code
stringlengths
281
23.7M
def buildFKeyStmt(conn, tableName, key): unqIndex = getUniqueIndex(conn, key['table']) keyList = getFKeyList(conn, key['table']) keyStmt = [] for colName in unqIndex: keyKey = search_keyList(keyList, colName) if keyKey: newStmt = buildFKeyStmt(conn, key['table'], keyKey) for row in newStmt: keyStmt.append(row) else: keyStmt.append({'table': tableName, 'column': colName, 'joinTable': key['table'], 'joinColumn': key['to']}) return keyStmt
class ExtendedNotifiers(HasTraits): def __init__(self, **traits): ok_listeners = [self.method_listener_0, self.method_listener_1, self.method_listener_2, self.method_listener_3, self.method_listener_4] for listener in ok_listeners: self._on_trait_change(listener, 'ok', dispatch='extended') fail_listeners = [self.failing_method_listener_0, self.failing_method_listener_1, self.failing_method_listener_2, self.failing_method_listener_3, self.failing_method_listener_4] for listener in fail_listeners: self._on_trait_change(listener, 'fail', dispatch='extended') super().__init__(**traits) ok = Float fail = Float rebind_calls_0 = List rebind_calls_1 = List rebind_calls_2 = List rebind_calls_3 = List rebind_calls_4 = List exceptions_from = List def method_listener_0(self): self.rebind_calls_0.append(True) def method_listener_1(self, new): self.rebind_calls_1.append(new) def method_listener_2(self, name, new): self.rebind_calls_2.append((name, new)) def method_listener_3(self, obj, name, new): self.rebind_calls_3.append((obj, name, new)) def method_listener_4(self, obj, name, old, new): self.rebind_calls_4.append((obj, name, old, new)) def failing_method_listener_0(self): self.exceptions_from.append(0) raise Exception('error') def failing_method_listener_1(self, new): self.exceptions_from.append(1) raise Exception('error') def failing_method_listener_2(self, name, new): self.exceptions_from.append(2) raise Exception('error') def failing_method_listener_3(self, obj, name, new): self.exceptions_from.append(3) raise Exception('error') def failing_method_listener_4(self, obj, name, old, new): self.exceptions_from.append(4) raise Exception('error')
def collect_general_telemetry_data(session, telemetry_user): endpoints = session.query(Endpoint.name).all() blueprints = set((get_blueprint(endpoint) for (endpoint,) in endpoints)) no_of_endpoints = len(endpoints) no_of_blueprints = len(blueprints) counts = session.query(Endpoint.monitor_level, func.count(Endpoint.monitor_level)).group_by(Endpoint.monitor_level).all() counts_dict = dict(counts) level_zeros_count = counts_dict.get(0, 0) level_ones_count = counts_dict.get(1, 0) level_twos_count = counts_dict.get(2, 0) level_threes_count = counts_dict.get(3, 0) data = {'endpoints': no_of_endpoints, 'blueprints': no_of_blueprints, 'time_initialized': telemetry_user.last_initialized.strftime('%Y-%m-%d %H:%M:%S'), 'monitoring_0': level_zeros_count, 'monitoring_1': level_ones_count, 'monitoring_2': level_twos_count, 'monitoring_3': level_threes_count} post_to_back_if_telemetry_enabled('UserSession', **data)
class TestGetRegexCleanedLayoutBlockWithPrefixSuffix(): def test_should_return_original_block_for_non_matching_regex(self): layout_block = LayoutBlock.for_text('test') (prefix_block, cleaned_block, suffix_block) = get_regex_cleaned_layout_block_with_prefix_suffix(layout_block, 'other') assert (not prefix_block.lines) assert (cleaned_block == layout_block) assert (not suffix_block.lines) def test_should_return_original_block_for_empty_block(self): layout_block = LayoutBlock(lines=[]) (prefix_block, cleaned_block, suffix_block) = get_regex_cleaned_layout_block_with_prefix_suffix(layout_block, 'other') assert (not prefix_block.lines) assert (cleaned_block == layout_block) assert (not suffix_block.lines) def test_should_return_prefix_for_prefix_match(self): layout_block = LayoutBlock.for_text('a b c d') (prefix_block, cleaned_block, suffix_block) = get_regex_cleaned_layout_block_with_prefix_suffix(layout_block, '.*?(b.*)') assert (prefix_block.text == 'a') assert (cleaned_block.text == 'b c d') assert (not suffix_block.lines) def test_should_return_suffix_for_suffix_match(self): layout_block = LayoutBlock.for_text('a b c d') (prefix_block, cleaned_block, suffix_block) = get_regex_cleaned_layout_block_with_prefix_suffix(layout_block, '(.*)d') assert (not prefix_block.lines) assert (cleaned_block.text == 'a b c') assert (suffix_block.text == 'd') def test_should_return_prefix_suffix_for_prefix_suffix_match(self): layout_block = LayoutBlock.for_text('a b c d') (prefix_block, cleaned_block, suffix_block) = get_regex_cleaned_layout_block_with_prefix_suffix(layout_block, 'a(.*)d') assert (prefix_block.text == 'a') assert (cleaned_block.text == 'b c') assert (suffix_block.text == 'd')
def _parse_cache_to_checkpoint_action_required(cache: dict[(str, Any)]) -> CheckpointActionRequired: collection = (CollectionAddress(cache['collection']['dataset'], cache['collection']['collection']) if cache.get('collection') else None) action_needed = ([ManualAction(**action) for action in cache['action_needed']] if cache.get('action_needed') else None) return CheckpointActionRequired(step=cache['step'], collection=collection, action_needed=action_needed)
class StubEditor(Editor): is_event = Bool() auxiliary_value = Any() auxiliary_list = List() auxiliary_event = Event() auxiliary_cv_int = Int(sync_value='from') auxiliary_cv_float = Float() def init(self, parent): self.control = FakeControl() self.is_event = self.factory.is_event if self.is_event: self.control.on_trait_change(self.update_object, 'control_event') else: self.control.on_trait_change(self.update_object, 'control_value') self.set_tooltip() def dispose(self): if self.is_event: self.control.on_trait_change(self.update_object, 'control_event', remove=True) else: self.control.on_trait_change(self.update_object, 'control_value', remove=True) super().dispose() def update_editor(self): if self.is_event: self.control.control_event = True else: self.control.control_value = self.value def update_object(self, new): if (self.control is not None): if (not self._no_update): self._no_update = True try: self.value = new finally: self._no_update = False def set_tooltip_text(self, control, text): control.tooltip = text def set_focus(self, parent): pass
def pytest_collection_modifyitems(config, items): if config.getoption('--network'): global _dev_network _dev_network = config.getoption('--network') if config.getoption('--evm'): target = 'evm' else: target = config.getoption('--target') for (flag, fixture) in TARGET_OPTS.items(): if (target == flag): continue for test in [i for i in items if (fixture in i.fixturenames)]: items.remove(test) if (target != 'core'): fixtures = set(TARGET_OPTS.values()) for test in [i for i in items if (not fixtures.intersection(i.fixturenames))]: items.remove(test)
def get_stock_rating_data(debug=False): global data_to_add global allStockData counter = 0 print('\nCalculating Stock Ratings...\n') with tqdm(total=allStockData.shape[0]) as pbar: for row in allStockData.iterrows(): (ticker, sector) = (row[1]['Ticker'], row[1]['Sector']) category_grades = get_category_grades(ticker, sector) stock_rating = get_stock_rating(category_grades) data_to_add['Overall Rating'].append(stock_rating) data_to_add['Valuation Grade'].append(convert_to_letter_grade(category_grades['Valuation'][(- 1)])) data_to_add['Profitability Grade'].append(convert_to_letter_grade(category_grades['Profitability'][(- 1)])) data_to_add['Growth Grade'].append(convert_to_letter_grade(category_grades['Growth'][(- 1)])) data_to_add['Performance Grade'].append(convert_to_letter_grade(category_grades['Performance'][(- 1)])) counter += 1 pbar.update(1) if ((debug == True) and (counter == 10)): break
_required _required _POST def settings_form(request, hostname): if (hostname is None): vm = None else: vm = get_vm(request, hostname) if request.user.is_admin(request): action = None form = AdminServerSettingsForm(request, vm, request.POST, prefix='opt') else: action = 'update' form = ServerSettingsForm(request, vm, request.POST, prefix='opt') if form.is_valid(): status = form.save(action=action, args=(form.current_hostname,)) if (status == 204): return HttpResponse(None, status=status) elif (status in (200, 201)): if (form.action == 'delete'): return redirect('vm_list') else: return redirect('vm_details', hostname=form.saved_hostname) return render(request, 'gui/vm/settings_form.html', {'settingsform': form, 'vm': vm, 'mb_addon': SIZE_FIELD_MB_ADDON, 'percent_addon': SIZE_FIELD_PERCENT_ADDON})
class IndexWrapperForCfGrib(): def __init__(self, index=None, ignore_keys=[]): self.index = index self.ignore_keys = ignore_keys def __getstate__(self): return dict(index=serialise_state(self.index), ignore_keys=self.ignore_keys) def __setstate__(self, state): self.index = deserialise_state(state['index']) self.ignore_keys = state['ignore_keys'] def __getitem__(self, n): return ItemWrapperForCfGrib(self.index[n], ignore_keys=self.ignore_keys) def __len__(self): return len(self.index)
class OptionSeriesErrorbarSonificationDefaultinstrumentoptionsMappingPan(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class OptionSonificationGlobalcontexttracksMappingPlaydelay(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def value(self): return self._config_get(None) def value(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
(arrays_OI_O_BI(max_batch=8, max_out=8, max_in=8)) def test_dropout_gives_zero_gradients(W_b_input): model = chain(get_model(W_b_input), Dropout(1.0)) (nr_batch, nr_out, nr_in) = get_shape(W_b_input) (W, b, input_) = W_b_input for node in model.walk(): if (node.name == 'dropout'): node.attrs['dropout_rate'] = 1.0 (fwd_dropped, finish_update) = model.begin_update(input_) grad_BO = numpy.ones((nr_batch, nr_out), dtype='f') grad_BI = finish_update(grad_BO) assert all(((val == 0.0) for val in grad_BI.flatten()))
class UtilsTest(unittest.TestCase): def test_json_hook(self): example_input = {'date': '/Date(+1300)/'} self.assertEqual(xero.utils.json_load_object_hook(example_input), {'date': datetime.datetime(2015, 3, 21, 0, 0)}) example_input = {'date': '2015-04-29T00:00:00'} self.assertEqual(xero.utils.json_load_object_hook(example_input), {'date': datetime.date(2015, 4, 29)}) example_input = {'date': '2015-04-29T10:21:03'} self.assertEqual(xero.utils.json_load_object_hook(example_input), {'date': datetime.datetime(2015, 4, 29, 10, 21, 3)}) self.assertEqual(xero.utils.json_load_object_hook({'date': 6}), {'date': 6}) self.assertEqual(xero.utils.json_load_object_hook({'date': None}), {'date': None}) example_input = {'date': '/Date(0+0000)/'} self.assertEqual(xero.utils.json_load_object_hook(example_input), {'date': '/Date(0+0000)/'}) def test_parse_date(self): self.assertEqual(xero.utils.parse_date('/Date(+1200)/'), datetime.datetime(2015, 5, 7, 0, 0)) self.assertEqual(xero.utils.parse_date('/Date(+1200)/'), datetime.datetime(2008, 9, 16, 10, 28, 51, 500000)) self.assertEqual(xero.utils.parse_date('/Date()/'), datetime.datetime(2015, 8, 10, 10, 55, 33, 355000)) self.assertEqual(xero.utils.parse_date('2015-04-29T00:00:00'), datetime.date(2015, 4, 29)) self.assertEqual(xero.utils.parse_date('2015-04-29T10:21:03'), datetime.datetime(2015, 4, 29, 10, 21, 3)) self.assertEqual(xero.utils.parse_date('not a date'), None) self.assertEqual(xero.utils.parse_date('/Date(0+0000)/'), None)
def get_datasets(root: str): transform_train = transforms.Compose([transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.201))]) transform_cv = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.201))]) tr_set = torchvision.datasets.CIFAR10(root=root, train=True, download=True, transform=transform_train) cv_set = torchvision.datasets.CIFAR10(root=root, train=False, download=True, transform=transform_cv) return (tr_set, cv_set)
class conn_tracking_zone(oxm): type_len = 119810 def __init__(self, value=None): if (value != None): self.value = value else: self.value = 0 return def pack(self): packed = [] packed.append(struct.pack('!L', self.type_len)) packed.append(struct.pack('!H', self.value)) return ''.join(packed) def unpack(reader): obj = conn_tracking_zone() _type_len = reader.read('!L')[0] assert (_type_len == 119810) obj.value = reader.read('!H')[0] return obj def __eq__(self, other): if (type(self) != type(other)): return False if (self.value != other.value): return False return True def pretty_print(self, q): q.text('conn_tracking_zone {') with q.group(): with q.indent(2): q.breakable() q.text('value = ') q.text(('%#x' % self.value)) q.breakable() q.text('}')
def main(): module_spec = schema_to_module_spec(versioned_schema) mkeyname = None fields = {'access_token': {'required': False, 'type': 'str', 'no_log': True}, 'enable_log': {'required': False, 'type': 'bool', 'default': False}, 'vdom': {'required': False, 'type': 'str', 'default': 'root'}, 'member_path': {'required': False, 'type': 'str'}, 'member_state': {'type': 'str', 'required': False, 'choices': ['present', 'absent']}, 'log_fortianalyzer_cloud_filter': {'required': False, 'type': 'dict', 'default': None, 'options': {}}} for attribute_name in module_spec['options']: fields['log_fortianalyzer_cloud_filter']['options'][attribute_name] = module_spec['options'][attribute_name] if (mkeyname and (mkeyname == attribute_name)): fields['log_fortianalyzer_cloud_filter']['options'][attribute_name]['required'] = True module = AnsibleModule(argument_spec=fields, supports_check_mode=False) check_legacy_fortiosapi(module) is_error = False has_changed = False result = None diff = None versions_check_result = None if module._socket_path: connection = Connection(module._socket_path) if ('access_token' in module.params): connection.set_option('access_token', module.params['access_token']) if ('enable_log' in module.params): connection.set_option('enable_log', module.params['enable_log']) else: connection.set_option('enable_log', False) fos = FortiOSHandler(connection, module, mkeyname) versions_check_result = check_schema_versioning(fos, versioned_schema, 'log_fortianalyzer_cloud_filter') (is_error, has_changed, result, diff) = fortios_log_fortianalyzer_cloud(module.params, fos) else: module.fail_json(**FAIL_SOCKET_MSG) if (versions_check_result and (versions_check_result['matched'] is False)): module.warn('Ansible has detected version mismatch between FortOS system and your playbook, see more details by specifying option -vvv') if (not is_error): if (versions_check_result and (versions_check_result['matched'] is False)): module.exit_json(changed=has_changed, version_check_warning=versions_check_result, meta=result, diff=diff) else: module.exit_json(changed=has_changed, meta=result, diff=diff) elif (versions_check_result and (versions_check_result['matched'] is False)): module.fail_json(msg='Error in repo', version_check_warning=versions_check_result, meta=result) else: module.fail_json(msg='Error in repo', meta=result)
class TyperTest(unittest.TestCase): def test_typer(self) -> None: self.maxDiff = None bmg = BMGraphBuilder() c0 = bmg.add_constant(0.0) c1 = bmg.add_constant(1.0) c2 = bmg.add_constant(2.0) c3 = bmg.add_constant(3.0) norm = bmg.add_normal(c0, c1) ns = bmg.add_sample(norm) d = bmg.add_division(ns, c2) a = bmg.add_addition(d, c3) e = bmg.add_exp(a) neg = bmg.add_negate(a) typer = SupportedTyper() self.assertTrue(typer[ns]) self.assertTrue((norm in typer)) self.assertTrue((c0 in typer)) self.assertTrue((c1 in typer)) self.assertFalse((d in typer)) self.assertFalse((a in typer)) self.assertFalse((c2 in typer)) self.assertFalse((c3 in typer)) self.assertFalse((e in typer)) self.assertFalse((neg in typer)) self.assertFalse(typer[e]) self.assertTrue((a in typer)) self.assertTrue((d in typer)) self.assertTrue((c3 in typer)) self.assertTrue((c2 in typer)) self.assertFalse((neg in typer)) self.assertFalse(typer[d]) self.assertFalse(typer[a]) self.assertFalse(typer[e]) self.assertTrue(typer[c2]) self.assertTrue(typer[c3]) c4 = bmg.add_constant(0.5) m = bmg.add_multiplication(ns, c4) a.inputs[0] = m self.assertFalse(typer[a]) typer.update_type(a) self.assertTrue(typer[a]) self.assertTrue((m in typer)) self.assertTrue((c4 in typer)) self.assertFalse((neg in typer)) self.assertTrue(typer[m]) self.assertTrue(typer[e])
class EvalTableFilter(TableFilter): name = 'Default evaluation filter' expression = Expression filter_view = Group('expression') def filter(self, object): if (self._traits is None): self._traits = object.trait_names() try: return eval(self.expression_, globals(), object.trait_get(*self._traits)) except: return False def description(self): return self.expression
def extractOtherworldsinwordWordpressCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('riad', 'The Roommates Were Ecstatic to See Their Roommate in a Dress', 'translated'), ('bwc', 'the boss wants to be coaxed', 'translated'), ('the boss wants to be coaxed', 'the boss wants to be coaxed', 'translated'), ('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
class AcceptHeaderVersioning(BaseVersioning): invalid_version_message = _('Invalid version in "Accept" header.') def determine_version(self, request, *args, **kwargs): media_type = MediaType(request.accepted_media_type) version = media_type.params.get(self.version_param, self.default_version) version = unicode_ if (not self.is_allowed_version(version)): raise exceptions.NotAcceptable(self.invalid_version_message) return version
.django_db def test_award_count_cfo_agencies_only(client, monkeypatch, award_data, helpers, elasticsearch_award_index): setup_elasticsearch_test(monkeypatch, elasticsearch_award_index) helpers.mock_current_fiscal_year(monkeypatch) resp = client.get(url.format(filters='?group=cfo')) results = resp.data['results'] assert (resp.status_code == status.HTTP_200_OK) assert (len(results) == 1)
