Datasets:

semeru

/

Galeras-3k_deduped

like 0

apps/applications/models/application.py

fix: 应用树隐藏mongodb节点

jumpserver

Python

application.py

def create_types_tree_nodes(cls, pid, counts, show_empty=True, show_count=True): nodes = [] temp_pid = pid type_category_mapper = const.AppType.type_category_mapper() types = const.AppType.type_category_mapper().keys() for tp in types: # TODO: Temporary exclude mongodb if tp == const.AppType.mongodb: continue if not settings.XPACK_ENABLED and const.AppType.is_xpack(tp): continue category = type_category_mapper.get(tp) pid = cls.create_tree_id(pid, 'category', category.value) i = cls.create_tree_id(pid, 'type', tp.value) node = cls.create_choice_node( tp, i, pid, tp='type', counts=counts, opened=False, show_empty=show_empty, show_count=show_count ) pid = temp_pid if not node: continue nodes.append(node) return nodes

60edbb36a19188570113f9b5b2b60d01412a280d

https://github.com/jumpserver/jumpserver.git

def create_types_tree_nodes(cls, pid, counts, show_empty=True, show_count=True): nodes = [] temp_pid = pid type_category_mapper = const.AppType.type_category_mapper() types = const.AppType.type_category_mapper().keys() for tp in types: # TODO: Temporary exclude mongodb if tp == const.AppType.mongodb: continue if not settings.XPACK_ENABLED and const.AppType.is_xpack(tp): continue category = type_category_mapper.get(tp) pid = cls.create_tree_id(pid, 'category', category.value) i = cls.create_tree_id(pid, 'type', tp.value) node = cls.create_choice_node( tp, i, pid, tp='type', counts=counts, opened=False, show_empty=show_empty, show_count=show_count ) pid = temp_pid i

create_types_tree_nodes

test/test_prototype_transforms.py

rename features._Feature to datapoints._Datapoint (#7002) * rename features._Feature to datapoints.Datapoint * _Datapoint to Datapoint * move is_simple_tensor to transforms.utils * fix CI * move Datapoint out of public namespace

vision

Python

test_prototype_transforms.py

def test__transform(self, p, transform_cls, func_op_name, kwargs, mocker): transform = transform_cls(p=p, **kwargs) fn = mocker.patch(f"torchvision.prototype.transforms.functional.{func_op_name}") inpt = mocker.MagicMock(spec=datapoints.Image) _ = transform(inpt) if p > 0.0: fn.assert_called_once_with(inpt, **kwargs) else: assert fn.call_count == 0

a8007dcdfb5159a711fa343d2ac4bb7df826975f

https://github.com/pytorch/vision.git

def test__transform(self, p, transform_cls, func_op_name, kwargs, mocker): transform = transform_cls(p=p, **kwargs) fn = mocker.patch(f"torchvision.prototype.transforms.functional.{func_op_name}") inpt = mocker.MagicMock(

test__transform

python/ray/data/tests/test_context_propagation.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

Python

test_context_propagation.py

def test_map_batches(ray_start_regular_shared): context = DatasetContext.get_current() context.foo = 70003 ds = ray.data.range(1).map_batches(lambda x: [DatasetContext.get_current().foo]) assert ds.take_all()[0] == 70003

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

https://github.com/ray-project/ray.git

def test_map_batches(ray_start_regular_shared): context = DatasetContext.get_current() context.foo = 70003 ds = ray.data.range(1).map_batches(lambda x: [DatasetContext.get_current().foo]) assert ds.take_all()[0] == 70003

test_map_batches

homeassistant/components/zha/core/channels/lighting.py

ZHA light entity cleanup (#75573) * use base class attributes * initial hue and saturation support * spec is 65536 not 65535 * fixes * enhanced current hue * fix comparison * clean up * fix channel test * oops * report enhanced current hue

core

Python

lighting.py

def hs_supported(self) -> bool: return ( self.zcl_color_capabilities is not None and lighting.Color.ColorCapabilities.Hue_and_saturation in self.zcl_color_capabilities )

04c6b9c51963418ffebddc7753939700fbea7e42

https://github.com/home-assistant/core.git

def hs_supported(self) -> bool: return ( self.zcl_color_capabilities is not None and lighting.Color.ColorCapabilities.Hue_and_saturation in self.zcl_color_capabilities

hs_supported

python/ray/tune/insufficient_resources_manager.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

Python

insufficient_resources_manager.py

def _get_insufficient_resources_warning_threshold() -> float: if is_ray_cluster(): return float( os.environ.get( "TUNE_WARN_INSUFFICENT_RESOURCE_THRESHOLD_S_AUTOSCALER", "60" ) ) else: # Set the default to 10s so that we don't prematurely determine that # a cluster cannot fulfill the resources requirements. # TODO(xwjiang): Change it back once #18608 is resolved. return float(os.environ.get("TUNE_WARN_INSUFFICENT_RESOURCE_THRESHOLD_S", "60")) # TODO(xwjiang): Consider having a help page with more detailed instructions. @lru_cache()

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

@lru_cache()

https://github.com/ray-project/ray.git

def _get_insufficient_resources_warning_threshold() -> float: if is_ray_cluster(): return float( os.environ.get( "TUNE_WARN_INSUFFICENT_RESOURCE_THRESHOLD_S_AUTOSCALER", "60" ) ) else: # Set the default to 10s so that we don't prematurely determine that # a cluster cannot fulfill the resources requirements. # TODO(xwjiang): Change it back once #18608 is resolved. return float(os.environ.get("TUNE_WARN_INSUFFICENT_RESOURCE_THRESHOLD_S", "60")) # TODO(x

_get_insufficient_resources_warning_threshold

homeassistant/components/ecobee/notify.py

Load ecobee notify platform via discovery (#78558) * Fix ecobee notify platform KeyError * set up notify platform via discovery * address comments * fix isort * Apply suggestions from code review Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

core

Python

notify.py

def send_message(self, message="", **kwargs): targets = kwargs.get(ATTR_TARGET) if not targets: raise ValueError("Missing required argument: target") for target in targets: thermostat_index = int(target) self.ecobee.send_message(thermostat_index, message)

da099532fe837604383d5e195be4a0320941a87c

https://github.com/home-assistant/core.git

def send_message(self, message="", **kwargs): targets = kwargs.get(ATTR_TARGET) if not targets: raise ValueError("Missing required argument: target") for target in targets: thermostat_index = int(target) self.ecobee.send_message(thermostat_index, mess

send_message

sklearn/neighbors/tests/test_neighbors.py

TST use global_dtype in sklearn/neighbors/tests/test_neighbors.py (#22663) Co-authored-by: Jérémie du Boisberranger Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

scikit-learn

Python

test_neighbors.py

def test_same_knn_parallel(algorithm): X, y = datasets.make_classification( n_samples=30, n_features=5, n_redundant=0, random_state=0 ) X_train, X_test, y_train, y_test = train_test_split(X, y) clf = neighbors.KNeighborsClassifier(n_neighbors=3, algorithm=algorithm) clf.fit(X_train, y_train) y = clf.predict(X_test) dist, ind = clf.kneighbors(X_test) graph = clf.kneighbors_graph(X_test, mode="distance").toarray() clf.set_params(n_jobs=3) clf.fit(X_train, y_train) y_parallel = clf.predict(X_test) dist_parallel, ind_parallel = clf.kneighbors(X_test) graph_parallel = clf.kneighbors_graph(X_test, mode="distance").toarray() assert_array_equal(y, y_parallel) assert_allclose(dist, dist_parallel) assert_array_equal(ind, ind_parallel) assert_allclose(graph, graph_parallel) @pytest.mark.parametrize("algorithm", ALGORITHMS)

7931262d737d89b795d1ea5790c44003c13c741c

@pytest.mark.parametrize("algorithm", ALGORITHMS)

https://github.com/scikit-learn/scikit-learn.git

def test_same_knn_parallel(algorithm): X, y = datasets.make_classification( n_samples=3

test_same_knn_parallel

tests/snuba/api/endpoints/test_organization_events.py

fix(tests): Fix dnd backend test flakes (#37916) This PR fixes 3 major flakes: Fixes SENTRY-TESTS-3J5: Just sort the project id order Fixes SENTRY-TESTS-3HQ: Flakes because we calculate the retention in the test once and the value returned in the response is calculated a little while after. We don't need to test for seconds granularity so replacing seconds to 0. Fixes SENTRY-TESTS-3J0: Successively calling before_now results in some flakes particularly in tests that are calculating aggregates on transaction.duration. Introduced a load_data method that takes a datetime object timestamp and a timedelta duration calculates the offset based on timestamp to get start_timestamp.

sentry

Python

test_organization_events.py

def test_count_miserable_new_alias_field(self): ProjectTransactionThreshold.objects.create( project=self.project, organization=self.project.organization, threshold=400, metric=TransactionMetric.DURATION.value, ) events = [ ("one", 400), ("one", 400), ("two", 3000), ("two", 3000), ("three", 300), ("three", 3000), ] for idx, event in enumerate(events): data = self.load_data( timestamp=before_now(minutes=(10 + idx)), duration=timedelta(milliseconds=event[1]), ) data["event_id"] = f"{idx}" * 32 data["transaction"] = f"/count_miserable/horribilis/{event[0]}" data["user"] = {"email": f"{idx}@example.com"} self.store_event(data, project_id=self.project.id) query = { "field": [ "transaction", "count_miserable(user)", ], "query": "event.type:transaction", "project": [self.project.id], "sort": "count_miserable_user", } response = self.do_request( query, ) assert response.status_code == 200, response.content assert len(response.data["data"]) == 3 data = response.data["data"] assert data[0]["count_miserable(user)"] == 0 assert data[1]["count_miserable(user)"] == 1 assert data[2]["count_miserable(user)"] == 2 query["query"] = "event.type:transaction count_miserable(user):>0" response = self.do_request( query, ) assert response.status_code == 200, response.content assert len(response.data["data"]) == 2 data = response.data["data"] assert abs(data[0]["count_miserable(user)"]) == 1 assert abs(data[1]["count_miserable(user)"]) == 2

ab993b32614bb83d17d10e1041817e43dd6f5980

https://github.com/getsentry/sentry.git

def test_count_miserable_new_alias_field(self): ProjectTransactionThreshold.objects.create( project=self.project, organization=self.project.organization, threshold=400, metric=TransactionMetric.DURATION.value, ) events = [ ("one", 400), ("one", 400), ("two", 3000), ("two", 3000), ("three", 300), ("three", 3000), ] for idx, event in enumerate(events): data = self.load_data( timestamp=before_now(minutes=(10 + idx)), duration=timedelta(milliseconds=event[1]), ) data["event_id"] = f"{idx}" * 32 data["transaction"] = f"/count_miserable/horribilis/{event[0]}" data["user"] = {"email": f"{idx}@example.com"} self.store_event(data, project_id=self.project.id) query = { "field": [ "transaction", "count_miserable(user)", ], "query": "event.type:transaction", "project": [self.project.id], "sort": "count_miserable_user", } response = self.do_request( query, ) assert response.status_code == 200, response.content assert len(response.data["data"]) == 3 data = response.data["data"] assert data[0]["count_miserable(user)"] == 0 assert data[1]["count_miserable(user)"] == 1 assert data[2]["count_miserable(user)"] == 2 query["query"] = "event.type:trans

test_count_miserable_new_alias_field

openbb_terminal/terminal_controller.py

Add intro command + improve plot style + internationalisation consistency (#2899) * improve style of plots * remove the blend which doesnt look nice in some machines * remove translation for arguments to be coherent * Add intro command * add check to understand if its first time user to run intro by default * intro doesnt require docs * silly catch * fix line length * anoter lengthy line * unused import * unused import * words * allow to quit earlier * style * fix thing for u didi * actual fix * last try Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: james <jmaslek11@gmail.com>

OpenBBTerminal

Python

terminal_controller.py

def call_intro(self, _): console.print(panel.Panel("[purple]Welcome to the OpenBB Terminal.[/purple]")) console.print( "\nThe following walkthrough will guide you towards making the most out of the OpenBB Terminal.\n\n" "Press Enter to continue or 'q' followed by Enter to exit." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#1 - Commands vs menu.[/purple]")) console.print( "\nMenus are a collection of 'commands' and 'sub-menus'.\n" "You can identify them through their distinct color and a '>' at the beginning of the line\n\n" "For instance:\n" "[menu]> stocks access historical pricing data, options, sector [/menu]" "[menu]and industry, and overall due diligence [/menu]\n\n\n" "Commands are expected to return data either as a chart or table.\n" "You can identify them through their distinct color\n\n" "For instance:\n" "[cmds]> news display news articles based on term and data sources [/cmds]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#2 - Using commands[/purple]")) console.print( "\nCommands throughout the terminal can have additional arguments.\n\n" "Let's say that in the current menu, you want to have more information about the command 'news'. \n\n" "You can either see the available arguments in the terminal, using: [param]news -h[/param]\n\n", "or you can find out more about it with an output example on the browser, using: [param]about news[/param]", ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#3 - Setting API Keys[/purple]")) console.print( "\nThe OpenBB Terminal does not own any of the data you have access to.\n\n" "Instead, we provide the infrastructure to access over 100 different data sources from a single location.\n\n" "Thus, it is necessary for each user to set their own API keys for the various third party sources\n\n" "You can find more about this on the '[param]keys[/param]' menu.\n\n" "For many commands, there are multiple data sources that can be selected.\n\n" "The help menu shows the data sources supported by each command.\n\n" "For instance:\n" "[cmds] load load a specific stock ticker and additional info for analysis [/cmds]" "[src][YahooFinance, IEXCloud, AlphaVantage, Polygon, EODHD] [/src]\n\n" "The user can go into the '[param]sources[/param]' menu and select their preferred default data source." ) if input("") == "q": return console.print("\n") console.print( panel.Panel("[purple]#4 - Symbol dependent menus and commands[/purple]") ) console.print( "\nThroughout the terminal, you will see commands and menus greyed out.\n\n" "These menus or commands cannot be accessed until an object is loaded.\n\n" "Let's take as an example the '[param]stocks[/param]' menu.\n\n" "You will see that the command '[param]disc[/param]' is available as its goal is to discover new tickers:\n" "[menu]> stocks access historical pricing data, options, sector [/menu]\n\n" "On the other hand, '[param]fa[/param]' menu (fundamental analysis) requires a ticker to be loaded.\n\n" "And therefore, appears as:\n" "[dim]> fa fundamental analysis of loaded ticker [/dim]\n\n" "Once a ticker is loaded with: [param]load TSLA[/param]\n\n" "The '[param]fa[/param]' menu will be available as:\n" "[menu]> fa fundamental analysis of loaded ticker [/menu]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#5 - Terminal Navigation[/purple]")) console.print( "\nThe terminal has a tree like structure, where menus branch off into new menus.\n\n" "The users current location is displayed before the text prompt.\n\n" "For instance, if the user is inside the menu disc which is inside stocks, the following prompt " "will appear: \n2022 Oct 18, 21:53 (🦋) [param]/stocks/disc/[/param] $\n\n" "If the user wants to go back to the menu above, all they need to do is type '[param]q[/param]'.\n\n" "If the user wants to go back to the home of the terminal, they can type '[param]/[/param]' instead.\n\n" "Note: Always type '[param]h[/param]' to know what commands are available in each menu" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#6 - Command Pipeline[/purple]")) console.print( "\nThe terminal offers the capability of allowing users to speed up their navigation and command execution." "\n\nTherefore, typing the following prompt is valid:\n" "2022 Oct 18, 21:53 (🦋) / $ [param]stocks/load TSLA/dd/pt[/param]\n\n" "In this example, the terminal - in a single action - will go into '[param]stocks[/param]' menu, " "run command '[param]load[/param]' with '[param]TSLA[/param]' as input, \n" "go into sub-menu '[param]dd[/param]' (due diligence) and run the command '[param]pt[/param]' (price target)." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#6 - OpenBB Scripts[/purple]")) console.print( "\nThe command pipeline capability is great, but the user experience wasn't great copy-pasting large " "lists of commands.\n\n" "We allow the user to create a text file of the form:\n\n" "[param]FOLDER_PATH/my_script.openbb[/param]\n" "stocks\nload TSLA\ndd\npt\n\n" "which can be run through the '[param]exe[/param]' command in the home menu, with:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]exe FOLDER_PATH/my_script.openbb[/param]\n\n" ) if input("") == "q": return console.print("\n") console.print( panel.Panel("[purple]#7 - OpenBB Scripts with Arguments[/purple]") ) console.print( "\nThe user can create a script that includes arguments for the commands.\n\n" "Example:\n\n" "[param]FOLDER_PATH/my_script_with_variable_input.openbb[/param]\n" "stocks\n# this is a comment\nload $ARGV[0]\ndd\npt\nq\nload $ARGV[1]\ncandle\n\n" "and then, if this script is run with:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]exe FOLDER_PATH/my_script_with_variable_input.openbb " "-i AAPL,MSFT[/param]\n\n" "This means that the [param]pt[/param] will run on [param]AAPL[/param] while " "[param]candle[/param] on [param]MSFT[/param]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#8 - OpenBB Script Generation/purple]")) console.print( "\n" "To make it easier for users to create scripts, we have created a " "command that 'records' user commands " "directly into a script.\n\n" "From the home menu, the user can run:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]record[/param]\n\n" "and then perform your typical investment research workflow before entering\n\n" "2022 Oct 18, 22:33 (🦋) / $ [param]stop[/param]\n\n" "After stopping, the script will be saved to the 'scripts' folder." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#9 - Terminal Customization[/purple]")) console.print( "\nUsers should explore the [param]settings[/param] and [param]featflags[/param] menus " "to configure their terminal.\n\n" "The fact that our terminal is fully open source allows users to be able to customize " "anything they want.\n\n" "If you are interested in contributing to the project, please check:\n" "[param]https://github.com/OpenBB-finance/OpenBBTerminal[/param]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#10 - Support[/purple]")) console.print( "\n" "We are nothing without our community, hence we put a lot of effort in being here for you.\n\n" "If you find any bug that you wish to report to improve the terminal you can do so with:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]support CMD[/param]\n\n" "which should open a form in your browser where you can report the bug in said 'CMD'.\n\n" "If you want to know more, or have any further question. Please join us on Discord:\n" "[param]https://openbb.co/discord[/param]" )

3762693df7a1f8cdfeba5e14c4438f993a2eead0

https://github.com/OpenBB-finance/OpenBBTerminal.git

def call_intro(self, _): console.print(panel.Panel("[purple]Welcome to the OpenBB Terminal.[/purple]")) console.print( "\nThe following walkthrough will guide you towards making the most out of the OpenBB Terminal.\n\n" "Press Enter to continue or 'q' followed by Enter to exit." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#1 - Commands vs menu.[/purple]")) console.print( "\nMenus are a collection of 'commands' and 'sub-menus'.\n" "You can identify them through their distinct color and a '>' at the beginning of the line\n\n" "For instance:\n" "[menu]> stocks access historical pricing data, options, sector [/menu]" "[menu]and industry, and overall due diligence [/menu]\n\n\n" "Commands are expected to return data either as a chart or table.\n" "You can identify them through their distinct color\n\n" "For instance:\n" "[cmds]> news display news articles based on term and data sources [/cmds]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#2 - Using commands[/purple]")) console.print( "\nCommands throughout the terminal can have additional arguments.\n\n" "Let's say that in the current menu, you want to have more information about the command 'news'. \n\n" "You can either see the available arguments in the terminal, using: [param]news -h[/param]\n\n", "or you can find out more about it with an output example on the browser, using: [param]about news[/param]", ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#3 - Setting API Keys[/purple]")) console.print( "\nThe OpenBB Terminal does not own any of the data you have access to.\n\n" "Instead, we provide the infrastructure to access over 100 different data sources from a single location.\n\n" "Thus, it is necessary for each user to set their own API keys for the various third party sources\n\n" "You can find more about this on the '[param]keys[/param]' menu.\n\n" "For many commands, there are multiple data sources that can be selected.\n\n" "The help menu shows the data sources supported by each command.\n\n" "For instance:\n" "[cmds] load load a specific stock ticker and additional info for analysis [/cmds]" "[src][YahooFinance, IEXCloud, AlphaVantage, Polygon, EODHD] [/src]\n\n" "The user can go into the '[param]sources[/param]' menu and select their preferred default data source." ) if input("") == "q": return console.print("\n") console.print( panel.Panel("[purple]#4 - Symbol dependent menus and commands[/purple]") ) console.print( "\nThroughout the terminal, you will see commands and menus greyed out.\n\n" "These menus or commands cannot be accessed until an object is loaded.\n\n" "Let's take as an example the '[param]stocks[/param]' menu.\n\n" "You will see that the command '[param]disc[/param]' is available as its goal is to discover new tickers:\n" "[menu]> stocks access historical pricing data, options, sector [/menu]\n\n" "On the other hand, '[param]fa[/param]' menu (fundamental analysis) requires a ticker to be loaded.\n\n" "And therefore, appears as:\n" "[dim]> fa fundamental analysis of loaded ticker [/dim]\n\n" "Once a ticker is loaded with: [param]load TSLA[/param]\n\n" "The '[param]fa[/param]' menu will be available as:\n" "[menu]> fa fundamental analysis of loaded ticker [/menu]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#5 - Terminal Navigation[/purple]")) console.print( "\nThe terminal has a tree like structure, where menus branch off into new menus.\n\n" "The users current location is displayed before the text prompt.\n\n" "For instance, if the user is inside the menu disc which is inside stocks, the following prompt " "will appear: \n2022 Oct 18, 21:53 (🦋) [param]/stocks/disc/[/param] $\n\n" "If the user wants to go back to the menu above, all they need to do is type '[param]q[/param]'.\n\n" "If the user wants to go back to the home of the terminal, they can type '[param]/[/param]' instead.\n\n" "Note: Always type '[param]h[/param]' to know what commands are available in each menu" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#6 - Command Pipeline[/purple]")) console.print( "\nThe terminal offers the capability of allowing users to speed up their navigation and command execution." "\n\nTherefore, typing the following prompt is valid:\n" "2022 Oct 18, 21:53 (🦋) / $ [param]stocks/load TSLA/dd/pt[/param]\n\n" "In this example, the terminal - in a single action - will go into '[param]stocks[/param]' menu, " "run command '[param]load[/param]' with '[param]TSLA[/param]' as input, \n" "go into sub-menu '[param]dd[/param]' (due diligence) and run the command '[param]pt[/param]' (price target)." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#6 - OpenBB Scripts[/purple]")) console.print( "\nThe command pipeline capability is great, but the user experience wasn't great copy-pasting large " "lists of commands.\n\n" "We allow the user to create a text file of the form:\n\n" "[param]FOLDER_PATH/my_script.openbb[/param]\n" "stocks\nload TSLA\ndd\npt\n\n" "which can be run through the '[param]exe[/param]' command in the home menu, with:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]exe FOLDER_PATH/my_script.openbb[/param]\n\n" ) if input("") == "q": return console.print("\n") console.print( panel.Panel("[purple]#7 - OpenBB Scripts with Arguments[/purple]") ) console.print( "\nThe user can create a script that includes arguments for the commands.\n\n" "Example:\n\n" "[param]FOLDER_PATH/my_script_with_variable_input.openbb[/param]\n" "stocks\n# this is a comment\nload $ARGV[0]\ndd\npt\nq\nload $ARGV[1]\ncandle\n\n" "and then, if this script is run with:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]exe FOLDER_PATH/my_script_with_variable_input.openbb " "-i AAPL,MSFT[/param]\n\n" "This means that the [param]pt[/param] will run on [param]AAPL[/param] while " "[param]candle[/param] on [param]MSFT[/param]" ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#8 - OpenBB Script Generation/purple]")) console.print( "\n" "To make it easier for users to create scripts, we have created a " "command that 'records' user commands " "directly into a script.\n\n" "From the home menu, the user can run:\n" "2022 Oct 18, 22:33 (🦋) / $ [param]record[/param]\n\n" "and then perform your typical investment research workflow before entering\n\n" "2022 Oct 18, 22:33 (🦋) / $ [param]stop[/param]\n\n" "After stopping, the script will be saved to the 'scripts' folder." ) if input("") == "q": return console.print("\n") console.print(panel.Panel("[purple]#9 - Terminal Customization[/purple]")) console.print( "\nUsers should explore the [param]settings[/param] and [param]featflags[/param] menus " "to configure their terminal.\n\n" "The fact that our terminal is fully open source allows users to be able to customize " "anything they want.\n\n" "If you are interested in contributing to the project, please check:\n" "[param]https://github.com/OpenBB-finance/Open

