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semeru

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Semeru Lab 7

tests/test_datasets/test_pipelines/utils.py

def check_result_same(results, pipeline_results, check_keys): for key in check_keys: if results.get(key, None) is None: continue if isinstance(results[key], (BitmapMasks, PolygonMasks)): assert_allclose(pipeline_results[key].to_ndarray(), results[key].to_ndarray()) else: assert_allclose(pipeline_

Refactor Autoaugment

check_result_same

6146a83cb898110ba0170f956903b74741a6ac37

mmdetection

utils.py

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

Python

def check_result_same(results, pipeline_results, check_keys): for key in check_keys: if results.get(key, None) is None: continue if isinstance(results[key], (BitmapMasks, PolygonMasks)): assert_allclose(pipeline_results[key].to_ndarray(), results[key].to_ndarray()) else: assert_allclose(pipeline_results[key], results[key])

scripts/release.py

def get_rasa_sdk_version() -> Text: dependencies_filename = "pyproject.toml" toml_data = toml.load(project_root() / dependencies_filename) try:

add changelog for 3.0.6 release (#10771) * add changelog * update poetry.lock

get_rasa_sdk_version

40d5139b3ec136b82e28cdc80d99076b9e6b1e6a

rasa

release.py

https://github.com/RasaHQ/rasa.git

Python

def get_rasa_sdk_version() -> Text: dependencies_filename = "pyproject.toml" toml_data = toml.load(project_root() / dependencies_filename) try: sdk_version = toml_data["tool"]["poetry"]["dependencies"]["rasa-sdk"] return sdk_version[1:].strip() except AttributeError: raise Exception(f"Failed to find Rasa SDK version in {dependencies_filename}")

tests/handlers/test_e2e_room_keys.py

def test_update_omitted_version(self) -> None: version = self.get_success( self.handler.create_version( self.local_user, { "algorithm": "m.megolm_backup.v1", "auth_data": "first_version_auth_data", }, ) ) self.assertEqual(version, "1") self.get_success( self.handler.update_version( self.local_user, version, { "algorithm": "m.megolm_backup.v1", "auth_data": "revised_first_version_auth_data", }, ) ) # check we can retrieve it as the current version res = self.get_success(self.handler.get_version_info(self.local_user)) del res["etag"] # etag is opaque, so don't test i

Add missing type hints to tests.handlers. (#14680) And do not allow untyped defs in tests.handlers.

test_update_omitted_version

652d1669c5a103b1c20478770c4aaf18849c09a3

synapse

test_e2e_room_keys.py

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

Python

def test_update_omitted_version(self) -> None: version = self.get_success( self.handler.create_version( self.local_user, { "algorithm": "m.megolm_backup.v1", "auth_data": "first_version_auth_data", }, ) ) self.assertEqual(version, "1") self.get_success( self.handler.update_version( self.local_user, version, { "algorithm": "m.megolm_backup.v1", "auth_data": "revised_first_version_auth_data", }, ) ) # check we can retrieve it as the current version res = self.get_success(self.handler.get_version_info(self.local_user)) del res["etag"] # etag is opaque, so don't test its contents self.assertDictEqual( res, { "algorithm": "m.megolm_backup.v1", "auth_data": "revised_first_version_auth_data", "version": version, "count": 0, }, )

sympy/geometry/plane.py

def parameter_value(self, other, u, v=None): from sympy.geometry.point import Point if not isinstance(other, GeometryEntity): other = Point(other, dim=self.ambient_dimension) if not isinstance(other, Point): raise ValueError("o

Updated import locations

parameter_value

498015021131af4dbb07eb110e5badaba8250c7b

sympy

plane.py

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

Python

def parameter_value(self, other, u, v=None): from sympy.geometry.point import Point if not isinstance(other, GeometryEntity): other = Point(other, dim=self.ambient_dimension) if not isinstance(other, Point): raise ValueError("other must be a point") if other == self.p1: return other if isinstance(u, Symbol) and v is None: delta = self.arbitrary_point(u) - self.p1 eq = delta - (other - self.p1).unit sol = solve(eq, u, dict=True) elif isinstance(u, Symbol) and isinstance(v, Symbol): pt = self.arbitrary_point(u, v) sol = solve(pt - other, (u, v), dict=True) else: raise ValueError('expecting 1 or 2 symbols') if not sol: raise ValueError("Given point is not on %s" % func_name(self)) return sol[0] # {t: tval} or {u: uval, v: vval}

@register

ppdet/modeling/architectures/pose3d_metro.py

def orthographic_projection(X, camera): camera = camera.reshape((-1, 1, 3)) X_trans = X[:, :, :2] + camera[:, :, 1:] shape = paddle.shape(X_trans) X_2d = (camera[:, :, 0] * X_trans.reshape((shape[0], -1))).reshape(shape) return X_2d

pose3d metro modeling (#6612) * pose3d metro modeling * delete extra comments

orthographic_projection

d4e34fe165c09db65fd00113708be1b711ac957c

PaddleDetection

pose3d_metro.py

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

Python

def orthographic_projection(X, camera): camera = camera.reshape((-1, 1, 3)) X_trans = X[:, :, :2] + camera[:, :, 1:] shape = paddle.shape(X_trans) X_2d = (camera[:, :, 0] * X_trans.reshape((shape[0], -1))).reshape(shape) return X_2d @register

python/ray/util/sgd/torch/worker_group.py

def _load_state_id(self, state_id): remote_calls = [ worker.load_state_stream.remote(state_id) for worker in self.remote_workers ]

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

_load_state_id

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

worker_group.py

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

Python

def _load_state_id(self, state_id): remote_calls = [ worker.load_state_stream.remote(state_id) for worker in self.remote_workers ] return remote_calls

sympy/geometry/line.py

def __new__(cls, p1, pt=None, angle=None, **kwargs): p1 = Point(p1, dim=2) if pt is not None and angle is None: try: p2 = Point(pt, dim=2) except (NotImplementedError, TypeError, ValueError): raise ValueError(filldedent()) if p1 == p2: raise ValueError('A Ray requires two distinct points.') elif angle is not None and pt is None: # we need to know if the angle is an odd multiple of pi/2 angle = sympify(angle) c = _pi_coeff(angle) p2 = None if c is not None: if c.is_Rational: if c.q == 2: if c.p == 1: p2 = p1 + Point(0, 1) elif c.p == 3: p2 = p1 + Point(0, -1) elif c.q == 1: if c.p == 0: p2 = p1 + Point(1, 0) elif c.p == 1: p2 = p1 + Point(-1, 0) if p2 is None: c *= S.Pi else: c = angle % (2*S.Pi) if not p2: m = 2*c/S.Pi left = And(1 < m, m < 3) # is it in quadrant 2 or 3? x = Piecewise((-1, left), (Piecewise((0, Eq(m % 1, 0)), (1, True)), True)) y = Piecewise((-tan(c), left), (Piecewise((1, Eq(m, 1)), (-1, Eq(m, 3)),

Use sympify less

__new__

2a1afca9477eb781f16d5d6b63fa37abed7740a3

sympy

line.py

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

Python

def __new__(cls, p1, pt=None, angle=None, **kwargs): p1 = Point(p1, dim=2) if pt is not None and angle is None: try: p2 = Point(pt, dim=2) except (NotImplementedError, TypeError, ValueError): raise ValueError(filldedent()) if p1 == p2: raise ValueError('A Ray requires two distinct points.') elif angle is not None and pt is None: # we need to know if the angle is an odd multiple of pi/2 angle = sympify(angle) c = _pi_coeff(angle) p2 = None if c is not None: if c.is_Rational: if c.q == 2: if c.p == 1: p2 = p1 + Point(0, 1) elif c.p == 3: p2 = p1 + Point(0, -1) elif c.q == 1: if c.p == 0: p2 = p1 + Point(1, 0) elif c.p == 1: p2 = p1 + Point(-1, 0) if p2 is None: c *= S.Pi else: c = angle % (2*S.Pi) if not p2: m = 2*c/S.Pi left = And(1 < m, m < 3) # is it in quadrant 2 or 3? x = Piecewise((-1, left), (Piecewise((0, Eq(m % 1, 0)), (1, True)), True)) y = Piecewise((-tan(c), left), (Piecewise((1, Eq(m, 1)), (-1, Eq(m, 3)), (tan(c), True)), True)) p2 = p1 + Point(x, y) else: raise ValueError('A 2nd point or keyword "angle" must be used.') return LinearEntity2D.__new__(cls, p1, p2, **kwargs)

test/lib/ansible_test/_internal/delegation.py

def delegate_command(args, host_state, exclude, require): # type: (EnvironmentConfig, HostState, t.List[str], t.List[str]) -> None con = host_state.controller_profile.get_origin_controller_connection() working_directory = host_state.controller_profile.get_working_directory() host_delegation = not isinstance(args.controller, OriginConfig) if host_delegation: if data_context().content.collection: content_root = os.path.join(working_directory, data_context().content.collection.directory) else: content_root = os.path.join(working_directory, 'ansible') ansible_bin_path = os.path.join(working_directory, 'ansible', 'bin') with tempfile.NamedTemporaryFile(prefix='ansible-source-', suffix='.tgz') as payl

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.

delegate_command

a06fa496d3f837cca3c437ab6e9858525633d147

ansible

delegation.py

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

Python

def delegate_command(args, host_state, exclude, require): # type: (EnvironmentConfig, HostState, t.List[str], t.List[str]) -> None con = host_state.controller_profile.get_origin_controller_connection() working_directory = host_state.controller_profile.get_working_directory() host_delegation = not isinstance(args.controller, OriginConfig) if host_delegation: if data_context().content.collection: content_root = os.path.join(working_directory, data_context().content.collection.directory) else: content_root = os.path.join(working_directory, 'ansible') ansible_bin_path = os.path.join(working_directory, 'ansible', 'bin') with tempfile.NamedTemporaryFile(prefix='ansible-source-', suffix='.tgz') as payload_file: create_payload(args, payload_file.name) con.extract_archive(chdir=working_directory, src=payload_file) else: content_root = working_directory ansible_bin_path = ANSIBLE_BIN_PATH command = generate_command(args, host_state.controller_profile.python, ansible_bin_path, content_root, exclude, require) if isinstance(con, SshConnection): ssh = con.settings else: ssh = None options = [] if isinstance(args, IntegrationConfig) and args.controller.is_managed and all(target.is_managed for target in args.targets): if not args.allow_destructive: options.append('--allow-destructive') with support_container_context(args, ssh) as containers: # type: t.Optional[ContainerDatabase] if containers: options.extend(['--containers', json.dumps(containers.to_dict())]) # Run unit tests unprivileged to prevent stray writes to the source tree. # Also disconnect from the network once requirements have been installed. if isinstance(args, UnitsConfig) and isinstance(con, DockerConnection): pytest_user = 'pytest' writable_dirs = [ os.path.join(content_root, ResultType.JUNIT.relative_path), os.path.join(content_root, ResultType.COVERAGE.relative_path), ] con.run(['mkdir', '-p'] + writable_dirs) con.run(['chmod', '777'] + writable_dirs) con.run(['chmod', '755', working_directory]) con.run(['chmod', '644', os.path.join(content_root, args.metadata_path)]) con.run(['useradd', pytest_user, '--create-home']) con.run(insert_options(command, options + ['--requirements-mode', 'only'])) container = con.inspect() networks = container.get_network_names() if networks is not None: for network in networks: con.disconnect_network(network) else: display.warning('Network disconnection is not supported (this is normal under podman). ' 'Tests will not be isolated from the network. Network-related tests may misbehave.') options.extend(['--requirements-mode', 'skip']) con.user = pytest_user success = False try: con.run(insert_options(command, options)) success = True finally: if host_delegation: download_results(args, con, content_root, success)

dask/dataframe/io/tests/test_parquet.py

def test_in_predicate_requires_an_iterable(tmp_path, engine, filter_value): path = tmp_path / "gh_8720_pandas.parquet" df = pd.DataFrame( {"A": [1, 2, 3, 4], "B": [1, 1, 2, 2]}, ) df.to_parquet(path, engine=engine) with pytest.raises(TypeError, match="Value of 'in' filter"): dd.read_parquet(path, engine=engine, filters=filter_value) # pandas to_parquet outputs a single file, dask outputs a folder with global # metadata that changes the filtering code path ddf = dd.from_pandas(df, npartitions=2) path = tmp_path / "gh_8720_dask.parquet" ddf.to_parquet(path, engine=engine) with pytest.raises(TypeError, match=

Check that values for the `in` predicate in `read_parquet` are correct (#8846) As reported in #8720, the _flatten_filters function required the value to be hashable. This implicitly required the value to be a tuple, although lists and sets would also be appropriate since they support the 'in' operation. _flatten_filters was only used to determine which columns should be filtered, so it can be refactored and removed. The 'in' predicate also requires that the value be iterable. Non-iterable values are now caught and an appropriate message is raised indicating what the user needs to change. This must be done in two places to support both fastparquet and pyarrow.