def distance_matrix_new(target, leaf_only=False, topological=False): t = target.root real_outgroup = t.children[0] t.set_outgroup(target) n2dist = {target: 0} for n in target.get_descendants('preorder'): n2dist[n] = (n2dist[n.up] + (topological or n.dist)) sister = target.get_sisters()[0] n2dist[sister] = ((topological or sister.dist) + (topological or target.dist)) for n in sister.get_descendants('preorder'): n2dist[n] = (n2dist[n.up] + (topological or n.dist)) t.set_outgroup(real_outgroup) return n2dist
def _partial_quarterly_schedule_for_year(year): for quarter in range(1, 4): baker.make('submissions.DABSSubmissionWindowSchedule', is_quarter=True, submission_fiscal_year=year, submission_fiscal_quarter=quarter, submission_fiscal_month=(quarter * 3), submission_reveal_date=f'{year}-{(quarter * 3)}-15')
def test_caller_with_block_identifier(w3, math_contract): start_num = w3.eth.get_block('latest').number assert (math_contract.caller.counter() == 0) w3.provider.make_request(method='evm_mine', params=[5]) math_contract.functions.incrementCounter().transact() math_contract.functions.incrementCounter().transact() output1 = math_contract.caller(block_identifier=(start_num + 6)).counter() output2 = math_contract.caller(block_identifier=(start_num + 7)).counter() assert (output1 == 1) assert (output2 == 2)
class THBattleUTBootstrap(BootstrapAction): game: THBattle def __init__(self, params: Dict[(str, Any)], items: Dict[(Player, List[GameItem])], players: BatchList[Player]): self.source = self.target = None self.params = params self.items = items self.players = players def apply_action(self) -> bool: from thb.characters.alice import Alice pl = self.players g = self.game g.players = BatchList([Alice(p) for p in pl]) g.roles = {p: PlayerRole(THBUnitRole) for p in pl} items = self.items _ = roll(g, pl, items) sync_primitive(1, pl) sync_primitive(2, pl) sync_primitive(3, pl) sync_primitive(4, pl) sync_primitive(5, pl) sync_primitive(6, pl) raise GameEnded(self.players)
class OptionPlotoptionsBarSonificationDefaultinstrumentoptionsMappingTime(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class OptionSeriesScatter3dDataMarkerStatesSelect(Options): def enabled(self): return self._config_get(True) def enabled(self, flag: bool): self._config(flag, js_type=False) def fillColor(self): return self._config_get('#cccccc') def fillColor(self, text: str): self._config(text, js_type=False) def lineColor(self): return self._config_get('#000000') def lineColor(self, text: str): self._config(text, js_type=False) def lineWidth(self): return self._config_get(2) def lineWidth(self, num: float): self._config(num, js_type=False) def radius(self): return self._config_get(None) def radius(self, num: float): self._config(num, js_type=False)
class AssetBuildingTestRunner(DiscoverRunner): os.environ['DJANGO_LIVE_TEST_SERVER_ADDRESS'] = '0.0.0.0:6080-6580' def build_suite(self, test_labels, extra_tests=None, **kwargs): if ((os.environ.get('TEST_SUITE', '') == 'functional') and (len(test_labels) == 0)): test_labels = ['frontend.tests.functional'] return super(AssetBuildingTestRunner, self).build_suite(test_labels, extra_tests, **kwargs) def setup_test_environment(self): os.environ['API_HOST'] = (' % MockApiServer.api_port()) npm_cmd = 'mkdir -p ../../static/js && npm run build' if (('SKIP_NPM_BUILD' not in os.environ) and (os.environ.get('TEST_SUITE', '') != 'nonfunctional')): subprocess.check_call(npm_cmd, shell=True, cwd=(settings.APPS_ROOT + '/media/js')) if (not os.environ.get('BROWSER')): os.environ['BROWSER'] = 'firefox:latest:Windows 10' if (os.environ.get('TEST_SUITE', '') != 'nonfunctional'): MockApiServer().start() super(AssetBuildingTestRunner, self).setup_test_environment()
def test_multi_stage_build_batch(): uid_generator = string_generator() request_info1 = dm.RequestInfo(input=np.array(range(10)), parameters={'gif_id': 12}) request_object1 = dm.RequestObject(uid=next(uid_generator), request_info=request_info1, source_id='internal_123_124', model=stub_model) request_info2 = dm.RequestInfo(input=np.array(range(10)), parameters={}) request_object2 = dm.RequestObject(uid=next(uid_generator), request_info=request_info2, source_id='internal_123_123', model=blur_stateful_model) request_info3 = dm.RequestInfo(input=np.array(range(10)), parameters={}) request_object3 = dm.RequestObject(uid=next(uid_generator), request_info=request_info3, source_id='internal_123_125', model=stub_stateful_model) request_info4 = dm.RequestInfo(input=np.array(range(10)), parameters={}) request_object4 = dm.RequestObject(uid=next(uid_generator), request_info=request_info4, source_id='internal_123_121', model=stub_stateful_model) request_info5 = dm.RequestInfo(input=np.array(range(10)), parameters={}) request_object5 = dm.RequestObject(uid=next(uid_generator), request_info=request_info5, source_id='internal_123_123', model=blur_stateful_model) request_info6 = dm.RequestInfo(input=np.array(range(10)), parameters={}) request_object6 = dm.RequestObject(uid=next(uid_generator), request_info=request_info6, source_id='internal_123_123', model=blur_stateful_model) request_info7 = dm.RequestInfo(input=np.array(range(10)), parameters={'gif_id': 12}) request_object7 = dm.RequestObject(uid=next(uid_generator), request_info=request_info7, source_id='internal_123_127', model=blur_model) batch_uid_generator = string_generator() expected_value = dm.Batches(batches=[dm.BatchObject(uid=next(batch_uid_generator), requests_info=[request_object1.request_info], model=stub_model, request_objects=[request_object1]), dm.BatchObject(uid=next(batch_uid_generator), requests_info=[request_object2.request_info, request_object5.request_info, request_object6.request_info], source_id=request_object2.source_id, model=blur_stateful_model, request_objects=[request_object2, request_object5, request_object6]), dm.BatchObject(uid=next(batch_uid_generator), requests_info=[request_object3.request_info], model=stub_stateful_model, source_id=request_object3.source_id, request_objects=[request_object3]), dm.BatchObject(uid=next(batch_uid_generator), requests_info=[request_object4.request_info], model=stub_stateful_model, source_id=request_object4.source_id, request_objects=[request_object4]), dm.BatchObject(uid=next(batch_uid_generator), requests_info=[request_object7.request_info], model=blur_model, request_objects=[request_object7])]) build_batch_generator = string_generator() result_value = build_batches([request_object1, request_object2, request_object3], uid_generator=build_batch_generator) result_value = build_batches([request_object4, request_object5, request_object6, request_object7], existing_batches=result_value, uid_generator=build_batch_generator) assert (result_value == expected_value)
class Migration(migrations.Migration): dependencies = [('wagtailcore', '0030_index_on_pagerevision_created_at'), ('home', '0015_auto__0102')] operations = [migrations.CreateModel(name='FormField', fields=[('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('sort_order', models.IntegerField(blank=True, editable=False, null=True)), ('label', models.CharField(help_text='The label of the form field', max_length=255, verbose_name='label')), ('field_type', models.CharField(choices=[('singleline', 'Single line text'), ('multiline', 'Multi-line text'), ('email', 'Email'), ('number', 'Number'), ('url', 'URL'), ('checkbox', 'Checkbox'), ('checkboxes', 'Checkboxes'), ('dropdown', 'Drop down'), ('radio', 'Radio buttons'), ('date', 'Date'), ('datetime', 'Date/time')], max_length=16, verbose_name='field type')), ('required', models.BooleanField(default=True, verbose_name='required')), ('choices', models.TextField(blank=True, help_text='Comma separated list of choices. Only applicable in checkboxes, radio and dropdown.', verbose_name='choices')), ('default_value', models.CharField(blank=True, help_text='Default value. Comma separated values supported for checkboxes.', max_length=255, verbose_name='default value')), ('help_text', models.CharField(blank=True, max_length=255, verbose_name='help text'))], options={'abstract': False, 'ordering': ['sort_order']}), migrations.CreateModel(name='FormPage', fields=[('page_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='wagtailcore.Page')), ('to_address', models.CharField(blank=True, help_text='Optional - form submissions will be emailed to these addresses. Separate multiple addresses by comma.', max_length=255, verbose_name='to address')), ('from_address', models.CharField(blank=True, max_length=255, verbose_name='from address')), ('subject', models.CharField(blank=True, max_length=255, verbose_name='subject')), ('intro', wagtail.core.fields.RichTextField(blank=True)), ('thank_you_text', wagtail.core.fields.RichTextField(blank=True))], options={'abstract': False}, bases=('wagtailcore.page',)), migrations.AddField(model_name='formfield', name='page', field=modelcluster.fields.ParentalKey(on_delete=django.db.models.deletion.CASCADE, related_name='form_fields', to='home.FormPage'))]
def test_container_error(): obj = errors.ContainerError('code', 'my message', errors.ContainerError.Kind.RECOVERABLE, execution.ExecutionError.ErrorKind.SYSTEM) assert (obj.code == 'code') assert (obj.message == 'my message') assert (obj.kind == errors.ContainerError.Kind.RECOVERABLE) assert (obj.origin == 2) obj2 = errors.ContainerError.from_flyte_idl(obj.to_flyte_idl()) assert (obj == obj2) assert (obj2.code == 'code') assert (obj2.message == 'my message') assert (obj2.kind == errors.ContainerError.Kind.RECOVERABLE) assert (obj2.origin == 2)
('cuda.grouped_fmha_style_b2b_bmm.func_call') def grouped_fmha_style_b2b_bmm_gen_function_call(func_attrs, indent=' '): assert (len(func_attrs['outputs']) == 1) assert (len(func_attrs['inputs']) in (3, 4)) output_name = func_attrs['outputs'][0]._attrs['name'] q_name = func_attrs['inputs'][0]._attrs['name'] k_name = func_attrs['inputs'][1]._attrs['name'] v_name = func_attrs['inputs'][2]._attrs['name'] bias_name = 'nullptr' if (len(func_attrs['inputs']) == 4): bias_name = func_attrs['inputs'][3]._attrs['name'] q_shape = func_attrs['inputs'][0]._attrs['shape'] jagged_intvar = q_shape[0] batch_size_str = jagged_intvar.batch_dim()._attrs['name'] if (len(jagged_intvar.jagged_dims()) != 1): raise RuntimeError(f'Only support 1 jagged dim in grouped_fmha_style_b2b_bmm for now! Current jagged intvar: {jagged_intvar}') max_seq_length_dim = jagged_intvar.jagged_dims()[0].max_value() max_seq_length_str = (str(max_seq_length_dim.value()) if isinstance(max_seq_length_dim, IntImm) else max_seq_length_dim._attrs['name']) num_heads_str = q_shape[1]._attrs['name'] offset = f'{jagged_intvar.offsets_var_name()}.data[0]' return FUNC_CALL_TEMPLATE.render(func_name=func_attrs['name'], output=output_name, query=q_name, key=k_name, value=v_name, bias=bias_name, accum_ptr='global_workspace_', batch_size=batch_size_str, seq_length=max_seq_length_str, seq_length_kv=max_seq_length_str, num_heads=num_heads_str, offset=offset, indent=indent)
def _split(ops: Ops, Xp: Padded) -> Tuple[(Padded, Padded)]: half = (Xp.data.shape[(- 1)] // 2) X_l2r = Xp.data[cast(Tuple[(slice, slice)], (..., slice(None, half)))] X_r2l = Xp.data[cast(Tuple[(slice, slice)], (..., slice(half)))] return (Padded(X_l2r, Xp.size_at_t, Xp.lengths, Xp.indices), Padded(X_r2l, Xp.size_at_t, Xp.lengths, Xp.indices))
class OptionSeriesPyramidAccessibility(Options): def description(self): return self._config_get(None) def description(self, text: str): self._config(text, js_type=False) def descriptionFormat(self): return self._config_get(None) def descriptionFormat(self, text: str): self._config(text, js_type=False) def enabled(self): return self._config_get(None) def enabled(self, flag: bool): self._config(flag, js_type=False) def exposeAsGroupOnly(self): return self._config_get(None) def exposeAsGroupOnly(self, flag: bool): self._config(flag, js_type=False) def keyboardNavigation(self) -> 'OptionSeriesPyramidAccessibilityKeyboardnavigation': return self._config_sub_data('keyboardNavigation', OptionSeriesPyramidAccessibilityKeyboardnavigation) def point(self) -> 'OptionSeriesPyramidAccessibilityPoint': return self._config_sub_data('point', OptionSeriesPyramidAccessibilityPoint)
def get_security_info(esp, args): si = esp.get_security_info() print() title = 'Security Information:' print(title) print(('=' * len(title))) print('Flags: {:#010x} ({})'.format(si['flags'], bin(si['flags']))) print('Key Purposes: {}'.format(si['key_purposes'])) if ((si['chip_id'] is not None) and (si['api_version'] is not None)): print('Chip ID: {}'.format(si['chip_id'])) print('API Version: {}'.format(si['api_version'])) flags = si['flags'] if get_security_flag_status('SECURE_BOOT_EN', flags): print('Secure Boot: Enabled') if get_security_flag_status('SECURE_BOOT_AGGRESSIVE_REVOKE', flags): print('Secure Boot Aggressive key revocation: Enabled') revoked_keys = [] for (i, key) in enumerate(['SECURE_BOOT_KEY_REVOKE0', 'SECURE_BOOT_KEY_REVOKE1', 'SECURE_BOOT_KEY_REVOKE2']): if get_security_flag_status(key, flags): revoked_keys.append(i) if (len(revoked_keys) > 0): print('Secure Boot Key Revocation Status:\n') for i in revoked_keys: print(f''' Secure Boot Key{i} is Revoked ''') else: print('Secure Boot: Disabled') flash_crypt_cnt = bin(si['flash_crypt_cnt']) if ((flash_crypt_cnt.count('1') % 2) != 0): print('Flash Encryption: Enabled') else: print('Flash Encryption: Disabled') CRYPT_CNT_STRING = 'SPI Boot Crypt Count (SPI_BOOT_CRYPT_CNT)' if (esp.CHIP_NAME == 'esp32'): CRYPT_CNT_STRING = 'Flash Crypt Count (FLASH_CRYPT_CNT)' print(f"{CRYPT_CNT_STRING}: {si['flash_crypt_cnt']:#x}") if get_security_flag_status('DIS_DOWNLOAD_DCACHE', flags): print('Dcache in UART download mode: Disabled') if get_security_flag_status('DIS_DOWNLOAD_ICACHE', flags): print('Icache in UART download mode: Disabled') hard_dis_jtag = get_security_flag_status('HARD_DIS_JTAG', flags) soft_dis_jtag = get_security_flag_status('SOFT_DIS_JTAG', flags) if hard_dis_jtag: print('JTAG: Permenantly Disabled') elif soft_dis_jtag: print('JTAG: Software Access Disabled') if get_security_flag_status('DIS_USB', flags): print('USB Access: Disabled')
class VersionTreeModel(QtGui.QStandardItemModel): def __init__(self, flat_view=False, *args, **kwargs): QtGui.QStandardItemModel.__init__(self, *args, **kwargs) logger.debug('VersionTreeModel.__init__() is started') self.root = None self.root_versions = [] self.reference_resolution = None self.flat_view = flat_view logger.debug('VersionTreeModel.__init__() is finished') def populateTree(self, versions): logger.debug('VersionTreeModel.populateTree() is started') self.setColumnCount(7) self.setHorizontalHeaderLabels(['Do Update?', 'Thumbnail', 'Task', 'Take', 'Current', 'Latest', 'Action', 'Updated By', 'Notes']) self.root_versions = versions for version in versions: self.appendRow(VersionItem.generate_version_row(None, self, version)) logger.debug('VersionTreeModel.populateTree() is finished') def canFetchMore(self, index): logger.debug(('VersionTreeModel.canFetchMore() is started for index: %s' % index)) if (not index.isValid()): return_value = False else: item = self.itemFromIndex(index) return_value = item.canFetchMore() logger.debug(('VersionTreeModel.canFetchMore() is finished for index: %s' % index)) return return_value def fetchMore(self, index): logger.debug(('VersionTreeModel.canFetchMore() is started for index: %s' % index)) if index.isValid(): item = self.itemFromIndex(index) item.fetchMore() logger.debug(('VersionTreeModel.canFetchMore() is finished for index: %s' % index)) def hasChildren(self, index): logger.debug(('VersionTreeModel.hasChildren() is started for index: %s' % index)) if (not index.isValid()): return_value = (len(self.root_versions) > 0) elif self.flat_view: return False else: item = self.itemFromIndex(index) return_value = False if item: return_value = item.hasChildren() logger.debug(('VersionTreeModel.hasChildren() is finished for index: %s' % index)) return return_value
