Datasets:

semeru

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

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Semeru Lab 7

get_batch_no

def get_batch_no(doctype, txt, searchfield, start, page_len, filters): doctype = "Batch" cond = "" if filters.get("posting_date"): cond = "and (batch.expiry_date is null or batch.expiry_date >= %(posting_date)s)" batch_nos = None args = { "item_code": filters.get("item_code"), "warehouse": filters.get("warehouse"), "posting_date": filters.get("posting_date"), "txt": "%{0}%".format(txt), "start": start, "page_len": page_len, } having_clause = "having sum(sle.actual_qty) > 0" if filters.get("is_return"): having_clause = "" meta = frappe.get_meta(doctype, cached=True) searchfields = meta.get_search_fields() search_columns = "" search_cond = "" if searchfields: search_columns = ", " + ", ".join(searchfields) search_cond = " or " + " or ".join([field + " like %(txt)s" for field in searchfields]) if args.get("warehouse"): searchfields = ["batch." + field for field in searchfields] if searchfields: search_columns = ", " + ", ".join(searchfields) search_cond = " or " + " or ".join([field + " like %(txt)s" for field in searchfields]) batch_nos = frappe.db.sql( .format( search_columns=search_columns, cond=cond, match_conditions=get_match_cond(doctype), having_clause=having_clause, search_cond=search_cond, ), args, ) return batch_nos else: return frappe.db.sql( .format( cond, search_columns=search_columns, search_cond=search_cond, match_conditions=get_match_cond(doctype), ), args, ) @frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

9baa2229761c5415f29646a1a5bed4a3f4981e05

@frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

queries.py

fix: specify allowed doctype in queries (#31761)

erpnext

erpnext/controllers/queries.py

Python

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

allow_serial_nos_with_different_item

def allow_serial_nos_with_different_item(sle_serial_no, sle): allow_serial_nos = False if sle.voucher_type == "Stock Entry" and cint(sle.actual_qty) > 0: stock_entry = frappe.get_cached_doc("Stock Entry", sle.voucher_no) if stock_entry.purpose in ("Repack", "Manufacture"): for d in stock_entry.get("items"): if d.serial_no and (d.s_warehouse if not sle.is_cancelled else d.t_warehouse): serial_nos = get_serial_nos(d.serial_no) if sle_serial_no in serial_nos: allow_serial_nos = True return allow_serial_nos

494bd9ef78313436f0424b918f200dab8fc7c20b

serial_no.py

style: format code with black

erpnext

erpnext/stock/doctype/serial_no/serial_no.py

Python

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

find_latest_deps_file

def find_latest_deps_file(build_data_working, ansible_version): # imports here so that they don't cause unnecessary deps for all of the plugins from packaging.version import Version data_dir = os.path.join(build_data_working, ansible_version) deps_files = glob.glob(os.path.join(data_dir, '*.deps')) if not deps_files: raise Exception('No deps files exist for version {0}'.format(ansible_version)) # Find the latest version of the deps file for this major version latest = None latest_ver = Version('0') for filename in deps_files: deps_data = parse_deps_file(filename) new_version = Version(deps_data['_ansible_version']) if new_version > latest_ver: latest_ver = new_version latest = filename if latest is None: raise NoSuchFile('Could not find an ansible deps file in {0}'.format(data_dir)) return latest # # Subcommand core #

9545f2e0deae73d142047f02b499940b07b700aa

docs_build.py

stable docs build: do not use YAML parsing/serialization for .deps files (#79233) * Do not use YAML parsing/serialization for .deps files. * Prevent crash.

ansible

hacking/build_library/build_ansible/command_plugins/docs_build.py

Python

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

move_tone_curve

def move_tone_curve(img, low_y, high_y): input_dtype = img.dtype if low_y < 0 or low_y > 1: raise ValueError("low_shift must be in range [0, 1]") if high_y < 0 or high_y > 1: raise ValueError("high_shift must be in range [0, 1]") if input_dtype != np.uint8: raise ValueError("Unsupported image type {}".format(input_dtype)) t = np.linspace(0.0, 1.0, 256) # Defines responze of a four-point bezier curve

43201769f044e2f1bcd594a6e5c251903cf14c49

functional.py

Upgrade black to 22.3.0 (#1181) * Upgrade black to 22.3.0 * Remove sphinx docs build

albumentations

albumentations/augmentations/functional.py

Python

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

apply_str

def apply_str(self) -> DataFrame | Series: # Caller is responsible for checking isinstance(self.f, str) f = cast(str, self.f) obj = self.obj # Support for `frame.transform('method')` # Some methods (shift, etc.) require the axis argument, others # don't, so inspect and insert if necessary. func = getattr(obj, f, None) if callable(func): sig = inspect.getfullargspec(func) if self.axis != 0 and ( "axis" not in sig.args or f in ("corrwith", "mad", "skew") ): raise ValueError(f"Operation {f} does not support axis=1") elif "axis" in sig.args: self.kwargs["axis"] = self.axis return self._try_aggregate_string_function(obj, f, *self.args, **self.kwargs)

d1485e76b7c48316c0d54f1a4df26c4467792670

apply.py

CLN: Refactor groupby._make_wrapper (#48400) * CLN: Refactor groupby._make_wrapper * Remove type: ignore * Revert behavior change for corrwith; fix skew and mad * Add docstring

pandas

pandas/core/apply.py

Python

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

completed_annotations

def completed_annotations(self): if self.project.skip_queue == self.project.SkipQueue.IGNORE_SKIPPED: return self.annotations.filter(Q(ground_truth=False)) else: return self.annotations.filter(Q_finished_annotations)

074af782e6f351c711f18d8ad6a05aa4f632339c

models.py

feat: DEV-469: Skip queue (#1693) * DEV-469 Skip queue project setting * DEV-469 review fixes * Merge migrations (DEV-469) * Update requirements-test.txt * Update requirements-test.txt * Update test_exception.py * Revert "Update test_exception.py" This reverts commit b9c686c9bacaf298bafe3a207352cc5260fef737. * Revert "Update requirements-test.txt" This reverts commit 3704d29978761089bcd008506f9e1c30a162bb3a. * Revert "Update requirements-test.txt" This reverts commit 50273847ae2872b31bccc376d04a3afff0efcf21. * Recalc is_labeled after skip_queue change (DEV-469) * Fix migrations (DEV-469) Co-authored-by: Max Tkachenko <[email protected]> Co-authored-by: niklub <[email protected]> Co-authored-by: nik <[email protected]>

label-studio

label_studio/tasks/models.py

Python

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

test_get_result_correctness

async def test_get_result_correctness(graph1): (_, _, _, dag) = graph1 handle = serve.run(DAGDriver.bind(dag)) visualizer = GraphVisualizer() visualizer.visualize_with_gradio(handle, _launch=False) await visualizer._send_request(random.randint(0, 100), 1, 2) values = await asyncio.gather( *[ (visualizer._get_result(node.get_stable_uuid())) for node in visualizer.node_to_block ] ) assert {1, 2} <= set(values) @pytest.mark.asyncio

4c970cc88247f7cfa7351297b8b5050f2372742e

@pytest.mark.asyncio

test_gradio_visualization.py

[serve] Visualize Deployment Graph with Gradio (#27897)

ray

python/ray/serve/tests/test_gradio_visualization.py

Python

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

test_get_backfill_points_in_room

def test_get_backfill_points_in_room(self): setup_info = self._setup_room_for_backfill_tests() room_id = setup_info.room_id backfill_points = self.get_success( self.store.get_backfill_points_in_room(room_id) ) backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points] self.assertListEqual( backfill_event_ids, ["b6", "b5", "b4", "2", "b3", "b2", "b1"] )

ac1a31740b6d0dfda4d57a25762aaddfde981caf

test_event_federation.py

Only try to backfill event if we haven't tried before recently (#13635) Only try to backfill event if we haven't tried before recently (exponential backoff). No need to keep trying the same backfill point that fails over and over. Fix https://github.com/matrix-org/synapse/issues/13622 Fix https://github.com/matrix-org/synapse/issues/8451 Follow-up to https://github.com/matrix-org/synapse/pull/13589 Part of https://github.com/matrix-org/synapse/issues/13356

synapse

tests/storage/test_event_federation.py

Python

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

_mixup_transform

def _mixup_transform(self, results): assert 'mix_results' in results assert len( results['mix_results']) == 1, 'MixUp only support 2 images now !' if results['mix_results'][0]['gt_bboxes'].shape[0] == 0: # empty bbox return results retrieve_results = results['mix_results'][0] retrieve_img = retrieve_results['img'] jit_factor = random.uniform(*self.ratio_range) is_filp = random.uniform(0, 1) > self.flip_ratio if len(retrieve_img.shape) == 3: out_img = np.ones( (self.dynamic_scale[0], self.dynamic_scale[1], 3), dtype=retrieve_img.dtype) * self.pad_val else: out_img = np.ones( self.dynamic_scale, dtype=retrieve_img.dtype) * self.pad_val # 1. keep_ratio resize scale_ratio = min(self.dynamic_scale[0] / retrieve_img.shape[0], self.dynamic_scale[1] / retrieve_img.shape[1]) retrieve_img = mmcv.imresize( retrieve_img, (int(retrieve_img.shape[1] * scale_ratio), int(retrieve_img.shape[0] * scale_ratio))) # 2. paste out_img[:retrieve_img.shape[0], :retrieve_img.shape[1]] = retrieve_img # 3. scale jit scale_ratio *= jit_factor out_img = mmcv.imresize(out_img, (int(out_img.shape[1] * jit_factor), int(out_img.shape[0] * jit_factor))) # 4. flip if is_filp: out_img = out_img[:, ::-1, :] # 5. random crop ori_img = results['img'] origin_h, origin_w = out_img.shape[:2] target_h, target_w = ori_img.shape[:2] padded_img = np.zeros( (max(origin_h, target_h), max(origin_w, target_w), 3)).astype(np.uint8) padded_img[:origin_h, :origin_w] = out_img x_offset, y_offset = 0, 0 if padded_img.shape[0] > target_h: y_offset = random.randint(0, padded_img.shape[0] - target_h) if padded_img.shape[1] > target_w: x_offset = random.randint(0, padded_img.shape[1] - target_w) padded_cropped_img = padded_img[y_offset:y_offset + target_h, x_offset:x_offset + target_w] # 6. adjust bbox retrieve_gt_bboxes = retrieve_results['gt_bboxes'] retrieve_gt_bboxes[:, 0::2] = retrieve_gt_bboxes[:, 0::2] * scale_ratio retrieve_gt_bboxes[:, 1::2] = retrieve_gt_bboxes[:, 1::2] * scale_ratio if self.bbox_clip_border: retrieve_gt_bboxes[:, 0::2] = np.clip(retrieve_gt_bboxes[:, 0::2], 0, origin_w) retrieve_gt_bboxes[:, 1::2] = np.clip(retrieve_gt_bboxes[:, 1::2], 0, origin_h) if is_filp: retrieve_gt_bboxes[:, 0::2] = ( origin_w - retrieve_gt_bboxes[:, 0::2][:, ::-1]) # 7. filter cp_retrieve_gt_bboxes = retrieve_gt_bboxes.copy() cp_retrieve_gt_bboxes[:, 0::2] = \ cp_retrieve_gt_bboxes[:, 0::2] - x_offset cp_retrieve_gt_bboxes[:, 1::2] = \ cp_retrieve_gt_bboxes[:, 1::2] - y_offset if self.bbox_clip_border: cp_retrieve_gt_bboxes[:, 0::2] = np.clip( cp_retrieve_gt_bboxes[:, 0::2], 0, target_w) cp_retrieve_gt_bboxes[:, 1::2] = np.clip( cp_retrieve_gt_bboxes[:, 1::2], 0, target_h) # 8. mix up ori_img = ori_img.astype(np.float32) mixup_img = 0.5 * ori_img + 0.5 * padded_cropped_img.astype(np.float32) retrieve_gt_labels = retrieve_results['gt_labels'] if not self.skip_filter: keep_list = self._filter_box_candidates(retrieve_gt_bboxes.T, cp_retrieve_gt_bboxes.T) retrieve_gt_labels = retrieve_gt_labels[keep_list] cp_retrieve_gt_bboxes = cp_retrieve_gt_bboxes[keep_list] mixup_gt_bboxes = np.concatenate( (results['gt_bboxes'], cp_retrieve_gt_bboxes), axis=0) mixup_gt_labels = np.concatenate( (results['gt_labels'], retrieve_gt_labels), axis=0) # remove outside bbox inside_inds = find_inside_bboxes(mixup_gt_bboxes, target_h, target_w) mixup_gt_bboxes = mixup_gt_bboxes[inside_inds] mixup_gt_labels = mixup_gt_labels[inside_inds] results['img'] = mixup_img.astype(np.uint8) results['img_shape'] = mixup_img.shape results['gt_bboxes'] = mixup_gt_bboxes results['gt_labels'] = mixup_gt_labels return results

