Datasets:

semeru

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text-code-galeras-code-generation-from-docstring-3k-deduped

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Semeru Lab 7

def writelines(self, lines): self._checkClosed() for line in lines: self.write(line) io.IOBase.register(IOBase)

python3.10.4/Lib/_pyio.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pyio.py

writelines

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

add python 3.10.4 for windows

def _on_slider_update(self, value) -> None: self.scale_var.set(f"{value}%")

lib/training/preview_tk.py

faceswap

Python

7da2cc3dd266aabebf41a31384cc2e0e7e5af6e5

preview_tk.py

_on_slider_update

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

Training - Use custom preview pop-out

def unrank_binary(self, rank, superset): bits = bin(rank)[2:].rjust(len(superset), '0') return Subset.subset_from_bitlist(superset, bits)

sympy/combinatorics/subsets.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

subsets.py

unrank_binary

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

Updated import locations

def lcm_list(seq, *gens, **args): seq = sympify(seq)

sympy/polys/polytools.py

sympy

Python

29e153dd0a70a3fe97c2a9a5f752334e937023c5

polytools.py

lcm_list

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

update some type hints

def _calculate_mean_and_var(self, x, axes, keep_dims): if self.synchronized: return self._sync_calculate_mean_and_var(x, axes, keep_dims) else: return super()._calculate_mean_and_var(x, axes, keep_dims)

keras/layers/normalization/batch_normalization.py

keras

Python

8c401c032b3021f89609eac79bd1c881b9bbc84f

batch_normalization.py

_calculate_mean_and_var

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

Merge `SyncBatchNormalization` into `BatchNormalization` with parameter `use_sync` PiperOrigin-RevId: 482921013

def format_block(self) -> str: if self.summary: block = self.summary else: block = '\n'.join(m.format() for m in self.messages) message = block.strip() # Hack to remove ANSI color reset code from SubprocessError messages. message = message.replace(display.clear, '') return message

test/lib/ansible_test/_internal/test.py

ansible

Python

3eb0485dd92c88cc92152d3656d94492db44b183

test.py

format_block

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

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.

def row(self): return self["row"]

packages/python/plotly/plotly/graph_objs/funnelarea/_domain.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_domain.py

row

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

switch to black .22

def active(self) -> Optional[Scope]: ctx = current_context() return ctx.scope

synapse/logging/scopecontextmanager.py

synapse

Python

6ad012ef89c966cbb3616c1be63d964db48d49ca

scopecontextmanager.py

active

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

More type hints for `synapse.logging` (#13103) Completes type hints for synapse.logging.scopecontextmanager and (partially) for synapse.logging.opentracing.

def to_sql(cls, qc, **kwargs): # we first insert an empty DF in order to create the full table in the database # This also helps to validate the input against pandas # we would like to_sql() to complete only when all rows have been inserted into the database # since the mapping operation is non-blocking, each partition will return an empty DF # so at the end, the blocking operation will be this empty DF to_pandas empty_df = qc.getitem_row_array([0]).to_pandas().head(0) empty_df.to_sql(**kwargs) # so each partition will append its respective DF kwargs["if_exists"] = "append" columns = qc.columns

modin/core/execution/ray/implementations/pandas_on_ray/io/io.py

modin

Python

0faf4675140415e17d4112f9d0d37cfe87770b9e

io.py

to_sql

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

REFACTOR-#3871: move related to pandas functionality into 'PandasOnRayIO' class (#3872) Signed-off-by: Anatoly Myachev <[email protected]>

def align_xlabels(self, axs=None): if axs is None: axs = self.axes axs = [ax for ax in np.ravel(axs) if ax.get_subplotspec() is not None] for ax in axs: _log.debug(' Working on: %s', ax.get_xlabel()) rowspan = ax.get_subplotspec().rowspan pos = ax.xaxis.get_label_position() # top or bottom # Search through other axes for label positions that are same as # this one and that share the appropriate row number. # Add to a grouper associated with each axes of siblings. # This list is inspected in `axis.draw` by # `axis._update_label_position`. for axc in axs: if axc.xaxis.get_label_position() == pos: rowspanc = axc.get_subplotspec().rowspan if (pos == 'top' and rowspan.start == rowspanc.start or pos == 'bottom' and rowspan.stop == rowspanc.stop): # grouper for groups of xlabels to align self._align_label_groups['x'].join(ax, axc)

lib/matplotlib/figure.py

matplotlib

Python

c73f4c455514cf5422d27bf38c93250de8316b21

figure.py

align_xlabels

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

Merge SubplotBase into AxesBase.

def _pad_spatial_dims(x, x_shape, padding, is_conv1d): # Add empty padding for batch and feature dimensions. no_pad = ((0, 0),) padding = tuple(padding) if is_conv1d: padding = no_pad + padding + no_pad # Add empty padding for dummy dimension, too. padding = no_pad + padding + no_pad + no_pad else: padding = no_pad + padding + no_pad x = tf.pad(x, padding) assert len(x.shape) == len(padding) x_shape = tuple(p0 + xs + p1 for xs, (p0, p1) in zip(x_shape, padding)) jax2tf._assert_matching_abstract_shape(x, x_shape) return x, x_shape

jax/experimental/jax2tf/impl_no_xla.py

jax

Python

b22121c0c1579dd5108825becac42d5db1b29276

impl_no_xla.py

_pad_spatial_dims

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

[jax2tf] Fixes for handling of convolutions with shape_polymorphism and enable_xla=False Issue: #11402 Due to a typo we were running no tests for convolutions with shape polymorphism and enable_xla=False. Added a few more tests from #11402 (Thanks @sdenton4). The main issue was that in presence of shape polymorphism we cannot just use `x.shape` for a TF value `x` because it will contain `None` in the place of unknown dimensions. We must use instead the JAX abstract values. This does not fix all issues reported in #11402, there is still the computation of padding or padding="SAME". Commented out the corresponding test.

def _intervals(self, sym): from sympy.solvers.inequalities import _solve_inequality assert isinstance(self, Piecewise)

sympy/functions/elementary/piecewise.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

piecewise.py

_intervals

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

Updated import locations

def subword_index(self, word, w): low = -1 high = -1 for i in range(len(word)-len(w)+1): if word.subword(i, i+len(w)) == w: low = i high = i+len(w) break if low == high == -1: return -1, -1 return low, high

sympy/combinatorics/pc_groups.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

pc_groups.py

subword_index

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

Updated import locations

def _add_unique_metric_name(self, metric_name, metric_fn, output_index): # For multi-output models, prepend the output names to the metric name. if len(self.output_names) > 1: # If we're loading from an already-serialized model, we've already # prepended the output name, and we don't want to do it again. # # Alternatively, we may be receiving a stateless metric (e.g. the string # "accuracy") rather than a `Metric` object, in which case we want to # prepend the output name even if we are loading a serialized model. if not getattr(metric_fn, "_from_serialized", False): metric_name = "%s_%s" % ( self.output_names[output_index], metric_name, ) j = 1 base_metric_name = metric_name while metric_name in self.metrics_names: metric_name = "%s_%d" % (base_metric_name, j) j += 1 return metric_name

keras/engine/training_v1.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_v1.py

_add_unique_metric_name

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def close(self) -> None: return

plugins/convert/writer/opencv.py

faceswap

Python

049314429f71a21e6595e9d27e9e36f6a3479c42

opencv.py

close

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

Convert: Add option to output mask separately for draw-transparent

def get_tables(self) -> Response: return self.native_query( str(text(f).bindparams( bindparam('database', value=self.database, type_=String) ).compile(compile_kwargs={"literal_binds": True})) )

mindsdb/integrations/handlers/teradata_handler/teradata_handler.py

mindsdb

Python

47c5e0ac2d89807f8ff7239d423a3d346bd39a1e

teradata_handler.py

get_tables

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

feat: add teradata integration

def get_project_name(doctype, txt, searchfield, start, page_len, filters): cond = "" if filters and filters.get("customer"): cond = % ( frappe.db.escape(filters.get("customer")) ) fields = get_fields("Project", ["name", "project_name"]) searchfields = frappe.get_meta("Project").get_search_fields() searchfields = " or ".join([field + " like %(txt)s" for field in searchfields]) return frappe.db.sql( .format( fields=", ".join(["`tabProject`.{0}".format(f) for f in fields]), cond=cond, scond=searchfields, match_cond=get_match_cond(doctype), start=start, page_len=page_len, ), {"txt": "%{0}%".format(txt), "_txt": txt.replace("%", "")}, ) @frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext/controllers/queries.py

@frappe.whitelist() @frappe.validate_and_sanitize_search_inputs

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

queries.py

get_project_name

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

style: format code with black

async def test_visit_collection_with_private_pydantic(self): input = PrivatePydantic(x=1) input._y = 2 input._z = 4 result = await visit_collection( input, visit_fn=visit_even_numbers, return_data=False ) assert result is None assert EVEN == {2, 4} result = await visit_collection( input, visit_fn=negative_even_numbers, return_data=True ) assert result == input assert result.__private_attributes__ == input.__private_attributes__ breakpoint() assert result._y == -2 assert result._z == -4

tests/utilities/test_collections.py

prefect

Python

c33f87fc7e0b6fb4714a88b492e7545f4dbd821f

test_collections.py

test_visit_collection_with_private_pydantic

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

get private attrs working

def load_data(self, ds, basedir, variable_manager=None, loader=None): # import here to avoid a dependency loop from ansible.playbook import Playbook from ansible.playbook.play import Play # first, we use the original parent method to correctly load the object # via the load_data/preprocess_data system we normally use for other # playbook objects new_obj = super(PlaybookInclude, self).load_data(ds, variable_manager, loader) all_vars = self.vars.copy() if variable_manager: all_vars.update(variable_manager.get_vars()) templar = Templar(loader=loader, variables=all_vars) # then we use the object to load a Playbook pb = Playbook(loader=loader) file_name = templar.template(new_obj.import_playbook) # check for FQCN resource = _get_collection_playbook_path(file_name) if resource is not None: playbook = resource[1] playbook_collection = resource[2] else: # not FQCN try path playbook = file_name if not os.path.isabs(playbook): playbook = os.path.join(basedir, playbook) # might still be collection playbook playbook_collection = _get_collection_name_from_path(playbook) if playbook_collection: # it is a collection playbook, setup default collections AnsibleCollectionConfig.default_collection = playbook_collection else: # it is NOT a collection playbook, setup adjecent paths AnsibleCollectionConfig.playbook_paths.append(os.path.dirname(os.path.abspath(to_bytes(playbook, errors='surrogate_or_strict')))) pb._load_playbook_data(file_name=playbook, variable_manager=variable_manager, vars=self.vars.copy()) # finally, update each loaded playbook entry with any variables specified # on the included playbook and/or any tags which may have been set for entry in pb._entries: # conditional includes on a playbook need a marker to skip gathering if new_obj.when and isinstance(entry, Play): entry._included_conditional = new_obj.when[:] temp_vars = entry.vars.copy() temp_vars.update(new_obj.vars) param_tags = temp_vars.pop('tags', None) if param_tags is not None: entry.tags.extend(param_tags.split(',')) entry.vars = temp_vars entry.tags = list(set(entry.tags).union(new_obj.tags)) if entry._included_path is None: entry._included_path = os.path.dirname(playbook) # Check to see if we need to forward the conditionals on to the included # plays. If so, we can take a shortcut here and simply prepend them to # those attached to each block (if any) if new_obj.when: for task_block in (entry.pre_tasks + entry.roles + entry.tasks + entry.post_tasks): task_block._when = new_obj.when[:] + task_block.when[:] return pb

