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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

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

def replaceHTMLEntity(t): return _htmlEntityMap.get(t.entity) # it's easy to get these comment structures wrong - they're very common, so may as well make them available cStyleComment = Combine(Regex(r"/\*(?:[^*]|\*(?!/))*") + '*/').setName("C style comment") "Comment of the form ``/* ... */``" htmlComment = Regex(r"<!--[\s\S]*?-->").setName("HTML comment") "Comment of the form ``<!-- ... -->``" restOfLine = Regex(r".*").leaveWhitespace().setName("rest of line") dblSlashComment = Regex(r"//(?:\\\n|[^\n])*").setName("// comment") "Comment of the form ``// ... (to end of line)``" cppStyleComment = Combine(R

upd; format

replaceHTMLEntity

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

pyparsing.py

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

Python

def replaceHTMLEntity(t): return _htmlEntityMap.get(t.entity) # it's easy to get these comment structures wrong - they're very common, so may as well make them available cStyleComment = Combine(Regex(r"/\*(?:[^*]|\*(?!/))*") + '*/').setName("C style comment") "Comment of the form ``/* ... */``" htmlComment = Regex(r"<!--[\s\S]*?-->").setName("HTML comment") "Comment of the form ``<!-- ... -->``" restOfLine = Regex(r".*").leaveWhitespace().setName("rest of line") dblSlashComment = Regex(r"//(?:\\\n|[^\n])*").setName("// comment") "Comment of the form ``// ... (to end of line)``" cppStyleComment = Combine(Regex(r"/\*(?:[^*]|\*(?!/))*") + '*/' | dblSlashComment).setName("C++ style comment") "Comment of either form :class:`cStyleComment` or :class:`dblSlashComment`" javaStyleComment = cppStyleComment "Same as :class:`cppStyleComment`" pythonStyleComment = Regex(r"#.*").setName("Python style comment") "Comment of the form ``# ... (to end of line)``" _commasepitem = Combine(OneOrMore(Word(printables, excludeChars=',') + Optional(Word(" \t") + ~Literal(",") + ~LineEnd()))).streamline().setName("commaItem") commaSeparatedList = delimitedList(Optional(quotedString.copy() | _commasepitem, default="")).setName("commaSeparatedList") # some other useful expressions - using lower-case class name since we are really using this as a namespace

tests/integration_tests/utils.py

def read_csv_with_nan(path, nan_percent=0.0): df = pd.read_csv(path) if nan_percent > 0: num_rows = len(df) for col in df.columns: for row in random.sampl

Adds regression tests for #2020 (#2021) * fixes nans in dask df engine * adds tests * fixes with logs * fixes * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * cleanup * checking accuracy closeness * investigates ray batcher dropping samples with logs * clean up for PR review * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * cleanup * add missing test param * updated sampling to nan_percent% of rows in each col * cleanup Co-authored-by: Geoffrey Angus <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

read_csv_with_nan

9ae57a93ee4011c3d56cb0284ec07a861f3c88ff

ludwig

utils.py

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

Python

def read_csv_with_nan(path, nan_percent=0.0): df = pd.read_csv(path) if nan_percent > 0: num_rows = len(df) for col in df.columns: for row in random.sample(range(num_rows), int(round(nan_percent * num_rows))): df[col].iloc[row] = np.nan return df

modules/image/text_to_image/stable_diffusion/diffusers/models/resnet.py

def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1): assert isinstance(factor, int) and factor >= 1 # Setup filter kernel. if k is None: k = [1] * factor # setup kernel k = np.asarray(k, dtype=np.float32) if k.ndim == 1: k = np.outer(k, k) k /= np.sum(k) k = k * (gain * (factor**2)) if self.use_conv: convH = w.shape[2] convW = w.shape[3] inC = w.shape[1] p = (k.shape[0] - factor) - (convW - 1) stride = (factor, factor) # Determine data dimensions. stride = [1, 1, factor, factor] output_shape = ((x.shape[2] - 1) * factor + convH, (x.shape[3] - 1) * factor + convW) output_padding = ( output_shape[0] - (x.shape[2] - 1) * stride[0] - convH, output_shape[1] - (x.shape[3] - 1) * stride[1] - convW, ) assert output_padding[0] >= 0 and output_padding[1] >= 0 inC = w.shape[1] num_groups = x.shape[1] // inC # Transpose weights. w = paddle.reshape(w, (num_groups, -1, inC, convH, convW)) w = w[..., ::-1, ::-1].transpose([0, 2, 1, 3, 4]) w = paddle.reshape(w, (num_groups * inC, -1, convH, convW)) x = F.conv2d_transpose(x, w, st

Add stable diffusion module

_upsample_2d

a6790a651a12eb391060e533868bf0ba197f6f7e

PaddleHub

resnet.py

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

Python

def _upsample_2d(self, x, w=None, k=None, factor=2, gain=1): assert isinstance(factor, int) and factor >= 1 # Setup filter kernel. if k is None: k = [1] * factor # setup kernel k = np.asarray(k, dtype=np.float32) if k.ndim == 1: k = np.outer(k, k) k /= np.sum(k) k = k * (gain * (factor**2)) if self.use_conv: convH = w.shape[2] convW = w.shape[3] inC = w.shape[1] p = (k.shape[0] - factor) - (convW - 1) stride = (factor, factor) # Determine data dimensions. stride = [1, 1, factor, factor] output_shape = ((x.shape[2] - 1) * factor + convH, (x.shape[3] - 1) * factor + convW) output_padding = ( output_shape[0] - (x.shape[2] - 1) * stride[0] - convH, output_shape[1] - (x.shape[3] - 1) * stride[1] - convW, ) assert output_padding[0] >= 0 and output_padding[1] >= 0 inC = w.shape[1] num_groups = x.shape[1] // inC # Transpose weights. w = paddle.reshape(w, (num_groups, -1, inC, convH, convW)) w = w[..., ::-1, ::-1].transpose([0, 2, 1, 3, 4]) w = paddle.reshape(w, (num_groups * inC, -1, convH, convW)) x = F.conv2d_transpose(x, w, stride=stride, output_padding=output_padding, padding=0) x = upfirdn2d_native(x, paddle.to_tensor(k), pad=((p + 1) // 2 + factor - 1, p // 2 + 1)) else: p = k.shape[0] - factor x = upfirdn2d_native(x, paddle.to_tensor(k), up=factor, pad=((p + 1) // 2 + factor - 1, p // 2)) return x

test/lib/ansible_test/_internal/docker_util.py

def get_network_names(self) -> t.Optional[t.List[str]]: i

ansible-test - Use more native type hints. (#78435) * ansible-test - Use more native type hints. Simple search and replace to switch from comments to native type hints for return types of functions with no arguments. * ansible-test - Use more native type hints. Conversion of simple single-line function annotation type comments to native type hints. * ansible-test - Use more native type hints. Conversion of single-line function annotation type comments with default values to native type hints. * ansible-test - Use more native type hints. Manual conversion of type annotation comments for functions which have pylint directives.

get_network_names

3eb0485dd92c88cc92152d3656d94492db44b183

ansible

docker_util.py

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

Python

def get_network_names(self) -> t.Optional[t.List[str]]: if self.networks is None: return None return sorted(self.networks)

erpnext/projects/report/project_wise_stock_tracking/project_wise_stock_tracking.py

def get_delivered_items_cost(): dn_items = frappe.db.sql( , as_dict=1, ) si_items = frappe.db.sql( , as_dict=1, ) dn_item_map = {} for item in dn_items: dn_item_map.setdefault(item.project, item.amount) for item in si_items:

style: format code with black

get_delivered_items_cost

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

project_wise_stock_tracking.py

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

Python

def get_delivered_items_cost(): dn_items = frappe.db.sql( , as_dict=1, ) si_items = frappe.db.sql( , as_dict=1, ) dn_item_map = {} for item in dn_items: dn_item_map.setdefault(item.project, item.amount) for item in si_items: dn_item_map.setdefault(item.project, item.amount) return dn_item_map

sympy/tensor/tensor.py

def __new__(cls, *args, **kw_args): is_canon_bp = kw_args.get('is_canon_bp', False) args = list(map(_sympify, args)) free = [get_free_indices(arg) for arg in args] free = set(itertools.chain(*free)) #flatten free newargs = [] for arg in args: dum_this = set(get_dummy_indices(arg)) dum_other = [get_dummy_indices(a) for a in newargs] dum_other = set(itertools.chain(*dum_other)) #flatten dum_other free_this = set(get_free_indices(arg)) if len(dum_this.intersect

move dummy index deduping to TensMul.__new__ Also removed _eval_subs and _xreplace. All tests pass.

__new__

6c55ca197b0f795047d8f8ee0d871ab36600d560

sympy

tensor.py

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

Python

def __new__(cls, *args, **kw_args): is_canon_bp = kw_args.get('is_canon_bp', False) args = list(map(_sympify, args)) free = [get_free_indices(arg) for arg in args] free = set(itertools.chain(*free)) #flatten free newargs = [] for arg in args: dum_this = set(get_dummy_indices(arg)) dum_other = [get_dummy_indices(a) for a in newargs] dum_other = set(itertools.chain(*dum_other)) #flatten dum_other free_this = set(get_free_indices(arg)) if len(dum_this.intersection(free)) > 0: exclude = free_this.union(free, dum_other) newarg = TensMul._dedupe_indices(arg, exclude, arg._index_structure) else: newarg = arg newargs.append(newarg) args = newargs # Flatten: args = [i for arg in args for i in (arg.args if isinstance(arg, (TensMul, Mul)) else [arg])] args, indices, free, dum = TensMul._tensMul_contract_indices(args, replace_indices=False) # Data for indices: index_types = [i.tensor_index_type for i in indices] index_structure = _IndexStructure(free, dum, index_types, indices, canon_bp=is_canon_bp) obj = TensExpr.__new__(cls, *args) obj._indices = indices obj._index_types = index_types[:] obj._index_structure = index_structure obj._free = index_structure.free[:] obj._dum = index_structure.dum[:] obj._free_indices = {x[0] for x in obj.free} obj._rank = len(obj.free) obj._ext_rank = len(obj._index_structure.free) + 2*len(obj._index_structure.dum) obj._coeff = S.One obj._is_canon_bp = is_canon_bp return obj index_types = property(lambda self: self._index_types) free = property(lambda self: self._free) dum = property(lambda self: self._dum) free_indices = property(lambda self: self._free_indices) rank = property(lambda self: self._rank) ext_rank = property(lambda self: self._ext_rank)

tests/sentry/incidents/test_action_handlers.py

def test_context_for_crash_rate_alert(self): status = TriggerStatus.ACTIVE incident = self.create_incident() alert_rule = self.create_alert_rule( aggregate="percentage(sessions_crashed, sessions) AS _crash_rate_alert_aggregate" ) alert_rule_trigger = self.create_alert_rule_trigger(alert_rule) action = self.create_alert_rule_trigger_action( alert_rule_trigger=alert_rule_trigger, triggered_for_incident=incident ) assert ( generate_incident_trigger_email_context( self.project, incident, action.alert_rule_trigger, status, IncidentStatus.CRITICAL )["aggregate"] == "percentage(sessions_crashed, sessions)" )

fix(metric_alerts): Make sure critical triggers resolve properly when no action is set on a warning trigger (#31883) ### Problem If we have an alert set up like: - Warning: 50. Action: None - Critical: 100. Action: Slack Then if we go from critical -> warning state the slack resolve action will fail to fire. ### Cause The reason this happens is related to a previous fix. For an alert like - Warning: 50. Action: Slack - Critical: 100. Action: Slack When going from critical -> warning the critical action would be marked as resolved. This would cause a slack notification with `Resolved` to be sent to the channel. This is misleading, because the alert is still active, just in the warning state. What we want here is to fire a warning notification instead. The initial fix for this was that when we resolved a critical trigger, we’d check and see whether there was an active warning trigger. If so, we’d send a warning trigger fire to our actions, rather than a critical trigger resolve. This works ok for many cases, but fails when the actions on the warning trigger are different to those on the critical trigger. ### Fix Substituting the warning trigger for the critical trigger causes us subtle bugs. So, instead of this, when triggering fires/resolves on our action handlers we will also pass along the incident state change that the trigger/resolve caused the incident to go into. So if a critical trigger resolves, we check what state it would have put the incident in. If there’s a warning trigger, then the state is warning. If no warning trigger, the state is closed. This state is then used to appropriately generate the messages that we send to users via our various actions. So now, If we have an alert set up like: - Warning: 50. Action: None - Critical: 100. Action: Slack If this goes from - critical -> warning OR critical -> resolved we will send `IncidentStatus.WARNING` to any actions related to the critical trigger. - warning -> resolved We do nothing since there are no actions on the warning trigger If we have an alert set up like: - Warning: 50. Action: Slack - Critical: 100. Action: Slack If this goes from: - critical -> warning: critical trigger, `IncidentStatus.Warning` - warning -> resolved: warning trigger, `IncidentStatus.Closed` - critical -> resolved: Since we de-dupe triggers to avoid spamming the user, we will select the warning trigger here, and send `IncidentStatus.closed` If we have an alert set up like: - Warning: 50. Action: Slack - Critical: 100. Action: Pagerduty If this goes from: - critical -> warning: critical trigger, `IncidentStatus.Warning` sent to Pagerduty. Nothing sent to Slack - warning -> resolved: warning trigger, `IncidentStatus.Closed` sent to Slack. Nothing sent to Pagerduty - critical -> resolved: Critical trigger, `IncidentStatus.Warning` sent to Pagerduty. Warning trigger, `IncidentStatus.Closed` sent to Slack. We don’t de-dupe here since the actions are different.

test_context_for_crash_rate_alert

146fba432a32568be7d0b884dae0c39a6c33a11f

sentry

test_action_handlers.py

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

Python

def test_context_for_crash_rate_alert(self): status = TriggerStatus.ACTIVE incident = self.create_incident() alert_rule = self.create_alert_rule( aggregate="percentage(sessions_crashed, sessions) AS _crash_rate_alert_aggregate" ) alert_rule_trigger = self.create_alert_rule_trigger(alert_rule) action = self.create_alert_rule_trigger_action( alert_rule_trigger=alert_rule_trigger, triggered_for_incident=incident ) assert ( generate_incident_trigger_email_context( self.project, incident, action.alert_rule_trigger, status, IncidentStatus.CRITICAL )["aggregate"] == "percentage(sessions_crashed, sessions)" )

django/template/loaders/base.py

def get_template(self, template_name, skip=None): tried = [] for origin in self.get_template_sources(template_name): if skip is n

Refs #33476 -- Reformatted code with Black.

get_template

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

base.py

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

Python

def get_template(self, template_name, skip=None): tried = [] for origin in self.get_template_sources(template_name): if skip is not None and origin in skip: tried.append((origin, "Skipped to avoid recursion")) continue try: contents = self.get_contents(origin) except TemplateDoesNotExist: tried.append((origin, "Source does not exist")) continue else: return Template( contents, origin, origin.template_name, self.engine, ) raise TemplateDoesNotExist(template_name, tried=tried)

@keras_export("keras.optimizers.experimental.Optimizer", v1=[])

keras/optimizers/optimizer_experimental/optimizer.py

def from_config(cls, config): if "learning_rate" in config: if isinstance(config["learning_rate"], dict): config["learning_rate"] = learning_rate_schedule.deserialize( config["learning_rate"] ) return cls(

