Datasets:

semeru

/

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

like 0

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

packages/python/plotly/plotly/graph_objs/layout/_legend.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_legend.py

itemdoubleclick

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

switch to black .22

def _generate_legacy_events_context_id_query() -> Select: # This can be removed once we no longer have event_ids in the states table return ( select( *EVENT_COLUMNS, literal(value=None, type_=sqlalchemy.String).label("shared_data"), States.state, States.entity_id, States.attributes, StateAttributes.shared_attrs, ) .outerjoin(States, (Events.event_id == States.event_id)) .where(States.last_updated == States.last_changed) .where(_not_continuous_entity_matcher()) .outerjoin( StateAttributes, (States.attributes_id == StateAttributes.attributes_id) ) )

homeassistant/components/logbook/__init__.py

core

Python

26177bd080b4eb6d11cfd9fbdd158be36f4983d4

__init__.py

_generate_legacy_events_context_id_query

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

Convert logbook to use lambda_stmt (#71624)

def get_mailbox_list(value): mailbox_list = MailboxList() while value and value[0] != ';': try: token, value = get_mailbox(value) mailbox_list.append(token) except errors.HeaderParseError: leader = None if value[0] in CFWS_LEADER: leader, value = get_cfws(value) if not value or value[0] in ',;': mailbox_list.append(leader) mailbox_list.defects.append(errors.ObsoleteHeaderDefect( "empty element in mailbox-list")) else: token, value = get_invalid_mailbox(value, ',;') if leader is not None: token[:0] = [leader] mailbox_list.append(token) mailbox_list.defects.append(errors.InvalidHeaderDefect( "invalid mailbox in mailbox-list")) elif value[0] == ',': mailbox_list.defects.append(errors.ObsoleteHeaderDefect( "empty element in mailbox-list")) else: token, value = get_invalid_mailbox(value, ',;') if leader is not None: token[:0] = [leader] mailbox_list.append(token) mailbox_list.defects.append(errors.InvalidHeaderDefect( "invalid mailbox in mailbox-list")) if value and value[0] not in ',;': # Crap after mailbox; treat it as an invalid mailbox. # The mailbox info will still be available. mailbox = mailbox_list[-1] mailbox.token_type = 'invalid-mailbox' token, value = get_invalid_mailbox(value, ',;') mailbox.extend(token) mailbox_list.defects.append(errors.InvalidHeaderDefect( "invalid mailbox in mailbox-list")) if value and value[0] == ',': mailbox_list.append(ListSeparator) value = value[1:] return mailbox_list, value

python3.10.4/Lib/email/_header_value_parser.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_header_value_parser.py

get_mailbox_list

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

add python 3.10.4 for windows

def _clone_config(self, config): old_path = os.path.abspath(get_testdata(config)) new_path = os.path.join(self._temp_directory, config) shutil.copy2(old_path, new_path) return new_path

tests/functional/eks/test_kubeconfig.py

aws-cli

Python

1a6b498657ec5dd29ddf4f6b240c6fc0c5d88f7a

test_kubeconfig.py

_clone_config

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

Deprecate Kubernetes client API version v1alpha1 Kubernetes has deprecated v1alpha1, v1beta1 has been available since Kubernetes v1.11 (kubernetes/kubernetes#64482), and EKS currently supports Kubernetes versions v1.16 through v1.21. This is a breaking change for clients running versions v1.10 and older, which haven't been supported by EKS since September 2019. "aws eks get-token" now respects the KUBERNETES_EXEC_INFO environment variable and conservatively falls back to v1alpha1, which is supported by Kubernetes versions 1.10 through 1.22 (released upstream August 2021, to be released by EKS in Q4 2021). It also now supports "v1beta1" and "v1". "aws eks update-kubeconfig" now writes "v1beta1" in the kubeconfig which will be supported by Kubernetes until 1.29 (aproximately December 2023). At or around that date, we can change the default version written to kubeconfigs to "v1" Signed-off-by: Micah Hausler <mhausler@amazon.com>

def test_clear_task_instances_dr_state(self, state, last_scheduling, dag_maker): with dag_maker( 'test_clear_task_instances', start_date=DEFAULT_DATE, end_date=DEFAULT_DATE + datetime.timedelta(days=10), ) as dag: EmptyOperator(task_id='0') EmptyOperator(task_id='1', retries=2) dr = dag_maker.create_dagrun( state=State.RUNNING, run_type=DagRunType.SCHEDULED, ) ti0, ti1 = sorted(dr.task_instances, key=lambda ti: ti.task_id) dr.last_scheduling_decision = DEFAULT_DATE ti0.state = TaskInstanceState.SUCCESS ti1.state = TaskInstanceState.SUCCESS session = dag_maker.session session.flush() # we use order_by(task_id) here because for the test DAG structure of ours # this is equivalent to topological sort. It would not work in general case # but it works for our case because we specifically constructed test DAGS # in the way that those two sort methods are equivalent qry = session.query(TI).filter(TI.dag_id == dag.dag_id).order_by(TI.task_id).all() clear_task_instances(qry, session, dag_run_state=state, dag=dag) session.flush() session.refresh(dr) assert dr.state == state assert dr.start_date is None if state == State.QUEUED else dr.start_date assert dr.last_scheduling_decision == last_scheduling

tests/models/test_cleartasks.py

airflow

Python

49e336ae0302b386a2f47269a6d13988382d975f

test_cleartasks.py

test_clear_task_instances_dr_state

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

Replace usage of `DummyOperator` with `EmptyOperator` (#22974) * Replace usage of `DummyOperator` with `EmptyOperator`

def downgrade(): conn = op.get_bind() if conn.dialect.name == "sqlite": # in sqlite TEXT and STRING column types are the same return if conn.dialect.name == "mysql": op.alter_column( 'connection', 'description', existing_type=sa.Text(5000), type_=sa.String(length=5000), existing_nullable=True, ) else: # postgres does not allow size modifier for text type op.alter_column( 'connection', 'description', existing_type=sa.Text(), type_=sa.String(length=5000), existing_nullable=True, )

airflow/migrations/versions/64a7d6477aae_fix_description_field_in_connection_to_.py

airflow

Python

69f6f9e01b6df76c3c8fa266d460324163957887

64a7d6477aae_fix_description_field_in_connection_to_.py

downgrade

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

Autogenerate migration reference doc (#21601) * document airflow version in each alembic migration module and use this to autogen the doc * update each migration module to have the same description used in migration ref (so it can be used in autogen)

def _canonicalize_dtype(x64_enabled, dtype): try: dtype = np.dtype(dtype) except TypeError as e: raise TypeError(f'dtype {dtype!r} not understood') from e if x64_enabled: return dtype else: return _dtype_to_32bit_dtype.get(dtype, dtype)

jax/_src/dtypes.py

jax

Python

329de7c9cc1b77f9caacf2163a77a9d8496c379b

dtypes.py

_canonicalize_dtype

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

Only use config.x64_enabled as the memo cache key for canonicalize_dtype, not any other fields. This saves the time to repeatedly build a tuple as a cache key. Reduces the time for CustomLinearSolveTest.test_custom_linear_solve_pytree on my workstation from 110s to 85s. PiperOrigin-RevId: 422632700

def copyDataFiles(): for included_datafile in getIncludedDataFiles(): # TODO: directories should be resolved to files. if ( not isinstance(included_datafile, (IncludedDataFile)) or included_datafile.needsCopy() ): _handleDataFile( included_datafile, )

nuitka/freezer/IncludedDataFiles.py

Nuitka

Python

abfb99b0a05dd76d2ecc6ebc20732a271857c6c8

IncludedDataFiles.py

copyDataFiles

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

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

def _check_pyarrow_version(): global _VERSION_VALIDATED if not _VERSION_VALIDATED: if os.environ.get(RAY_DISABLE_PYARROW_VERSION_CHECK, "0") == "1": _VERSION_VALIDATED = True return try: import pyarrow except ModuleNotFoundError: # pyarrow not installed, short-circuit. return import pkg_resources if not hasattr(pyarrow, "__version__"): logger.warning( "You are using the 'pyarrow' module, but the exact version is unknown " "(possibly carried as an internal component by another module). Please " f"make sure you are using pyarrow >= {MIN_PYARROW_VERSION}, < " f"{MAX_PYARROW_VERSION} to ensure compatibility with Ray Datasets. " "If you want to disable this pyarrow version check, set the " f"environment variable {RAY_DISABLE_PYARROW_VERSION_CHECK}=1." ) else: version = pyarrow.__version__ if ( pkg_resources.packaging.version.parse(version) < pkg_resources.packaging.version.parse(MIN_PYARROW_VERSION) ) or ( pkg_resources.packaging.version.parse(version) >= pkg_resources.packaging.version.parse(MAX_PYARROW_VERSION) ): raise ImportError( f"Datasets requires pyarrow >= {MIN_PYARROW_VERSION}, < " f"{MAX_PYARROW_VERSION}, but {version} is installed. Reinstall " f'with `pip install -U "pyarrow<{MAX_PYARROW_VERSION}"`. ' "If you want to disable this pyarrow version check, set the " f"environment variable {RAY_DISABLE_PYARROW_VERSION_CHECK}=1." ) _VERSION_VALIDATED = True

python/ray/data/_internal/util.py

ray

Python

ee0fbf9d43dfa05fdf90ad0515b2671cac16a92b

util.py

_check_pyarrow_version

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

[Datasets] Add upper bound to pyarrow version check. (#29674) We previously weren't checking that the 7.0.0 pyarrow upper bound was being respected. This PR adds this upper bound check.

