() return False

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# encoding: utf-8 # module _imp # from (built-in) # by generator 1.147 """ (Extremely) low-level import machinery bits as used by importlib and imp. """ # no imports # functions def acquire_lock(*args, **kwargs): # real signature unknown """ Acquires the interpreter's import lock for the current thread. This lock should be used by import hooks to ensure thread-safety when importing modules. On platforms without threads, this function does nothing. """ pass def create_builtin(*args, **kwargs): # real signature unknown """ Create an extension module. """ pass def create_dynamic(*args, **kwargs): # real signature unknown """ Create an extension module. """ pass def exec_builtin(*args, **kwargs): # real signature unknown """ Initialize a built-in module. """ pass def exec_dynamic(*args, **kwargs): # real signature unknown """ Initialize an extension module. """ pass def extension_suffixes(*args, **kwargs): # real signature unknown """ Returns the list of file suffixes used to identify extension modules. """ pass def get_frozen_object(*args, **kwargs): # real signature unknown """ Create a code object for a frozen module. """ pass def init_frozen(*args, **kwargs): # real signature unknown """ Initializes a frozen module. """ pass def is_builtin(*args, **kwargs): # real signature unknown """ Returns True if the module name corresponds to a built-in module. """ pass def is_frozen(*args, **kwargs): # real signature unknown """ Returns True if the module name corresponds to a frozen module. """ pass def is_frozen_package(*args, **kwargs): # real signature unknown """ Returns True if the module name is of a frozen package. """ pass def lock_held(*args, **kwargs): # real signature unknown """ Return True if the import lock is currently held, else False. On platforms without threads, return False. """ pass def release_lock(*args, **kwargs): # real signature unknown """ Release the interpreter's import lock. On platforms without threads, this function does nothing. """ pass def _fix_co_filename(*args, **kwargs): # real signature unknown """ Changes code.co_filename to specify the passed-in file path. code Code object to change. path File path to use. """ pass # classes class __loader__(object): """ Meta path import for built-in modules. All methods are either class or static methods to avoid the need to instantiate the class. """ @classmethod def create_module(cls, *args, **kwargs): # real signature unknown """ Create a built-in module """ pass @classmethod def exec_module(cls, *args, **kwargs): # real signature unknown """ Exec a built-in module """ pass @classmethod def find_module(cls, *args, **kwargs): # real signature unknown """ Find the built-in module. If 'path' is ever specified then the search is considered a failure. This method is deprecated. Use find_spec() instead. """ pass @classmethod def find_spec(cls, *args, **kwargs): # real signature unknown pass @classmethod def get_code(cls, *args, **kwargs): # real signature unknown """ Return None as built-in modules do not have code objects. """ pass @classmethod def get_source(cls, *args, **kwargs): # real signature unknown """ Return None as built-in modules do not have source code. """ pass @classmethod def is_package(cls, *args, **kwargs): # real signature unknown """ Return False as built-in modules are never packages. """ pass @classmethod def load_module(cls, *args, **kwargs): # real signature unknown """ Load the specified module into sys.modules and return it. This method is deprecated. Use loader.exec_module instead. """ pass def module_repr(module): # reliably restored by inspect """ Return repr for the module. The method is deprecated. The import machinery does the job itself. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass __weakref__ = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """list of weak references to the object (if defined)""" __dict__ = None # (!) real value is "mappingproxy({'__module__': '_frozen_importlib', '__doc__': 'Meta path import for built-in modules.\\n\\n All methods are either class or static methods to avoid the need to\\n instantiate the class.\\n\\n ', 'module_repr': <staticmethod object at 0x7fd1b260b048>, 'find_spec': <classmethod object at 0x7fd1b260b080>, 'find_module': <classmethod object at 0x7fd1b260b0b8>, 'create_module': <classmethod object at 0x7fd1b260b0f0>, 'exec_module': <classmethod object at 0x7fd1b260b128>, 'get_code': <classmethod object at 0x7fd1b260b198>, 'get_source': <classmethod object at 0x7fd1b260b208>, 'is_package': <classmethod object at 0x7fd1b260b278>, 'load_module': <classmethod object at 0x7fd1b260b2b0>, '__dict__': <attribute '__dict__' of 'BuiltinImporter' objects>, '__weakref__': <attribute '__weakref__' of 'BuiltinImporter' objects>})" # variables with complex values __spec__ = None # (!) real value is "ModuleSpec(name='_imp', loader=<class '_frozen_importlib.BuiltinImporter'>)"

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#!/usr/bin/env python from spf.mr.language.type_.complex_type import ComplexType from spf.mr.lambda_.logic_language_services import LogicLanguageServices from spf.mr.lambda_.visitor.api import LogicalExpressionVisitorI class GetAllPredicates(LogicalExpressionVisitorI): def __init__(self): self.predicates = set() @staticmethod def of(expr): visitor = GetAllPredicates() visitor.visit(expr) return visitor.predicates def visit_lambda(self, lambda_): lambda_.get_argument().accept(self) lambda_.get_body().accept(self) def visit_literal(self, literal): literal.get_predicate().accept(self) for arg in literal.get_arguments(): arg.accept(self) def visit_logical_constant(self, logical_constant): if (isinstance(logical_constant.get_type(), ComplexType) and not LogicLanguageServices.is_coordination_predicate(logical_constant) and not LogicLanguageServices.is_array_index_predicate(logical_constant) and not LogicLanguageServices.is_array_sub_predicate(logical_constant)): self.predicates.add(logical_constant) def visit_logical_expression(self, logical_expr): logical_expr.accept(self) def visit_variable(self, variable): return

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oneplus.lau@gmail.com

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class Bob: def hey(self, msg): if self.is_silence(msg): return "Fine. Be that way!" elif self.is_shout(msg): return "Woah, chill out!" elif self.is_question(msg): return "Sure." else: return "Whatever." def is_silence(self, msg): return msg is None or msg.strip() == '' def is_shout(self, msg): return msg.isupper() def is_question(self, msg): return msg.endswith("?")

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rrc@berkeley.edu

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# Python - 3.6.0 test.describe('Testing sum_array') test.assert_equals(sum_array([]), 0) test.assert_equals(sum_array([1, 2, 3]), 6) test.assert_equals(sum_array([1.1, 2.2, 3.3]), 6.6) test.assert_equals(sum_array([4, 5, 6]), 15) test.assert_equals(sum_array(range(101)), 5050)

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while True: age = input('Enter your age: ') age = int(age) if age <= 3: print('Your ticked is free.') elif age > 3 and age <= 12: print('Your ticket costs $10.') elif age > 12 and age < 100: print('Your ticket costs $15.') else: break

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# Copyright 2016 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import optparse from blinkpy.common.checkout.baseline_optimizer import BaselineOptimizer from blinkpy.tool.commands.analyze_baselines import AnalyzeBaselines from blinkpy.tool.commands.rebaseline_unittest import BaseTestCase class _FakeOptimizer(BaselineOptimizer): def read_results_by_directory(self, baseline_name): if baseline_name.endswith('txt'): return {'LayoutTests/passes/text.html': '123456'} return {} class TestAnalyzeBaselines(BaseTestCase): command_constructor = AnalyzeBaselines def setUp(self): super(TestAnalyzeBaselines, self).setUp() self.port = self.tool.port_factory.get('test') self.tool.port_factory.get = (lambda port_name=None, options=None: self.port) self.lines = [] self.command._optimizer_class = _FakeOptimizer self.command._write = (lambda msg: self.lines.append(msg)) def test_default(self): self.command.execute(optparse.Values(dict(suffixes='txt', missing=False, platform=None)), ['passes/text.html'], self.tool) self.assertEqual(self.lines, ['passes/text-expected.txt:', ' (generic): 123456']) def test_missing_baselines(self): self.command.execute( optparse.Values( dict( suffixes='png,txt', missing=True, platform=None)), ['passes/text.html'], self.tool) self.assertEqual(self.lines, ['passes/text-expected.png: (no baselines found)', 'passes/text-expected.txt:', ' (generic): 123456'])

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arnaud@geometry.ee

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lxtxl/aws_cli

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#!/usr/bin/python # -*- codding: utf-8 -*- import os import sys sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__)))) from common.execute_command import write_three_parameter # url : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/attach-disk.html if __name__ == '__main__': """ create-disk : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/create-disk.html delete-disk : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/delete-disk.html detach-disk : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/detach-disk.html get-disk : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/get-disk.html get-disks : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/lightsail/get-disks.html """ parameter_display_string = """ # disk-name : The unique Lightsail disk name (e.g., my-disk ). # instance-name : The name of the Lightsail instance where you want to utilize the storage disk. # disk-path : The disk path to expose to the instance (e.g., /dev/xvdf ). """ add_option_dict = {} add_option_dict["parameter_display_string"] = parameter_display_string # ex: add_option_dict["no_value_parameter_list"] = "--single-parameter" write_three_parameter("lightsail", "attach-disk", "disk-name", "instance-name", "disk-path", add_option_dict)

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#calss header class _BETRAYALS(): def __init__(self,): self.name = "BETRAYALS" self.definitions = betrayal self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['betrayal']

