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semeru

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Semeru Lab 7

bokeh/models/callbacks.py

Generalize tooltips and add description to widgets (#12154) * Generalize tooltips and add description to widgets * Fail in old compiler if TS had errors * Update font-awesome icon's implementation * Add models representing element queries * Introduce a ViewManager for a Document * Make LayoutDOM a UIElement * Expose Tooltip's target property * Make embed_items (etc.) return ViewManager * Ignore Undefined/Intrinsic initializer values * Update visual baselines * Use explicit __all__ exports in models.ui * Use the correct DOM element in mousedown * Allow attach tooltips to UIElements * Redesign and generalize menus * Add HelpButton and BuiltinIcon models * Fix eager eval in Instance's sphinx_link * Add LayoutDOM.context_menu property * Let TooltipView handle initial rendering * Add position to a Tooltip to display it * Move icons to the ui module * Make menu items UI elements * Allow to reference property values in DOM * Redesign stylesheet management, avoid style * Add experimental support for third-party icons * Add a stub Dialog UI component implementation * Add SetValue(obj, attr, value) callback model * Allow Callback models in js_{event,property}_callbacks * Allow to display Inspector in a dialog box * Rename Separator->Divider for consistent naming * Preliminary support for icon sizing * Split up models/dom/index.ts into sub-modules * Update font-awesome example * Add more unit tests for core/util/iterator * Add SVGIcon and update docstrings * Add/Improve docstrings in models/dom.py * More docstrings * Apply review suggestions Co-authored-by: Bryan Van de Ven <bryan@bokeh.org> Co-authored-by: Bryan Van de Ven <bryan@bokeh.org>

bokeh

Python

callbacks.py

def _check_if_provided_a_valid_value(self): descriptor = self.obj.lookup(self.attr) if descriptor.property.is_valid(self.value): return None else: return f"{self.value!r} is not a valid value for {self.obj}.{self.attr}" # TODO: class Show(Callback): target = Required(Either(Instance(DOMNode), Instance(UIElement))) # TODO: class Hide(Callback): ... #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Code #-----------------------------------------------------------------------------

700b5be79008ec576dc9994ee48850da43277d3e

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

def _check_if_provided_a_valid_value(self): descriptor = self.obj.lookup(self.attr) if descriptor.property.is_valid(self.value): return None else: return f"{self.value!r} is not a valid value for {self.obj}.{self.attr}" # TODO: class Show(Callback): target = Required(Either(Instance(DOMNode), Instance(UIElement))) # TODO: class Hide(Callback): ... #----------------------------------------------------------------------------- # Dev API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Private API #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Code #---

_check_if_provided_a_valid_value

homeassistant/components/lock/__init__.py

Adjust type hints for LockEntityFeature (#82256)

core

Python

__init__.py

def supported_features(self) -> LockEntityFeature | int: return self._attr_supported_features

8570d3aabeb0bde1345659087849acd9de946ce5

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

def supported_features(self) -> LockEntityFeature | int: return self._attr_supported_features

supported_features

tests/components/samsungtv/conftest.py

Use async rest api in SamsungTV (#67369) Co-authored-by: epenet <epenet@users.noreply.github.com>

core

Python

conftest.py

def rest_api_fixture() -> Mock: with patch( "homeassistant.components.samsungtv.bridge.SamsungTVAsyncRest", autospec=True, ) as rest_api_class: rest_api_class.return_value.rest_device_info.return_value = { "id": "uuid:be9554b9-c9fb-41f4-8920-22da015376a4", "device": { "modelName": "82GXARRS", "wifiMac": "aa:bb:cc:dd:ee:ff", "name": "[TV] Living Room", "type": "Samsung SmartTV", "networkType": "wireless", }, } yield rest_api_class.return_value @pytest.fixture(name="remotews")

1556868d562b0426effd0d556b9665d2865a8018

@pytest.fixture(name="remotews")

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

def rest_api_fixture() -> Mock: with patch( "homeassistant.components.samsungtv.bridge.SamsungTVAsyncRest",

rest_api_fixture

Lib/test/test_posix.py

bpo-46426: Improve tests for the dir_fd argument (GH-30668) Ensure that directory file descriptors refer to directories different from the current directory, and that src_dir_fd and dst_dir_fd refer to different directories. Add context manager open_dir_fd() in test.support.os_helper.

cpython

Python

test_posix.py

def prepare(self): TestPosixDirFd.count += 1 name = f'{os_helper.TESTFN}_{self.count}' base_dir = f'{os_helper.TESTFN}_{self.count}base' posix.mkdir(base_dir) self.addCleanup(posix.rmdir, base_dir) fullname = os.path.join(base_dir, name) assert not os.path.exists(fullname) with os_helper.open_dir_fd(base_dir) as dir_fd: yield (dir_fd, name, fullname)

54610bb448a9cf5be77d53b66169fca4c11be6cb

https://github.com/python/cpython.git

def prepare(self): TestPosixDirFd.count

prepare

d2l/mxnet.py

Refactoring Attention scoring functions and Bahdanau Attention (#2095) * Attention scoring funcs * attn * sequence mask * remove accents

d2l-en

Python

mxnet.py

def transpose_qkv(X, num_heads): # Shape of input X: (batch_size, no. of queries or key-value pairs, # num_hiddens). Shape of output X: (batch_size, no. of queries or # key-value pairs, num_heads, num_hiddens / num_heads) X = X.reshape(X.shape[0], X.shape[1], num_heads, -1) # Shape of output X: (batch_size, num_heads, no. of queries or key-value # pairs, num_hiddens / num_heads) X = X.transpose(0, 2, 1, 3) # Shape of output: (batch_size * num_heads, no. of queries or key-value # pairs, num_hiddens / num_heads) return X.reshape(-1, X.shape[2], X.shape[3])

098975b3dce69956e5ebc5f95a04589d2bfc8c22

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

def transpose_qkv(X, num_heads): # Shape of input X: (batch_size, no. of queries or key-value pairs,

transpose_qkv

lib/mpl_toolkits/axisartist/tests/test_axislines.py

Add facecolor to axisline style

matplotlib

Python

test_axislines.py

def test_axisline_style_size_color(): fig = plt.figure(figsize=(2, 2)) ax = fig.add_subplot(axes_class=AxesZero) ax.axis["xzero"].set_axisline_style("-|>", size=2.0, facecolor='r') ax.axis["xzero"].set_visible(True) ax.axis["yzero"].set_axisline_style("->, size=1.5") ax.axis["yzero"].set_visible(True) for direction in ("left", "right", "bottom", "top"): ax.axis[direction].set_visible(False)

3fee7584e2f03049f4dec0ccdf4055cb0e38e05b

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

def test_axisline_style_size_color(): f

test_axisline_style_size_color

tests/components/zwave_js/conftest.py

Fix zwave_js addon info (#76044) * Add add-on store info command * Use add-on store info command in zwave_js * Fix init tests * Update tests * Fix method for addon store info * Fix response parsing * Fix store addon installed response parsing * Remove addon info log that can contain network keys * Add supervisor store addon info test * Default to version None if add-on not installed Co-authored-by: Mike Degatano <michael.degatano@gmail.com> Co-authored-by: Mike Degatano <michael.degatano@gmail.com>

core

Python

conftest.py

def mock_addon_running(addon_store_info, addon_info): addon_store_info.return_value = { "installed": "1.0.0", "state": "started", "version": "1.0.0", } addon_info.return_value["state"] = "started" addon_info.return_value["version"] = "1.0.0" return addon_info @pytest.fixture(name="addon_installed")

842cc060f80a632032dacbe1e2eaa8ca6421eda0

@pytest.fixture(name="addon_installed")

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

def mock_addon_running(addon_store_info, addon_info): addon_store_info.return_value = { "installed": "1.0.0", "state": "started", "version": "1.0.0", } addon_info.return_value["state"] = "started" addon_info.return_value["version"] = "1.0.0" retur

mock_addon_running

release/tune_tests/cloud_tests/workloads/_tune_script.py

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

ray

Python

_tune_script.py

def fn_trainable(config, checkpoint_dir=None): if checkpoint_dir: with open(os.path.join(checkpoint_dir, "checkpoint.json"), "rt") as fp: state = json.load(fp) else: state = {"internal_iter": 0} for i in range(state["internal_iter"], config["max_iterations"]): state["internal_iter"] = i time.sleep(config["sleep_time"]) if i % config["checkpoint_freq"] == 0: with tune.checkpoint_dir(step=i) as cd: with open(os.path.join(cd, "checkpoint.json"), "wt") as fp: json.dump(state, fp) tune.report( score=i * 10 * config["score_multiplied"], internal_iter=state["internal_iter"], )

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

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

def fn_trainable(config, checkpoint_dir=None): if checkpoint_dir: with open(os.path.join(checkpoint_dir, "checkpoint.json"), "rt") as fp: state = json.load(fp) else: state = {"internal_iter": 0} for i in range(state["internal_iter"], config["max_iterations"]): state["internal_iter"] = i time.sleep(config["sleep_time"]) if i % config["checkpoint_freq"] == 0: with tune.checkpoint_dir(step=i) as cd: with open(os.path.join(cd, "checkpoint.json"), "wt") as fp:

fn_trainable

wagtail/search/backends/elasticsearch5.py

Reformat with black

wagtail

Python

elasticsearch5.py

def get_content_type(self): return self.model._meta.app_label + "." + self.model.__name__

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def get_content_type(self): return self.model.

get_content_type

pandas/tests/arrays/test_datetimes.py

BUG: DatetimeArray.astype(Sparse) (#50082) * BUG: DatetimeArray.astype(Sparse) * GH ref

pandas

Python

test_datetimes.py

def test_astype_to_sparse_dt64(self): # GH#50082 dti = pd.date_range("2016-01-01", periods=4) dta = dti._data result = dta.astype("Sparse[datetime64[ns]]") assert result.dtype == "Sparse[datetime64[ns]]" assert (result == dta).all()

7c208c8907f5ab18f807366c0c5e26ae1dbca299

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

def test_astype_to_sparse_dt64(self): # GH#50082 dti = pd.date_range("2016-01-01", periods=4) dta = dti._data result =

test_astype_to_sparse_dt64

src/pip/_vendor/colorama/tests/ansitowin32_test.py

Upgrade colorama to 0.4.6

pip

Python

ansitowin32_test.py

def testCallWin32UsesLookup(self): listener = Mock() stream = AnsiToWin32(listener) stream.win32_calls = { 1: (lambda *_, **__: listener(11),), 2: (lambda *_, **__: listener(22),), 3: (lambda *_, **__: listener(33),), } stream.call_win32('m', (3, 1, 99, 2)) self.assertEqual( [a[0][0] for a in listener.call_args_list], [33, 11, 22] )

8cda1c34eb865c1be5b72e8295f7ca7adfdeb113

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

def testCallWin32UsesLookup(self): listener = Mock() stream = AnsiToWin32(listener) stream.win32_calls = { 1: (lambda *_, **__: listener(11),), 2: (lambda *_, **__: listener(22),), 3: (lambda *_, **__: listener(33),), } stream.call_win32('m', (3, 1, 99, 2)) self.assertEqual( [a[0][0] for a in listener.call_args_list], [33, 11

testCallWin32UsesLookup

wagtail/core/models/__init__.py

Reformat with black

wagtail

Python

__init__.py

def active(self): return self.filter( Q(status=WorkflowState.STATUS_IN_PROGRESS) | Q(status=WorkflowState.STATUS_NEEDS_CHANGES) )

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def active(self): return self.filter( Q(status=

active

homeassistant/components/traccar/device_tracker.py

Bump pytraccar to 1.0.0 (#75671)

core

Python

device_tracker.py

async def import_events(self): start_intervel = datetime.utcnow() events = await self._api.get_reports_events( devices=[device.id for device in self._devices], start_time=start_intervel, end_time=start_intervel - self._scan_interval, event_types=self._event_types.keys(), ) if events is not None: for event in events: self._hass.bus.async_fire( f"traccar_{self._event_types.get(event.type)}", { "device_traccar_id": event.device_id, "device_name": next( ( dev.name for dev in self._devices if dev.id == event.device_id ), None, ), "type": event.type, "serverTime": event.event_time, "attributes": event.attributes, }, )

e87c2b9e2590eadcaa14f7256388675fcc64918d

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

async def import_events(self): start_intervel = datetime.utcnow() events = await self._api.get_reports_events( devices=[device.id for device in self._devices], start_time=start_intervel, end_time=start_intervel - self._scan_interval, event_types=self._event_types.keys(), ) if events is not None: for event in events: self._hass.bus.async_fire( f"traccar_{self._event_types.get(event.type)}", { "device_traccar_id": event.device_id, "device_name": next( ( dev.name for dev in self._devices

import_events

sandbox/vertical_container.py

[layouts] Fix vertical layout bug with centered content

textual

Python

vertical_container.py

async def action_remove_placeholder(self): placeholders = self.query("Placeholder") placeholders_count = len(placeholders) for i, placeholder in enumerate(placeholders): if i == placeholders_count - 1: await self.remove(placeholder) placeholder.parent.children._nodes.remove(placeholder) self.refresh(repaint=True, layout=True) self.refresh_css()