_oriented class SPHSolver(): method_WCSPH = 0 method_PCISPH = 1 method_DFSPH = 2 methods = {'WCSPH': method_WCSPH, 'PCISPH': method_PCISPH, 'DFSPH': method_DFSPH} material_fluid = 1 material_bound = 0 materials = {'fluid': material_fluid, 'bound': material_bound} def __init__(self, res, screen_to_world_ratio, bound, alpha=0.5, dx=0.2, max_num_particles=(2 ** 20), padding=12, max_time=5.0, max_steps=50000, dynamic_allocate=False, adaptive_time_step=True, method=0): self.method = method self.adaptive_time_step = adaptive_time_step self.dim = len(res) self.res = res self.screen_to_world_ratio = screen_to_world_ratio self.dynamic_allocate = dynamic_allocate self.padding = (2 * dx) self.max_time = max_time self.max_steps = max_steps self.max_num_particles = max_num_particles self.g = (- 9.8) self.alpha = alpha self.rho_0 = 1000.0 self.CFL_v = 0.25 self.CFL_a = 0.05 self.df_fac = 1.3 self.dx = dx self.dh = (self.dx * self.df_fac) self.dt = ti.field(ti.f32, shape=()) self.m = ((self.dx ** self.dim) * self.rho_0) self.grid_size = (2 * self.dh) self.grid_pos = np.ceil(((np.array(res) / self.screen_to_world_ratio) / self.grid_size)).astype(int) self.top_bound = bound[0] self.bottom_bound = bound[1] self.left_bound = bound[2] self.right_bound = bound[3] self.gamma = 7.0 self.c_0 = 200.0 self.s_f = ti.field(ti.f32, shape=()) self.it = 0 self.max_it = 0 self.sub_max_iteration = 3 self.rho_err = ti.Vector.field(1, dtype=ti.f32, shape=()) self.max_rho_err = ti.Vector.field(1, dtype=ti.f32, shape=()) self.sum_rho_err = ti.field(ti.f32, shape=()) self.sum_drho = ti.field(ti.f32, shape=()) self.source_bound = ti.Vector.field(self.dim, dtype=ti.f32, shape=2) self.source_velocity = ti.Vector.field(self.dim, dtype=ti.f32, shape=()) self.source_pressure = ti.Vector.field(1, dtype=ti.f32, shape=()) self.source_density = ti.Vector.field(1, dtype=ti.f32, shape=()) self.particle_num = ti.field(ti.i32, shape=()) self.particle_positions = ti.Vector.field(self.dim, dtype=ti.f32) self.particle_velocity = ti.Vector.field(self.dim, dtype=ti.f32) self.particle_positions_new = ti.Vector.field(self.dim, dtype=ti.f32) self.particle_velocity_new = ti.Vector.field(self.dim, dtype=ti.f32) self.particle_pressure = ti.Vector.field(1, dtype=ti.f32) self.particle_pressure_acc = ti.Vector.field(self.dim, dtype=ti.f32) self.particle_density = ti.Vector.field(1, dtype=ti.f32) self.particle_density_new = ti.Vector.field(1, dtype=ti.f32) self.particle_alpha = ti.Vector.field(1, dtype=ti.f32) self.particle_stiff = ti.Vector.field(1, dtype=ti.f32) self.color = ti.field(dtype=ti.f32) self.material = ti.field(dtype=ti.f32) self.d_velocity = ti.Vector.field(self.dim, dtype=ti.f32) self.d_density = ti.Vector.field(1, dtype=ti.f32) self.grid_num_particles = ti.field(ti.i32) self.grid2particles = ti.field(ti.i32) self.particle_num_neighbors = ti.field(ti.i32) self.particle_neighbors = ti.field(ti.i32) self.max_num_particles_per_cell = 100 self.max_num_neighbors = 100 self.max_v = 0.0 self.max_a = 0.0 self.max_rho = 0.0 self.max_pressure = 0.0 if dynamic_allocate: ti.root.dynamic(ti.i, max_num_particles, (2 ** 18)).place(self.particle_positions, self.particle_velocity, self.particle_pressure, self.particle_density, self.particle_density_new, self.d_velocity, self.d_density, self.material, self.color, self.particle_positions_new, self.particle_velocity_new, self.particle_pressure_acc, self.particle_alpha, self.particle_stiff) else: ti.root.dense(ti.i, (2 ** 18)).place(self.particle_positions, self.particle_velocity, self.particle_pressure, self.particle_density, self.particle_density_new, self.d_velocity, self.d_density, self.material, self.color, self.particle_positions_new, self.particle_velocity_new, self.particle_pressure_acc, self.particle_alpha, self.particle_stiff) if (self.dim == 2): grid_snode = ti.root.dense(ti.ij, self.grid_pos) grid_snode.place(self.grid_num_particles) grid_snode.dense(ti.k, self.max_num_particles_per_cell).place(self.grid2particles) else: grid_snode = ti.root.dense(ti.ijk, self.grid_pos) grid_snode.place(self.grid_num_particles) grid_snode.dense(ti.l, self.max_num_particles_per_cell).place(self.grid2particles) nb_node = ti.root.dynamic(ti.i, max_num_particles) nb_node.place(self.particle_num_neighbors) nb_node.dense(ti.j, self.max_num_neighbors).place(self.particle_neighbors) if (method == SPHSolver.method_WCSPH): self.dt.from_numpy(np.array(((0.1 * self.dh) / self.c_0), dtype=np.float32)) self.CFL_v = 0.2 self.CFL_a = 0.2 if (method == SPHSolver.method_PCISPH): self.s_f.from_numpy(np.array(1.0, dtype=np.float32)) if self.adaptive_time_step: self.dt.from_numpy(np.array(0.0015, dtype=np.float32)) else: self.dt.from_numpy(np.array(0.00015, dtype=np.float32)) if (method == SPHSolver.method_DFSPH): self.dt.from_numpy(np.array(((1.0 * self.dh) / self.c_0), dtype=np.float32)) self.CFL_v = 0.3 self.CFL_a = 0.05 def compute_grid_index(self, pos): return (pos / (2 * self.dh)).cast(int) def allocate_particles(self): for p_i in range(self.particle_num[None]): cell = self.compute_grid_index(self.particle_positions[p_i]) offs = self.grid_num_particles[cell].atomic_add(1) self.grid2particles[(cell, offs)] = p_i def is_in_grid(self, c): res = 1 for i in ti.static(range(self.dim)): res = ti.atomic_and(res, (0 <= c[i] < self.grid_pos[i])) return res def is_fluid(self, p): return self.material[p] def search_neighbors(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] nb_i = 0 if ((self.is_fluid(p_i) == 1) or (self.is_fluid(p_i) == 0)): cell = self.compute_grid_index(self.particle_positions[p_i]) for offs in ti.static(ti.grouped(ti.ndrange(*((((- 1), 2),) * self.dim)))): cell_to_check = (cell + offs) if (self.is_in_grid(cell_to_check) == 1): for j in range(self.grid_num_particles[cell_to_check]): p_j = self.grid2particles[(cell_to_check, j)] if ((nb_i < self.max_num_neighbors) and (p_j != p_i) and ((pos_i - self.particle_positions[p_j]).norm() < (self.dh * 2.0))): self.particle_neighbors[(p_i, nb_i)] = p_j nb_i.atomic_add(1) self.particle_num_neighbors[p_i] = nb_i def cubic_kernel(self, r, h): k = (10.0 / ((7.0 * np.pi) * (h ** self.dim))) q = (r / h) res = ti.cast(0.0, ti.f32) if (q <= 1.0): res = (k * ((1 - (1.5 * (q ** 2))) + (0.75 * (q ** 3)))) elif (q < 2.0): res = ((k * 0.25) * ((2 - q) ** 3)) return res def cubic_kernel_derivative(self, r, h): k = (10.0 / ((7.0 * np.pi) * (h ** self.dim))) q = (r / h) res = ti.cast(0.0, ti.f32) if (q < 1.0): res = ((k / h) * (((- 3) * q) + (2.25 * (q ** 2)))) elif (q < 2.0): res = (((- 0.75) * (k / h)) * ((2 - q) ** 2)) return res def rho_derivative(self, ptc_i, ptc_j, r, r_mod): return ((self.m * self.cubic_kernel_derivative(r_mod, self.dh)) * (self.particle_velocity[ptc_i] - self.particle_velocity[ptc_j]).dot((r / r_mod))) def p_update(self, rho, rho_0=1000.0, gamma=7.0, c_0=20.0): b = ((rho_0 * (c_0 ** 2)) / gamma) return (b * (((rho / rho_0) ** gamma) - 1.0)) def pressure_force(self, ptc_i, ptc_j, r, r_mod): res = ti.Vector([0.0 for _ in range(self.dim)]) res = (((((- self.m) * ((self.particle_pressure[ptc_i][0] / (self.particle_density[ptc_i][0] ** 2)) + (self.particle_pressure[ptc_j][0] / (self.particle_density[ptc_j][0] ** 2)))) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) return res def viscosity_force(self, ptc_i, ptc_j, r, r_mod): res = ti.Vector([0.0 for _ in range(self.dim)]) v_xy = (self.particle_velocity[ptc_i] - self.particle_velocity[ptc_j]).dot(r) if (v_xy < 0): vmu = (((((- 2.0) * self.alpha) * self.dx) * self.c_0) / (self.particle_density[ptc_i][0] + self.particle_density[ptc_j][0])) res = (((((((- self.m) * vmu) * v_xy) / ((r_mod ** 2) + (0.01 * (self.dx ** 2)))) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) return res def simulate_collisions(self, ptc_i, vec, d): c_f = 0.3 self.particle_positions[ptc_i] += (vec * d) self.particle_velocity[ptc_i] -= (((1.0 + c_f) * self.particle_velocity[ptc_i].dot(vec)) * vec) if (self.method == SPHSolver.method_DFSPH): self.particle_velocity_new[ptc_i] -= (((1.0 + c_f) * self.particle_velocity_new[ptc_i].dot(vec)) * vec) def enforce_boundary(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): pos = self.particle_positions[p_i] if (pos[0] < (self.left_bound + (0.5 * self.padding))): self.simulate_collisions(p_i, ti.Vector([1.0, 0.0]), ((self.left_bound + (0.5 * self.padding)) - pos[0])) if (pos[0] > (self.right_bound - (0.5 * self.padding))): self.simulate_collisions(p_i, ti.Vector([(- 1.0), 0.0]), ((pos[0] - self.right_bound) + (0.5 * self.padding))) if (pos[1] > (self.top_bound - self.padding)): self.simulate_collisions(p_i, ti.Vector([0.0, (- 1.0)]), ((pos[1] - self.top_bound) + self.padding)) if (pos[1] < (self.bottom_bound + self.padding)): self.simulate_collisions(p_i, ti.Vector([0.0, 1.0]), ((self.bottom_bound + self.padding) - pos[1])) def wc_compute_deltas(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_v = ti.Vector([0.0 for _ in range(self.dim)]) d_rho = 0.0 for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = ti.max(r.norm(), 1e-05) d_rho += self.rho_derivative(p_i, p_j, r, r_mod) if (self.is_fluid(p_i) == 1): d_v += self.viscosity_force(p_i, p_j, r, r_mod) d_v += self.pressure_force(p_i, p_j, r, r_mod) if (self.is_fluid(p_i) == 1): val = [0.0 for _ in range((self.dim - 1))] val.extend([self.g]) d_v += ti.Vector(val) self.d_velocity[p_i] = d_v self.d_density[p_i][0] = d_rho def wc_update_time_step(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_velocity[p_i] += (self.dt[None] * self.d_velocity[p_i]) self.particle_positions[p_i] += (self.dt[None] * self.particle_velocity[p_i]) self.particle_density[p_i][0] += (self.dt[None] * self.d_density[p_i][0]) self.particle_pressure[p_i][0] = self.p_update(self.particle_density[p_i][0], self.rho_0, self.gamma, self.c_0) def pci_scaling_factor(self): grad_sum = ti.Vector([0.0 for _ in range(self.dim)]) grad_dot_sum = 0.0 range_num = ti.cast(((self.dh * 2.0) / self.dx), ti.i32) half_range = ti.cast((0.5 * range_num), ti.i32) for x in range((- half_range), half_range): for y in range((- half_range), half_range): r = ti.Vector([((- x) * self.dx), ((- y) * self.dx)]) r_mod = r.norm() if ((2.0 * self.dh) > r_mod > 1e-05): grad = ((self.cubic_kernel_derivative(r_mod, self.dh) * r) / r_mod) grad_sum += grad grad_dot_sum += grad.dot(grad) beta = (2 * (((self.dt[None] * self.m) / self.rho_0) ** 2)) self.s_f[None] = (1.0 / ti.max((beta * (grad_sum.dot(grad_sum) + grad_dot_sum)), 1e-06)) def pci_pos_vel_prediction(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_velocity_new[p_i] = (self.particle_velocity[p_i] + (self.dt[None] * (self.d_velocity[p_i] + self.particle_pressure_acc[p_i]))) self.particle_positions_new[p_i] = (self.particle_positions[p_i] + (self.dt[None] * self.particle_velocity_new[p_i])) self.max_rho_err[None][0] = 0.0 def pci_update_pressure(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions_new[p_i] d_rho = 0.0 curr_rho = 0.0 for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions_new[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 1e-05): d_rho += (self.cubic_kernel_derivative(r_mod, self.dh) * (self.particle_velocity_new[p_i] - self.particle_velocity_new[p_j]).dot((r / r_mod))) self.d_density[p_i][0] = d_rho self.rho_err[None][0] = ((self.particle_density[p_i][0] + (self.dt[None] * d_rho)) - self.rho_0) self.max_rho_err[None][0] = max(abs(self.rho_err[None][0]), self.max_rho_err[None][0]) self.particle_pressure[p_i][0] += (self.s_f[None] * self.rho_err[None][0]) def pci_update_pressure_force(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions_new[p_i] d_vp = ti.Vector([0.0 for _ in range(self.dim)]) for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions_new[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 1e-05): d_vp += self.pressure_force(p_i, p_j, r, r_mod) self.particle_pressure_acc[p_i] = d_vp def pci_pc_iteration(self): self.pci_pos_vel_prediction() self.pci_update_pressure() self.pci_update_pressure_force() def pci_compute_deltas(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_v = ti.Vector([0.0 for _ in range(self.dim)]) for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if ((r_mod > 1e-05) and (self.is_fluid(p_i) == 1)): d_v += self.viscosity_force(p_i, p_j, r, r_mod) if (self.is_fluid(p_i) == 1): val = [0.0 for _ in range((self.dim - 1))] val.extend([self.g]) d_v += ti.Vector(val) self.d_velocity[p_i] = d_v self.particle_pressure[p_i][0] = 0.0 self.particle_pressure_acc[p_i] = ti.Vector([0.0 for _ in range(self.dim)]) def pci_update_time_step(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_velocity[p_i] += (self.dt[None] * (self.d_velocity[p_i] + self.particle_pressure_acc[p_i])) self.particle_positions[p_i] += (self.dt[None] * self.particle_velocity[p_i]) self.particle_density[p_i][0] += (self.dt[None] * self.d_density[p_i][0]) def df_compute_deltas(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_v = ti.Vector([0.0 for _ in range(self.dim)]) for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if ((r_mod > 0.0001) and (self.is_fluid(p_i) == 1)): d_v += self.viscosity_force(p_i, p_j, r, r_mod) if (self.is_fluid(p_i) == 1): val = [0.0 for _ in range((self.dim - 1))] val.extend([self.g]) d_v += ti.Vector(val) self.d_velocity[p_i] = d_v def df_predict_velocities(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_velocity_new[p_i] = (self.particle_velocity[p_i] + (self.dt[None] * self.d_velocity[p_i])) def df_correct_density_predict(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_rho = 0.0 for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = ti.max(r.norm(), 1e-05) if (self.is_fluid(p_j) == 1): d_rho += ((self.m * self.cubic_kernel_derivative(r_mod, self.dh)) * (self.particle_velocity_new[p_i] - self.particle_velocity_new[p_j]).dot((r / r_mod))) elif (self.is_fluid(p_j) == 0): d_rho += ((self.m * self.cubic_kernel_derivative(r_mod, self.dh)) * self.particle_velocity_new[p_i].dot((r / r_mod))) self.particle_density_new[p_i][0] = (self.particle_density[p_i][0] + (self.dt[None] * d_rho)) err = ti.max(0.0, (self.particle_density_new[p_i][0] - self.rho_0)) self.particle_stiff[p_i][0] = (err * self.particle_alpha[p_i][0]) self.sum_rho_err[None] += err def df_correct_density_adapt_vel(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_v = ti.Vector([0.0 for _ in range(self.dim)]) for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 0.0001): if (self.is_fluid(p_j) == 1): d_v += ((((self.m * (self.particle_stiff[p_i][0] + self.particle_stiff[p_j][0])) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) elif (self.is_fluid(p_j) == 0): d_v += ((((self.m * self.particle_stiff[p_i][0]) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) self.particle_velocity_new[p_i] += (d_v / ti.max(self.dt[None], 1e-05)) self.particle_pressure_acc[p_i] = (d_v / ti.max((self.dt[None] * self.dt[None]), 1e-08)) def df_update_positions(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_positions[p_i] += (self.dt[None] * self.particle_velocity_new[p_i]) def df_compute_density_alpha(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] grad_sum = ti.Vector([0.0 for _ in range(self.dim)]) grad_square_sum = 0.0 curr_rho = 0.0 for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 0.0001): grad_val = (((self.m * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) grad_sum += grad_val if (self.is_fluid(p_j) == 1): grad_square_sum += grad_val.dot(grad_val) curr_rho += (self.m * self.cubic_kernel(r_mod, self.dh)) self.particle_density[p_i][0] = curr_rho self.particle_alpha[p_i][0] = ((- 1.0) / ti.max((grad_sum.dot(grad_sum) + grad_square_sum), 1e-06)) def df_correct_divergence_compute_drho(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_rho = 0.0 for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 0.0001): if (self.is_fluid(p_j) == 1): d_rho += ((self.m * (self.particle_velocity_new[p_i] - self.particle_velocity_new[p_j]).dot((r / r_mod))) * self.cubic_kernel_derivative(r_mod, self.dh)) elif (self.is_fluid(p_j) == 0): d_rho += ((self.m * self.particle_velocity_new[p_i].dot((r / r_mod))) * self.cubic_kernel_derivative(r_mod, self.dh)) self.d_density[p_i][0] = ti.max(d_rho, 0.0) if (((self.particle_density[p_i][0] + (self.dt[None] * self.d_density[p_i][0])) < self.rho_0) and (self.particle_density[p_i][0] < self.rho_0)): self.d_density[p_i][0] = 0.0 self.particle_stiff[p_i][0] = (self.d_density[p_i][0] * self.particle_alpha[p_i][0]) self.sum_drho[None] += self.d_density[p_i][0] def df_correct_divergence_adapt_vel(self): for p_i in range(self.particle_num[None]): pos_i = self.particle_positions[p_i] d_v = ti.Vector([0.0 for _ in range(self.dim)]) for j in range(self.particle_num_neighbors[p_i]): p_j = self.particle_neighbors[(p_i, j)] pos_j = self.particle_positions[p_j] r = (pos_i - pos_j) r_mod = r.norm() if (r_mod > 1e-05): if (self.is_fluid(p_j) == 1): d_v += ((((self.m * (self.particle_stiff[p_i][0] + self.particle_stiff[p_j][0])) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) elif (self.is_fluid(p_j) == 0): d_v += ((((self.m * self.particle_stiff[p_i][0]) * self.cubic_kernel_derivative(r_mod, self.dh)) * r) / r_mod) self.particle_velocity_new[p_i] += d_v self.particle_pressure_acc[p_i] = (d_v / self.dt[None]) def df_update_velocities(self): for p_i in range(self.particle_num[None]): if (self.is_fluid(p_i) == 1): self.particle_velocity[p_i] = self.particle_velocity_new[p_i] def sim_info(self, output=False): print('Time step: ', self.dt[None]) print(('Domain: (%s, %s, %s, %s)' % (self.x_min, self.x_max, self.y_min, self.y_max))) print(('Fluid area: (%s, %s, %s, %s)' % (self.left_bound, self.right_bound, self.bottom_bound, self.top_bound))) print('Grid: ', self.grid_pos) def sim_info_realtime(self, frame, t, curr_start, curr_end, total_start): print(('Step: %d, physics time: %s, progress: %s %%, time used: %s, total time used: %s' % (frame, t, (100 * np.max([(t / self.max_time), (frame / self.max_steps)])), (curr_end - curr_start), (curr_end - total_start)))) print(('Max velocity: %s, Max acceleration: %s, Max density: %s, Max pressure: %s' % (self.max_v, self.max_a, self.max_rho, self.max_pressure))) if (self.method == SPHSolver.methods['PCISPH']): print(('Max iter: %d, Max density variation: %s' % (self.max_it, self.max_rho_err[None][0]))) if (self.method == SPHSolver.methods['DFSPH']): print(('Max iter: %d, Max density variation: %s' % (self.it, (self.sum_rho_err[None] / self.particle_num[None])))) print(('Max iter: %d, Max divergence variation: %s' % (self.it, (self.sum_drho[None] / self.particle_num[None])))) print('Adaptive time step: ', self.dt[None]) def adaptive_step(self): total_num = self.particle_num[None] self.max_v = np.max(np.linalg.norm(self.particle_velocity.to_numpy()[:total_num], 2, axis=1)) dt_cfl = ((self.CFL_v * self.dh) / self.max_v) self.max_a = np.max(np.linalg.norm((self.d_velocity.to_numpy() + self.particle_pressure_acc.to_numpy())[:total_num], 2, axis=1)) dt_f = (self.CFL_a * np.sqrt((self.dh / self.max_a))) if (self.adaptive_time_step and (self.method == SPHSolver.method_DFSPH)): self.dt[None] = np.min([dt_cfl, dt_f]) return self.max_rho = np.max(self.particle_density.to_numpy()[:total_num]) self.max_pressure = np.max(self.particle_pressure.to_numpy()[:total_num]) dt_a = ((0.2 * self.dh) / (self.c_0 * np.sqrt(((self.max_rho / self.rho_0) ** self.gamma)))) if (self.adaptive_time_step and (self.method == SPHSolver.method_WCSPH)): self.dt[None] = np.min([dt_cfl, dt_f, dt_a]) if (self.adaptive_time_step and (self.method == SPHSolver.method_PCISPH)): self.dt[None] = np.min([dt_cfl, dt_f]) def step(self, frame, t, total_start): curr_start = time.process_time() self.grid_num_particles.fill(0) self.particle_neighbors.fill((- 1)) self.allocate_particles() self.search_neighbors() if (self.method == SPHSolver.methods['WCSPH']): self.wc_compute_deltas() self.wc_update_time_step() elif (self.method == SPHSolver.methods['PCISPH']): self.pci_compute_deltas() self.pci_scaling_factor() self.it = 0 self.max_it = 0 while ((self.max_rho_err[None][0] >= (0.01 * self.rho_0)) or (self.it < self.sub_max_iteration)): self.pci_pc_iteration() self.it += 1 self.max_it += 1 self.max_it = max(self.it, self.max_it) if (self.it > 1000): print(('Warning: PCISPH density does not converge, iterated %d steps' % self.it)) break self.pci_update_time_step() elif (self.method == SPHSolver.methods['DFSPH']): self.df_compute_density_alpha() self.it = 0 self.sum_drho[None] = 0.0 while ((self.sum_drho[None] >= ((0.01 * self.particle_num[None]) * self.rho_0)) or (self.it < 1)): self.sum_drho[None] = 0.0 self.df_correct_divergence_compute_drho() self.df_correct_divergence_adapt_vel() self.it += 1 if (self.it > 1000): print(('Warning: DFSPH divergence does not converge, iterated %d steps' % self.it)) break self.df_update_velocities() self.df_compute_deltas() self.adaptive_step() self.df_predict_velocities() self.it = 0 self.sum_rho_err[None] = 0.0 while ((self.sum_rho_err[None] >= ((0.01 * self.particle_num[None]) * self.rho_0)) or (self.it < 2)): self.sum_rho_err[None] = 0.0 self.df_correct_density_predict() self.df_correct_density_adapt_vel() self.it += 1 if (self.it > 1000): print(('Warning: DFSPH density does not converge, iterated %d steps' % self.it)) break self.df_update_positions() self.enforce_boundary() if (self.method != SPHSolver.methods['DFSPH']): self.adaptive_step() curr_end = time.process_time() if ((frame % 10) == 0): self.sim_info_realtime(frame, t, curr_start, curr_end, total_start) return self.dt[None] def fill_particle(self, i, x, material, color, velocity, pressure, density): self.particle_positions[i] = x self.particle_positions_new[i] = x self.particle_velocity[i] = velocity self.particle_velocity_new[i] = velocity self.d_velocity[i] = ti.Vector([0.0 for _ in range(self.dim)]) self.particle_pressure[i] = pressure self.particle_pressure_acc[i] = ti.Vector([0.0 for _ in range(self.dim)]) self.particle_density[i] = density self.particle_density_new[i] = density self.d_density[i][0] = 0.0 self.particle_alpha[i][0] = 0.0 self.particle_stiff[i][0] = 0.0 self.color[i] = color self.material[i] = material def fill(self, new_particles: ti.i32, new_positions: ti.types.ndarray(), new_material: ti.i32, color: ti.i32): for i in range(self.particle_num[None], (self.particle_num[None] + new_particles)): self.material[i] = new_material x = ti.Vector.zero(ti.f32, self.dim) for k in ti.static(range(self.dim)): x[k] = new_positions[(k, (i - self.particle_num[None]))] self.fill_particle(i, x, new_material, color, self.source_velocity[None], self.source_pressure[None], self.source_density[None]) def set_source_velocity(self, velocity): if (velocity is not None): velocity = list(velocity) assert (len(velocity) == self.dim) self.source_velocity[None] = velocity else: for i in range(self.dim): self.source_velocity[None][i] = 0 def set_source_pressure(self, pressure): if (pressure is not None): self.source_pressure[None] = pressure else: self.source_pressure[None][0] = 0.0 def set_source_density(self, density): if (density is not None): self.source_density[None] = density else: self.source_density[None][0] = 0.0 def add_cube(self, lower_corner, cube_size, material, color=, density=None, pressure=None, velocity=None): num_dim = [] for i in range(self.dim): num_dim.append(np.arange(lower_corner[i], (lower_corner[i] + cube_size[i]), self.dx)) num_new_particles = reduce((lambda x, y: (x * y)), [len(n) for n in num_dim]) assert ((self.particle_num[None] + num_new_particles) <= self.max_num_particles) new_positions = np.array(np.meshgrid(*num_dim, sparse=False, indexing='ij'), dtype=np.float32) new_positions = new_positions.reshape((- 1), reduce((lambda x, y: (x * y)), list(new_positions.shape[1:]))) print(new_positions.shape) for i in range(self.dim): self.source_bound[0][i] = lower_corner[i] self.source_bound[1][i] = cube_size[i] self.set_source_velocity(velocity=velocity) self.set_source_pressure(pressure=pressure) self.set_source_density(density=density) self.fill(num_new_particles, new_positions, material, color) self.particle_num[None] += num_new_particles def copy_dynamic_nd(self, np_x: ti.types.ndarray(), input_x: ti.template()): for i in range(self.particle_num[None]): for j in ti.static(range(self.dim)): np_x[(i, j)] = input_x[i][j] def copy_dynamic(self, np_x: ti.types.ndarray(), input_x: ti.template()): for i in range(self.particle_num[None]): np_x[i] = input_x[i] def particle_info(self): np_x = np.ndarray((self.particle_num[None], self.dim), dtype=np.float32) self.copy_dynamic_nd(np_x, self.particle_positions) np_v = np.ndarray((self.particle_num[None], self.dim), dtype=np.float32) self.copy_dynamic_nd(np_v, self.particle_velocity) np_material = np.ndarray((self.particle_num[None],), dtype=np.int32) self.copy_dynamic(np_material, self.material) np_color = np.ndarray((self.particle_num[None],), dtype=np.int32) self.copy_dynamic(np_color, self.color) return {'position': np_x, 'velocity': np_v, 'material': np_material, 'color': np_color}
class VPNApplicationBuilder(Builder): VPNs = {'express_vpn': {'macos': {'app': '/Applications/ExpressVPN.app'}, 'windows': {'app': windows_safe_path('C:\\Program Files (x86)\\ExpressVPN\\xvpn-ui\\ExpressVpn.exe'), 'tap': 'ExpressVPN Tap Adapter'}, 'linux': {'app': '/usr/bin/expressvpn'}}} def name(): return 'vpn_application' def build(self, device, config): return GenericVPNBuilder(VPNApplicationBuilder.VPNs).build(device, config)
class OptionPlotoptionsSankeyLabelStyle(Options): def fontSize(self): return self._config_get('0.8em') def fontSize(self, num: float): self._config(num, js_type=False) def fontWeight(self): return self._config_get('bold') def fontWeight(self, text: str): self._config(text, js_type=False)
def extractTrackingFeedpressIt(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
class ExampleAutoSchemaDuplicate2(generics.GenericAPIView): serializer_class = ExampleSerializerModel schema = AutoSchema(component_name='Duplicate') def get(self, *args, **kwargs): from datetime import datetime now = datetime.now() serializer = self.get_serializer(data=now.date(), datetime=now) return Response(serializer.data)
class TestMacOSPacketCaptureConnectWhenNoNetwork(LocalPacketCaptureTestCase): def __init__(self, devices, config): super().__init__(devices, config) self.original_active_services = None def test(self): services = self.localhost['network_tool'].network_services_in_priority_order() interfaces = [service.interface() for service in services if service.active()] self.original_active_services = [service for service in services if service.active()] primary_service = self.original_active_services[0] L.describe('Disable all active services') for service in self.original_active_services: service.disable() L.describe('Open and connect the VPN application') self.localhost['vpn_application'].open_and_connect() L.describe('Capture traffic') self.localhost['packet_capturer'].start(interfaces) L.describe('Wait for the VPN application to notice the interruption') self.localhost['vpn_application'].wait_for_connection_interrupt_detection() L.describe('Enable primary network service') primary_service.enable() L.info('Enabled {}'.format(primary_service)) L.describe('Reconnect the VPN') self.localhost['vpn_application'].connect() L.describe('Determine the VPN server IP') vpn_server_ip = self.localhost['vpn_application'].vpn_server_ip() L.info('VPN server IP is {}'.format(vpn_server_ip)) L.describe('Stop capturing traffic') self.localhost['packet_capturer'].stop() L.describe('Analyse packets to ensure we saw no traffic leaking') packets = self.localhost['packet_capturer'].get_capture(interfaces) unmatched = self.traffic_filter.filter_traffic(packets, local=True)[1] unmatched = self.traffic_filter.filter_traffic(unmatched, link_local=True)[1] unmatched = self.traffic_filter.filter_traffic(unmatched, multicast=True)[1] unmatched = self.traffic_filter.filter_traffic(unmatched, dst_ip=True)[1] self.assertEmpty(unmatched, json.dumps(unmatched, indent=2)) def teardown(self): for service in self.original_active_services: if (not service.enabled()): service.enable() super().teardown()
def test_setup_argparser(): log_file_path = 'any/given/path' args = setup_argparser('test', 'test description', command_line_options=['script_name', '--log_file', log_file_path, 'ANY_FILE']) assert (args.debug is False) assert (args.log_file == log_file_path) assert (args.log_level is None)
def setup_windows_console(): if ((not sys.platform.startswith('win')) or ('MSYSTEM' in os.environ) or ('CYGWIN' in os.environ)): return force_console = (('-v' in sys.argv) or ('--verbose' in sys.argv)) if ((not _create_or_attach_console(create=force_console, title='ElectrumSV Console')) and force_console): MB_ICONERROR = 16 MB_OK = 0 ctypes.windll.user32.MessageBoxW(0, 'Failed to get a console', 'ElectronSV', (MB_OK | MB_ICONERROR)) sys.exit(1)
class CyclopolisStation(BikeShareStation): def __init__(self, name, latitude, longitude, bikes, free, extra): super(CyclopolisStation, self).__init__() self.name = name self.latitude = latitude self.longitude = longitude self.bikes = bikes self.free = free self.extra = extra
def get_class(path: str) -> type: try: cls = _locate(path) if (not isinstance(cls, type)): raise ValueError((f"Located non-class of type '{type(cls).__name__}'" + f" while loading '{path}'")) return cls except Exception as e: log.error(f'Error getting class at {path}: {e}') raise e
def test_transformer_on_integer_variables(): df = pd.DataFrame({'var1': [0, 1, 0, 2, 3, 4, 5, 6, 8, 10], 'var2': [12, 11, 10, 15, 13, 12, 11, 10, 10, 20]}) dft = pd.DataFrame({'var1': {0: 0.0, 1: 0., 2: 0.0, 3: 1., 4: 1., 5: 2., 6: 2., 7: 2., 8: 3., 9: 3.}, 'var2': {0: 0., 1: 0., 2: 0., 3: 0., 4: 0., 5: 0., 6: 0., 7: 0., 8: 0., 9: 0.}}) X_tr = YeoJohnsonTransformer().fit_transform(df) pd.testing.assert_frame_equal(X_tr, dft)
def serialize(A): if isinstance(A, str): return (0, A) if isinstance(A, numpy.ndarray): dt = A.dtype if ((not dt.isnative) or (dt.num < 1) or (dt.num >= len(dataType))): return (DATATYPE_UNKNOWN, None) ft = dataType[dt.num] if (ft == (- 1)): return (DATATYPE_UNKNOWN, None) if A.flags['C_CONTIGUOUS']: return (ft, A.tostring()) AC = A.copy('C') return (ft, AC.tostring()) if isinstance(A, int): return (DATATYPE_INT32, struct.pack('i', A)) if isinstance(A, float): return (DATATYPE_FLOAT64, struct.pack('d', A)) return (DATATYPE_UNKNOWN, None)
class DiscountCode(SoftDeletionModel): __tablename__ = 'discount_codes' __table_args__ = (UniqueConstraint('event_id', 'code', 'deleted_at', name='uq_event_discount_code'),) id = db.Column(db.Integer, primary_key=True) code = db.Column(CIText, nullable=False) discount_url = db.Column(db.String) value = db.Column(db.Float, nullable=False) type = db.Column(db.String, nullable=False) is_active = db.Column(db.Boolean, default=True) tickets_number = db.Column(db.Integer) min_quantity = db.Column(db.Integer, default=1) max_quantity = db.Column(db.Integer, default=100) valid_from = db.Column(db.DateTime(timezone=True), nullable=True) valid_till = db.Column(db.DateTime(timezone=True), nullable=True) event_id = db.Column(db.Integer, db.ForeignKey('events.id', ondelete='CASCADE')) event = db.relationship('Event', backref='discount_codes', foreign_keys=[event_id]) created_at = db.Column(db.DateTime(timezone=True), default=func.now()) marketer_id = db.Column(db.Integer, db.ForeignKey('users.id', ondelete='CASCADE')) marketer = db.relationship('User', backref='discount_codes_') used_for = db.Column(db.String, nullable=False) def get_service_name() -> str: return 'discount_code' def __repr__(self) -> str: return ('<DiscountCode %r>' % self.id) def get_confirmed_attendees_query(self): return TicketHolder.query.filter_by(deleted_at=None).filter_by(is_discount_applied=True).join(Order).filter_by(discount_code_id=self.id).filter(Order.status.in_(['completed', 'placed', 'pending', 'initializing'])) def confirmed_attendees(self): return self.get_confirmed_attendees_query().all() def confirmed_attendees_count(self) -> int: return get_count(self.get_confirmed_attendees_query()) def valid_expire_time(self): return (self.valid_till or self.event.ends_at) def get_supported_tickets(self, ticket_ids=None): query = Ticket.query.with_parent(self).filter_by(deleted_at=None) if ticket_ids: query = query.filter(Ticket.id.in_(ticket_ids)) return query def is_available(self, tickets=None, ticket_holders=None): return is_discount_available(self, tickets=tickets, ticket_holders=ticket_holders) def validate(self, tickets=None, ticket_holders=None, event_id=None): return validate_discount_code(self, tickets=tickets, ticket_holders=ticket_holders, event_id=event_id)
def main(): segmk = Segmaker('design.bits') fuz_dir = os.getenv('FUZDIR', None) assert fuz_dir with open(os.path.join(fuz_dir, 'attrs.json'), 'r') as attr_file: attrs = json.load(attr_file) print('Loading tags') with open('params.json') as f: params = json.load(f) site = params['site'] for (param, param_info) in attrs.items(): value = params[param] param_type = param_info['type'] param_digits = param_info['digits'] param_values = param_info['values'] if (param_type == BIN): bitstr = [int(x) for x in '{value:0{digits}b}'.format(value=value, digits=param_digits)[::(- 1)]] for i in range(param_digits): segmk.add_site_tag(site, ('%s[%u]' % (param, i)), bitstr[i]) else: assert (param_type == BOOL) segmk.add_site_tag(site, param, (value == 'TRUE')) segmk.compile(bitfilter=bitfilter) segmk.write()
def fortios_firewall_schedule(data, fos, check_mode): fos.do_member_operation('firewall.schedule', 'recurring') if data['firewall_schedule_recurring']: resp = firewall_schedule_recurring(data, fos, check_mode) else: fos._module.fail_json(msg=('missing task body: %s' % 'firewall_schedule_recurring')) if check_mode: return resp return ((not is_successful_status(resp)), (is_successful_status(resp) and (resp['revision_changed'] if ('revision_changed' in resp) else True)), resp, {})
def test_rule_get_storage_destination_local(db: Session, policy: Policy, storage_config: StorageConfig, storage_config_default_local: StorageConfig) -> None: rule: Rule = policy.rules[0] rule_storage_config = rule.get_storage_destination(db) assert (rule_storage_config == storage_config) rule.storage_destination = None rule_storage_config = rule.get_storage_destination(db) assert (rule_storage_config == storage_config_default_local) rule.storage_destination = storage_config rule_storage_config = rule.get_storage_destination(db) assert (rule_storage_config == storage_config)
class SSHCommandSessionTest(AsyncTestCase): def setUp(self) -> None: super().setUp() self.mock_options = {} self.mocks = MockService(self.mock_options, self._loop) test_device = self.mock_device('test-dev-1') self.devinfo = self._run_loop(self.mocks.device_db.get(test_device))[0] self._mock_asyncssh = patch('fbnet.command_runner.command_session.asyncssh').start() self.options = {'client_ip': '10.10.10.10', 'client_port': 1010, 'open_timeout': 10} def tearDown(self) -> None: self.mocks.tearDown() super().tearDown() def mock_session(self, service: MockService, devinfo: 'DeviceInfo', options: typing.Dict[(str, typing.Any)], loop: 'FcrTestEventLoop') -> SSHCommandSession: session = SSHCommandSession(service=service, devinfo=devinfo, options=options, loop=loop) session._stream_reader = AsyncMock(spec=CommandStreamReader) session._stream_writer = Mock(spec=asyncio.StreamWriter) session._captured_time_ms = Mock(wraps=session.captured_time_ms) mock_response = b'run_command response' session.run_command = AsyncMock(return_value=mock_response) return session def mock_device(self, name: str, console: typing.Optional[str]=None, command_prompts: typing.Optional[typing.Dict[(str, str)]]=None) -> Mock: return Mock(hostname=name, console=console, command_prompts=command_prompts, pre_setup_commands=[], clear_command=None) _test async def test_external_communication_time_reset(self) -> None: session = self.mock_session(service=self.mocks, devinfo=self.devinfo, options=self.options, loop=self._loop) session._conn = AsyncMock(spec_set=session._conn) self._mock_asyncssh.create_connection = AsyncMock(spec_set=self._mock_asyncssh.create_connection, return_value=(Mock(), Mock())) session._conn.create_session = AsyncMock(spec_set=session._conn.create_session, return_value=(Mock(), Mock())) self.assertFalse(session._connected) session._connected = True (await session.connect()) (await session.wait_until_connected(10)) self.assertTrue(session._connected) self.assertEqual(session.captured_time_ms.increment_external_communication_time_ms.call_count, 1) session._stream_reader.reset_mock() session.captured_time_ms.reset_mock() (await session._setup_connection()) self.assertEqual(session.captured_time_ms.increment_external_communication_time_ms.call_count, session._stream_reader.feed_data.call_count) session.captured_time_ms.reset_time() session._stream_reader.reset_mock() session.captured_time_ms.reset_mock() res = (await session.run_command(b'test1\n')) self.assertEqual(res, b'run_command response') self.assertEqual(session.captured_time_ms.increment_external_communication_time_ms.call_count, session._stream_reader.feed_data.call_count) _test async def test_external_communication_time_no_reset(self) -> None: session = self.mock_session(service=self.mocks, devinfo=self.devinfo, options=self.options, loop=self._loop) session._conn = AsyncMock(spec_set=session._conn) self._mock_asyncssh.create_connection = AsyncMock(spec_set=self._mock_asyncssh.create_connection, return_value=(Mock(), Mock())) session._conn.create_session = AsyncMock(spec_set=session._conn.create_session, return_value=(Mock(), Mock())) self.assertFalse(session._connected) session._connected = True (await session.connect()) (await session.wait_until_connected()) self.assertTrue(session._connected) self.assertEqual(session.captured_time_ms.increment_external_communication_time_ms.call_count, 1) session._stream_reader.reset_mock() (await session._setup_connection()) res = (await session.run_command(b'test1\n')) self.assertEqual(res, b'run_command response') self.assertEqual(session.captured_time_ms.increment_external_communication_time_ms.call_count, (session._stream_reader.feed_data.call_count + 1))