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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# Copyright 2021 Kacper Kluk, Paweł Anikiel, Jagoda Kamińska. 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. # ============================================================================== import math import nvidia.dali as dali def input_tfrecord( tfrecord_files, tfrecord_idxs, device, shard_id, num_shards, random_shuffle=True ): inputs = dali.fn.readers.tfrecord( path=tfrecord_files, index_path=tfrecord_idxs, features={ "image/encoded": dali.tfrecord.FixedLenFeature( (), dali.tfrecord.string, "" ), "image/height": dali.tfrecord.FixedLenFeature((), dali.tfrecord.int64, -1), "image/width": dali.tfrecord.FixedLenFeature((), dali.tfrecord.int64, -1), "image/object/bbox/xmin": dali.tfrecord.VarLenFeature( dali.tfrecord.float32, 0.0 ), "image/object/bbox/xmax": dali.tfrecord.VarLenFeature( dali.tfrecord.float32, 0.0 ), "image/object/bbox/ymin": dali.tfrecord.VarLenFeature( dali.tfrecord.float32, 0.0 ), "image/object/bbox/ymax": dali.tfrecord.VarLenFeature( dali.tfrecord.float32, 0.0 ), "image/object/class/label": dali.tfrecord.VarLenFeature( dali.tfrecord.int64, 0 ), }, shard_id=shard_id, num_shards=num_shards, random_shuffle=random_shuffle, ) images = dali.fn.decoders.image( inputs["image/encoded"], device="mixed" if device == "gpu" else "cpu", output_type=dali.types.RGB, ) xmin = inputs["image/object/bbox/xmin"] xmax = inputs["image/object/bbox/xmax"] ymin = inputs["image/object/bbox/ymin"] ymax = inputs["image/object/bbox/ymax"] bboxes = dali.fn.transpose(dali.fn.stack(xmin, ymin, xmax, ymax), perm=[1, 0]) classes = dali.fn.cast(inputs["image/object/class/label"], dtype=dali.types.INT32) return ( images, bboxes, classes, dali.fn.cast(inputs["image/width"], dtype=dali.types.FLOAT), dali.fn.cast(inputs["image/height"], dtype=dali.types.FLOAT), ) def input_coco( images_path, annotations_path, device, shard_id, num_shards, random_shuffle=True ): encoded, bboxes, classes = dali.fn.readers.coco( file_root=images_path, annotations_file=annotations_path, ratio=True, ltrb=True, shard_id=shard_id, num_shards=num_shards, random_shuffle=random_shuffle, ) images = dali.fn.decoders.image( encoded, device="mixed" if device == "gpu" else "cpu", output_type=dali.types.RGB, ) shape = dali.fn.peek_image_shape(encoded, dtype=dali.types.FLOAT) heights = shape[0] widths = shape[1] return ( images, bboxes, classes, widths, heights, ) def normalize_flip(images, bboxes, p=0.5): flip = dali.fn.random.coin_flip(probability=p) images = dali.fn.crop_mirror_normalize( images, mirror=flip, mean=[0.485 * 255, 0.456 * 255, 0.406 * 255], std=[0.229 * 255, 0.224 * 255, 0.225 * 255], output_layout=dali.types.NHWC ) bboxes = dali.fn.bb_flip(bboxes, horizontal=flip, ltrb=True) return images, bboxes def gridmask(images, widths, heights): p = dali.fn.random.coin_flip() ratio = 0.4 * p angle = dali.fn.random.normal(mean=-1, stddev=1) * 10.0 * (math.pi / 180.0) l = dali.math.min(0.5 * heights, 0.3 * widths) r = dali.math.max(0.5 * heights, 0.3 * widths) tile = dali.fn.cast( (dali.fn.random.uniform(range=[0.0, 1.0]) * (r - l) + l), dtype=dali.types.INT32, ) gridmask = dali.fn.grid_mask( images, ratio=ratio, angle=angle, tile=tile ) return images def random_crop_resize( images, bboxes, classes, widths, heights, output_size, scaling=[0.1, 2.0] ): if scaling is None: scale_factor = 1.0 else: scale_factor = dali.fn.random.uniform(range=scaling) sizes = dali.fn.stack(heights, widths) image_scale = dali.math.min( scale_factor * output_size[0] / widths, scale_factor * output_size[1] / heights, ) scaled_sizes = dali.math.floor(sizes * image_scale + 0.5) images = dali.fn.resize( images, size=scaled_sizes ) anchors, shapes, bboxes, classes = dali.fn.random_bbox_crop( bboxes, classes, crop_shape=output_size, input_shape=dali.fn.cast(scaled_sizes, dtype=dali.types.INT32), bbox_layout="xyXY", allow_no_crop=False, total_num_attempts=64, ) images = dali.fn.slice( images, anchors, shapes, normalized_anchor=False, normalized_shape=False, out_of_bounds_policy="pad" ) return ( images, bboxes, classes, ) def bbox_to_effdet_format(bboxes, image_size): w = image_size[0] h = image_size[1] M = [0.0, h, 0.0, 0.0, w, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, h, 0.0, 0.0, w, 0.0] return dali.fn.coord_transform(bboxes, M=M)

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GRSEB9S/mystic

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#!/usr/bin/env python # # Author: Alta Fang (altafang @caltech and alta @princeton) # Author: Mike McKerns (mmckerns @caltech and @uqfoundation) # Copyright (c) 1997-2016 California Institute of Technology. # Copyright (c) 2016-2017 The Uncertainty Quantification Foundation. # License: 3-clause BSD. The full license text is available at: # - https://github.com/uqfoundation/mystic/blob/master/LICENSE """ chebyshevinputs.py -- cost function container module for NelderMeadSimplexSolver and PowellDirectionalSolver for testsolvers_pyre.py """ from mystic.models.poly import chebyshev8cost as cost from mystic.models.poly import chebyshev8coeffs from mystic.termination import * ND = 9 maxiter = 999 from numpy import inf import random from mystic.tools import random_seed random_seed(123) x0 = [random.uniform(-5,5) + chebyshev8coeffs[i] for i in range(ND)] # used with SetStrictRanges min_bounds = [ 0,-1,-300,-1, 0,-1,-100,-inf,-inf] max_bounds = [200, 1, 0, 1,200, 1, 0, inf, inf] termination = CandidateRelativeTolerance() #termination = VTR() #termination = ChangeOverGeneration() #termination = NormalizedChangeOverGeneration() # End of file

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superf2t/TIL

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#02-004.py print('yyyy', 'mm', 'dd') print('2022', '02', '20', sep='-', end='') print(' -- BIG EVENT DAY --')

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""" WSGI config for fiber project. This module contains the WSGI application used by Django's development server and any production WSGI deployments. It should expose a module-level variable named ``application``. Django's ``runserver`` and ``runfcgi`` commands discover this application via the ``WSGI_APPLICATION`` setting. Usually you will have the standard Django WSGI application here, but it also might make sense to replace the whole Django WSGI application with a custom one that later delegates to the Django one. For example, you could introduce WSGI middleware here, or combine a Django application with an application of another framework. """ import os import SocketServer from wsgiref import handlers SocketServer.BaseServer.handle_error = lambda *args, **kwargs: None handlers.BaseHandler.log_exception = lambda *args, **kwargs: None # We defer to a DJANGO_SETTINGS_MODULE already in the environment. This breaks # if running multiple sites in the same mod_wsgi process. To fix this, use # mod_wsgi daemon mode with each site in its own daemon process, or use # os.environ["DJANGO_SETTINGS_MODULE"] = "fiber.settings" os.environ.setdefault("DJANGO_SETTINGS_MODULE", "DjangoApp.settings") # This application object is used by any WSGI server configured to use this # file. This includes Django's development server, if the WSGI_APPLICATION # setting points here. from django.core.wsgi import get_wsgi_application application = get_wsgi_application() # Apply WSGI middleware here. # from helloworld.wsgi import HelloWorldApplication # application = HelloWorldApplication(application)

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from __future__ import print_function from setuptools import setup, find_packages, Command from setuptools.command.sdist import sdist from setuptools.command.build_py import build_py from setuptools.command.egg_info import egg_info from subprocess import check_call import os import sys import platform here = os.path.dirname(os.path.abspath(__file__)) node_root = os.path.join(here, 'js') is_repo = os.path.exists(os.path.join(here, '.git')) npm_path = os.pathsep.join([ os.path.join(node_root, 'node_modules', '.bin'), os.environ.get('PATH', os.defpath), ]) from distutils import log log.set_verbosity(log.DEBUG) log.info('setup.py entered') log.info('$PATH=%s' % os.environ['PATH']) LONG_DESCRIPTION = 'WorldWideTelescope Jupyter widget' def js_prerelease(command, strict=False): """decorator for building minified js/css prior to another command""" class DecoratedCommand(command): def run(self): jsdeps = self.distribution.get_command_obj('jsdeps') if not is_repo and all(os.path.exists(t) for t in jsdeps.targets): # sdist, nothing to do command.run(self) return try: self.distribution.run_command('jsdeps') except Exception as e: missing = [t for t in jsdeps.targets if not os.path.exists(t)] if strict or missing: log.warn('rebuilding js and css failed') if missing: log.error('missing files: %s' % missing) raise e else: log.warn('rebuilding js and css failed (not a problem)') log.warn(str(e)) command.run(self) update_package_data(self.distribution) return DecoratedCommand def update_package_data(distribution): """update package_data to catch changes during setup""" build_py = distribution.get_command_obj('build_py') # distribution.package_data = find_package_data() # re-init build_py options which load package_data build_py.finalize_options() class NPM(Command): description = 'install package.json dependencies using npm' user_options = [] node_modules = os.path.join(node_root, 'node_modules') targets = [ os.path.join(here, 'pywwt_web', 'static', 'extension.js'), os.path.join(here, 'pywwt_web', 'static', 'index.js') ] def initialize_options(self): pass def finalize_options(self): pass def get_npm_name(self): npmName = 'npm'; if platform.system() == 'Windows': npmName = 'npm.cmd'; return npmName; def has_npm(self): npmName = self.get_npm_name(); try: check_call([npmName, '--version']) return True except: return False def should_run_npm_install(self): package_json = os.path.join(node_root, 'package.json') node_modules_exists = os.path.exists(self.node_modules) return self.has_npm() def run(self): has_npm = self.has_npm() if not has_npm: log.error("`npm` unavailable. If you're running this command using sudo, make sure `npm` is available to sudo") env = os.environ.copy() env['PATH'] = npm_path if self.should_run_npm_install(): log.info("Installing build dependencies with npm. This may take a while...") npmName = self.get_npm_name(); check_call([npmName, 'install'], cwd=node_root, stdout=sys.stdout, stderr=sys.stderr) os.utime(self.node_modules, None) for t in self.targets: if not os.path.exists(t): msg = 'Missing file: %s' % t if not has_npm: msg += '\nnpm is required to build a development version of a widget extension' raise ValueError(msg) # update package data in case this created new files update_package_data(self.distribution) version_ns = {} with open(os.path.join(here, 'pywwt_web', '_version.py')) as f: exec(f.read(), {}, version_ns) setup_args = { 'name': 'pywwt_web', 'version': version_ns['__version__'], 'description': 'WorldWideTelescope Jupyter widget', 'long_description': LONG_DESCRIPTION, 'include_package_data': True, 'data_files': [ ('share/jupyter/nbextensions/pywwt_web', [ 'pywwt_web/static/extension.js', 'pywwt_web/static/index.js', 'pywwt_web/static/index.js.map', 'pywwt_web/static/wwt.html', 'pywwt_web/static/wwt_json_api.js', ]), ], 'install_requires': [ 'ipywidgets>=7.0.0', 'ipyevents', 'traitlets', 'astropy', ], 'packages': find_packages(), 'zip_safe': False, 'cmdclass': { 'build_py': js_prerelease(build_py), 'egg_info': js_prerelease(egg_info), 'sdist': js_prerelease(sdist, strict=True), 'jsdeps': NPM, }, 'author': 'Thomas P. Robitaille', 'author_email': 'thomas.robitaille@gmail.com', 'url': 'https://github.com/astrofrog/pywwt_web', 'keywords': [ 'ipython', 'jupyter', 'widgets', ], 'classifiers': [ 'Development Status :: 4 - Beta', 'Framework :: IPython', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'Topic :: Multimedia :: Graphics', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', ] } setup(**setup_args)