2d25807f495d2fbd64eb0909b1320ad0cc8e7b7d

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

async def action_remove_placeholder(self): placeholders = self.query(

action_remove_placeholder

doc/source/tutorial/examples/morphology_binary_dilation_erosion.py

DOC: added example for morphology: generate_binary_structure, binary_dilation and erosion (#15244) Co-authored-by: Pamphile Roy <roy.pamphile@gmail.com>

scipy

Python

morphology_binary_dilation_erosion.py

def ball(radius, dtype=np.uint8): n = 2 * radius + 1 Z, Y, X = np.mgrid[ -radius: radius: n * 1j, -radius: radius: n * 1j, -radius: radius: n * 1j ] s = X ** 2 + Y ** 2 + Z ** 2 return np.array(s <= radius * radius, dtype=dtype)

a0d44d5be19a84b4cb1984eb795dd0266f665c76

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

def ball(radius, dtype=np.uint8): n = 2 * radius + 1 Z, Y, X = np.mgrid[ -radius: radius: n * 1j, -radius: radius: n * 1j, -radius: radius: n * 1j ] s = X ** 2 + Y ** 2 + Z ** 2 return np.array(s

ball

tests/unit_tests/chains/test_react.py

Harrison/add react chain (#24) from https://arxiv.org/abs/2210.03629 still need to think if docstore abstraction makes sense

langchain

Python

test_react.py

def test_predict_until_observation_error() -> None: outputs = ["foo\nAction 1: foo"] fake_llm = FakeListLLM(outputs) fake_llm_chain = LLMChain(llm=fake_llm, prompt=_FAKE_PROMPT) with pytest.raises(ValueError): predict_until_observation(fake_llm_chain, "", 1)

ce7b14b84381c766ae42a0f71953b2a56c024dbb

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

def test_predict_until_observation_error() -> None: outputs = ["foo\nAction

test_predict_until_observation_error

tests/onnx/test_onnx_v2.py

Add support for Perceiver ONNX export (#17213) * Start adding perceiver support for ONNX * Fix pad token bug for fast tokenizers * Fix formatting * Make get_preprocesor more opinionated (processor priority, otherwise tokenizer/feature extractor) * Clean docs format * Minor cleanup following @sgugger's comments * Fix typo in docs * Fix another docs typo * Fix one more typo in docs * Update src/transformers/onnx/utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/onnx/utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/onnx/utils.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

transformers

Python

test_onnx_v2.py

def _onnx_export(self, test_name, name, model_name, feature, onnx_config_class_constructor, device="cpu"): from transformers.onnx import export model_class = FeaturesManager.get_model_class_for_feature(feature) config = AutoConfig.from_pretrained(model_name) model = model_class.from_config(config) onnx_config = onnx_config_class_constructor(model.config) if is_torch_available(): from transformers.utils import torch_version if torch_version < onnx_config.torch_onnx_minimum_version: pytest.skip( "Skipping due to incompatible PyTorch version. Minimum required is" f" {onnx_config.torch_onnx_minimum_version}, got: {torch_version}" ) preprocessor = get_preprocessor(model_name) # Useful for causal lm models that do not use pad tokens. if isinstance(preprocessor, PreTrainedTokenizerBase) and not getattr(config, "pad_token_id", None): config.pad_token_id = preprocessor.eos_token_id with NamedTemporaryFile("w") as output: try: onnx_inputs, onnx_outputs = export( preprocessor, model, onnx_config, onnx_config.default_onnx_opset, Path(output.name), device=device ) validate_model_outputs( onnx_config, preprocessor, model, Path(output.name), onnx_outputs, onnx_config.atol_for_validation, ) except (RuntimeError, ValueError) as e: self.fail(f"{name}, {feature} -> {e}")

babeff5524bf3d5d62cfa70e1297158a755b0810

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

def _onnx_export(self, test_name, name, model_name, feature, onnx_config_class_constructor, device="cpu"): from transformers.onnx import export model_class = FeaturesManager.get_model_class_for_feature(feature) config = AutoConfig.from_pretrained(model_name) model = model_class.from_config(config) onnx_config = onnx_config_class_constructor(model.config) if is_torch_available(): from transformers.utils import torch_version if torch_version < onnx_config.torch_onnx_minimum_version: pytest.skip( "Skipping due to incompatible PyTorch version. Minimum required is" f" {onnx_config.torch_onnx_minimum_version}, got: {torch_version}" ) preprocessor = get_preprocessor(model_name) # Useful for causal lm models that do not use pad tokens. if isinstance(preprocessor, PreTrainedTokenizerBase) and not getattr(config, "pad_token_id", None): config.pad_token_id = preprocessor.eos_token_id with NamedTemporaryFile("w") as output: try: onnx_inputs, onnx_outputs = export( preprocessor, model, onnx_config, onnx_config.default_onnx_opset, Path(output.name), device=device ) validate_model_outputs( onnx_config, preprocessor, model, Path(output.name), onnx_outputs, onnx_config.atol_for_validation, ) except (RuntimeError, Valu

_onnx_export

.venv/lib/python3.8/site-packages/pip/_internal/resolution/resolvelib/candidates.py

upd; format

transferlearning

Python

candidates.py

def __eq__(self, other): # type: (Any) -> bool if isinstance(other, self.__class__): return links_equivalent(self._link, other._link) return False

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

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

def __eq__(self, other): # type: (Any) -> bool if isinstance(other, self.__class__): return links_equivalent(self._link, other._link) ret

__eq__

wagtail/admin/tests/tests.py

Refine dashboard design - summary panels * Update colours and icons for summary panels * add h1 id for aria referencing * rework layout to use flex box & not floats * move summary styles to own component scss file * now functions correctly in RTL mode

wagtail

Python

tests.py

def test_summary_items(self): response = self.client.get(reverse("wagtailadmin_home")) self.assertEqual(response.status_code, 200) self.assertContains(response, "<li>0 broken links</li>") # check that media attached to summary items is correctly pulled in if DJANGO_VERSION >= (4, 1): self.assertContains( response, '<link href="/static/testapp/css/broken-links.css" media="all" rel="stylesheet">', html=True, ) else: self.assertContains( response, '<link href="/static/testapp/css/broken-links.css" type="text/css" media="all" rel="stylesheet">', html=True, )

22e904fb01e0206f95019f0c8ea0db80c7d4efc8

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

def test_summary_items(self): response = self.client.get(reverse("wagtailadmin_home")) self.assertEqual(response.status_code, 200) self.assertContains(response, "<li>0 broken links</li>") #

test_summary_items

src/pip/_internal/metadata/importlib.py

Try to cover Path interface differences

pip

Python

importlib.py

def canonical_name(self) -> NormalizedName: # Try to get the name from the metadata directory name. This is much # faster than reading metadata. if self._info_location is None: return self._get_dist_normalized_name() stem, suffix = os.path.splitext(self._info_location.name) if suffix not in (".dist-info", ".egg-info"): return self._get_dist_normalized_name() name, _, _ = stem.partition("-") return canonicalize_name(name)

846d8e59654078ecc020933ca82e6f1ff2bb44ca

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

def canonical_name(self) -> NormalizedName: # Try to get the name from the metadata directory name. This is much # faster than reading metadata. if self._info_location is None: return self._get_dist_normalized_name() stem, suffix = os.path.splitext(self._info_location.name) if suffix not in (".dist-info", ".egg-info"): return self._get_dist_normalized_name() name, _, _ = stem.partition("-")

canonical_name

cps/web.py

Better epub cover parsing with multiple cover-image items Code cosmetics renamed variables refactored xml page generation refactored prepare author

calibre-web

Python

web.py

def render_adv_search_results(term, offset=None, order=None, limit=None): sort_param = order[0] if order else [db.Books.sort] pagination = None cc = get_cc_columns(filter_config_custom_read=True) calibre_db.session.connection().connection.connection.create_function("lower", 1, db.lcase) if not config.config_read_column: query = (calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, ub.ReadBook).select_from(db.Books) .outerjoin(ub.ReadBook, and_(db.Books.id == ub.ReadBook.book_id, int(current_user.id) == ub.ReadBook.user_id))) else: try: read_column = cc[config.config_read_column] query = (calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, read_column.value) .select_from(db.Books) .outerjoin(read_column, read_column.book == db.Books.id)) except (KeyError, AttributeError): log.error("Custom Column No.%d is not existing in calibre database", config.config_read_column) # Skip linking read column query = calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, None) query = query.outerjoin(ub.ArchivedBook, and_(db.Books.id == ub.ArchivedBook.book_id, int(current_user.id) == ub.ArchivedBook.user_id)) q = query.outerjoin(db.books_series_link, db.Books.id == db.books_series_link.c.book) \ .outerjoin(db.Series) \ .filter(calibre_db.common_filters(True)) # parse multiselects to a complete dict tags = dict() elements = ['tag', 'serie', 'shelf', 'language', 'extension'] for element in elements: tags['include_' + element] = term.get('include_' + element) tags['exclude_' + element] = term.get('exclude_' + element) author_name = term.get("author_name") book_title = term.get("book_title") publisher = term.get("publisher") pub_start = term.get("publishstart") pub_end = term.get("publishend") rating_low = term.get("ratinghigh") rating_high = term.get("ratinglow") description = term.get("comment") read_status = term.get("read_status") if author_name: author_name = author_name.strip().lower().replace(',', '|') if book_title: book_title = book_title.strip().lower() if publisher: publisher = publisher.strip().lower() search_term = [] cc_present = False for c in cc: if c.datatype == "datetime": column_start = term.get('custom_column_' + str(c.id) + '_start') column_end = term.get('custom_column_' + str(c.id) + '_end') if column_start: search_term.extend([u"{} >= {}".format(c.name, format_date(datetime.strptime(column_start, "%Y-%m-%d").date(), format='medium', locale=get_locale()) )]) cc_present = True if column_end: search_term.extend([u"{} <= {}".format(c.name, format_date(datetime.strptime(column_end, "%Y-%m-%d").date(), format='medium', locale=get_locale()) )]) cc_present = True elif term.get('custom_column_' + str(c.id)): search_term.extend([(u"{}: {}".format(c.name, term.get('custom_column_' + str(c.id))))]) cc_present = True if any(tags.values()) or author_name or book_title or \ publisher or pub_start or pub_end or rating_low or rating_high \ or description or cc_present or read_status: search_term, pub_start, pub_end = extend_search_term(search_term, author_name, book_title, publisher, pub_start, pub_end, tags, rating_high, rating_low, read_status) # q = q.filter() if author_name: q = q.filter(db.Books.authors.any(func.lower(db.Authors.name).ilike("%" + author_name + "%"))) if book_title: q = q.filter(func.lower(db.Books.title).ilike("%" + book_title + "%")) if pub_start: q = q.filter(func.datetime(db.Books.pubdate) > func.datetime(pub_start)) if pub_end: q = q.filter(func.datetime(db.Books.pubdate) < func.datetime(pub_end)) q = adv_search_read_status(q, read_status) if publisher: q = q.filter(db.Books.publishers.any(func.lower(db.Publishers.name).ilike("%" + publisher + "%"))) q = adv_search_text(q, tags['include_tag'], tags['exclude_tag'], db.Tags.id) q = adv_search_text(q, tags['include_serie'], tags['exclude_serie'], db.Series.id) q = adv_search_text(q, tags['include_extension'], tags['exclude_extension'], db.Data.format) q = adv_search_shelf(q, tags['include_shelf'], tags['exclude_shelf']) q = adv_search_language(q, tags['include_language'], tags['exclude_language'], ) q = adv_search_ratings(q, rating_high, rating_low, ) if description: q = q.filter(db.Books.comments.any(func.lower(db.Comments.text).ilike("%" + description + "%"))) # search custom culumns try: q = adv_search_custom_columns(cc, term, q) except AttributeError as ex: log.error_or_exception(ex) flash(_("Error on search for custom columns, please restart Calibre-Web"), category="error") q = q.order_by(*sort_param).all() flask_session['query'] = json.dumps(term) ub.store_combo_ids(q) result_count = len(q) if offset is not None and limit is not None: offset = int(offset) limit_all = offset + int(limit) pagination = Pagination((offset / (int(limit)) + 1), limit, result_count) else: offset = 0 limit_all = result_count entries = calibre_db.order_authors(q[offset:limit_all], list_return=True, combined=True) return render_title_template('search.html', adv_searchterm=search_term, pagination=pagination, entries=entries, result_count=result_count, title=_(u"Advanced Search"), page="advsearch", order=order[1]) @web.route("/advsearch", methods=['GET']) @login_required_if_no_ano

4545f4a20d9ff90b99bbd4e3e34b6de4441d6367

@web.route("/advsearch", methods=['GET']) @login_required_if_no_ano

https://github.com/janeczku/calibre-web.git

def render_adv_search_results(term, offset=None, order=None, limit=None): sort_param = order[0] if order else [db.Books.sort] pagination = None cc = get_cc_columns(filter_config_custom_read=True) calibre_db.session.connection().connection.connection.create_function("lower", 1, db.lcase) if not config.config_read_column: query = (calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, ub.ReadBook).select_from(db.Books) .outerjoin(ub.ReadBook, and_(db.Books.id == ub.ReadBook.book_id, int(current_user.id) == ub.ReadBook.user_id))) else: try: read_column = cc[config.config_read_column] query = (calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, read_column.value) .select_from(db.Books) .outerjoin(read_column, read_column.book == db.Books.id)) except (KeyError, AttributeError): log.error("Custom Column No.%d is not existing in calibre database", config.config_read_column) # Skip linking read column query = calibre_db.session.query(db.Books, ub.ArchivedBook.is_archived, None) query = query.outerjoin(ub.ArchivedBook, and_(db.Books.id == ub.ArchivedBook.book_id, int(current_user.id) == ub.ArchivedBook.user_id)) q = query.outerjoin(db.books_series_link, db.Books.id == db.books_series_link.c.book) \ .outerjoin(db.Series) \ .filter(calibre_db.common_filters(True)) # parse multiselects to a complete dict tags = dict() elements = ['tag', 'serie', 'shelf', 'language', 'extension'] for element in elements: tags['include_' + element] = term.get('include_' + element) tags['exclude_' + element] = term.get('exclude_' + element) author_name = term.get("author_name") book_title = term.get("book_title") publisher = term.get("publisher") pub_start = term.get("publishstart") pub_end = term.get("publishend") rating_low = term.get("ratinghigh") rating_high = term.get("ratinglow") description = term.get("comment") read_status = term.get("read_status") if author_name: author_name = author_name.strip().lower().replace(',', '|') if book_title: book_title = book_title.strip().lower() if publisher: publisher = publisher.strip().lower() s

render_adv_search_results

django/core/management/commands/migrate.py

Refs #33476 -- Reformatted code with Black.

django

Python

migrate.py

def migration_progress_callback(self, action, migration=None, fake=False): if self.verbosity >= 1: compute_time = self.verbosity > 1 if action == "apply_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Applying %s..." % migration, ending="") self.stdout.flush() elif action == "apply_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) if fake: self.stdout.write(self.style.SUCCESS(" FAKED" + elapsed)) else: self.stdout.write(self.style.SUCCESS(" OK" + elapsed)) elif action == "unapply_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Unapplying %s..." % migration, ending="") self.stdout.flush() elif action == "unapply_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) if fake: self.stdout.write(self.style.SUCCESS(" FAKED" + elapsed)) else: self.stdout.write(self.style.SUCCESS(" OK" + elapsed)) elif action == "render_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Rendering model states...", ending="") self.stdout.flush() elif action == "render_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) self.stdout.write(self.style.SUCCESS(" DONE" + elapsed))

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def migration_progress_callback(self, action, migration=None, fake=False): if self.verbosity >= 1: compute_time = self.verbosity > 1 if action == "apply_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Applying %s..." % migration, ending="") self.stdout.flush() elif action == "apply_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) if fake: self.stdout.write(self.style.SUCCESS(" FAKED" + elapsed)) else: self.stdout.write(self.style.SUCCESS(" OK" + elapsed)) elif action == "unapply_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Unapplying %s..." % migration, ending="") self.stdout.flush() elif action == "unapply_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) if fake: self.stdout.write(self.style.SUCCESS(" FAKED" + elapsed)) else: self.stdout.write(self.style.SUCCESS(" OK" + elapsed)) elif action == "render_start": if compute_time: self.start = time.monotonic() self.stdout.write(" Rendering model states...", ending="") self.stdout.flush() elif action == "render_success": elapsed = ( " (%.3fs)" % (time.monotonic() - self.start) if compute_time else "" ) self.stdout.write(self.style.SUCCESS(" DONE" + elapsed))

migration_progress_callback

test/test_pipeline.py

Refactor Pipeline peripherals (#2253) * move peripheral stuff to utils, add more and better tests * Update Documentation & Code Style * move config related peripherals to config module, fix tests * Update Documentation & Code Style * remove unnecessary list comprehensions * apply ZanSara's feedback * remove classes in pipeline utils Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

haystack

Python

test_pipeline.py

def test_validate_pipeline_config_invalid_component_param_key(): with pytest.raises(ValueError, match="is not a valid config variable name"): validate_config({"components": [{"name": "test", "type": "test", "params": {"\btest": "test"}}]})

f7a01624e0581a05800ed31ddb1bbb32b169b256

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

def test_validate_pipeline_config_invalid_component_param_key(): with pytest.raises(ValueError, match="is not a valid config variable name"): validate_config({"components"

test_validate_pipeline_config_invalid_component_param_key

erpnext/payroll/doctype/additional_salary/additional_salary.py

style: format code with black

erpnext

Python

additional_salary.py

def get_additional_salaries(employee, start_date, end_date, component_type): comp_type = "Earning" if component_type == "earnings" else "Deduction" additional_sal = frappe.qb.DocType("Additional Salary") component_field = additional_sal.salary_component.as_("component") overwrite_field = additional_sal.overwrite_salary_structure_amount.as_("overwrite") additional_salary_list = ( frappe.qb.from_(additional_sal) .select( additional_sal.name, component_field, additional_sal.type, additional_sal.amount, additional_sal.is_recurring, overwrite_field, additional_sal.deduct_full_tax_on_selected_payroll_date, ) .where( (additional_sal.employee == employee) & (additional_sal.docstatus == 1) & (additional_sal.type == comp_type) ) .where( additional_sal.payroll_date[start_date:end_date] | ((additional_sal.from_date <= end_date) & (additional_sal.to_date >= end_date)) ) .run(as_dict=True) ) additional_salaries = [] components_to_overwrite = [] for d in additional_salary_list: if d.overwrite: if d.component in components_to_overwrite: frappe.throw( _( "Multiple Additional Salaries with overwrite property exist for Salary Component {0} between {1} and {2}." ).format(frappe.bold(d.component), start_date, end_date), title=_("Error"), ) components_to_overwrite.append(d.component) additional_salaries.append(d) return additional_salaries

