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semeru

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code-code-galeras-code-completion-from-docstring-3k-deduped

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Semeru Lab 7

@receiver(post_save, sender=Annotation)

label_studio/tasks/models.py

def delete_project_summary_annotations_before_updating_annotation(sender, instance, **kwargs): try: old_annotation = sender.objects.get(id=instance.id) except Annotation.DoesNotExist: # annotation just created - do nothing return old_annotation.decrease_project_summary_counters() # update task counters if annotation changes it's was_cancelled status task = instance.task if old_annotation.was_cancelled != instance.was_cancelled: if instance.was_cancelled: task.cancelled_annotations = task.cancelled_annotations + 1 task.total_annotations = task.total_annotations - 1 else: task.cancelled_annotations = task.cancelled_annotations - 1 task.total_annotations = task.total_annotations + 1 task.update_is_labeled() Task.objects.filter(id=instance.task.id).update( is_labeled=task.is_labeled, total_annot

fix: DEV-2406: Fix counters for skipped annotations (#2364) * fix: DEV-2406: Fix counters for skipped annotations * Fixes Co-authored-by: makseq-ubnt <makseq@gmail.com>

delete_project_summary_annotations_before_updating_annotation

50583d9ed6bfd2a837d0168e1690529a31efa2f7

label-studio

models.py

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

Python

def delete_project_summary_annotations_before_updating_annotation(sender, instance, **kwargs): try: old_annotation = sender.objects.get(id=instance.id) except Annotation.DoesNotExist: # annotation just created - do nothing return old_annotation.decrease_project_summary_counters() # update task counters if annotation changes it's was_cancelled status task = instance.task if old_annotation.was_cancelled != instance.was_cancelled: if instance.was_cancelled: task.cancelled_annotations = task.cancelled_annotations + 1 task.total_annotations = task.total_annotations - 1 else: task.cancelled_annotations = task.cancelled_annotations - 1 task.total_annotations = task.total_annotations + 1 task.update_is_labeled() Task.objects.filter(id=instance.task.id).update( is_labeled=task.is_labeled, total_annotations=task.total_annotations, cancelled_annotations=task.cancelled_annotations ) @receiver(post_save, sender=Annotation)

modules/image/keypoint_detection/hand_pose_localization/model.py

def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_threads): # 对运行位置进行配置 if use_gpu:

update hand_pose_localization (#1967) * update hand_pose_localization * add clean func

load_config

6b42963d62833925ffed1cdb73400e7d528a5353

PaddleHub

model.py

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

Python

def load_config(self, modelpath, use_gpu, gpu_id, use_mkldnn, cpu_threads): # 对运行位置进行配置 if use_gpu: try: int(os.environ.get('CUDA_VISIBLE_DEVICES')) except Exception: print( ) use_gpu = False if os.path.isdir(modelpath): if os.path.exists(os.path.join(modelpath, "__params__")): # __model__ + __params__ model = os.path.join(modelpath, "__model__") params = os.path.join(modelpath, "__params__") config = Config(model, params) elif os.path.exists(os.path.join(modelpath, "params")): # model + params model = os.path.join(modelpath, "model") params = os.path.join(modelpath, "params") config = Config(model, params) elif os.path.exists(os.path.join(modelpath, "__model__")): # __model__ + others config = Config(modelpath) else: raise Exception( "Error! Can\'t find the model in: %s. Please check your model path." % os.path.abspath(modelpath)) elif os.path.exists(modelpath + ".pdmodel"): # *.pdmodel + *.pdiparams model = modelpath + ".pdmodel" params = modelpath + ".pdiparams" config = Config(model, params) elif isinstance(modelpath, Config): config = modelpath else: raise Exception( "Error! Can\'t find the model in: %s. Please check your model path." % os.path.abspath(modelpath)) # 设置参数 if use_gpu: config.enable_use_gpu(100, gpu_id) else: config.disable_gpu() config.set_cpu_math_library_num_threads(cpu_threads) if use_mkldnn: config.enable_mkldnn() config.disable_glog_info() # 返回配置 return config # 预测器创建函数

src/sentry/lang/javascript/processor_smcache.py

def trim_line(line, column=0): line = line.strip("\n") ll = len(line) if ll <= 150: return line if column > ll: column = ll start = max(column - 60, 0) # Round down if it brings us close to the edge if start < 5: start = 0 end = min(start + 140, ll) # Round up to the end if it's close if end > ll - 5: end = ll # If we are bumped all the way to the end, # make sure we still get a full 140 characters in the line if end == ll: start = max(end - 140, 0) line = line[start:end] if end < ll: # we've snipped from the end line += " {snip}" if start > 0:

feat(processor): Use JavaScriptSmCacheStacktraceProcessor by default for internal projects (#41390) This PR builds on top of https://github.com/getsentry/sentry/pull/40951/ and prepares us for gradual rollout.

trim_line

67c8215ba3f246937fd7e1fbb02f33050a1c0456

sentry

processor_smcache.py

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

Python

def trim_line(line, column=0): line = line.strip("\n") ll = len(line) if ll <= 150: return line if column > ll: column = ll start = max(column - 60, 0) # Round down if it brings us close to the edge if start < 5: start = 0 end = min(start + 140, ll) # Round up to the end if it's close if end > ll - 5: end = ll # If we are bumped all the way to the end, # make sure we still get a full 140 characters in the line if end == ll: start = max(end - 140, 0) line = line[start:end] if end < ll: # we've snipped from the end line += " {snip}" if start > 0: # we've snipped from the beginning line = "{snip} " + line return line

tests/storage/test_background_update.py

def test_background_update_default_batch_set_by_config(self): self.get_success( self.store.db_pool.simple_insert( "background_updates", values={"update_name": "test_update", "progress_json": '{"my_key": 1}'}, ) ) self.update_handler.side_effect = self.update self.update_handler.reset_mock() res = self.get_success( self.updates.do_next_background_update(False), by=0.

Add config settings for background update parameters (#11980)

test_background_update_default_batch_set_by_config

ef3619e61d84493d98470eb2a69131d15eb1166b

synapse

test_background_update.py

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

Python

def test_background_update_default_batch_set_by_config(self): self.get_success( self.store.db_pool.simple_insert( "background_updates", values={"update_name": "test_update", "progress_json": '{"my_key": 1}'}, ) ) self.update_handler.side_effect = self.update self.update_handler.reset_mock() res = self.get_success( self.updates.do_next_background_update(False), by=0.01, ) self.assertFalse(res) # on the first call, we should get run with the default background update size specified in the config self.update_handler.assert_called_once_with({"my_key": 1}, 20)

django/contrib/sessions/backends/file.py

def _expiry_date(self, session_data): return session_data.get("_session_expiry") or ( self._last_modification() + datetime.timedelta(seconds=self.get_session_cookie_ag

Refs #33476 -- Reformatted code with Black.

_expiry_date

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

file.py

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

Python

def _expiry_date(self, session_data): return session_data.get("_session_expiry") or ( self._last_modification() + datetime.timedelta(seconds=self.get_session_cookie_age()) )

src/transformers/models/trocr/processing_trocr.py

def __call__(self, *args, **kwargs): # For backward compatibility if self._in_target_context_manager: return self.current_processor(*args, **kwargs) images = kwargs.pop("images", None) text = kwargs.pop("text", None) if len(args) > 0: images = args[0] args = args[1:] if images is None and text is None: raise ValueError("Yo

Change audio kwarg to images in TROCR processor (#18421) Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

__call__

0b8c1b6994082950044452a670e8417a5ebc2db0

transformers

processing_trocr.py

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

Python

def __call__(self, *args, **kwargs): # For backward compatibility if self._in_target_context_manager: return self.current_processor(*args, **kwargs) images = kwargs.pop("images", None) text = kwargs.pop("text", None) if len(args) > 0: images = args[0] args = args[1:] if images is None and text is None: raise ValueError("You need to specify either an `images` or `text` input to process.") if images is not None: inputs = self.feature_extractor(images, *args, **kwargs) if text is not None: encodings = self.tokenizer(text, **kwargs) if text is None: return inputs elif images is None: return encodings else: inputs["labels"] = encodings["input_ids"] return inputs

netbox/extras/reports.py

def get_report(module_name, report_name): reports = get_reports() module = reports.get(module_name) if module is None: return None report = module.get(report_name) if report is None: return None return report

Allow reports to be nested in submodules

get_report

356ff457be08d5527920c617eb598f24a6edbc3d

netbox

reports.py

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

Python

def get_report(module_name, report_name): reports = get_reports() module = reports.get(module_name) if module is None: return None report = module.get(report_name) if report is None: return None return report

tests/config/test_workers.py

def test_worker_duty_configs(self) -> None: worker1_config = self._make_worker_config( worker_app="synapse.app.generic_worker", worker_name="worker1", extras={ "notify_appservice

Add the `update_user_directory_from_worker` configuration option (superseding `update_user_directory`) to allow a generic worker to be designated as the worker to update the user directory. (#12654) Co-authored-by: Shay <hillerys@element.io>

test_worker_duty_configs

699192fc1a1055a4bec2345bc80f120f28470c73

synapse

test_workers.py

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

Python

def test_worker_duty_configs(self) -> None: worker1_config = self._make_worker_config( worker_app="synapse.app.generic_worker", worker_name="worker1", extras={ "notify_appservices_from_worker": "worker2", "update_user_directory_from_worker": "worker1", }, ) self.assertFalse(worker1_config.should_notify_appservices) self.assertTrue(worker1_config.should_update_user_directory) worker2_config = self._make_worker_config( worker_app="synapse.app.generic_worker", worker_name="worker2", extras={ "notify_appservices_from_worker": "worker2", "update_user_directory_from_worker": "worker1", }, ) self.assertTrue(worker2_config.should_notify_appservices) self.assertFalse(worker2_config.should_update_user_directory)

python/ray/runtime_context.py

def actor_id(self): # only worker mode has actor_id assert ( self.worker.mode == ray.worker.

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

actor_id

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

runtime_context.py

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

Python

def actor_id(self): # only worker mode has actor_id assert ( self.worker.mode == ray.worker.WORKER_MODE ), f"This method is only available when the process is a\ worker. Current mode: {self.worker.mode}" actor_id = self.worker.actor_id return actor_id if not actor_id.is_nil() else None

wagtail/contrib/settings/tests/test_admin.py

def test_redirect_to_current(self): start_url = reverse("wagtailsettings

Reformat with black

test_redirect_to_current

d10f15e55806c6944827d801cd9c2d53f5da4186

wagtail

test_admin.py

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

Python

def test_redirect_to_current(self): start_url = reverse("wagtailsettings:edit", args=["tests", "testsetting"]) dest_url = reverse( "wagtailsettings:edit", args=["tests", "testsetting", self.other_site.pk] ) response = self.client.get( start_url, follow=True, HTTP_HOST=self.other_site.hostname ) self.assertRedirects( response, dest_url, status_code=302, fetch_redirect_response=False )

freqtrade/freqai/base_models/FreqaiMultiOutputClassifier.py

def fit(self, X, y, sample_weight=None, fit_params=None): if not hasattr(self.estimator, "fit"): raise ValueError("The base estimator should implement a fit method") y = self._validate_data(X="no_validation", y=y, multi_output=True) if is_classifier(self): check_classification_targets(y) if y.ndim == 1: raise ValueError( "y must have at least two dimensions for " "multi-output regression but has only one." ) if sample_weight is not None and not has_fit_parameter( self.estimator, "sample_weight" ): raise ValueError("Underlying estimator does not support sample weights.") if not fit_params: fit_params = [None] * y.shape[1] self.estimators_ = Parallel(n_jobs=self.n_jobs)( delayed(_fit_estimator)( self.estimator, X, y[:, i], sample_weight, **fit_params[i] )

add strat and config for testing on PR

fit

217add70bd010cae584db5aa13a7d5e76011e2bd

freqtrade

FreqaiMultiOutputClassifier.py

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

Python

def fit(self, X, y, sample_weight=None, fit_params=None): if not hasattr(self.estimator, "fit"): raise ValueError("The base estimator should implement a fit method") y = self._validate_data(X="no_validation", y=y, multi_output=True) if is_classifier(self): check_classification_targets(y) if y.ndim == 1: raise ValueError( "y must have at least two dimensions for " "multi-output regression but has only one." ) if sample_weight is not None and not has_fit_parameter( self.estimator, "sample_weight" ): raise ValueError("Underlying estimator does not support sample weights.") if not fit_params: fit_params = [None] * y.shape[1] self.estimators_ = Parallel(n_jobs=self.n_jobs)( delayed(_fit_estimator)( self.estimator, X, y[:, i], sample_weight, **fit_params[i] ) for i in range(y.shape[1]) ) self.classes_ = [] for estimator in self.estimators_: self.classes_.extend(estimator.classes_) if hasattr(self.estimators_[0], "n_features_in_"): self.n_features_in_ = self.estimators_[0].n_features_in_ if hasattr(self.estimators_[0], "feature_names_in_"): self.feature_names_in_ = self.estimators_[0].feature_names_in_ return self

nni/retiarii/nn/pytorch/api.py

def inner_choices(self) -> Iterable['ValueChoice']: for arg in self.arguments: if isinstance(arg, ValueChoiceX): yield from arg.inner_choices()

Composition of `ValueChoice` (#4435)

inner_choices

a36dc07e8d39ec4438fd660c98f6f4551ff5f4a6

nni

api.py

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

Python

def inner_choices(self) -> Iterable['ValueChoice']: for arg in self.arguments: if isinstance(arg, ValueChoiceX): yield from arg.inner_choices()

sympy/tensor/index_methods.py

def get_indices(expr): # We call ourself recursively to d

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

get_indices

24f1e7730119fe958cc8e28411f790c9a5ec04eb

sympy

index_methods.py

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

Python

def get_indices(expr): # We call ourself recursively to determine indices of sub expressions. # break recursion if isinstance(expr, Indexed): c = expr.indices inds, dummies = _remove_repeated(c) return inds, {} elif expr is None: return set(), {} elif isinstance(expr, Idx): return {expr}, {} elif expr.is_Atom: return set(), {} # recurse via specialized functions else: if expr.is_Mul: return _get_indices_Mul(expr) elif expr.is_Add: return _get_indices_Add(expr) elif expr.is_Pow or isinstance(expr, exp): return _get_indices_Pow(expr) elif isinstance(expr, Piecewise): # FIXME: No support for Piecewise yet return set(), {} elif isinstance(expr, Function): # Support ufunc like behaviour by returning indices from arguments. # Functions do not interpret repeated indices across arguments # as summation ind0 = set() for arg in expr.args: ind, sym = get_indices(arg) ind0 |= ind return ind0, sym # this test is expensive, so it should be at the end elif not expr.has(Indexed): return set(), {} raise NotImplementedError( "FIXME: No specialized handling of type %s" % type(expr))

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

def dist_location(dist): # type: (Distribution) -> str egg_link = egg_link_path(dist) if egg_link: return normalize_path(egg_lin

upd; format

dist_location

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

misc.py

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

Python

def dist_location(dist): # type: (Distribution) -> str egg_link = egg_link_path(dist) if egg_link: return normalize_path(egg_link) return normalize_path(dist.location)

pandas/_testing/_io.py

def can_connect(url, error_classes=None): if error_classes is None: error_classes = _get_default_network_errors() try: with urlopen(url, time