c9e1906f00505621b0247ab364feb0ca862fa98c

transforms.py

[Fix] Fix MixUp transform filter boxes failing case. Added test case (#7080)

mmdetection

mmdet/datasets/pipelines/transforms.py

Python

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

authenticate

def authenticate(self, _=None): # TODO: remove unused var acceptance_wait_time = self.opts["acceptance_wait_time"] acceptance_wait_time_max = self.opts["acceptance_wait_time_max"] if not acceptance_wait_time_max: acceptance_wait_time_max = acceptance_wait_time with salt.channel.client.ReqChannel.factory( self.opts, crypt="clear" ) as channel: while True: creds = self.sign_in(channel=channel) if creds == "retry": if self.opts.get("caller"): # We have a list of masters, so we should break # and try the next one in the list. if self.opts.get("local_masters", None): error = SaltClientError( "Minion failed to authenticate" " with the master, has the " "minion key been accepted?" ) break else: print( "Minion failed to authenticate with the master, " "has the minion key been accepted?" ) sys.exit(2) if acceptance_wait_time: log.info( "Waiting %s seconds before retry.", acceptance_wait_time ) time.sleep(acceptance_wait_time) if acceptance_wait_time < acceptance_wait_time_max: acceptance_wait_time += acceptance_wait_time log.debug( "Authentication wait time is %s", acceptance_wait_time ) continue break self._creds = creds self._crypticle = Crypticle(self.opts, creds["aes"])

70972c8016ff5d6fbdd7f83776077b0936f60dea

crypt.py

Use salt.channel.client instead of salt.transport.client

salt

salt/crypt.py

Python

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

test_not_collapsed_with_legacy

def test_not_collapsed_with_legacy(self): # Sidebar should not be collapsed because the feature flag is not enabled self.client.cookies['wagtail_sidebar_collapsed'] = '1' response = self.client.get(reverse('wagtailadmin_home')) self.assertNotContains(response, 'sidebar-collapsed')

18c4d7c81356dbd5c4503db2ea24b21492512317

test_menu.py

Update Wagtail test cases to match slim sidebar capabilities and implementation details

wagtail

wagtail/admin/tests/test_menu.py

Python

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

default

def default(method): method._is_default = True # pylint: disable=protected-access return method

84afc5193d38057e2e2badf9c889ea87d80d8fbf

generic_utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/utils/generic_utils.py

Python

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

tokenize_wrapper

def tokenize_wrapper(input): skip = {token.NEWLINE, token.INDENT, token.DEDENT} tokens = tokenize.generate_tokens(io.StringIO(input).readline) for quintuple in tokens: type, value, start, end, line_text = quintuple if type not in skip: yield quintuple

8198943edd73a363c266633e1aa5b2a9e9c9f526

patcomp.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/lib2to3/patcomp.py

Python

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

test_get_serials

def test_get_serials(): expected = [ "180720d39cd2db3244ba037417241e90", "1768ac4e5b72bf1d0df0df118b34b959", ] mock = MagicMock( return_value=( "CertInfo\r\n" "================ Certificate 0 ================\r\n" "Serial Number: 180720d39cd2db3244ba037417241e90\r\n" "OtherStuff\r\n" "\r\n" "================ Certificate 1 ================\r\n" "Serial Number: 1768ac4e5b72bf1d0df0df118b34b959\r\n" "OtherStuff" ) ) with patch.dict(certutil.__salt__, {"cmd.run": mock}): out = certutil.get_stored_cert_serials("TrustedPublisher") mock.assert_called_once_with('certutil.exe -store "TrustedPublisher"') assert expected == out

a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857

test_win_certutil.py

Add tests, fix state module

salt

tests/pytests/unit/modules/test_win_certutil.py

Python

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

build_partition

def build_partition(cls, partition_ids, column_widths): return np.array( [ [ cls.frame_partition_cls( part_id[0], length=part_id[2], width=col_width, ) for part_id, col_width in zip(part_ids, column_widths) ] for part_ids in partition_ids ] )

8864bc197974da6d8cda2de2f35ca31d561be1cc

parquet_dispatcher.py

PERF-#4305: Parallelize `read_parquet` over row groups (#4700) Co-authored-by: mvashishtha <[email protected]>

modin

modin/core/io/column_stores/parquet_dispatcher.py

Python

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

__new__

def __new__(cls, stylename, **kwargs): # The "class" should have the _style_list attribute, which is a mapping # of style names to style classes. _list = stylename.replace(" ", "").split(",") _name = _list[0].lower() try: _cls = cls._style_list[_name] except KeyError as err: raise ValueError(f"Unknown style: {stylename}") from err try: _args_pair = [cs.split("=") for cs in _list[1:]] _args = {k: float(v) for k, v in _args_pair} except ValueError as err: raise ValueError(f"Incorrect style argument: {stylename}") from err return _cls(**{**_args, **kwargs})

075ff0952896f44d7d0b0b3318f0978ae53f84d7

patches.py

Small style fixes.

matplotlib

lib/matplotlib/patches.py

Python

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

get_roi_rel_points_train

def get_roi_rel_points_train(self, mask_pred, labels, cfg): point_coords = get_uncertain_point_coords_with_randomness( mask_pred, labels, cfg.num_points, cfg.oversample_ratio, cfg.importance_sample_ratio) return point_coords

c576e5d570bf64a99e2c6817ed7b5c0084a44a55

mask_point_head.py

[Enhance] Take point sample related functions out of mask_point_head (#7353) add point sample replace function in mask_point_head

mmdetection

mmdet/models/roi_heads/mask_heads/mask_point_head.py

Python

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

tempdir_registry

def tempdir_registry() -> Iterator[TempDirectoryTypeRegistry]: global _tempdir_registry old_tempdir_registry = _tempdir_registry _tempdir_registry = TempDirectoryTypeRegistry() try: yield _tempdir_registry finally: _tempdir_registry = old_tempdir_registry

f3166e673fe8d40277b804d35d77dcdb760fc3b3

temp_dir.py

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

pipenv

pipenv/patched/notpip/_internal/utils/temp_dir.py

Python

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

lexicographers_mutual_information

def lexicographers_mutual_information(cooccurrence): with np.errstate(invalid="ignore", divide="ignore"): result = cooccurrence * mutual_information(cooccurrence) return np.array(result)

1d7341e93d1f03387699fb3c6ae0b6c0e464296f

python_utils.py

Add new item similarity metrics for SAR (#1754) * Add mutual information similarity in SAR * Add lexicographers mutual information similarity for SAR * Add cosine similarity for SAR * Add inclusion index for SAR * Typos * Change SARSingleNode to SAR * Convert item similarity matrix to np.array * Update * Update SAR tests * Remove unused imports * Add explanations for new similarity metrics

recommenders

recommenders/utils/python_utils.py

Python

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

set_title

def set_title(self, title, prop=None): self._legend_title_box._text.set_text(title) if title: self._legend_title_box._text.set_visible(True) self._legend_title_box.set_visible(True) else: self._legend_title_box._text.set_visible(False) self._legend_title_box.set_visible(False) if prop is not None: self._legend_title_box._text.set_fontproperties(prop) self.stale = True

b9cdf3e2a68bd3d30ad7233b223f88d37044dab3

legend.py

ENH: add the ability to control label alignment in legends Co-authored-by: Tim Hoffmann <[email protected]>

matplotlib

lib/matplotlib/legend.py

Python

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

get_free_open_trades

def get_free_open_trades(self) -> int: open_trades = Trade.get_open_trade_count() return max(0, self.config['max_open_trades'] - open_trades)

87a3115073562e9abc7efd792569020435a01f6e

freqtradebot.py

Add get_open_trade_count() to simplify getting open trade count.

freqtrade

freqtrade/freqtradebot.py

Python

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

native_unit_of_measurement

def native_unit_of_measurement(self) -> str | None: raw_units = self.raw_unit_of_measurement # Check if this is a known index pair UOM if isinstance(raw_units, dict) or raw_units in (UOM_ON_OFF, UOM_INDEX): return None if raw_units in ( UnitOfTemperature.FAHRENHEIT, UnitOfTemperature.CELSIUS, UOM_DOUBLE_TEMP, ): return self.hass.config.units.temperature_unit return raw_units

a6ddac9004b7f73633f2019f3b5267e1486756c1

sensor.py

Use UnitOfTemperature in integrations (i-m) (#84307)

core

homeassistant/components/isy994/sensor.py

Python

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

find_target_completion

def find_target_completion(target_func, prefix, short): # type: (t.Callable[[], t.Iterable[CompletionTarget]], str, bool) -> t.List[str] try: targets = target_func() matches = list(walk_completion_targets(targets, prefix, short)) return matches except Exception as ex: # pylint: disable=locally-disabled, broad-except return ['%s' % ex]

86779cc90376ea70bafa7044b12ce5132409fd63

target.py

ansible-test - Code cleanup. This helps prepare for a future pylint upgrade.

ansible

test/lib/ansible_test/_internal/target.py

Python

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

test_pipeline_simple

def test_pipeline_simple(self): arr = np.random.randint(0, 1000, (1000, 1000)) df = pd.DataFrame(arr)

3d4404e9d9a9b2a3327f8aee664a8e71ac1f18b8

test_pipeline.py

FEAT-#4412: Add Batch Pipeline API to Modin (#4452) Co-authored-by: Yaroslav Igoshev <[email protected]> Co-authored-by: Mahesh Vashishtha <[email protected]> Signed-off-by: Rehan Durrani <[email protected]>

modin

modin/experimental/batch/test/test_pipeline.py

Python

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

__mul__

def __mul__(self, factor): factor = sympify(factor) coords = [simplify(x*factor) for x in self.args] return Point(coords, evaluate=False)