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

from_config

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

optimizer.py

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

Python

def from_config(cls, config): if "learning_rate" in config: if isinstance(config["learning_rate"], dict): config["learning_rate"] = learning_rate_schedule.deserialize( config["learning_rate"] ) return cls(**config) base_optimizer_keyword_args = # pylint: disable=g-classes-have-attributes @keras_export("keras.optimizers.experimental.Optimizer", v1=[])

airflow/providers/amazon/aws/log/s3_task_handler.py

def close(self): # When application exit, system shuts down all handlers by # calling close method. Here we check if logger is already # closed to prevent uploading the log to remote storage multiple # times when `logging.shutdown` is called. if self.closed: return super().close() if not self.upload_on_close: return local_loc = os.path.join(self.local_base, self.log_relative_path) remote_loc = os.path.join(self.remote_base, self.log_relative_path) if os.path.exists(local_loc): # read log and remove old logs to get just the latest additions log = pathlib.Path(local_loc).read_text() self.s3_write(log, remote_loc) # Mark closed so we don't double write if close is called twice self.clo

Light Refactor and Clean-up AWS Provider (#23907)

close

595981c8ad3cfeb4ad7a4514d00060e978aa9d81

airflow

s3_task_handler.py

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

Python

def close(self): # When application exit, system shuts down all handlers by # calling close method. Here we check if logger is already # closed to prevent uploading the log to remote storage multiple # times when `logging.shutdown` is called. if self.closed: return super().close() if not self.upload_on_close: return local_loc = os.path.join(self.local_base, self.log_relative_path) remote_loc = os.path.join(self.remote_base, self.log_relative_path) if os.path.exists(local_loc): # read log and remove old logs to get just the latest additions log = pathlib.Path(local_loc).read_text() self.s3_write(log, remote_loc) # Mark closed so we don't double write if close is called twice self.closed = True

tests/view_tests/views.py

def safestring_in_template_exception(request): template = Template('{% extends "<script>alert(1);</script>" %}') try: template.render(Cont

Fixed #33461 -- Escaped template errors in the technical 500 debug page.

safestring_in_template_exception

c5c7a15b09368a58340d3a65ba9d1f1441e92dc8

django

views.py

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

Python

def safestring_in_template_exception(request): template = Template('{% extends "<script>alert(1);</script>" %}') try: template.render(Context()) except Exception: return technical_500_response(request, *sys.exc_info())

tests/test_config_entries.py

async def test_unique_id_in_progress(hass, manager): mock_integration(hass, Mo

Search/replace RESULT_TYPE_* by FlowResultType enum (#74642)

test_unique_id_in_progress

7cd68381f1d4f58930ffd631dfbfc7159d459832

core

test_config_entries.py

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

Python

async def test_unique_id_in_progress(hass, manager): mock_integration(hass, MockModule("comp")) mock_entity_platform(hass, "config_flow.comp", None)

tests/storage/test_event_chain.py

def test_simple(self) -> None: event_factory = self.hs.get_event_builder_factory() bob = "@creator:test" alice = "@alice:test" room_id = "!room:test" # Ensure that we have a rooms entry so that we generate the chain index. self.get_success( self.store.store_room( room_id=room_id, room_creator_user_id="", is_public=True, room_version=RoomVersions.V6, ) ) create = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Create, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "create"}, }, ).build(prev_event_ids=[], auth_event_ids=[]) ) bob_join = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": bob, "sender": bob, "room_id": room_id, "content": {"tag": "bob_join"}, }, ).build(prev_event_ids=[], auth_event_ids=[create.event_id]) ) power = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.PowerLevels, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "power"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id], ) ) alice_invite = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": bob, "room_id": room_id, "content": {"tag": "alice_invite"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) alice_join = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": alice, "room_id": room_id, "content": {"tag": "alice_join"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, alice_invite.event_id, power.event_id], ) ) power_2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.PowerLevels, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "power_2"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) bob_join_2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": bob, "sender": bob, "room_id": room_id, "content": {"tag": "bob_join_2"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) alice_join2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": alice, "room_id": room_id, "content": {"tag": "alice_join2"}, }, ).build( prev_event_ids=[], auth_event_ids=[ create.event_id, alice_join.event_id, power_2.event_id, ], ) ) events = [ create, bob_join, power, alice_invite, alice_join, bob_join_2, power_2, alice_join2, ] expected_links = [ (bob_join, create), (power, create), (power, bob_join), (alice_invite, create), (alice_invite, power), (alice_invite, bob_join), (bob_join_2, power), (alice_join2, power_2), ] self.persist(events) chain_map, link_map = self.fetch_chains(events) # Check that the expected links and only the expected links have been # added. self.assertEqual(len(expected_links), len(list(link_map.get_additions()))) for start, end in expected_links: start_id, start_seq = chain_map[start.event_id] end_id, end_seq = chain_map[end.event_id]

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

test_simple

3ac412b4e2f8c5ba11dc962b8a9d871c1efdce9b

synapse

test_event_chain.py

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

Python

def test_simple(self) -> None: event_factory = self.hs.get_event_builder_factory() bob = "@creator:test" alice = "@alice:test" room_id = "!room:test" # Ensure that we have a rooms entry so that we generate the chain index. self.get_success( self.store.store_room( room_id=room_id, room_creator_user_id="", is_public=True, room_version=RoomVersions.V6, ) ) create = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Create, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "create"}, }, ).build(prev_event_ids=[], auth_event_ids=[]) ) bob_join = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": bob, "sender": bob, "room_id": room_id, "content": {"tag": "bob_join"}, }, ).build(prev_event_ids=[], auth_event_ids=[create.event_id]) ) power = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.PowerLevels, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "power"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id], ) ) alice_invite = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": bob, "room_id": room_id, "content": {"tag": "alice_invite"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) alice_join = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": alice, "room_id": room_id, "content": {"tag": "alice_join"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, alice_invite.event_id, power.event_id], ) ) power_2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.PowerLevels, "state_key": "", "sender": bob, "room_id": room_id, "content": {"tag": "power_2"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) bob_join_2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": bob, "sender": bob, "room_id": room_id, "content": {"tag": "bob_join_2"}, }, ).build( prev_event_ids=[], auth_event_ids=[create.event_id, bob_join.event_id, power.event_id], ) ) alice_join2 = self.get_success( event_factory.for_room_version( RoomVersions.V6, { "type": EventTypes.Member, "state_key": alice, "sender": alice, "room_id": room_id, "content": {"tag": "alice_join2"}, }, ).build( prev_event_ids=[], auth_event_ids=[ create.event_id, alice_join.event_id, power_2.event_id, ], ) ) events = [ create, bob_join, power, alice_invite, alice_join, bob_join_2, power_2, alice_join2, ] expected_links = [ (bob_join, create), (power, create), (power, bob_join), (alice_invite, create), (alice_invite, power), (alice_invite, bob_join), (bob_join_2, power), (alice_join2, power_2), ] self.persist(events) chain_map, link_map = self.fetch_chains(events) # Check that the expected links and only the expected links have been # added. self.assertEqual(len(expected_links), len(list(link_map.get_additions()))) for start, end in expected_links: start_id, start_seq = chain_map[start.event_id] end_id, end_seq = chain_map[end.event_id] self.assertIn( (start_seq, end_seq), list(link_map.get_links_between(start_id, end_id)) ) # Test that everything can reach the create event, but the create event # can't reach anything. for event in events[1:]: self.assertTrue( link_map.exists_path_from( chain_map[event.event_id], chain_map[create.event_id] ), ) self.assertFalse( link_map.exists_path_from( chain_map[create.event_id], chain_map[event.event_id], ), )

homeassistant/components/withings/common.py

async def _do_retry(self, func, attempts=3) -> Any: # pylint: disable=no-self-use exception = None for attempt in range(1, attempts + 1): _LOGGER.debug("Attempt %s of %s", attempt, attempts) try: return await func() except Exception as exception1: # pylint: disable=broad-except _LOGGER.debug( "Failed attempt %s of %s (%s)", attempt, attempts, exce

Fix withings race condition for access token (#69107)

_do_retry

ccd5ada3414b8b51835a7a29b2e5c2a70464987f

core

common.py

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

Python

async def _do_retry(self, func, attempts=3) -> Any: # pylint: disable=no-self-use exception = None for attempt in range(1, attempts + 1): _LOGGER.debug("Attempt %s of %s", attempt, attempts) try: return await func() except Exception as exception1: # pylint: disable=broad-except _LOGGER.debug( "Failed attempt %s of %s (%s)", attempt, attempts, exception1 ) # Make each backoff pause a little bit longer await asyncio.sleep(0.5 * attempt) exception = exception1 continue if exception: raise exception

python3.10.4/Lib/lib2to3/refactor.py

def refactor_doctest(self, block, lineno, indent, filename): try: tree = self.parse_block(block, lineno, indent) except Exception as err: if self.logger.isEnabledFor(logging.DEBUG): for line in block: self.log_debug("Source: %s", line.rstrip("\n")) self.log_error("Can't parse docstring in %s line %s: %s: %s", filename, lineno, err.__class__.__name__, err) return block if self.refactor_tree(tree, filename): new = str(tree).splitlines(keepends=True) # Undo the adjustment of the line numbers in wrap_toks() below. clipped, new = new[:lineno-1], new[lineno-1:] assert clipped == ["\n"] * (lineno-1), clipped if not new[-1].endswith("\n"): new[-1] += "\n" block = [indent + self.PS1 + new.pop(0)] if new:

add python 3.10.4 for windows

refactor_doctest

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

refactor.py

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

Python

def refactor_doctest(self, block, lineno, indent, filename): try: tree = self.parse_block(block, lineno, indent) except Exception as err: if self.logger.isEnabledFor(logging.DEBUG): for line in block: self.log_debug("Source: %s", line.rstrip("\n")) self.log_error("Can't parse docstring in %s line %s: %s: %s", filename, lineno, err.__class__.__name__, err) return block if self.refactor_tree(tree, filename): new = str(tree).splitlines(keepends=True) # Undo the adjustment of the line numbers in wrap_toks() below. clipped, new = new[:lineno-1], new[lineno-1:] assert clipped == ["\n"] * (lineno-1), clipped if not new[-1].endswith("\n"): new[-1] += "\n" block = [indent + self.PS1 + new.pop(0)] if new: block += [indent + self.PS2 + line for line in new] return block

mindsdb/integrations/handlers/bigquery_handler/bigquery_handler.py

def get_tables(self, dataset_id) -> Response: client = self.connect()

Add handler

get_tables

cbe6767de6152a78348a8047244e5e3305b24e04

mindsdb

bigquery_handler.py

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

Python

def get_tables(self, dataset_id) -> Response: client = self.connect() result = client.list_tables(dataset_id) return result

PyInstaller/depend/dylib.py

def mac_set_relative_dylib_deps(libname, distname): from macholib import util from macholib.MachO import MachO # Ignore bootloader; otherwise PyInstaller fails with exception like # 'ValueError: total_size > low_offset (288 > 0)' if os.path.basename(libname) in _BOOTLOADER_FNAMES: return # Determine how many directories up ('../') is the directory with shared dynamic libraries. # E.g., ./qt4_plugins/images/

Fix typos (#6782) [skip ci]

mac_set_relative_dylib_deps

1a7d704ffbabb433007e3ba04750c2f13ade48e5

pyinstaller

dylib.py

https://github.com/pyinstaller/pyinstaller.git

Python

def mac_set_relative_dylib_deps(libname, distname): from macholib import util from macholib.MachO import MachO # Ignore bootloader; otherwise PyInstaller fails with exception like # 'ValueError: total_size > low_offset (288 > 0)' if os.path.basename(libname) in _BOOTLOADER_FNAMES: return # Determine how many directories up ('../') is the directory with shared dynamic libraries. # E.g., ./qt4_plugins/images/ -> ./../../ parent_dir = '' # Check if distname is not only base filename. if os.path.dirname(distname): parent_level = len(os.path.dirname(distname).split(os.sep)) parent_dir = parent_level * (os.pardir + os.sep)

keras/testing_infra/test_utils.py

def get_v2_optimizer(name, **kwargs): try: return _V2_OPTIMIZER_MAP[name](**kwargs) except KeyError:

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

get_v2_optimizer

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

test_utils.py

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

Python

def get_v2_optimizer(name, **kwargs): try: return _V2_OPTIMIZER_MAP[name](**kwargs) except KeyError: raise ValueError( "Could not find requested v2 optimizer: {}\nValid choices: {}".format( name, list(_V2_OPTIMIZER_MAP.keys()) ) )

python3.10.4/Lib/ipaddress.py

def _prefix_from_ip_int(cls, ip_int): trailing_zeroes = _count_righthand_zero_bits(ip_int, cls._max_prefixlen) prefixlen = cls._max_prefixlen - trailing_zeroes leading_ones = ip_int >> trailing_zeroes

add python 3.10.4 for windows

_prefix_from_ip_int

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

ipaddress.py

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

Python

def _prefix_from_ip_int(cls, ip_int): trailing_zeroes = _count_righthand_zero_bits(ip_int, cls._max_prefixlen) prefixlen = cls._max_prefixlen - trailing_zeroes leading_ones = ip_int >> trailing_zeroes all_ones = (1 << prefixlen) - 1 if leading_ones != all_ones: byteslen = cls._max_prefixlen // 8 details = ip_int.to_bytes(byteslen, 'big') msg = 'Netmask pattern %r mixes zeroes & ones' raise ValueError(msg % details) return prefixlen

spacy/pipeline/entity_linker.py

def batch_has_learnable_example(self, examples): for eg in examples: for ent in eg.predicted.ents: candidates = list(self.get_candidates(self.kb, ent)) if candidates: return True return False

Fix entity linker batching (#9669) * Partial fix of entity linker batching * Add import * Better name * Add `use_gold_ents` option, docs * Change to v2, create stub v1, update docs etc. * Fix error type Honestly no idea what the right type to use here is. ConfigValidationError seems wrong. Maybe a NotImplementedError? * Make mypy happy * Add hacky fix for init issue * Add legacy pipeline entity linker * Fix references to class name * Add __init__.py for legacy * Attempted fix for loss issue * Remove placeholder V1 * formatting * slightly more interesting train data * Handle batches with no usable examples This adds a test for batches that have docs but not entities, and a check in the component that detects such cases and skips the update step as thought the batch were empty. * Remove todo about data verification Check for empty data was moved further up so this should be OK now - the case in question shouldn't be possible. * Fix gradient calculation The model doesn't know which entities are not in the kb, so it generates embeddings for the context of all of them. However, the loss does know which entities aren't in the kb, and it ignores them, as there's no sensible gradient. This has the issue that the gradient will not be calculated for some of the input embeddings, which causes a dimension mismatch in backprop. That should have caused a clear error, but with numpyops it was causing nans to happen, which is another problem that should be addressed separately. This commit changes the loss to give a zero gradient for entities not in the kb. * add failing test for v1 EL legacy architecture * Add nasty but simple working check for legacy arch * Clarify why init hack works the way it does * Clarify use_gold_ents use case * Fix use gold ents related handling * Add tests for no gold ents and fix other tests * Use aligned ents function (not working) This doesn't actually work because the "aligned" ents are gold-only. But if I have a different function that returns the intersection, *then* this will work as desired. * Use proper matching ent check This changes the process when gold ents are not used so that the intersection of ents in the pred and gold is used. * Move get_matching_ents to Example * Use model attribute to check for legacy arch * Rename flag * bump spacy-legacy to lower 3.0.9 Co-authored-by: svlandeg <[email protected]>

batch_has_learnable_example

91acc3ea75d219ad07ed2b106e7b8bdcb01516dd

spaCy

entity_linker.py

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

Python

def batch_has_learnable_example(self, examples): for eg in examples: for ent in eg.predicted.ents: candidates = list(self.get_candidates(self.kb, ent)) if candidates: return True return False

awx/main/tasks/callback.py

def get_delayed_update_fields(self): self.extra_update_fields['emitted_events'] = self.event_ct if 'got an unexpected keyword argument' in self.extra_update_fields.get('result_traceback', ''): self.delay_up