[ "thomas.robitaille@gmail.com" ]

thomas.robitaille@gmail.com

3d3bc331ab73351b87c588a6cf3ba8fd4c1b2615

036a41c913b3a4e7ae265e22a672dd89302d3200

/0701-0800/0753/0753_Python_1.py

d567ce2e39bf38d32a69b1d68ed59a8f1b2f5b4c

[]

no_license

ChangxingJiang/LeetCode

e76f96ebda68d7ade53575354479cfc33ad4f627

a2209206cdd7229dd33e416f611e71a984a8dd9e

refs/heads/master

2023-04-13T15:23:35.174390

2021-04-24T05:54:14

272,088,506

0

null

UTF-8

Python

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647

py

class Solution: def crackSafe(self, n: int, k: int) -> str: visited = set() def dfs(s1): visited.add(s1) for v in range(k): s2 = s1[1:] + str(v) if s2 not in visited: dfs(s2) stack.append(s1[0]) # 处理其他进制的情况 stack = ["0" * (n - 1)] dfs("0" * n) return "".join(stack[::-1]) if __name__ == "__main__": print(Solution().crackSafe(1, 1)) # 0 print(Solution().crackSafe(1, 2)) # 01 print(Solution().crackSafe(2, 2)) # 00110 print(Solution().crackSafe(3, 2)) # 0011101000

[ "1278729001@qq.com" ]

1278729001@qq.com

6d5cafe13cb9ef0722a1efcabebe9b56f3fa71b8

bfda3af75d94767a5cb265bd68c17cfbf94e3ee1

/rabbithole/zombit_infection/solution.py

89fa08b0dd806b896d3f205eee6feea9361d0b2f

[]

no_license

orenlivne/euler

d0e5b956a46eacfe423fbd6c52918beb91eea140

2afdd8bccdc5789c233e955b1ca626cea618eb9b

refs/heads/master

2020-12-29T02:24:36.479708

2016-12-15T21:27:33

20,263,482

1

null

UTF-8

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2,420

py

#------------------------------------------------------------------------------- # Rabbit hole - zombit_infection problem #------------------------------------------------------------------------------- INFECTED = -1 MAX_STRENGTH = 10000 class Population(object): __DUMMY = MAX_STRENGTH + 1 def __init__(self, population): self.__population = Population.__pad(population) def __eq__(self, other): return self.__population == other.__population def __ne__(self, other): return self.__population != other.__population def __repr__(self): return self.population().__repr__() def copy(self): # Returns a deep copy of the 2D population array. other = Population([[0]]) other.__population = [row[:] for row in self.__population] return other def population(self): return [row[1:-1] for row in self.__population[1:-1]] def attempt_to_infect(self, i, j, strength): # Accounts for padding. self.__attempt_to_infect(i+1, j+1, strength) def spread_infection(self, strength): n, m = self.__size() for i in xrange(1, n): for j in xrange(1, m): self.__spread_infection_at(i, j, strength) def __spread_infection_at(self, i, j, strength): p = self.__population if p[i][j] == INFECTED: self.__attempt_to_infect(i-1, j, strength) self.__attempt_to_infect(i+1, j, strength) self.__attempt_to_infect(i, j-1, strength) self.__attempt_to_infect(i, j+1, strength) def __attempt_to_infect(self, i, j, strength): if self.__population[i][j] <= strength: self.__population[i][j] = INFECTED @staticmethod def __pad(population): m = len(population[0]) d = Population.__DUMMY return [[d] * m] + [[d] + row + [d] for row in population] + [[d] * m] def __size(self): return len(self.__population), len(self.__population[0]) def answer(population, x, y, strength): p = Population(population) old_p = p.copy() p.attempt_to_infect(y, x, strength) while p != old_p: old_p = p.copy() p.spread_infection(strength) return p.population() if __name__ == '__main__': assert answer([[1, 2, 3], [2, 3, 4], [3, 2, 1]], 0, 0, 2) == [[-1, -1, 3], [-1, 3, 4], [3, 2, 1]] assert answer([[6, 7, 2, 7, 6], [6, 3, 1, 4, 7], [0, 2, 4, 1, 10], [8, 1, 1, 4, 9], [8, 7, 4, 9, 9]], 2, 1, 5) == [[6, 7, -1, 7, 6], [6, -1, -1, -1, 7], [-1, -1, -1, -1, 10], [8, -1, -1, -1, 9], [8, 7, -1, 9, 9]]

[ "oren.livne@gmail.com" ]

oren.livne@gmail.com

280b56265c17385bb306b00dd2eac116091880da

632099ac0d895943cbbeb9048a2cdfcd21102411

/LV2_LX2_LC2_LD2/FaderfoxScript.py

ab0b79d02ffebba36ac72ee6d9b6a6dc837d6ef1

[]

no_license

Toniigor/AbletonLive9_RemoteScripts

7f4bbf759a79629584413f6d1797005e8cd7f2ff

fed1e5ee61ea12ea6360107a65a6e666364353ff

refs/heads/master

2021-01-16T21:19:25.330221

2014-06-06T12:33:03

null

0

null

UTF-8

Python

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4,154

py

#Embedded file name: /Users/versonator/Jenkins/live/Projects/AppLive/Resources/MIDI Remote Scripts/LV2_LX2_LC2_LD2/FaderfoxScript.py import Live from consts import * import sys from FaderfoxHelper import FaderfoxHelper from ParamMap import ParamMap from Devices import * class FaderfoxScript: __filter_funcs__ = ['update_display', 'log', 'song'] __module__ = __name__ __doc__ = 'Automap script for Faderfox controllers' __version__ = 'V1.1' __name__ = 'Generic Faderfox Script' def __init__(self, c_instance): self.suffix = '' self.is_lv1 = False FaderfoxScript.realinit(self, c_instance) def realinit(self, c_instance): self.c_instance = c_instance self.helper = FaderfoxHelper(self) self.param_map = ParamMap(self) self.mixer_controller = None self.device_controller = None self.transport_controller = None self.components = [] live = 'Live 6 & 7' if self.is_live_5(): live = 'Live 5' self.show_message(self.__name__ + ' ' + self.__version__ + ' for ' + live) self.is_lv1 = False def is_live_5(self): return hasattr(Live, 'is_live_5') def log(self, string): pass def logfmt(self, fmt, *args): pass def disconnect(self): for c in self.components: c.disconnect() def application(self): return Live.Application.get_application() def song(self): return self.c_instance.song() def suggest_input_port(self): return str('') def suggest_output_port(self): return str('') def can_lock_to_devices(self): return True def lock_to_device(self, device): if self.device_controller: self.device_controller.lock_to_device(device) def unlock_to_device(self, device): if self.device_controller: self.device_controller.unlock_from_device(device) def set_appointed_device(self, device): if self.device_controller: self.device_controller.set_appointed_device(device) def toggle_lock(self): self.c_instance.toggle_lock() def suggest_map_mode(self, cc_no, channel): return Live.MidiMap.MapMode.absolute def restore_bank(self, bank): pass def show_message(self, message): if hasattr(self.c_instance, 'show_message'): self.c_instance.show_message(message) def instance_identifier(self): return self.c_instance.instance_identifier() def connect_script_instances(self, instanciated_scripts): pass def request_rebuild_midi_map(self): self.c_instance.request_rebuild_midi_map() def send_midi(self, midi_event_bytes): self.c_instance.send_midi(midi_event_bytes) def refresh_state(self): for c in self.components: c.refresh_state() def build_midi_map(self, midi_map_handle): self.log('script build midi map') script_handle = self.c_instance.handle() self.param_map.remove_mappings() for c in self.components: self.log('build midi map on %s' % c) c.build_midi_map(script_handle, midi_map_handle) def update_display(self): for c in self.components: c.update_display() def receive_midi(self, midi_bytes): channel = midi_bytes[0] & CHAN_MASK status = midi_bytes[0] & STATUS_MASK if status == CC_STATUS: cc_no = midi_bytes[1] cc_value = midi_bytes[2] for c in self.components: c.receive_midi_cc(channel, cc_no, cc_value) self.param_map.receive_midi_cc(channel, cc_no, cc_value) elif status == NOTEON_STATUS or status == NOTEOFF_STATUS: note_no = midi_bytes[1] note_vel = midi_bytes[2] for c in self.components: c.receive_midi_note(channel, status, note_no, note_vel) self.param_map.receive_midi_note(channel, status, note_no, note_vel) else: raise False or AssertionError, 'Unknown MIDI message %s' % str(midi_bytes)