lib/ansible/playbook/playbook_include.py

ansible

Python

43153c58310d02223f2cb0964f4255ba1ac4ed53

playbook_include.py

load_data

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

`FieldAttribute`s as descriptors (#73908)

def arraydtick(self): return self["arraydtick"]

packages/python/plotly/plotly/graph_objs/carpet/_aaxis.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_aaxis.py

arraydtick

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

switch to black .22

def to_dict(self) -> Dict[str, any]: input_features = [feat for feat in self.input_features.to_list() if feat["active"]] output_features = [feat for feat in self.output_features.to_list() if feat["active"]] config_dict = { "model_type": self.model_type, "input_features": input_features, "output_features": output_features, "trainer": self.trainer.to_dict(), "preprocessing": self.preprocessing.to_dict(), "hyperopt": self.hyperopt, "defaults": self.defaults.to_dict(), } if self.combiner is not None: config_dict["combiner"] = self.combiner.to_dict() return convert_submodules(config_dict)

ludwig/schema/model_config.py

ludwig

Python

e2dbab9adf85a018bc6279c9538d995a2227f619

model_config.py

to_dict

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

fix: Restrict allowed top-level config keys (#2826) * fix * add ludwig_version * prints * remove extra

def local_rank() -> int:

python/ray/train/train_loop_utils.py

"""Get the local rank of thisrank of the worker on its..block::

ray

Python

0e8eb8aedb3e158da8c3e7378e818ce87ca7813e

train_loop_utils.py

local_rank

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

[AIR] More Train and Tune session deprecations (#28856) Signed-off-by: Amog Kamsetty [email protected] Finish marking train. and tune. session APIs as deprecated

def _build_test_case(self, task_data, host_data): name = '[%s] %s: %s' % (host_data.name, task_data.play, task_data.name) duration = host_data.finish - task_data.start if self._task_relative_path and task_data.path: junit_classname = os.path.relpath(task_data.path, self._task_relative_path) else: junit_classname = task_data.path if self._replace_out_of_tree_path is not None and junit_classname.startswith('../'): junit_classname = self._replace_out_of_tree_path + os.path.basename(junit_classname) if self._task_class == 'true': junit_classname = re.sub(r'\.yml:[0-9]+$', '', junit_classname) if host_data.status == 'included': return TestCase(name=name, classname=junit_classname, time=duration, system_out=str(host_data.result)) res = host_data.result._result rc = res.get('rc', 0) dump = self._dump_results(res, indent=0) dump = self._cleanse_string(dump) if host_data.status == 'ok': return TestCase(name=name, classname=junit_classname, time=duration, system_out=dump) test_case = TestCase(name=name, classname=junit_classname, time=duration) if host_data.status == 'failed': if 'exception' in res: message = res['exception'].strip().split('\n')[-1] output = res['exception'] test_case.errors.append(TestError(message=message, output=output)) elif 'msg' in res: message = res['msg'] test_case.failures.append(TestFailure(message=message, output=dump)) else: test_case.failures.append(TestFailure(message='rc=%s' % rc, output=dump)) elif host_data.status == 'skipped': if 'skip_reason' in res: message = res['skip_reason'] else: message = 'skipped' test_case.skipped = message return test_case

lib/ansible/plugins/callback/junit.py

ansible

Python

fbb5d56bd274c44b193cb95f0230b9352f62aab2

junit.py

_build_test_case

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

ansible-test - Use relative paths in junit output. (#76871) * ansible-test - Use relative paths in junit output. Also fix a traceback in the junit callback during automatic fact gathering. * ansible-test - Handle out-of-tree JUnit paths.

def model_fn(features, labels, mode, params, config): del config hparams = params length = features.length spec = features.spec is_training = mode == tf_estimator.ModeKeys.TRAIN if is_training: onset_labels = labels.onsets offset_labels = labels.offsets velocity_labels = labels.velocities frame_labels = labels.labels frame_label_weights = labels.label_weights if hparams.stop_activation_gradient and not hparams.activation_loss: raise ValueError( 'If stop_activation_gradient is true, activation_loss must be true.') losses = {} with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=is_training): with tf.variable_scope('onsets'): onset_outputs = acoustic_model( spec, hparams, lstm_units=hparams.onset_lstm_units, lengths=length) onset_probs = slim.fully_connected( onset_outputs, constants.MIDI_PITCHES, activation_fn=tf.sigmoid, scope='onset_probs') # onset_probs_flat is used during inference. onset_probs_flat = flatten_maybe_padded_sequences(onset_probs, length) if is_training: onset_labels_flat = flatten_maybe_padded_sequences(onset_labels, length) onset_losses = tf_utils.log_loss(onset_labels_flat, onset_probs_flat) tf.losses.add_loss(tf.reduce_mean(onset_losses)) losses['onset'] = onset_losses with tf.variable_scope('offsets'): offset_outputs = acoustic_model( spec, hparams, lstm_units=hparams.offset_lstm_units, lengths=length) offset_probs = slim.fully_connected( offset_outputs, constants.MIDI_PITCHES, activation_fn=tf.sigmoid, scope='offset_probs') # offset_probs_flat is used during inference. offset_probs_flat = flatten_maybe_padded_sequences(offset_probs, length) if is_training: offset_labels_flat = flatten_maybe_padded_sequences( offset_labels, length) offset_losses = tf_utils.log_loss(offset_labels_flat, offset_probs_flat) tf.losses.add_loss(tf.reduce_mean(offset_losses)) losses['offset'] = offset_losses with tf.variable_scope('velocity'): velocity_outputs = acoustic_model( spec, hparams, lstm_units=hparams.velocity_lstm_units, lengths=length) velocity_values = slim.fully_connected( velocity_outputs, constants.MIDI_PITCHES, activation_fn=None, scope='onset_velocities') velocity_values_flat = flatten_maybe_padded_sequences( velocity_values, length) if is_training: velocity_labels_flat = flatten_maybe_padded_sequences( velocity_labels, length) velocity_loss = tf.reduce_sum( onset_labels_flat * tf.square(velocity_labels_flat - velocity_values_flat), axis=1) tf.losses.add_loss(tf.reduce_mean(velocity_loss)) losses['velocity'] = velocity_loss with tf.variable_scope('frame'): if not hparams.share_conv_features: # TODO(eriche): this is broken when hparams.frame_lstm_units > 0 activation_outputs = acoustic_model( spec, hparams, lstm_units=hparams.frame_lstm_units, lengths=length) activation_probs = slim.fully_connected( activation_outputs, constants.MIDI_PITCHES, activation_fn=tf.sigmoid, scope='activation_probs') else: activation_probs = slim.fully_connected( onset_outputs, constants.MIDI_PITCHES, activation_fn=tf.sigmoid, scope='activation_probs') probs = [] if hparams.stop_onset_gradient: probs.append(tf.stop_gradient(onset_probs)) else: probs.append(onset_probs) if hparams.stop_activation_gradient: probs.append(tf.stop_gradient(activation_probs)) else: probs.append(activation_probs) if hparams.stop_offset_gradient: probs.append(tf.stop_gradient(offset_probs)) else: probs.append(offset_probs) combined_probs = tf.concat(probs, 2) if hparams.combined_lstm_units > 0: outputs = lstm_layer( combined_probs, hparams.combined_lstm_units, lengths=length if hparams.use_lengths else None, stack_size=hparams.combined_rnn_stack_size, use_cudnn=hparams.use_cudnn, bidirectional=hparams.bidirectional) else: outputs = combined_probs frame_probs = slim.fully_connected( outputs, constants.MIDI_PITCHES, activation_fn=tf.sigmoid, scope='frame_probs') frame_probs_flat = flatten_maybe_padded_sequences(frame_probs, length) if is_training: frame_labels_flat = flatten_maybe_padded_sequences(frame_labels, length) frame_label_weights_flat = flatten_maybe_padded_sequences( frame_label_weights, length) if hparams.weight_frame_and_activation_loss: frame_loss_weights = frame_label_weights_flat else: frame_loss_weights = None frame_losses = tf_utils.log_loss( frame_labels_flat, frame_probs_flat, weights=frame_loss_weights) tf.losses.add_loss(tf.reduce_mean(frame_losses)) losses['frame'] = frame_losses if hparams.activation_loss: if hparams.weight_frame_and_activation_loss: activation_loss_weights = frame_label_weights else: activation_loss_weights = None activation_losses = tf_utils.log_loss( frame_labels_flat, flatten_maybe_padded_sequences(activation_probs, length), weights=activation_loss_weights) tf.losses.add_loss(tf.reduce_mean(activation_losses)) losses['activation'] = activation_losses frame_predictions = frame_probs_flat > hparams.predict_frame_threshold onset_predictions = onset_probs_flat > hparams.predict_onset_threshold offset_predictions = offset_probs_flat > hparams.predict_offset_threshold frame_predictions = tf.expand_dims(frame_predictions, axis=0) onset_predictions = tf.expand_dims(onset_predictions, axis=0) offset_predictions = tf.expand_dims(offset_predictions, axis=0) velocity_values = tf.expand_dims(velocity_values_flat, axis=0) metrics_values = metrics.define_metrics( frame_probs=frame_probs, onset_probs=onset_probs, frame_predictions=frame_predictions, onset_predictions=onset_predictions, offset_predictions=offset_predictions, velocity_values=velocity_values, length=features.length, sequence_label=labels.note_sequence, frame_labels=labels.labels, sequence_id=features.sequence_id, hparams=hparams) for label, loss_collection in losses.items(): loss_label = 'losses/' + label metrics_values[loss_label] = loss_collection def predict_sequence():

