Datasets:

semeru

/

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

like 1

test_task_name_consume_folder

def test_task_name_consume_folder(self): result1 = TaskResult.objects.create( task_id=str(uuid.uuid4()), task_name="documents.tasks.some_task", status=celery.states.SUCCESS, task_args="\"('/consume/anothertest.pdf',)\"", task_kwargs="\"{'override_tag_ids': None}\"", ) _ = PaperlessTask.objects.create(attempted_task=result1) response = self.client.get(self.ENDPOINT) self.assertEqual(response.status_code, 200) self.assertEqual(len(response.data), 1) returned_data = response.data[0] self.assertEqual(returned_data["name"], "anothertest.pdf")

5b66ef0a748fd5570361a2a1ed6147e0462568d2

test_api.py

Updates how task_args and task_kwargs are parsed, adds testing to cover everything I can think of

paperless-ngx

src/documents/tests/test_api.py

Python

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

_prepare_registry

def _prepare_registry(self): # noqa cur = self.internal_registry.cursor() if ('models',) not in list(cur.execute("SELECT name FROM sqlite_master WHERE type='table';")): cur.execute() # TODO: dtype_dict? self.internal_registry.commit()

30877cf7ead465750763822b3c88f970c870d9dd

mlflow_integration.py

feat: add mlflow, mysql, base handlers

mindsdb

mindsdb/integrations/mlflow_handler/mlflow/mlflow_integration.py

Python

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

_get_threads

def _get_threads(self) -> MultiThread: # TODO Check if multiple threads actually speeds anything up save_queue = queue_manager.get_queue("convert_out") patch_queue = queue_manager.get_queue("patch") return MultiThread(self._converter.process, patch_queue, save_queue, thread_count=self._pool_processes, name="patch")

1022651eb8a7741014f5d2ec7cbfe882120dfa5f

convert.py

Bugfix: convert - Gif Writer - Fix non-launch error on Gif Writer - convert plugins - linting - convert/fs_media/preview/queue_manager - typing - Change convert items from dict to Dataclass

faceswap

scripts/convert.py

Python

https://github.com/deepfakes/faceswap.git

parseline

def parseline(self, line): line = line.strip() if not line: return None, None, line elif line[0] == '?': line = 'help ' + line[1:] elif line[0] == '!': if hasattr(self, 'do_shell'): line = 'shell ' + line[1:] else: return None, None, line i, n = 0, len(line) while i < n and line[i] in self.identchars: i = i+1 cmd, arg = line[:i], line[i:].strip() return cmd, arg, line

8198943edd73a363c266633e1aa5b2a9e9c9f526

cmd.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/cmd.py

Python

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

_get_animated_artists

def _get_animated_artists(self): return tuple([a for ax_ in self.ax.get_figure().get_axes() for a in ax_.get_children() if a.get_animated() and a not in self.artists])

334cc617b8ed3b6b4ec6cb64ff16a040ef454149

widgets.py

Fix z_order

matplotlib

lib/matplotlib/widgets.py

Python

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

test_message

def test_message(self) -> None: room_id = self.helper.create_room_as( self.other_user_id, tok=self.other_access_token ) # The user should be in the room. self.helper.join(room_id, self.banned_user_id, tok=self.banned_access_token) # Sending a message should complete successfully. result = self.helper.send_event( room_id=room_id, type=EventTypes.Message, content={"msgtype": "m.text", "body": "with right label"}, tok=self.banned_access_token, ) self.assertIn("event_id", result) event_id = result["event_id"] latest_events = self.get_success( self.store.get_latest_event_ids_in_room(room_id) ) self.assertNotIn(event_id, latest_events)

1901cb1d4a8b7d9af64493fbd336e9aa2561c20c

test_shadow_banned.py

Add type hints to `tests/rest/client` (#12084)

synapse

tests/rest/client/test_shadow_banned.py

Python

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

_get_streams

def _get_streams(self): params = self.session.http.get(self.url, schema=validate.Schema( re.compile( r, re.VERBOSE | re.DOTALL, ), validate.none_or_all( validate.get("json"), validate.parse_json(), { "contentId": validate.any(str, int), validate.optional("streamId"): str, validate.optional("idec"): str, validate.optional("token"): str, }, ), )) if not params: log.error("Could not find player manager data") return params.update({ "video": (unquote(params.pop("token")) if params.get("token") is not None else params.pop("streamId")), "noflash": "yes", "embedded": "0", }) url_parsed = urlparse(self.url) skip_vods = url_parsed.netloc.endswith("m4sport.hu") and url_parsed.path.startswith("/elo") self.session.http.headers.update({"Referer": self.url}) playlists = self.session.http.get(self.PLAYER_URL, params=params, schema=validate.Schema( re.compile(r"pl\.setup\s*\(\s*(?P<json>{.*?})\s*\)\s*;", re.DOTALL), validate.none_or_all( validate.get("json"), validate.parse_json(), {"playlist": [{ "file": validate.url(), "type": str, }]}, validate.get("playlist"), validate.filter(lambda p: p["type"] == "hls"), validate.filter(lambda p: not skip_vods or "vod" not in p["file"]), validate.map(lambda p: update_scheme("https://", p["file"])), ), )) for url in playlists or []: yield from HLSStream.parse_variant_playlist(self.session, url).items() __plugin__ = Mediaklikk

08209aecf41706dc1eb0171466d88d7fb02aefca

mediaklikk.py

plugins: refactor validation schemas Refactor validation schemas of plugins where schemas are not defined as class attributes or where no major changes are needed: - Use `validate.none_or_all(...)` - Replace `validate.transform(pattern.search)` with `pattern` and fix schemas using `validate.regex(pattern)` where a regex has to match - Move pattern definitions from class attributes to schema definitions - Fix some patterns in regards to quotation matching - Remove unneeded type validations, like `str` for example - Remove unneeded `TypeError` exceptions from try-except code blocks - Fix minor style issues where it makes sense - use double quotes - add trailing commas - fix indentation

streamlink

src/streamlink/plugins/mediaklikk.py

Python

https://github.com/streamlink/streamlink.git

test_upload_file_with_supplied_mimetype

def test_upload_file_with_supplied_mimetype(self) -> None: fp = StringIO("zulip!") fp.name = "pasted_file" result = self.api_post( self.example_user("hamlet"), "/api/v1/user_uploads?mimetype=image/png", {"file": fp} ) uri = self.assert_json_success(result)["uri"] self.assertTrue(uri.endswith("pasted_file.png"))

a142fbff85302c5e3acb2e204eca2e9c75dbc74b

test_upload.py

tests: Refactor away result.json() calls with helpers. Signed-off-by: Zixuan James Li <p359101898@gmail.com>

zulip

zerver/tests/test_upload.py

Python

https://github.com/zulip/zulip.git

write_graph6

def write_graph6(G, path, nodes=None, header=True): return write_graph6_file(G, path, nodes=nodes, header=header) @not_implemented_for("directed") @not_implemented_for("multigraph")

9b63ca1a0d46a1f50bcc59eda52be02721a134db

@not_implemented_for("directed") @not_implemented_for("multigraph")

graph6.py

Remove old Appveyor cruft (#5924) * Remove old Appveyor cruft * Fix Windows issue

networkx

networkx/readwrite/graph6.py

Python

https://github.com/networkx/networkx.git

test_forked_graph_cleanup

def test_forked_graph_cleanup(self) -> None: r # Create the room graph event_id_a = self.create_and_send_event(self.room_id, self.user) event_id_b = self.create_and_send_event(self.room_id, self.user) event_id_sf1 = self.create_and_send_event( self.room_id, self.user, True, [event_id_a] ) event_id_sf2 = self.create_and_send_event( self.room_id, self.user, True, [event_id_a, event_id_b] ) event_id_sf3 = self.create_and_send_event( self.room_id, self.user, True, [event_id_sf1] ) self.create_and_send_event( self.room_id, self.user, True, [event_id_sf2, event_id_sf3] ) # SF4 event_id_c = self.create_and_send_event( self.room_id, self.user, False, [event_id_sf3] ) # Add the new extremity and check the latest events are as expected self.add_extremity(self.room_id, event_id_a) latest_event_ids = self.get_success( self.store.get_latest_event_ids_in_room(self.room_id) ) self.assertEqual(set(latest_event_ids), {event_id_a, event_id_b, event_id_c}) # Run the background update and check it did the right thing self.run_background_update() latest_event_ids = self.get_success( self.store.get_latest_event_ids_in_room(self.room_id) ) self.assertEqual(set(latest_event_ids), {event_id_b, event_id_c})

3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b

test_cleanup_extrems.py

Require types in tests.storage. (#14646) Adds missing type hints to `tests.storage` package and does not allow untyped definitions.

synapse

tests/storage/test_cleanup_extrems.py

Python

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

_test_settings_get

def _test_settings_get(self, key, default=None, prefixed=None): settings_dict = self.connection.settings_dict val = settings_dict["TEST"].get(key, default) if val is None and prefixed: val = TEST_DATABASE_PREFIX + settings_dict[prefixed] return val

9c19aff7c7561e3a82978a272ecdaad40dda5c00

creation.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/oracle/creation.py

Python

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

throw

def throw(self, typ, val=None, tb=None): if val is None: if tb is None: raise typ val = typ() if tb is not None: val = val.with_traceback(tb) raise val

8198943edd73a363c266633e1aa5b2a9e9c9f526

_collections_abc.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_collections_abc.py

Python

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

count_non_terminated_nodes

def count_non_terminated_nodes() -> int: provider_config = _generate_provider_config(ray_cluster_namespace="default") kuberay_node_provider = _get_node_provider( provider_config=provider_config, cluster_name="raycluster-autoscaler" ) nodes = kuberay_node_provider.non_terminated_nodes({}) return len(nodes)

c4a259828b9cfbfb4f09059f74808893a6d20b76

non_terminated_nodes_count.py

[kuberay] Update KubeRay operator commit, turn autoscaler RPC drain back on (#27077) This PR: - Updates the KubeRay operator commit used in the Ray CI autoscaling test - Uses the RayCluster autoscaling sample config from the KubeRay repo in place of of a config from the Ray repo - Turns the autoscaler RPC worker drain back on, as I saw some dead node messages from the GCS, and the RPC drain is supposed to avoid those. Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>

ray

python/ray/tests/kuberay/scripts/non_terminated_nodes_count.py

Python

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

all_equal

def all_equal(iterable): g = itertools.groupby(iterable) return next(g, True) and not next(g, False)

8f1ba4de582c5e5282c022a7713a56b47302cabe

util.py

Backport parser/alignment optimizations from `feature/refactor-parser` (#10952)

spaCy

spacy/util.py

Python

https://github.com/explosion/spaCy.git

pagination_querystring

def pagination_querystring(context, page_number, page_key="p"): return querystring(context, **{page_key: page_number}) @register.inclusion_tag( "wagtailadmin/pages/listing/_pagination.html", takes_context=True )

d10f15e55806c6944827d801cd9c2d53f5da4186

@register.inclusion_tag( "wagtailadmin/pages/listing/_pagination.html", takes_context=True )

wagtailadmin_tags.py

Reformat with black

wagtail

wagtail/admin/templatetags/wagtailadmin_tags.py

Python

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

test_knn_imputer_keep_empty_features

def test_knn_imputer_keep_empty_features(keep_empty_features): X = np.array([[1, np.nan, 2], [3, np.nan, np.nan]]) imputer = KNNImputer(keep_empty_features=keep_empty_features) for method in ["fit_transform", "transform"]: X_imputed = getattr(imputer, method)(X) if keep_empty_features: assert X_imputed.shape == X.shape assert_array_equal(X_imputed[:, 1], 0) else: assert X_imputed.shape == (X.shape[0], X.shape[1] - 1)

d8fa96c29828e3ca79ddd5d7466521ac4d95213c

test_impute.py

ENH keep features with all missing values during imputation (#24770) Co-authored-by: Chiara Marmo <cmarmo@users.noreply.github.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Vitor SRG <vitorssrg@gmail.com> Fixes https://github.com/scikit-learn/scikit-learn/pull/16695 Fixes https://github.com/scikit-learn/scikit-learn/issues/16426 Fixes https://github.com/scikit-learn/scikit-learn/issues/16977

scikit-learn

sklearn/impute/tests/test_impute.py

Python

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

test_batch_idx

def test_batch_idx(self) -> int: if self.trainer is None: return 0 return self.trainer.test_loop.epoch_loop.batch_progress.current.processed

8a549a550cb10189ff1db382f546a40cd1c6c5b3

base.py

Integrate progress tracking into the progress bar (#11213)

lightning

pytorch_lightning/callbacks/progress/base.py

Python

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

_get_one_trial_job

def _get_one_trial_job(self): if not self.generated_hyper_configs: ret = { 'parameter_id': '-1_0_0', 'parameter_source': 'algorithm', 'parameters': '' } self.send(CommandType.NoMoreTrialJobs, nni.dump(ret)) return None assert self.generated_hyper_configs params = self.generated_hyper_configs.pop(0) ret = { 'parameter_id': params[0], 'parameter_source': 'algorithm', 'parameters': params[1] } self.parameters[params[0]] = params[1] return ret