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def get_additional_salaries(employee, start_date, end_date, component_type): comp_type = "Earning" if component_type == "earnings" else "Deduction" additional_sal = frappe.qb.DocType("Additional Salary") component_field = additional_sal.salary_component.as_("component") overwrite_field = additional_sal.overwrite_salary_structure_amount.as_("overwrite") additional_salary_list = ( frappe.qb.from_(additional_sal) .select( additional_sal.name, component_field, additional_sal.type, additional_sal.amount, additional_sal.is_recurring, overwrite_field, additional_sal.deduct_full_tax_on_selected_payroll_date, ) .where( (additional_sal.employee == employee) & (additional_sal.docstatus == 1) & (additional_sal.type == comp_type) ) .where( additional_sal.payroll_date[start_date:end_date] |

get_additional_salaries

tests/admin_scripts/management/commands/label_command.py

Refs #33476 -- Reformatted code with Black.

django

Python

label_command.py

def handle_label(self, label, **options): print( "EXECUTE:LabelCommand label=%s, options=%s" % (label, sorted(options.items())) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def handle_label(self, label, **options):

handle_label

youtube_dl/jsinterp.py

[jsinterp] Improve JS language support (#31175) * operator ?? * operator ?. * operator ** * accurate operator functions * `undefined` handling * object literals {a: 1, "b": expr} * more tests for weird JS comparisons: see https://github.com/ytdl-org/youtube-dl/issues/31173#issuecomment-1217854397.

youtube-dl

Python

jsinterp.py

def _all_operators(): return itertools.chain( # Ref: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Operator_Precedence _SC_OPERATORS, _LOG_OPERATORS, _COMP_OPERATORS, _OPERATORS)

b0a60ce2032172aeaaf27fe3866ab72768f10cb2

https://github.com/ytdl-org/youtube-dl.git

def _all_operators(): return itertools.chain( # Ref: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/Operator_Precedence

_all_operators

tests/end2end/fixtures/quteprocess.py

qt6 tests: Fix remaining PyQt5 references

qutebrowser

Python

quteprocess.py

def wait_scroll_pos_changed(self, x=None, y=None): __tracebackhide__ = (lambda e: e.errisinstance(testprocess.WaitForTimeout)) if (x is None and y is not None) or (y is None and x is not None): raise ValueError("Either both x/y or neither must be given!") if x is None and y is None: point = 'Py*.QtCore.QPoint(*, *)' # not counting 0/0 here elif x == '0' and y == '0': point = 'Py*.QtCore.QPoint()' else: point = 'Py*.QtCore.QPoint({}, {})'.format(x, y) self.wait_for(category='webview', message='Scroll position changed to ' + point)

deb21acdebd77c6dc6d5fe4d8cad75e4ca074138

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

def wait_scroll_pos_changed(self, x=None, y=None): __tracebackhide__ = (lambda e: e.errisinstance(testprocess.WaitForTimeout)) if (x is None and y is not None) or (y is None and x is not None): raise ValueError("Either both x/y or neither must be given!") if x is None and y is None: point = 'Py*.QtCore.QPoint(*, *)' # not counting 0/0 here elif x == '0' and y

wait_scroll_pos_changed

tests/plugins/test_rtve.py

plugins.rtve: fix ZTNR.translate

streamlink

Python

test_rtve.py

def test_translate_has_streams(): # real payload with modified end (IEND chunk of size 0), to reduce test size data = \ "iVBORw0KGgoAAAANSUhEUgAAAVQAAAFUCAIAAAD08FPiAAACr3RFWHRXczlVSWdtM2ZPTGY4b2R4" \ "dWo5aHZnRlRhOndvZEtxN3pLOG5oNGRpbT1vREBTWHhOMGtzUVomNndAWkV5cz1GOUlCSiYxdDcy" \ "QmdDOFM2NGFVJmh1Nzk2bUpwOFVJOE1DJlpAY2lzdGcmbEUmRE5DZFV4SHpEOFgvLmppZ1l4b3M1" \ "QU1lOnl3ZS04VlBwQkZvLlFMUWZHTy1vQjNVeHhfVDF1JkRSQTpPP2J4Wm0zbFlxS3IjAEhEX1JF" \ "QURZJSUwNTYwNzI4Mjg4MzUyNjQyMzUxMTA0Mzg0NzI4NzY4NDEyODAzODU0ODMwMDQ3NzcwNDEx" \ "MDAyODE1MzM3NDU3ODAxMDg3MjgxNTg1MzMzNDE3MTYxMTE4NzQ1MTU3MjYxOTUwNzI4NzEyNDgw" \ "MzI4NTM1ODM1ODU3MzQyNzE0NjcyODE2NTgzNDI4NTE0NTg1MzIwMzgxODU3NDY0NzUwODI3OTQ0" \ "ODg3NjEzMTUzNDMxMTUxNzYzNDU1NzE0MDA1MDUzNDIxODE0ODYyNDIzODM2MTczMzQ0NjAwNTIw" \ "NTU2NDYyNDgxODYzNDA2MzA4MTE0ODUxMTQ2Mzg2MzYyMjQ4Mjc3MjIyMjUzNjMxMjI1MjEzMTU0" \ "NjI1NjIyMjM3MTA4NjEwNjI0NTYyNTMxNTA2ODEyMjQ2MzYzNzE0MzY4MDU1MTgxNTQ2NTU3MTMx" \ "NTI0NzU4MTU2NjAxMjY0MjA1MDU2MzcwMDM3NzcwMjA0MTYxMzE3MjQxMTI2NzYzMzUyNjY3NTQ1" \ "NTA1MTUxNTc2NTEzMTUwNjcxNDcyMDI2MTQyMjczNTI4NzExNjA4NTU3NjIzMzMxMzU0NDM1Mzgw" \ "MTI0MTQzMTU1MTMyNzc4ODI1MjcyMjUwMjY4MzYyMDUzMjQzNjA0MTYyMzkhB8fSAAAAAElFTkQAAAAACg==" assert list(ZTNR.translate(data)) == [ ( "HD_READY", "https://rtvehlsvodlote7modo2.rtve.es/mediavodv2/resources/TE_NGVA/mp4/5/3/1656573649835.mp4/video.m3u8" + "?hls_no_audio_only=true&idasset=6638770" ), ]

8bd58c047ca38e9bb639a6948e45b4387fc5d147

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

def test_translate_has_streams(): # real payload with modified end (IEND chunk of size 0), to reduce test size data = \ "iVBORw0KGgoAAAANSUhEUgAAAVQAAAFUCAIAAAD08FPiAAACr3RFWHRXczlVSWdtM2ZPTGY4b2R4" \ "dWo5aHZnRlRhOndvZEtxN3pLOG5oNGRpbT1vREBTWHhOMGtzUVomNndAWkV5cz1GOUlCSiYxdDcy" \ "QmdDOFM2NGFVJmh1Nzk2bUpwOFVJOE1DJlpAY2lzdGcmbEUmRE5DZFV4SHpEO

test_translate_has_streams

tests/storage/test_event_federation.py

Fix overflows in /messages backfill calculation (#13936) * Reproduce bug * Compute `least_function` first * Substitute `least_function` with an f-string * Bugfix: avoid overflow Co-authored-by: Eric Eastwood <erice@element.io>

synapse

Python

test_event_federation.py

def test_get_insertion_event_backward_extremities_in_room(self): setup_info = self._setup_room_for_insertion_backfill_tests() room_id = setup_info.room_id depth_map = setup_info.depth_map # Try at "insertion_eventB" backfill_points = self.get_success( self.store.get_insertion_event_backward_extremities_in_room( room_id, depth_map["insertion_eventB"], limit=100 ) ) backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points] self.assertEqual(backfill_event_ids, ["insertion_eventB", "insertion_eventA"]) # Try at "insertion_eventA" backfill_points = self.get_success( self.store.get_insertion_event_backward_extremities_in_room( room_id, depth_map["insertion_eventA"], limit=100 ) ) backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points] # Event "2" has a depth of 2 but is not included here because we only # know the approximate depth of 5 from our event "3". self.assertListEqual(backfill_event_ids, ["insertion_eventA"])

e8f30a76caa4394ebb3e77c56df951e3626b3fdd

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

def test_get_insertion_event_backward_extremities_in_room(self): setup_info = self._setup_room_for_insertion_backfill_tests() room_id = setup_info.room_id depth_map = setup_info.depth_map # Try at "insertion_eventB" backfill_points = self.get_success( self.store.get_insertion_event_backward_extremities_in_room( room_id, depth_map["insertion_eventB"], limit=100 ) ) backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points] self.assertEqual(backfill_event_ids, ["insertion_eventB", "insertion_eventA"]) # Try at "insertion_eventA" backfill_points = self.get_success( self.store.get_insertion_event_backward_extremities_in_room( room_id, depth_map["insertion_eventA"], limit=100 ) ) backfill_event_ids = [backfill_point[0] for backfill_point in backfill_points] # Event "2" has a depth of 2 but is not included here because we only # know the approximate depth of 5 from our event "3". self.assertListEqual(backfill_event_ids, ["insertion_eventA"])

test_get_insertion_event_backward_extremities_in_room

erpnext/education/doctype/topic/topic.py

style: format code with black

erpnext

Python

topic.py

def add_topic_to_courses(topic, courses, mandatory=False): courses = json.loads(courses) for entry in courses: course = frappe.get_doc("Course", entry) course.append("topics", {"topic": topic, "topic_name": topic}) course.flags.ignore_mandatory = True course.save() frappe.db.commit() frappe.msgprint( _("Topic {0} has been added to all the selected courses successfully.").format( frappe.bold(topic) ), title=_("Courses updated"), indicator="green", ) @frappe.whitelist()

494bd9ef78313436f0424b918f200dab8fc7c20b

@frappe.whitelist()

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

def add_topic_to_courses(topic, courses, mandatory=False): courses = json.loads(courses) for entry in courses: course = frappe.get_doc("Course", entry) course.append("topics", {"topic": topic, "topic_name": topic}) course.flags.ignore_mandatory = True course.save() frappe.db.commit() frappe.msgprint( _("Topic {0} has been added to all the selected courses successfully.").format( frappe.bold(

add_topic_to_courses

lib/matplotlib/widgets.py

Fix drawing animated artists changed in selector callback

matplotlib

Python

widgets.py

def update(self): if not self.ax.get_visible() or self.ax.figure._cachedRenderer is None: return False if self.useblit: if self.background is not None: self.canvas.restore_region(self.background) else: self.update_background(None) for artist in self.artists + self._get_animated_artists(): if artist.stale: self.ax.draw_artist(artist) self.canvas.blit(self.ax.bbox) else: self.canvas.draw_idle() return False

da31ed386482845629a8505f81810ddb341514fb

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

def update(self): if not self.ax.get_visible() or self.ax.figure._cachedRenderer is None: return False if self.useblit: if self.background is not None: self.canvas.restore_region(self.background) else: self.update_background(None) for artist in self.artists + self._get_animated_artists(): if artist.stale:

update

langchain/llms/huggingface_hub.py

Harrison/llm saving (#331) Co-authored-by: Akash Samant <70665700+asamant21@users.noreply.github.com>

langchain

Python

huggingface_hub.py

def _identifying_params(self) -> Mapping[str, Any]: _model_kwargs = self.model_kwargs or {} return { **{"repo_id": self.repo_id, "task": self.task}, **{"model_kwargs": _model_kwargs}, }

9bb7195085a843db3f53e4fd9a51c79f3698a19d

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

def _identifying_params(self) -> Mapping[str, Any]: _mod

_identifying_params

mkdocs/tests/config/config_options_tests.py

Refactor config_options_tests to use less implementation details Prevent missed warnings, test more error messages. And minor fixes to error messages themselves.

mkdocs

Python

config_options_tests.py

def test_invalid_children_config_int(self): with self.expect_error(option="Expected nav to be a list, got a int: 1"): self.get_config(self.Schema, {'option': [{"foo.md": [{"bar.md": 1}]}]})

3fd48806aa3fe6c571e0669afcbc4327f4c032e4

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

def test_invalid_children_config_int(self): with self.expect_error(option="Expected nav to be a list, got a int: 1"): self.get

test_invalid_children_config_int

octavia-cli/integration_tests/conftest.py

🐛 octavia-cli: use `list` endpoint instead of `list_latest` (#11505)

airbyte

Python

conftest.py

def destination_state_path(octavia_test_project_directory): state_path = f"{octavia_test_project_directory}/destinations/postgres/state.yaml" silent_remove(state_path) yield state_path silent_remove(state_path) @pytest.fixture(scope="session")

9f21fae6684e6833e8896d017cd5c859046b61a7

@pytest.fixture(scope="session")

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

def destination_state_path(octavia_test_project_directory): state_path = f"{octavia_test_project_directory}/destinations/postgres/state.yaml" silent_remove(state_path) yield state_path

destination_state_path

homeassistant/components/squeezebox/media_player.py

Update integrations to pass target player when resolving media (#72597)

core

Python

media_player.py

async def async_play_media(self, media_type, media_id, **kwargs): cmd = "play" index = None if kwargs.get(ATTR_MEDIA_ENQUEUE): cmd = "add" if media_source.is_media_source_id(media_id): media_type = MEDIA_TYPE_MUSIC play_item = await media_source.async_resolve_media( self.hass, media_id, self.entity_id ) media_id = play_item.url if media_type in MEDIA_TYPE_MUSIC: if not media_id.startswith(SQUEEZEBOX_SOURCE_STRINGS): # do not process special squeezebox "source" media ids media_id = async_process_play_media_url(self.hass, media_id) await self._player.async_load_url(media_id, cmd) return if media_type == MEDIA_TYPE_PLAYLIST: try: # a saved playlist by number payload = { "search_id": int(media_id), "search_type": MEDIA_TYPE_PLAYLIST, } playlist = await generate_playlist(self._player, payload) except ValueError: # a list of urls content = json.loads(media_id) playlist = content["urls"] index = content["index"] else: payload = { "search_id": media_id, "search_type": media_type, } playlist = await generate_playlist(self._player, payload) _LOGGER.debug("Generated playlist: %s", playlist) await self._player.async_load_playlist(playlist, cmd) if index is not None: await self._player.async_index(index)