Delay update of artifacts and error fields until final job save (#11832) * Delay update of artifacts until final job save Save tracebacks from receptor module to callback object Move receptor traceback check up to be more logical Use new mock_me fixture to avoid DB call with me method Update the special runner message to the delay_update pattern * Move special runner message into post-processing of callback fields

get_delayed_update_fields

452744b67e02823879e722fe574984a2d760ed60

awx

callback.py

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

Python

def get_delayed_update_fields(self): self.extra_update_fields['emitted_events'] = self.event_ct if 'got an unexpected keyword argument' in self.extra_update_fields.get('result_traceback', ''): self.delay_update(result_traceback=ANSIBLE_RUNNER_NEEDS_UPDATE_MESSAGE) return self.extra_update_fields

wagtail/search/tests/test_indexed_class.py

def get_checks_result(warning_id=None): checks_result = checks.run_checks() if warning_id: return [ warning for warning in

add check for correct search_fields on pages - fixes #4940

get_checks_result

d964675ee8fcb7ea58681ac8869733a86d58e4ec

wagtail

test_indexed_class.py

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

Python

def get_checks_result(warning_id=None): checks_result = checks.run_checks() if warning_id: return [ warning for warning in checks_result if warning.id == warning_id] return checks_result

pandas/core/config_init.py

def use_bottleneck_cb(key) -> None:

TYP: return values in core/*.py (#47587) * TYP: return values in core/*.py * fix test * to_html * to_html part 2 * DataFrame.query * more overloads * fix query? * increase stacklevel by one * fix rename_axis * and an overload for DataFrame.eval * address comments * fix typevar

use_bottleneck_cb

9612375ca28ade056f15d4338f1bfde5d045c9fc

pandas

config_init.py

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

Python

def use_bottleneck_cb(key) -> None: from pandas.core import nanops nanops.set_use_bottleneck(cf.get_option(key)) use_numexpr_doc =

pandas/tests/io/test_stata.py

def test_repeated_column_labels(self, datapath): # GH 13923, 2577

TST: Don't use autouse fixture in test_stata (#45831)

test_repeated_column_labels

c055dc4e6be9fc1b68d873a1ace286322dadd5e1

pandas

test_stata.py

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

Python

def test_repeated_column_labels(self, datapath): # GH 13923, 25772 msg = with pytest.raises(ValueError, match=msg): read_stata( datapath("io", "data", "stata", "stata15.dta"), convert_categoricals=True, )

PySimpleGUI.py

def string_width_in_pixels(cls, font, string): # if no windows have been created (there is no hidden master root to rely on) then temporarily make a window so the meas

Enable Text class methods to be called prior to any windows being created: string_width_in_pixels, char_height_in_pixels, char_width_in_pixels. Removed destruction of hidden master root from popup_get_file & popup_get_folder (was old code)

string_width_in_pixels

acaae54a1ade24b2e55f7274ae4db747160a38db

PySimpleGUI

PySimpleGUI.py

https://github.com/PySimpleGUI/PySimpleGUI.git

Python

def string_width_in_pixels(cls, font, string): # if no windows have been created (there is no hidden master root to rely on) then temporarily make a window so the measurement can happen if Window.NumOpenWindows == 0: root = tk.Tk() else: root = None size = 0 try: size = tkinter.font.Font(font=font).measure(string) # string's width except Exception as e: _error_popup_with_traceback('Exception retrieving string width in pixels', e) if root is not None: root.destroy() return size

keras/saving/saving_utils.py

def model_call_inputs(model, keep_original_batch_size=False): input_specs = model.save_spec(dynamic_batch=not keep_original_batch_size) if input_specs is None: return None, None input_specs =

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

model_call_inputs

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

saving_utils.py

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

Python

def model_call_inputs(model, keep_original_batch_size=False): input_specs = model.save_spec(dynamic_batch=not keep_original_batch_size) if input_specs is None: return None, None input_specs = _enforce_names_consistency(input_specs) return input_specs

nuitka/plugins/standard/DataFileCollectorPlugin.py

def _getSubDirectoryFolders(self, module, sub_dirs): module_dir = module.getCompileTimeDirectory() file_list = [] data_dirs = [os.path.join(module_dir, subdir) for subdir in sub_dirs] # Gather the full file list, probably makes no sense to include bytecode files file_list = sum( ( getFileList( data_dir, ignore_dirs=("__pycache__",), ignore_suffixes=(".pyc",) ) for data_dir in data_dirs ), [], ) if not file_list: msg = "No files or folders found for '%s' in subfolder(s) %r (%r)." % ( module.getFullName(), sub_dirs, data_dirs, ) self.warning(msg) is_package = ( module.isCompiledPythonPackage() or module.isUncompiledPythonPackage() ) # We need to preserve the package target path in the dist folder. if is_package: package_part = module.getFullName().asPath() else: package = module.getFullName().getPackageName() if package is None: package_part = "" else: package_part = package.asPath() item_set = OrderedSet() for f in file_list: target = os.path.join(package_part, os.path.relpath(f, module_dir)) dir_name = os.path.dirname(target) item_set.

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

_getSubDirectoryFolders

abfb99b0a05dd76d2ecc6ebc20732a271857c6c8

Nuitka

DataFileCollectorPlugin.py

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

Python

def _getSubDirectoryFolders(self, module, sub_dirs): module_dir = module.getCompileTimeDirectory() file_list = [] data_dirs = [os.path.join(module_dir, subdir) for subdir in sub_dirs] # Gather the full file list, probably makes no sense to include bytecode files file_list = sum( ( getFileList( data_dir, ignore_dirs=("__pycache__",), ignore_suffixes=(".pyc",) ) for data_dir in data_dirs ), [], ) if not file_list: msg = "No files or folders found for '%s' in subfolder(s) %r (%r)." % ( module.getFullName(), sub_dirs, data_dirs, ) self.warning(msg) is_package = ( module.isCompiledPythonPackage() or module.isUncompiledPythonPackage() ) # We need to preserve the package target path in the dist folder. if is_package: package_part = module.getFullName().asPath() else: package = module.getFullName().getPackageName() if package is None: package_part = "" else: package_part = package.asPath() item_set = OrderedSet() for f in file_list: target = os.path.join(package_part, os.path.relpath(f, module_dir)) dir_name = os.path.dirname(target) item_set.add(dir_name) return self.makeIncludedEmptyDirectories( source_path=module_dir, dest_paths=item_set, reason="Subdirectories of module %s" % module.getFullName(), tags="config", )

tests/sentry/api/endpoints/test_organization_metric_data.py

def test_orderby_percentile_with_many_fields_one_entity_no_data(self): for metric in [ TransactionMRI.MEASUREMENTS_FCP.value, "transaction", ]: perf_indexer_record(self.organization.id, metric) response = self.get_success_response( self.organization.slug, field=[ f"p50({TransactionMetricKey.MEASUREMENTS_LCP.value})", f"p50({TransactionMetricKey.MEASUREMENTS_FCP.value})", ], statsPeriod="1h", interval="1h", groupBy=["project_id", "transaction"], orderBy=f"p50({TransactionMetricKey.MEASUREMENTS_LCP.value})", useCase="performance", ) groups = response.data["groups"] assert

feat(metrics): Support rate for derived metric [TET-129 TET-127] (#38792) Adds support for operation `rate` to be able to compute performance related metrics such as tpm, tps, epm, eps This PR achieves this by: - Defining rate as a derived operation that produces its own SnQL rather than trying to compute the data sketch aggregate and using that directly - Replaces `filter_conditions_func` that used to just produce a snql condition to be used a conditional aggregate with `snql_func` that instead produces a SnQL function - Replaces the logic in `get_entity` on MetricsExpression to determine the entity from the MRI rather than from the aggregate applied

test_orderby_percentile_with_many_fields_one_entity_no_data

35ec251212b82e5d9468062a3ab5945d8e739002

sentry

test_organization_metric_data.py

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

Python

def test_orderby_percentile_with_many_fields_one_entity_no_data(self): for metric in [ TransactionMRI.MEASUREMENTS_FCP.value, "transaction", ]: perf_indexer_record(self.organization.id, metric) response = self.get_success_response( self.organization.slug, field=[ f"p50({TransactionMetricKey.MEASUREMENTS_LCP.value})", f"p50({TransactionMetricKey.MEASUREMENTS_FCP.value})", ], statsPeriod="1h", interval="1h", groupBy=["project_id", "transaction"], orderBy=f"p50({TransactionMetricKey.MEASUREMENTS_LCP.value})", useCase="performance", ) groups = response.data["groups"] assert len(groups) == 0

lib/training/preview_tk.py

def _add_save_button(self) -> None: logger.debug("Adding save button") button = tk.Button(self, text="Save", cursor="hand2", command=lambda: self.save_var.set(True)) button.pack(side=tk.LEFT) logger.debug("Added save burron: '%s'", button)

Training - Use custom preview pop-out

_add_save_button

7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5

faceswap

preview_tk.py

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

Python

def _add_save_button(self) -> None: logger.debug("Adding save button") button = tk.Button(self, text="Save", cursor="hand2", command=lambda: self.save_var.set(True)) button.pack(side=tk.LEFT) logger.debug("Added save burron: '%s'", button)

src/prefect/context.py

def temporary_environ_defaults(**kwargs): old_env = os.environ.copy() try: for var in kwargs: # TODO: Consider warning on conflicts os.environ.setdefault(var, str(kwargs[var])) yield {var: os.environ[var] for var in kwargs} finally: for var in kwargs: if old_env.get(var): os.environ[var] = old_env[var] else: os.environ.pop(var, None)

Introduce basic profile context management

temporary_environ_defaults

a9e67e2311c1e4a056b9e740cc739360896aab92

prefect

context.py

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

Python

def temporary_environ_defaults(**kwargs): old_env = os.environ.copy() try: for var in kwargs: # TODO: Consider warning on conflicts os.environ.setdefault(var, str(kwargs[var])) yield {var: os.environ[var] for var in kwargs} finally: for var in kwargs: if old_env.get(var): os.environ[var] = old_env[var] else: os.environ.pop(var, None)

tests/sentry/api/endpoints/test_organization_metric_details.py

def test_same_entity_multiple_metric_ids_missing_data(self, mocked_derived_metrics): mocked_derived_metrics.return_value = MOCKED_DERIVED_METRICS_2 _indexer_record(self.organization.id, "metric_foo_doe") self.store_sessi

feat(metrics): make indexer more configurable (#35604) This makes the sentry_metrics indexer more configurable in the following ways, to enable indexing on the ingest-performance-metrics topic: - configurable input Kafka topic - configurable output Kafka topic - configurable model from which to pull index results - tags for internal metrics to distinguish between the two modes operationally

test_same_entity_multiple_metric_ids_missing_data

7f60db924ea37f34e0cfe6856777239e2a2ffe13

sentry

test_organization_metric_details.py

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

Python

def test_same_entity_multiple_metric_ids_missing_data(self, mocked_derived_metrics): mocked_derived_metrics.return_value = MOCKED_DERIVED_METRICS_2 _indexer_record(self.organization.id, "metric_foo_doe") self.store_session( self.build_session( project_id=self.project.id, started=(time.time() // 60) * 60, status="ok", release="[email protected]", errors=2, ) ) response = self.get_response( self.organization.slug, "derived_metric.multiple_metrics", ) assert response.status_code == 404 assert response.json()["detail"] == ( "Not all the requested metrics or the constituent metrics in " "['derived_metric.multiple_metrics'] have data in the dataset" )

keras/utils/kernelized_utils.py

def _align_matrices(x, y): x_matrix = _to_matrix(x) y_matrix = _to_matrix(y) x_shape = x_matrix.shape y_shape = y_matrix.shape if y_shape[1] != x_shape[1]: # dimensions do

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

_align_matrices

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

kernelized_utils.py

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

Python

def _align_matrices(x, y): x_matrix = _to_matrix(x) y_matrix = _to_matrix(y) x_shape = x_matrix.shape y_shape = y_matrix.shape if y_shape[1] != x_shape[1]: # dimensions do not match. raise ValueError( "The outermost dimensions of the input tensors should match. " f"Received y = {y_shape[1]} vs x = {x_shape[1]}." ) x_tile = tf.tile(tf.expand_dims(x_matrix, 1), [1, y_shape[0], 1]) y_tile = tf.tile(tf.expand_dims(y_matrix, 0), [x_shape[0], 1, 1]) return x_tile, y_tile

tests/storage/test_events.py

def test_prune_gap_if_dummy_local(self): body = self.helper.send(self.room_id, body="Test", tok=self.token) body = self.helper.send_event( self.room_id, type=EventTypes.Dummy, content={}, tok=self.token ) local_message_event_id = body["event_id"] self.assert_extremities([local_message_event_id]) # Advance the clock for many days to make the old extremity "old". We # also set the depth to "lots". self.reactor.advance(7 * 24 * 60 * 60) # Fudge a second event which points to an event we don't have. This is a # state event so that the state changes (otherwise we won't prune the # extremity as they'll have the same state group). remote_event_2 = event_from_pdu_json( { "type": EventTypes.Member, "state_key": "@user:other2", "content": {"membership": Membership.JOIN}, "room_id": self.room_id, "sender": "@user:other2", "depth": 10000, "prev_events": ["$some_unknown_message"], "auth

Pull out less state when handling gaps mk2 (#12852)

test_prune_gap_if_dummy_local

b83bc5fab57b37f75a79d02213d6032c586fd36e

synapse

test_events.py

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

Python

def test_prune_gap_if_dummy_local(self): body = self.helper.send(self.room_id, body="Test", tok=self.token) body = self.helper.send_event( self.room_id, type=EventTypes.Dummy, content={}, tok=self.token ) local_message_event_id = body["event_id"] self.assert_extremities([local_message_event_id]) # Advance the clock for many days to make the old extremity "old". We # also set the depth to "lots". self.reactor.advance(7 * 24 * 60 * 60) # Fudge a second event which points to an event we don't have. This is a # state event so that the state changes (otherwise we won't prune the # extremity as they'll have the same state group). remote_event_2 = event_from_pdu_json( { "type": EventTypes.Member, "state_key": "@user:other2", "content": {"membership": Membership.JOIN}, "room_id": self.room_id, "sender": "@user:other2", "depth": 10000, "prev_events": ["$some_unknown_message"], "auth_events": [], "origin_server_ts": self.clock.time_msec(), }, RoomVersions.V6, ) state_before_gap = self.get_success( self.state.get_current_state_ids(self.room_id) ) self.persist_event(remote_event_2, state=state_before_gap) # Check the new extremity is just the new remote event. self.assert_extremities([remote_event_2.event_id, local_message_event_id])

keras/saving/saved_model/save_impl.py

def _reset_layer_losses(parent_layer): losses_dict = {} for layer in utils.list_all_layers_and_sublayers(parent_layer): losses_dict[layer] = { 'losses': layer._losses[:], 'eager_losses

Support Keras saving/loading for ShardedVariables with arbitrary partitions. PiperOrigin-RevId: 439837516

_reset_layer_losses

e61cbc52fd3b0170769c120e9b8dabc8c4205322

keras

save_impl.py

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

Python

def _reset_layer_losses(parent_layer): losses_dict = {} for layer in utils.list_all_layers_and_sublayers(parent_layer): losses_dict[layer] = { 'losses': layer._losses[:], 'eager_losses': layer._eager_losses[:] } with utils.no_automatic_dependency_tracking_scope(layer): layer._losses = [] layer._eager_losses = [] return losses_dict

tests/admin_changelist/tests.py

def test_result_list_editable_html(self): new_parent = Parent.objects.create(name="parent") new_child = Child.objects.create(name="name", parent=new_parent) request = self.factory.get("/child/") request.user = self.superuser m = ChildAdmin(Child, custom_site) # Test with list_editable fields m.list_display = ["id", "name", "parent"] m.list_display_links = ["id"] m.list_editable = ["name"] cl = m.get_changelist_instance(request) FormSet = m.get_changelist_formset(request) cl.formset = FormSet(queryset=cl.result_list) template = Template( "{% load admin_list %}{% spaceless %}{% result_list cl %}{% endspaceless %}" ) context = Context({"cl": cl, "opts": Child._meta}) table_output = template.render(context) # make sure that hidden fields are in the correct place hiddenfields_div = ( '<div class="hiddenfields">' '<input type="hidden" name="form-0-id" value="%d" id="id_form-0-id">' "</div>" ) % new_child.id self.assertInHTML(

