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semeru

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code-text-galeras-code-summarization-3k-deduped

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Semeru Lab 7

test_usage_lib_get_cluster_config_to_report

def test_usage_lib_get_cluster_config_to_report(monkeypatch, tmp_path, reset_lib_usage): cluster_config_file_path = tmp_path / "ray_bootstrap_config.yaml" cluster_config_file_path.write_text( ) cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( cluster_config_file_path ) assert cluster_config_to_report.cloud_provider == "aws" assert cluster_config_to_report.min_workers is None assert cluster_config_to_report.max_workers == 1 assert cluster_config_to_report.head_node_instance_type is None assert cluster_config_to_report.worker_node_instance_types is None cluster_config_file_path.write_text( ) cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( cluster_config_file_path ) assert cluster_config_to_report.cloud_provider == "gcp" assert cluster_config_to_report.min_workers == 1 assert cluster_config_to_report.max_workers is None assert cluster_config_to_report.head_node_instance_type == "m5.large" assert cluster_config_to_report.worker_node_instance_types == list( {"m3.large", "Standard_D2s_v3", "n1-standard-2"} ) cluster_config_file_path.write_text( ) cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( cluster_config_file_path ) assert cluster_config_to_report.cloud_provider is None assert cluster_config_to_report.min_workers is None assert cluster_config_to_report.max_workers is None assert cluster_config_to_report.head_node_instance_type is None assert cluster_config_to_report.worker_node_instance_types == ["m5.large"] cluster_config_file_path.write_text("[invalid") cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( cluster_config_file_path ) assert cluster_config_to_report == ClusterConfigToReport() cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( tmp_path / "does_not_exist.yaml" ) assert cluster_config_to_report == ClusterConfigToReport() monkeypatch.setenv("KUBERNETES_SERVICE_HOST", "localhost") cluster_config_to_report = ray_usage_lib.get_cluster_config_to_report( tmp_path / "does_not_exist.yaml" ) assert cluster_config_to_report.cloud_provider == "kubernetes" assert cluster_config_to_report.min_workers is None assert cluster_config_to_report.max_workers is None assert cluster_config_to_report.head_node_instance_type is None assert cluster_config_to_report.worker_node_instance_types is None @pytest.mark.skipif( sys.platform == "win32", reason="Test depends on runtime env feature not supported on Windows.", )

5fb61abba3f583a1aa080623623af0b79de9e3f3

@pytest.mark.skipif( sys.platform == "win32", reason="Test depends on runtime env feature not supported on Windows.", )

test_usage_stats.py

[Usage Stats][Hotfix] Import usage reported from workers. (#25785) ## Why are these changes needed? We currently only record usage stats from drivers. This can lose some of information when libraries are imported from workers (e.g., doing some rllib import from trainable). @jjyao just for the future reference.

ray

python/ray/tests/test_usage_stats.py

Python

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

_process_contour_level_args

def _process_contour_level_args(self, args): if self.levels is None: if len(args) == 0: levels_arg = 7 # Default, hard-wired. else: levels_arg = args[0] else: levels_arg = self.levels if isinstance(levels_arg, Integral): self.levels = self._autolev(levels_arg) else: self.levels = np.asarray(levels_arg, np.float64) if not self.filled: inside = (self.levels > self.zmin) & (self.levels < self.zmax) levels_in = self.levels[inside] if len(levels_in) == 0: self.levels = [self.zmin] _api.warn_external( "No contour levels were found within the data range.") if self.filled and len(self.levels) < 2: raise ValueError("Filled contours require at least 2 levels.") if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0: raise ValueError("Contour levels must be increasing")

1068a6faa19767724437461bcfb88c6852ec435c

contour.py

Remove unnecessary np.{,as}array / astype calls. Quite often numpy will call asarray for us, saving us the need to call asarray explicitly. When we do call asarray (or array) ourselves, a dtype can directly be passed in, rather than immediately calling astype immediately after. Passing the dtype makes it unnecessary for asarray to infer the dtype of the passed-in container, and can also save an extra array allocation if asarray first has to allocate an array of a type and astype immediately has to allocate an array of another type.

matplotlib

lib/matplotlib/contour.py

Python

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

test_delete_post

def test_delete_post(self): # Send request response = self.client.post( reverse("wagtailimages:delete_multiple", args=(self.image.id,)) ) # Check response self.assertEqual(response.status_code, 200) self.assertEqual(response["Content-Type"], "application/json") # Make sure the image is deleted self.assertFalse(Image.objects.filter(id=self.image.id).exists()) # Check JSON response_json = json.loads(response.content.decode()) self.assertIn("image_id", response_json) self.assertIn("success", response_json) self.assertEqual(response_json["image_id"], self.image.id) self.assertTrue(response_json["success"]) @override_settings(WAGTAILIMAGES_IMAGE_MODEL="tests.CustomImage")

d10f15e55806c6944827d801cd9c2d53f5da4186

@override_settings(WAGTAILIMAGES_IMAGE_MODEL="tests.CustomImage")

test_admin_views.py

Reformat with black

wagtail

wagtail/images/tests/test_admin_views.py

Python

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

is_media_file

def is_media_file(self): return not (self.is_documentation_page() or self.is_static_page())

e7f07cc82ab2be920ab426ba07456d8b2592714d

files.py

Remove spaces at the ends of docstrings, normalize quotes

mkdocs

mkdocs/structure/files.py

Python

https://github.com/mkdocs/mkdocs.git

get_all

def get_all() -> pd.DataFrame: bursa = all_bursa() is_open_list = [] for exchange in bursa.index: is_open = check_if_open(bursa, exchange) is_open_list.append(is_open) bursa["open"] = is_open_list return bursa[["name", "short_name", "open"]] @log_start_end(log=logger)

33a041e5bf93ce93ab1a19adbc5ed74c2f1eb337

@log_start_end(log=logger)

bursa_model.py

Trading hours stock feature (#1697)

OpenBBTerminal

openbb_terminal/stocks/tradinghours/bursa_model.py

Python

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

distro_release_info

def distro_release_info(self): # type: () -> Dict[str, str] return self._distro_release_info

f3166e673fe8d40277b804d35d77dcdb760fc3b3

distro.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

pipenv

pipenv/patched/notpip/_vendor/distro.py

Python

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

set_constrained_layout

def set_constrained_layout(self, constrained): if constrained is None: constrained = mpl.rcParams['figure.constrained_layout.use'] _constrained = bool(constrained) _parameters = constrained if isinstance(constrained, dict) else {} if _constrained: self.set_layout_engine(ConstrainedLayoutEngine(**_parameters)) self.stale = True

ec4dfbc3c83866f487ff0bc9c87b0d43a1c02b22

figure.py

ENH: implement and use base layout_engine for more flexible layout.

matplotlib

lib/matplotlib/figure.py

Python

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

_default

def _default(obj): if isinstance(obj, datetime): if is_naive(obj): obj = convert_to_utc(obj) return obj.isoformat() elif isinstance(obj, date): return obj.strftime('%Y-%m-%d') elif isinstance(obj, Decimal): _, _, exponent = obj.as_tuple() if exponent >= 0: # No digits after the decimal point. return int(obj) # Technically lossy due to floating point errors, but the best we # can do without implementing a custom encode function. return float(obj) elif np is not None and isinstance( obj, ( np.int_, np.intc, np.intp, np.int8, np.int16, np.int32, np.int64, np.uint8, np.uint16, np.uint32, np.uint64, ), ): return int(obj) elif np is not None and isinstance(obj, np.bool_): return bool(obj) elif np is not None and isinstance( obj, (np.float_, np.float16, np.float32, np.float64, np.complex_, np.complex64, np.complex128) ): return float(obj) elif k8s is not None and isinstance(obj, (k8s.V1Pod, k8s.V1ResourceRequirements)): from airflow.kubernetes.pod_generator import PodGenerator return PodGenerator.serialize_pod(obj) raise TypeError(f"Object of type '{obj.__class__.__name__}' is not JSON serializable")

451a6f4d9ff8b744075e2f25099046c77f28179e

json.py

Speed up grid_data endpoint by 10x (#24284) * Speed up grid_data endpoint by 10x These changes make the endpoint go from almost 20s down to 1.5s and the changes are two fold: 1. Keep datetimes as objects for as long as possible Previously we were converting start/end dates for a task group to a string, and then in the parent parsing it back to a datetime to find the min and max of all the child nodes. The fix for that was to leave it as a datetime (or a pendulum.DateTime technically) and use the existing `AirflowJsonEncoder` class to "correctly" encode these objects on output. 2. Reduce the number of DB queries from 1 per task to 1. The removed `get_task_summaries` function was called for each task, and was making a query to the database to find info for the given DagRuns. The helper function now makes just a single DB query for all tasks/runs and constructs a dict to efficiently look up the ti by run_id. * Add support for mapped tasks in the grid data * Don't fail when not all tasks have a finish date. Note that this possibly has incorrect behaviour, in that the end_date of a TaskGroup is set to the max of all the children's end dates, even if some are still running. (This is the existing behaviour and is not changed or altered by this change - limiting it to just performance fixes)

airflow

airflow/utils/json.py

Python

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

repeat_elements

def repeat_elements(x, rep, axis): x_shape = x.shape.as_list() # For static axis if x_shape[axis] is not None: # slices along the repeat axis splits = tf.split(value=x, num_or_size_splits=x_shape[axis], axis=axis) # repeat each slice the given number of reps x_rep = [s for s in splits for _ in range(rep)] return concatenate(x_rep, axis) # Here we use tf.tile to mimic behavior of np.repeat so that # we can handle dynamic shapes (that include None). # To do that, we need an auxiliary axis to repeat elements along # it and then merge them along the desired axis. # Repeating auxiliary_axis = axis + 1 x_shape = tf.shape(x) x_rep = tf.expand_dims(x, axis=auxiliary_axis) reps = np.ones(len(x.shape) + 1) reps[auxiliary_axis] = rep x_rep = tf.tile(x_rep, reps) # Merging reps = np.delete(reps, auxiliary_axis) reps[axis] = rep reps = tf.constant(reps, dtype="int32") x_shape *= reps x_rep = tf.reshape(x_rep, x_shape) # Fix shape representation x_shape = x.shape.as_list() x_rep.set_shape(x_shape) x_rep._keras_shape = tuple(x_shape) return x_rep @keras_export("keras.backend.repeat") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

84afc5193d38057e2e2badf9c889ea87d80d8fbf

@keras_export("keras.backend.repeat") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

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

test_annotate_signature

def test_annotate_signature(): fig, ax = plt.subplots() annotate_params = inspect.signature(ax.annotate).parameters annotation_params = inspect.signature(mtext.Annotation).parameters assert list(annotate_params.keys()) == list(annotation_params.keys()) for p1, p2 in zip(annotate_params.values(), annotation_params.values()): assert p1 == p2 @image_comparison(['fill_units.png'], savefig_kwarg={'dpi': 60})

c4116bb841f6d2c0911c87c89817998342d67c5c

@image_comparison(['fill_units.png'], savefig_kwarg={'dpi': 60})

test_axes.py

Make signature of Axes.annotate() more explicit. The signature is identical to Annotation. This makes the parameters explicit instead of `*args`, which improves usability. On the downside, this introduces redundancy. But we can bear that. The signature will not change often and I've added a test that ensures the signatures stay synchronized.

matplotlib

lib/matplotlib/tests/test_axes.py

Python

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

_check_thread

def _check_thread(self): if self._thread_id is None: return thread_id = threading.get_ident() if thread_id != self._thread_id: raise RuntimeError( "Non-thread-safe operation invoked on an event loop other " "than the current one")

8198943edd73a363c266633e1aa5b2a9e9c9f526

base_events.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/base_events.py

Python

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

add_gridspec

def add_gridspec(self, nrows=1, ncols=1, **kwargs): _ = kwargs.pop('figure', None) # pop in case user has added this... gs = GridSpec(nrows=nrows, ncols=ncols, figure=self, **kwargs) return gs