test_in_predicate_requires_an_iterable

9000abdd43772a82dcbf7999c5126b571d698d8a

dask

test_parquet.py

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

Python

def test_in_predicate_requires_an_iterable(tmp_path, engine, filter_value): path = tmp_path / "gh_8720_pandas.parquet" df = pd.DataFrame( {"A": [1, 2, 3, 4], "B": [1, 1, 2, 2]}, ) df.to_parquet(path, engine=engine) with pytest.raises(TypeError, match="Value of 'in' filter"): dd.read_parquet(path, engine=engine, filters=filter_value) # pandas to_parquet outputs a single file, dask outputs a folder with global # metadata that changes the filtering code path ddf = dd.from_pandas(df, npartitions=2) path = tmp_path / "gh_8720_dask.parquet" ddf.to_parquet(path, engine=engine) with pytest.raises(TypeError, match="Value of 'in' filter"): dd.read_parquet(path, engine=engine, filters=filter_value)

test/lib/ansible_test/_internal/config.py

def only_targets(self, target_type): # type: (t.Type[THostConfig]) -> t.List[THostConfig] if not self.targets: raise Exception('There must be one or more targets.') assert type_guard(self.targets, targ

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.

only_targets

a06fa496d3f837cca3c437ab6e9858525633d147

ansible

config.py

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

Python

def only_targets(self, target_type): # type: (t.Type[THostConfig]) -> t.List[THostConfig] if not self.targets: raise Exception('There must be one or more targets.') assert type_guard(self.targets, target_type) return t.cast(t.List[THostConfig], self.targets)

lib/matplotlib/widgets.py

def _get_animated_artists(self): return tuple([a for ax_ in self.ax.get_figure().get_axes() for a in ax_.g

Fix z_order

_get_animated_artists

334cc617b8ed3b6b4ec6cb64ff16a040ef454149

matplotlib

widgets.py

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

Python

def _get_animated_artists(self): return tuple([a for ax_ in self.ax.get_figure().get_axes() for a in ax_.get_children() if a.get_animated() and a not in self.artists])

lib/mpl_toolkits/axisartist/axislines.py

def new_gridlines(self, ax): g

Get rcParams from mpl

new_gridlines

438d30b227b1fef7e8733578f851e76a8e360f24

matplotlib

axislines.py

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

Python

def new_gridlines(self, ax): gridlines = GridlinesCollection( None, transform=ax.transData, colors=mpl.rcParams['grid.color'], linestyles=mpl.rcParams['grid.linestyle'], linewidths=mpl.rcParams['grid.linewidth']) ax._set_artist_props(gridlines) gridlines.set_grid_helper(self) ax.axes._set_artist_props(gridlines) # gridlines.set_clip_path(self.axes.patch) # set_clip_path need to be deferred after Axes.cla is completed. # It is done inside the cla. return gridlines

pipenv/patched/notpip/_vendor/pygments/util.py

def duplicates_removed(it, already_seen=()): lst = [] seen = set() for i in it: if i in seen or i in already_seen: continue lst.append(i) seen.

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

duplicates_removed

f3166e673fe8d40277b804d35d77dcdb760fc3b3

pipenv

util.py

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

Python

def duplicates_removed(it, already_seen=()): lst = [] seen = set() for i in it: if i in seen or i in already_seen: continue lst.append(i) seen.add(i) return lst

numpy/ma/extras.py

def masked_all(shape, dtype=float): a = masked_array(np.empty(shape, dtype),

DOC: fix data type of parameter shape (#21251) `np.ma.masked_all` uses `np.empty` under the hood, so the parameter description for shape in `masked_all` should be updated to match that of `np.empty`. Relevant issue: #21203

masked_all

119bf865b15747bea815ec3ced10e2bbc1ba8de1

numpy

extras.py

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

Python

def masked_all(shape, dtype=float): a = masked_array(np.empty(shape, dtype), mask=np.ones(shape, make_mask_descr(dtype))) return a

@not_implemented_for("directed")

networkx/algorithms/centrality/closeness.py

def closeness_centrality(G, u=None, distance=None, wf_improved=True): r if G.is_directed(): G = G.reverse() # create a reversed graph view if distance is not None: # use Dijkstra's algorithm with specified attribute as edge weight path_length = functools.partial( nx.single_source_dijkstra_path_length, weight=distance ) else: path_length = nx.single_source_shortest_path_length if u is None: nodes = G.nodes

added example to closeness.py (#5645) * added example on closeness * docstring improvement

closeness_centrality

58b63cb57cd1747c23611ee0b46991a5be2db751

networkx

closeness.py

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

Python

def closeness_centrality(G, u=None, distance=None, wf_improved=True): r if G.is_directed(): G = G.reverse() # create a reversed graph view if distance is not None: # use Dijkstra's algorithm with specified attribute as edge weight path_length = functools.partial( nx.single_source_dijkstra_path_length, weight=distance ) else: path_length = nx.single_source_shortest_path_length if u is None: nodes = G.nodes else: nodes = [u] closeness_centrality = {} for n in nodes: sp = path_length(G, n) totsp = sum(sp.values()) len_G = len(G) _closeness_centrality = 0.0 if totsp > 0.0 and len_G > 1: _closeness_centrality = (len(sp) - 1.0) / totsp # normalize to number of nodes-1 in connected part if wf_improved: s = (len(sp) - 1.0) / (len_G - 1) _closeness_centrality *= s closeness_centrality[n] = _closeness_centrality if u is not None: return closeness_centrality[u] else: return closeness_centrality @not_implemented_for("directed")

synapse/storage/databases/main/event_push_actions.py

async def _remove_old_push_actions_that_have_rotated(self) -> None: # We want to clear out anything that is older than a day that *has* already # been rotated. rotated_upto_stream_ordering = await self.db_pool.simple_select_one_onecol( table="event_push_summary_stream_ordering", keyvalues={}, retcol="stream_ordering",

Clarifications for event push action processing. (#13485) * Clarifies comments. * Fixes an erroneous comment (about return type) added in #13455 (ec24813220f9d54108924dc04aecd24555277b99). * Clarifies the name of a variable. * Simplifies logic of pulling out the latest join for the requesting user.

_remove_old_push_actions_that_have_rotated

46bd7f4ed9020bbed459c03a11c26d7f7c3093b0

synapse

event_push_actions.py

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

Python

async def _remove_old_push_actions_that_have_rotated(self) -> None: # We want to clear out anything that is older than a day that *has* already # been rotated. rotated_upto_stream_ordering = await self.db_pool.simple_select_one_onecol( table="event_push_summary_stream_ordering", keyvalues={}, retcol="stream_ordering", ) max_stream_ordering_to_delete = min( rotated_upto_stream_ordering, self.stream_ordering_day_ago )

tests/export_tests.py

def test_indent(): multiline_string = indented_multiline_string =

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

test_indent

388616b6247ca4ea8de4e2f340d6206aee523541

tpot

export_tests.py

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

Python

def test_indent(): multiline_string = indented_multiline_string = assert indented_multiline_string == _indent(multiline_string, 4)

onnx/tools/update_model_dims.py

def update_inputs_outputs_dims(model, input_dims, output_dims): # type: (ModelProto, Dict[Text, List[Any]], Dict[Text, List[Any]]) -> ModelProto dim_param_set = set() # type: Set[Text]

six: remove all references (#3926) * six: remove all references ONNX has dropped python 2 support and does not need this anymore. Signed-off-by: Chris Hua <hua.christopher@gmail.com> * six: use bytes for binary_type I misread the changes; the correct migration is binary_type -> bytes in python3. Signed-off-by: Christopher Hua <chua@squareup.com> * remove additional checks for Python version no more need to check for Python 3 Signed-off-by: Christopher Hua <chua@squareup.com> * remove unused import Signed-off-by: Christopher Hua <chua@squareup.com> Co-authored-by: Ashwini Khade <askhade@microsoft.com> Co-authored-by: Chun-Wei Chen <jacky82226@gmail.com>

update_inputs_outputs_dims

2e70f6769ca9b9d0e859fbbd6854f3abc478897b

onnx

update_model_dims.py

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

Python

def update_inputs_outputs_dims(model, input_dims, output_dims): # type: (ModelProto, Dict[Text, List[Any]], Dict[Text, List[Any]]) -> ModelProto dim_param_set = set() # type: Set[Text]

mindsdb/integrations/lightwood_handler/lightwood_handler/utils.py

def get_aliased_columns(aliased_columns, model_alias, targets, mode=None): for col in targets: if mode == 'input': if str(col.parts[0]) != model_alias and col.alias is not None: aliased_columns[aliased_columns.index(col.parts[-1])] = str(col.alias) if mode == 'output': if str(col.parts[0]) == model_alias and col.alias is not None: aliased_columns[aliased_columns.index('prediction')] = str(col.alias) return aliased_columns

add utils file

get_aliased_columns

0c2fc2e6f9d32e8b6785890cdfd7a2bf320b4273

mindsdb

utils.py

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

Python

def get_aliased_columns(aliased_columns, model_alias, targets, mode=None): for col in targets: if mode == 'input': if str(col.parts[0]) != model_alias and col.alias is not None: aliased_columns[aliased_columns.index(col.parts[-1])] = str(col.alias) if mode == 'output': if str(col.parts[0]) == model_alias and col.alias is not None: aliased_columns[aliased_columns.index('prediction')] = str(col.alias) return aliased_columns

netbox/utilities/urls.py

def get_model_urls(app_label, model_name): paths = [] # Retrieve reg

#9072: Implement a mechanism for dynamically registering model detail views

get_model_urls

0d7851ed9de2792ea6d9ed223c315c235290ddd7

netbox

urls.py

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

Python

def get_model_urls(app_label, model_name): paths = [] # Retrieve registered views for this model try: views = registry['views'][app_label][model_name] except KeyError: # No views have been registered for this model views = [] for view in views: # Import the view class or function callable = import_string(view['path']) if issubclass(callable, View): callable = callable.as_view() # Create a path to the view paths.append( path(f"{view['name']}/", callable, name=f"{model_name}_{view['name']}", kwargs=view['kwargs']) ) return paths

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

def head(self, url, **kwargs): r kwargs.setdefault("allow_redirects", False) return self.request

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

head

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

pipenv

sessions.py

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

Python

def head(self, url, **kwargs): r kwargs.setdefault("allow_redirects", False) return self.request("HEAD", url, **kwargs)

src/prefect/agent.py

async def get_and_submit_flow_runs(self) -> List[FlowRun]: if not self.started: raise RuntimeError("Agent is not started. Use `async with OrionAgent()...`") self.logger.debug("Checking for flow runs...") submittable_runs = await self.client.read_flow_runs( sort=FlowRunSort.NEXT_SCHEDULED_S

Improve `prefect orion start` output

get_and_submit_flow_runs

9efee44dbee3a326e3e754139f4ea0d721849561

prefect

agent.py

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

Python

async def get_and_submit_flow_runs(self) -> List[FlowRun]: if not self.started: raise RuntimeError("Agent is not started. Use `async with OrionAgent()...`") self.logger.debug("Checking for flow runs...") submittable_runs = await self.client.read_flow_runs( sort=FlowRunSort.NEXT_SCHEDULED_START_TIME_ASC, flow_run_filter=self.flow_run_query_filter(), ) for flow_run in submittable_runs: self.logger.info(f"Submitting flow run '{flow_run.id}'") self.submitting_flow_run_ids.add(flow_run.id) self.task_group.start_soon( self.submit_run, flow_run, ) return submittable_runs

python3.10.4/Lib/email/_header_value_parser.py

def get_quoted_string(value): quoted_string = QuotedString() if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) quoted_string.append(token) token, value = get_bare_quoted_string(value) quoted_string.append(token) if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) quoted_string.append(token) return quoted_string, value

add python 3.10.4 for windows

get_quoted_string

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

_header_value_parser.py

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

Python

def get_quoted_string(value): quoted_string = QuotedString() if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) quoted_string.append(token) token, value = get_bare_quoted_string(value) quoted_string.append(token) if value and value[0] in CFWS_LEADER: token, value = get_cfws(value) quoted_string.append(token) return quoted_string, value

airbyte-integrations/bases/source-acceptance-test/source_acceptance_test/tests/test_core.py

def test_defined_keyword_exist_in_schema(self, keyword, discovered_catalog): schemas_errors = [] for stream_name, stream in discovered_catalog.items(): check_result = find_keyword_schema(stream.json_schema, key=keyword) if check_result: schemas_errors

SAT: check for not allowed keywords `allOf`, `not` in connectors schema (#9851) * test_defined_keyword_exist_in_schema added Signed-off-by: Sergey Chvalyuk <grubberr@gmail.com>

test_defined_keyword_exist_in_schema

c8ee3f834120aa365acaa90b5eb583ac52c476ca

airbyte

test_core.py

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

Python

def test_defined_keyword_exist_in_schema(self, keyword, discovered_catalog): schemas_errors = [] for stream_name, stream in discovered_catalog.items(): check_result = find_keyword_schema(stream.json_schema, key=keyword) if check_result: schemas_errors.append(stream_name) assert not schemas_errors, f"Found not allowed `{keyword}` keyword for selected streams: {schemas_errors}."

django/core/management/utils.py

def normalize_path_patterns(patterns): patterns = [os.path.normcase(p) for p in patterns] dir_suffixes = {"%s*" % path_sep for path_sep in {"/", os.sep}} norm_patterns = [] for pattern in patterns: for dir_suffix in dir_suffixes: if pattern.endswith(dir_suffix): norm_patterns.append(pattern[: -len(dir_suffix)]) break else: norm_patt

Refs #33476 -- Reformatted code with Black.