TST: Check network URL statuses in tests (#45949)

can_connect

4bc68b39511fdf1dffe91bd315ffee9565b90d1a

pandas

_io.py

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

Python

def can_connect(url, error_classes=None): if error_classes is None: error_classes = _get_default_network_errors() try: with urlopen(url, timeout=20) as response: # Timeout just in case rate-limiting is applied if response.status != 200: return False except error_classes: return False else: return True # ------------------------------------------------------------------ # File-IO

tests/sentry/incidents/endpoints/test_serializers.py

def test_valid_slack_channel_id(self): integration = Integration.objects.create( external_id="1", provider="slack", metadata={"access_token": "xoxp-xxxxxxxxx-xxxxxxxxxx-xxxxxxxxxxxx"}, ) integration.add_organization(self.organization, self.user) base_params = self.valid_params.copy() base_params.update( { "type": AlertRuleTriggerAction.get_registered_type( AlertRuleTriggerAction.Type.SLACK ).slug, "targetType": ACTION_TARGET_TYPE_TO_STRING[ AlertRuleTriggerAction.TargetType.SPECIFIC ], "targetIdentifier": "merp", "integration": str(integration.id), } ) context = self.context.copy() context.update({"input_channel_id": "CSVK0921"}) responses.add( method=responses.GET, url="https://

ref(serializers): Split up large file (#31359)

test_valid_slack_channel_id

efb962b72c649c18c466afae41722384d111824b

sentry

test_serializers.py

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

Python

def test_valid_slack_channel_id(self): integration = Integration.objects.create( external_id="1", provider="slack", metadata={"access_token": "xoxp-xxxxxxxxx-xxxxxxxxxx-xxxxxxxxxxxx"}, ) integration.add_organization(self.organization, self.user) base_params = self.valid_params.copy() base_params.update( { "type": AlertRuleTriggerAction.get_registered_type( AlertRuleTriggerAction.Type.SLACK ).slug, "targetType": ACTION_TARGET_TYPE_TO_STRING[ AlertRuleTriggerAction.TargetType.SPECIFIC ], "targetIdentifier": "merp", "integration": str(integration.id), } ) context = self.context.copy() context.update({"input_channel_id": "CSVK0921"}) responses.add( method=responses.GET, url="https://slack.com/api/conversations.info", status=200, content_type="application/json", body=json.dumps({"ok": "true", "channel": {"name": "merp", "id": "CSVK0921"}}), ) serializer = AlertRuleTriggerActionSerializer(context=context, data=base_params) assert serializer.is_valid() serializer.save() # # Make sure the action was created. alert_rule_trigger_actions = list( AlertRuleTriggerAction.objects.filter(integration=integration) ) assert len(alert_rule_trigger_actions) == 1

python3.10.4/Lib/ctypes/_aix.py

def get_legacy(members): if AIX_ABI == 64: # AIX 64-bit member is

add python 3.10.4 for windows

get_legacy

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

_aix.py

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

Python

def get_legacy(members): if AIX_ABI == 64: # AIX 64-bit member is one of shr64.o, shr_64.o, or shr4_64.o expr = r'shr4?_?64\.o' member = get_one_match(expr, members) if member: return member else: # 32-bit legacy names - both shr.o and shr4.o exist. # shr.o is the preferred name so we look for shr.o first # i.e., shr4.o is returned only when shr.o does not exist for name in ['shr.o', 'shr4.o']: member = get_one_match(re.escape(name), members) if member: return member return None

salt/states/iptables.py

def set_policy(name, table="filter", family="ipv4", **kwargs): ret = {"name": name, "changes": {}, "result": None, "comment": ""} for ignore in _STATE_INTERNAL_KEYWORDS: if ignore in kwargs: del kwargs[ignore] if ( __salt__["iptables.get_policy"](table, kwargs["chain"], family) == kwargs["policy"] ): ret["result"] = True ret[ "comment" ] = "iptables default policy for chain {} on table {} for {} already set to {}".format( kwargs["chain"], table, family, kwargs["policy"] ) return ret if __opts__["test"]: ret["comment"] = ( "iptables default policy for chain {} on table {} for {} needs to be set" " to {}".format(kwargs["chain"], table, family, kwargs["policy"]) ) return ret if not __salt__["iptables.set_policy"]( table, kwargs["chain"], kwargs["policy"], family ): ret["changes"] = {"locale": name} ret["result"] = True ret

salt.states.iptables: Document the save parameter The examples mention this, but the reference documentation did not, and it isn't obvious from the example that minimal installations of some operating systems (in particular Debian) don't have all the necessary packages to make it effective, even if iptables itself is installed. Signed-off-by: Simon McVittie <smcv@collabora.com>

set_policy

497ebde11325333cf8e1c0e4eeec185a55fb6ace

salt

iptables.py

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

Python

def set_policy(name, table="filter", family="ipv4", **kwargs): ret = {"name": name, "changes": {}, "result": None, "comment": ""} for ignore in _STATE_INTERNAL_KEYWORDS: if ignore in kwargs: del kwargs[ignore] if ( __salt__["iptables.get_policy"](table, kwargs["chain"], family) == kwargs["policy"] ): ret["result"] = True ret[ "comment" ] = "iptables default policy for chain {} on table {} for {} already set to {}".format( kwargs["chain"], table, family, kwargs["policy"] ) return ret if __opts__["test"]: ret["comment"] = ( "iptables default policy for chain {} on table {} for {} needs to be set" " to {}".format(kwargs["chain"], table, family, kwargs["policy"]) ) return ret if not __salt__["iptables.set_policy"]( table, kwargs["chain"], kwargs["policy"], family ): ret["changes"] = {"locale": name} ret["result"] = True ret["comment"] = "Set default policy for {} to {} family {}".format( kwargs["chain"], kwargs["policy"], family ) if "save" in kwargs and kwargs["save"]: if kwargs["save"] is not True: filename = kwargs["save"] else: filename = None __salt__["iptables.save"](filename=filename, family=family) ret[ "comment" ] = "Set and saved default policy for {} to {} family {}".format( kwargs["chain"], kwargs["policy"], family ) return ret else: ret["result"] = False ret["comment"] = "Failed to set iptables default policy" return ret

tests/end2end/fixtures/quteprocess.py

def _after_start(self): delay = self.request.config.getoption('--qute-delay-start') if delay: with self.disable_capturing(): print(f"- waiting {delay}ms for quteprocess " f"(PID: {self.proc.processId()})...") time.

quteprocess: Add --qute-delay-start Allows for some rudimentary debugging of subprocesses.

_after_start

496c14bc9e0afb6c6787a0a167a1cb623ce5e2ff

qutebrowser

quteprocess.py

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

Python

def _after_start(self): delay = self.request.config.getoption('--qute-delay-start') if delay: with self.disable_capturing(): print(f"- waiting {delay}ms for quteprocess " f"(PID: {self.proc.processId()})...") time.sleep(delay / 1000)

salt/modules/vault.py

def list_secrets(path, default=None): if default is None: default = CommandExecutionError log.debug("Listing vault secret keys for %s in %s", __grains__["id"], path) version2 = __utils__["vault.is_v2"](path) if version2["v2"]: path = version2["metadata"] try: url = "v1/{}".format(path) response = __utils__["vault.make_request"]("LIST", url) if response.status_code != 200: response

Don't pass Error as default value in vault.py

list_secrets

681ea37f212619266424f00173d0affa27002071

salt

vault.py

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

Python

def list_secrets(path, default=None): if default is None: default = CommandExecutionError log.debug("Listing vault secret keys for %s in %s", __grains__["id"], path) version2 = __utils__["vault.is_v2"](path) if version2["v2"]: path = version2["metadata"] try: url = "v1/{}".format(path) response = __utils__["vault.make_request"]("LIST", url) if response.status_code != 200: response.raise_for_status() return response.json()["data"] except Exception as err: # pylint: disable=broad-except if default is CommandExecutionError: raise CommandExecutionError( "Failed to list secrets! {}: {}".format(type(err).__name__, err) ) return default

@RunIf(skip_windows=True, fairscale=True) @mock.patch("pytorch_lightning.strategies.DDPShardedStrategy._wrap_optimizers", autospec=True) @pytest.mark.parametrize(["params", "expected_buffer_size"], [(dict(), 0), (dict(reduce_buffer_size=128), 128)]) @pytest.mark.parametrize("num_nodes", [1, 2])

tests/strategies/test_sharded_strategy.py

def test_custom_kwargs_sharded(tmpdir, cls): strategy = cls(reduce_fp16=True) strategy.model = Mock(spec=LightningModule) strategy.model.trainer = Mock() class_name = "sharded" if isinstance(strategy, DDPShardedStrategy) else "sharded_spawn" with mock.patch(f"pytorch_lightning.strategies.{class_name}.ShardedDataParallel", autosp

Rename training plugin test files & names to strategy (#11303)

test_custom_kwargs_sharded

650c710efacd633fa283955145342bb64063c883

lightning

test_sharded_strategy.py

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

Python

def test_custom_kwargs_sharded(tmpdir, cls): strategy = cls(reduce_fp16=True) strategy.model = Mock(spec=LightningModule) strategy.model.trainer = Mock() class_name = "sharded" if isinstance(strategy, DDPShardedStrategy) else "sharded_spawn" with mock.patch(f"pytorch_lightning.strategies.{class_name}.ShardedDataParallel", autospec=True) as mock_sharded: strategy.configure_ddp() args, kwargs = mock_sharded.call_args assert "reduce_fp16" in kwargs assert kwargs["reduce_fp16"] @RunIf(skip_windows=True, fairscale=True) @mock.patch("pytorch_lightning.strategies.DDPShardedStrategy._wrap_optimizers", autospec=True) @pytest.mark.parametrize(["params", "expected_buffer_size"], [(dict(), 0), (dict(reduce_buffer_size=128), 128)]) @pytest.mark.parametrize("num_nodes", [1, 2])

""" # This file was generated by 'versioneer.py' (0.21) from # revision-control system data, or from the parent directory name of an # unpacked source archive. Distribution tarballs contain a pre-generated copy # of this file. import

versioneer.py

def versions_from_parentdir(parentdir_prefix, root, verbose): rootdirs = [] for _ in range(3): dirname = os.path.basename(root) if dirname.startswith(parent

add auto tag

versions_from_parentdir

f0194812568c83585ff09488fe7f67df300938cc

rembg

versioneer.py

https://github.com/danielgatis/rembg.git

Python

def versions_from_parentdir(parentdir_prefix, root, verbose): rootdirs = [] for _ in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return {"version": dirname[len(parentdir_prefix):], "full-revisionid": None, "dirty": False, "error": None, "date": None} rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print("Tried directories %s but none started with prefix %s" % (str(rootdirs), parentdir_prefix)) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") SHORT_VERSION_PY = %s

django/contrib/admin/options.py

def response_add(self, request, obj, post_url_continue=None): opts = obj._meta preserved_filters = self.get_preserved_filters(request) obj_url = reverse( "admin:%s_%s_change" % (opts.app_label, opts.model_name), args=(quote(obj.pk),), current_app=self.admin_site.name, ) # Add a link to the object's change form if the user can edit the obj. if self.has_change_permission(request, obj): obj_repr = format_html('<a href="{}">{}</a>', urlquote(obj_url), obj) else: obj_repr = str(obj) msg_dict = { "name": opts.verbose_name, "obj": obj_repr, } # Here, we distinguish between different save types by checking for # the presence of keys in request.POST. if IS_POPUP_VAR in request.POST: to_field = request.POST.get(TO_FIELD_VAR) if to_field: attr = str(to_field) else: attr = obj._meta.pk.attname value = obj.serializable_value(attr) popup_response_data = json.dumps( { "value": str(value), "obj": str(obj), } ) return TemplateResponse( request, self.popup_response_template or [ "admin/%s/%s/popup_response.html" % (opt

Refs #33476 -- Reformatted code with Black.

response_add

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

options.py

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

Python

def response_add(self, request, obj, post_url_continue=None): opts = obj._meta preserved_filters = self.get_preserved_filters(request) obj_url = reverse( "admin:%s_%s_change" % (opts.app_label, opts.model_name), args=(quote(obj.pk),), current_app=self.admin_site.name, ) # Add a link to the object's change form if the user can edit the obj. if self.has_change_permission(request, obj): obj_repr = format_html('<a href="{}">{}</a>', urlquote(obj_url), obj) else: obj_repr = str(obj) msg_dict = { "name": opts.verbose_name, "obj": obj_repr, } # Here, we distinguish between different save types by checking for # the presence of keys in request.POST. if IS_POPUP_VAR in request.POST: to_field = request.POST.get(TO_FIELD_VAR) if to_field: attr = str(to_field) else: attr = obj._meta.pk.attname value = obj.serializable_value(attr) popup_response_data = json.dumps( { "value": str(value), "obj": str(obj), } ) return TemplateResponse( request, self.popup_response_template or [ "admin/%s/%s/popup_response.html" % (opts.app_label, opts.model_name), "admin/%s/popup_response.html" % opts.app_label, "admin/popup_response.html", ], { "popup_response_data": popup_response_data, }, ) elif "_continue" in request.POST or ( # Redirecting after "Save as new". "_saveasnew" in request.POST and self.save_as_continue and self.has_change_permission(request, obj) ): msg = _("The {name} “{obj}” was added successfully.") if self.has_change_permission(request, obj): msg += " " + _("You may edit it again below.") self.message_user(request, format_html(msg, **msg_dict), messages.SUCCESS) if post_url_continue is None: post_url_continue = obj_url post_url_continue = add_preserved_filters( {"preserved_filters": preserved_filters, "opts": opts}, post_url_continue, ) return HttpResponseRedirect(post_url_continue) elif "_addanother" in request.POST: msg = format_html( _( "The {name} “{obj}” was added successfully. You may add another {name} below." ), **msg_dict, ) self.message_user(request, msg, messages.SUCCESS) redirect_url = request.path redirect_url = add_preserved_filters( {"preserved_filters": preserved_filters, "opts": opts}, redirect_url ) return HttpResponseRedirect(redirect_url) else: msg = format_html( _("The {name} “{obj}” was added successfully."), **msg_dict ) self.message_user(request, msg, messages.SUCCESS) return self.response_post_save_add(request, obj)

src/paperless_mail/tests/test_parsers.py

def test_tika_parse_unreachable(self): html = '<html><he

add test comments

test_tika_parse_unreachable

4aa318598fd0dc6c5d4e08dd2a13e7bf614511ec

paperless-ngx

test_parsers.py

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

Python

def test_tika_parse_unreachable(self): html = '<html><head><meta http-equiv="content-type" content="text/html; charset=UTF-8"></head><body><p>Some Text</p></body></html>' # Check if exception is raised when Tika cannot be reached. self.parser.tika_server = "" self.assertRaises(ParseError, self.parser.tika_parse, html)

tests/tpot_tests.py

def test_read_config_file_2(): tpot_obj = TPOTRegressor() assert_raises(ValueError, tpot

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

test_read_config_file_2

388616b6247ca4ea8de4e2f340d6206aee523541

tpot

tpot_tests.py

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

Python

def test_read_config_file_2(): tpot_obj = TPOTRegressor() assert_raises(ValueError, tpot_obj._read_config_file, "tests/test_config.py.bad")

netbox/netbox/staging.py

def pre_delete_handler(self, sender, instance, **kwargs): key = self.get_key_for_instance(instance) object_type = instance._meta.verbose_name # Delete an existing object logger.debug(f"[{self.branch}] Staging deletion of {object_type} {instance} (PK: {instance.pk})") self.queue[key] = (ChangeActionChoices.ACTION_DELETE, Non

Closes #10851: New staging mechanism (#10890) * WIP * Convert checkout() context manager to a class * Misc cleanup * Drop unique constraint from Change model * Extend staging tests * Misc cleanup * Incorporate M2M changes * Don't cancel wipe out creation records when an object is deleted * Rename Change to StagedChange * Add documentation for change staging

pre_delete_handler

a5308ea28e851a4ddb65a4e7ca2297b641e5891f

netbox

staging.py

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

Python

def pre_delete_handler(self, sender, instance, **kwargs): key = self.get_key_for_instance(instance) object_type = instance._meta.verbose_name # Delete an existing object logger.debug(f"[{self.branch}] Staging deletion of {object_type} {instance} (PK: {instance.pk})") self.queue[key] = (ChangeActionChoices.ACTION_DELETE, None)

python/ray/serve/experimental/gradio_visualize_graph.py

def _reset_state(self): self.cache = {}

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

_reset_state

4c970cc88247f7cfa7351297b8b5050f2372742e

ray

gradio_visualize_graph.py

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

Python

def _reset_state(self): self.cache = {} self.resolved_nodes = 0 self.finished_last_inference = True # maps DAGNode uuid to unique instance of a gradio block self.node_to_block: Dict[DAGNode, Any] = {} # maps InputAttributeNodes to unique instance of interactive gradio block self.input_key_to_blocks: Dict[int, Any] = {}

dash/testing/browser.py

def find_element(self, selector):

:hocho: deprecated find_element(s)_by_css_selector

find_element

5dfa6b0782803cb0635119ee1dcf8775dd76c8a7

dash

browser.py

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

Python

def find_element(self, selector): return self.driver.find_element(By.CSS_SELECTOR, selector)

lib/tests/streamlit/caching/memo_test.py

def test_bad_persist_value(self): with self.assertRaises(StreamlitAPIException) as e:

st.memo/singleton: cache-specific clear() functionality (#4184) Gives `@st.memo` and `@st.singleton` a per-cache `clear()` function, similar to Python's [functools.lru_cache API](https://docs.python.org/3/library/functools.html#functools.lru_cache). You can use it like this: ```python @st.experimental_memo def foo(val): return val foo(1), foo(2), foo(3) foo.clear() # Clear foo's cache *only* ``` (This PR also bundles in a few very minor cleanups and missing docstrings for memo + singleton).