def cogview_attention(self, attention_scores, alpha=32): scaled_attention_scores = attention_scores / alpha max_value = scaled_attention_scores.amax(dim=(-1)).unsqueeze(-1) new_attention_scores = (scaled_attention_scores - max_value) * alpha return nn.Softmax(dim=-1)(new_attention_scores)

src/transformers/models/layoutlmv3/modeling_layoutlmv3.py

transformers

Python

31ee80d55673f32c0f5d50936f371e661b74b21a

modeling_layoutlmv3.py

cogview_attention

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

Add LayoutLMv3 (#17060) * Make forward pass work * More improvements * Remove unused imports * Remove timm dependency * Improve loss calculation of token classifier * Fix most tests * Add docs * Add model integration test * Make all tests pass * Add LayoutLMv3FeatureExtractor * Improve integration test + make fixup * Add example script * Fix style * Add LayoutLMv3Processor * Fix style * Add option to add visual labels * Make more tokenizer tests pass * Fix more tests * Make more tests pass * Fix bug and improve docs * Fix import of processors * Improve docstrings * Fix toctree and improve docs * Fix auto tokenizer * Move tests to model folder * Move tests to model folder * change default behavior add_prefix_space * add prefix space for fast * add_prefix_spcae set to True for Fast * no space before `unique_no_split` token * add test to hightligh special treatment of added tokens * fix `test_batch_encode_dynamic_overflowing` by building a long enough example * fix `test_full_tokenizer` with add_prefix_token * Fix tokenizer integration test * Make the code more readable * Add tests for LayoutLMv3Processor * Fix style * Add model to README and update init * Apply suggestions from code review * Replace asserts by value errors * Add suggestion by @ducviet00 * Add model to doc tests * Simplify script * Improve README * a step ahead to fix * Update pair_input_test * Make all tokenizer tests pass - phew * Make style * Add LayoutLMv3 to CI job * Fix auto mapping * Fix CI job name * Make all processor tests pass * Make tests of LayoutLMv2 and LayoutXLM consistent * Add copied from statements to fast tokenizer * Add copied from statements to slow tokenizer * Remove add_visual_labels attribute * Fix tests * Add link to notebooks * Improve docs of LayoutLMv3Processor * Fix reference to section Co-authored-by: SaulLu <lucilesaul.com@gmail.com> Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

def check_planarity(G, counterexample=False): planarity_state = LRPlanarity(G) embedding = planarity_state.lr_planarity() if embedding is None: # graph is not planar if counterexample: return False, get_counterexample(G) else: return False, None else: # graph is planar return True, embedding

networkx/algorithms/planarity.py

networkx

Python

1af7d49d70869081e5cb64d17165652f1b26c57b

planarity.py

check_planarity

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

Improve documentation of PlanarEmbedding class (#5523) * Improve documentation of PlanarEmbedding * Fix type * Make suggested changes * rst formatting nits. * Update networkx/algorithms/planarity.py Co-authored-by: Dan Schult <dschult@colgate.edu> * Run black for formatting Co-authored-by: Ross Barnowski <rossbar@berkeley.edu> Co-authored-by: Dan Schult <dschult@colgate.edu>

def draw(self, renderer): if not self.get_visible(): return self._recompute_transform() width = self.convert_xunits(self.width) height = self.convert_yunits(self.height) # If the width and height of ellipse are not equal, take into account # stretching when calculating angles to draw between

lib/matplotlib/patches.py

matplotlib

Python

cf995d1304bfa7f660e7158b5121a46e54f869f2

patches.py

draw

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

Remove ineffective exclusion of Arcs without parent Axes. The `if not hasattr(self, 'axes'): raise RuntimeError(...)` check was ineffectual, as artists now always have an Axes attribute, which can just be None for some artists. In fact, small Arcs are drawn just fine without a parent Axes; e.g. ``` from pylab import * from matplotlib.patches import * fig = figure() fig.add_artist(Ellipse((.2, .2), .1, .3, angle=45)) # for comparison fig.add_artist(Arc((.2, .2), .1, .3, angle=45, theta1=0, theta2=45)) ``` works just fine. Remove the check, and adjust the docs accordingly. On the other hand, large arcs *did* previously fail, but that occurred a bit further down, when computing `transforms.BboxTransformTo(self.axes.bbox)` (`self.axes` is None --> AttributeError). Fix that by using the figure bbox in that case (as the point is to limit the drawing to the unclipped area, which is the whole figure for Arcs without a parent Axes).

def _async_setup_scanner_watchdog(self) -> None: self._start_time = self._last_detection = MONOTONIC_TIME() if not self._cancel_watchdog: self._cancel_watchdog = async_track_time_interval( self.hass, self._async_scanner_watchdog, SCANNER_WATCHDOG_INTERVAL )

homeassistant/components/bluetooth/base_scanner.py

core

Python

0e2ebfe5c45716250280186234123f170e3bd08c

base_scanner.py

_async_setup_scanner_watchdog

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

Move bluetooth watchdog into the scanner base class (#83888)

def test_image_crafter_index(encoder_doc_array, tmpdir):