normalize_path_patterns

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

utils.py

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

Python

def normalize_path_patterns(patterns): patterns = [os.path.normcase(p) for p in patterns] dir_suffixes = {"%s*" % path_sep for path_sep in {"/", os.sep}} norm_patterns = [] for pattern in patterns: for dir_suffix in dir_suffixes: if pattern.endswith(dir_suffix): norm_patterns.append(pattern[: -len(dir_suffix)]) break else: norm_patterns.append(pattern) return norm_patterns

packages/syft/src/syft/core/node/common/node_service/success_resp_message.py

def get_protobuf_schema() -> GeneratedProtocolMessageType: return ErrorResponseMessage_PB

ADD new Syft ErrorResponseMessage

get_protobuf_schema

14892f3e25065f85fcca953eac681f50880c0c48

PySyft

success_resp_message.py

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

Python

def get_protobuf_schema() -> GeneratedProtocolMessageType: return ErrorResponseMessage_PB

tests/rest/media/test_media_retention.py

def test_remote_media_cache_retention(self) -> None: # Advance 31 days (in seconds) self.reactor.advance(31 * 24 * 60 * 60) # Check that media has been correctly purged. # Local media should be unaffected. # Remote media accessed <30 days ago should still exist. self._assert_if_mxc_uris_purged( purged=[ (self.remote_server_name, self.remote_not_recently_accessed_media),

Add config options for media retention (#12732)

test_remote_media_cache_retention

2fc787c341ff540e5880932f116498ec0ed7a2c2

synapse

test_media_retention.py

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

Python

def test_remote_media_cache_retention(self) -> None: # Advance 31 days (in seconds) self.reactor.advance(31 * 24 * 60 * 60) # Check that media has been correctly purged. # Local media should be unaffected. # Remote media accessed <30 days ago should still exist. self._assert_if_mxc_uris_purged( purged=[ (self.remote_server_name, self.remote_not_recently_accessed_media), ], not_purged=[ (self.remote_server_name, self.remote_recently_accessed_media), (self.hs.config.server.server_name, self.local_recently_accessed_media), ( self.hs.config.server.server_name, self.local_not_recently_accessed_media, ), (self.hs.config.server.server_name, self.local_never_accessed_media), ], )

scapy/arch/windows/__init__.py

def setmodulation(self, modu): # type: (int) -> bool # According to https://nmap.org/npcap/guide/npcap-devguide.html#npcap-feature-dot11 # noqa: E501 self._check_npcap_requirement() _modus = { 0: "dsss", 1: "fhss", 2: "irbaseband", 3: "ofdm", 4: "hrdss", 5: "erp",

[Hinty] Core typing: windows (#3684) * Core typing: windows Co-authored-by: Pierre <pierre@droids-corp.org>

setmodulation

a2b7a28faff1db058dd22ce097a268e0ad5d1d33

scapy

__init__.py

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

Python

def setmodulation(self, modu): # type: (int) -> bool # According to https://nmap.org/npcap/guide/npcap-devguide.html#npcap-feature-dot11 # noqa: E501 self._check_npcap_requirement() _modus = { 0: "dsss", 1: "fhss", 2: "irbaseband", 3: "ofdm", 4: "hrdss", 5: "erp", 6: "ht", 7: "vht", 8: "ihv", 9: "mimo-ofdm", 10: "mimo-ofdm", } m = _modus.get(modu, "unknown") if isinstance(modu, int) else modu return self._npcap_set("modu", str(m))

salt/transport/rabbitmq.py

def _on_connection_error(self, connection, exception): log.error("Failed to connect", exc_info=True)

Start to add base class defs

_on_connection_error

ab4803984bce4a4de7cc10910e7310c4babf557e

salt

rabbitmq.py

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

Python

def _on_connection_error(self, connection, exception): log.error("Failed to connect", exc_info=True)

pandas/core/indexes/multi.py

def is_monotonic_decreasing(self) -> bool:

DOC: Add numpydoc SS06 validation (#47885)

is_monotonic_decreasing

62a69beddbedde349891378992c902c0b9341a9f

pandas

multi.py

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

Python

def is_monotonic_decreasing(self) -> bool: # monotonic decreasing if and only if reverse is monotonic increasing return self[::-1].is_monotonic_increasing

tests/sentry/notifications/test_notifications.py

def test_sends_assignment_notification(self): url = f"/api/0/issues/{self.group.id}/" with self.tasks(): response = self.client.put(url, format="json", data={"assignedTo": self.user.username}) assert response.status_code == 200, response.content msg = mail.outbox[0] # check the txt version assert f"assigned {self.s

fix(notifications): Use `metrics_key` (#34572)

test_sends_assignment_notification

1730c481f1a8a71446326fa1ff72e10663016385

sentry

test_notifications.py

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

Python

def test_sends_assignment_notification(self): url = f"/api/0/issues/{self.group.id}/" with self.tasks(): response = self.client.put(url, format="json", data={"assignedTo": self.user.username}) assert response.status_code == 200, response.content msg = mail.outbox[0] # check the txt version assert f"assigned {self.short_id} to themselves" in msg.body # check the html version assert f"{self.short_id}</a> to themselves</p>" in msg.alternatives[0][0] attachment, text = get_attachment() assert text == f"Issue assigned to {self.name} by themselves" assert attachment["title"] == self.group.title assert ( attachment["footer"] == f"{self.project.slug} | <http://testserver/settings/account/notifications/workflow/?referrer=assigned_activity-slack-user|Notification Settings>" )

django/db/migrations/questioner.py

def _ask_default(self, default=''): self.prompt_output.write('Please enter the default value as valid Python.') if default: self.prompt_output.write( f"Accept the default '{default}' by pressing 'Enter' or " f"provide another value." ) self.prompt_output.write( 'The datetime and django.utils.timezone modules are available, so ' 'it is possible to provide e.g. timezone.now as a valu

Refs #29026 -- Allowed customizing InteractiveMigrationQuestioner's prompt destination. Previously, the questioner did not obey the value of stdout provided to the command.

_ask_default

0ab58c120939093fea90822f376e1866fc714d1f

django

questioner.py

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

Python

def _ask_default(self, default=''): self.prompt_output.write('Please enter the default value as valid Python.') if default: self.prompt_output.write( f"Accept the default '{default}' by pressing 'Enter' or " f"provide another value." ) self.prompt_output.write( 'The datetime and django.utils.timezone modules are available, so ' 'it is possible to provide e.g. timezone.now as a value.' ) self.prompt_output.write("Type 'exit' to exit this prompt") while True: if default: prompt = "[default: {}] >>> ".format(default) else: prompt = ">>> " self.prompt_output.write(prompt, ending='') code = input() if not code and default: code = default if not code: self.prompt_output.write("Please enter some code, or 'exit' (without quotes) to exit.") elif code == "exit": sys.exit(1) else: try: return eval(code, {}, {'datetime': datetime, 'timezone': timezone}) except (SyntaxError, NameError) as e: self.prompt_output.write('Invalid input: %s' % e)

certbot-apache/certbot_apache/_internal/parser.py

def reset_modules(self) -> None: self.modules = {} self.update_modules

Add typing to certbot.apache (#9071) * Add typing to certbot.apache Co-authored-by: Adrien Ferrand <ferrand.ad@gmail.com>

reset_modules

7d9e9a49005de7961e84d2a7c608db57dbab3046

certbot

parser.py

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

Python

def reset_modules(self) -> None: self.modules = {} self.update_modules() self.parse_modules()

rllib/agents/ppo/tests/test_ddppo.py

def test_ddppo_compilation(self):

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

test_ddppo_compilation

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

ray

test_ddppo.py

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

Python

def test_ddppo_compilation(self): config = ppo.ddppo.DEFAULT_CONFIG.copy() config["num_gpus_per_worker"] = 0 num_iterations = 2 for _ in framework_iterator(config, frameworks="torch"): trainer = ppo.ddppo.DDPPOTrainer(config=config, env="CartPole-v0") for i in range(num_iterations): results = trainer.train() check_train_results(results) print(results) # Make sure, weights on all workers are the same (including # local one). weights = trainer.workers.foreach_worker(lambda w: w.get_weights()) for w in weights[1:]: check(w, weights[0]) check_compute_single_action(trainer) trainer.stop()

@keras_export('keras.metrics.categorical_crossentropy', 'keras.losses.categorical_crossentropy') @tf.__internal__.dispatch.add_dispatch_support

keras/losses.py

def log_cosh(y_true, y_pred): y_pred = tf.convert_to_tensor(y_pred) y_true = tf.cast(y_true, y_pred.dtype) def _logcosh(x): return x + tf.math.softplus(-

Fix keras docstrings PiperOrigin-RevId: 424275818

log_cosh

89879e2c76e86c685e44c47a6cdb82f7e645c142

keras

losses.py

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

Python

def log_cosh(y_true, y_pred): y_pred = tf.convert_to_tensor(y_pred) y_true = tf.cast(y_true, y_pred.dtype) def _logcosh(x): return x + tf.math.softplus(-2. * x) - tf.cast( tf.math.log(2.), x.dtype) return backend.mean(_logcosh(y_pred - y_true), axis=-1) @keras_export('keras.metrics.categorical_crossentropy', 'keras.losses.categorical_crossentropy') @tf.__internal__.dispatch.add_dispatch_support

keras/engine/training.py

def make_predict_function(self, force=False): if self.predict_function is not None and not force: return self.predict_function

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

make_predict_function

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

training.py

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

Python

def make_predict_function(self, force=False): if self.predict_function is not None and not force: return self.predict_function

sklearn/feature_selection/_rfe.py

def fit(self, X, y, **fit_params):

MAINT Add parameter validation to RFE and RFECV. (#24137) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>

fit

c9d4e1f86e6d8c58441b1aa01d0a79f25cf3a999

scikit-learn

_rfe.py

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

Python

def fit(self, X, y, **fit_params): self._validate_params() return self._fit(X, y, **fit_params)

tests/cli/test_storage.py

def test_invalid_number_selection_fails(): number_string = "99999999" result = get_first_menu_and_fail(number_string) lines = result.stdout.splitlines() # Strange string addition are due to coloring, I believe assert lines[-1] == f"\x1b[31mInvalid selection {number_string}\x1b[0m" assert result.exit_code == 1

basic tests for storage cli

test_invalid_number_selection_fails

21b8eed6887646c8c2a752961a84c855dd4fed22

prefect

test_storage.py

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

Python

def test_invalid_number_selection_fails(): number_string = "99999999" result = get_first_menu_and_fail(number_string) lines = result.stdout.splitlines() # Strange string addition are due to coloring, I believe assert lines[-1] == f"\x1b[31mInvalid selection {number_string}\x1b[0m" assert result.exit_code == 1

sympy/utilities/misc.py

def filldedent(s, w=70, **kwargs): return '\n' + fill(de

Pass keyword arguments to filldedent() through to fill()

filldedent

2047f4855577845b1b99e0926b887d313725a6e7

sympy

misc.py

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

Python

def filldedent(s, w=70, **kwargs): return '\n' + fill(dedent(str(s)).strip('\n'), width=w, **kwargs)

numpy/lib/arraysetops.py

def in1d(ar1, ar2, assume_unique=False, invert=False, kind=None): # Ravel both arrays, behavior for the first array could be different ar1 = np.asarray(ar1).ravel() ar2 = np.asarray(ar2).ravel() # Ensure that iteration through object arrays yields size-1 arrays if ar2.dtype == object: ar2 = ar2.reshape(-1, 1) # Convert booleans to uint8 so we can use the fast integer algorithm if ar1.dtype == bool: ar1 = ar1.view(np.uint8) if ar2.dtype == bool: ar2 = ar2.view(np.uint8) # Check if we can use a fast integer algorithm: integer_arrays = (np.issubdtype(ar1.dtype, np.integer) and np.issubdtype(ar2.dtype, np.integer)) if kind not in {None, 'sort', 'table'}: raise ValueError( "Invalid kind: {0}. ".format(kind) + "Please use None, 'sort' or 'table'.") if integer_arrays and kind in {None, 'table'}: ar2_min = np.min(ar2) ar2_max = np.max(ar2) ar2_range = int(ar2_max) - int(ar2_min) # Constraints on whether we can actually use the table method: range_safe_from_overflow = ar2_range < np.iinfo(ar2.dtype).max below_memory_constraint = ar2_range <= 6 * (ar1.size + ar2.size) # Optimal performance is for approximately # log10(size) > (log10(range) - 2.27) / 0.927. # However, here we set the requirement that by default # the intermediate array can only be 6x # the combined memory allocation of the original # arrays. See discussion on # https://github.com/numpy/numpy/pull/12065. if ( range_safe_from_overflow and (below_memory_constraint or kind == 'table') ): if invert: outgoing_array = np.ones_like(ar1, dtype=bool) else: outgoing_array = np.zeros_like(ar1, dtype=bool) # Make elements 1 where the integer exists in ar2 if invert: isin_helper_ar = np.ones(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 0 else: isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 1 # Mask out elements we know won't work basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min) outgoing_array[basic_mask] = isin_helper_ar[ar1[basic_mask] - ar2_min] return outgoing_array elif kind == 'table': # not range_safe_from_overflow raise RuntimeError( "You have specified kind='table', " "but the range of values in `ar2` exceeds the " "maximum integer of the datatype. " "Please set `kind` to None or 'sort'." ) elif kind == 'table': raise ValueError( "The 'table' method is only " "supported for boolean or integer arrays. " "Please select 'sort' or None for kind." ) # Check if one of the arrays may contain arbitrary objects contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject # This code is run when # a) the first condition is true, making the code significantly faster # b) the second condition is true (i.e. `ar1` or `ar2` may contain # arbitrary objects), since then sorting is not guaranteed to work if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object: if invert: mask = np.ones(len(ar1), dtype=bool) for a in ar2: mask &= (ar1 != a) else: mask = np.zeros(len(ar1), dtype=bool) for a in ar2: mask |= (ar1 == a) return mask # Otherwise use sorting if not assume_unique: ar1, rev_idx = np.unique(