9b6abd0b4933811e0a45c2535ab8fd107db65dd9

figure.py

DOC: improve grammar and consistency

matplotlib

lib/matplotlib/figure.py

Python

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

_register_arrow_data_serializer

def _register_arrow_data_serializer(serialization_context): import pyarrow as pa if os.environ.get(RAY_DISABLE_CUSTOM_ARROW_DATA_SERIALIZATION, "0") == "1": return # Register custom reducer for Arrow Arrays. array_types = _get_arrow_array_types() for array_type in array_types: serialization_context._register_cloudpickle_reducer( array_type, _arrow_array_reduce ) # Register custom reducer for Arrow ChunkedArrays. serialization_context._register_cloudpickle_reducer( pa.ChunkedArray, _arrow_chunkedarray_reduce ) # Register custom reducer for Arrow RecordBatches. serialization_context._register_cloudpickle_reducer( pa.RecordBatch, _arrow_recordbatch_reduce ) # Register custom reducer for Arrow Tables. serialization_context._register_cloudpickle_reducer(pa.Table, _arrow_table_reduce)

c1d62d46495f0157faf3168aa87eed350802e10f

arrow_serialization.py

[Datasets] Arrow 7.0.0+ Support: Use Arrow IPC format for pickling Arrow data to circumvent slice view buffer truncation bug. (#29055) This PR registers a custom serializer for Array arrays, chunked arrays, record batches, and tables that works around an Arrow serialization bug that serializes the entire underlying data buffer when serializing zero-copy slice views. The custom serializer uses the Arrow IPC format as the underlying pickled representation.

ray

python/ray/data/_internal/arrow_serialization.py

Python

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

get_swisscom_data

def get_swisscom_data(self): url = f"http://{self.host}/ws" headers = {"Content-Type": "application/x-sah-ws-4-call+json"} data = devices = {} try: request = requests.post(url, headers=headers, data=data, timeout=10) except ( requests.exceptions.ConnectionError, requests.exceptions.Timeout, requests.exceptions.ConnectTimeout, ): _LOGGER.info("No response from Swisscom Internet Box") return devices if "status" not in request.json(): _LOGGER.info("No status in response from Swisscom Internet Box") return devices for device in request.json()["status"]: with suppress(KeyError, requests.exceptions.RequestException): devices[device["Key"]] = { "ip": device["IPAddress"], "mac": device["PhysAddress"], "host": device["Name"], "status": device["Active"], } return devices

2bab6447a924d63d253b210f9a6ab3ea3ca67e7d

device_tracker.py

Replaces aiohttp.hdrs CONTENT_TYPE with plain string for the Swisscom integration (#76568)

core

homeassistant/components/swisscom/device_tracker.py

Python

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

run_interpret

def run_interpret(interface, raw_input): if isinstance(interface.interpretation, list): # Either "default" or "shap" processed_input = [input_component.preprocess(raw_input[i]) for i, input_component in enumerate(interface.input_components)] original_output = interface.run_prediction(processed_input) scores, alternative_outputs = [], [] for i, (x, interp) in enumerate(zip(raw_input, interface.interpretation)): if interp == "default": input_component = interface.input_components[i] neighbor_raw_input = list(raw_input) if input_component.interpret_by_tokens: tokens, neighbor_values, masks = input_component.tokenize( x) interface_scores = [] alternative_output = [] for neighbor_input in neighbor_values: neighbor_raw_input[i] = neighbor_input processed_neighbor_input = [input_component.preprocess(neighbor_raw_input[i]) for i, input_component in enumerate(interface.input_components)] neighbor_output = interface.run_prediction( processed_neighbor_input) processed_neighbor_output = [output_component.postprocess( neighbor_output[i]) for i, output_component in enumerate(interface.output_components)] alternative_output.append( processed_neighbor_output) interface_scores.append(quantify_difference_in_label( interface, original_output, neighbor_output)) alternative_outputs.append(alternative_output) scores.append( input_component.get_interpretation_scores( raw_input[i], neighbor_values, interface_scores, masks=masks, tokens=tokens)) else: neighbor_values, interpret_kwargs = input_component.get_interpretation_neighbors( x) interface_scores = [] alternative_output = [] for neighbor_input in neighbor_values: neighbor_raw_input[i] = neighbor_input processed_neighbor_input = [input_component.preprocess(neighbor_raw_input[i]) for i, input_component in enumerate(interface.input_components)] neighbor_output = interface.run_prediction( processed_neighbor_input) processed_neighbor_output = [output_component.postprocess( neighbor_output[i]) for i, output_component in enumerate(interface.output_components)] alternative_output.append( processed_neighbor_output) interface_scores.append(quantify_difference_in_label( interface, original_output, neighbor_output)) alternative_outputs.append(alternative_output) interface_scores = [-score for score in interface_scores] scores.append( input_component.get_interpretation_scores( raw_input[i], neighbor_values, interface_scores, **interpret_kwargs)) elif interp == "shap" or interp == "shapley": try: import shap # type: ignore except (ImportError, ModuleNotFoundError): raise ValueError( "The package `shap` is required for this interpretation method. Try: `pip install shap`") input_component = interface.input_components[i] if not (input_component.interpret_by_tokens): raise ValueError( "Input component {} does not support `shap` interpretation".format(input_component)) tokens, _, masks = input_component.tokenize(x) # construct a masked version of the input

85b0d2df3458236b5e8c343febc507f94c1e60ad

interpretation.py

brought back sessions for TF 1.x

gradio

gradio/interpretation.py

Python

https://github.com/gradio-app/gradio.git

parse_args

def parse_args(args): # Use the file's docstring for the help text and don't let argparse reformat it. parser = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) parser.add_argument('--css', type=str, required=True, help='hostname of code signing server') group = parser.add_mutually_exclusive_group() # We use 'store_false' and a destination related to the other type of # artifact to cause the flag being set to disable publishing of the other # artifact. This makes using the parsed arguments later on a little simpler # and cleaner. group.add_argument('--snaps-only', action='store_false', dest='publish_windows', help='Skip publishing other artifacts and only publish the snaps') group.add_argument('--windows-only', action='store_false', dest='publish_snaps', help='Skip publishing other artifacts and only publish the Windows installer') return parser.parse_args(args)

6e1696ba32ef8c1162bb0cd85df5a22113952828

finish_release.py

Add Signed Windows Installer Workflow (#9076) * Add Code Signing action for Windows Installer * Clean up variable names and input * Amend and add to documentation per PR guidelines * Update tools/finish_release.py Co-authored-by: Brad Warren <[email protected]> * Update tools/finish_release.py Amend typo Co-authored-by: Brad Warren <[email protected]> * Amend release script for better work flow - SCP commands to upload and download unsigned & signed installers from CSS * Collapse spaces * Update tools/finish_release.py Co-authored-by: Brad Warren <[email protected]> * Create new windows signer function * Update Windows Installer Script - Update change log - add new function for signing and document - @TODO Streammline SSH session * Remove Azure and Github release methods - Methods moved to CSS - Reduced to a ssh function that triggers the process on a CSS * Amend Chnagelog and Remove Unneeded Deps * Update tools/finish_release.py Co-authored-by: Brad Warren <[email protected]> * Add Verison Fetch Function - For the purpose of snap releases - Add back package to dev extras for function * Chaneg path in ssh command * Amend release script * Amend the ssh command for CSS * Update tools/finish_release.py Co-authored-by: Brad Warren <[email protected]> * Update script with proper path and subprocess call * Update ssh command * Correct typo in path * Fix typo in path * Update certbot/CHANGELOG.md Co-authored-by: ohemorange <[email protected]> * Remove missed conflict text Co-authored-by: Brad Warren <[email protected]> Co-authored-by: ohemorange <[email protected]>

certbot

tools/finish_release.py

Python

https://github.com/certbot/certbot.git

get_context_data

def get_context_data(self, parent_context): context = parent_context.copy() if requires_request_arg(self.get_url): warn( "%s.get_url should no longer take a 'request' argument. " "See https://docs.wagtail.org/en/stable/releases/2.15.html#template-components-2-15" % type(self).__name__, category=RemovedInWagtail217Warning ) url = self.get_url(parent_context['request'], parent_context) else: url = self.get_url(parent_context) context.update({ 'label': self.label, 'url': url, 'name': self.name, 'classname': self.classname, 'icon_name': self.icon_name, 'request': parent_context['request'], }) return context

e9183a95c88fe2eaf4c1d3aff9833633509713f3

action_menu.py

Update docs links to reference new domain

wagtail

wagtail/admin/action_menu.py

Python

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

_parse_tag

def _parse_tag(tag): # type: (str) -> str match = re.match('^v?(.+?)-(\\d+)-g[a-f0-9]+$', tag) if match: # remove the 'v' prefix and add a '.devN' suffix return '%s.dev%s' % (match.group(1), match.group(2)) else: # just remove the 'v' prefix return re.sub('^v', '', tag)

402677d50cc007cb5b39dc0fdb8934dae36cf6ac

__init__.py

Update git format

scapy

scapy/__init__.py

Python

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

handle

def handle(self, *args, **options): jt = options['jt'] threshold = options['threshold'] history = options['history'] ignore = options['ignore'] print('## ' + JobTemplate.objects.get(pk=jt).name + f' (last {history} runs)\n') with connection.cursor() as cursor: cursor.execute( f ) slowest_events = cursor.fetchall()

d3eb2c197595c29c4a3f7b38cd609ce953009623

bottleneck.py

Add new flak8 rules to do some meaningful corrections

awx

awx/main/management/commands/bottleneck.py

Python

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

test_multiple_output_keys_error

def test_multiple_output_keys_error() -> None: chain = FakeChain(the_output_keys=["foo", "bar"]) with pytest.raises(ValueError): chain.run("bar")

8d0869c6d3ed63b2b15d4f75ea664e089dcc569d

test_base.py

change run to use args and kwargs (#367) Before, `run` was not able to be called with multiple arguments. This expands the functionality.

langchain

tests/unit_tests/chains/test_base.py

Python

https://github.com/hwchase17/langchain.git

get_best_result

def get_best_result(self) -> Result: return self._trial_to_result(self._experiment_analysis.best_trial)

4b28bc3f09ebcc9c0d6262355b394452a11667fc

result_grid.py

[Tuner part1] Add Tuner interface. (#22975)

ray

python/ray/tune/result_grid.py

Python

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

get_lookup

def get_lookup(self, lookup_name): if lookup_name not in ["exact", "in", "isnull"]: raise TypeError("Lookup type %s is not supported." % lookup_name) return super().get_lookup(lookup_name)

0ad4aa9d9fe3beb3fd20aaedd961b3c2c800efb1

fields.py

ref(django-3.2): Vendor django picklefield (#35727) * ref(django-3.2): Vendor django picklefield Django-picklefield hasn't been updated in 2 years, but we need it. We also need to upgrade to django 3.2 which means we need to update picklefield. * Remove reference to django-picklefield * Fix the module name to use underscore * style(lint): Auto commit lint changes * Remove versioning code Co-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>

sentry

src/django_picklefield/fields.py

Python

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

test_legend_label_with_leading_underscore

def test_legend_label_with_leading_underscore(): fig, ax = plt.subplots() line, = ax.plot([0, 1], label='_foo') with pytest.warns(UserWarning, match=r"starts with '_'.*excluded from the legend."): legend = ax.legend(handles=[line]) assert len(legend.legendHandles) == 0 @image_comparison(['legend_labels_first.png'], remove_text=True)

8573a52853df59579236a6096abbecd409c26982

@image_comparison(['legend_labels_first.png'], remove_text=True)

test_legend.py

Clarify warning about labels with leading underscores. Replaces and closes #17488. Co-authored-by: Clement Walter <[email protected]>

matplotlib

lib/matplotlib/tests/test_legend.py

Python

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

_async_process_on_unload

async def _async_process_on_unload(self) -> None: if self._on_unload is not None: while self._on_unload: self._on_unload.pop()() while self._pending_tasks: pending = [task for task in self._pending_tasks if not task.done()] self._pending_tasks.clear() if pending: await asyncio.gather(*pending)