call_intro

mindsdb/integrations/mlflow_handler/mlflow/mlflow_integration.py

fix tests and reformat

mindsdb

Python

mlflow_integration.py

def connect(self, **kwargs) -> Dict[str, int]: # noqa print(kwargs) self.mlflow_server_url = kwargs['mlflow_server_url'] self.mlflow_server_path = kwargs['model_registry_path'] self.connection = MlflowClient(self.mlflow_server_url, self.mlflow_server_path) self.storage = SqliteStorageHandler(context=self.name, config=kwargs['config']) return self.check_status()

0fd3b436c38f38bcae6fed9e14dc4d2a12e90793

https://github.com/mindsdb/mindsdb.git

def connect(self, **kwargs) -> Dict[str, int]: # noqa print(kwargs) self.mlflow_server_url = kwargs['mlflow_server_url'] self.mlflow_server_path = kwargs['model_registry_path'] self.connection = MlflowClient(self.mlflow_server_url, self.mlflow_server_path) self.storage = SqliteStorageHandler(context=self.name, config=kwarg

connect

python/ray/serve/handle.py

Revert "[all_tests][python] Remove calling of get_event_loop from pyt… (#30382) This reverts commit 784e66b.

ray

Python

handle.py

def _make_router(self) -> Router: return Router( self.controller_handle, self.deployment_name, event_loop=asyncio.get_event_loop(), )

c7115135ea131b29bd6ff3d32e4f90297e5e770e

https://github.com/ray-project/ray.git

def _make_router(self) -> Router: ret

_make_router

src/sentry/models/deploy.py

feat(release-activity): backend support for tracking release activity (#36608) Alpha Workflow 2.0 feature for tracking activity when an issue occurs in an active release-deployment time-window. This adds the backend components needed to support surfacing the notification activity in the frontend.

sentry

Python

deploy.py

def notify_if_ready(cls, deploy_id, fetch_complete=False): from sentry.models import ( Activity, Environment, Organization, ReleaseActivity, ReleaseCommit, ReleaseHeadCommit, ) lock_key = cls.get_lock_key(deploy_id) lock = locks.get(lock_key, duration=30, name="deploy_notify") with TimedRetryPolicy(10)(lock.acquire): deploy = cls.objects.filter(id=deploy_id).select_related("release").get() if deploy.notified: return release = deploy.release environment = Environment.objects.get( organization_id=deploy.organization_id, id=deploy.environment_id ) if not fetch_complete: release_has_commits = ReleaseCommit.objects.filter( organization_id=release.organization_id, release=release ).exists() if not release_has_commits: # check if we have head commits, which # would indicate that we're waiting for # fetch_commits to complete if ReleaseHeadCommit.objects.filter( organization_id=release.organization_id, release=release ).exists(): return activity = None for project in deploy.release.projects.all(): activity = Activity.objects.create( type=ActivityType.DEPLOY.value, project=project, ident=Activity.get_version_ident(release.version), data={ "version": release.version, "deploy_id": deploy.id, "environment": environment.name, }, datetime=deploy.date_finished, ) # Somewhat hacky, only send notification for one # Deploy Activity record because it will cover all projects if activity is not None: activity.send_notification() deploy.update(notified=True) # XXX(workflow): delete this after WF 2.0 experiment over try: org = Organization.objects.get_from_cache(id=deploy.organization_id) except Organization.DoesNotExist: org = None if org and features.has("organizations:active-release-monitor-alpha", org): ReleaseActivity.objects.create( type=ReleaseActivityType.DEPLOYED.value, release=release, data={"environment": str(environment.name)}, )

15e21309086e5e97fa66f0d5234cb3110bcf34f1

https://github.com/getsentry/sentry.git

def notify_if_ready(cls, deploy_id, fetch_complete=False): from sentry.models import ( Activity, Environment, Organization, ReleaseActivity, ReleaseCommit, ReleaseHeadCommit, ) lock_key = cls.get_lock_key(deploy_id) lock = locks.get(lock_key, duration=30, name="deploy_notify") with TimedRetryPolicy(10)(lock.acquire): deploy = cls.objects.filter(id=deploy_id).select_related("release").get() if deploy.notified: return release = deploy.release environment = Environment.objects.get( organization_id=deploy.organization_id, id=deploy.environment_id ) if not fetch_complete: release_has_commits = ReleaseCommit.objects.filter( organization_id=release.organization_id, release=release ).exists() if not release_has_commits: # check if we have head commits, which # would indicate that we're waiting for # fetch_commits to complete if ReleaseHeadCommit.objects.filter( organization_id=release.organization_id, release=release ).exists(): return activity = None for project in deploy.release.projects.all(): activity = Activity.objects.create( type=ActivityType.DEPLOY.value, project=project, ident=Activity.get_version_ident(release.version), data={ "version": release.version, "deploy_id": deploy.id, "environment": environment.name, }, datetime=deploy.date_finished, ) # Somewhat hacky, only send notification for one # Deploy Activity record because it will cover all projects if activity is not None: activity.send_notification() deploy.update(notified=True) # XXX(workflow): delete this after WF 2.0 experiment over try: org = Organization.objects.get_from_cache(id=deploy.organization_id) except Organization.DoesNotExist: org = None if org and features.has("organizations:active-release-monitor-alpha", org):

notify_if_ready

tests/unit/keyinput/test_basekeyparser.py

Run scripts/dev/rewrite_enums.py

qutebrowser

Python

test_basekeyparser.py

def test_binding_with_shift(self, prompt_keyparser): for key, modifiers in [(Qt.Key.Key_Y, Qt.KeyboardModifier.NoModifier), (Qt.Key.Key_Shift, Qt.KeyboardModifier.ShiftModifier), (Qt.Key.Key_Y, Qt.KeyboardModifier.ShiftModifier)]: info = keyutils.KeyInfo(key, modifiers) prompt_keyparser.handle(info.to_event()) prompt_keyparser.execute.assert_called_once_with('yank -s', None)

0877fb0d78635692e481c8bde224fac5ad0dd430

https://github.com/qutebrowser/qutebrowser.git

def test_binding_with_shift(self, prompt_keyparser): for key, modifiers in [(Qt.Key.Key_Y, Qt.KeyboardModifier.NoModifier), (Qt.Key.Key_Shift, Qt.KeyboardModifier.ShiftModifier), (Qt.Key.Key_Y, Qt.KeyboardModifier.ShiftModifier)]: info = keyutils.KeyInfo(key

test_binding_with_shift

examples/dev_sandbox.py

Displaying tabs with underline

textual

Python

dev_sandbox.py

def on_mount(self): self.tabs = Tabs( [ Tab("One", name="one"), Tab("Two", name="two"), Tab("Three", name="three"), Tab("Four", name="four"), Tab("Five", name="five"), Tab("Six", name="six"), Tab("Seven", name="seven"), Tab("Eight", name="eight"), ], ) self.tabs.active_tab_name = "one" self.mount( header=self.tabs, content=PanelWidget(), footer=Widget(), sidebar=Widget(), ) BasicApp.run(css_file="dev_sandbox.scss", watch_css=True, log="textual.log")

b2f7c2ac850ab43020706c3e5b6660db1f25507a

https://github.com/Textualize/textual.git

def on_mount(self): self.tabs = Tabs( [ Tab("One", name="one"), Tab("Two", name="two"), Tab("Three", name="three"), Tab("Four", name="four"), Tab("Five", name="five"), Tab("Six", name="six"), Tab("Seven", name="seven"), Tab("Eight", name="eight"), ], ) self.tabs.active_tab_name = "one" sel

on_mount

python3.10.4/Lib/email/message.py

add python 3.10.4 for windows

XX-Net

Python

message.py

def get_filename(self, failobj=None): missing = object() filename = self.get_param('filename', missing, 'content-disposition') if filename is missing: filename = self.get_param('name', missing, 'content-type') if filename is missing: return failobj return utils.collapse_rfc2231_value(filename).strip()

8198943edd73a363c266633e1aa5b2a9e9c9f526

https://github.com/XX-net/XX-Net.git

def get_filename(self, failobj=None): missing = object() filename = self.get_param('filename', missing, 'content-disposition') if filename is missing: filename = self.get_param('name', missing, 'content-type') if filename is missing: return failobj return utils.coll

get_filename

packages/syft/src/syft/core/tensor/tensor.py

working ndept pointer

PySyft

Python

tensor.py

def _object2bytes(self) -> bytes: schema = get_capnp_schema(schema_file="tensor.capnp") tensor_struct: CapnpModule = schema.Tensor # type: ignore tensor_msg = tensor_struct.new_message() # this is how we dispatch correct deserialization of bytes tensor_msg.magicHeader = serde_magic_header(type(self)) chunk_bytes(sy.serialize(self.child, to_bytes=True), "child", tensor_msg) tensor_msg.publicShape = sy.serialize(self.public_shape, to_bytes=True) tensor_msg.publicDtype = self.public_dtype tensor_msg.tagName = self.tag_name return tensor_msg.to_bytes_packed()

0805df03a6a8e068bfbe039e0664a842f50ad5de

https://github.com/OpenMined/PySyft.git

def _object2bytes(self) -> bytes: schema = get_capnp_schema(schema_file="tensor.capnp") tensor_struct: CapnpModule = schema.Tensor # type: ignore tensor_msg = tensor_struct.new_message() # this is how we dispatch correct deserialization of bytes tensor_msg.magicHeader = serde_magic_header(type(self)) chunk_bytes(sy.serialize(self.child, to_bytes=True), "child", tensor_msg) tensor_msg.publicShape = sy.serialize(self.pub

_object2bytes

numpy/polynomial/_polybase.py

MAINT: limit the number of decimals in Polynomial representation (#21654) * limit the number of decimals in Polynomial representation * tests pass * parenthesize exponential notation in polynomials * fixed a long line warning * added polynomial printoptions tests * polynomial printoptions typo fixed * made switch to exp notation in polynomial display more natural * added a test on switching polynomials to exp notation * fixed linter errors/warnings * support for nanstr and infstr printoptions in polynomials * 10^8 threshold for switching to exp notation when displaying polynomials * merged in PR #21696 fixing issue #21695 * made linter happy * made some docstring tests pass * fixed the docs Co-authored-by: Lev Maximov <lev.maximov@gmail.com>

numpy

Python

_polybase.py

def _repr_latex_scalar(x, parens=False): # TODO: we're stuck with disabling math formatting until we handle # exponents in this function return r'\text{{{}}}'.format(pu.format_float(x, parens=parens))

a5535dc6242b0decae1e65a3d4feb220fefedc49

https://github.com/numpy/numpy.git

def _repr_latex_scalar(x, parens=False): # TODO: we're stuck with disabling math formatting until we handle # exponents in this function return r'\text{{{}}}'.format(pu.format_float(x, parens=

_repr_latex_scalar

pipenv/environment.py

Issue 4993 Add standard pre commit hooks and apply linting. (#4994) * Add .pre-commit-config.yaml to the project and exclude tests (for now). This does not include the MyPy linting that pip does but does include everything else.

pipenv

Python

environment.py

def reverse_dependency(cls, node): new_node = { "package_name": node["package_name"], "installed_version": node["installed_version"], "required_version": node["required_version"], } for dependency in node.get("dependencies", []): for dep in cls.reverse_dependency(dependency): new_dep = dep.copy() new_dep["parent"] = (node["package_name"], node["installed_version"]) yield new_dep yield new_node

9a3b3ce70621af6f9adaa9eeac9cf83fa149319c

https://github.com/pypa/pipenv.git

def reverse_dependency(cls, node): new_node = { "package_name": node["package_name"], "installed_version": node["installed_version"], "required_version": node["required_version"], } for dependency in node.get("dependencies", []): for dep in cls.reverse_dependency(dependency): new_dep = dep.copy() new_dep["parent

reverse_dependency

tests/sentry/api/endpoints/test_organization_metric_data.py

fix(tests) - use _indexer_record instead of indexer.record (#35908) fix a test that was added after I branched off and changed this file structure for my feature

sentry

Python

test_organization_metric_data.py

def test_validate_include_meta_not_enabled_by_default(self): self.create_release(version="foo", project=self.project) for tag in ("release", "environment"): _indexer_record(self.project.organization_id, tag) response = self.get_success_response( self.project.organization.slug, project=self.project.id, field="sum(sentry.sessions.session)", groupBy="environment", query="", ) assert response.data["meta"] == []

a8264817cfe5a4c03515869c010c78d04a710f1e

https://github.com/getsentry/sentry.git

def test_validate_include_meta_not_enabled_by_default(self): self.create_release(version="foo", project=self.project) for tag in ("release", "environment"): _indexer_record(self.project.organization_id, tag) response = self.get_success_response( self.project.organiz

test_validate_include_meta_not_enabled_by_default

ppdet/modeling/rbox_utils.py

Refactor rbox (#6704) * refactor rbox * modify the code of save results * fix some problem * add .gitignore in dataset/dota * fix test anno path

PaddleDetection

Python

rbox_utils.py

def rbox2poly_np(rboxes): polys = [] for i in range(len(rboxes)): x_ctr, y_ctr, width, height, angle = rboxes[i][:5] tl_x, tl_y, br_x, br_y = -width / 2, -height / 2, width / 2, height / 2 rect = np.array([[tl_x, br_x, br_x, tl_x], [tl_y, tl_y, br_y, br_y]]) R = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]]) poly = R.dot(rect) x0, x1, x2, x3 = poly[0, :4] + x_ctr y0, y1, y2, y3 = poly[1, :4] + y_ctr poly = np.array([x0, y0, x1, y1, x2, y2, x3, y3], dtype=np.float32) poly = get_best_begin_point_single(poly) polys.append(poly) polys = np.array(polys) return polys

e55e41945d42db787a0f7c557d53d06a6b24536b

https://github.com/PaddlePaddle/PaddleDetection.git

def rbox2poly_np(rboxes): polys = [] for i in range(len(rboxes)): x_ctr, y_ctr, width, height, angle = rboxes[i][:5] tl_x, tl_y, br_x, br_y = -width / 2, -height / 2, width / 2, height / 2 rect = np.array([[tl_x, br_x, br_x, tl_x], [tl_y, tl_y, br_y, br_y]]) R = np.array([[np.cos(angle), -np.sin(angle)], [np.sin(angle), np.cos(angle)]]) poly = R.dot(rect) x0, x1, x2, x3 = poly[0, :4] + x_ctr y0, y1, y

rbox2poly_np

tests/io/test_sql.py

Add ability to read-write to SQL databases. (#4928) * Add ability to read-write to SQL databases. * Fix issue where pandas<1.4.0 doesn't return the number of rows * Fix issue where connections were not closed properly * Apply suggestions from code review Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> * Change according to reviews * Change according to reviews * Inherit from AbstractDatasetInputStream in SqlDatasetReader * Revert typing in SQLDatasetReader as we do not support Connexion * Align API with Pandas/Daskk * Update tests * Update docs * Update some more tests * Missing comma * Small docs fix * Style * Update src/datasets/arrow_dataset.py Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> * Update src/datasets/packaged_modules/sql/sql.py Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> * Address some comments * Address the rest * Improve tests * sqlalchemy required tip Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> Co-authored-by: mariosasko <mariosasko777@gmail.com>

datasets

Python

test_sql.py

def iter_sql_file(sqlite_path): with contextlib.closing(sqlite3.connect(sqlite_path)) as con: cur = con.cursor() cur.execute("SELECT * FROM dataset") for row in cur: yield row @require_sqlalchemy

d7dfbc83d68e87ba002c5eb2555f7a932e59038a

@require_sqlalchemy

https://github.com/huggingface/datasets.git

def iter_sql_file(sqlite_path): with contextlib.closing(sqlite3.connect(sqlite_path)) as con: cur = con.cursor() cur.execute("SELECT * FROM dataset") for row in cur: yield row

iter_sql_file

src/sentry/integrations/vercel/webhook.py

chore(vercel): Remove deprecated project webhooks (#36260) This PR fulfills a plan from August 2021 in which Vercel had deprecated project webhooks and we held onto compatability for a fair bit longer than expected. We will continue to support the /delete route since existing integrations for self hosted users should still work, but we can now update the self hosted docs to use /webhook as is the case for most of our integrations.

sentry

Python

webhook.py

def verify_signature(request): signature = request.META.get("HTTP_X_VERCEL_SIGNATURE") secret = options.get("vercel.client-secret") expected = hmac.new( key=secret.encode("utf-8"), msg=bytes(request.body), digestmod=hashlib.sha1 ).hexdigest() return constant_time_compare(expected, signature)

fe544b17a269e5ff6f86208dcf38c492f904dbb7

https://github.com/getsentry/sentry.git

def verify_signature(request): signature = request.META.get("HTTP_X_VERCEL_SIGNATURE") secret = options.get("vercel.client-secret") expected = hmac.new( key=secret.encode("utf-8"), msg=bytes(request.body), digestmod=hashlib.sha1 ).hexdigest() return constant_time_compare(expected, sig

verify_signature

keras/preprocessing/image_test.py

Add f-string format and lint with flynt on the whole codebase

keras

Python

image_test.py

def test_dataframe_iterator_class_mode_raw(self): tmpdir = self.create_tempdir() all_test_images = _generate_test_images(include_rgba=True) # save the images in the paths filenames = [] count = 0 for test_images in all_test_images: for im in test_images: filename = f"image-{count}.png" im.save(os.path.join(tmpdir.full_path, filename)) filenames.append(filename) count += 1 # case for 1D output df = pd.DataFrame({"filename": filenames}).assign( output_0=np.random.uniform(size=len(filenames)), output_1=np.random.uniform(size=len(filenames)), ) df_iterator = image.ImageDataGenerator().flow_from_dataframe( df, y_col="output_0", directory=tmpdir.full_path, batch_size=3, shuffle=False, class_mode="raw", ) batch_x, batch_y = next(df_iterator) self.assertIsInstance(batch_x, np.ndarray) self.assertLen(batch_x.shape, 4) self.assertIsInstance(batch_y, np.ndarray) self.assertEqual(batch_y.shape, (3,)) self.assertAllEqual(batch_y, df["output_0"].values[:3]) # case with a 2D output df_iterator = image.ImageDataGenerator().flow_from_dataframe( df, y_col=["output_0", "output_1"], directory=tmpdir.full_path, batch_size=3, shuffle=False, class_mode="raw", ) batch_x, batch_y = next(df_iterator) self.assertIsInstance(batch_x, np.ndarray) self.assertLen(batch_x.shape, 4) self.assertIsInstance(batch_y, np.ndarray) self.assertEqual(batch_y.shape, (3, 2)) self.assertAllEqual(batch_y, df[["output_0", "output_1"]].values[:3])

be73ac1a1e25d9abd4d793cba9707098d7adf231

https://github.com/keras-team/keras.git

def test_dataframe_iterator_class_mode_raw(self): tmpdir = self.create_tempdir() all_test_images = _generate_test_images(include_rgba=True) # save the images in the paths filenames = [] count = 0 for test_images in all_test_images: for im in test_images: filename = f"image-{count}.png" im.save(os.path.join(tmpdir.full_path, filename)) filenames.append(filename) count += 1 # case for 1D output df = pd.DataFrame({"filename": filenames}).assign( output_0=np.random.uniform(size=len(filenames)), output_1=np.random.uniform(size=len(filenames)), ) df_iterator = image.ImageDataGenerator().flow_from_dataframe( df, y_col="output_0", directory=tmpdir.full_path, batch_size=3, shuffle=False, class_mode="raw", ) batch_x, batch_y = next(df_iterator) self.assertIsInstance(batch_x, np.ndarray) self.assertLen(batch_x.shape, 4) self.assertIsInstance(batch_y, np.ndarray) self.assertEqual(batch_y.shape, (3,)) self.assertAllEqual(batch_y, df["output_0"].values[:3]) # case with a 2D output df_iterator = image.ImageDataGenerator().flow_from_dataframe( df, y_col=["output_0", "output_1"], directory=tmpdir.full_path, batch_size=3, shuffle=False, class_mode="raw", ) batch_x, batch_y = next(df_iterator) self.assertIsInstance(batch_x, np.ndarray) self.assertLen(batch_x.shape, 4) self.assertIsInstance(batch_y, np.ndarray) self.assertEqual(batch_y.shape, (3, 2)) self.assertAllEqual(batch_y, df[["output_0", "output_1"]].value

test_dataframe_iterator_class_mode_raw

tools/eval.py

[smalldet] fix slice_infer (#6744) * fix slice_infer * fix doc, test=document_fix