087c0b59edb4f6233849e2cf6eb9057474251934

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

async def async_play_media(self, media_type, media_id, **kwargs): cmd = "play" index = None if kwargs.get(ATTR_MEDIA_ENQUEUE): cmd = "add" if media_source.is_media_source_id(media_id): media_type = MEDIA_TYPE_MUSIC play_item = await media_source.async_resolve_media( self.hass, media_id, self.entity_id ) media_id = play_item.url if media_type in MEDIA_TYPE_MUSIC: if not media_id.startswith(SQUEEZEBOX_SOURCE_STRINGS): # do not process special squeezebox "source" media ids media_id = async_process_play_media_url(self.hass, media_id) await se

async_play_media

cps/helper.py

Better epub cover parsing with multiple cover-image items Code cosmetics renamed variables refactored xml page generation refactored prepare author

calibre-web

Python

helper.py

def get_sorted_author(value): value2 = None try: if ',' not in value: regexes = [r"^(JR|SR)\.?$", r"^I{1,3}\.?$", r"^IV\.?$"] combined = "(" + ")|(".join(regexes) + ")" value = value.split(" ") if re.match(combined, value[-1].upper()): if len(value) > 1: value2 = value[-2] + ", " + " ".join(value[:-2]) + " " + value[-1] else: value2 = value[0] elif len(value) == 1: value2 = value[0] else: value2 = value[-1] + ", " + " ".join(value[:-1]) else: value2 = value except Exception as ex: log.error("Sorting author %s failed: %s", value, ex) if isinstance(list, value2): value2 = value[0] else: value2 = value return value2

4545f4a20d9ff90b99bbd4e3e34b6de4441d6367

https://github.com/janeczku/calibre-web.git

def get_sorted_author(value): value2 = None try: if ',' not in value: regexes = [r"^(JR|SR)\.?$", r"^I{1,3}\.?$", r"^IV\.?$"] combined = "(" + ")|(".join(regexes) + ")" value = value.split(" ") if re.match(combined, value[-1].upper()): if len(value) > 1: value2 = value[-2] + ", " + " ".join(value[:-2]) + " " + value[-1] else: value2 = value[0] elif len(value) == 1: value2 = value[0] else: value2 = value[-1] + ", " + " ".join(value[:-1]) else: value2 = value except Exception as ex: log.error("Sorting author %s failed: %s", value, ex) if isins

get_sorted_author

modules/image/semantic_segmentation/lseg/module.py

Add LSeg Module (#2038) * add LSeg * add LSeg README * add requirements.txt * update README * update module * update * update * update * update * pre-commit * update * save jpg -> save png * bgr -> bgra * fix typo * pre-commit

PaddleHub

Python

module.py

def run_cmd(self, argvs): self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name), prog='hub run {}'.format(self.name), usage='%(prog)s', add_help=True) self.parser.add_argument('--input_path', type=str, help="path to image.") self.parser.add_argument('--labels', type=str, nargs='+', help="segmentation labels.") self.parser.add_argument('--output_dir', type=str, default='lseg_output', help="The directory to save output images.") args = self.parser.parse_args(argvs) self.segment(image=args.input_path, labels=args.labels, visualization=True, output_dir=args.output_dir) return 'segmentation results are saved in %s' % args.output_dir

98d598b7fe14ddca68f8107a66a1f8a3e4ce2bd8

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

def run_cmd(self, argvs): self.parser = argparse.ArgumentParser(description="Run the {} module.".format(self.name), prog='hub run {}'.format(self.name), usage='%(prog)s', add_help=True) self.parser.add_argument('--input_path', type=str, help="path to image.") self.parser.a

run_cmd

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

Balanced joint maximum mean discrepancy for deep transfer learning

transferlearning

Python

test_python_layer.py

def python_net_file(): with tempfile.NamedTemporaryFile(mode='w+', delete=False) as f: f.write() return f.name

cc4d0564756ca067516f71718a3d135996525909

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

def python_net_file(): with tempfile.NamedTemporaryFile(mode='w+', delet

python_net_file

keras/engine/training.py

When interactive logging is disabled (using absl logging) and verbose="auto", we will use verbose=2, which does not print the progress bar. PiperOrigin-RevId: 420939364

keras

Python

training.py

def _detect_save_format(filepath): filepath = io_utils.path_to_string(filepath) if saving_utils.is_hdf5_filepath(filepath): return filepath, 'h5' # Filepath could be a TensorFlow checkpoint file prefix or SavedModel # directory. It's possible for filepath to be both a prefix and directory. # Prioritize checkpoint over SavedModel. if _is_readable_tf_checkpoint(filepath): save_format = 'tf' elif tf.saved_model.contains_saved_model(filepath): ckpt_path = os.path.join(filepath, tf.saved_model.VARIABLES_DIRECTORY, tf.saved_model.VARIABLES_FILENAME) if _is_readable_tf_checkpoint(ckpt_path): filepath = ckpt_path save_format = 'tf' else: raise ValueError('Unable to load weights. filepath {} appears to be a ' 'SavedModel directory, but checkpoint either doesn\'t ' 'exist, or is incorrectly formatted.'.format(filepath)) else: # Not a TensorFlow checkpoint. This filepath is likely an H5 file that # doesn't have the hdf5/keras extensions. save_format = 'h5' return filepath, save_format

ba6fddb32d20ccd0759c90d19978b02da6568fe7

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

def _detect_save_format(filepath): filepath = io_utils.path_to_string(filepath) if saving_utils.is_hdf5_filepath(filepath): return filepath, 'h5' # Filepath could be a TensorFlow checkpoint file prefix or SavedModel # directory. It's possible for filepath to be both a prefix and directory. # Prioritize checkpoint over SavedModel. if _is_readable_tf_checkpoint(filepath): save_format = 'tf' elif tf.saved_model.contains_saved_model(filepath): ckpt_path = os.path.join(filepath, tf.saved_model.VARIABLES_DIRECTORY, tf.saved_model.VARIABLES_FILENAME) if _is_readable_tf_checkpoint(ckpt_

_detect_save_format

modin/core/execution/dispatching/factories/test/test_dispatcher.py

FEAT-#5230: Support external query compiler and IO (#5231) Signed-off-by: Devin Petersohn <devin.petersohn@gmail.com> Co-authored-by: Vasily Litvinov <fam1ly.n4me@yandex.ru>

modin

Python

test_dispatcher.py

def test_set_execution(): with _switch_execution("Bar", "Foo"): assert FactoryDispatcher.get_factory() == FooOnBarFactory

fd776a5a4faf7695d461f369bb2470dcb8aa2745

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

def test_set_execution(): with _switch_execution("Bar", "Foo"): assert FactoryDispatcher.get_factory() == FooOnBarFactory

test_set_execution

saleor/graphql/meta/mutations.py

Catch update_fields did not affect any rows errors and return response with message (#9225) * Add select_for_update() to querysets in checkout and meta mutations * Remove redundant select_for_update * Remove reduntant file after merging conflicts * Catch update_fields did not affect any rows errors and return response with message * Review changes * Update products.py

saleor

Python

mutations.py

def get_instance(cls, info, **data): object_id = data.get("id") qs = data.get("qs", None) try: type_name, _ = from_global_id_or_error(object_id) # ShippingMethodType represents the ShippingMethod model if type_name == "ShippingMethodType": qs = shipping_models.ShippingMethod.objects return cls.get_node_or_error(info, object_id, qs=qs) except GraphQLError as e: if instance := cls.get_instance_by_token(object_id, qs): return instance raise ValidationError( { "id": ValidationError( str(e), code=MetadataErrorCode.GRAPHQL_ERROR.value ) } )

e85f83b4c7ef25e18509577dbc808893a3484f61

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

def get_instance(cls, info, **data): object_id = data.get("id") qs = data.get("qs", None) try: type_name, _ = from_global_id_or_error(object_id) # ShippingMethodType represents the ShippingMethod model if type_name == "ShippingMethodType": qs = shipping_models.ShippingMethod.objects return cls.get_node_or_error(info, object_id, qs=qs) except GraphQLError as e: if instance := cls.get_instance_by_token(object_id, qs): return instance raise ValidationError( { "id": ValidationError( str(e), code=MetadataErrorCode.GRAPHQL_ERROR.value ) } )

get_instance

src/documents/tests/test_tasks.py

addes tests: - barcode-39 - barcode-128 - qr barcodes - test for consumption Signed-off-by: Florian Brandes <florian.brandes@posteo.de>

paperless-ngx

Python

test_tasks.py

def test_barcode_reader_unreadable(self): test_file = os.path.join( os.path.dirname(__file__), "samples", "barcodes", "barcode-39-PATCHT-unreadable.png", ) img = Image.open(test_file) self.assertEqual(tasks.barcode_reader(img), [])

10ca515ac527b746d6a948d6aebca5d253923b64

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

def test_barcode_reader_unreadable(self): test_file = os.path.join( os.path.dirname(__file__), "samples", "barcodes", "barcode-39-PATCHT-unreadable.png", ) img = Image.open(test_file)

test_barcode_reader_unreadable

homeassistant/components/mqtt/device_tracker/schema_discovery.py

Improve MQTT type hints part 8 (#81034) * Improve typing device_tracker discovery * Improve typing device_tracker yaml * Add test source_type attribute * Follow up comment * Initialize at `__init__` not at class level. * Use full name for return variable * Correct import, remove assert * Use AsyncSeeCallback

core

Python

schema_discovery.py

def source_type(self) -> SourceType | str: source_type: SourceType | str = self._config[CONF_SOURCE_TYPE] return source_type

bcae6d604e2967c7475f0caa4b1b5e4e76ab88bf

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

def source_type(self) -> SourceType | str: sour

source_type

tests/sentry/api/test_client_state.py

Client State endpoint (#33135) * Client State endpoint * fixes * use configured cluster key * Add tests * make endpoint private * updates * fix tests

sentry

Python

test_client_state.py

def test_large_payload(self): resp = self.client.put( self.path, {"test": 300 * "Dummy Data"}, ) assert resp.status_code == 413

cef95dd7be74a43fb986e7bb3cd638481de0fc2f

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

def test_large_payload(self): resp = self.client.put(

test_large_payload

wagtail/admin/tests/tests.py

Reformat with black

wagtail

Python

tests.py

def test_not_logged_in_redirect(self): response = self.client.get("/admin/sdfgdsfgdsfgsdf/") # Check that the user was redirected to the login page and that next was set correctly self.assertRedirects( response, reverse("wagtailadmin_login") + "?next=/admin/sdfgdsfgdsfgsdf/" )

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def test_not_logged_in_redirect(self): response = self.

test_not_logged_in_redirect

keras/optimizers/optimizer_v2/utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

utils.py

def make_global_gradient_clipnorm_fn(clipnorm): if clipnorm is None: return lambda grads_and_vars: grads_and_vars

84afc5193d38057e2e2badf9c889ea87d80d8fbf

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

def make_global_gradient_clipnorm_fn(clipnorm): if clipnorm is None: retur

make_global_gradient_clipnorm_fn

pandas/tests/frame/methods/test_reindex.py

BUG: reindex using wrong fill value when indexing cols and index for uint dtypes (#48185)

pandas

Python

test_reindex.py

def test_reindex_uint_dtypes_fill_value(self, any_unsigned_int_numpy_dtype): # GH#48184 df = DataFrame({"a": [1, 2], "b": [1, 2]}, dtype=any_unsigned_int_numpy_dtype) result = df.reindex(columns=list("abcd"), index=[0, 1, 2, 3], fill_value=10) expected = DataFrame( {"a": [1, 2, 10, 10], "b": [1, 2, 10, 10], "c": 10, "d": 10}, dtype=any_unsigned_int_numpy_dtype, ) tm.assert_frame_equal(result, expected)

d0268e719f899789f9606beb4592a17d27086b4c

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

def test_reindex_uint_dtypes_fill_value(self, any_unsigned_int_numpy_dtype): # GH#48184 df = DataFrame({"a": [1, 2], "b":

test_reindex_uint_dtypes_fill_value

keras/layers/rnn/time_distributed.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

time_distributed.py

def compute_output_shape(self, input_shape): input_shape = tf_utils.convert_shapes(input_shape, to_tuples=False) child_input_shape = tf.nest.map_structure( self._remove_timesteps, input_shape ) child_output_shape = self.layer.compute_output_shape(child_input_shape) child_output_shape = tf_utils.convert_shapes( child_output_shape, to_tuples=False ) timesteps = tf_utils.convert_shapes(input_shape) timesteps = tf.nest.flatten(timesteps)[1]

84afc5193d38057e2e2badf9c889ea87d80d8fbf

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

def compute_output_shape(self, input_shape): input_shape = tf_utils.convert_shapes(input_shape, to_tuples=False) child_input_shape = tf.nest.map_structure( self._remove_timesteps, input_shape )

compute_output_shape

sklearn/tests/test_random_projection.py

MAINT Use `_validate_params` in RandomProjection family (#23831) Co-authored-by: Meekail Zain <34613774+Micky774@users.noreply.github.com>

scikit-learn

Python

test_random_projection.py

def test_random_projection_transformer_invalid_input(): n_components = "auto" fit_data = [[0, 1, 2]] for RandomProjection in all_RandomProjection: with pytest.raises(ValueError): RandomProjection(n_components=n_components).fit(fit_data)

dcd0d4f054b4586f617d35885df05eaae4708876

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

def test_random_projection_transformer_invalid_input(): n_components = "auto" fit_data = [[0, 1, 2]] for RandomProjection in all_RandomProjection: with pytest.raises(ValueError): RandomProjection(n

test_random_projection_transformer_invalid_input

homeassistant/components/demo/vacuum.py

Add EntityFeature enum to Vacuum (#69121)

core

Python

vacuum.py

def turn_off(self, **kwargs): if self.supported_features & VacuumEntityFeature.TURN_OFF == 0: return self._state = False self._status = "Charging" self.schedule_update_ha_state()