tests/unit/helloworld/multimodal/test_executors.py

jina

Python

933415bfa1f9eb89f935037014dfed816eb9815d

test_executors.py

test_image_crafter_index

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

feat: star routing (#3900) * feat(proto): adjust proto for star routing (#3844) * feat(proto): adjust proto for star routing * feat(proto): generate proto files * feat(grpc): refactor grpclet interface (#3846) * feat: refactor connection pool for star routing (#3872) * feat(k8s): add more labels to k8s deployments * feat(network): refactor connection pool * feat(network): refactor k8s pool * feat: star routing graph gateway (#3877) * feat: star routing - refactor grpc data runtime (#3887) * feat(runtimes): refactor grpc dataruntime * fix(tests): adapt worker runtime tests * fix(import): fix import * feat(proto): enable sending multiple lists (#3891) * feat: star routing gateway (#3893) * feat: star routing gateway all protocols (#3897) * test: add streaming and prefetch tests (#3901) * feat(head): new head runtime for star routing (#3899) * feat(head): new head runtime * feat(head): new head runtime * style: fix overload and cli autocomplete * feat(network): improve proto comments Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(worker): merge docs in worker runtime (#3905) * feat(worker): merge docs in worker runtime * feat(tests): assert after clean up * feat(tests): star routing runtime integration tests (#3908) * fix(tests): fix integration tests * test: test runtimes fast slow request (#3910) * feat(zmq): purge zmq, zed, routing_table (#3915) * feat(zmq): purge zmq, zed, routing_table * style: fix overload and cli autocomplete * feat(zmq): adapt comment in dependency list * style: fix overload and cli autocomplete * fix(tests): fix type tests Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * test: add test gateway to worker connection (#3921) * feat(pea): adapt peas for star routing (#3918) * feat(pea): adapt peas for star routing * style: fix overload and cli autocomplete * feat(pea): add tests * feat(tests): add failing head pea test Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(tests): integration tests for peas (#3923) * feat(tests): integration tests for peas * feat(pea): remove _inner_pea function * feat: star routing container pea (#3922) * test: rescue tests (#3942) * fix: fix streaming tests (#3945) * refactor: move docker run to run (#3948) * feat: star routing pods (#3940) * feat(pod): adapt pods for star routing * feat(pods): adapt basepod to star routing * feat(pod): merge pod and compound pod * feat(tests): fix tests * style: fix overload and cli autocomplete * feat(test): add container pea int test * feat(ci): remove more unnecessary tests * fix(tests): remove jinad runtime * feat(ci): remove latency tracking * fix(ci): fix ci def * fix(runtime): enable runtime to be exited * fix(tests): wrap runtime test in process * fix(runtimes): remove unused runtimes * feat(runtimes): improve cancel wait * fix(ci): build test pip again in ci * fix(tests): fix a test * fix(test): run async in its own process * feat(pod): include shard in activate msg * fix(pea): dont join * feat(pod): more debug out * feat(grpc): manage channels properly * feat(pods): remove exitfifo * feat(network): add simple send retry mechanism * fix(network): await pool close * fix(test): always close grpc server in worker * fix(tests): remove container pea from tests * fix(tests): reorder tests * fix(ci): split tests * fix(ci): allow alias setting * fix(test): skip a test * feat(pods): address comments Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * test: unblock skipped test (#3957) * feat: jinad pea (#3949) * feat: jinad pea * feat: jinad pea * test: remote peas * test: toplogy tests with jinad * ci: parallel jobs * feat(tests): add pod integration tests (#3958) * feat(tests): add pod integration tests * fix(tests): make tests less flaky * fix(test): fix test * test(pea): remote pea topologies (#3961) * test(pea): remote pea simple topology * test: remote pea topologies * refactor: refactor streamer result handling (#3960) * feat(k8s): adapt K8s Pod for StarRouting (#3964) * test: optimize k8s test * test: increase timeout and use different namespace * test: optimize k8s test * test: build and load image when needed * test: refactor k8s test * test: fix image name error * test: fix k8s image load * test: fix typoe port expose * test: update tests in connection pool and handling * test: remove unused fixture * test: parameterize docker images * test: parameterize docker images * test: parameterize docker images * feat(k8s): adapt k8s pod for star routing * fix(k8s): dont overwrite add/remove function in pool * fix(k8s): some fixes * fix(k8s): some more fixes * fix(k8s): linting * fix(tests): fix tests * fix(tests): fix k8s unit tests * feat(k8s): complete k8s integration test * feat(k8s): finish k8s tests * feat(k8s): fix test * fix(tests): fix test with no name * feat(k8s): unify create/replace interface * feat(k8s): extract k8s port constants * fix(tests): fix tests * fix(tests): wait for runtime being ready in tests * feat(k8s): address comments Co-authored-by: bwanglzu <bo.wang@jina.ai> * feat(flow): adapt Flow for StarRouting (#3986) * feat(flow): add routes * feat(flow): adapt flow to star routing * style: fix overload and cli autocomplete * feat(flow): handle empty topologies * feat(k8s): allow k8s pool disabling * style: fix overload and cli autocomplete * fix(test): fix test with mock * fix(tests): fix more tests * feat(flow): clean up tests * style: fix overload and cli autocomplete * fix(tests): fix more tests * feat: add plot function (#3994) * fix(tests): avoid hanging tests * feat(flow): add type hinting * fix(test): fix duplicate exec name in test * fix(tests): fix more tests * fix(tests): enable jinad test again * fix(tests): random port fixture * fix(style): replace quotes Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * feat(ci): bring back ci (#3997) * feat(ci): enable ci again * style: fix overload and cli autocomplete * feat(ci): add latency tracking * feat(ci): bring back some tests * fix(tests): remove invalid port test * feat(ci): disable daemon and distributed tests * fix(tests): fix entrypoint in hub test * fix(tests): wait for gateway to be ready * fix(test): fix more tests * feat(flow): do rolling update and scale sequentially * fix(tests): fix more tests * style: fix overload and cli autocomplete * feat: star routing hanging pods (#4011) * fix: try to handle hanging pods better * test: hanging pods test work * fix: fix topology graph problem * test: add unit test to graph * fix(tests): fix k8s tests * fix(test): fix k8s test * fix(test): fix k8s pool test * fix(test): fix k8s test * fix(test): fix k8s connection pool setting * fix(tests): make runtime test more reliable * fix(test): fix routes test * fix(tests): make rolling update test less flaky * feat(network): gurantee unique ports * feat(network): do round robin for shards * fix(ci): increase pytest timeout to 10 min Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix(ci): fix ci file * feat(daemon): jinad pod for star routing * Revert "feat(daemon): jinad pod for star routing" This reverts commit ed9b37ac862af2e2e8d52df1ee51c0c331d76f92. * feat(daemon): remote jinad pod support (#4042) * feat(daemon): add pod tests for star routing * feat(daemon): add remote pod test * test(daemon): add remote pod arguments test * test(daemon): add async scale test * test(daemon): add rolling update test * test(daemon): fix host * feat(proto): remove message proto (#4051) * feat(proto): remove message proto * fix(tests): fix tests * fix(tests): fix some more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * fix(tests): fix more tests * feat(proto): put docs back in data * fix(proto): clean up * feat(proto): clean up * fix(tests): skip latency tracking * fix(test): fix hub test * fix(tests): fix k8s test * fix(test): some test clean up * fix(style): clean up style issues * feat(proto): adjust for rebase * fix(tests): bring back latency tracking * fix(tests): fix merge accident * feat(proto): skip request serialization (#4074) * feat: add reduce to star routing (#4070) * feat: add reduce on shards to head runtime * test: add reduce integration tests with fixed order * feat: add reduce on needs * chore: get_docs_matrix_from_request becomes public * style: fix overload and cli autocomplete * docs: remove undeterministic results warning * fix: fix uses_after * test: assert correct num docs after reducing in test_external_pod * test: correct asserts after reduce in test_rolling_update * fix: no reduce if uses_after_address is set * fix: get_docs_from_request only if needed * fix: fix tests after merge * refactor: move reduce from data_request_handler to head * style: fix overload and cli autocomplete * chore: apply suggestions * fix: fix asserts * chore: minor test fix * chore: apply suggestions * test: remove flow tests with external executor (pea) * fix: fix test_expected_messages_routing * fix: fix test_func_joiner * test: adapt k8s test Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * fix(k8s): fix static pool config * fix: use custom protoc doc generator image (#4088) * fix: use custom protoc doc generator image * fix(docs): minor doc improvement * fix(docs): use custom image * fix(docs): copy docarray * fix: doc building local only * fix: timeout doc building * fix: use updated args when building ContainerPea * test: add container PeaFactory test * fix: force pea close on windows (#4098) * fix: dont reduce if uses exist (#4099) * fix: dont use reduce if uses exist * fix: adjust reduce tests * fix: adjust more reduce tests * fix: fix more tests * fix: adjust more tests * fix: ignore non jina resources (#4101) * feat(executor): enable async executors (#4102) * feat(daemon): daemon flow on star routing (#4096) * test(daemon): add remote flow test * feat(daemon): call scale in daemon * feat(daemon): remove tail args and identity * test(daemon): rename scalable executor * test(daemon): add a small delay in async test * feat(daemon): scale partial flow only * feat(daemon): call scale directly in partial flow store * test(daemon): use asyncio sleep * feat(daemon): enable flow level distributed tests * test(daemon): fix jinad env workspace config * test(daemon): fix pod test use new port rolling update * feat(daemon): enable distribuetd tests * test(daemon): remove duplicate tests and zed runtime test * test(daemon): fix stores unit test * feat(daemon): enable part of distributed tests * feat(daemon): enable part of distributed tests * test: correct test paths * test(daemon): add client test for remote flows * test(daemon): send a request with jina client * test(daemon): assert async generator * test(daemon): small interval between tests * test(daemon): add flow test for container runtime * test(daemon): add flow test for container runtime * test(daemon): fix executor name * test(daemon): fix executor name * test(daemon): use async client fetch result * test(daemon): finish container flow test * test(daemon): enable distributed in ci * test(daemon): enable distributed in ci * test(daemon): decare flows and pods * test(daemon): debug ci if else * test(daemon): debug ci if else * test(daemon): decare flows and pods * test(daemon): correct test paths * test(daemon): add small delay for async tests * fix: star routing fixes (#4100) * docs: update docs * fix: fix Request.__repr__ * docs: update flow remarks * docs: fix typo * test: add non_empty_fields test * chore: remove non_empty_fields test * feat: polling per endpoint (#4111) * feat(polling): polling per endpoint configurable * fix: adjust tests * feat(polling): extend documentation * style: fix overload and cli autocomplete * fix: clean up * fix: adjust more tests * fix: remove repeat from flaky test * fix: k8s test * feat(polling): address pr feedback * feat: improve docs Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * feat(grpc): support connect grpc server via ssl tunnel (#4092) * feat(grpc): support ssl grpc connect if port is 443 * fix(grpc): use https option instead of detect port automatically * chore: fix typo * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * fix: update jina/peapods/networking.py Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * test(networking): add test for peapods networking * fix: address comments Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> * feat(polling): unify polling args (#4113) * fix: several issues for jinad pods (#4119) * fix: activate for jinad pods * fix: dont expose worker pod in partial daemon * fix: workspace setting * fix: containerized flows * fix: hub test * feat(daemon): remote peas on star routing (#4112) * test(daemon): fix request in peas * test(daemon): fix request in peas * test(daemon): fix sync async client test * test(daemon): enable remote peas test * test(daemon): replace send message to send request * test(daemon): declare pea tests in ci * test(daemon): use pea args fixture * test(daemon): head pea use default host * test(daemon): fix peas topologies * test(daemon): fix pseudo naming * test(daemon): use default host as host * test(daemon): fix executor path * test(daemon): add remote worker back * test(daemon): skip local remote remote topology * fix: jinad pea test setup * fix: jinad pea tests * fix: remove invalid assertion Co-authored-by: jacobowitz <tobias.jacobowitz@posteo.de> * feat: enable daemon tests again (#4132) * feat: enable daemon tests again * fix: remove bogy empty script file * fix: more jinad test fixes * style: fix overload and cli autocomplete * fix: scale and ru in jinad * fix: fix more jinad tests Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> * fix: fix flow test * fix: improve pea tests reliability (#4136) Co-authored-by: Joan Fontanals <joan.martinez@jina.ai> Co-authored-by: Jina Dev Bot <dev-bot@jina.ai> Co-authored-by: Deepankar Mahapatro <deepankar.mahapatro@jina.ai> Co-authored-by: bwanglzu <bo.wang@jina.ai> Co-authored-by: AlaeddineAbdessalem <alaeddine-13@live.fr> Co-authored-by: Zhaofeng Miao <522856232@qq.com>