00810235c92b492a966c6021021d49360ffb3cdd

config_entries.py

Track tasks adding entities (#73828) * Track tasks adding entities * Update homeassistant/config_entries.py * fix cast tests Co-authored-by: J. Nick Koston <[email protected]>

core

homeassistant/config_entries.py

Python

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

cursor_text_start

def cursor_text_start(self) -> bool: if self.cursor_index == 0: return False self.cursor_index = 0 return True

dd18ecbdbe744812509630935a877424202f2a70

_text_backend.py

Docstring improvements

textual

src/textual/_text_backend.py

Python

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

async_create_post_interval_update_cb

def async_create_post_interval_update_cb(self) -> None: self._post_interval_update_cb_canceller = async_call_later( self.hass, get_unavailability_interval(self.ping_interval), self.async_post_interval_update, )

af4e37339a39badd5596e8bc9ba86d6c1994aa1b

sia_entity_base.py

Add Connectivity sensor to SIA (#64305) * implemented connectivity sensor * further cleanup off update code * cleanup and tighter behaviour for attributes * added seperate connectivity class to binary sensor * callbacks and keys * redid name and unique_id logic, non-breaking result * using entry more in inits * Fix import * fix ping_interval in sia_entity_base * added ping_interval default to next * fixed next Co-authored-by: Martin Hjelmare <[email protected]>

core

homeassistant/components/sia/sia_entity_base.py

Python

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

test_doorbell_update_via_pubnub

async def test_doorbell_update_via_pubnub(hass): doorbell_one = await _mock_doorbell_from_fixture(hass, "get_doorbell.json") pubnub = AugustPubNub() await _create_august_with_devices(hass, [doorbell_one], pubnub=pubnub) assert doorbell_one.pubsub_channel == "7c7a6672-59c8-3333-ffff-dcd98705cccc" binary_sensor_k98gidt45gul_name_motion = hass.states.get( "binary_sensor.k98gidt45gul_name_motion" ) assert binary_sensor_k98gidt45gul_name_motion.state == STATE_OFF binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "imagecapture", "data": { "result": { "created_at": "2021-03-16T01:07:08.817Z", "secure_url": "https://dyu7azbnaoi74.cloudfront.net/zip/images/zip.jpeg", }, }, }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_image_capture = hass.states.get( "binary_sensor.k98gidt45gul_name_image_capture" ) assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_ON pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "doorbell_motion_detected", "data": { "event": "doorbell_motion_detected", "image": { "height": 640, "width": 480, "format": "jpg", "created_at": "2021-03-16T02:36:26.886Z", "bytes": 14061, "secure_url": "https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg", "url": "https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg", "etag": "09e839331c4ea59eef28081f2caa0e90", }, "doorbellName": "Front Door", "callID": None, "origin": "mars-api", "mutableContent": True, }, }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_motion = hass.states.get( "binary_sensor.k98gidt45gul_name_motion" ) assert binary_sensor_k98gidt45gul_name_motion.state == STATE_ON binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF new_time = dt_util.utcnow() + datetime.timedelta(seconds=40) native_time = datetime.datetime.now() + datetime.timedelta(seconds=40) with patch( "homeassistant.components.august.binary_sensor._native_datetime", return_value=native_time, ): async_fire_time_changed(hass, new_time) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_image_capture = hass.states.get( "binary_sensor.k98gidt45gul_name_image_capture" ) assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_OFF pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "buttonpush", }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_ON new_time = dt_util.utcnow() + datetime.timedelta(seconds=40) native_time = datetime.datetime.now() + datetime.timedelta(seconds=40) with patch( "homeassistant.components.august.binary_sensor._native_datetime", return_value=native_time, ): async_fire_time_changed(hass, new_time) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF

ea5b18c1ef16b64cd7916f2540692ab5de2d2edf

test_binary_sensor.py

Split august motion and image capture binary sensors (#62154)

core

tests/components/august/test_binary_sensor.py

Python

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

test_prefill_form_backcompat

def test_prefill_form_backcompat(extras, expected): mock_form = mock.Mock() mock_form.data = {"conn_id": "test", "extra": json.dumps(extras), "conn_type": "test"} cmv = ConnectionModelView() cmv.extra_fields = ['extra__test__my_param'] # this is set by `lazy_add_provider_discovered_options_to_connection_form` cmv.extra_field_name_mapping['extra__test__my_param'] = 'my_param' cmv.prefill_form(form=mock_form, pk=1) assert mock_form.extra__test__my_param.data == expected @pytest.mark.parametrize('field_name', ['extra__test__custom_field', 'custom_field']) @mock.patch('airflow.utils.module_loading.import_string') @mock.patch('airflow.providers_manager.ProvidersManager.hooks', new_callable=PropertyMock)

1dfae80412377eef0a38637535d6a1d3393cc4fe

@pytest.mark.parametrize('field_name', ['extra__test__custom_field', 'custom_field']) @mock.patch('airflow.utils.module_loading.import_string') @mock.patch('airflow.providers_manager.ProvidersManager.hooks', new_callable=PropertyMock)

test_views_connection.py

Enable use of custom conn extra fields without prefix (#22607) Previously, connection "extra" fields which were added as custom fields in the webserver connection form had to be named with prefix `extra__<conn_type>__`. This was because custom fields are registered globally on the connection view model, so the prefix was necessary to prevent collisions. But the prefix is ugly and cumbersome in the `extra` field. So now what we do is add this prefix when defining the field internally in the model, and strip it when saving the connection. This doesn't change any providers -- each of those will have to be updated in order to use no-prefix custom fields, with special care to handle backcompat.

airflow

tests/www/views/test_views_connection.py

Python

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

_build_test_case

def _build_test_case(self, task_data, host_data): name = '[%s] %s: %s' % (host_data.name, task_data.play, task_data.name) duration = host_data.finish - task_data.start if self._task_relative_path and task_data.path: junit_classname = os.path.relpath(task_data.path, self._task_relative_path) else: junit_classname = task_data.path if self._replace_out_of_tree_path is not None and junit_classname.startswith('../'): junit_classname = self._replace_out_of_tree_path + os.path.basename(junit_classname) if self._task_class == 'true': junit_classname = re.sub(r'\.yml:[0-9]+$', '', junit_classname) if host_data.status == 'included': return TestCase(name=name, classname=junit_classname, time=duration, system_out=str(host_data.result)) res = host_data.result._result rc = res.get('rc', 0) dump = self._dump_results(res, indent=0) dump = self._cleanse_string(dump) if host_data.status == 'ok': return TestCase(name=name, classname=junit_classname, time=duration, system_out=dump) test_case = TestCase(name=name, classname=junit_classname, time=duration) if host_data.status == 'failed': if 'exception' in res: message = res['exception'].strip().split('\n')[-1] output = res['exception'] test_case.errors.append(TestError(message=message, output=output)) elif 'msg' in res: message = res['msg'] test_case.failures.append(TestFailure(message=message, output=dump)) else: test_case.failures.append(TestFailure(message='rc=%s' % rc, output=dump)) elif host_data.status == 'skipped': if 'skip_reason' in res: message = res['skip_reason'] else: message = 'skipped' test_case.skipped = message return test_case

fbb5d56bd274c44b193cb95f0230b9352f62aab2

junit.py

ansible-test - Use relative paths in junit output. (#76871) * ansible-test - Use relative paths in junit output. Also fix a traceback in the junit callback during automatic fact gathering. * ansible-test - Handle out-of-tree JUnit paths.

ansible

lib/ansible/plugins/callback/junit.py

Python

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

_check_lazy_references

def _check_lazy_references(apps, ignore=None): pending_models = set(apps._pending_operations) - (ignore or set()) # Short circuit if there aren't any errors. if not pending_models: return [] from django.db.models import signals model_signals = { signal: name for name, signal in vars(signals).items() if isinstance(signal, signals.ModelSignal) }

9c19aff7c7561e3a82978a272ecdaad40dda5c00

model_checks.py

Refs #33476 -- Reformatted code with Black.

django

django/core/checks/model_checks.py

Python

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

activated

def activated(self, include_extras=True, extra_dists=None): if not extra_dists: extra_dists = [] original_path = sys.path original_prefix = sys.prefix parent_path = Path(__file__).absolute().parent vendor_dir = parent_path.joinpath("vendor").as_posix() patched_dir = parent_path.joinpath("patched").as_posix() parent_path = parent_path.as_posix() self.add_dist("pip") prefix = self.prefix.as_posix() with vistir.contextmanagers.temp_environ(), vistir.contextmanagers.temp_path(): os.environ["PATH"] = os.pathsep.join( [ vistir.compat.fs_str(self.script_basedir), vistir.compat.fs_str(self.prefix.as_posix()), os.environ.get("PATH", ""), ] ) os.environ["PYTHONIOENCODING"] = vistir.compat.fs_str("utf-8") os.environ["PYTHONDONTWRITEBYTECODE"] = vistir.compat.fs_str("1") if self.is_venv: os.environ["PYTHONPATH"] = self.base_paths["PYTHONPATH"] os.environ["VIRTUAL_ENV"] = vistir.compat.fs_str(prefix) else: if not self.project.s.PIPENV_USE_SYSTEM and not os.environ.get( "VIRTUAL_ENV" ): os.environ["PYTHONPATH"] = self.base_paths["PYTHONPATH"] os.environ.pop("PYTHONHOME", None) sys.path = self.sys_path sys.prefix = self.sys_prefix site.addsitedir(self.base_paths["purelib"]) pip = self.safe_import("pip") # noqa pip_vendor = self.safe_import("pip._vendor") pep517_dir = os.path.join(os.path.dirname(pip_vendor.__file__), "pep517") site.addsitedir(pep517_dir) os.environ["PYTHONPATH"] = os.pathsep.join( [os.environ.get("PYTHONPATH", self.base_paths["PYTHONPATH"]), pep517_dir] ) if include_extras: site.addsitedir(parent_path) sys.path.extend([parent_path, patched_dir, vendor_dir]) extra_dists = list(self.extra_dists) + extra_dists for extra_dist in extra_dists: if extra_dist not in self.get_working_set(): extra_dist.activate(self.sys_path) try: yield finally: sys.path = original_path sys.prefix = original_prefix

9a3b3ce70621af6f9adaa9eeac9cf83fa149319c

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

pipenv/environment.py

Python

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

delete_tasks_annotations

def delete_tasks_annotations(project, queryset, **kwargs): task_ids = queryset.values_list('id', flat=True) annotations = Annotation.objects.filter(task__id__in=task_ids) count = annotations.count() annotations_ids = list(annotations.values('id')) annotations.delete() emit_webhooks_for_instance(project.organization, project, WebhookAction.ANNOTATIONS_DELETED, annotations_ids) bulk_update_stats_project_tasks(queryset) return {'processed_items': count, 'detail': 'Deleted ' + str(count) + ' annotations'}

85152f2c8c7f8b301b28fcd771f13b5c166c59eb

basic.py

fix: DEV-1486: fix dm action when deleting all annotations, finished state is not updated (#1923) Co-authored-by: Max Tkachenko <[email protected]>

label-studio

label_studio/data_manager/actions/basic.py

Python

https://github.com/heartexlabs/label-studio.git

load

def load(self, rawdata): if isinstance(rawdata, str): self.__parse_string(rawdata) else: # self.update() wouldn't call our custom __setitem__ for key, value in rawdata.items(): self[key] = value return

8198943edd73a363c266633e1aa5b2a9e9c9f526

cookies.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/http/cookies.py

Python

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

_assert_same_graph

def _assert_same_graph(original_item, item): original_graph = getattr(original_item, "graph", None) graph = getattr(item, "graph", None) if original_graph and graph and original_graph is not graph: raise ValueError( "%s must be from the same graph as %s (graphs are %s and %s)." % (item, original_item, graph, original_graph) )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