498015021131af4dbb07eb110e5badaba8250c7b

point.py

Updated import locations

sympy

sympy/geometry/point.py

Python

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

value

def value(self): if hasattr(self, '_m_value'): return self._m_value self._m_value = (self.b & 127) return getattr(self, '_m_value', None)

002f919dda5f01d067c2e786426c68751551d15c

vlq_base128_le.py

update kaitai definitions

mitmproxy

mitmproxy/contrib/kaitaistruct/vlq_base128_le.py

Python

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

notify

def notify(self, notification, raise_exception=False): event = notification.event try: return self.notify_users( event.group, event, triggering_rules=[r.label for r in notification.rules] ) except ( ApiError, HTTPError, InvalidIdentity, PluginError, SSLError, UrllibHTTPError, ) as err: self.logger.info( "notification-plugin.notify-failed", extra={ "error": str(err), "plugin": self.slug, "project_id": event.group.project_id, "organization_id": event.group.project.organization_id, }, ) if raise_exception: raise err return False

542484c0cd71625e62e086f3f7c5aaf85360f724

notify.py

fix(plugins): Silence error (#32042)

sentry

src/sentry/plugins/bases/notify.py

Python

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

create_single_host

def create_single_host(name, variables): # type: (str, t.Dict[str, t.Union[str, int]]) -> Inventory return Inventory(host_groups=dict(all={name: variables}))

a06fa496d3f837cca3c437ab6e9858525633d147

host_profiles.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/host_profiles.py

Python

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

test_syncer_hanging_sync_with_timeout

def test_syncer_hanging_sync_with_timeout(temp_data_dirs): tmp_source, tmp_target = temp_data_dirs

ed5b9e5439811becd062ef7734b1afceca2c7d07

test_syncer.py

[Tune] Add timeout for experiment checkpoint syncing to cloud (#30855) #28155 introduced a sync timeout for trainable checkpoint syncing to the cloud, in the case that the sync operation (default is with pyarrow) hangs. This PR adds a similar timeout for experiment checkpoint cloud syncing. Signed-off-by: Justin Yu <[email protected]>

ray

python/ray/tune/tests/test_syncer.py

Python

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

draw

def draw(self, renderer): self._set_lims() # this sets the scale in case the parent has set its scale. self._set_scale() super().draw(renderer)

8387676bc049d7b3e071846730c632e6ced137ed

_secondary_axes.py

Clean up code in SecondaryAxis

matplotlib

lib/matplotlib/axes/_secondary_axes.py

Python

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

decode

def decode(self, bboxes, pred_bboxes, max_shape=None): bboxes = get_box_tensor(bboxes) assert len(pred_bboxes) == 2 cls_preds, offset_preds = pred_bboxes assert cls_preds.size(0) == bboxes.size(0) and offset_preds.size( 0) == bboxes.size(0) bboxes, loc_confidence = bucket2bbox(bboxes, cls_preds, offset_preds, self.num_buckets, self.scale_factor, max_shape, self.clip_border) if self.use_box_type: bboxes = HorizontalBoxes(bboxes, clone=False) return bboxes, loc_confidence

d915740fa8228cf57741b27d9e5d66e358456b8e

bucketing_bbox_coder.py

[Refactor] Refactor anchor head and base head with boxlist (#8625) * Refactor anchor head * Update * Update * Update * Add a series of boxes tools * Fix box type to support n x box_dim boxes * revert box type changes * Add docstring * refactor retina_head * Update * Update * Fix comments * modify docstring of coder and ioucalculator * Replace with_boxlist with use_box_type

mmdetection

mmdet/models/task_modules/coders/bucketing_bbox_coder.py

Python

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

test_include_block_tag_with_plain_value

def test_include_block_tag_with_plain_value(self): result = render_to_string( "tests/blocks/include_block_test.html", { "test_block": 42, }, ) self.assertIn("<body>42</body>", result)

d10f15e55806c6944827d801cd9c2d53f5da4186

test_blocks.py

Reformat with black

wagtail

wagtail/core/tests/test_blocks.py

Python

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

meta_from_array

def meta_from_array(x, ndim=None, dtype=None): # If using x._meta, x must be a Dask Array, some libraries (e.g. zarr) # implement a _meta attribute that are incompatible with Dask Array._meta if hasattr(x, "_meta") and isinstance(x, Array): x = x._meta if dtype is None and x is None: raise ValueError("You must specify the meta or dtype of the array") if np.isscalar(x): x = np.array(x) if x is None: x = np.ndarray elif dtype is None and hasattr(x, "dtype"): dtype = x.dtype if isinstance(x, type): x = x(shape=(0,) * (ndim or 0), dtype=dtype) if isinstance(x, list) or isinstance(x, tuple): ndims = [ 0 if isinstance(a, numbers.Number) else a.ndim if hasattr(a, "ndim") else len(a) for a in x ] a = [a if nd == 0 else meta_from_array(a, nd) for a, nd in zip(x, ndims)] return a if isinstance(x, list) else tuple(x) if ( not hasattr(x, "shape") or not hasattr(x, "dtype") or not isinstance(x.shape, tuple) ): return x if ndim is None: ndim = x.ndim try: meta = x[tuple(slice(0, 0, None) for _ in range(x.ndim))] if meta.ndim != ndim: if ndim > x.ndim: meta = meta[(Ellipsis,) + tuple(None for _ in range(ndim - meta.ndim))] meta = meta[tuple(slice(0, 0, None) for _ in range(meta.ndim))] elif ndim == 0: meta = meta.sum() else: meta = meta.reshape((0,) * ndim) if meta is np.ma.masked: meta = np.ma.array(np.empty((0,) * ndim, dtype=dtype or x.dtype), mask=True) except Exception: meta = np.empty((0,) * ndim, dtype=dtype or x.dtype) if np.isscalar(meta): meta = np.array(meta) if dtype and meta.dtype != dtype: try: meta = meta.astype(dtype) except ValueError as e: if ( any( s in str(e) for s in [ "invalid literal", "could not convert string to float", ] ) and meta.dtype.kind in "SU" ): meta = np.array([]).astype(dtype) else: raise e return meta

7471eb3d1e9ccf085b70b219413aa891c8c2c167

utils.py

masked scalars input to da.from_array (#8895)

dask

dask/array/utils.py

Python

https://github.com/dask/dask.git

async_update

async def async_update(self, *, tries=0): attrs = {} closer_time = None try: yandex_reply = await self.requester.get_stop_info(self._stop_id) except CaptchaError as ex: _LOGGER.error( "%s. You may need to disable the integration for some time", ex, ) return try: data = yandex_reply["data"] except KeyError as key_error: _LOGGER.warning( "Exception KeyError was captured, missing key is %s. Yandex returned: %s", key_error, yandex_reply, ) if tries > 0: return await self.requester.set_new_session() await self.async_update(tries=tries + 1) return stop_name = data["name"] transport_list = data["transports"] for transport in transport_list: for thread in transport["threads"]: if "Events" not in thread["BriefSchedule"]: continue if thread.get("noBoarding") is True: continue for event in thread["BriefSchedule"]["Events"]: # Railway route depends on the essential stops and # can vary over time. # City transport has the fixed name for the route if "railway" in transport["Types"]: route = " - ".join( [x["name"] for x in thread["EssentialStops"]] ) else: route = transport["name"] if self._routes and route not in self._routes: # skip unnecessary route info continue if "Estimated" not in event and "Scheduled" not in event: continue departure = event.get("Estimated") or event["Scheduled"] posix_time_next = int(departure["value"]) if closer_time is None or closer_time > posix_time_next: closer_time = posix_time_next if route not in attrs: attrs[route] = [] attrs[route].append(departure["text"]) attrs[STOP_NAME] = stop_name if closer_time is None: self._state = None else: self._state = dt_util.utc_from_timestamp(closer_time).replace(microsecond=0) self._attrs = attrs

62690759d483b03932939d28bbf87ce3b293c486

sensor.py

Move attribution to standalone attribute [t-z] (#80521)

core

homeassistant/components/yandex_transport/sensor.py

Python

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

_linear_predictor

def _linear_predictor(self, X): check_is_fitted(self) X = self._validate_data( X, accept_sparse=["csr", "csc", "coo"], dtype=[np.float64, np.float32], ensure_2d=True, allow_nd=False, reset=False, ) return X @ self.coef_ + self.intercept_

75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc

glm.py

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

scikit-learn

sklearn/linear_model/_glm/glm.py

Python

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

async_added_to_hass

async def async_added_to_hass(self): self.async_on_remove( self.device.events.async_add_listener(self.async_write_ha_state) ) if (last_state := await self.async_get_last_state()) is not None: self._attr_is_on = last_state.state == STATE_ON

29a2df3dfcf3b5d1fb6cf20b413e024eb0ebf597

binary_sensor.py

Restore ONVIF sensors (#70393) Co-authored-by: Paulus Schoutsen <[email protected]>

core

homeassistant/components/onvif/binary_sensor.py

Python

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

extensions

def extensions(self) -> list[tuple[int, bytes]]: ret = [] if self._client_hello.extensions: for extension in self._client_hello.extensions.extensions: body = getattr(extension, "_raw_body", extension.body) ret.append((extension.type, body)) return ret

e83ec8390ad6be6a86cfcfc57bce14cb8861bf32

tls.py

`pyupgrade --py39-plus **/*.py`

mitmproxy

mitmproxy/tls.py

Python

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

build_runtime_context

def build_runtime_context(self) -> "RuntimeContext": # Defer the import of RuntimeContext until needed to avoid cycles from ray.runtime_context import RuntimeContext return RuntimeContext(self)

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

runtime_context.py

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

ray

python/ray/util/client/runtime_context.py

Python

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

test_make_tarball_latin1

def test_make_tarball_latin1(self): self.test_make_tarball('årchiv') # note this isn't a real word

8198943edd73a363c266633e1aa5b2a9e9c9f526

test_archive_util.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/tests/test_archive_util.py

Python

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

ensure_schema_for_first_block

def ensure_schema_for_first_block(self) -> Optional[Union["pyarrow.Schema", type]]: get_schema = cached_remote_fn(_get_schema) try: block = next(self.iter_blocks()) except (StopIteration, ValueError): # Dataset is empty (no blocks) or was manually cleared. return None schema = ray.get(get_schema.remote(block)) # Set the schema. self._metadata[0].schema = schema return schema

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

block_list.py

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

ray

python/ray/data/impl/block_list.py

Python

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

parse257

def parse257(resp): if resp[:3] != '257': raise error_reply(resp) if resp[3:5] != ' "': return '' # Not compliant to RFC 959, but UNIX ftpd does this dirname = '' i = 5 n = len(resp) while i < n: c = resp[i] i = i+1 if c == '"': if i >= n or resp[i] != '"': break i = i+1 dirname = dirname + c return dirname

8198943edd73a363c266633e1aa5b2a9e9c9f526

ftplib.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/ftplib.py

Python

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

to_bag

def to_bag(df, index=False, format="tuple"): from ...bag.core import Bag if not isinstance(df, (DataFrame, Series)): raise TypeError("df must be either DataFrame or Series") name = "to_bag-" + tokenize(df, index, format) if format == "frame": # Use existing graph and name of df, but # drop meta to produce a Bag collection dsk = df.dask name = df._name else: dsk = { (name, i): (_df_to_bag, block, index, format) for (i, block) in enumerate(df.__dask_keys__()) } dsk.update(df.__dask_optimize__(df.__dask_graph__(), df.__dask_keys__())) return Bag(dsk, name, df.npartitions)