PaddleDetection

Python

eval.py

def parse_args(): parser = ArgsParser() parser.add_argument( "--output_eval", default=None, type=str, help="Evaluation directory, default is current directory.") parser.add_argument( '--json_eval', action='store_true', default=False, help='Whether to re eval with already exists bbox.json or mask.json') parser.add_argument( "--slim_config", default=None, type=str, help="Configuration file of slim method.") # TODO: bias should be unified parser.add_argument( "--bias", action="store_true", help="whether add bias or not while getting w and h") parser.add_argument( "--classwise", action="store_true", help="whether per-category AP and draw P-R Curve or not.") parser.add_argument( '--save_prediction_only', action='store_true', default=False, help='Whether to save the evaluation results only') parser.add_argument( "--amp", action='store_true', default=False, help="Enable auto mixed precision eval.") # for smalldet slice_infer parser.add_argument( "--slice_infer", action='store_true', help="Whether to slice the image and merge the inference results for small object detection." ) parser.add_argument( '--slice_size', nargs='+', type=int, default=[640, 640], help="Height of the sliced image.") parser.add_argument( "--overlap_ratio", nargs='+', type=float, default=[0.25, 0.25], help="Overlap height ratio of the sliced image.") parser.add_argument( "--combine_method", type=str, default='nms', help="Combine method of the sliced images' detection results, choose in ['nms', 'nmm', 'concat']." ) parser.add_argument( "--match_threshold", type=float, default=0.6, help="Combine method matching threshold.") parser.add_argument( "--match_metric", type=str, default='ios', help="Combine method matching metric, choose in ['iou', 'ios'].") args = parser.parse_args() return args

486121eaa4ad142dde25ff7a77a2070f5a4571d4

https://github.com/PaddlePaddle/PaddleDetection.git

def parse_args(): parser = ArgsParser() parser.add_argument( "--output_eval", default=None, type=str, help="Evaluation directory, default is current directory.") parser.add_argument( '--json_eval', action='store_true', default=False, help='Whether to re eval with already exists bbox.json or mask.json') parser.add_argument( "--slim_config", default=None, type=str, help="Configuration file of slim method.") # TODO: bias should be unified parser.add_argument( "--bias", action="store_true", help="whether add bias or not while getting w and h") parser.add_argument(

parse_args

ludwig/data/preprocessing.py

Update missing value strategy to only allow bfill and ffill (#2457) * push changes * working missing value strategy * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Add type hints to backward compatibility transformations * Update test to test both missing value strategy updates Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ludwig

Python

preprocessing.py

def handle_missing_values(dataset_cols, feature, preprocessing_parameters): missing_value_strategy = preprocessing_parameters["missing_value_strategy"] # Check for the precomputed fill value in the metadata computed_fill_value = preprocessing_parameters.get("computed_fill_value") if ( missing_value_strategy in {FILL_WITH_CONST, FILL_WITH_MODE, FILL_WITH_MEAN, FILL_WITH_FALSE} and computed_fill_value is not None ): dataset_cols[feature[COLUMN]] = dataset_cols[feature[COLUMN]].fillna( computed_fill_value, ) elif missing_value_strategy in {BFILL, FFILL}: dataset_cols[feature[COLUMN]] = dataset_cols[feature[COLUMN]].fillna( method=missing_value_strategy, ) elif missing_value_strategy == DROP_ROW: # Here we only drop from this series, but after preprocessing we'll do a second # round of dropping NA values from the entire output dataframe, which will # result in the removal of the rows. dataset_cols[feature[COLUMN]] = dataset_cols[feature[COLUMN]].dropna() else: raise ValueError(f"Invalid missing value strategy {missing_value_strategy}")

0ab41a299cc690940b750a79b704d69544315702

https://github.com/ludwig-ai/ludwig.git

def handle_missing_values(dataset_cols, feature, preprocessing_parameters): missing_value_strategy = preprocessing_parameters["missing_value_strategy"] # Check for the precomputed fill value in the metadata computed_fill_value = preprocessing_parameters.get("computed_fill_value") if ( missing_value_strategy in {FILL_WITH_CONST, FILL_WITH_MODE, FILL_WITH_MEAN, FILL_WITH_FAL

handle_missing_values

tests/sentry/integrations/slack/notifications/test_new_processing_issues.py

Revert "fix(notifications): Use `metrics_key` (#34572)" This reverts commit 1730c481f1a8a71446326fa1ff72e10663016385. Co-authored-by: marcos.gaeta via Slack <marcos.gaeta@sentry.io>

sentry

Python

test_new_processing_issues.py

def test_new_processing_issue(self, mock_func): notification = NewProcessingIssuesActivityNotification( Activity( project=self.project, user=self.user, type=ActivityType.NEW_PROCESSING_ISSUES, data={ "issues": get_issues_data(), "reprocessing_active": True, }, ) ) with self.tasks(): notification.send() attachment, text = get_attachment() assert ( text == f"Processing issues on <{self.project.slug}|http://testserver/settings/{self.organization.slug}/projects/{self.project.slug}/processing-issues/" ) assert ( attachment["text"] == f"Some events failed to process in your project {self.project.slug}" ) assert ( attachment["footer"] == f"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=new-processing-issues-activity-slack-user|Notification Settings>" )

04f013dd203f286aaf27b1c887bb72a2e24a498e

https://github.com/getsentry/sentry.git

def test_new_processing_issue(self, mock_func): notification = NewProcessingIssuesActivityNotification( Activity( project=self.project, user=self.user, type=ActivityType.NEW_PROCESSING_ISSUES, data={ "issues": get_issues_data(), "reprocessing_active": True, }, ) ) with self.tasks(): notification.send() attachment, text = get_attachment() assert ( text == f"Processing issues on <{self.project.slug}|http://testserver/settings/{self.organization.slug}/projects/{self.project.slug}/processing-issues/" ) assert ( attachment["text"] == f"Some events failed to process in your project {self.project.slug}" ) assert ( attachment["footer"] == f"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=new

test_new_processing_issue

tests/test_doctor.py

Remove snapshottest to reduce number of dependencies (#1433) Having an extra package that can be replaced with something already included makes packaging easier. For instance, in Debian, one would have to either be fortunate to find an existing package or go over the trouble of creating such package and all its dependencies. I believe this CL is a good small compromise considering the benefit it brings.

thumbor

Python

test_doctor.py

def test_get_doctor_output(capsys, doctor_output): run_doctor( { "nocolor": True, "config": "./tests/invalid-thumbor.conf", }, print_version=False, exit_with_error=False, check_pyexiv=False, ) assert capsys.readouterr().out == doctor_output

0e845259cd3d49b39889ae15df19922af0ef7269

https://github.com/thumbor/thumbor.git

def test_get_doctor_output(capsys, doctor_output): run_doctor( { "nocolor": True, "config": "./tests/invalid-thumbor.conf", }, print_version=False, exit_with_error=False, che

test_get_doctor_output

python3.10.4/Lib/importlib/metadata/__init__.py

add python 3.10.4 for windows

XX-Net

Python

__init__.py

def _deps_from_requires_text(cls, source): return cls._convert_egg_info_reqs_to_simple_reqs(Sectioned.read(source))

8198943edd73a363c266633e1aa5b2a9e9c9f526

https://github.com/XX-net/XX-Net.git

def _deps_from_requires_text(cls, source): return cls._convert_egg_info_reqs_to_simple_r

_deps_from_requires_text

tests/strategy/test_interface.py

Fix typo causing an implicit bug

freqtrade

Python

test_interface.py

def test_returns_latest_signal(ohlcv_history): ohlcv_history.loc[1, 'date'] = arrow.utcnow() # Take a copy to correctly modify the call mocked_history = ohlcv_history.copy() mocked_history['enter_long'] = 0 mocked_history['exit_long'] = 0 mocked_history['enter_short'] = 0 mocked_history['exit_short'] = 0 # Set tags in lines that don't matter to test nan in the sell line mocked_history.loc[0, 'enter_tag'] = 'wrong_line' mocked_history.loc[0, 'exit_tag'] = 'wrong_line' mocked_history.loc[1, 'exit_long'] = 1 assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, True, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 1 assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 0 assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 1 mocked_history.loc[1, 'enter_tag'] = 'buy_signal_01' assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, 'buy_signal_01') assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 0 mocked_history.loc[1, 'enter_short'] = 1 mocked_history.loc[1, 'exit_short'] = 0 mocked_history.loc[1, 'enter_tag'] = 'sell_signal_01' # Don't provide short signal while in spot mode assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) _STRATEGY.config['trading_mode'] = 'futures' # Short signal get's ignored as can_short is not set. assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) _STRATEGY.can_short = True assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.SHORT, 'sell_signal_01') assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (True, False, None) mocked_history.loc[1, 'enter_short'] = 0 mocked_history.loc[1, 'exit_short'] = 1 mocked_history.loc[1, 'exit_tag'] = 'sell_signal_02' assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal( 'ETH/BTC', '5m', mocked_history) == (False, False, 'sell_signal_02') assert _STRATEGY.get_exit_signal( 'ETH/BTC', '5m', mocked_history, True) == (False, True, 'sell_signal_02') _STRATEGY.can_short = False _STRATEGY.config['trading_mode'] = 'spot'

b9b5d749bb36cfb8820756e3b4d3bb35534eab56

https://github.com/freqtrade/freqtrade.git

def test_returns_latest_signal(ohlcv_history): ohlcv_history.loc[1, 'date'] = arrow.utcnow() # Take a copy to correctly modify the call mocked_history = ohlcv_history.copy() mocked_history['enter_long'] = 0 mocked_history['exit_long'] = 0 mocked_history['enter_short'] = 0 mocked_history['exit_short'] = 0 # Set tags in lines that don't matter to test nan in the sell line mocked_history.loc[0, 'enter_tag'] = 'wrong_line' mocked_history.loc[0, 'exit_tag'] = 'wrong_line' mocked_history.loc[1, 'exit_long'] = 1 assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, True, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 1 assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 0 assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 1 mocked_history.loc[1, 'enter_tag'] = 'buy_signal_01' assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.LONG, 'buy_signal_01') assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (True, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (False, False, None) mocked_history.loc[1, 'exit_long'] = 0 mocked_history.loc[1, 'enter_long'] = 0 mocked_history.loc[1, 'enter_short'] = 1 mocked_history.loc[1, 'exit_short'] = 0 mocked_history.loc[1, 'enter_tag'] = 'sell_signal_01' # Don't provide short signal while in spot mode assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) _STRATEGY.config['trading_mode'] = 'futures' # Short signal get's ignored as can_short is not set. assert _STRATEGY.get_entry_signal('ETH/BTC', '5m', mocked_history) == (None, None) _STRATEGY.can_short = True assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (SignalDirection.SHORT, 'sell_signal_01') assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history) == (False, False, None) assert _STRATEGY.get_exit_signal('ETH/BTC', '5m', mocked_history, True) == (True, False, None) mocked_history.loc[1, 'enter_short'] = 0 mocked_history.loc[1, 'exit_short'] = 1 mocked_history.loc[1, 'exit_tag'] = 'sell_signal_02' assert _STRATEGY.get_entry_signal( 'ETH/BTC', '5m', mocked_history) == (None, None) assert _STRATEGY.get_exit_signal( 'ETH/BTC', '5m', mocked_history) == (False, False, 'sell_signal_02') assert _STRATEGY.get_exit_signal( 'ETH/B

test_returns_latest_signal

tools/box_distribution.py

fix sm_use for ppyoloe_head and output for box_dis (#7288) * fix sm_use for ppyoloe_head and output for box_dis * fix pos_embed of training

PaddleDetection

Python

box_distribution.py

def get_ratio_infos(jsonfile, out_img, eval_size, small_stride): coco = COCO(annotation_file=jsonfile) allannjson = json.load(open(jsonfile, 'r')) be_im_id = allannjson['annotations'][0]['image_id'] be_im_w = [] be_im_h = [] ratio_w = [] ratio_h = [] for ann in tqdm(allannjson['annotations']): if ann['iscrowd']: continue x0, y0, w, h = ann['bbox'][:] if be_im_id == ann['image_id']: be_im_w.append(w) be_im_h.append(h) else: im_w = coco.imgs[be_im_id]['width'] im_h = coco.imgs[be_im_id]['height'] im_m_w = np.mean(be_im_w) im_m_h = np.mean(be_im_h) dis_w = im_m_w / im_w dis_h = im_m_h / im_h ratio_w.append(dis_w) ratio_h.append(dis_h) be_im_id = ann['image_id'] be_im_w = [w] be_im_h = [h] im_w = coco.imgs[be_im_id]['width'] im_h = coco.imgs[be_im_id]['height'] im_m_w = np.mean(be_im_w) im_m_h = np.mean(be_im_h) dis_w = im_m_w / im_w dis_h = im_m_h / im_h ratio_w.append(dis_w) ratio_h.append(dis_h) mid_w = median(ratio_w) mid_h = median(ratio_h) reg_ratio = [] ratio_all = ratio_h + ratio_w for r in ratio_all: if r < 0.2: reg_ratio.append(r) elif r < 0.4: reg_ratio.append(r/2) else: reg_ratio.append(r/4) reg_ratio = sorted(reg_ratio) max_ratio = reg_ratio[int(0.95*len(reg_ratio))] reg_max = round(max_ratio*eval_size/small_stride) ratio_w = [i * 1000 for i in ratio_w] ratio_h = [i * 1000 for i in ratio_h] print(f'Suggested reg_range[1] is {reg_max+1}' ) print(f'Median of ratio_w is {mid_w}') print(f'Median of ratio_h is {mid_h}') print('all_img with box: ', len(ratio_h)) print('all_ann: ', len(allannjson['annotations'])) draw_distribution(ratio_w, ratio_h, out_img)

64b51f095305d5c5b477b177b35de6fec174c8b8

https://github.com/PaddlePaddle/PaddleDetection.git

def get_ratio_infos(jsonfile, out_img, eval_size, small_stride): coco = COCO(annotation_file=jsonfile) allannjson = json.

get_ratio_infos

python/ray/air/config.py

[AIR] Fix `ResourceChangingScheduler` not working with AIR (#26307) This PR ensures that the new trial resources set by `ResourceChangingScheduler` are respected by the train loop logic by modifying the scaling config to match. Previously, even though trials had their resources updated, the scaling config was not modified which lead to eg. new workers not being spawned in the `DataParallelTrainer` even though resources were available. In order to accomplish this, `ScalingConfigDataClass` is updated to allow equality comparisons with other `ScalingConfigDataClass`es (using the underlying PGF) and to create a `ScalingConfigDataClass` from a PGF. Please note that this is an internal only change intended to actually make `ResourceChangingScheduler` work. In the future, `ResourceChangingScheduler` should be updated to operate on `ScalingConfigDataClass`es instead of PGFs as it is now. That will require a deprecation cycle.

ray

Python

config.py

def as_placement_group_factory(self) -> "PlacementGroupFactory": from ray.tune.execution.placement_groups import PlacementGroupFactory trainer_resources = self._trainer_resources_not_none trainer_bundle = [trainer_resources] worker_resources = { "CPU": self.num_cpus_per_worker, "GPU": self.num_gpus_per_worker, } worker_resources_extra = ( {} if self.resources_per_worker is None else self.resources_per_worker ) worker_bundles = [ {**worker_resources, **worker_resources_extra} for _ in range(self.num_workers if self.num_workers else 0) ] bundles = trainer_bundle + worker_bundles return PlacementGroupFactory(bundles, strategy=self.placement_strategy)

b3878e26d765e28dd7c69abadbd856181037db97

https://github.com/ray-project/ray.git

def as_placement_group_factory(self) -> "PlacementGroupFactory": from ray.tune.execution.placement_groups import PlacementGroupFactory

as_placement_group_factory

wagtail/core/blocks/list_block.py

Implement a ListValue type for ListBlocks

wagtail

Python

list_block.py

def bulk_to_python(self, values): # 'values' is a list of lists of child block values; concatenate them into one list so that # we can make a single call to child_block.bulk_to_python lengths = [len(val) for val in values] raw_values = list(itertools.chain.from_iterable(values)) converted_values = self.child_block.bulk_to_python(raw_values) # split converted_values back into sub-lists of the original lengths result = [] offset = 0 for sublist_len in lengths: result.append(ListValue(values=converted_values[offset:offset + sublist_len])) offset += sublist_len return result

4a848bfb4e3ec1a84a3d36fda577c1ed784de498

https://github.com/wagtail/wagtail.git

def bulk_to_python(self, values): # 'values' is a list of lists of child block values; concatenate them into one list so that # we can make a single call to child_block.bulk_to_python lengths = [len(val) for val in values] raw_values = list(itertools.chain.from_iterable(values)) converted_values = self.child_block.bulk_to_python(raw_values) # split converted_values back into sub-lists of the original lengths result = [] offset = 0 for sublist_len in lengths: result.append(ListValue(values=converted_values[offset:offset + sublist_len])) offset += sublist_len return

bulk_to_python

tests/unit/bokeh/models/test_glyphs.py

Fix passing of kwargs in Image glyph's constructor (#12081)

bokeh

Python

test_glyphs.py

def test_Image_kwargs() -> None: glyph = Image(x=0, y=0, dw=10, dh=10) assert glyph.image == field("image") assert glyph.x == 0 assert glyph.y == 0 assert glyph.dw == 10 assert glyph.dh == 10 assert glyph.dilate is False

14ea3e941229c5069232bf29b48a57f4fb44394a

https://github.com/bokeh/bokeh.git

def test_Image_kwargs() -> None: glyph

test_Image_kwargs

ivy/core/general.py

moved all inplace methods from gradients submodule to general submodule, as inplace ops are also relevant for non-Variable tensors.

ivy

Python

general.py

def inplace_increment(x, val, f=None): return _cur_framework(x, f=f).inplace_increment(x, val)

ec8341197ccdd240a346a95c2a434e5ef9f9ef72

https://github.com/unifyai/ivy.git

def inplace_increment(x, val, f=None): return _cur_fra

inplace_increment

erpnext/loan_management/doctype/loan/loan.py

feat: Refund entry against loans

erpnext

Python

loan.py

def make_refund_jv(loan, amount=0, reference_number=None, reference_date=None, submit=0): loan_details = frappe.db.get_value('Loan', loan, ['applicant_type', 'applicant', 'loan_account', 'payment_account', 'posting_date', 'company', 'name', 'total_payment', 'total_principal_paid'], as_dict=1) loan_details.doctype = 'Loan' loan_details[loan_details.applicant_type.lower()] = loan_details.applicant if not amount: amount = flt(loan_details.total_principal_paid - loan_details.total_payment) if amount < 0: frappe.throw(_('No excess amount pending for refund')) refund_jv = get_payment_entry(loan_details, { "party_type": loan_details.applicant_type, "party_account": loan_details.loan_account, "amount_field_party": 'debit_in_account_currency', "amount_field_bank": 'credit_in_account_currency', "amount": amount, "bank_account": loan_details.payment_account }) if reference_number: refund_jv.cheque_no = reference_number if reference_date: refund_jv.cheque_date = reference_date if submit: refund_jv.submit() return refund_jv

c68c70f8bc88d9b05d64774ba070a34c059b7d30

https://github.com/frappe/erpnext.git

def make_refund_jv(loan, amount=0, reference_number=None, reference_date=None, submit=0): loan_details = frappe.db.get_value('Loan', loan, ['applicant_type', 'applicant', 'loan_account', 'payment_account', 'posting_date', 'company', 'name', 'total_payment', 'total_principal_paid'], as_dict=1) loan_details.doctype = 'Loan' loan_details[loan_details.applicant_type.lower()] = loan_details.applicant if not amount: amount = flt(loan_details.total_principal_paid - loan_details.total_payment) if amount < 0: frappe.throw(_('No excess amount pending for refund')) refund_jv = get_payment_entry(loan_details, { "party_type": loan_details.applicant_type, "party_account": loan_details.loan_account, "amount_field_party": 'debit_in_account_currency', "amount_field_bank": 'credit_in_account_currency', "amount": amount, "bank_account": loan_details.payment_account }) if reference_number: r

make_refund_jv

tests/test_modeling_utils.py

[Half precision] Make sure half-precision is correct (#182) * [Half precision] Make sure half-precision is correct * Update src/diffusers/models/unet_2d.py * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py * correct some tests * Apply suggestions from code review Co-authored-by: Suraj Patil <surajp815@gmail.com> * finalize * finish Co-authored-by: Suraj Patil <surajp815@gmail.com>

diffusers

Python

test_modeling_utils.py

def test_stable_diffusion(self): sd_pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-1-diffusers") prompt = "A painting of a squirrel eating a burger" generator = torch.Generator(device=torch_device).manual_seed(0) with torch.autocast("cuda"): output = sd_pipe( [prompt], generator=generator, guidance_scale=6.0, num_inference_steps=20, output_type="np" ) image = output["sample"] image_slice = image[0, -3:, -3:, -1] assert image.shape == (1, 512, 512, 3) expected_slice = np.array([0.898, 0.9194, 0.91, 0.8955, 0.915, 0.919, 0.9233, 0.9307, 0.8887]) assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2