.parametrize('ops', ALL_OPS) .parametrize('dtype', FLOAT_TYPES) def test_reduce_first(ops, dtype): X = ops.asarray2f([[1.0, 6.0], [2.0, 7.0], [3.0, 8.0], [4.0, 9.0], [5.0, 10.0]], dtype=dtype) lengths = ops.asarray1i([3, 2]) (Y, starts_ends) = ops.reduce_first(X, lengths) ops.xp.testing.assert_array_equal(starts_ends, ops.asarray1i([0, 3, 5])) ops.xp.testing.assert_allclose(Y, [[1.0, 6.0], [4.0, 9.0]]) lengths = ops.asarray1i([3, 0, 2]) with pytest.raises(ValueError, match='all sequence lengths must be > 0'): ops.reduce_last(X, lengths) lengths = ops.asarray1i([3, 2, 1]) with pytest.raises(IndexError, match='lengths must sum up to the number of rows'): ops.reduce_last(X, lengths)
def create_post(board: BoardModel, thread: ThreadModel, post: PostModel, sage: bool) -> Tuple[(PostResultModel, int, int)]: start_time = now() with session() as s: post_orm_model = post.to_orm_model() s.add(post_orm_model) to_thread_orm_model = s.query(ThreadOrmModel).filter_by(id=thread.id).one() post_orm_model.thread = to_thread_orm_model post_orm_model.refno = 0 to_thread_orm_model.refno_counter = (ThreadOrmModel.refno_counter + 1) s.commit() post_refno = post_orm_model.refno = to_thread_orm_model.refno_counter post_id = post_orm_model.id if post.files: for file in post.files: file_orm_model = file.to_orm_model() file_orm_model.post_id = post_id s.add(file_orm_model) if post.moderator: post_orm_model.moderator_id = post.moderator.id modify_date = now() if ((not sage) and (post_refno <= board.config.bump_limit)): to_thread_orm_model.last_modified = modify_date s.commit() insert_time = (now() - start_time) start_time = now() _invalidate_thread_cache(s, thread, board) _invalidate_board_pages_catalog_cache(s, board) document_cache.purge_thread(board, thread, True) document_cache.purge_board(board) cache_time = (now() - start_time) res = PostResultModel.from_board_name_thread_refno_post_refno(board.name, thread.refno, post_refno) return (res, insert_time, cache_time)
def commit_changes(changes: t.List[str]) -> CommittedChanges: log.info('Committing updates') body: t.Optional[str] if (len(changes) > 1): subject = 'Update {} modules'.format(len(changes)) body = '\n'.join(changes) message = ((subject + '\n\n') + body) else: subject = changes[0] body = None message = subject base_branch: t.Optional[str] base_branch = subprocess.check_output(['git', 'branch', '--show-current'], text=True).strip() if (not base_branch): base_branch = None check_call(['git', 'checkout', '{0}']) check_call(['git', 'commit', '-am', message]) tree = subprocess.check_output(['git', 'rev-parse', 'HEAD^{tree}'], text=True).strip() branch = f'update-{tree[:7]}' try: subprocess.run(['git', 'rev-parse', '--verify', branch], capture_output=True, check=True) except subprocess.CalledProcessError: check_call(['git', 'checkout', '-b', branch]) return CommittedChanges(subject=subject, body=body, commit=tree, branch=branch, base_branch=base_branch)
_blueprint.route('/api/packages/wiki/') _blueprint.route('/api/packages/wiki') def api_packages_wiki_list(): project_objs = models.Project.all(Session) projects = [] for project in project_objs: for package in project.packages: tmp = f'* {package.package_name} {project.regex} {project.version_url}' projects.append(tmp) return flask.Response('\n'.join(projects), content_type='text/plain;charset=UTF-8')
class OptionPlotoptionsBulletStatesSelect(Options): def animation(self) -> 'OptionPlotoptionsBulletStatesSelectAnimation': return self._config_sub_data('animation', OptionPlotoptionsBulletStatesSelectAnimation) def borderColor(self): return self._config_get('#000000') def borderColor(self, text: str): self._config(text, js_type=False) def color(self): return self._config_get('#cccccc') def color(self, text: str): self._config(text, js_type=False) def enabled(self): return self._config_get(True) def enabled(self, flag: bool): self._config(flag, js_type=False)
def update(proj_dir): check_exists_with_error() if (not has_local_changes(proj_dir)): subprocess.call('git pull', cwd=proj_dir, shell=True) update_submodule(proj_dir) return True else: log.warn('skipping {}, uncommitted or unpushed changes!'.format(proj_dir)) return False
class OptionPlotoptionsAreasplinerangeSonificationDefaultinstrumentoptionsMappingFrequency(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class FFmpegBackend(BaseEncodingBackend): name = 'FFmpeg' def __init__(self) -> None: self.params: List[str] = ['-threads', str(settings.VIDEO_ENCODING_THREADS), '-y', '-strict', '-2'] self.ffmpeg_path: str = getattr(settings, 'VIDEO_ENCODING_FFMPEG_PATH', which('ffmpeg')) self.ffprobe_path: str = getattr(settings, 'VIDEO_ENCODING_FFPROBE_PATH', which('ffprobe')) if (not self.ffmpeg_path): raise exceptions.FFmpegError('ffmpeg binary not found: {}'.format((self.ffmpeg_path or ''))) if (not self.ffprobe_path): raise exceptions.FFmpegError('ffprobe binary not found: {}'.format((self.ffmpeg_path or ''))) def check(cls) -> List[checks.Error]: errors = super(FFmpegBackend, cls).check() try: FFmpegBackend() except exceptions.FFmpegError as e: errors.append(checks.Error(e.msg, hint='Please install ffmpeg.', obj=cls, id='video_conversion.E001')) return errors def _spawn(self, cmd: List[str]) -> subprocess.Popen: try: return subprocess.Popen(cmd, shell=False, stderr=subprocess.PIPE, universal_newlines=False) except OSError as e: raise exceptions.FFmpegError('Error while running ffmpeg binary') from e def encode(self, source_path: str, target_path: str, params: List[str]) -> Generator[(float, None, None)]: total_time = self.get_media_info(source_path)['duration'] cmd = [self.ffmpeg_path, '-i', source_path, *self.params, *params, target_path] process = self._spawn(cmd) reader = io.TextIOWrapper(process.stderr, newline=None) while (process.poll() is None): line = reader.readline() try: time_str = RE_TIMECODE.findall(line)[0] except IndexError: continue time: float = 0 for part in time_str.split(':'): time = ((60 * time) + float(part)) percent = round((time / total_time), 2) logger.debug('yield {}%'.format(percent)) (yield percent) if (os.path.getsize(target_path) == 0): raise exceptions.FFmpegError('File size of generated file is 0') if (process.returncode != 0): raise exceptions.FFmpegError('`{}` exited with code {:d}'.format(' '.join(map(str, process.args)), process.returncode)) (yield 100) def _parse_media_info(self, data: bytes) -> Dict: media_info = json.loads(data) media_info['video'] = [stream for stream in media_info['streams'] if (stream['codec_type'] == 'video')] media_info['audio'] = [stream for stream in media_info['streams'] if (stream['codec_type'] == 'audio')] media_info['subtitle'] = [stream for stream in media_info['streams'] if (stream['codec_type'] == 'subtitle')] del media_info['streams'] return media_info def get_media_info(self, video_path: str) -> Dict[(str, Union[(int, float)])]: cmd = [self.ffprobe_path, '-i', video_path] cmd.extend(['-hide_banner', '-loglevel', 'warning']) cmd.extend(['-print_format', 'json']) cmd.extend(['-show_format', '-show_streams']) stdout = subprocess.check_output(cmd) media_info = self._parse_media_info(stdout) return {'duration': float(media_info['format']['duration']), 'width': int(media_info['video'][0]['width']), 'height': int(media_info['video'][0]['height'])} def get_thumbnail(self, video_path: str, at_time: float=0.5) -> str: filename = os.path.basename(video_path) (filename, __) = os.path.splitext(filename) (_, image_path) = tempfile.mkstemp(suffix='_{}.jpg'.format(filename)) video_duration = self.get_media_info(video_path)['duration'] if (at_time > video_duration): raise exceptions.InvalidTimeError() thumbnail_time = at_time cmd = [self.ffmpeg_path, '-i', video_path, '-vframes', '1'] cmd.extend(['-ss', str(thumbnail_time), '-y', image_path]) subprocess.check_call(cmd) if (not os.path.getsize(image_path)): os.unlink(image_path) raise exceptions.InvalidTimeError() return image_path
.parametrize('file_name, max_context', [('gsub_51', 2), ('gsub_52', 2), ('gsub_71', 1), ('gpos_91', 1)]) def test_max_ctx_calc_features_ttx(file_name, max_context): ttx_path = os.path.join(os.path.dirname(__file__), 'data', '{}.ttx'.format(file_name)) font = TTFont() font.importXML(ttx_path) assert (maxCtxFont(font) == max_context)
class OptionPlotoptionsVariwideSonificationDefaultinstrumentoptionsMappingTime(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
(frozen=True) class ProductionChildInfo(): child_name: str production_name: str symbol: type symbol_optional: bool arity: ProductionChildArity annotation: Any def validate_child(self, child): def error(msg): raise GrammarError(msg) if (child is None): if (not self.is_node_optional): error(f"Expected child '{child}' in node of type '{self.production_name}'.Consider using the 'Optional[T]' type annotation.") else: is_sequence = isinstance(child, (list, tuple, Sequence)) if (is_sequence and (not self.is_list)): error(f"Unexpected sequence-like field '{self.child_name}' in node of type '{self.production_name}'.Consider using the 'Sequence[T]' type annotation.") if ((not is_sequence) and self.is_list): error(f"Expected sequence-like field '{self.child_name}' but got single node value in node of type '{self.production_name}'.") for e in (child if is_sequence else [child]): possible_types = {self.symbol} possible_types |= ({type(None)} if self.symbol_optional else set()) child_type_name = type(e).__name__ child_type_names = [c.__name__ for c in possible_types] types_invalid = [(not isinstance(e, c)) for c in possible_types] if all(types_invalid): error(f"Expected child of type in {child_type_names} but got '{child_type_name}' in node of type '{self.production_name}'.") if ((e is not None) and Production.is_abstract(type(e))): error(f'Found instance of abstract production {type(e).__name__}.') def is_list(self): return (self.arity in {ProductionChildArity.LIST, ProductionChildArity.LIST_OPTIONAL}) def is_node_optional(self): return ((self.arity is ProductionChildArity.LIST_OPTIONAL) or self.symbol_optional) def to_string(self): result = self.symbol.__name__ result = (f'{result}?' if self.symbol_optional else result) result = (f'({result})*' if (self.arity is ProductionChildArity.LIST) else result) result = (f'(({result})*)?' if (self.arity is ProductionChildArity.LIST_OPTIONAL) else result) return result def __str__(self) -> str: return ('[RuleOutput: %s]' % self.to_string()) def from_type_hint(type_hint, production_name, child_name): symbol = None modifiers = [] type_hint_element = type_hint while (symbol is None): if isinstance(type_hint_element, _GenericAlias): type_params = type_hint_element.__args__ annotation_type = type_hint_element.__origin__ if (annotation_type in [Sequence, list, tuple]): modifiers.append('list') type_hint_element = type_params[0] elif (annotation_type is Union): if (not ((len(type_params) == 2) and (type(None) in type_params))): return None modifiers.append('opt') (type_hint_element, *_) = {t for t in type_params if (t is not type(None))} else: return None elif Production.is_production(type_hint_element): symbol = type_hint_element else: return None def constructor(*args): return ProductionChildInfo(child_name, production_name, symbol, *args) if (not modifiers): info = constructor(False, ProductionChildArity.SINGLE, type_hint) elif (modifiers == ['opt']): info = constructor(True, ProductionChildArity.SINGLE, type_hint) elif (modifiers == ['list']): info = constructor(False, ProductionChildArity.LIST, type_hint) elif (modifiers == ['list', 'opt']): info = constructor(True, ProductionChildArity.LIST, type_hint) elif (modifiers == ['opt', 'list']): info = constructor(False, ProductionChildArity.LIST_OPTIONAL, type_hint) elif (modifiers == ['opt', 'list', 'opt']): info = constructor(True, ProductionChildArity.LIST_OPTIONAL, type_hint) else: raise RuntimeError() return info
def gen_dsps(): db = Database(util.get_db_root(), util.get_part()) grid = db.grid() for tile_name in sorted(grid.tiles()): loc = grid.loc_of_tilename(tile_name) gridinfo = grid.gridinfo_at_loc(loc) sites = [] for (site_name, site_type) in gridinfo.sites.items(): if (site_type in ['DSP48E1']): sites.append(site_name) sites.sort() if (len(sites) == 0): continue if (gridinfo.tile_type[(- 1)] == 'L'): int_grid_x = (loc.grid_x + 2) int_tile_type = 'INT_L' else: int_grid_x = (loc.grid_x - 2) int_tile_type = 'INT_R' int_tile_locs = [(int_grid_x, loc.grid_y), (int_grid_x, (loc.grid_y - 1)), (int_grid_x, (loc.grid_y - 2)), (int_grid_x, (loc.grid_y - 3)), (int_grid_x, (loc.grid_y - 4))] int_tiles = [] for int_tile_loc in int_tile_locs: int_gridinfo = grid.gridinfo_at_loc(int_tile_loc) assert (int_gridinfo.tile_type == int_tile_type), (int_gridinfo.tile_type, int_tile_type) int_tiles.append(grid.tilename_at_loc(int_tile_loc)) (yield (tile_name, sites, int_tiles))
class _PaletteTool(HasTraits): group = Any() def __init__(self, tool_palette, image_cache, item, show_labels): self.item = item self.tool_palette = tool_palette action = self.item.action label = action.name if (action.style == 'widget'): raise NotImplementedError('WxPython does not support widgets in palettes') if label.endswith('...'): label = label[:(- 3)] label = label.replace('&', '') path = action.image.absolute_path bmp = image_cache.get_bitmap(path) kind = action.style tooltip = action.tooltip longtip = action.description if (not show_labels): label = '' self.tool_id = tool_palette.add_tool(label, bmp, kind, tooltip, longtip) tool_palette.toggle_tool(self.tool_id, action.checked) tool_palette.enable_tool(self.tool_id, action.enabled) tool_palette.on_tool_event(self.tool_id, self._on_tool) action.observe(self._on_action_enabled_changed, 'enabled') action.observe(self._on_action_checked_changed, 'checked') return def dispose(self): action = self.item.action action.observe(self._on_action_enabled_changed, 'enabled', remove=True) action.observe(self._on_action_checked_changed, 'checked', remove=True) def _on_action_enabled_changed(self, event): action = event.object self.tool_palette.enable_tool(self.tool_id, action.enabled) def _on_action_checked_changed(self, event): action = event.object if (action.style == 'radio'): if event.new: for item in self.item.parent.items: if (item is not self.item): item.action.checked = False self.tool_palette.toggle_tool(self.tool_id, event.new) return def _on_tool(self, event): action = self.item.action action_event = ActionEvent() action.checked = (self.tool_palette.get_tool_state(self.tool_id) == 1) action.perform(action_event) return
def _iter_avro_records(decoder, header, codec, writer_schema, named_schemas, reader_schema, options): sync_marker = header['sync'] read_block = BLOCK_READERS.get(codec) if (not read_block): raise ValueError(f'Unrecognized codec: {codec}') block_count = 0 while True: try: block_count = decoder.read_long() except EOFError: return block_fo = read_block(decoder) for i in range(block_count): (yield read_data(BinaryDecoder(block_fo), writer_schema, named_schemas, reader_schema, options)) skip_sync(decoder.fo, sync_marker)
class Trainer(): def __init__(self, model: Union[(PreTrainedModel, nn.Module)]=None, args: TrainingArguments=None, train_dataset: Dataset=None, eval_dataset: Optional[Dataset]=None): if (args is None): output_dir = 'tmp_trainer' logger.info(f'No `TrainingArguments` passed, using `output_dir={output_dir}`.') args = TrainingArguments(output_dir=output_dir) self.args = args set_seed(self.args.seed) if (model is None): raise RuntimeError('`Trainer` requires a `model`') if torch.cuda.is_available(): self.model = model.cuda() else: self.model = model self.train_dataset = train_dataset self.eval_dataset = eval_dataset self.best_epoch = 0 self.best_metric = 0.0 def train(self, resume_from_checkpoint: Optional[Union[(str, bool)]]=None, **kwargs): args = self.args epochs_trained = 0 device = args.device num_train_epochs = args.num_train_epochs learning_rate = args.learning_rate train_batch_size = args.train_batch_size train_dataset = self.train_dataset train_dataloader = self.get_train_dataloader() step_size = int(((len(train_dataset) / train_batch_size) * 200)) if (args.n_gpu > 1): self.model = nn.DataParallel(self.model) optimizer = Adam(self.model.parameters(), lr=learning_rate) scheduler = lr_scheduler.StepLR(optimizer, step_size=step_size, gamma=self.args.gamma) for epoch in range(epochs_trained, num_train_epochs): for param_group in optimizer.param_groups: param_group['lr'] = (learning_rate * (0.1 ** (epoch // int((num_train_epochs * 0.8))))) self.model.train() epoch_losses = AverageMeter() with tqdm(total=(len(train_dataset) - (len(train_dataset) % train_batch_size))) as t: t.set_description(f'epoch: {epoch}/{(num_train_epochs - 1)}') for data in train_dataloader: (inputs, labels) = data inputs = inputs.to(device) labels = labels.to(device) preds = self.model(inputs) criterion = nn.L1Loss() loss = criterion(preds, labels) epoch_losses.update(loss.item(), len(inputs)) optimizer.zero_grad() loss.backward() optimizer.step() scheduler.step() t.set_postfix(loss=f'{epoch_losses.avg:.6f}') t.update(len(inputs)) self.eval(epoch) def eval(self, epoch): args = self.args if isinstance(self.model, nn.DataParallel): scale = self.model.module.config.scale else: scale = self.model.config.scale device = args.device eval_dataloader = self.get_eval_dataloader() epoch_psnr = AverageMeter() epoch_ssim = AverageMeter() self.model.eval() for data in eval_dataloader: (inputs, labels) = data inputs = inputs.to(device) labels = labels.to(device) with torch.no_grad(): preds = self.model(inputs) metrics = compute_metrics(EvalPrediction(predictions=preds, labels=labels), scale=scale) epoch_psnr.update(metrics['psnr'], len(inputs)) epoch_ssim.update(metrics['ssim'], len(inputs)) print(f'scale:{str(scale)} eval psnr: {epoch_psnr.avg:.2f} ssim: {epoch_ssim.avg:.4f}') if (epoch_psnr.avg > self.best_metric): self.best_epoch = epoch self.best_metric = epoch_psnr.avg print(f'best epoch: {epoch}, psnr: {epoch_psnr.avg:.6f}, ssim: {epoch_ssim.avg:.6f}') self.save_model() def _load_state_dict_in_model(self, state_dict): load_result = self.model.load_state_dict(state_dict, strict=False) def _save_checkpoint(self, model, trial, metrics=None): checkpoint_folder = f'{PREFIX_CHECKPOINT_DIR}-{self.state.global_step}' run_dir = self.args.output_dir output_dir = os.path.join(run_dir, checkpoint_folder) self.save_model(output_dir) def save_model(self, output_dir: Optional[str]=None): output_dir = (output_dir if (output_dir is not None) else self.args.output_dir) os.makedirs(output_dir, exist_ok=True) if (not isinstance(self.model, PreTrainedModel)): scale = self.model.config.scale if (scale is not None): weights_name = WEIGHTS_NAME_SCALE.format(scale=scale) else: weights_name = WEIGHTS_NAME weights = copy.deepcopy(self.model.state_dict()) torch.save(weights, os.path.join(output_dir, weights_name)) else: self.model.save_pretrained(output_dir) def get_train_dataloader(self) -> DataLoader: if (self.train_dataset is None): raise ValueError('Trainer: training requires a train_dataset.') train_dataset = self.train_dataset return DataLoader(dataset=train_dataset, batch_size=self.args.train_batch_size, shuffle=True, num_workers=self.args.dataloader_num_workers, pin_memory=self.args.dataloader_pin_memory) def get_eval_dataloader(self) -> DataLoader: eval_dataset = self.eval_dataset if (eval_dataset is None): eval_dataset = self.train_dataset return DataLoader(dataset=eval_dataset, batch_size=1)