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

rewrite

def rewrite(C, alpha, w): v = C._schreier_free_group.identity for i in range(len(w)): x_i = w[i] v = v*C.P[alpha][C.A_dict[x_i]] alpha = C.table[alpha][C.A_dict[x_i]] return v # Pg 350, section 2.5.2 from [2]

498015021131af4dbb07eb110e5badaba8250c7b

fp_groups.py

Updated import locations

sympy

sympy/combinatorics/fp_groups.py

Python

https://github.com/sympy/sympy.git

login

def login(self, request, extra_context=None): if request.method == 'GET' and self.has_permission(request): # Already logged-in, redirect to admin index index_path = reverse('admin:index', current_app=self.name) return HttpResponseRedirect(index_path) # Since this module gets imported in the application's root package, # it cannot import models from other applications at the module level, # and django.contrib.admin.forms eventually imports User. from django.contrib.admin.forms import AdminAuthenticationForm from django.contrib.auth.views import LoginView context = { **self.each_context(request), 'title': _('Log in'), 'subtitle': None, 'app_path': request.get_full_path(), 'username': request.user.get_username(), } if (REDIRECT_FIELD_NAME not in request.GET and REDIRECT_FIELD_NAME not in request.POST): context[REDIRECT_FIELD_NAME] = reverse('admin:index', current_app=self.name) context.update(extra_context or {}) defaults = { 'extra_context': context, 'authentication_form': self.login_form or AdminAuthenticationForm, 'template_name': self.login_template or 'admin/login.html', } request.current_app = self.name return LoginView.as_view(**defaults)(request)

0a4a5e5bacc354df3132d0fcf706839c21afb89d

sites.py

Refs #32681 -- Fixed VariableDoesNotExist when rendering some admin template. Regression in 84609b3205905097d7d3038d32e6101f012c0619. Follow up to 4e5bbb6ef2287126badd32842b239f4a8a7394ca. Thanks Sourav Kumar for the report.

django

django/contrib/admin/sites.py

Python

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

get_font_preamble

def get_font_preamble(cls): font_preamble, command = cls._get_font_preamble_and_command() return font_preamble

13147992b317c29c6e832ca7f6d05bf48aeb0718

texmanager.py

Move towards making texmanager stateless. Previously, TexManager needed to call get_font_config at a specific place in the middle of processing to update some internal attributes before proceeding with TeX source generation. Instead, move towards making TexManager stateless (except for caching), i.e. the user facing API should be thought of as a bunch of independently callable functions `make_tex()`, `make_dvi()`, etc. (they will probably stay as methods on a "empty" TexManager object for a long time for backcompat, in fact).

matplotlib

lib/matplotlib/texmanager.py

Python

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

addIncludedDataFilesFromPackageOptions

def addIncludedDataFilesFromPackageOptions(): # Cyclic dependency from nuitka import ModuleRegistry for module in ModuleRegistry.getDoneModules(): if module.isCompiledPythonPackage() or module.isUncompiledPythonPackage(): package_name = module.getFullName() match, reason = package_name.matchesToShellPatterns( patterns=getShallIncludePackageData() ) if match: package_directory = module.getCompileTimeDirectory() pkg_filenames = getFileList( package_directory, ignore_dirs=("__pycache__",), ignore_suffixes=(".py", ".pyw", ".pyc", ".pyo", ".dll") + getSharedLibrarySuffixes(), ) if pkg_filenames: file_reason = "package '%s' %s" % (package_name, reason) for pkg_filename in pkg_filenames: rel_path = os.path.join( package_name.asPath(), os.path.relpath(pkg_filename, package_directory), ) addIncludedDataFile( makeIncludedDataFile( source_path=pkg_filename, dest_path=rel_path, reason=file_reason, tracer=options_logger, tags="user,package_data", ) ) # Circular dependency from nuitka.plugins.Plugins import Plugins # Plugins provide per module through this. for module in ModuleRegistry.getDoneModules(): for included_datafile in Plugins.considerDataFiles(module=module): addIncludedDataFile(included_datafile)

abfb99b0a05dd76d2ecc6ebc20732a271857c6c8

IncludedDataFiles.py

Plugins: Massive cleanup of data file handling * Move data file handling out of standalone only, allowing support for other modes as well. * Attach logger and tags to data file objects.

Nuitka

nuitka/freezer/IncludedDataFiles.py

Python

https://github.com/Nuitka/Nuitka.git

get_xframe_options_value

def get_xframe_options_value(self, request, response): return getattr(settings, "X_FRAME_OPTIONS", "DENY").upper()

9c19aff7c7561e3a82978a272ecdaad40dda5c00

clickjacking.py

Refs #33476 -- Reformatted code with Black.

django

django/middleware/clickjacking.py

Python

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

validate_config

def validate_config(self, config): site_dir = config_options.SiteDir() docs_dir = config_options.Dir() fname = os.path.join(os.path.abspath('..'), 'mkdocs.yml') config['docs_dir'] = docs_dir.validate(config['docs_dir']) config['site_dir'] = site_dir.validate(config['site_dir']) schema = [ ('site_dir', site_dir), ('docs_dir', docs_dir), ] cfg = Config(schema, fname) cfg.load_dict(config) failed, warned = cfg.validate() if failed: raise config_options.ValidationError(failed) return True

e7f07cc82ab2be920ab426ba07456d8b2592714d

config_options_tests.py

Remove spaces at the ends of docstrings, normalize quotes

mkdocs

mkdocs/tests/config/config_options_tests.py

Python

https://github.com/mkdocs/mkdocs.git

axis

def axis(self): axis = self.vector_part().normalize() return Quaternion(0, axis.b, axis.c, axis.d)

72a2eb0cd1dda000a1fe56bb0fc8ff1f3c119bd9

quaternion.py

made changes

sympy

sympy/algebras/quaternion.py

Python

https://github.com/sympy/sympy.git

editor_attributes

def editor_attributes(self, image, alt_text): return { "data-embedtype": "image", "data-id": image.id, "data-format": self.name, "data-alt": escape(alt_text), }

d10f15e55806c6944827d801cd9c2d53f5da4186

formats.py

Reformat with black

wagtail

wagtail/images/formats.py

Python

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

find_head_tail

def find_head_tail(self, points, orientation_thr): assert points.ndim == 2 assert points.shape[0] >= 4 assert points.shape[1] == 2 assert isinstance(orientation_thr, float) if len(points) > 4: pad_points = np.vstack([points, points[0]]) edge_vec = pad_points[1:] - pad_points[:-1] theta_sum = [] adjacent_vec_theta = [] for i, edge_vec1 in enumerate(edge_vec): adjacent_ind = [x % len(edge_vec) for x in [i - 1, i + 1]] adjacent_edge_vec = edge_vec[adjacent_ind] temp_theta_sum = np.sum( self.vector_angle(edge_vec1, adjacent_edge_vec)) temp_adjacent_theta = self.vector_angle(adjacent_edge_vec[0], adjacent_edge_vec[1]) theta_sum.append(temp_theta_sum) adjacent_vec_theta.append(temp_adjacent_theta) theta_sum_score = np.array(theta_sum) / np.pi adjacent_theta_score = np.array(adjacent_vec_theta) / np.pi poly_center = np.mean(points, axis=0) edge_dist = np.maximum( norm( pad_points[1:] - poly_center, axis=-1), norm( pad_points[:-1] - poly_center, axis=-1)) dist_score = edge_dist / np.max(edge_dist) position_score = np.zeros(len(edge_vec)) score = 0.5 * theta_sum_score + 0.15 * adjacent_theta_score score += 0.35 * dist_score if len(points) % 2 == 0: position_score[(len(score) // 2 - 1)] += 1 position_score[-1] += 1 score += 0.1 * position_score pad_score = np.concatenate([score, score]) score_matrix = np.zeros((len(score), len(score) - 3)) x = np.arange(len(score) - 3) / float(len(score) - 4) gaussian = 1. / (np.sqrt(2. * np.pi) * 0.5) * np.exp(-np.power( (x - 0.5) / 0.5, 2.) / 2) gaussian = gaussian / np.max(gaussian) for i in range(len(score)): score_matrix[i, :] = score[i] + pad_score[(i + 2):(i + len( score) - 1)] * gaussian * 0.3 head_start, tail_increment = np.unravel_index(score_matrix.argmax(), score_matrix.shape) tail_start = (head_start + tail_increment + 2) % len(points) head_end = (head_start + 1) % len(points) tail_end = (tail_start + 1) % len(points) if head_end > tail_end: head_start, tail_start = tail_start, head_start head_end, tail_end = tail_end, head_end head_inds = [head_start, head_end] tail_inds = [tail_start, tail_end] else: if self.vector_slope(points[1] - points[0]) + self.vector_slope( points[3] - points[2]) < self.vector_slope(points[ 2] - points[1]) + self.vector_slope(points[0] - points[ 3]): horizontal_edge_inds = [[0, 1], [2, 3]] vertical_edge_inds = [[3, 0], [1, 2]] else: horizontal_edge_inds = [[3, 0], [1, 2]] vertical_edge_inds = [[0, 1], [2, 3]] vertical_len_sum = norm(points[vertical_edge_inds[0][0]] - points[ vertical_edge_inds[0][1]]) + norm(points[vertical_edge_inds[1][ 0]] - points[vertical_edge_inds[1][1]]) horizontal_len_sum = norm(points[horizontal_edge_inds[0][ 0]] - points[horizontal_edge_inds[0][1]]) + norm(points[ horizontal_edge_inds[1][0]] - points[horizontal_edge_inds[1] [1]]) if vertical_len_sum > horizontal_len_sum * orientation_thr: head_inds = horizontal_edge_inds[0] tail_inds = horizontal_edge_inds[1] else: head_inds = vertical_edge_inds[0] tail_inds = vertical_edge_inds[1] return head_inds, tail_inds

9f62b610dea6161627200ed85d92e19b1923279a

fce_targets.py

add fcenet

PaddleOCR

ppocr/data/imaug/fce_targets.py

Python

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

_is_dataframe

def _is_dataframe(self) -> bool: return issubclass(self._pandas_class, pandas.DataFrame)