051b34635fda2fc310898a6a602c89be8663b77f

https://github.com/huggingface/diffusers.git

def test_stable_diffusion(self): sd_pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-1-diffusers") prompt = "A painting of a squirrel eating a burger" generator = torch.Generator(device=torc

test_stable_diffusion

pandas/tests/extension/test_arrow.py

ENH/TST: Add BaseInterfaceTests tests for ArrowExtensionArray PT2 (#47468)

pandas

Python

test_arrow.py

def test_fillna_limit_backfill(self, data_missing, using_array_manager, request): if using_array_manager and pa.types.is_duration( data_missing.dtype.pyarrow_dtype ): request.node.add_marker( pytest.mark.xfail( reason="Checking ndim when using arraymanager with duration type" ) ) super().test_fillna_limit_backfill(data_missing)

dc36ce1b3f6578833ca44cc7a5e49a75ddb02ec7

https://github.com/pandas-dev/pandas.git

def test_fillna_limit_backfill(self, data_missing, using_array_manager, request): if using_array_manager and pa.types.is_duration( data_missing.dtype.pyarrow_dtype ): request.node.add_marker( pytest.mark.xfail( reason="

test_fillna_limit_backfill

homeassistant/components/landisgyr_heat_meter/sensor.py

Add Landis+Gyr Heat Meter integration (#73363) * Add Landis+Gyr Heat Meter integration * Add contant for better sensor config * Add test for init * Refactor some of the PR suggestions in config_flow * Apply small fix * Correct total_increasing to total * Add test for restore state * Add MWh entity that can be added as gas on the energy dashoard * Remove GJ as unit * Round MWh to 5 iso 3 digits * Update homeassistant/components/landisgyr_heat_meter/const.py * Update CODEOWNERS Co-authored-by: Erik Montnemery <erik@montnemery.com>

core

Python

sensor.py

async def async_added_to_hass(self): await super().async_added_to_hass() state = await self.async_get_last_sensor_data() if state: self._attr_native_value = state.native_value

7a497c1e6e5a0d44b9418a754470ca9dd35e9719

https://github.com/home-assistant/core.git

async def async_added_to_hass(self): await super().async_added_to_hass() state = await

async_added_to_hass

src/datasets/formatting/formatting.py

Support for decoding Image/Audio types in map when format type is not default one (#5252) * Add iter to arrow dataset and iterable dataset * Remove decoded from formatters * First attempt * Minor fix in np formatter * Fixes * Add tests for iter method * Minor test refactor * Add (and update) tests * Code fixes * Fix iter for drop_last_batch=True and pyarrow<=8 * Make `supports_lazy_decoding` class attribute of formatters * Update docs * Update lazy dict * Test lazy formatting * Lazily extract columns * Update tests * Update iter benchmark in docs * Fix CI * Add select to docs * Add array_concat * CI fix * Apply suggestions from code review Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> * Style * Add comments from code review Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> * Add test with sliced arrays * Use array_concat only for extension arrays * fix None -> empty array warning * fix map with mix of lazy dict and regular dict * fix benchmarks * fix tests * fix tests Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com> Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

datasets

Python

formatting.py

def __repr__(self): self._format_all() return repr(self.data) if config.PY_VERSION >= version.parse("3.9"): # merging with the union ("|") operator is supported in Python 3.9+

a528472ad7e164588f568b75b3b3e36ff71996d2

https://github.com/huggingface/datasets.git

def __repr__(self): self._format_all() return repr(self.d

__repr__

ppocr/modeling/backbones/__init__.py

add ppocrv3 rec (#6033) * add ppocrv3 rec

PaddleOCR

Python

__init__.py

def build_backbone(config, model_type): if model_type == "det" or model_type == "table": from .det_mobilenet_v3 import MobileNetV3 from .det_resnet_vd import ResNet from .det_resnet_vd_sast import ResNet_SAST support_dict = ["MobileNetV3", "ResNet", "ResNet_SAST"] elif model_type == "rec" or model_type == "cls": from .rec_mobilenet_v3 import MobileNetV3 from .rec_resnet_vd import ResNet from .rec_resnet_fpn import ResNetFPN from .rec_mv1_enhance import MobileNetV1Enhance from .rec_nrtr_mtb import MTB from .rec_resnet_31 import ResNet31 from .rec_resnet_aster import ResNet_ASTER from .rec_micronet import MicroNet from .rec_efficientb3_pren import EfficientNetb3_PREN from .rec_svtrnet import SVTRNet support_dict = [ 'MobileNetV1Enhance', 'MobileNetV3', 'ResNet', 'ResNetFPN', 'MTB', "ResNet31", "ResNet_ASTER", 'MicroNet', 'EfficientNetb3_PREN', 'SVTRNet' ] elif model_type == "e2e": from .e2e_resnet_vd_pg import ResNet support_dict = ['ResNet'] elif model_type == 'kie': from .kie_unet_sdmgr import Kie_backbone support_dict = ['Kie_backbone'] elif model_type == "table": from .table_resnet_vd import ResNet from .table_mobilenet_v3 import MobileNetV3 support_dict = ["ResNet", "MobileNetV3"] elif model_type == 'vqa': from .vqa_layoutlm import LayoutLMForSer, LayoutLMv2ForSer, LayoutLMv2ForRe, LayoutXLMForSer, LayoutXLMForRe support_dict = [ "LayoutLMForSer", "LayoutLMv2ForSer", 'LayoutLMv2ForRe', "LayoutXLMForSer", 'LayoutXLMForRe' ] else: raise NotImplementedError module_name = config.pop("name") assert module_name in support_dict, Exception( "when model typs is {}, backbone only support {}".format(model_type, support_dict)) module_class = eval(module_name)(**config) return module_class

f6532a0e51222c4385dd41a0f9de169f188ac29a

https://github.com/PaddlePaddle/PaddleOCR.git

def build_backbone(config, model_type): if model_type == "det" or model_type == "table": from .det_mobilenet_v3 import MobileNetV3 from .det_resnet_vd import ResNet from .det_resnet_vd_sast import ResNet_SAST support_dict = ["MobileNetV3", "ResNet", "ResNet_SAST"] elif model_type == "rec" or model_type == "cls": from .rec_mobilenet_v3 import MobileNetV3 from .rec_resnet_vd import ResNet from .rec_resnet_fpn import ResNetFPN from .rec_mv1_enhance import Mobil

build_backbone

tests/components/recorder/test_websocket_api.py

Support non-live database migration (#72433) * Support non-live database migration * Tweak startup order, add test * Address review comments * Fix typo * Clarify comment about promoting dependencies * Tweak * Fix merge mistake * Fix some tests * Fix additional test * Fix additional test * Adjust tests * Improve test coverage

core

Python

test_websocket_api.py

async def test_recorder_info(hass, hass_ws_client, recorder_mock): client = await hass_ws_client() # Ensure there are no queued events await async_wait_recording_done(hass) await client.send_json({"id": 1, "type": "recorder/info"}) response = await client.receive_json() assert response["success"] assert response["result"] == { "backlog": 0, "max_backlog": 40000, "migration_in_progress": False, "migration_is_live": False, "recording": True, "thread_running": True, }

fd6ffef52f337df71542b48565a95300c0ab2766

https://github.com/home-assistant/core.git

async def test_recorder_info(hass, hass_ws_client, recorder_mock): client = await hass_ws_client() # Ensure there are no queued events await async_wait_recording_done(hass) await client.send_json({"id": 1, "type": "recorder

test_recorder_info

tests/contenttypes_tests/test_operations.py

Refs #33476 -- Reformatted code with Black.

django

Python

test_operations.py

def test_existing_content_type_rename_other_database(self): ContentType.objects.using("other").create( app_label="contenttypes_tests", model="foo" ) other_content_types = ContentType.objects.using("other").filter( app_label="contenttypes_tests" ) call_command( "migrate", "contenttypes_tests", database="other", interactive=False, verbosity=0, ) self.assertFalse(other_content_types.filter(model="foo").exists()) self.assertTrue(other_content_types.filter(model="renamedfoo").exists()) call_command( "migrate", "contenttypes_tests", "zero", database="other", interactive=False, verbosity=0, ) self.assertTrue(other_content_types.filter(model="foo").exists()) self.assertFalse(other_content_types.filter(model="renamedfoo").exists())

9c19aff7c7561e3a82978a272ecdaad40dda5c00

https://github.com/django/django.git

def test_existing_content_type_rename_other_database(self): ContentType.objects.using("other").create( app_label="contenttypes_tests", model="foo" ) other_content_types = ContentType.objects.using("other").filter( app_label="contenttypes_tests" ) call_command( "migrate", "contenttypes_tests", database="other", interactive=False, verbosity=0, ) self.assertFalse(other_content_types.filter(model="foo").exists()) self.assertTrue(other_content_types.filter(model="renamedfoo").exists()) call_command( "migrate", "contenttypes_tests", "zero", database="other", interactive=False, verbosity=0, ) self.assertTrue(other_content_types.filter(model="foo").exists()) self.assertFalse(other_content_types.filter(model="renamedfoo").exists())

test_existing_content_type_rename_other_database

tests/test_integration.py

Add DCA order adjust test

freqtrade

Python

test_integration.py

def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: default_conf_usdt['position_adjustment_enable'] = True freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) mocker.patch.multiple( 'freqtrade.exchange.Exchange', fetch_ticker=ticker_usdt, get_fee=fee, amount_to_precision=lambda s, x, y: y, price_to_precision=lambda s, x, y: y, ) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=False) patch_get_signal(freqtrade) freqtrade.strategy.custom_entry_price = lambda **kwargs: ticker_usdt['ask'] * 0.96 freqtrade.enter_positions() assert len(Trade.get_trades().all()) == 1 trade = Trade.get_trades().first() assert len(trade.orders) == 1 assert trade.open_order_id is not None assert pytest.approx(trade.stake_amount) == 60 assert trade.open_rate == 1.96 # No adjustment freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 1 assert trade.open_order_id is not None assert pytest.approx(trade.stake_amount) == 60 # Cancel order and place new one freqtrade.strategy.adjust_entry_price = MagicMock(return_value=1.99) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 2 assert trade.open_order_id is not None # Open rate is not adjusted yet assert trade.open_rate == 1.96 # Fill order mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=True) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 2 assert trade.open_order_id is None # Open rate is not adjusted yet assert trade.open_rate == 1.99 # 2nd order - not filling freqtrade.strategy.adjust_trade_position = MagicMock(return_value=120) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=False) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 3 assert trade.open_order_id is not None assert trade.open_rate == 1.99 assert trade.orders[-1].price == 1.96 assert trade.orders[-1].cost == 120 # Replace new order with diff. order at a lower price freqtrade.strategy.adjust_entry_price = MagicMock(return_value=1.95) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 4 assert trade.open_order_id is not None assert trade.open_rate == 1.99 assert trade.orders[-1].price == 1.95 assert pytest.approx(trade.orders[-1].cost) == 120 # Fill DCA order freqtrade.strategy.adjust_trade_position = MagicMock(return_value=None) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=True) freqtrade.strategy.adjust_entry_price = MagicMock(side_effect=ValueError) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 4 assert trade.open_order_id is None assert pytest.approx(trade.open_rate) == 1.963153456 assert trade.orders[-1].price == 1.95 assert pytest.approx(trade.orders[-1].cost) == 120 assert trade.orders[-1].status == 'closed' assert pytest.approx(trade.amount) == 91.689215 # Check the 2 filled orders equal the above amount assert pytest.approx(trade.orders[1].amount) == 30.150753768 assert pytest.approx(trade.orders[-1].amount) == 61.538461232

108903f7f0c968f88a3b2520a8cc8e7753c4c2e1

https://github.com/freqtrade/freqtrade.git

def test_dca_order_adjust(default_conf_usdt, ticker_usdt, fee, mocker) -> None: default_conf_usdt['position_adjustment_enable'] = True freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt) mocker.patch.multiple( 'freqtrade.exchange.Exchange', fetch_ticker=ticker_usdt, get_fee=fee, amount_to_precision=lambda s, x, y: y, price_to_precision=lambda s, x, y: y, ) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=False) patch_get_signal(freqtrade) freqtrade.strategy.custom_entry_price = lambda **kwargs: ticker_usdt['ask'] * 0.96 freqtrade.enter_positions() assert len(Trade.get_trades().all()) == 1 trade = Trade.get_trades().first() assert len(trade.orders) == 1 assert trade.open_order_id is not None assert pytest.approx(trade.stake_amount) == 60 assert trade.open_rate == 1.96 # No adjustment freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 1 assert trade.open_order_id is not None assert pytest.approx(trade.stake_amount) == 60 # Cancel order and place new one freqtrade.strategy.adjust_entry_price = MagicMock(return_value=1.99) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 2 assert trade.open_order_id is not None # Open rate is not adjusted yet assert trade.open_rate == 1.96 # Fill order mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=True) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 2 assert trade.open_order_id is None # Open rate is not adjusted yet assert trade.open_rate == 1.99 # 2nd order - not filling freqtrade.strategy.adjust_trade_position = MagicMock(return_value=120) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=False) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 3 assert trade.open_order_id is not None assert trade.open_rate == 1.99 assert trade.orders[-1].price == 1.96 assert trade.orders[-1].cost == 120 # Replace new order with diff. order at a lower price freqtrade.strategy.adjust_entry_price = MagicMock(return_value=1.95) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 4 assert trade.open_order_id is not None assert trade.open_rate == 1.99 assert trade.orders[-1].price == 1.95 assert pytest.approx(trade.orders[-1].cost) == 120 # Fill DCA order freqtrade.strategy.adjust_trade_position = MagicMock(return_value=None) mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled', return_value=True) freqtrade.strategy.adjust_entry_price = MagicMock(side_effect=ValueError) freqtrade.process() trade = Trade.get_trades().first() assert len(trade.orders) == 4 assert trade.open_order_id is None assert pytest.approx(trade.open_rate) == 1.963153456 assert trade.orders[-1].price == 1.95 assert pytest.approx(trade.orders[-1].cost) == 120 a

test_dca_order_adjust

tests/models/test_hooks.py

Add `LightningModule.lr_scheduler_step` (#10249) Co-authored-by: Carlos Mocholi <carlossmocholi@gmail.com>

lightning

Python

test_hooks.py

def _auto_train_batch(trainer, model, batches, device=torch.device("cpu"), current_epoch=0, **kwargs): using_native_amp = kwargs.get("amp_backend") == "native" using_deepspeed = kwargs.get("strategy") == "deepspeed" out = [] for i in range(batches): out.extend( [ dict(name="on_before_batch_transfer", args=(ANY, 0)), dict(name="transfer_batch_to_device", args=(ANY, device, 0)), dict(name="on_after_batch_transfer", args=(ANY, 0)), # TODO: `on_batch_{start,end}` dict(name="Callback.on_batch_start", args=(trainer, model)), dict(name="Callback.on_train_batch_start", args=(trainer, model, ANY, i)), dict(name="on_train_batch_start", args=(ANY, i)), dict(name="forward", args=(ANY,)), dict(name="training_step", args=(ANY, i)), dict(name="training_step_end", args=(dict(loss=ANY),)), dict(name="Callback.on_before_zero_grad", args=(trainer, model, ANY)), dict(name="on_before_zero_grad", args=(ANY,)), dict(name="optimizer_zero_grad", args=(current_epoch, i, ANY, 0)), dict(name="Callback.on_before_backward", args=(trainer, model, ANY)), dict(name="on_before_backward", args=(ANY,)), # DeepSpeed handles backward internally *([dict(name="backward", args=(ANY, ANY, 0))] if not using_deepspeed else []), dict(name="Callback.on_after_backward", args=(trainer, model)), dict(name="on_after_backward"), # note: unscaling happens here in the case of AMP dict(name="Callback.on_before_optimizer_step", args=(trainer, model, ANY, 0)), dict(name="on_before_optimizer_step", args=(ANY, 0)), *([dict(name="log_grad_norm", args=ANY)] if not using_deepspeed else []), dict( name="clip_gradients", args=(ANY,), kwargs=dict(gradient_clip_val=None, gradient_clip_algorithm=None), ), dict( name="configure_gradient_clipping", args=(ANY, 0), kwargs=dict(gradient_clip_val=None, gradient_clip_algorithm=None), ), # this is after because it refers to the `LightningModule.optimizer_step` hook which encapsulates # the actual call to `PrecisionPlugin.optimizer_step` dict( name="optimizer_step", args=(current_epoch, i, ANY, 0, ANY), kwargs=dict(on_tpu=False, using_lbfgs=False, using_native_amp=using_native_amp), ), *( [dict(name="lr_scheduler_step", args=(ANY, 0, None))] if i == (trainer.num_training_batches - 1) else [] ), dict(name="Callback.on_train_batch_end", args=(trainer, model, dict(loss=ANY), ANY, i)), dict(name="on_train_batch_end", args=(dict(loss=ANY), ANY, i)), dict(name="Callback.on_batch_end", args=(trainer, model)), ] ) return out

82c8875f33addb0becd7761c95e9674ccc98c7ee

https://github.com/Lightning-AI/lightning.git

def _auto_train_batch(trainer, model, batches, device=torch.device("cpu"), current_epoch=0, **kwargs): using_native_amp = kwargs.get("amp_backend") == "native" using_deepspeed = kwargs.get("strategy") == "deepspeed" out = [] for i in range(batches): out.extend( [ dict(name="on_before_batch_transfer", args=(ANY, 0)), dict(name="transfer_batch_to_device", args=(ANY, device, 0)), dict(name="on_after_batch_transfer", args=(ANY, 0)), # TODO: `on_batch_{start,end}` dict(name="Callback.on_batch_start", args=(trainer, model)), dict(name="Callback.on_train_batch_start", args=(trainer, model, ANY, i)), dict(name="on_train_batch_start", args=(ANY, i)), dict(name="forward", args=(ANY,)), dict(name="training_step", args=(ANY, i)), dict(name="training_step_end", args=(dict(loss=ANY),)), dict(name="Callback.on_before_zero_grad", args=(trainer, model, ANY)), dict(name="on_before_zero_grad", args=(ANY,)), dict(name="optimizer_zero_grad", args=(current_epoch, i, ANY, 0)), dict(name="Callback.on_before_backward", args=(trainer,

_auto_train_batch

ldm/modules/image_degradation/bsrgan.py

release more models

stablediffusion

Python

bsrgan.py

def degradation_bsrgan_variant(image, sf=4, isp_model=None): image = util.uint2single(image) isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25 sf_ori = sf h1, w1 = image.shape[:2] image = image.copy()[:w1 - w1 % sf, :h1 - h1 % sf, ...] # mod crop h, w = image.shape[:2] hq = image.copy() if sf == 4 and random.random() < scale2_prob: # downsample1 if np.random.rand() < 0.5: image = cv2.resize(image, (int(1 / 2 * image.shape[1]), int(1 / 2 * image.shape[0])), interpolation=random.choice([1, 2, 3])) else: image = util.imresize_np(image, 1 / 2, True) image = np.clip(image, 0.0, 1.0) sf = 2 shuffle_order = random.sample(range(7), 7) idx1, idx2 = shuffle_order.index(2), shuffle_order.index(3) if idx1 > idx2: # keep downsample3 last shuffle_order[idx1], shuffle_order[idx2] = shuffle_order[idx2], shuffle_order[idx1] for i in shuffle_order: if i == 0: image = add_blur(image, sf=sf) elif i == 1: image = add_blur(image, sf=sf) elif i == 2: a, b = image.shape[1], image.shape[0] # downsample2 if random.random() < 0.75: sf1 = random.uniform(1, 2 * sf) image = cv2.resize(image, (int(1 / sf1 * image.shape[1]), int(1 / sf1 * image.shape[0])), interpolation=random.choice([1, 2, 3])) else: k = fspecial('gaussian', 25, random.uniform(0.1, 0.6 * sf)) k_shifted = shift_pixel(k, sf) k_shifted = k_shifted / k_shifted.sum() # blur with shifted kernel image = ndimage.filters.convolve(image, np.expand_dims(k_shifted, axis=2), mode='mirror') image = image[0::sf, 0::sf, ...] # nearest downsampling image = np.clip(image, 0.0, 1.0) elif i == 3: # downsample3 image = cv2.resize(image, (int(1 / sf * a), int(1 / sf * b)), interpolation=random.choice([1, 2, 3])) image = np.clip(image, 0.0, 1.0) elif i == 4: # add Gaussian noise image = add_Gaussian_noise(image, noise_level1=2, noise_level2=25) elif i == 5: # add JPEG noise if random.random() < jpeg_prob: image = add_JPEG_noise(image) # elif i == 6: # # add processed camera sensor noise # if random.random() < isp_prob and isp_model is not None: # with torch.no_grad(): # img, hq = isp_model.forward(img.copy(), hq) # add final JPEG compression noise image = add_JPEG_noise(image) image = util.single2uint(image) example = {"image":image} return example # TODO incase there is a pickle error one needs to replace a += x with a = a + x in add_speckle_noise etc...