Refs #33476 -- Reformatted code with Black.

test_result_list_editable_html

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests.py

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

Python

def test_result_list_editable_html(self): new_parent = Parent.objects.create(name="parent") new_child = Child.objects.create(name="name", parent=new_parent) request = self.factory.get("/child/") request.user = self.superuser m = ChildAdmin(Child, custom_site) # Test with list_editable fields m.list_display = ["id", "name", "parent"] m.list_display_links = ["id"] m.list_editable = ["name"] cl = m.get_changelist_instance(request) FormSet = m.get_changelist_formset(request) cl.formset = FormSet(queryset=cl.result_list) template = Template( "{% load admin_list %}{% spaceless %}{% result_list cl %}{% endspaceless %}" ) context = Context({"cl": cl, "opts": Child._meta}) table_output = template.render(context) # make sure that hidden fields are in the correct place hiddenfields_div = ( '<div class="hiddenfields">' '<input type="hidden" name="form-0-id" value="%d" id="id_form-0-id">' "</div>" ) % new_child.id self.assertInHTML( hiddenfields_div, table_output, msg_prefix="Failed to find hidden fields" ) # make sure that list editable fields are rendered in divs correctly editable_name_field = ( '<input name="form-0-name" value="name" class="vTextField" ' 'maxlength="30" type="text" id="id_form-0-name">' ) self.assertInHTML( '<td class="field-name">%s</td>' % editable_name_field, table_output, msg_prefix='Failed to find "name" list_editable field', )

wagtail/admin/tests/ui/test_tables.py

def test_title_column(self): root_page = Page.objects.filter(depth=2).first() blog = Site.objects.create(

Allow passing arbitrary link attributes to TitleColumn

test_title_column

5994cc43dfc5cc1ed891ab78eff3a3bcf56f6830

wagtail

test_tables.py

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

Python

def test_title_column(self): root_page = Page.objects.filter(depth=2).first() blog = Site.objects.create( hostname="blog.example.com", site_name="My blog", root_page=root_page ) gallery = Site.objects.create( hostname="gallery.example.com", site_name="My gallery", root_page=root_page ) data = [blog, gallery] table = Table( [ TitleColumn( "hostname", url_name="wagtailsites:edit", link_classname="choose-site", link_attrs={"data-chooser": "yes"}, ), Column("site_name", label="Site name"), ], data, ) html = self.render_component(table) self.assertHTMLEqual( html, % (blog.pk, gallery.pk), )

src/transformers/models/realm/tokenization_realm.py

def _clean_text(self, text): output = [] for char in text: cp = ord(char) if cp == 0 or cp == 0xFFFD or _is_control(char): continue if _is_whitespace(char): output.append

Add FastTokenizer to REALM (#15211) * Remove BertTokenizer abstraction * Add FastTokenizer to REALM * Fix config archive map * Fix copies * Update realm.mdx * Apply suggestions from code review

_clean_text

841d979190319098adc8101f9820a02ee3be4c8b

transformers

tokenization_realm.py

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

Python

def _clean_text(self, text): output = [] for char in text: cp = ord(char) if cp == 0 or cp == 0xFFFD or _is_control(char): continue if _is_whitespace(char): output.append(" ") else: output.append(char) return "".join(output)

openbb_terminal/cryptocurrency/crypto_controller.py

def call_candle(self, other_args): if self.symbol: parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="candle", description=, ) ns_parser = parse_known_args_and_warn( parser, other_args, EXPORT_BOTH_RAW_DATA_AND_FIGURES ) if ns_parser: plot_chart(

refactoring load, changed chart to candle (#1838) * refactoring load, changed chart to candle * updating load * refactor done, missing tests * fixed chart * refactor * linting * tests failing * fix minh issues * auto completion for load * linting * Tests : cryptocurrency/controller ; remove mocking of functions which are not used anymore * Cryptocurrency/Controller : call_headlines ; fix bug * Tests : cryptocurrency/controller ; mock function * Tests : cryptocurrency/due_diligence ; fix expected output * cryptocurrency/due_diligence ; mock functions Co-authored-by: Chavithra <[email protected]> Co-authored-by: minhhoang1023 <[email protected]> Co-authored-by: James Maslek <[email protected]>

call_candle

0e03b9e9e41aaa61cdec5d674a9f2c64ab8d3394

OpenBBTerminal

crypto_controller.py

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

Python

def call_candle(self, other_args): if self.symbol: parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="candle", description=, ) ns_parser = parse_known_args_and_warn( parser, other_args, EXPORT_BOTH_RAW_DATA_AND_FIGURES ) if ns_parser: plot_chart( symbol=self.symbol, currency=self.current_currency, prices_df=self.current_df, )

tests/components/bayesian/test_binary_sensor.py

async def test_load_values_when_added_to_hass(hass): config = { "binary_sensor": {

Bayesian - support `unique_id:` (#79879) * support unique_id * adds test for unique_ids

test_load_values_when_added_to_hass

fe7402375d2f899a7edd6ac326d2c1998b4c43da

core

test_binary_sensor.py

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

Python

async def test_load_values_when_added_to_hass(hass): config = { "binary_sensor": { "name": "Test_Binary", "platform": "bayesian", "unique_id": "3b4c9563-5e84-4167-8fe7-8f507e796d72", "device_class": "connectivity", "observations": [ { "platform": "state", "entity_id": "sensor.test_monitored", "to_state": "off", "prob_given_true": 0.8, "prob_given_false": 0.4, } ], "prior": 0.2, "probability_threshold": 0.32, } } hass.states.async_set("sensor.test_monitored", "off") await hass.async_block_till_done() assert await async_setup_component(hass, "binary_sensor", config) await hass.async_block_till_done() entity_registry = async_get_entities(hass) assert ( entity_registry.entities["binary_sensor.test_binary"].unique_id == "bayesian-3b4c9563-5e84-4167-8fe7-8f507e796d72" ) state = hass.states.get("binary_sensor.test_binary") assert state.attributes.get("device_class") == "connectivity" assert state.attributes.get("observations")[0]["prob_given_true"] == 0.8 assert state.attributes.get("observations")[0]["prob_given_false"] == 0.4

tests/providers/databricks/operators/test_databricks_sql.py

def test_copy_with_target_credential(self): expression = "col1, col2" op = DatabricksCopyIntoOperator( file_location=COPY_FILE_LOCATION, file_format='CSV', table_name='test', task_id=TASK_ID, expression_list=expression, storage_credential='abc', credential={'AZURE_SAS_TOKEN': 'abc'}, ) asse

Update to the released version of DBSQL connector Also added additional parameters for further customization of connection if it's required

test_copy_with_target_credential

6a3d6cc32b4e3922d259c889460fe82e0ebf3663

airflow

test_databricks_sql.py

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

Python

def test_copy_with_target_credential(self): expression = "col1, col2" op = DatabricksCopyIntoOperator( file_location=COPY_FILE_LOCATION, file_format='CSV', table_name='test', task_id=TASK_ID, expression_list=expression, storage_credential='abc', credential={'AZURE_SAS_TOKEN': 'abc'}, ) assert ( op._create_sql_query() == f.strip() )

.venv/lib/python3.8/site-packages/pip/_internal/commands/debug.py

def show_actual_vendor_versions(vendor_txt_versions): # type: (Dict[str, str]) -> None for module_name, expected_version in vendor_txt_versions.items(): extra_message = '' actual_version = get_vendor_version_from_module(module_name) if not actual_version: extra_message = ' (Un

upd; format

show_actual_vendor_versions

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

debug.py

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

Python

def show_actual_vendor_versions(vendor_txt_versions): # type: (Dict[str, str]) -> None for module_name, expected_version in vendor_txt_versions.items(): extra_message = '' actual_version = get_vendor_version_from_module(module_name) if not actual_version: extra_message = ' (Unable to locate actual module version, using'\ ' vendor.txt specified version)' actual_version = expected_version elif parse_version(actual_version) != parse_version(expected_version): extra_message = ' (CONFLICT: vendor.txt suggests version should'\ ' be {})'.format(expected_version) logger.info('%s==%s%s', module_name, actual_version, extra_message)

youtube_dl/utils.py

def escape_rfc3986(s): if sys.version_info < (3, 0) and isinstance(s, compat_str): s = s.encode('utf-

[utils] Ensure RFC3986 encoding result is unicode

escape_rfc3986

556862bc911bb54435b7b0b01451789b884b0390

youtube-dl

utils.py

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

Python

def escape_rfc3986(s): if sys.version_info < (3, 0) and isinstance(s, compat_str): s = s.encode('utf-8') # ensure unicode: after quoting, it can always be converted return compat_str(compat_urllib_parse.quote(s, b"%/;:@&=+$,!~*'()?#[]"))

gamestonk_terminal/cryptocurrency/due_diligence/dd_controller.py

def call_social(self, other_args): parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="social", description=, ) ns_parser = parse_known_args_and_warn( parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED ) if ns_parser: pycoingecko_view.display_social( self.coin_map_df["CoinGecko"

Crypto menu refactor (#1119) * enabled some crypto commands in dd to be called independent of source loaded * support for coin_map_df in all dd functions + load ta and plot chart refactor * updated tests and removed coingecko scrapping where possible * removed ref of command from hugo * updated pycoingecko version * refactoring load * refactored load to fetch prices; pred can run independent of source now * load by default usd on cp/cg and usdt on cb/bin * updated to rich for formatting and updated dependencies * fixed changes requested * update docs * revert discord requirements * removed absolute from calculate change for price * fixing pr issues * fix loading issue when similar coins exist, move coins to home, fill n/a * update docs for coins * adds load to ta and pred menu

call_social

ea964109d654394cc0a5237e6ec5510ba6404097

OpenBBTerminal

dd_controller.py

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

Python

def call_social(self, other_args): parser = argparse.ArgumentParser( add_help=False, formatter_class=argparse.ArgumentDefaultsHelpFormatter, prog="social", description=, ) ns_parser = parse_known_args_and_warn( parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED ) if ns_parser: pycoingecko_view.display_social( self.coin_map_df["CoinGecko"], export=ns_parser.export )

tests/snuba/api/endpoints/test_project_event_details.py

def test_ignores_different_group(self): url = reverse( "sentry-api-0-project-event-details", kwargs={ "event_id": self.next_transaction_event.event_id, "project_slug": self.next_transaction_event.project.slug, "organization_slug": self.next_transacti

feat(perf issues): Return prev/next for transaction events (#38274) * feat(perf issues): Return prev/next for transaction events

test_ignores_different_group

6d7681529f68a87e41d4c11a4aa1e6732cb15ade

sentry

test_project_event_details.py

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

Python

def test_ignores_different_group(self): url = reverse( "sentry-api-0-project-event-details", kwargs={ "event_id": self.next_transaction_event.event_id, "project_slug": self.next_transaction_event.project.slug, "organization_slug": self.next_transaction_event.project.organization.slug, }, ) with self.feature("organizations:performance-issues"): response = self.client.get(url, format="json", data={"group_id": self.group.id}) assert response.status_code == 200, response.content assert response.data["id"] == str(self.next_transaction_event.event_id) assert response.data["nextEventID"] is None

sympy/tensor/tensor.py

def _dedupe_indices(new, exclude, index_structure): inds_self = set(exclude) dums_new = set(get_dummy_indices(new)) conflicts = dums_new.intersection(inds_self) if len(conflicts) == 0: return None inds_self.update(dums_new) self_args_free = [(i, None) for i in inds_self] gen = index_structure._get_generator_for_dummy_indices(self_args_free) repl = {} for d in conflicts: if -d in repl.keys(): continue newname = gen(d.te

_dedupe_indices: convert to staticmethod index_structure is now an additional argument

_dedupe_indices

b5f5ec455e7d003fa214a215475a3fa2407760cc

sympy

tensor.py

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

Python

def _dedupe_indices(new, exclude, index_structure): inds_self = set(exclude) dums_new = set(get_dummy_indices(new)) conflicts = dums_new.intersection(inds_self) if len(conflicts) == 0: return None inds_self.update(dums_new) self_args_free = [(i, None) for i in inds_self] gen = index_structure._get_generator_for_dummy_indices(self_args_free) repl = {} for d in conflicts: if -d in repl.keys(): continue newname = gen(d.tensor_index_type) new_d = d.func(newname, *d.args[1:]) repl[d] = new_d repl[-d] = -new_d if len(repl) == 0: return None new_renamed = new._replace_indices(repl) return new_renamed

lib/matplotlib/spines.py

def get_window_extent(self, renderer=None): # make sure the location is updated so that transforms etc are correct: self._adjust_location() bb = super().get_window_extent(renderer=renderer) if self.axis is None or not self.axis.get_visible(): return bb bboxes = [bb] drawn_ticks = self.axis._update_ticks() major_tick = next(iter({*drawn_ticks} & {*self.axis.majorTicks}), None) minor_tick = next(iter({*drawn_ticks} & {*self.axis.minorTicks}), None) for tick in [major_tick, minor_tick]: if tick is None: continue bb0 = bb.frozen() tickl = tick._size tickdir = tick._tickdir if tickdir == 'out': padout = 1 padin = 0 elif tickdir == 'in': padout = 0 padin = 1 else: padout = 0.5 padin = 0.5 padout = padout * tickl / 72 * self.figure.dpi padin = padin * tickl / 72 * self.figure.dpi if tick.tick1line.get_visible(): if self.spine_type == 'left': bb0.x0 = bb0.x0 - padout bb0.x1 = bb0.x1 + padin elif self.spine_type == 'bottom': bb0.y0 = bb0.y0 - padout bb0.y1 = bb0.y1 + padin if tick.tick2line.get_visible(): if self.spine_type == 'right': bb0.x1 = bb0.x1 + padout bb0.x0 = bb0.x0 - padin elif self.spine_type == 'top': bb0.y1 = bb0.y1 + padout bb0.y0 = bb0.y0 - padout

Fix issue with space allocated for single tick that should not be there Co-authored-by: Antony Lee <[email protected]>

get_window_extent

3804cdd8f1771065f9c8616c57357c2b190c3a05

matplotlib

spines.py

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

Python

def get_window_extent(self, renderer=None): # make sure the location is updated so that transforms etc are correct: self._adjust_location() bb = super().get_window_extent(renderer=renderer) if self.axis is None or not self.axis.get_visible(): return bb bboxes = [bb] drawn_ticks = self.axis._update_ticks() major_tick = next(iter({*drawn_ticks} & {*self.axis.majorTicks}), None) minor_tick = next(iter({*drawn_ticks} & {*self.axis.minorTicks}), None) for tick in [major_tick, minor_tick]: if tick is None: continue bb0 = bb.frozen() tickl = tick._size tickdir = tick._tickdir if tickdir == 'out': padout = 1 padin = 0 elif tickdir == 'in': padout = 0 padin = 1 else: padout = 0.5 padin = 0.5 padout = padout * tickl / 72 * self.figure.dpi padin = padin * tickl / 72 * self.figure.dpi if tick.tick1line.get_visible(): if self.spine_type == 'left': bb0.x0 = bb0.x0 - padout bb0.x1 = bb0.x1 + padin elif self.spine_type == 'bottom': bb0.y0 = bb0.y0 - padout bb0.y1 = bb0.y1 + padin if tick.tick2line.get_visible(): if self.spine_type == 'right': bb0.x1 = bb0.x1 + padout bb0.x0 = bb0.x0 - padin elif self.spine_type == 'top': bb0.y1 = bb0.y1 + padout bb0.y0 = bb0.y0 - padout bboxes.append(bb0) return mtransforms.Bbox.union(bboxes)

sympy/physics/continuum_mechanics/truss.py

def apply_support(self, location, type): if location not in self._node_labels: raise ValueError("Support must be added on a known node") else: self._supports[location] = type if type == "pinned": self._loads['R_'+str(location)+'_x']= [] self._loads['R_'+

remove_load method added along with other changes

apply_support

99ede53223eafb56b2c2b4ab7b8a6764b628c9d9

sympy

truss.py

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

Python

def apply_support(self, location, type): if location not in self._node_labels: raise ValueError("Support must be added on a known node") else: self._supports[location] = type if type == "pinned": self._loads['R_'+str(location)+'_x']= [] self._loads['R_'+str(location)+'_y']= [] elif type == "roller": self._loads['R_'+str(location)+'_y']= [] if 'R_'+str(location)+'_x' in list(self._loads): self._loads.pop('R_'+str(location)+'_x')

homeassistant/components/xiaomi_miio/vacuum.py

def timers(self) -> list[dict[str, Any]]: retu

Improve type hints in xiaomi_miio vacuum entities (#76563) Co-authored-by: Teemu R. <[email protected]>

timers

54fc17e10de0752c03d6b95153c3d8168f76ea44

core

vacuum.py

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

Python

def timers(self) -> list[dict[str, Any]]: return [ { "enabled": timer.enabled, "cron": timer.cron, "next_schedule": as_utc(timer.next_schedule), } for timer in self.coordinator.data.timers ]