magenta/models/onsets_frames_transcription/model.py

magenta

Python

f73ff0c91f0159a925fb6547612199bb7c915248

model.py

model_fn

https://github.com/magenta/magenta.git

Explicitly import estimator from tensorflow as a separate import instead of accessing it via tf.estimator and depend on the tensorflow estimator target. PiperOrigin-RevId: 436568278

async def test_reload_entry_with_new_config(hass, tmp_path): config_old = [{"name": "test_old1", "command_topic": "test-topic_old"}] config_yaml_new = { "mqtt": { "light": [{"name": "test_new_modern", "command_topic": "test-topic_new"}] }, # Test deprecated YAML configuration under the platform key # Scheduled to be removed in HA core 2022.12 "light": [ { "platform": "mqtt", "name": "test_new_legacy", "command_topic": "test-topic_new", } ], } await help_test_setup_manual_entity_from_yaml(hass, "light", config_old) assert hass.states.get("light.test_old1") is not None await help_test_entry_reload_with_new_config(hass, tmp_path, config_yaml_new) assert hass.states.get("light.test_old1") is None assert hass.states.get("light.test_new_modern") is not None assert hass.states.get("light.test_new_legacy") is not None @patch("homeassistant.components.mqtt.PLATFORMS", [Platform.LIGHT])

tests/components/mqtt/test_init.py

@patch("homeassistant.components.mqtt.PLATFORMS", [Platform.LIGHT])

core

Python

b3a48389789549b3cb1aabd042310137baccc9b9

test_init.py

test_reload_entry_with_new_config

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

Refactor MQTT tests to use modern platform schema part 1 (#77387) * Tests alarm_control_panel * Tests binary_sensor * Tests button * Tests camera * Tests Climate + corrections default config * Tests cover * Tests device_tracker * Tests fan * Tests humidifier * Fix test_supported_features test fan * Tests init * Tests legacy vacuum * Derive DEFAULT_CONFIG_LEGACY from DEFAULT_CONFIG * Commit suggestion comment changes

def suspend(self): if POSIX: self._send_signal(signal.SIGSTOP) else: # pragma: no cover self._proc.suspend()

psutil/__init__.py

psutil

Python

471b19d2aa799cd73bded23379e864dd35bec2b6

__init__.py

suspend

https://github.com/giampaolo/psutil.git

Fix typos

def _simulate_installation_of(to_install, package_set): # type: (List[InstallRequirement], PackageSet) -> Set[NormalizedName] # Keep track of packages that were installed installed = set() # Modify it as installing requirement_set would (assuming no errors) for inst_req in to_install: abstract_dist = make_distribution_for_install_requirement(inst_req) dist = abstract_dist.get_pkg_resources_distribution() assert dist is not None name = canonicalize_name(dist.key) package_set[name] = PackageDetails(dist.version, dist.requires()) installed.add(name) return installed

.venv/lib/python3.8/site-packages/pip/_internal/operations/check.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

check.py

_simulate_installation_of

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

upd; format

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), )

wagtail/admin/tests/ui/test_tables.py

wagtail

Python

5994cc43dfc5cc1ed891ab78eff3a3bcf56f6830

test_tables.py

test_title_column

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

Allow passing arbitrary link attributes to TitleColumn

def silence_transformers_logs(from_pretrained_func):

haystack/modeling/model/language_model.py

haystack

Python

a59bca366174d9c692fa19750c24d65f47660ef7

language_model.py

silence_transformers_logs

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

Apply black formatting (#2115) * Testing black on ui/ * Applying black on docstores * Add latest docstring and tutorial changes * Create a single GH action for Black and docs to reduce commit noise to the minimum, slightly refactor the OpenAPI action too * Remove comments * Relax constraints on pydoc-markdown * Split temporary black from the docs. Pydoc-markdown was obsolete and needs a separate PR to upgrade * Fix a couple of bugs * Add a type: ignore that was missing somehow * Give path to black * Apply Black * Apply Black * Relocate a couple of type: ignore * Update documentation * Make Linux CI run after applying Black * Triggering Black * Apply Black * Remove dependency, does not work well * Remove manually double trailing commas * Update documentation Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

def num_columns(self): return self.table.num_columns

src/datasets/table.py

datasets

Python

e35be138148333078284b942ccc9ed7b1d826f97

table.py

num_columns

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

Update docs to new frontend/UI (#3690) * WIP: update docs to new UI * make style * Rm unused * inject_arrow_table_documentation __annotations__ * hasattr(arrow_table_method, "__annotations__") * Update task_template.rst * Codeblock PT-TF-SPLIT * Convert loading scripts * Convert docs to mdx * Fix mdx * Add <Tip> * Convert mdx tables * Fix codeblock * Rm unneded hashlinks * Update index.mdx * Redo dev change * Rm circle ci `build_doc` & `deploy_doc` * Rm unneeded files * Update docs reamde * Standardize to `Example::` * mdx logging levels doc * Table properties inject_arrow_table_documentation * ``` to ```py mdx * Add Tips mdx * important,None -> <Tip warning={true}> * More misc * Center imgs * Update instllation page * `setup.py` docs section * Rm imgs since they are in hf.co * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * Update index mdx * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * just `Dataset` obj * Addedversion just italics * Update ReadInstruction doc example syntax * Change docstring for `prepare_for_task` * Chore * Remove `code` syntax from headings * Rm `code` syntax from headings * Hashlink backward compatability * S3FileSystem doc * S3FileSystem doc updates * index.mdx updates * Add darkmode gifs * Index logo img css classes * Index mdx dataset logo img size * Docs for DownloadMode class * Doc DownloadMode table * format docstrings * style * Add doc builder scripts (#3790) * add doc builder scripts * fix docker image * Docs new UI actions no self hosted (#3793) * No self hosted * replace doc injection by actual docstrings * Docstring formatted Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> Co-authored-by: Lysandre Debut <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> * Rm notebooks from docs actions since they dont exi * Update tsting branch * More docstring * Chore * bump up node version * bump up node * ``` -> ```py for audio_process.mdx * Update .github/workflows/build_documentation.yml Co-authored-by: Quentin Lhoest <[email protected]> * Uodate dev doc build * remove run on PR * fix action * Fix gh doc workflow * forgot this change when merging master * Update build doc Co-authored-by: Steven Liu <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Lysandre Debut <[email protected]>

def compute(self) -> Tensor: # self.total maps to the number of observations in preds/target computed during update() if self.total <= 1: logger.warning( ) return torch.tensor(float("nan")) return _r2_score_compute( self.sum_squared_error, self.sum_error, self.residual, self.total, self.adjusted, self.multioutput )

ludwig/modules/metric_modules.py

ludwig

Python

dfdc98caa35f38665dbe045ccff431715e976841

metric_modules.py

compute

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

Update R2 score to handle single sample computation (#2235) * Update R2 scores to handle single sample computation

def convert_to_legacy_optimizer(optimizer): if not isinstance(optimizer, base_optimizer.Optimizer): raise ValueError( "`convert_to_legacy_optimizer` should only be called " "on instances of `tf.keras.optimizers.Optimizer`, but " f"received {optimizer} of type {type(optimizer)}." ) optimizer_name = optimizer.__class__.__name__.lower() config = optimizer.get_config() # Remove fields that only exist in experimental optimizer. keys_to_remove = [ "weight_decay", "use_ema", "ema_momentum", "ema_overwrite_frequency", "jit_compile", "is_legacy_optimizer", ] for key in keys_to_remove: config.pop(key, None) # Learning rate can be a custom LearningRateSchedule, which is stored as # a dict in config, and cannot be deserialized. if isinstance( optimizer._learning_rate, learning_rate_schedule.LearningRateSchedule ): config["learning_rate"] = optimizer._learning_rate legacy_optimizer_config = { "class_name": optimizer_name, "config": config, } return deserialize(legacy_optimizer_config, use_legacy_optimizer=True) @keras_export("keras.optimizers.get")

keras/optimizers/__init__.py

@keras_export("keras.optimizers.get")

keras

Python

5a105aadbdc6fde2c2529280c4789864adbb81c7

__init__.py

convert_to_legacy_optimizer

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

Move new optimizer out of optimizer_experimental/ directory. PiperOrigin-RevId: 488998585

def test_non_existing_file_download(self) -> None: hamlet = self.example_user("hamlet") self.login_user(hamlet) response = self.client_get( f"http://{hamlet.realm.host}/user_uploads/{hamlet.realm_id}/ff/gg/abc.py" ) self.assertEqual(response.status_code, 404) self.assert_in_response("File not found.", response)

zerver/tests/test_upload.py

zulip

Python

5ff4754090259dea52c0554d82eeaf601490f383

test_upload.py

test_non_existing_file_download

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

test_upload: Fix some URLs to uploaded files. Using http://localhost:9991 is incorrect - e.g. messages sent with file urls constructed trigger do_claim_attachments to be called with empty list in potential_path_ids. realm.host should be used in all these places, like in the other tests in the file.