ca86da3a30c4e080d4db8c25fca73de843663cb4

https://github.com/Stability-AI/stablediffusion.git

def degradation_bsrgan_variant(image, sf=4, isp_model=None): image = util.uint2single(image) isp_prob, jpeg_prob, scale2_prob = 0.25, 0.9, 0.25 sf_ori = sf h1, w1 = image.shape[:2] image = image.copy()[:w1 - w1 % sf, :h1 - h1 % sf, ...] # mod crop h, w = image.shape[:2] hq = image.copy() if sf == 4 and random.random() < scale2_prob: # downsample1 if np.random.rand() < 0.5: image = cv2.resize(image, (int(1 / 2 * image.shape[1]), int(1 / 2 * image.shape[0])), interpolation=random.choice([1, 2, 3])) else: image = util.imresize_np(image, 1 / 2, True) image = np.clip(image, 0.0, 1.0) sf = 2 shu

degradation_bsrgan_variant

src/sentry/integrations/msteams/integration.py

feat(msteams): Allow personal installation for Sentry in MS Teams (#36749) - Allow personal installation of Sentry for Microsoft Teams. This would allow MS Teams users to receive personal notifications for Sentry events like Slack. Currently, it is only possible to receive issue and incident notifications in `teams`. - The installation message/card is modified to allow the user to set up an integration from the personal chat as well. Upon successful installation a card will be presented with an option to configure notification settings. - Create an integration with `tenant_id` as the `external_id`, as we don't know the user's team from personal chat context. All users with the same `tenant_id` would be scoped under this integration.

sentry

Python

integration.py

def build_integration(self, state): data = state[self.key] external_id = data["external_id"] external_name = data["external_name"] service_url = data["service_url"] user_id = data["user_id"] conversation_id = data["conversation_id"] # TODO: add try/except for request errors token_data = get_token_data() integration = { "name": external_name, "external_id": external_id, "metadata": { "access_token": token_data["access_token"], "expires_at": token_data["expires_at"], "service_url": service_url, "installation_type": data["installation_type"], "tenant_id": data["tenant_id"], }, "user_identity": { "type": "msteams", "external_id": user_id, "scopes": [], "data": {}, }, "post_install_data": {"conversation_id": conversation_id}, } return integration

be379770e90f6b7f97109f1cbdffd1e4749402ba

https://github.com/getsentry/sentry.git

def build_integration(self, state): data = state[self.key] external_id = data["external_id"] external_name = data["external_name"] service_url = data["service_url"]

build_integration

mitmproxy/proxy/layers/quic.py

[quic] bugfixes and simplified connection opening

mitmproxy

Python

quic.py

def transmit(self) -> layer.CommandGenerator[None]: assert self.quic is not None # send all queued datagrams for data, addr in self.quic.datagrams_to_send(now=self._loop.time()): yield commands.SendData(self.conn, data, addr) # mark an existing wakeup command as obsolete if it now longer matches the time timer = self.quic.get_timer() if self._request_wakeup_command_and_timer is not None: command, existing_timer = self._request_wakeup_command_and_timer if existing_timer != timer: self._obsolete_wakeup_commands.add(command) self._request_wakeup_command_and_timer = None # request a new wakeup if necessary if timer is not None and self._request_wakeup_command_and_timer is None: command = commands.RequestWakeup(timer - self._loop.time()) self._request_wakeup_command_and_timer = (command, timer) yield command _handle_event = state_start

2426d3d03847e0273707436268d79c24616b3e74

https://github.com/mitmproxy/mitmproxy.git

def transmit(self) -> layer.CommandGenerator[None]: assert self.quic is not None # send all queued datagrams for data, addr in self.quic.datagrams_to_send(now=self._loop.time()): yield commands.SendData(self.conn, data, addr) # mark an existing wakeup command as obsolete if it now longer matches the time timer = self.quic.get_timer() if self._request_wakeup_command_and_timer is not None: command, existing_ti

transmit

salt/utils/event.py

Address docs and hard coded strings

salt

Python

event.py

def get_master_event(opts, sock_dir, listen=True, io_loop=None, raise_errors=False): return MasterEvent( sock_dir, opts, listen=listen, io_loop=io_loop, raise_errors=raise_errors )

25c2ae356bcf684cbe20f776e1ffcab0f8aeb80c

https://github.com/saltstack/salt.git

def get_master_event(opts, sock_dir, listen=True, io_loop=None, raise_errors=False): return MasterEvent( sock_dir, opts, listen=listen, io_loop=io_l

get_master_event

jina/parsers/orchestrate/runtimes/remote.py

fix: list-like args passed as string (#5464) Co-authored-by: Alaeddine Abdessalem <alaeddine-13@live.fr>

jina

Python

remote.py

def _add_host(arg_group): arg_group.add_argument( '--host', '--host-in', type=str, default=__default_host__, help=f'The host address of the runtime, by default it is {__default_host__}.', )

87912a37ce7ab3c3b63c12b48d6cdfe31f81742c

https://github.com/jina-ai/jina.git

def _add_host(arg_group): arg_group.add_argument( '--host', '--host-in', type=str, default=__default_host__, help=f'The host address of the runtime, by default it is {__default_host__}.',

_add_host

apps/users/signal_handlers.py

perf: 设置默认的角色，系统用户角色添加权限 (#7898) * perf: 修改 role handler * perf: 设置默认的角色，系统用户角色添加权限 * perf: authentication 还是放到系统中吧 Co-authored-by: ibuler <ibuler@qq.com> Co-authored-by: Jiangjie.Bai <32935519+BaiJiangJie@users.noreply.github.com>

jumpserver

Python

signal_handlers.py

def on_user_create_set_default_system_role(sender, instance, created, **kwargs): if not created: return has_system_role = instance.system_roles.all().exists() if not has_system_role: logger.debug("Receive user create signal, set default role") instance.set_default_system_role() @receiver(post_user_create)

34e75099a3bc8b32d6e823660f5162094d17e511

@receiver(post_user_create)

https://github.com/jumpserver/jumpserver.git

def on_user_create_set_default_system_role(sender, instance, created, **kwargs): if not created:

on_user_create_set_default_system_role

vocoder/fregan/stft_loss.py

Added missing files for Fre-GAN (#579) * The new vocoder Fre-GAN is now supported * Improved some fregan details * Fixed the problem that the existing model could not be loaded to continue training when training GAN * Updated reference papers * GAN training now supports DistributedDataParallel (DDP) * Added requirements.txt * GAN training uses single card training by default * Added note about GAN vocoder training with multiple GPUs * Added missing files for Fre-GAN

MockingBird

Python

stft_loss.py

def stft(x, fft_size, hop_size, win_length, window): x_stft = torch.stft(x, fft_size, hop_size, win_length, window) real = x_stft[..., 0] imag = x_stft[..., 1] # NOTE(kan-bayashi): clamp is needed to avoid nan or inf return torch.sqrt(torch.clamp(real ** 2 + imag ** 2, min=1e-7)).transpose(2, 1)

6a793cea8488ad40fcad6ab30f9d82bc920ac114

https://github.com/babysor/MockingBird.git

def stft(x, fft_size, hop_size, win_length, window): x_stft = t

stft

homeassistant/components/mqtt/cover.py

Add mqtt encoding support for publishing (#62739) * encoding support for mqtt publishing - todo tests * signature allows None values for qos and retain * common test for mqtt publishing encoding * better test with command templates * more tests * fix tests alarm control panel+tests light basic * tests light json and template * add tests vacuum and fix tests light_template

core

Python

cover.py

async def async_close_cover(self, **kwargs): await mqtt.async_publish( self.hass, self._config.get(CONF_COMMAND_TOPIC), self._config[CONF_PAYLOAD_CLOSE], self._config[CONF_QOS], self._config[CONF_RETAIN], self._config[CONF_ENCODING], ) if self._optimistic: # Optimistically assume that cover has changed state. self._state = STATE_CLOSED if self._config.get(CONF_GET_POSITION_TOPIC): self._position = self.find_percentage_in_range( self._config[CONF_POSITION_CLOSED], COVER_PAYLOAD ) self.async_write_ha_state()

d0c4f0fec4216e4193da716001b5e13e1e3f2106

https://github.com/home-assistant/core.git

async def async_close_cover(self, **kwargs): await mqtt.async_publish( self.hass, self._config.get(CONF_COMMAND_TOPIC), self._config[CONF_PAYLOAD_CLOSE], self._config[CONF_QOS], self._config[CONF_RETAIN], self._config[CONF_ENCODING], ) if self._optimistic: # Optimistically assume that cover has changed state. se

async_close_cover

code/deep/BJMMD/caffe/python/caffe/test/test_coord_map.py

Balanced joint maximum mean discrepancy for deep transfer learning

transferlearning

Python

test_coord_map.py

def test_rect(self): n3x3 = coord_net_spec(ks=3, stride=1, pad=0) n5x5 = coord_net_spec(ks=5, stride=2, pad=10) n3x5 = coord_net_spec(ks=[3, 5], stride=[1, 2], pad=[0, 10]) ax_3x3, a_3x3, b_3x3 = coord_map_from_to(n3x3.deconv, n3x3.data) ax_5x5, a_5x5, b_5x5 = coord_map_from_to(n5x5.deconv, n5x5.data) ax_3x5, a_3x5, b_3x5 = coord_map_from_to(n3x5.deconv, n3x5.data) self.assertTrue(ax_3x3 == ax_5x5 == ax_3x5) self.assertEquals(a_3x3, a_3x5[0]) self.assertEquals(b_3x3, b_3x5[0]) self.assertEquals(a_5x5, a_3x5[1]) self.assertEquals(b_5x5, b_3x5[1])

cc4d0564756ca067516f71718a3d135996525909

https://github.com/jindongwang/transferlearning.git

def test_rect(self): n3x3 = coord_net_spec(ks=3, stride=1, pad=0) n5x5 = coord_net_spec(ks=5, stride=2, pad=10) n3x5 = coord_net_spec(ks=[3, 5], stride=[1, 2], pad=[0, 10]) ax_3x3, a_3x3, b_3x3 = coord_map_from_to(n3x3.deconv, n3x3.data) ax_5x5, a_5x5, b_5x5 = coord_map_from_to(n5x5.deconv, n5x5.data) ax_3x5, a_3x5, b_3x5 = coord_map_from_to(n3x5.deconv, n3x5.data) self.assertTrue(ax_3x3 == ax_5x5 == ax_3x5) self.assertEquals(a_3x3, a_3x5[0])

test_rect

PPOCRLabel/libs/autoDialog.py

Add [ time left ] while predicting the image for user to know the situation

PaddleOCR

Python

autoDialog.py

def handleProgressBarSingal(self, i): self.pb.setValue(i) # calculate time left of auto labeling avg_time = (time.time() - self.time_start) / i # Use average time to prevent time fluctuations time_left = str(datetime.timedelta(seconds=avg_time * (self.lender - i))) self.setWindowTitle("PPOCRLabel -- " + f"Time Left: {time_left}") # show

c267107926bbbd977fc9d67d3c39fb5e1b77028b

https://github.com/PaddlePaddle/PaddleOCR.git

def handleProgressBarSingal(self, i): self.pb.setValue(i)

handleProgressBarSingal

python/ccxt/async_support/zaif.py

1.71.83 [ci skip]

ccxt

Python

zaif.py

def describe(self): return self.deep_extend(super(zaif, self).describe(), { 'id': 'zaif', 'name': 'Zaif', 'countries': ['JP'], 'rateLimit': 2000, 'version': '1', 'has': { 'CORS': None, 'spot': True, 'margin': None, # has but unimplemented 'swap': False, 'future': False, 'option': False, 'cancelOrder': True, 'createMarketOrder': None, 'createOrder': True, 'fetchBalance': True, 'fetchClosedOrders': True, 'fetchFundingHistory': False, 'fetchFundingRate': False, 'fetchFundingRateHistory': False, 'fetchFundingRates': False, 'fetchIndexOHLCV': False, 'fetchMarkets': True, 'fetchMarkOHLCV': False, 'fetchOpenOrders': True, 'fetchOrderBook': True, 'fetchPremiumIndexOHLCV': False, 'fetchTicker': True, 'fetchTrades': True, 'withdraw': True, }, 'urls': { 'logo': 'https://user-images.githubusercontent.com/1294454/27766927-39ca2ada-5eeb-11e7-972f-1b4199518ca6.jpg', 'api': 'https://api.zaif.jp', 'www': 'https://zaif.jp', 'doc': [ 'https://techbureau-api-document.readthedocs.io/ja/latest/index.html', 'https://corp.zaif.jp/api-docs', 'https://corp.zaif.jp/api-docs/api_links', 'https://www.npmjs.com/package/zaif.jp', 'https://github.com/you21979/node-zaif', ], 'fees': 'https://zaif.jp/fee?lang=en', }, 'fees': { 'trading': { 'percentage': True, 'taker': self.parse_number('0.001'), 'maker': self.parse_number('0'), }, }, 'api': { 'public': { 'get': [ 'depth/{pair}', 'currencies/{pair}', 'currencies/all', 'currency_pairs/{pair}', 'currency_pairs/all', 'last_price/{pair}', 'ticker/{pair}', 'trades/{pair}', ], }, 'private': { 'post': [ 'active_orders', 'cancel_order', 'deposit_history', 'get_id_info', 'get_info', 'get_info2', 'get_personal_info', 'trade', 'trade_history', 'withdraw', 'withdraw_history', ], }, 'ecapi': { 'post': [ 'createInvoice', 'getInvoice', 'getInvoiceIdsByOrderNumber', 'cancelInvoice', ], }, 'tlapi': { 'post': [ 'get_positions', 'position_history', 'active_positions', 'create_position', 'change_position', 'cancel_position', ], }, 'fapi': { 'get': [ 'groups/{group_id}', 'last_price/{group_id}/{pair}', 'ticker/{group_id}/{pair}', 'trades/{group_id}/{pair}', 'depth/{group_id}/{pair}', ], }, }, 'options': { # zaif schedule defines several market-specific fees 'fees': { 'BTC/JPY': {'maker': 0, 'taker': 0}, 'BCH/JPY': {'maker': 0, 'taker': 0.3 / 100}, 'BCH/BTC': {'maker': 0, 'taker': 0.3 / 100}, 'PEPECASH/JPY': {'maker': 0, 'taker': 0.01 / 100}, 'PEPECASH/BT': {'maker': 0, 'taker': 0.01 / 100}, }, }, 'exceptions': { 'exact': { 'unsupported currency_pair': BadRequest, # {"error": "unsupported currency_pair"} }, 'broad': { }, }, })

ff158ebe7e1ed14772139737d13bb5edfd6d9430

https://github.com/ccxt/ccxt.git

def describe(self): return self.deep_extend(super(zaif, self).describe(), { 'id': 'zaif', 'name': 'Zaif', 'countries': ['JP'], 'rateLimit': 2000, 'version': '1', 'has': { 'CORS': None, 'spot': True, 'margin': None, # has but unimplemented 'swap': False, 'future': False, 'option': False, 'cancelOrder': True, 'createMarketOrder': None, 'createOrder': True, 'fetchBalance': True, 'fetchClosedOrders': True, 'fetchFundingHistory': False, 'fetchFundingRate': False, 'fetchFundingRateHistory': False, 'fetchFundingRates': False, 'fetchIndexOHLCV': False, 'fetchMarkets': True, 'fetchMarkOHLCV': False, 'fetchOpenOrders': True, 'fetchOrderBook': True, 'fetchPremiumIndexOHLCV': False, 'fetchTicker': True, 'fetchTrades': True, 'withdraw': True, }, 'urls': { 'logo': 'https://user-images.githubusercontent.com/1294454/27766927-39ca2ada-5eeb-11e7-972f-1b4199518ca6.jpg', 'api': 'https://api.zaif.jp', 'www': 'https://zaif.jp', 'doc': [ 'https://techbureau-api-document.readthedocs.io/ja/latest/index.html', 'https://corp.zaif.jp/api-docs', 'https://corp.zaif.jp/api-docs/api_links', 'https://www.npmjs.com/package/zaif.jp', 'https://github.com/you21979/node-zaif', ], 'fees': 'https://zaif.jp/fee?lang=en', }, 'fees': { 'trading': { 'percentage': True, 'taker': self.parse_number('0.001'), 'maker': self.parse_number('0'), }, }, 'api': { 'public': { 'get': [ 'depth/{pair}', 'currencies/{pair}', 'currencies/all', 'currency_pairs/{pair}', 'currency_pairs/all', 'last_price/{pair}', 'ticker/{pair}', 'trades/{pair}', ], }, 'private': { 'post': [ 'active_orders', 'cancel_order', 'deposit_history', 'get_id_info', 'get_info', 'get_info2', 'get_personal_info', 'trade', 'trade_history', 'withdraw', 'withdraw_history', ], }, 'ecapi': { 'post': [ 'createInvoice', 'getInvoice', 'getInvoiceIdsByOrderNumber', 'cancelInvoice', ], }, 'tlapi': { 'post': [ 'get_positions', 'position_history', 'active_positions', 'create_position', 'change_position', 'cancel_position', ], }, 'fapi': { 'get': [ 'groups/{group_id}', 'last_price/{group_id}/{pair}', 'ticker/{group_id}/{pair}', 'trades/{group_id}/{pair}', 'depth/{group_id}/{pair}', ], }, }, 'options': { # zaif schedule defines several market-specific fees 'fees': { 'BTC/JPY': {'maker': 0, 'taker': 0}, 'BCH/JPY': {'maker': 0, 'taker': 0.3 / 100}, 'BCH/BTC': {'maker': 0, 'taker': 0.3 / 100}, 'PEPECASH/JPY': {'maker':

describe

python/ray/tests/test_failure_2.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

Python

test_failure_2.py

def test_raylet_node_manager_server_failure(ray_start_cluster_head, log_pubsub): cluster = ray_start_cluster_head redis_port = int(cluster.address.split(":")[1]) # Reuse redis port to make node manager grpc server fail to start. with pytest.raises(Exception): cluster.add_node(wait=False, node_manager_port=redis_port) # wait for max 10 seconds.

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

https://github.com/ray-project/ray.git

def test_raylet_node_manager_server_failure(ray_start_cluster_head, log_pubsub): cluster = ray_start_cluster_head redis_port = int(cluster.address.split(":")[1]) # Reuse redis port to make node manager grpc server fail to start. with pytest.raises(Exception): cluster.add_node(w

test_raylet_node_manager_server_failure

src/sentry/runner/commands/repair.py

ref(models): `ActivityType` (#34978) ## Objective: We want to separate enum logic from Model logic. This breaks a lot of circular dependencies.

sentry

Python

repair.py

def fix_group_counters(): from django.db import connection click.echo("Correcting Group.num_comments counter") cursor = connection.cursor() cursor.execute( , [ActivityType.NOTE.value], ) @click.command() @click.option( "--with-docs/--without-docs", default=False, help="Synchronize and repair embedded documentation. This " "is disabled by default.", ) @configuration

b9f5a910dc841b85f58d46266ec049ae5a7fd305

@click.command() @click.option( "--with-docs/--without-docs", default=False, help="Synchronize and repair embedded documentation. This " "is disabled by default.", ) @configuration

https://github.com/getsentry/sentry.git

def fix_group_counters(): from django.db import connection click.echo("Correcting Group.num_comments counter") cursor = connection.cursor() cursor.execute( , [ActivityType.NOTE.value], ) @click.command() @click.option( "--with-do

fix_group_counters

tests/test_config.py

Rename IMPERIAL_SYSTEM to US_CUSTOMARY_SYSTEM (#80253) * Rename IMPERIAL_SYSTEM * Deprecate is_metric property and adjust tests * Adjust unit_system config validation * Add yaml tests * Add tests for private name * Fix incorrect rebase * Adjust docstring * Add store migration * Update unit_system.py * Minimise test tweaks * Fix tests * Add conversion to migration * Rename new key and adjust tests * Adjust websocket_detect_config * Move original_unit_system tracking to subclass

core

Python

test_config.py

async def test_igration_and_updating_configuration(hass, hass_storage): core_data = { "data": { "elevation": 10, "latitude": 55, "location_name": "Home", "longitude": 13, "time_zone": "Europe/Copenhagen", "unit_system": "imperial", "external_url": "https://www.example.com", "internal_url": "http://example.local", "currency": "BTC", }, "key": "core.config", "version": 1, "minor_version": 1, } hass_storage["core.config"] = dict(core_data) await config_util.async_process_ha_core_config( hass, {"allowlist_external_dirs": "/etc"} ) await hass.config.async_update(latitude=50, currency="USD") expected_new_core_data = copy.deepcopy(core_data) # From async_update above expected_new_core_data["data"]["latitude"] = 50 expected_new_core_data["data"]["currency"] = "USD" # 1.1 -> 1.2 store migration with migrated unit system expected_new_core_data["data"]["unit_system_v2"] = "us_customary" expected_new_core_data["minor_version"] = 2 assert hass_storage["core.config"] == expected_new_core_data assert hass.config.latitude == 50 assert hass.config.currency == "USD"

67d1dde69fbacf33f2c39ea14d89f2afa425ed18

https://github.com/home-assistant/core.git

async def test_igration_and_updating_configuration(hass, hass_storage): core_data = { "data": { "elevation": 10, "latitude": 55, "location_name": "Home", "longitude": 13, "time_zone": "Europe/Copenhagen", "unit_system": "imperial", "external_url": "https://www.example.com", "internal_url": "http://example.local", "currency": "BTC", }, "key": "core.config", "version": 1, "minor_version": 1, } hass_storage["core.config"] = dict(core_data) await config_util.async_process_ha_core_config( hass, {"allowlist_external_dirs": "/etc"} ) await hass.config.async_update(latitude=50, currency="USD") expected_new_core_data = copy.deepcopy(core_data) # From async_update above expected_new_core_data["data"]["latitude"] = 50 expected_new_core_data["data"]["currency"] = "USD" # 1.1 -> 1.2 store migration with migrated unit system expected_new_core_data["data"]["unit_system_v2"] = "us_customary" expected_new_core_data["minor_version"] = 2 assert hass_storage["core.config"] == expected_new_core_data assert hass.config.latitude == 50 assert hass.config.currency == "USD"

test_igration_and_updating_configuration

mmdet/models/detectors/base.py

Refactor interface of two-stage detector

mmdetection

Python

base.py

def with_shared_head(self) -> bool: return hasattr(self, 'roi_head') and self.roi_head.with_shared_head