TTS/tts/utils/visual.py

def plot_avg_pitch(pitch, chars, fig_size=(30, 10), output_fig=False): old_fig_size = plt.rcParams["figure.figsize"] if fig_size is not None: plt.rcParams["figure.figsize"] = fig_size fig, ax = plt.subplots() x = np.array(range(len(chars)))

Plot pitch over input characters

plot_avg_pitch

5169d4eb32407ca0278046aaffc56ca6f9e9ef32

TTS

visual.py

https://github.com/coqui-ai/TTS.git

Python

def plot_avg_pitch(pitch, chars, fig_size=(30, 10), output_fig=False): old_fig_size = plt.rcParams["figure.figsize"] if fig_size is not None: plt.rcParams["figure.figsize"] = fig_size fig, ax = plt.subplots() x = np.array(range(len(chars))) my_xticks = [c for c in chars] plt.xticks(x, my_xticks) ax.set_xlabel("characters") ax.set_ylabel("freq") ax2 = ax.twinx() ax2.plot(pitch, linewidth=5.0, color="red") ax2.set_ylabel("F0") plt.rcParams["figure.figsize"] = old_fig_size if not output_fig: plt.close() return fig

sympy/ntheory/generate.py

def composite(nth): n = as_int(nth) if n < 1: raise ValueError("nth must be a positive integer; composite(1) == 4") composite_arr = [4, 6, 8, 9, 10, 12, 14, 15, 16, 18] if n <= 10: return composite_arr[n - 1] a, b = 4, sieve._list[-1] if n <= b - primepi(b) - 1: while a < b - 1: mid = (a + b) >> 1

Refactored import ordering in functions

composite

e0dc14eca132f37c5f49369eb4051eae37c9b119

sympy

generate.py

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

Python

def composite(nth): n = as_int(nth) if n < 1: raise ValueError("nth must be a positive integer; composite(1) == 4") composite_arr = [4, 6, 8, 9, 10, 12, 14, 15, 16, 18] if n <= 10: return composite_arr[n - 1] a, b = 4, sieve._list[-1] if n <= b - primepi(b) - 1: while a < b - 1: mid = (a + b) >> 1 if mid - primepi(mid) - 1 > n: b = mid else: a = mid if isprime(a): a -= 1 return a from sympy.functions.elementary.exponential import log from sympy.functions.special.error_functions import li a = 4 # Lower bound for binary search b = int(n*(log(n) + log(log(n)))) # Upper bound for the search. while a < b: mid = (a + b) >> 1 if mid - li(mid) - 1 > n: b = mid else: a = mid + 1 n_composites = a - primepi(a) - 1 while n_composites > n: if not isprime(a): n_composites -= 1 a -= 1 if isprime(a): a -= 1 return a

@set_module('numpy')

numpy/lib/twodim_base.py

def histogram2d(x, y, bins=10, range=None, density=None, weights=None): from numpy import histogramdd if len(x) != len(y): raise ValueError('x and y must have the same length.') try: N = len(bins) except TypeError: N = 1 if N != 1 and N != 2: xedges = yedges = asarray(bins) bins = [xedges, yedges] hist, edges = histogramdd([x, y], bins, range, density, weights) return hist, edges[0], edges[1] @set_module('numpy')

DEP: Remove `normed=` keyword argument from histogroms The normed keyword argument has been deprecated for a long time. This removes it, replacing its position with the new density argument.

histogram2d

2215054472616df563faa4613734426c790d4217

numpy

twodim_base.py

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

Python

def histogram2d(x, y, bins=10, range=None, density=None, weights=None): from numpy import histogramdd if len(x) != len(y): raise ValueError('x and y must have the same length.') try: N = len(bins) except TypeError: N = 1 if N != 1 and N != 2: xedges = yedges = asarray(bins) bins = [xedges, yedges] hist, edges = histogramdd([x, y], bins, range, density, weights) return hist, edges[0], edges[1] @set_module('numpy')

homeassistant/components/dlna_dms/dms.py

def available(self) -> bool: return self._device is not None and self._device.profile_device.available

Add dlna_dms integration to support DLNA Digital Media Servers (#66437)

available

b19bf9b147f4321e89d1f7f01e68337f2102f460

core

dms.py

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

Python

def available(self) -> bool: return self._device is not None and self._device.profile_device.available

keras/distribute/distributed_training_utils_v1.py

def _get_input_from_iterator(iterator, model): next_element = iterator.get_next() # `len(nest.flatten(x))` is going to not count empty elements such as {}. # len(nest.flatten([[0,1,2], {}])) is 3 and not 4. The `next_element` is # going to get flattened in `_prepare_feed_values` to work around that. Empty # elements are going to get filtered out as part of the flattening. if len(tf.nest.flatten(next_element)) == len(model.inputs): x = next_element y = None sample_weights = None elif len(tf.nest.flatten(next_element)) == ( len(model.inputs) + len(model.outputs) ): x, y = next_element sample_weights = None else: x, y, sample_weights = next_element # Validate that all the elements in x and y are of the same type and shape. validate_distributed_dataset_inputs(

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

_get_input_from_iterator

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

distributed_training_utils_v1.py

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

Python

def _get_input_from_iterator(iterator, model): next_element = iterator.get_next() # `len(nest.flatten(x))` is going to not count empty elements such as {}. # len(nest.flatten([[0,1,2], {}])) is 3 and not 4. The `next_element` is # going to get flattened in `_prepare_feed_values` to work around that. Empty # elements are going to get filtered out as part of the flattening. if len(tf.nest.flatten(next_element)) == len(model.inputs): x = next_element y = None sample_weights = None elif len(tf.nest.flatten(next_element)) == ( len(model.inputs) + len(model.outputs) ): x, y = next_element sample_weights = None else: x, y, sample_weights = next_element # Validate that all the elements in x and y are of the same type and shape. validate_distributed_dataset_inputs( model._distribution_strategy, x, y, sample_weights ) return x, y, sample_weights

@array_function_from_c_func_and_dispatcher(_multiarray_umath.where)

numpy/core/multiarray.py

def inner(a, b): return (a, b) @array_function_from_c_func_and_dispatcher(_multiarray_umath.where)

DIC: Misc RST reformatting. This contains various RST reformatting. One, moving `(C)` one line up, is specific to a bug in tree-sitter-rst that mis parses this section. Another is adding one black line for a similar reason where `..` is seen as section underline by tree-sitter-rst. This is some shuffling of section underline: try to be consitant, `=`, then `-`, then `~`, with this refactor there is also no more section that use backticks as underline. Note in particular that non-consitency of underline lead to a problem in datetime64 section where "weekmasks" (underlined with `-`) were actually a level-4 heading instead of a level 2 or 3 I guess, and thus were nested under the `busday_count()` section. You'll note also 2 formulas that are under double-quotes as they are not references.

inner

84eeca630ec9c5bf580bc456035c87d8591c1389

numpy

multiarray.py

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

Python

def inner(a, b): return (a, b) @array_function_from_c_func_and_dispatcher(_multiarray_umath.where)

lib/matplotlib/collections.py

def contains(self, mouseevent): inside, info = self._default_contains(mouseevent) if inside is not None: return inside, info if not self.get_visible(): return False, {} pickradius = ( float(self._picker) if isinstance(self._picker, Number) and self._picker is not True # the bool, not just nonzero or 1 else self._pickradius) if self.axes: self.axes._unstale_viewLim() transform, offset_trf, offsets, paths = self._prepare_points() # Tests if the point is contained on one of the polygons formed # by the control points of each of the paths. A point is considered

Switch transOffset to offset_transform. Note that most APIs *previously* already accepted *offset_transform* as kwarg, due to the presence of the `set_offset_transform` setter. Prefer that name (shortening it to `offset_trf` for local variables). Backcompat for the old `transOffset` name is kept in most places by introducing a property alias.

contains

c25cf96cfb7e6fc9ad75347cb2a32193c501e82c

matplotlib

collections.py

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

Python

def contains(self, mouseevent): inside, info = self._default_contains(mouseevent) if inside is not None: return inside, info if not self.get_visible(): return False, {} pickradius = ( float(self._picker) if isinstance(self._picker, Number) and self._picker is not True # the bool, not just nonzero or 1 else self._pickradius) if self.axes: self.axes._unstale_viewLim() transform, offset_trf, offsets, paths = self._prepare_points() # Tests if the point is contained on one of the polygons formed # by the control points of each of the paths. A point is considered # "on" a path if it would lie within a stroke of width 2*pickradius # following the path. If pickradius <= 0, then we instead simply check # if the point is *inside* of the path instead. ind = _path.point_in_path_collection( mouseevent.x, mouseevent.y, pickradius, transform.frozen(), paths, self.get_transforms(), offsets, offset_trf, pickradius <= 0) return len(ind) > 0, dict(ind=ind)

jina/orchestrate/deployments/__init__.py

def deployments(self) -> List[Dict]: return [ { 'name': self.name,

refactor: rename pod to deployment (#4230) * refactor: rename pod to deployment * style: fix overload and cli autocomplete * fix: undo daemon mistake * refactor: leftover cleanup * fix: more test fixes * fix: more fixes * fix: more fixes * fix: more fixes * fix: more tests * fix: fix more tests * refactor: fix more tests * refactor: more tests fixes * refactor: rename pea to pod * refactor: adjust docs * refactor: complete pea renaming * refactor: more fixes * fix: pea_type in k8s yamls * fix: adjust pod args name * refactor: rename peapods parser folder * fix: da init Co-authored-by: Jina Dev Bot <[email protected]>

deployments

13edc16d806fb5d77a6849551178ccc75937f25f

jina

__init__.py

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

Python

def deployments(self) -> List[Dict]: return [ { 'name': self.name, 'head_host': self.head_host, 'head_port_in': self.head_port_in, } ]

qutebrowser/browser/webkit/http.py

def parse_content_disposition(reply): is_inline = True filename = None content_disposition_header = b'Content-Disposition' # First check if the Content-Disposition header has a filename # attribute. if reply.hasRawHeader(content_disposition_header): # We use the unsafe variant of the filename as we sanitize it via # os.path.basename later. try: value = bytes(reply.rawHeader(content_disposition_header)) log.network.debug("Parsing Content-Disposition: {value!r}") content_disposition = ContentDisposition.parse(value) filename = content_disposition.filename() except ContentDispositionError as e: log.network.error(f"Error while parsing filenam

Simplify some syntax Found via pyupgrade

parse_content_disposition

bd8c940320b7d8476b422edd9c417703db64f603

qutebrowser

http.py

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

Python

def parse_content_disposition(reply): is_inline = True filename = None content_disposition_header = b'Content-Disposition' # First check if the Content-Disposition header has a filename # attribute. if reply.hasRawHeader(content_disposition_header): # We use the unsafe variant of the filename as we sanitize it via # os.path.basename later. try: value = bytes(reply.rawHeader(content_disposition_header)) log.network.debug("Parsing Content-Disposition: {value!r}") content_disposition = ContentDisposition.parse(value) filename = content_disposition.filename() except ContentDispositionError as e: log.network.error(f"Error while parsing filename: {e}") else: is_inline = content_disposition.is_inline() # Then try to get filename from url if not filename: filename = reply.url().path().rstrip('/') # If that fails as well, use a fallback if not filename: filename = 'qutebrowser-download' return is_inline, os.path.basename(filename)

seaborn/_core/properties.py

def _get_categorical_mapping(self, scale, data): levels = categorical_order(data, scale.order) n = len(levels) values = scale.values if isinstance(values, dict): self._check_dict_entries(levels, values) # TODO where to ensure that dict values have consistent representation? colors = [values[x] for x in levels] elif isinstance(values, list): colors = self._check_list_length(levels, scale.values) elif isinstance(values, tuple): colors = blend_palette(values, n) elif isinstance(values, str): colors = color_palette(values, n) elif values is None: if n <= len(get_color_cycle()): # Use current (global) default palette colors = color_palette(n_colors=n) else: colors = color_palette("husl", n) else: scale_class = scale.__class__.__name__ msg = " ".join([ f"Scale values for {self.variable} with a {scale_class} mapping", f"must be string, lis

Transition mappings->properties, leaving a few loose ends

_get_categorical_mapping

a07ef69882ed76e09a0ed43d6f3ea33780c1b2be

seaborn

properties.py

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

Python

def _get_categorical_mapping(self, scale, data): levels = categorical_order(data, scale.order) n = len(levels) values = scale.values if isinstance(values, dict): self._check_dict_entries(levels, values) # TODO where to ensure that dict values have consistent representation? colors = [values[x] for x in levels] elif isinstance(values, list): colors = self._check_list_length(levels, scale.values) elif isinstance(values, tuple): colors = blend_palette(values, n) elif isinstance(values, str): colors = color_palette(values, n) elif values is None: if n <= len(get_color_cycle()): # Use current (global) default palette colors = color_palette(n_colors=n) else: colors = color_palette("husl", n) else: scale_class = scale.__class__.__name__ msg = " ".join([ f"Scale values for {self.variable} with a {scale_class} mapping", f"must be string, list, tuple, or dict; not {type(scale.values)}." ]) raise TypeError(msg) # If color specified here has alpha channel, it will override alpha property colors = self._standardize_colors(colors)

lib/matplotlib/colorbar.py

def minorlocator(self, loc): self._long_axis().set_minor_locator(loc)

MNT: make colorbars locators and formatters properties

minorlocator

6010bb43ed01c48c7c403569dd210490b236a853

matplotlib

colorbar.py

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

Python

def minorlocator(self, loc): self._long_axis().set_minor_locator(loc) self._minorlocator = loc

@pytest.mark.parametrize( "time_zone", ["Europe/Berlin", "America/Chicago", "US/Hawaii", "UTC"] )

tests/components/recorder/test_models.py

def test_process_datetime_to_timestamp_freeze_time(time_zone, hass): hass.config.set_time_zone(time_zone) utc_now = dt_util.utcnow() with freeze_time(utc_now): epoch = utc_now.timestamp() assert process_datetime_to_timestamp(dt_util.utcnow()) == epoch now = dt_util.now() assert process_datetime_to_timestamp(now) == epoch @pytest.mark.parametrize( "time_zone", ["Europe/Berlin", "America/Chicago", "US/Hawaii