2d37066ce59064ed6121720e03424e4dc73c2b43

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

def turn_off(self, **kwargs):

turn_off

sklearn/tests/test_pipeline.py

MAINT Clean deprecation for 1.2: normalize in linear models (#24391)

scikit-learn

Python

test_pipeline.py

def test_pipeline_raise_set_params_error(): # Test pipeline raises set params error message for nested models. pipe = Pipeline([("cls", LinearRegression())]) # expected error message error_msg = re.escape( "Invalid parameter 'fake' for estimator Pipeline(steps=[('cls'," " LinearRegression())]). Valid parameters are: ['memory', 'steps', 'verbose']." ) with pytest.raises(ValueError, match=error_msg): pipe.set_params(fake="nope") # invalid outer parameter name for compound parameter: the expected error message # is the same as above. with pytest.raises(ValueError, match=error_msg): pipe.set_params(fake__estimator="nope") # expected error message for invalid inner parameter error_msg = re.escape( "Invalid parameter 'invalid_param' for estimator LinearRegression(). Valid" " parameters are: ['copy_X', 'fit_intercept', 'n_jobs', 'positive']." ) with pytest.raises(ValueError, match=error_msg): pipe.set_params(cls__invalid_param="nope")

e41753ebd57c44ae91b389f190c43ddc0b384a75

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

def test_pipeline_raise_set_params_error(): # Test pipeline raises set params error message for nested models. pipe = Pipeline([("cls", LinearRegression())]) # expected error message error_msg = re.escape( "Invalid parameter 'fake' for estimator Pipeline(steps=[('cls'," " LinearRegression())]). Valid parameters are: ['memory', 'steps', 'verbose']." ) with pytest.raises(ValueError, match=error_msg): pipe.set_params(fake="nope") # invalid outer parameter name for compound parameter: the expected error message # is the same as above. with pytest.raises(ValueError, match=error_msg): pipe.set_params(fake__estimator="nope") # expected error message for invalid inner parameter error_msg = re.escape( "Invalid parameter 'invalid_param' for estimator LinearRegression(). Valid" " parameters

test_pipeline_raise_set_params_error

tests/rpc/test_rpc_webhook.py

webhookbuy -> webhookentry

freqtrade

Python

test_rpc_webhook.py

def test_exception_send_msg(default_conf, mocker, caplog): default_conf["webhook"] = get_webhook_dict() del default_conf["webhook"]["webhookentry"] webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf) webhook.send_msg({'type': RPCMessageType.ENTRY}) assert log_has(f"Message type '{RPCMessageType.ENTRY}' not configured for webhooks", caplog) default_conf["webhook"] = get_webhook_dict() default_conf["webhook"]["webhookentry"]["value1"] = "{DEADBEEF:8f}" msg_mock = MagicMock() mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock) webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf) msg = { 'type': RPCMessageType.ENTRY, 'exchange': 'Binance', 'pair': 'ETH/BTC', 'limit': 0.005, 'order_type': 'limit', 'stake_amount': 0.8, 'stake_amount_fiat': 500, 'stake_currency': 'BTC', 'fiat_currency': 'EUR' } webhook.send_msg(msg) assert log_has("Problem calling Webhook. Please check your webhook configuration. " "Exception: 'DEADBEEF'", caplog) msg_mock = MagicMock() mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock) msg = { 'type': 'DEADBEEF', 'status': 'whatever' } with pytest.raises(NotImplementedError): webhook.send_msg(msg)

7d3116f9fbe446a31837f483aa9bef550d7a1d3d

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

def test_exception_send_msg(default_conf, mocker, caplog): default_conf["webhook"] = get_webhook_dict() del default_conf["webhook"]["webhookentry"] webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf) webhook.send_msg({'type': RPCMessageType.ENTRY}) assert log_has(f"Message type '{RPCMessageType.ENTRY}' not configured for webhooks", caplog) default_conf["webhook"] = get_webhook_dict() default_conf["webhook"]["webhookentry"]["value1"] = "{DEADBEEF:8f}" msg_mock = MagicMock() mocker.patch("freqtrade.rpc.webhook.Webhook._send_msg", msg_mock) webhook = Webhook(RPC(get_patched_freqtradebot(mocker, default_conf)), default_conf) msg = { 'type': RPCMessageType.ENTRY, 'exchange': 'Binance', 'pair': 'ETH/BTC', 'limit': 0

test_exception_send_msg

keras/optimizers/optimizer_experimental/optimizer.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

optimizer.py

def learning_rate(self, learning_rate): if isinstance( self._learning_rate, learning_rate_schedule.LearningRateSchedule ): raise TypeError( "This optimizer was created with a `LearningRateSchedule`" " object as its `learning_rate` constructor argument, " "hence its learning rate is not settable. If you need the" " learning rate to be settable, you should instantiate " "the optimizer with a float `learning_rate` argument." ) self._learning_rate.assign(learning_rate)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

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

def learning_rate(self, learning_rate): if isinstance( self._learning_rate, learning_rate_schedule.LearningRateSchedule ): raise TypeError( "This optimizer was created with a `LearningRateSchedule`" " object as its `learning_rate` constructor argument, " "hence its learning rate is not settable. If you need

learning_rate

keras/tests/model_architectures.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

model_architectures.py

def call(self, inputs, **kwargs): x = self.dense1(inputs) x = self.dp(x) x = self.bn(x) return self.dense2(x)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

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

def call(self, inputs, **kwargs): x = self.dense1(inputs)

call

dashboard/modules/job/tests/test_job_manager.py

[jobs] Rename JobData -> JobInfo (#22499) `JobData` could be confused with the actual output data of a job, `JobInfo` makes it more clear that this is status information + metadata.

ray

Python

test_job_manager.py

async def test_failed_runtime_env_validation(self, job_manager): run_cmd = f"python {_driver_script_path('override_env_var.py')}" job_id = job_manager.submit_job( entrypoint=run_cmd, runtime_env={"working_dir": "path_not_exist"} ) data = job_manager.get_job_info(job_id) assert data.status == JobStatus.FAILED assert "path_not_exist is not a valid URI" in data.message

58e5f0140d247059ca45b249446614929930c126

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

async def test_failed_runtime_env_validation(self, job_manager): run_cmd = f"python {_driver_script_path('override_env_var.py')}" job_id = job_manager.submit

test_failed_runtime_env_validation

jaxlib/lapack.py

feat: refactor code using pyupgrade This PR upgrades legacy Python code to 3.7+ code using pyupgrade: ```sh pyupgrade --py37-plus --keep-runtime-typing **.py ``` a

jax

Python

lapack.py

def syevd_mhlo(dtype, a, lower=False): a_type = ir.RankedTensorType(a.type) dims = a_type.shape assert len(dims) >= 2 m, n = dims[-2:] assert m == n batch_dims = tuple(dims[:-2]) num_bd = len(batch_dims) b = 1 for d in batch_dims: b *= d layout = (num_bd, num_bd + 1) + tuple(range(num_bd - 1, -1, -1)) i32_type = ir.IntegerType.get_signless(32) if dtype == np.float32: fn = b"lapack_ssyevd" eigvals_type = ir.F32Type.get() workspace = [ ir.RankedTensorType.get([_lapack.syevd_work_size(n)], a_type.element_type), ir.RankedTensorType.get([_lapack.syevd_iwork_size(n)], i32_type), ] workspace_layouts = [[0], [0]] elif dtype == np.float64: fn = b"lapack_dsyevd" eigvals_type = ir.F64Type.get() workspace = [ ir.RankedTensorType.get([_lapack.syevd_work_size(n)], a_type.element_type), ir.RankedTensorType.get([_lapack.syevd_iwork_size(n)], i32_type), ] workspace_layouts = [[0], [0]] elif dtype == np.complex64: fn = b"lapack_cheevd" eigvals_type = ir.F32Type.get() workspace = [ ir.RankedTensorType.get([_lapack.heevd_work_size(n)], a_type.element_type), ir.RankedTensorType.get([_lapack.heevd_rwork_size(n)], eigvals_type), ir.RankedTensorType.get([_lapack.syevd_iwork_size(n)], i32_type), ] workspace_layouts = [[0], [0], [0]] elif dtype == np.complex128: fn = b"lapack_zheevd" eigvals_type = ir.F64Type.get() workspace = [ ir.RankedTensorType.get([_lapack.heevd_work_size(n)], a_type.element_type), ir.RankedTensorType.get([_lapack.heevd_rwork_size(n)], eigvals_type), ir.RankedTensorType.get([_lapack.syevd_iwork_size(n)], i32_type), ] workspace_layouts = [[0], [0], [0]] else: raise NotImplementedError(f"Unsupported dtype {dtype}") scalar_layout = [] layout = (num_bd, num_bd + 1) + tuple(range(num_bd - 1, -1, -1)) out = custom_call( fn, [ a.type, ir.RankedTensorType.get(batch_dims + (n,), eigvals_type), ir.RankedTensorType.get(batch_dims, i32_type), ] + workspace, [_mhlo_s32(1 if lower else 0), _mhlo_s32(b), _mhlo_s32(n), a], operand_layouts=[scalar_layout] * 3 + [layout], result_layouts=[ layout, tuple(range(num_bd, -1, -1)), tuple(range(num_bd - 1, -1, -1)), ] + workspace_layouts) return out[:3] # # geev: Nonsymmetric eigendecomposition

17de89b16ac5ee05aee03115d858e67489eab973

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

def syevd_mhlo(dtype, a, lower=False): a_type = ir.RankedTensorType(a.type) dims = a_type.shape assert len(dims) >= 2 m, n = dims[-2:] assert m == n batch_dims = tuple(dims[:-2]) num_bd = len(batch_dims) b = 1 for d in batch_dims: b *= d layout = (num_bd, num_bd + 1) + tuple(range(num_bd - 1, -1, -1)) i32_type = ir.IntegerType.get_signless(32) if dtype == np.float32: fn = b"lapack_ssyevd" eigvals_type = ir.F32Type.get() workspace = [ ir.RankedTensorType.get([_lapack.syevd_work_size(n)],

syevd_mhlo

zerver/tests/test_message_edit.py

python: Replace string concatenations with f-strings.

zulip

Python

test_message_edit.py

def test_move_message_to_stream_and_topic(self) -> None: (user_profile, old_stream, new_stream, msg_id, msg_id_later) = self.prepare_move_topics( "iago", "test move stream", "new stream", "test" ) with queries_captured() as queries, cache_tries_captured() as cache_tries: result = self.client_patch( f"/json/messages/{msg_id}", { "message_id": msg_id, "stream_id": new_stream.id, "propagate_mode": "change_all", "topic": "new topic", }, ) self.assert_length(queries, 52) self.assert_length(cache_tries, 13) messages = get_topic_messages(user_profile, old_stream, "test") self.assert_length(messages, 1) self.assertEqual( messages[0].content, f"This topic was moved by @_**Iago|{user_profile.id}** to #**new stream>new topic**", ) messages = get_topic_messages(user_profile, new_stream, "new topic") self.assert_length(messages, 4) self.assertEqual( messages[3].content, f"This topic was moved here from #**test move stream>test** by @_**Iago|{user_profile.id}**", ) self.assert_json_success(result)

d560d124a304a2f6dd467200aab7f070a78bf155

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

def test_move_message_to_stream_and_topic(self) -> None: (user_profile, old_stream, new_stream, msg_id, msg_id_later) = self.prepare_move_topics( "iago", "

test_move_message_to_stream_and_topic

homeassistant/components/matter/entity.py

Add matter integration BETA (#83064) * Add matter base (#79372) Co-authored-by: Marcel van der Veldt <m.vanderveldt@outlook.com> * Add matter server add-on flow (#82698) * Add matter server add-on flow * Fix stale error argument * Clean docstrings * Use localhost as default address * Add matter websocket api foundation (#82848) * Add matter config entry add-on management (#82865) * Use matter refactored server/client library (#83003) Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Bump python-matter-server to 1.0.6 (#83059) * Extend matter websocket api (#82948) * Extend matter websocket api * Finish docstring * Fix pin type * Adjust api after new client * Adjust api to frontend for now Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

core

Python

entity.py

async def async_added_to_hass(self) -> None: await super().async_added_to_hass() # Subscribe to attribute updates. for attr_cls in self.entity_description.subscribe_attributes: if matter_attr := self.get_matter_attribute(attr_cls): self._attributes_map[attr_cls] = matter_attr.path self._unsubscribes.append( self.matter_client.subscribe( self._on_matter_event, EventType.ATTRIBUTE_UPDATED, self._device_type_instance.node.node_id, matter_attr.path, ) ) continue # not sure if this can happen, but just in case log it. LOGGER.warning("Attribute not found on device: %s", attr_cls) # make sure to update the attributes once self._update_from_device()

e2308fd15cec4dfdd25d843b72cd3071657fd5b8

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

async def async_added_to_hass(self) -> None: await super().async_added_to_hass() # Subscribe to attribute updates. for attr_cls in self.entity_description.subscribe_attributes: if matter_attr := self.get_matter_attribute(attr_cls): self._attributes_map[attr_cls] = matter_attr.path self._unsubscribes.append( self.matter_client.subscribe( self._on_matter_event, EventType.ATTRIBUT

async_added_to_hass

python3.10.4/Lib/_pydecimal.py

add python 3.10.4 for windows

XX-Net

Python

_pydecimal.py

def _sqrt_nearest(n, a): if n <= 0 or a <= 0: raise ValueError("Both arguments to _sqrt_nearest should be positive.") b=0 while a != b: b, a = a, a--n//a>>1 return a

8198943edd73a363c266633e1aa5b2a9e9c9f526

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

def _sqrt_nearest(n, a): i

_sqrt_nearest

apps/applications/serializers/application.py

perf: 账号备份优化 (#7503) * perf: 账号备份优化 * feat: 优化账号备份获取有序备份字段列表 Co-authored-by: feng626 <1304903146@qq.com> Co-authored-by: Michael Bai <baijiangjie@gmail.com>

jumpserver

Python

application.py

def app(self): if isinstance(self.instance, models.Application): instance = self.instance else: instance = None return instance

def9bedd3093e88f56618b068f3db53a042e6c1e

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

def app(self): if isinstance(self.instance, models.Application): instance = self.instance else: instance = None return instance

app

pandas/core/indexes/base.py

DEPR: DatetimeIndex.intersection with mixed timezones cast to UTC, not object (#45357) * DEPR: DatetimeIndex.intersection with mixed timezones cast to UTC instead of object * GH ref * mypy fixup Co-authored-by: Jeff Reback <jeff@reback.net>

pandas

Python

base.py

def union(self, other, sort=None): self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not is_dtype_equal(self.dtype, other.dtype): if ( isinstance(self, ABCMultiIndex) and not is_object_dtype(unpack_nested_dtype(other)) and len(other) > 0 ): raise NotImplementedError( "Can only union MultiIndex with MultiIndex or Index of tuples, " "try mi.to_flat_index().union(other) instead." ) self._deprecate_dti_setop(other, "union") dtype = self._find_common_type_compat(other) left = self.astype(dtype, copy=False) right = other.astype(dtype, copy=False) return left.union(right, sort=sort) elif not len(other) or self.equals(other): # NB: whether this (and the `if not len(self)` check below) come before # or after the is_dtype_equal check above affects the returned dtype return self._get_reconciled_name_object(other) elif not len(self): return other._get_reconciled_name_object(self) result = self._union(other, sort=sort) return self._wrap_setop_result(other, result)

4e034ec0006b6c05160ce67ea1420ce28f295c91

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

def union(self, other, sort=None): self._validate_sort_keyword(sort) self._assert_can_do_setop(other) other, result_name = self._convert_can_do_setop(other) if not is_dtype_equal(self.dtype, other.dtype): if ( isinstance(self, ABCMultiIndex) and not is_object_dtype(unpack_nested_dtype(other)) and len(other) > 0 ): raise NotImplementedError( "Can only union MultiIndex with MultiIndex or Index of tuples, " "try mi.to_flat_index().union(other) instead." ) self._deprecate_dti_setop(other, "union") dtype = self._find_common_type_compat(other) left = self.astype(dtype, copy=False) right = other.astype(dtype, copy=False) return left.union(right, sort=sort) elif not len(other) or self.equals(other): # NB: whether this (and the `if not len(self)` check below) come before # or after the is_dtype_equal check above affects the returned dtype return self._get_reconciled_name_object(other) elif not len(self): return other._get_reconciled_name_object(self) result = self._union(other, sort=sort) return self._wrap_

union

erpnext/manufacturing/doctype/workstation_type/test_workstation_type.py

test: test case to check workstation type

erpnext

Python

test_workstation_type.py

def create_workstation_type(**args): args = frappe._dict(args) if workstation_type := frappe.db.exists("Workstation Type", args.workstation_type): return frappe.get_doc("Workstation Type", workstation_type) else: doc = frappe.new_doc("Workstation Type") doc.update(args) doc.insert() return doc