MAINT: change kind names for in1d - Switch dictionary->table, mergesort->sort

in1d

4ed458f16d9dd64554ccf49e315c5b8fb577d4cd

numpy

arraysetops.py

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

Python

def in1d(ar1, ar2, assume_unique=False, invert=False, kind=None): # Ravel both arrays, behavior for the first array could be different ar1 = np.asarray(ar1).ravel() ar2 = np.asarray(ar2).ravel() # Ensure that iteration through object arrays yields size-1 arrays if ar2.dtype == object: ar2 = ar2.reshape(-1, 1) # Convert booleans to uint8 so we can use the fast integer algorithm if ar1.dtype == bool: ar1 = ar1.view(np.uint8) if ar2.dtype == bool: ar2 = ar2.view(np.uint8) # Check if we can use a fast integer algorithm: integer_arrays = (np.issubdtype(ar1.dtype, np.integer) and np.issubdtype(ar2.dtype, np.integer)) if kind not in {None, 'sort', 'table'}: raise ValueError( "Invalid kind: {0}. ".format(kind) + "Please use None, 'sort' or 'table'.") if integer_arrays and kind in {None, 'table'}: ar2_min = np.min(ar2) ar2_max = np.max(ar2) ar2_range = int(ar2_max) - int(ar2_min) # Constraints on whether we can actually use the table method: range_safe_from_overflow = ar2_range < np.iinfo(ar2.dtype).max below_memory_constraint = ar2_range <= 6 * (ar1.size + ar2.size) # Optimal performance is for approximately # log10(size) > (log10(range) - 2.27) / 0.927. # However, here we set the requirement that by default # the intermediate array can only be 6x # the combined memory allocation of the original # arrays. See discussion on # https://github.com/numpy/numpy/pull/12065. if ( range_safe_from_overflow and (below_memory_constraint or kind == 'table') ): if invert: outgoing_array = np.ones_like(ar1, dtype=bool) else: outgoing_array = np.zeros_like(ar1, dtype=bool) # Make elements 1 where the integer exists in ar2 if invert: isin_helper_ar = np.ones(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 0 else: isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 1 # Mask out elements we know won't work basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min) outgoing_array[basic_mask] = isin_helper_ar[ar1[basic_mask] - ar2_min] return outgoing_array elif kind == 'table': # not range_safe_from_overflow raise RuntimeError( "You have specified kind='table', " "but the range of values in `ar2` exceeds the " "maximum integer of the datatype. " "Please set `kind` to None or 'sort'." ) elif kind == 'table': raise ValueError( "The 'table' method is only " "supported for boolean or integer arrays. " "Please select 'sort' or None for kind." ) # Check if one of the arrays may contain arbitrary objects contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject # This code is run when # a) the first condition is true, making the code significantly faster # b) the second condition is true (i.e. `ar1` or `ar2` may contain # arbitrary objects), since then sorting is not guaranteed to work if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object: if invert: mask = np.ones(len(ar1), dtype=bool) for a in ar2: mask &= (ar1 != a) else: mask = np.zeros(len(ar1), dtype=bool) for a in ar2: mask |= (ar1 == a) return mask # Otherwise use sorting if not assume_unique: ar1, rev_idx = np.unique(ar1, return_inverse=True) ar2 = np.unique(ar2) ar = np.concatenate((ar1, ar2)) # We need this to be a stable sort, so always use 'mergesort' # here. The values from the first array should always come before # the values from the second array. order = ar.argsort(kind='mergesort') sar = ar[order] if invert: bool_ar = (sar[1:] != sar[:-1]) else: bool_ar = (sar[1:] == sar[:-1]) flag = np.concatenate((bool_ar, [invert])) ret = np.empty(ar.shape, dtype=bool) ret[order] = flag if assume_unique: return ret[:len(ar1)] else: return ret[rev_idx]

tests/rest/admin/test_user.py

def test_devices(self) -> None: # Login in as the user self._get_token() # Check that we don't see a new device in our devices list channel = self.make_request( "GET", "devices", b"{}", access_token=self.other_user_tok ) self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body) # We should only see the one device (from the login in `prepare`) self.assertEqual(len(

Add type hints to `tests/rest/admin` (#11851)

test_devices

901b264c0c88f39cbfb8b2229e0dc57968882658

synapse

test_user.py

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

Python

def test_devices(self) -> None: # Login in as the user self._get_token() # Check that we don't see a new device in our devices list channel = self.make_request( "GET", "devices", b"{}", access_token=self.other_user_tok ) self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body) # We should only see the one device (from the login in `prepare`) self.assertEqual(len(channel.json_body["devices"]), 1)

pydantic/_internal/_validation_functions.py

def in_ipython() -> bool: try: eval('__IPYTHON__') except NameError:

Switching to `pydantic_core` (#4516) * working on core schema generation * adapting main.py * getting tests to run * fix tests * disable pyright, fix mypy * moving to class-based model generation * working on validators * change how models are created * start fixing test_main.py * fixing mypy * SelfType * recursive models working, more tests fixed * fix tests on <3.10 * get docs build to pass * starting to cleanup types.py * starting works on custom types * working on using annotated-types * using annoated types for constraints * lots of cleanup, fixing network tests * network tests passing :tada: * working on types * working on types and cleanup * fixing UUID type, restructing again * more types and newer pydantic-core * working on Iterable * more test_types tests * support newer pydantic-core, fixing more test_types.py * working through more test_types.py * test_types.py at last passing locally :tada: * fixing more tests in test_types.py * fix datetime_parse tests and linting * get tests running again, rename to test_datetime.py * renaming internal modules * working through mypy errors * fixing mypy * refactoring _generate_schema.py * test_main.py passing * uprev deps * fix conftest and linting? * importing Annotated * ltining * import Annotated from typing_extensions * fixing 3.7 compatibility * fixing tests on 3.9 * fix linting * fixing SecretField and 3.9 tests * customising get_type_hints * ignore warnings on 3.11 * spliting repr out of utils * removing unused bits of _repr, fix tests for 3.7 * more cleanup, removing many type aliases * clean up repr * support namedtuples and typeddicts * test is_union * removing errors, uprev pydantic-core * fix tests on 3.8 * fixing private attributes and model_post_init * renaming and cleanup * remove unnecessary PydanticMetadata inheritance * fixing forward refs and mypy tests * fix signatures, change how xfail works * revert mypy tests to 3.7 syntax * correct model title * try to fix tests * fixing ClassVar forward refs * uprev pydantic-core, new error format * add "force" argument to model_rebuild * Apply suggestions from code review Suggestions from @tiangolo and @hramezani :pray: Co-authored-by: Hasan Ramezani <hasan.r67@gmail.com> Co-authored-by: Sebastián Ramírez <tiangolo@gmail.com> * more suggestions from @tiangolo * extra -> json_schema_extra on Field Co-authored-by: Hasan Ramezani <hasan.r67@gmail.com> Co-authored-by: Sebastián Ramírez <tiangolo@gmail.com>

in_ipython

594effa279668bd955e98f1cd5c036b37d3bbd40

pydantic

_validation_functions.py

https://github.com/pydantic/pydantic.git

Python

def in_ipython() -> bool: try: eval('__IPYTHON__') except NameError: return False else: # pragma: no cover return True

sklearn/utils/tests/test_param_validation.py

def test_stroptions_deprecated_internal_subset():

MNT Param validation: do not expose internal values in error msg (#23459) * allow to not expose internal valid params in error msg * ensure deprecated and internal do not overlap * deprecated and internal must be subsets of options * black

test_stroptions_deprecated_internal_subset

122876e9ab1ab494b4bf0ca3360d5a1527caf2e7

scikit-learn

test_param_validation.py

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

Python

def test_stroptions_deprecated_internal_subset(): with pytest.raises(ValueError, match="deprecated options must be a subset"): StrOptions({"a", "b", "c"}, deprecated={"a", "d"}) with pytest.raises(ValueError, match="internal options must be a subset"): StrOptions({"a", "b", "c"}, internal={"a", "d"})

tests/admin_views/tests.py

def test_change_view_without_object_change_permission(self): change_url = reverse("admin9:admin_views_article_change", args=(self.a1.pk,)) self.client.force_login(self.viewuser) response = self.client.get(change_url) self.assertEqual(response.context["title"], "View article") self.assertContains(response, "<title>View article | Django site admin</title>") self.assertContains(response, "<h1>View article</h1>") self.assertContains( response, '<a href="/test_admin/admin9/admin_views/article/" class="closelink">Close</a>', )

Refs #33476 -- Reformatted code with Black.

test_change_view_without_object_change_permission

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests.py

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

Python

def test_change_view_without_object_change_permission(self): change_url = reverse("admin9:admin_views_article_change", args=(self.a1.pk,)) self.client.force_login(self.viewuser) response = self.client.get(change_url) self.assertEqual(response.context["title"], "View article") self.assertContains(response, "<title>View article | Django site admin</title>") self.assertContains(response, "<h1>View article</h1>") self.assertContains( response, '<a href="/test_admin/admin9/admin_views/article/" class="closelink">Close</a>', )

pandas/__init__.py

def __getattr__(name): import warnings if name in __deprecated_num_index_names: warnings.warn( f"pandas.{name} is deprecated " "and will be removed from pandas in a future version. " "Use pandas.Index with the appropriate dtype instead.", FutureWarning, stacklevel=2, ) from pandas.core.api import Float64Index, Int64Index, UInt64Index return { "Float64Index": Float64Index, "Int64Index": Int64Index, "UInt64Index": UInt64Index, }[name] elif name == "datetime": warnings.warn( "The pandas.datetime class is deprecated " "and will be removed from pandas in a future version. " "Import from datetime module instead.", FutureWarning, stacklevel=2, ) from datetime import datetime as dt return dt elif name == "np": warnings.warn( "The pandas.np module is deprecated " "and will be removed from pandas in a future version. " "Import numpy directly instead.", FutureWarning, stacklevel=2, ) import numpy as np return np elif name in {"SparseSeries", "SparseDataFrame"}: warnings.warn( f"The {name} class is removed from pandas. Accessing it from " "the top-level namespace will also be removed in the next version.", FutureWarning, stacklevel=2, ) retur

API: hide NumericIndex from public top-level namespace in favor of pd.Index (#44819)

__getattr__

abd74363b3f911cbba79cfd4d78fb17521b39928

pandas

__init__.py

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

Python

def __getattr__(name): import warnings if name in __deprecated_num_index_names: warnings.warn( f"pandas.{name} is deprecated " "and will be removed from pandas in a future version. " "Use pandas.Index with the appropriate dtype instead.", FutureWarning, stacklevel=2, ) from pandas.core.api import Float64Index, Int64Index, UInt64Index return { "Float64Index": Float64Index, "Int64Index": Int64Index, "UInt64Index": UInt64Index, }[name] elif name == "datetime": warnings.warn( "The pandas.datetime class is deprecated " "and will be removed from pandas in a future version. " "Import from datetime module instead.", FutureWarning, stacklevel=2, ) from datetime import datetime as dt return dt elif name == "np": warnings.warn( "The pandas.np module is deprecated " "and will be removed from pandas in a future version. " "Import numpy directly instead.", FutureWarning, stacklevel=2, ) import numpy as np return np elif name in {"SparseSeries", "SparseDataFrame"}: warnings.warn( f"The {name} class is removed from pandas. Accessing it from " "the top-level namespace will also be removed in the next version.", FutureWarning, stacklevel=2, ) return type(name, (), {}) elif name == "SparseArray": warnings.warn( "The pandas.SparseArray class is deprecated " "and will be removed from pandas in a future version. " "Use pandas.arrays.SparseArray instead.", FutureWarning, stacklevel=2, ) from pandas.core.arrays.sparse import SparseArray as _SparseArray return _SparseArray raise AttributeError(f"module 'pandas' has no attribute '{name}'") # module level doc-string __doc__ = # Use __all__ to let type checkers know what is part of the public API. # Pandas is not (yet) a py.typed library: the public API is determined # based on the documentation. __all__ = [ "BooleanDtype", "Categorical", "CategoricalDtype", "CategoricalIndex", "DataFrame", "DateOffset", "DatetimeIndex", "DatetimeTZDtype", "ExcelFile", "ExcelWriter", "Flags", "Float32Dtype", "Float64Dtype", "Grouper", "HDFStore", "Index", "IndexSlice", "Int16Dtype", "Int32Dtype", "Int64Dtype", "Int8Dtype", "Interval", "IntervalDtype", "IntervalIndex", "MultiIndex", "NA", "NaT", "NamedAgg", "Period", "PeriodDtype", "PeriodIndex", "RangeIndex", "Series", "SparseDtype", "StringDtype", "Timedelta", "TimedeltaIndex", "Timestamp", "UInt16Dtype", "UInt32Dtype", "UInt64Dtype", "UInt8Dtype", "api", "array", "arrays", "bdate_range", "concat", "crosstab", "cut", "date_range", "describe_option", "errors", "eval", "factorize", "get_dummies", "get_option", "infer_freq", "interval_range", "io", "isna", "isnull", "json_normalize", "lreshape", "melt", "merge", "merge_asof", "merge_ordered", "notna", "notnull", "offsets", "option_context", "options", "period_range", "pivot", "pivot_table", "plotting", "qcut", "read_clipboard", "read_csv", "read_excel", "read_feather", "read_fwf", "read_gbq", "read_hdf", "read_html", "read_json", "read_orc", "read_parquet", "read_pickle", "read_sas", "read_spss", "read_sql", "read_sql_query", "read_sql_table", "read_stata", "read_table", "read_xml", "reset_option", "set_eng_float_format", "set_option", "show_versions", "test", "testing", "timedelta_range", "to_datetime", "to_numeric", "to_pickle", "to_timedelta", "tseries", "unique", "value_counts", "wide_to_long", ]

salt/modules/file.py

def readlink(path, canonicalize=False): path = os.path.expanduser(path) if not os.path.isabs(path): raise SaltInvocationError("Path to link must be absolute.") if not os.path.islink(path): raise SaltInvocationError("A valid link was not specified