8a6f6a7b95762df4e44bc4d82ce33a7c388a0676

io.py

Move Bag.map_partitions to Blockwise (#8646) 1. Adds `format="frame"` option to `dataframe.io.to_bag` (effectively returning a zero-copy view of the same dask graph, that no-longer tracks meta/divisions) 2. Revises `Bag.map_partitions` to use `blockwise` (and to support the `token=` option) 3. Modifies the ACA code path to use a `Bag.map_partitions` for any blockwise operations where partitions may loose "dataframe-like" properties. This represents an alternative to using `map_partitions` incorrectly in ACA. It is also an alternative to the low-level `blockwise` API.

dask

dask/dataframe/io/io.py

Python

https://github.com/dask/dask.git

_get_no_faces

def _get_no_faces(self): self.output_message = "Frames with no faces" for frame in tqdm(self._items, desc=self.output_message): logger.trace(frame) # type:ignore frame_name = frame["frame_fullname"] if not self._alignments.frame_has_faces(frame_name): logger.debug("Returning: '%s'", frame_name) yield frame_name

892d8626ed4e7f834ac5607af59f14f5476d5997

jobs.py

Bugfix: Alignments tool - don't error on from-faces job

faceswap

tools/alignments/jobs.py

Python

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

_perform_invalid_key_test

def _perform_invalid_key_test(self, key, expected_warning): msg = expected_warning.replace(key, cache.make_key(key)) tests = [ ("add", [key, 1]), ("get", [key]), ("set", [key, 1]), ("incr", [key]), ("decr", [key]), ("touch", [key]), ("delete", [key]), ("get_many", [[key, "b"]]), ("set_many", [{key: 1, "b": 2}]), ("delete_many", [[key, "b"]]), ] for operation, args in tests: with self.subTest(operation=operation): with self.assertRaises(InvalidCacheKey) as cm: getattr(cache, operation)(*args) self.assertEqual(str(cm.exception), msg)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/cache/tests.py

Python

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

test_deploy

def test_deploy(self, mock_func): release = Release.objects.create( version="meow" * 10, organization_id=self.project.organization_id, date_released=timezone.now(), ) # The projects can appear out of order. projects = (self.project, self.create_project(name="battlesnake")) SLUGS_TO_PROJECT = {project.slug: project for project in projects} for project in projects: release.add_project(project) deploy = Deploy.objects.create( release=release, organization_id=self.organization.id, environment_id=self.environment.id, ) notification = ReleaseActivityNotification( Activity( project=self.project, user=self.user, type=ActivityType.RELEASE.value, data={"version": release.version, "deploy_id": deploy.id}, ) ) with self.tasks(): notification.send() attachment, text = get_attachment() assert ( text == f"Release {release.version} was deployed to {self.environment.name} for these projects" ) first_project = None for i in range(len(projects)): project = SLUGS_TO_PROJECT[attachment["actions"][i]["text"]] if not first_project: first_project = project assert ( attachment["actions"][i]["url"] == f"http://testserver/organizations/{self.organization.slug}/releases/" f"{release.version}/?project={project.id}&unselectedSeries=Healthy/" ) assert ( attachment["footer"] == f"{first_project.slug} | <http://testserver/settings/account/notifications/" f"deploy/?referrer=release_activity-slack-user|Notification Settings>" )

b9f5a910dc841b85f58d46266ec049ae5a7fd305

test_deploy.py

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

sentry

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

Python

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

test_option_then_setting

def test_option_then_setting(self): args = [ "base_command", "testlabel", "--option_a=x", "--settings=alternate_settings", ] self._test(args)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_scripts/tests.py

Python

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

_pandas_dtype_needs_early_conversion

def _pandas_dtype_needs_early_conversion(pd_dtype): try: from pandas.api.types import ( is_extension_array_dtype, is_float_dtype, is_integer_dtype, is_sparse, ) except ImportError: return False if is_sparse(pd_dtype) or not is_extension_array_dtype(pd_dtype): # Sparse arrays will be converted later in `check_array` # Only handle extension arrays for integer and floats return False elif is_float_dtype(pd_dtype): # Float ndarrays can normally support nans. They need to be converted # first to map pd.NA to np.nan return True elif is_integer_dtype(pd_dtype): # XXX: Warn when converting from a high integer to a float return True return False

ee5a1b69d1dfa99635a10f0a5b54ec263cedf866

validation.py

DOC, MNT Typos found by codespell (#22906)

scikit-learn

sklearn/utils/validation.py

Python

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

on_motion

def on_motion(self, etype, me): if self.disabled or me.dispatch_mode == MODE_DONT_DISPATCH: return if me.type_id not in self.motion_filter: return filtered = self.motion_filter[me.type_id] if filtered[0] is self and len(filtered) == 1: return if me.dispatch_mode == MODE_DEFAULT_DISPATCH: last_filtered = filtered[-1] for widget in self.children[:]: if widget.dispatch('on_motion', etype, me): return True if widget is last_filtered: return if me.dispatch_mode == MODE_FILTERED_DISPATCH: widgets = filtered[1:] if filtered[0] is self else filtered[:] for widget in widgets: if widget.dispatch('on_motion', etype, me): return True # # Default event handlers #

1830123ba3edf7290b7c6cb1c6f406ccf1d0e5d4

widget.py

Feature: EventManagerBase (#7658) * Added EventManagerBase class and event_managers attribute to WindowBase class. * Added on_motion event to Widget class. * Updated post_dispatch_input in EventLoopBase to skip non-touch events. * Using type ids in MouseMotionEventProvider. * Added on_motion method to Widget subclasses. * Updated Widget.on_motion method to dispatch to filtered widgets if 'pos' is not in me.profile. * Changed motion_filter property in Widget to store key to list values. * Updated Widget.on_motion to not dispatch event to children if widget is disabled. * Widget: Using flags to control dispatching in on_motion method. * Widget: Don't dispatch on_motion to children if only self is registered. * Widget: Removed collision on disabled check from on_motion method. * Widget: Added docstrings for motion_filter and related methods. * EventManager: Moved motion event flags to eventmanager/__init__.py module. * ScreenManager: Overrode the on_motion method. * WindowBase: Using attributes event_managers and event_managers_dict. * WindowBase: Added doc for register_event_manager and unregister_event_manager methods. * Widget: Improved default dispatch to stop after the last registered widgets. * EventManagerBase: Added initial docs class and module. * Widget: Added experimental warnings to motion_filter property and to on_motion and (un)register_for_motion_event methods. * WindowBase: Added docs for event_managers and event_managers_dict attributes. * MotionEvent: Added type_id and flags to push_attrs list. * EventManagerBase: Added versionadded tag on all flags. * EventManagerBase: Use dispatch modes instead of flags.

kivy

kivy/uix/widget.py

Python

https://github.com/kivy/kivy.git

call_ef

def call_ef(self, other_args): parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="ef", description=, ) parser.add_argument( "-vs", "--value-short", dest="short_allocation", help="Amount to allocate to portfolio in short positions", type=float, default=self.params["short_allocation"] if "short_allocation" in self.params else 0.0, ) if other_args and "-" not in other_args[0][0]: other_args.insert(0, "-n") parser.add_argument( "-n", "--number-portfolios", default=self.params["amount_portfolios"] if "amount_portfolios" in self.params else 100, type=check_non_negative, dest="amount_portfolios", help="Number of portfolios to simulate", ) parser.add_argument( "-se", "--seed", default=self.params["random_seed"] if "random_seed" in self.params else 123, type=check_non_negative, dest="random_seed", help="Seed used to generate random portfolios", ) parser.add_argument( "-t", "--tangency", action="store_true", dest="tangency", default=self.params["tangency"] if "tangency" in self.params else False, help="Adds the optimal line with the risk-free asset", ) parser.add_argument( "--no_plot", action="store_false", dest="plot_tickers", default=True, help="Whether or not to plot the tickers for the assets provided", ) parser = self.po_parser( parser, rm=True, mt=True, p=True, s=True, e=True, lr=True, freq=True, mn=True, th=True, r=True, a=True, v=True, ) ns_parser = self.parse_known_args_and_warn(parser, other_args) if ns_parser: if len(self.tickers) < 2: console.print( "Please have at least 2 loaded tickers to calculate weights.\n" ) return optimizer_view.display_ef( symbols=self.tickers, interval=ns_parser.historic_period, start_date=ns_parser.start_period, end_date=ns_parser.end_period, log_returns=ns_parser.log_returns, freq=ns_parser.return_frequency, maxnan=ns_parser.max_nan, threshold=ns_parser.threshold_value, method=ns_parser.nan_fill_method, risk_measure=ns_parser.risk_measure.lower(), risk_free_rate=ns_parser.risk_free, alpha=ns_parser.significance_level, value=ns_parser.long_allocation, value_short=ns_parser.short_allocation, n_portfolios=ns_parser.amount_portfolios, seed=ns_parser.random_seed, tangency=ns_parser.tangency, plot_tickers=ns_parser.plot_tickers, )

83377868b25b91b608f04cbda9383f838dff74cd

po_controller.py

PO_controller refactoring and tests (#2725) * Adding tests * Added tests to po_controller * Refactored po controller * fix custom_resets * fix load * add disable timeout * pylint Co-authored-by: DidierRLopes <[email protected]> Co-authored-by: montezdesousa <[email protected]> Co-authored-by: montezdesousa <[email protected]>

OpenBBTerminal

openbb_terminal/portfolio/portfolio_optimization/po_controller.py

Python

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

is_pinned

def is_pinned(self) -> bool: specifiers = self.specifier return len(specifiers) == 1 and next(iter(specifiers)).operator in {"==", "==="}

f3166e673fe8d40277b804d35d77dcdb760fc3b3

req_install.py

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

pipenv

pipenv/patched/notpip/_internal/req/req_install.py

Python

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

_generate_legacy_events_context_id_query

def _generate_legacy_events_context_id_query() -> Select: # This can be removed once we no longer have event_ids in the states table return ( select( *EVENT_COLUMNS, literal(value=None, type_=sqlalchemy.String).label("shared_data"), States.state, States.entity_id, States.attributes, StateAttributes.shared_attrs, ) .outerjoin(States, (Events.event_id == States.event_id)) .where(States.last_updated == States.last_changed) .where(_not_continuous_entity_matcher()) .outerjoin( StateAttributes, (States.attributes_id == StateAttributes.attributes_id) ) )

26177bd080b4eb6d11cfd9fbdd158be36f4983d4

__init__.py

Convert logbook to use lambda_stmt (#71624)

core

homeassistant/components/logbook/__init__.py

Python

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

test_poisson_glmnet

def test_poisson_glmnet(): # library("glmnet") # options(digits=10) # df <- data.frame(a=c(-2,-1,1,2), b=c(0,0,1,1), y=c(0,1,1,2)) # x <- data.matrix(df[,c("a", "b")]) # y <- df$y # fit <- glmnet(x=x, y=y, alpha=0, intercept=T, family="poisson", # standardize=F, thresh=1e-10, nlambda=10000) # coef(fit, s=1) # (Intercept) -0.12889386979 # a 0.29019207995 # b 0.03741173122 X = np.array([[-2, -1, 1, 2], [0, 0, 1, 1]]).T y = np.array([0, 1, 1, 2]) glm = PoissonRegressor( alpha=1, fit_intercept=True, tol=1e-7, max_iter=300, ) glm.fit(X, y) assert_allclose(glm.intercept_, -0.12889386979, rtol=1e-5) assert_allclose(glm.coef_, [0.29019207995, 0.03741173122], rtol=1e-5)