def readable(self): # type: () -> bool return True

.venv/lib/python3.8/site-packages/pip/_internal/network/lazy_wheel.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

lazy_wheel.py

readable

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

upd; format

def _generate_pynsist_config(repo_path, build_path): print('Generate pynsist configuration') installer_cfg_path = os.path.join(build_path, 'installer.cfg') certbot_pkg_path = os.path.join(repo_path, 'certbot') certbot_version = subprocess.check_output([sys.executable, '-c', 'import certbot; print(certbot.__version__)'], universal_newlines=True, cwd=certbot_pkg_path).strip() # If we change the installer name from `certbot-beta-installer-win_amd64.exe`, it should # also be changed in tools/create_github_release.py with open(installer_cfg_path, 'w') as file_h: file_h.write(.format(certbot_version=certbot_version, installer_suffix='win_amd64' if PYTHON_BITNESS == 64 else 'win32', python_bitness=PYTHON_BITNESS, python_version='.'.join(str(item) for item in PYTHON_VERSION))) return installer_cfg_path

windows-installer/windows_installer/construct.py

certbot

Python

f251a13f322e10c530897be31aa07a1199061f10

construct.py

_generate_pynsist_config

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

Remove Windows 2016 environment, generate 64 bit installer (#9202) * Remove Windows 2016 environment, generate 64 bit installer * Add note to changelog * Use win_amd64 as installer suffix * Bump PYTHON_BITNESS to 64 * Require 64 bit Windows for the installer_build job * Update certbot install path * update windows test name * Base installer suffix on PYTHON_BITNESS again * Update changelog to request users uninstall old version

def get_worker_host(pod_args, pod_is_container, head_is_container): # Check if the current pod and head are both containerized on the same host # If so __docker_host__ needs to be advertised as the worker's address to the head worker_host = ( __docker_host__ if (pod_is_container and (head_is_container or in_docker())) and host_is_local(pod_args.host) else pod_args.host ) return worker_host

jina/orchestrate/deployments/__init__.py

jina

Python

ef662b529b2a2eecea7bb99759a9f7b9d86d3062

__init__.py

get_worker_host

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

feat: add grpc health checking (#4779)

def step(self, action_dict): self.resetted = False self.steps += 1 logger.debug( "====> [SUMOTestMultiAgentEnv:step] Episode: %d - Step: %d <====", self.episodes, self.steps, ) dones = {} dones["__all__"] = False shuffled_agents = sorted( action_dict.keys() ) # it may seem not smar to sort something that # may need to be shuffled afterwards, but it # is a matter of consistency instead of using # whatever insertion order was used in the dict if self._config["scenario_config"]["agent_rnd_order"]: # randomize the agent order to minimize SUMO's # insertion queues impact logger.debug("Shuffling the order of the agents.") self.rndgen.shuffle(shuffled_agents) # in-place shuffle # Take action for agent in shuffled_agents: self.agents[agent].step(action_dict[agent], self.simulation) logger.debug("Before SUMO") ongoing_simulation = self.simulation.step( until_end=False, agents=set(action_dict.keys()) ) logger.debug("After SUMO") # end of the episode if not ongoing_simulation: logger.info("Reached the end of the SUMO simulation.") dones["__all__"] = True obs, rewards, infos = {}, {}, {} for agent in action_dict: # check for collisions if self.simulation.collisions[agent] > 0: # punish the agent and remove it from the simulation dones[agent] = True obs[agent] = [0, 0] rewards[agent] = -self.agents[agent].config["max_speed"] # infos[agent] = "Collision" self.simulation.traci_handler.remove(agent, reason=tc.REMOVE_VAPORIZED) else: dones[agent] = agent not in self.simulation.veh_subscriptions obs[agent] = self.get_observation(agent) rewards[agent] = self.get_reward(agent) # infos[agent] = "" logger.debug("Observations: %s", pformat(obs)) logger.debug("Rewards: %s", pformat(rewards)) logger.debug("Dones: %s", pformat(dones)) logger.debug("Info: %s", pformat(infos)) logger.debug("========================================================") return obs, rewards, dones, dones, infos ########################################################################### # ACTIONS & OBSERATIONS SPACE

rllib/examples/simulators/sumo/marlenvironment.py

ray

Python

8e680c483ce326cefc62e44f68ab1a6948b1c3d2

marlenvironment.py

step

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

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

def _peeloff_pi(arg): r pi_coeff = S.Zero rest_terms = [] for a in Add.make_args(arg): K = a.coeff(S.Pi) if K and K.is_rational: pi_coeff += K else: rest_terms.append(a) if pi_coeff is S.Zero: return arg, S.Zero m1 = (pi_coeff % S.Half) m2 = pi_coeff - m1 if m2.is_integer or ((2*m2).is_integer and m2.is_even is False): return Add(*(rest_terms + [m1*pi])), m2 return arg, S.Zero

sympy/functions/elementary/trigonometric.py

sympy

Python

cda8dfe6f45dc5ed394c2f5cda706cd6c729f713

trigonometric.py

_peeloff_pi

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

Improved documentation formatting

def _randint(seed=None): if seed is None: return randint elif isinstance(seed, int): rng.seed(seed) return randint elif is_sequence(seed): seed = list(seed) # make a copy seed.reverse()

sympy/core/random.py

sympy

Python

092c0c6ea1e6f435a2cddb6e6fe723088b73bd81

random.py

_randint

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

Add sympy.core.random to Sphinx

def _get_curr_status(self) -> Tuple[DeploymentStatusInfo, bool]: # TODO(edoakes): we could make this more efficient in steady-state by # having a "healthy" flag that gets flipped if an update or replica # failure happens. target_version = self._target_version target_replica_count = self._target_replicas all_running_replica_cnt = self._replicas.count(states=[ReplicaState.RUNNING]) running_at_target_version_replica_cnt = self._replicas.count( states=[ReplicaState.RUNNING], version=target_version ) failed_to_start_count = self._replica_constructor_retry_counter failed_to_start_threshold = min( MAX_DEPLOYMENT_CONSTRUCTOR_RETRY_COUNT, target_replica_count * 3 ) # Got to make a call to complete current deploy() goal after # start failure threshold reached, while we might still have # pending replicas in current goal. if ( failed_to_start_count >= failed_to_start_threshold and failed_to_start_threshold != 0 ): if running_at_target_version_replica_cnt > 0: # At least one RUNNING replica at target state, partial # success; We can stop tracking constructor failures and # leave it to the controller to fully scale to target # number of replicas and only return as completed once # reached target replica count self._replica_constructor_retry_counter = -1 else: return ( DeploymentStatusInfo( status=DeploymentStatus.FAILED, message=( "The Deployment constructor failed " f"{failed_to_start_count} times in a row. See " "logs for details." ), ), False, ) # If we have pending ops, the current goal is *not* ready. if ( self._replicas.count( states=[ ReplicaState.STARTING, ReplicaState.UPDATING, ReplicaState.RECOVERING, ReplicaState.STOPPING, ] ) == 0 ): # Check for deleting. if target_replica_count == 0 and all_running_replica_cnt == 0: return DeploymentStatusInfo(status=DeploymentStatus.UPDATING), True # Check for a non-zero number of deployments. elif target_replica_count == running_at_target_version_replica_cnt: return DeploymentStatusInfo(status=DeploymentStatus.RUNNING), False return ( DeploymentStatusInfo( status=DeploymentStatus.UPDATING, message=( f"Running replicas of target version: " f"{running_at_target_version_replica_cnt}, target " "replicas: {target_replica_count}" ), ), False, )

python/ray/serve/deployment_state.py

ray

Python

48adb6f7bb335b28fb0fb0d1190bd6c5dfc8ddfa

deployment_state.py

_get_curr_status

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

[serve] Introduce DeploymentStatus, poll for statuses instead of using async goals (#22121)

def _batch_format_to_use(cls) -> BatchFormat: has_pandas_implemented = cls._predict_pandas != Predictor._predict_pandas has_numpy_implemented = cls._predict_numpy != Predictor._predict_numpy if has_pandas_implemented and has_numpy_implemented: return cls.preferred_batch_format() elif has_pandas_implemented: return BatchFormat.PANDAS elif has_numpy_implemented: return BatchFormat.NUMPY else: raise NotImplementedError( f"Predictor {cls.__name__} must implement at least one of " "`_predict_pandas` and `_predict_numpy`." )

python/ray/train/predictor.py

ray

Python

326d84f1149319809191e7887155df7f04f6f46a

predictor.py

_batch_format_to_use

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

[AIR][Predictor] Enable numpy based predictor (#28917) Co-authored-by: Clark Zinzow <[email protected]> Co-authored-by: Amog Kamsetty <[email protected]>

async def read(self) -> discord.Message: msg = await self.queue.get() if msg is None and self.expired: raise ChannelExpiredException() return msg

bot/channel_handlers.py

Open-Assistant

Python

3205491166e190512608bf01754815cadae47a92

channel_handlers.py

read

https://github.com/LAION-AI/Open-Assistant.git

add channel handler async msg routing

def yamlcheck(python): result = json.loads(raw_command([python.path, os.path.join(ANSIBLE_TEST_TARGET_TOOLS_ROOT, 'yamlcheck.py')], capture=True)[0]) if not result['yaml']: return None return result['cloader']

test/lib/ansible_test/_internal/util_common.py

ansible

Python

d19b506ce8c5ee43865b1cead2246fc07cc8902b

util_common.py

yamlcheck

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

ansible-test - Clean up future boilerplate. (#76874) * ansible-test - Clarify need for empty __init__.py * ansible-test - Update code-smell boilerplate. * Update code-smell boilerplate for core. * Update future boilerplate test for ansible-test. All ansible-test code (except for targets) and core-specific sanity tests now use the same boilerplate. The test also checks for unwanted `__future__` and `metaclass` boilerplate. * Relocate target tools to the correct directory. Several tools used on target Python versions were incorrectly placed in the controller directory.