46430db4f965a2d7e2853ce52cad828344e84ec7

https://github.com/open-mmlab/mmdetection.git

def with_shared_head(self) -> bool: return hasattr(self, 'roi_head') and self.roi_head.with_shared_head

with_shared_head

mitmproxy/proxy/layers/quic.py

[autofix.ci] apply automated fixes

mitmproxy

Python

quic.py

def receive_close(self) -> layer.CommandGenerator[None]: assert self.quic # if `_close_event` is not set, the underlying connection has been closed # we turn this into a QUIC close event as well close_event = self.quic._close_event or quic_events.ConnectionTerminated( QuicErrorCode.NO_ERROR, None, "Connection closed." ) yield from self.event_to_child( QuicConnectionClosed( self.conn, close_event.error_code, close_event.frame_type, close_event.reason_phrase, ) )

8c2428c9d355ca5fbc3dd90e9820ceb1cc795837

https://github.com/mitmproxy/mitmproxy.git

def receive_close(self) -> layer.CommandGenerator[None]: assert self.quic # if `_close_event` is not set, the underlying connection has been closed # we turn this into a QUIC close event as well close_event = self.quic._close_event or quic_events.ConnectionTerminated( QuicErrorCod

receive_close

tests/gamestonk_terminal/economy/test_economy_controller.py

Tests : Economy + Conftest (#1260) * Updating tests : economy * Updating tests : removing breaklines * Updating tests : economy * Updating tests : conftest * Updating tests : economy

OpenBBTerminal

Python

test_economy_controller.py

def test_call_cls(mocker): mocker.patch("os.system") controller = economy_controller.EconomyController(queue=None) controller.call_cls([]) assert controller.queue == [] os.system.assert_called_once_with("cls||clear") @pytest.mark.vcr(record_mode="none") @pytest.mark.parametrize( "func, queue, expected_queue", [ ( "call_exit", [], ["quit", "quit"], ), ("call_exit", ["help"], ["quit", "quit", "help"]), ("call_home", [], ["quit"]), ("call_help", [], []), ("call_quit", [], ["quit"]), ("call_quit", ["help"], ["quit", "help"]), ( "call_reset", [], [ "quit", "reset", "economy", ], ), ( "call_reset", ["help"], [ "quit", "reset", "economy", "help", ], ), ], )

683a8bdd83c1b931df111a5b2b8b19350930b73a

@pytest.mark.vcr(record_mode="none") @pytest.mark.parametrize( "func, queue, expected_queue", [ ( "call_exit", [], ["quit", "quit"], ), ("call_exit", ["help"], ["quit", "quit", "help"]), ("call_home", [], ["quit"]), ("call_help", [], []), ("call_quit", [], ["quit"]), ("call_quit", ["help"], ["quit", "help"]), ( "call_reset", [], [ "quit", "reset", "economy", ], ), ( "call_reset", ["help"], [ "quit", "reset", "economy", "help", ], ), ], )

https://github.com/OpenBB-finance/OpenBBTerminal.git

def test_call_cls(mocker): mocker.patch("os.system") controller = economy_controller.EconomyController(queue=None) controller.call_cls([]) assert controller.queue == [] os.system.assert_called_once_with("cls||clear") @pytest.mark.vcr(record_mode="none") @pyt

test_call_cls

pandas/tests/io/xml/test_xml.py

ENH: Add large file support for read_xml (#45724) * ENH: Add large file support for read_xml * Combine tests, slightly fix docs * Adjust pytest decorator on URL test; fix doc strings * Adjust tests for helper function * Add iterparse feature to some tests * Add IO docs link in docstring

pandas

Python

test_xml.py

def test_url_path_error(parser): url = "https://www.w3schools.com/xml/books.xml" with pytest.raises( ParserError, match=("iterparse is designed for large XML files") ): read_xml( url, parser=parser, iterparse={"row": ["shape", "degrees", "sides", "date"]}, )

fa7e31b8b19eb03dceebd09d03798363daae07d9

https://github.com/pandas-dev/pandas.git

def test_url_path_error(parser): url = "https://www.w3schools.com/xml/books.xml" with pytest.raises( ParserError, match=("iterparse is designed for large XML fi

test_url_path_error

tests/components/forked_daapd/test_media_player.py

Support announce and enqueue in forked-daapd (#77744)

core

Python

test_media_player.py

def test_master_state(hass, mock_api_object): state = hass.states.get(TEST_MASTER_ENTITY_NAME) assert state.state == STATE_PAUSED assert state.attributes[ATTR_FRIENDLY_NAME] == "forked-daapd server" assert state.attributes[ATTR_SUPPORTED_FEATURES] == SUPPORTED_FEATURES assert not state.attributes[ATTR_MEDIA_VOLUME_MUTED] assert state.attributes[ATTR_MEDIA_VOLUME_LEVEL] == 0.2 assert state.attributes[ATTR_MEDIA_CONTENT_ID] == 12322 assert state.attributes[ATTR_MEDIA_CONTENT_TYPE] == MediaType.MUSIC assert state.attributes[ATTR_MEDIA_DURATION] == 0.05 assert state.attributes[ATTR_MEDIA_POSITION] == 0.005 assert state.attributes[ATTR_MEDIA_TITLE] == "No album" # reversed for url assert state.attributes[ATTR_MEDIA_ARTIST] == "Some artist" assert state.attributes[ATTR_MEDIA_ALBUM_NAME] == "Some song" # reversed assert state.attributes[ATTR_MEDIA_ALBUM_ARTIST] == "The xx" assert state.attributes[ATTR_MEDIA_TRACK] == 1 assert not state.attributes[ATTR_MEDIA_SHUFFLE]

420285f7ef1e170f599cf22c031987e2ceefa353

https://github.com/home-assistant/core.git

def test_master_state(hass, mock_api_object): state = hass.states.get(TEST_MASTER_ENTITY_NAME) assert state.state == STATE_PAUSED assert state.attributes[ATTR_FRIENDLY_NAME]

test_master_state

modules/image/text_to_image/disco_diffusion_cnclip_vitb16/resize_right/interp_methods.py

add disco_diffusion_cnclip_vitb16 module

PaddleHub

Python

interp_methods.py

def lanczos2(x): fw, to_dtype, eps = set_framework_dependencies(x) return (((fw.sin(pi * x) * fw.sin(pi * x / 2) + eps) / ((pi**2 * x**2 / 2) + eps)) * to_dtype(abs(x) < 2)) @support_sz(6)

f4d6e64cdc132ae868699a0ba442f4ab1d304a14

@support_sz(6)

https://github.com/PaddlePaddle/PaddleHub.git

def lanczos2(x): fw, to_dtype, eps = set_framework_dependencies(x) return (((fw.sin(pi * x) * fw.sin(pi * x / 2) + eps) / ((pi**2 * x**2 / 2

lanczos2

wagtail/core/tests/test_page_model.py

Reformat with black

wagtail

Python

test_page_model.py

def test_copy_page_copies_recursively_to_the_same_tree(self): events_index = EventIndex.objects.get(url_path="/home/events/") old_christmas_event = ( events_index.get_children().filter(slug="christmas").first().specific ) old_christmas_event.save_revision() with self.assertRaises(Exception) as exception: events_index.copy( recursive=True, update_attrs={"title": "New events index", "slug": "new-events-index"}, to=events_index, ) self.assertEqual( str(exception.exception), "You cannot copy a tree branch recursively into itself", )

d10f15e55806c6944827d801cd9c2d53f5da4186

https://github.com/wagtail/wagtail.git

def test_copy_page_copies_recursively_to_the_same_tree(self): events_index = EventIndex.objects.get(url_path="/home/events/") old_christmas_event = ( events_index.get_children().filter(slug="christmas").first().specific ) old_christmas_event.save_revision() with self.assertRaises(Exception) as exception: events_index.copy( recursive=True, update_attrs={"title": "New events index", "slug": "new-events-index"}, to=events_index, ) self.assertEqual( str(exception.exception), "You cannot copy a tree branch recursively into itself", )

test_copy_page_copies_recursively_to_the_same_tree

awscli/utils.py

Improved readablity and simplified logic to find first quote character. * Updated "_find_quote_char_in_part" function, previously it was scanning input string multiple times however proposed logic does the same thing in single iteration. * Code branching is also reduced, only one if block is required.

aws-cli

Python

utils.py

def _find_quote_char_in_part(part): quote_char = None for ch in part: if ch in ('"', "'"): quote_char = ch break return quote_char

3c7e82860c6bd219f67d4373c715efb805500074

https://github.com/aws/aws-cli.git

def _find_quote_char_in_part(part): quote_char = None for ch in part: if ch in ('"', "'"): quote_char

_find_quote_char_in_part

pandas/core/arrays/numeric.py

BUG: NumericArray * td64_array (#45622)

pandas

Python

numeric.py

def _arith_method(self, other, op): op_name = op.__name__ omask = None if isinstance(other, BaseMaskedArray): other, omask = other._data, other._mask elif is_list_like(other): if not isinstance(other, ExtensionArray): other = np.asarray(other) if other.ndim > 1: raise NotImplementedError("can only perform ops with 1-d structures") # We wrap the non-masked arithmetic logic used for numpy dtypes # in Series/Index arithmetic ops. other = ops.maybe_prepare_scalar_for_op(other, (len(self),)) pd_op = ops.get_array_op(op) other = ensure_wrapped_if_datetimelike(other) mask = self._propagate_mask(omask, other) if other is libmissing.NA: result = np.ones_like(self._data) if "truediv" in op_name and self.dtype.kind != "f": # The actual data here doesn't matter since the mask # will be all-True, but since this is division, we want # to end up with floating dtype. result = result.astype(np.float64) else: # Make sure we do this before the "pow" mask checks # to get an expected exception message on shape mismatch. if self.dtype.kind in ["i", "u"] and op_name in ["floordiv", "mod"]: # ATM we don't match the behavior of non-masked types with # respect to floordiv-by-zero pd_op = op with np.errstate(all="ignore"): result = pd_op(self._data, other) if op_name == "pow": # 1 ** x is 1. mask = np.where((self._data == 1) & ~self._mask, False, mask) # x ** 0 is 1. if omask is not None: mask = np.where((other == 0) & ~omask, False, mask) elif other is not libmissing.NA: mask = np.where(other == 0, False, mask) elif op_name == "rpow": # 1 ** x is 1. if omask is not None: mask = np.where((other == 1) & ~omask, False, mask) elif other is not libmissing.NA: mask = np.where(other == 1, False, mask) # x ** 0 is 1. mask = np.where((self._data == 0) & ~self._mask, False, mask) return self._maybe_mask_result(result, mask, other, op_name) _HANDLED_TYPES = (np.ndarray, numbers.Number)

57d7768c205d30cc50ba9b42d60d24d1e32eb249

https://github.com/pandas-dev/pandas.git

def _arith_method(self, other, op): op_name = op.__name__ omask = None if isinstance(other, BaseMaskedArray): other, omask = other._data, other._mask elif is_list_like(other): if not isinstance(other, ExtensionArray): other = np.asarray(other) if other.ndim > 1: raise NotImplementedError("can only perform ops with 1-d structures") # We wrap the non-masked arithmetic logic used for numpy dtypes # in Series/Index arithmetic ops. other = ops.maybe_prepare_scalar_for_op(other, (len(self),)) pd_op = ops.get_array_op(op) other

_arith_method

lib/matplotlib/backends/backend_gtk3.py

Separately track modifier keys for mouse events. Whether the event modifiers are directly available on enter/leave events depends on the backend, but all are handled here (except possibly for macos, which I haven't checked).

matplotlib

Python

backend_gtk3.py

def button_press_event(self, widget, event): MouseEvent("button_press_event", self, *self._mpl_coords(event), event.button, modifiers=self._mpl_modifiers(event.state), guiEvent=event)._process() return False # finish event propagation?

b4e9e3131cdd7f1ad33ea06e21e7d3e51762af91

https://github.com/matplotlib/matplotlib.git

def button_press_event(self, widget, event): MouseEvent("button_press_event", self,

button_press_event

python/ray/util/inspect.py

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

ray

Python

inspect.py

def is_cython(obj): # TODO(suo): We could split these into two functions, one for Cython # functions and another for Cython methods. # TODO(suo): There doesn't appear to be a Cython function 'type' we can # check against via isinstance. Please correct me if I'm wrong.

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

https://github.com/ray-project/ray.git

def is_cython(obj): # TODO(suo): We could split these into two functions, one for Cython # functions and another for Cyth

is_cython

tests/models/test_cleartasks.py

Replace usage of `DummyOperator` with `EmptyOperator` (#22974) * Replace usage of `DummyOperator` with `EmptyOperator`

airflow

Python

test_cleartasks.py

def test_clear_task_instances_without_task(self, dag_maker): with dag_maker( 'test_clear_task_instances_without_task', start_date=DEFAULT_DATE, end_date=DEFAULT_DATE + datetime.timedelta(days=10), ) as dag: task0 = EmptyOperator(task_id='task0') task1 = EmptyOperator(task_id='task1', retries=2) dr = dag_maker.create_dagrun( state=State.RUNNING, run_type=DagRunType.SCHEDULED, ) ti0, ti1 = sorted(dr.task_instances, key=lambda ti: ti.task_id) ti0.refresh_from_task(task0) ti1.refresh_from_task(task1) ti0.run() ti1.run() # Remove the task from dag. dag.task_dict = {} assert not dag.has_task(task0.task_id) assert not dag.has_task(task1.task_id) with create_session() as session: # we use order_by(task_id) here because for the test DAG structure of ours # this is equivalent to topological sort. It would not work in general case # but it works for our case because we specifically constructed test DAGS # in the way that those two sort methods are equivalent qry = session.query(TI).filter(TI.dag_id == dag.dag_id).order_by(TI.task_id).all() clear_task_instances(qry, session) # When dag is None, max_tries will be maximum of original max_tries or try_number. ti0.refresh_from_db() ti1.refresh_from_db() # Next try to run will be try 2 assert ti0.try_number == 2 assert ti0.max_tries == 1 assert ti1.try_number == 2 assert ti1.max_tries == 2

49e336ae0302b386a2f47269a6d13988382d975f

https://github.com/apache/airflow.git

def test_clear_task_instances_without_task(self, dag_maker): with dag_maker( 'test_clear_task_instances_without_task', start_date=DEFAULT_DATE, end_date=DEFAULT_DATE + datetime.timedelta(days=10), ) as dag: task0 = EmptyOperator(task_id='task0') task1 = EmptyOperator(task_id='task1', retries=2) dr = dag_maker.create_dagrun( state=State.RUNNING, run_type=DagRunType.SCHEDULED, ) ti0, ti1 = sorted(dr.task_instances, key=lambda ti: ti.task_id) ti0.refresh_from_task(task0) ti1.refresh_from_task(task1) ti0.run() ti1.run() # Remove the task from dag. dag.task_dict = {} assert not dag.has_task(task0.task_id) assert not dag.has_task(task1.task_id) with create_session() as session: # we use order_by(task_id) here because for the test DAG structure of ours # this is equivalent to topological sort. It would not work in general case # but it works for our case because we specifically constructed test DAGS # in the way that those two sort methods are equivalent qry = session.query(TI).filter(TI.dag_id == dag.dag_id).order_by(TI.task_id).all() clear_task_instances(qry, session) # When dag is None

test_clear_task_instances_without_task

src/PIL/ImageFile.py

Remove redundant parentheses

Pillow

Python

ImageFile.py

def set_as_raw(self, data, rawmode=None): if not rawmode: rawmode = self.mode d = Image._getdecoder(self.mode, "raw", rawmode) d.setimage(self.im, self.state.extents()) s = d.decode(data) if s[0] >= 0: raise ValueError("not enough image data") if s[1] != 0: raise ValueError("cannot decode image data")

ee85e387bab535e2339b9d3cd1ab87c61d23af15

https://github.com/python-pillow/Pillow.git

def set_as_raw(self, data, rawmode=None):

set_as_raw

setup.py

refactor: remove jinad (#4550)

jina

Python

setup.py

def register_ac(): import os import re from pathlib import Path home = str(Path.home()) resource_path = 'jina/resources/completions/jina.%s' regex = r'#\sJINA_CLI_BEGIN(.*)#\sJINA_CLI_END' _check = {'zsh': '.zshrc', 'bash': '.bashrc', 'fish': '.fish'}

2ce767517532ebbf85ade4b84cfba0f7bb69c4f9

https://github.com/jina-ai/jina.git

def register_ac(): import os import re from pathlib import Path home = str(Path.home()) resource_path = 'jina/resources/completions/jina.%s' regex

register_ac

python/ccxt/async_support/ndax.py

1.70.82 [ci skip]

ccxt

Python

ndax.py

async def fetch_markets(self, params={}): omsId = self.safe_integer(self.options, 'omsId', 1) request = { 'omsId': omsId, } response = await self.publicGetGetInstruments(self.extend(request, params)) # # [ # { # "OMSId":1, # "InstrumentId":3, # "Symbol":"LTCBTC", # "Product1":3, # "Product1Symbol":"LTC", # "Product2":1, # "Product2Symbol":"BTC", # "InstrumentType":"Standard", # "VenueInstrumentId":3, # "VenueId":1, # "SortIndex":0, # "SessionStatus":"Running", # "PreviousSessionStatus":"Stopped", # "SessionStatusDateTime":"2020-11-25T19:42:15.245Z", # "SelfTradePrevention":true, # "QuantityIncrement":0.0000000100000000000000000000, # "PriceIncrement":0.0000000100000000000000000000, # "MinimumQuantity":0.0100000000000000000000000000, # "MinimumPrice":0.0000010000000000000000000000, # "VenueSymbol":"LTCBTC", # "IsDisable":false, # "MasterDataId":0, # "PriceCollarThreshold":0.0000000000000000000000000000, # "PriceCollarPercent":0.0000000000000000000000000000, # "PriceCollarEnabled":false, # "PriceFloorLimit":0.0000000000000000000000000000, # "PriceFloorLimitEnabled":false, # "PriceCeilingLimit":0.0000000000000000000000000000, # "PriceCeilingLimitEnabled":false, # "CreateWithMarketRunning":true, # "AllowOnlyMarketMakerCounterParty":false, # "PriceCollarIndexDifference":0.0000000000000000000000000000, # "PriceCollarConvertToOtcEnabled":false, # "PriceCollarConvertToOtcClientUserId":0, # "PriceCollarConvertToOtcAccountId":0, # "PriceCollarConvertToOtcThreshold":0.0000000000000000000000000000, # "OtcConvertSizeThreshold":0.0000000000000000000000000000, # "OtcConvertSizeEnabled":false, # "OtcTradesPublic":true, # "PriceTier":0 # }, # ] # result = [] for i in range(0, len(response)): market = response[i] id = self.safe_string(market, 'InstrumentId') # lowercaseId = self.safe_string_lower(market, 'symbol') baseId = self.safe_string(market, 'Product1') quoteId = self.safe_string(market, 'Product2') base = self.safe_currency_code(self.safe_string(market, 'Product1Symbol')) quote = self.safe_currency_code(self.safe_string(market, 'Product2Symbol')) sessionStatus = self.safe_string(market, 'SessionStatus') isDisable = self.safe_value(market, 'IsDisable') sessionRunning = (sessionStatus == 'Running') result.append({ 'id': id, 'symbol': base + '/' + quote, 'base': base, 'quote': quote, 'settle': None, 'baseId': baseId, 'quoteId': quoteId, 'settleId': None, 'type': 'spot', 'spot': True, 'margin': False, 'swap': False, 'future': False, 'option': False, 'active': (sessionRunning and not isDisable), 'contract': False, 'linear': None, 'inverse': None, 'contractSize': None, 'expiry': None, 'expiryDatetime': None, 'strike': None, 'optionType': None, 'precision': { 'amount': self.safe_number(market, 'QuantityIncrement'), 'price': self.safe_number(market, 'PriceIncrement'), }, 'limits': { 'leverage': { 'min': None, 'max': None, }, 'amount': { 'min': self.safe_number(market, 'MinimumQuantity'), 'max': None, }, 'price': { 'min': self.safe_number(market, 'MinimumPrice'), 'max': None, }, 'cost': { 'min': None, 'max': None, }, }, 'info': market, }) return result

1cfeeec8240c4c7e93e632cd9e42be2a1be33b16

https://github.com/ccxt/ccxt.git

async def fetch_markets(self, params={}): omsId = self.safe_integer(self.options, 'omsId', 1) request = { 'omsId': omsId, } response = await self.publicGetGetInstruments(self.extend(request, params)) # # [ # { # "OMSId":1, # "InstrumentId":3, # "Symbol":"LTCBTC", # "Product1":3, # "Product1Symbol":"LTC", # "Product2":1, # "Product2Symbol":"BTC", # "InstrumentType":"Standard", # "VenueInstrumentId":3, # "VenueId":1, # "SortIndex":0, # "SessionStatus":"Running", # "PreviousSessionStatus":"Stopped", # "SessionStatusDateTime":"2020-11-25T19:42:15.245Z", # "SelfTradePrevention":true, # "QuantityIncrement":0.0000000100000000000000000000, # "PriceIncrement":0.0000000100000000000000000000, # "MinimumQuantity":0.0100000000000000000000000000, # "MinimumPrice":0.0000010000000000000000000000, # "VenueSymbol":"LTCBTC", # "IsDisable":false, # "MasterDataId":0, # "PriceCollarThreshold":0.0000000000000000000000000000, # "PriceCollarPercent":0.0000000000000000000000000000, # "PriceCollarEnabled":false, # "PriceFloorLimit":0.0000000000000000000000000000, # "PriceFloorLimitEnabled":false, # "PriceCeilingLimit":0.0000000000000000000000000000, # "PriceCeilingLimitEnabled":false, # "CreateWithMarketRunning":true, # "AllowOnlyMarketMakerCounterParty":false, # "PriceCollarIndexDifference":0.0000000000000000000000000000, # "PriceCollarConvertToOtcEnabled":false, # "PriceCollarCon

fetch_markets

python3.10.4/Lib/inspect.py

add python 3.10.4 for windows

XX-Net

Python

inspect.py

def getinnerframes(tb, context=1): framelist = [] while tb: frameinfo = (tb.tb_frame,) + getframeinfo(tb, context) framelist.append(FrameInfo(*frameinfo)) tb = tb.tb_next return framelist