2ebc9cf51bfc773e3d4c898f5a33c0f60ad7ebc5

base.py

REFACTOR-#5310: Remove some hasattr('columns') checks. (#5311) Signed-off-by: mvashishtha <[email protected]>

modin

modin/pandas/base.py

Python

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

forward_loss

def forward_loss(self, pixel_values, pred, mask): target = self.patchify(pixel_values) if self.config.norm_pix_loss: mean = tf.reduce_mean(target, axis=-1, keepdims=True) var = tf.math.reduce_variance(target, axis=-1, keepdims=True) target = (target - mean) / (var + 1.0e-6) ** 0.5 loss = (pred - target) ** 2 loss = tf.reduce_mean(loss, axis=-1) # [batch_size, num_patches], mean loss per patch loss = tf.reduce_sum(loss * mask) / tf.reduce_sum(mask) # mean loss on removed patches return loss

b681e12d5963490d29c2a77ba7346ee050e46def

modeling_tf_vit_mae.py

[ViTMAE] Fix docstrings and variable names (#17710) * Fix docstrings and variable names * Rename x to something better * Improve messages * Fix docstrings and add test for greyscale images Co-authored-by: Niels Rogge <[email protected]>

transformers

src/transformers/models/vit_mae/modeling_tf_vit_mae.py

Python

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

extract_frames

def extract_frames(self, bpf_buffer): # Ensure that the BPF buffer contains at least the header len_bb = len(bpf_buffer) if len_bb < _bpf_hdr_len: return # Extract useful information from the BPF header bh_hdr = bpf_hdr.from_buffer_copy(bpf_buffer) if bh_hdr.bh_datalen == 0: return # Get and store the Scapy object frame_str = bpf_buffer[ bh_hdr.bh_hdrlen:bh_hdr.bh_hdrlen + bh_hdr.bh_caplen ] if _NANOTIME: ts = bh_hdr.bh_tstamp.tv_sec + 1e-9 * bh_hdr.bh_tstamp.tv_nsec else: ts = bh_hdr.bh_tstamp.tv_sec + 1e-6 * bh_hdr.bh_tstamp.tv_usec self.received_frames.append( (self.guessed_cls, frame_str, ts) ) # Extract the next frame end = self.bpf_align(bh_hdr.bh_hdrlen, bh_hdr.bh_caplen) if (len_bb - end) >= 20: self.extract_frames(bpf_buffer[end:])

adaa923db82be88e5bd84b4046faa23f2b69d0ed

supersocket.py

Major BPF improvements This adds: - timestamps support - structures of bpf_hdr - nanosecond precision on FREEBSD - cleanups

scapy

scapy/arch/bpf/supersocket.py

Python

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

as_content_primitive

def as_content_primitive(self, radical=False, clear=True): con, prim = self.func(*[_keep_coeff(*a.as_content_primitive( radical=radical, clear=clear)) for a in self.args]).primitive() if not clear and not con.is_Integer and prim.is_Add: con, d = con.as_numer_denom() _p = prim/d if any(a.as_coeff_Mul()[0].is_Integer for a in _p.args): prim = _p else: con /= d if radical and prim.is_Add: # look for common radicals that can be removed args = prim.args rads = [] common_q = None for m in args: term_rads = defaultdict(list) for ai in Mul.make_args(m): if ai.is_Pow: b, e = ai.as_base_exp() if e.is_Rational and b.is_Integer: term_rads[e.q].append(abs(int(b))**e.p) if not term_rads: break if common_q is None: common_q = set(term_rads.keys()) else: common_q = common_q & set(term_rads.keys()) if not common_q: break rads.append(term_rads) else: # process rads # keep only those in common_q for r in rads: for q in list(r.keys()): if q not in common_q: r.pop(q) for q in r: r[q] = Mul(*r[q]) # find the gcd of bases for each q G = [] for q in common_q: g = reduce(igcd, [r[q] for r in rads], 0) if g != 1: G.append(g**Rational(1, q)) if G: G = Mul(*G) args = [ai/G for ai in args] prim = G*prim.func(*args) return con, prim

19114acf6514bc87f5c8cfde35e0fcab88965be7

add.py

Code optimizations

sympy

sympy/core/add.py

Python

https://github.com/sympy/sympy.git

_add_projection

def _add_projection(self, frame): proj = CalciteProjectionNode( frame._table_cols, [self._ref(frame, col) for col in frame._table_cols] ) self._push(proj) return proj

e5b1888cd932909e49194d58035da34b210b91c4

calcite_builder.py

FEAT-#4946: Replace OmniSci with HDK (#4947) Co-authored-by: Iaroslav Igoshev <[email protected]> Signed-off-by: Andrey Pavlenko <[email protected]>

modin

modin/experimental/core/execution/native/implementations/hdk_on_native/calcite_builder.py

Python

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

closing

def closing(pool): # type: (Pool) -> Iterator[Pool] try: yield pool finally: # For Pool.imap*, close and join are needed # for the returned iterator to begin yielding. pool.close() pool.join() pool.terminate()

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

parallel.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/utils/parallel.py

Python

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

_cov

def _cov(self, min_periods, ddof, numeric_only): # noqa: PR01, RT01, D200 if not numeric_only: return self._default_to_pandas( pandas.DataFrame.cov, min_periods=min_periods, ddof=ddof, numeric_only=numeric_only, ) numeric_df = self.drop( columns=[ i for i in self.dtypes.index if not is_numeric_dtype(self.dtypes[i]) ] ) is_notna = True if all(numeric_df.notna().all()): if min_periods is not None and min_periods > len(numeric_df): result = np.empty((numeric_df.shape[1], numeric_df.shape[1])) result.fill(np.nan) return numeric_df.__constructor__(result) else: cols = numeric_df.columns idx = cols.copy() numeric_df = numeric_df.astype(dtype="float64") denom = 1.0 / (len(numeric_df) - ddof) means = numeric_df.mean(axis=0) result = numeric_df - means result = result.T._query_compiler.conj().dot(result._query_compiler) else: result = numeric_df._query_compiler.cov(min_periods=min_periods) is_notna = False if is_notna: result = numeric_df.__constructor__( query_compiler=result, index=idx, columns=cols ) result *= denom else: result = numeric_df.__constructor__(query_compiler=result) return result

7871c7bc5adeeaca9b6fc4b88482be8b18333faa

dataframe.py

FEAT-#4989: Switch pandas version to 1.5 (#5037) Co-authored-by: Mahesh Vashishtha <[email protected]> Co-authored-by: Anatoly Myachev <[email protected]> Co-authored-by: Jonathan Shi <[email protected]> Co-authored-by: Iaroslav Igoshev <[email protected]> Signed-off-by: Vasily Litvinov <[email protected]>

modin

modin/pandas/dataframe.py

Python

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

_object2proto

def _object2proto(self) -> PublishDatasetMessage_PB: return PublishDatasetMessage_PB( msg_id=serialize(self.id), address=serialize(self.address), reply_to=serialize(self.reply_to), dataset_id=self.dataset_id, deployment_id=self.deployment_id, host_or_ip = self.host_or_ip, protocol = self.protocol, port = self.port, client=serialize(self.client), )

54c0a2f6738090252dc2b2863eb3c13b1bcb9e6a

oblv_messages.py

Changes for publishing dataset and passing actions to enclave

PySyft

packages/syft/src/syft/core/node/common/node_service/oblv/oblv_messages.py

Python

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

async_update

async def async_update(self) -> None: _LOGGER.debug("Updating %s", self._config_entry_id) if self._manager: status_info = self._manager.status_info() if status_info: self._update_from_status_info(status_info)

b043053aadab57435c768d1e0fe3892367686999

sensor.py

Improve entity type hints [g] (#77145)

core

homeassistant/components/gdacs/sensor.py

Python

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

test_notification_permission_workaround

def test_notification_permission_workaround(): try: notifications = QWebEnginePage.Feature.Notifications except AttributeError: pytest.skip("No Notifications member") permissions = webenginetab._WebEnginePermissions assert permissions._options[notifications] == 'content.notifications.enabled' assert permissions._messages[notifications] == 'show notifications'

0877fb0d78635692e481c8bde224fac5ad0dd430

test_webenginetab.py

Run scripts/dev/rewrite_enums.py

qutebrowser

tests/unit/browser/webengine/test_webenginetab.py

Python

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

test_data_parameter_replacement

def test_data_parameter_replacement(): program = ( "import logging; " "logging.basicConfig(level=logging.DEBUG); " "import matplotlib.pyplot as plt" ) cmd = [sys.executable, "-c", program] completed_proc = subprocess.run(cmd, text=True, capture_output=True) assert 'data parameter docstring error' not in completed_proc.stderr

686c9e5a413e31c46bb049407d5eca285bcab76d

test_preprocess_data.py

Fix spelling errors

matplotlib

lib/matplotlib/tests/test_preprocess_data.py

Python

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

submit_failure

def submit_failure(cls, trigger_id, exc=None, session=None): for task_instance in session.query(TaskInstance).filter( TaskInstance.trigger_id == trigger_id, TaskInstance.state == State.DEFERRED ): # Add the error and set the next_method to the fail state traceback = format_exception(type(exc), exc, exc.__traceback__) if exc else None task_instance.next_method = "__fail__" task_instance.next_kwargs = {"error": "Trigger failure", "traceback": traceback} # Remove ourselves as its trigger task_instance.trigger_id = None # Finally, mark it as scheduled so it gets re-queued task_instance.state = State.SCHEDULED

4ad21f5f7c2d416cf813a860564bc2bf3e161d46

trigger.py

Log traceback in trigger excs (#21213)

airflow

airflow/models/trigger.py

Python

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

uname_attr

def uname_attr(self, attribute): # type: (str) -> str return self._uname_info.get(attribute, "")

f3166e673fe8d40277b804d35d77dcdb760fc3b3

distro.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

pipenv

pipenv/patched/notpip/_vendor/distro.py

Python

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

_set_item_existing_loc

def _set_item_existing_loc(self, row_loc, col_loc, item): row_lookup, col_lookup = self._compute_lookup(row_loc, col_loc) self._setitem_positional( row_lookup, col_lookup, item, axis=self._determine_setitem_axis( row_lookup, col_lookup, is_scalar(row_loc), is_scalar(col_loc) ), )

11ba4811e6db11740e11fd33d3cdfba8ce5bec54

indexing.py

FIX-#3764: Ensure df.loc with a scalar out of bounds appends to df (#3765) Co-authored-by: Devin Petersohn <[email protected]> Co-authored-by: Bill Wang <[email protected]> Co-authored-by: Vasily Litvinov <[email protected]>

modin

modin/pandas/indexing.py

Python

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

test_exclude_glob_case5_include_strong

def test_exclude_glob_case5_include_strong(): incl_dom = {} incl_glob = {} incl_ent = {"binary_sensor.working"} excl_dom = {"binary_sensor"} excl_glob = {"binary_sensor.*"} excl_ent = {"light.ignoreme", "sensor.notworking"} testfilter = generate_filter( incl_dom, incl_ent, excl_dom, excl_ent, incl_glob, excl_glob ) assert testfilter("sensor.test") assert testfilter("sensor.notworking") is False assert testfilter("light.test") assert testfilter("light.ignoreme") is False assert testfilter("binary_sensor.working") assert testfilter("binary_sensor.another") is False assert testfilter("sun.sun") is True

a8349a4866d22cddbca9ac9367d4affae39a8325

test_entityfilter.py

Adjust entity filters to make includes stronger than excludes (#74080) * Adjust entity filters to make includes stronger than excludes Fixes #59080 * adjust test for stronger entity glob includes * sync with docs

core

tests/helpers/test_entityfilter.py

Python

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

_bool_arith_fallback

def _bool_arith_fallback(op_str, a, b): if _has_bool_dtype(a) and _has_bool_dtype(b): if op_str in _BOOL_OP_UNSUPPORTED: warnings.warn( f"evaluating in Python space because the {repr(op_str)} " "operator is not supported by numexpr for the bool dtype, " f"use {repr(_BOOL_OP_UNSUPPORTED[op_str])} instead.", stacklevel=find_stack_level(inspect.currentframe()), ) return True return False

e94faa23e24c0abf9db74d79cfebe06676577867

expressions.py

WARN,TST check stacklevel for all warnings (#47998) * use find_stack_level everywhere * fixup * pyx fixups * fixup test_optional_dependency * fixup api * set check_stacklevel=False for some tests * use lru_cache for currentframe * fixup import in __init__ * add missing imports to pyx files * add missing import * fixup import in conversion * revert some __init__ changes * start n=1 * temporarily dont check stacklevel in _check_plot_works * catch some more warnings * dont check stacklevel in check_plot_works * fixup * ignore stacklevel in check_plot_works

pandas

pandas/core/computation/expressions.py

Python

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

compute_output_shape

def compute_output_shape(self, input_shape): if tf.executing_eagerly(): # In this case we build the model first in order to do shape inference. # This is acceptable because the framework only calls # `compute_output_shape` on shape values that the layer would later be # built for. It would however cause issues in case a user attempts to # use `compute_output_shape` manually with shapes that are incompatible # with the shape the Layer will be called on (these users will have to # implement `compute_output_shape` themselves). self._maybe_build(input_shape) graph_name = str(self.name) + "_scratch_graph" with tf.__internal__.FuncGraph(graph_name).as_default(): input_shape = tf_utils.convert_shapes( input_shape, to_tuples=False )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_layer.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/base_layer.py