98c1a77f61900d486f46d284c49fb65675dbee6a

bohb_advisor.py

Support multiple HPO experiments in one process (#4855)

nni

nni/algorithms/hpo/bohb_advisor/bohb_advisor.py

Python

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

get_menu_item

def get_menu_item(self, order=None): return ModelAdminMenuItem(self, order or self.get_menu_order())

b8a9a2d319b06fc2318d68d05b5a6cdf85b5b33d

options.py

Deprecate wagtail.contrib.modeladmin.menus.SubMenu in favour of wagtail.admin.menu.Menu The Menu class was not originally designed to accept menu items at constructor time (instead requiring them to be passed via hooks); ModelAdmin's SubMenu class patched this functionality in, and the documentation for extending admin views piggybacked on this. Add this functionality to the base Menu class so that we don't have this unnecessary dependency on ModelAdmin.

wagtail

wagtail/contrib/modeladmin/options.py

Python

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

get_failure

def get_failure(self, d, exc): deferred: Deferred[Any] = ensureDeferred(d) self.pump() return self.failureResultOf(deferred, exc)

33ebee47e4e96a2b6fdf72091769e59034dc550f

unittest.py

Remove redundant `get_success` calls in test code (#12346) There are a bunch of places we call get_success on an immediate value, which is unnecessary. Let's rip them out, and remove the redundant functionality in get_success and friends.

synapse

tests/unittest.py

Python

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

get_client_ip

def get_client_ip(request, additional_headers=()): HTTP_HEADERS = ( 'HTTP_X_REAL_IP', 'HTTP_X_FORWARDED_FOR', 'REMOTE_ADDR', *additional_headers ) for header in HTTP_HEADERS: if header in request.META: client_ip = request.META[header].split(',')[0] try: return ipaddress.ip_address(client_ip) except ValueError: raise ValueError(f"Invalid IP address set for {header}: {client_ip}") # Could not determine the client IP address from request headers return None

a38a880e67d78eba52f19cc4c2613e9399939c2f

request.py

Refactor source IP resolution logic

netbox

netbox/utilities/request.py

Python

https://github.com/netbox-community/netbox.git

save_video_meta_data

def save_video_meta_data(self, pts_time, keyframes): if pts_time[0] != 0: pts_time, keyframes = self._pad_leading_frames(pts_time, keyframes) sample_filename = next(fname for fname in self.data) basename = sample_filename[:sample_filename.rfind("_")] logger.debug("sample filename: %s, base filename: %s", sample_filename, basename) logger.info("Saving video meta information to Alignments file") for idx, pts in enumerate(pts_time): meta = dict(pts_time=pts, keyframe=idx in keyframes) key = f"{basename}_{idx + 1:06d}.png" if key not in self.data: self.data[key] = dict(video_meta=meta, faces=[]) else: self.data[key]["video_meta"] = meta logger.debug("Alignments count: %s, timestamp count: %s", len(self.data), len(pts_time)) if len(self.data) != len(pts_time): raise FaceswapError( "There is a mismatch between the number of frames found in the video file " f"({len(pts_time)}) and the number of frames found in the alignments file " f"({len(self.data)}).\nThis can be caused by a number of issues:" "\n - The video has a Variable Frame Rate and FFMPEG is having a hard time " "calculating the correct number of frames." "\n - You are working with a Merged Alignments file. This is not supported for " "your current use case." "\nYou should either extract the video to individual frames, re-encode the " "video at a constant frame rate and re-run extraction or work with a dedicated " "alignments file for your requested video.") self.save()

5e73437be47f2410439a3c6716de96354e6a0c94

alignments.py

lib.align updates: - alignments.py - Add typed dicts for imported alignments - Explicitly check for presence of thumb value in alignments dict - linting - detected_face.py - Typing - Linting - Legacy support for pre-aligned face - Update dependencies to new property names

faceswap

lib/align/alignments.py

Python

https://github.com/deepfakes/faceswap.git

unweighted_minimum_spanning_digraph

def unweighted_minimum_spanning_digraph(tree, children=iter, shapes=None, attr=None): return edges2dot( edge_closure( tree, lambda node: unweighted_minimum_spanning_dict(tree, children)[node] ), shapes, attr, ) ########################################################################## # Breadth-First / Depth-first Searches with Cycle Detection ##########################################################################

692adaff901dd9daf29400fdf3385130aefbfb2a

util.py

Fix some tests in Wordnet-related DocStrings

nltk

nltk/util.py

Python

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

_gorg

def _gorg(cls): assert isinstance(cls, GenericMeta) if hasattr(cls, '_gorg'): return cls._gorg while cls.__origin__ is not None: cls = cls.__origin__ return cls _PROTO_WHITELIST = ['Callable', 'Awaitable', 'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator', 'Hashable', 'Sized', 'Container', 'Collection', 'Reversible', 'ContextManager', 'AsyncContextManager']

f3166e673fe8d40277b804d35d77dcdb760fc3b3

typing_extensions.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/typing_extensions.py

Python

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

lemmas

def lemmas(self, lang="eng"): if lang == "eng": return self._lemmas elif self._name: self._wordnet_corpus_reader._load_lang_data(lang) lemmark = [] lemmy = self.lemma_names(lang) for lem in lemmy: temp = Lemma( self._wordnet_corpus_reader, self, lem, self._wordnet_corpus_reader._lexnames.index(self.lexname()), 0, None, ) temp._lang = lang lemmark.append(temp) return lemmark

75f4e2183a80904dd3a6f958072ae2d063b51fad

wordnet.py

Handle wordnet synsets that were lost in mapping

nltk

nltk/corpus/reader/wordnet.py

Python

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

test_cross_validation

def test_cross_validation(self): testargs = .split() with mock.patch.dict(os.environ, {"TESTING_MOCKED_DATALOADERS": "0"}): output = subprocess.run( self._launch_args + testargs, universal_newlines=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE ).stdout results = ast.literal_eval(re.findall("({.+})", output)[-1]) self.assertGreaterEqual(results["accuracy"], 0.75)

23c0341262bd396a3ba9265614b3818d6e08a6c1

test_examples.py

Refactor tests to use accelerate launch (#373) Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

accelerate

tests/test_examples.py

Python

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

parse_headers

def parse_headers(fp, _class=HTTPMessage): headers = _read_headers(fp) hstring = b''.join(headers).decode('iso-8859-1') return email.parser.Parser(_class=_class).parsestr(hstring)

8198943edd73a363c266633e1aa5b2a9e9c9f526

client.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/http/client.py

Python

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

is_executable

def is_executable(path): # This function's signature needs to be repeated # as the first line of its docstring. # This method is reused by the basic module, # the repetition helps the basic module's html documentation come out right. # http://www.sphinx-doc.org/en/master/usage/extensions/autodoc.html#confval-autodoc_docstring_signature # These are all bitfields so first bitwise-or all the permissions we're # looking for, then bitwise-and with the file's mode to determine if any # execute bits are set. return ((stat.S_IXUSR | stat.S_IXGRP | stat.S_IXOTH) & os.stat(path)[stat.ST_MODE])

fee90b15a25b588bfb8a9ff047e851d43e78511f

file.py

Misc typo fixes in module_utils (#76564)

ansible

lib/ansible/module_utils/common/file.py

Python

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

project_group_token

def project_group_token(self, group_tokens): # [B, num_output_groups, C] <- [B, num_group_tokens, C] projected_group_tokens = self.mlp_inter(group_tokens) projected_group_tokens = self.norm_post_tokens(projected_group_tokens) return projected_group_tokens

6c8f4c9a938a09749ea1b19a5fa2a8dd27e99a29

modeling_groupvit.py

Adding GroupViT Models (#17313) * add group vit and fixed test (except slow) * passing slow test * addressed some comments * fixed test * fixed style * fixed copy * fixed segmentation output * fixed test * fixed relative path * fixed copy * add ignore non auto configured * fixed docstring, add doc * fixed copies * Apply suggestions from code review merge suggestions Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * resolve comment, renaming model * delete unused attr * use fix copies * resolve comments * fixed attn * remove unused vars * refactor tests * resolve final comments * add demo notebook * fixed inconsitent default * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * rename stage->stages * Create single GroupViTEncoderLayer class * Update conversion script * Simplify conversion script * Remove cross-attention class in favor of GroupViTAttention * Convert other model as well, add processor to conversion script * addressing final comment * fixed args * Update src/transformers/models/groupvit/modeling_groupvit.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

transformers

src/transformers/models/groupvit/modeling_groupvit.py

Python

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

write_media_player_states

def write_media_player_states(self) -> None: dispatcher_send(self.hass, SONOS_MEDIA_UPDATED, self.soco.uid)

cfd763db40544c31077b46631bbdd9655581dfe9

media.py

Refactor Sonos media metadata handling (#66840) Co-authored-by: Paulus Schoutsen <paulus@home-assistant.io>

core

homeassistant/components/sonos/media.py

Python

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

select_option

def select_option(self, selector, value): from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import Select select = Select(self.selenium.find_element(By.CSS_SELECTOR, selector)) select.select_by_value(value)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/tests.py

Python

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

_random_choice

def _random_choice(self) -> List[int]: retval = [random.choice(indices) for indices in self._indices] logger.debug(retval) return retval

1022651eb8a7741014f5d2ec7cbfe882120dfa5f

preview.py

Bugfix: convert - Gif Writer - Fix non-launch error on Gif Writer - convert plugins - linting - convert/fs_media/preview/queue_manager - typing - Change convert items from dict to Dataclass

faceswap

tools/preview/preview.py

Python

https://github.com/deepfakes/faceswap.git

test_has_related_field_in_list_display_fk

def test_has_related_field_in_list_display_fk(self): state = State.objects.create(name="Karnataka") City.objects.create(state=state, name="Bangalore") response = self.client.get(reverse("admin:admin_views_city_changelist"), {}) response.context["cl"].list_display = ["id", "name", "state"] self.assertIs(response.context["cl"].has_related_field_in_list_display(), True) response.context["cl"].list_display = ["id", "name", "state_id"] self.assertIs(response.context["cl"].has_related_field_in_list_display(), False)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

exit_with_error

def exit_with_error(message, code=1, **kwargs): kwargs.setdefault("style", "red") app.console.print(message, **kwargs) raise typer.Exit(code)

c0cb1fee460c1bded9e3eb741ad7979402844bf8

base.py

Update `set` command; allow CLI `console` object to be patched

prefect

src/prefect/cli/base.py

Python

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

trigger_tool

def trigger_tool(self, name, sender=None, canvasevent=None, data=None): tool = self.get_tool(name) if tool is None: return if sender is None: sender = self if isinstance(tool, backend_tools.ToolToggleBase): self._handle_toggle(tool, canvasevent, data) tool.trigger(sender, canvasevent, data) # Actually trigger Tool. s = 'tool_trigger_%s' % name event = ToolTriggerEvent(s, sender, tool, canvasevent, data) self._callbacks.process(s, event)

eec341a3a5918a59b212afffc2f9285bada1f276

backend_managers.py

Remove several unused variables

matplotlib

lib/matplotlib/backend_managers.py

Python

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

save_file

def save_file(self, name, file_path, file_name=None): files_metadata = self.get_files() if name in [x['name'] for x in files_metadata]: raise Exception(f'File already exists: {name}') if file_name is None: file_name = Path(file_path).name file_dir = None try: df, _col_map = FileHandler._handle_source(file_path) ds_meta = { 'row_count': len(df), 'column_names': list(df.columns) } file_record = db.File( name=name, company_id=ctx.company_id, source_file_path=file_name, file_path='', row_count=ds_meta['row_count'], columns=ds_meta['column_names'] ) db.session.add(file_record) db.session.commit() store_file_path = f'file_{ctx.company_id}_{file_record.id}' file_record.file_path = store_file_path db.session.commit() file_dir = Path(self.dir).joinpath(store_file_path) file_dir.mkdir(parents=True, exist_ok=True) source = file_dir.joinpath(file_name) # NOTE may be delay between db record exists and file is really in folder shutil.move(file_path, str(source)) self.fs_store.put(store_file_path, base_dir=self.dir) except Exception as e: log.logger.error(e) raise finally: if file_dir is not None: shutil.rmtree(file_dir) return file_record.id

7f0d38c3925c981d015e8624662c8e0c13aa4d97

file_controller.py

get company_id from context

mindsdb

mindsdb/interfaces/file/file_controller.py

Python

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

get_source_link

def get_source_link(browser): source = [] try: source.append( browser.find_element( By.XPATH, read_xpath(get_source_link.__name__, "image") ).get_attribute("src") ) except NoSuchElementException: source.append( browser.find_element( By.XPATH, read_xpath(get_source_link.__name__, "video") ).get_attribute("src") ) source.append( browser.find_element( By.XPATH, read_xpath(get_source_link.__name__, "image_alt") ).get_attribute("src") ) return source

2a157d452611d37cf50ccb7d56ff1a06e9790ecb

clarifai_util.py

PR - Fix `extract_text_from_element()`and `find_element*()` to `find_element()` (#6438) * Updated getUserData() and find_element* Signed-off-by: elulcao <elulcao@icloud.com> Thanks @breuerfelix for reviewing, 🚀 People in this thread please let me know if something is not OK, IG changed a lot these days. 🤗 @her