8198943edd73a363c266633e1aa5b2a9e9c9f526

https://github.com/XX-net/XX-Net.git

def getinnerframes(tb, context=1): framelist = [] while tb: frameinfo = (tb.tb_frame,) + g

getinnerframes

erpnext/regional/india/e_invoice/utils.py

style: format code with black

erpnext

Python

utils.py

def show_link_to_error_log(invoice, einvoice): err_log = log_error(einvoice) link_to_error_log = get_link_to_form("Error Log", err_log.name, "Error Log") frappe.throw( _( "An error occurred while creating e-invoice for {}. Please check {} for more information." ).format(invoice.name, link_to_error_log), title=_("E Invoice Creation Failed"), )

494bd9ef78313436f0424b918f200dab8fc7c20b

https://github.com/frappe/erpnext.git

def show_link_to_error_log(invoice, einvoice): err_log = log_error(einvoice) link_to_error_log = get_link_to_form("Error Log", err_

show_link_to_error_log

tests/sentry/api/endpoints/test_user_notification_details.py

ref(tests): Remove `get_valid_response()` (#34822)

sentry

Python

test_user_notification_details.py

def test_lookup_other_user(self): user_b = self.create_user(email="b@example.com") self.get_error_response(user_b.id, status_code=403)

096b5511e244eecd8799b2a0324655207ce8985e

https://github.com/getsentry/sentry.git

def test_lookup_other_user(self): user_b = s

test_lookup_other_user

saleor/plugins/webhook/tests/subscription_webhooks/fixtures.py

Improve subscription payload tests and structure (#9719) * Refactor and update tests for subscriptions * Refactor and update tests for subscriptions * fixes after rebasing * fix category payload genertor * small fixes * fixes after rebase * fix linters errors * add sorting to payload generators, fixes after review * fix linters * remove commented

saleor

Python

fixtures.py

def subscription_page_created_webhook(subscription_webhook): return subscription_webhook( subscription_queries.PAGE_CREATED, WebhookEventAsyncType.PAGE_CREATED ) @pytest.fixture

107cfb229e75f14efc75a20c3d1f421ccb50f244

@pytest.fixture

https://github.com/saleor/saleor.git

def subscription_page_created_webhook(subscription_webhook): return subscription_webhook( subscription_queries.PAGE_CREATED, WebhookEventAsyncType.PAGE_CREATED ) @pytest.fi

subscription_page_created_webhook

onnx/backend/test/case/node/dropout.py

Use Python type annotations rather than comments (#3962) * These have been supported since Python 3.5. ONNX doesn't support Python < 3.6, so we can use the annotations. Diffs generated by https://pypi.org/project/com2ann/. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Remove MYPY conditional logic in gen_proto.py It breaks the type annotations and shouldn't be needed. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Get rid of MYPY bool from more scripts Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * move Descriptors class above where its referenced in type annotation Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fixes Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * remove extra blank line Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotations Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotation in gen_docs Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix Operators.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix TestCoverage.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix protoc-gen-mypy.py Signed-off-by: Gary Miguel <garymiguel@microsoft.com>

onnx

Python

dropout.py

def export_training_default_ratio_mask() -> None: seed = np.int64(0) node = onnx.helper.make_node( 'Dropout', inputs=['x', 'r', 't'], outputs=['y', 'z'], seed=seed ) x = np.random.randn(3, 4, 5).astype(np.float32) r = np.float32(0.5) t = np.bool_(True) y, z = dropout(x, r, training_mode=t, return_mask=True) expect(node, inputs=[x, r, t], outputs=[y, z], name='test_training_dropout_default_mask')

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

https://github.com/onnx/onnx.git

def export_training_default_ratio_mask() -> None: seed = np.int64(0) node = onnx.helper.make_node( 'Dropout', inputs=['x', 'r', 't'], outputs=['y', 'z'], seed=seed ) x = np.random.randn(3, 4, 5).astype(np.float32) r = np.float32(0.5) t = np.bool_(True) y, z = dropout(x, r, training_mode=t, return_mask=True) expect(node, inputs=[x, r, t],

export_training_default_ratio_mask

pandas/tests/io/xml/test_xml_dtypes.py

ENH: Add large file support for read_xml (#45724) * ENH: Add large file support for read_xml * Combine tests, slightly fix docs * Adjust pytest decorator on URL test; fix doc strings * Adjust tests for helper function * Add iterparse feature to some tests * Add IO docs link in docstring

pandas

Python

test_xml_dtypes.py

def test_dtype_nullable_int(parser): df_result = read_xml(xml_types, dtype={"sides": "Int64"}, parser=parser) df_iter = read_xml_iterparse( xml_types, parser=parser, dtype={"sides": "Int64"}, iterparse={"row": ["shape", "degrees", "sides"]}, ) df_expected = DataFrame( { "shape": ["square", "circle", "triangle"], "degrees": [360, 360, 180], "sides": Series([4.0, float("nan"), 3.0]).astype("Int64"), } ) tm.assert_frame_equal(df_result, df_expected) tm.assert_frame_equal(df_iter, df_expected)

fa7e31b8b19eb03dceebd09d03798363daae07d9

https://github.com/pandas-dev/pandas.git

def test_dtype_nullable_int(parser): df_result = read_xml(xml_types, dtype={"sides": "Int64"}, parser=parser) df_iter = read_xml_iterparse( xml_types, parser=parser, dtype={"sides": "Int64"}, iterparse={"row": ["shape", "degrees", "sides"]}, ) df_expected = DataFrame( { "shape": ["square", "circle", "triangle"], "degrees": [360, 360, 180], "sides": Series([4.0, float("nan"), 3.0]).astype("Int64"),

test_dtype_nullable_int

code/deep/BJMMD/caffe/python/caffe/test/test_coord_map.py

Balanced joint maximum mean discrepancy for deep transfer learning

transferlearning

Python

test_coord_map.py

def test_nd_conv(self): n = caffe.NetSpec() # define data with 3 spatial dimensions, otherwise the same net n.data = L.Input(shape=dict(dim=[2, 3, 100, 100, 100])) n.conv = L.Convolution( n.data, num_output=10, kernel_size=[3, 3, 3], stride=[1, 1, 1], pad=[0, 1, 2]) n.pool = L.Pooling( n.conv, pool=P.Pooling.MAX, kernel_size=2, stride=2, pad=0) n.deconv = L.Deconvolution( n.pool, num_output=10, kernel_size=4, stride=2, pad=0) ax, a, b = coord_map_from_to(n.deconv, n.data) self.assertEquals(ax, 1) self.assertTrue(len(a) == len(b)) self.assertTrue(np.all(a == 1)) self.assertEquals(b[0] - 1, b[1]) self.assertEquals(b[1] - 1, b[2])

cc4d0564756ca067516f71718a3d135996525909

https://github.com/jindongwang/transferlearning.git

def test_nd_conv(self): n = caffe.NetSpec() # define data with 3 spatial dimensions, otherwise the same net n.data = L.Input(shape=dict(dim=[2, 3, 100, 100, 100])) n.conv = L.Convolution( n.data,

test_nd_conv

tests/components/logbook/test_init.py

Add json decode caching to logbook (#71080)

core

Python

test_init.py

def test_unsupported_attributes_in_cache_throws(hass): entity_attr_cache = logbook.EntityAttributeCache(hass) event = MockLazyEventPartialState(EVENT_STATE_CHANGED) with pytest.raises(ValueError): entity_attr_cache.get("sensor.xyz", "not_supported", event)

b8442d9340b569d10e0593bb0576bdcdb9ea55e3

https://github.com/home-assistant/core.git

def test_unsupported_attributes_in_cache_throws(hass): entity_attr_cache = logbook.EntityAttributeCache(hass) event = MockLazyEventPartialState(EVENT_STATE_CHANGED) with pytest.raises(ValueError): ent

test_unsupported_attributes_in_cache_throws

scapy/contrib/http2.py

E275 - Missing whitespace after keyword (#3711) Co-authored-by: Alexander Aring <alex.aring@gmail.com> Co-authored-by: Anmol Sarma <me@anmolsarma.in> Co-authored-by: antoine.torre <torreantoine1@gmail.com> Co-authored-by: Antoine Vacher <devel@tigre-bleu.net> Co-authored-by: Arnaud Ebalard <arno@natisbad.org> Co-authored-by: atlowl <86038305+atlowl@users.noreply.github.com> Co-authored-by: Brian Bienvenu <brian@bienvenu.id.au> Co-authored-by: Chris Packham <chris.packham@alliedtelesis.co.nz> Co-authored-by: CQ <cq674350529@163.com> Co-authored-by: Daniel Collins <kinap@users.noreply.github.com> Co-authored-by: Federico Maggi <federico.maggi@gmail.com> Co-authored-by: Florian Maury <florian.maury@ssi.gouv.fr> Co-authored-by: _Frky <3105926+Frky@users.noreply.github.com> Co-authored-by: g-mahieux <37588339+g-mahieux@users.noreply.github.com> Co-authored-by: gpotter2 <gabriel@potter.fr> Co-authored-by: Guillaume Valadon <guillaume@valadon.net> Co-authored-by: Hao Zheng <haozheng10@gmail.com> Co-authored-by: Haresh Khandelwal <hareshkhandelwal@gmail.com> Co-authored-by: Harri Hämäläinen <hhamalai@iki.fi> Co-authored-by: hecke <hecke@naberius.de> Co-authored-by: Jan Romann <jan.romann@gmail.com> Co-authored-by: Jan Sebechlebsky <sebechlebskyjan@gmail.com> Co-authored-by: jdiog0 <43411724+jdiog0@users.noreply.github.com> Co-authored-by: jockque <38525640+jockque@users.noreply.github.com> Co-authored-by: Julien Bedel <30991560+JulienBedel@users.noreply.github.com> Co-authored-by: Keith Scott <kscott@mitre.org> Co-authored-by: Kfir Gollan <kfir@drivenets.com> Co-authored-by: Lars Munch <lars@segv.dk> Co-authored-by: ldp77 <52221370+ldp77@users.noreply.github.com> Co-authored-by: Leonard Crestez <cdleonard@gmail.com> Co-authored-by: Marcel Patzlaff <mpatzlaff@benocs.com> Co-authored-by: Martijn Thé <martijnthe@users.noreply.github.com> Co-authored-by: Martine Lenders <authmillenon@gmail.com> Co-authored-by: Michael Farrell <micolous+git@gmail.com> Co-authored-by: Michał Mirosław <mirq-linux@rere.qmqm.pl> Co-authored-by: mkaliszan <mkaliszan@benocs.com> Co-authored-by: mtury <maxence.tury@ssi.gouv.fr> Co-authored-by: Neale Ranns <nranns@cisco.com> Co-authored-by: Octavian Toader <Octavian.Toader@belden.com> Co-authored-by: Peter Eisenlohr <peter@eisenlohr.org> Co-authored-by: Phil <phil@secdev.org> Co-authored-by: Pierre Lalet <pierre@droids-corp.org> Co-authored-by: Pierre Lorinquer <pierre.lorinquer@ssi.gouv.fr> Co-authored-by: piersoh <42040737+piersoh@users.noreply.github.com> Co-authored-by: plorinquer <pierre.lorinquer@ssi.gouv.fr> Co-authored-by: pvinci <pvinci@users.noreply.github.com> Co-authored-by: Rahul Jadhav <nyrahul@gmail.com> Co-authored-by: Robin Jarry <robin.jarry@6wind.com> Co-authored-by: romain-perez <51962832+romain-perez@users.noreply.github.com> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <sd@queasysnail.net> Co-authored-by: Sebastian Baar <sebastian.baar@gmx.de> Co-authored-by: sebastien mainand <sebastien.mainand@ssi.gouv.fr> Co-authored-by: smehner1 <smehner1@gmail.com> Co-authored-by: speakinghedge <hecke@naberius.de> Co-authored-by: Steven Van Acker <steven@singularity.be> Co-authored-by: Thomas Faivre <thomas.faivre@6wind.com> Co-authored-by: Tran Tien Dat <peter.trantiendat@gmail.com> Co-authored-by: Wael Mahlous <wael.mahlous@gmail.com> Co-authored-by: waeva <74464394+waeva@users.noreply.github.com> Co-authored-by: Alexander Aring <alex.aring@gmail.com> Co-authored-by: Anmol Sarma <me@anmolsarma.in> Co-authored-by: antoine.torre <torreantoine1@gmail.com> Co-authored-by: Antoine Vacher <devel@tigre-bleu.net> Co-authored-by: Arnaud Ebalard <arno@natisbad.org> Co-authored-by: atlowl <86038305+atlowl@users.noreply.github.com> Co-authored-by: Brian Bienvenu <brian@bienvenu.id.au> Co-authored-by: Chris Packham <chris.packham@alliedtelesis.co.nz> Co-authored-by: CQ <cq674350529@163.com> Co-authored-by: Daniel Collins <kinap@users.noreply.github.com> Co-authored-by: Federico Maggi <federico.maggi@gmail.com> Co-authored-by: Florian Maury <florian.maury@ssi.gouv.fr> Co-authored-by: _Frky <3105926+Frky@users.noreply.github.com> Co-authored-by: g-mahieux <37588339+g-mahieux@users.noreply.github.com> Co-authored-by: gpotter2 <gabriel@potter.fr> Co-authored-by: Guillaume Valadon <guillaume@valadon.net> Co-authored-by: Hao Zheng <haozheng10@gmail.com> Co-authored-by: Haresh Khandelwal <hareshkhandelwal@gmail.com> Co-authored-by: Harri Hämäläinen <hhamalai@iki.fi> Co-authored-by: hecke <hecke@naberius.de> Co-authored-by: Jan Romann <jan.romann@gmail.com> Co-authored-by: Jan Sebechlebsky <sebechlebskyjan@gmail.com> Co-authored-by: jdiog0 <43411724+jdiog0@users.noreply.github.com> Co-authored-by: jockque <38525640+jockque@users.noreply.github.com> Co-authored-by: Julien Bedel <30991560+JulienBedel@users.noreply.github.com> Co-authored-by: Keith Scott <kscott@mitre.org> Co-authored-by: Kfir Gollan <kfir@drivenets.com> Co-authored-by: Lars Munch <lars@segv.dk> Co-authored-by: ldp77 <52221370+ldp77@users.noreply.github.com> Co-authored-by: Leonard Crestez <cdleonard@gmail.com> Co-authored-by: Marcel Patzlaff <mpatzlaff@benocs.com> Co-authored-by: Martijn Thé <martijnthe@users.noreply.github.com> Co-authored-by: Martine Lenders <authmillenon@gmail.com> Co-authored-by: Michael Farrell <micolous+git@gmail.com> Co-authored-by: Michał Mirosław <mirq-linux@rere.qmqm.pl> Co-authored-by: mkaliszan <mkaliszan@benocs.com> Co-authored-by: mtury <maxence.tury@ssi.gouv.fr> Co-authored-by: Neale Ranns <nranns@cisco.com> Co-authored-by: Octavian Toader <Octavian.Toader@belden.com> Co-authored-by: Peter Eisenlohr <peter@eisenlohr.org> Co-authored-by: Phil <phil@secdev.org> Co-authored-by: Pierre Lalet <pierre@droids-corp.org> Co-authored-by: Pierre Lorinquer <pierre.lorinquer@ssi.gouv.fr> Co-authored-by: piersoh <42040737+piersoh@users.noreply.github.com> Co-authored-by: pvinci <pvinci@users.noreply.github.com> Co-authored-by: Rahul Jadhav <nyrahul@gmail.com> Co-authored-by: Robin Jarry <robin.jarry@6wind.com> Co-authored-by: romain-perez <51962832+romain-perez@users.noreply.github.com> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <sd@queasysnail.net> Co-authored-by: Sebastian Baar <sebastian.baar@gmx.de> Co-authored-by: sebastien mainand <sebastien.mainand@ssi.gouv.fr> Co-authored-by: smehner1 <smehner1@gmail.com> Co-authored-by: Steven Van Acker <steven@singularity.be> Co-authored-by: Thomas Faivre <thomas.faivre@6wind.com> Co-authored-by: Tran Tien Dat <peter.trantiendat@gmail.com> Co-authored-by: Wael Mahlous <wael.mahlous@gmail.com> Co-authored-by: waeva <74464394+waeva@users.noreply.github.com>

scapy

Python

http2.py

def _parse_multi_byte(self, s): # type: (str) -> int assert len(s) >= 2 tmp_len = len(s) value = 0 i = 1 byte = orb(s[i]) # For CPU sake, stops at an arbitrary large number! max_value = 1 << 64 # As long as the MSG is set, an another byte must be read while byte & 0x80: value += (byte ^ 0x80) << (7 * (i - 1)) if value > max_value: raise error.Scapy_Exception( 'out-of-bound value: the string encodes a value that is too large (>2^{{64}}): {}'.format(value) # noqa: E501 ) i += 1 assert i < tmp_len, 'EINVAL: x: out-of-bound read: the string ends before the AbstractUVarIntField!' # noqa: E501 byte = orb(s[i]) value += byte << (7 * (i - 1)) value += self._max_value assert value >= 0 return value

08b1f9d67c8e716fd44036a027bdc90dcb9fcfdf

https://github.com/secdev/scapy.git

def _parse_multi_byte(self, s): # type: (str) -> int assert len(s) >= 2 tmp_len = len(s) value = 0 i = 1 byte = orb(s[i]) # For CPU sake, stops at an arbitrary large numb

_parse_multi_byte

python3.10.4/Lib/email/iterators.py

add python 3.10.4 for windows

XX-Net

Python

iterators.py

def walk(self): yield self if self.is_multipart(): for subpart in self.get_payload(): yield from subpart.walk()  # These two functions are imported into the Iterators.py interface module.