def get_rename_function(mapper):

pandas/core/common.py

pandas

Python

830130a543619fe945365fdea5e6e5877fe81c6f

common.py

get_rename_function

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

TYP: Series.quantile (#47304) * TYP: Series.quantile * common.py

def _call_boxer(self, candc_out, verbose=False): f = None try: fd, temp_filename = tempfile.mkstemp( prefix="boxer-", suffix=".in", text=True ) f = os.fdopen(fd, "w") f.write(candc_out.decode("utf-8")) finally: if f: f.close() args = [ "--box", "false", "--semantics", "drs", #'--flat', 'false', # removed from boxer "--resolve", ["false", "true"][self._resolve], "--elimeq", ["false", "true"][self._elimeq], "--format", "prolog", "--instantiate", "true", "--input", temp_filename, ] stdout = self._call(None, self._boxer_bin, args, verbose) os.remove(temp_filename) return stdout

nltk/sem/boxer.py

nltk

Python

c6d9e0529eecce2c0742ca47135b28e5316611e0

boxer.py

_call_boxer

https://github.com/nltk/nltk.git

Update boxer.py Used to have this py2 to py3 error TypeError: write() argument must be str, not bytes

def unique_id() -> str: return binascii.hexlify(os.urandom(16)).decode("utf-8")

certbot-apache/certbot_apache/_internal/apache_util.py

certbot

Python

7d9e9a49005de7961e84d2a7c608db57dbab3046

apache_util.py

unique_id

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

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

def add_auto_adjustable_area(self, use_axes, pad=0.1, adjust_dirs=None): if adjust_dirs is None: adjust_dirs = ["left", "right", "bottom", "top"] for d in adjust_dirs: self.append_size(d, Size._AxesDecorationsSize(use_axes, d) + pad)

lib/mpl_toolkits/axes_grid1/axes_divider.py

matplotlib

Python

eb12b029ffe2f110540a4338684d1a729d1ddfc5

axes_divider.py

add_auto_adjustable_area

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

Document, test, and simplify impl. of auto_adjustable_area. Document behavior of auto_adjustable_area, and slightly modernize the example. Simplify its implementation: `Padded` is just size addition and `GetExtentHelper` and `SizeFromFunc` can reasonably be fused into a single class; none of them are used anywhere else, so just deprecate them as public APIs. Add a test.

def test_failure_subschema(self, obj): with pytest.raises(validate.ValidationError) as cm: validate.validate(validate.attr({"foo": str}), obj) assert_validationerror(cm.value, )

tests/test_api_validate.py

streamlink

Python

d09112ab1f6db6aa605650fe1ff6a3028344f90d

test_api_validate.py

test_failure_subschema

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

plugin.api.validate: rewrite tests Completely rewrite tests using pytest, with full coverage

def clear_checkbox_id(self, name): return name + "_id"

django/forms/widgets.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

widgets.py

clear_checkbox_id

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

Refs #33476 -- Reformatted code with Black.

def done(self): with self._condition: return self._state in [CANCELLED, CANCELLED_AND_NOTIFIED, FINISHED]

python3.10.4/Lib/concurrent/futures/_base.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_base.py

done

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

add python 3.10.4 for windows

def get_data(filters): data = [] conditions = get_conditions(filters) salary_slips = frappe.db.sql( % (conditions), as_dict=1, ) component_type_dict = frappe._dict( frappe.db.sql( ) ) if not len(component_type_dict): return [] entry = frappe.db.sql( % (conditions, ", ".join(["%s"] * len(component_type_dict))), tuple(component_type_dict.keys()), as_dict=1, ) data_list = prepare_data(entry, component_type_dict) for d in salary_slips: total = 0 if data_list.get(d.name): employee = { "employee": data_list.get(d.name).get("employee"), "employee_name": data_list.get(d.name).get("employee_name"), "pf_account": data_list.get(d.name).get("pf_account"), } if data_list.get(d.name).get("Provident Fund"): employee["pf_amount"] = data_list.get(d.name).get("Provident Fund") total += data_list.get(d.name).get("Provident Fund") if data_list.get(d.name).get("Additional Provident Fund"): employee["additional_pf"] = data_list.get(d.name).get("Additional Provident Fund") total += data_list.get(d.name).get("Additional Provident Fund") if data_list.get(d.name).get("Provident Fund Loan"): employee["pf_loan"] = data_list.get(d.name).get("Provident Fund Loan") total += data_list.get(d.name).get("Provident Fund Loan") employee["total"] = total data.append(employee) return data @frappe.whitelist()

erpnext/regional/report/provident_fund_deductions/provident_fund_deductions.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

provident_fund_deductions.py

get_data

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

style: format code with black

def dag_list_import_errors(args): dagbag = DagBag(process_subdir(args.subdir)) data = [] for filename, errors in dagbag.import_errors.items(): data.append({"filepath": filename, "error": errors}) AirflowConsole().print_as( data=data, output=args.output, ) @cli_utils.action_cli @suppress_logs_and_warning

airflow/cli/commands/dag_command.py

@cli_utils.action_cli @suppress_logs_and_warning

airflow

Python

e1134590973355549272b1f3a213dbfa29698df7

dag_command.py

dag_list_import_errors

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

Add `list-import-errors` to `airflow dags` command (#22084) This will help users to see the dags with import error and enable scripts process the output

def mktime_tz(data): if data[9] is None: # No zone info, so localtime is better assumption than GMT return time.mktime(data[:8] + (-1,)) else: t = calendar.timegm(data) return t - data[9]

python3.10.4/Lib/email/_parseaddr.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_parseaddr.py

mktime_tz

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

add python 3.10.4 for windows

def identbodychars(cls): return "".join( sorted( set( cls.identchars + "0123456789" + "".join( [c for c in cls._chars_for_ranges if ("_" + c).isidentifier()] ) ) ) )

pipenv/patched/notpip/_vendor/pyparsing/unicode.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

unicode.py

identbodychars

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

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

def require_tf(test_case): return unittest.skipUnless(is_tf_available(), "test requires TensorFlow")(test_case)

src/transformers/testing_utils.py

transformers

Python

57e6464ac9a31156f1c93e59107323e6ec01309e

testing_utils.py

require_tf

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

Update all require decorators to use skipUnless when possible (#16999)

def test_constrained_layout23(): for i in range(2): fig = plt.figure(layout="constrained", clear=True, num="123") gs = fig.add_gridspec(1, 2) sub = gs[0].subgridspec(2, 2) fig.suptitle("Suptitle{}".format(i)) @image_comparison(['test_colorbar_location.png'], remove_text=True, style='mpl20')

lib/matplotlib/tests/test_constrainedlayout.py

@image_comparison(['test_colorbar_location.png'], remove_text=True, style='mpl20')

matplotlib

Python

ec4dfbc3c83866f487ff0bc9c87b0d43a1c02b22

test_constrainedlayout.py

test_constrained_layout23

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

ENH: implement and use base layout_engine for more flexible layout.