Fix process_datetime_to_timestamp and add test coverage (#71755)

test_process_datetime_to_timestamp_freeze_time

1d9fb4bca871f97109684419f0f9526a0c151f2d

core

test_models.py

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

Python

def test_process_datetime_to_timestamp_freeze_time(time_zone, hass): hass.config.set_time_zone(time_zone) utc_now = dt_util.utcnow() with freeze_time(utc_now): epoch = utc_now.timestamp() assert process_datetime_to_timestamp(dt_util.utcnow()) == epoch now = dt_util.now() assert process_datetime_to_timestamp(now) == epoch @pytest.mark.parametrize( "time_zone", ["Europe/Berlin", "America/Chicago", "US/Hawaii", "UTC"] )

tools/alignments/jobs.py

def _spatially_filter(self) -> np.ndarray: logger.debug("Spatially Filter") assert self._shapes_model is not None landmarks_norm = self._normalized["l

Alignments Tool - Typing, Documentation + Re-org

_spatially_filter

e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1

faceswap

jobs.py

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

Python

def _spatially_filter(self) -> np.ndarray: logger.debug("Spatially Filter") assert self._shapes_model is not None landmarks_norm = self._normalized["landmarks"] # Convert to matrix form landmarks_norm_table = np.reshape(landmarks_norm, [68 * 2, landmarks_norm.shape[2]]).T # Project onto shapes model and reconstruct landmarks_norm_table_rec = self._shapes_model.inverse_transform( self._shapes_model.transform(landmarks_norm_table)) # Convert back to shapes (numKeypoint, num_dims, numFrames) landmarks_norm_rec = np.reshape(landmarks_norm_table_rec.T, [68, 2, landmarks_norm.shape[2]]) # Transform back to image co-ordinates retval = self._normalized_to_original(landmarks_norm_rec, self._normalized["scale_factors"], self._normalized["mean_coords"]) logger.debug("Spatially Filtered: %s", retval) return retval

sympy/combinatorics/free_groups.py

def letter_form(self): return tuple(flatten([(i,)*j if j > 0 else (-i,)*(-j) for i, j in se

Updated import locations

letter_form

498015021131af4dbb07eb110e5badaba8250c7b

sympy

free_groups.py

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

Python

def letter_form(self): return tuple(flatten([(i,)*j if j > 0 else (-i,)*(-j) for i, j in self.array_form]))

freqtrade/rpc/rpc.py

def _handle_default_message(self, type, data): logger.debug(f"Received message from Leader

Refactoring, minor improvements, data provider improvements

_handle_default_message

2b5f0678772bea0abaf4abe93efc55de43ea3e0e

freqtrade

rpc.py

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

Python

def _handle_default_message(self, type, data): logger.debug(f"Received message from Leader of type {type}: {data}")

nni/nas/oneshot/pytorch/base_lightning.py

def export_probs(self) -> dict[str, Any]: result = {} for module in self.nas_modules: try: result.update(module.export_probs(memo=result)) except NotImplementedE

Enhancement of one-shot NAS (v2.9) (#5049)

export_probs

f77db747d07d5c90a3a9f70bb17f71d4573f329e

nni

base_lightning.py

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

Python

def export_probs(self) -> dict[str, Any]: result = {} for module in self.nas_modules: try: result.update(module.export_probs(memo=result)) except NotImplementedError: warnings.warn( 'Some super-modules you have used did not implement export_probs. You might find some logs are missing.', UserWarning ) return result

@region_silo_endpoint

src/sentry/api/endpoints/organization_releases.py

def debounce_update_release_health_data(organization, project_ids): # Figure out which projects need to get updates from the snuba. should_update = {} cache_keys = ["debounce-health:%d" % id for id in project_ids] cache_data = cache.get_many(cache_keys) for project_id, cache_key in zip(project_ids, cache_keys): if cache_data.get(cache_key) is None: should_update[project_id] = cache_key if not should_update: return projects = {p.id: p for p in Project.objects.get_many_from_cache(should_update.keys())} # This gives us updates for all release-projects which have seen new # health data over the last days. It will miss releases where the last # date is longer than what `get_changed_project_release_model_adoptions` # considers recent. project_releases = release_health.get_changed_project_release_model_adoptions( should_update.keys() ) # Check which we already have rows for. existing = set( ReleaseProject.objects.filter( project_id__in=[x[0] for x in project_releases], release__version__in=[x[1] for x in project_releases], ).values_list("project_id", "release__version") ) to_upsert = [] for key in project_releases: if key not in existing: to_upsert.append(key) if to_upsert: dates = release_health.get_oldest_health_data_for_releases(to_upsert) for project_id, version in to_upsert: project = projects.get(project_id) if project is None: # should not happen continue # Ignore versions that were saved with an empty string before validation was added

fix(releases): Use Release.is_valid_version on adding releases (#40930)

debounce_update_release_health_data

0cfac5c8bd83bcc7b96f3294c41a96524b883786

sentry

organization_releases.py

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

Python

def debounce_update_release_health_data(organization, project_ids): # Figure out which projects need to get updates from the snuba. should_update = {} cache_keys = ["debounce-health:%d" % id for id in project_ids] cache_data = cache.get_many(cache_keys) for project_id, cache_key in zip(project_ids, cache_keys): if cache_data.get(cache_key) is None: should_update[project_id] = cache_key if not should_update: return projects = {p.id: p for p in Project.objects.get_many_from_cache(should_update.keys())} # This gives us updates for all release-projects which have seen new # health data over the last days. It will miss releases where the last # date is longer than what `get_changed_project_release_model_adoptions` # considers recent. project_releases = release_health.get_changed_project_release_model_adoptions( should_update.keys() ) # Check which we already have rows for. existing = set( ReleaseProject.objects.filter( project_id__in=[x[0] for x in project_releases], release__version__in=[x[1] for x in project_releases], ).values_list("project_id", "release__version") ) to_upsert = [] for key in project_releases: if key not in existing: to_upsert.append(key) if to_upsert: dates = release_health.get_oldest_health_data_for_releases(to_upsert) for project_id, version in to_upsert: project = projects.get(project_id) if project is None: # should not happen continue # Ignore versions that were saved with an empty string before validation was added if not Release.is_valid_version(version): continue # We might have never observed the release. This for instance can # happen if the release only had health data so far. For these cases # we want to create the release the first time we observed it on the # health side. release = Release.get_or_create( project=project, version=version, date_added=dates.get((project_id, version)) ) # Make sure that the release knows about this project. Like we had before # the project might not have been associated with this release yet. release.add_project(project) # Debounce updates for a minute cache.set_many(dict(zip(should_update.values(), [True] * len(should_update))), 60) @region_silo_endpoint

python3.10.4/Lib/dis.py

def show_code(co, *, file=None): print(code_info(co), file=file) _Instruction = collections.namedtuple("_Instruction", "opname opcode arg argval argrepr offset starts_line is_jump_target") _Instruction.opname.__doc__ = "Human readable name for operation" _Instruction.opcode.__doc__ = "Numeric co

add python 3.10.4 for windows

show_code

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

dis.py

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

Python

def show_code(co, *, file=None): print(code_info(co), file=file) _Instruction = collections.namedtuple("_Instruction", "opname opcode arg argval argrepr offset starts_line is_jump_target") _Instruction.opname.__doc__ = "Human readable name for operation" _Instruction.opcode.__doc__ = "Numeric code for operation" _Instruction.arg.__doc__ = "Numeric argument to operation (if any), otherwise None" _Instruction.argval.__doc__ = "Resolved arg value (if known), otherwise same as arg" _Instruction.argrepr.__doc__ = "Human readable description of operation argument" _Instruction.offset.__doc__ = "Start index of operation within bytecode sequence" _Instruction.starts_line.__doc__ = "Line started by this opcode (if any), otherwise None" _Instruction.is_jump_target.__doc__ = "True if other code jumps to here, otherwise False" _OPNAME_WIDTH = 20 _OPARG_WIDTH = 5

@_copy_docstring_and_deprecators(matplotlib.image.imread)

lib/matplotlib/pyplot.py

def set_cmap(cmap): cmap = colormaps[cmap] rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap)

MNT: convert tests and internal usage way from using mpl.cm.get_cmap

set_cmap

a17f4f3bd63e3ca3754f96d7db4ce5197720589b

matplotlib

pyplot.py

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

Python

def set_cmap(cmap): cmap = colormaps[cmap] rc('image', cmap=cmap.name) im = gci() if im is not None: im.set_cmap(cmap) @_copy_docstring_and_deprecators(matplotlib.image.imread)

qutebrowser/completion/completionwidget.py

def completion_item_focus(self, which, history=False): if history: if (self._cmd.text() == ':' or self._cmd.history.is_browsing() or not self._active): if which == 'next': self._cmd.command_history_next() return

mypy: Upgrade to PyQt5-stubs 5.15.6.0 For some unknown reason, those new stubs cause a *lot* of things now to be checked by mypy which formerly probably got skipped due to Any being implied somewhere. The stubs themselves mainly improved, with a couple of regressions too. In total, there were some 337 (!) new mypy errors. This commit fixes almost all of them, and the next commit improves a fix to get things down to 0 errors again. Overview of the changes: ==== qutebrowser/app.py - Drop type ignore due to improved stubs. ==== qutebrowser/browser/browsertab.py - Specify the type of _widget members more closely than just QWidget. This is debatable: I suppose the abstract stuff shouldn't need to know anything about the concrete backends at all. But it seems like we cut some corners when initially implementing things, and put some code in browsertab.py just because the APIs of both backends happened to be compatible. Perhaps something to reconsider once we drop QtWebKit and hopefully implement a dummy backend. - Add an additional assertion in AbstractAction.run_string. This is already covered by the isinstance(member, self.action_base) above it, but that's too dynamic for mypy to understand. - Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x and y components), not a single int. - Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x and y components), not a single int. - Fix the argument types of AbstractScroller.to_perc, as it's possible to pass fractional percentages too. - Specify the type for AbstractHistoryPrivate._history. See above (_widget) re this being debatable. - Fix the return type of AbstractTabPrivate.event_target(), which can be None (see #3888). - Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS return value), not None. - Fix the argument type for AbstractTabPrivate.toggle_inspector: position can be None to use the last used position. - Declare the type of sub-objects of AbstractTab. - Fix the return value of AbstractTab.icon(), which is the QIcon, not None. ==== qutebrowser/browser/commands.py - Make sure the active window is a MainWindow (with a .win_id attribute). ==== qutebrowser/browser/downloadview.py - Add _model() which makes sure that self.model() is a DownloadModel, not None or any other model. This is needed because other methods access a variety of custom attributes on it, e.g. last_index(). ==== qutebrowser/browser/greasemonkey.py - Add an ignore for AbstractDownload.requested_url which we patch onto the downloads. Probably would be nicer to add it as a proper attribute which always gets set by the DownloadManager. ==== qutebrowser/browser/hints.py - Remove type ignores for QUrl.toString(). - Add a new type ignore for combining different URL flags (which works, but is not exactly type safe... still probably a regression in the stubs). - Make sure the things we get back from self._get_keyparser are what we actually expect. Probably should introduce a TypedDict (and/or overloads for _get_keyparser with typing.Literal) to teach mypy about the exact return value. See #7098. This is needed because we access Hint/NormalKeyParser-specific attributes such as .set_inhibited_timout() or .update_bindings(). ==== qutebrowser/browser/inspector.py - Similar changes than in browsertab.py to make some types where we share API (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next commit. ==== qutebrowser/browser/network/pac.py - Remove now unneeded type ignore for signal. ==== qutebrowser/browser/qtnetworkdownloads.py - Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an AbstractDownload), so that we can call ._uses_nam() on it. ==== qutebrowser/browser/qutescheme.py - Remove now unneeded type ignore for QUrl flags. ==== qutebrowser/browser/urlmarks.py - Specify the type of UrlMarkManager._lineparser, as those only get initialized in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist. ==== qutebrowser/browser/webelem.py - New casts to turn single KeyboardModifier (enum) entries into KeyboardModifiers (flags). Might not be needed anymore with Qt 6. - With that, casting the final value is now unneeded. ==== qutebrowser/browser/webengine/notification.py - Remove now unneeded type ignore for signal. - Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished() is a QProcess, not just any QObject. ==== qutebrowser/browser/webengine/webenginedownloads.py - Remove now unneeded type ignores for signals. ==== qutebrowser/browser/webengine/webengineelem.py - Specify the type of WebEngineElement._tab. - Remove now unneeded type ignore for mixed flags. ==== qutebrowser/browser/webengine/webengineinspector.py - See changes to inspector.py and next commit. - Remove now unneeded type ignore for signal. ==== qutebrowser/browser/webengine/webenginequtescheme.py - Remove now unneeded type ignore for mixed flags. ==== qutebrowser/browser/webengine/webenginesettings.py - Ignore access of .setter attribute which we patch onto QWebEngineProfile. Would be nice to have a subclass or wrapper-class instead. ==== qutebrowser/browser/webengine/webenginetab.py - Specified the type of _widget members more closely than just QWidget. See browsertab.py changes for details. - Remove some now-unneeded type ignores for creating FindFlags. - Specify more concrete types for WebEngineTab members where we actually need to access WebEngine-specific attributes. - Make sure the page we get is our custom WebEnginePage subclass, not just any QWebEnginePage. This is needed because we access custom attributes on it. ==== qutebrowser/browser/webengine/webview.py - Make sure the page we get is our custom WebEnginePage subclass, not just any QWebEnginePage. This is needed because we access custom attributes on it. ==== qutebrowser/browser/webkit/network/networkreply.py - Remove now unneeded type ignores for signals. ==== qutebrowser/browser/webkit/webkitinspector.py - See changes to inspector.py and next commit. ==== qutebrowser/browser/webkit/webkittab.py - Specify the type of _widget members more closely than just QWidget. See browsertab.py changes for details. - Add a type ignore for WebKitAction because our workaround needs to treat them as ints (which is allowed by PyQt, even if not type-safe). - Add new ignores for findText calls: The text is a QString and can be None; the flags are valid despite mypy thinking they aren't (stubs regression?). - Specify the type for WebKitHistoryPrivate._history, because we access WebKit-specific attributes. See above (_widget) re this being debatable. - Make mypy aware that .currentFrame() and .frameAt() can return None (stubs regression?). - Make sure the .page() and .page().networkAccessManager() are our subclasses rather than the more generic QtWebKit objects, as we use custom attributes. - Add new type ignores for signals (stubs regression!) ==== qutebrowser/browser/webkit/webpage.py - Make sure the .networkAccessManager() is our subclass rather than the more generic QtWebKit object, as we use custom attributes. - Replace a cast by a type ignore. The cast didn't work anymore. ==== qutebrowser/browser/webkit/webview.py - Make sure the .page() is our subclass rather than the more generic QtWebKit object, as we use custom attributes. ==== qutebrowser/commands/userscripts.py - Remove now unneeded type ignore for signal. ==== qutebrowser/completion/completer.py - Add a new _completion() getter (which ensures it actually gets the completion view) rather than accessing the .parent() directly (which could be any QObject). ==== qutebrowser/completion/completiondelegate.py - Make sure self.parent() is a CompletionView (no helper method as there is only one instance). - Remove a now-unneeded type ignore for adding QSizes. ==== qutebrowser/completion/completionwidget.py - Add a ._model() getter which ensures that we get a CompletionModel (with custom attributes) rather than Qt's .model() which can be any QAbstractItemModel (or None). - Removed a now-unneeded type ignore for OR-ing flags. ==== qutebrowser/completion/models/completionmodel.py - Remove now unneeded type ignores for signals. - Ignore a complaint about .set_pattern() not being defined. Completion categories don't share any common parent class, so it would be good to introduce a typing.Protocol for this. See #7098. ==== qutebrowser/components/misccommands.py - Removed a now-unneeded type ignore for OR-ing flags. ==== qutebrowser/components/readlinecommands.py - Make sure QApplication.instance() is a QApplication (and not just a QCoreApplication). This includes the former "not None" check. ==== qutebrowser/components/scrollcommands.py - Add basic annotation for "funcs" dict. Could have a callable protocol to specify it needs a count kwarg, see #7098. ==== qutebrowser/config/stylesheet.py - Correctly specify that stylesheet apply to QWidgets, not any QObject. - Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy about this with overloads and protocols (stylesheet for set_register being None => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not worth the troble. See #7098. ==== qutebrowser/keyinput/keyutils.py - Remove some now-unneeded type ignores and add a cast for using a single enum value as flags. Might need to look at this again with Qt 6 support. ==== qutebrowser/keyinput/modeman.py - Add a FIXME for using a TypedDict, see comments for hints.py above. ==== qutebrowser/mainwindow/mainwindow.py - Remove now-unneeded type ignores for calling with OR-ed flags. - Improve where we cast from WindowType to WindowFlags, no int needed - Use new .tab_bar() getter, see below. ==== qutebrowser/mainwindow/prompt.py - Remove now-unneeded type ignores for calling with OR-ed flags. ==== qutebrowser/mainwindow/statusbar/bar.py - Adjust type ignores around @pyqtProperty. The fact one is still needed seems like a stub regression. ==== qutebrowser/mainwindow/statusbar/command.py - Fix type for setText() override (from QLineEdit): text can be None (QString in C++). ==== qutebrowser/mainwindow/statusbar/url.py - Adjust type ignores around @pyqtProperty. The fact one is still needed seems like a stub regression. ==== qutebrowser/mainwindow/tabbedbrowser.py - Specify that TabDeque manages browser tabs, not any QWidgets. It accesses AbstractTab-specific attributes. - Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access .maybe_hide. - Fix the annotations for stored marks: Scroll positions are a QPoint, not int. - Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and .widget(), which ensures that the return values are valid AbstractTabs (or None for _tab_by_idx). This is needed because we access AbstractTab-specific attributes. - For some places, where the tab can be None, continue using .currentTab() but add asserts. - Remove some now-unneeded [unreachable] ignores, as mypy knows about the None possibility now. ==== qutebrowser/mainwindow/tabwidget.py - Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and .widget() are of type TabBar and AbstractTab, respectively. - Add additional assertions where we expect ._tab_by_idx() to never be None. - Remove dead code in get_tab_fields for handling a None y scroll position. I was unable to find any place in the code where this could be set to None. - Remove some now-unneeded type ignores and casts, as mypy now knows that _type_by_idx() could be None. - Work around a strange instance where mypy complains about not being able to find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility, despite it clearly being shown as a bool *inside* that class without any annotation. - Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in fact a TabWidget. ==== qutebrowser/misc/crashsignal.py - Remove now unneeded type ignores for signals. ==== qutebrowser/misc/editor.py - Remove now unneeded type ignores for signals. ==== qutebrowser/misc/ipc.py - Remove now unneeded type ignores for signals. - Add new type ignores for .error() which is both a signal and a getter (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was renamed to errorOccurred in 5.15. ==== qutebrowser/misc/objects.py - Make sure mypy knows that objects.app is our custom Application (with custom attributes) rather than any QApplication. ==== qutebrowser/utils/objreg.py - Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol, but ideally, the whole objreg stuff should die one day anyways. ==== tests/unit/completion/test_completer.py - Make CompletionWidgetStub inherit from CompletionView so that it passes the new isinstance() asserts in completer.py (see above).