.parametrize('name,kwargs,in_data,out_data', TEST_CASES) def test_layers_from_config(name, kwargs, in_data, out_data): cfg = {'': name, **kwargs} filled_cfg = registry.fill({'config': cfg}) assert srsly.is_json_serializable(filled_cfg) model = registry.resolve({'config': cfg})['config'] if ('LSTM' in name): model = with_padded(model) valid = True with data_validation(valid): model.initialize(in_data, out_data) (Y, backprop) = model(in_data, is_train=True) if model.has_dim('nO'): assert (get_width(Y) == model.get_dim('nO')) assert_data_match(Y, out_data) dX = backprop(Y) assert_data_match(dX, in_data) model._to_ops(NoDropoutOps()) model.predict(in_data)
def extractDemonictofuWordpressCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None if ('WATTT' in item['tags']): return buildReleaseMessageWithType(item, 'WATTT', vol, chp, frag=frag, postfix=postfix) return False
def obtain_extract_partition_sql(config: dict, is_null_partition: bool=False) -> str: if (not config.get('optional_predicate')): config['optional_predicate'] = 'WHERE' else: config['optional_predicate'] += ' AND ' if is_null_partition: sql = EXTRACT_NULL_PARTITION_SQL else: sql = EXTRACT_PARTITION_SQL return sql.format(**config).format(**config)
class TestImages(unittest.TestCase): def test_roundtrip_rgb8(self): arr = np.random.randint(0, 256, size=(240, 360, 3)).astype(np.uint8) msg = ros_numpy.msgify(Image, arr, encoding='rgb8') arr2 = ros_numpy.numpify(msg) np.testing.assert_equal(arr, arr2) def test_roundtrip_mono(self): arr = np.random.randint(0, 256, size=(240, 360)).astype(np.uint8) msg = ros_numpy.msgify(Image, arr, encoding='mono8') arr2 = ros_numpy.numpify(msg) np.testing.assert_equal(arr, arr2) def test_roundtrip_big_endian(self): arr = np.random.randint(0, 256, size=(240, 360)).astype('>u2') msg = ros_numpy.msgify(Image, arr, encoding='mono16') self.assertEqual(msg.is_bigendian, True) arr2 = ros_numpy.numpify(msg) np.testing.assert_equal(arr, arr2) def test_roundtrip_little_endian(self): arr = np.random.randint(0, 256, size=(240, 360)).astype('<u2') msg = ros_numpy.msgify(Image, arr, encoding='mono16') self.assertEqual(msg.is_bigendian, False) arr2 = ros_numpy.numpify(msg) np.testing.assert_equal(arr, arr2) def test_bad_encodings(self): mono_arr = np.random.randint(0, 256, size=(240, 360)).astype(np.uint8) mono_arrf = np.random.randint(0, 256, size=(240, 360)).astype(np.float32) rgb_arr = np.random.randint(0, 256, size=(240, 360, 3)).astype(np.uint8) rgb_arrf = np.random.randint(0, 256, size=(240, 360, 3)).astype(np.float32) with self.assertRaises(TypeError): msg = ros_numpy.msgify(Image, rgb_arr, encoding='mono8') with self.assertRaises(TypeError): msg = ros_numpy.msgify(Image, mono_arrf, encoding='mono8') with self.assertRaises(TypeError): msg = ros_numpy.msgify(Image, rgb_arrf, encoding='rgb8') with self.assertRaises(TypeError): msg = ros_numpy.msgify(Image, mono_arr, encoding='rgb8')
.skip_ci ('pyscf') def test_oniom3(): run_dict = {'geom': {'type': 'redund', 'fn': 'lib:oniom3alkyl.pdb'}, 'calc': {'type': 'oniom', 'calcs': {'real': {'type': 'pyscf', 'basis': 'sto3g', 'pal': 2}, 'mid': {'type': 'pyscf', 'basis': '321g', 'pal': 2}, 'high': {'type': 'pyscf', 'basis': '431g', 'pal': 2}}, 'models': {'high': {'inds': list(range(7, 16)), 'calc': 'high'}, 'mid': {'inds': list(range(4, 19)), 'calc': 'mid'}}}, 'opt': {'thresh': 'gau_tight'}} res = run_from_dict(run_dict) print() opt = res.opt assert opt.is_converged assert (opt.cur_cycle == 7) geom = res.opt_geom res = do_final_hessian(geom, save_hessian=False) nus = res.nus np.testing.assert_allclose(nus[[(- 1), (- 5)]], (3750.1537948, 3566.366994), atol=0.01)
class AbstractCrudObject(AbstractObject): def __init__(self, fbid=None, parent_id=None, api=None): super(AbstractCrudObject, self).__init__() self._api = (api or FacebookAdsApi.get_default_api()) self._changes = {} if (parent_id is not None): warning_message = 'parent_id as a parameter of constructor is being deprecated.' logging.warning(warning_message) self._parent_id = parent_id self._data['id'] = fbid self._include_summary = True def __setitem__(self, key, value): if ((key not in self._data) or (self._data[key] != value)): self._changes[key] = value super(AbstractCrudObject, self).__setitem__(key, value) if ('_setitem_trigger' in dir(self)): self._setitem_trigger(key, value) return self def __delitem__(self, key): del self._data[key] self._changes.pop(key, None) def __eq__(self, other): return (isinstance(other, self.__class__) and self.get_id() and other.get_id() and (self.get_id() == other.get_id())) def __ne__(self, other): return (not self.__eq__(other)) def get_by_ids(cls, ids, params=None, fields=None, api=None): api = (api or FacebookAdsApi.get_default_api()) params = dict((params or {})) cls._assign_fields_to_params(fields, params) params['ids'] = ','.join(map(str, ids)) response = api.call('GET', ['/'], params=params) result = [] for (fbid, data) in response.json().items(): obj = cls(fbid, api=api) obj._set_data(data) result.append(obj) return result def get_id(self): return (self[self.Field.id] if (hasattr(self, 'Field') and hasattr(self.Field, 'Field')) else self['id']) def get_parent_id(self): warning_message = 'parent_id is being deprecated.' logging.warning(warning_message) return (self._parent_id or FacebookAdsApi.get_default_account_id()) def get_api(self): return self._api def get_id_assured(self): if (not self.get(self.Field.id)): raise FacebookBadObjectError(('%s object needs an id for this operation.' % self.__class__.__name__)) return self.get_id() def get_parent_id_assured(self): warning_message = 'parent_id is being deprecated.' logging.warning(warning_message) if (not self.get_parent_id()): raise FacebookBadObjectError(('%s object needs a parent_id for this operation.' % self.__class__.__name__)) return self.get_parent_id() def get_api_assured(self): api = self.get_api() if (not api): raise FacebookBadObjectError(('%s does not yet have an associated api object.\nDid you forget to instantiate an API session with: FacebookAdsApi.init(app_id, app_secret, access_token)' % self.__class__.__name__)) return api def _clear_history(self): self._changes = {} if ('filename' in self._data): del self._data['filename'] return self def _set_data(self, data): for key in map(str, data): self[key] = data[key] self._changes.pop(key, None) self._json = data return self def export_changed_data(self): return self.export_value(self._changes) def export_data(self): return self.export_changed_data() def clear_id(self): del self[self.Field.id] return self def get_node_path(self): return (self.get_id_assured(),) def get_node_path_string(self): return '/'.join(self.get_node_path()) def remote_create(self, batch=None, failure=None, files=None, params=None, success=None, api_version=None): warning_message = '`remote_create` is being deprecated, please update your code with new function.' logging.warning(warning_message) if self.get_id(): raise FacebookBadObjectError(('This %s object was already created.' % self.__class__.__name__)) if (not ('get_endpoint' in dir(self))): raise TypeError(('Cannot create object of type %s.' % self.__class__.__name__)) params = ({} if (not params) else params.copy()) params.update(self.export_all_data()) request = None if hasattr(self, 'api_create'): request = self.api_create(self.get_parent_id_assured(), pending=True) else: request = FacebookRequest(node_id=self.get_parent_id_assured(), method='POST', endpoint=self.get_endpoint(), api=self._api, target_class=self.__class__, response_parser=ObjectParser(reuse_object=self)) request.add_params(params) request.add_files(files) if (batch is not None): def callback_success(response): self._set_data(response.json()) self._clear_history() if success: success(response) def callback_failure(response): if failure: failure(response) return batch.add_request(request=request, success=callback_success, failure=callback_failure) else: response = request.execute() self._set_data(response._json) self._clear_history() return self def remote_read(self, batch=None, failure=None, fields=None, params=None, success=None, api_version=None): warning_message = '`remote_read` is being deprecated, please update your code with new function.' logging.warning(warning_message) params = dict((params or {})) if hasattr(self, 'api_get'): request = self.api_get(pending=True) else: request = FacebookRequest(node_id=self.get_id_assured(), method='GET', endpoint='/', api=self._api, target_class=self.__class__, response_parser=ObjectParser(reuse_object=self)) request.add_params(params) request.add_fields(fields) if (batch is not None): def callback_success(response): self._set_data(response.json()) if success: success(response) def callback_failure(response): if failure: failure(response) batch_call = batch.add_request(request=request, success=callback_success, failure=callback_failure) return batch_call else: self = request.execute() return self def remote_update(self, batch=None, failure=None, files=None, params=None, success=None, api_version=None): warning_message = '`remote_update` is being deprecated, please update your code with new function.' logging.warning(warning_message) params = ({} if (not params) else params.copy()) params.update(self.export_changed_data()) self._set_data(params) if hasattr(self, 'api_update'): request = self.api_update(pending=True) else: request = FacebookRequest(node_id=self.get_id_assured(), method='POST', endpoint='/', api=self._api, target_class=self.__class__, response_parser=ObjectParser(reuse_object=self)) request.add_params(params) request.add_files(files) if (batch is not None): def callback_success(response): self._clear_history() if success: success(response) def callback_failure(response): if failure: failure(response) batch_call = batch.add_request(request=request, success=callback_success, failure=callback_failure) return batch_call else: request.execute() self._clear_history() return self def remote_delete(self, batch=None, failure=None, params=None, success=None, api_version=None): warning_message = '`remote_delete` is being deprecated, please update your code with new function.' logging.warning(warning_message) if hasattr(self, 'api_delete'): request = self.api_delete(pending=True) else: request = FacebookRequest(node_id=self.get_id_assured(), method='DELETE', endpoint='/', api=self._api) request.add_params(params) if (batch is not None): def callback_success(response): self.clear_id() if success: success(response) def callback_failure(response): if failure: failure(response) batch_call = batch.add_request(request=request, success=callback_success, failure=callback_failure) return batch_call else: request.execute() self.clear_id() return self def remote_save(self, *args, **kwargs): warning_message = '`remote_save` is being deprecated, please update your code with new function.' logging.warning(warning_message) if self.get_id(): return self.remote_update(*args, **kwargs) else: return self.remote_create(*args, **kwargs) def remote_archive(self, batch=None, failure=None, success=None): if (('Status' not in dir(self)) or ('archived' not in dir(self.Status))): raise TypeError(('Cannot archive object of type %s.' % self.__class__.__name__)) return self.api_create(params={'status': self.Status.archived}, batch=batch, failure=failure, success=success) save = remote_save def iterate_edge(self, target_objects_class, fields=None, params=None, fetch_first_page=True, include_summary=True, endpoint=None): source_object = self cursor = Cursor(source_object, target_objects_class, fields=fields, params=params, include_summary=include_summary, endpoint=endpoint) if fetch_first_page: cursor.load_next_page() return cursor def iterate_edge_async(self, target_objects_class, fields=None, params=None, is_async=False, include_summary=True, endpoint=None): from facebook_business.adobjects.adreportrun import AdReportRun synchronous = (not is_async) synchronous_iterator = self.iterate_edge(target_objects_class, fields, params, fetch_first_page=synchronous, include_summary=include_summary) if synchronous: return synchronous_iterator if (not params): params = {} else: params = dict(params) self.__class__._assign_fields_to_params(fields, params) if (endpoint is None): endpoint = target_objects_class.get_endpoint() response = self.get_api_assured().call('POST', (self.get_id_assured(), endpoint), params=params).json() result = AdReportRun() if ('report_run_id' in response): response['id'] = response['report_run_id'] result._set_data(response) return result def edge_object(self, target_objects_class, fields=None, params=None, endpoint=None): params = ({} if (not params) else params.copy()) params['limit'] = '1' for obj in self.iterate_edge(target_objects_class, fields=fields, params=params, endpoint=endpoint): return obj return None def assure_call(self): if (not self._api): raise FacebookBadObjectError('Api call cannot be made if api is not set')
.django_db def test_spending_over_time_funny_dates_ordering(client, monkeypatch, elasticsearch_transaction_index, populate_models): setup_elasticsearch_test(monkeypatch, elasticsearch_transaction_index) group = 'month' test_payload = {'group': group, 'subawards': False, 'filters': {'time_period': [{'start_date': '2010-02-01', 'end_date': '2010-03-31'}, {'start_date': '2011-02-01', 'end_date': '2011-03-31'}]}, 'messages': [get_time_period_message()]} expected_response = {'results': [{'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '5'}}, {'aggregated_amount': 100.0, 'time_period': {'fiscal_year': '2010', 'month': '6'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '7'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '8'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '9'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '10'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '11'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2010', 'month': '12'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2011', 'month': '1'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2011', 'month': '2'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2011', 'month': '3'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2011', 'month': '4'}}, {'aggregated_amount': 0.0, 'time_period': {'fiscal_year': '2011', 'month': '5'}}, {'aggregated_amount': 110.0, 'time_period': {'fiscal_year': '2011', 'month': '6'}}], 'group': 'month', 'messages': [get_time_period_message()]} resp = client.post(get_spending_over_time_url(), content_type='application/json', data=json.dumps(test_payload)) assert (resp.status_code == status.HTTP_200_OK) assert (expected_response == resp.data), 'Unexpected or missing content!' confirm_proper_ordering(group, resp.data['results'])
class OptionSeriesVariwideSonificationTracksMappingTime(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
.network def test_pooch_logging_level(): with TemporaryDirectory() as local_store: path = Path(local_store) urls = {'tiny-data.txt': (BASEURL + 'tiny-data.txt')} pup = Pooch(path=path, base_url='', registry=REGISTRY, urls=urls) with capture_log('CRITICAL') as log_file: fname = pup.fetch('tiny-data.txt') assert (log_file.getvalue() == '') check_tiny_data(fname)