[ "julien@julienbayle.net" ]

julien@julienbayle.net

60e5e0f2797c0695cd4072eff7577dd65a303961

a0dda8be5892a390836e19bf04ea1d098e92cf58

/视频+刷题/python3/匿名函数的应用.py

540378ee420e3f304633dae548a39b13d84afdac

[]

no_license

wmm98/homework1

d9eb67c7491affd8c7e77458ceadaf0357ea5e6b

cd1f7f78e8dbd03ad72c7a0fdc4a8dc8404f5fe2

refs/heads/master

2020-04-14T19:22:21.733111

2019-01-08T14:09:58

164,055,018

1

0

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UTF-8

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'''用匿名函数实现多个功能''' ''' def sum(a, b, function): result = function(a, b) print(result) sum(22, 11, lambda x, y: x + y) sum(22, 11, lambda x, y: x - y) ''' def num(a, b, func): result = func(a, b) print(result) func_new = input("请输入一个新的匿名函数") func_new = eval(func_new) # 转换 num(11, 12, func_new)

[ "792545884@qq.com" ]

792545884@qq.com

b9f8c48b18733c4773a4d947d22798aadc2d97fe

e9aa61aa74eb69f946a66b6ac5a90f12ec744295

/tests/integration/test_resolve_command.py

d4b4d243f266411ac5114bfc3f14e42ef0a36bfa

[ "LicenseRef-scancode-unknown-license-reference", "MIT" ]

permissive

abueide/lbry

2c2bc35255f82fade22561d673b299c0df35dfea

7f5deaf6c80422a30b3714d4bf12e028756ed9fe

refs/heads/master

2021-01-21T12:58:41.093354

2019-04-12T12:58:00

2019-04-16T18:18:23

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0

MIT

2019-04-12T21:04:56

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UTF-8

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3,855

py

import json from lbrynet.testcase import CommandTestCase class ResolveCommand(CommandTestCase): async def test_resolve(self): tx = await self.channel_create('@abc', '0.01') channel_id = tx['outputs'][0]['claim_id'] # resolving a channel @abc response = await self.resolve('lbry://@abc') self.assertSetEqual({'lbry://@abc'}, set(response)) self.assertIn('certificate', response['lbry://@abc']) self.assertNotIn('claim', response['lbry://@abc']) self.assertEqual(response['lbry://@abc']['certificate']['name'], '@abc') self.assertEqual(response['lbry://@abc']['claims_in_channel'], 0) await self.stream_create('foo', '0.01', channel_id=channel_id) await self.stream_create('foo2', '0.01', channel_id=channel_id) # resolving a channel @abc with some claims in it response = await self.resolve('lbry://@abc') self.assertSetEqual({'lbry://@abc'}, set(response)) self.assertIn('certificate', response['lbry://@abc']) self.assertNotIn('claim', response['lbry://@abc']) self.assertEqual(response['lbry://@abc']['certificate']['name'], '@abc') self.assertEqual(response['lbry://@abc']['claims_in_channel'], 2) # resolving claim foo within channel @abc response = await self.resolve('lbry://@abc/foo') self.assertSetEqual({'lbry://@abc/foo'}, set(response)) claim = response['lbry://@abc/foo'] self.assertIn('certificate', claim) self.assertIn('claim', claim) self.assertEqual(claim['claim']['name'], 'foo') self.assertEqual(claim['claim']['channel_name'], '@abc') self.assertEqual(claim['certificate']['name'], '@abc') self.assertEqual(claim['claims_in_channel'], 0) # resolving claim foo by itself response = await self.resolve('lbry://foo') self.assertSetEqual({'lbry://foo'}, set(response)) claim = response['lbry://foo'] self.assertIn('certificate', claim) self.assertIn('claim', claim) self.assertEqual(claim['claim']['name'], 'foo') self.assertEqual(claim['claim']['channel_name'], '@abc') self.assertEqual(claim['certificate']['name'], '@abc') self.assertEqual(claim['claims_in_channel'], 0) # resolving from the given permanent url new_response = await self.resolve(claim['claim']['permanent_url']) self.assertEqual(new_response[claim['claim']['permanent_url']], claim) # resolving multiple at once response = await self.resolve(['lbry://foo', 'lbry://foo2']) self.assertSetEqual({'lbry://foo', 'lbry://foo2'}, set(response)) claim = response['lbry://foo2'] self.assertIn('certificate', claim) self.assertIn('claim', claim) self.assertEqual(claim['claim']['name'], 'foo2') self.assertEqual(claim['claim']['channel_name'], '@abc') self.assertEqual(claim['certificate']['name'], '@abc') self.assertEqual(claim['claims_in_channel'], 0) # resolve has correct depth tx_details = await self.blockchain.get_raw_transaction(claim['claim']['txid']) self.assertEqual(claim['claim']['depth'], json.loads(tx_details)['confirmations']) # resolve handles invalid data txid = await self.blockchain_claim_name("gibberish", "cafecafe", "0.1") await self.generate(1) response = await self.resolve("lbry://gibberish") self.assertSetEqual({'lbry://gibberish'}, set(response)) claim = response['lbry://gibberish']['claim'] self.assertEqual(claim['name'], 'gibberish') self.assertEqual(claim['hex'], 'cafecafe') self.assertFalse(claim['decoded_claim']) self.assertEqual(claim['txid'], txid) self.assertEqual(claim['effective_amount'], "0.1")

[ "lex@damoti.com" ]

lex@damoti.com

6463120100067e88f76a9d5be84a539e55539baa

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/my_tiff_package/my_tiff_package/__init__.py

34da447454fa182f4e7bc7d7df34feb2f0f2bde8

[]

no_license

danielballan/reader-intake-adapter

20424026ecc23f7aa9ab6ae2035988e60b0ca244

f06ae1c9aef4e8277e81b5903a54d1a124590457

refs/heads/master

2022-04-07T05:50:38.877360

2020-03-05T15:12:10

null

0

null

UTF-8

Python

false

1,752

py

import dask.array import tifffile class TIFFReader: """ Accepts file, filepath, or filepath glob. """ container = 'dask.array.core.Array' def __init__(self, file): if isinstance(file, str): # file is a filepath or filepath glob import os if os.path.isfile(file): self._tiff_files = [tifffile.TiffFile(file)] else: import glob self._tiff_files = [tifffile.TiffFile(file_) for file_ in glob.glob(file)] else: # file is a file buffer self._tiff_files = [tifffile.TiffFile(file)] self._file = file # only used in __repr__ self._closed = False def __repr__(self): return f"{self.__class__.__name__}({self._file!r})" def read(self): if self._closed: raise Closed(f"{self} is closed and can no longer be read.") stack = [] for tf in self._tiff_files: assert len(tf.series) == 1 # should be True by construction series = tf.series[0] dtype = series.dtype for page in series.pages: stack.append(dask.array.from_delayed( dask.delayed(page.asarray)(), shape=page.shape, dtype=dtype)) return dask.array.stack(stack) def close(self): self._closed = True for tf in self._tiff_files: tf.close() def __enter__(self): return self def __exit__(self, *exc_details): self.close() class Closed(Exception): ... # intake compatibility from reader_adapter import adapt # noqa TIFFDataSource = adapt(TIFFReader, 'TIFFDataSource')

[ "dallan@bnl.gov" ]

dallan@bnl.gov

282f9f494bed1bf028d83c8f4c05f917f6111523

29da2ca6def1270be13a3096685a8e5d82828dff

/CIM14/CPSM/Equipment/Wires/SeriesCompensator.py

3d24c9da21e451acecdfd4f1a62596944c6ded43

[ "MIT" ]

permissive

rimbendhaou/PyCIM

75eb3bcd3729b2410c03f3d5c66d6f1e05e21df3

d578bb0bf1af344342bd23344385ed9c06c2d0ee

refs/heads/master

2022-04-28T01:16:12.673867

2020-04-16T02:19:09

256,085,381

0

MIT

2020-04-16T02:15:20

2020-04-16T02:08:14

null

UTF-8

Python

false

2,022

py

# Copyright (C) 2010-2011 Richard Lincoln # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to # deal in the Software without restriction, including without limitation the # rights to use, copy, modify, merge, publish, distribute, sublicense, and/or # sell copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS # IN THE SOFTWARE. from CIM14.CPSM.Equipment.Core.ConductingEquipment import ConductingEquipment class SeriesCompensator(ConductingEquipment): """A Series Compensator is a series capacitor or reactor or an AC transmission line without charging susceptance. It is a two terminal device.- [R9.3] is satisfied by navigation to ConnectivityNode and Substation """ def __init__(self, r=0.0, x=0.0, *args, **kw_args): """Initialises a new 'SeriesCompensator' instance. @param r: Positive sequence resistance. @param x: Positive sequence reactance. """ #: Positive sequence resistance. self.r = r #: Positive sequence reactance. self.x = x super(SeriesCompensator, self).__init__(*args, **kw_args) _attrs = ["r", "x"] _attr_types = {"r": float, "x": float} _defaults = {"r": 0.0, "x": 0.0} _enums = {} _refs = [] _many_refs = []