7bd06e6fbc30ebd92b18055983e3b88fa9545e2a

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

def create_workstation_type(**args): args = frappe._dict(args) if workstation_type := frappe.db.exists("Workstation Type", args.workstation_type): return frappe.get_doc("Workstation Type", workstation_type) else: doc = frappe.new_doc("Workstation Type") doc.update(args) doc.insert() retur

create_workstation_type

cps/editbooks.py

Better epub cover parsing with multiple cover-image items Code cosmetics renamed variables refactored xml page generation refactored prepare author

calibre-web

Python

editbooks.py

def edit_single_cc_data(book_id, book, column_id, to_save): cc = (calibre_db.session.query(db.CustomColumns) .filter(db.CustomColumns.datatype.notin_(db.cc_exceptions)) .filter(db.CustomColumns.id == column_id) .all()) return edit_cc_data(book_id, book, to_save, cc)

4545f4a20d9ff90b99bbd4e3e34b6de4441d6367

https://github.com/janeczku/calibre-web.git

def edit_single_cc_data(book_id, book, column_id, to_save): cc = (calibre_db.session.query(db.CustomColumns) .filter(db.CustomColumns

edit_single_cc_data

modules/image/text_to_image/stable_diffusion/diffusers/schedulers/scheduling_karras_ve.py

Add stable diffusion module

PaddleHub

Python

scheduling_karras_ve.py

def set_timesteps(self, num_inference_steps): self.num_inference_steps = num_inference_steps self.timesteps = np.arange(0, self.num_inference_steps)[::-1].copy() self.schedule = [(self.sigma_max * (self.sigma_min**2 / self.sigma_max**2)**(i / (num_inference_steps - 1))) for i in self.timesteps] self.schedule = np.array(self.schedule, dtype=np.float32) self.set_format(tensor_format=self.tensor_format)

a6790a651a12eb391060e533868bf0ba197f6f7e

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

def set_timesteps(self, num_inference_steps): self.num_inference_steps = num_inference_steps self.timesteps = np.arange(0, self.num_inference_steps)[::-1].copy() self.schedule = [(self.sigma_max * (self.sigma_min**2 / self.sigma_max**2)**(i / (num_inference_steps - 1))) for i in self.timest

set_timesteps

tests/maskformer/test_feature_extraction_maskformer.py

Maskformer (#15682) * maskformer * conflicts * conflicts * minor fixes * feature extractor test fix refactor MaskFormerLoss following conversation MaskFormer related types should not trigger a module time import error missed one removed all the types that are not used update config mapping minor updates in the doc resolved conversation that doesn't need a discussion minor changes resolved conversations fixed DetrDecoder * minor changes minor changes fixed mdx file test feature_extractor return types functional losses -> classes removed the return type test for the feature extractor minor changes + style + quality * conflicts? * rebase master * readme * added missing files * deleded poolformers test that where in the wrong palce * CI * minor changes * Apply suggestions from code review Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * resolved conversations * minor changes * conversations [Unispeech] Fix slow tests (#15818) * remove soundfile old way of loading audio * Adapt slow test [Barthez Tokenizer] Fix saving (#15815) [TFXLNet] Correct tf xlnet generate (#15822) * [TFXLNet] Correct tf xlnet * adapt test comment Fix the push run (#15807) Fix semantic segmentation pipeline test (#15826) Fix dummy_inputs() to dummy_inputs in symbolic_trace doc (#15776) Add model specific output classes to PoolFormer model docs (#15746) * Added model specific output classes to poolformer docs * Fixed Segformer typo in Poolformer docs Adding the option to return_timestamps on pure CTC ASR models. (#15792) * Adding the option to return_timestamps on pure CTC ASR models. * Remove `math.prod` which was introduced in Python 3.8 * int are not floats. * Reworking the PR to support "char" vs "word" output. * Fixup! * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/pipelines/automatic_speech_recognition.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Quality. Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> HFTracer.trace should use/return self.graph to be compatible with torch.fx.Tracer (#15824) Fix tf.concatenate + test past_key_values for TF models (#15774) * fix wrong method name tf.concatenate * add tests related to causal LM / decoder * make style and quality * clean-up * Fix TFBertModel's extended_attention_mask when past_key_values is provided * Fix tests * fix copies * More tf.int8 -> tf.int32 in TF test template * clean-up * Update TF test template * revert the previous commit + update the TF test template * Fix TF template extended_attention_mask when past_key_values is provided * Fix some styles manually * clean-up * Fix ValueError: too many values to unpack in the test * Fix more: too many values to unpack in the test * Add a comment for extended_attention_mask when there is past_key_values * Fix TFElectra extended_attention_mask when past_key_values is provided * Add tests to other TF models * Fix for TF Electra test: add prepare_config_and_inputs_for_decoder * Fix not passing training arg to lm_head in TFRobertaForCausalLM * Fix tests (with past) for TF Roberta * add testing for pask_key_values for TFElectra model Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> [examples/summarization and translation] fix readme (#15833) Add ONNX Runtime quantization for text classification notebook (#15817) Re-enable doctests for the quicktour (#15828) * Re-enable doctests for the quicktour * Re-enable doctests for task_summary (#15830) * Remove & Framework split model report (#15825) Add TFConvNextModel (#15750) * feat: initial implementation of convnext in tensorflow. * fix: sample code for the classification model. * chore: added checked for from the classification model. * chore: set bias initializer in the classification head. * chore: updated license terms. * chore: removed ununsed imports * feat: enabled argument during using drop_path. * chore: replaced tf.identity with layers.Activation(linear). * chore: edited default checkpoint. * fix: minor bugs in the initializations. * partial-fix: tf model errors for loading pretrained pt weights. * partial-fix: call method updated * partial-fix: cross loading of weights (4x3 variables to be matched) * chore: removed unneeded comment. * removed playground.py * rebasing * rebasing and removing playground.py. * fix: renaming TFConvNextStage conv and layer norm layers * chore: added initializers and other minor additions. * chore: added initializers and other minor additions. * add: tests for convnext. * fix: integration tester class. * fix: issues mentioned in pr feedback (round 1). * fix: how output_hidden_states arg is propoagated inside the network. * feat: handling of arg for pure cnn models. * chore: added a note on equal contribution in model docs. * rebasing * rebasing and removing playground.py. * feat: encapsulation for the convnext trunk. * Fix variable naming; Test-related corrections; Run make fixup * chore: added Joao as a contributor to convnext. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * chore: corrected copyright year and added comment on NHWC. * chore: fixed the black version and ran formatting. * chore: ran make style. * chore: removed from_pt argument from test, ran make style. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * fix: tests in the convnext subclass, ran make style. * rebasing * rebasing and removing playground.py. * rebasing * rebasing and removing playground.py. * chore: moved convnext test to the correct location * fix: locations for the test file of convnext. * fix: convnext tests. * chore: applied sgugger's suggestion for dealing w/ output_attentions. * chore: added comments. * chore: applied updated quality enviornment style. * chore: applied formatting with quality enviornment. * chore: revert to the previous tests/test_modeling_common.py. * chore: revert to the original test_modeling_common.py * chore: revert to previous states for test_modeling_tf_common.py and modeling_tf_utils.py * fix: tests for convnext. * chore: removed output_attentions argument from convnext config. * chore: revert to the earlier tf utils. * fix: output shapes of the hidden states * chore: removed unnecessary comment * chore: reverting to the right test_modeling_tf_common.py. * Styling nits Co-authored-by: ariG23498 <aritra.born2fly@gmail.com> Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com> * minor changes * doc fix in feature extractor * doc * typose * removed detr logic from config * removed detr logic from config * removed num_labels * small fix in the config * auxilary -> auxiliary * make style * some test is failing * fix a weird char in config prevending doc-builder * retry to fix the doc-builder issue * make style * new try to fix the doc builder * CI * change weights to facebook Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: ariG23498 <aritra.born2fly@gmail.com> Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

transformers

Python

test_feature_extraction_maskformer.py

def prepare_feat_extract_dict(self): return { "do_resize": self.do_resize, "size": self.size, "max_size": self.max_size, "do_normalize": self.do_normalize, "image_mean": self.image_mean, "image_std": self.image_std, "size_divisibility": self.size_divisibility, }

d83d22f578276e9f201b0b3b0f8f9bd68e86c133

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

def prepare_feat_extract_dict(self): return { "do_resize": self.do_resize, "size": self.size, "max_size": self.max_size, "do_no

prepare_feat_extract_dict

test/mitmproxy/tools/console/test_statusbar.py

clean up `statusbar.py`

mitmproxy

Python

test_statusbar.py

def test_shorten_message(message, ready_message): assert statusbar.shorten_message(message, max_width=30) == ready_message

db7074a37dd9d696b6ca085df90a9c84d434f97a

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

def test_shorten_message(message, ready_message): assert statusbar.shorten_message(message, max_width=30) == ready_message

test_shorten_message

jax/interpreters/pxla.py

Move _get_array_mapping from gda.py to pxla.py PiperOrigin-RevId: 459891853

jax

Python

pxla.py

def _check_gda_or_array_xla_sharding_match(args, in_array_mappings): from jax.experimental.global_device_array import GlobalDeviceArray from jax.experimental.array import Array for arg, inp_array_mapping in safe_zip(args, in_array_mappings): if not isinstance(arg, (GlobalDeviceArray, Array)): continue # TODO(yashkatariya): For `Array` check the `sharding` directly when pxla # takes sharding instances. arr_type, arr_mapping = ( ('GDA', _get_array_mapping(arg.mesh_axes)) if isinstance(arg, GlobalDeviceArray) else ('Array', _get_array_mapping(arg.sharding.spec)) ) if inp_array_mapping != arr_mapping: raise ValueError( f"{arr_type} sharding does not match the input sharding. " f"Got {arr_type} spec: {array_mapping_to_axis_resources(arr_mapping)} and " f"auto sharding spec: {array_mapping_to_axis_resources(inp_array_mapping)} " f"for {arr_type}: {arg}")

09ba51f323a2675d5f31b3a8829f7dcd7d989e24

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

def _check_gda_or_array_xla_sharding_match(args, in_array_mappings):

_check_gda_or_array_xla_sharding_match

erpnext/manufacturing/doctype/operation/operation_dashboard.py

style: format code with black

erpnext

Python

operation_dashboard.py

def get_data(): return { "fieldname": "operation", "transactions": [{"label": _("Manufacture"), "items": ["BOM", "Work Order", "Job Card"]}], }

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def get_data(): return { "fieldname": "operation", "transactions": [{"label": _("Manuf

get_data

airbyte-integrations/connectors/source-orb/unit_tests/test_source.py

🎉 New Source: Orb (#9985) * V1 of source_orb connector * add boostrap.md file * add clause on Pagination to bootstrap.md * add SUMMARY documentation * add lookback_window_days connector parameter * Add support for start_date parameter * Add ability to transform record in order to un-nest IDs * Add support for extracting event properties based on connector configuration

airbyte

Python

test_source.py

def test_check_connection_fail(mocker): responses.add(responses.GET, "https://api.billwithorb.com/v1/ping", json={"error": "Unauthorized"}, status=401) source = SourceOrb() logger_mock = MagicMock() (ok, err) = source.check_connection(logger_mock, MagicMock()) assert (ok, type(err)) == (False, HTTPError)

1e0ac30ebdcfce55a5644bcd486044da45c93dd6

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

def test_check_connection_fail(mocker): responses.a

test_check_connection_fail

tests/integration/pods/test_pod.py

fix: return responses (#4343)

jina

Python

test_pod.py

async def test_pods_with_replicas_advance_faster(port_generator): head_port = port_generator() port_expose = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{head_port}"]}}' # create a single head pod head_pod = _create_head_pod(head_port, 'head') head_pod.start() # create a single gateway pod gateway_pod = _create_gateway_pod(graph_description, pod_addresses, port_expose) gateway_pod.start() # create the shards pods = [] for i in range(10): # create worker worker_port = port_generator() # create a single worker pod worker_pod = _create_worker_pod(worker_port, f'pod0/{i}', 'FastSlowExecutor') pods.append(worker_pod) worker_pod.start() await asyncio.sleep(0.1) head_pod.wait_start_success() gateway_pod.wait_start_success() for pod in pods: # this would be done by the Pod, its adding the worker to the head pod.wait_start_success() activate_msg = ControlRequest(command='ACTIVATE') activate_msg.add_related_entity('worker', '127.0.0.1', pod.args.port_in) GrpcConnectionPool.send_request_sync(activate_msg, f'127.0.0.1:{head_port}') c = Client(return_responses=True, host='localhost', port=port_expose, asyncio=True) input_docs = [Document(text='slow'), Document(text='fast')] responses = c.post('/', inputs=input_docs, request_size=1, return_results=True) response_list = []

2efe175c975975532f6e3fd326ed280addf20eba

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

async def test_pods_with_replicas_advance_faster(port_generator): head_port = port_generator() port_expose = port_generator() graph_description = '{"start-gateway": ["pod0"], "pod0": ["end-gateway"]}' pod_addresses = f'{{"pod0": ["0.0.0.0:{head_port}"]}}' # create a single head pod head_pod =

test_pods_with_replicas_advance_faster

ludwig/utils/data_utils.py

fix: restore existing credentials when exiting use_credentials context manager (#2112)

ludwig

Python

data_utils.py

def use_credentials(creds): if creds is None: with contextlib.nullcontext(): yield return # https://filesystem-spec.readthedocs.io/en/latest/features.html#configuration # This allows us to avoid having to plumb the `storage_options` kwargs through # every remote FS call in Ludwig. This implementation is restricted to one thread # in the process acquiring the lock at once. with GLOBAL_CRED_LOCK: with tempfile.TemporaryDirectory() as tmpdir: fname = os.path.join(tmpdir, "conf.json") with open(fname, "w") as f: json.dump(creds, f) # Backup any existing credentials old_conf = dict(**conf) conf.clear() set_conf_files(tmpdir, conf) try: yield finally: # Restore previous credentials with open(fname, "w") as f: json.dump(old_conf, f) conf.clear() set_conf_files(tmpdir, conf)

2471b6b3f925303f337e0de9ded2cba8e23c9be9

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

def use_credentials(creds): if creds is None: with contextlib.nullcontext():

use_credentials

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

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

onnx

Python

quantizelinear.py

def export() -> None: node = onnx.helper.make_node('QuantizeLinear', inputs=['x', 'y_scale', 'y_zero_point'], outputs=['y'],) x = np.array([0, 2, 3, 1000, -254, -1000]).astype(np.float32) y_scale = np.float32(2) y_zero_point = np.uint8(128) y = np.array([128, 129, 130, 255, 1, 0]).astype(np.uint8) expect(node, inputs=[x, y_scale, y_zero_point], outputs=[y], name='test_quantizelinear')