def test_positive_integer_or_none_3(): assert_raises(Exception, positive_integer_or_none, 'foobar')

tests/driver_tests.py

tpot

Python

388616b6247ca4ea8de4e2f340d6206aee523541

driver_tests.py

test_positive_integer_or_none_3

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

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

def get_list_display_add_buttons(self, request): return self.list_display_add_buttons or self.get_list_display(request)[0]

wagtail/contrib/modeladmin/options.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

options.py

get_list_display_add_buttons

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

Reformat with black

def _update_size_variant(self) -> None: width, height = self.size position_data = { "width": width, "height": height, } self.update(Panel(Align.center(Pretty(position_data)), title="Placeholder"))

src/textual/widgets/_placeholder.py

textual

Python

67947d5806bb3181eba349f0da3fd35e0542d1be

_placeholder.py

_update_size_variant

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

Fix documentation about the variant 'size'.

def mass_matrix_full_implicit(self): return self._mass_matrix_full(False)

sympy/physics/mechanics/kane.py

sympy

Python

1e522ee112f19216f367b457b6804fd58b94f28b

kane.py

mass_matrix_full_implicit

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

redo of #22626 based on feedback

def test_import_error(self): self.write_settings_with_import_error("settings.py") args = ["check", "admin_scripts"] out, err = self.run_manage(args) self.assertNoOutput(out) self.assertOutput(err, "No module named") self.assertOutput(err, "foo42bar")

tests/admin_scripts/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_import_error

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

Refs #33476 -- Reformatted code with Black.

def test_displacy_parse_spans_with_kb_id_options(en_vocab): doc = Doc(en_vocab, words=["Welcome", "to", "the", "Bank", "of", "China"]) doc.spans["sc"] = [ Span(doc, 3, 6, "ORG", kb_id="Q790068"), Span(doc, 5, 6, "GPE", kb_id="Q148"), ] spans = displacy.parse_spans( doc, {"kb_url_template": "https://wikidata.org/wiki/{}"} ) assert isinstance(spans, dict) assert spans["text"] == "Welcome to the Bank of China " assert spans["spans"] == [ { "start": 15, "end": 28, "start_token": 3, "end_token": 6, "label": "ORG", "kb_id": "Q790068", "kb_url": "https://wikidata.org/wiki/Q790068", }, { "start": 23, "end": 28, "start_token": 5, "end_token": 6, "label": "GPE", "kb_id": "Q148", "kb_url": "https://wikidata.org/wiki/Q148", }, ]

spacy/tests/test_displacy.py

spaCy

Python

a79cd3542b3dd667d8a97293462e22ed26a04ee5

test_displacy.py

test_displacy_parse_spans_with_kb_id_options

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

Add displacy support for overlapping Spans (#10332) * Fix docstring for EntityRenderer * Add warning in displacy if doc.spans are empty * Implement parse_spans converter One notable change here is that the default spans_key is sc, and it's set by the user through the options. * Implement SpanRenderer Here, I implemented a SpanRenderer that looks similar to the EntityRenderer except for some templates. The spans_key, by default, is set to sc, but can be configured in the options (see parse_spans). The way I rendered these spans is per-token, i.e., I first check if each token (1) belongs to a given span type and (2) a starting token of a given span type. Once I have this information, I render them into the markup. * Fix mypy issues on typing * Add tests for displacy spans support * Update colors from RGB to hex Co-authored-by: Ines Montani <ines@ines.io> * Remove unnecessary CSS properties * Add documentation for website * Remove unnecesasry scripts * Update wording on the documentation Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com> * Put typing dependency on top of file * Put back z-index so that spans overlap properly * Make warning more explicit for spans_key Co-authored-by: Ines Montani <ines@ines.io> Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

def __getitem__(self, key): if key is None: key = self._key() value = self._get_recursive(key) if value is None: value = self[key] = self.default_factory() return value

keras/backend.py

keras

Python

3613c3defc39c236fb1592c4f7ba1a9cc887343a

backend.py

__getitem__

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

Remove pylint comments. PiperOrigin-RevId: 452353044

def resume_end(self) -> None: assert self.trainer.state.fn is not None if self.resume_checkpoint_path: if self.trainer.state.fn == TrainerFn.FITTING: rank_zero_info(f"Restored all states from the checkpoint file at {self.resume_checkpoint_path}") elif self.trainer.state.fn in (TrainerFn.VALIDATING, TrainerFn.TESTING, TrainerFn.PREDICTING): rank_zero_info(f"Loaded model weights from checkpoint at {self.resume_checkpoint_path}") # TODO: remove resume_from_checkpoint_fit_path in v2.0 if ( self.trainer.state.fn == TrainerFn.FITTING and self.resume_checkpoint_path == self.resume_from_checkpoint_fit_path ): self.resume_from_checkpoint_fit_path = None self.resume_checkpoint_path = None self._loaded_checkpoint = {} # clear cache after restore torch.cuda.empty_cache() # wait for all to catch up self.trainer.strategy.barrier("CheckpointConnector.resume_end")

pytorch_lightning/trainer/connectors/checkpoint_connector.py

lightning

Python

5693a94c320297cf007f3bfd13ce4d7deeb1954a

checkpoint_connector.py

resume_end

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

Extend the deprecation of `Trainer(resume_from_checkpoint)` (#11334)

def unfrack_path(pathsep=False, follow=True):

lib/ansible/cli/arguments/option_helpers.py

ansible

Python

b1ff0f4ebc7e964f8f67ffc344815a0d23577f45

option_helpers.py

unfrack_path

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

vault secrets file, keep context when symlink (#78734) * vault secrets file, keep context when symlink fixes #18319 Co-authored-by: Sloane Hertel <19572925+s-hertel@users.noreply.github.com>

def get_freq(self) -> str | None: if not self.is_monotonic or not self.index._is_unique: return None delta = self.deltas[0] ppd = periods_per_day(self._reso) if delta and _is_multiple(delta, ppd): return self._infer_daily_rule() # Business hourly, maybe. 17: one day / 65: one weekend if self.hour_deltas in ([1, 17], [1, 65], [1, 17, 65]): return "BH" # Possibly intraday frequency. Here we use the # original .asi8 values as the modified values # will not work around DST transitions. See #8772 if not self.is_unique_asi8: return None delta = self.deltas_asi8[0] pph = ppd // 24 ppm = pph // 60 pps = ppm // 60 if _is_multiple(delta, pph): # Hours return _maybe_add_count("H", delta / pph) elif _is_multiple(delta, ppm): # Minutes return _maybe_add_count("T", delta / ppm) elif _is_multiple(delta, pps): # Seconds return _maybe_add_count("S", delta / pps) elif _is_multiple(delta, (pps // 1000)): # Milliseconds return _maybe_add_count("L", delta / (pps // 1000)) elif _is_multiple(delta, (pps // 1_000_000)): # Microseconds return _maybe_add_count("U", delta / (pps // 1_000_000)) else: # Nanoseconds return _maybe_add_count("N", delta)

pandas/tseries/frequencies.py

pandas

Python

e9350a4affbb424aaecad279f638a0dd1584df68

frequencies.py

get_freq

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

infer_freq handle non-nano (#47126) * infer_freq handle non-nano * remove unused import

def require_tensorflow(test_case): if not is_tensorflow_available(): return unittest.skip("test requires TensorFlow")(test_case) else: return test_case

src/accelerate/test_utils/testing.py

accelerate

Python

5668270de74a09e5bff15891054f73ddbb1176ac

testing.py

require_tensorflow

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

Add logging capabilities (#293) Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> - Added experiment tracking API, and support for Weights and Biases, TensorBoard, and CometML + Tests - Added `tensorflow` to a new dependency list to be used during tests - Added three new functions in `Accelerator` to interact with the API

def _errt(self): # Count (UI, OI) pairs for truncation points until we find the segment where (ui, oi) crosses the truncation line self.coords = self._get_truncation_coordinates() if (0.0, 0.0) in self.coords: # Truncation line goes through origo, so ERRT cannot be counted if (self.ui, self.oi) != (0.0, 0.0): return float("inf") else: return float("nan") if (self.ui, self.oi) == (0.0, 0.0): # (ui, oi) is origo; define errt as 0.0 return 0.0 # Count the intersection point # Note that (self.ui, self.oi) cannot be (0.0, 0.0) and self.coords has different coordinates # so we have actual line segments instead of a line segment and a point intersection = _count_intersection( ((0, 0), (self.ui, self.oi)), self.coords[-2:] ) # Count OP (length of the line from origo to (ui, oi)) op = sqrt(self.ui**2 + self.oi**2) # Count OT (length of the line from origo to truncation line that goes through (ui, oi)) ot = sqrt(intersection[0] ** 2 + intersection[1] ** 2) # OP / OT tells how well the stemming algorithm works compared to just truncating words return op / ot