[ "rwl@thinker.cable.virginmedia.net" ]

rwl@thinker.cable.virginmedia.net

19517ca7ef64c2333ba5aa5f106fb3d0b5e76ce3

0b9622c6d67ddcb252a7a4dd9b38d493dfc9a25f

/HackerRank/30daysChallenge/Day21.py

c3c18c68d2565763a4359b71e362ce6b8b0e1447

[]

no_license

d80b2t/python

eff2b19a69b55d73c4734fb9bc115be1d2193e2d

73603b90996221e0bcd239f9b9f0458b99c6dc44

refs/heads/master

2020-05-21T20:43:54.501991

2017-12-24T12:55:59

61,330,956

0

null

UTF-8

Python

false

204

py

""" Nota Bene: Day 21 was about Generics. This was acutally not a Python solveable challenge (only C++, C#, Java 7, Java 8 and Swift) were offered, so no code was written here or progress made. """

[ "npross@lbl.gov" ]

npross@lbl.gov

b13111418e3b0d4dfe2eaa935cff789e858685ea

a983c40db193d9294ea93628c57f514e0e6e9c2a

/src/shop/api.py

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[ "MIT" ]

permissive

ElinSwedin/foobar-api

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7ab204894c7579dd3f9dec3d2cee1166eb046199

refs/heads/develop

2021-01-19T12:26:27.085054

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2017-02-17T11:05:38

82,311,799

2

0

null

2017-02-17T15:43:49

null

UTF-8

Python

false

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import logging from django.db import transaction from django.contrib.contenttypes.models import ContentType from . import models, enums, suppliers, exceptions log = logging.getLogger(__name__) @transaction.atomic def create_product(code, name): """Create an product""" product_obj = models.Product( code=code, name=name ) product_obj.save() return product_obj @transaction.atomic def update_product(id, **kwargs): product_obj = models.Product.objects.get(id=id) for k, v in kwargs.items(): setattr(product_obj, k, v) product_obj.save() def get_product(id): """Return item with given id. Returns None if the product does not exist. """ try: return models.Product.objects.get(id=id) except models.Product.DoesNotExist: return None def get_product_transactions_by_ref(reference): """Return item transactions with given reference.""" ct = ContentType.objects.get_for_model(reference) return models.ProductTransaction.objects.filter( reference_ct=ct, reference_id=reference.pk, ) @transaction.atomic def create_product_transaction(product_id, trx_type, qty, reference=None): """ Create item transaction for given item. It automagically takes care of updating the quantity for the product. """ product_obj = models.Product.objects.get(id=product_id) ct = None if reference is not None: ct = ContentType.objects.get_for_model(reference) trx_obj = product_obj.transactions.create( trx_type=trx_type, qty=qty, reference_ct=ct, reference_id=reference.pk if reference is not None else None ) return trx_obj @transaction.atomic def cancel_product_transaction(trx_id): trx_obj = models.ProductTransaction.objects.get(id=trx_id) trx_obj.trx_status = enums.TrxStatus.CANCELED trx_obj.save() def list_products(start=None, limit=None, **kwargs): """Returns a list of products matching the criteria. Criteria should be passed to the function as keyword arguments. Criteria arguments support Django field lookups. """ return models.Product.objects.filter(**kwargs)[start:limit] def list_categories(): return models.ProductCategory.objects.all() @transaction.atomic def get_supplier_product(supplier_id, sku): """Returns supplier product for given SKU. If the product does not exist in the local database, fetch it from the supplier. """ try: return models.SupplierProduct.objects.get( supplier_id=supplier_id, sku=sku ) except models.SupplierProduct.DoesNotExist: pass # Product has not been found in the database. Let's fetch it from # the supplier. supplier_obj = models.Supplier.objects.get(id=supplier_id) supplier_api = suppliers.get_supplier_api(supplier_obj.internal_name) product_data = supplier_api.retrieve_product(sku) if product_data is None: log.warning('Product not found (sku: %s, supplier: %s', sku, supplier_id) return None product_obj = models.SupplierProduct.objects.create( supplier_id=supplier_id, sku=sku, price=product_data.price, name=product_data.name ) return product_obj def parse_report(supplier_internal_name, report_path): """Parses a report file and returns parsed items.""" supplier_api = suppliers.get_supplier_api(supplier_internal_name) return supplier_api.parse_delivery_report(report_path) @transaction.atomic def populate_delivery(delivery_id): """Populates the delivery with products based on the imported report.""" delivery_obj = models.Delivery.objects.get(id=delivery_id) supplier_obj = delivery_obj.supplier items = parse_report(supplier_obj.internal_name, delivery_obj.report.path) for item in items: product_obj = get_supplier_product(supplier_obj.id, item.sku) if product_obj is not None: models.DeliveryItem.objects.create( delivery=delivery_obj, supplier_product_id=product_obj.id, qty=item.qty * product_obj.qty_multiplier, price=item.price / product_obj.qty_multiplier ) return delivery_obj @transaction.atomic def process_delivery(delivery_id): """Adjusts the stock quantities based on the delivery data.""" delivery_obj = models.Delivery.objects.get(id=delivery_id) assert delivery_obj.valid, ('Some of the delivered items are not ' 'associated with a product in the system.') for item in delivery_obj.delivery_items.all(): supplier_product = item.supplier_product create_product_transaction( product_id=supplier_product.product.id, trx_type=enums.TrxType.INVENTORY, qty=item.qty, reference=item ) delivery_obj.locked = True delivery_obj.save() @transaction.atomic def initiate_stocktaking(chunk_size=10): """Initiates a stock-taking procedure for all the products.""" stocktake_qs = models.Stocktake.objects # Make sure that there is no stock-taking in progress if not stocktake_qs.filter(locked=False).count() == 0: raise exceptions.APIException('Stock-taking already in progress.') stocktake_obj = stocktake_qs.create() # Order products by category, so that chunk contain mostly that share # category. Products in the same category are most often placed near each # other, which should make the process of stock-taking more effective. product_objs = list(models.Product.objects.all().order_by('category')) for i in range(0, len(product_objs), chunk_size): chunk_obj = stocktake_obj.chunks.create() chunk_products = product_objs[i:i + chunk_size] for p in chunk_products: chunk_obj.items.create(product=p) return stocktake_obj @transaction.atomic def finalize_stocktaking(stocktake_id): """Applies the result of stock taking to the stock quantities.""" stocktake_obj = models.Stocktake.objects.get(id=stocktake_id) if stocktake_obj.locked: raise exceptions.APIException('Stock-taking already finished.') # Make sure that all the chunks are finished chunk_objs = stocktake_obj.chunks.all() if not all(obj.locked for obj in chunk_objs): raise exceptions.APIException('Found unfinished chunks.') for chunk_obj in chunk_objs: for item_obj in chunk_obj.items.all(): product_obj = item_obj.product create_product_transaction( product_id=product_obj.id, trx_type=enums.TrxType.CORRECTION, qty=item_obj.qty - product_obj.qty, reference=item_obj ) stocktake_obj.locked = True stocktake_obj.save() return stocktake_obj def finalize_stocktake_chunk(chunk_id): """Marks given chunk as finished.""" chunk_obj = models.StocktakeChunk.objects.get(id=chunk_id) if chunk_obj.locked: raise exceptions.APIException('Chunk already locked.') chunk_obj.locked = True chunk_obj.owner = None chunk_obj.save() @transaction.atomic def assign_free_stocktake_chunk(user_id, stocktake_id): """Assigns a free stock-take chunk to a user, if any free left. If user is already assigned to a chunk, that chunk should be returned. """ chunk_qs = models.StocktakeChunk.objects.select_for_update() try: return chunk_qs.get( stocktake_id=stocktake_id, owner_id=user_id ) except models.StocktakeChunk.DoesNotExist: pass chunk_objs = chunk_qs.filter( stocktake_id=stocktake_id, locked=False, owner__isnull=True ) if not chunk_objs: return None chunk_obj = chunk_objs.first() chunk_obj.owner_id = user_id chunk_obj.save() return chunk_obj

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def isnumber(s): for i in range(len(s)): if s[i] < '0' or s[i] > '9': return False return True def solution(s): if (len(s) == 4 or len(s) == 6) and isnumber(s): return True return False