def imag(self): return self["imag"]

packages/python/plotly/plotly/graph_objs/_scattersmith.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_scattersmith.py

imag

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

switch to black .22

def test_get_conn_uri_non_existent_key(self): conn_id = "test_mysql" secret_id = 'airflow/connections/test_postgres' create_param = { 'Name': secret_id, } param = { 'SecretId': secret_id, 'SecretString': 'postgresql://airflow:airflow@host:5432/airflow', } secrets_manager_backend = SecretsManagerBackend() secrets_manager_backend.client.create_secret(**create_param) secrets_manager_backend.client.put_secret_value(**param) assert secrets_manager_backend.get_conn_uri(conn_id=conn_id) is None assert secrets_manager_backend.get_connection(conn_id=conn_id) is None

tests/providers/amazon/aws/secrets/test_secrets_manager.py

airflow

Python

79a2f79ff85a740d6b3680215dc2c9a143ddafbb

test_secrets_manager.py

test_get_conn_uri_non_existent_key

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

cleanup usage of `get_connections()`` from test suite (#23757) The function is deprecated and raises warnings https://github.com/apache/airflow/pull/10192 Replacing the usage with `get_connection()`

def _create_trial_info(self, expr_dir): meta = self._build_trial_meta(expr_dir) self.logger.debug("Create trial for %s" % meta) trial_record = TrialRecord.from_json(meta) trial_record.save()

python/ray/tune/automlboard/backend/collector.py

ray

Python

d2f0c3b2f64b41f6541f6521e98cf3a37577c016

collector.py

_create_trial_info

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

Clean up docstyle in data, ml, and tune packages (#25188)

def image_svg(viz, env): svgstr = viz.svg( svgstr=svgstr, opts=dict(title='Example of SVG Rendering') )

example/components/image.py

visdom

Python

b4115c0337b1bacc876bef1ece97e8fa8b3e2834

image.py

image_svg

https://github.com/fossasia/visdom.git

test: split demo.py into seperate files and functions

def escape_eid(eid): return eid.replace('/', '_')

py/visdom/utils/server_utils.py

visdom

Python

60c90e313e106c0af62339d29eeda0e62823c648

server_utils.py

escape_eid

https://github.com/fossasia/visdom.git

Refactoring server.py into more intentional files

def size(self) -> int | np.signedinteger: return np.prod(self.shape)

dask/array/core.py

dask

Python

1a760229fc18c0c7df41669a13a329a287215819

core.py

size

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

Only import IPython if type checking (#9230)

def icicle(self): return self["icicle"]

packages/python/plotly/plotly/graph_objs/layout/template/_data.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_data.py

icicle

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

switch to black .22

def _async_update_rssi(self) -> None: for ( unique_id, ibeacon_advertisement, ) in self._last_ibeacon_advertisement_by_unique_id.items(): address = unique_id.split("_")[-1] if ( service_info := bluetooth.async_last_service_info( self.hass, address, connectable=False ) ) and service_info.rssi != ibeacon_advertisement.rssi: ibeacon_advertisement.update_rssi(service_info.rssi) async_dispatcher_send( self.hass, signal_seen(unique_id), ibeacon_advertisement, )

homeassistant/components/ibeacon/coordinator.py

core

Python

02731efc4cb3f7ee94b0c08aecc10e3a5209dbf4

coordinator.py

_async_update_rssi

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

Handle iBeacons that broadcast multiple different uuids (#79011) * Handle iBeacons that broadcast multiple different uuids * fix flip-flopping between uuids * naming

def session(): return Session()

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

sessions.py

session

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

upd; format

async def async_update(self, log_errors=True): if not self._async_client: self._async_client = get_async_client( self._hass, verify_ssl=self._verify_ssl ) rendered_headers = template.render_complex(self._headers, parse_result=False) rendered_params = template.render_complex(self._params) _LOGGER.debug("Updating from %s", self._resource) try: response = await self._async_client.request( self._method, self._resource, headers=rendered_headers, params=rendered_params, auth=self._auth, content=self._request_data, timeout=self._timeout, follow_redirects=True, ) self.data = response.text self.headers = response.headers except httpx.TimeoutException as ex: if log_errors: _LOGGER.error("Timeout while fetching data: %s", self._resource) self.last_exception = ex self.data = None self.headers = None except httpx.RequestError as ex: if log_errors: _LOGGER.error( "Error fetching data: %s failed with %s", self._resource, ex ) self.last_exception = ex self.data = None self.headers = None

homeassistant/components/rest/data.py

core

Python

599d61a4da096227ce4d5ba1dc0eaabceea56f49

data.py

async_update

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

Fix payload in rest (#80544)

async def test_auth(hass, aioclient_mock): expiration_time = time.time() + 86400 create_config_entry(expiration_time).add_to_hass(hass) # Prepare to capture credentials in API request. Empty payloads just mean # no devices or structures are loaded. aioclient_mock.get(f"{API_URL}/enterprises/{PROJECT_ID}/structures", json={}) aioclient_mock.get(f"{API_URL}/enterprises/{PROJECT_ID}/devices", json={}) # Prepare to capture credentials for Subscriber captured_creds = None

tests/components/nest/test_api.py

core

Python

c576a68d336bc91fd82c299d9b3e5dfdc1c14960

test_api.py

test_auth

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

Upgrade pytest-aiohttp (#82475) * Upgrade pytest-aiohttp * Make sure executors, tasks and timers are closed Some test will trigger warnings on garbage collect, these warnings spills over into next test. Some test trigger tasks that raise errors on shutdown, these spill over into next test. This is to mimic older pytest-aiohttp and it's behaviour on test cleanup. Discussions on similar changes for pytest-aiohttp are here: https://github.com/pytest-dev/pytest-asyncio/pull/309 * Replace loop with event_loop * Make sure time is frozen for tests * Make sure the ConditionType is not async /home-assistant/homeassistant/helpers/template.py:2082: RuntimeWarning: coroutine 'AsyncMockMixin._execute_mock_call' was never awaited def wrapper(*args, **kwargs): Enable tracemalloc to get traceback where the object was allocated. See https://docs.pytest.org/en/stable/how-to/capture-warnings.html#resource-warnings for more info. * Increase litejet press tests with a factor 10 The times are simulated anyway, and we can't stop the normal event from occuring. * Use async handlers for aiohttp tests/components/motioneye/test_camera.py::test_get_still_image_from_camera tests/components/motioneye/test_camera.py::test_get_still_image_from_camera tests/components/motioneye/test_camera.py::test_get_stream_from_camera tests/components/motioneye/test_camera.py::test_get_stream_from_camera tests/components/motioneye/test_camera.py::test_camera_option_stream_url_template tests/components/motioneye/test_camera.py::test_camera_option_stream_url_template /Users/joakim/src/hass/home-assistant/venv/lib/python3.9/site-packages/aiohttp/web_urldispatcher.py:189: DeprecationWarning: Bare functions are deprecated, use async ones warnings.warn( * Switch to freezegun in modbus tests The tests allowed clock to tick in between steps * Make sure skybell object are fully mocked Old tests would trigger attempts to post to could services: ``` DEBUG:aioskybell:HTTP post https://cloud.myskybell.com/api/v3/login/ Request with headers: {'content-type': 'application/json', 'accept': '*/*', 'x-skybell-app-id': 'd2b542c7-a7e4-4e1e-b77d-2b76911c7c46', 'x-skybell-client-id': '1f36a3c0-6dee-4997-a6db-4e1c67338e57'} ``` * Fix sorting that broke after rebase

def authenticate(request=None, **credentials): username = credentials.get('username') for backend, backend_path in _get_backends(return_tuples=True): # 预先检查，不浪费认证时间 if not backend.username_can_authenticate(username): continue # 原生 backend_signature = inspect.signature(backend.authenticate) try: backend_signature.bind(request, **credentials) except TypeError: # This backend doesn't accept these credentials as arguments. Try the next one. continue try: user = backend.authenticate(request, **credentials) except PermissionDenied: # This backend says to stop in our tracks - this user should not be allowed in at all. break if user is None: continue # 再次检查遇检查中遗漏的用户 if not backend.user_can_authenticate(user): continue # Annotate the user object with the path of the backend. user.backend = backend_path return user # The credentials supplied are invalid to all backends, fire signal user_login_failed.send(sender=__name__, credentials=_clean_credentials(credentials), request=request) auth.authenticate = authenticate

apps/authentication/mixins.py

jumpserver

Python

edfca5eb2486c2f006257723ffeda6f56b170170

mixins.py

authenticate

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

Fix rbac (#7699) * perf: 优化 suggesstion * perf: 修改 migrations * feat: 添加OIDC认证逻辑 * perf: 修改 backend * perf: 优化认证backends * perf: 优化认证backends * perf: 优化CAS认证, 用户多域名进行访问时回调到各自域名 Co-authored-by: ibuler <[email protected]>

def config_test(self) -> None: try: util.run_script([self.conf('ctl'), "-c", self.nginx_conf, "-t"]) except errors.SubprocessError as err: raise errors.MisconfigurationError(str(err))

certbot-nginx/certbot_nginx/_internal/configurator.py

certbot

Python

16aad35d31a887dab157f9d4f5e0fe9218d06064

configurator.py

config_test

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

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

def print_stack(self, *, limit=None, file=None): return base_tasks._task_print_stack(self, limit, file)

python3.10.4/Lib/asyncio/tasks.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

tasks.py

print_stack

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

add python 3.10.4 for windows

def _rename_tmp_file(self) -> None: os.rename(self._video_tmp_file, self._output_filename) logger.debug("Removing temp file") if os.path.isfile(self._video_tmp_file): os.remove(self._video_tmp_file)

plugins/convert/writer/ffmpeg.py

faceswap

Python

60291d49c4da1cd260fbc0b04aa6a312eedfefbb

ffmpeg.py

_rename_tmp_file

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

ffmpeg writer: Create new filename if output pre-exists

def get_tightbbox(self, renderer=None): bbox = self.get_window_extent(renderer) if self.get_clip_on(): clip_box = self.get_clip_box() if clip_box is not None: bbox = Bbox.intersection(bbox, clip_box) clip_path = self.get_clip_path() if clip_path is not None: clip_path = clip_path.get_fully_transformed_path() bbox = Bbox.intersection(bbox, clip_path.get_extents()) return bbox

lib/matplotlib/artist.py

matplotlib

Python

24b16804731d3a724e4ec0984da140b1a6b05c66

artist.py

get_tightbbox

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

MNT: make renderer always optional

async def logout(): confirm_logged_in() profiles = prefect.settings.load_profiles() profiles.update_active_profile() update_profile(PREFECT_API_URL=None, PREFECT_API_KEY=None) profile = prefect.context.get_settings_context() exit_with_success(f"Successfully logged out in profile {profile.name!r}") @workspace_app.command()

src/prefect/cli/cloud.py

@workspace_app.command()

prefect

Python

b0af6cf8b1eaea33ee6809efc770fc041908b7ca

cloud.py

logout

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

Refactor settings context

def test_post_save_change_redirect(self): Person.objects.create(name="John Doe") self.assertEqual(Person.objects.count(), 1) person = Person.objects.all()[0] post_url = reverse( "admin_custom_urls:admin_custom_urls_person_change", args=[person.pk] ) response = self.client.post(post_url, {"name": "Jack Doe"}) self.assertRedirects( response, reverse( "admin_custom_urls:admin_custom_urls_person_delete", args=[person.pk] ), )

tests/admin_custom_urls/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_post_save_change_redirect

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

Refs #33476 -- Reformatted code with Black.