completion_item_focus

a20bb67a878b2e68abf8268c1b0a27f018d01352

qutebrowser

completionwidget.py

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

Python

def completion_item_focus(self, which, history=False): if history: if (self._cmd.text() == ':' or self._cmd.history.is_browsing() or not self._active): if which == 'next': self._cmd.command_history_next() return elif which == 'prev': self._cmd.command_history_prev() return else: raise cmdutils.CommandError("Can't combine --history with " "{}!".format(which)) if not self._active: return selmodel = self.selectionModel() indices = { 'next': lambda: self._next_idx(upwards=False), 'prev': lambda: self._next_idx(upwards=True), 'next-category': lambda: self._next_category_idx(upwards=False), 'prev-category': lambda: self._next_category_idx(upwards=True), 'next-page': lambda: self._next_page(upwards=False), 'prev-page': lambda: self._next_page(upwards=True), } idx = indices[which]() if not idx.isValid(): return selmodel.setCurrentIndex( idx, QItemSelectionModel.ClearAndSelect | QItemSelectionModel.Rows) # if the last item is focused, try to fetch more next_idx = self.indexBelow(idx) if not self.visualRect(next_idx).isValid(): self.expandAll() count = self._model().count() if count == 0: self.hide() elif count == 1 and config.val.completion.quick: self.hide() elif config.val.completion.show == 'auto': self.show()

tools/manual/detected_faces.py

def _background_extract(self, output_folder, progress_queue): _io = dict(saver=ImagesSaver(get_folder(output_folder), as_bytes=True), loader=ImagesLoader(self._input_location, count=self._alignments.frames_count)) for frame_idx, (filename, image) in enumerate(_io["loader"].load()): logger.trace("Outputting frame: %s: %s", frame_idx, filename) src_filename = os.path.basename(filename) frame_name = os.path.splitext(src_filename)[0] progress_queue.put(1) for face_idx, face in enumerate(self._frame_faces[frame_idx]): output = f"{frame_name}_{face_idx}.png" aligned = AlignedFace(face.landmarks_xy, image=image, centering="head", size=512) # TODO user selectable size meta = dict(alignments=face.to_png_meta(), source=dict(alignments_version=self._alignments.version, original_filename=output, face_index=face_idx, source_filename=src_filename, source_is_video=self._globals.is_video, source_frame_dims=image.shape[:2]))

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

_background_extract

5e73437be47f2410439a3c6716de96354e6a0c94

faceswap

detected_faces.py

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

Python

def _background_extract(self, output_folder, progress_queue): _io = dict(saver=ImagesSaver(get_folder(output_folder), as_bytes=True), loader=ImagesLoader(self._input_location, count=self._alignments.frames_count)) for frame_idx, (filename, image) in enumerate(_io["loader"].load()): logger.trace("Outputting frame: %s: %s", frame_idx, filename) src_filename = os.path.basename(filename) frame_name = os.path.splitext(src_filename)[0] progress_queue.put(1) for face_idx, face in enumerate(self._frame_faces[frame_idx]): output = f"{frame_name}_{face_idx}.png" aligned = AlignedFace(face.landmarks_xy, image=image, centering="head", size=512) # TODO user selectable size meta = dict(alignments=face.to_png_meta(), source=dict(alignments_version=self._alignments.version, original_filename=output, face_index=face_idx, source_filename=src_filename, source_is_video=self._globals.is_video, source_frame_dims=image.shape[:2])) b_image = encode_image(aligned.face, ".png", metadata=meta) _io["saver"].save(output, b_image) _io["saver"].close()

src/paperless_tesseract/tests/test_checks.py

def test_multi_part_language(self, m): m.return_value = ["chi_sim", "eng"] msgs = check_default_language_available(None) self.assertEqual(len

Fixes language code checks around two part languages

test_multi_part_language

55ef0d4a1b62c3abe8500cad97ddeecf9f746b84

paperless-ngx

test_checks.py

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

Python

def test_multi_part_language(self, m): m.return_value = ["chi_sim", "eng"] msgs = check_default_language_available(None) self.assertEqual(len(msgs), 0)

awx/main/tasks/callback.py

def finished_callback(self, runner_obj):

Decoupled callback functions from BaseTask Class --- Removed all callback functions from 'jobs.py' and put them in a new file '/awx/main/tasks/callback.py' --- Modified Unit tests unit moved --- Moved 'update_model' from jobs.py to /awx/main/utils/update_model.py

finished_callback

443bdc1234682dd0004bae372078512fcf37cce9

awx

callback.py

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

Python

def finished_callback(self, runner_obj): event_data = { 'event': 'EOF', 'final_counter': self.event_ct, 'guid': self.guid, } event_data.setdefault(self.event_data_key, self.instance.id) self.dispatcher.dispatch(event_data)

@pytest.mark.parametrize( "sensitive_fields", [ {"NonExistingType": {}}, {"Product": {"nonExistingField"}}, {"Node": {"id"}}, ], )

saleor/webhook/observability/tests/test_obfuscation.py

def test_anonymize_gql_operation_response_with_fragment_spread(gql_operation_factory): query = result = {"data": "result"} sensitive_fields = {"

Observability reporter (#9803) * Initial commit * Add observability celery beat task * Add observability_reporter_task and observability_send_events * Convert payload to camel case * Add fakeredis to dev dependencies * Add redis buffer tests * Refactor buffer * Update * Optimize buffer * Add tests * Add types-redis to dev dependencies * Refactor * Fix after rebase * Refactor opentracing * Add opentracing to observability tasks * Add more tests * Fix buffer fixtures * Report dropped events * Fix buffer tests * Refactor get_buffer * Refactor unit tests * Set Redis connection client_name * Refactor redis tests * Fix test_get_or_create_connection_pool * Fix JsonTruncText comparison * Add more generate_event_delivery_attempt_payload tests

test_anonymize_gql_operation_response_with_fragment_spread

7ea7916c65357741c3911e307acb58d547a5e91a

saleor

test_obfuscation.py

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

Python

def test_anonymize_gql_operation_response_with_fragment_spread(gql_operation_factory): query = result = {"data": "result"} sensitive_fields = {"Product": {"name"}} operation_result = gql_operation_factory(query, result=result) anonymize_gql_operation_response(operation_result, sensitive_fields) assert operation_result.result["data"] == MASK @pytest.mark.parametrize( "sensitive_fields", [ {"NonExistingType": {}}, {"Product": {"nonExistingField"}}, {"Node": {"id"}}, ], )

@py_random_state(3)

networkx/algorithms/bipartite/generators.py

def complete_bipartite_graph(n1, n2, create_using=None): G = nx.empty_g

Adjust the usage of nodes_or_number decorator (#5599) * recorrect typo in decorators.py * Update tests to show troubles in current code * fix troubles with usage of nodes_or_number * fix typo * remove nodes_or_number where that makes sense * Reinclude nodes_or_numbers and add some tests for nonstandard usage * fix typowq * hopefully final tweaks (no behavior changes * Update test_classic.py Co-authored-by: Jarrod Millman <[email protected]>

complete_bipartite_graph

de1d00f20e0bc14f1cc911b3486e50225a8fa168

networkx

generators.py

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

Python

def complete_bipartite_graph(n1, n2, create_using=None): G = nx.empty_graph(0, create_using) if G.is_directed(): raise nx.NetworkXError("Directed Graph not supported") n1, top = n1 n2, bottom = n2 if isinstance(n1, numbers.Integral) and isinstance(n2, numbers.Integral): bottom = [n1 + i for i in bottom] G.add_nodes_from(top, bipartite=0) G.add_nodes_from(bottom, bipartite=1) if len(G) != len(top) + len(bottom): raise nx.NetworkXError("Inputs n1 and n2 must contain distinct nodes") G.add_edges_from((u, v) for u in top for v in bottom) G.graph["name"] = f"complete_bipartite_graph({n1}, {n2})" return G @py_random_state(3)

python3.10.4/Lib/asyncio/sslproto.py

def shutdown(self, callback=None): if self._state == _UNWRAPPED: raise RuntimeError('no security layer present') if self._state == _SHUTDOWN: raise RuntimeError('shutdown in progress') assert self._state in (_WRAPPED, _DO_HANDSHAKE) self._state = _SHUTDOWN self._shutdown_cb = callback ssldata, ap

add python 3.10.4 for windows

shutdown

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

sslproto.py

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

Python

def shutdown(self, callback=None): if self._state == _UNWRAPPED: raise RuntimeError('no security layer present') if self._state == _SHUTDOWN: raise RuntimeError('shutdown in progress') assert self._state in (_WRAPPED, _DO_HANDSHAKE) self._state = _SHUTDOWN self._shutdown_cb = callback ssldata, appdata = self.feed_ssldata(b'') assert appdata == [] or appdata == [b''] return ssldata

salt/cloud/clouds/proxmox.py

def preferred_ip(vm_, ips): proto = config.get_cloud_config_value( "protocol", vm_, __opts__, default="ipv4", search_global=False ) family = socket.AF_INET if proto == "ipv6": family = socket.AF_INET6 for ip in ips: ignore_ip = ignore_cidr(vm_, ip) if ignore_ip: continue try: socket.inet_pton(family, ip) return ip except Exception: # pylint: disable=broad-except continue return False

Add support for get IP-address from agent

preferred_ip

a5679caf65c7c79cd72841b6e5793b9b693744c9

salt

proxmox.py

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

Python

def preferred_ip(vm_, ips): proto = config.get_cloud_config_value( "protocol", vm_, __opts__, default="ipv4", search_global=False ) family = socket.AF_INET if proto == "ipv6": family = socket.AF_INET6 for ip in ips: ignore_ip = ignore_cidr(vm_, ip) if ignore_ip: continue try: socket.inet_pton(family, ip) return ip except Exception: # pylint: disable=broad-except continue return False

erpnext/accounts/doctype/account/account.py

def get_parent_account(doctype, txt, searchfield, start, page_len, filters): return frappe.db.sql( % ("%s", searchfield, "%s", "%s", "%s"), (filters["company"], "%%%s%%" % txt, page_len, start), as_list=1,

refactor: use db independent offset syntax (#31345) * chore: use db independent offset syntax * fix: typo * style: reformat code to black spec Co-authored-by: Ankush Menat <[email protected]>

get_parent_account

00ef499739959630cd7cf97419fbb6ca59be05f2

erpnext

account.py

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

Python

def get_parent_account(doctype, txt, searchfield, start, page_len, filters): return frappe.db.sql( % ("%s", searchfield, "%s", "%s", "%s"), (filters["company"], "%%%s%%" % txt, page_len, start), as_list=1, )

keras/utils/kernelized_utils.py

def exact_laplacian_kernel(x, y, stddev): r x_aligned, y_aligned = _align_matrices(x, y) diff_l1_norm = tf.reduce_sum(tf.abs(tf.subtract(x_aligned, y_aligned)), 2)

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

exact_laplacian_kernel

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

kernelized_utils.py

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

Python

def exact_laplacian_kernel(x, y, stddev): r x_aligned, y_aligned = _align_matrices(x, y) diff_l1_norm = tf.reduce_sum(tf.abs(tf.subtract(x_aligned, y_aligned)), 2) return tf.exp(-diff_l1_norm / stddev)

sklearn/manifold/_isomap.py

def transform(self, X): check_is_fitted(self) if self.n_neighbors is not None: distances, indices = self.nbrs_.kneighbors(X, return_dis

ENH Isomap supports radius-based neighbors (#19794) Co-authored-by: Tom Dupré la Tour <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Thomas J. Fan <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]>

transform

71656844586f212324678804ace73f7a266deb00

scikit-learn

_isomap.py

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

Python

def transform(self, X): check_is_fitted(self) if self.n_neighbors is not None: distances, indices = self.nbrs_.kneighbors(X, return_distance=True) else: distances, indices = self.nbrs_.radius_neighbors(X, return_distance=True) # Create the graph of shortest distances from X to # training data via the nearest neighbors of X. # This can be done as a single array operation, but it potentially # takes a lot of memory. To avoid that, use a loop: n_samples_fit = self.nbrs_.n_samples_fit_ n_queries = distances.shape[0] G_X = np.zeros((n_queries, n_samples_fit)) for i in range(n_queries): G_X[i] = np.min(self.dist_matrix_[indices[i]] + distances[i][:, None], 0) G_X **= 2 G_X *= -0.5 return self.kernel_pca_.transform(G_X)

manim/mobject/svg/svg_mobject.py

def generate_config_style_dict(self) -> dict[str, str]: keys_converting_dict = { "fill": ("color", "fill_color"), "fill-opacity": ("opacity", "fill_opacity"), "stroke": ("color", "stroke_color"), "stroke-opacity": ("opacity", "stroke_opacity"), "stroke-width": ("stroke_width",), } svg_default_dict = self.svg_default result = {} for