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

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

def export() -> None: node = onnx.helper.make_node(

export

body/human_pose/ambiguity_aware/lib/core/config.py

update

insightface

Python

config.py

def _update_dict(k, v): for vk, vv in v.items(): if vk in config[k]: config[k][vk] = vv else: raise ValueError("{}.{} not exist in config.py".format(k, vk))

4b3c8211b3e3eca5f9fdf6553bbd45c9c7587b0d

https://github.com/deepinsight/insightface.git

def _update_dict(k, v): for vk, vv in v.items(): if vk in config[k]: config[k][vk] = vv

_update_dict

pipenv/patched/notpip/_internal/commands/search.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

Python

search.py

def add_options(self) -> None: self.cmd_opts.add_option( "-i", "--index", dest="index", metavar="URL", default=PyPI.pypi_url, help="Base URL of Python Package Index (default %default)", ) self.parser.insert_option_group(0, self.cmd_opts)

f3166e673fe8d40277b804d35d77dcdb760fc3b3

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

def add_options(self) -> None: self.cmd_opts.add_option( "-i", "--index", dest="index", metavar="URL", default=PyPI.pypi_url,

add_options

sklearn/decomposition/tests/test_pca.py

FIX Reduces memory usage of `PCA.transform` (#22553)

scikit-learn

Python

test_pca.py

def test_variance_correctness(copy): rng = np.random.RandomState(0) X = rng.randn(1000, 200) pca = PCA().fit(X) pca_var = pca.explained_variance_ / pca.explained_variance_ratio_ true_var = np.var(X, ddof=1, axis=0).sum() np.testing.assert_allclose(pca_var, true_var)

2e213c618841f3635885bab034606512c40a7fd4

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

def test_variance_correctness(copy): rng = np.random.RandomState(0) X = rng.randn(1000, 200) pca = PCA().fit(X) pca_var = pca.explained_variance_ / pca.exp

test_variance_correctness

dashboard/modules/snapshot/snapshot_head.py

[dashboard] Add `component_activities` API (#25996) Add /api/component_activities to the dashboard snapshot router which returns whether various Ray components are considered active This currently only contains a response entry for drivers, but will add entries for other components on request as followups

ray

Python

snapshot_head.py

async def get_component_activities(self, req) -> aiohttp.web.Response: # Get activity information for driver timeout = req.query.get("timeout", None) if timeout and timeout.isdigit(): timeout = int(timeout) else: timeout = 5 driver_activity_info = await self._get_job_activity_info(timeout=timeout) resp = {"driver": dataclasses.asdict(driver_activity_info)} return aiohttp.web.Response( text=json.dumps(resp), content_type="application/json", status=aiohttp.web.HTTPOk.status_code, )

8fc340967654a09cfe00abfc325471258ea5b4e8

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

async def get_component_activities(self, req) -> aiohttp.web.Response: # Get activity information for driver timeout = req.query.get("timeout", None) if timeout and timeout.isdigit(): timeout = int(timeout) else: timeout = 5 dr

get_component_activities

parlai/core/build_data.py

[circle] Fixing broken unit tests (#4343)

ParlAI

Python

build_data.py

def download_from_google_drive(gd_id, destination): URL = 'https://docs.google.com/uc?export=download' with get_http_session() as session: response = session.get(URL, params={'id': gd_id}, stream=True) token = _get_confirm_token(response) or 't' if token: response.close() params = {'id': gd_id, 'confirm': token} response = session.get(URL, params=params, stream=True) CHUNK_SIZE = 32768 with PathManager.open(destination, 'wb') as f: for chunk in response.iter_content(CHUNK_SIZE): if chunk: # filter out keep-alive new chunks f.write(chunk) response.close()

5322cd4f5821e339bf1edab98d93b5a008b97a2b

https://github.com/facebookresearch/ParlAI.git

def download_from_google_drive(gd_id, destination): URL = 'https://docs.google.com/uc?export=download' with get_http_session() as session: response = session.get(URL, params={'id': gd_id}, stream=True) token = _get_confirm_token(response) or 't' if token: response.close() params = {'id': gd_id, 'confirm': token} response = session.get(URL, p

download_from_google_drive

tests/sentry/snuba/test_tasks.py

refs(metric_alerts): Consolidate `QueryDatasets` and `Dataset` (#36894) This refactor pr removes `QueryDatasets` and just uses `Dataset` everywhere. `QueryDatasets` existed before `Dataset`, but `Dataset` is now more widely used and is more up to date. The values here are the same, `Dataset` just supports a few more datasets. We already make sure that only datasets that are valid for alerts can be passed to the alert rules api, so this won't allow people to attempt to create alerts on datasets that don't support them.

sentry

Python

test_tasks.py

def test_event_types(self): self.create_release(self.project, version="something") expected_conditions = [ And( [ Or( [ Condition(Column(name="type"), Op.EQ, "error"), Condition(Column(name="type"), Op.EQ, "default"), ] ), Or( [ Condition( Function( "ifNull", parameters=[Column(name="tags[sentry:release]"), ""] ), Op.IN, ["something"], ), Condition( Function( "ifNull", parameters=[Column(name="tags[sentry:release]"), ""] ), Op.IN, ["123"], ), ] ), ] ), Condition(Column(name="project_id"), Op.IN, (self.project.id,)), ] self.run_test( SnubaQuery.Type.ERROR, Dataset.Events, "count_unique(user)", "release:latest OR release:123", expected_conditions, entity_extra_fields={ "event_types": [ SnubaQueryEventType.EventType.ERROR, SnubaQueryEventType.EventType.DEFAULT, ] }, )

e1482001662b446c7c2be7c9daa19cba562c615c

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

def test_event_types(self): self.create_release(self.project, version="something") expected_conditions = [ And( [ Or( [ Condition

test_event_types

lib/matplotlib/figure.py

DOC: improve grammar and consistency

matplotlib

Python

figure.py

def add_artist(self, artist, clip=False): artist.set_figure(self) self.artists.append(artist) artist._remove_method = self.artists.remove if not artist.is_transform_set(): artist.set_transform(self.transSubfigure) if clip: artist.set_clip_path(self.patch) self.stale = True return artist

9b6abd0b4933811e0a45c2535ab8fd107db65dd9

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

def add_artist(self, artist, clip=False): artist.set_figure(self) self.artists.append(artist) artist._remove_method = self.artists.remove if not artist.is_transform_set():

add_artist

netbox/ipam/forms/models.py

Clean up validation

netbox

Python

models.py

def clean(self): super().clean() interface = self.cleaned_data.get('interface') vminterface = self.cleaned_data.get('vminterface') vlan = self.cleaned_data.get('vlan') if not (interface or vminterface or vlan): raise ValidationError('A termination must specify an interface or VLAN.') if len([x for x in (interface, vminterface, vlan) if x]) > 1: raise ValidationError('A termination can only have one terminating object (an interface or VLAN).') self.instance.assigned_object = interface or vminterface or vlan

4bb4bbce1461bee0644e97900006e3fe6d71a3e4

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

def clean(self): super().clean() interface = self.cleaned_data.get('interface') vminterface = self.cleaned_data.get('vminterface') vlan = self.cleaned_data.get('vlan') if not (interface or vminterface or vlan): raise ValidationError('A termination must specify an inter

clean

mitmproxy/connection.py

make it black!

mitmproxy

Python

connection.py

def __setattr__(self, name, value): if name in ("address", "via"): connection_open = ( self.__dict__.get("state", ConnectionState.CLOSED) is ConnectionState.OPEN ) # assigning the current value is okay, that may be an artifact of calling .set_state(). attr_changed = self.__dict__.get(name) != value if connection_open and attr_changed: raise RuntimeError(f"Cannot change server.{name} on open connection.") return super().__setattr__(name, value)

b3587b52b25077f68116b9852b041d33e7fc6601

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

def __setattr__(self, name, value): if name in ("address", "via"): connection_open = ( self.__dict__.get("state", ConnectionState.CLOSED) is ConnectionState.OPEN ) # assigning the current value is okay, that may be an artifact of calling .set_state(). attr_changed = self.__dict__.get(name) != value if connection_open and attr_changed:

__setattr__

django/db/models/expressions.py

Refs #33476 -- Reformatted code with Black.

django

Python

expressions.py

def as_sql(self, *args, **kwargs): raise ValueError( "This queryset contains a reference to an outer query and may " "only be used in a subquery." )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def as_sql(self, *args, **kwargs): raise ValueError( "This queryset contains a

as_sql

saleor/graphql/app/types.py

Improved metadata permissions for apps (#9726) * Add improvment for handling permissions for apps * Fix failing tests * Apply changes after review * Add missing space in query description * Use permission name fields * Apply changes after review * Use + instead of f for field descriptions

saleor

Python

types.py

def has_access_to_app_public_meta(root, info) -> bool: auth_token = info.context.decoded_auth_token or {} if auth_token.get("type") == JWT_THIRDPARTY_ACCESS_TYPE: _, app_id = from_global_id_or_error(auth_token["app"], "App") else: app_id = info.context.app.id if info.context.app else None if app_id is not None and int(app_id) == root.id: return True requester = get_user_or_app_from_context(info.context) return requester.has_perm(AppPermission.MANAGE_APPS)

20675c93d276101412b22439794d645a0a2fb3bd

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

def has_access_to_app_public_meta(root, info) -> bool: auth_token = info.context.decoded_auth_token or {} if auth_token.get("type") == JWT_THIRDPARTY_ACCESS_TYPE: _, app_id = from_global_id_or_error(auth_token["app"], "App") else: app_id = info.context.app.id if info.context.app else None if app_id is not None and int(app_id) == root.id: return True requester = get_user_or_app_from_context(info.context) return requester.has_perm(AppPermission.MANAGE_APPS)

has_access_to_app_public_meta

saleor/graphql/order/mutations/order_confirm.py

Use dataloader for plugin manager (#10581) * Use dataloader for plugin manager * Temporary fix for context fixtures * Change layer where inactive user is rejected during auth * Missed merge * Rename 'load_pllugins' to 'load_plugin_manager' * Refactor middleware tests that turned to dataloaders tests to separate file * Use anonymous dataloader, remove TODOs * Use relative imports

saleor

Python

order_confirm.py

def perform_mutation(cls, root, info, **data): order = cls.get_instance(info, **data) order.status = OrderStatus.UNFULFILLED order.save(update_fields=["status", "updated_at"]) order_info = fetch_order_info(order) payment = order_info.payment manager = load_plugin_manager(info.context) app = load_app(info.context) if payment_transactions := list(order.payment_transactions.all()): try: # We use the last transaction as we don't have a possibility to # provide way of handling multiple transaction here payment_transaction = payment_transactions[-1] request_charge_action( transaction=payment_transaction, manager=manager, charge_value=payment_transaction.authorized_value, channel_slug=order.channel.slug, user=info.context.user, app=app, ) except PaymentError as e: raise ValidationError( str(e), code=OrderErrorCode.MISSING_TRANSACTION_ACTION_REQUEST_WEBHOOK, ) elif payment and payment.is_authorized and payment.can_capture(): gateway.capture(payment, manager, channel_slug=order.channel.slug) site = load_site(info.context) transaction.on_commit( lambda: order_captured( order_info, info.context.user, app, payment.total, payment, manager, site.settings, ) ) transaction.on_commit( lambda: order_confirmed( order, info.context.user, app, manager, send_confirmation_email=True, ) ) return OrderConfirm(order=order)

ac2d4ac172d37dd8e866b679b1a6538745b43c2b

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

def perform_mutation(cls, root, info, **data): order = cls.get_instance(info, **data) order.status = OrderStatus.UNFULFILLED order.save(update_fields=["status", "updated_at"]) order_info = fetch_order_info(order) payment = order_info.payment manager = load_plugin_manager(info.context) app = load_app(info.context) if payment_transactions := list(order.payment_transactions.all()): try: # We use the last transaction as we don't have a possibility to # provide way of handling multiple transaction here payment_transaction = payment_transactions[-1] request_charge_action( transaction=payment_transaction, manager=manager, charge_value=payment_transaction.authorized_value, channel_slug=order.channel.slug, user=info.context.user, app=app, ) except PaymentError as e: raise ValidationError( str(e), code=OrderErrorCode.MISSING_TRANSACTION_ACTION_REQUEST_WEBHOOK, ) elif payment and payment.is_authorized and payment.can_capture(): gateway.capture(payment, manager, channel_slug=order.channel.slug) site = load_

perform_mutation

sympy/physics/continuum_mechanics/beam.py

Added solving for torsion for circular cross-sections

sympy

Python

beam.py

def apply_moment_load(self, value, start, order, dir="y"): x = self.variable value = sympify(value) start = sympify(start) order = sympify(order) if dir == "x": if not order == -2: self._moment_load_vector[0] += value else: if start in list(self._torsion_moment): self._torsion_moment[start] += value else: self._torsion_moment[start] = value self._load_Singularity[0] += value*SingularityFunction(x, start, order) elif dir == "y": if not order == -2: self._moment_load_vector[1] += value self._load_Singularity[0] += value*SingularityFunction(x, start, order) else: if not order == -2: self._moment_load_vector[2] += value self._load_Singularity[0] += value*SingularityFunction(x, start, order)

efb5f1f2b5a90d9542a4b4be7af75c9af079fa92

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

def apply_moment_load(self, value, start, order, dir="y"): x = self.variable value = sympify(value) start = sympify(start) order = sympify(order) if dir == "x": if not order == -2: self._moment_load_vector[0] += value else: if start in list(self._torsion_moment): self._torsion_moment[start] += value else: self._torsion_moment[start] = value self._load_Singularity[0] += value*SingularityFunction(x, start, order) elif dir == "y": if not order == -2: self._moment_load_vector[1] += value self._load_Singularity[0] += value*SingularityFunction(x, start, order) else: if not order == -2: self._moment_load_vector[2] += value self._load_Singularity[0] += value*SingularityFunction(x, start, order)

apply_moment_load

tests/unit/keyinput/test_keyutils.py

keyutils: Move public functions to KeyInfo This avoids the temptation of creating a Qt.Key() manually, which needs to be checked for ValueError with PyQt 6.2 due to its handling of unknown enum values. This is exactly what happened in RegisterKeyParser, which caused such a ValueError: https://github.com/qutebrowser/qutebrowser/issues/7047#issuecomment-1163288560 Closes #7047

qutebrowser

Python

test_keyutils.py

def test_is_special(key, modifiers, special): assert keyutils.KeyInfo(key, modifiers).is_special() == special @pytest.mark.parametrize('key, ismodifier', [ (Qt.Key.Key_Control, True), (Qt.Key.Key_X, False), (Qt.Key.Key_Super_L, False), # Modifier but not in _MODIFIER_MAP ])

f7753550f2c1dcb2348e4779fd5287166754827e

@pytest.mark.parametrize('key, ismodifier', [ (Qt.Key.Key_Control, True), (Qt.Key.Key_X, False), (Qt.Key.Key_Super_L, False), # Modifier but not in _MODIFIER_MAP ])