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import random from random import randint class Entity(): """docstring for Entity""" def __init__(self,name, health): self.name = name self.health = health def get_name(self): return self.name def get_health(self): return self.health def is_alive(self): if self.health > 0: return True else: return False def equip_weapon(self, weapon_for_entity): setattr(self, "weapon", weapon_for_entity) return True def has_weapon(self): return hasattr(self, "weapon") def take_damage(self, damage_points): self.health -= damage_points return self.health def take_healing(self, healing_points): if self.health > 0 and self.health < 100: self.health += healing_points return self.health def attack(self): if self.has_weapon(): return self.weapon.damage else: return 10 class Hero(Entity): """docstring for Hero""" def __init__(self, name, health, nickname): super().__init__(name, health) self.nickname = nickname def get_nickname(self): return self.nickname def known_as(self): return self.name + " the " + self.nickname class Orc(Entity): """docstring for Org""" def __init__(self, name, health, berserk_factor): super().__init__(name, health) self.berserk_factor = berserk_factor def attack(self): return self.berserk_factor*(super().attack()) class Weapon(): """docstring for Weapon""" def __init__(self, Type, damage, critical_strike_percent): self.Type = Type self.damage = damage self.critical_strike_percent = critical_strike_percent def getType(self): return self.Type def getCriticalStrikePercent(self): return self.critical_strike_percent def critical_hit(self): random_strike_percent = random.uniform(0,1) if self.critical_strike_percent > random_strike_percent: self.critical_strike_percent *= 2 return self.critical_strike_percent else: return self.critical_strike_percent class Fight(): """docstring for Fight""" def __init__(self, new_hero, new_orc): self.hero = new_hero self.orc = new_orc def who_starts(self): random_who_starts = randint(1,100) if random_who_starts <= 50: first = self.hero return first else: return self.orc def get_opponent(self,first): if first == self.hero: return self.orc else: return self.hero def simulate_fight(self): first = self.who_starts() print("%s starts" % first.name) second = self.get_opponent(first) if first.has_weapon()==False: weapon_bare_hands = Weapon("his bare hands!", 5, 0.09) setattr(Entity, "weapon", weapon_bare_hands) if second.has_weapon()==False: weapon_bare_hands = Weapon("his bare hands!", 5, 0.09) setattr(Entity, "weapon", weapon_bare_hands) while True: damage = first.attack() print("%s attacks with %s" % (first.name, first.weapon.Type)) second.take_damage(damage) print("%s is hurted" % (first.name)) if second.is_alive() == False: print("%s died" % second.name) break damage = second.attack() print("%s attacks with %s" % (first.name, second.weapon.Type)) first.take_damage(damage) print("%s is hurted" % (second.name)) if first.is_alive() == False: print("%s died" % first.name) break if first.is_alive(): return first return second class Dungeon(): """docstring for Dungein""" def __init__(self, file_to_read): file = open(file_to_read, "r") self.unparsed_map = file.read() file.close() def get_map(self): return self.unparsed_map def print_map(self): print(self.get_map())

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mileto94@abv.bg

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#!/home/ivy/Documents/Moringa-school-projects/core-projects/python/hood/virtual/bin/python # -*- coding: utf-8 -*- import re import sys from pip._internal import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "nziokaivy@gmail.com" ]

nziokaivy@gmail.com

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/Code-Scraps/old_modules/SpiceBot/Main/forfuckssake.py

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2020-05-02T21:51:01.297114

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#!/usr/bin/env python # coding=utf-8 from __future__ import unicode_literals, absolute_import, print_function, division import sopel.module import sys import os moduledir = os.path.dirname(__file__) shareddir = os.path.dirname(os.path.dirname(os.path.dirname(__file__))) sys.path.append(shareddir) from BotShared import * # author jimender2 @sopel.module.commands('forfuckssake','ffs') def mainfunction(bot, trigger): enablestatus, triggerargsarray, botcom, instigator = spicebot_prerun(bot, trigger, 'forfuckssake') if not enablestatus: # IF "&&" is in the full input, it is treated as multiple commands, and is split commands_array = spicemanip(bot, triggerargsarray, "split_&&") if commands_array == []: commands_array = [[]] for command_split_partial in commands_array: triggerargsarray_part = spicemanip(bot, command_split_partial, 'create') execute_main(bot, trigger, triggerargsarray_part, botcom, instigator) def execute_main(bot, trigger, triggerargsarray, botcom, instigator): osd(bot, trigger.sender, 'say', "For fuck sakes lizard people, get your shit together!!")

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from circularly_linked_list.insert_cyclic_list import insert from data_structures.singly_linked_list_node import SinglyLinkedListNode from test_helpers.test_helpers import get_cyclic_list_values def test_insert(): head = None assert get_cyclic_list_values(insert(head, 1)) == [1] head = SinglyLinkedListNode(1) head.next = head assert get_cyclic_list_values(insert(head, 2)) == [1, 2] head = SinglyLinkedListNode(3) head.next = SinglyLinkedListNode(4) head.next.next = SinglyLinkedListNode(1) head.next.next.next = head assert get_cyclic_list_values(insert(head, 2)) == [3, 4, 1, 2]

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import pymongo myclient = pymongo.MongoClient("mongodb+srv://students:321321@firstcluster-bxilw.gcp.mongodb.net/test?retryWrites=true&w=majority") mydb = myclient["mydatabase"] mycol = mydb["students"] mylist = [ { "_id": 1, "name": "John", "address": "Highway 37"}, { "_id": 2, "name": "Peter", "address": "Lowstreet 27"}, { "_id": 3, "name": "Amy", "address": "Apple st 652"}, { "_id": 4, "name": "Hannah", "address": "Mountain 21"}, { "_id": 5, "name": "Michael", "address": "Valley 345"}, { "_id": 6, "name": "Sandy", "address": "Ocean blvd 2"}, { "_id": 7, "name": "Betty", "address": "Green Grass 1"}, { "_id": 8, "name": "Richard", "address": "Sky st 331"}, { "_id": 9, "name": "Susan", "address": "One way 98"}, { "_id": 10, "name": "Vicky", "address": "Yellow Garden 2"}, { "_id": 11, "name": "Ben", "address": "Park Lane 38"}, { "_id": 12, "name": "William", "address": "Central st 954"}, { "_id": 13, "name": "Chuck", "address": "Main Road 989"}, { "_id": 14, "name": "Viola", "address": "Sideway 1633"} ] x = mycol.insert_many(mylist) #print a list of the _id values of the inserted documents: print(x.inserted_ids)

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Bonasolvo/npf-dev-roles

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from npf.core.workflow.models import WorkflowTaskInstance class WorkflowMyTaskInstance(WorkflowTaskInstance): """ Прокси-модель: Экземпляр задачи. Используется для фильтрации всех задач по текущему пользователю и вывода списка "Мои задачи". """ class Meta: verbose_name = 'Задача' verbose_name_plural = 'Мои задачи' proxy = True

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tymashh@Mac-Tymashh.local

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/modules/cctbx_project/cctbx/development/electron_density_sampling.py

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from __future__ import absolute_import, division, print_function from cctbx import xray from cctbx import miller from cctbx.command_line.structure_factor_timings import read_structure import sys def timings(structure, wing_cutoff=1.e-3): print("wing_cutoff for following fft calculations: %3.1e"%wing_cutoff) for calc_type,exp_table_one_over_step_size in (("exp function:",0), ("exp table:",-100)): print(calc_type) for d_min in [4,3,2,1]: structure_ng = structure.deep_copy_scatterers() structure_ng.scattering_type_registry(d_min=d_min, table="n_gaussian") structure_4g = structure.deep_copy_scatterers() structure_4g.scattering_type_registry(table="it1992") miller_set = miller.build_set( crystal_symmetry=structure, d_min=d_min, anomalous_flag=False) miller_set.show_summary() times = [] for structure in (structure_ng, structure_4g): structure.scattering_type_registry().show_summary() f_calc_object = xray.structure_factors.from_scatterers( miller_set=miller_set, wing_cutoff=wing_cutoff, exp_table_one_over_step_size=exp_table_one_over_step_size)( xray_structure=structure, miller_set=miller_set, algorithm="fft") times.append(f_calc_object.manager().estimate_time_fft.time_sampling) print(" %.2f seconds," % times[-1]) print("d_min=%d: %.2f s / %.2f s" % (d_min, times[0], times[1]), end=' ') if (times[1] != 0): print("= %.2f" % (times[0] / times[1]), end=' ') print() sys.stdout.flush() print() def run(args): assert len(args) == 1 structure = read_structure(args[0]) structure.show_summary() print() timings(structure=structure) if (__name__ == "__main__"): run(sys.argv[1:])

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# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # 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 proto # type: ignore __protobuf__ = proto.module( package="google.ads.googleads.v9.errors", marshal="google.ads.googleads.v9", manifest={"AdGroupAdErrorEnum",}, ) class AdGroupAdErrorEnum(proto.Message): r"""Container for enum describing possible ad group ad errors. """ class AdGroupAdError(proto.Enum): r"""Enum describing possible ad group ad errors.""" UNSPECIFIED = 0 UNKNOWN = 1 AD_GROUP_AD_LABEL_DOES_NOT_EXIST = 2 AD_GROUP_AD_LABEL_ALREADY_EXISTS = 3 AD_NOT_UNDER_ADGROUP = 4 CANNOT_OPERATE_ON_REMOVED_ADGROUPAD = 5 CANNOT_CREATE_DEPRECATED_ADS = 6 CANNOT_CREATE_TEXT_ADS = 7 EMPTY_FIELD = 8 RESOURCE_REFERENCED_IN_MULTIPLE_OPS = 9 AD_TYPE_CANNOT_BE_PAUSED = 10 AD_TYPE_CANNOT_BE_REMOVED = 11 CANNOT_UPDATE_DEPRECATED_ADS = 12 __all__ = tuple(sorted(__protobuf__.manifest))

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# Copyright 2020 Huawei Technologies Co., Ltd # # 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 numpy as np import mindspore.common.dtype as mstype import mindspore.nn as nn import mindspore.context as context from mindspore import Tensor from mindspore.ops import operations as P from mindspore.common.parameter import Parameter context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") lr = 0.01 l1 = 0.0 l2 = 0.0 lr_power = -0.5 class Net(nn.Cell): def __init__(self): super(Net, self).__init__() self.fused_sparse_ftrl = P.FusedSparseFtrl(lr=0.1, l1=0.0, l2=0.0, lr_power=-0.5) self.var = Parameter(Tensor(np.ones([3, 3]).astype(np.float32)), name="var") self.accum = Parameter(Tensor(np.ones([3, 3]).astype(np.float32)), name="accum") self.linear = Parameter(Tensor(np.ones([3, 3]).astype(np.float32)), name="linear") def construct(self, grad, indices): return self.fused_sparse_ftrl(self.var, self.accum, self.linear, grad, indices) def test_net(): gradient = Tensor(np.array([-3, 2, 3, 0, 0, 0, -4, -1, -2]) .reshape([3, 3]).astype(np.float32)) indices = Tensor(np.ones([3]), mstype.int32) net = Net() output = net(gradient, indices) print(output) print(net.var.data) print(net.accum.data) print(net.linear.data)