InstaPy

instapy/clarifai_util.py

Python

https://github.com/InstaPy/InstaPy.git

test_changelist_with_no_change_url

def test_changelist_with_no_change_url(self): o = UnchangeableObject.objects.create() response = self.client.get( reverse("admin:admin_views_unchangeableobject_changelist") ) # Check the format of the shown object -- shouldn't contain a change link self.assertContains( response, '<th class="field-__str__">%s</th>' % o, html=True )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

test_cancellation_while_waiting_for_write_lock

def test_cancellation_while_waiting_for_write_lock(self): rwlock = ReadWriteLock() key = "key" # 1. A reader takes the lock and blocks. reader_d, _, unblock_reader = self._start_blocking_reader( rwlock, key, "read completed" ) # 2. A writer waits for the reader to complete. writer1_d, _, unblock_writer1 = self._start_blocking_writer( rwlock, key, "write 1 completed" ) # 3. A second writer waits for both the reader and first writer to complete. # This writer will be cancelled later. writer2_d, _ = self._start_nonblocking_writer(rwlock, key, "write 2 completed") self.assertFalse(writer2_d.called) # 4. A third writer waits for the second writer to complete. writer3_d, _ = self._start_nonblocking_writer(rwlock, key, "write 3 completed") self.assertFalse(writer3_d.called) # 5. The second writer is cancelled, but continues waiting for the lock. # The reader, first writer and third writer should not be cancelled. # The first writer should still be waiting on the reader. # The third writer should still be waiting on the second writer. writer2_d.cancel() self.assertNoResult(writer2_d) self.assertFalse(reader_d.called, "Reader was unexpectedly cancelled") self.assertFalse(writer1_d.called, "First writer was unexpectedly cancelled") self.assertFalse( writer3_d.called, "Third writer was unexpectedly cancelled or given the lock before the first " "writer finished", ) # 6. Unblock the reader, which should complete. # The first writer should be given the lock and block. # The third writer should still be waiting on the second writer. unblock_reader.callback(None) self.assertEqual("read completed", self.successResultOf(reader_d)) self.assertNoResult(writer2_d) self.assertFalse( writer3_d.called, "Third writer was unexpectedly given the lock before the first writer " "finished", ) # 7. Unblock the first writer, which should complete. unblock_writer1.callback(None) self.assertEqual("write 1 completed", self.successResultOf(writer1_d)) # 8. The second writer should take the lock and release it immediately, since it # has been cancelled. self.failureResultOf(writer2_d, CancelledError) # 9. The third writer should take the lock and complete. self.assertTrue( writer3_d.called, "Third writer is stuck waiting for a cancelled writer" ) self.assertEqual("write 3 completed", self.successResultOf(writer3_d))

605d161d7d585847fd1bb98d14d5281daeac8e86

test_rwlock.py

Add cancellation support to `ReadWriteLock` (#12120) Also convert `ReadWriteLock` to use async context managers. Signed-off-by: Sean Quah <seanq@element.io>

synapse

tests/util/test_rwlock.py

Python

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

current_year

def current_year(context): context["current_year"] = datetime.datetime.now().year return context

bbf17ea692e437cec908eae6759ffff8092fb42e

pandas_web.py

WEB: Add new footer to web (#48557)

pandas

web/pandas_web.py

Python

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

remove_field

def remove_field(self, model, field): # Special-case implicit M2M tables if field.many_to_many and field.remote_field.through._meta.auto_created: return self.delete_model(field.remote_field.through) # It might not actually have a column behind it if field.db_parameters(connection=self.connection)["type"] is None: return # Drop any FK constraints, MySQL requires explicit deletion if field.remote_field: fk_names = self._constraint_names(model, [field.column], foreign_key=True) for fk_name in fk_names: self.execute(self._delete_fk_sql(model, fk_name)) # Delete the column sql = self.sql_delete_column % { "table": self.quote_name(model._meta.db_table), "column": self.quote_name(field.column), } self.execute(sql) # Reset connection if required if self.connection.features.connection_persists_old_columns: self.connection.close() # Remove all deferred statements referencing the deleted column. for sql in list(self.deferred_sql): if isinstance(sql, Statement) and sql.references_column( model._meta.db_table, field.column ): self.deferred_sql.remove(sql)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

schema.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/base/schema.py

Python

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

get_characters_loss

def get_characters_loss(ops, docs, prediction, nr_char): target_ids = numpy.vstack([doc.to_utf8_array(nr_char=nr_char) for doc in docs]) target_ids = target_ids.reshape((-1,)) target = ops.asarray(to_categorical(target_ids, n_classes=256), dtype="f") target = target.reshape((-1, 256 * nr_char)) diff = prediction - target loss = (diff**2).sum() d_target = diff / float(prediction.shape[0]) return loss, d_target

91ccacea12a46c62ccb5e7f6de891a37cb71e184

multi_task.py

Auto-format code with black (#10209) * Auto-format code with black * add black requirement to dev dependencies and pin to 22.x * ignore black dependency for comparison with setup.cfg Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com> Co-authored-by: svlandeg <svlandeg@github.com>

spaCy

spacy/ml/models/multi_task.py

Python

https://github.com/explosion/spaCy.git

test_k_fold_cv

def test_k_fold_cv(): boston = load_boston() clf = make_pipeline( OneHotEncoder( categorical_features='auto', sparse=False, minimum_fraction=0.05 ), LinearRegression() ) cross_val_score(clf, boston.data, boston.target, cv=KFold(n_splits=10, shuffle=True))

388616b6247ca4ea8de4e2f340d6206aee523541

one_hot_encoder_tests.py

Revert "Deployed 7ccda9a with MkDocs version: 1.3.0" This reverts commit bd9629c40e01241766197119b581a99409b07068.

tpot

tests/one_hot_encoder_tests.py

Python

https://github.com/EpistasisLab/tpot.git

_create_mock_app_session

def _create_mock_app_session(*args, **kwargs): mock_id = mock.PropertyMock( return_value="mock_id:%s" % ServerTestCase._next_session_id ) ServerTestCase._next_session_id += 1 mock_session = mock.MagicMock(AppSession, autospec=True, *args, **kwargs) type(mock_session).id = mock_id return mock_session

704eab3478cf69847825b23dabf15813a8ac9fa2

server_test_case.py

Rename and refactor `Report` machinery (#4141) This refactor renames (almost) everything related to the outdated "report" concept with more precise concepts that we use throughout our code, primarily "script run", "session", and "app".

streamlit

lib/tests/server_test_case.py

Python

https://github.com/streamlit/streamlit.git

_check_folder

def _check_folder(self) -> None: err = None if not self._faces_dir: err = "ERROR: Output faces folder not provided." elif not os.path.isdir(self._faces_dir): logger.debug("Creating folder: '%s'", self._faces_dir) os.makedirs(self._faces_dir) elif os.listdir(self._faces_dir): err = f"ERROR: Output faces folder should be empty: '{self._faces_dir}'" if err: logger.error(err) sys.exit(0) logger.verbose("Creating output folder at '%s'", self._faces_dir)

a9908b46f77dc66ac7efe7100ea0eed4b1f2b460

jobs.py

Alignments tool - Replace 'extract-large' with 'min-size'

faceswap

tools/alignments/jobs.py

Python

https://github.com/deepfakes/faceswap.git

stable_semver

def stable_semver(): from packaging.version import Version return Version(__version__).base_version

1d82b8822120db088bfeb6c8eae7ec8df9703783

version.py

Updated distutils.Version to packaging.Version

plotly.py

packages/python/plotly/plotly/version.py

Python

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

test_column_feature_type_mismatch_fill

def test_column_feature_type_mismatch_fill(): cat_feat = category_feature() bin_feat = binary_feature() input_features = [cat_feat] output_features = [bin_feat] config = {"input_features": input_features, "output_features": output_features} # Construct dataframe with int-like column representing a categorical feature df = pd.DataFrame( { cat_feat[NAME]: pd.Series(pd.array([None] + [1] * 24, dtype=pd.Int64Dtype())), bin_feat[NAME]: pd.Series([True] * 25), } ) # run preprocessing backend = LocalTestBackend() ludwig_model = LudwigModel(config, backend=backend) train_ds, val_ds, test_ds, _ = ludwig_model.preprocess(dataset=df) @pytest.mark.parametrize("format", ["file", "df"])

1e6dbeff57fc5065b97dd018b904b9907468676f

@pytest.mark.parametrize("format", ["file", "df"])

test_preprocessing.py

Treat dataset columns as object dtype during first pass of handle_missing_values (#2398)

ludwig

tests/integration_tests/test_preprocessing.py

Python

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

test_xsum_summarization_same_as_fairseq

def test_xsum_summarization_same_as_fairseq(self): model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-xsum").to(torch_device) tok = self.default_tokenizer PGE_ARTICLE = EXPECTED_SUMMARY = ( "California's largest power company has begun shutting off electricity to thousands of customers in the" " state." ) dct = tok.batch_encode_plus( [PGE_ARTICLE], max_length=1024, padding="max_length", truncation=True, return_tensors="pt", ).to(torch_device) hypotheses_batch = model.generate( input_ids=dct["input_ids"], attention_mask=dct["attention_mask"], num_beams=2, max_length=62, min_length=11, length_penalty=1.0, no_repeat_ngram_size=3, early_stopping=True, decoder_start_token_id=model.config.eos_token_id, ) decoded = tok.batch_decode( hypotheses_batch, skip_special_tokens=True, ) self.assertEqual(EXPECTED_SUMMARY, decoded[0])

afe5d42d8d1d80af911ed980c2936bfe887078f6

test_modeling_bart.py

Black preview (#17217) * Black preview * Fixup too! * Fix check copies * Use the same version as the CI * Bump black

transformers

tests/models/bart/test_modeling_bart.py

Python

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

test_get_nodes_for_order_with_uuid_id

def test_get_nodes_for_order_with_uuid_id(order_list): # given global_ids = [to_global_id("Order", order.pk) for order in order_list] # Make sure function works even if duplicated ids are provided global_ids.append(to_global_id("Order", order_list[0].pk)) # when orders = get_nodes(global_ids, Order) # then assert orders == order_list

41b87559118f560c223f83d405efe9b406701d17

test_graphql.py

Migrate order id from int to UUID (#9324) * Add migration to change order id from int to UUID (#9281) * Change order token to uuid * Migrate order id to uuid * Fix failing tests * Apply code review suggestions * Fix payment migration dependencies * Fix typo in order migration name * Handle old order ids for order queries * Hanlde old order ids for order mutations * Add order relation to GiftCardEvent model * Deprecate order token related queries and fields (#9295) * Deprecate order.token field * Update description of orderByToken query * Update prepare_order_search_document_value method * Update changelog * Update schema file

saleor

saleor/graphql/core/tests/test_graphql.py

Python

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

string_to_tokentype

def string_to_tokentype(s): if isinstance(s, _TokenType): return s if not s: return Token node = Token for item in s.split('.'): node = getattr(node, item) return node # Map standard token types to short names, used in CSS class naming. # If you add a new item, please be sure to run this file to perform # a consistency check for duplicate values. STANDARD_TYPES = { Token: '', Text: '', Whitespace: 'w', Escape: 'esc', Error: 'err', Other: 'x', Keyword: 'k', Keyword.Constant: 'kc', Keyword.Declaration: 'kd', Keyword.Namespace: 'kn', Keyword.Pseudo: 'kp', Keyword.Reserved: 'kr', Keyword.Type: 'kt', Name: 'n', Name.Attribute: 'na', Name.Builtin: 'nb', Name.Builtin.Pseudo: 'bp', Name.Class: 'nc', Name.Constant: 'no', Name.Decorator: 'nd', Name.Entity: 'ni', Name.Exception: 'ne', Name.Function: 'nf', Name.Function.Magic: 'fm', Name.Property: 'py', Name.Label: 'nl', Name.Namespace: 'nn', Name.Other: 'nx', Name.Tag: 'nt', Name.Variable: 'nv', Name.Variable.Class: 'vc', Name.Variable.Global: 'vg', Name.Variable.Instance: 'vi', Name.Variable.Magic: 'vm', Literal: 'l', Literal.Date: 'ld', String: 's', String.Affix: 'sa', String.Backtick: 'sb', String.Char: 'sc', String.Delimiter: 'dl', String.Doc: 'sd', String.Double: 's2', String.Escape: 'se', String.Heredoc: 'sh', String.Interpol: 'si', String.Other: 'sx', String.Regex: 'sr', String.Single: 's1', String.Symbol: 'ss', Number: 'm', Number.Bin: 'mb', Number.Float: 'mf', Number.Hex: 'mh', Number.Integer: 'mi', Number.Integer.Long: 'il', Number.Oct: 'mo', Operator: 'o', Operator.Word: 'ow', Punctuation: 'p', Comment: 'c', Comment.Hashbang: 'ch', Comment.Multiline: 'cm', Comment.Preproc: 'cp', Comment.PreprocFile: 'cpf', Comment.Single: 'c1', Comment.Special: 'cs', Generic: 'g', Generic.Deleted: 'gd', Generic.Emph: 'ge', Generic.Error: 'gr', Generic.Heading: 'gh', Generic.Inserted: 'gi', Generic.Output: 'go', Generic.Prompt: 'gp', Generic.Strong: 'gs', Generic.Subheading: 'gu', Generic.Traceback: 'gt', }

f3166e673fe8d40277b804d35d77dcdb760fc3b3

token.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/pygments/token.py

Python

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

get_emp_list

def get_emp_list(sal_struct, cond, end_date, payroll_payable_account): return frappe.db.sql( % cond, { "sal_struct": tuple(sal_struct), "from_date": end_date, "payroll_payable_account": payroll_payable_account, }, as_dict=True, )