.unit class TestMergeCredentialsEnvironment(): (os.environ, {'FIDES__CREDENTIALS__POSTGRES_1__CONNECTION_STRING': 'postgresql+psycopg2://fides:env_variable.com:5439/fidesctl_test', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__REGION': 'us-east-1', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY_ID': 'ACCESS_KEY_ID_1', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY': 'ACCESS_KEY_1'}, clear=True) def test_merge_credentials(self) -> None: credentials_dict: Dict = dict() merge_credentials_environment(credentials_dict) assert (credentials_dict == {'postgres_1': {'connection_string': 'postgresql+psycopg2://fides:env_variable.com:5439/fidesctl_test'}, 'aws_account_1': {'region': 'us-east-1', 'access_key_id': 'ACCESS_KEY_ID_1', 'access_key': 'ACCESS_KEY_1'}}) (os.environ, {'FIDES__CREDENTIALS__POSTGRES_1__CONNECTION_STRING': 'postgresql+psycopg2://fides:env_variable.com:5439/fidesctl_test', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY_ID': 'ACCESS_KEY_ID_1', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY': 'ACCESS_KEY_1'}, clear=True) def test_mixed_configs(self) -> None: credentials_dict = {'aws_account_1': {'region': 'us-east-1'}} merge_credentials_environment(credentials_dict) assert (credentials_dict == {'postgres_1': {'connection_string': 'postgresql+psycopg2://fides:env_variable.com:5439/fidesctl_test'}, 'aws_account_1': {'region': 'us-east-1', 'access_key_id': 'ACCESS_KEY_ID_1', 'access_key': 'ACCESS_KEY_1'}}) (os.environ, {'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY_ID': 'ACCESS_KEY_ID_OVERRIDE', 'FIDES__CREDENTIALS__AWS_ACCOUNT_1__ACCESS_KEY': 'ACCESS_KEY_OVERRIDE'}, clear=True) def test_environment_override(self) -> None: credentials_dict = {'aws_account_1': {'region': 'us-east-1', 'access_key_id': 'ACCESS_KEY_ID_1', 'access_key': 'ACCESS_KEY_1'}} merge_credentials_environment(credentials_dict) assert (credentials_dict == {'aws_account_1': {'region': 'us-east-1', 'access_key_id': 'ACCESS_KEY_ID_OVERRIDE', 'access_key': 'ACCESS_KEY_OVERRIDE'}})
def extractBujangtranslationWordpressCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('PCN', 'Pendekar Cambuk Naga', 'translated'), ('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
def test_and_qualifier(alice, bob, my_logic): def _is_alice(connection, logic): assert isinstance(alice, ConnectionAPI) return (connection is alice) def _is_my_logic(connection, logic): assert isinstance(logic, LogicAPI) return (logic is my_logic) qualifier = AndQualifier(_is_alice, _is_my_logic) assert (qualifier(alice, my_logic) is True) assert (qualifier(bob, my_logic) is False) assert (qualifier(alice, SimpleLogic()) is False) assert (qualifier(bob, SimpleLogic()) is False)
def chain_setup(w3): old_chain_id = remove_0x_prefix(to_hex(w3.eth.get_block(0)['hash'])) block_hash = remove_0x_prefix(to_hex(w3.eth.get_block('earliest').hash)) old_chain_uri = f'blockchain://{old_chain_id}/block/{block_hash}' match_data = {old_chain_uri: {'x': 'x'}, f'blockchain://1234/block/{block_hash}': {'x': 'x'}} no_match_data = {f'blockchain://56775ac59d0774e6b603a79c4218efeb5653b99ba0ff14db983bac2662251a8a/block/{block_hash}': {'x': 'x'}} return (w3, match_data, no_match_data, old_chain_uri)
class TestGtLtMatchers(): def setup_method(self): self.str = get_search_result_track() def test_gt_bitrate_matcher_true(self): matcher = search._GtMatcher('__bitrate', 100000, (lambda x: x)) self.str.track.set_tag_raw('__bitrate', 128000) assert matcher.match(self.str) def test_gt_bitrate_matcher_false(self): matcher = search._GtMatcher('__bitrate', 100000, (lambda x: x)) self.str.track.set_tag_raw('__bitrate', 28000) assert (not matcher.match(self.str)) def test_lt_bitrate_matcher_true(self): matcher = search._LtMatcher('__bitrate', 100000, (lambda x: x)) self.str.track.set_tag_raw('__bitrate', 28000) assert matcher.match(self.str) def test_lt_bitrate_matcher_false(self): matcher = search._LtMatcher('__bitrate', 100000, (lambda x: x)) self.str.track.set_tag_raw('__bitrate', 128000) assert (not matcher.match(self.str))
.unit def test_parse_manifest(): expected_result = models.DataCategory(organization_fides_key=1, fides_key='some_resource', name='Test resource 1', description='Test Description') test_dict = {'organization_fides_key': 1, 'fides_key': 'some_resource', 'name': 'Test resource 1', 'description': 'Test Description'} actual_result = parse.parse_dict('data_category', test_dict) assert (actual_result == expected_result)
def simulate_calls_with_limiter(num_calls: int, rate_limit_requests: List[RateLimiterRequest]) -> Dict: limiter: RateLimiter = RateLimiter() call_log = {} for _ in range(num_calls): limiter.limit(requests=rate_limit_requests) current_time = int(time.time()) count = call_log.get(current_time, 0) call_log[current_time] = (count + 1) time.sleep(0.002) return call_log
class OptionSeriesXrangeSonificationDefaultspeechoptionsMappingRate(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class TestMatcher(): def setup_method(self): self.strack = get_search_result_track() self.strack.track.set_tag_raw('artist', ['foo', 'bar']) (search._Matcher, '_matches', return_value=True) def test_match_list_true(self, mock_method): matcher = search._Matcher('artist', 'bar', (lambda x: x)) assert matcher.match(self.strack) mock_method.assert_called_with('foo') (search._Matcher, '_matches', return_value=False) def test_match_list_false(self, mock_method): matcher = search._Matcher('artist', 'bar', (lambda x: x)) assert (not matcher.match(self.strack)) mock_method.assert_has_calls([call('foo'), call('bar')]) (search._Matcher, '_matches', return_value=True) def test_match_list_none(self, mock_method): matcher = search._Matcher('album', None, (lambda x: x)) assert matcher.match(self.strack) mock_method.assert_called_with(None) def test_matches(self): matcher = search._Matcher('album', None, (lambda x: x)) with pytest.raises(NotImplementedError): matcher._matches('foo')
def init_db(): global _scoped_session global _session_cls global _engine global OrmModelBase _engine = create_engine(connect_string(), pool_size=config.database_pool_size, echo=config.database_echo_sql) _session_cls = sessionmaker(autocommit=False, autoflush=False, bind=_engine) _scoped_session = scoped_session(_session_cls) import uchan.lib.ormmodel
class ScheduleTimeColumn(Column): name = 'schedule_time' display = _('Schedule') size = 80 def __init__(self, *args): Column.__init__(self, *args) self.timeout_id = None event.add_ui_callback(self.on_queue_current_playlist_changed, 'queue_current_playlist_changed', player.QUEUE) event.add_ui_callback(self.on_playback_player_start, 'playback_player_start', player.PLAYER) event.add_ui_callback(self.on_playback_player_end, 'playback_player_end', player.PLAYER) def data_func(self, col, cell, model, iter, user_data): text = None playlist = self.container.playlist if ((not self.player.is_stopped()) and (playlist is self.player.queue.current_playlist) and (playlist.shuffle_mode == 'disabled') and (playlist.repeat_mode != 'track')): track = model.get_value(iter, 0) position = playlist.index(track) current_position = playlist.current_position if (position > current_position): try: delay = sum((t.get_tag_raw('__length') for t in playlist[current_position:position])) except TypeError: pass else: delay -= self.player.get_time() schedule_time = time.localtime((time.time() + delay)) text = time.strftime('%H:%M', schedule_time) cell.props.text = text def start_timer(self): timeout_id = self.timeout_id if (timeout_id is not None): GLib.source_remove(timeout_id) self.timeout_id = GLib.timeout_add_seconds(60, self.on_timeout) def stop_timer(self): timeout_id = self.timeout_id if (timeout_id is not None): GLib.source_remove(timeout_id) self.timeout_id = None self.on_timeout() def on_timeout(self): self.queue_resize() view = self.get_tree_view() if (view is not None): view.queue_draw() return True self.timeout_id = None return False def on_queue_current_playlist_changed(self, e, queue, current_playlist): self.stop_timer() if (current_playlist is self.container.playlist): self.start_timer() def on_playback_player_start(self, e, player, track): self.stop_timer() if (self.player.queue.current_playlist is self.container.playlist): logger.debug('Playback started, enabling realtime updates') self.start_timer() def on_playback_player_end(self, e, player, track): self.stop_timer()
class CashFlowStatement(DocType): id = Keyword() securityId = Keyword() code = Keyword() reportPeriod = Date() timestamp = Date() reportEventDate = Date() cashFromSellingCommoditiesOrOfferingLabor = Float() refundOfTaxAndFeeReceived = Float() cashReceivedRelatingToOtherOperatingActivities = Float() subTotalOfCashInflowsFromOperatingActivities = Float() cashPaidForGoodsAndServices = Float() cashPaidToAndOnBehalfOfemployees = Float() paymentsOfTaxesAndSurcharges = Float() cashPaidRelatingToOtherOperatingActivities = Float() subTotalOfCashOutflowsFromOperatingActivities = Float() netCashFlowsFromOperatingActivities = Float() cashReceivedFromDisposalOfInvestments = Float() cashReceivedFromReturnsOnIvestments = Float() netCashReceivedFromDisposalAssets = Float() netCashReceivedFromDisposalSubsidiaries = Float() cashReceivedFromOtherInvesting = Float() subTotalOfCashInflowsFromInvesting = Float() cashPaidToAcquireFixedAssets = Float() cashPaidToAcquireInvestments = Float() netCashPaidToAcquireSubsidiaries = Float() cashPaidRelatingToOtherInvesting = Float() subTotalOfCashOutflowsFromInvesting = Float() netCashFlowsFromInvesting = Float() cashReceivedFromCapitalContributions = Float() cashReceivedFromMinorityShareholdersOfSubsidiaries = Float() cashReceivedFromBorrowings = Float() cashReceivedFromIssuingBonds = Float() cashReceivedRelatingToOtherFinancingActivities = Float() subTotalOfCashInflowsFromFinancingActivities = Float() cashRepaymentsOfBorrowings = Float() cashPaymentsForInterestExpensesAndDistributionOfDividendsOrProfits = Float() cashPaymentsForDividendsOrProfitToMinorityShareholders = Float() cashPaymentsRelatingToOtherFinancingActivities = Float() subTotalOfCashOutflowsFromFinancingActivities = Float() netCashFlowsFromFinancingActivities = Float() effectOfForeignExchangeRate = Float() netIncreaseInCash = Float() cashAtBeginningOfyear = Float() cashAtEndOfyear = Float() netProfit = Float() minorityBookValue = Float() unrealisedInvestmentLosses = Float() allowanceForAssetDevaluation = Float() depreciationOfFixedAssets = Float() amorizationOfIntangibleAssets = Float() longTermDeferredExpenses = Float() decreaseOfDeferredExpenses = Float() IncreaseOfwithholdingExpenses = Float() lossOnDisposalOfFixedAssets = Float() lossOnFixedAssetsDamaged = Float() lossOnFairValueChange = Float() changeOnDeferredRevenue = Float() estimatedLiabilities = Float() financingExpenses = Float() investmentLoss = Float() decreaseOnDeferredIncomeTaxAssets = Float() increaseOnDeferredIncomeTaxLiabilities = Float() decreaseInInventories = Float() decreaseInReceivablesUnderOperatingActivities = Float() increaseInReceivablesUnderOperatingActivities = Float() decreaseOnAmountDue = Float() increaseOnSettlementNotYetCompleted = Float() other = Float() netCashFlowFromOperatingActivities = Float() debtsTransferToCapital = Float() oneYearDueConvertibleBonds = Float() financingRentToFixedAsset = Float() cashAtTheEndOfPeriod = Float() cashAtTheBeginningOfPeriod = Float() cashEquivalentsAtTheEndOfPeriod = Float() cashEquivalentsAtTheBeginningOfPeriod = Float() netIncreaseInCashAndCashEquivalents = Float() class Meta(): index = 'cash_flow_statement' doc_type = 'doc' all = MetaField(enabled=False) dynamic = MetaField('strict')
.parametrize('is_admin', [True, False]) def test_user_create_success(dashboard_user, session, is_admin): username = str(uuid.uuid4()) password = str(uuid.uuid4()) response = dashboard_user.post('dashboard/api/user/create', data={'username': username, 'password': password, 'password2': password, 'is_admin': ('true' if is_admin else 'false')}) assert (response.status_code == 200) assert (response.data == b'OK') user = session.query(User).filter((User.username == username)).one() assert user.check_password(password) assert (user.is_admin is is_admin)
class TestFunctions(): def test_func_default_return_null(self): assert (evalpy('def foo():pass\nprint(foo(), 1)') == 'null 1') assert (evalpy('def foo():return\nprint(foo(), 1)') == 'null 1') def test_func_call_compilation(self): assert (py2js('foo()') == 'foo();') assert (py2js('foo(3, 4)') == 'foo(3, 4);') assert (py2js('foo(3, 4+1)') == 'foo(3, 4 + 1);') assert py2js('foo(3, *args)') assert py2js('a.foo(3, *args)') def test_simple_funcs_dont_parse_kwargs(self): code = py2js('def foo(): pass') assert ('parse_kwargs' not in code) assert ('kw_values' not in code) code = py2js('def foo(a, b, c): pass') assert ('parse_kwargs' not in code) assert ('kw_values' not in code) code = py2js('def foo(a, *c): pass') assert ('parse_kwargs' not in code) assert ('kw_values' not in code) code = py2js('def foo(a, b=1, c="foo"): pass') assert ('parse_kwargs' not in code) assert ('kw_values' not in code) def test_when_funcs_do_parse_kwargs(self): code = py2js('def foo(a, **c): pass') assert ('parse_kwargs' in code) assert ('kw_values' not in code) if (sys.version_info > (3,)): code = py2js('def foo(a, *, b=1, c="foo"): pass') assert ('parse_kwargs' in code) assert ('kw_values' in code) if (sys.version_info > (3,)): code = py2js('def foo(a, *, b=1, c="foo", **d): pass') assert ('parse_kwargs' in code) assert ('kw_values' in code) def test_func1(self): code = py2js(func1) lines = [line for line in code.split('\n') if line] assert (len(lines) == 4) assert (lines[1] == 'func1 = function flx_func1 () {') assert lines[2].startswith(' ') assert (lines[3] == '};') def test_function_call_simple(self): code = "def foo(x): return x + 1\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(3)')) == '4') assert (evalpy((code + 'd.foo(3)')) == '4') def test_function_call_varargs(self): code = "def foo(x, *xx): return x + sum(xx)\nd = {'foo':foo}\nfive=[2, 3]\n" assert (evalpy((code + 'foo(1, 2, 3)')) == '6') assert (evalpy((code + 'd.foo(1, 2, 3)')) == '6') assert (evalpy((code + 'foo(1, *five)')) == '6') assert (evalpy((code + 'd.foo(1, *five)')) == '6') def test_function_call_default_args(self): code = "def foo(a=2, b=3, c=4): return a+b+c;\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(1, 2, 3)')) == '6') assert (evalpy((code + 'd.foo(1, 2, 3)')) == '6') assert (evalpy((code + 'foo(1, 2)')) == '7') assert (evalpy((code + 'd.foo(1, 2)')) == '7') assert (evalpy((code + 'foo(1)')) == '8') assert (evalpy((code + 'd.foo(1)')) == '8') assert (evalpy((code + 'foo()')) == '9') assert (evalpy((code + 'd.foo()')) == '9') ((sys.version_info < (3,)), reason='no keyword only args in legacy py') def test_function_call_keyword_only_args(self): code = "def foo(*, a=2, b=3, c=4): return a+b+c;\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(a=1, b=2, c=3)')) == '6') assert (evalpy((code + 'd.foo(a=1, b=2, c=3)')) == '6') assert (evalpy((code + 'foo(b=10)')) == '16') assert (evalpy((code + 'd.foo(b=10)')) == '16') code = "def foo(*x, a=2, b=3, c=4): return (sum(x) if x else 0) + a+b+c;\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(a=1, b=2, c=3)')) == '6') assert (evalpy((code + 'd.foo(a=1, b=2, c=3)')) == '6') assert (evalpy((code + 'foo(b=10)')) == '16') assert (evalpy((code + 'd.foo(b=10)')) == '16') assert (evalpy((code + 'foo(100, 200, b=10)')) == '316') assert (evalpy((code + 'd.foo(100, 200, b=10)')) == '316') assert (evalpy((code + 'try:\n foo(d=4)\nexcept TypeError:\n print("ha")')) == 'ha') assert (evalpy((code + 'try:\n d.foo(d=4)\nexcept TypeError:\n print("ha")')) == 'ha') code = "def foo(a=2): return a\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(a=3)')) == '{ flx_args: [], flx_kwargs: { a: 3 } }') assert (evalpy((code + 'd.foo(a=3)')) == '{ flx_args: [], flx_kwargs: { a: 3 } }') def test_function_call_kwargs(self): code = "def foo(a, b=9, **x): return repr([a, b]) + repr(x);\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(1, 2)')) == '[1,2]{}') assert (evalpy((code + 'foo(1, 2, 3)')) == '[1,2]{}') assert (evalpy((code + 'foo(1, b=3)')) == '[1,9]{"b":3}') assert (evalpy((code + 'foo(1, b=3, c=4)')) == '[1,9]{"b":3,"c":4}') assert (evalpy((code + 'd.foo(1, 2)')) == '[1,2]{}') assert (evalpy((code + 'd.foo(1, b=3, c=4)')) == '[1,9]{"b":3,"c":4}') def test_function_call_args_and_kwargs(self): code = 'def foo(*args, **kwargs): return args;\n' assert (evalpy((code + 'foo(1, 2, 3)')) == '[ 1, 2, 3 ]') assert (evalpy((code + 'foo(1, 2, 3, a=3)')) == '[ 1, 2, 3 ]') assert (evalpy((code + 'foo(1, 2, 3, **{"b":4})')) == '[ 1, 2, 3 ]') assert (evalpy((code + 'foo(a=3, **{"b":4})')) == '[]') code = 'def foo(*args, **kwargs): return kwargs;\n' assert (evalpy((code + 'foo(1, 2, 3)')) == '{}') assert (evalpy((code + 'foo(1, 2, 3, a=3)')) == '{ a: 3 }') assert (evalpy((code + 'foo(1, 2, 3, **{"b":4})')) == '{ b: 4 }') assert (evalpy((code + 'foo(a=3, **{"b":4})')) == '{ a: 3, b: 4 }') ((sys.version_info < (3,)), reason='no keyword only args in legacy py') def test_function_call_keyword_only_args_and_kwargs(self): code = "def foo(*, a=3, b=4, **x): return repr([a, b]) + repr(x);\nd = {'foo':foo}\n" assert (evalpy((code + 'foo(1)')) == '[3,4]{}') assert (evalpy((code + 'foo(a=1, b=2)')) == '[1,2]{}') assert (evalpy((code + 'foo(a=1, b=2, c=5)')) == '[1,2]{"c":5}') assert (evalpy((code + 'd.foo(1)')) == '[3,4]{}') assert (evalpy((code + 'd.foo(a=1, b=2, c=5)')) == '[1,2]{"c":5}') code = 'def foo(a, b=2, *, c=3, **x): return repr([a, b, c]) + repr(x);\n' assert (evalpy((code + 'foo(1)')) == '[1,2,3]{}') assert (evalpy((code + 'foo(1, b=8)')) == '[1,2,3]{"b":8}') assert (evalpy((code + 'foo(1, c=8)')) == '[1,2,8]{}') assert (evalpy((code + 'foo(1, d=8)')) == '[1,2,3]{"d":8}') def method1(self): return def test_method1(self): code = py2js(self.method1) lines = [line for line in code.split('\n') if line] assert (len(lines) == 4) assert (lines[1] == 'method1 = function () {') assert lines[2].startswith(' ') assert (lines[3] == '};') def test_default_args(self): def func(self, foo, bar=2): return (foo - bar) code = py2js(func) lines = [line for line in code.split('\n') if line] assert (lines[1] == 'func = function (foo, bar) {') assert ('2' in code) assert (evaljs((code + 'func(2)')) == '0') assert (evaljs((code + 'func(4, 3)')) == '1') assert (evaljs((code + 'func(0, 0)')) == '0') def test_var_args1(self): def func(self, *args): return args code1 = py2js(func) code2 = py2js('func(2, 3)') assert (evaljs((code1 + code2), False) == '[2,3]') code2 = py2js('func()') assert (evaljs((code1 + code2), False) == '[]') code2 = py2js('a=[2,3]\nfunc(*a)') assert (evaljs((code1 + code2), False) == '[2,3]') code2 = py2js('a=[2,3]\nfunc(1,2,*a)') assert (evaljs((code1 + code2), False) == '[1,2,2,3]') def