test_bad_persist_value

b7f417f86ed4ca12c522d8ae5c147f932ffc7d40

streamlit

memo_test.py

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

Python

def test_bad_persist_value(self): with self.assertRaises(StreamlitAPIException) as e:

nuitka/OptionParsing.py

def _getDataFileTagsOptionHelp(): return % ", ".join( "'%s' (%s)" % d for d in data_files_tags ) data_file_tags_option = data_group.add_option( "--data-file-tags", action="append", dest="data_file_tags", metavar="DATA_TAGS", default=[], ) parser.add_option_group(data_group) execute_group = OptionGroup(parser, "Immediate execution after compilation") execute_group.add_option( "--run", action="store_true", dest="immediate_execution", default=is_nuitka_run, help= % ("on" if is_nuitka_run else "off"), ) execute_group.add_option( "--debugger", "--gdb", action="store_true", dest="debugger", default=False, help=, ) execute_group.add_option( "--execute-with-pythonpath", action="store_true", dest="keep_pythonpath", default=False, help=, ) parser.add_option_group(execute_group) dump_group = OptionGroup(parser, "Dump options for internal tree") dump_group.add_option( "--xml", action="store_true", dest="dump_xml", default=False, help="Dump the final result of optimization as XML, then exit.", ) parser.add_option_group(dump_group) codegen_group = OptionGroup(parser, "Code generation choices") codegen_group.add_option( "--disable-bytecode-cache", action="store_true", dest="disable_bytecode_cache", default=False, help=, ) codegen_group.add_option( "--full-compat", action="store_false", dest="improved", default=True, help=, ) codegen_group.add_option( "--file-reference-choice", action="store", dest="file_reference_mode", metavar="MODE", choices=("original", "runtime", "frozen"), default=None, help=, ) codegen_group.add_option( "--module-name-choice", action="store", dest="module_name_mode", metavar="MODE", choices=("original", "runtime"), default=None, help=, ) parser.add_option_group(codegen_group) output_group = OptionGroup(parser, "Output choices") output_group.add_option( "-o", action="store", dest="output_filename", metavar="FILENAME", default=None, help= % "<program_name>" + (".exe" if getOS() == "Windows" else ".bin"), ) output_group.add_option( "--output-dir", action="store", dest="output_dir", metavar="DIRECTORY", default="", help=, ) output_group.add_option( "--remove-output", action="store_true", dest="remove_build", default=False, help=, ) output_group.add_option( "--no-pyi-file", action="store_false", dest="pyi_file", default=True, help=, ) parser.add_option_group(output_group) debug_group = OptionGroup(parser, "Debug features") debug_group.add_option( "--debug", action="store_true", dest="debug", default=False, help=, ) debug_group.add_option( "--unstripped", action="store_true", dest="unstripped", default=False, help=, ) debug_group.add_option( "--profile", action="store_true", dest="profile", default=False, help=, ) debug_group.add_option( "--internal-graph", action="store_true", dest="graph", default=False, help=, ) debug_group.add_option( "--trace-execution", action="store_true", dest="trace_execution", default=False, help=, ) debug_group.add_option( "--recompile-c-only", action="store_true", dest="recompile_c_only", default=False, help=, ) debug_group.add_option( "--generate-c-only", action="store_true", dest="generate_c_only", default=False, help=, ) debug_group.add_option( "--experimental", action="append", dest="experimental", metavar="FLAG", default=[], help=, ) debug_group.add_option( "--explain-imports", action="store_true", dest="explain_imports", default=False, help=SUPPRESS_HELP, ) debug_group.add_option( "--low-memory", action="store_true", dest="low_memory", default=False, help=, ) if os.name == "nt": debug_group.add_option( "--disable-dll-dependency-cache", action="store_true", dest="no_dependency_cache", default=False, help=, ) debug_group.add_option( "--force-dll-dependency-cache-update", action="store_true", dest="update_dependency_cache", default=False, help=, ) # This is for testing framework, "coverage.py" hates to loose the process. And # we can use it to make sure it's not done unknowingly. parser.add_option( "--must-not-re-execute", action="store_false", dest="allow_reexecute", default=True, help=SUPPRESS_HELP, ) parser.add_option_group(debug_group) c_compiler_group = OptionGroup(parser, "Backend C compiler choice") c_compiler_group.add_option( "--clang", action="store_true", dest="clang", default=False, help=, ) c_compiler_group.add_option( "--mingw64", action="store_true", dest="mingw64", default=False, help=, ) c_compiler_group.add_option( "--msvc", action="store", dest="msvc_version", default=None, help=, ) c_compiler_group.add_option( "-j", "--jobs", action="store", dest="jobs", metavar="N", default=None, help=, ) c_compiler_group.add_option( "--lto", action="store", dest="lto", metavar="choice", default="auto", choices=("yes", "no", "auto"), help=, ) c_compiler_group.add_option( "--static-libpython", action="store", dest="static_libpython", metavar="choice", default="auto", choices=("yes", "no", "auto"), help=, ) c_compiler_group.add_option( "--disable-ccache", action="store_true", dest="disable_ccache", default=False, help=, ) parser.add_option_group(c_compiler_group) pgo_group = OptionGroup(parser, "PGO compilation choices") pgo_group.add_option( "--pgo", action="store_true", dest="is_c_pgo", default=False, help=, ) pgo_group.add_option( "--pgo-python", action="store_true", dest="is_python_pgo", default=False, help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-python-input", action="store", dest="python_pgo_input", default=None, help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-python-policy-unused-module", action="store", dest="python_pgo_policy_unused_module", choices=("include", "exclude", "bytecode"), default="include", help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-args", action="store", dest="pgo_args", default="", help=, ) pgo_group.add_option( "--pgo-executable", action="store", dest="pgo_executable", default=None, help=, ) parser.add_option_group(pgo_group) tracing_group = OptionGroup(parser, "Tracing features") tracing_group.add_option( "--quiet", action="store_true", dest="quiet", default=False, help=, ) tracing_group.add_option( "--show-scons", action="store_true", dest="show_scons", default=False, help=, ) tracing_group.add_option( "--show-progress", action="store_true", dest="show_progress", default=False, help=, ) tracing_group.add_option( "--no-progressbar", action="store_false", dest="progress_bar", default=True, help=, ) tracing_group.add_option( "--show-memory", action="store_true", dest="show_memory", default=False, help=, ) tracing_group.add_option( "--show-modules", action="store_true", dest="show_inclusion", default=False, help=, ) tracing_group.add_option( "--show-modules-output", action="store", dest="show_inclusion_output", metavar="PATH", default=None, help=, ) tracing_group.add_option( "--report", action="store", dest="compilation_report_filename", default=None, help=, ) tracing_group.add_option( "--verbose", action="store_true", dest="verbose", default=False, help=, ) tracing_group.add_option( "--verbose-output", action="store", dest="verbose_output", metavar="PATH", default=None, help=, ) parser.add_option_group(tracing_group) windows_group = OptionGroup(parser, "Windows specific controls") windows_group.add_option( "--windows-dependency-tool", action="store", dest="dependency_tool", default=None, help=SUPPRESS_HELP, ) windows_group.add_option( "--windows-disable-console", action="store_true", dest="disable_console", default=False, help=, ) windows_group.add_option( "--windows-icon-from-ico", action="append", dest="icon_path", metavar="ICON_PATH", default=[], help=, ) windows_group.add_option( "--windows-icon-from-exe", action="store", dest="icon_exe_path", metavar="ICON_EXE_PATH", default=None, help="Copy executable icons from this existing executable (Windows only).", ) windows_group.add_option( "--onefile-windows-splash-screen-image", action="store", dest="splash_screen_image", default=None, help=, ) windows_group.add_option( "--windows-uac-admin", action="store_true", dest="windows_uac_admin", metavar="WINDOWS_UAC_ADMIN", default=False, help="Request Windows User Control, to grant admin rights on execution. (Windows only). Defaults to off.", ) windows_group.add_option( "--windows-uac-uiaccess", action="store_true", dest="windows_uac_uiaccess", metavar="WINDOWS_UAC_UIACCESS", default=False, help=, ) windows_group.add_option( "--windows-company-name", action="store", dest="windows_company_name", metavar="WINDOWS_COMPANY_NAME", default=None, help=, ) windows_group.add_option( "--windows-product-name", action="store", dest="windows_product_name", metavar="WINDOWS_PRODUCT_NAME", default=None, help=, ) windows_group.add_option( "--windows-file-version", action="store", dest="windows_file_version", metavar="WINDOWS_FILE_VERSION", default=None, help=, ) windows_group.add_option( "--windows-product-version", action="store", dest="windows_product_version", metavar="WINDOWS_PRODUCT_VERSION", default=None, help=, ) windows_group.add_option( "--windows-file-description", action="store", dest="windows_

Plugins: Added ability to provide data file tags

_getDataFileTagsOptionHelp

e940705671f341139487d79b0eb0b6b9104f0a71

Nuitka

OptionParsing.py

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

Python

def _getDataFileTagsOptionHelp(): return % ", ".join( "'%s' (%s)" % d for d in data_files_tags ) data_file_tags_option = data_group.add_option( "--data-file-tags", action="append", dest="data_file_tags", metavar="DATA_TAGS", default=[], ) parser.add_option_group(data_group) execute_group = OptionGroup(parser, "Immediate execution after compilation") execute_group.add_option( "--run", action="store_true", dest="immediate_execution", default=is_nuitka_run, help= % ("on" if is_nuitka_run else "off"), ) execute_group.add_option( "--debugger", "--gdb", action="store_true", dest="debugger", default=False, help=, ) execute_group.add_option( "--execute-with-pythonpath", action="store_true", dest="keep_pythonpath", default=False, help=, ) parser.add_option_group(execute_group) dump_group = OptionGroup(parser, "Dump options for internal tree") dump_group.add_option( "--xml", action="store_true", dest="dump_xml", default=False, help="Dump the final result of optimization as XML, then exit.", ) parser.add_option_group(dump_group) codegen_group = OptionGroup(parser, "Code generation choices") codegen_group.add_option( "--disable-bytecode-cache", action="store_true", dest="disable_bytecode_cache", default=False, help=, ) codegen_group.add_option( "--full-compat", action="store_false", dest="improved", default=True, help=, ) codegen_group.add_option( "--file-reference-choice", action="store", dest="file_reference_mode", metavar="MODE", choices=("original", "runtime", "frozen"), default=None, help=, ) codegen_group.add_option( "--module-name-choice", action="store", dest="module_name_mode", metavar="MODE", choices=("original", "runtime"), default=None, help=, ) parser.add_option_group(codegen_group) output_group = OptionGroup(parser, "Output choices") output_group.add_option( "-o", action="store", dest="output_filename", metavar="FILENAME", default=None, help= % "<program_name>" + (".exe" if getOS() == "Windows" else ".bin"), ) output_group.add_option( "--output-dir", action="store", dest="output_dir", metavar="DIRECTORY", default="", help=, ) output_group.add_option( "--remove-output", action="store_true", dest="remove_build", default=False, help=, ) output_group.add_option( "--no-pyi-file", action="store_false", dest="pyi_file", default=True, help=, ) parser.add_option_group(output_group) debug_group = OptionGroup(parser, "Debug features") debug_group.add_option( "--debug", action="store_true", dest="debug", default=False, help=, ) debug_group.add_option( "--unstripped", action="store_true", dest="unstripped", default=False, help=, ) debug_group.add_option( "--profile", action="store_true", dest="profile", default=False, help=, ) debug_group.add_option( "--internal-graph", action="store_true", dest="graph", default=False, help=, ) debug_group.add_option( "--trace-execution", action="store_true", dest="trace_execution", default=False, help=, ) debug_group.add_option( "--recompile-c-only", action="store_true", dest="recompile_c_only", default=False, help=, ) debug_group.add_option( "--generate-c-only", action="store_true", dest="generate_c_only", default=False, help=, ) debug_group.add_option( "--experimental", action="append", dest="experimental", metavar="FLAG", default=[], help=, ) debug_group.add_option( "--explain-imports", action="store_true", dest="explain_imports", default=False, help=SUPPRESS_HELP, ) debug_group.add_option( "--low-memory", action="store_true", dest="low_memory", default=False, help=, ) if os.name == "nt": debug_group.add_option( "--disable-dll-dependency-cache", action="store_true", dest="no_dependency_cache", default=False, help=, ) debug_group.add_option( "--force-dll-dependency-cache-update", action="store_true", dest="update_dependency_cache", default=False, help=, ) # This is for testing framework, "coverage.py" hates to loose the process. And # we can use it to make sure it's not done unknowingly. parser.add_option( "--must-not-re-execute", action="store_false", dest="allow_reexecute", default=True, help=SUPPRESS_HELP, ) parser.add_option_group(debug_group) c_compiler_group = OptionGroup(parser, "Backend C compiler choice") c_compiler_group.add_option( "--clang", action="store_true", dest="clang", default=False, help=, ) c_compiler_group.add_option( "--mingw64", action="store_true", dest="mingw64", default=False, help=, ) c_compiler_group.add_option( "--msvc", action="store", dest="msvc_version", default=None, help=, ) c_compiler_group.add_option( "-j", "--jobs", action="store", dest="jobs", metavar="N", default=None, help=, ) c_compiler_group.add_option( "--lto", action="store", dest="lto", metavar="choice", default="auto", choices=("yes", "no", "auto"), help=, ) c_compiler_group.add_option( "--static-libpython", action="store", dest="static_libpython", metavar="choice", default="auto", choices=("yes", "no", "auto"), help=, ) c_compiler_group.add_option( "--disable-ccache", action="store_true", dest="disable_ccache", default=False, help=, ) parser.add_option_group(c_compiler_group) pgo_group = OptionGroup(parser, "PGO compilation choices") pgo_group.add_option( "--pgo", action="store_true", dest="is_c_pgo", default=False, help=, ) pgo_group.add_option( "--pgo-python", action="store_true", dest="is_python_pgo", default=False, help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-python-input", action="store", dest="python_pgo_input", default=None, help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-python-policy-unused-module", action="store", dest="python_pgo_policy_unused_module", choices=("include", "exclude", "bytecode"), default="include", help=SUPPRESS_HELP, ) pgo_group.add_option( "--pgo-args", action="store", dest="pgo_args", default="", help=, ) pgo_group.add_option( "--pgo-executable", action="store", dest="pgo_executable", default=None, help=, ) parser.add_option_group(pgo_group) tracing_group = OptionGroup(parser, "Tracing features") tracing_group.add_option( "--quiet", action="store_true", dest="quiet", default=False, help=, ) tracing_group.add_option( "--show-scons", action="store_true", dest="show_scons", default=False, help=, ) tracing_group.add_option( "--show-progress", action="store_true", dest="show_progress", default=False, help=, ) tracing_group.add_option( "--no-progressbar", action="store_false", dest="progress_bar", default=True, help=, ) tracing_group.add_option( "--show-memory", action="store_true", dest="show_memory", default=False, help=, ) tracing_group.add_option( "--show-modules", action="store_true", dest="show_inclusion", default=False, help=, ) tracing_group.add_option( "--show-modules-output", action="store", dest="show_inclusion_output", metavar="PATH", default=None, help=, ) tracing_group.add_option( "--report", action="store", dest="compilation_report_filename", default=None, help=, ) tracing_group.add_option( "--verbose", action="store_true", dest="verbose", default=False, help=, ) tracing_group.add_option( "--verbose-output", action="store", dest="verbose_output", metavar="PATH", default=None, help=, ) parser.add_option_group(tracing_group) windows_group = OptionGroup(parser, "Windows specific controls") windows_group.add_option( "--windows-dependency-tool", action="store", dest="dependency_tool", default=None, help=SUPPRESS_HELP, ) windows_group.add_option( "--windows-disable-console", action="store_true", dest="disable_console", default=False, help=, ) windows_group.add_option( "--windows-icon-from-ico", action="append", dest="icon_path", metavar="ICON_PATH", default=[], help=, ) windows_group.add_option( "--windows-icon-from-exe", action="store", dest="icon_exe_path", metavar="ICON_EXE_PATH", default=None, help="Copy executable icons from this existing executable (Windows only).", ) windows_group.add_option( "--onefile-windows-splash-screen-image", action="store", dest="splash_screen_image", default=None, help=, ) windows_group.add_option( "--windows-uac-admin", action="store_true", dest="windows_uac_admin", metavar="WINDOWS_UAC_ADMIN", default=False, help="Request Windows User Control, to grant admin rights on execution. (Windows only). Defaults to off.", ) windows_group.add_option( "--windows-uac-uiaccess", action="store_true", dest="windows_uac_uiaccess", metavar="WINDOWS_UAC_UIACCESS", default=False, help=, ) windows_group.add_option( "--windows-company-name", action="store", dest="windows_company_name", metavar="WINDOWS_COMPANY_NAME", default=None, help=, ) windows_group.add_option( "--windows-product-name", action="store", dest="windows_product_name", metavar="WINDOWS_PRODUCT_NAME", default=None, help=, ) windows_group.add_option( "--windows-file-version", action="store", dest="windows_file_version", metavar="WINDOWS_FILE_VERSION", default=None, help=, ) windows_group.add_option( "--windows-product-version", action="store", dest="windows_product_version", metavar="WINDOWS_PRODUCT_VERSION", default=None, help=, ) windows_group.add_option( "--windows-file-description", action="store", dest="windows_file_description", metavar="WINDOWS_FILE_DESCRIPTION", default=None, help=, ) windows_group.add_option( "--windows-onefile-tempdir", "--onefile-tempdir", action="store_true", dest="is_onefile_tempdir", metavar="ONEFILE_TEMPDIR", default=False, help=SUPPRESS_HELP, ) windows_group.add_option( "--windows-onefile-tempdir-spec", "--onefile-tempdir-spec", action="store", dest="onefile_tempdir_spec", metavar="ONEFILE_TEMPDIR_SPEC", default=None, help=, ) windows_group.add_option( "--windows-force-stdout-spec", action="store", dest="force_stdout_spec", metavar="WINDOWS_FORCE_STDOUT_SPEC", default=None, help=, ) windows_group.add_option( "--windows-force-stderr-spec", action="store", dest="force_stderr_spec", metavar="WINDOWS_FORCE_STDERR_SPEC", default=None, help=, ) parser.add_option_group(windows_group) macos_group = OptionGroup(parser, "macOS specific controls") macos_group.add_option( "--macos-target-arch", action="store", dest="macos_target_arch", choices=("universal", "arm64", "x86_64"), metavar="MACOS_TARGET_ARCH", default=None, help=, ) macos_group.add_option( "--macos-disable-console", "--disable-console", action="store_true", dest="disable_console", default=False, help=, ) macos_group.add_option( "--macos-create-app-bundle", action="store_true", dest="macos_create_bundle", default=False, help=, ) macos_group.add_option( "--macos-onefile-icon", action="append", dest="icon_path", metavar="ICON_PATH", default=[], help="Add executable icon for binary to use. Can be given only one time. Defaults to Python icon if available.", ) macos_group.add_option( "--macos-signed-app-name", action="store", dest="macos_signed_app_name", metavar="MACOS_SIGNED_APP_NAME", default=None, help=, ) macos_group.add_option( "--macos-app-name", action="store", dest="macos_app_name", metavar="MACOS_APP_NAME", default=None, help=, ) macos_group.add_option( "--macos-app-version", action="store", dest="macos_app_version", metavar="MACOS_APP_VERSION", default=None, help=, ) parser.add_option_group(macos_group) linux_group = OptionGroup(parser, "Linux specific controls") linux_group.add_option( "--linux-onefile-icon", action="append", dest="icon_path", metavar="ICON_PATH", default=[], help="Add executable icon for onefile binary to use. Can be given only one time. Defaults to Python icon if available.", ) linux_group.add_option( "--linux-onefile-compression", action="store", dest="appimage_compression", choices=("gzip", "xz"), metavar="COMPRESSION", default="gzip", help="Compression method to use for Linux onefile builds. Defaults to gzip for faster decompression", ) parser.add_option_group(linux_group) plugin_group = OptionGroup(parser, "Plugin control") plugin_group.add_option( "--enable-plugin", "--plugin-enable", action="append", dest="plugins_enabled", metavar="PLUGIN_NAME", default=[], help=, ) plugin_group.add_option( "--disable-plugin", "--plugin-disable", action="append", dest="plugins_disabled", metavar="PLUGIN_NAME", default=[], help=, ) plugin_group.add_option( "--plugin-no-detection", action="store_false", dest="detect_missing_plugins", default=True, help=, ) plugin_group.add_option( "--plugin-list", action="store_true", dest="list_plugins", default=False, help=, ) parser.add_option_group(plugin_group) plugin_group.add_option( "--user-plugin", action="append", dest="user_plugins", metavar="PATH", default=[], help="The file name of user plugin. Can be given multiple times. Default empty.", ) plugin_group.add_option( "--persist-source-changes", action="store_true", dest="persist_source_changes", default=False, help=, )

wagtail/admin/tests/test_workflows.py

def test_collect_workflow_action_data_post(self): response = self.client.post( reverse( "wagtailadmin_pages:collect_workflow_action_data", args=( self.page