494bd9ef78313436f0424b918f200dab8fc7c20b

payroll_entry.py

style: format code with black

erpnext

erpnext/payroll/doctype/payroll_entry/payroll_entry.py

Python

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

match_tree_files

def match_tree_files(self, root, on_error=None, follow_links=None): files = util.iter_tree_files(root, on_error=on_error, follow_links=follow_links) return self.match_files(files) # Alias `match_tree_files()` as `match_tree()`. match_tree = match_tree_files

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

pathspec.py

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

ray

python/ray/_private/thirdparty/pathspec/pathspec.py

Python

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

cycle

def cycle(parser, token): # Note: This returns the exact same node on each {% cycle name %} call; # that is, the node object returned from {% cycle a b c as name %} and the # one returned from {% cycle name %} are the exact same object. This # shouldn't cause problems (heh), but if it does, now you know. # # Ugly hack warning: This stuffs the named template dict into parser so # that names are only unique within each template (as opposed to using # a global variable, which would make cycle names have to be unique across # *all* templates. # # It keeps the last node in the parser to be able to reset it with # {% resetcycle %}. args = token.split_contents() if len(args) < 2: raise TemplateSyntaxError("'cycle' tag requires at least two arguments") if len(args) == 2: # {% cycle foo %} case. name = args[1] if not hasattr(parser, "_named_cycle_nodes"): raise TemplateSyntaxError( "No named cycles in template. '%s' is not defined" % name ) if name not in parser._named_cycle_nodes: raise TemplateSyntaxError("Named cycle '%s' does not exist" % name) return parser._named_cycle_nodes[name] as_form = False if len(args) > 4: # {% cycle ... as foo [silent] %} case. if args[-3] == "as": if args[-1] != "silent": raise TemplateSyntaxError( "Only 'silent' flag is allowed after cycle's name, not '%s'." % args[-1] ) as_form = True silent = True args = args[:-1] elif args[-2] == "as": as_form = True silent = False if as_form: name = args[-1] values = [parser.compile_filter(arg) for arg in args[1:-2]] node = CycleNode(values, name, silent=silent) if not hasattr(parser, "_named_cycle_nodes"): parser._named_cycle_nodes = {} parser._named_cycle_nodes[name] = node else: values = [parser.compile_filter(arg) for arg in args[1:]] node = CycleNode(values) parser._last_cycle_node = node return node @register.tag

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@register.tag

defaulttags.py

Refs #33476 -- Reformatted code with Black.

django

django/template/defaulttags.py

Python

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

cmpfiles

def cmpfiles(a, b, common, shallow=True): res = ([], [], []) for x in common: ax = os.path.join(a, x) bx = os.path.join(b, x) res[_cmp(ax, bx, shallow)].append(x) return res # Compare two files. # Return: # 0 for equal # 1 for different # 2 for funny cases (can't stat, etc.) #

8198943edd73a363c266633e1aa5b2a9e9c9f526

filecmp.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/filecmp.py

Python

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

_set_partitions

def _set_partitions(n): p = [0]*n q = [0]*n nc = 1 yield nc, q while nc != n: m = n while 1: m -= 1 i = q[m] if p[i] != 1: break q[m] = 0 i += 1 q[m] = i m += 1 nc += m - n p[0] += n - m if i == nc: p[nc] = 0 nc += 1 p[i - 1] -= 1 p[i] += 1 yield nc, q

f3b08522003f40868afb20304fc0fa5b16d13f6a

iterables.py

Cleanup documentation

sympy

sympy/utilities/iterables.py

Python

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

standard_b64decode

def standard_b64decode(s): return b64decode(s) _urlsafe_encode_translation = bytes.maketrans(b'+/', b'-_') _urlsafe_decode_translation = bytes.maketrans(b'-_', b'+/')

8198943edd73a363c266633e1aa5b2a9e9c9f526

base64.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/base64.py

Python

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

__repr__

def __repr__(self): if self._other is _SENTINEL: return "<ANY>" return repr(self._other) ANY = _HA_ANY()

3884e16b46f438e4a13bcab4fe0df3b2188de767

common.py

Add tests.common.ANY (#84240)

core

tests/common.py

Python

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

_set_execing_flag

def _set_execing_flag(self): if self._execing: raise RuntimeError("Nested set_execing_flag call") self._execing = True try: yield finally: self._execing = False

2a0ec52386e6d1594aa5cfe39bef2bfb89a59416

script_runner.py

Saner "execution control request" handling (#4383) ### Background Currently, a `ForwardMsg` enqueued from an `st.foo()` call results in a twisty path: 1. `st.foo()` retrieves the current `ScriptRunContext` and calls its `enqueue` function 1. `ScriptRunContext.enqueue` calls the `AppSession.enqueue` callback 2. `AppSession.enqueue` retrieves the current `ScriptRunner` and calls its `maybe_handle_execution_control_request` function 3. `ScriptRunner.maybe_handle_execution_control_request` optionally interrupts its own script's execution to respond to a STOP or RERUN request. (In other words, the message results in this call chain: ScriptRunContext -> AppSession -> ScriptRunner.) This is weird for a couple reasons: 1. `ScriptRunner.maybe_handle_execution_control_request` should be private. The circumstances in which it's legal to be called are very specific, and `AppSession.enqueue` currently has some ScriptRunner "business logic" inside it. 2. The call chain should really be ScriptRunContext -> ScriptRunner -> AppSession. (AppSession creates ScriptRunner which in turn creates ScriptRunContext. After creation, AppSession should ideally never have to communicate directly with its ScriptRunner - especially in a future where there may be multiple ScriptRunners attached to a single AppSession.) ### Resolution With this PR, `maybe_handle_execution_control_request` is a private method, and an enqueued `ForwardMsg` now "bubbles up" from ScriptRunContext -> ScriptRunner -> AppSession. AppSession no longer knows about execution control requests; they are handled internally by ScriptRunner. (The salient change is that ScriptRunner gets a new `_enqueue` function that is called by `ScriptRunContext.enqueue`, rather than `ScriptRunContext.enqueue` calling `AppSession.enqueue` directly. The execution control request handling happens inside this new `ScriptRunner.enqueue` function, which then calls up to `AppSession.enqueue`.)

streamlit

lib/streamlit/script_runner.py

Python

https://github.com/streamlit/streamlit.git

column_sql

def column_sql(self, model, field, include_default=False): # Get the column's type and use that as the basis of the SQL. db_params = field.db_parameters(connection=self.connection) column_db_type = db_params["type"] # Check for fields that aren't actually columns (e.g. M2M). if column_db_type is None: return None, None params = [] return ( " ".join( # This appends to the params being returned. self._iter_column_sql( column_db_type, params, model, field, include_default ) ), params, )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

schema.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/base/schema.py

Python

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

_set_output

def _set_output(self): now = datetime.now().strftime("%Y%m%d_%H%M%S") folder_name = f"drawn_landmarks_{now}" if self._frames.is_video: dest_folder = os.path.dirname(self._frames.folder) else: dest_folder = self._frames.folder output_folder = os.path.join(dest_folder, folder_name) logger.debug("Creating folder: '%s'", output_folder) os.makedirs(output_folder) return output_folder

a9908b46f77dc66ac7efe7100ea0eed4b1f2b460

jobs.py

Alignments tool - Replace 'extract-large' with 'min-size'

faceswap

tools/alignments/jobs.py

Python

https://github.com/deepfakes/faceswap.git

test_gymnasium_old_api_but_wrapped

def test_gymnasium_old_api_but_wrapped(self): from gymnasium.wrappers import EnvCompatibility register_env( "test", lambda env_ctx: EnvCompatibility(GymnasiumOldAPI(env_ctx)), ) algo = ( PPOConfig() .environment(env="test") .rollouts(num_envs_per_worker=2, num_rollout_workers=2) .build() ) algo.train() algo.stop()

8e680c483ce326cefc62e44f68ab1a6948b1c3d2

test_gym_env_apis.py

[RLlib] gymnasium support (new `Env.reset()/step()/seed()/render()` APIs). (#28369)

ray

rllib/tests/backward_compat/test_gym_env_apis.py

Python

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

test_stacking_classifier_base_regressor

def test_stacking_classifier_base_regressor(): X_train, X_test, y_train, y_test = train_test_split( scale(X_iris), y_iris, stratify=y_iris, random_state=42 ) clf = StackingClassifier(estimators=[("ridge", Ridge())]) clf.fit(X_train, y_train) clf.predict(X_test) clf.predict_proba(X_test) assert clf.score(X_test, y_test) > 0.8

b1807ff8ead319a08294beeaae90c3f03b2bb8ac

test_stacking.py

ENH StackingClassifier allows regressors in its first layer (#24538) Co-authored-by: Tom Dupré la Tour <tom.duprelatour.10@gmail.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

scikit-learn

sklearn/ensemble/tests/test_stacking.py

Python

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

error

def error(self, flow): if ( self.not_in_timeout(self.last_trigger, self.timeout) and flow.error is not None and not isinstance(flow.error, HttpSyntaxException) ): self.last_trigger = time.time() logger.error(f"Watchdog triggered! Cause: {flow}") self.error_event.set() # save the request which might have caused the problem if flow.request: with (self.flow_dir / f"{datetime.utcnow().isoformat()}.curl").open( "w" ) as f: f.write(curl_command(flow)) with (self.flow_dir / f"{datetime.utcnow().isoformat()}.raw").open( "wb" ) as f: f.write(raw(flow))

8c2428c9d355ca5fbc3dd90e9820ceb1cc795837

watchdog.py

[autofix.ci] apply automated fixes

mitmproxy

examples/contrib/webscanner_helper/watchdog.py

Python

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

device_class

def device_class(self) -> CoverDeviceClass: if isinstance(self.node, Awning): return CoverDeviceClass.AWNING if isinstance(self.node, Blind): return CoverDeviceClass.BLIND if isinstance(self.node, GarageDoor): return CoverDeviceClass.GARAGE if isinstance(self.node, Gate): return CoverDeviceClass.GATE if isinstance(self.node, RollerShutter): return CoverDeviceClass.SHUTTER if isinstance(self.node, Window): return CoverDeviceClass.WINDOW return CoverDeviceClass.WINDOW

10dc38e0ec27f7bef990ee431459342f9c3c52b4

cover.py

Adjust CoverEntity property type hints in components (#73943) * Adjust CoverEntity property type hints in components * Revert changes to rflink * Revert changes to wilight

core

homeassistant/components/velux/cover.py

Python

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

validate_syllables

def validate_syllables(self, syllable_list): valid_syllables = [] front = "" vowel_pattern = re.compile("|".join(self.vowels)) for i, syllable in enumerate(syllable_list): if syllable in punctuation: valid_syllables.append(syllable) continue if not vowel_pattern.search(syllable): if len(valid_syllables) == 0: front += syllable else: valid_syllables = valid_syllables[:-1] + [ valid_syllables[-1] + syllable ] else: if len(valid_syllables) == 0: valid_syllables.append(front + syllable) else: valid_syllables.append(syllable) return valid_syllables

ea006df9885bd1e5f439cd05359d047d83276b73

sonority_sequencing.py

Greatly improve SyllableTokenizer time performance on some edge cases Mainly when tokenizing numbers

nltk

nltk/tokenize/sonority_sequencing.py

Python

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

test_check_dataframe_with_only_boolean

def test_check_dataframe_with_only_boolean(): pd = importorskip("pandas", minversion="1.0") df = pd.DataFrame({"bool": pd.Series([True, False, True], dtype="boolean")}) array = check_array(df, dtype=None) assert array.dtype == np.float64 assert_array_equal(array, [[True], [False], [True]])

8d7935827d01d95239710c9c519bb1905f46b645

test_validation.py

ENH check_array returns numeric array w/ mixed typed dataframes (#22237) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

scikit-learn

sklearn/utils/tests/test_validation.py

Python

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

get_used_alternative_items

def get_used_alternative_items(purchase_order=None, work_order=None): cond = "" if purchase_order: cond = "and ste.purpose = 'Send to Subcontractor' and ste.purchase_order = '{0}'".format( purchase_order ) elif work_order: cond = "and ste.purpose = 'Material Transfer for Manufacture' and ste.work_order = '{0}'".format( work_order ) if not cond: return {} used_alternative_items = {} data = frappe.db.sql( .format( cond ), as_dict=1, ) for d in data: used_alternative_items[d.original_item] = d return used_alternative_items

494bd9ef78313436f0424b918f200dab8fc7c20b

stock_entry.py

style: format code with black

erpnext

erpnext/stock/doctype/stock_entry/stock_entry.py

Python

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

generate_schema

def generate_schema(route, viewset=None, view=None, view_function=None, patterns=None): from django.urls import path from drf_spectacular.generators import SchemaGenerator from rest_framework import routers from rest_framework.viewsets import ViewSetMixin if viewset: assert issubclass(viewset, ViewSetMixin) router = routers.SimpleRouter() router.register(route, viewset, basename=route) patterns = router.urls elif view: patterns = [path(route, view.as_view())] elif view_function: patterns = [path(route, view_function)] else: assert route is None and isinstance(patterns, list) generator = SchemaGenerator(patterns=patterns) schema = generator.get_schema(request=None, public=True) validate_schema(schema) # make sure generated schemas are always valid return schema