75a94f518f7bd7d0bf581ffb67d9f961e3c4efbc

test_glm.py

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

scikit-learn

sklearn/linear_model/_glm/tests/test_glm.py

Python

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

detect_reporter

def _detect_reporter(**kwargs) -> TuneReporterBase: if IS_NOTEBOOK: kwargs.setdefault("overwrite", not has_verbosity(Verbosity.V2_TRIAL_NORM)) progress_reporter = JupyterNotebookReporter(**kwargs) else: progress_reporter = CLIReporter(**kwargs) return progress_reporter

eb69c1ca286a2eec594f02ddaf546657a8127afd

progress_reporter.py

[air] Add annotation for Tune module. (#27060) Co-authored-by: Kai Fricke <[email protected]>

ray

python/ray/tune/progress_reporter.py

Python

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

_w_intercept_raw

def _w_intercept_raw(self, coef, X): if not self.base_loss.is_multiclass: if self.fit_intercept: intercept = coef[-1] weights = coef[:-1] else: intercept = 0.0 weights = coef raw_prediction = X @ weights + intercept else: # reshape to (n_classes, n_dof) if coef.ndim == 1: weights = coef.reshape((self.base_loss.n_classes, -1), order="F") else: weights = coef if self.fit_intercept: intercept = weights[:, -1] weights = weights[:, :-1] else: intercept = 0.0 raw_prediction = X @ weights.T + intercept # ndarray, likely C-contiguous return weights, intercept, raw_prediction

d8d5637cfe372dd353dfc9f79dbb63c3189a9ecc

_linear_loss.py

ENH Loss module LogisticRegression (#21808) * ENH replace loss in linear logistic regression * MNT remove logistic regression's own loss functions * CLN remove comment * DOC add whatsnew * DOC more precise whatsnew * CLN restore improvements of #19571 * ENH improve fit time by separating mat-vec in multiclass * DOC update whatsnew * not only a bit ;-) * DOC note memory benefit for multiclass case * trigger CI * trigger CI * CLN rename variable to hess_prod * DOC address reviewer comments * CLN remove C/F for 1d arrays * CLN rename to gradient_per_sample * CLN rename alpha to l2_reg_strength * ENH respect F-contiguity * TST fix sag tests * CLN rename to LinearModelLoss * CLN improve comments according to review * CLN liblinear comment * TST add / move test to test_linear_loss.py * CLN comment placement * trigger CI * CLN add comment about contiguity of raw_prediction * DEBUG debian-32 * DEBUG test only linear_model module * Revert "DEBUG test only linear_model module" This reverts commit 9d6e6987ff4fbcd32fc9a07944b260688162e14b. * DEBUG test -k LogisticRegression * Revert "DEBUG test -k LogisticRegression" This reverts commit c20316704185da400857b0a3f32935ee1b56c8d9. * Revert "DEBUG debian-32" This reverts commit ef0b98f23251d1b2b0bd8801e456f258392a8d18. * DEBUG set n_jobs=1 * Revert "DEBUG set n_jobs=1" This reverts commit c7f6f72a8c1ee21299786130e097df248fc1a0fb. * CLN always use n_threads=1 * CLN address review * ENH avoid array copy * CLN simplify L2 norm * CLN rename w to weights * CLN rename to hessian_sum and hx_sum * CLN address review * CLN rename to init arg and attribute to base_loss * CLN apply review suggestion Co-authored-by: Alexandre Gramfort <[email protected]> * CLN base_loss instead of _loss attribute Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Alexandre Gramfort <[email protected]>

scikit-learn

sklearn/linear_model/_linear_loss.py

Python

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

_make_class_weight_map_fn

def _make_class_weight_map_fn(class_weight): class_ids = list(sorted(class_weight.keys())) expected_class_ids = list(range(len(class_ids))) if class_ids != expected_class_ids: error_msg = ( "Expected `class_weight` to be a dict with keys from 0 to one less " "than the number of classes, found {}" ).format(class_weight) raise ValueError(error_msg) class_weight_tensor = tf.convert_to_tensor( [class_weight[int(c)] for c in class_ids] )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

data_adapter.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/data_adapter.py

Python

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

convert_continuos_f0

def convert_continuos_f0(f0): # get uv information as binary f0 = np.copy(f0) uv = np.float32(f0 != 0) # get start and end of f0 if (f0 == 0).all(): print("| all of the f0 values are 0.") return uv, f0 start_f0 = f0[f0 != 0][0] end_f0 = f0[f0 != 0][-1] # padding start and end of f0 sequence start_idx = np.where(f0 == start_f0)[0][0] end_idx = np.where(f0 == end_f0)[0][-1] f0[:start_idx] = start_f0 f0[end_idx:] = end_f0 # get non-zero frame index nz_frames = np.where(f0 != 0)[0] # perform linear interpolation f = interp1d(nz_frames, f0[nz_frames]) cont_f0 = f(np.arange(0, f0.shape[0])) return uv, cont_f0

7eef3bfde63d03acbd1fc9a15a5e56bef47c0ef7

cwt.py

Add Diffsinger Module (#2120) * add diffsinger * update README * update README

PaddleHub

modules/audio/svs/diffsinger/utils/cwt.py

Python

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

test_dates

def test_dates(self, mock_handler): df = pd.DataFrame([ {'a': 1, 'b': dt.datetime(2020, 1, 1)}, {'a': 2, 'b': dt.datetime(2020, 1, 2)}, {'a': 1, 'b': dt.datetime(2020, 1, 3)}, ]) self.set_handler(mock_handler, name='pg', tables={'tasks': df}) # --- use predictor --- predictor = { 'name': 'task_model', 'predict': 'p', 'dtypes': { 'p': dtype.float, 'a': dtype.integer, 'b': dtype.categorical }, 'predicted_value': 3.14 } self.set_predictor(predictor) ret = self.command_executor.execute_command(parse_sql(f, dialect='mindsdb')) assert ret.error_code is None assert len(ret.data) == 2 # is last datetime value of a = 1 assert ret.data[0][1].isoformat() == dt.datetime(2020, 1, 3).isoformat()

5b1cd41a6202873e49c9ec43c770cf7d1f700adb

test_executor.py

keep datetype from predictor

mindsdb

tests/unit/test_executor.py

Python

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

isfuture

def isfuture(obj): return (hasattr(obj.__class__, '_asyncio_future_blocking') and obj._asyncio_future_blocking is not None)

8198943edd73a363c266633e1aa5b2a9e9c9f526

base_futures.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/asyncio/base_futures.py

Python

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

density

def density(w, **kwargs): if kwargs: warnings.warn( "Additional keyword arguments are deprecated in version 1.2 and will be" " removed in version 1.4.", FutureWarning, ) if hasattr(w, "toarray"): d = float(w.nnz) / (w.shape[0] * w.shape[1]) else: d = 0 if w is None else float((w != 0).sum()) / w.size return d

5d8a1994620713c2e4226fb8e40fef7e81af1103

extmath.py

API Deprecate the extra keyword arguments of utils.extmath.density (#24523) Co-authored-by: Meekail Zain <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/utils/extmath.py

Python

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

get_faces_in_frame

def get_faces_in_frame(self, frame_name): logger.trace("Getting faces for frame_name: '%s'", frame_name) return self._data.get(frame_name, {}).get("faces", [])

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

test_switch_change_alarm_state

async def test_switch_change_alarm_state(hass, utcnow): helper = await setup_test_component(hass, create_security_system_service) await hass.services.async_call( "alarm_control_panel", "alarm_arm_home", {"entity_id": "alarm_control_panel.testdevice"}, blocking=True, ) helper.async_assert_service_values( ServicesTypes.SECURITY_SYSTEM, { CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 0, }, ) await hass.services.async_call( "alarm_control_panel", "alarm_arm_away", {"entity_id": "alarm_control_panel.testdevice"}, blocking=True, ) helper.async_assert_service_values( ServicesTypes.SECURITY_SYSTEM, { CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 1, }, ) await hass.services.async_call( "alarm_control_panel", "alarm_arm_night", {"entity_id": "alarm_control_panel.testdevice"}, blocking=True, ) helper.async_assert_service_values( ServicesTypes.SECURITY_SYSTEM, { CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 2, }, ) await hass.services.async_call( "alarm_control_panel", "alarm_disarm", {"entity_id": "alarm_control_panel.testdevice"}, blocking=True, ) helper.async_assert_service_values( ServicesTypes.SECURITY_SYSTEM, { CharacteristicsTypes.SECURITY_SYSTEM_STATE_TARGET: 3, }, )

58b8c30221a6f6e5acbbe98b7e3298b03fb741f5

test_alarm_control_panel.py

Improve homekit_controller tests (#65266)

core

tests/components/homekit_controller/test_alarm_control_panel.py

Python

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

test_cache_multiple_objects

def test_cache_multiple_objects(self): sites = Site.objects.all() search_backend.cache(sites) content_type = ContentType.objects.get_for_model(Site) self.assertEqual( CachedValue.objects.filter(object_type=content_type).count(), len(SiteIndex.fields) * sites.count() ) for site in sites: for field_name, weight in SiteIndex.fields: self.assertTrue( CachedValue.objects.filter( object_type=content_type, object_id=site.pk, field=field_name, value=getattr(site, field_name), weight=weight ), )

9628dead07ccef9608b32906aa8194bc948e5a09

test_search.py

Closes #10560: New global search (#10676) * Initial work on new search backend * Clean up search backends * Return only the most relevant result per object * Clear any pre-existing cached entries on cache() * #6003: Implement global search functionality for custom field values * Tweak field weights & document guidance * Extend search() to accept a lookup type * Move get_registry() out of SearchBackend * Enforce object permissions when returning search results * Add indexers for remaining models * Avoid calling remove() on non-cacheable objects * Use new search backend by default * Extend search backend to filter by object type * Clean up search view form * Enable specifying lookup logic * Add indexes for value field * Remove object type selector from search bar * Introduce SearchTable and enable HTMX for results * Enable pagination * Remove legacy search backend * Cleanup * Use a UUID for CachedValue primary key * Refactoring search methods * Define max search results limit * Extend reindex command to support specifying particular models * Add clear() and size to SearchBackend * Optimize bulk caching performance * Highlight matched portion of field value * Performance improvements for reindexing * Started on search tests * Cleanup & docs * Documentation updates * Clean up SearchIndex * Flatten search registry to register by app_label.model_name * Clean up search backend classes * Clean up RestrictedGenericForeignKey and RestrictedPrefetch * Resolve migrations conflict

netbox

netbox/netbox/tests/test_search.py

Python

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

convert

def convert(gr, raw_node): type, value, context, children = raw_node if children or type in gr.number2symbol: # If there's exactly one child, return that child instead of # creating a new node. if len(children) == 1: return children[0] return Node(type, children, context=context) else: return Leaf(type, value, context=context)

8198943edd73a363c266633e1aa5b2a9e9c9f526

pytree.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/lib2to3/pytree.py

Python

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

has_lib

def has_lib(self): return (self.distribution.has_pure_modules() or self.distribution.has_ext_modules())