Reformat with black

test_collect_workflow_action_data_post

d10f15e55806c6944827d801cd9c2d53f5da4186

wagtail

test_workflows.py

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

Python

def test_collect_workflow_action_data_post(self): response = self.client.post( reverse( "wagtailadmin_pages:collect_workflow_action_data", args=( self.page.id, "approve", self.page.current_workflow_task_state.id, ), ), {"comment": "This is my comment"}, ) self.assertEqual(response.status_code, 200) response_json = json.loads(response.content) self.assertEqual(response_json["step"], "success") self.assertEqual( response_json["cleaned_data"], {"comment": "This is my comment"} )

mindsdb/integrations/handlers/lightwood_handler/tests/test_lightwood_handler.py

def test_02_train_predictor(self): query = f response = self.handler.native_query(query) self.assertTrue(response.type ==

add more TS tests

test_02_train_predictor

871793d4fbd99f454c0c1ff14db6ce3c385e656c

mindsdb

test_lightwood_handler.py

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

Python

def test_02_train_predictor(self): query = f response = self.handler.native_query(query) self.assertTrue(response.type == RESPONSE_TYPE.OK)

@TRANSFORMS.register_module()

mmdet/datasets/pipelines/loading.py

def __call__(self, results): img = results['img'] if self.to_float32: img = img.astype(np.float32) results['img_path'] = None results['img'] = img height, width = img.shape[:2] results['height'] = height results['width'] = width results['ori_height'] = height

Refacter Visualization

__call__

c71a160c5193b92f6a4f56c113e96b63decf8354

mmdetection

loading.py

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

Python

def __call__(self, results): img = results['img'] if self.to_float32: img = img.astype(np.float32) results['img_path'] = None results['img'] = img height, width = img.shape[:2] results['height'] = height results['width'] = width results['ori_height'] = height results['ori_width'] = width return results @TRANSFORMS.register_module()

python/ray/tests/test_advanced_4.py

def test_jemalloc_env_var_propagate(): gcs_ptype = ray.ray_constants.PROCESS_TYPE_GCS_SERVER expected = {} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path="", jemalloc_conf="", jemalloc_comps=[], process_type=gcs_ptype ) assert actual == expected actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=None, jemalloc_conf="a,b,c", jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER], process_type=gcs_ptype, ) assert actual == expected library_path = "/abc" expected = {"LD_PRELOAD": library_path} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=library_path, jemalloc_conf="", jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER], process_type=gcs_ptype, ) assert actual == expect

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

test_jemalloc_env_var_propagate

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

test_advanced_4.py

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

Python

def test_jemalloc_env_var_propagate(): gcs_ptype = ray.ray_constants.PROCESS_TYPE_GCS_SERVER expected = {} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path="", jemalloc_conf="", jemalloc_comps=[], process_type=gcs_ptype ) assert actual == expected actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=None, jemalloc_conf="a,b,c", jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER], process_type=gcs_ptype, ) assert actual == expected library_path = "/abc" expected = {"LD_PRELOAD": library_path} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=library_path, jemalloc_conf="", jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER], process_type=gcs_ptype, ) assert actual == expected # comps should be a list type. with pytest.raises(AssertionError): ray._private.services.propagate_jemalloc_env_var( jemalloc_path=library_path, jemalloc_conf="", jemalloc_comps="ray.ray_constants.PROCESS_TYPE_GCS_SERVER,", process_type=gcs_ptype, ) # When comps don't match the process_type, it should return an empty dict. expected = {} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=library_path, jemalloc_conf="", jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_RAYLET], process_type=gcs_ptype, ) library_path = "/abc" malloc_conf = "a,b,c" expected = {"LD_PRELOAD": library_path, "MALLOC_CONF": malloc_conf} actual = ray._private.services.propagate_jemalloc_env_var( jemalloc_path=library_path, jemalloc_conf=malloc_conf, jemalloc_comps=[ray.ray_constants.PROCESS_TYPE_GCS_SERVER], process_type=gcs_ptype, ) assert actual == expected

mmdet/models/dense_heads/dense_test_mixins.py

def aug_test_bboxes(self, feats, img_metas, rescale=False): # check with_nms argument gb_sig = signature(self.get_results) gb_args = [p.name for p in gb_sig.parameters.values()] gbs_sig = signature(self._get_results_single) gbs_args = [p.name for p in gbs_sig.parameters.values()] assert ('with_nms' in gb_args) and ('with_nms' in gbs_args), \ f'{self.__class__.__name__}' \ ' does not support test-time augmentation' aug_bboxes = [] aug_scores = [] aug_labels = [] for x, img_meta in zip(feats, img_metas): # only one image in the batch outs = self.forward(x) bbox_outputs = self.get_results( *outs, img_metas=img_meta, cfg=self.test_cfg, rescale=False, with_nms=False)[0] aug_bboxes.append(bbox_outputs.bboxes) aug_scores.append(bbox_outputs.scores) if len(bbox_outputs) >= 3: aug_labels.append(bbox_outputs.labels) # after merging, bboxes will be rescaled to the original image size merged_bboxes, merged_scores = self.merge_aug_bboxes( aug_bboxes, aug_scores, img_metas) merged_labels = torch.cat(aug_labels, dim=0) if aug_labels else None if merged_bboxes.numel() == 0: det_bboxes = torch.cat([merged_bboxes, merged_scores[:, None]], -1) return [ (det_bboxes, merged_labels), ] det_bboxes, keep_idxs = batched_nms(merged_bboxes, merged_scores, merged_labels, self.test_cfg.nms) det_bboxes = det_bboxes[:self.test_cfg.max_per_img] det_labels = merged_labels[keep_idxs][:self.test_cfg.max_per_img] if rescale:

[Refactor] Refactor dense head outputs to InstanceResults.

aug_test_bboxes

9a3bf7660e6ced54672741095f96df07919f9ba7

mmdetection

dense_test_mixins.py

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

Python

def aug_test_bboxes(self, feats, img_metas, rescale=False): # check with_nms argument gb_sig = signature(self.get_results) gb_args = [p.name for p in gb_sig.parameters.values()] gbs_sig = signature(self._get_results_single) gbs_args = [p.name for p in gbs_sig.parameters.values()] assert ('with_nms' in gb_args) and ('with_nms' in gbs_args), \ f'{self.__class__.__name__}' \ ' does not support test-time augmentation' aug_bboxes = [] aug_scores = [] aug_labels = [] for x, img_meta in zip(feats, img_metas): # only one image in the batch outs = self.forward(x) bbox_outputs = self.get_results( *outs, img_metas=img_meta, cfg=self.test_cfg, rescale=False, with_nms=False)[0] aug_bboxes.append(bbox_outputs.bboxes) aug_scores.append(bbox_outputs.scores) if len(bbox_outputs) >= 3: aug_labels.append(bbox_outputs.labels) # after merging, bboxes will be rescaled to the original image size merged_bboxes, merged_scores = self.merge_aug_bboxes( aug_bboxes, aug_scores, img_metas) merged_labels = torch.cat(aug_labels, dim=0) if aug_labels else None if merged_bboxes.numel() == 0: det_bboxes = torch.cat([merged_bboxes, merged_scores[:, None]], -1) return [ (det_bboxes, merged_labels), ] det_bboxes, keep_idxs = batched_nms(merged_bboxes, merged_scores, merged_labels, self.test_cfg.nms) det_bboxes = det_bboxes[:self.test_cfg.max_per_img] det_labels = merged_labels[keep_idxs][:self.test_cfg.max_per_img] if rescale: _det_bboxes = det_bboxes else: _det_bboxes = det_bboxes.clone() _det_bboxes[:, :4] *= det_bboxes.new_tensor( img_metas[0][0]['scale_factor']) results = InstanceData() results.bboxes = _det_bboxes[:, :4] results.scores = _det_bboxes[:, 4] results.labels = det_labels return [results]

synapse/replication/tcp/protocol.py

def pauseProducing(self) -> None: logger.info("[%s] Pause producing", self.id()) self.state = ConnectionStat

Add missing type hints to synapse.replication. (#11938)

pauseProducing

d0e78af35e519ff76bd23e786007f3e7130d90f7

synapse

protocol.py

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

Python

def pauseProducing(self) -> None: logger.info("[%s] Pause producing", self.id()) self.state = ConnectionStates.PAUSED

python3.10.4/Lib/_collections_abc.py

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

add python 3.10.4 for windows

throw

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

_collections_abc.py

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

Python

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

pipenv/patched/notpip/_vendor/rich/console.py

def _exit_buffer(self) -> None: se

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

_exit_buffer

f3166e673fe8d40277b804d35d77dcdb760fc3b3

pipenv

console.py

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

Python

def _exit_buffer(self) -> None: self._buffer_index -= 1 self._check_buffer()

homeassistant/components/switchbot/coordinator.py

def flatten_sensors_data(sensor): if "temp" in sensor["data"]: sensor["data"]["temp

Add Switchbot hygrometers (#75325) * Switchbot add support for hygrometers * Update CODEOWNERS * Improve debug * Remove redundant mention to temp unit * Adopt FlowResultType * Modify SwitchBot data within coordinator * Increase logging for switchbot sensor * Revert "Increase logging for switchbot sensor" This reverts commit d8b377429c562fc7044a3c98a6e976e4cd71847e. Co-authored-by: J. Nick Koston <nick@koston.org>

flatten_sensors_data

148f96351052b0a4ba31e7d15dad16d7639e1ceb

core

coordinator.py

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

Python

def flatten_sensors_data(sensor): if "temp" in sensor["data"]: sensor["data"]["temperature"] = sensor["data"]["temp"]["c"] return sensor

keras/feature_column/sequence_feature_column_test.py

def test_shared_embedding_column_with_non_sequence_categorical(self): with tf.Graph().as_default(): vocabulary_size = 3 sparse_input_a = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) sparse_input_b = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) categorical_column_a = ( tf.feature_column.categorical_column_with_identity( key="aaa", num_buckets=vocabulary_size ) ) categorical_column_b = ( tf.feature_column.categorical_column_with_identity( key="bbb", num_buckets=vocabulary_size ) ) shared_embedding_columns = tf.feature_column.shared_embeddings( [categorical_column_a, categorical_column_b], dimension=2 ) sequence_input_layer = ksfc.SequenceFeatures( shared_embedding_columns ) with self.assertRaisesRegex( ValueError, r"In embedding_column: aaa_shared_embedding\. " r"categorical_column must " r"be of type SequenceCategoricalColumn to use " r"SequenceFeatures\.", ): _, _ = sequence_input_layer( {"aaa": sparse_input_a,

resolve line-too-long in feature_column

test_shared_embedding_column_with_non_sequence_categorical

6fafb567af4e4d9f42974d0b6c55b18bc03e17eb

keras

sequence_feature_column_test.py

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

Python

def test_shared_embedding_column_with_non_sequence_categorical(self): with tf.Graph().as_default(): vocabulary_size = 3 sparse_input_a = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) sparse_input_b = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) categorical_column_a = ( tf.feature_column.categorical_column_with_identity( key="aaa", num_buckets=vocabulary_size ) ) categorical_column_b = ( tf.feature_column.categorical_column_with_identity( key="bbb", num_buckets=vocabulary_size ) ) shared_embedding_columns = tf.feature_column.shared_embeddings( [categorical_column_a, categorical_column_b], dimension=2 ) sequence_input_layer = ksfc.SequenceFeatures( shared_embedding_columns ) with self.assertRaisesRegex( ValueError, r"In embedding_column: aaa_shared_embedding\. " r"categorical_column must " r"be of type SequenceCategoricalColumn to use " r"SequenceFeatures\.", ): _, _ = sequence_input_layer( {"aaa": sparse_input_a, "bbb": sparse_input_b} )

openbb_terminal/helper_funcs.py

def get_next_stock_market_days(last_stock_day, n_next_days) -> list: n_days = 0 l_pred_days = [] years: list = [] holidays: list = [] if isinstance(last_stock_day, datetime): while n_days < n_next_days: last_stock_day += timedelta(ho

Forecasting Menu [Work in Progress] (#1933) * Gave forecasting memory * Fixed scripts, refactored * FIxed poetry lock * edge case check for forecast target * Improved combine and load functionality * Cleaned up translations * Fixed issue with covariates * Fixed issue checking covariates * Another covariates check fix * Ignored regr and linregr warnings * Fixed covariate issues * switched from forecasting to forecast * Finished transition to forecast * Can add entire dataset with one command * Improved combine description * Removed naming covariates * Created new installation * typo * Make plot show dates if available * Added better handling or users without the menu * Removed unused file * Fix * Better handling for nontraditional datasets * Fixed black and pylint * Fixed tests * Added darts install to main tests * Working on darts with CI * Added back test file * Made large tables print better * naive baseline * typo * Finished naive * no dollar on prediction * fixed positive MAPE bug * quick refactoring * Fixed two different args for same thing * added extra patience * linreg mape fix * info fix * Refactored API, bumped to Darts 0.21.0 * Added fixes * Increased verbosity for wrong column * Updated dependencies * Hid warnings * Fixed importing * Fixed tests * Fixed ugly seasonal plotting * Fixed forecast line color * Switched chart output to blue * Simplified lambda_price_prediction_color * fixed residuals * Chnage * Removed darts from CI per Chavi * Added fixes to tests * Added knnfix * Fixed issue where n!= o * Added changes * Added changes * Imrpoved forecast dash * Added Theo notebook * Added enhancements to dash * Added notebook * Added fix for jupyter lab * Added debug stuff * Change * Updated docs * Fixed formatting * Fixed formatting * Removed prints * Filtered some info * Added button to run model * Improved api * Added secret feautr (no peeking Martin) * Cleaned code * Fixed tests * Added test fixes * Added fixes * Fixes * FIxes for pres * Remove bad tests * Removed knn * Fixed issues with removing mc * doc for conda * Added forecast improvements * Added streamlit support * Fixed issues * fix expo with streamlit due to quantile() * fixed performance issues with streamlit for now.. * clean up historical forecast with new trainer * quick fix for regression trainer params * Added fixes * quick fix for other fix for regression trainer params * table formatting for timestamp * potential fix for inf in feature engineered datasets * Basic working in new format * dw * Trying * Fixed issues * Improved graphing * fixing trainer for LR and formatting * doge and linting * page break * automatic cleaning of datasets * automatic cleaning of datasets- fix * Fixed forecast dates * Made dashboard prettier * Added fixes * Added fixes * Added options * Fixed error * remove caching * adding in spinner * Added vairable n_predict in streamlit * Added mypy fix * renaming and range change * new index for n predict * check positive float for window size * Update _index.md * Update _index.md * Update _index.md * Update _index.md * Update _index.md * Update _index.md * Update _index.md * Update _index.md * Update _index.md * renaming * reorg files * Update _index.md * hidden which command for versions * Update _index.md * Update _index.md * which: ns parser * hugo for: which * hugo for: forecasting fix * formatting black * update stock controller test * Lay groundwork for better residual plotting * improved delete to allow for periods in title * improved automatic cleaning of inf * Added new API * Added new API * Added new API * formatting for black * Updated our testing CI * Reverted changes * Added forecast docs * Fixed mypy issues * Fixes tests * Did some refactoring, added a report * new api in streamlit * Added integrated tests * Update _index.md * improved loading in custom dataset * menu spacing * installer fixes * Added docs fixes * Adding comments to test if commit working * Fixed report * naming conventions * formatting * removing unused var * Made last report imporvements * Update README.md * Added fix * Switched to warning * Added fixes * Added fixes * Added fixes * Added fixes * Update economy av view test * Remove forgotten print statement * Update depencencies * Added verbosity to pytest * Added fixes * Fixed pylint * Fixed actions checkout * Added fixes Co-authored-by: colin99d <colin99delahunty@gmail.com> Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: James Simmons <simmonsj330@gmail.com> Co-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com> Co-authored-by: Theodore Aptekarev <aptekarev@gmail.com>

get_next_stock_market_days

7fd72d9ee1e8847717195859bf6d608268a94e2f

OpenBBTerminal

helper_funcs.py

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

Python

def get_next_stock_market_days(last_stock_day, n_next_days) -> list: n_days = 0 l_pred_days = [] years: list = [] holidays: list = [] if isinstance(last_stock_day, datetime): while n_days < n_next_days: last_stock_day += timedelta(hours=24) year = last_stock_day.date().year if year not in years: years.append(year) holidays += us_market_holidays(year) # Check if it is a weekend if last_stock_day.date().weekday() > 4: continue # Check if it is a holiday if last_stock_day.strftime("%Y-%m-%d") in holidays: continue # Otherwise stock market is open n_days += 1 l_pred_days.append(last_stock_day) else: while n_days < n_next_days: l_pred_days.append(last_stock_day + 1 + n_days) n_days += 1 return l_pred_days

@pytest.mark.asyncio @pytest.mark.parametrize( "failures", [ [True, True, True, True, True], [False, False, False, False, False], [False, True, False, True, False], [False, False, False, True, True], [True, True, False, False, False], ], )

dashboard/tests/test_state_head.py

async def test_max_concurrent_in_progress_functions(extra_req_num): max_req = 10 a = A(max_num_call=max_req) # Run more than allowed concurrent async functions should trigger rate limiting res_arr = await asyncio.gather( *[a.fn1() if i % 2 == 0 else a.fn2() for i in range(max_req + extra_req_num)] ) fail_cnt = 0 for ok in res_arr: fail_cnt += 0 if ok else 1 expected_fail_cnt = max(0, extra_req_num) assert fail_cnt == expected_fail_cnt, ( f"{expected_fail_cnt} out of {max_req + extra_req_num} " f"concurrent runs should fail with max={max_req} but {fail_cnt}." ) assert a.num_call_ == 0, "All requests should be done" @pytest.mark.asyncio @pytest.mark.parametrize( "failures", [ [True, True, True, True, True], [False, False, False, False, False], [False, True, False, True, False], [False, False, False, True, True], [True, True, False, False, False], ], )

[Core | State Observability] Implement API Server (Dashboard) HTTP Requests Throttling (#26257) This is to limit the max number of HTTP requests the dashboard (API server) will accept before rejecting more requests. This will make sure the observability requests do not overload the downstream systems (raylet/gcs) when delegating too many concurrent state observability requests to the cluster.

test_max_concurrent_in_progress_functions

365ffe21e592589880e3116302705b5e08a5b81f

ray

test_state_head.py

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

Python

async def test_max_concurrent_in_progress_functions(extra_req_num): max_req = 10 a = A(max_num_call=max_req) # Run more than allowed concurrent async functions should trigger rate limiting res_arr = await asyncio.gather( *[a.fn1() if i % 2 == 0 else a.fn2() for i in range(max_req + extra_req_num)] ) fail_cnt = 0 for ok in res_arr: fail_cnt += 0 if ok else 1 expected_fail_cnt = max(0, extra_req_num) assert fail_cnt == expected_fail_cnt, ( f"{expected_fail_cnt} out of {max_req + extra_req_num} " f"concurrent runs should fail with max={max_req} but {fail_cnt}." ) assert a.num_call_ == 0, "All requests should be done" @pytest.mark.asyncio @pytest.mark.parametrize( "failures", [ [True, True, True, True, True], [False, False, False, False, False], [False, True, False, True, False], [False, False, False, True, True], [True, True, False, False, False], ], )

d2l/mxnet.py

def transpose_qkv(X, num_heads): # Shape of input `X`: # (`batch_size`, no.