4319707cbd0d7783596fd4a4b7e707d55f97f629

__init__.py

feat(apidocs): Added the framework for schema tests (#38422) The functions shown, gives us a way to test any changes we make to SentrySchema

sentry

tests/sentry/apidocs/__init__.py

Python

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

mock_4x4x4_devices

def mock_4x4x4_devices(one_device_per_chip): return mock_devices(4, 4, 4, 'TPU v4', one_device_per_chip)

3f9e45e0c5b035de27b14588cd3b4cfd5f3c1f04

mesh_utils_test.py

[mesh_utils] Support creating device meshes for hybrid networks Also makes some NFCs to other mesh_utils code. PiperOrigin-RevId: 442581767

jax

tests/mesh_utils_test.py

Python

https://github.com/google/jax.git

categorize_changes

def categorize_changes(args, paths, verbose_command=None): # type: (TestConfig, t.List[str], t.Optional[str]) -> ChangeDescription mapper = PathMapper(args) commands = { 'sanity': set(), 'units': set(), 'integration': set(), 'windows-integration': set(), 'network-integration': set(), } # type: t.Dict[str, t.Set[str]] focused_commands = collections.defaultdict(set) deleted_paths = set() # type: t.Set[str] original_paths = set() # type: t.Set[str] additional_paths = set() # type: t.Set[str] no_integration_paths = set() # type: t.Set[str] for path in paths: if not os.path.exists(path): deleted_paths.add(path) continue original_paths.add(path) dependent_paths = mapper.get_dependent_paths(path) if not dependent_paths: continue display.info('Expanded "%s" to %d dependent file(s):' % (path, len(dependent_paths)), verbosity=2) for dependent_path in dependent_paths: display.info(dependent_path, verbosity=2) additional_paths.add(dependent_path) additional_paths -= set(paths) # don't count changed paths as additional paths if additional_paths: display.info('Expanded %d changed file(s) into %d additional dependent file(s).' % (len(paths), len(additional_paths))) paths = sorted(set(paths) | additional_paths) display.info('Mapping %d changed file(s) to tests.' % len(paths)) none_count = 0 for path in paths: tests = mapper.classify(path) if tests is None: focused_target = False display.info('%s -> all' % path, verbosity=1) tests = all_tests(args) # not categorized, run all tests display.warning('Path not categorized: %s' % path) else: focused_target = bool(tests.pop(FOCUSED_TARGET, None)) and path in original_paths tests = dict((key, value) for key, value in tests.items() if value) if focused_target and not any('integration' in command for command in tests): no_integration_paths.add(path) # path triggers no integration tests if verbose_command: result = '%s: %s' % (verbose_command, tests.get(verbose_command) or 'none') # identify targeted integration tests (those which only target a single integration command) if 'integration' in verbose_command and tests.get(verbose_command): if not any('integration' in command for command in tests if command != verbose_command): if focused_target: result += ' (focused)' result += ' (targeted)' else: result = '%s' % tests if not tests.get(verbose_command): # minimize excessive output from potentially thousands of files which do not trigger tests none_count += 1 verbosity = 2 else: verbosity = 1 if args.verbosity >= verbosity: display.info('%s -> %s' % (path, result), verbosity=1) for command, target in tests.items(): commands[command].add(target) if focused_target: focused_commands[command].add(target) if none_count > 0 and args.verbosity < 2: display.notice('Omitted %d file(s) that triggered no tests.' % none_count) for command, targets in commands.items(): targets.discard('none') if any(target == 'all' for target in targets): commands[command] = {'all'} sorted_commands = dict((c, sorted(targets)) for c, targets in commands.items() if targets) focused_commands = dict((c, sorted(targets)) for c, targets in focused_commands.items()) for command, targets in sorted_commands.items(): if targets == ['all']: sorted_commands[command] = [] # changes require testing all targets, do not filter targets changes = ChangeDescription() changes.command = verbose_command changes.changed_paths = sorted(original_paths) changes.deleted_paths = sorted(deleted_paths) changes.regular_command_targets = sorted_commands changes.focused_command_targets = focused_commands changes.no_integration_paths = sorted(no_integration_paths) return changes

a06fa496d3f837cca3c437ab6e9858525633d147

__init__.py

ansible-test - Code cleanup and refactoring. (#77169) * Remove unnecessary PyCharm ignores. * Ignore intentional undefined attribute usage. * Add missing type hints. Fix existing type hints. * Fix docstrings and comments. * Use function to register completion handler. * Pass strings to display functions. * Fix CompositeAction handling of dest argument. * Use consistent types in expressions/assignments. * Use custom function to keep linters happy. * Add missing raise for custom exception. * Clean up key/value type handling in cloud plugins. * Use dataclass instead of dict for results. * Add custom type_guard function to check lists. * Ignore return type that can't be checked (yet). * Avoid changing types on local variables.

ansible

test/lib/ansible_test/_internal/classification/__init__.py

Python

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

test_grouped_annotation_in_group_by

def test_grouped_annotation_in_group_by(self): qs = ( Book.objects.annotate(xprice=F("price")) .filter(rating=4.0) .values("rating", "xprice") .annotate(count=Count("publisher_id", distinct=True)) .values("count", "rating") .order_by("count") ) self.assertEqual( list(qs), [ {"rating": 4.0, "count": 1}, {"rating": 4.0, "count": 2}, ], )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/aggregation/tests.py

Python

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

get_admin_log

def get_admin_log(parser, token): tokens = token.contents.split() if len(tokens) < 4: raise template.TemplateSyntaxError( "'get_admin_log' statements require two arguments" ) if not tokens[1].isdigit(): raise template.TemplateSyntaxError( "First argument to 'get_admin_log' must be an integer" ) if tokens[2] != "as": raise template.TemplateSyntaxError( "Second argument to 'get_admin_log' must be 'as'" ) if len(tokens) > 4: if tokens[4] != "for_user": raise template.TemplateSyntaxError( "Fourth argument to 'get_admin_log' must be 'for_user'" ) return AdminLogNode( limit=tokens[1], varname=tokens[3], user=(tokens[5] if len(tokens) > 5 else None), )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

log.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/templatetags/log.py

Python

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

binned

def binned(self) -> List[List[str]]: if not self._binned: self._binned = self._binning() logger.debug({f"bin_{idx}": len(bin_) for idx, bin_ in enumerate(self._binned)}) return self._binned

98d01760e469fd2108eed8d0b0a1ba6297c3177c

sort_methods.py

Overhaul sort: - Standardize image data reading and writing - Optimize loading (just one pass required) - Make all sort groups binnable (to greater or lesser results) - Add sort by pitch - Deprecate multiple options - linting, docs + locales

faceswap

tools/sort/sort_methods.py

Python

https://github.com/deepfakes/faceswap.git

_make_estimator

def _make_estimator(self, append=True, random_state=None): estimator = clone(self.base_estimator_) estimator.set_params(**{p: getattr(self, p) for p in self.estimator_params}) # TODO: Remove in v1.2 # criterion "mse" and "mae" would cause warnings in every call to # DecisionTreeRegressor.fit(..) if isinstance(estimator, (DecisionTreeRegressor, ExtraTreeRegressor)): if getattr(estimator, "criterion", None) == "mse": estimator.set_params(criterion="squared_error") elif getattr(estimator, "criterion", None) == "mae": estimator.set_params(criterion="absolute_error") # TODO(1.3): Remove # max_features = 'auto' would cause warnings in every call to # Tree.fit(..) if isinstance(estimator, BaseDecisionTree): if getattr(estimator, "max_features", None) == "auto": if isinstance(estimator, DecisionTreeClassifier): estimator.set_params(max_features="sqrt") elif isinstance(estimator, DecisionTreeRegressor): estimator.set_params(max_features=1.0) if random_state is not None: _set_random_states(estimator, random_state) if append: self.estimators_.append(estimator) return estimator

e5736afb316038c43301d2c53ce39f9a89b64495

_base.py

API Deprecate max_feature=`auto` for tree classes (#22476) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>

scikit-learn

sklearn/ensemble/_base.py

Python

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

lattice_reference

def lattice_reference(G, niter=5, D=None, connectivity=True, seed=None): import numpy as np from networkx.utils import cumulative_distribution, discrete_sequence local_conn = nx.connectivity.local_edge_connectivity if len(G) < 4: raise nx.NetworkXError("Graph has less than four nodes.") # Instead of choosing uniformly at random from a generated edge list, # this algorithm chooses nonuniformly from the set of nodes with # probability weighted by degree. G = G.copy() keys, degrees = zip(*G.degree()) # keys, degree cdf = cumulative_distribution(degrees) # cdf of degree nnodes = len(G) nedges = nx.number_of_edges(G) if D is None: D = np.zeros((nnodes, nnodes)) un = np.arange(1, nnodes) um = np.arange(nnodes - 1, 0, -1) u = np.append((0,), np.where(un < um, un, um)) for v in range(int(np.ceil(nnodes / 2))): D[nnodes - v - 1, :] = np.append(u[v + 1 :], u[: v + 1]) D[v, :] = D[nnodes - v - 1, :][::-1] niter = niter * nedges # maximal number of rewiring attempts per 'niter' max_attempts = int(nnodes * nedges / (nnodes * (nnodes - 1) / 2)) for _ in range(niter): n = 0 while n < max_attempts: # pick two random edges without creating edge list # choose source node indices from discrete distribution (ai, ci) = discrete_sequence(2, cdistribution=cdf, seed=seed) if ai == ci: continue # same source, skip a = keys[ai] # convert index to label c = keys[ci] # choose target uniformly from neighbors b = seed.choice(list(G.neighbors(a))) d = seed.choice(list(G.neighbors(c))) bi = keys.index(b) di = keys.index(d) if b in [a, c, d] or d in [a, b, c]: continue # all vertices should be different # don't create parallel edges if (d not in G[a]) and (b not in G[c]): if D[ai, bi] + D[ci, di] >= D[ai, ci] + D[bi, di]: # only swap if we get closer to the diagonal G.add_edge(a, d) G.add_edge(c, b) G.remove_edge(a, b) G.remove_edge(c, d) # Check if the graph is still connected if connectivity and local_conn(G, a, b) == 0: # Not connected, revert the swap G.remove_edge(a, d) G.remove_edge(c, b) G.add_edge(a, b) G.add_edge(c, d) else: break n += 1 return G @py_random_state(3) @not_implemented_for("directed") @not_implemented_for("multigraph")

bd56814a8e9c988fc3d12801315226f249af1419

@py_random_state(3) @not_implemented_for("directed") @not_implemented_for("multigraph")

smallworld.py

Keep omega within [-1, 1] bounds (#5216) * Adjusted calculation of small-world metric omega to be within the correct bounds * Update docstring to reflect that there is no hard bound on omega * add release note * maint: rm print statements from tests. * Update release file per comment Co-authored-by: Dan Schult <dschult@colgate.edu> Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>

networkx

networkx/algorithms/smallworld.py

Python

https://github.com/networkx/networkx.git

transpose_output

def transpose_output(self, X): X = X.reshape(-1, self.num_heads, X.shape[1], X.shape[2]) X = X.transpose(0, 2, 1, 3) return X.reshape(X.shape[0], X.shape[1], -1)

f0be7e672bc0a7c77005d5c79452d796cfe1a06b

mxnet.py

Refactor Multihead Attn, Self Attn, and Transformer (#2096) * multihead attn * self attn and pos encoding * simplify * before EncoderBlock * before tmencoder * before decoder block * before training * transformer code * rm seq2seq encoder old * fix bahdanau attn map * transformer done, perf tuned * clean super

d2l-en

d2l/mxnet.py

Python

https://github.com/d2l-ai/d2l-en.git

test_decoder_model_past_with_large_inputs

def test_decoder_model_past_with_large_inputs(self): config_and_inputs = self.model_tester.prepare_config_and_inputs_for_decoder() self.model_tester.create_and_check_decoder_model_past_large_inputs(*config_and_inputs)

8635407bc724c45142c1f91dbc9ef3ea681e1a56

test_modeling_tf_{{cookiecutter.lowercase_modelname}}.py

Fix tf.concatenate + test past_key_values for TF models (#15774) * fix wrong method name tf.concatenate * add tests related to causal LM / decoder * make style and quality * clean-up * Fix TFBertModel's extended_attention_mask when past_key_values is provided * Fix tests * fix copies * More tf.int8 -> tf.int32 in TF test template * clean-up * Update TF test template * revert the previous commit + update the TF test template * Fix TF template extended_attention_mask when past_key_values is provided * Fix some styles manually * clean-up * Fix ValueError: too many values to unpack in the test * Fix more: too many values to unpack in the test * Add a comment for extended_attention_mask when there is past_key_values * Fix TFElectra extended_attention_mask when past_key_values is provided * Add tests to other TF models * Fix for TF Electra test: add prepare_config_and_inputs_for_decoder * Fix not passing training arg to lm_head in TFRobertaForCausalLM * Fix tests (with past) for TF Roberta * add testing for pask_key_values for TFElectra model Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

transformers

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/test_modeling_tf_{{cookiecutter.lowercase_modelname}}.py