nltk/metrics/paice.py

nltk

Python

0fac0c0f8e4618c2bdd3d2137d5fb8a80f581246

paice.py

_errt

https://github.com/nltk/nltk.git

Update black to 22.3.0 The most recent release of Click (8.1.0) was breaking Black. See psf/black#2964

def get_tf_version(): global _TF_VERS # pylint:disable=global-statement if _TF_VERS is None: import tensorflow as tf # pylint:disable=import-outside-toplevel _TF_VERS = float(".".join(tf.__version__.split(".")[:2])) # pylint:disable=no-member return _TF_VERS

lib/utils.py

faceswap

Python

c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf

utils.py

get_tf_version

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

Update code to support Tensorflow versions up to 2.8 (#1213) * Update maximum tf version in setup + requirements * - bump max version of tf version in launcher - standardise tf version check * update keras get_custom_objects for tf>2.6 * bugfix: force black text in GUI file dialogs (linux) * dssim loss - Move to stock tf.ssim function * Update optimizer imports for compatibility * fix logging for tf2.8 * Fix GUI graphing for TF2.8 * update tests * bump requirements.txt versions * Remove limit on nvidia-ml-py * Graphing bugfixes - Prevent live graph from displaying if data not yet available * bugfix: Live graph. Collect loss labels correctly * fix: live graph - swallow inconsistent loss errors * Bugfix: Prevent live graph from clearing during training * Fix graphing for AMD

def _compile_output(self) -> Union[List[str], List[Tuple[str, int]]]: action = self._job.replace("-", "_") processor = getattr(self, f"_get_{action}") logger.debug("Processor: %s", processor) return [item for item in processor()] # pylint:disable=unnecessary-comprehension

tools/alignments/jobs.py

faceswap

Python

e2a77e7c6e84e81f642cb22f528e25e3f2d2dbc1

jobs.py

_compile_output

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

Alignments Tool - Typing, Documentation + Re-org

def find_submodule_and_param_name(model, long_key, start_prefix): if len(start_prefix) > 0 and long_key.startswith(start_prefix): long_key = ".".join(long_key.split(".")[1:]) split_key = long_key.split(".") submodule = model while len(split_key) > 1: if hasattr(submodule, split_key[0]): submodule = getattr(submodule, split_key[0]) del split_key[0] else: submodule = None break if submodule == model: submodule = None return submodule, split_key[0]

src/transformers/modeling_utils.py

transformers

Python

5da33f872913255d64717efe745a053975bbc28e

modeling_utils.py

find_submodule_and_param_name

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

[modeling utils] revamp `from_pretrained(..., low_cpu_mem_usage=True)` + tests (#16657) * add low_cpu_mem_usage tests * wip: revamping * wip * install /usr/bin/time * wip * cleanup * cleanup * cleanup * cleanup * cleanup * fix assert * put the wrapper back * cleanup; switch to bert-base-cased * Trigger CI * Trigger CI

def test_task_group_context_mix(): from airflow.decorators import task

tests/utils/test_task_group.py

airflow

Python

49e336ae0302b386a2f47269a6d13988382d975f

test_task_group.py

test_task_group_context_mix

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

Replace usage of `DummyOperator` with `EmptyOperator` (#22974) * Replace usage of `DummyOperator` with `EmptyOperator`

def add_noise_to_input(self, sample, sigma, generator=None): if self.s_min <= sigma <= self.s_max: gamma = min(self.s_churn / self.num_inference_steps, 2**0.5 - 1) else: gamma = 0 # sample eps ~ N(0, S_noise^2 * I) eps = self.s_noise * torch.randn(sample.shape, generator=generator).to(sample.device) sigma_hat = sigma + gamma * sigma sample_hat = sample + ((sigma_hat**2 - sigma**2) ** 0.5 * eps) return sample_hat, sigma_hat

src/diffusers/schedulers/scheduling_karras_ve.py

diffusers

Python

dd10da76a78e9566d12ddf1eb5aac90021b7e51d

scheduling_karras_ve.py

add_noise_to_input

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

Add an alternative Karras et al. stochastic scheduler for VE models (#160) * karras + VE, not flexible yet * Fix inputs incompatibility with the original unet * Roll back sigma scaling * Apply suggestions from code review * Old comment * Fix doc

def _getPythonForSconsExePath(): python_exe = Options.getPythonPathForScons() if python_exe is not None: return python_exe scons_supported_pythons = ("3.5", "3.6", "3.7", "3.8", "3.9", "3.10") if not Utils.isWin32Windows(): scons_supported_pythons += ("2.7", "2.6") # Our inline copy needs no other module, just the right version of Python is needed. python_for_scons = findInstalledPython( python_versions=scons_supported_pythons, module_name=None, module_version=None ) if python_for_scons is None: if Utils.isWin32Windows(): scons_python_requirement = "Python 3.5 or higher" else: scons_python_requirement = "Python 2.6, 2.7 or Python >= 3.5" Tracing.scons_logger.sysexit( % scons_python_requirement ) return python_for_scons.getPythonExe() @contextlib.contextmanager

nuitka/build/SconsInterface.py

@contextlib.contextmanager

Nuitka

Python

c4ce69f97f7fefbcf637e9e59b6df056ad03eb16

SconsInterface.py

_getPythonForSconsExePath

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

Scons: Refactor Python scan for major cleanup * This is in preparation of making it reusable for onefile compression which also has a simular need.

def test_func(self, qapp): pytest.importorskip("qutebrowser.qt.opengl") version.opengl_info()

tests/unit/utils/test_version.py

qutebrowser

Python

d387b1a1084b9649009e5cffb9d71facc80bb41f

test_version.py

test_func

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

tests: Adjust most imports

def classifiers(self): url = self.repository+'?:action=list_classifiers' response = urllib.request.urlopen(url) log.info(self._read_pypi_response(response))

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

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

register.py

classifiers

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

add python 3.10.4 for windows

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

packages/python/plotly/plotly/graph_objs/bar/marker/_colorbar.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_colorbar.py

yanchor

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

switch to black .22

def _debugger_window_is_open(): if _Debugger.debugger is None: return False debugger = _Debugger.debugger if debugger.popout_window or debugger.watcher_window: return True return False

PySimpleGUI.py

PySimpleGUI

Python

37c3afc8ca0dc0057a23ab512ee8b879074dd119

PySimpleGUI.py

_debugger_window_is_open

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

ButtonMenu.Click aliased added. Debugger - automatically adds a timeout to read calls if a debug window is open. Still need to handle user-level multi-window support.

def detected_faces(self) -> List["DetectedFace"]: return self._detected_faces

plugins/extract/pipeline.py

faceswap

Python

1022651eb8a7741014f5d2ec7cbfe882120dfa5f

pipeline.py

detected_faces

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

Bugfix: convert - Gif Writer - Fix non-launch error on Gif Writer - convert plugins - linting - convert/fs_media/preview/queue_manager - typing - Change convert items from dict to Dataclass

def _check_input_folder(self) -> bool: if not os.path.exists(self._args.input_dir): logger.error("Input location %s not found.", self._args.input_dir) sys.exit(1) if (os.path.isfile(self._args.input_dir) and os.path.splitext(self._args.input_dir)[1].lower() in _video_extensions): logger.info("Input Video: %s", self._args.input_dir) retval = True else: logger.info("Input Directory: %s", self._args.input_dir) retval = False return retval

scripts/fsmedia.py

faceswap

Python

1022651eb8a7741014f5d2ec7cbfe882120dfa5f

fsmedia.py

_check_input_folder

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

Bugfix: convert - Gif Writer - Fix non-launch error on Gif Writer - convert plugins - linting - convert/fs_media/preview/queue_manager - typing - Change convert items from dict to Dataclass

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

tools/manual/detected_faces.py

faceswap

Python

5e73437be47f2410439a3c6716de96354e6a0c94

detected_faces.py

_background_extract

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

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

def test_default_kwargs():

tests/unit/test_isolation.py

pyinstaller

Python

3ba0aaf983f5223000a713c9275ea66e21f78b11

test_isolation.py

test_default_kwargs

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

tests: add a test for calling isolated function with default (kw)args Add tests that show that current implementation does not transfer default arguments (function.__defaults__) nor default keyword-only arguments (function.__kwdefaults__) to the child process, resulting in a missing-positional-argument error unless all optional arguments are explicitly provided.