[PaddlePaddle] Merge master into Paddle branch (#1186) * change 15.2 title in chinese version (#1109) change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘ * 修改部分语义表述 (#1105) * Update r0.17.5 (#1120) * Bump versions in installation * 94行typo: （“bert.mall”）->（“bert.small”） (#1129) * line 313: "bert.mall" -> "bert.small" (#1130) * fix: update language as native reader (#1114) * Fix the translation of "stride" (#1115) * Update index.md (#1118) 修改部分语义表述 * Update self-attention-and-positional-encoding.md (#1133) 依照本书的翻译习惯，将pooling翻译成汇聚 * maybe a comment false (#1149) * maybe a little false * maybe a little false * A minor bug in the rcnn section (Chinese edition) (#1148) * Update bert.md (#1137) 一个笔误 # 假设batch_size=2，num_pred_positions=3 # 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1] * Update calculus.md (#1135) * fix typo in git documentation (#1106) * fix: Update the Chinese translation in lr-scheduler.md (#1136) * Update lr-scheduler.md * Update chapter_optimization/lr-scheduler.md Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * fix translation for kaggle-house-price.md (#1107) * fix translation for kaggle-house-price.md * fix translation for kaggle-house-price.md Signed-off-by: sunhaizhou <haizhou.sun@smartmore.com> * Update weight-decay.md (#1150) * Update weight-decay.md 关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解 关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。 并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释 解释为何会增加复杂性以及为何需要细粒度工具。 * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Fix a spelling error (#1161) * Update gru.md (#1152) The key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state. 翻译错误 * Unify the function naming (#1113) Unify naming of the function 'init_xavier()'. * Update mlp-concise.md (#1166) * Update mlp-concise.md 语句不通顺 * Update environment.md 语序异常 * Update config.ini * fix the imprecise description (#1168) Co-authored-by: yuande <yuande> * fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175) * Fix some typos. (#1163) * Update batch-norm.md (#1170) fixing typos u->x in article * Update linear-regression.md (#1090) We invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that 原译文把who也直接翻译出来了。 * Update mlp.md (#1117) * Update mlp.md 修改部分语义表述 * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Correct a translation error. (#1091) * Correct a translation error. * Update chapter_computer-vision/image-augmentation.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update aws.md (#1121) * Update aws.md * Update chapter_appendix-tools-for-deep-learning/aws.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update image-augmentation.md (#1093) * Update anchor.md (#1088) fix a minor issue in code * Update anchor.md * Update image-augmentation.md * fix typo and improve translation in chapter_linear-networks\softmax-regression.md (#1087) * Avoid `torch.meshgrid` user warning (#1174) Avoids the following user warning: ```python ~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] ``` * bump to 2.0.0-beta1 * Update sequence.md * bump beta1 on readme * Add latex code block background to config * BLD: Bump python support version 3.9 (#1183) * BLD: Bump python support version 3.9 * Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4 * BLD: Bump torch and tensorflow * Update Jenkinsfile * Update chapter_installation/index.md * Update chapter_installation/index.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update config.ini * Update INFO.md * Update INFO.md * Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187) * resolve the conflicts * revise from publisher (#1089) * revise from publisher * d2l api * post_latex * revise from publisher * revise ch11 * Delete d2l-Copy1.bib * clear cache * rm d2lbook clear * debug anchor * keep original d2l doc Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal> Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: Aston Zhang <asv325@gmail.com> * 重复语句 (#1188) Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Improve expression for chapter_preliminaries/pandas.md (#1184) * Update pandas.md * Improve expression * Improve expression * Update chapter_preliminaries/pandas.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Improce expression for chapter_preliminaries/linear-algebra.md (#1185) * Improce expression * Improve code comments * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Fix multibox_detection bugs * Update d2l to 0.17.5 version * restore older version * Upgrade pandas * change to python3.8 * Test warning log * relocate warning log * test logs filtering * Update gru.md * Add DeprecationWarning filter * Test warning log * Update attention mechanisms & computational performance * Update multilayer perceptron& linear & convolution networks & computer vision * Update recurrent&optimition&nlp pretraining & nlp applications * ignore warnings * Update index.md * Update linear networks * Update multilayer perceptrons&deep learning computation * Update preliminaries * Check and Add warning filter * Update kaggle-cifar10.md * Update object-detection-dataset.md * Update ssd.md fcn.md * Update hybridize.md * Update hybridize.md Signed-off-by: sunhaizhou <haizhou.sun@smartmore.com> Co-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com> Co-authored-by: Xinwei Liu <xinzone@outlook.com> Co-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com> Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com> Co-authored-by: gyro永不抽风 <1247006353@qq.com> Co-authored-by: CanChengZheng <zcc550169544@163.com> Co-authored-by: linlin <jajupmochi@gmail.com> Co-authored-by: iuk <liukun0104@gmail.com> Co-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com> Co-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com> Co-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com> Co-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com> Co-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com> Co-authored-by: Ming Liu <akira.liu@njnu.edu.cn> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: silenceZheng66 <13754430639@163.com> Co-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com> Co-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com> Co-authored-by: Krahets <krahets@163.com> Co-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com> Co-authored-by: Jameson <miraclecome@gmail.com> Co-authored-by: P. Yao <12227516+YaoPengCN@users.noreply.github.com> Co-authored-by: Yulv-git <34329208+Yulv-git@users.noreply.github.com> Co-authored-by: Liu,Xiao <45966993+liuxiao916@users.noreply.github.com> Co-authored-by: YIN, Gang <1246410+yingang@users.noreply.github.com> Co-authored-by: Joe-HZ <58297431+Joe-HZ@users.noreply.github.com> Co-authored-by: lybloveyou <102609904+lybloveyou@users.noreply.github.com> Co-authored-by: VigourJiang <jiangfuqiang154@163.com> Co-authored-by: zxhd863943427 <74853597+zxhd863943427@users.noreply.github.com> Co-authored-by: LYF <27893441+liyufan@users.noreply.github.com> Co-authored-by: Aston Zhang <asv325@gmail.com> Co-authored-by: xiaotinghe <xiaotih@amazon.com> Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal> Co-authored-by: Holly-Max <60691735+Holly-Max@users.noreply.github.com> Co-authored-by: HinGwenWoong <peterhuang0323@qq.com> Co-authored-by: Shuai Zhang <cheungdaven@gmail.com>

transpose_qkv

b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2

d2l-zh

mxnet.py

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

Python

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])

airflow/models/taskinstance.py

def current_state(self, session=NEW_SESSION) -> str: return ( session.query(TaskInstance.state) .filter( TaskInstance.dag_id == self.dag_id, TaskInstance.task_id == self.ta

No need to load whole ti in current_state (#22764) Co-authored-by: Jed Cunningham <66968678+jedcunningham@users.noreply.github.com> Co-authored-by: Tzu-ping Chung <uranusjr@gmail.com>

current_state

4eaf9bcddfb370222b4386b02975974bb253f614

airflow

taskinstance.py

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

Python

def current_state(self, session=NEW_SESSION) -> str: return ( session.query(TaskInstance.state) .filter( TaskInstance.dag_id == self.dag_id, TaskInstance.task_id == self.task_id, TaskInstance.run_id == self.run_id, ) .scalar() )

networkx/generators/small.py

def house_graph(create_using=None): description = [ "adjacencylist", "House Graph", 5, [[2, 3],

Docstrings for the small.py module (#5240) * added description for the first 5 small graphs * modified descriptions based on comment and added description for two more functions * added doctrings to all the functions * Minor touchups. Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>

house_graph

dec723f072eb997a497a159dbe8674cd39999ee9

networkx

small.py

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

Python

def house_graph(create_using=None): description = [ "adjacencylist", "House Graph", 5, [[2, 3], [1, 4], [1, 4, 5], [2, 3, 5], [3, 4]], ] G = make_small_undirected_graph(description, create_using) return G

pipenv/patched/pip/_vendor/requests/utils.py

def check_header_validity(header): name, value = header for part in header: if type(part) not in HEADER_VALIDATORS: raise InvalidHeader( f"Header part ({part!r})

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

check_header_validity

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

pipenv

utils.py

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

Python

def check_header_validity(header): name, value = header for part in header: if type(part) not in HEADER_VALIDATORS: raise InvalidHeader( f"Header part ({part!r}) from {{{name!r}: {value!r}}} must be " f"of type str or bytes, not {type(part)}" ) _validate_header_part(name, "name", HEADER_VALIDATORS[type(name)][0]) _validate_header_part(value, "value", HEADER_VALIDATORS[type(value)][1])

saleor/graphql/order/tests/test_order.py

def test_orderline_query(staff_api_client, permission_manage_orders, fulfilled_order): order = fulfilled_order query = line = order.lines.first() metadata_key = "md key" metadata_value = "md value" line.store_value_in_private_metadata({metadata_key: metadata_value}) line.store_value_in_metadata({metadata_key: metadata_value}) line.save() staff_api_client.user.user_permissions.add(permission_manage_orders) response = staff_api_client.post_graphql(query) content = get_graphql_content(response) order_data = content["data"]["orders"]["edges"][0]["node"] first_order_data_line = order_data["lines"][0] variant_id = graphene.Node.to_global_id("ProductVariant", line.variant.pk) assert first_order_data_line["thumbnail"] is None assert first_order_data_line["variant"]["id"] == variant_id assert first_order_data_line["quantity"] == line.quantity assert first_order_data_line["unitPrice"]["currency"] == line.unit_price.currency assert first_order_data_line["metadata"] == [ {"key": metadata_key, "value": metadata_value} ] assert first_order_data_line["privateMetadata"] == [ {"key": metadata_key, "value": metadata_value} ] expected_unit_price = Money( amount=str(first_order_data_line["unitPrice"

Metadata added to checkout and order lines (#10040) * Metadata added to checkout and order lines * CHANGELOG.md update * Missing tests added

test_orderline_query

a68553e1a55e3a1bd32826cdce294d27f74175e9

saleor

test_order.py

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

Python

def test_orderline_query(staff_api_client, permission_manage_orders, fulfilled_order): order = fulfilled_order query = line = order.lines.first() metadata_key = "md key" metadata_value = "md value" line.store_value_in_private_metadata({metadata_key: metadata_value}) line.store_value_in_metadata({metadata_key: metadata_value}) line.save() staff_api_client.user.user_permissions.add(permission_manage_orders) response = staff_api_client.post_graphql(query) content = get_graphql_content(response) order_data = content["data"]["orders"]["edges"][0]["node"] first_order_data_line = order_data["lines"][0] variant_id = graphene.Node.to_global_id("ProductVariant", line.variant.pk) assert first_order_data_line["thumbnail"] is None assert first_order_data_line["variant"]["id"] == variant_id assert first_order_data_line["quantity"] == line.quantity assert first_order_data_line["unitPrice"]["currency"] == line.unit_price.currency assert first_order_data_line["metadata"] == [ {"key": metadata_key, "value": metadata_value} ] assert first_order_data_line["privateMetadata"] == [ {"key": metadata_key, "value": metadata_value} ] expected_unit_price = Money( amount=str(first_order_data_line["unitPrice"]["gross"]["amount"]), currency="USD", ) assert first_order_data_line["totalPrice"]["currency"] == line.unit_price.currency assert expected_unit_price == line.unit_price.gross expected_total_price = Money( amount=str(first_order_data_line["totalPrice"]["gross"]["amount"]), currency="USD", ) assert expected_total_price == line.unit_price.gross * line.quantity allocation = line.allocations.first() allocation_id = graphene.Node.to_global_id("Allocation", allocation.pk) warehouse_id = graphene.Node.to_global_id( "Warehouse", allocation.stock.warehouse.pk ) assert first_order_data_line["allocations"] == [ { "id": allocation_id, "quantity": allocation.quantity_allocated, "warehouse": {"id": warehouse_id}, } ]

scapy/layers/inet.py

def in4_pseudoheader(proto, u, plen): # type: (int, IP, int) -> bytes if u.len is not None: if u.ihl is None: olen = sum(len(x) for x in u.options) ihl = 5 + olen // 4 + (1 if olen % 4 else 0) else: ihl = u.ihl ln = max(u.len - 4 * ihl, 0) else: ln = plen # Filter out IPOption_LSRR and IPOption_SSRR sr_options = [opt for opt in u.options if isinstance(opt, IPOption_LSRR) or isinstance(opt, IPOption_SSRR)] len_sr_options = len(sr_options) if len_sr_options == 1 and len(sr_options[0].routers): # The checksum must be computed using the final # destination address u.dst = sr_options[0].routers[-1] elif len_sr_options > 1: message = "Found %d Source Routing Options! " message += "Falling back to IP.dst for checksum computation." warning(message, len_sr_options) return struct.pack("!4s4sHH", inet_pton(socket.AF_IN

Support TCP-MD5 and TCP-AO (#3358) Support TCP-MD5 and TCP-AO

in4_pseudoheader

20ac1d00389d0735e6d8cd1347f0a53f478144ba

scapy

inet.py

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

Python

def in4_pseudoheader(proto, u, plen): # type: (int, IP, int) -> bytes if u.len is not None: if u.ihl is None: olen = sum(len(x) for x in u.options) ihl = 5 + olen // 4 + (1 if olen % 4 else 0) else: ihl = u.ihl ln = max(u.len - 4 * ihl, 0) else: ln = plen # Filter out IPOption_LSRR and IPOption_SSRR sr_options = [opt for opt in u.options if isinstance(opt, IPOption_LSRR) or isinstance(opt, IPOption_SSRR)] len_sr_options = len(sr_options) if len_sr_options == 1 and len(sr_options[0].routers): # The checksum must be computed using the final # destination address u.dst = sr_options[0].routers[-1] elif len_sr_options > 1: message = "Found %d Source Routing Options! " message += "Falling back to IP.dst for checksum computation." warning(message, len_sr_options) return struct.pack("!4s4sHH", inet_pton(socket.AF_INET, u.src), inet_pton(socket.AF_INET, u.dst), proto, ln)

modin/core/storage_formats/base/doc_utils.py

def doc_resample_fillna(method, refer_to, params=None, overwrite_template_params=False): action = f"fill missing values in each group in

REFACTOR-#4093: Refactor base to be smaller (#4220) Signed-off-by: jeffreykennethli <jkli@ponder.io>

doc_resample_fillna

be9d382e35a9b87565499c029056afe1ddce6f37

modin

doc_utils.py

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

Python

def doc_resample_fillna(method, refer_to, params=None, overwrite_template_params=False): action = f"fill missing values in each group independently using {method} method" params_substitution = "limit : int\n" if params: params_substitution = ( params if overwrite_template_params else format_string( "{params}\n{params_substitution}", params=params, params_substitution=params_substitution, ) ) build_rules = "- QueryCompiler contains unsampled data with missing values filled." return doc_resample( action=action, extra_params=params_substitution, build_rules=build_rules, refer_to=refer_to, ) doc_dt = partial( doc_qc_method, template=, one_column_method=True, refer_to_module_name="Series.dt", ) doc_dt_timestamp = partial(doc_dt, dt_type="datetime") doc_dt_interval = partial(doc_dt, dt_type="interval") doc_dt_period = partial(doc_dt, dt_type="period") doc_dt_round = partial( doc_qc_method, template=, one_column_method=True, refer_to_module_name="Series.dt", ) doc_str_method = partial( doc_qc_method, template=, one_column_method=True, refer_to_module_name="Series.str", )

erpnext/utilities/transaction_base.py

def delete_events(ref_type, ref_name): events = ( frappe.db.sql_list( , (ref_type, ref_name), ) or [] ) if events: frappe.delete_doc("Event", events, for_reload=True)

style: format code with black

delete_events

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

transaction_base.py

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

Python

def delete_events(ref_type, ref_name): events = ( frappe.db.sql_list( , (ref_type, ref_name), ) or [] ) if events: frappe.delete_doc("Event", events, for_reload=True)

python/ray/serve/deployment_state.py

def check_started(self) -> ReplicaStartupStatus: status, version = self._actor.check_ready() if status == ReplicaStartupStatus.SUCCEEDED: # Re-assign Depl