test_var_args2(self): def func(self, foo, *args): return args code1 = py2js(func) code2 = py2js('func(0, 2, 3)') assert (evaljs((code1 + code2), False) == '[2,3]') code2 = py2js('func(0)') assert (evaljs((code1 + code2), False) == '[]') code2 = py2js('a=[0,2,3]\nfunc(*a)') assert (evaljs((code1 + code2), False) == '[2,3]') code2 = py2js('a=[2,3]\nfunc(0,1,2,*a)') assert (evaljs((code1 + code2), False) == '[1,2,2,3]') def test_self_becomes_this(self): def func(self): return self.foo code = py2js(func) lines = [line.strip() for line in code.split('\n') if line] assert ('return this.foo;' in lines) def test_lambda(self): assert (evalpy('f=lambda x:x+1\nf(2)') == '3') assert (evalpy('(lambda x:x+1)(2)') == '3') def test_scope(self): def func(self): def foo(z): y = 2 stub = False only_here = 1 return ((x + y) + z) x = 1 y = 0 y = 1 z = 1 res = foo(3) stub = True return (res + y) code = py2js(func) i = code.splitlines().index('var func;') assert (i >= 0) vars1 = code.splitlines()[(i + 2)] vars2 = code.splitlines()[(i + 4)] assert vars1.strip().startswith('var ') assert vars2.strip().startswith('var ') assert (('y' in vars1) and ('y' in vars2)) assert (('stub' in vars1) and ('stub' in vars2)) assert (('only_here' in vars2) and ('only_here' not in vars1)) assert (evaljs((code + 'func()')) == '7') def test_scope2(self): def func1(self): x = 1 def func2(self): x = 1 y = (lambda : None) def func3(self): x = 1 def y(): pass assert ('var x' in py2js(func1)) assert ('var x' in py2js(func2)) assert ('var x' in py2js(func3)) def test_recursion(self=None): code = 'def f(i): i *= 2; return i if i > 10 else f(i)\n\n' assert (evalpy((code + 'f(1)')) == '16') clscode = 'class G:\n def __init__(self): self.i = 1\n\n' code = (clscode + ' def f(self): self.i *= 2; return self.i if self.i > 10 else self.f()\n\n') assert (evalpy((code + 'g = G(); g.f()')) == '16') code = (clscode + ' def f(self):\n def h(): self.i *= 2; return self.i if self.i > 10 else h()\n\n') assert (evalpy((code + ' return h()\n\ng = G(); g.f()')) == '16') def test_global(self): assert (py2js('global foo;foo = 3').strip() == 'foo = 3;') def func1(): def inner(): x = 3 x = 2 inner() return x def func2(): def inner(): global x x = 3 x = 2 inner() return x assert (evaljs((py2js(func1) + 'func1()')) == '2') assert (evaljs((py2js(func2) + 'func2()')) == '3') ((sys.version_info < (3,)), reason='no nonlocal on legacy Python') def test_nonlocal(self): assert (py2js('nonlocal foo;foo = 3').strip() == 'foo = 3;') func3_code = 'def func3():\n def inner():\n nonlocal x\n x = 3\n x = 2\n inner()\n return x\n ' assert (evaljs((py2js(func3_code) + 'func3()')) == '3') ((sys.version_info < (3,)), reason='no nonlocal on legacy Python') def test_global_vs_nonlocal(self): js1 = py2js('global foo;foo = 3') js2 = py2js('nonlocal foo;foo = 3') assert (js1.meta['vars_unknown'] == set()) assert (js2.meta['vars_unknown'] == set()) assert (js1.meta['vars_global'] == set(['foo'])) assert (js2.meta['vars_global'] == set()) code = 'if True:\n x = 1\n y = 1\n def inner1():\n x = 2\n y = 2\n def inner2():\n global x\n nonlocal y\n print(x, y)\n inner2()\n inner1()\n undefined\n ' def test_raw_js(self): def func(a, b): RawJS('\n var c = 3;\n return a + b + c;\n ') code = py2js(func) assert (evaljs((code + 'func(100, 10)')) == '113') assert (evaljs((code + 'func("x", 10)')) == 'x103') def test_docstring(self): def func(a, b): return (a + b) code = py2js(func) assert (evaljs((code + 'func(100, 10)')) == '110') assert (evaljs((code + 'func("x", 10)')) == 'x10') assert (code.count('// docstring') == 1) def test_async_and_await(self): if (sys.version_info < (3, 6)): return foo = py2js('async def foo(): return 42\n\n') spam = py2js('async def spam(): print(await foo())\n\n') eggs = py2js('async def eggs(): return await foo()\n\n') js = ((foo + spam) + eggs) assert ('Promise' in evaljs((js + 'foo()'))) assert ('Promise' in evaljs((js + 'spam()'))) assert ('Promise' in evaljs((js + 'eggs()'))) assert ('42' in evaljs((js + 'spam()'))) assert ('42' not in evaljs((js + 'eggs()')))
(scope='function') def create_test_repo(create_test_db): data = dict() data['repo1'] = Repository(name='Test Repo 1', code='TR1', linux_path='/test/repo/1/linux/path', windows_path='T:/test/repo/1/windows/path', osx_path='/test/repo/1/osx/path') data['repo2'] = Repository(name='Test Repo 2', code='TR2', linux_path='/test/repo/2/linux/path', windows_path='T:/test/repo/2/windows/path', osx_path='/test/repo/2/osx/path') data['repo3'] = Repository(name='Test Repo 3', code='TR3', linux_path='/test/repo/3/linux/path', windows_path='T:/test/repo/3/windows/path', osx_path='/test/repo/3/osx/path') data['repo4'] = Repository(name='Test Repo 4', code='TR4', linux_path='/test/repo/4/linux/path', windows_path='T:/test/repo/4/windows/path', osx_path='/test/repo/4/osx/path') data['repo5'] = Repository(name='Test Repo 5', code='TR5', linux_path='/test/repo/5/linux/path', windows_path='T:/test/repo/5/windows/path', osx_path='/test/repo/5/osx/path') data['all_repos'] = [data['repo1'], data['repo2'], data['repo3'], data['repo4'], data['repo5']] DBSession.add_all(data['all_repos']) DBSession.commit() (yield data)
class TestWifiOffWifi(MultimachineTestCase): def test(self): L.describe('Open and connect the VPN application') self.target_device['vpn_application'].open_and_connect() L.describe('Capture traffic') self.capture_device['packet_capturer'].start() L.describe('Generate whatever traffic you want') message_and_await_enter('Are you done?') L.describe('Disconnect WiFi') self.target_device['settings'].disable_wifi() message_and_await_enter('Wait until the application has noticed.') L.describe('Connect WiFi') self.target_device['settings'].enable_wifi() L.describe('Generate whatever traffic you want') message_and_await_enter('Are you done?') L.describe('Stop capturing traffic') packets = self.capture_device['packet_capturer'].stop() whitelist = self.capture_device.local_ips() L.debug('Excluding {} from analysis'.format(whitelist)) self.traffic_analyser.get_vpn_server_ip(packets, whitelist)
class AbstractTeiTrainingDataGenerator(TeiTrainingDataGenerator): def __init__(self, root_training_xml_element_path: Sequence[str], training_xml_element_path_by_label: Mapping[(str, Sequence[str])], root_tag: str='tei', use_tei_namespace: bool=True, element_maker: Optional[ElementMaker]=None, reset_training_xml_element_path_by_label: Optional[Mapping[(str, Sequence[str])]]=None, default_tei_filename_suffix: Optional[str]=None, default_data_filename_suffix: Optional[str]=None, default_tei_sub_directory: Optional[str]=None, default_data_sub_directory: Optional[str]=None): self.root_training_xml_element_path = root_training_xml_element_path self.root_parent_training_xml_element_path = root_training_xml_element_path[:(- 1)] self.training_xml_element_path_by_label = training_xml_element_path_by_label self.reset_training_xml_element_path_by_label = (reset_training_xml_element_path_by_label or {}) self._training_xml_element_paths = {tuple(element_path) for (label, element_path) in training_xml_element_path_by_label.items() if ((label not in OTHER_LABELS) and (tuple(element_path) != tuple(root_training_xml_element_path)))} self.other_element_path = training_xml_element_path_by_label.get('<other>') if (element_maker is None): element_maker = (TEI_E if use_tei_namespace else NO_NS_TEI_E) self.element_maker = element_maker self.root_tag = root_tag self.default_tei_filename_suffix = default_tei_filename_suffix self.default_data_filename_suffix = default_data_filename_suffix self.default_tei_sub_directory = default_tei_sub_directory self.default_data_sub_directory = default_data_sub_directory def get_default_tei_filename_suffix(self) -> Optional[str]: return self.default_tei_filename_suffix def get_default_data_filename_suffix(self) -> Optional[str]: return self.default_data_filename_suffix def get_default_tei_sub_directory(self) -> Optional[str]: return self.default_tei_sub_directory def get_default_data_sub_directory(self) -> Optional[str]: return self.default_data_sub_directory def get_training_xml_path_for_label(self, label: Optional[str], current_path: Sequence[str]) -> Sequence[str]: if ((not label) or (label in OTHER_LABELS)): if (label and (self.other_element_path is not None)): return self.other_element_path if (tuple(current_path) in self._training_xml_element_paths): LOGGER.debug('found current path in element paths, returning parent: %r', current_path) return current_path[:(- 1)] LOGGER.debug('not found current path in element paths, returning current: %r', current_path) return current_path training_xml_path = self.training_xml_element_path_by_label.get((label or '')) if (not training_xml_path): note_type = get_default_note_type_for_label(label) LOGGER.info('label not mapped, creating note: %r', label) training_xml_path = (list(self.root_training_xml_element_path) + [f'note[="{note_type}"]']) return training_xml_path def get_reset_training_xml_path_for_label(self, label: Optional[str], prefix: Optional[str]) -> Optional[Sequence[str]]: if ((prefix != 'B') or (not label)): return None return self.reset_training_xml_element_path_by_label.get(label) def write_xml_for_model_data_with_instructions_iterable(self, xml_writer: XmlTreeWriter, model_data_or_instruction_iterable: Iterable[Union[(LayoutModelData, ExtractInstruction)]]): default_path = xml_writer.current_path LOGGER.debug('default_path: %r', default_path) pending_whitespace = '' prev_label: str = '' pending_reset_path: Optional[List[str]] = None for model_data_or_instruction in model_data_or_instruction_iterable: if isinstance(model_data_or_instruction, LayoutModelData): model_data = model_data_or_instruction layout_token = model_data.layout_token assert (layout_token is not None) prefixed_label = get_model_data_label(model_data) (prefix, label) = get_split_prefix_label((prefixed_label or '')) xml_element_path = self.get_training_xml_path_for_label(label, current_path=xml_writer.current_path) reset_path = self.get_reset_training_xml_path_for_label(label=label, prefix=prefix) if (pending_reset_path is not None): reset_path = pending_reset_path pending_reset_path = None LOGGER.debug('label: %r (%r: %r; reset_path=%r)', label, prefix, xml_element_path, reset_path) if (reset_path is not None): xml_writer.require_path(reset_path) elif ((prev_label not in OTHER_LABELS) and pending_whitespace and (not is_same_or_parent_path_of(xml_writer.current_path, xml_element_path))): LOGGER.debug('closing element before adding whitespace, %r -> %r', xml_writer.current_path, xml_element_path) xml_writer.require_path(xml_writer.current_path[:(- 1)]) elif ((prefix == 'B') and (label not in OTHER_LABELS)): xml_writer.require_path(xml_element_path[:(- 1)]) xml_writer.require_path_or_below(xml_element_path) xml_writer.append_text(pending_whitespace) pending_whitespace = '' xml_writer.require_path(xml_element_path) xml_writer.append_text(layout_token.text) pending_whitespace = layout_token.whitespace prev_label = label elif isinstance(model_data_or_instruction, ResetExtractInstruction): pending_reset_path = model_data_or_instruction.reset_element_path elif isinstance(model_data_or_instruction, NewLineExtractInstruction): xml_writer.append(self.element_maker('lb')) pending_whitespace = '\n' xml_writer.require_path(default_path) xml_writer.append_text(pending_whitespace) def iter_model_data_or_instruction_for_model_data_iterable(self, model_data_iterable: Iterable[LayoutModelData]) -> Iterable[Union[(LayoutModelData, ExtractInstruction)]]: return iter_model_data_with_new_line_instruction(model_data_iterable) def write_xml_for_model_data_iterable(self, xml_writer: XmlTreeWriter, model_data_iterable: Iterable[LayoutModelData]): self.write_xml_for_model_data_with_instructions_iterable(xml_writer, self.iter_model_data_or_instruction_for_model_data_iterable(model_data_iterable)) def _get_xml_writer(self) -> XmlTreeWriter: return XmlTreeWriter(self.element_maker(self.root_tag), element_maker=self.element_maker) def get_post_processed_xml_root(self, xml_root: etree.ElementBase): return xml_root def get_training_tei_xml_for_multiple_model_data_iterables(self, model_data_iterables: Iterable[Iterable[LayoutModelData]]) -> etree.ElementBase: xml_writer = self._get_xml_writer() xml_writer.require_path(self.root_parent_training_xml_element_path) for model_data_iterable in model_data_iterables: xml_writer.require_path(self.root_parent_training_xml_element_path) xml_writer.require_path(self.root_training_xml_element_path) self.write_xml_for_model_data_iterable(xml_writer, model_data_iterable=model_data_iterable) return self.get_post_processed_xml_root(xml_writer.root) def get_training_tei_xml_for_model_data_iterable(self, model_data_iterable: Iterable[LayoutModelData]) -> etree.ElementBase: return self.get_training_tei_xml_for_multiple_model_data_iterables([model_data_iterable])
def password(v): if ((v == '\n') or (v == ' ')): return 'Password cannot be a newline or space!' if (9 <= len(v) <= 20): if re.search('(.)\\1\\1', v): return 'Weak Password: Same character repeats three or more times in a row' if re.search('(..)(.*?)\\1', v): return 'Weak password: Same string pattern repetition' else: return 'Strong Password!' else: return 'Password length must be 9-20 characters!'
def build_integrations_manifest(overwrite: bool, rule_integrations: list=[], integration: str=None) -> None: def write_manifests(integrations: dict) -> None: manifest_file = gzip.open(MANIFEST_FILE_PATH, 'w+') manifest_file_bytes = json.dumps(integrations).encode('utf-8') manifest_file.write(manifest_file_bytes) manifest_file.close() if overwrite: if MANIFEST_FILE_PATH.exists(): MANIFEST_FILE_PATH.unlink() final_integration_manifests = ({integration: {} for integration in rule_integrations} or {integration: {}}) rule_integrations = (rule_integrations or [integration]) for integration in rule_integrations: integration_manifests = get_integration_manifests(integration) for manifest in integration_manifests: validated_manifest = IntegrationManifestSchema(unknown=EXCLUDE).load(manifest) package_version = validated_manifest.pop('version') final_integration_manifests[integration][package_version] = validated_manifest if (overwrite and rule_integrations): write_manifests(final_integration_manifests) elif (integration and (not overwrite)): manifest_file = gzip.open(MANIFEST_FILE_PATH, 'rb') manifest_file_bytes = manifest_file.read() manifest_file_contents = json.loads(manifest_file_bytes.decode('utf-8')) manifest_file.close() manifest_file_contents[integration] = final_integration_manifests[integration] write_manifests(manifest_file_contents) print(f'final integrations manifests dumped: {MANIFEST_FILE_PATH}')
class TestTrack(): def test_finds_default_challenge(self): default_challenge = track.Challenge('default', description='default challenge', default=True) another_challenge = track.Challenge('other', description='non-default challenge', default=False) assert (default_challenge == track.Track(name='unittest', description='unittest track', challenges=[another_challenge, default_challenge]).default_challenge) def test_default_challenge_none_if_no_challenges(self): assert (track.Track(name='unittest', description='unittest track', challenges=[]).default_challenge is None) def test_finds_challenge_by_name(self): default_challenge = track.Challenge('default', description='default challenge', default=True) another_challenge = track.Challenge('other', description='non-default challenge', default=False) assert (another_challenge == track.Track(name='unittest', description='unittest track', challenges=[another_challenge, default_challenge]).find_challenge_or_default('other')) def test_uses_default_challenge_if_no_name_given(self): default_challenge = track.Challenge('default', description='default challenge', default=True) another_challenge = track.Challenge('other', description='non-default challenge', default=False) assert (default_challenge == track.Track(name='unittest', description='unittest track', challenges=[another_challenge, default_challenge]).find_challenge_or_default('')) def test_does_not_find_unknown_challenge(self): default_challenge = track.Challenge('default', description='default challenge', default=True) another_challenge = track.Challenge('other', description='non-default challenge', default=False) with pytest.raises(exceptions.InvalidName) as exc: track.Track(name='unittest', description='unittest track', challenges=[another_challenge, default_challenge]).find_challenge_or_default('unknown-name') assert (exc.value.args[0] == 'Unknown challenge [unknown-name] for track [unittest]') def test_index_names(self): idx1 = track.Index(name='foo') idx2 = track.Index(name='bar') track_ = track.Track(name='unittest', description='unittest track', indices=[idx1, idx2]) assert (track_.index_names() == ['foo', 'bar'])
def upgrade(): op.execute('COMMIT') try: op.execute('SHOW bdr.permit_ddl_locking') op.execute('SET LOCAL bdr.permit_ddl_locking = true') except exc.ProgrammingError: pass op.execute("UPDATE updates SET request = 'stable' WHERE request = 'batched'") op.execute('ALTER TYPE ck_update_request RENAME TO ck_update_request_old') op.execute("CREATE TYPE ck_update_request AS ENUM('testing', 'obsolete', 'unpush', 'revoke', 'stable')") op.execute('ALTER TABLE updates ALTER COLUMN request TYPE ck_update_request USING request::text::ck_update_request') op.execute('ALTER TABLE composes ALTER COLUMN request TYPE ck_update_request USING request::text::ck_update_request') op.execute('DROP TYPE ck_update_request_old')
class ForumSerializerss(serializers.ModelSerializer): authors = UserSerializer(read_only=True) category = Forum_plateSerializers(read_only=True) comment_set = CommentSerializers(many=True) add_time = serializers.DateTimeField(format='%Y-%m-%d %H:%M:%S', required=False, read_only=True) class Meta(): model = Forum fields = '__all__'