Use salt.utils.path.readlink to handle junctions on Windows

readlink

6680407756aac9ee0eaf150f3a69622b658f7321

salt

file.py

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

Python

def readlink(path, canonicalize=False): path = os.path.expanduser(path) if not os.path.isabs(path): raise SaltInvocationError("Path to link must be absolute.") if not os.path.islink(path): raise SaltInvocationError("A valid link was not specified.") if canonicalize: return os.path.realpath(path) else: return salt.utils.path.readlink(path)

@contextlib.contextmanager

sympy/testing/pytest.py

def warns_deprecated_sympy(): with warns(SymPyDeprecationWarning): yield @contextlib.contextmanager

Note that warns_deprecated_sympy should not be used outside of the test suite

warns_deprecated_sympy

fdaacf84861404f7857081bc85850a781a78979f

sympy

pytest.py

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

Python

def warns_deprecated_sympy(): with warns(SymPyDeprecationWarning): yield @contextlib.contextmanager

numpy/testing/_private/utils.py

def assert_array_equal(x, y, err_msg='', verbose=True, *, strict=False): __tracebackhide__ =

ENH: Add strict parameter to assert_array_equal. (#21595) Fixes #9542 Co-authored-by: Bas van Beek <43369155+BvB93@users.noreply.github.com>

assert_array_equal

cafec60a5e28af98fb8798049edd7942720d2d74

numpy

utils.py

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

Python

def assert_array_equal(x, y, err_msg='', verbose=True, *, strict=False): __tracebackhide__ = True # Hide traceback for py.test assert_array_compare(operator.__eq__, x, y, err_msg=err_msg, verbose=verbose, header='Arrays are not equal', strict=strict)

lib/matplotlib/transforms.py

def update_from_data_x(self, x, ignore=None): x = np.ravel(x) self.update

[Doc] Fix ndarray-links for arguments

update_from_data_x

f16da868d016363c4cd734b2abd6535230b094df

matplotlib

transforms.py

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

Python

def update_from_data_x(self, x, ignore=None): x = np.ravel(x) self.update_from_data_xy(np.column_stack([x, np.ones(x.size)]), ignore=ignore, updatey=False)

tests/csrf_tests/tests.py

def test_https_malformed_referer(self): malformed_referer_msg = "Referer checking failed - Referer is malformed." req = self._get_POST_request_with_token() req._is_secure_override = True req.META["HTTP_REFERER"] = "http://http://www.example.com/" mw = CsrfViewMiddleware(post_form_view) self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains( response, "Referer checking failed - Referer is insecure while host is secure.", status_code=403, ) # Empty req.META["HTTP_REFERER"] = "" self._check_referer_r

Refs #33476 -- Reformatted code with Black.

test_https_malformed_referer

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests.py

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

Python

def test_https_malformed_referer(self): malformed_referer_msg = "Referer checking failed - Referer is malformed." req = self._get_POST_request_with_token() req._is_secure_override = True req.META["HTTP_REFERER"] = "http://http://www.example.com/" mw = CsrfViewMiddleware(post_form_view) self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains( response, "Referer checking failed - Referer is insecure while host is secure.", status_code=403, ) # Empty req.META["HTTP_REFERER"] = "" self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains(response, malformed_referer_msg, status_code=403) # Non-ASCII req.META["HTTP_REFERER"] = "ØBöIß" self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains(response, malformed_referer_msg, status_code=403) # missing scheme # >>> urlparse('//example.com/') # ParseResult(scheme='', netloc='example.com', path='/', params='', query='', fragment='') req.META["HTTP_REFERER"] = "//example.com/" self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains(response, malformed_referer_msg, status_code=403) # missing netloc # >>> urlparse('https://') # ParseResult(scheme='https', netloc='', path='', params='', query='', fragment='') req.META["HTTP_REFERER"] = "https://" self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains(response, malformed_referer_msg, status_code=403) # Invalid URL # >>> urlparse('https://[') # ValueError: Invalid IPv6 URL req.META["HTTP_REFERER"] = "https://[" self._check_referer_rejects(mw, req) response = mw.process_view(req, post_form_view, (), {}) self.assertContains(response, malformed_referer_msg, status_code=403)

tools/test/test_gen_backend_stubs.py

def test_missing_cpp_namespace(self) -> None: y

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

test_missing_cpp_namespace

bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d

pytorch

test_gen_backend_stubs.py

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

Python

def test_missing_cpp_namespace(self) -> None: yaml_str = output_error = self.get_errors_from_gen_backend_stubs(yaml_str) self.assertExpectedInline(output_error, )

networkx/algorithms/shortest_paths/weighted.py

def single_source_dijkstra_path_length(G, source, cutoff=None, weight="weight"): return multi_source_dijkstra_path_length(G, {source}, cutoff=cutoff, weight=weight)

Hide edges with a weight of None in A*. (#5945) * Hide edges with a weight of None in A*. This matches the Dijkstra's weight interface. * Update Dijkstra's and A* docs for weights of None. * Add tests for A* with weight of None. * Add another test for A* with a weight function. * Document that None indicates a hidden edge.

single_source_dijkstra_path_length

d82815dba6c8ddce19cd49f700298dc82a58f066

networkx

weighted.py

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

Python

def single_source_dijkstra_path_length(G, source, cutoff=None, weight="weight"): return multi_source_dijkstra_path_length(G, {source}, cutoff=cutoff, weight=weight)

gamestonk_terminal/stocks/behavioural_analysis/ba_controller.py

def print_help(self): has_ticker_start = "" if self.ticker else "[unvl]" has_ticker_end = "" if self.ticker else "[/unvl]" help_text = f c

Terminal Wide Rich (#1161) * My idea for how we handle Rich moving forward * remove independent consoles * FIxed pylint issues * add a few vars * Switched print to console * More transitions * Changed more prints * Replaced all prints * Fixing tabulate * Finished replace tabulate * Finished removing rich from Tabulate * add Panel around menu * add GST watermark under feature flag * Fixed 46 tests * Delete test_screener[False].yaml * Delete test_screener[True].yaml * Fixed the rest of the tests * add help and source color vars and use rgb * rich on stocks/options * update rich on disc, dps, sia * rich in gov, ins and scr menus * ba and ca menus with rich * Fixed import issue * Fixed some tests * removed termcolor * Removed prettytable * add rich to remaining stocks menus * FIxed linting issue * Added James' changes * Updated dependencies * Add rich to cryptocurrency menu * refactor economy and forex * refactor etf with rich * refactor mfunds * refactor rich rest * not specify style so default color works well on any background * Fixing mypy issues * Updated tests * More test fixes * James' test fixes * Updating tests : stocks/screener - fix cassettes using BR * Updating tests : crypto * Updating tests : disable DEBUG_MODE * Updating tests : stocks/fa/yfinance * minor fixes that escape * Improve the rich table function (that replaces tabulate :D ) * Fixed bad code * delete rogue file + dcf fix + NoConsole * sia mypy * fuck you linter * fuck you linter pt 2 * skip hehe * i hate the black linter * ubuntu mypy attempt * Update : rich_config + gtff * Updating tests : conftest * Updating tests : stocks * Update : rich_config * Updating : rich_config * make panel configurable for Theodore :b * colors update * Merged * Updating : rich_config + feature_flags * Updating : rich_config * Updating tests : stocks * Updating : feature_flags Co-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt> Co-authored-by: Chavithra PARANA <chavithra@gmail.com> Co-authored-by: james <jmaslek11@gmail.com> Co-authored-by: jose-donato <zmcdonato@gmail.com>

print_help

82747072c511beb1b2672846ae2ee4aec53eb562

OpenBBTerminal

ba_controller.py

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

Python

def print_help(self): has_ticker_start = "" if self.ticker else "[unvl]" has_ticker_end = "" if self.ticker else "[/unvl]" help_text = f console.print(text=help_text, menu="Stocks - Behavioural Analysis")

PyInstaller/lib/modulegraph/util.py

def iterate_instructions(code_object): # The arg extension the EXTENDED_ARG opcode represents is automatically handled by get_instructions() but the # instruction is left in. Get rid of it to make subsequent parsing easie

Make modulegraph EXTENDED_ARG opcode aware (#7055). Fix :class:`AssertionError` during build when analysing a ``.pyc`` file containing more that 255 variable names followed by an import statement all in the same namespace. Fixes #7055.

iterate_instructions

299ff39d1260cf80241b81ed39bbb89b78709583

pyinstaller

util.py

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

Python

def iterate_instructions(code_object): # The arg extension the EXTENDED_ARG opcode represents is automatically handled by get_instructions() but the # instruction is left in. Get rid of it to make subsequent parsing easier/safer. yield from (i for i in get_instructions(code_object) if i.opname != "EXTENDED_ARG") yield None # For each constant in this code object that is itself a code object, # parse this constant in the same manner. for constant in code_object.co_consts: if inspect.iscode(constant): yield from iterate_instructions(constant)

python/ray/tune/tuner.py

def fit(self) -> ResultGrid: if not self._is_ray_client: try: return self._local_tuner.fit() except Exception as e:

[docs/air] Fix up some minor docstrings (#28361)

fit

5c500f6308dce526c50a5230029fb4909b492a35

ray

tuner.py

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

Python

def fit(self) -> ResultGrid: if not self._is_ray_client: try: return self._local_tuner.fit() except Exception as e: raise TuneError( f"Tune run failed. " f'Please use tuner = Tuner.restore("' f'{self._local_tuner.get_experiment_checkpoint_dir()}") to resume.' ) from e else: experiment_checkpoint_dir = ray.get( self._remote_tuner.get_experiment_checkpoint_dir.remote() ) try: return ray.get(self._remote_tuner.fit.remote()) except Exception as e: raise TuneError( f"Tune run failed. " f'Please use tuner = Tuner.restore("' f'{experiment_checkpoint_dir}") to resume.' ) from e

homeassistant/components/tradfri/base_class.py

def _handle_coordinator_update(self) -> None: sel

Implement coordinator class for Tradfri integration (#64166) * Initial commit coordinator * More coordinator implementation * More coordinator implementation * Allow integration reload * Move API calls to try/catch block * Move back fixture * Remove coordinator test file * Ensure unchanged file * Ensure unchanged conftest.py file * Remove coordinator key check * Apply suggestions from code review Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Import RequestError * Move async_setup_platforms to end of setup_entry * Remove centralised handling of device data and device controllers * Remove platform_type argument * Remove exception * Remove the correct exception * Refactor coordinator error handling * Apply suggestions from code review Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Remove platform type from base class * Remove timeout context manager * Refactor exception callback * Simplify starting device observation * Update test * Move observe start into update method * Remove await self.coordinator.async_request_refresh() * Refactor cover.py * Uncomment const.py * Add back extra_state_attributes * Update homeassistant/components/tradfri/coordinator.py Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Refactor switch platform * Expose switch state * Refactor sensor platform * Put back accidentally deleted code * Add set_hub_available * Apply suggestions from code review Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Fix tests for fan platform * Update homeassistant/components/tradfri/base_class.py Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Update homeassistant/components/tradfri/base_class.py Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Fix non-working tests * Refresh sensor state * Remove commented line * Add group coordinator * Add groups during setup * Refactor light platform * Fix tests * Move outside of try...except * Remove error handler * Remove unneeded methods * Update sensor * Update .coveragerc * Move signal * Add signals for groups * Fix signal Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

_handle_coordinator_update

9d404b749a0aa0d0527e145c911559df5ecf2afd

core

base_class.py

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

Python

def _handle_coordinator_update(self) -> None: self._refresh() super()._handle_coordinator_update()

dask/dataframe/core.py

def _skew_1d(self, column, bias=True, nan_policy="propagate"): # import depends on scipy, not installed by default from dask.array import stats as da_stats if pd.Int64Dtype.is_dtype(column._meta_nonempty): column = column.astype("f8") if not np.issubdtype(column.dtype, np.number): column = column.astype("f8") name = self._token_prefix + "skew-1d-" + tokenize(column) array_skew

absolufy-imports - No relative - PEP8 (#8796) Conversation in https://github.com/dask/distributed/issues/5889