def prefixsrc(self): return self["prefixsrc"]

packages/python/plotly/plotly/graph_objs/table/_cells.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_cells.py

prefixsrc

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

switch to black .22

def get_conditions(filters): filters = frappe._dict(filters) if filters else frappe._dict({}) conditions = frappe._dict({}) conditions.company = filters.company or frappe.defaults.get_user_default("company") conditions.end_date = filters.period_end_date or frappe.utils.today() conditions.start_date = filters.period_start_date or frappe.utils.add_months( conditions.end_date, -1 ) conditions.sales_order = filters.sales_order or [] return conditions

erpnext/selling/report/payment_terms_status_for_sales_order/payment_terms_status_for_sales_order.py

erpnext

Python

1bac7930834d6f688950e836c45305a62e7ecb3f

payment_terms_status_for_sales_order.py

get_conditions

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

feat: Payment Terms Status report - calculate status at runtime for payment terms based on invoices - invoices are used in FIFO method

def call(self, src_files, dest_files): # :var src_done: True if there are no more files from the source left. src_done = False # :var dest_done: True if there are no more files form the dest left. dest_done = False # :var src_take: Take the next source file from the generated files if # true src_take = True # :var dest_take: Take the next dest file from the generated files if # true dest_take = True while True: try: if (not src_done) and src_take: src_file = advance_iterator(src_files) except StopIteration: src_file = None src_done = True try: if (not dest_done) and dest_take: dest_file = advance_iterator(dest_files) except StopIteration: dest_file = None dest_done = True if (not src_done) and (not dest_done): src_take = True dest_take = True compare_keys = self.compare_comp_key(src_file, dest_file) if compare_keys == 'equal': should_sync = self._sync_strategy.determine_should_sync( src_file, dest_file ) if should_sync: yield src_file elif compare_keys == 'less_than': src_take = True dest_take = False should_sync = self._not_at_dest_sync_strategy.determine_should_sync(src_file, None) if should_sync: yield src_file elif compare_keys == 'greater_than': src_take = False dest_take = True should_sync = self._not_at_src_sync_strategy.determine_should_sync(None, dest_file) if should_sync: yield dest_file elif (not src_done) and dest_done: src_take = True should_sync = self._not_at_dest_sync_strategy.determine_should_sync(src_file, None) if should_sync: yield src_file elif src_done and (not dest_done): dest_take = True should_sync = self._not_at_src_sync_strategy.determine_should_sync(None, dest_file) if should_sync: yield dest_file else: break

awscli/customizations/s3/comparator.py

aws-cli

Python

8a16d7d8ce5e3f97fb100af7a960224f7f80137d

comparator.py

call

https://github.com/aws/aws-cli.git

Delete extra whitespace A correction that does not affect the operation.

def _bool_arith_fallback(op_str, a, b): if _has_bool_dtype(a) and _has_bool_dtype(b): if op_str in _BOOL_OP_UNSUPPORTED: warnings.warn( f"evaluating in Python space because the {repr(op_str)} " "operator is not supported by numexpr for the bool dtype, " f"use {repr(_BOOL_OP_UNSUPPORTED[op_str])} instead.", stacklevel=find_stack_level(inspect.currentframe()), ) return True return False

pandas/core/computation/expressions.py

pandas

Python

e94faa23e24c0abf9db74d79cfebe06676577867

expressions.py

_bool_arith_fallback

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

WARN,TST check stacklevel for all warnings (#47998) * use find_stack_level everywhere * fixup * pyx fixups * fixup test_optional_dependency * fixup api * set check_stacklevel=False for some tests * use lru_cache for currentframe * fixup import in __init__ * add missing imports to pyx files * add missing import * fixup import in conversion * revert some __init__ changes * start n=1 * temporarily dont check stacklevel in _check_plot_works * catch some more warnings * dont check stacklevel in check_plot_works * fixup * ignore stacklevel in check_plot_works

def get_file_breaks(self, filename): filename = self.canonic(filename) if filename in self.breaks: return self.breaks[filename] else: return []

python3.10.4/Lib/bdb.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

bdb.py

get_file_breaks

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

add python 3.10.4 for windows

def radius(G, e=None, usebounds=False, weight=None): if usebounds is True and e is None and not G.is_directed(): return _extrema_bounding(G, compute="radius", weight=weight) if e is None: e = eccentricity(G, weight=weight) return min(e.values())

networkx/algorithms/distance_measures.py

networkx

Python

28f78cfa9a386620ee1179582fda1db5ffc59f84

distance_measures.py

radius

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

Add weight distance metrics (#5305) Adds the weight keyword argument to allow users to compute weighted distance metrics e.g. diameter, eccentricity, periphery, etc. The kwarg works in the same fashion as the weight param for shortest paths - i.e. if a string, look up with edge attr by key, if callable, compute the weight via the function. Default is None, meaning return unweighted result which is the current behavior. Co-authored-by: Dan Schult <[email protected]> Co-authored-by: Ross Barnowski <[email protected]>

def write(self, args, path): # type: (CommonConfig, str) -> None # NOTE: Switching the inventory generation to write JSON would be nice, but is currently not possible due to the use of hard-coded inventory filenames. # The name `inventory` works for the POSIX integration tests, but `inventory.winrm` and `inventory.networking` will only parse in INI format. # If tests are updated to use the `INVENTORY_PATH` environment variable, then this could be changed. # Also, some tests detect the test type by inspecting the suffix on the inventory filename, which would break if it were changed. inventory_text = '' for group, hosts in self.host_groups.items(): inventory_text += f'[{group}]\n' for host, variables in hosts.items(): kvp = ' '.join(f'{key}="{value}"' for key, value in variables.items()) inventory_text += f'{host} {kvp}\n' inventory_text += '\n' for group, children in (self.extra_groups or {}).items(): inventory_text += f'[{group}]\n' for child in children: inventory_text += f'{child}\n' inventory_text += '\n' inventory_text = inventory_text.strip() if not args.explain: write_text_file(path, inventory_text + '\n') display.info(f'>>> Inventory\n{inventory_text}', verbosity=3)

test/lib/ansible_test/_internal/host_profiles.py

ansible

Python

fe349a1ccd658d86cfcf10eecdce9d48ece6176c

host_profiles.py

write

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

ansible-test - Enhance the shell command. (#77734) * ansible-test - Add shell --export option. * ansible-test - Support cmd args for shell command. Also allow shell to be used without a valid layout if no delegation is required. * ansible-test - Improve stderr/stdout consistency. By default all output goes to stdout only, with the exception of a fatal error. When using any of the following, all output defaults to stderr instead: * sanity with the `--lint` option -- sanity messages to stdout * coverage analyze -- output to stdout if the output file is `/dev/stdout` * shell -- shell output to stdout This fixes issues two main issues: * Unpredictable output order when using both info and error/warning messages. * Mixing of lint/command/shell output with bootstrapping messages on stdout. * ansible-test - Add changelog fragment.

def ambient_dimension(self): return len(self.args[0])

sympy/geometry/curve.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

curve.py

ambient_dimension

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

Updated import locations

def from_pandas(cls, *args, **kwargs): return cls(pa.Table.from_pandas(*args, **kwargs))

src/datasets/table.py

datasets

Python

e35be138148333078284b942ccc9ed7b1d826f97

table.py

from_pandas

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

Update docs to new frontend/UI (#3690) * WIP: update docs to new UI * make style * Rm unused * inject_arrow_table_documentation __annotations__ * hasattr(arrow_table_method, "__annotations__") * Update task_template.rst * Codeblock PT-TF-SPLIT * Convert loading scripts * Convert docs to mdx * Fix mdx * Add <Tip> * Convert mdx tables * Fix codeblock * Rm unneded hashlinks * Update index.mdx * Redo dev change * Rm circle ci `build_doc` & `deploy_doc` * Rm unneeded files * Update docs reamde * Standardize to `Example::` * mdx logging levels doc * Table properties inject_arrow_table_documentation * ``` to ```py mdx * Add Tips mdx * important,None -> <Tip warning={true}> * More misc * Center imgs * Update instllation page * `setup.py` docs section * Rm imgs since they are in hf.co * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * Update index mdx * Update docs/source/access.mdx Co-authored-by: Steven Liu <[email protected]> * just `Dataset` obj * Addedversion just italics * Update ReadInstruction doc example syntax * Change docstring for `prepare_for_task` * Chore * Remove `code` syntax from headings * Rm `code` syntax from headings * Hashlink backward compatability * S3FileSystem doc * S3FileSystem doc updates * index.mdx updates * Add darkmode gifs * Index logo img css classes * Index mdx dataset logo img size * Docs for DownloadMode class * Doc DownloadMode table * format docstrings * style * Add doc builder scripts (#3790) * add doc builder scripts * fix docker image * Docs new UI actions no self hosted (#3793) * No self hosted * replace doc injection by actual docstrings * Docstring formatted Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> Co-authored-by: Lysandre Debut <[email protected]> Co-authored-by: Mishig Davaadorj <[email protected]> * Rm notebooks from docs actions since they dont exi * Update tsting branch * More docstring * Chore * bump up node version * bump up node * ``` -> ```py for audio_process.mdx * Update .github/workflows/build_documentation.yml Co-authored-by: Quentin Lhoest <[email protected]> * Uodate dev doc build * remove run on PR * fix action * Fix gh doc workflow * forgot this change when merging master * Update build doc Co-authored-by: Steven Liu <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Quentin Lhoest <[email protected]> Co-authored-by: Lysandre Debut <[email protected]>

def divides(p, n): sympy_deprecation_warning( , deprecated_since_version="1.11", active_deprecations_target='deprecated-carmichael-static-methods', ) return n % p == 0

sympy/functions/combinatorial/numbers.py

sympy

Python

b27e2b44626d138bd6ea235fbf114644baa5b144

numbers.py

divides

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

Deprecate redundant static methods

def is_decompressed(self) -> bool: return type(self._pb_body) in [ jina_pb2.DataRequestProto, jina_pb2.DataRequestProtoWoData, ]

jina/types/request/data.py

jina

Python

c3849c6fee4a65a77a82b2cfda9670d727ff0f53

data.py

is_decompressed

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

feat: allow to access parameters of data request wo loading data (#4991)

def model_file_path_key(self): return f"{self.tag_to_agent()[self.value]}_response_model_path"

projects/bb3/agents/module.py

ParlAI

Python

b1acb681207559da56a787ba96e16f0e23697d92

module.py

model_file_path_key

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

Patch 8322 (#4709) * add dafetymix teacher * safety_mix teacher * safety_mix teacher pos and neg teachers * add tests for teacher * add license info * improvement * add task list * add task list and lint * add init.py * adding some patch to director * seeker changes * th * 3 * jing * changes * z and r * remove .opts * fix docs * add contrractions * lint Co-authored-by: Dexter Ju <[email protected]> Co-authored-by: Jing Xu <[email protected]>

def swish(x): return tf.nn.silu(x) @keras_export("keras.activations.relu") @tf.__internal__.dispatch.add_dispatch_support

keras/activations.py

@keras_export("keras.activations.relu") @tf.__internal__.dispatch.add_dispatch_support