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

def test_is_special(key, modifiers, special): assert keyutils.KeyInfo(key, modifiers).is_special() == special @pytest.mark.parametrize('key, ismodifier', [ (Qt.Key.Key_Control, True), (Qt.Key.Key_X, False), (Qt.Key.Key_Super_L, False), # Modifier but not in _MODIFIER_MAP ])

test_is_special

tests/snuba/api/endpoints/test_organization_events_mep.py

ref(MEP): Add new option to query tag values as strings from clickhouse (#36397) Co-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>

sentry

Python

test_organization_events_mep.py

def test_non_metrics_tag_with_implicit_format_metrics_dataset(self): self.store_transaction_metric( 1, tags={"environment": "staging", "transaction": "foo_transaction"}, timestamp=self.min_ago, ) response = self.do_request( { "field": ["test", "p50(transaction.duration)"], "query": "event.type:transaction", "dataset": "metrics", "per_page": 50, } ) assert response.status_code == 400, response.content

5ceaca63890c6c660b4d061e800ccbf8c90c6e20

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

def test_non_metrics_tag_with_implicit_format_metrics_dataset(self): self.store_transaction_metric( 1, tags={"environment": "staging", "transaction": "foo_transaction"}, timestamp=self.min_ago, ) response = self.do_request( { "field": ["test", "p50(transaction.duration)"], "query": "event.type:transaction", "dataset": "metrics", "per_page": 50, } ) assert response.status_code == 400, response.content

test_non_metrics_tag_with_implicit_format_metrics_dataset

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

add python 3.10.4 for windows

XX-Net

Python

sdist.py

def _add_defaults_optional(self): optional = ['test/test*.py', 'setup.cfg'] for pattern in optional: files = filter(os.path.isfile, glob(pattern)) self.filelist.extend(files)

8198943edd73a363c266633e1aa5b2a9e9c9f526

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

def _add_defaults_optional(self): optional = ['test/test*.py',

_add_defaults_optional

plugins/extract/pipeline.py

extract: Add batch processing mode

faceswap

Python

pipeline.py

def input_queue(self) -> EventQueue: qname = f"extract{self._instance}_{self._current_phase[0]}_in" retval = self._queues[qname] logger.trace("%s: %s", qname, retval) # type: ignore return retval

13cfb3f39e72e9ca181f173b7b3db2a048db0d08

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

def input_queue(self) -> EventQueue: qname = f"extract{self._instance}_{self._current_phase[0]}_in" retval = self._queu

input_queue

tests/admin_views/tests.py

Refs #33476 -- Reformatted code with Black.

django

Python

tests.py

def test_custom_admin_site_view(self): self.client.force_login(self.superuser) response = self.client.get(reverse("admin2:my_view")) self.assertEqual(response.content, b"Django is a magical pony!")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def test_custom_admin_site_view(self): self.client.

test_custom_admin_site_view

pandas/tests/extension/test_arrow.py

BUG/TST: fix a bunch of arraymanager+pyarrow tests (#48428) * BUG/TST: fix a bunch of arraymanager+pyarrow tests * remove unnecessary using_array_manager

pandas

Python

test_arrow.py

def test_setitem_mask_aligned(self, data, as_callable, setter, request): tz = getattr(data.dtype.pyarrow_dtype, "tz", None) if pa_version_under2p0 and tz not in (None, "UTC"): request.node.add_marker( pytest.mark.xfail( reason=(f"Not supported by pyarrow < 2.0 with timestamp type {tz}") ) ) super().test_setitem_mask_aligned(data, as_callable, setter)

12dce19a74b7cd5badad0f61ca079b873c1b6089

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

def test_setitem_mask_aligned(self, data, as_callable, setter, request): tz = getattr(data.dtype.pyarrow_dtype, "tz", None) if pa_version_under2p0 and tz not in (None, "UTC"): request.node.add_marker( pytest.mark.xfail( reason=(f"Not supported by pyarrow < 2.0 with timestamp type {tz}") ) ) super().test_setitem_mask_aligned(data, as

test_setitem_mask_aligned

wagtail/admin/tests/test_contentstate.py

Reformat with black

wagtail

Python

test_contentstate.py

def test_wrapped_block_retains_key(self): # Test a block which uses a wrapper correctly receives the key defined on the inner element converter = ContentstateConverter(features=["h1", "ol", "bold", "italic"]) result = converter.to_database_format( json.dumps( { "entityMap": {}, "blocks": [ { "inlineStyleRanges": [], "text": "The rules of Fight Club", "depth": 0, "type": "header-one", "key": "00000", "entityRanges": [], }, { "inlineStyleRanges": [], "text": "You do not talk about Fight Club.", "depth": 0, "type": "ordered-list-item", "key": "00001", "entityRanges": [], }, { "inlineStyleRanges": [], "text": "You do not talk about Fight Club.", "depth": 0, "type": "ordered-list-item", "key": "00002", "entityRanges": [], }, ], } ) ) self.assertHTMLEqual( result, , )

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def test_wrapped_block_retains_key(self): # Test a block which uses a wrapper correctly receives the key defined on the inner element converter = ContentstateConverter(features=["h1", "ol", "bold", "italic"]) result = converter.to_database_format( json.dumps( { "entityMap": {}, "blocks": [ { "inlineStyleRanges": [], "text": "The rules of Fight Club", "depth": 0, "type": "header-one", "key": "00000", "entityRanges": [], }, { "inlineStyleRanges": [], "text": "You do not talk about Fight Club.", "depth": 0, "type": "ordered-list-item", "key": "00001", "entityRanges": [], }, { "inlineStyleRanges": [], "text": "You do not talk about Fight Clu

test_wrapped_block_retains_key

airbyte-integrations/connectors/source-mixpanel/unit_tests/test_property_transformation.py

:tada: Source Mixpanel: Beta preparation (#13372) * Add extra mode to Source, to allow run acceptance tests * move streams into distinct modules * Add property name transformation for Export stream for avoiding collisions * Update doc * Add `date_window_size`

airbyte

Python

test_property_transformation.py

def export_response(): return setup_response( 200, { "event": "Problem event", "properties": { "distinct_id": "1d694fd9-31a5-4b99-9eef-ae63112063ed", "$userName": "1", "userName": "2", "username": "3", }, }, )

d79b319819650f99fae2ab8c6c8d3ab25d474cf1

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

def export_response(): return setup_response( 200, { "event": "Problem event", "properties": { "distinct_id": "1d694fd9-31a5-4b99-9eef-ae6

export_response

airbyte-integrations/connectors/source-google-ads/unit_tests/test_source.py

Source Google Ads: Improve unit and integration tests (#12651) * #12650 source Googel ads: tests * #12650 source google ads: add changelog item * #12650 source google ads: add comments to tests * auto-bump connector version Co-authored-by: Octavia Squidington III <octavia-squidington-iii@users.noreply.github.com>

airbyte

Python

test_source.py

def client_mock(config): google_api = GoogleAds(credentials=config["credentials"], customer_id=config["customer_id"]) client = AdGroupAdReport( start_date=config["start_date"], api=google_api, conversion_window_days=config["conversion_window_days"], time_zone="local" ) client._customer_id = "1234567890" return client @pytest.fixture()

d4f8b25b8e3e109db866352cf1dcec0d73c92cbd

@pytest.fixture()

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

def client_mock(config): google_api = GoogleAds(credentials=config["credentials"], customer_id=config["customer_id"]) client = AdGroupAdReport( start_date=config["start_date"], api=google_api, conversion_window_days=config["

client_mock

erpnext/patches/v14_0/rearrange_company_fields.py

style: format code with black

erpnext

Python

rearrange_company_fields.py

def execute(): custom_fields = { "Company": [ dict( fieldname="hra_section", label="HRA Settings", fieldtype="Section Break", insert_after="asset_received_but_not_billed", collapsible=1, ), dict( fieldname="basic_component", label="Basic Component", fieldtype="Link", options="Salary Component", insert_after="hra_section", ), dict( fieldname="hra_component", label="HRA Component", fieldtype="Link", options="Salary Component", insert_after="basic_component", ), dict(fieldname="hra_column_break", fieldtype="Column Break", insert_after="hra_component"), dict( fieldname="arrear_component", label="Arrear Component", fieldtype="Link", options="Salary Component", insert_after="hra_column_break", ), dict( fieldname="non_profit_section", label="Non Profit Settings", fieldtype="Section Break", insert_after="arrear_component", collapsible=1, ), dict( fieldname="company_80g_number", label="80G Number", fieldtype="Data", insert_after="non_profit_section", ), dict( fieldname="with_effect_from", label="80G With Effect From", fieldtype="Date", insert_after="company_80g_number", ), dict( fieldname="non_profit_column_break", fieldtype="Column Break", insert_after="with_effect_from" ), dict( fieldname="pan_details", label="PAN Number", fieldtype="Data", insert_after="non_profit_column_break", ), ] } create_custom_fields(custom_fields, update=True)

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def execute(): custom_fields = { "Company": [ dict( fieldname="hra_section", label="HRA Settings", fieldtype="Section Break", insert_after="asset_received_but_not_billed", collapsible=1, ), dict( fieldname="basic_component", label="Basic Component", fieldtype="Link", options="Salary Component", insert_after="hra_section", ), dict( fieldname="hra_component", label="HRA Component", fieldtype="Link", options="Salary Compo

execute

django/templatetags/i18n.py

Refs #33476 -- Reformatted code with Black.

django

Python

i18n.py

def do_get_available_languages(parser, token): # token.split_contents() isn't useful here because this tag doesn't accept variable as arguments args = token.contents.split() if len(args) != 3 or args[1] != "as": raise TemplateSyntaxError( "'get_available_languages' requires 'as variable' (got %r)" % args ) return GetAvailableLanguagesNode(args[2]) @register.tag("get_language_info")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@register.tag("get_language_info")

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

def do_get_available_languages(parser, token): # token.split_contents() isn't useful here because this tag doesn't accept variable as arguments args = token.contents.split() if len(args) != 3 or args[1] != "as":

do_get_available_languages

setup.py

Bump Python version to 3.7~3.9 (#4475)

nni

Python

setup.py

def _setup(): setuptools.setup( name = 'nni', version = release or '999.dev0', description = 'Neural Network Intelligence project', long_description = open('README.md', encoding='utf-8').read(), long_description_content_type = 'text/markdown', url = 'https://github.com/Microsoft/nni', author = 'Microsoft NNI Team', author_email = 'nni@microsoft.com', license = 'MIT', classifiers = [ 'License :: OSI Approved :: MIT License', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows :: Windows 10', 'Operating System :: POSIX :: Linux', 'Programming Language :: Python :: 3 :: Only', 'Topic :: Scientific/Engineering :: Artificial Intelligence', ], packages = _find_python_packages(), package_data = { 'nni': _find_requirements_txt() + _find_default_config(), # setuptools issue #1806 'nni_node': _find_node_files() # note: this does not work before building }, data_files = _get_data_files(), python_requires = '>=3.7', install_requires = _read_requirements_txt('dependencies/required.txt'), extras_require = { 'SMAC': _read_requirements_txt('dependencies/required_extra.txt', 'SMAC'), 'BOHB': _read_requirements_txt('dependencies/required_extra.txt', 'BOHB'), 'PPOTuner': _read_requirements_txt('dependencies/required_extra.txt', 'PPOTuner'), 'DNGO': _read_requirements_txt('dependencies/required_extra.txt', 'DNGO'), }, setup_requires = ['requests'], entry_points = { 'console_scripts' : [ 'nnictl = nni.tools.nnictl.nnictl:parse_args' ] }, cmdclass = { 'build': Build, 'build_ts': BuildTs, 'clean': Clean, 'develop': Develop, } )

c56568c9733fa286c1753a54fab2fd892a5cf6d5

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

def _setup(): setuptools.setup( name = 'nni', version = release or '999.dev0', description = 'Neural Network Intelligence project', long_description = open('README.md', encoding='utf-8').read(), long_description_content_type = 'text/markdown', url = 'https://github.com/Microsoft/nni', author = 'Microsoft NNI Team', author_email = 'nni@microsoft.com', license = 'MIT', classifiers = [ 'License :: OSI Approved :: MIT License', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows :: Windows 10', 'Operating System :: POSIX :: Linux', 'Programming Language :: Python :: 3 :: Only', 'Topic :: Scientific/Engineering :: Artificial Intelligence', ], packages = _find_python_packages(), package_data = { 'nni': _find_requirements_txt() + _find_default_config(), # setuptools issue #1806 'nni_node': _find_node_files() # note: this does not work before building }, data_files = _get_data_files(), python_requires = '>=3.7', install_requires = _read_requirements_txt('dependencies/required.txt'), extras_require = { 'SMAC': _read_requirements_txt('dependencies/required_extra.txt', 'SMAC'), 'BOHB': _read_requirements_txt('dependencies/required_extra.txt', 'BOHB'), 'PPOTuner': _read_requirements_txt('dependencies/required_extra.txt', 'PPOTuner'), 'DNGO': _read_requirements_txt('dependencies/required_extra.txt', 'DNGO'), }, setup_requires = ['requests'], entry_points

_setup

tests/models/cvt/test_modeling_cvt.py

Add CvT (#17299) * Adding cvt files * Adding cvt files * changes in init file * Adding cvt files * changes in init file * Style fixes * Address comments from code review * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Format lists in docstring * Fix copies * Apply suggestion from code review Co-authored-by: AnugunjNaman <anugunjjha@gmail.com> Co-authored-by: Ayushman Singh <singhayushman13@protonmail.com> Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

transformers

Python

test_modeling_cvt.py

def create_and_test_config_common_properties(self): config = self.config_class(**self.inputs_dict) self.parent.assertTrue(hasattr(config, "embed_dim")) self.parent.assertTrue(hasattr(config, "num_heads"))

adc0ff25028d29af30386f2d7d3f85e290fbef57

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

def create_and_test_config_common_properties(self): config = self.config_class(**self.inputs_dict) self.parent.assertTrue(hasattr(config, "embed_dim")) self.parent.assertTrue(hasattr(c

create_and_test_config_common_properties

gensim/models/keyedvectors.py

Fix typo in word2vec and KeyedVectors docstrings (#3365) * Add missing word in word2vec docstring * Fix docstring typo in KeyedVectors distances() word_or_vector, not word_or_vectors

gensim

Python

keyedvectors.py

def distances(self, word_or_vector, other_words=()): if isinstance(word_or_vector, _KEY_TYPES): input_vector = self.get_vector(word_or_vector) else: input_vector = word_or_vector if not other_words: other_vectors = self.vectors else: other_indices = [self.get_index(word) for word in other_words] other_vectors = self.vectors[other_indices] return 1 - self.cosine_similarities(input_vector, other_vectors)

7f314ee10c9ad83816aa795c5ef6ebc378de3acf

https://github.com/RaRe-Technologies/gensim.git

def distances(self, word_or_vector, other_words=()): if isinstance(word_or_vector, _KEY_TYPES): input_vector = self.get_vector(word_or_vector) else: input_vector = word_or_vector if not other_words: other_vectors = self.vectors else: other_indices = [self.get_index(word) for word in

distances

tests/admin_default_site/tests.py

Refs #33476 -- Reformatted code with Black.

django

Python

tests.py

def test_use_custom_admin_site(self): self.assertEqual(admin.site.__class__.__name__, "CustomAdminSite")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def test_use_custom_admin_site(self): self.assertEqual(admin.site.__class__.__name__, "CustomAdminSite")

test_use_custom_admin_site