_skew_1d

cccb9d8d8e33a891396b1275c2448c352ef40c27

dask

core.py

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

Python

def _skew_1d(self, column, bias=True, nan_policy="propagate"): # import depends on scipy, not installed by default from dask.array import stats as da_stats if pd.Int64Dtype.is_dtype(column._meta_nonempty): column = column.astype("f8") if not np.issubdtype(column.dtype, np.number): column = column.astype("f8") name = self._token_prefix + "skew-1d-" + tokenize(column) array_skew = da_stats.skew( column.values, axis=0, bias=bias, nan_policy=nan_policy ) layer = {(name, 0): (methods.wrap_skew_reduction, (array_skew._name,), None)} graph = HighLevelGraph.from_collections(name, layer, dependencies=[array_skew]) return new_dd_object( graph, name, column._meta_nonempty.skew(), divisions=[None, None] )

tests/components/sensor/test_init.py

def test_device_classes_aligned(): for device_class in NumberDeviceClass: assert hasattr(SensorDeviceClass, device_class.name) assert getattr(SensorDeviceClass, device_class.name).value ==

Align number and sensor device classes (#81909) * Align number and sensor device classes * Add tests * Tweak tests

test_device_classes_aligned

b6586d5c34bf7ea5c30fbb1b62c438078ea14f39

core

test_init.py

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

Python

def test_device_classes_aligned(): for device_class in NumberDeviceClass: assert hasattr(SensorDeviceClass, device_class.name) assert getattr(SensorDeviceClass, device_class.name).value == device_class.value

networkx/algorithms/operators/all.py

def intersection_all(graphs): R = None for i, G in enumerate(graphs): G_nodes_set = set(G.nodes) G_edges_set = set(G.edges(keys=True) if G.is_multigraph() else G.edges()) if i == 0: # create new graph R = G.__class__() node_intersection = G_nodes_set edge_intersection = G_edges_set

Make all.py generator friendly (#5984) * Make compose_all generator friendly * Make disjoint_union_all and intersection_all generator friendly * Refactor disjoint_union_all to yield relabeled graphs * Make union_all generator friendly * Fix intersection_all * Fix union_all signature * Allow passing an infinite rename generator to union_all * Copy over generalizations to binary.py * Clean up rename * Simplify first_label in disjoint_union_all * Simplify disjoint_union_all * Add missing R.graph.update in intersection_all

intersection_all

50ff08de69c6e9541cd6c029bede5dabf56cfe73

networkx

all.py

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

Python

def intersection_all(graphs): R = None for i, G in enumerate(graphs): G_nodes_set = set(G.nodes) G_edges_set = set(G.edges(keys=True) if G.is_multigraph() else G.edges()) if i == 0: # create new graph R = G.__class__() node_intersection = G_nodes_set edge_intersection = G_edges_set elif G.is_multigraph() != R.is_multigraph(): raise nx.NetworkXError("All graphs must be graphs or multigraphs.") else: node_intersection &= G_nodes_set edge_intersection &= G_edges_set R.graph.update(G.graph) if R is None: raise ValueError("cannot apply intersection_all to an empty list") R.add_nodes_from(node_intersection) R.add_edges_from(edge_intersection) return R

@functools.lru_cache(maxsize=None)

pipenv/patched/notpip/_internal/locations/__init__.py

def _looks_like_red_hat_scheme() -> bool:

Vendor in pip 21.2.4 release (from pip 21.2.2 prior). (#5009) * Vendor in pip 21.2.4 release (from pip 21.2.2 prior). * Add news fragment for pip 21.2.4 vendor update. * Add potentially missing LICENSE files

_looks_like_red_hat_scheme

7e33fcae4384563b4c927fd44318c29dd524a097

pipenv

__init__.py

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

Python

def _looks_like_red_hat_scheme() -> bool: from distutils.command.install import install from distutils.dist import Distribution cmd: Any = install(Distribution()) cmd.finalize_options() return ( cmd.exec_prefix == f"{os.path.normpath(sys.exec_prefix)}/local" and cmd.prefix == f"{os.path.normpath(sys.prefix)}/local" ) @functools.lru_cache(maxsize=None)

airflow/providers/databricks/operators/databricks_sql.py

def _create_sql_query(self) -> str: escaper = ParamEscaper() maybe_with = "" if self._encryption is not None or self._credential is not None: maybe_encryption = "" if self._encryption is not None: maybe_encryption = self._generate_options("ENCRYPTION", escaper, self._encryption, False) maybe_credential = "" if self._credential is not None: maybe_credential = self._generate_options("CREDENTIAL", escaper, self._credential, False) maybe_with = f" WITH ({maybe_credential} {maybe_encryption})" location = escaper.escape_item(self._file_location) + maybe_with if self._expression_list is not None: location = f"(SELECT {self._expression_list} FROM {location})" files_or_pattern = "" if self._pattern is not None: files_or_pattern = f"PATTERN = {escaper.escape_item(self._pattern)}\n" elif self._files is not None: files_or_pattern = f"FILES = {escaper.e

Add new options to DatabricksCopyIntoOperator (#22076) This includes: * `encryption` - to specify encryption options for a given location * `credential` - to specify authentication options for a given location * `validate` - to control validation of schema & data

_create_sql_query

401419432082d222b823e4f2a66f21e5cc3ab28d

airflow

databricks_sql.py

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

Python

def _create_sql_query(self) -> str: escaper = ParamEscaper() maybe_with = "" if self._encryption is not None or self._credential is not None: maybe_encryption = "" if self._encryption is not None: maybe_encryption = self._generate_options("ENCRYPTION", escaper, self._encryption, False) maybe_credential = "" if self._credential is not None: maybe_credential = self._generate_options("CREDENTIAL", escaper, self._credential, False) maybe_with = f" WITH ({maybe_credential} {maybe_encryption})" location = escaper.escape_item(self._file_location) + maybe_with if self._expression_list is not None: location = f"(SELECT {self._expression_list} FROM {location})" files_or_pattern = "" if self._pattern is not None: files_or_pattern = f"PATTERN = {escaper.escape_item(self._pattern)}\n" elif self._files is not None: files_or_pattern = f"FILES = {escaper.escape_item(self._files)}\n" format_options = self._generate_options("FORMAT_OPTIONS", escaper, self._format_options) + "\n" copy_options = self._generate_options("COPY_OPTIONS", escaper, self._copy_options) + "\n" validation = "" if self._validate is not None: if isinstance(self._validate, bool): if self._validate: validation = "VALIDATE ALL\n" elif isinstance(self._validate, int): if self._validate < 0: raise AirflowException( "Number of rows for validation should be positive, got: " + str(self._validate) ) validation = f"VALIDATE {self._validate} ROWS\n" else: raise AirflowException("Incorrect data type for validate parameter: " + type(self._validate)) # TODO: think on how to make sure that table_name and expression_list aren't used for SQL injection sql = f return sql.strip()

keras/wrappers/scikit_learn.py

def predict(self, x, **kwargs):

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

predict

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

scikit_learn.py

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

Python

def predict(self, x, **kwargs): proba = self.model.predict(x, **kwargs) if proba.shape[-1] > 1: classes = proba.argmax(axis=-1) else: classes = (proba > 0.5).astype("int32") return self.classes_[classes]

modules/image/text_recognition/ppocrv3_det_ch/processor.py

def resize_image_type0(self, img): limit_side_len = self.max_side_len h, w, _ = img.shape # limit the max side if max(h, w) > limit_side_len: if h > w: ratio = float(limit_side_len) / h else: ratio = float(limit_side_len) / w else: ratio = 1. resize_h = int(h * ratio) resize_w = int(w * ratio) resize_h = int(round(resize_h / 32) * 32) resize_w = int(round(resize_w / 32) * 32) try: if int(resize_w) <= 0 or int(resize_h) <= 0: return None, (None, None) img = cv2.resize(img, (int(resize_w), int(resize_h))) except:

add module

resize_image_type0

9b3119dfb63c4cbb7acfb9f1f1c09ac24e6d68d2

PaddleHub

processor.py

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

Python

def resize_image_type0(self, img): limit_side_len = self.max_side_len h, w, _ = img.shape # limit the max side if max(h, w) > limit_side_len: if h > w: ratio = float(limit_side_len) / h else: ratio = float(limit_side_len) / w else: ratio = 1. resize_h = int(h * ratio) resize_w = int(w * ratio) resize_h = int(round(resize_h / 32) * 32) resize_w = int(round(resize_w / 32) * 32) try: if int(resize_w) <= 0 or int(resize_h) <= 0: return None, (None, None) img = cv2.resize(img, (int(resize_w), int(resize_h))) except: print(img.shape, resize_w, resize_h) sys.exit(0) ratio_h = resize_h / float(h) ratio_w = resize_w / float(w) # return img, np.array([h, w]) return img, [ratio_h, ratio_w]

keras/engine/training.py

def metrics(self): metrics = [] if self._is_compiled: # TODO(omalleyt): Track `LossesContainer` and `MetricsContainer` objects # so that attr names are not l

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

metrics

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

training.py

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

Python

def metrics(self): metrics = [] if self._is_compiled: # TODO(omalleyt): Track `LossesContainer` and `MetricsContainer` objects # so that attr names are not load-bearing. if self.compiled_loss is not None: metrics += self.compiled_loss.metrics if self.compiled_metrics is not None: metrics += self.compiled_metrics.metrics for l in self._flatten_layers(): metrics.extend(l._metrics) # pylint: disable=protected-access return metrics

django/contrib/messages/api.py

def set_level(request, level): if not hasattr(request, "_messages"): retur

Refs #33476 -- Reformatted code with Black.

set_level

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

api.py

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

Python

def set_level(request, level): if not hasattr(request, "_messages"): return False request._messages.level = level return True

networkx/algorithms/lowest_common_ancestors.py

def all_pairs_lowest_common_ancestor(G, pairs=None): if not nx.is_directed_acyclic_graph(G): raise nx.NetworkXError

Replace LCA with naive implementations (#5883) * WIP: Replace functions to evaluate tests. * Raise prompt exceptions by wrapping generator. * Fix erroneous ground-truth self-ancestor in tests. * Move pair creation outside of generator and validate. * Convert input with fromkeys to preserve order and rm duplicates. * Replace LCA implementations & update tests. * Test cleanup: move new tests into old class. Allows us to get rid of duplication/another test setup. * Rm naive fns from refguide. * Add release note. * Remove unused imports. * Remove missed duplicate function (bad rebase). Co-authored-by: Dilara Tekinoglu <dilaranurtuncturk@gmail.com>

all_pairs_lowest_common_ancestor

19c1454d3dfa70a893ea67f2d78515658e8c08e5

networkx

lowest_common_ancestors.py

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

Python

def all_pairs_lowest_common_ancestor(G, pairs=None): if not nx.is_directed_acyclic_graph(G): raise nx.NetworkXError("LCA only defined on directed acyclic graphs.") if len(G) == 0: raise nx.NetworkXPointlessConcept("LCA meaningless on null graphs.") if pairs is None: pairs = combinations_with_replacement(G, 2) else: # Convert iterator to iterable, if necessary. Trim duplicates. pairs = dict.fromkeys(pairs) # Verify that each of the nodes in the provided pairs is in G nodeset = set(G) for pair in pairs: if set(pair) - nodeset: raise nx.NodeNotFound( f"Node(s) {set(pair) - nodeset} from pair {pair} not in G." ) # Once input validation is done, construct the generator

tests/test_task_runners.py

async def test_is_pickleable_after_start(self, task_runner): task_runner.client_kwargs["set_as_default"] = True

Introduces testing module and task runner standard test suite (PrefectHQ/orion#1655)

test_is_pickleable_after_start

7895fb5013aa98955bb31be96953ac13979a5b94

prefect

test_task_runners.py

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

Python

async def test_is_pickleable_after_start(self, task_runner): task_runner.client_kwargs["set_as_default"] = True

python3.10.4/Lib/asyncio/base_events.py

def _add_callback_signalsafe(self, handle): self._add_callback(handle) self._write_to_self()

add python 3.10.4 for windows

_add_callback_signalsafe

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

base_events.py

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

Python

def _add_callback_signalsafe(self, handle): self._add_callback(handle) self._write_to_self()

spotdl/utils/ffmpeg.py

def get_local_ffmpeg() -> Optional[Path]:

v4 init

get_local_ffmpeg

fa2ad657482aca9dc628e6d7062b8badf2706bb6

spotify-downloader

ffmpeg.py

https://github.com/spotDL/spotify-downloader.git

Python

def get_local_ffmpeg() -> Optional[Path]: ffmpeg_path = Path( get_spotdl_path(), "ffmpeg" + ".exe" if platform.system() == "Windows" else "" ) if ffmpeg_path.is_file(): return ffmpeg_path return None

salt/modules/cmdmod.py

def _render_cmd(cmd, cwd, template, saltenv=None, pillarenv=None, pillar_override=None): if saltenv is None: saltenv = __opts__.get("saltenv", "base") if not template: return (cmd, cwd) # render the path as a template using path_template_engine as the engine if template not in salt.utils.templates.TEMPLATE_REGISTRY: raise CommandExecutionError( "Attempted to render file paths with unavailable engine {}".format(template) ) kwargs = {} kwargs["salt"] = __salt__ if pillarenv is not None or pillar_override is not None: pillarenv = pillarenv or __opts__["pillarenv"] kwargs["pillar"] = _gather_pillar(pillarenv, pillar_override)

fixes salt bug 61507

_render_cmd

21d3f4bc9eb7b9fb1118c59073595a9e9ee836bd

salt

cmdmod.py

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

Python

def _render_cmd(cmd, cwd, template, saltenv=None, pillarenv=None, pillar_override=None): if saltenv is None: saltenv = __opts__.get("saltenv", "base") if not template: return (cmd, cwd) # render the path as a template using path_template_engine as the engine if template not in salt.utils.templates.TEMPLATE_REGISTRY: raise CommandExecutionError( "Attempted to render file paths with unavailable engine {}".format(template) ) kwargs = {} kwargs["salt"] = __salt__ if pillarenv is not None or pillar_override is not None: pillarenv = pillarenv or __opts__["pillarenv"] kwargs["pillar"] = _gather_pillar(pillarenv, pillar_override) else: kwargs["pillar"] = __pillar__ kwargs["grains"] = __grains__ kwargs["opts"] = __opts__ kwargs["saltenv"] = saltenv

tests/rest/media/v1/test_html_preview.py

def test_windows_1252(self) -> None: html = b tree = decode_body(html, "http://example.com/test.html") og = parse