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

generate_config_style_dict

309c9d41eb734ca85a7aea5533f88a6d4ee7c944

manim

svg_mobject.py

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

Python

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

test/lib/ansible_test/_internal/bootstrap.py

def get_variables(self): # type: () -> t.Dict[str, t.Union[str, t.List[str]]] return dict(

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.

get_variables

a06fa496d3f837cca3c437ab6e9858525633d147

ansible

bootstrap.py

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

Python

def get_variables(self): # type: () -> t.Dict[str, t.Union[str, t.List[str]]] return dict( bootstrap_type=self.bootstrap_type, controller='yes' if self.controller else '', python_versions=self.python_versions, ssh_key_type=self.ssh_key.KEY_TYPE, ssh_private_key=self.ssh_key.key_contents, ssh_public_key=self.ssh_key.pub_contents, )

python3.10.4/Lib/enum.py

def _create_pseudo_member_(cls, value): pseudo_member = cls._value2member_map_.get(value, None) if pseudo_member is None:

add python 3.10.4 for windows

_create_pseudo_member_

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

enum.py

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

Python

def _create_pseudo_member_(cls, value): pseudo_member = cls._value2member_map_.get(value, None) if pseudo_member is None: # verify all bits are accounted for _, extra_flags = _decompose(cls, value) if extra_flags: raise ValueError("%r is not a valid %s" % (value, cls.__qualname__)) # construct a singleton enum pseudo-member pseudo_member = object.__new__(cls) pseudo_member._name_ = None pseudo_member._value_ = value # use setdefault in case another thread already created a composite # with this value pseudo_member = cls._value2member_map_.setdefault(value, pseudo_member) return pseudo_member

sklearn/preprocessing/_encoders.py

def _identify_infrequent(self, category_count, n_samples, col_idx): if isinstance(self.min_frequency, numbers.Integral): infrequent_mask = category_count < self.min_frequency elif isinstance(self.min_frequency, numbers.Real): min_frequency_abs = n_samples * self.min_frequency infrequent_mask = category_count < min_frequency_abs else: infrequent_mask = np.zeros(category_count.shape[0], dtype=bool) n_current_features = category_count.size - infrequent_mask.sum() + 1 if self.max_categories is not None and self.max_categories < n_current_features: # stable sort to preserve original co

ENH Adds infrequent categories to OneHotEncoder (#16018) * ENH Completely adds infrequent categories * STY Linting * STY Linting * DOC Improves wording * DOC Lint * BUG Fixes * CLN Address comments * CLN Address comments * DOC Uses math to description float min_frequency * DOC Adds comment regarding drop * BUG Fixes method name * DOC Clearer docstring * TST Adds more tests * FIX Fixes mege * CLN More pythonic * CLN Address comments * STY Flake8 * CLN Address comments * DOC Fix * MRG * WIP * ENH Address comments * STY Fix * ENH Use functiion call instead of property * ENH Adds counts feature * CLN Rename variables * DOC More details * CLN Remove unneeded line * CLN Less lines is less complicated * CLN Less diffs * CLN Improves readiabilty * BUG Fix * CLN Address comments * TST Fix * CLN Address comments * CLN Address comments * CLN Move docstring to userguide * DOC Better wrapping * TST Adds test to handle_unknown='error' * ENH Spelling error in docstring * BUG Fixes counter with nan values * BUG Removes unneeded test * BUG Fixes issue * ENH Sync with main * DOC Correct settings * DOC Adds docstring * DOC Immprove user guide * DOC Move to 1.0 * DOC Update docs * TST Remove test * DOC Update docstring * STY Linting * DOC Address comments * ENH Neater code * DOC Update explaination for auto * Update sklearn/preprocessing/_encoders.py Co-authored-by: Roman Yurchak <[email protected]> * TST Uses docstring instead of comments * TST Remove call to fit * TST Spelling error * ENH Adds support for drop + infrequent categories * ENH Adds infrequent_if_exist option * DOC Address comments for user guide * DOC Address comments for whats_new * DOC Update docstring based on comments * CLN Update test with suggestions * ENH Adds computed property infrequent_categories_ * DOC Adds where the infrequent column is located * TST Adds more test for infrequent_categories_ * DOC Adds docstring for _compute_drop_idx * CLN Moves _convert_to_infrequent_idx into its own method * TST Increases test coverage * TST Adds failing test * CLN Careful consideration of dropped and inverse_transform * STY Linting * DOC Adds docstrinb about dropping infrequent * DOC Uses only * DOC Numpydoc * TST Includes test for get_feature_names_out * DOC Move whats new * DOC Address docstring comments * DOC Docstring changes * TST Better comments * TST Adds check for handle_unknown='ignore' for infrequent * CLN Make _infrequent_indices private * CLN Change min_frequency default to None * DOC Adds comments * ENH adds support for max_categories=1 * ENH Describe lexicon ordering for ties * DOC Better docstring * STY Fix * CLN Error when explicity dropping an infrequent category * STY Grammar Co-authored-by: Joel Nothman <[email protected]> Co-authored-by: Roman Yurchak <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

_identify_infrequent

7f0006c8aad1a09621ad19c3db19c3ff0555a183

scikit-learn

_encoders.py

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

Python

def _identify_infrequent(self, category_count, n_samples, col_idx): if isinstance(self.min_frequency, numbers.Integral): infrequent_mask = category_count < self.min_frequency elif isinstance(self.min_frequency, numbers.Real): min_frequency_abs = n_samples * self.min_frequency infrequent_mask = category_count < min_frequency_abs else: infrequent_mask = np.zeros(category_count.shape[0], dtype=bool) n_current_features = category_count.size - infrequent_mask.sum() + 1 if self.max_categories is not None and self.max_categories < n_current_features: # stable sort to preserve original count order smallest_levels = np.argsort(category_count, kind="mergesort")[ : -self.max_categories + 1 ] infrequent_mask[smallest_levels] = True output = np.flatnonzero(infrequent_mask) return output if output.size > 0 else None

airflow/providers/google/cloud/hooks/kubernetes_engine.py

def get_conn(self) -> container_v1.ClusterManagerClient: if self._client is None: credentials = self._get_credentials() self._client = container_v1.ClusterManagerClient(credentials=credent

Extract ClientInfo to module level (#21554)

get_conn

1b568d73e1dfb838a3a0446e3a6063b9f27f04b8

airflow

kubernetes_engine.py

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

Python

def get_conn(self) -> container_v1.ClusterManagerClient: if self._client is None: credentials = self._get_credentials() self._client = container_v1.ClusterManagerClient(credentials=credentials, client_info=CLIENT_INFO) return self._client # To preserve backward compatibility # TODO: remove one day

python3.10.4/Lib/asyncio/coroutines.py

def iscoroutinefunction(func): return (inspect.isco

add python 3.10.4 for windows

iscoroutinefunction

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

coroutines.py

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

Python

def iscoroutinefunction(func): return (inspect.iscoroutinefunction(func) or getattr(func, '_is_coroutine', None) is _is_coroutine) # Prioritize native coroutine check to speed-up # asyncio.iscoroutine. _COROUTINE_TYPES = (types.CoroutineType, types.GeneratorType, collections.abc.Coroutine, CoroWrapper) _iscoroutine_typecache = set()

homeassistant/helpers/storage.py

async def async_load(self) -> _T | None: if self._load_task is None: self._load_task = self.hass.async_create_task(self._async_load()) return await self._load_task

Make Store a generic class (#74617)

async_load

16900dcef15bdb9016feabd12bfec94d61ed4df6

core

storage.py

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

Python

async def async_load(self) -> _T | None: if self._load_task is None: self._load_task = self.hass.async_create_task(self._async_load()) return await self._load_task

homeassistant/components/vera/lock.py

def extra_state_attributes(self) -> dict[str, Any] | None: data = super().extra

Remove vera from mypy ignore list (#64474) * Remove vera from mypy ignore list * Fix pylint

extra_state_attributes

03bf2cdd56eb9a0a9ed56d7afb700d5f7d9cf75e

core

lock.py

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

Python

def extra_state_attributes(self) -> dict[str, Any] | None: data = super().extra_state_attributes or {} last_user = self.vera_device.get_last_user_alert() if last_user is not None: data[ATTR_LAST_USER_NAME] = last_user[1] data[ATTR_LOW_BATTERY] = self.vera_device.get_low_battery_alert() return data

IPython/core/interactiveshell.py

def magic(self, arg_s): warnings.warn( "`magic(...)` is deprecated since IPython 0.13 (warning added in " "8.1), use run_line_magic(magic_name, parameter_s).", DeprecationWarning, stacklevel=2, ) # TODO: should we issue a loud deprecation warning here? magic_name, _, magic_arg_s = arg_s.partition(' ') magic_name = magic_name.lstrip(prefilter.ESC_MAGIC) return self.run_line_magic(magic_name, magic_arg_s, _stack_depth=2) #------------------------------------------------------------------------- # Th

Update old deprecation

magic

e306c9d3f707de42b47a1e7c4c8034d6862fba5f

ipython

interactiveshell.py

https://github.com/ipython/ipython.git

Python

def magic(self, arg_s): warnings.warn( "`magic(...)` is deprecated since IPython 0.13 (warning added in " "8.1), use run_line_magic(magic_name, parameter_s).", DeprecationWarning, stacklevel=2, ) # TODO: should we issue a loud deprecation warning here? magic_name, _, magic_arg_s = arg_s.partition(' ') magic_name = magic_name.lstrip(prefilter.ESC_MAGIC) return self.run_line_magic(magic_name, magic_arg_s, _stack_depth=2) #------------------------------------------------------------------------- # Things related to macros #-------------------------------------------------------------------------

.venv/lib/python3.8/site-packages/pip/_internal/commands/__init__.py

def create_command(name, **kwargs): # type: (str, **Any) -> Command module_path, class_name, summary = commands_dict[name] module = importlib.import_module(module_path) command_class = getattr(module, class_name) command = command_cl

upd; format

create_command

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

__init__.py

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

Python

def create_command(name, **kwargs): # type: (str, **Any) -> Command module_path, class_name, summary = commands_dict[name] module = importlib.import_module(module_path) command_class = getattr(module, class_name) command = command_class(name=name, summary=summary, **kwargs) return command

python/ray/data/dataset.py

def to_pandas_refs(self) -> List[ObjectRef["pandas.DataFrame"]]: block_to_df = cached_remote_fn(_block_to_df) return [block_to_df.remote(b

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

to_pandas_refs

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

dataset.py

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

Python

def to_pandas_refs(self) -> List[ObjectRef["pandas.DataFrame"]]: block_to_df = cached_remote_fn(_block_to_df) return [block_to_df.remote(block) for block in self._blocks.get_blocks()]

@array_function_dispatch(_hvdsplit_dispatcher)

numpy/lib/shape_base.py

def hsplit(ary, indices_or_sections): if _nx.ndim(ary) == 0: raise ValueError('hsplit only works on arrays of 1 or more dimensions') if ary.ndim > 1: return split(ary, indices_or_sections, 1) else: retur

DOC: Include special case in `hsplit` doc (#20974)

hsplit

1cacb2ffb1113167a4995f4f4c183f9a8356c2f0

numpy

shape_base.py

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

Python

def hsplit(ary, indices_or_sections): if _nx.ndim(ary) == 0: raise ValueError('hsplit only works on arrays of 1 or more dimensions') if ary.ndim > 1: return split(ary, indices_or_sections, 1) else: return split(ary, indices_or_sections, 0) @array_function_dispatch(_hvdsplit_dispatcher)

erpnext/accounts/doctype/loyalty_program/test_loyalty_program.py

def get_points_earned(self): def get_returned_amount(): returned_amount = frappe.db.sql( , self.name, ) return abs(flt(returned_amount[0][0])) if returned_amount else 0 lp_details = get_loyalty_program_details_with_points( self.customer, company=self.company, loyalty_program=self.loyalty_program, expiry_date=self.posting_date, include_expired_entry=True, ) if ( lp_details and getdate(lp_details.

style: format code with black

get_points_earned

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

test_loyalty_program.py

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

Python

def get_points_earned(self): def get_returned_amount(): returned_amount = frappe.db.sql( , self.name, ) return abs(flt(returned_amount[0][0])) if returned_amount else 0 lp_details = get_loyalty_program_details_with_points( self.customer, company=self.company, loyalty_program=self.loyalty_program, expiry_date=self.posting_date, include_expired_entry=True, ) if ( lp_details and getdate(lp_details.from_date) <= getdate(self.posting_date) and (not lp_details.to_date or getdate(lp_details.to_date) >= getdate(self.posting_date)) ): returned_amount = get_returned_amount() eligible_amount = flt(self.grand_total) - cint(self.loyalty_amount) - returned_amount points_earned = cint(eligible_amount / lp_details.collection_factor) return points_earned or 0

lib/model/losses_plaid.py

def _get_kernel(self) -> plaidml.tile.Value: coords = np.arange(self._filter_size, dtype="float32") coords -= (self._filter_size - 1) / 2. kernel = np.square(coords) kernel *= -0.5 / np.square(self._filter_sigma) kernel = np.reshape(kernel, (1, -1)) + np.reshape(kernel, (-1, 1)) kernel = K.constant(np.reshape(kernel, (1, -1))) kernel = K.softmax(kernel) kernel = K.reshape(kernel, (

SSIM Updates - Standardize DSSIM Function - Implement MSSIM function for AMD

_get_kernel

04337e0c5efd442c1ce3e2da193dd8749f1e30d8

faceswap

losses_plaid.py

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

Python

def _get_kernel(self) -> plaidml.tile.Value: coords = np.arange(self._filter_size, dtype="float32") coords -= (self._filter_size - 1) / 2. kernel = np.square(coords) kernel *= -0.5 / np.square(self._filter_sigma) kernel = np.reshape(kernel, (1, -1)) + np.reshape(kernel, (-1, 1)) kernel = K.constant(np.reshape(kernel, (1, -1))) kernel = K.softmax(kernel) kernel = K.reshape(kernel, (self._filter_size, self._filter_size, 1, 1)) return kernel

wagtail/core/tests/test_blocks.py

def test_default_default(self): block = blocks.ListBlock(blocks.CharBlock(default='chocolate')) self.assertEqual(list(block.get_default()), ['chocolate']) block.set_name('test_shoppinglistblock')

Implement a ListValue type for ListBlocks

test_default_default

4a848bfb4e3ec1a84a3d36fda577c1ed784de498

wagtail

test_blocks.py

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

Python

def test_default_default(self): block = blocks.ListBlock(blocks.CharBlock(default='chocolate')) self.assertEqual(list(block.get_default()), ['chocolate']) block.set_name('test_shoppinglistblock') js_args = ListBlockAdapter().js_args(block) self.assertEqual(js_args[2], 'chocolate')

pandas/io/formats/xml.py

def convert_empty_str_key(self) -> None:

CLN/DOC: typos (#46328) * fix typos * fix typo * fix typo * fix typo

convert_empty_str_key

a72fa1b400234d3a05342f17c3c0b1e3993a6bd8

pandas

xml.py

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

Python

def convert_empty_str_key(self) -> None: if self.namespaces and "" in self.namespaces.keys(): self.namespaces[None] = self.namespaces.pop("", "default")

wagtail/images/tests/tests.py

def test_get_with_custom_key_using_default_key(self): # Generate signature signature = generate_signature(self.image.id, "fill-800x600") # Get the image response = self.client.get( reverse( "wagtailimages_serve_custom_key", args=(signature, self.image.id, "fill-800x600"),

Reformat with black

test_get_with_custom_key_using_default_key