8198943edd73a363c266633e1aa5b2a9e9c9f526

install.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/command/install.py

Python

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

get_all_providers

def get_all_providers() -> List[str]: from setup import PROVIDERS_REQUIREMENTS return list(PROVIDERS_REQUIREMENTS.keys())

3ed07474649b1e202f9b106105fef21f7b2cfddc

verify_providers.py

Seperate provider verification as standalone breeze command (#23454) This is another step in simplifying and converting to Python all of the CI/local development tooling. This PR separates out verification of providers as a separate breeze command `verify-provider-packages`. It was previously part of "prepare_provider_packages.py" but it has been now extracted to a separate in-container python file and it was wrapped with breeze's `verify-provider-packages` command. No longer provider verification is run with "preparing provider docs" nor "preparing provider packages" - it's a standaline command. This command is also used in CI now to run the tests: * all provider packages are built and created on CI together with   airflow version * the packages are installed inside the CI image and providers are verified * the 2.1 version of Airflow is installed together with all 2.1 - compatible providers and provider verification is run there too. This all is much simpler now - we got rediof some 500 lines of bash code again in favour of breeze python code. Fixes: #23430

airflow

scripts/in_container/verify_providers.py

Python

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

test_orderby_percentile_with_many_fields_transactions_unsupported_fields

def test_orderby_percentile_with_many_fields_transactions_unsupported_fields(self): response = self.get_response( self.organization.slug, field=[ "p50(sentry.transactions.measurements.lcp)", "sum(user_misery)", ], statsPeriod="1h", interval="1h", datasource="snuba", groupBy=["project_id", "transaction"], orderBy="p50(sentry.transactions.measurements.lcp)", ) assert response.status_code == 400 assert ( response.json()["detail"] == "Multi-field select order by queries is not supported for metric user_misery" )

9af098891a8243d08ee5ab6e51925a082135e3f2

test_organization_metrics.py

feat(metrics): Support multi-field orderby for performance [INGEST-805] (#31162) * feat(metrics): Support metrics multi-field orderby queries Adds support for the performance table to the metrics organization data endpoint

sentry

tests/sentry/api/endpoints/test_organization_metrics.py

Python

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

get_result

def get_result(self) -> Any: if not self._complete.is_set(): logger.warning("Aborting attempt to retrieve result from a LongRunningTask that is " "still running") return None if self.err: logger.debug("Error caught in thread") self._config.set_cursor_default(widget=self._widget) raise self.err[1].with_traceback(self.err[2]) logger.debug("Getting result from thread") retval = self._queue.get() logger.debug("Got result from thread") self._config.set_cursor_default(widget=self._widget) return retval

dc18c74eea0c7837a820d27628cb12b0824fa30e

utils.py

Bugfix: Preview for extract in batch mode

faceswap

lib/gui/utils.py

Python

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

get_snap_revisions

def get_snap_revisions(snap, version): print('Getting revision numbers for', snap, version) cmd = ['snapcraft', 'status', snap] process = subprocess.run(cmd, check=True, stdout=subprocess.PIPE, universal_newlines=True) pattern = f'^\s+candidate\s+{version}\s+(\d+)\s*' revisions = re.findall(pattern, process.stdout, re.MULTILINE) assert len(revisions) == SNAP_ARCH_COUNT, f'Unexpected number of snaps found for {snap} {version} (expected {SNAP_ARCH_COUNT}, found {len(revisions)})' return revisions

39e8d14e1b221bf37526cc05ecc83beee30a3c57

finish_release.py

Set up 2.0 pre-releases (#9400) * update credential info * update release tooling to use candidate channel * split deploy jobs * pass parameter through * add 2.0 pipeline prerelease * add comments * quote file path

certbot

tools/finish_release.py

Python

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

dup_zz_mignotte_bound

def dup_zz_mignotte_bound(f, K): from sympy.functions.combinatorial.factorials import binomial d = dup_degree(f) delta = _ceil(d / 2) delta2 = _ceil(delta / 2) # euclidean-norm eucl_norm = K.sqrt( sum( [cf**2 for cf in f] ) ) # biggest values of binomial coefficients (p. 538 of reference) t1 = binomial(delta - 1, delta2) t2 = binomial(delta - 1, delta2 - 1) lc = K.abs(dup_LC(f, K)) # leading coefficient bound = t1 * eucl_norm + t2 * lc # (p. 538 of reference) bound += dup_max_norm(f, K) # add max coeff for irreducible polys bound = _ceil(bound / 2) * 2 # round up to even integer return bound

e0dc14eca132f37c5f49369eb4051eae37c9b119

factortools.py

Refactored import ordering in functions

sympy

sympy/polys/factortools.py

Python

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

require_accelerate

def require_accelerate(test_case): return unittest.skipUnless(is_accelerate_available(), "test requires accelerate")(test_case)

2fbb237967f5d1b2eb65c2131954f23a24bd29ef

testing_utils.py

Add the auto_find_batch_size capability from Accelerate into Trainer (#17068) Co-authored-by: Sylvain Gugger <[email protected]> - Adds auto_batch_size finder - Moves training loop to an inner training loop

transformers

src/transformers/testing_utils.py

Python

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

get_strategy_run_id

def get_strategy_run_id(strategy) -> str: digest = hashlib.sha1() config = deepcopy(strategy.config) # Options that have no impact on results of individual backtest. not_important_keys = ('strategy_list', 'original_config', 'telegram', 'api_server') for k in not_important_keys: if k in config: del config[k] digest.update(rapidjson.dumps(config, default=str, number_mode=rapidjson.NM_NATIVE).encode('utf-8')) with open(strategy.__file__, 'rb') as fp: digest.update(fp.read()) return digest.hexdigest().lower()

16861db653ec8166f73fc8480894f186a137e7bd

misc.py

Implement previous backtest result reuse when config and strategy did not change.

freqtrade

freqtrade/misc.py

Python

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

fit

def fit(self, X, y=None): self._validate_params() dtype = bool if self.metric in PAIRWISE_BOOLEAN_FUNCTIONS else float if dtype == bool and X.dtype != bool: msg = ( "Data will be converted to boolean for" f" metric {self.metric}, to avoid this warning," " you may convert the data prior to calling fit." ) warnings.warn(msg, DataConversionWarning) X = self._validate_data(X, dtype=dtype, accept_sparse="csr") if self.metric == "precomputed" and issparse(X): with warnings.catch_warnings(): warnings.simplefilter("ignore", SparseEfficiencyWarning) # Set each diagonal to an explicit value so each point is its # own neighbor X.setdiag(X.diagonal()) memory = check_memory(self.memory) ( self.ordering_, self.core_distances_, self.reachability_, self.predecessor_, ) = memory.cache(compute_optics_graph)( X=X, min_samples=self.min_samples, algorithm=self.algorithm, leaf_size=self.leaf_size, metric=self.metric, metric_params=self.metric_params, p=self.p, n_jobs=self.n_jobs, max_eps=self.max_eps, ) # Extract clusters from the calculated orders and reachability if self.cluster_method == "xi": labels_, clusters_ = cluster_optics_xi( reachability=self.reachability_, predecessor=self.predecessor_, ordering=self.ordering_, min_samples=self.min_samples, min_cluster_size=self.min_cluster_size, xi=self.xi, predecessor_correction=self.predecessor_correction, ) self.cluster_hierarchy_ = clusters_ elif self.cluster_method == "dbscan": if self.eps is None: eps = self.max_eps else: eps = self.eps if eps > self.max_eps: raise ValueError( "Specify an epsilon smaller than %s. Got %s." % (self.max_eps, eps) ) labels_ = cluster_optics_dbscan( reachability=self.reachability_, core_distances=self.core_distances_, ordering=self.ordering_, eps=eps, ) self.labels_ = labels_ return self

ed3172b6c5c733906ce3aa2316c4ad60b5c26d10

_optics.py

MAINT Parameters validation for OPTICS (#24326) Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/cluster/_optics.py

Python

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

_filter_boxes

def _filter_boxes(self, patch, boxes): center = boxes.centers.numpy() mask = (center[:, 0] > patch[0]) * (center[:, 1] > patch[1]) * ( center[:, 0] < patch[2]) * ( center[:, 1] < patch[3]) return mask

af063a6f25ddae4de90646f86b2db824f3d00138

transforms.py

[Refactor] Refactor pipelines with boxlist. (#8562) * Refactor pipelines and data_preprocesser by boxlist * Refactor browse_dataset.py * Update * Update * Update * Update * update * Update * Change with_box_wrapped to with_boxlist * Fix comments * Fix commits * Update UT

mmdetection

mmdet/datasets/transforms/transforms.py

Python

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

_normalize_index

def _normalize_index(index, axis_size): if issubdtype(_dtype(index), np.unsignedinteger): return index if core.is_constant_dim(axis_size): axis_size_val = _lax_const(index, axis_size) else: axis_size_val = lax.convert_element_type(core.dimension_as_value(axis_size), _dtype(index)) return lax.select( lax.lt(index, _lax_const(index, 0)), lax.add(index, axis_size_val), index) TAKE_ALONG_AXIS_DOC = @_wraps(np.take_along_axis, update_doc=False, lax_description=TAKE_ALONG_AXIS_DOC) @partial(jit, static_argnames=('axis', 'mode'))

92ca76a0395ad32423e681b6d6ce6d84c361852b

@_wraps(np.take_along_axis, update_doc=False, lax_description=TAKE_ALONG_AXIS_DOC) @partial(jit, static_argnames=('axis', 'mode'))

lax_numpy.py

Skip normalization of unsigned indices

jax

jax/_src/numpy/lax_numpy.py

Python

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

state_checkpoint_interval

def state_checkpoint_interval(self) -> Optional[int]: if self._is_finished: return 1 return 100

27b5ba338656b9adbfc8ebd90960a200a14d5935

streams.py

:tada: Source Looker: Migrate to native CDK (#9609)

airbyte

airbyte-integrations/connectors/source-looker/source_looker/streams.py

Python

https://github.com/airbytehq/airbyte.git

timezone_tag

def timezone_tag(parser, token): bits = token.split_contents() if len(bits) != 2: raise TemplateSyntaxError("'%s' takes one argument (timezone)" % bits[0]) tz = parser.compile_filter(bits[1]) nodelist = parser.parse(("endtimezone",)) parser.delete_first_token() return TimezoneNode(nodelist, tz) @register.tag("get_current_timezone")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@register.tag("get_current_timezone")

tz.py

Refs #33476 -- Reformatted code with Black.