Python

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

test_error_wrong_input_output_name

def test_error_wrong_input_output_name(self) -> None: m1, m2 = _load_model(m1_def), _load_model(m2_def) self.assertRaises(ValueError, compose.merge_models, m1, m2, io_map=[("wrong_outname", "B01"), ("B10", "B11"), ("B20", "B21")]) # Wrong output name self.assertRaises(ValueError, compose.merge_models, m1, m2, io_map=[("B00", "wrong_input"), ("B10", "B11"), ("B20", "B21")])

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

compose_test.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 <[email protected]> * Remove MYPY conditional logic in gen_proto.py It breaks the type annotations and shouldn't be needed. Signed-off-by: Gary Miguel <[email protected]> * Get rid of MYPY bool from more scripts Signed-off-by: Gary Miguel <[email protected]> * move Descriptors class above where its referenced in type annotation Signed-off-by: Gary Miguel <[email protected]> * fixes Signed-off-by: Gary Miguel <[email protected]> * remove extra blank line Signed-off-by: Gary Miguel <[email protected]> * fix type annotations Signed-off-by: Gary Miguel <[email protected]> * fix type annotation in gen_docs Signed-off-by: Gary Miguel <[email protected]> * fix Operators.md Signed-off-by: Gary Miguel <[email protected]> * fix TestCoverage.md Signed-off-by: Gary Miguel <[email protected]> * fix protoc-gen-mypy.py Signed-off-by: Gary Miguel <[email protected]>

onnx

onnx/test/compose_test.py

Python

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

get_local_am_pm

def get_local_am_pm(): am_local = time(1).strftime("%p") pm_local = time(13).strftime("%p") return am_local, pm_local @pytest.fixture(params=["string", "pathlike", "buffer"])

ae6dc976d334e791b3e215cf6e63a267675cccbe

@pytest.fixture(params=["string", "pathlike", "buffer"])

test_format.py

BUG: Fixed Unicode decoding error in `Period.strftime` when a locale-specific directive is used (#46405) * Added test representative of #46319. Should fail on CI * Added a gha worker with non utf 8 zh_CN encoding * Attempt to fix the encoding so that locale works * Added the fix, but not using it for now, until CI is able to reproduce the issue. * Crazy idea: maybe simply removing the .utf8 modifier will use the right encoding ! * Hopefully fixing the locale not available error * Now simply generating the locale, not updating the ubuntu one * Trying to install the locale without enabling it * Stupid mistake * Testing the optional locale generator condition * Put back all runners * Added whatsnew * Now using the fix * As per code review: moved locale-switching fixture `overridden_locale` to conftest * Flake8 * Added comments on the runner * Added a non-utf8 locale in the `it_IT` runner. Added the zh_CN.utf8 locale in the tests * Improved readability of fixture `overridden_locale` as per code review * Added two comments on default encoding * Fixed #46319 by adding a new `char_to_string_locale` function in the `tslibs.util` module, able to decode char* using the current locale. * As per code review: modified the test to contain non-utf8 chars. Fixed the resulting issue. * Split the test in two for clarity * Fixed test and flake8 error. * Updated whatsnew to ref #46468 . Updated test name * Removing wrong whatsnew bullet * Nitpick on whatsnew as per code review * Fixed build error rst directive * Names incorrectly reverted in last merge commit * Fixed test_localization so that #46595 can be demonstrated on windows targets (even if today these do not run on windows targets, see #46597) * Fixed `tm.set_locale` context manager, it could error and leak when category LC_ALL was used. Fixed #46595 * Removed the fixture as per code review, and added corresponding parametrization in tests. * Dummy mod to trigger CI again * reverted dummy mod * Attempt to fix the remaining error on the numpy worker * Fixed issue in `_from_ordinal` * Added asserts to try to understand * Reverted debugging asserts and applied fix for numpy repeat from #47670. * Fixed the last issue on numpy dev: a TypeError message had changed * Code review: Removed `EXTRA_LOC` * Code review: removed commented line * Code review: reverted out of scope change * Code review: reverted out of scope change * Fixed unused import * Fixed revert mistake * Moved whatsnew to 1.6.0 * Update pandas/tests/io/parser/test_quoting.py Co-authored-by: Sylvain MARIE <[email protected]>

pandas

pandas/tests/io/formats/test_format.py

Python

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

_get_directory_stash

def _get_directory_stash(self, path): # type: (str) -> str try: save_dir = AdjacentTempDirectory(path) # type: TempDirectory except OSError: save_dir = TempDirectory(kind="uninstall") self._save_dirs[os.path.normcase(path)] = save_dir return save_dir.path

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

req_uninstall.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/req/req_uninstall.py

Python

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

sqrt

def sqrt(x): zero = _constant_to_tensor(0.0, x.dtype.base_dtype) x = tf.maximum(x, zero) return tf.sqrt(x) @keras_export("keras.backend.exp") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

84afc5193d38057e2e2badf9c889ea87d80d8fbf

@keras_export("keras.backend.exp") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

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

_handle_random_seed

def _handle_random_seed(seed=None): if isinstance(seed, np.random.RandomState): rng = seed else: try: # General interface for seeding on numpy >= 1.17 rng = np.random.default_rng(seed) except AttributeError: # We are on numpy < 1.17, handle options ourselves if isinstance(seed, (numbers.Integral, np.integer)): rng = np.random.RandomState(seed) elif seed is None: rng = np.random.RandomState() else: err = "{} cannot be used to seed the random number generator" raise ValueError(err.format(seed)) return rng

5910d6ef50196c8bd1f4ed40a5da202a39d7f62c

algorithms.py

docs: fix typos (#2899) * Small typo fixes * Catch an additional typo Co-authored-by: Michael Waskom <[email protected]>

seaborn

seaborn/algorithms.py

Python

https://github.com/mwaskom/seaborn.git

get_admin_form_fields

def get_admin_form_fields(self, response): fields = [] for fieldset in response.context["adminform"]: for field_line in fieldset: fields.extend(field_line) return fields

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

_fit

def _fit(self, X, y, max_iter, alpha, fit_path, normalize, Xy=None): n_features = X.shape[1] X, y, X_offset, y_offset, X_scale = _preprocess_data( X, y, self.fit_intercept, normalize, self.copy_X ) if y.ndim == 1: y = y[:, np.newaxis] n_targets = y.shape[1] Gram = self._get_gram(self.precompute, X, y) self.alphas_ = [] self.n_iter_ = [] self.coef_ = np.empty((n_targets, n_features), dtype=X.dtype) if fit_path: self.active_ = [] self.coef_path_ = [] for k in range(n_targets): this_Xy = None if Xy is None else Xy[:, k] alphas, active, coef_path, n_iter_ = lars_path( X, y[:, k], Gram=Gram, Xy=this_Xy, copy_X=self.copy_X, copy_Gram=True, alpha_min=alpha, method=self.method, verbose=max(0, self.verbose - 1), max_iter=max_iter, eps=self.eps, return_path=True, return_n_iter=True, positive=self.positive, ) self.alphas_.append(alphas) self.active_.append(active) self.n_iter_.append(n_iter_) self.coef_path_.append(coef_path) self.coef_[k] = coef_path[:, -1] if n_targets == 1: self.alphas_, self.active_, self.coef_path_, self.coef_ = [ a[0] for a in (self.alphas_, self.active_, self.coef_path_, self.coef_) ] self.n_iter_ = self.n_iter_[0] else: for k in range(n_targets): this_Xy = None if Xy is None else Xy[:, k] alphas, _, self.coef_[k], n_iter_ = lars_path( X, y[:, k], Gram=Gram, Xy=this_Xy, copy_X=self.copy_X, copy_Gram=True, alpha_min=alpha, method=self.method, verbose=max(0, self.verbose - 1), max_iter=max_iter, eps=self.eps, return_path=False, return_n_iter=True, positive=self.positive, ) self.alphas_.append(alphas) self.n_iter_.append(n_iter_) if n_targets == 1: self.alphas_ = self.alphas_[0] self.n_iter_ = self.n_iter_[0] self._set_intercept(X_offset, y_offset, X_scale) return self

1c094728a33f05bb6c83d7b856b87254964e0e8c

_least_angle.py

CLN clean _preprocess_data in linear_model (#22762)

scikit-learn

sklearn/linear_model/_least_angle.py

Python

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

delete_instance

def delete_instance(self, instance_id): request = DeleteInstanceRequest() request.set_InstanceId(instance_id) request.set_Force(True) logging.info("Delete %s command submit successfully", instance_id) self._send_request(request)

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

utils.py

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

ray

python/ray/autoscaler/_private/aliyun/utils.py

Python

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

__aenter__

async def __aenter__(self): await self.before_transition(self.context) self.context.rule_signature.append(str(self.__class__)) return self.context

e935e13e0f2abf2be02b548bbd7e874d131162b0

rules.py

Push nullified transition logic into GlobalTransforms - we may choose to run some bookkeeping even if a transition is aborted

prefect

src/prefect/orion/orchestration/rules.py

Python

https://github.com/PrefectHQ/prefect.git

write_hashes

def write_hashes(filename): [head, tail] = os.path.split(filename) new_filename = f"{head}/hashed-{tail}" shutil.copy(filename, new_filename) with open(filename) as in_file: data = json.loads(in_file.read()) click.echo(f"Event ID: {data['event_id']}") click.echo("Writing span hashes") config = load_span_grouping_config({"id": DEFAULT_CONFIG_ID}) results = config.execute_strategy(data) with open(new_filename, "w") as out_file: results.write_to_event(data) out_file.write(json.dumps(data, indent=4)) click.echo("Done") click.echo("\n")

9738a416a27cd77a3d9a2e506c31d8280e0bf1af

spans.py

feat(suspect-spans): Add CLI script for testing hashing output (#40668) Adds a CLI script for testing our spans hashes. Given a file, runs grouping, and writes the result to a new JSON file.

sentry

src/sentry/runner/commands/spans.py

Python

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

_get_ordered_dummies

def _get_ordered_dummies(mul, verbose=False): # setup dicts to avoid repeated calculations in key() args = Mul.make_args(mul) fac_dum = { fac: fac.atoms(Dummy) for fac in args } fac_repr = { fac: __kprint(fac) for fac in args } all_dums = set().union(*fac_dum.values()) mask = {} for d in all_dums: if d.assumptions0.get('below_fermi'): mask[d] = '0' elif d.assumptions0.get('above_fermi'): mask[d] = '1' else: mask[d] = '2' dum_repr = {d: __kprint(d) for d in all_dums}

24f1e7730119fe958cc8e28411f790c9a5ec04eb

secondquant.py

Fix various typos Found via `codespell -q 3 -L aboves,aline,ans,aother,arithmetics,assum,atleast,braket,clen,declar,declars,dorder,dum,enew,fo,fro,inout,iself,ist,ket,lamda,lightyear,lightyears,nd,numer,numers,orderd,ot,pring,rcall,rever,ro,ser,siz,splitted,sring,supercedes,te,tht,unequality,upto,vas,versin,whet`

sympy

sympy/physics/secondquant.py

Python

https://github.com/sympy/sympy.git

_pprint_semantics_within_frame

def _pprint_semantics_within_frame(self, vnframe, indent=""): pieces = [] for predicate in vnframe["semantics"]: arguments = [argument["value"] for argument in predicate["arguments"]] pieces.append( f"{'¬' if predicate['negated'] else ''}{predicate['predicate_value']}({', '.join(arguments)})" ) return "\n".join(f"{indent}* {piece}" for piece in pieces)

8b43b49b0cd8c12cae1d48df27edfdd98cf859fd

verbnet.py

Read 'bool' field from VerbNet

nltk

nltk/corpus/reader/verbnet.py

Python

https://github.com/nltk/nltk.git

dev_clone_iter

def dev_clone_iter(xs, devs): if isinstance(devs, str): devs = [devs] return DevClonedIter([dev_clone(x, devs) for x in xs], devs)

d743336b1f3654cd0315f380f43eed4116997c1d

device.py

renamed dev_str arg to dev for all methods.