def _tune_legacy_checkpoint_score_attr(self) -> Optional[str]: if self.checkpoint_score_attribute is None: return self.checkpoint_score_attribute prefix = "" if self.checkpoint_score_order == MIN: prefix = "min-" return f"{prefix}{self.checkpoint_score_attribute}" # Alias for backwards compatibility deprecation_message = ( "`CheckpointStrategy` is deprecated and will be removed in " "the future. Please use `ray.air.config.CheckpointStrategy` " "instead." ) @Deprecated(message=deprecation_message) @dataclass

python/ray/util/ml_utils/checkpoint_manager.py

@Deprecated(message=deprecation_message) @dataclass

ray

Python

dc7ed086a5038775e378b32cb31fb4a79f418dd9

checkpoint_manager.py

_tune_legacy_checkpoint_score_attr

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

[AIR] More checkpoint configurability, `Result` extension (#25943) This PR: * Allows the user to set `keep_checkpoints_num` and `checkpoint_score_attr` in `RunConfig` using the `CheckpointStrategy` dataclass * Adds two new fields to the `Result` object - `best_checkpoints` - a list of saved best checkpoints as determined by `CheckpointingConfig`.

def test_receive_data_before_server_connected(tctx): assert ( Playbook(tcp.TCPLayer(tctx), hooks=False) << OpenConnection(tctx.server) >> DataReceived(tctx.client, b"hello!") >> reply(None, to=-2) << SendData(tctx.server, b"hello!") )

test/mitmproxy/proxy/layers/test_tcp.py

mitmproxy

Python

b3587b52b25077f68116b9852b041d33e7fc6601

test_tcp.py

test_receive_data_before_server_connected

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

make it black!

def demo_tp(rank, args): print(f"Running basic Megatron style TP example on rank {rank}.") setup(rank, args.world_size) # create a sharding plan based on the given world_size. module_sharding_plan = _get_toy_module_sharding_plan( args.world_size ) # create model and move it to GPU with id rank model = ToyModel().cuda(rank) # Shard the module based on created plan. shard_module(model, module_sharding_plan) # Create a optimizer for the sharded module. optimizer = _get_toy_module_optim(model, 0.002) # Perform a num of iterations of forward/backward # and optimizations for the sharded module. for _ in range(args.iter_nums): inp = torch.rand(20, 10).cuda(rank) output = model(inp) output.sum().backward() optimizer.step() cleanup()

distributed/sharded_tensor/tensor_parallel.py

examples

Python

9ba53df5a19131e6926027b2e73aaa77cec17272

tensor_parallel.py

demo_tp

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

Gh/fduwjj/2/base (#1007) * test ghstack [ghstack-poisoned] * Update base for Update on "[PT-D] Add an example for Megatron-LM style example" [ghstack-poisoned] * Update base for Update on "[PT-D] Add an example for Megatron-LM style example" [ghstack-poisoned] * Update base for Update on "[PT-D] Add an example for Megatron-LM style example" [ghstack-poisoned] * Update base for Update on "[PT-D] Add an example for Megatron-LM style example" [ghstack-poisoned] * [PT-D] Add an example for Megatron-LM style example (#1006) * [PT-D] Add an example for Megatron-LM style example [ghstack-poisoned] * Update on "[PT-D] Add an example for Megatron-LM style example" [ghstack-poisoned]

def makelink(self, tarinfo, targetpath): try: # For systems that support symbolic and hard links. if tarinfo.issym(): os.symlink(tarinfo.linkname, targetpath) else: # See extract(). if os.path.exists(tarinfo._link_target): os.link(tarinfo._link_target, targetpath) else: self._extract_member(self._find_link_target(tarinfo), targetpath) except symlink_exception: if tarinfo.issym(): linkpath = os.path.join(os.path.dirname(tarinfo.name), tarinfo.linkname) else: linkpath = tarinfo.linkname else: try: self._extract_member(self._find_link_target(tarinfo), targetpath) except KeyError: raise ExtractError("unable to resolve link inside archive")

pipenv/patched/notpip/_vendor/distlib/_backport/tarfile.py

pipenv

Python

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0

tarfile.py

makelink

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

Vendor in pip 22.1.2

def get_rules(self) -> RulesMap:

src/textual/css/styles.py

textual

Python

116f3735b68e8dd293dba4b3a183f98afbd0b167

styles.py

get_rules

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

docstrings

def test_fillna_frame(self): super().test_fillna_frame() unhashable = pytest.mark.xfail(reason="Unhashable")

pandas/tests/extension/json/test_json.py

pandas

Python

24652cf178c12562585639cba39c46d62b95f107

test_json.py

test_fillna_frame

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

TST: Convert skip -> xfail (#46427)

def push(self, exit): # We use an unbound method rather than a bound method to follow # the standard lookup behaviour for special methods. _cb_type = type(exit) try: exit_method = _cb_type.__exit__ except AttributeError: # Not a context manager, so assume it's a callable. self._push_exit_callback(exit) else: self._push_cm_exit(exit, exit_method) return exit # Allow use as a decorator.

python3.10.4/Lib/contextlib.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

contextlib.py

push

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

add python 3.10.4 for windows

async def test_filter_non_existent_column(state_api_manager): data_source_client = state_api_manager.data_source_client id = b"1234" data_source_client.get_all_worker_info.return_value = GetAllWorkerInfoReply( worker_table_data=[ generate_worker_data(id, pid=1), generate_worker_data(b"12345", pid=2), ], total=2, ) result = await state_api_manager.list_workers( option=create_api_options(filters=[("exit_type", "=", "INTENDED_SYSTEM_EXIT")]) ) assert len(result.result) == 0

python/ray/tests/test_state_api.py

ray

Python

37f4692aa805eba230e2879c098320111788a64c

test_state_api.py

test_filter_non_existent_column

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

[State Observability] Fix "No result for get crashing the formatting" and "Filtering not handled properly when key missing in the datum" #26881 Fix two issues No result for get crashing the formatting Filtering not handled properly when key missing in the datum

def _url(self, hashed_name_func, name, force=False, hashed_files=None): if settings.DEBUG and not force: hashed_name, fragment = name, "" else: clean_name, fragment = urldefrag(name) if urlsplit(clean_name).path.endswith("/"): # don't hash paths hashed_name = name else: args = (clean_name,) if hashed_files is not None: args += (hashed_files,) hashed_name = hashed_name_func(*args) final_url = super().url(hashed_name) # Special casing for a @font-face hack, like url(myfont.eot?#iefix") # http://www.fontspring.com/blog/the-new-bulletproof-font-face-syntax query_fragment = "?#" in name # [sic!] if fragment or query_fragment: urlparts = list(urlsplit(final_url)) if fragment and not urlparts[4]: urlparts[4] = fragment if query_fragment and not urlparts[3]: urlparts[2] += "?" final_url = urlunsplit(urlparts) return unquote(final_url)

django/contrib/staticfiles/storage.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

storage.py

_url

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

Refs #33476 -- Reformatted code with Black.

def set_raw_scale(self, in_, scale): self.__check_input(in_) self.raw_scale[in_] = scale

code/deep/BJMMD/caffe/python/caffe/io.py

transferlearning

Python

cc4d0564756ca067516f71718a3d135996525909

io.py

set_raw_scale

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

Balanced joint maximum mean discrepancy for deep transfer learning

def list_distinfo_files(self): base = os.path.dirname(self.path) for path, checksum, size in self._get_records(): # XXX add separator or use real relpath algo if not os.path.isabs(path): path = os.path.join(base, path) if path.startswith(self.path): yield path

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

database.py

list_distinfo_files

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

upd; format

def validate(self): if not self._check_schedule_interval_matches_timetable(): raise AirflowDagInconsistent( f"inconsistent schedule: timetable {self.timetable.summary!r} " f"does not match schedule_interval {self.schedule_interval!r}", ) self.params.validate() self.timetable.validate()

airflow/models/dag.py

airflow

Python

a1a9a8f9a3adc63e783cf3fd699066f35e488d4f

dag.py

validate

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

Check bag DAG schedule_interval match tiemtable (#23113) This guards against the DAG's timetable or schedule_interval from being changed after it's created. Validation is done by creating a timetable and check its summary matches schedule_interval. The logic is not bullet-proof, especially if a custom timetable does not provide a useful summary. But this is the best we can do.