django

django/templatetags/tz.py

Python

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

update

def update(self) -> None: with self.lock: # Fetch valid stop information once if not self._origin: stops = self._pygtfs.stops_by_id(self.origin) if not stops: self._available = False _LOGGER.warning("Origin stop ID %s not found", self.origin) return self._origin = stops[0] if not self._destination: stops = self._pygtfs.stops_by_id(self.destination) if not stops: self._available = False _LOGGER.warning( "Destination stop ID %s not found", self.destination ) return self._destination = stops[0] self._available = True # Fetch next departure self._departure = get_next_departure( self._pygtfs, self.origin, self.destination, self._offset, self._include_tomorrow, ) # Define the state as a UTC timestamp with ISO 8601 format if not self._departure: self._state = None else: self._state = self._departure["departure_time"].replace( tzinfo=dt_util.UTC ) # Fetch trip and route details once, unless updated if not self._departure: self._trip = None else: trip_id = self._departure["trip_id"] if not self._trip or self._trip.trip_id != trip_id: _LOGGER.debug("Fetching trip details for %s", trip_id) self._trip = self._pygtfs.trips_by_id(trip_id)[0] route_id = self._departure["route_id"] if not self._route or self._route.route_id != route_id: _LOGGER.debug("Fetching route details for %s", route_id) self._route = self._pygtfs.routes_by_id(route_id)[0] # Fetch agency details exactly once if self._agency is None and self._route: _LOGGER.debug("Fetching agency details for %s", self._route.agency_id) try: self._agency = self._pygtfs.agencies_by_id(self._route.agency_id)[0] except IndexError: _LOGGER.warning( "Agency ID '%s' was not found in agency table, " "you may want to update the routes database table " "to fix this missing reference", self._route.agency_id, ) self._agency = False # Assign attributes, icon and name self.update_attributes() if self._agency: self._attr_attribution = self._agency.agency_name else: self._attr_attribution = None if self._route: self._icon = ICONS.get(self._route.route_type, ICON) else: self._icon = ICON name = ( f"{getattr(self._agency, 'agency_name', DEFAULT_NAME)} " f"{self.origin} to {self.destination} next departure" ) if not self._departure: name = f"{DEFAULT_NAME}" self._name = self._custom_name or name

c717fd19de01fc822d146cc5e353959dfa86d5f7

sensor.py

Move attribution to standalone attribute [e-g] (#80513)

core

homeassistant/components/gtfs/sensor.py

Python

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

file_exists

def file_exists(self, filename): if not self.hass.config.is_allowed_path(filename): _LOGGER.warning("Path not allowed: %s", filename) return False if not os.path.isfile(filename): _LOGGER.warning("Not a file: %s", filename) return False return True

aa57907c1878b5d7bdaf258e0b135c189abb8f27

notify.py

Improve logging for Discord integration (#68160)

core

homeassistant/components/discord/notify.py

Python

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

get

def get(self): response = { 'learn': False, 'predict': False, 'analyse': False } if os.name != 'posix': return response for process_type in response: processes_dir = Path(tempfile.gettempdir()).joinpath(f'mindsdb/processes/{process_type}/') if not processes_dir.is_dir(): continue process_marks = [x.name for x in processes_dir.iterdir()] for p_mark in process_marks: pid = int(p_mark.split('-')[0]) try: psutil.Process(pid) except Exception: processes_dir.joinpath(p_mark).unlink() else: response[process_type] = True return response @ns_conf.route('/telemetry')

44d7ef0e08e5144870ad2831ce6e221f9044c47c

@ns_conf.route('/telemetry')

util.py

'files' route

mindsdb

mindsdb/api/http/namespaces/util.py

Python

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

get_task_type_filter_choices

def get_task_type_filter_choices(self): task_type_choices = [ (model, model.get_verbose_name()) for model in self.task_models ] task_type_choices.sort(key=lambda task_type: task_type[1].lower()) return task_type_choices

284380672da91b5f1d5ea35e01b5b86d7a534dbb

workflows.py

add another helper method get_task_type_filter_choices

wagtail

wagtail/admin/views/workflows.py

Python

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

test_workflow_action_via_edit_view

def test_workflow_action_via_edit_view(self): # Post self.client.post( reverse("wagtailadmin_pages:edit", args=(self.page.id,)), { "title": "This title was edited while approving", "slug": str(self.page.slug), "content": str(self.page.content), "action-workflow-action": "True", "workflow-action-name": "approve", "workflow-action-extra-data": '{"comment": "my comment"}', }, ) # Check that the workflow was approved workflow_state = WorkflowState.objects.get( page=self.page, requested_by=self.submitter ) self.assertEqual(workflow_state.status, workflow_state.STATUS_APPROVED) # Check that the task was approved task_state = workflow_state.current_task_state self.assertEqual(task_state.status, task_state.STATUS_APPROVED) # Check that the comment was added to the task state correctly self.assertEqual(task_state.comment, "my comment") # Check that page edits made at the same time as the action have been saved page = Page.objects.get(id=self.page.id) self.assertEqual( page.get_latest_revision_as_page().title, "This title was edited while approving", )

d10f15e55806c6944827d801cd9c2d53f5da4186

test_workflows.py

Reformat with black

wagtail

wagtail/admin/tests/test_workflows.py

Python

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

test_zeroVector

def test_zeroVector(self): self.assertTrue(zeroVector(10).__str__().count("0") == 10)

f0af0c43340763724f139fa68aa1e5a9ffe458b4

tests.py

refactor: clean code Signed-off-by: slowy07 <[email protected]>

Python

linear-algebra-python/src/tests.py

Python

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

test_user_can_supply_a_sidecar_container_and_volume

def test_user_can_supply_a_sidecar_container_and_volume(self): manifest = KubernetesJob( command=["echo", "hello"], job={ "apiVersion": "batch/v1", "kind": "Job", "metadata": {"labels": {}}, "spec": { "template": { "spec": { "parallelism": 1, "completions": 1, "restartPolicy": "Never", "containers": [ { "name": "prefect-job", "env": [], }, { "name": "my-sidecar", "image": "cool-peeps/cool-code:latest", "volumeMounts": [ {"name": "data-volume", "mountPath": "/data/"} ], }, ], "volumes": [ {"name": "data-volume", "hostPath": "/all/the/data/"} ], } } }, }, ).build_job() pod = manifest["spec"]["template"]["spec"] assert pod["volumes"] == [{"name": "data-volume", "hostPath": "/all/the/data/"}] # the prefect-job container is still populated assert pod["containers"][0]["name"] == "prefect-job" assert pod["containers"][0]["command"] == ["echo", "hello"] assert pod["containers"][1] == { "name": "my-sidecar", "image": "cool-peeps/cool-code:latest", "volumeMounts": [{"name": "data-volume", "mountPath": "/data/"}], }

daddc2985f0cba6c6e0ae3903232cbca155e7e91

test_kubernetes_job.py

Port KubernetesFlowRunner tests to KubernetesJob tests

prefect

tests/infrastructure/test_kubernetes_job.py

Python

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

addCondition

def addCondition(self, *fns, **kwargs): for fn in fns: self.parseAction.append(conditionAsParseAction(fn, message=kwargs.get('message'), fatal=kwargs.get('fatal', False))) self.callDuringTry = self.callDuringTry or kwargs.get("callDuringTry", False) return self

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

pyparsing.py

upd; format

transferlearning

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

Python

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

call_arktrades

def call_arktrades(self, other_args): parser = argparse.ArgumentParser( add_help=False, prog="arktrades", description=, ) parser.add_argument( "-l", "--limit", help="Limit of rows to show", dest="limit", default=10, type=check_positive, ) parser.add_argument( "-s", "--show_ticker", action="store_true", default=False, help="Flag to show ticker in table", dest="show_ticker", ) if other_args and "-" not in other_args[0][0]: other_args.insert(0, "-l") ns_parser = parse_known_args_and_warn( parser, other_args, export_allowed=EXPORT_ONLY_RAW_DATA_ALLOWED ) if ns_parser: ark_view.display_ark_trades( ticker=self.ticker, num=ns_parser.limit, export=ns_parser.export, show_ticker=ns_parser.show_ticker, )

42b1acf5c3d2f9e9922ac8c4e956fffc08a5d7ae

dd_controller.py

Add an API wrapper for terminal functions to be used in python (#1170) * Initial implementation of the API wrapper for stocks/disc * Create a file for helper classes * Move models namespace class where it belongs... TO THE HELPER_CLASSES🚀 * Add backtesting api wrapper * Add ba api wrapper * Add dps api wrapper * Fix flake8 warnings in command help strings * Add comparison analysis models * Add dd api wrapper * Add fa api wrapper * Add gov api wrapper * Add ins api wrapper *note the note * Add options api wrapper *note the note * Add prediction api wrapper * Add api support for importing models from both local and common contexts * Add qa api wrapper * Add screener api wrapper *note the note * Fix typos in sia controller * Add sia api wrapper * Add ta api wrapper * Disable linting for specific lines that fail in CI * Remove deprecated parameter * Add exception handling when prediction packages are not installed

OpenBBTerminal

gamestonk_terminal/stocks/due_diligence/dd_controller.py

Python

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

_solve_svd_design_matrix

def _solve_svd_design_matrix(self, alpha, y, sqrt_sw, X_mean, singvals_sq, U, UT_y): w = ((singvals_sq + alpha) ** -1) - (alpha**-1) if self.fit_intercept: # detect intercept column normalized_sw = sqrt_sw / np.linalg.norm(sqrt_sw) intercept_dim = _find_smallest_angle(normalized_sw, U) # cancel the regularization for the intercept w[intercept_dim] = -(alpha**-1) c = np.dot(U, self._diag_dot(w, UT_y)) + (alpha**-1) * y G_inverse_diag = self._decomp_diag(w, U) + (alpha**-1) if len(y.shape) != 1: # handle case where y is 2-d G_inverse_diag = G_inverse_diag[:, np.newaxis] return G_inverse_diag, c

1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe

_ridge.py

MNT Update black to stable version (#22474)

scikit-learn

sklearn/linear_model/_ridge.py

Python

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

test_parallel_state_with_long_tag

def test_parallel_state_with_long_tag(state, state_tree): short_command = "helloworld" long_command = short_command * 25 sls_contents = .format( short_command, long_command ) with pytest.helpers.temp_file("issue-49738.sls", sls_contents, state_tree): ret = state.sls( "issue-49738", __pub_jid="1", # Because these run in parallel we need a fake JID ) comments = sorted(x.comment for x in ret) expected = sorted( 'Command "{}" run'.format(x) for x in (short_command, long_command) ) assert comments == expected, "{} != {}".format(comments, expected) @pytest.mark.skip_on_darwin(reason="Test is broken on macosx") @pytest.mark.skip_on_windows( reason=( "Functional testing this on windows raises unicode errors. " "Tested in tests/pytests/integration/modules/state/test_state.py" ) )

f2a783643de61cac1ff3288b40241e5ce6e1ddc8

@pytest.mark.skip_on_darwin(reason="Test is broken on macosx") @pytest.mark.skip_on_windows( reason=( "Functional testing this on windows raises unicode errors. " "Tested in tests/pytests/integration/modules/state/test_state.py" ) )

test_state.py

Update to latest ``pyupgrade`` hook. Stop skipping it on CI. Signed-off-by: Pedro Algarvio <[email protected]>

salt

tests/pytests/functional/modules/state/test_state.py

Python

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

process_downloaded_dataset

def process_downloaded_dataset(self): makedirs(self.processed_temp_path, exist_ok=True) for dataset in ["training", "testing"]: print(f">>> create ludwig formatted {dataset} data") labels, images = self.read_source_dataset(dataset, self.raw_dataset_path) self.write_output_dataset(labels, images, os.path.join(self.processed_temp_path, dataset)) self.output_training_and_test_data() rename(self.processed_temp_path, self.processed_dataset_path) print(">>> completed data preparation")