ivy

ivy/core/device.py

Python

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

test_ts

def test_ts(self, mock_handler): # TS df2 = pd.DataFrame(pd.date_range(start='1/1/2018', end='1/31/2018'), columns=['t']) df3 = df2.copy() df2['a'] = 'a' df2['x'] = range(1, 32) df3['a'] = 'b' df3['x'] = range(11, 42) df = pd.concat([df2, df3]) self.set_handler(mock_handler, name='pg', tables={'df': df}) # create project self.run_sql('create database proj') # TS predictor # create predictor self.run_sql() self.wait_predictor('proj', 'modelx') # run predict ret = self.run_sql() # LW can predict assert list(ret.x) == [42, 43, 44]

9ce5a21dd6359fd7e8ebf78051ce9e97bd195ec9

test_lightwood.py

ML handler supbrocess (#3377) * log -> logger dividing components: app initialize parse args set env.MINDSDB_CONFIG_PATH config requiers env.MINDSDB_CONFIG_PATH sets env.MINDSDB_DB_CON Config() - makes initialization log uses config initialize_log - makes initialization database uses env.MINDSDB_DB_CON have init() method file storage uses config * partial sync for model storage interfaces * ml handler in subprocess interface * fix delete model * fix: model with error in success status * fix: remove hf predictor * fix pg handler * MLHandlerPersistWrapper keeps wrapper process opened * predictor with error keeps 'success' status #3362 * lock for sending tasks to subprocess one by one * check target of predictor before run learn in subproccess * fix check target * fix: json_ai override and problem definition generation * fix None case * folder for ml handler tests * fix: add timeseries_settings key to learn_args * fixes in lw_handler * fix: del join_learn_process * tests for LW handler * finish unit test for LW * changes in tests: - set-project -> to base class - return of ml handler is dataframe - draft for project structure test * merge from staging * create_validation method to check learn params before send to subprocess fixes of HF fixed version of transformers in HF requirements Co-authored-by: Patricio Cerda Mardini <[email protected]>

mindsdb

tests/unit/ml_handlers/test_lightwood.py

Python

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

sys_tags

def sys_tags(**kwargs): # type: (bool) -> Iterator[Tag] warn = _warn_keyword_parameter("sys_tags", kwargs) interp_name = interpreter_name() if interp_name == "cp": for tag in cpython_tags(warn=warn): yield tag else: for tag in generic_tags(): yield tag for tag in compatible_tags(): yield tag

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

tags.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_vendor/packaging/tags.py

Python

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

mixin_http_gateway_parser

def mixin_http_gateway_parser(parser=None): gp = add_arg_group(parser, title='HTTP Gateway') gp.add_argument( '--title', type=str, help='The title of this HTTP server. It will be used in automatics docs such as Swagger UI.', ) gp.add_argument( '--description', type=str, help='The description of this HTTP server. It will be used in automatics docs such as Swagger UI.', ) gp.add_argument( '--cors', action='store_true', default=False, help=, ) gp.add_argument( '--default-swagger-ui', action='store_true', default=False, help='If set, the default swagger ui is used for `/docs` endpoint. ', ) gp.add_argument( '--no-debug-endpoints', action='store_true', default=False, help='If set, /status /post endpoints are removed from HTTP interface. ', ) gp.add_argument( '--no-crud-endpoints', action='store_true', default=False, help=, ) gp.add_argument( '--expose-endpoints', type=str, help=, ) gp.add_argument( '--uvicorn-kwargs', action=KVAppendAction, metavar='KEY: VALUE', nargs='*', help=, ) gp.add_argument( '--grpc-server-kwargs', action=KVAppendAction, metavar='KEY: VALUE', nargs='*', help=, ) gp.add_argument( '--ssl-certfile', type=str, help=, dest='ssl_certfile', ) gp.add_argument( '--ssl-keyfile', type=str, help=, dest='ssl_keyfile', )

dd5f08e9d0c535de2f0e6b106db3b21c597752cd

remote.py

feat: add grpc tls support on gateway (#4522)

jina

jina/parsers/orchestrate/runtimes/remote.py

Python

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

next

def next(self): self._check("ra") if self.firstmember is not None: m = self.firstmember self.firstmember = None return m # Read the next block. self.fileobj.seek(self.offset) tarinfo = None while True: try: tarinfo = self.tarinfo.fromtarfile(self) except EOFHeaderError as e: if self.ignore_zeros: self._dbg(2, "0x%X: %s" % (self.offset, e)) self.offset += BLOCKSIZE continue except InvalidHeaderError as e: if self.ignore_zeros: self._dbg(2, "0x%X: %s" % (self.offset, e)) self.offset += BLOCKSIZE continue elif self.offset == 0: raise ReadError(str(e)) except EmptyHeaderError: if self.offset == 0: raise ReadError("empty file") except TruncatedHeaderError as e: if self.offset == 0: raise ReadError(str(e)) except SubsequentHeaderError as e: raise ReadError(str(e)) break if tarinfo is not None: self.members.append(tarinfo) else: self._loaded = True return tarinfo #-------------------------------------------------------------------------- # Little helper methods:

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

tarfile.py

Vendor in pip 22.1.2

pipenv

pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py

Python

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

generate_config_style_dict

def generate_config_style_dict(self) -> dict[str, str]: keys_converting_dict = { "fill": ("color", "fill_color"), "fill-opacity": ("opacity", "fill_opacity"), "stroke": ("color", "stroke_color"), "stroke-opacity": ("opacity", "stroke_opacity"), "stroke-width": ("stroke_width",), } svg_default_dict = self.svg_default result = {} for svg_key, style_keys in keys_converting_dict.items(): for style_key in style_keys: if svg_default_dict[style_key] is None: continue result[svg_key] = str(svg_default_dict[style_key]) return result

309c9d41eb734ca85a7aea5533f88a6d4ee7c944

svg_mobject.py

Ported improved implementation of :class:`.SVGMobject` from 3b1b/manim (#2898) * port SVGMobject from 3b1b/manim * added svgelements as dependency * revert change of default values * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * set default stroke_width of svg elements to 0 if not set * fix handling of circles with different rx/ry * turn more methods into staticmethods * removed duplicated method * set/adapt stroke-width of some test SVGs * updated control data * forgot some control data * fixed init_colors in tex_mobject and text_mobject * minor changes, added docstrings * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * module docstring, removed import * vector_to_coords changed again * nail sphinx version to below 5.1 to fix rtd (?) * update test_text control data for science * changed Brace to use VMobjectFromSVGPath * remove unused classes and methods depending on old SVG path implementation * remove style_utils and svg_path modules * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * change test_text to use monospace font * restore geometry.polygram * added get_mobject_type_class auxiliary method; changed polyline implementation to ad-hoc approach * restore test_text to previous version * skip Use tags as svgelements already populates them Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

manim

manim/mobject/svg/svg_mobject.py

Python

https://github.com/ManimCommunity/manim.git

test_update_from_select

def test_update_from_select(self, mock_handler): self.set_handler(mock_handler, name='pg', tables={'tasks': self.df}) # --- use predictor --- predictor = { 'name': 'task_model', 'predict': 'p', 'dtypes': { 'p': dtype.float, 'a': dtype.integer, 'b': dtype.categorical, 'c': dtype.datetime }, 'predicted_value': 'ccc' } self.set_predictor(predictor) sql = ret = self.command_executor.execute_command( parse_sql(sql, dialect='mindsdb')) assert ret.error_code is None # 1 select and 2 updates assert mock_handler().query.call_count == 3 # second is update assert mock_handler().query.call_args_list[1][0][0].to_string() == "update table2 set a1=1, c1='ccc' where (a1 = 1) AND (b1 = 'ccc')" # @patch('mindsdb.integrations.handlers.postgres_handler.Handler') # def test_union_type_mismatch(self, mock_handler): # self.set_handler(mock_handler, name='pg', tables={'tasks': self.df}) # # sql = # from mindsdb.api.mysql.mysql_proxy.utilities import ErSqlWrongArguments # with pytest.raises(ErSqlWrongArguments): # self.command_executor.execute_command(parse_sql(sql, dialect='mindsdb'))

0dadd5cecec68f252a08637f695b0e4b573b316f

test_executor.py

support of update command #2454

mindsdb

tests/unit/test_executor.py

Python

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

synchronize_between_processes

def synchronize_between_processes(self): t = reduce_across_processes([self.count, self.total]) t = t.tolist() self.count = int(t[0]) self.total = t[1]

e556640badaa3d565e8a1238154265eaccf9f49c

utils.py

Reduce variance of evaluation in reference (#5819) * Change code to reduce variance in eval * Remove unnecessary new line * Fix missing import warnings * Fix the warning on video_classification * Fix bug to get len of UniformClipSampler

vision

references/segmentation/utils.py

Python

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

convert_types

def convert_types(self, schema, col_type_dict, row, stringify_dict=False) -> list: return [ self.convert_type(value, col_type_dict.get(name), stringify_dict=stringify_dict) for name, value in zip(schema, row) ]

766726f2e3a282fcd2662f5dc6e9926dc38a6540

sql_to_gcs.py

Fix `PostgresToGCSOperator` does not allow nested JSON (#23063) * Avoid double json.dumps for json data export in PostgresToGCSOperator. * Fix CI

airflow

airflow/providers/google/cloud/transfers/sql_to_gcs.py

Python

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

__next__

def __next__(self): if "run" not in self.unresolved_spec: raise TuneError("Must specify `run` in {}".format(self.unresolved_spec)) if self.variants and self.variants.has_next(): # This block will be skipped upon instantiation. # `variants` will be set later after the first loop. resolved_vars, spec = next(self.variants) return self.create_trial(resolved_vars, spec) if self.points_to_evaluate: config = self.points_to_evaluate.pop(0) self.num_samples_left -= 1 self.variants = _VariantIterator( get_preset_variants( self.unresolved_spec, config, constant_grid_search=self.constant_grid_search, random_state=self.random_state, ), lazy_eval=self.lazy_eval, ) resolved_vars, spec = next(self.variants) return self.create_trial(resolved_vars, spec) elif self.num_samples_left > 0: self.variants = _VariantIterator( generate_variants( self.unresolved_spec, constant_grid_search=self.constant_grid_search, random_state=self.random_state, ), lazy_eval=self.lazy_eval, ) self.num_samples_left -= 1 resolved_vars, spec = next(self.variants) return self.create_trial(resolved_vars, spec) else: raise StopIteration

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

basic_variant.py

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

ray

python/ray/tune/suggest/basic_variant.py

Python

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

test_tweedie_link_auto

def test_tweedie_link_auto(power, expected_link_class): y = np.array([0.1, 0.5]) # in range of all distributions X = np.array([[1], [2]]) glm = TweedieRegressor(link="auto", power=power).fit(X, y) assert isinstance(glm._linear_loss.base_loss.link, expected_link_class) @pytest.mark.parametrize("power", [0, 1, 1.5, 2, 3]) @pytest.mark.parametrize("link", ["log", "identity"])

75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc

@pytest.mark.parametrize("power", [0, 1, 1.5, 2, 3]) @pytest.mark.parametrize("link", ["log", "identity"])

test_glm.py

ENH migrate GLMs / TweedieRegressor to linear loss (#22548) Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]>

scikit-learn

sklearn/linear_model/_glm/tests/test_glm.py

Python

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

gmean

def gmean(a, axis=0, dtype=None, weights=None): r if not isinstance(a, np.ndarray): # if not an ndarray object attempt to convert it log_a = np.log(np.array(a, dtype=dtype)) elif dtype: # Must change the default dtype allowing array type if isinstance(a, np.ma.MaskedArray): log_a = np.log(np.ma.asarray(a, dtype=dtype)) else: log_a = np.log(np.asarray(a, dtype=dtype)) else: log_a = np.log(a) if weights is not None: weights = np.asanyarray(weights, dtype=dtype) return np.exp(np.average(log_a, axis=axis, weights=weights)) @_axis_nan_policy_factory( lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True, result_unpacker=lambda x: (x,), kwd_samples=['weights'])