8198943edd73a363c266633e1aa5b2a9e9c9f526

https://github.com/XX-net/XX-Net.git

def walk(self): yield self if self.is_multipart(): for subpart in self.get_payload(): yield from subpart.walk()  # These two functions are

walk

onnx/backend/test/case/node/reduce_log_sum.py

Use Python type annotations rather than comments (#3962) * These have been supported since Python 3.5. ONNX doesn't support Python < 3.6, so we can use the annotations. Diffs generated by https://pypi.org/project/com2ann/. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Remove MYPY conditional logic in gen_proto.py It breaks the type annotations and shouldn't be needed. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Get rid of MYPY bool from more scripts Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * move Descriptors class above where its referenced in type annotation Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fixes Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * remove extra blank line Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotations Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotation in gen_docs Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix Operators.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix TestCoverage.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix protoc-gen-mypy.py Signed-off-by: Gary Miguel <garymiguel@microsoft.com>

onnx

Python

reduce_log_sum.py

def export_keepdims() -> None: node = onnx.helper.make_node( 'ReduceLogSum', inputs=['data'], outputs=["reduced"] ) data = np.random.ranf([3, 4, 5]).astype(np.float32) reduced = np.log(np.sum(data, keepdims=True)) expect(node, inputs=[data], outputs=[reduced], name='test_reduce_log_sum_default')

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

https://github.com/onnx/onnx.git

def export_keepdims() -> None: node = onnx.helper.make_node( 'ReduceLogSum',

export_keepdims

homeassistant/components/upnp/coordinator.py

Move upnp derived sensors to library, be more robust about failing getting some data (#79955)

core

Python

coordinator.py

async def _async_update_data(self) -> Mapping[str, Any]: try: return await self.device.async_get_data() except UpnpCommunicationError as exception: LOGGER.debug( "Caught exception when updating device: %s, exception: %s", self.device, exception, ) raise UpdateFailed( f"Unable to communicate with IGD at: {self.device.device_url}" ) from exception

d50795af2b861e28e717f0479ad6e800b7030620

https://github.com/home-assistant/core.git

async def _async_update_data(self) -> Mapping[str, Any]: try: return await self.device.async_get_data() except UpnpCommunicationError as exception: LOGGER.debug( "Caught exception when updating device: %s, exception: %s", self.device, exception, ) raise UpdateFailed( f"Unable to communicate with IGD at: {self.de

_async_update_data

src/documents/consumer.py

Adds further testing to cover scripts with non-zero exit codes

paperless-ngx

Python

consumer.py

def run_pre_consume_script(self): if not settings.PRE_CONSUME_SCRIPT: return if not os.path.isfile(settings.PRE_CONSUME_SCRIPT): self._fail( MESSAGE_PRE_CONSUME_SCRIPT_NOT_FOUND, f"Configured pre-consume script " f"{settings.PRE_CONSUME_SCRIPT} does not exist.", ) self.log("info", f"Executing pre-consume script {settings.PRE_CONSUME_SCRIPT}") filepath_arg = os.path.normpath(self.path) script_env = os.environ.copy() script_env["DOCUMENT_SOURCE_PATH"] = filepath_arg try: completed_proc = run( args=[ settings.PRE_CONSUME_SCRIPT, filepath_arg, ], env=script_env, capture_output=True, ) self._log_script_outputs(completed_proc) # Raises exception on non-zero output completed_proc.check_returncode() except Exception as e: self._fail( MESSAGE_PRE_CONSUME_SCRIPT_ERROR, f"Error while executing pre-consume script: {e}", exc_info=True, exception=e, )

057f6016cc92f6d21b04b9a16dc6f0b255c8b401

https://github.com/paperless-ngx/paperless-ngx.git

def run_pre_consume_script(self): if not settings.PRE_CONSUME_SCRIPT: return if not os.path.isfile(settings.PRE_CONSUME_SCRIPT): self._fail( MESSAGE_PRE_CONSUME_SCRIPT_NOT_FOUND, f"Configured pre-consume script " f"{settings.PRE_CONSUME_SCRIPT} does not exist.", ) self.log("info", f"Executing pre-consume script {settings.PRE_CONSUME_SCRIPT}") filepath_arg = os.path.normpath(self.path) script_env = os.environ.copy() script_env["DOCUMENT_SOURCE_PATH"] = filepath_arg try: completed_proc = run( args=[ settings.PRE_CONSUME_SCRIPT, filepath_arg, ], env=script_env, capture_output=True, ) self._log_script_outputs(completed_proc) # Raises exception on non-zero output completed_proc.check_returncode() except Exception as e: self._fail( MESSAGE_PRE_CONSUME_SCRIPT_ERROR, f"Error while executing pre-consume script: {e}", exc_info=True, exception=e,

run_pre_consume_script

keras/distribute/mirrored_strategy_test.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

mirrored_strategy_test.py

def testTrainAndServeWithKPL(self, distribution): use_adapt = False test_utils_obj = kpl_test_utils.DistributeKplTestUtils() with distribution.scope(): ( feature_mapper, label_mapper, ) = test_utils_obj.define_kpls_for_training(use_adapt) model = test_utils_obj.define_model() optimizer = rmsprop.RMSprop(learning_rate=0.1) accuracy = keras.metrics.Accuracy()

84afc5193d38057e2e2badf9c889ea87d80d8fbf

https://github.com/keras-team/keras.git

def testTrainAndServeWithKPL(self, distribution): use_adapt = False test_utils_obj = kpl_test_utils.DistributeKplTestUtils(

testTrainAndServeWithKPL

setup_ts.py

Bump node.js to 18 (#5206)

nni

Python

setup_ts.py

def copy_nni_node(version): _print('Copying files') if sys.version_info >= (3, 8): shutil.copytree('ts/nni_manager/dist', 'nni_node', dirs_exist_ok=True) else: for item in os.listdir('ts/nni_manager/dist'): subsrc = os.path.join('ts/nni_manager/dist', item) subdst = os.path.join('nni_node', item) if os.path.isdir(subsrc): shutil.copytree(subsrc, subdst) else: shutil.copy2(subsrc, subdst) shutil.copyfile('ts/nni_manager/package-lock.json', 'nni_node/package-lock.lock') Path('nni_node/nni_manager.tsbuildinfo').unlink() package_json = json.load(open('ts/nni_manager/package.json')) if version: while len(version.split('.')) < 3: # node.js semver requires at least three parts version = version + '.0' package_json['version'] = version json.dump(package_json, open('nni_node/package.json', 'w'), indent=2) if sys.platform == 'win32': # On Windows, manually install node-gyp for sqlite3. _npm('ts/nni_manager', 'install', '--global', 'node-gyp') # reinstall without development dependencies prod_path = Path('nni_node').resolve() _yarn(str(prod_path), 'install', '--production') shutil.copytree('ts/webui/build', 'nni_node/static') if jupyter_lab_major_version == '2': shutil.copytree('ts/jupyter_extension/build', 'nni_node/jupyter-extension/build') shutil.copytree(os.path.join(sys.exec_prefix, 'share/jupyter/lab/extensions'), 'nni_node/jupyter-extension/extensions') elif version or Path('ts/jupyter_extension/dist').exists(): shutil.copytree('ts/jupyter_extension/dist', 'nni_node/jupyter-extension') _yarn_env = dict(os.environ) # `Path('nni_node').resolve()` does not work on Windows if the directory not exists _yarn_env['PATH'] = str(Path().resolve() / 'nni_node') + path_env_seperator + os.environ['PATH'] _yarn_path = Path().resolve() / 'toolchain/yarn/bin' / yarn_executable _npm_path = Path().resolve() / 'toolchain/node' / npm_executable

071dfb2dcff2f2a0b66a60f5faf51a97dc135328

https://github.com/microsoft/nni.git

def copy_nni_node(version): _print('Copying files') if sys.version_info >= (3, 8): shutil.copytree('ts/nni_manager/dist', 'nni_node', dirs_exist_ok=True) else: for item in os.listdir('ts/nni_manager/dist'): subsrc = os.path.join('ts/nni_manager/dist', item) subdst = os.path.join('nni_node', item) if os.path.isdir(subsrc): shutil.copytree(subsrc, subdst) else: shutil.copy2(subsrc, subdst) shutil.copyfile('ts/nni_manager/package-lock.json', 'nni_node/package-lock.lock') Path('nni_node/nni_manager.tsbuildinfo').unlink() package_json = json.load(open('ts/nni_manager/package.json')) if version: while len(version.split('.')) < 3: # node.js semver requires at least three parts version = version + '.0' package_json['version'] = version json.dump(package_json, open('nni_node/package.json', 'w'), indent=2) if sys.platform == 'win32': # On Windows, manually install node-gyp for sqlite3. _npm('ts/nni_manager', 'install', '--global', 'node-gyp') # reinstall without development dependencies prod_path = Path('nni_node').resolve() _yarn(str(prod_path), 'install', '--production') shutil.copytree('ts/webui/build', 'nni_node/static') if jupyter_lab_major_version == '2': shutil.copytree('ts/jupyter_extension/build', 'nni_node/jupyter-extension/build') shutil.copytree(os.path.join(sys.exec_prefix, 'share/jupyter/lab/extensions'), 'nni_node/jupyter-extension/extensions') elif version or Path('ts/jupyter_extension/dist').exists(): sh

copy_nni_node

pandas/tests/io/excel/test_readers.py

ENH: Add use nullable dtypes to read_excel (#49091)

pandas

Python

test_readers.py

def test_use_nullable_dtypes(self, read_ext): # GH#36712 if read_ext == ".xlsb": pytest.skip("No engine for filetype: 'xlsb'") df = DataFrame( { "a": Series([1, 3], dtype="Int64"), "b": Series([2.5, 4.5], dtype="Float64"), "c": Series([True, False], dtype="boolean"), "d": Series(["a", "b"], dtype="string"), "e": Series([pd.NA, 6], dtype="Int64"), "f": Series([pd.NA, 7.5], dtype="Float64"), "g": Series([pd.NA, True], dtype="boolean"), "h": Series([pd.NA, "a"], dtype="string"), "i": Series([pd.Timestamp("2019-12-31")] * 2), "j": Series([pd.NA, pd.NA], dtype="Int64"), } ) with tm.ensure_clean(read_ext) as file_path: df.to_excel(file_path, "test", index=False) result = pd.read_excel( file_path, sheet_name="test", use_nullable_dtypes=True ) tm.assert_frame_equal(result, df)

22e591f2d142b20ba294c40236954d377c7b22ed

https://github.com/pandas-dev/pandas.git

def test_use_nullable_dtypes(self, read_ext): # GH#36712 if read_ext == ".xlsb": pytest.skip("No engine for filetype: 'xlsb'") df = DataFrame( { "a": Seri

test_use_nullable_dtypes

ppdet/modeling/heads/pico_head.py

Simplify picodet postprocess (#5650)

PaddleDetection

Python

pico_head.py

def _generate_anchors(self, feats=None): # just use in eval time anchor_points = [] stride_tensor = [] for i, stride in enumerate(self.fpn_stride): if feats is not None: _, _, h, w = feats[i].shape else: h = math.ceil(self.eval_size[0] / stride) w = math.ceil(self.eval_size[1] / stride) shift_x = paddle.arange(end=w) + self.cell_offset shift_y = paddle.arange(end=h) + self.cell_offset shift_y, shift_x = paddle.meshgrid(shift_y, shift_x) anchor_point = paddle.cast( paddle.stack( [shift_x, shift_y], axis=-1), dtype='float32') anchor_points.append(anchor_point.reshape([-1, 2])) stride_tensor.append( paddle.full( [h * w, 1], stride, dtype='float32')) anchor_points = paddle.concat(anchor_points) stride_tensor = paddle.concat(stride_tensor) return anchor_points, stride_tensor

c612935d8d7431f3a730cf5e213159f6b20938d1

https://github.com/PaddlePaddle/PaddleDetection.git

def _generate_anchors(self, feats=None): # just use in eval time anchor_points = [] stride_tensor = [] for i, stride in enumerate(self.fpn_stride): if feats is not None: _, _, h, w = feats[i].shape else: h = math.ceil(self.eval_size[0] / stride) w = math.ceil(self.eval_size[1] / stride) shift_x = paddle.arange(end=w) + self.cell_offset shift_y = paddle.arange(end=h) + self.cell_offset shift_y, shift_x = paddle.meshgrid(shift_y, shift_x) anchor_point = paddle.cast( paddle.stack( [shift_x, shift_y], axis=-1), dtype='float32') anchor_points.append(anchor_point.reshape([-1, 2])) stride_tensor.append( paddle.full( [h * w, 1], stride, dtype='float32')) ancho

_generate_anchors

test/test_pipeline.py

Validate YAML files without loading the nodes (#2438) * Remove BasePipeline and make a module for RayPipeline * Can load pipelines from yaml, plenty of issues left * Extract graph validation logic into _add_node_to_pipeline_graph & refactor load_from_config and add_node to use it * Fix pipeline tests * Move some tests out of test_pipeline.py and create MockDenseRetriever * myoy and pylint (silencing too-many-public-methods) * Fix issue found in some yaml files and in schema files * Fix paths to YAML and fix some typos in Ray * Fix eval tests * Simplify MockDenseRetriever * Fix Ray test * Accidentally pushed merge coinflict, fixed * Typo in schemas * Typo in _json_schema.py * Slightly reduce noisyness of version validation warnings * Fix version logs tests * Fix version logs tests again * remove seemingly unused file * Add check and test to avoid adding the same node to the pipeline twice * Update Documentation & Code Style * Revert config to pipeline_config * Remo0ve unused import * Complete reverting to pipeline_config * Some more stray config= * Update Documentation & Code Style * Feedback * Move back other_nodes tests into pipeline tests temporarily * Update Documentation & Code Style * Fixing tests * Update Documentation & Code Style * Fixing ray and standard pipeline tests * Rename colliding load() methods in dense retrievers and faiss * Update Documentation & Code Style * Fix mypy on ray.py as well * Add check for no root node * Fix tests to use load_from_directory and load_index * Try to workaround the disabled add_node of RayPipeline * Update Documentation & Code Style * Fix Ray test * Fix FAISS tests * Relax class check in _add_node_to_pipeline_graph * Update Documentation & Code Style * Try to fix mypy in ray.py * unused import * Try another fix for Ray * Fix connector tests * Update Documentation & Code Style * Fix ray * Update Documentation & Code Style * use BaseComponent.load() in pipelines/base.py * another round of feedback * stray BaseComponent.load() * Update Documentation & Code Style * Fix FAISS tests too Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: tstadel <60758086+tstadel@users.noreply.github.com>

haystack

Python

test_pipeline.py

def test_graph_validation_invalid_node(): docstore = MockDocumentStore() retriever = DummyRetriever(document_store=docstore) pipeline = Pipeline() pipeline.add_node(name="DocStore", component=docstore, inputs=["Query"]) with pytest.raises(PipelineConfigError, match="Cannot find node 'InvalidNode'"): pipeline.add_node(name="Retriever", component=retriever, inputs=["InvalidNode"])

f8e02310bf0dfbd1ab79a1c3c73434e0aeba4f4b

https://github.com/deepset-ai/haystack.git

def test_graph_validation_invalid_node(): docstore = MockDocumentStore() retriever = DummyRetriever(document_store=docstore) pipeline = Pipeline() pipeline.add_node(name="DocStore"

test_graph_validation_invalid_node

tests/ludwig/features/test_image_feature.py

Update missing value strategy to only allow bfill and ffill (#2457) * push changes * working missing value strategy * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Add type hints to backward compatibility transformations * Update test to test both missing value strategy updates Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ludwig

Python

test_image_feature.py

def test_image_preproc_module_bad_num_channels(): metadata = { "preprocessing": { "missing_value_strategy": BFILL, "in_memory": True, "resize_method": "interpolate", "scaling": "pixel_normalization", "num_processes": 1, "infer_image_num_channels": True, "infer_image_dimensions": True, "infer_image_max_height": 256, "infer_image_max_width": 256, "infer_image_sample_size": 100, "height": 12, "width": 12, "num_channels": 2, }, "reshape": (2, 12, 12), } module = _ImagePreprocessing(metadata) with pytest.raises(ValueError): module(torch.rand(2, 3, 10, 10)) @pytest.mark.parametrize("resize_method", [INTERPOLATE, CROP_OR_PAD]) @pytest.mark.parametrize(["num_channels", "num_channels_expected"], [(1, 3), (3, 1)])

0ab41a299cc690940b750a79b704d69544315702

@pytest.mark.parametrize("resize_method", [INTERPOLATE, CROP_OR_PAD]) @pytest.mark.parametrize(["num_channels", "num_channels_expected"], [(1, 3), (3, 1)])

https://github.com/ludwig-ai/ludwig.git

def test_image_preproc_module_bad_num_channels(): metadata = { "preprocessing": { "missing_value_strategy": BFILL, "in_memory": True, "resize_method": "interpolate", "scaling": "pixel_normalization", "num_processes": 1, "infer_image_num_channels": True, "infer_image_dimensions": True, "infer_image_max_height": 256, "infer_image_max_width": 256, "infer_image_sample_size": 100, "height": 12, "width": 12, "num_channels": 2, }, "reshape": (2, 12, 12), } module = _ImagePreprocessing(metadata) with pytest.raises(ValueError): module(torch.rand(2, 3, 10, 10)) @pytest.mark.parametrize("resize_method", [INTERPOLATE,

test_image_preproc_module_bad_num_channels

python3.10.4/Lib/ast.py

add python 3.10.4 for windows

XX-Net

Python

ast.py

def visit_arg(self, node): self.write(node.arg) if node.annotation: self.write(": ") self.traverse(node.annotation)

8198943edd73a363c266633e1aa5b2a9e9c9f526

https://github.com/XX-net/XX-Net.git

def visit_arg(self, node): self.write(

visit_arg

tests/openbb_terminal/portfolio/test_portfolio_model.py

Adding new portfolio metrics (#2029) * Making pa active + pa minor features Makes pa actice and adds country to the df. The groupby command also gets percents of holding allocation. It also fixes warnings and prepares for a later pr that I'm currently working on. * Fix linting * black linter * Fixes Should fix everything * Linting * Making pa controller to base class standard * Fix linting * first metrics * Adding calmar ratio * Adding metrics to controller * Linting * Linting * Test fixes * Test fixes * Adding tests * Linting * Restructuring added tests * Linting * Updating hugo website and fixing help * Fixing commands * Fix kelly criterion command * Fixing tests * Linting * More linting Co-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt> Co-authored-by: Jeroen Bouma <jer.bouma@gmail.com>

OpenBBTerminal

Python

test_portfolio_model.py

def test_tracking_error(recorder): result_df, _ = portfolio_model.get_tracking_error( portfolio_returns, benchmark_returns ) recorder.capture(result_df)

89297fadc4b5f9381b259f16314e44f9ba9be7bd

https://github.com/OpenBB-finance/OpenBBTerminal.git

def test_tracking_error(recorder): result_df, _ = portfolio_model.get_tracking_error( portfolio_return

test_tracking_error

pandas/tests/arithmetic/test_datetime64.py

API: dont do type inference on arithmetic results (#49714) * API: dont do type inference on arithmetic results * mypy fixup * use concat_compat * dont infer in TimedeltaArray * update addsub * avoid messing with box_expected

pandas

Python

test_datetime64.py

def test_dt64arr_addsub_object_dtype_2d(): # block-wise DataFrame operations will require operating on 2D # DatetimeArray/TimedeltaArray, so check that specifically. dti = date_range("1994-02-13", freq="2W", periods=4) dta = dti._data.reshape((4, 1)) other = np.array([[pd.offsets.Day(n)] for n in range(4)]) assert other.shape == dta.shape with tm.assert_produces_warning(PerformanceWarning): result = dta + other with tm.assert_produces_warning(PerformanceWarning): expected = (dta[:, 0] + other[:, 0]).reshape(-1, 1) tm.assert_numpy_array_equal(result, expected) with tm.assert_produces_warning(PerformanceWarning): # Case where we expect to get a TimedeltaArray back result2 = dta - dta.astype(object) assert result2.shape == (4, 1) assert all(td.value == 0 for td in result2.ravel())

35a7f807ac9f02128333c1b5df0f03c897d13445

https://github.com/pandas-dev/pandas.git

def test_dt64arr_addsub_object_dtype_2d(): # block-wise DataFrame operations will require operating on 2D # DatetimeArray/TimedeltaArray, so check that specifically. dti = date_range("1994-02-13", freq="2W", periods=4) dta = dti._data.reshape((4, 1)) other = np.array([[pd.offsets.Day(n)] for n in range(4)]) assert other.shape == dta.shape with tm.assert_produces_warning(PerformanceWarning):

test_dt64arr_addsub_object_dtype_2d

lib/ansible/galaxy/collection/concrete_artifact_manager.py

ansible-galaxy collection - ensure dependencies are a dict (#77561) * fix traceback when installing collection with dependencies set to None

ansible

Python

concrete_artifact_manager.py

def get_direct_collection_dependencies(self, collection): # type: (Candidate | Requirement) -> dict[str, str] collection_dependencies = self.get_direct_collection_meta(collection)['dependencies'] if collection_dependencies is None: collection_dependencies = {} return collection_dependencies # type: ignore[return-value]

4d69c09695c8f78b95edf51314999be3c19b62eb

https://github.com/ansible/ansible.git

def get_direct_collection_dependencies(self, collection): #

get_direct_collection_dependencies

rllib/offline/tests/test_dataset_reader.py

[RLlib] improved unittests for dataset_reader and fixed bugs (#26458)

ray

Python

test_dataset_reader.py

def test_absolute_zip(self): # this should work regardless of where th current working directory is. with tempfile.TemporaryDirectory() as tmp_dir: cwdir = os.getcwd() os.chdir(tmp_dir) unzipped_paths = _unzip_if_needed( [str(Path(self.absolute_path) / "enormous.zip")], "json" ) self.assertEqual( str(Path(unzipped_paths[0]).absolute()), str(Path("./").absolute() / "enormous.json"), ) assert all([Path(fpath).exists() for fpath in unzipped_paths]) os.chdir(cwdir) # @TODO: unskip when this is fixed

569fe0109629048d08e1d9e023f7769f10bd2244

https://github.com/ray-project/ray.git

def test_absolute_zip(self): # this should work regardless of where th current working directory is. with tempfile.TemporaryDirectory() as tmp_dir: cwdir = os.getcwd() os.chdir(tmp_dir) unzipped_paths = _unzip_if_needed( [str(Path(self.absolute_pat

test_absolute_zip

VoiceAssistant/Project_Basic_struct/speechtotext.py

VoiceAssistant This is Voice Assistant coded using Python which can do the following: - 1. Speak Text entered by User. 2. Search anything on Google. 3. Search anything on Wikipedia. 4. Read an MS Word(docx) document. 5. Read a book(PDF). 6. Can be used as a Dictator.

Python

Python

speechtotext.py

def stt(): with sr.Microphone() as source: # read the audio data from the default microphone audio_data = r.record(source, duration=5) print("Recognizing...") # convert speech to text text = r.recognize_google(audio_data) print(text)

39c49e07066b2a53e176d555af6a7bf8aabb8a9c

https://github.com/geekcomputers/Python.git

def stt(): with sr.Microphone() as source: # read the audio data from the default microphone audio_data = r.record(source, duration=5)

stt

modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/partition.py

FEAT-#5053: Add pandas on unidist execution with MPI backend (#5059) Signed-off-by: Igoshev, Iaroslav <iaroslav.igoshev@intel.com>

modin

Python

partition.py

def _apply_list_of_funcs(call_queue, partition): # pragma: no cover for func, f_args, f_kwargs in call_queue: func = deserialize(func) args = deserialize(f_args) kwargs = deserialize(f_kwargs) try: partition = func(partition, *args, **kwargs) # Sometimes Arrow forces us to make a copy of an object before we operate on it. We # don't want the error to propagate to the user, and we want to avoid copying unless # we absolutely have to. except ValueError: partition = func(partition.copy(), *args, **kwargs) return ( partition, len(partition) if hasattr(partition, "__len__") else 0, len(partition.columns) if hasattr(partition, "columns") else 0, unidist.get_ip(), )

193505fdf0c984743397ba3df56262f30aee13a8

https://github.com/modin-project/modin.git

def _apply_list_of_funcs(call_queue, partition): # pragma: no cover for func, f_args, f_kwargs in call_queue: func = deserialize(func) args = deserialize(f_args) kwargs = deserialize(f_kwargs) try: partition = func(partition, *args,

_apply_list_of_funcs

wagtail/embeds/blocks.py

Reformat with black

wagtail

Python

blocks.py

def get_prep_value(self, value): # serialisable value should be a URL string if value is None: return "" else: return value.url

d10f15e55806c6944827d801cd9c2d53f5da4186

https://github.com/wagtail/wagtail.git

def get_prep_value(self, value): # serialisable value should be a URL string if value is None: return "" else: return value.url

get_prep_value