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import sd # Import the required classes. from sd.api.sdproperty import SDPropertyCategory from sd.api.sdvalueserializer import SDValueSerializer # Get and print information regarding the selected nodes. def printSelectedNodesInfo(nodes): for node in nodes: definition = node.getDefinition() nodeId = node.getIdentifier() print("node %s, id = %s" % (definition.getLabel(), nodeId)) # Create a list of each property category enumeration item. categories = [ SDPropertyCategory.Annotation, SDPropertyCategory.Input, SDPropertyCategory.Output ] # Get node properties for each property category. for category in categories: props = definition.getProperties(category) # Get the label and identifier of each property. for prop in props: label = prop.getLabel() propId = prop.getId() # Get the connection for the currently accessed property. if prop.isConnectable(): connections = node.getPropertyConnections(prop) if connections: print("Propery %s is connected!!!" % label) continue # Get the value for the currently accessed property. value = node.getPropertyValue(prop) if value: print("Property %s, id = %s, value = %s" % (label, propId, SDValueSerializer.sToString(value)))

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import os import shutil import subprocess import sys from typing import Optional from pipx.constants import WINDOWS from pipx.util import PipxError def has_venv() -> bool: try: import venv # noqa return True except ImportError: return False # The following code was copied from https://github.com/uranusjr/pipx-standalone # which uses the same technique to build a completely standalone pipx # distribution. # # If we are running under the Windows embeddable distribution, # venv isn't available (and we probably don't want to use the # embeddable distribution as our applications' base Python anyway) # so we try to locate the system Python and use that instead. def find_py_launcher_python(python_version: Optional[str] = None) -> Optional[str]: py = shutil.which("py") if py and python_version: py = subprocess.run( [py, f"-{python_version}", "-c", "import sys; print(sys.executable)"], capture_output=True, text=True, ).stdout.strip() return py def _find_default_windows_python() -> str: if has_venv(): return sys.executable python = find_py_launcher_python() or shutil.which("python") if python is None: raise PipxError("No suitable Python found") # If the path contains "WindowsApps", it's the store python if "WindowsApps" not in python: return python # Special treatment to detect Windows Store stub. # https://twitter.com/zooba/status/1212454929379581952 proc = subprocess.run( [python, "-V"], stdout=subprocess.PIPE, stderr=subprocess.DEVNULL ) if proc.returncode != 0: # Cover the 9009 return code pre-emptively. raise PipxError("No suitable Python found") if not proc.stdout.strip(): # A real Python should print version, Windows Store stub won't. raise PipxError("No suitable Python found") return python # This executable seems to work. def _get_sys_executable() -> str: if WINDOWS: return _find_default_windows_python() else: return sys.executable def _get_absolute_python_interpreter(env_python: str) -> str: which_python = shutil.which(env_python) if not which_python: raise PipxError(f"Default python interpreter '{env_python}' is invalid.") return which_python env_default_python = os.environ.get("PIPX_DEFAULT_PYTHON") if not env_default_python: DEFAULT_PYTHON = _get_sys_executable() else: DEFAULT_PYTHON = _get_absolute_python_interpreter(env_default_python)

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# This code is part of Qiskit. # # (C) Copyright IBM 2017, 2020. # # This code is licensed under the Apache License, Version 2.0. You may # obtain a copy of this license in the LICENSE.txt file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain this # copyright notice, and modified files need to carry a notice indicating # that they have been altered from the originals. """ Data-encoding circuits ====================== In machine learning, pattern recognition and image processing, a **data-encoding circuit** starts from an initial set of measured data and builds derived values (also known as **features**) intended to be informative and non-redundant, facilitating the subsequent learning and generalization steps, and in some cases leading to better human interpretations. A feature map is related to **dimensionality reduction**; it involves reducing the amount of resources required to describe a large set of data. When performing analysis of complex data, one of the major problems stems from the number of variables involved. Analysis with a large number of variables generally requires a large amount of memory and computation power, and may even cause a classification algorithm to overfit to training samples and generalize poorly to new samples. When the input data to an algorithm is too large to be processed and is suspected to be redundant (for example, the same measurement is provided in both pounds and kilograms), then it can be transformed into a reduced set of features, named a **feature vector**. The process of determining a subset of the initial features is called **feature selection**. The selected features are expected to contain the relevant information from the input data, so that the desired task can be performed by using the reduced representation instead of the complete initial data. """ from .pauli_feature_map import PauliFeatureMap from .z_feature_map import ZFeatureMap from .zz_feature_map import ZZFeatureMap from .state_preparation import StatePreparation __all__ = ["PauliFeatureMap", "ZFeatureMap", "ZZFeatureMap", "StatePreparation"]

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""" Experiment to evaluate the effect of the size on computation time """ import time import numpy as np from sklearn.decomposition import RandomizedPCA import nimfa import argparse import CP_APR import sptensor import sptenmat # Load the original data filename = 'data/hf-tensor-level1-data.dat' X = sptensor.loadTensor(filename) R = 40 iters=70 samples=10 pcaModel = RandomizedPCA(n_components=R) stats = np.zeros((1, 6)) parser = argparse.ArgumentParser() parser.add_argument("pat", type=int, help="number of patients") args = parser.parse_args() pn = args.pat patList = np.arange(pn) ix = np.in1d(X.subs[:,0].ravel(), patList) idx = np.where(ix)[0] xprime = sptensor.sptensor(X.subs[idx, :], X.vals[idx], [pn, X.shape[1], X.shape[2]]) flatX = sptenmat.sptenmat(xprime, [0]).tocsrmat() # matricize along the first mode stats = np.zeros((1,6)) ## NMF Timing for k in range(samples): startTime = time.time() nmfModel = nimfa.mf(flatX, method="nmf", max_iter=iters, rank=R) nmfResult = nimfa.mf_run(nmfModel) elapsed = time.time() - startTime stats = np.vstack((stats, np.array([R, iters, pn, k, "NMF", elapsed]))) ## PCA Timing for k in range(samples): startTime = time.time() pcaModel.fit(flatX) elapsed = time.time() - startTime stats = np.vstack((stats, np.array([R, iters, pn, k, "PCA", elapsed]))) ## Tensor factorization timing for k in range(samples): startTime = time.time() CP_APR.cp_apr(xprime, R, maxiters=iters) elapsed = time.time() - startTime stats = np.vstack((stats, np.array([R, iters, pn, k, "CP_APR", elapsed]))) stats = np.delete(stats, (0), axis=0) outFile = "results/patient-cpu-{0}.csv".format(pn) np.savetxt(outFile, stats, fmt="%s", delimiter="|") print "load data local infile '/home/joyce/workspace/Health/analysis/tensor/{0}' into table comp_metrics fields terminated by '|' ;\n".format(outFile)

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from django.db import migrations def create_customtext(apps, schema_editor): CustomText = apps.get_model("home", "CustomText") customtext_title = "Dared 3" CustomText.objects.create(title=customtext_title) def create_homepage(apps, schema_editor): HomePage = apps.get_model("home", "HomePage") homepage_body = """ <h1 class="display-4 text-center">Dared 3</h1> <p class="lead"> This is the sample application created and deployed from the Crowdbotics app. You can view list of packages selected for this application below. </p>""" HomePage.objects.create(body=homepage_body) def create_site(apps, schema_editor): Site = apps.get_model("sites", "Site") custom_domain = "dared-3-22630.botics.co" site_params = { "name": "Dared 3", } if custom_domain: site_params["domain"] = custom_domain Site.objects.update_or_create(defaults=site_params, id=1) class Migration(migrations.Migration): dependencies = [ ("home", "0001_initial"), ("sites", "0002_alter_domain_unique"), ] operations = [ migrations.RunPython(create_customtext), migrations.RunPython(create_homepage), migrations.RunPython(create_site), ]

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import pp from gdslib.load import load def coupler_ring(c=pp.c.coupler_ring, **kwargs): """ coupler for half a ring .. code:: N0 N1 | | \ / \ / ---=========--- W0 length_x E0 """ m = load(c, **kwargs) return m if __name__ == "__main__": import matplotlib.pyplot as plt import numpy as np wav = np.linspace(1520, 1570, 1024) * 1e-9 f = 3e8 / wav c = coupler_ring() s = c.s_parameters(freq=f) plt.plot(wav, np.abs(s[:, 1] ** 2)) print(c.pins) plt.show()

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j

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import tensorflow as tf from forkan.models import VAE from forkan.datasets import load_atari_normalized learning_rate = 1e-4 beta = 5.5 latents = 20 for name in ['pong', 'breakout', 'boxing', 'gopher', 'upndown']: data = load_atari_normalized(name) v = VAE(data.shape[1:], name=name, lr=learning_rate, beta=beta, latent_dim=latents) v.train(data, num_episodes=50, print_freq=-1) tf.reset_default_graph() del data del v

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#!/usr/bin/env python import sys for line in sys.stdin: try: line = line.strip() # split the line into words words = line.split() # increase counters if words[0] == "WARC-Target-URI:" : uri = words[1].split("/") print '%s\t%s' % (uri[0]+"//"+uri[2], 1) except Exception: "" #hadoop jar /usr/local/apache/hadoop2/share/hadoop/tools/lib/hadoop-streaming-2.6.0.jar -file /mapper.py -mapper /mapper.py -file /reducer.py -reducer /reducer.py -input /text.txt -output /output