Add type hints to `tests/rest` (#12146) * Add type hints to `tests/rest` * newsfile * change import from `SigningKey`

test_windows_1252

7e91107be1a4287873266e588a3c5b415279f4c8

synapse

test_html_preview.py

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

Python

def test_windows_1252(self) -> None: html = b tree = decode_body(html, "http://example.com/test.html") og = parse_html_to_open_graph(tree, "http://example.com/test.html") self.assertEqual(og, {"og:title": "ó", "og:description": "Some text."})

homeassistant/helpers/template.py

def square_root(value, default=_SENTINEL): try: return m

Fail template functions when no default specified (#71687)

square_root

4885331509eeffe50f42d76b234996467b06170f

core

template.py

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

Python

def square_root(value, default=_SENTINEL): try: return math.sqrt(float(value)) except (ValueError, TypeError): if default is _SENTINEL: raise_no_default("sqrt", value) return default

tests/test_core.py

async def test_track_task_functions(event_loop): hass = ha.HomeAssistant() try: assert hass._track_task hass.async_stop_track_tasks() assert not hass._track_task hass.async_track_tasks() assert hass._track_task finally: await hass.async_stop()

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

test_track_task_functions

c576a68d336bc91fd82c299d9b3e5dfdc1c14960

core

test_core.py

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

Python

async def test_track_task_functions(event_loop): hass = ha.HomeAssistant() try: assert hass._track_task hass.async_stop_track_tasks() assert not hass._track_task hass.async_track_tasks() assert hass._track_task finally: await hass.async_stop()

homeassistant/components/kaleidescape/media_player.py

def media_position_updated_at(self) -> datetime | None:

Add Kaleidescape integration (#67711)

media_position_updated_at

ea82f2e293f43d3e5be103a64b68d088c4b65545

core

media_player.py

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

Python

def media_position_updated_at(self) -> datetime | None: if self._device.movie.play_status in KALEIDESCAPE_PLAYING_STATES: return utcnow() return None

python3.10.4/Lib/asyncio/sslproto.py

def write(self, data): if n

add python 3.10.4 for windows

write

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

sslproto.py

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

Python

def write(self, data): if not isinstance(data, (bytes, bytearray, memoryview)): raise TypeError(f"data: expecting a bytes-like instance, " f"got {type(data).__name__}") if not data: return self._ssl_protocol._write_appdata(data)

manim/mobject/svg/text_mobject.py

def _extract_color_tags(self): tags = re.finditer( r'<color\s+col="([^"]+)"(\s+offset="([^"]+)")?>(.+?)</color>', self.original_text, re.S, ) colormap = [] for tag in tags: start = self._count_real_chars(self.original_text[: tag.start(0)]) end = start + self._count_real_chars(tag.group(4)) offsets = tag.group(3).split(",") if tag.group(3) else [0] start_offset = int(offsets[0]) if offsets[0] else 0 end_offset = int(offsets[1]) if len(offsets) == 2 and offsets[1] else 0 colormap.append( { "start": start, "end": end, "color": tag.group(1), "start_offset": start_offset, "end_offset": end_offset,

Hide more private methods from the docs. (#2468) * hide privs from text_mobject.py * hide privs from tex_mobject.py * hide privs from code_mobject.py * hide privs from svg_mobject.py * remove SVGPath and utils from __init__.py * don't import string_to_numbers * hide privs from geometry.py * hide privs from matrix.py * hide privs from numbers.py * hide privs from three_dimensions.py * forgot underscore under set_stroke_width_from_length * there were more i missed * unhidea method that was used in docs * forgot other text2hash * remove svg_path from docs

_extract_color_tags

902e7eb4f0147b5882a613b67467e38a1d47f01e

manim

text_mobject.py

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

Python

def _extract_color_tags(self): tags = re.finditer( r'<color\s+col="([^"]+)"(\s+offset="([^"]+)")?>(.+?)</color>', self.original_text, re.S, ) colormap = [] for tag in tags: start = self._count_real_chars(self.original_text[: tag.start(0)]) end = start + self._count_real_chars(tag.group(4)) offsets = tag.group(3).split(",") if tag.group(3) else [0] start_offset = int(offsets[0]) if offsets[0] else 0 end_offset = int(offsets[1]) if len(offsets) == 2 and offsets[1] else 0 colormap.append( { "start": start, "end": end, "color": tag.group(1), "start_offset": start_offset, "end_offset": end_offset, }, ) self.text = re.sub("<color[^>]+>(.+?)</color>", r"\1", self.text, 0, re.S) return colormap

frequency_response.py

def write_readme(self, file_path, parametric_eq_peqs=None, fixed_band_eq_peq=None): file_path = os.path.abspath(file_path) dir_path = os.path.dirname(file_path) model = self.name # Write model s = '# {}\n'.format(model) s += 'See [usage instructions](https://github.com/jaakkopasanen/AutoEq#usage) for more options and info.\n\n' # Add parametric EQ settings if parametric_eq_peqs is not None: s += '### Parametric EQs\n'

Added PEQ configs to CLI and function interfaces. Improved default value handling for PEQ parameters and added more predefined configs. Removed legacy PEQ optimization. Fixed readme write. Improved shelf filter initialization. Added plot method to PEQ. Notebook for comparing old and new optimizers. Bug fixes.

write_readme

9120cdffe618c6c2ff16fe6a311b6a1367efdbc8

AutoEq

frequency_response.py

https://github.com/jaakkopasanen/AutoEq.git

Python

def write_readme(self, file_path, parametric_eq_peqs=None, fixed_band_eq_peq=None): file_path = os.path.abspath(file_path) dir_path = os.path.dirname(file_path) model = self.name # Write model s = '# {}\n'.format(model) s += 'See [usage instructions](https://github.com/jaakkopasanen/AutoEq#usage) for more options and info.\n\n' # Add parametric EQ settings if parametric_eq_peqs is not None: s += '### Parametric EQs\n' if len(parametric_eq_peqs) > 1: compound = PEQ(self.frequency.copy(), parametric_eq_peqs[0].fs, []) n = 0 filter_ranges = '' preamps = '' for i, peq in enumerate(parametric_eq_peqs): for filt in peq.filters: compound.add_filter(filt) filter_ranges += f'1-{len(peq.filters) + n}' preamps += f'{-compound.max_gain - 0.1:.1f} dB' if i < len(parametric_eq_peqs) - 2: filter_ranges += ', ' preamps += ', ' elif i == len(parametric_eq_peqs) - 2: filter_ranges += ' or ' preamps += ' or ' n += len(peq.filters) s += f'You can use filters {filter_ranges}. Apply preamp of {preamps}, respectively.\n\n' else: compound = PEQ(self.frequency.copy(), parametric_eq_peqs[0].fs, []) for peq in parametric_eq_peqs: for filt in peq.filters: compound.add_filter(filt) s += f'Apply preamp of -{compound.max_gain + 0.1:.1f} dB when using parametric equalizer.\n\n' s += compound.markdown_table() + '\n\n' # Add fixed band eq if fixed_band_eq_peq is not None: s += f'### Fixed Band EQs\nWhen using fixed band (also called graphic) equalizer, apply preamp of ' \ f'**-{fixed_band_eq_peq.max_gain + 0.1:.1f} dB** (if available) and set gains manually with these ' \ f'parameters.\n\n{fixed_band_eq_peq.markdown_table()}\n\n' # Write image link img_path = os.path.join(dir_path, model + '.png') if os.path.isfile(img_path): img_url = f'./{os.path.split(img_path)[1]}' img_url = urllib.parse.quote(img_url, safe="%/:=&?~#+!$,;'@()*[]") s += f'### Graphs\n\n' # Write file with open(file_path, 'w', encoding='utf-8') as f: f.write(s)

haystack/telemetry.py

def _get_execution_environment(): if os.environ.get("CI", "False").lower() == "true": execution_env

Add basic telemetry features (#2314) * add basic telemetry features * change pipeline_config to _component_config * Update Documentation & Code Style * add super().__init__() calls to error classes * make posthog mock work with python 3.7 * Update Documentation & Code Style * update link to docs web page * log exceptions, send event for raised HaystackErrors, refactor Path(CONFIG_PATH) * add comment on send_event in BaseComponent.init() and fix mypy * mock NonPrivateParameters and fix pylint undefined-variable * Update Documentation & Code Style * check model path contains multiple / * add test for writing to file * add test for en-/disable telemetry * Update Documentation & Code Style * merge file deletion methods and ignore pylint global statement * Update Documentation & Code Style * set env variable in demo to activate telemetry * fix mock of HAYSTACK_TELEMETRY_ENABLED * fix mypy and linter * add CI as env variable to execution contexts * remove threading, add test for custom error event * Update Documentation & Code Style * simplify config/log file deletion * add test for final event being sent * force writing config file in test * make test compatible with python 3.7 * switch to posthog production server * Update Documentation & Code Style Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

_get_execution_environment

ac5617e757e9ace6f30b7291686d9dbbc339f433

haystack

telemetry.py

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

Python

def _get_execution_environment(): if os.environ.get("CI", "False").lower() == "true": execution_env = "ci" elif "google.colab" in sys.modules: execution_env = "colab" elif "KUBERNETES_SERVICE_HOST" in os.environ: execution_env = "kubernetes" elif HAYSTACK_DOCKER_CONTAINER in os.environ: execution_env = os.environ.get(HAYSTACK_DOCKER_CONTAINER) # check if pytest is imported elif "pytest" in sys.modules: execution_env = "test" else: try: execution_env = get_ipython().__class__.__name__ # pylint: disable=undefined-variable except NameError: execution_env = "script" return execution_env

.venv/lib/python3.8/site-packages/pip/_internal/index/collector.py

def _ensure_html_response(url, session): # type: (str, PipSession) -> None scheme, netloc, path, query, fragment = urllib.parse.urlsplit(url) if scheme not in {'http', 'https'}: raise _NotHTTP() resp = session.head(url, allow_redirects=True) raise_for_status(resp) _ensure_html

upd; format

_ensure_html_response

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

collector.py

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

Python

def _ensure_html_response(url, session): # type: (str, PipSession) -> None scheme, netloc, path, query, fragment = urllib.parse.urlsplit(url) if scheme not in {'http', 'https'}: raise _NotHTTP() resp = session.head(url, allow_redirects=True) raise_for_status(resp) _ensure_html_header(resp)

pipenv/vendor/tomlkit/parser.py

def _parse_item(self) -> Optional[Tuple[Optional[Key], Item]]: self.mark() with self._state as state: while True: c = self._current if c

Update tomlkit==0.9.2 Used: python -m invoke vendoring.update --package=tomlkit

_parse_item

8faa74cdc9da20cfdcc69f5ec29b91112c95b4c9

pipenv

parser.py

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

Python

def _parse_item(self) -> Optional[Tuple[Optional[Key], Item]]: self.mark() with self._state as state: while True: c = self._current if c == "\n": # Found a newline; Return all whitespace found up to this point. self.inc() return None, Whitespace(self.extract()) elif c in " \t\r": # Skip whitespace. if not self.inc(): return None, Whitespace(self.extract()) elif c == "#": # Found a comment, parse it indent = self.extract() cws, comment, trail = self._parse_comment_trail() return None, Comment(Trivia(indent, cws, comment, trail)) elif c == "[": # Found a table, delegate to the calling function. return else: # Begining of a KV pair. # Return to beginning of whitespace so it gets included # as indentation for the KV about to be parsed. state.restore = True break return self._parse_key_value(True)

sympy/tensor/tensor.py

def _xreplace(self, rule): if self in rule: return rule[self], True elif rule: rule = self._dedupe_indices_in_rule(rule) args = [] changed = False for a in self.args: _xreplace = getattr(a, '_xreplace', None) if _xreplace is not None: a_xr = _xreplace(rule) args.append(a_xr[0]) changed |= a_xr[1] else: args.append(a) args = tuple(args) if changed: r

Add TensMul._xreplace to dedupe dummy indices This apparently should not be done. https://github.com/sympy/sympy/pull/24333#issuecomment-1333783127

_xreplace

49222e1e3645ca6948277b8e1a9b526daeb0948d

sympy

tensor.py

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

Python

def _xreplace(self, rule): if self in rule: return rule[self], True elif rule: rule = self._dedupe_indices_in_rule(rule) args = [] changed = False for a in self.args: _xreplace = getattr(a, '_xreplace', None) if _xreplace is not None: a_xr = _xreplace(rule) args.append(a_xr[0]) changed |= a_xr[1] else: args.append(a) args = tuple(args) if changed: return self.func(*args), True return self, False

homeassistant/components/mpd/media_player.py

async def async_turn_on(self) -> None: await self._client.play() await self._update_playlists(no_throttle=True)

Improve entity type hints [m] (#77816)

async_turn_on

6355e682fa4aeb526570597d919ad1fb76755b9a

core

media_player.py

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

Python

async def async_turn_on(self) -> None: await self._client.play() await self._update_playlists(no_throttle=True)

keras/distribute/distributed_training_utils_v1.py

def _build_network_on_replica(model, mode, inputs=None, targets=None): # Need to do imports here since we run into a circular dependency error. from keras import models # pylint: disable=g-import-not-at-top from keras.engine import sequential # pylint: disable=g-import-not-at-top # We rely on the internal methods to avoid having share_weights weights in the # public API. if isinstance(model, sequential.Sequential): updated_model = models._clone_sequential_model( model, input_tensors=inputs, layer_fn=models.share_weights ) else: updated_model = models._clone_functional_model( model, input_tensors=inputs, layer_fn=models.share_weights ) # Callable losses added directly to a functional Model need to be added # here. updated_model._callable_losses = model._callable_losses # Recast all low precision outputs back to float32 since we only casted # the inputs to bfloat16 and not targets. This is done so that we can preserve # precision when calculating the loss value.