56869131c8e0a0d6e1af86cc1a000c61e83efcf6

@_axis_nan_policy_factory( lambda x: x, n_samples=1, n_outputs=1, too_small=0, paired=True, result_unpacker=lambda x: (x,), kwd_samples=['weights'])

_stats_py.py

DOC: stats: correct doc display

scipy

scipy/stats/_stats_py.py

Python

https://github.com/scipy/scipy.git

_wrap_model

def _wrap_model(self): if not self.is_wrapped: for _, wrapper in reversed(self.get_modules_wrapper().items()): _setattr(self.bound_model, wrapper.name, wrapper) wrapper._weight2buffer() self.is_wrapped = True

2566badb06095b9e3ea16eb6f00fd58da65a95fd

pruner.py

[Model Compression] Pruning Wrapper Refactor (#4488)

nni

nni/algorithms/compression/v2/pytorch/base/pruner.py

Python

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

check_convert_parameter

def check_convert_parameter(name, value, parameter): try: # Try to cast the value to the correct type if int or float if parameter.type_ is int: new_value = parameter.type_(float(value)) elif parameter.type_ is float: new_value = parameter.type_(value) elif parameter.type_ is bool: new_value = strtobool(value) else: new_value = value except ValueError: new_value = parameter.default console.print( f"[red]'{name}' format should be '{parameter.type_.__name__}' type[/red]", f"[red]and could not be converted. Setting default '{new_value}'.\n[/red]", ) return new_value

faca7ab67d1ce5d0ae0e5c862332bcfc37f72ea9

params_helpers.py

Portfolio optimization bug fixes (#3675) * remove hcp * add prams dict to statics * little controller bug * fix view bug * avoid crash if one stock * check params on setup * create parameter class * check and convert parameters using class * change params name to avoid confusion * create a parameter statics dict * change some funcs names * remove unused imports * remove default dict * optional type * add multi choices * cast only int and float * fix completer * fix bugs with parameter validation * fix bugs with parameter validation * add excel formatting * sdk needs mapping as well, controller takes care of this in terminal * small formating * add some safe guard try except * controller bugs * oops * change export path of parameters to portfolio folder * add more commands to scripts * catch optimization exception * log errors * black and exceptions * add flag to test * black * flake8 * forgot this * pylint * change defaults * fix ef default * fix bl * sync sdk defaults * sync last defaults * fix plot heat and add more choices to controller autocomplete * patch weights * fix wrong bool parsing Co-authored-by: James Maslek <[email protected]>

OpenBBTerminal

openbb_terminal/portfolio/portfolio_optimization/parameters/params_helpers.py

Python

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

test_remember_collapsed

def test_remember_collapsed(self): # Sidebar should not be collapsed self.client.cookies["wagtail_sidebar_collapsed"] = "0" response = self.client.get(reverse("wagtailadmin_home")) self.assertNotContains(response, "sidebar-collapsed") # Sidebar should be collapsed self.client.cookies["wagtail_sidebar_collapsed"] = "1" response = self.client.get(reverse("wagtailadmin_home")) self.assertContains(response, "sidebar-collapsed")

d10f15e55806c6944827d801cd9c2d53f5da4186

test_menu.py

Reformat with black

wagtail

wagtail/admin/tests/test_menu.py

Python

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

test_minibatch_dictionary_learning_warns_and_ignore_n_iter

def test_minibatch_dictionary_learning_warns_and_ignore_n_iter(): warn_msg = "'n_iter' is deprecated in version 1.1" with pytest.warns(FutureWarning, match=warn_msg): model = MiniBatchDictionaryLearning(batch_size=256, n_iter=2, max_iter=2).fit(X) assert model.n_iter_ == 2

06834fc8e197f1f308f5ab690ec73a66b6b0b10b

test_dict_learning.py

DEPR deprecate n_iter in MiniBatchSparsePCA (#23726) Co-authored-by: Jérémie du Boisberranger <[email protected]> Co-authored-by: jeremie du boisberranger <[email protected]> Co-authored-by: Olivier Grisel <[email protected]>

scikit-learn

sklearn/decomposition/tests/test_dict_learning.py

Python

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

installed_with_setuptools_egg_info

def installed_with_setuptools_egg_info(self) -> bool: info_location = self.info_location if not info_location: return False if not info_location.endswith(".egg-info"): return False return pathlib.Path(info_location).is_dir()

f3166e673fe8d40277b804d35d77dcdb760fc3b3

base.py

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

pipenv

pipenv/patched/notpip/_internal/metadata/base.py

Python

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

generate_hash

def generate_hash(): generate = True conn = sqlite3.connect(DB_FILE) c = conn.cursor() while generate: hash = uuid.uuid4().hex c.execute( , (hash,), ) generate = c.fetchone() is not None conn.commit() return hash

cc0cff893f9d7d472788adc2510c123967b384fe

queueing.py

Format The Codebase - black formatting - isort formatting

gradio

gradio/queueing.py

Python

https://github.com/gradio-app/gradio.git

unrank_gray

def unrank_gray(self, rank, superset): graycode_bitlist = GrayCode.unrank(len(superset), rank) return Subset.subset_from_bitlist(superset, graycode_bitlist)

498015021131af4dbb07eb110e5badaba8250c7b

subsets.py

Updated import locations

sympy

sympy/combinatorics/subsets.py

Python

https://github.com/sympy/sympy.git

resample_sidelines

def resample_sidelines(self, sideline1, sideline2, resample_step): assert sideline1.ndim == sideline2.ndim == 2 assert sideline1.shape[1] == sideline2.shape[1] == 2 assert sideline1.shape[0] >= 2 assert sideline2.shape[0] >= 2 assert isinstance(resample_step, float) length1 = sum([ norm(sideline1[i + 1] - sideline1[i]) for i in range(len(sideline1) - 1) ]) length2 = sum([ norm(sideline2[i + 1] - sideline2[i]) for i in range(len(sideline2) - 1) ]) total_length = (length1 + length2) / 2 resample_point_num = max(int(float(total_length) / resample_step), 1) resampled_line1 = self.resample_line(sideline1, resample_point_num) resampled_line2 = self.resample_line(sideline2, resample_point_num) return resampled_line1, resampled_line2

9f62b610dea6161627200ed85d92e19b1923279a

fce_targets.py

add fcenet

PaddleOCR

ppocr/data/imaug/fce_targets.py

Python

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

set_read_only

def set_read_only(self, names, msg="Attribute is read-only"): new_read_only = {name: msg for name in names} if getattr(self, "_read_only", False): self._read_only.update(new_read_only) else: object.__setattr__(self, "_read_only", new_read_only)

b3bb96da2002383625b7ff595d9862a4f0085c17

_utils.py

Make AttributeDict additive ._read_only attribute is now a dict of name -> msgs Overrides .update() method to use __setitem__ implementation Includes updates to unit tests

dash

dash/_utils.py

Python

https://github.com/plotly/dash.git

test_help_text_examples_are_contextualized

def test_help_text_examples_are_contextualized(): rendered_inline = render(spacing_invalid_value("padding", "inline")) assert "widget.styles.padding" in rendered_inline rendered_css = render(spacing_invalid_value("padding", "css")) assert "padding:" in rendered_css

91783b7c1e06a45e93fd89dbdb6aa3d1a9c2e990

test_help_text.py

Testing for help text

textual

tests/css/test_help_text.py

Python

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

test_unlock_post_own_snippet_with_bad_permissions

def test_unlock_post_own_snippet_with_bad_permissions(self): # Remove privileges from user self.user.is_superuser = False self.user.groups.add(Group.objects.get(name="Editors")) self.user.save() # Lock the snippet self.lock_snippet(self.user) next_url = reverse("wagtailadmin_home") response = self.client.post(self.get_url("unlock"), {"next": next_url}) self.refresh_snippet() # Check response self.assertRedirects(response, next_url) # Check that the snippet is not locked self.assertFalse(self.snippet.locked) self.assertIsNone(self.snippet.locked_by) self.assertIsNone(self.snippet.locked_at)

10dbbddaf35607e4257f50dd960520a1268dd225

test_locking.py

Add tests for locking snippets

wagtail

wagtail/snippets/tests/test_locking.py

Python

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

to_integral_value

def to_integral_value(self, rounding=None, context=None): if context is None: context = getcontext() if rounding is None: rounding = context.rounding if self._is_special: ans = self._check_nans(context=context) if ans: return ans return Decimal(self) if self._exp >= 0: return Decimal(self) else: return self._rescale(0, rounding) # the method name changed, but we provide also the old one, for compatibility to_integral = to_integral_value

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_pydecimal.py

Python

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

_update_trial_info

def _update_trial_info(self, expr_dir): trial_id = expr_dir[-8:] meta_file = os.path.join(expr_dir, EXPR_META_FILE) meta = parse_json(meta_file) result_file = os.path.join(expr_dir, EXPR_RESULT_FILE) offset = self._result_offsets.get(trial_id, 0) results, new_offset = parse_multiple_json(result_file, offset) self._add_results(results, trial_id) self._result_offsets[trial_id] = new_offset if meta: TrialRecord.objects.filter(trial_id=trial_id).update( trial_status=meta["status"], end_time=timestamp2date(meta.get("end_time", None)), ) elif len(results) > 0: metrics = { "episode_reward": results[-1].get("episode_reward_mean", None), "accuracy": results[-1].get("mean_accuracy", None), "loss": results[-1].get("loss", None), } if results[-1].get("done"): TrialRecord.objects.filter(trial_id=trial_id).update( trial_status="TERMINATED", end_time=results[-1].get("date", None), metrics=str(metrics), ) else: TrialRecord.objects.filter(trial_id=trial_id).update( metrics=str(metrics) )

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

collector.py

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

ray

python/ray/tune/automlboard/backend/collector.py

Python

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

test_avatar_allowed_mime_type_per_room

def test_avatar_allowed_mime_type_per_room(self): self._setup_local_files( { "good": {"mimetype": "image/png"}, "bad": {"mimetype": "application/octet-stream"}, } ) room_id = self.helper.create_room_as(tok=self.owner_tok) channel = self.make_request( "PUT", f"/rooms/{room_id}/state/m.room.member/{self.owner}", content={"membership": "join", "avatar_url": "mxc://test/bad"}, access_token=self.owner_tok, ) self.assertEqual(channel.code, 403, channel.result) self.assertEqual( channel.json_body["errcode"], Codes.FORBIDDEN, channel.json_body ) channel = self.make_request( "PUT", f"/rooms/{room_id}/state/m.room.member/{self.owner}", content={"membership": "join", "avatar_url": "mxc://test/good"}, access_token=self.owner_tok, ) self.assertEqual(channel.code, 200, channel.result)

bf60da1a60096fac5fb778b732ff2214862ac808

test_profile.py

Configurable limits on avatars (#11846) Only allow files which file size and content types match configured limits to be set as avatar. Most of the inspiration from the non-test code comes from matrix-org/synapse-dinsic#19

synapse

tests/rest/client/test_profile.py

Python

https://github.com/matrix-org/synapse.git

test_blocked_public_room_list_over_federation

def test_blocked_public_room_list_over_federation(self): channel = self.make_signed_federation_request( "GET", "/_matrix/federation/v1/publicRooms", ) self.assertEquals(403, channel.code)

c3db7a0b59d48b8872bc24096f9a2467ef35f703

test_server.py

Tests: replace mocked Authenticator with the real thing (#11913) If we prepopulate the test homeserver with a key for a remote homeserver, we can make federation requests to it without having to stub out the authenticator. This has two advantages: * means that what we are testing is closer to reality (ie, we now have complete tests for the incoming-request-authorisation flow) * some tests require that other objects be signed by the remote server (eg, the event in `/send_join`), and doing that would require a whole separate set of mocking out. It's much simpler just to use real keys.

synapse