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#!/usr/bin/env python # -*- coding: UTF-8 -*- # coding=utf-8 """ @author: Li Tian @contact: 694317828@qq.com @software: pycharm @file: statistic_word5.py @time: 2019/4/29 10:39 @desc: 用tf.while_loop来实现解码过程 """ import tensorflow as tf import codecs # 读取checkpoint的路径。9000表示是训练程序在第9000步保存的checkpoint CHECKPOINT_PATH = "./new_seq2seq_ckpt" # 模型参数。必须与训练时的模型参数保持一致。 # LSTM的隐藏层规模 HIDDEN_SIZE = 1024 # 深层循环神经网络中LSTM结构的层数 NUM_LAYERS = 2 # 源语言词汇表大小 SRC_VOCAB_SIZE = 10000 # 目标语言词汇表大小 TRG_VOCAB_SIZE = 4000 # 在Softmax层和词向量层之间共享参数 SHARE_EMB_AND_SOFTMAX = True # 词汇表中<sos>和<eos>的ID。在解码过程中需要用<sos>作为第一步的输入，并将检查是否是<eos>，因此需要知道这两个符号的ID SOS_ID = 1 EOS_ID = 2 # 词汇表文件 SRC_VOCAB = "en.vocab" TRG_VOCAB = "zh.vocab" # 定义NMTModel类来描述模型 class NMTModel(object): # 在模型的初始化函数中定义模型要用到的变量 def __init__(self): # 与训练时的__init__函数相同。通常在训练程序和解码程序中复用NMTModel类以及__init__函数，以确保解码时和训练时定义的变量是相同的 # 定义编码器和解码器所使用的LSTM结构 self.enc_cell = tf.nn.rnn_cell.MultiRNNCell([tf.nn.rnn_cell.BasicLSTMCell(HIDDEN_SIZE) for _ in range(NUM_LAYERS)]) self.dec_cell = tf.nn.rnn_cell.MultiRNNCell([tf.nn.rnn_cell.BasicLSTMCell(HIDDEN_SIZE) for _ in range(NUM_LAYERS)]) # 为源语言和目标语言分别定义词向量 self.src_embedding = tf.get_variable("src_emb", [SRC_VOCAB_SIZE, HIDDEN_SIZE]) self.trg_embedding = tf.get_variable("trg_emb", [TRG_VOCAB_SIZE, HIDDEN_SIZE]) # 定义softmax层的变量 if SHARE_EMB_AND_SOFTMAX: self.softmax_weight = tf.transpose(self.trg_embedding) else: self.softmax_weight = tf.get_variable("weight", [HIDDEN_SIZE, TRG_VOCAB_SIZE]) self.softmax_bias = tf.get_variable("softmax_bias", [TRG_VOCAB_SIZE]) def inference(self, src_input): # 虽然输入只有一个句子，但因为dynamic_rnn要求输入是batch的形式，因此这里将输入句子整理为大小为1的batch src_size = tf.convert_to_tensor([len(src_input)], dtype=tf.int32) src_input = tf.convert_to_tensor([src_input], dtype=tf.int32) src_emb = tf.nn.embedding_lookup(self.src_embedding, src_input) # 使用dynamic_rnn构造编码器。这一步与训练时相同 with tf.variable_scope("encoder"): enc_outputs, enc_state = tf.nn.dynamic_rnn(self.enc_cell, src_emb, src_size, dtype=tf.float32) # 设置解码的最大步数。这是为了避免在极端情况出现无限循环的问题。 MAX_DEC_LEN = 100 with tf.variable_scope("decoder/rnn/multi_rnn_cell"): # 使用一个变长的TensorArray来存储生成的句子 init_array = tf.TensorArray(dtype=tf.int32, size=0, dynamic_size=True, clear_after_read=False) # 填入第一个单词<sos>作为解码器的输入 init_array = init_array.write(0, SOS_ID) # 构建初始的循环状态。循环状态包含循环神经网络的隐藏状态，保存生成句子的TensorArray，以及记录解码步数的一个整数step init_loop_var = (enc_state, init_array, 0) # tf.while_loop的循环条件 # 循环直到解码器输出<eos>，或者达到最大步数为止。 def continue_loop_condition(state, trg_ids, step): return tf.reduce_all(tf.logical_and(tf.not_equal(trg_ids.read(step), EOS_ID), tf.less(step, MAX_DEC_LEN-1))) def loop_body(state, trg_ids, step): # 读取最后一步输出的单词，并读取其词向量 trg_input = [trg_ids.read(step)] trg_emb = tf.nn.embedding_lookup(self.trg_embedding, trg_input) # 这里不使用dynamic_rnn，而是直接调用dec_cell向前计算一步。 dec_outputs, next_state = self.dec_cell.call(state=state, inputs=trg_emb) # 计算每个可能的输出单词对应的logit，并选取logit值最大的单词作为这一步的输出。 output = tf.reshape(dec_outputs, [-1, HIDDEN_SIZE]) logits = (tf.matmul(output, self.softmax_weight) + self.softmax_bias) next_id = tf.argmax(logits, axis=1, output_type=tf.int32) # 将这一步输出的单词写入循环状态的trg_ids中 trg_ids = trg_ids.write(step+1, next_id[0]) return next_state, trg_ids, step+1 # 执行tf.while_loop，返回最终状态 state, trg_ids, step = tf.while_loop(continue_loop_condition, loop_body, init_loop_var) return trg_ids.stack() def main(): # 定义训练用的循环神经网络模型 with tf.variable_scope("nmt_model", reuse=None): model = NMTModel() # 定义一个测试的例子 test_sentence = "This is a test ." print(test_sentence) # 根据英文词汇表，将测试句子转为单词ID。结尾加上<eos>的编号 test_sentence = test_sentence + " <eos>" with codecs.open(SRC_VOCAB, 'r', 'utf-8') as vocab: src_vocab = [w.strip() for w in vocab.readlines()] # 运用dict，将单词和id对应起来组成字典，用于后面的转换 src_id_dict = dict((src_vocab[x], x) for x in range(SRC_VOCAB_SIZE)) test_en_ids = [(src_id_dict[en_text] if en_text in src_id_dict else src_id_dict['<unk>']) for en_text in test_sentence.split()] print(test_en_ids) # 建立解码所需的计算图 output_op = model.inference(test_en_ids) sess = tf.Session() saver = tf.train.Saver() saver.restore(sess, CHECKPOINT_PATH) # 读取翻译结果 output_ids = sess.run(output_op) print(output_ids) # 根据中文词汇表，将翻译结果转换为中文文字。 with codecs.open(TRG_VOCAB, "r", "utf-8") as f_vocab: trg_vocab = [w.strip() for w in f_vocab.readlines()] output_text = ''.join([trg_vocab[x] for x in output_ids[1:-1]]) # 输出翻译结果 print(output_text) sess.close() if __name__ == "__main__": main()

[ "694317828@qq.com" ]

694317828@qq.com

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/pacman103/core/spinnman/spinnman_utilities.py

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BRML/HBP-spinnaker-cerebellum

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__author__ = 'stokesa6' import os class SpinnmanUtilities(object): def __init__(self, dao=None, input_file=None): self.runtime = None self.total_processors = None self.app_loads = list() self.mem_writes_from_file = list() self.mem_writes = list() if dao is not None: directory = dao.get_reports_directory("transceiver_commands") self.output_file = os.path.join(directory, "transceiver_commands") self.output = open(self.output_file, "wb") self.output_data = list() if input_file is not None: self.read_in_file(input_file) def write_extra_data(self, runtime, total_processors): self.output_data.insert(0, "TOTAL_PROCESSORS:{}:".format(total_processors)) self.output_data.insert(0, "RUNTIME:{}:".format(runtime)) # different types of writes def write_app_load_command(self, key, region, core_part_of_region, app_id): self.output_data.append("APPLOAD:{}:{}:{}:{}:".format(key, region, core_part_of_region, app_id)) def write_selects(self, x, y, p): self.output_data.append("SELECT:{}:{}:{}:".format(x, y, p)) def write_mem_from_file(self, address, type_word, filename): self.output_data.append("WRITE_MEM_FROM_FILE:{}:{}:{}:". format(address, int(type_word), filename)) def write_mem(self, address, type_word, structure): self.output_data.append("WRITE_MEM:{}:{}:{}:". format(address, int(type_word), structure)) def close(self): for line in self.output_data: self.output.write(line + "\n") self.output.flush() self.output.close() def get_run_time(self): return self.runtime def get_total_processors(self): return self.total_processors def get_app_loads(self): return self.app_loads def get_mem_writes(self): return self.mem_writes def get_mem_writes_from_file(self): return self.mem_writes_from_file def read_in_file(self, input_file): inputfile = open(input_file, "r") content = inputfile.readlines() self.runtime = content[0].split(":")[1] self.total_processors = content[1].split(":")[1] self.app_loads = list() data = None line = 0 for line in range(2, len(content)): bits = content[line].split(":") if bits[0] == "APPLOAD": data = dict() data['key'] = bits[1] data['region'] = bits[2] data['core_part_of_region'] = bits[3] data['app_id'] = bits[4] self.app_loads.append(data) elif bits[0] == "SELECT": data = dict() data['x'] = bits[1] data['y'] = bits[2] data['p'] = bits[3] elif bits[0] == "WRITE_MEM": self.mem_writes.append(data) data = dict() data['address'] = bits[1] data['type_word'] = bits[2] data['structure'] = bits[3] self.mem_writes.append(data) elif bits[0] == "WRITE_MEM_FROM_FILE": self.mem_writes_from_file.append(data) data = dict() data['address'] = bits[1] data['type_word'] = bits[2] data['filename'] = bits[3] self.mem_writes_from_file.append(data)

[ "dr.christoph.richter@gmail.com" ]

dr.christoph.richter@gmail.com