Python

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

get_dependencies_from_index

def get_dependencies_from_index(dep, sources=None, pip_options=None, wheel_cache=None): session, finder = get_finder(sources=sources, pip_options=pip_options) dep.is_direct = True requirements = None setup_requires = {} with temp_environ(), ExitStack() as stack: if not wheel_cache: wheel_cache = stack.enter_context(_get_wheel_cache()) os.environ["PIP_EXISTS_ACTION"] = "i" if dep.editable and not dep.prepared and not dep.req: setup_info = SetupInfo.from_ireq(dep) results = setup_info.get_info() setup_requires.update(results["setup_requires"]) requirements = set(results["requires"].values()) else: results = shims.resolve(dep) requirements = [v for v in results.values() if v.name != dep.name] requirements = set([format_requirement(r) for r in requirements]) if not dep.editable and is_pinned_requirement(dep) and requirements is not None: DEPENDENCY_CACHE[dep] = list(requirements) return requirements

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

dependencies.py

Rename notpip to pip. Vendor in pip-22.2.1 and latest requirementslib and vistir.

pipenv

pipenv/vendor/requirementslib/models/dependencies.py

Python

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

_get_sourcefile

def _get_sourcefile(bytecode_path): if len(bytecode_path) == 0: return None rest, _, extension = bytecode_path.rpartition('.') if not rest or extension.lower()[-3:-1] != 'py': return bytecode_path try: source_path = source_from_cache(bytecode_path) except (NotImplementedError, ValueError): source_path = bytecode_path[:-1] return source_path if _path_isfile(source_path) else bytecode_path

8198943edd73a363c266633e1aa5b2a9e9c9f526

_bootstrap_external.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/importlib/_bootstrap_external.py

Python

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

reset_display_options

def reset_display_options() -> None: pd.reset_option("^display.", silent=True) # ----------------------------------------------------------------------------- # Comparators

f538568afc2c76c2d738d32e3544cf9fe6742960

__init__.py

TYP: misc return type annotations (#47558)

pandas

pandas/_testing/__init__.py

Python

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

test_edit_save_as_delete_inline

def test_edit_save_as_delete_inline(self): post_data = self.inline_post_data.copy() post_data.update( { "_saveasnew": "Save+as+new", "article_set-1-section": "1", "article_set-2-section": "1", "article_set-2-DELETE": "1", "article_set-3-section": "1", } ) response = self.client.post( reverse("admin:admin_views_section_change", args=(self.s1.pk,)), post_data ) self.assertEqual(response.status_code, 302) # started with 3 articles, one was deleted. self.assertEqual(Section.objects.latest("id").article_set.count(), 2)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

_compute_fans

def _compute_fans(shape): if len(shape) < 1: # Just to avoid errors for constants. fan_in = fan_out = 1 elif len(shape) == 1: fan_in = fan_out = shape[0] elif len(shape) == 2: fan_in = shape[0] fan_out = shape[1] else: # Assuming convolution kernels (2D, 3D, or more). # kernel shape: (..., input_depth, depth) receptive_field_size = 1 for dim in shape[:-2]: receptive_field_size *= dim fan_in = shape[-2] * receptive_field_size fan_out = shape[-1] * receptive_field_size return int(fan_in), int(fan_out) @test_combinations.generate(test_combinations.combine(mode=["graph", "eager"]))

84afc5193d38057e2e2badf9c889ea87d80d8fbf

@test_combinations.generate(test_combinations.combine(mode=["graph", "eager"]))

initializers_test.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/initializers/initializers_test.py

Python

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

sparse_categorical_matches

def sparse_categorical_matches(y_true, y_pred): reshape_matches = False y_pred = tf.convert_to_tensor(y_pred) y_true = tf.convert_to_tensor(y_true) y_true_org_shape = tf.shape(y_true) y_pred_rank = y_pred.shape.ndims y_true_rank = y_true.shape.ndims # If the shape of y_true is (num_samples, 1), squeeze to (num_samples,) if ( (y_true_rank is not None) and (y_pred_rank is not None) and (len(backend.int_shape(y_true)) == len(backend.int_shape(y_pred))) ): y_true = tf.squeeze(y_true, [-1]) reshape_matches = True y_pred = tf.math.argmax(y_pred, axis=-1) # If the predicted output and actual output types don't match, force cast them # to match. if backend.dtype(y_pred) != backend.dtype(y_true): y_pred = tf.cast(y_pred, backend.dtype(y_true)) matches = tf.cast(tf.equal(y_true, y_pred), backend.floatx()) if reshape_matches: matches = tf.reshape(matches, shape=y_true_org_shape) return matches

84afc5193d38057e2e2badf9c889ea87d80d8fbf

metrics_utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/utils/metrics_utils.py

Python

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

query_yes_no

def query_yes_no(question, default="yes"): valid = {"yes": "yes", "y": "yes", "ye": "yes", "no": "no", "n": "no"} prompt = {None: " [y/n] ", "yes": " [Y/n] ", "no": " [y/N] "}.get(default, None) if not prompt: raise ValueError("invalid default answer: '%s'" % default) reply = None while not reply: sys.stdout.write(colorize(question, Colors.PROMPT) + prompt) choice = input().lower() reply = None if default and not choice: reply = default elif choice in valid: reply = valid[choice] else: print_failure("Please respond with 'yes' or 'no' (or 'y' or 'n').\n") return reply == "yes"

7bf15bf33644ef13e34dff63beaf8d19387219be

updateHostsFile.py

Use https in more places

hosts

updateHostsFile.py

Python

https://github.com/StevenBlack/hosts.git

wait_start_success

def wait_start_success(self) -> None: if not self.args.noblock_on_start: raise ValueError( f'{self.wait_start_success!r} should only be called when `noblock_on_start` is set to True' ) try: if self.uses_before_pea is not None: self.uses_before_pea.wait_start_success() if self.uses_after_pea is not None: self.uses_after_pea.wait_start_success() if self.head_pea is not None: self.head_pea.wait_start_success() for shard_id in self.shards: self.shards[shard_id].wait_start_success() self.activate() except: self.close() raise

933415bfa1f9eb89f935037014dfed816eb9815d

__init__.py

feat: star routing (#3900) * feat(proto): adjust proto for star routing (#3844) * feat(proto): adjust proto for star routing * feat(proto): generate proto files * feat(grpc): refactor grpclet interface (#3846) * feat: refactor connection pool for star routing (#3872) * feat(k8s): add more labels to k8s deployments * feat(network): refactor connection pool * feat(network): refactor k8s pool * feat: star routing graph gateway (#3877) * feat: star routing - refactor grpc data runtime (#3887) * feat(runtimes): refactor grpc dataruntime * fix(tests): adapt worker runtime tests * fix(import): fix import * feat(proto): enable sending multiple lists (#3891) * feat: star routing gateway (#3893) * feat: star routing gateway all protocols (#3897) * test: add streaming and prefetch tests (#3901) * feat(head): new head runtime for star routing (#3899) * feat(head): new head runtime * feat(head): new head runtime * style: fix overload and cli autocomplete * feat(network): improve proto comments Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(worker): merge docs in worker runtime (#3905) * feat(worker): merge docs in worker runtime * feat(tests): assert after clean up * feat(tests): star routing runtime integration tests (#3908) * fix(tests): fix integration tests * test: test runtimes fast slow request (#3910) * feat(zmq): purge zmq, zed, routing_table (#3915) * feat(zmq): purge zmq, zed, routing_table * style: fix overload and cli autocomplete * feat(zmq): adapt comment in dependency list * style: fix overload and cli autocomplete * fix(tests): fix type tests Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * test: add test gateway to worker connection (#3921) * feat(pea): adapt peas for star routing (#3918) * feat(pea): adapt peas for star routing * style: fix overload and cli autocomplete * feat(pea): add tests * feat(tests): add failing head pea test Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(tests): integration tests for peas (#3923) * feat(tests): integration tests for peas * feat(pea): remove _inner_pea function * feat: star routing container pea (#3922) * test: rescue tests (#3942) * fix: fix streaming tests (#3945) * refactor: move docker run to run (#3948) * feat: star routing pods (#3940) * feat(pod): adapt pods for star routing * feat(pods): adapt basepod to star routing * feat(pod): merge pod and compound pod * feat(tests): fix tests * style: fix overload and cli autocomplete * feat(test): add container pea int test * feat(ci): remove more unnecessary tests * fix(tests): remove jinad runtime * feat(ci): remove latency tracking * fix(ci): fix ci def * fix(runtime): enable runtime to be exited * fix(tests): wrap runtime test in process * fix(runtimes): remove unused runtimes * feat(runtimes): improve cancel wait * fix(ci): build test pip again in ci * fix(tests): fix a test * fix(test): run async in its own process * feat(pod): include shard in activate msg * fix(pea): dont join * feat(pod): more debug out * feat(grpc): manage channels properly * feat(pods): remove exitfifo * feat(network): add simple send retry mechanism * fix(network): await pool close * fix(test): always close grpc server in worker * fix(tests): remove container pea from tests * fix(tests): reorder tests * fix(ci): split tests * fix(ci): allow alias setting * fix(test): skip a test * feat(pods): address comments Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * test: unblock skipped test (#3957) * feat: jinad pea (#3949) * feat: jinad pea * feat: jinad pea * test: remote peas * test: toplogy tests with jinad * ci: parallel jobs * feat(tests): add pod integration tests (#3958) * feat(tests): add pod integration tests * fix(tests): make tests less flaky * fix(test): fix test * test(pea): remote pea topologies (#3961) * test(pea): remote pea simple topology * test: remote pea topologies * refactor: refactor streamer result handling (#3960) * feat(k8s): adapt K8s Pod for StarRouting (#3964) * test: optimize k8s test * test: increase timeout and use different namespace * test: optimize k8s test * test: build and load image when needed * test: refactor k8s test * test: fix image name error * test: fix k8s image load * test: fix typoe port expose * test: update tests in connection pool and handling * test: remove unused fixture * test: parameterize docker images * test: parameterize docker images * test: parameterize docker images * feat(k8s): adapt k8s pod for star routing * fix(k8s): dont overwrite add/remove function in pool * fix(k8s): some fixes * fix(k8s): some more fixes * fix(k8s): linting * fix(tests): fix tests * fix(tests): fix k8s unit tests * feat(k8s): complete k8s integration test * feat(k8s): finish k8s tests * feat(k8s): fix test * fix(tests): fix test with no name * feat(k8s): unify create/replace interface * feat(k8s): extract k8s port constants * fix(tests): fix tests * fix(tests): wait for runtime being ready in tests * feat(k8s): address comments Co-authored-by: bwanglzu <bo.wang@jina.ai> * feat(flow): adapt Flow for StarRouting (#3986) * feat(flow): add routes * feat(flow): adapt flow to star routing * style: fix overload and cli autocomplete * feat(flow): handle empty topologies * feat(k8s): allow k8s pool disabling * style: fix overload and cli autocomplete * fix(test): fix test with mock * fix(tests): fix more tests * feat(flow): clean up tests * style: fix overload and cli autocomplete * fix(tests): fix more tests * feat: add plot function (#3994) * fix(tests): avoid hanging tests * feat(flow): add type hinting * fix(test): fix duplicate exec name in test * fix(tests): fix more tests * fix(tests): enable jinad test again * fix(tests): random port fixture * fix(style): replace quotes Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * feat(ci): bring back ci (#3997) * feat(ci): enable ci again * style: fix overload and cli autocomplete * feat(ci): add latency tracking * feat(ci): bring back some tests * fix(tests): remove invalid port test * feat(ci): disable daemon and distributed tests * fix(tests): fix entrypoint in hub test * fix(tests): wait for gateway to be ready * fix(test): fix more tests * feat(flow): do rolling update and scale sequentially * fix(tests): fix more tests * style: fix overload and cli autocomplete * feat: star routing hanging pods (#4011) * fix: try to handle hanging pods better * test: hanging pods test work * fix: fix topology graph problem * test: add unit test to graph * fix(tests): fix k8s tests * fix(test): fix k8s test * fix(test): fix k8s pool test * fix(test): fix k8s test * fix(test): fix k8s connection pool setting * fix(tests): make runtime test more reliable * fix(test): fix routes test * fix(tests): make rolling update test less flaky * feat(network): gurantee unique ports * feat(network): do round robin for shards * fix(ci): increase pytest timeout to 10 min Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix(ci): fix ci file * feat(daemon): jinad pod for star routing * Revert "feat(daemon): jinad pod for star routing" This reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92. * feat(daemon): remote jinad pod support (#4042) * feat(daemon): add pod tests for star routing * feat(daemon): add remote pod test * test(daemon): add remote pod arguments test * test(daemon): add async scale test * test(daemon): add rolling update test * test(daemon): fix host * feat(proto): remove message proto (#4051) * feat(proto): remove message proto * fix(tests): fix tests * fix(tests): fix some more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * feat(proto): put docs back in data * fix(proto): clean up * feat(proto): clean up * fix(tests): skip latency tracking * fix(test): fix hub test * fix(tests): fix k8s test * fix(test): some test clean up * fix(style): clean up style issues * feat(proto): adjust for rebase * fix(tests): bring back latency tracking * fix(tests): fix merge accident * feat(proto): skip request serialization (#4074) * feat: add reduce to star routing (#4070) * feat: add reduce on shards to head runtime * test: add reduce integration tests with fixed order * feat: add reduce on needs * chore: get_docs_matrix_from_request becomes public * style: fix overload and cli autocomplete * docs: remove undeterministic results warning * fix: fix uses_after * test: assert correct num docs after reducing in test_external_pod * test: correct asserts after reduce in test_rolling_update * fix: no reduce if uses_after_address is set * fix: get_docs_from_request only if needed * fix: fix tests after merge * refactor: move reduce from data_request_handler to head * style: fix overload and cli autocomplete * chore: apply suggestions * fix: fix asserts * chore: minor test fix * chore: apply suggestions * test: remove flow tests with external executor (pea) * fix: fix test_expected_messages_routing * fix: fix test_func_joiner * test: adapt k8s test Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * fix(k8s): fix static pool config * fix: use custom protoc doc generator image (#4088) * fix: use custom protoc doc generator image * fix(docs): minor doc improvement * fix(docs): use custom image * fix(docs): copy docarray * fix: doc building local only * fix: timeout doc building * fix: use updated args when building ContainerPea * test: add container PeaFactory test * fix: force pea close on windows (#4098) * fix: dont reduce if uses exist (#4099) * fix: dont use reduce if uses exist * fix: adjust reduce tests * fix: adjust more reduce tests * fix: fix more tests * fix: adjust more tests * fix: ignore non jina resources (#4101) * feat(executor): enable async executors (#4102) * feat(daemon): daemon flow on star routing (#4096) * test(daemon): add remote flow test * feat(daemon): call scale in daemon * feat(daemon): remove tail args and identity * test(daemon): rename scalable executor * test(daemon): add a small delay in async test * feat(daemon): scale partial flow only * feat(daemon): call scale directly in partial flow store * test(daemon): use asyncio sleep * feat(daemon): enable flow level distributed tests * test(daemon): fix jinad env workspace config * test(daemon): fix pod test use new port rolling update * feat(daemon): enable distribuetd tests * test(daemon): remove duplicate tests and zed runtime test * test(daemon): fix stores unit test * feat(daemon): enable part of distributed tests * feat(daemon): enable part of distributed tests * test: correct test paths * test(daemon): add client test for remote flows * test(daemon): send a request with jina client * test(daemon): assert async generator * test(daemon): small interval between tests * test(daemon): add flow test for container runtime * test(daemon): add flow test for container runtime * test(daemon): fix executor name * test(daemon): fix executor name * test(daemon): use async client fetch result * test(daemon): finish container flow test * test(daemon): enable distributed in ci * test(daemon): enable distributed in ci * test(daemon): decare flows and pods * test(daemon): debug ci if else * test(daemon): debug ci if else * test(daemon): decare flows and pods * test(daemon): correct test paths * test(daemon): add small delay for async tests * fix: star routing fixes (#4100) * docs: update docs * fix: fix Request.__repr__ * docs: update flow remarks * docs: fix typo * test: add non_empty_fields test * chore: remove non_empty_fields test * feat: polling per endpoint (#4111) * feat(polling): polling per endpoint configurable * fix: adjust tests * feat(polling): extend documentation * style: fix overload and cli autocomplete * fix: clean up * fix: adjust more tests * fix: remove repeat from flaky test * fix: k8s test * feat(polling): address pr feedback * feat: improve docs Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(grpc): support connect grpc server via ssl tunnel (#4092) * feat(grpc): support ssl grpc connect if port is 443 * fix(grpc): use https option instead of detect port automatically * chore: fix typo * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * test(networking): add test for peapods networking * fix: address comments Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * feat(polling): unify polling args (#4113) * fix: several issues for jinad pods (#4119) * fix: activate for jinad pods * fix: dont expose worker pod in partial daemon * fix: workspace setting * fix: containerized flows * fix: hub test * feat(daemon): remote peas on star routing (#4112) * test(daemon): fix request in peas * test(daemon): fix request in peas * test(daemon): fix sync async client test * test(daemon): enable remote peas test * test(daemon): replace send message to send request * test(daemon): declare pea tests in ci * test(daemon): use pea args fixture * test(daemon): head pea use default host * test(daemon): fix peas topologies * test(daemon): fix pseudo naming * test(daemon): use default host as host * test(daemon): fix executor path * test(daemon): add remote worker back * test(daemon): skip local remote remote topology * fix: jinad pea test setup * fix: jinad pea tests * fix: remove invalid assertion Co-authored-by: jacobowitz <tobias.jacobowitz@posteo.de> * feat: enable daemon tests again (#4132) * feat: enable daemon tests again * fix: remove bogy empty script file * fix: more jinad test fixes * style: fix overload and cli autocomplete * fix: scale and ru in jinad * fix: fix more jinad tests Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * fix: fix flow test * fix: improve pea tests reliability (#4136) Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai> Co-authored-by: bwanglzu <bo.wang@jina.ai> Co-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr> Co-authored-by: Zhaofeng Miao <522856232@qq.com>