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

activations.py

swish

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def item_details(doctype, txt, searchfield, start, page_len, filters): from erpnext.controllers.queries import get_match_cond return frappe.db.sql( % ("%s", searchfield, "%s", get_match_cond(doctype), "%s", "%s"), ((filters or {}).get("delivery_note"), "%%%s%%" % txt, page_len, start), )

erpnext/stock/doctype/packing_slip/packing_slip.py

erpnext

Python

00ef499739959630cd7cf97419fbb6ca59be05f2

packing_slip.py

item_details

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

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]>

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

nni/nas/oneshot/pytorch/base_lightning.py

nni

Python

f77db747d07d5c90a3a9f70bb17f71d4573f329e

base_lightning.py

export_probs

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

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

def clear(self): self._block_partition_refs = [None for _ in self._block_partition_refs] self._block_partition_meta_refs = [ None for _ in self._block_partition_meta_refs ] self._cached_metadata = [None for _ in self._cached_metadata] self._stats_actor = None

python/ray/data/_internal/lazy_block_list.py

ray

Python

b1cad0a1121c06cae55aaed32f2b901b2b725521

lazy_block_list.py

clear

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

[Datasets] Use detached lifetime for stats actor (#25271) The actor handle held at Ray client will become dangling if the Ray cluster is shutdown, and in such case if the user tries to get the actor again it will result in crash. This happened in a real user and blocked them from making progress. This change makes the stats actor detached, and instead of keeping a handle, we access it via its name. This way we can make sure re-create this actor if the cluster gets restarted. Co-authored-by: Ubuntu <[email protected]>

def _read_all_pages(self, endpoint): internal_data = [] while True: resp = self._session.get(endpoint) if resp.status_code == 200: internal_data += resp.json() if "next" in resp.links: endpoint = resp.links["next"]["url"] else: logger.debug("Exiting pagination loop") break else: logger.warning(f"Request to {endpoint} return HTTP {resp.status_code}") break return internal_data

.github/scripts/github.py

paperless-ngx

Python

0b8eff9643c12aa7c766538d8a3e4194934cf44c

github.py

_read_all_pages

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

Extends the cleanup of image versions to the library images and all the registry cache images as well

def lazy(func, *resultclasses):

django/utils/functional.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

functional.py

lazy

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

Refs #33476 -- Reformatted code with Black.

def chromatic_polynomial(G): r import sympy x = sympy.Symbol("x") stack = deque() stack.append(nx.MultiGraph(G, contraction_idx=0)) polynomial = 0 while stack: G = stack.pop() edges = list(G.edges) if not edges: polynomial += (-1) ** G.graph["contraction_idx"] * x ** len(G) else: e = edges[0] C = nx.contracted_edge(G, e, self_loops=True) C.graph["contraction_idx"] = G.graph["contraction_idx"] + 1 C.remove_edge(e[0], e[0]) G.remove_edge(*e) stack.append(G) stack.append(C) return polynomial

networkx/algorithms/polynomials.py

networkx

Python

a3a383f7a90e478df40bc9d746c925f2c94a5a2b

polynomials.py

chromatic_polynomial

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

Chromatic polynomial (#5675) Adds chromatic_polynomial function to the graph polynomials package.

def reidemeister_presentation(fp_grp, H, C=None, homomorphism=False): if not C: C = coset_enumeration_r(fp_grp, H) C.compress(); C.standardize() define_schreier_generators(C, homomorphism=homomorphism) reidemeister_relators(C) gens, rels = C._schreier_generators, C._reidemeister_relators gens, rels = simplify_presentation(gens, rels, change_gens=True) C.schreier_generators = tuple(gens) C.reidemeister_relators = tuple(rels) if homomorphism: _gens = [] for gen in gens: _gens.append(C._schreier_gen_elem[str(gen)]) return C.schreier_generators, C.reidemeister_relators, _gens return C.schreier_generators, C.reidemeister_relators FpGroupElement = FreeGroupElement

sympy/combinatorics/fp_groups.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

fp_groups.py

reidemeister_presentation

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

Updated import locations

def test_preserve_username_case(self): user = User.objects.create_user("forms_test2", "[email protected]", "test") self.assertEqual(user.email, "[email protected]") user = User.objects.create_user("forms_test3", "tesT", "test") self.assertEqual(user.email, "tesT")

tests/auth_tests/test_forms.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

test_forms.py

test_preserve_username_case

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

Refs #33476 -- Reformatted code with Black.

def clean_up_synthetic_data(): shutil.rmtree("audio_files", ignore_errors=True) shutil.rmtree("image_files", ignore_errors=True)

ludwig/utils/triton_utils.py

ludwig

Python

ed8d9cf20843744f18593b22fb6a30eaf5f325eb

triton_utils.py

clean_up_synthetic_data

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

Triton ensemble export (#2251)

def load_weights_only(model, filepath): temp_dir = None archive = None if filepath.endswith(".weights.h5"): # TODO: download file if h5 filepath is remote weights_store = H5IOStore(filepath, mode="r") elif filepath.endswith(".keras"): archive = zipfile.ZipFile(filepath, "r") weights_store = H5IOStore( _VARS_FNAME + ".h5", archive=archive, mode="r" ) _load_state( model, weights_handler=weights_store, assets_handler=None, inner_path="", visited_trackables=set(), ) weights_store.close() if temp_dir and tf.io.gfile.exists(temp_dir): tf.io.gfile.rmtree(temp_dir) if archive: archive.close()

keras/saving/experimental/saving_lib.py

keras

Python

e6f739a31247c43a86c37c33b0b8b2ba6be6a5f6

saving_lib.py

load_weights_only

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

- Add standalone weights file saving/loading functionality. - Switch to in-memory, single write / single read archive saving for better performance. - Remove ability to pick between zipping or not zipping a Keras saved artifact: it's always a zip archive now. PiperOrigin-RevId: 483705728

def cg(A, b, x0=None, *, tol=1e-5, atol=0.0, maxiter=None, M=None): return _isolve(_cg_solve, A=A, b=b, x0=x0, tol=tol, atol=atol, maxiter=maxiter, M=M, check_symmetric=True)

jax/_src/scipy/sparse/linalg.py

jax

Python

998d60dd07d2c33438f606307de0276bcf110428

linalg.py

cg

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

DOC: clarify parameter types in cg/bicgstab

def _get_database_display_str(self, verbosity, database_name): return "'%s'%s" % ( self.connection.alias, (" ('%s')" % database_name) if verbosity >= 2 else "", )

django/db/backends/base/creation.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

creation.py

_get_database_display_str

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

Refs #33476 -- Reformatted code with Black.

def pre_run_hook(self, instance, private_data_dir): instance.log_lifecycle("pre_run") # Before task is started, ensure that job_event partitions exist create_partition(instance.event_class._meta.db_table, start=instance.created)

awx/main/tasks/jobs.py

awx

Python

e87fabe6bb84691472ab67e5da737c9fe515cf3f

jobs.py

pre_run_hook

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

Submit job to dispatcher as part of transaction (#12573) Make it so that submitting a task to the dispatcher happens as part of the transaction. this applies to dispatcher task "publishers" which NOTIFY the pg_notify queue if the transaction is not successful, it will not be sent, as per postgres docs This keeps current behavior for pg_notify listeners practically, this only applies for the awx-manage run_dispatcher service this requires creating a separate connection and keeping it long-lived arbitrary code will occasionally close the main connection, which would stop listening Stop sending the waiting status websocket message this is required because the ordering cannot be maintained with other changes here the instance group data is moved to the running websocket message payload Move call to create_partition from task manager to pre_run_hook mock this in relevant unit tests

def make_dataset(X, y, sample_weight, random_state=None): rng = check_random_state(random_state) # seed should never be 0 in SequentialDataset64 seed = rng.randint(1, np.iinfo(np.int32).max) if X.dtype == np.float32: CSRData = CSRDataset32 ArrayData = ArrayDataset32 else: CSRData = CSRDataset64 ArrayData = ArrayDataset64 if sp.issparse(X): dataset = CSRData(X.data, X.indptr, X.indices, y, sample_weight, seed=seed) intercept_decay = SPARSE_INTERCEPT_DECAY else: X = np.ascontiguousarray(X) dataset = ArrayData(X, y, sample_weight, seed=seed) intercept_decay = 1.0 return dataset, intercept_decay

sklearn/linear_model/_base.py

scikit-learn

Python

b4da3b406379b241bf5e81d0f60bbcddd424625b

_base.py

make_dataset

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

MNT ensure creation of dataset is deterministic in SGD (#19716) Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: Olivier Grisel <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>

def test_big_ndept() -> None: # for multiplier in [1, 10, 100, 1000]: for multiplier in [10]: ndim = 1_000_000 rows = 1 cols = 7 num_entites = 1000 upper = highest() lower = lowest() reference_data = np.random.randint( lower, upper, size=(multiplier * ndim, rows, cols), dtype=np.int32 ) big_ndept = NDEPT( child=reference_data, entities=[ishan() * num_entites], max_vals=make_bounds(reference_data, upper), min_vals=make_bounds(reference_data, lower), ) ndept_metrics = time_and_size_serde(big_ndept) print(multiplier, ndept_metrics) # break assert False

packages/syft/tests/syft/core/tensor/tensor_serde_test.py

PySyft

Python

b2768484a1b5720be74c78335502cd996e0b1895

tensor_serde_test.py

test_big_ndept

https://github.com/OpenMined/PySyft.git

WIP: Having issue with 10M NDEPT serde - options.traversalLimitInWords; Message is too large.