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

check_started

905258dbc19753c81039f993477e7ab027960729

ray

deployment_state.py

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

Python

def check_started(self) -> ReplicaStartupStatus: status, version = self._actor.check_ready() if status == ReplicaStartupStatus.SUCCEEDED: # Re-assign DeploymentVersion if start / update / recover succeeded # by reading re-computed version in RayServeReplica if version is not None: self._version = version return status

tests/components/homekit_controller/test_sensor.py

async def test_battery_low(hass, utcnow): helper = await setup_test_component( hass, create_battery_level_sensor, suffix="battery" ) state = await helper.async_update(

Improve homekit_controller tests (#65266)

test_battery_low

58b8c30221a6f6e5acbbe98b7e3298b03fb741f5

core

test_sensor.py

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

Python

async def test_battery_low(hass, utcnow): helper = await setup_test_component( hass, create_battery_level_sensor, suffix="battery" ) state = await helper.async_update( ServicesTypes.BATTERY_SERVICE, { CharacteristicsTypes.BATTERY_LEVEL: 1, CharacteristicsTypes.STATUS_LO_BATT: 0, }, ) assert state.attributes["icon"] == "mdi:battery-10" state = await helper.async_update( ServicesTypes.BATTERY_SERVICE, { CharacteristicsTypes.BATTERY_LEVEL: 1, CharacteristicsTypes.STATUS_LO_BATT: 1, }, ) assert state.attributes["icon"] == "mdi:battery-alert"

lib/model/loss/perceptual_loss_plaid.py

def _hyab(self, y_true, y_pred): delta = y_true

Add Flip Loss Function - Add Flip for AMD and TF - Split Perceptual Loss functions to own modules - Fix allowed input shape for models - Allow GUI tooltip to display at higher width

_hyab

582c2ce40c11ef235dd3f9100f70e1e2832f8dd3

faceswap

perceptual_loss_plaid.py

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

Python

def _hyab(self, y_true, y_pred): delta = y_true - y_pred root = K.sqrt(K.clip(K.pow(delta[..., 0:1], 2), self._epsilon, None)) delta_norm = frobenius_norm(delta[..., 1:3]) return root + delta_norm

tests/cli/commands/test_db_command.py

def test_dry_run(self, run_cleanup_mock, dry_run_arg, expected): args = self.parser.parse_args( [ 'db', 'clean', '--clean-before-timestamp', '2021-01-01', *dry_run_arg, ] ) db_command.cleanup_tables(args) run_cleanup_mock.assert_called_once_with( table_names=None, dry_run=expected, clean_before_ti

Don't rely on current ORM structure for db clean command (#23574) For command DB clean, by not relying on the ORM models, we will be able to use the command even when the metadatabase is not yet upgraded to the version of Airflow you have installed. Additionally we archive all rows before deletion.

test_dry_run

95bd6b71cc9f5da377e272707f7b68000d980939

airflow

test_db_command.py

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

Python

def test_dry_run(self, run_cleanup_mock, dry_run_arg, expected): args = self.parser.parse_args( [ 'db', 'clean', '--clean-before-timestamp', '2021-01-01', *dry_run_arg, ] ) db_command.cleanup_tables(args) run_cleanup_mock.assert_called_once_with( table_names=None, dry_run=expected, clean_before_timestamp=pendulum.parse('2021-01-01 00:00:00Z'), verbose=False, confirm=True, skip_archive=False, )

homeassistant/components/homekit/util.py

def async_dismiss_setup_message(hass, entry_id):

Import persistent notification (part 3) (#63900)

async_dismiss_setup_message

2eab3c8de1fd80a8f1456fd97389ca687c11ecb7

core

util.py

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

Python

def async_dismiss_setup_message(hass, entry_id): persistent_notification.async_dismiss(hass, entry_id)

django/apps/registry.py

def get_containing_app_config(self, object_name): self.check_apps_ready() candidates = [] for app_config in self.app_configs.values(): if object_name.startswith(app_config.name): subpath = object_name[len(app_config.name) :] if subpath == "" or subpath[0] == ".": candidates.append(app_config) if candidates: return sorted(candidates, key=lambd

Refs #33476 -- Reformatted code with Black.

get_containing_app_config

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

registry.py

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

Python

def get_containing_app_config(self, object_name): self.check_apps_ready() candidates = [] for app_config in self.app_configs.values(): if object_name.startswith(app_config.name): subpath = object_name[len(app_config.name) :] if subpath == "" or subpath[0] == ".": candidates.append(app_config) if candidates: return sorted(candidates, key=lambda ac: -len(ac.name))[0]

keras/engine/base_layer.py

def _track_variables(self, value): for val in tf.nest.flatten(value): if isinstance(val, tf.Variable): self._track_variable(val) elif tf_utils.is_extension_type(val): # Manually expand extension types to track resource variables. nested_vals = tf_utils.

Prepare keras for making ResourceVariables as CompositeTensors. We are going to let ResourceVariable be a subclass of CompositeTensor. Changes in this CL are necessary to not break existing code. Specifically, to track resource variables embedded in composite tensors, we will need to manually expand composite tensors layer by layer instead of replying on tf.nest. Currently resource variables are atoms and considered to have the same structure as tensors. So we could have one branch to be a resource variable and the other branch to be a tensor. After making resource variable as composite tensors, resource variables will be tf.nest sequences instead of atoms. To avoid the type spec mismatch, we replace resource variables with tf.nest atoms just for the purpose of tf.nest.assert_same_structure. PiperOrigin-RevId: 464573876

_track_variables

102ab667f513956d89f55f2f9480b9cdc5372eef

keras

base_layer.py

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

Python

def _track_variables(self, value): for val in tf.nest.flatten(value): if isinstance(val, tf.Variable): self._track_variable(val) elif tf_utils.is_extension_type(val): # Manually expand extension types to track resource variables. nested_vals = tf_utils.type_spec_from_value(val)._to_components( val ) self._track_variables(nested_vals)

certbot-apache/certbot_apache/_internal/configurator.py

def _create_vhost_v2(self, node): addrs = set() for param in node.parameters: addr = obj.Addr.fromstring(param) if addr: addrs.add(addr) is_ssl = False # Exclusion to match the behavior in get_virtual_hosts_v2 sslengine = node.find_directives("SSLEngine", exclude=False) if sslengine: for directive in sslengine: if directive.parameters[0].lower() == "on": is_ssl = True break # "SSLEngine on" might be set outside of <VirtualHost> # Treat vhosts with port 443 as ssl vhosts for addr in addrs: if addr.get_port() == "443": is_ssl = True enabled = apache_uti

Fully type certbot-nginx module (#9124) * Work in progress * Fix type * Work in progress * Work in progress * Work in progress * Work in progress * Work in progress * Oups. * Fix typing in UnspacedList * Fix logic * Finish typing * List certbot-nginx as fully typed in tox * Fix lint * Fix checks * Organize imports * Fix typing for Python 3.6 * Fix checks * Fix lint * Update certbot-nginx/certbot_nginx/_internal/configurator.py Co-authored-by: alexzorin <alex@zor.io> * Update certbot-nginx/certbot_nginx/_internal/configurator.py Co-authored-by: alexzorin <alex@zor.io> * Fix signature of deploy_cert regarding the installer interface * Update certbot-nginx/certbot_nginx/_internal/obj.py Co-authored-by: alexzorin <alex@zor.io> * Fix types * Update certbot-nginx/certbot_nginx/_internal/parser.py Co-authored-by: alexzorin <alex@zor.io> * Precise type * Precise _coerce possible inputs/outputs * Fix type * Update certbot-nginx/certbot_nginx/_internal/http_01.py Co-authored-by: ohemorange <ebportnoy@gmail.com> * Fix type * Remove an undesirable implementation. * Fix type Co-authored-by: alexzorin <alex@zor.io> Co-authored-by: ohemorange <ebportnoy@gmail.com>

_create_vhost_v2

16aad35d31a887dab157f9d4f5e0fe9218d06064

certbot

configurator.py

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

Python

def _create_vhost_v2(self, node): addrs = set() for param in node.parameters: addr = obj.Addr.fromstring(param) if addr: addrs.add(addr) is_ssl = False # Exclusion to match the behavior in get_virtual_hosts_v2 sslengine = node.find_directives("SSLEngine", exclude=False) if sslengine: for directive in sslengine: if directive.parameters[0].lower() == "on": is_ssl = True break # "SSLEngine on" might be set outside of <VirtualHost> # Treat vhosts with port 443 as ssl vhosts for addr in addrs: if addr.get_port() == "443": is_ssl = True enabled = apache_util.included_in_paths(node.filepath, self.parsed_paths) macro = False # Check if the VirtualHost is contained in a mod_macro block if node.find_ancestors("Macro"): macro = True vhost = obj.VirtualHost( node.filepath, None, addrs, is_ssl, enabled, modmacro=macro, node=node ) self._populate_vhost_names_v2(vhost) return vhost

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

def insert_on(self, path, loc=None, replace=False): loc = loc or self.location if not loc: return nloc = _normalize_cached(loc) bdir = os.path.dirname(nloc) npath = [(p and _normalize_cached(p) or p) for p in path] fo

upd; format

insert_on

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

__init__.py

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

Python

def insert_on(self, path, loc=None, replace=False): loc = loc or self.location if not loc: return nloc = _normalize_cached(loc) bdir = os.path.dirname(nloc) npath = [(p and _normalize_cached(p) or p) for p in path] for p, item in enumerate(npath): if item == nloc: if replace: break else: # don't modify path (even removing duplicates) if # found and not replace return elif item == bdir and self.precedence == EGG_DIST: # if it's an .egg, give it precedence over its directory # UNLESS it's already been added to sys.path and replace=False if (not replace) and nloc in npath[p:]: return if path is sys.path: self.check_version_conflict() path.insert(p, loc) npath.insert(p, nloc) break else: if path is sys.path: self.check_version_conflict() if replace: path.insert(0, loc) else: path.append(loc) return # p is the spot where we found or inserted loc; now remove duplicates while True: try: np = npath.index(nloc, p + 1) except ValueError: break else: del npath[np], path[np] # ha! p = np return

@add_start_docstrings( """ The XGLM Model transformer with a language modeling head on top (linear layer with weights tied to the input embeddings). """, XGLM_START_DOCSTRING, )

src/transformers/models/xglm/modeling_tf_xglm.py

def serving_output(self, output): pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None cross_attns = ( tf.convert_to_tensor(output.cross_attentions) if self.config.output_attent

Add TF implementation of `XGLMModel` (#16543) * Add TFXGLM models * Add todo: self.supports_xla_generation = False Co-authored-by: Daniel Stancl <stancld@Daniels-MacBook-Pro.local> Co-authored-by: Daniel Stancl <stancld@daniels-mbp.home> Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: Daniel <daniel.stancl@rossum.ai> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

serving_output

c72d7d91bf4899760725793421eff9da640c8527

transformers

modeling_tf_xglm.py

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

Python

def serving_output(self, output): pkv = tf.convert_to_tensor(output.past_key_values) if self.config.use_cache else None hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None cross_attns = ( tf.convert_to_tensor(output.cross_attentions) if self.config.output_attentions and self.config.add_cross_attention else None ) return TFBaseModelOutputWithPastAndCrossAttentions( last_hidden_state=output.hidden_states, past_key_values=pkv, hidden_states=hs, attentions=attns, cross_attentions=cross_attns, ) @add_start_docstrings( , XGLM_START_DOCSTRING, )

modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py

def _apply_func_to_list_of_partitions(cls, func, partitions, **kwargs): preprocessed_map_func = cls.preprocess_func(func) key_futures = RayWrapper.materialize( [ partition.apply(preprocessed_map_func, **kwargs) for partition in partitions ] ) gpu_managers = [partition.get_gpu_manager()

REFACTOR-#5009: use RayWrapper.materialize instead of ray.get (#5010) Signed-off-by: Myachev <anatoly.myachev@intel.com>

_apply_func_to_list_of_partitions

1dc16415333bf2428ee2b1f4d31ff94e66b9a0a6

modin

partition_manager.py

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

Python

def _apply_func_to_list_of_partitions(cls, func, partitions, **kwargs): preprocessed_map_func = cls.preprocess_func(func) key_futures = RayWrapper.materialize( [ partition.apply(preprocessed_map_func, **kwargs) for partition in partitions ] ) gpu_managers = [partition.get_gpu_manager() for partition in partitions] return cls._create_partitions(key_futures, gpu_managers)

python/ray/serve/deployment_function_executor_node.py

def _execute_impl(self, *args, **kwargs) -> ObjectRef: return self._deployment_function_handle.remote( *

[Serve][Deployment Graph][Perf] Add minimal executor DAGNode (#24754) closes #24475 Current deployment graph has big perf issues compare with using plain deployment handle, mostly because overhead of DAGNode traversal mechanism. We need this mechanism to empower DAG API, specially deeply nested objects in args where we rely on pickling; But meanwhile the nature of each execution becomes re-creating and replacing every `DAGNode` instances involved upon each execution, that incurs overhead. Some overhead is inevitable due to pickling and executing DAGNode python code, but they could be quite minimal. As I profiled earlier, pickling itself is quite fast for our benchmarks at magnitude of microseconds. Meanwhile the elephant in the room is DeploymentNode and its relatives are doing too much work in constructor that's beyond necessary, thus slowing everything down. So the fix is as simple as 1) Introduce a new set of executor dag node types that contains absolute minimal information that only preserves the DAG structure with traversal mechanism, and ability to call relevant deployment handles. 2) Add a simple new pass in our build() that generates and replaces nodes with executor dag to produce a final executor dag to run the graph. Current ray dag -> serve dag mixed a lot of stuff related to deployment generation and init args, in longer term we should remove them but our correctness depends on it so i rather leave it as separate PR. ### Current 10 node chain with deployment graph `.bind()` ``` chain_length: 10, num_clients: 1 latency_mean_ms: 41.05, latency_std_ms: 15.18 throughput_mean_tps: 27.5, throughput_std_tps: 3.2 ``` ### Using raw deployment handle without dag overhead ``` chain_length: 10, num_clients: 1 latency_mean_ms: 20.39, latency_std_ms: 4.57 throughput_mean_tps: 51.9, throughput_std_tps: 1.04 ``` ### After this PR: ``` chain_length: 10, num_clients: 1 latency_mean_ms: 20.35, latency_std_ms: 0.87 throughput_mean_tps: 48.4, throughput_std_tps: 1.43 ```

_execute_impl

f27e85cd7df5ca2873ef6231200a1530e16ac35d

ray

deployment_function_executor_node.py

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

Python

def _execute_impl(self, *args, **kwargs) -> ObjectRef: return self._deployment_function_handle.remote( *self._bound_args, **self._bound_kwargs )

@keras_export('keras.utils.load_img', 'keras.preprocessing.image.load_img')

keras/preprocessing/image.py

def save_img(path, x, data_format=None, file_format=None, scale=True, **kwargs): if data_format is None: data_format = backend.image_data_format() img = array_to_img(x, data_format=data_format, scale=scale) if img.mode == 'RGBA' and (file_format == 'jpg' or file_format == 'jpeg'): warnings.warn('The JPG format does not support ' 'RGBA images, converting to RGB.') img = img.conve

Copy image utils from keras_preprocessing directly into core keras This is not new code, we are just moving these utilities directly into keras from keras-preprocessing. For the library code, just fixed linting errors. For the test code, had to do more major changes to port from pytest, but hopefully any errors have been caught by the tests themselves. PiperOrigin-RevId: 427274651

save_img

373ad97c72ed1ac4b6898e85b2cfd7b016e4b469

keras

image.py

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

Python

def save_img(path, x, data_format=None, file_format=None, scale=True, **kwargs): if data_format is None: data_format = backend.image_data_format() img = array_to_img(x, data_format=data_format, scale=scale) if img.mode == 'RGBA' and (file_format == 'jpg' or file_format == 'jpeg'): warnings.warn('The JPG format does not support ' 'RGBA images, converting to RGB.') img = img.convert('RGB') img.save(path, format=file_format, **kwargs) @keras_export('keras.utils.load_img', 'keras.preprocessing.image.load_img')

wagtail/admin/views/pages/edit.py

def log_commenting_changes(self, changes, revision): for comment in changes["new_comments"]: comment.log_create(page_revision=revision, user=self.request.user) for comment in changes["edited_comments"]: comment.log_edit(page_revision=revision, user=self.request.user) for comment in changes["resolved_comments"]: comment.log_resolve(page_revision=revision, user=self.request.user) for comment in changes["deleted_comments"]: comment.log_delete(page_revision=revision, user=self.request.user) for comment, replies in changes["new_replies"]: for reply in replies: reply.log_create(page_revision=revision, user=self.request.user) for comment, replies in changes["edited_replies"]: for reply in replies: reply.log_edit(page_revision=revision, user=self.request.user) for comment, replies in changes["deleted_replies"]: for reply in replies: reply.log_delete(page_revision=revision, user=self.request.user)

Reformat with black

log_commenting_changes

d10f15e55806c6944827d801cd9c2d53f5da4186

wagtail

edit.py

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

Python

def log_commenting_changes(self, changes, revision): for comment in changes["new_comments"]: comment.log_create(page_revision=revision, user=self.request.user) for comment in changes["edited_comments"]: comment.log_edit(page_revision=revision, user=self.request.user) for comment in changes["resolved_comments"]: comment.log_resolve(page_revision=revision, user=self.request.user) for comment in changes["deleted_comments"]: comment.log_delete(page_revision=revision, user=self.request.user) for comment, replies in changes["new_replies"]: for reply in replies: reply.log_create(page_revision=revision, user=self.request.user) for comment, replies in changes["edited_replies"]: for reply in replies: reply.log_edit(page_revision=revision, user=self.request.user) for comment, replies in changes["deleted_replies"]: for reply in replies: reply.log_delete(page_revision=revision, user=self.request.user)

lib/matplotlib/patches.py

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

Small style fixes.