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

_build_network_on_replica

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

distributed_training_utils_v1.py

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

Python

def _build_network_on_replica(model, mode, inputs=None, targets=None): # Need to do imports here since we run into a circular dependency error. from keras import models # pylint: disable=g-import-not-at-top from keras.engine import sequential # pylint: disable=g-import-not-at-top # We rely on the internal methods to avoid having share_weights weights in the # public API. if isinstance(model, sequential.Sequential): updated_model = models._clone_sequential_model( model, input_tensors=inputs, layer_fn=models.share_weights ) else: updated_model = models._clone_functional_model( model, input_tensors=inputs, layer_fn=models.share_weights ) # Callable losses added directly to a functional Model need to be added # here. updated_model._callable_losses = model._callable_losses # Recast all low precision outputs back to float32 since we only casted # the inputs to bfloat16 and not targets. This is done so that we can preserve # precision when calculating the loss value.

keras/utils/tf_utils.py

def can_jit_compile(warn=False): if platform.system() == "Darwin" and "arm" in pla

Set `jit_compile` only when TensorFlow XLA is available for the platform. Fixes issue of using new optimizers on Mac M1 as TF on Mac M1 is not built with XLA. PiperOrigin-RevId: 497158007

can_jit_compile

1b32391798a952176b733660c940b1589c2fc8a4

keras

tf_utils.py

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

Python

def can_jit_compile(warn=False): if platform.system() == "Darwin" and "arm" in platform.processor().lower(): if warn: logging.warning( "Tensorflow is not compiled with XLA on Mac M1 Arm processors, " "so cannot set `jit_compile` to True." ) return False return True

rllib/algorithms/algorithm.py

def __setstate__(self, state) -> None: # TODO (sven): Validate that our config and the config in state are compatible. # For example, the model architectures may differ. # Also, what should the behavior be if e.g. some training parameter # (e.g. lr) changed? if hasattr(self, "workers") and "worker" in state: self.workers.local_worker().set_state(state["worker"]) remote_state = ray.put(state["worker"]) for r in self.workers.remote_workers(): r.set_state.remote(remote_state) if self.evaluation_workers: # If evaluation workers are used, also restore the policies # there in case they are used for evaluation purpose. for r in self.evaluation_workers.remote_workers(): r.set_state.remote(remote_state) # If necessary, restore replay data as well. if self.local_replay_buffer is not None: # TODO: Experimental functionality: Restore contents of replay # buffer from checkpoint, only if user has configured this. if self.config.get("store_buffer_in_checkpoints"): if "local_replay_buffer" in state: self.local_replay_buffer.set_state(state["local_replay_buffer"]) else: logger.warning( "`store_buffer_in_checkpoints` is True, but no replay "

[RLlib] Algorithm/Policy checkpoint overhaul and Policy Model export (in native formats). (#28166)

__setstate__

23b3a599b9df8100558c477e94b0b19b1a38ac27

ray

algorithm.py

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

Python

def __setstate__(self, state) -> None: # TODO (sven): Validate that our config and the config in state are compatible. # For example, the model architectures may differ. # Also, what should the behavior be if e.g. some training parameter # (e.g. lr) changed? if hasattr(self, "workers") and "worker" in state: self.workers.local_worker().set_state(state["worker"]) remote_state = ray.put(state["worker"]) for r in self.workers.remote_workers(): r.set_state.remote(remote_state) if self.evaluation_workers: # If evaluation workers are used, also restore the policies # there in case they are used for evaluation purpose. for r in self.evaluation_workers.remote_workers(): r.set_state.remote(remote_state) # If necessary, restore replay data as well. if self.local_replay_buffer is not None: # TODO: Experimental functionality: Restore contents of replay # buffer from checkpoint, only if user has configured this. if self.config.get("store_buffer_in_checkpoints"): if "local_replay_buffer" in state: self.local_replay_buffer.set_state(state["local_replay_buffer"]) else: logger.warning( "`store_buffer_in_checkpoints` is True, but no replay " "data found in state!" ) elif "local_replay_buffer" in state and log_once( "no_store_buffer_in_checkpoints_but_data_found" ): logger.warning( "`store_buffer_in_checkpoints` is False, but some replay " "data found in state!" ) if self.train_exec_impl is not None: self.train_exec_impl.shared_metrics.get().restore(state["train_exec_impl"])

test/mitmproxy/proxy/layers/http/test_http2.py

def test_http2_client_aborts(tctx, stream, when, how): server = P

make it black!

test_http2_client_aborts

b3587b52b25077f68116b9852b041d33e7fc6601

mitmproxy

test_http2.py

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

Python

def test_http2_client_aborts(tctx, stream, when, how): server = Placeholder(Server) flow = Placeholder(HTTPFlow) playbook, cff = start_h2_client(tctx) resp = Placeholder(bytes)

django/contrib/admin/options.py

def get_changelist_instance(self, request): list_display = self.get_list_display(request) list_display_links = self.get_list_display_links(request, list_display) # Add the action checkboxes if any actions are available. if self.get_actions(request): list_display = ["action_checkbox", *list_display] sortable_by = self.get_sortable_by(request) ChangeList = self.get_changelist(request) return ChangeList( request, self.model, list_display, list_display_links, self.get_list_filter(request), self.date_hierarchy, self.get_search_fields(request),

Refs #33476 -- Reformatted code with Black.

get_changelist_instance

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

options.py

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

Python

def get_changelist_instance(self, request): list_display = self.get_list_display(request) list_display_links = self.get_list_display_links(request, list_display) # Add the action checkboxes if any actions are available. if self.get_actions(request): list_display = ["action_checkbox", *list_display] sortable_by = self.get_sortable_by(request) ChangeList = self.get_changelist(request) return ChangeList( request, self.model, list_display, list_display_links, self.get_list_filter(request), self.date_hierarchy, self.get_search_fields(request), self.get_list_select_related(request), self.list_per_page, self.list_max_show_all, self.list_editable, self, sortable_by, self.search_help_text, )

jax/_src/lax/qdwh.py

def _use_cholesky(u, m, n, params): a, b, c = params _, N = u.shape x = c * (u.T.conj() @ u) + jnp.eye(N, dtype=jnp.dtype(u)) # Pads the lower-right corner with the identity matrix to prevent the Cholesky # decomposition from failing due to the matrix not being PSD if padded with # zeros. x = _mask(x, (n, n), jnp.eye(N,

Add support for padded arrays in QDWH algorithm. This change is in preparation for adding a jit-table QDWH-eig implementation. PiperOrigin-RevId: 448571523

_use_cholesky

db73670ec3fc72f75e6f832351620ac79e9b0c6f

jax

qdwh.py

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

Python

def _use_cholesky(u, m, n, params): a, b, c = params _, N = u.shape x = c * (u.T.conj() @ u) + jnp.eye(N, dtype=jnp.dtype(u)) # Pads the lower-right corner with the identity matrix to prevent the Cholesky # decomposition from failing due to the matrix not being PSD if padded with # zeros. x = _mask(x, (n, n), jnp.eye(N, dtype=x.dtype)) # `y` is lower triangular. y = lax_linalg.cholesky(x, symmetrize_input=False) z = lax_linalg.triangular_solve( y, u.T, left_side=True, lower=True, conjugate_a=True).conj() z = lax_linalg.triangular_solve(y, z, left_side=True, lower=True, transpose_a=True, conjugate_a=True).T.conj() e = b / c u = e * u + (a - e) * z return u

sympy/functions/elementary/piecewise.py

def piecewise_integrate(self, x, **kwargs): from sympy.integrals import integrate return self.func(*[(integrate(e, x, **kwargs), c) for e, c in self.args])

Improved documentation formatting

piecewise_integrate

cda8dfe6f45dc5ed394c2f5cda706cd6c729f713

sympy

piecewise.py

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

Python

def piecewise_integrate(self, x, **kwargs): from sympy.integrals import integrate return self.func(*[(integrate(e, x, **kwargs), c) for e, c in self.args])

cps/helper.py

def check_send_to_ereader(entry): formats = list() book_formats = list() if len(entry.data): for ele in iter(entry.data): if ele.uncompressed_size < config.mail_size: formats.append(ele.format) if 'EPUB' in formats: book_formats.append({'format': 'Epub', 'convert': 0, 'text':

Eenabled send epubs to E-Reader devices

check_send_to_ereader

fbac3e38ac116855b930ee60fb3c997337ae17b7

calibre-web

helper.py

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

Python

def check_send_to_ereader(entry): formats = list() book_formats = list() if len(entry.data): for ele in iter(entry.data): if ele.uncompressed_size < config.mail_size: formats.append(ele.format) if 'EPUB' in formats: book_formats.append({'format': 'Epub', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Epub')}) if 'MOBI' in formats: book_formats.append({'format': 'Mobi', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Mobi')}) if 'PDF' in formats: book_formats.append({'format': 'Pdf', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Pdf')}) if 'AZW' in formats: book_formats.append({'format': 'Azw', 'convert': 0, 'text': _('Send %(format)s to E-Reader', format='Azw')}) if config.config_converterpath: book_formats.extend(check_send_to_ereader_with_converter(formats)) return book_formats else: log.error(u'Cannot find book entry %d', entry.id) return None # Check if a reader is existing for any of the book formats, if not, return empty list, otherwise return # list with supported formats

sympy/stats/joint_rv_types.py

def Multinomial(syms, n, *p): if not isinstance(p[0], list): p = (list(p), ) return multivariate_rv(MultinomialDistribution, syms, n, p[0]) #------------------------------------------------------------------------------- # Negative

Improved some documentation in the stats module

Multinomial

7fe8e027ae1d7f683243c0229b961671a6cbb4c5

sympy

joint_rv_types.py

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

Python

def Multinomial(syms, n, *p): if not isinstance(p[0], list): p = (list(p), ) return multivariate_rv(MultinomialDistribution, syms, n, p[0]) #------------------------------------------------------------------------------- # Negative Multinomial Distribution --------------------------------------------

sympy/physics/qho_1d.py

def psi_n(n, x, m, omega): # sympify arguments n, x, m, omega = map(S, [n, x, m, omega]) nu = m * omega / hbar #

applied backtick correction to the remainder of the project

psi_n

a0989bcfd26470833cf03737941bfd80f511c745

sympy

qho_1d.py

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

Python

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)

python3.10.4/Lib/inspect.py

def getsourcefile(object): filename = getfile(object) all_bytecode_suffixes = importlib.machinery.DEBUG_BYTECODE_SUFFIXES[:] all_bytecode_suffixes += importlib.machinery.OPTIMIZED_BYTECODE_SUFFIXES[:] if any(filename.endswith(s) for s in all_bytecode_suffixes): filename = (os.path.splitext(filename)[0] + importlib.machinery.SOURCE_SUFFIXES[0]) elif any(filename.endswith(s) for s in

add python 3.10.4 for windows

getsourcefile

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

inspect.py

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

Python

def getsourcefile(object): filename = getfile(object) all_bytecode_suffixes = importlib.machinery.DEBUG_BYTECODE_SUFFIXES[:] all_bytecode_suffixes += importlib.machinery.OPTIMIZED_BYTECODE_SUFFIXES[:] if any(filename.endswith(s) for s in all_bytecode_suffixes): filename = (os.path.splitext(filename)[0] + importlib.machinery.SOURCE_SUFFIXES[0]) elif any(filename.endswith(s) for s in importlib.machinery.EXTENSION_SUFFIXES): return None if os.path.exists(filename): return filename # only return a non-existent filename if the module has a PEP 302 loader module = getmodule(object, filename) if getattr(module, '__loader__', None) is not None: return filename elif getattr(getattr(module, "__spec__", None), "loader", None) is not None: return filename # or it is in the linecache elif filename in linecache.cache: return filename

python3.10.4/Lib/importlib/_abc.py

def module_repr(self, module): warnings.warn("importlib.abc.Loader.module_repr() is deprecated and " "slated for removal in Python 3.12", DeprecationWarning

add python 3.10.4 for windows

module_repr

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

_abc.py

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

Python

def module_repr(self, module): warnings.warn("importlib.abc.Loader.module_repr() is deprecated and " "slated for removal in Python 3.12", DeprecationWarning) # The exception will cause ModuleType.__repr__ to ignore this method. raise NotImplementedError

tests/push/test_email.py

def test_need_validated_email(self): with

Support enabling/disabling pushers (from MSC3881) (#13799) Partial implementation of MSC3881

test_need_validated_email

8ae42ab8fa3c6b52d74c24daa7ca75a478fa4fbb

synapse

test_email.py

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