jina

jina/peapods/pods/__init__.py

Python

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

nD

def nD(i=None, brute=None, *, n=None, m=None): from sympy.integrals.integrals import integrate from sympy.functions.special.polynomials import laguerre from sympy.abc import x

e0dc14eca132f37c5f49369eb4051eae37c9b119

numbers.py

Refactored import ordering in functions

sympy

sympy/functions/combinatorial/numbers.py

Python

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

test_tf_non_distributed

def test_tf_non_distributed(ray_start_4_cpus): trainer = TorchTrainer( tf_quick_start_train_func, scaling_config=dict(num_workers=1) ) trainer.fit() # TODO: Refactor as a backend test.

b9a4f64f32389a1f76a7f74103b4d5da089ebb2b

test_examples.py

[AIR/train] Use new Train API (#25735) Uses the new AIR Train API for examples and tests. The `Result` object gets a new attribute - `log_dir`, pointing to the Trial's `logdir` allowing users to access tensorboard logs and artifacts of other loggers. This PR only deals with "low hanging fruit" - tests that need substantial rewriting or Train user guide are not touched. Those will be updated in followup PRs. Tests and examples that concern deprecated features or which are duplicated in AIR have been removed or disabled. Requires https://github.com/ray-project/ray/pull/25943 to be merged in first

ray

python/ray/train/tests/test_examples.py

Python

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

load_accelerator_state

def load_accelerator_state(input_dir, models, optimizers, process_index, scaler=None): # Model states for i, model in enumerate(models): weights_name = f"{MODEL_NAME}.bin" if i == 0 else f"{MODEL_NAME}_{i}.bin" input_model_file = os.path.join(input_dir, weights_name) models[i].load_state_dict(torch.load(input_model_file)) logger.info("All model weights loaded successfully") # Optimizer states for i, opt in enumerate(optimizers): optimizer_name = f"{OPTIMIZER_NAME}.bin" if i == 0 else f"{OPTIMIZER_NAME}_{i}.bin" input_optimizer_file = os.path.join(input_dir, optimizer_name) optimizers[i].load_state_dict(torch.load(input_optimizer_file)) logger.info("All optimizer states loaded successfully") # GradScaler state if scaler is not None: input_scaler_file = os.path.join(input_dir, SCALER_NAME) scaler.load_state_dict(torch.load(input_scaler_file)) logger.info("GradScaler state loaded successfully") # Random states states = torch.load(os.path.join(input_dir, f"{RNG_STATE_NAME}_{process_index}.pkl")) random.setstate(states["random_state"]) np.random.set_state(states["numpy_random_seed"]) torch.set_rng_state(states["torch_manual_seed"]) torch.cuda.set_rng_state_all(states["torch_cuda_manual_seed"]) # ^^ safe to call this function even if cuda is not available if is_tpu_available(): xm.set_rng_state(states["xm_seed"]) logger.info("All random states loaded successfully")

fb5ed62c102c0323486b89805e1888495de3db15

checkpointing.py

Convert documentation to the new front (#271) * Main conversion * Doc styling * Style * New front deploy * Fixes * Fixes * Fix new docstrings * Style

accelerate

src/accelerate/checkpointing.py

Python

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

__call__

def __call__(self, results): if random.random() < self.shift_ratio: img_shape = results['img'].shape[:2] random_shift_x = random.randint(-self.max_shift_px, self.max_shift_px) random_shift_y = random.randint(-self.max_shift_px, self.max_shift_px) new_x = max(0, random_shift_x) ori_x = max(0, -random_shift_x) new_y = max(0, random_shift_y) ori_y = max(0, -random_shift_y) # TODO: support mask and semantic segmentation maps. for key in results.get('bbox_fields', []): bboxes = results[key].copy() bboxes[..., 0::2] += random_shift_x bboxes[..., 1::2] += random_shift_y # clip border bboxes[..., 0::2] = np.clip(bboxes[..., 0::2], 0, img_shape[1]) bboxes[..., 1::2] = np.clip(bboxes[..., 1::2], 0, img_shape[0]) # remove invalid bboxes bbox_w = bboxes[..., 2] - bboxes[..., 0] bbox_h = bboxes[..., 3] - bboxes[..., 1] valid_inds = (bbox_w > self.filter_thr_px) & ( bbox_h > self.filter_thr_px) # If the shift does not contain any gt-bbox area, skip this # image. if key == 'gt_bboxes' and not valid_inds.any(): return results bboxes = bboxes[valid_inds] results[key] = bboxes # label fields. e.g. gt_labels and gt_labels_ignore label_key = self.bbox2label.get(key) if label_key in results: results[label_key] = results[label_key][valid_inds] for key in results.get('img_fields', ['img']): img = results[key] new_img = np.zeros_like(img) img_h, img_w = img.shape[:2] new_h = img_h - np.abs(random_shift_y) new_w = img_w - np.abs(random_shift_x) new_img[new_y:new_y + new_h, new_x:new_x + new_w] \ = img[ori_y:ori_y + new_h, ori_x:ori_x + new_w] results[key] = new_img return results

86037650f243a1ab0a515a22e831ea5dcddd6a7d

transforms.py

Unified name of orig as ori (#7456)

mmdetection

mmdet/datasets/pipelines/transforms.py

Python

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

svd

def svd(a, full_matrices=True, compute_uv=True, hermitian=False): import numpy as _nx a, wrap = _makearray(a) if hermitian: # note: lapack svd returns eigenvalues with s ** 2 sorted descending, # but eig returns s sorted ascending, so we re-order the eigenvalues # and related arrays to have the correct order if compute_uv: s, u = eigh(a) sgn = sign(s) s = abs(s) sidx = argsort(s)[..., ::-1] sgn = _nx.take_along_axis(sgn, sidx, axis=-1) s = _nx.take_along_axis(s, sidx, axis=-1) u = _nx.take_along_axis(u, sidx[..., None, :], axis=-1) # singular values are unsigned, move the sign into v vt = transpose(u * sgn[..., None, :]).conjugate() return wrap(u), s, wrap(vt) else: s = eigvalsh(a) s = s[..., ::-1] s = abs(s) return sort(s)[..., ::-1] _assert_stacked_2d(a) t, result_t = _commonType(a) extobj = get_linalg_error_extobj(_raise_linalgerror_svd_nonconvergence) m, n = a.shape[-2:] if compute_uv: if full_matrices: if m < n: gufunc = _umath_linalg.svd_m_f else: gufunc = _umath_linalg.svd_n_f else: if m < n: gufunc = _umath_linalg.svd_m_s else: gufunc = _umath_linalg.svd_n_s signature = 'D->DdD' if isComplexType(t) else 'd->ddd' u, s, vh = gufunc(a, signature=signature, extobj=extobj) u = u.astype(result_t, copy=False) s = s.astype(_realType(result_t), copy=False) vh = vh.astype(result_t, copy=False) return wrap(u), s, wrap(vh) else: if m < n: gufunc = _umath_linalg.svd_m else: gufunc = _umath_linalg.svd_n signature = 'D->d' if isComplexType(t) else 'd->d' s = gufunc(a, signature=signature, extobj=extobj) s = s.astype(_realType(result_t), copy=False) return s

40747ae50620631941e43dbbd5baaccab669922f

linalg.py

clarify svd documentation `u @ np.diag(s) @ vh` can only reproduce the original matrix when `full_matrices` is `False`, otherwise dimension does not match.