89d18365c41c4ded68edd2095349ce4a6caf5d18

__init__.py

Removes skimage and imageio dependencies replacing imsave with torchvision.utils.save_image (#1694)

ludwig

ludwig/datasets/mnist/__init__.py

Python

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

stack

def stack(self, level=-1, dropna=True): # noqa: PR01, RT01, D200 if not isinstance(self.columns, pandas.MultiIndex) or ( isinstance(self.columns, pandas.MultiIndex) and is_list_like(level) and len(level) == self.columns.nlevels ): return self._reduce_dimension( query_compiler=self._query_compiler.stack(level, dropna) ) else: return self.__constructor__( query_compiler=self._query_compiler.stack(level, dropna) )

b541b6c18e6fb4515e998b9b4f88528490cf69c6

dataframe.py

REFACTOR-#3948: Use `__constructor__` in `DataFrame` and `Series` classes (#5485) Signed-off-by: Anatoly Myachev <[email protected]>

modin

modin/pandas/dataframe.py

Python

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

set_seed

def set_seed(seed): random.seed(seed) np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed_all(seed)

5fdb54ece78b5d277fe26a3865beca8da0430495

igf.py

Add Information Gain Filtration algorithm (#16953) * Add information gain filtration algorithm * Complying with black requirements * Added author * Fixed import order * flake8 corrections Co-authored-by: Javier Turek <[email protected]>

transformers

examples/research_projects/information-gain-filtration/igf/igf.py

Python

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

test_step

def test_step(self, data): data = data_adapter.expand_1d(data) x, y, sample_weight = data_adapter.unpack_x_y_sample_weight(data) # These next two lines differ from the base method - they avoid issues when the labels are in # the input dict (and loss is computed internally) if y is None and "labels" in x: y = x["labels"] # Stops confusion with metric computations elif y is None and "input_ids" in x: # Just make any kind of dummy array to make loss work y = tf.zeros(tf.shape(x["input_ids"])[0], dtype=tf.int64) y_pred = self(x, training=False) self.compiled_loss(y, y_pred, sample_weight, regularization_losses=self.losses) # Updates stateful loss metrics. if isinstance(y_pred, TFSeq2SeqLMOutput) and isinstance(y, tf.Tensor): y_pred = y_pred["logits"] self.compiled_metrics.update_state(y, y_pred, sample_weight) # Collect metrics to return return_metrics = {} for metric in self.metrics: result = metric.result() if isinstance(result, dict): return_metrics.update(result) else: return_metrics[metric.name] = result # These next two lines are also not in the base method - they correct the displayed metrics # when we're using a dummy loss, to avoid a bogus "loss_loss" value being shown. if "loss" in return_metrics and "loss_loss" in return_metrics: del return_metrics["loss_loss"] return return_metrics

44eaa2b3036c5c9a83ed781e08e3dc50aae193a9

modeling_tf_utils.py

Update TF test_step to match train_step (#15111) * Update TF test_step to match train_step * Update compile() warning to be clearer about what to pass

transformers

src/transformers/modeling_tf_utils.py

Python

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

get_cloud_sync_client

def get_cloud_sync_client(remote_path): if remote_path.startswith(S3_PREFIX): if not distutils.spawn.find_executable("aws"): raise ValueError( "Upload uri starting with '{}' requires awscli tool" " to be installed".format(S3_PREFIX) ) sync_up_template = ( "aws s3 sync {source} {target} " "--only-show-errors {options}" ) sync_down_template = sync_up_template delete_template = ( "aws s3 rm {target} --recursive " "--only-show-errors {options}" ) exclude_template = "--exclude '{pattern}'" elif remote_path.startswith(GS_PREFIX): if not distutils.spawn.find_executable("gsutil"): raise ValueError( "Upload uri starting with '{}' requires gsutil tool" " to be installed".format(GS_PREFIX) ) sync_up_template = "gsutil rsync -r {options} {source} {target}" sync_down_template = sync_up_template delete_template = "gsutil rm -r {options} {target}" exclude_template = "-x '{regex_pattern}'" elif remote_path.startswith(HDFS_PREFIX): if not distutils.spawn.find_executable("hdfs"): raise ValueError( "Upload uri starting with '{}' requires hdfs tool" " to be installed".format(HDFS_PREFIX) ) sync_up_template = "hdfs dfs -put -f {source} {target}" sync_down_template = "hdfs dfs -get -f {source} {target}" delete_template = "hdfs dfs -rm -r {target}" exclude_template = None else: raise ValueError( f"Upload uri must start with one of: {ALLOWED_REMOTE_PREFIXES} " f"(is: `{remote_path}`)" ) return CommandBasedClient( sync_up_template, sync_down_template, delete_template, exclude_template ) @PublicAPI(stability="beta")

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

@PublicAPI(stability="beta")

sync_client.py

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

ray

python/ray/tune/sync_client.py

Python

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

test_hvac_mode_vs_hvac_action_current_mode_wrong

async def test_hvac_mode_vs_hvac_action_current_mode_wrong(hass, utcnow): helper = await setup_test_component(hass, create_thermostat_service) await helper.async_update( ServicesTypes.THERMOSTAT, { CharacteristicsTypes.TEMPERATURE_CURRENT: 22, CharacteristicsTypes.TEMPERATURE_TARGET: 21, CharacteristicsTypes.HEATING_COOLING_CURRENT: 1, CharacteristicsTypes.HEATING_COOLING_TARGET: 0, CharacteristicsTypes.RELATIVE_HUMIDITY_CURRENT: 50, CharacteristicsTypes.RELATIVE_HUMIDITY_TARGET: 45, }, ) state = await helper.poll_and_get_state() assert state.state == "off" assert state.attributes["hvac_action"] == "idle"

117c12d135039797e5c00e9f1c87ece7f4be13e0

test_climate.py

Fix Eve Thermo always showing as heating in homekit_controller even when off (#80019)

core

tests/components/homekit_controller/test_climate.py

Python

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

url_params_from_lookup_dict

def url_params_from_lookup_dict(lookups): params = {} if lookups and hasattr(lookups, "items"): for k, v in lookups.items(): if callable(v): v = v() if isinstance(v, (tuple, list)): v = ",".join(str(x) for x in v) elif isinstance(v, bool): v = ("0", "1")[v] else: v = str(v) params[k] = v return params

9c19aff7c7561e3a82978a272ecdaad40dda5c00

widgets.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/widgets.py

Python

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

from_biadjacency_matrix

def from_biadjacency_matrix(A, create_using=None, edge_attribute="weight"): r G = nx.empty_graph(0, create_using) n, m = A.shape # Make sure we get even the isolated nodes of the graph. G.add_nodes_from(range(n), bipartite=0) G.add_nodes_from(range(n, n + m), bipartite=1) # Create an iterable over (u, v, w) triples and for each triple, add an # edge from u to v with weight w. triples = ((u, n + v, d) for (u, v, d) in _generate_weighted_edges(A)) # If the entries in the adjacency matrix are integers and the graph is a # multigraph, then create parallel edges, each with weight 1, for each # entry in the adjacency matrix. Otherwise, create one edge for each # positive entry in the adjacency matrix and set the weight of that edge to # be the entry in the matrix. if A.dtype.kind in ("i", "u") and G.is_multigraph(): chain = itertools.chain.from_iterable triples = chain(((u, v, 1) for d in range(w)) for (u, v, w) in triples) G.add_weighted_edges_from(triples, weight=edge_attribute) return G

8a325d26aa7fdd3a72580c4720fa97f971bbefcb

matrix.py

Use scipy.sparse array datastructure (#6037) * Use scipy.sparse array datastructure * Add reminder to rm wrapper when scipy adds creation fns. * Rm mention of np matrix from code comment. * Update networkx/algorithms/bipartite/matrix.py Co-authored-by: Stefan van der Walt <[email protected]> Co-authored-by: Ross Barnowski <[email protected]> Co-authored-by: Stefan van der Walt <[email protected]>

networkx

networkx/algorithms/bipartite/matrix.py

Python

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

_get_default_coordinate_values

def _get_default_coordinate_values(self) -> list[float | complex]: x_numbers = self.get_x_axis().get_tick_range() y_numbers = self.get_y_axis().get_tick_range() y_numbers = [complex(0, y) for y in y_numbers if y != 0] return [*x_numbers, *y_numbers]

daf23c9d1031b12d9c119b8f6b7e60727d7f9242

coordinate_systems.py

Upgraded typehints (#2429) * Future Annotations * Delete template_twitter_post.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Apply suggestions from code review * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fixed broken RTD Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

manim

manim/mobject/coordinate_systems.py

Python

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

update

def update(self, **kwargs): for k, v in kwargs.items(): if k in self._AllowedKeys: setattr(self, k, v) else: raise AttributeError(f"{k} is an unknown keyword") for figmanager in _pylab_helpers.Gcf.figs.values(): for ax in figmanager.canvas.figure.axes: if ax.get_subplotspec() is not None: ss = ax.get_subplotspec().get_topmost_subplotspec() if ss.get_gridspec() == self: ax._set_position( ax.get_subplotspec().get_position(ax.figure))

c73f4c455514cf5422d27bf38c93250de8316b21

gridspec.py

Merge SubplotBase into AxesBase.

matplotlib

lib/matplotlib/gridspec.py

Python

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

test_valid_multiple_ops

def test_valid_multiple_ops(self) -> None: yaml_str = self.assert_success_from_gen_backend_stubs(yaml_str)

bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d

test_gen_backend_stubs.py

Revert "Revert D32498569: allow external backend codegen to toggle whether to generate out= and inplace kernels" (#69950) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69950 This reverts commit f6cad53443704dfe5a20cc62bee14d91e3bffcaa. Test Plan: Imported from OSS Reviewed By: albanD Differential Revision: D33113545 Pulled By: bdhirsh fbshipit-source-id: d6590294662588d36c09662dea65919ad4e1e288

pytorch

tools/test/test_gen_backend_stubs.py

Python

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

meet

def meet(self, timeout_s=180): if timeout_s <= 0: raise ValueError( "The 'timeout' argument must be positive. " "Got '{}'.".format(timeout_s) ) timeout_delta = datetime.timedelta(seconds=timeout_s) elapsed = datetime.timedelta(seconds=0) start_time = datetime.datetime.now() q, s = None, None if self._store_type == "redis" or self._store_type == "ray_internal_kv": while elapsed < timeout_delta: try: # I don't quite understand why we need gloo queue actor. q = ray.get_actor("gloo_queue") s = ray.get_actor(f"gloo_{self._group_name}_signal") break except ValueError: if self._context.rank == 0: if not q: ray.remote(gloo_util.glooQueue).options( name="gloo_queue", lifetime="detached" ).remote(1000) if not s: gloo_util.SignalActor.options( name=f"gloo_{self._group_name}_signal", lifetime="detached", ).remote(self._context.size) else: time.sleep(0.1) elapsed = datetime.datetime.now() - start_time if not q: raise RuntimeError("Unable to get gloo_queue.") if self._context.rank == 0: ray.get(q.put_nowait.remote(self._group_name)) while ray.get(q.index.remote(self._group_name)): time.sleep(0.1) self._context.connectFullMesh(self._store, self._device) ray.get(s.send.remote(self._context.rank)) if self._context.rank == 0: ray.get(s.wait.remote()) keys = [] keys += [f"rank_{i}" for i in range(self._context.size)] keys += [f"{i}" for i in range(self._context.size)] self._store.delKeys(keys) group_name = ray.get(q.get_nowait.remote()) assert group_name == self._group_name ray.kill(s)

905258dbc19753c81039f993477e7ab027960729

gloo_collective_group.py

Clean up docstyle in python modules and add LINT rule (#25272)

ray

python/ray/util/collective/collective_group/gloo_collective_group.py

Python