__new__

075ff0952896f44d7d0b0b3318f0978ae53f84d7

matplotlib

patches.py

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

Python

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

keras/engine/base_layer.py

def losses(self): collected_losses = [] for layer in self._flatten_layers(): # If any eager losses are present, we assume the model to be part of # an eager training loop (either a custom one or the one used when # `run_eagerly=True`) and so we always return just the eager losses. if layer._eager_losses: # Filter placeholder losses that may have been added by revived # layers. (see base_layer_utils for details). if ( layer._eager_losses[0] is not base_layer_utils.REVIVED_LOSS_PLACEHOLDER ): collected_losses.extend(layer._eager_losses) else: collected_losses.extend(layer._losses) for regularizer in layer._callable_losses:

reduct too long lines

losses

fa6d9107a498f7c2403ff28c7b389a1a0c5cc083

keras

base_layer.py

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

Python

def losses(self): collected_losses = [] for layer in self._flatten_layers(): # If any eager losses are present, we assume the model to be part of # an eager training loop (either a custom one or the one used when # `run_eagerly=True`) and so we always return just the eager losses. if layer._eager_losses: # Filter placeholder losses that may have been added by revived # layers. (see base_layer_utils for details). if ( layer._eager_losses[0] is not base_layer_utils.REVIVED_LOSS_PLACEHOLDER ): collected_losses.extend(layer._eager_losses) else: collected_losses.extend(layer._losses) for regularizer in layer._callable_losses: loss_tensor = regularizer() if loss_tensor is not None: collected_losses.append(loss_tensor) return collected_losses

sklearn/linear_model/_least_angle.py

def fit(self, X, y, Xy=None): self._validate_params() X, y = self._validate_data(X, y, y_numeric=True, multi_output=True) _normalize = _deprecate_normalize( self.normalize, default=True, estimator_name=self.__class__.__name__ ) alpha = getattr(self, "alp

MAINT Parameter Validation for Lars, LarsCV, LassoLars, LassoLarsCV and LassoLarsIC (#24033) Co-authored-by: jeremie du boisberranger <jeremiedbb@yahoo.fr>

fit

6c0e0b2e4723d11e29057635c7061a36bc1a8512

scikit-learn

_least_angle.py

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

Python

def fit(self, X, y, Xy=None): self._validate_params() X, y = self._validate_data(X, y, y_numeric=True, multi_output=True) _normalize = _deprecate_normalize( self.normalize, default=True, estimator_name=self.__class__.__name__ ) alpha = getattr(self, "alpha", 0.0) if hasattr(self, "n_nonzero_coefs"): alpha = 0.0 # n_nonzero_coefs parametrization takes priority max_iter = self.n_nonzero_coefs else: max_iter = self.max_iter if self.jitter is not None: rng = check_random_state(self.random_state) noise = rng.uniform(high=self.jitter, size=len(y)) y = y + noise self._fit( X, y, max_iter=max_iter, alpha=alpha, fit_path=self.fit_path, normalize=_normalize, Xy=Xy, ) return self

modules/image/text_to_image/disco_diffusion_ernievil_base/vit_b_16x/ernievil2/transformers/efficientnet.py

def _decode_block_string(block_string): assert isinstance(block_string, str) ops = block_string.split('_') options = {} for op in ops: splits = re.split(r'(\d.*)', op) if len(splits) >= 2: key, value = splits[:2] options[key] = value # Check stride cond_1 = ('s' in options and len(options['s']) == 1) cond_2 = ((len(options['s']) == 2) and (options['s'][0] == options['s

add disco_diffusion_ernievil_base

_decode_block_string

ffcde21305c61d950a9f93e57e6180c9a9665b87

PaddleHub

efficientnet.py

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

Python

def _decode_block_string(block_string): assert isinstance(block_string, str) ops = block_string.split('_') options = {} for op in ops: splits = re.split(r'(\d.*)', op) if len(splits) >= 2: key, value = splits[:2] options[key] = value # Check stride cond_1 = ('s' in options and len(options['s']) == 1) cond_2 = ((len(options['s']) == 2) and (options['s'][0] == options['s'][1])) assert (cond_1 or cond_2) return BlockArgs(kernel_size=int(options['k']), num_repeat=int(options['r']), input_filters=int(options['i']), output_filters=int(options['o']), expand_ratio=int(options['e']), id_skip=('noskip' not in block_string), se_ratio=float(options['se']) if 'se' in options else None, stride=[int(options['s'][0])])

numpy/lib/function_base.py

def copy(a, order='K', subok=False): return

Improve documentation formatting

copy

0307f89d48368a39ed97a252f9faed3c7bf64446

numpy

function_base.py

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

Python

def copy(a, order='K', subok=False): return array(a, order=order, subok=subok, copy=True) # Basic operations

python/ray/data/tests/test_context_propagation.py

def test_context_placement_group(): driver_code = proc = run_string_as_driver_no

[Datasets] Add explicit resource allocation option via a top-level scheduling strategy (#24438) Instead of letting Datasets implicitly use cluster resources in the margins of explicit allocations of other libraries, such as Tune, Datasets should provide an option for explicitly allocating resources for a Datasets workload for users that want to box Datasets in. This PR adds such an explicit resource allocation option, via exposing a top-level scheduling strategy on the DatasetContext with which a placement group can be given.

test_context_placement_group

68d4dd3a8b2defa5549cfa70e59aa26f2d4825a3

ray

test_context_propagation.py

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

Python

def test_context_placement_group(): driver_code = proc = run_string_as_driver_nonblocking(driver_code)

pandas/core/arrays/categorical.py

def reorder_categories(self, new_categories, ordered=None): if set(self.dtype.categories) != set(new_categories): raise ValueError( "items in new_categories are not the same as in old categories" ) return self.set_categories(new_categories, ordered=ordered)

DEPR: remove inplace arg in Categorical methods (#49321) * deprecate inplace arg in categorical methods * fix tests * add back test * doc fix * doc fixes * avoid constructing new objects on every iteration * cleanup

reorder_categories

ab6562a20bd894d02fb28675809698d5be0436f9

pandas

categorical.py

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

Python

def reorder_categories(self, new_categories, ordered=None): if set(self.dtype.categories) != set(new_categories): raise ValueError( "items in new_categories are not the same as in old categories" ) return self.set_categories(new_categories, ordered=ordered)

tests/rest/client/test_rooms.py

def test_get_member_list_no_permission_former_member_with_at_token(self): # create a room, invite the user and the user joins room_id = self.helper.create_room_as("@alice:red") self.helper.invite(room_id, "@alice:red", self.user_id) self.helper.join(room_id, self.user_id) # sync to get an at token channel = self.make_request("GET", "/sync") self.assertEqual(200, channel.code) sync_token = channel.json_body["next_batch"] # check that the user can see the member list to start with channel = self.make_request( "GET", "/rooms/%s/members?at=%s" % (room_id, sync_token) ) se

Replace assertEquals and friends with non-deprecated versions. (#12092)

test_get_member_list_no_permission_former_member_with_at_token

02d708568b476f2f7716000b35c0adfa4cbd31b3

synapse

test_rooms.py

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

Python

def test_get_member_list_no_permission_former_member_with_at_token(self): # create a room, invite the user and the user joins room_id = self.helper.create_room_as("@alice:red") self.helper.invite(room_id, "@alice:red", self.user_id) self.helper.join(room_id, self.user_id) # sync to get an at token channel = self.make_request("GET", "/sync") self.assertEqual(200, channel.code) sync_token = channel.json_body["next_batch"] # check that the user can see the member list to start with channel = self.make_request( "GET", "/rooms/%s/members?at=%s" % (room_id, sync_token) ) self.assertEqual(200, channel.code, msg=channel.result["body"]) # ban the user (Note: the user is actually allowed to see this event and # state so that they know they're banned!) self.helper.change_membership(room_id, "@alice:red", self.user_id, "ban") # invite a third user and let them join self.helper.invite(room_id, "@alice:red", "@bob:red") self.helper.join(room_id, "@bob:red") # now, with the original user, sync again to get a new at token channel = self.make_request("GET", "/sync") self.assertEqual(200, channel.code) sync_token = channel.json_body["next_batch"] # check the user can no longer see the updated member list channel = self.make_request( "GET", "/rooms/%s/members?at=%s" % (room_id, sync_token) ) self.assertEqual(403, channel.code, msg=channel.result["body"])

python3.10.4/Lib/difflib.py

def _keep_original_ws(s, tag_s): return ''.join( c if tag_c == " " and c.isspace() else tag_c for c, tag_c in zip(s, tag_s) )

add python 3.10.4 for windows

_keep_original_ws

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

difflib.py

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

Python

def _keep_original_ws(s, tag_s): return ''.join( c if tag_c == " " and c.isspace() else tag_c for c, tag_c in zip(s, tag_s) )

lib/matplotlib/cm.py

def unregister_cmap(name): cmap = _colormaps.get(name, None) _colormaps.unregister(name) return cmap

MNT: Remove cmap_d colormap access

unregister_cmap

fb902f735995372f345a8333804f5c6052f29770

matplotlib

cm.py

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

Python

def unregister_cmap(name): cmap = _colormaps.get(name, None) _colormaps.unregister(name) return cmap

src/datasets/utils/streaming_download_manager.py

def _get_extraction_protocol_with_magic_number(f) -> Optional[str]: magic_number = f.read(MAGIC_NUMBER_MAX_LENGTH) f.seek(0) for i in range(MAGIC_NUMBER_MAX_LENGTH): compression = MAGIC_NUMBER_TO_COMPRESSION_PROTOCOL.get(magic_number[: MAGIC_NUMBER_MAX_LENGTH - i]) if compression is not None: # TODO(QL): raise an error for .tar.gz files as

don't check f.loc in _get_extraction_protocol_with_magic_number (#4318)

_get_extraction_protocol_with_magic_number

17fd2ea68cf75b36369a9f018497875e292db26a

datasets

streaming_download_manager.py

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

Python

def _get_extraction_protocol_with_magic_number(f) -> Optional[str]: magic_number = f.read(MAGIC_NUMBER_MAX_LENGTH) f.seek(0) for i in range(MAGIC_NUMBER_MAX_LENGTH): compression = MAGIC_NUMBER_TO_COMPRESSION_PROTOCOL.get(magic_number[: MAGIC_NUMBER_MAX_LENGTH - i]) if compression is not None: # TODO(QL): raise an error for .tar.gz files as in _get_extraction_protocol return compression compression = MAGIC_NUMBER_TO_UNSUPPORTED_COMPRESSION_PROTOCOL.get(magic_number[: MAGIC_NUMBER_MAX_LENGTH - i]) if compression is not None: raise NotImplementedError(f"Compression protocol '{compression}' not implemented.")

salt/modules/lxc.py

def _get_veths(net_data): if isinstance(net_data, dict): net_data = list(net_data.items()) nics = salt.utils.odict.OrderedDict() current_nic = salt.utils.odict.OrderedDict() no_names = True for item in net_data: if item and isinstance(item, dict): item = list(item.items())[0] # skip LXC configuration comment lines, and play only with tuples conf elif isinstance(item, str): # deal with reflection of commented lxc config

Update to latest ``pyupgrade`` hook. Stop skipping it on CI. Signed-off-by: Pedro Algarvio <palgarvio@vmware.com>

_get_veths

f2a783643de61cac1ff3288b40241e5ce6e1ddc8

salt

lxc.py

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

Python

def _get_veths(net_data): if isinstance(net_data, dict): net_data = list(net_data.items()) nics = salt.utils.odict.OrderedDict() current_nic = salt.utils.odict.OrderedDict() no_names = True for item in net_data: if item and isinstance(item, dict): item = list(item.items())[0] # skip LXC configuration comment lines, and play only with tuples conf elif isinstance(item, str): # deal with reflection of commented lxc configs sitem = item.strip() if sitem.startswith("#") or not sitem: continue elif "=" in item: item = tuple(a.strip() for a in item.split("=", 1)) if item[0] == "lxc.network.type": current_nic = salt.utils.odict.OrderedDict() if item[0] == "lxc.network.name": no_names = False nics[item[1].strip()] = current_nic current_nic[item[0].strip()] = item[1].strip() # if not ethernet card name has been collected, assuming we collected # data for eth0 if no_names and current_nic: nics[DEFAULT_NIC] = current_nic return nics

nni/runtime/log.py

def start_stdout_logging() -> None: if '_stdout_' in _handlers: return

Logging refactor (step 1) - experiment handlers (#4792)

start_stdout_logging

4feab0e34b490500b06efd6e7e8a34d686702c2f

nni

log.py

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

Python

def start_stdout_logging() -> None: if '_stdout_' in _handlers: return handler = StreamHandler(sys.stdout) handler.setFormatter(_StdoutFormatter()) _handlers['_stdout_'] = handler _root_logger.addHandler(handler)

@frappe.whitelist()

erpnext/hr/doctype/job_offer/job_offer.py

def get_staffing_plan_detail(designation, company, offer_date): detail = frappe.db.sql( , (designation, company, offer_date), as_dict=1, ) return frappe._dict(detail[0]) if (detail and detail[0].parent) else None @frappe.whitelist()

style: format code with black

get_staffing_plan_detail

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

job_offer.py

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

Python

def get_staffing_plan_detail(designation, company, offer_date): detail = frappe.db.sql( , (designation, company, offer_date), as_dict=1, ) return frappe._dict(detail[0]) if (detail and detail[0].parent) else None @frappe.whitelist()

tests/push/test_push_rule_evaluator.py

def test_display_name(self) -> None: evaluator = self._get_evaluator({"body": "foo bar baz"}) condition = { "kind": "contains_display_name", } # Blank names are skipped. self.assertFalse(evaluator.matches(condition, "@user:test", "")) # Check a display name that doesn't match. self.assertFalse(evaluator.matches(condition, "@user:test", "not found")) # Check a display name which matches. self.assertTrue(evaluator.matches(condition, "@user:test", "foo")) # A display name that matches, but not a full word does not result in a match. self.assertFalse(evaluator.matches(condition, "@user:test", "ba")) # A display name should not be interpreted as a regular expression. self.assertFalse(evaluator.matches(condition, "@user:test",

Add type hints to tests files. (#12256)

test_display_name

9d21ecf7ceab55bc19c4457b8b07401b0b1623a7

synapse

test_push_rule_evaluator.py

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

Python

def test_display_name(self) -> None: evaluator = self._get_evaluator({"body": "foo bar baz"}) condition = { "kind": "contains_display_name", } # Blank names are skipped. self.assertFalse(evaluator.matches(condition, "@user:test", "")) # Check a display name that doesn't match. self.assertFalse(evaluator.matches(condition, "@user:test", "not found")) # Check a display name which matches. self.assertTrue(evaluator.matches(condition, "@user:test", "foo")) # A display name that matches, but not a full word does not result in a match. self.assertFalse(evaluator.matches(condition, "@user:test", "ba")) # A display name should not be interpreted as a regular expression. self.assertFalse(evaluator.matches(condition, "@user:test", "ba[rz]")) # A display name with spaces should work fine. self.assertTrue(evaluator.matches(condition, "@user:test", "foo bar"))

tests/pytests/functional/modules/file/test_readlink.py

def test_readlink_not_a_link(file, source): with pytest.raises(Salt

Add some funtional tests Add functional tests for the following: - file.readlink - file.replace - file.symlink Remove unit tests for file.replace as they are duplicated in the added functional test

test_readlink_not_a_link

a35b29b2651bf33c5d5b45e64bc7765ffde4aff4

salt

test_readlink.py

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

Python

def test_readlink_not_a_link(file, source): with pytest.raises(SaltInvocationError) as exc: file.readlink(path=source) assert "A valid link was not specified" in exc.value.message

erpnext/stock/report/stock_analytics/stock_analytics.py

def get_periodic_data(entry, filters): periodic_data = {} for d in entry: period = get_period(d.posting_date, filters) bal_qty = 0 # if period against item does not exist yet, instantiate it # insert existing balance dict against period, and add/subtract to it if periodic_data.get(d.item_code) and not periodic_data.get(d.item_code).get(period): previous_balance = periodic_data[d.item_code]["balance"].copy() periodic_data[d.item_code][period] = previous_balance if d.voucher_type == "Stock Reconciliation": if periodic_data.get(d.item_code) and periodic_data.get(d.item_code).get("balance").get( d.warehouse ): bal_qty = periodic_data[d.item_code]["balance"][d.warehouse] qty_diff = d.qty_after_transaction - bal_qty else: qty_diff = d.actual_qty if filters["value_quantity"] == "Quantity": value = qty_diff else: v

style: format code with black

get_periodic_data

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

stock_analytics.py

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

Python

def get_periodic_data(entry, filters): periodic_data = {} for d in entry: period = get_period(d.posting_date, filters) bal_qty = 0 # if period against item does not exist yet, instantiate it # insert existing balance dict against period, and add/subtract to it if periodic_data.get(d.item_code) and not periodic_data.get(d.item_code).get(period): previous_balance = periodic_data[d.item_code]["balance"].copy() periodic_data[d.item_code][period] = previous_balance if d.voucher_type == "Stock Reconciliation": if periodic_data.get(d.item_code) and periodic_data.get(d.item_code).get("balance").get( d.warehouse ): bal_qty = periodic_data[d.item_code]["balance"][d.warehouse] qty_diff = d.qty_after_transaction - bal_qty else: qty_diff = d.actual_qty if filters["value_quantity"] == "Quantity": value = qty_diff else: value = d.stock_value_difference # period-warehouse wise balance periodic_data.setdefault(d.item_code, {}).setdefault("balance", {}).setdefault(d.warehouse, 0.0) periodic_data.setdefault(d.item_code, {}).setdefault(period, {}).setdefault(d.warehouse, 0.0) periodic_data[d.item_code]["balance"][d.warehouse] += value periodic_data[d.item_code][period][d.warehouse] = periodic_data[d.item_code]["balance"][ d.warehouse ] return periodic_data

sklearn/utils/__init__.py

def shuffle(*arrays, random_state=None, n_samples=None): return resample( *arrays, replace=False, n_samples=n_samples, random_state=random_state )