numpy

numpy/linalg/linalg.py

Python

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

test_create_placeholder_if_not_exist_in_template

def test_create_placeholder_if_not_exist_in_template(self): page = create_page('Test', 'col_two.html', 'en') # I need to make it seem like the user added another placeholder to the SAME template. page._template_cache = 'col_three.html' request = self.get_request(page=page) context = SekizaiContext() context['request'] = request self.assertObjectDoesNotExist(page.placeholders.all(), slot='col_right') context = self.get_context(page=page) renderer = self.get_content_renderer(request) renderer.render_page_placeholder( 'col_right', context, inherit=False, page=page, ) self.assertObjectExist(page.placeholders.all(), slot='col_right')

c1290c9ff89cb00caa5469129fd527e9d82cd820

test_templatetags.py

ci: Added codespell (#7355) Co-authored-by: Christian Clauss <cclauss@me.com> * ci: codespell config taken from #7292

django-cms

cms/tests/test_templatetags.py

Python

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

extra_state_attributes

def extra_state_attributes(self) -> dict[str, int | float | None] | None: # Only add attributes to the original sensor if self.entity_description.key != "days_until_expiration": return None if self.coordinator.data is None: return None attrs = { ATTR_EXPIRES: self.coordinator.data.expiration_date.isoformat(), } if self.coordinator.data.name_servers: attrs[ATTR_NAME_SERVERS] = " ".join(self.coordinator.data.name_servers) if self.coordinator.data.last_updated: attrs[ATTR_UPDATED] = self.coordinator.data.last_updated.isoformat() if self.coordinator.data.registrar: attrs[ATTR_REGISTRAR] = self.coordinator.data.registrar return attrs

d15d081646c26d32f860d8f84b4f29d848dab148

sensor.py

Add data update coordinator to Whois (#64846) Co-authored-by: Joakim Sørensen <joasoe@gmail.com>

core

homeassistant/components/whois/sensor.py

Python

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

populate_deserializable_objects

def populate_deserializable_objects(): global LOCAL if not hasattr(LOCAL, 'ALL_OBJECTS'): LOCAL.ALL_OBJECTS = {} LOCAL.GENERATED_WITH_V2 = None if LOCAL.ALL_OBJECTS and LOCAL.GENERATED_WITH_V2 == tf.__internal__.tf2.enabled( ): # Objects dict is already generated for the proper TF version: # do nothing. return LOCAL.ALL_OBJECTS = {} LOCAL.GENERATED_WITH_V2 = tf.__internal__.tf2.enabled() base_cls = base_layer.Layer generic_utils.populate_dict_with_module_objects( LOCAL.ALL_OBJECTS, ALL_MODULES, obj_filter=lambda x: inspect.isclass(x) and issubclass(x, base_cls)) # Overwrite certain V1 objects with V2 versions if tf.__internal__.tf2.enabled(): generic_utils.populate_dict_with_module_objects( LOCAL.ALL_OBJECTS, ALL_V2_MODULES, obj_filter=lambda x: inspect.isclass(x) and issubclass(x, base_cls)) # These deserialization aliases are added for backward compatibility, # as in TF 1.13, "BatchNormalizationV1" and "BatchNormalizationV2" # were used as class name for v1 and v2 version of BatchNormalization, # respectively. Here we explicitly convert them to their canonical names. LOCAL.ALL_OBJECTS[ 'BatchNormalizationV1'] = batch_normalization_v1.BatchNormalization LOCAL.ALL_OBJECTS[ 'BatchNormalizationV2'] = batch_normalization.BatchNormalization # Prevent circular dependencies. from keras import models # pylint: disable=g-import-not-at-top from keras.premade.linear import LinearModel # pylint: disable=g-import-not-at-top from keras.premade.wide_deep import WideDeepModel # pylint: disable=g-import-not-at-top from keras.feature_column.sequence_feature_column import SequenceFeatures # pylint: disable=g-import-not-at-top LOCAL.ALL_OBJECTS['Input'] = input_layer.Input LOCAL.ALL_OBJECTS['InputSpec'] = input_spec.InputSpec LOCAL.ALL_OBJECTS['Functional'] = models.Functional LOCAL.ALL_OBJECTS['Model'] = models.Model LOCAL.ALL_OBJECTS['SequenceFeatures'] = SequenceFeatures LOCAL.ALL_OBJECTS['Sequential'] = models.Sequential LOCAL.ALL_OBJECTS['LinearModel'] = LinearModel LOCAL.ALL_OBJECTS['WideDeepModel'] = WideDeepModel if tf.__internal__.tf2.enabled(): from keras.feature_column.dense_features_v2 import DenseFeatures # pylint: disable=g-import-not-at-top LOCAL.ALL_OBJECTS['DenseFeatures'] = DenseFeatures else: from keras.feature_column.dense_features import DenseFeatures # pylint: disable=g-import-not-at-top LOCAL.ALL_OBJECTS['DenseFeatures'] = DenseFeatures # Merging layers, function versions. LOCAL.ALL_OBJECTS['add'] = merging.add LOCAL.ALL_OBJECTS['subtract'] = merging.subtract LOCAL.ALL_OBJECTS['multiply'] = merging.multiply LOCAL.ALL_OBJECTS['average'] = merging.average LOCAL.ALL_OBJECTS['maximum'] = merging.maximum LOCAL.ALL_OBJECTS['minimum'] = merging.minimum LOCAL.ALL_OBJECTS['concatenate'] = merging.concatenate LOCAL.ALL_OBJECTS['dot'] = merging.dot @keras_export('keras.layers.serialize')

85ccb4e108551b7444213276ffb4c4c09f22f886

@keras_export('keras.layers.serialize')

serialization.py

Refactor `merge.py` into smaller logically organized files hosted under a `merging` directory. PiperOrigin-RevId: 424162837

keras

keras/layers/serialization.py

Python

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

get_ordering

def get_ordering(self): ordering = self.get_validated_ordering() return [values[0] + name for name, values in ordering.items()]

d10f15e55806c6944827d801cd9c2d53f5da4186

views.py

Reformat with black

wagtail

wagtail/contrib/forms/views.py

Python

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

test_metrics_folder

def test_metrics_folder(): with _ray_start(include_dashboard=True) as context: session_dir = context["session_dir"] assert os.path.exists( f"{session_dir}/metrics/grafana/provisioning/dashboards/default.yml" ) assert os.path.exists( f"{session_dir}/metrics/grafana/provisioning/dashboards" "/default_grafana_dashboard.json" ) assert os.path.exists( f"{session_dir}/metrics/grafana/provisioning/datasources/default.yml" ) assert os.path.exists(f"{session_dir}/metrics/prometheus/prometheus.yml")

42da4445e7a3cb358a1a02ae433a004e9fa836b5

test_metrics_head.py

Export default configurations for grafana and prometheus (#28286)

ray

python/ray/tests/test_metrics_head.py

Python

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

logical_or

def logical_or(self, other, context=None): if context is None: context = getcontext() other = _convert_other(other, raiseit=True) if not self._islogical() or not other._islogical(): return context._raise_error(InvalidOperation) # fill to context.prec (opa, opb) = self._fill_logical(context, self._int, other._int) # make the operation, and clean starting zeroes result = "".join([str(int(a)|int(b)) for a,b in zip(opa,opb)]) return _dec_from_triple(0, result.lstrip('0') or '0', 0)

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

parse_header

def parse_header(line): parts = _parseparam(';' + line) key = parts.__next__() pdict = {} for p in parts: i = p.find('=') if i >= 0: name = p[:i].strip().lower() value = p[i+1:].strip() if len(value) >= 2 and value[0] == value[-1] == '"': value = value[1:-1] value = value.replace('\\\\', '\\').replace('\\"', '"') pdict[name] = value return key, pdict # Classes for field storage # =========================

8198943edd73a363c266633e1aa5b2a9e9c9f526

cgi.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/cgi.py

Python

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

test_unmovable_translation_pages

def test_unmovable_translation_pages(self): self.login() # BlogIndex needs translated pages before child pages can be translated self.fr_blog_index = self.en_blog_index.copy_for_translation(self.fr_locale) self.de_blog_index = self.en_blog_index.copy_for_translation(self.de_locale) # Create blog_post copies for translation self.fr_blog_post = self.en_blog_post.copy_for_translation(self.fr_locale) self.de_blog_post = self.en_blog_post.copy_for_translation(self.de_locale) # Confirm location of English blog post page before it is moved # Should be living at /blog/blog-post/ right now. But will eventually # exist at /blog-post/ self.assertEqual(self.en_blog_post.get_parent().id, self.en_blog_index.id) # Confirm the fr and de blog post pages are under the blog index page # We'll confirm these have not moved after ther POST request. original_translated_parent_ids = [ p.id for p in self.en_blog_index.get_translations() ] self.assertIn(self.fr_blog_post.get_parent().id, original_translated_parent_ids) self.assertIn(self.de_blog_post.get_parent().id, original_translated_parent_ids) response = self.client.post( reverse( "wagtailadmin_pages:move_confirm", args=( self.en_blog_post.id, self.en_homepage.id, ), ), follow=True, ) self.assertEqual(response.status_code, 200) self.en_blog_post.refresh_from_db() self.fr_blog_post.refresh_from_db() self.de_blog_post.refresh_from_db() # Check that the en_blog_post page has moved directly under the home page. self.assertEqual( self.en_blog_post.get_parent(update=True).id, self.en_homepage.id ) # Check if the fr and de pages exist under their original parent page (/blog/) self.assertIn( self.fr_blog_post.get_parent(update=True).id, original_translated_parent_ids ) self.assertIn( self.de_blog_post.get_parent(update=True).id, original_translated_parent_ids )

4cc10322a1c86c1137f5042a13d94d8017498bf7

test_wagtail_hooks.py

Sync tree: cascade unpublish, move and delete (#7984) * Add construct_synced_page_tree_list hook and use in page unpublish view * Implement construct_synced_page_tree_list in simple_translation but only when sync page tree is enabled * Add hook documentation * Add construct_synced_page_tree_list hook tests (#8058) * Move translated and alias pages when WAGTAIL_I18N_ENABLED and WAGTAILSIMPLETRANSLATION_SYNC_PAGE_TREE are enabled Co-Authored-By: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com> * Delete corresponding translations when WAGTAIL_I18N_ENABLED and WAGTAILSIMPLETRANSLATION_SYNC_PAGE_TREE are true Co-Authored-By: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com> * Rename the hook to be more specific * Update singular string version in confirm_move.html * Update test test_translation_count_in_context Co-authored-by: Kalob Taulien <4743971+KalobTaulien@users.noreply.github.com> Co-authored-by: Karl Hobley <karl@kaed.uk>

wagtail

wagtail/contrib/simple_translation/tests/test_wagtail_hooks.py

Python

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

canberra_distance

def canberra_distance(self, p): s, p = Point._normalize_dimension(self, Point(p)) if self.is_zero and p.is_zero: raise ValueError("Cannot project to the zero vector.") return Add(*((abs(a - b)/(abs(a) + abs(b))) for a, b in zip(s, p)))

498015021131af4dbb07eb110e5badaba8250c7b

point.py

Updated import locations

sympy

sympy/geometry/point.py

Python

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

test_sac_compilation

def test_sac_compilation(self): config = sac.DEFAULT_CONFIG.copy() config["Q_model"] = sac.DEFAULT_CONFIG["Q_model"].copy() config["num_workers"] = 0 # Run locally. config["n_step"] = 3 config["twin_q"] = True config["learning_starts"] = 0 config["prioritized_replay"] = True config["rollout_fragment_length"] = 10 config["train_batch_size"] = 10 # If we use default buffer size (1e6), the buffer will take up # 169.445 GB memory, which is beyond travis-ci's current (Mar 19, 2021) # available system memory (8.34816 GB). config["buffer_size"] = 40000 # Test with saved replay buffer. config["store_buffer_in_checkpoints"] = True num_iterations = 1 ModelCatalog.register_custom_model("batch_norm", KerasBatchNormModel) ModelCatalog.register_custom_model("batch_norm_torch", TorchBatchNormModel) image_space = Box(-1.0, 1.0, shape=(84, 84, 3)) simple_space = Box(-1.0, 1.0, shape=(3,)) tune.register_env( "random_dict_env", lambda _: RandomEnv( { "observation_space": Dict( { "a": simple_space, "b": Discrete(2), "c": image_space, } ), "action_space": Box(-1.0, 1.0, shape=(1,)), } ), ) tune.register_env( "random_tuple_env", lambda _: RandomEnv( { "observation_space": Tuple( [simple_space, Discrete(2), image_space] ), "action_space": Box(-1.0, 1.0, shape=(1,)), } ), ) for fw in framework_iterator(config, with_eager_tracing=True): # Test for different env types (discrete w/ and w/o image, + cont). for env in [ "random_dict_env", "random_tuple_env", # "MsPacmanNoFrameskip-v4", "CartPole-v0", ]: print("Env={}".format(env)) # Test making the Q-model a custom one for CartPole, otherwise, # use the default model. config["Q_model"]["custom_model"] = ( "batch_norm{}".format("_torch" if fw == "torch" else "") if env == "CartPole-v0" else None ) trainer = sac.SACTrainer(config=config, env=env) for i in range(num_iterations): results = trainer.train() check_train_results(results) print(results) check_compute_single_action(trainer) # Test, whether the replay buffer is saved along with # a checkpoint (no point in doing it for all frameworks since # this is framework agnostic). if fw == "tf" and env == "CartPole-v0": checkpoint = trainer.save() new_trainer = sac.SACTrainer(config, env=env) new_trainer.restore(checkpoint) # Get some data from the buffer and compare. data = trainer.local_replay_buffer.replay_buffers[ "default_policy" ]._storage[: 42 + 42] new_data = new_trainer.local_replay_buffer.replay_buffers[ "default_policy" ]._storage[: 42 + 42] check(data, new_data) new_trainer.stop() trainer.stop()

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

test_sac.py

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