def popitem(self): for key in self.sections(): value = self[key] del self[key] return key, value raise KeyError

python3.10.4/Lib/configparser.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

configparser.py

popitem

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

add python 3.10.4 for windows

def cleanup_cache_files(self) -> Dict[str, int]: self._check_values_type() return {k: dataset.cleanup_cache_files() for k, dataset in self.items()}

src/datasets/dataset_dict.py

datasets

Python

1904d0c0a3a96330d9b870cdca3e9a3a137f2977

dataset_dict.py

cleanup_cache_files

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

Add code examples for DatasetDict (#4245) * 📝 add code examples for DatasetDict * 🖍 apply quentin review

def test_recursion_to_deep(large_import_chain): if is_win: pytest.xfail("Worker is known to crash on Windows.") path, script = large_import_chain mg = modulegraph.ModuleGraph(path) # Increase recursion limit to 5 times of the default. Given the module import chain created above # this still should fail. with pytest.raises(RecursionError): mg.add_script(str(script))

tests/unit/test_recursion_limit.py

pyinstaller

Python

080d95d83bb7f60ce2ec25b0c81c207d303ec46c

test_recursion_limit.py

test_recursion_to_deep

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

Drop Python 3.6 support.

def field_as_sql(self, field, val): if field is None: # A field value of None means the value is raw. sql, params = val, [] elif hasattr(val, "as_sql"): # This is an expression, let's compile it. sql, params = self.compile(val) elif hasattr(field, "get_placeholder"): # Some fields (e.g. geo fields) need special munging before # they can be inserted. sql, params = field.get_placeholder(val, self, self.connection), [val] else: # Return the common case for the placeholder sql, params = "%s", [val] # The following hook is only used by Oracle Spatial, which sometimes # needs to yield 'NULL' and [] as its placeholder and params instead # of '%s' and [None]. The 'NULL' placeholder is produced earlier by # OracleOperations.get_geom_placeholder(). The following line removes # the corresponding None parameter. See ticket #10888. params = self.connection.ops.modify_insert_params(sql, params) return sql, params

django/db/models/sql/compiler.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

compiler.py

field_as_sql

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

Refs #33476 -- Reformatted code with Black.

def psi_n(n, x, m, omega): # sympify arguments n, x, m, omega = map(S, [n, x, m, omega]) nu = m * omega / hbar # normalization coefficient C = (nu/pi)**Rational(1, 4) * sqrt(1/(2**n*factorial(n))) return C * exp(-nu* x**2 /2) * hermite(n, sqrt(nu)*x)

sympy/physics/qho_1d.py

sympy

Python

a0989bcfd26470833cf03737941bfd80f511c745

qho_1d.py

psi_n

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

applied backtick correction to the remainder of the project

async def async_get_hev_cycle(self) -> None: if lifx_features(self.device)["hev"]: await async_execute_lifx(self.device.get_hev_cycle)

homeassistant/components/lifx/coordinator.py

core

Python

dde763418a1c4ee0ecff17de76b6d670670a3bb7

coordinator.py

async_get_hev_cycle

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

Add an RSSI sensor to the LIFX integration (#80993)

def subsets(seq, k=None, repetition=False): r if k is None: if not repetition: return chain.from_iterable((combinations(seq, k) for k in range(len(seq) + 1))) else: return chain.from_iterable((combinations_with_replacement(seq, k) for k in range(len(seq) + 1))) else: if not repetition: return combinations(seq, k) else: return combinations_with_replacement(seq, k)

sympy/utilities/iterables.py

sympy

Python

a25ba231f9c3fd6518f9ae81d1df0323898b9e44

iterables.py

subsets

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

Optimization of subsets() to use return rather than yield from By avoiding the use of yield in the body of iterables.subsets, Python sees it as just a regular function rather than a generator. Hence it can call generators and return the resulting generator objects, avoiding some overhead from a layer of yield from handling.

async def test_doorbell_update_via_pubnub(hass): doorbell_one = await _mock_doorbell_from_fixture(hass, "get_doorbell.json") pubnub = AugustPubNub() await _create_august_with_devices(hass, [doorbell_one], pubnub=pubnub) assert doorbell_one.pubsub_channel == "7c7a6672-59c8-3333-ffff-dcd98705cccc" binary_sensor_k98gidt45gul_name_motion = hass.states.get( "binary_sensor.k98gidt45gul_name_motion" ) assert binary_sensor_k98gidt45gul_name_motion.state == STATE_OFF binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "imagecapture", "data": { "result": { "created_at": "2021-03-16T01:07:08.817Z", "secure_url": "https://dyu7azbnaoi74.cloudfront.net/zip/images/zip.jpeg", }, }, }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_image_capture = hass.states.get( "binary_sensor.k98gidt45gul_name_image_capture" ) assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_ON pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "doorbell_motion_detected", "data": { "event": "doorbell_motion_detected", "image": { "height": 640, "width": 480, "format": "jpg", "created_at": "2021-03-16T02:36:26.886Z", "bytes": 14061, "secure_url": "https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg", "url": "https://dyu7azbnaoi74.cloudfront.net/images/1f8.jpeg", "etag": "09e839331c4ea59eef28081f2caa0e90", }, "doorbellName": "Front Door", "callID": None, "origin": "mars-api", "mutableContent": True, }, }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_motion = hass.states.get( "binary_sensor.k98gidt45gul_name_motion" ) assert binary_sensor_k98gidt45gul_name_motion.state == STATE_ON binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF new_time = dt_util.utcnow() + datetime.timedelta(seconds=40) native_time = datetime.datetime.now() + datetime.timedelta(seconds=40) with patch( "homeassistant.components.august.binary_sensor._native_datetime", return_value=native_time, ): async_fire_time_changed(hass, new_time) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_image_capture = hass.states.get( "binary_sensor.k98gidt45gul_name_image_capture" ) assert binary_sensor_k98gidt45gul_name_image_capture.state == STATE_OFF pubnub.message( pubnub, Mock( channel=doorbell_one.pubsub_channel, timetoken=_timetoken(), message={ "status": "buttonpush", }, ), ) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_ON new_time = dt_util.utcnow() + datetime.timedelta(seconds=40) native_time = datetime.datetime.now() + datetime.timedelta(seconds=40) with patch( "homeassistant.components.august.binary_sensor._native_datetime", return_value=native_time, ): async_fire_time_changed(hass, new_time) await hass.async_block_till_done() binary_sensor_k98gidt45gul_name_ding = hass.states.get( "binary_sensor.k98gidt45gul_name_ding" ) assert binary_sensor_k98gidt45gul_name_ding.state == STATE_OFF

tests/components/august/test_binary_sensor.py

core

Python

ea5b18c1ef16b64cd7916f2540692ab5de2d2edf

test_binary_sensor.py

test_doorbell_update_via_pubnub

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

Split august motion and image capture binary sensors (#62154)

def get_span_dict(span_list): strip_prefix = "python.ray.tests." span_names = {} for span in span_list: span_name = span["name"] if span_name.startswith(strip_prefix): span_name = span_name[len(strip_prefix) :] if span_name in span_names: span_names[span_name] += 1 else: span_names[span_name] = 1 return span_names

python/ray/tests/test_tracing.py

ray

Python

2cdb76789e6d0d59928891a4b520f588b7844edf

test_tracing.py

get_span_dict

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

Bump pytest from 5.4.3 to 7.0.1 (#26334) See #23676 for context. This is another attempt at that as I figured out what's going wrong in `bazel test`. Supersedes #24828. Now that there are Python 3.10 wheels for Ray 1.13 and this is no longer a blocker for supporting Python 3.10, I still want to make `bazel test //python/ray/tests/...` work for developing in a 3.10 env, and make it easier to add Python 3.10 tests to CI in future. The change contains three commits with rather descriptive commit message, which I repeat here: Pass deps to py_test in py_test_module_list Bazel macro py_test_module_list takes a `deps` argument, but completely ignores it instead of passes it to `native.py_test`. Fixing that as we are going to use deps of py_test_module_list in BUILD in later changes. cpp/BUILD.bazel depends on the broken behaviour: it deps-on a cc_library from a py_test, which isn't working, see upstream issue: https://github.com/bazelbuild/bazel/issues/701. This is fixed by simply removing the (non-working) deps. Depend on conftest and data files in Python tests BUILD files Bazel requires that all the files used in a test run should be represented in the transitive dependencies specified for the test target. For py_test, it means srcs, deps and data. Bazel enforces this constraint by creating a "runfiles" directory, symbolic links files in the dependency closure and run the test in the "runfiles" directory, so that the test shouldn't see files not in the dependency graph. Unfortunately, the constraint does not apply for a large number of Python tests, due to pytest (>=3.9.0, <6.0) resolving these symbolic links during test collection and effectively "breaks out" of the runfiles tree. pytest >= 6.0 introduces a breaking change and removed the symbolic link resolving behaviour, see pytest pull request https://github.com/pytest-dev/pytest/pull/6523 for more context. Currently, we are underspecifying dependencies in a lot of BUILD files and thus blocking us from updating to newer pytest (for Python 3.10 support). This change hopefully fixes all of them, and at least those in CI, by adding data or source dependencies (mostly for conftest.py-s) where needed. Bump pytest version from 5.4.3 to 7.0.1 We want at least pytest 6.2.5 for Python 3.10 support, but not past 7.1.0 since it drops Python 3.6 support (which Ray still supports), thus the version constraint is set to <7.1. Updating pytest, combined with earlier BUILD fixes, changed the ground truth of a few error message based unit test, these tests are updated to reflect the change. There are also two small drive-by changes for making test_traceback and test_cli pass under Python 3.10. These are discovered while debugging CI failures (on earlier Python) with a Python 3.10 install locally. Expect more such issues when adding Python 3.10 to CI.

async def dry_run(self, empty, context) -> jina_pb2.StatusProto: from docarray import DocumentArray from jina.clients.request import request_generator from jina.enums import DataInputType from jina.serve.executors import __dry_run_endpoint__ da = DocumentArray() try: req_iterator = request_generator( exec_endpoint=__dry_run_endpoint__, data=da, data_type=DataInputType.DOCUMENT, )

jina/serve/runtimes/gateway/grpc/__init__.py

async def dry_run(self, empty, context) -> jina_pb2.StatusProto: """ Process the the call requested by having a dry run call to every Executor in the graph :param empty: The service expects an empty protobuf message :param context: grpc context :returns: the response request """ from docarray import DocumentArray from jina.clients.request import request_generator from jina.enums import DataInputType from jina.serve.executors import __dry_run_endpoint__ da = DocumentArray() try: req_iterator = request_generator( exec_endpoint=__dry_run_endpoint__, data=da, data_type=DataInputType.DOCUMENT, )

jina

Python

ef662b529b2a2eecea7bb99759a9f7b9d86d3062

__init__.py

dry_run

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