DOC ensures sklearn.utils.shuffle passes numpydoc validation (#24367) Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

shuffle

49279c3267c0c54cdba80a571820c46f25fbe883

scikit-learn

__init__.py

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

Python

def shuffle(*arrays, random_state=None, n_samples=None): return resample( *arrays, replace=False, n_samples=n_samples, random_state=random_state )

test/lib/ansible_test/_internal/commands/sanity/integration_aliases.py

def check_changes(self, args, results): # type: (SanityConfig, Results) -> None integration_targets = list(walk_integration_targets()) module_targets = list(walk_module_targets()) integration_targets_by_name = dict((target.name, target) for target in integration_targets) module_names_by_path = dict((target.path, target.module) for target in module_targets) disabled_targets = [] unstable_targets = [] unsupported_targets = [] for command in [command for command in args.metadata.change_description.focused_command_targets if 'integration' in command]:

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

check_changes

a06fa496d3f837cca3c437ab6e9858525633d147

ansible

integration_aliases.py

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

Python

def check_changes(self, args, results): # type: (SanityConfig, Results) -> None integration_targets = list(walk_integration_targets()) module_targets = list(walk_module_targets()) integration_targets_by_name = dict((target.name, target) for target in integration_targets) module_names_by_path = dict((target.path, target.module) for target in module_targets) disabled_targets = [] unstable_targets = [] unsupported_targets = [] for command in [command for command in args.metadata.change_description.focused_command_targets if 'integration' in command]: for target in args.metadata.change_description.focused_command_targets[command]: if self.DISABLED in integration_targets_by_name[target].aliases: disabled_targets.append(target) elif self.UNSTABLE in integration_targets_by_name[target].aliases: unstable_targets.append(target) elif self.UNSUPPORTED in integration_targets_by_name[target].aliases: unsupported_targets.append(target) untested_modules = [] for path in args.metadata.change_description.no_integration_paths: module = module_names_by_path.get(path) if module: untested_modules.append(module) comments = [ self.format_comment(self.TEMPLATE_DISABLED, disabled_targets), self.format_comment(self.TEMPLATE_UNSTABLE, unstable_targets), self.format_comment(self.TEMPLATE_UNSUPPORTED, unsupported_targets), self.format_comment(self.TEMPLATE_UNTESTED, untested_modules), ] comments = [comment for comment in comments if comment] labels = dict( needs_tests=bool(untested_modules), disabled_tests=bool(disabled_targets), unstable_tests=bool(unstable_targets), unsupported_tests=bool(unsupported_targets), ) results.comments += comments results.labels.update(labels)

label_studio/tests/test_next_task.py

def test_overlap_first(business_client, setup_before_upload, show_overlap_first): c = business_client config = dict( title='test_overlap_first',

fix: DEV-1348: Fix _rearrange_overlap_cohort filter condition for overlap bulk update with concurrent import (#1844) * [fix] Rearrange overlap depending in annotations count * Fix next task test for not random overlap assignment * Delete unused method * Rename rearrange method to have back compatibility * Refactor to Q_finished_annotations from tasks.models * Fix filter for tasks with max annotations * Change filter for tasks with max annotations * Change project stats recalculation condition * Fix rearrange during import from storage * Change _rearrange_overlap_cohort filter condition * Switching to bulk_update in _rearrange_overlap_cohort * Stylize code * Add is_labeled on import * Fix tests * Fix tests * Fix tests more Co-authored-by: nik <nik@heartex.net> Co-authored-by: Sergei Ivashchenko <triklozoid@gmail.com> Co-authored-by: niklub <lubimov.nicolas@gmail.com> Co-authored-by: Max Tkachenko <makseq@gmail.com>

test_overlap_first

35125cca12ba1e8703c4284894e4e2db44ce7009

label-studio

test_next_task.py

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

Python

def test_overlap_first(business_client, setup_before_upload, show_overlap_first): c = business_client config = dict( title='test_overlap_first', is_published=True, maximum_annotations=1, show_overlap_first=show_overlap_first, sampling="Uniform sampling", label_config= ) project = make_project(config, business_client.user) annotation_result = json.dumps([{ 'from_name': 'text_class', 'to_name': 'text', 'type': 'choices', 'value': {'choices': ['class_A']} }]) num_tasks = 1000 overlap_cohort_percentage = 1 # set up tasks overlap setup_after_upload = True if setup_before_upload: r = c.patch( f'/api/projects/{project.id}/', data=json.dumps({'maximum_annotations': 2, 'overlap_cohort_percentage': overlap_cohort_percentage}), content_type='application/json' ) assert r.status_code == 200 setup_after_upload = False # create tasks tasks = [] for i in range(num_tasks): tasks.append({'data': {'text': f'this is {str(i)}'}}) r = business_client.post( f'/api/projects/{project.id}/tasks/bulk/', data=json.dumps(tasks), content_type='application/json') assert r.status_code == 201 if setup_after_upload: r = c.patch( f'/api/projects/{project.id}/', data=json.dumps({'maximum_annotations': 2, 'overlap_cohort_percentage': overlap_cohort_percentage}), content_type='application/json' ) assert r.status_code == 200 expected_tasks_with_overlap = int(overlap_cohort_percentage / 100. * num_tasks) assert Task.objects.filter(Q(project_id=project.id) & Q(overlap__gt=1)).count() == expected_tasks_with_overlap

sklearn/utils/extmath.py

def svd_flip(u, v, u_based_decision=True): if u_based_decision: # columns of u, rows of v max_abs_cols = np.argmax(np.abs(u), axis=0) signs = np.sign(u[max_abs_cols, range(u.shape[1])]) u *= signs v *= signs[:, np.newaxis] else: # rows of v, columns of u max_abs_rows = np.argmax(np.abs(v), axis=1) signs = np.sign(v[r

DOC Ensures that svd_flip passes numpydoc validation (#24581) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

svd_flip

97057d329da1786aa03206251aab68bf51312390

scikit-learn

extmath.py

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

Python

def svd_flip(u, v, u_based_decision=True): if u_based_decision: # columns of u, rows of v max_abs_cols = np.argmax(np.abs(u), axis=0) signs = np.sign(u[max_abs_cols, range(u.shape[1])]) u *= signs v *= signs[:, np.newaxis] else: # rows of v, columns of u max_abs_rows = np.argmax(np.abs(v), axis=1) signs = np.sign(v[range(v.shape[0]), max_abs_rows]) u *= signs v *= signs[:, np.newaxis] return u, v

rllib/policy/tf_policy.py

def extra_action_out_fn(self) -> Dict[str, TensorType]: extra_fetches = {} # Action-logp and action-prob. if self._sampled_action_logp is not None: extra_fetches

[RLlib] Migrate MAML, MB-MPO, MARWIL, and BC to use Policy sub-classing implementation. (#24914)

extra_action_out_fn

d5a6d46049d0ea0490c90366a081de79a87d0fac

ray

tf_policy.py

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

Python

def extra_action_out_fn(self) -> Dict[str, TensorType]: extra_fetches = {} # Action-logp and action-prob. if self._sampled_action_logp is not None: extra_fetches[SampleBatch.ACTION_PROB] = self._sampled_action_prob extra_fetches[SampleBatch.ACTION_LOGP] = self._sampled_action_logp # Action-dist inputs. if self._dist_inputs is not None: extra_fetches[SampleBatch.ACTION_DIST_INPUTS] = self._dist_inputs return extra_fetches

airflow/jobs/triggerer_job.py

async def cleanup_finished_triggers(self): for trigger_id, details in list(self.triggers.items()): if details["task"].done(): # Check to see if it exited for

Log traceback in trigger excs (#21213)

cleanup_finished_triggers

4ad21f5f7c2d416cf813a860564bc2bf3e161d46

airflow

triggerer_job.py

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

Python

async def cleanup_finished_triggers(self): for trigger_id, details in list(self.triggers.items()): if details["task"].done(): # Check to see if it exited for good reasons saved_exc = None try: result = details["task"].result() except (asyncio.CancelledError, SystemExit, KeyboardInterrupt): # These are "expected" exceptions and we stop processing here # If we don't, then the system requesting a trigger be removed - # which turns into CancelledError - results in a failure. del self.triggers[trigger_id] continue except BaseException as e: # This is potentially bad, so log it. self.log.exception("Trigger %s exited with error %s", details["name"], e) saved_exc = e else: # See if they foolishly returned a TriggerEvent if isinstance(result, TriggerEvent): self.log.error( "Trigger %s returned a TriggerEvent rather than yielding it", details["name"] ) # See if this exited without sending an event, in which case # any task instances depending on it need to be failed if details["events"] == 0: self.log.error( "Trigger %s exited without sending an event. Dependent tasks will be failed.", details["name"], ) self.failed_triggers.append((trigger_id, saved_exc)) del self.triggers[trigger_id] await asyncio.sleep(0)

rllib/contrib/sumo/utils.py

def get_global_travel_time(self): gtt = 0 for entity in self.tripinfo: gtt += self.get_duration(entity, default=0.0

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

get_global_travel_time

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

utils.py

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

Python

def get_global_travel_time(self): gtt = 0 for entity in self.tripinfo: gtt += self.get_duration(entity, default=0.0) for entity in self.personinfo: gtt += self.get_duration(entity, default=0.0) return gtt ########################################################################### # ROUTING

pipenv/patched/pip/_vendor/requests/sessions.py

def post(self, url, data=None, json=None, **kwargs): r re

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

post

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

pipenv

sessions.py

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

Python

def post(self, url, data=None, json=None, **kwargs): r return self.request("POST", url, data=data, json=json, **kwargs)

scapy/contrib/http2.py

def __getitem__(self, idx): # type: (int) -> HPackHdrEntry assert idx >= 0 if idx > type(self)._static_entries_last_idx: idx -= type(self)._static_entries_last_idx + 1 if idx >= len(self._dynamic_table): raise KeyError( 'EINVAL: idx: out-of-bound read: {}; maximum index: {}'.format(idx, len(self._dynamic_tab

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

__getitem__

08b1f9d67c8e716fd44036a027bdc90dcb9fcfdf

scapy

http2.py

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

Python

def __getitem__(self, idx): # type: (int) -> HPackHdrEntry assert idx >= 0 if idx > type(self)._static_entries_last_idx: idx -= type(self)._static_entries_last_idx + 1 if idx >= len(self._dynamic_table): raise KeyError( 'EINVAL: idx: out-of-bound read: {}; maximum index: {}'.format(idx, len(self._dynamic_table)) # noqa: E501 ) return self._dynamic_table[idx] return type(self)._static_entries[idx]

tests/admin_changelist/tests.py

def test_pagination(self): parent = Parent.objects.create(name="anything") for i in range(1, 31): Child.objects.create(name="name %s" % i, parent=parent) Child.objects.create(name="filtered %s" % i, parent=parent) request = self.factory.get("/child/") request.user = self.superuser # Test default queryset m = ChildAdmin(Child, custom_site) cl = m.get_changelist_instance(request) self.assertEqual(cl.queryset.count(), 60) self.assertEqual(cl.paginator.count, 60) self.assertEqual(list(

Refs #33476 -- Reformatted code with Black.

test_pagination

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests.py

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

Python

def test_pagination(self): parent = Parent.objects.create(name="anything") for i in range(1, 31): Child.objects.create(name="name %s" % i, parent=parent) Child.objects.create(name="filtered %s" % i, parent=parent) request = self.factory.get("/child/") request.user = self.superuser # Test default queryset m = ChildAdmin(Child, custom_site) cl = m.get_changelist_instance(request) self.assertEqual(cl.queryset.count(), 60) self.assertEqual(cl.paginator.count, 60) self.assertEqual(list(cl.paginator.page_range), [1, 2, 3, 4, 5, 6]) # Test custom queryset m = FilteredChildAdmin(Child, custom_site) cl = m.get_changelist_instance(request) self.assertEqual(cl.queryset.count(), 30) self.assertEqual(cl.paginator.count, 30) self.assertEqual(list(cl.paginator.page_range), [1, 2, 3])

sklearn/discriminant_analysis.py

def transform(self, X): if self.solver == "lsqr": raise NotImplementedError( "transform not implemented for 'lsqr' solver (use 'svd' or 'eigen')." ) check_is_fitted(self) X = self._validate_data(X, reset=False) if self.solver == "svd": X_new = np.dot(X - self.xbar_, self.scalings_) elif self.solver == "eigen": X_new = np.dot(X, self.scalings_) return X_new[:, : self._max_components]

DOC Add documentation on output shape of LDA.transform (#22238)

transform

ab08e4dba5f1f87b8c3395f32469a6ddb5e34f89

scikit-learn

discriminant_analysis.py

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

Python

def transform(self, X): if self.solver == "lsqr": raise NotImplementedError( "transform not implemented for 'lsqr' solver (use 'svd' or 'eigen')." ) check_is_fitted(self) X = self._validate_data(X, reset=False) if self.solver == "svd": X_new = np.dot(X - self.xbar_, self.scalings_) elif self.solver == "eigen": X_new = np.dot(X, self.scalings_) return X_new[:, : self._max_components]

tests/components/homekit_controller/test_climate.py

async def test_heater_cooler_hvac_mode_vs_hvac_action(hass, utcnow): helper = await setup_test_component(hass, create_heater_cooler_service) # Simulate that current temperature is above target temp # Heating might be on, but hvac_action currently 'off' await helper.async_update( ServicesTypes.HEATER_COOLER, { CharacteristicsTypes.TEMPERATURE_CURRENT: 22, CharacteristicsTypes.TEMPERATURE_HEATING_THRESHOLD: 21, CharacteristicsTypes.CURRENT_HEATER_COOLER_STATE: CurrentHeaterCoolerStateValues.IDLE, CharacteristicsTypes.TARGET_HEATER_COOLER_STATE: TargetHeaterCoolerStateValues.HEAT, CharacteristicsTypes.SWING_MODE: SwingModeValues.DISABLED, }, ) state = await helper.poll_and_get_state() assert state

Improve homekit_controller tests (#65266)

test_heater_cooler_hvac_mode_vs_hvac_action

58b8c30221a6f6e5acbbe98b7e3298b03fb741f5

core

test_climate.py

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

Python

async def test_heater_cooler_hvac_mode_vs_hvac_action(hass, utcnow): helper = await setup_test_component(hass, create_heater_cooler_service) # Simulate that current temperature is above target temp # Heating might be on, but hvac_action currently 'off' await helper.async_update( ServicesTypes.HEATER_COOLER, { CharacteristicsTypes.TEMPERATURE_CURRENT: 22, CharacteristicsTypes.TEMPERATURE_HEATING_THRESHOLD: 21, CharacteristicsTypes.CURRENT_HEATER_COOLER_STATE: CurrentHeaterCoolerStateValues.IDLE, CharacteristicsTypes.TARGET_HEATER_COOLER_STATE: TargetHeaterCoolerStateValues.HEAT, CharacteristicsTypes.SWING_MODE: SwingModeValues.DISABLED, }, ) state = await helper.poll_and_get_state() assert state.state == "heat" assert state.attributes["hvac_action"] == "idle" # Simulate that current temperature is below target temp # Heating might be on and hvac_action currently 'heat' await helper.async_update( ServicesTypes.HEATER_COOLER, { CharacteristicsTypes.TEMPERATURE_CURRENT: 19, CharacteristicsTypes.TEMPERATURE_HEATING_THRESHOLD: 21, CharacteristicsTypes.CURRENT_HEATER_COOLER_STATE: CurrentHeaterCoolerStateValues.HEATING, CharacteristicsTypes.TARGET_HEATER_COOLER_STATE: TargetHeaterCoolerStateValues.HEAT, CharacteristicsTypes.SWING_MODE: SwingModeValues.DISABLED, }, ) state = await helper.poll_and_get_state() assert state.state == "heat" assert state.attributes["hvac_action"] == "heating"

examples/contrib/webscanner_helper/watchdog.py

def not_in_timeout(cls, last_triggered, timeout): return ( last_triggered is None or timeout is None or (tim

[autofix.ci] apply automated fixes

not_in_timeout

8c2428c9d355ca5fbc3dd90e9820ceb1cc795837

mitmproxy

watchdog.py

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

Python

def not_in_timeout(cls, last_triggered, timeout): return ( last_triggered is None or timeout is None or (time.time() - last_triggered > timeout) )

parlai/core/torch_generator_agent.py

def get_rescored_finished(self, n_best=None): # if we never actually finished, force one if not self.finished: self.outputs[-1][0] = self.eos self.finished.append( _HypothesisTail( timestep=len(self.outputs) - 1, hypid=0, score=self.all_scores[-1][0], tokenid=self.outputs[-1][0], token_score=self.token_scores[0, -1] if self.token_scores is not None else None, token_rank=self.token_ranks[0, -1] if self.token_ranks is not None else None, ) ) rescored_finished = [] for finished_item in self.finished: current_length = finished_item.timestep + 1 # these weights are from Google NMT paper length_penalty = math.pow((1 + current_length) / 6, self.length_penalty) rescored_finished.append( _HypothesisTail( timestep=finished_item.timestep, h

Logging token level losses at inference time (#4169)

get_rescored_finished

daa85bf085c9e275cc65d0b03758d1f70742b57f

ParlAI

torch_generator_agent.py

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