def get_tokenizer(*args, **kwargs): return AlbertTokenizer.from_pretrained(pretrained_model_name_or_path='albert-base-v1', *args, **kwargs)

modules/text/language_model/albert-base-v1/module.py

PaddleHub

Python

26e56d098d7cebdc910e84ce1d0d1a909c1988c3

module.py

get_tokenizer

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

add albert-base-v1

def exit_with_error(message, code=1, **kwargs): kwargs.setdefault("style", "red") app.console.print(message, **kwargs) raise typer.Exit(code)

src/prefect/cli/base.py

prefect

Python

c0cb1fee460c1bded9e3eb741ad7979402844bf8

base.py

exit_with_error

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

Update `set` command; allow CLI `console` object to be patched

async def contracts_command(ctx, ticker="", past_transaction_days="", raw=""): try: # Debug user input if cfg.DEBUG: logger.debug( "!stocks.gov.contracts %s %s %s", ticker, past_transaction_days, raw ) if past_transaction_days == "": past_transaction_days = 10 else: if not past_transaction_days.lstrip("-").isnumeric(): raise Exception("Number has to be an integer") past_transaction_days = int(past_transaction_days) if raw in ["false", "False", "FALSE", ""]: raw = False if raw in ["true", "True", "TRUE"]: raw = True if raw not in [True, False]: raise Exception("raw argument has to be true or false") if ticker == "": raise Exception("A ticker is required") # Retrieve Data df_contracts = quiverquant_model.get_government_trading("contracts", ticker) if df_contracts.empty: raise Exception("No government contracts found") # Output Data df_contracts["Date"] = pd.to_datetime(df_contracts["Date"]).dt.date df_contracts = df_contracts[ df_contracts["Date"].isin( df_contracts["Date"].unique()[:past_transaction_days] ) ] df_contracts.drop_duplicates(inplace=True) fig, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI) df_contracts.groupby("Date").sum().div(1000).plot(kind="bar", rot=0, ax=ax) ax.set_ylabel("Amount ($1k)") ax.set_title(f"Sum of latest government contracts to {ticker}") fig.tight_layout() plt.savefig("gov_contracts.png") uploaded_image = gst_imgur.upload_image("gov_contracts.png", title="something") image_link = uploaded_image.link if cfg.DEBUG: logger.debug("Image URL: %s", image_link) title = f"Stocks: [quiverquant.com] Contracts by {ticker}" if raw: description = df_contracts.to_string() embed = discord.Embed( title=title, description=description, colour=cfg.COLOR ) else: embed = discord.Embed(title=title, colour=cfg.COLOR) embed.set_author( name=cfg.AUTHOR_NAME, icon_url=cfg.AUTHOR_ICON_URL, ) embed.set_image(url=image_link) os.remove("gov_contracts.png") await ctx.send(embed=embed) except Exception as e: embed = discord.Embed( title=f"ERROR Stocks: [quiverquant.com] Contracts by {ticker}", colour=cfg.COLOR, description=e, ) embed.set_author( name=cfg.AUTHOR_NAME, icon_url=cfg.AUTHOR_ICON_URL, ) await ctx.send(embed=embed)

discordbot/stocks/government/contracts.py

OpenBBTerminal

Python

f40ba0d256a78ab2b8461f0df3a9a52ca7dc5704

contracts.py

contracts_command

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

Bot logging fix (#1105) * Write bot logs to stdout instead of a file Heroku's logging uses the stdout and has problems with files * Send "you snooze you lose" only if debug flag is enabled * Replace print statements with logger entries in the economy menu * Add logging to bot menu command calls * Silence bandit warnings about the REPLACE_ME token * Organize imports and update logging in economy menu * Organize imports and update logging in dps menu * Organize imports and update logging in dd menu * Organize imports and update logging in gov menu * Organize imports and update logging in options menu * Organize imports and update logging in screener menu * Organize imports and update logging in ta menu * Revert automatic import sorting * Add logging to the options reaction helper

async def test_storage_is_updated_on_add(hass, hass_storage, utcnow): await setup_test_component(hass, create_lightbulb_service) entity_map: EntityMapStorage = hass.data[ENTITY_MAP] hkid = "00:00:00:00:00:00" # Is in memory store updated? assert hkid in entity_map.storage_data # Is saved out to store? await flush_store(entity_map.store) assert hkid in hass_storage[ENTITY_MAP]["data"]["pairings"]

tests/components/homekit_controller/test_storage.py

core

Python

b9c8d65940ec47a82332b8b1a67301da018ccadf

test_storage.py

test_storage_is_updated_on_add

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

Restore accessory state into pairing using new HKC methods (#75276)

def disable_run_logger(): with disable_logger("prefect.flow_run"), disable_logger("prefect.task_run"): yield

src/prefect/logging/loggers.py

prefect

Python

895a5203623c205ede2ee0c31f99be72822d5351

loggers.py

disable_run_logger

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

Add docstring

def add_to_apply_calls(self, func, *args, length=None, width=None, **kwargs): return PandasOnDaskDataframePartition( self._data, call_queue=self.call_queue + [[func, args, kwargs]], length=length, width=width, )

modin/core/execution/dask/implementations/pandas_on_dask/partitioning/partition.py

modin

Python

39b36eb2a2e3bf3d612933e1c78545a8bb28cde4

partition.py

add_to_apply_calls

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

PERF-#4794: Compute caches in `_propagate_index_objs` (#4888) Co-authored-by: Mahesh Vashishtha <mvashishtha@users.noreply.github.com> Signed-off-by: Myachev <anatoly.myachev@intel.com>

def use_numexpr_cb(key) -> None: from pandas.core.computation import expressions expressions.set_use_numexpr(cf.get_option(key)) use_numba_doc =

pandas/core/config_init.py

pandas

Python

9612375ca28ade056f15d4338f1bfde5d045c9fc

config_init.py

use_numexpr_cb

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

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

def test_unavailable_models(self): state = migrations.state.ProjectState() # Unavailable contenttypes.ContentType with self.assertNumQueries(0): create_permissions(self.app_config, verbosity=0, apps=state.apps) # Unavailable auth.Permission state = migrations.state.ProjectState(real_apps={"contenttypes"}) with self.assertNumQueries(0): create_permissions(self.app_config, verbosity=0, apps=state.apps)

tests/auth_tests/test_management.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

test_management.py

test_unavailable_models

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

Refs #33476 -- Reformatted code with Black.

def info(self): return self.headers

python3.10.4/Lib/http/client.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

client.py

info

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

add python 3.10.4 for windows

def get_timestamped_export_dir(export_dir_base): attempts = 0 while attempts < MAX_DIRECTORY_CREATION_ATTEMPTS: timestamp = int(time.time()) result_dir = tf.io.gfile.join( tf.compat.as_bytes(export_dir_base), tf.compat.as_bytes(str(timestamp)), ) if not tf.compat.v1.gfile.Exists(result_dir): # Collisions are still possible (though extremely unlikely): this # directory is not actually created yet, but it will be almost # instantly on return from this function. return result_dir time.sleep(1) attempts += 1 logging.warning( "Directory {} already exists; retrying (attempt {}/{})".format( tf.compat.as_str(result_dir), attempts, MAX_DIRECTORY_CREATION_ATTEMPTS, ) ) raise RuntimeError( "Failed to obtain a unique export directory name after " f"{MAX_DIRECTORY_CREATION_ATTEMPTS} attempts." )

keras/saving/utils_v1/export_utils.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

export_utils.py

get_timestamped_export_dir

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def compare(self, a, b): a = _convert_other(a, raiseit=True) return a.compare(b, context=self)

python3.10.4/Lib/_pydecimal.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

compare

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

add python 3.10.4 for windows

async def count_daily_user_type(self) -> Dict[str, int]:

synapse/storage/databases/main/registration.py

synapse

Python

1783156dbcf4164692e66275d1c29857c434995b

registration.py

count_daily_user_type

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

Add some type hints to datastore (#12423) * Add some type hints to datastore * newsfile * change `Collection` to `List` * refactor return type of `select_users_txn` * correct type hint in `stream.py` * Remove `Optional` in `select_users_txn` * remove not needed return type in `__init__` * Revert change in `get_stream_id_for_event_txn` * Remove import from `Literal`

def __iter__(self) -> Iterator[tuple[Hashable, NDFrameT]]: keys = self.keys if isinstance(keys, list) and len(keys) == 1: warnings.warn( ( "In a future version of pandas, a length 1 " "tuple will be returned when iterating over a " "a groupby with a grouper equal to a list of " "length 1. Don't supply a list with a single grouper " "to avoid this warning." ), FutureWarning, stacklevel=find_stack_level(), ) return self.grouper.get_iterator(self._selected_obj, axis=self.axis) # To track operations that expand dimensions, like ohlc OutputFrameOrSeries = TypeVar("OutputFrameOrSeries", bound=NDFrame)

pandas/core/groupby/groupby.py

pandas

Python

14de3fd9ca4178bfce5dd681fa5d0925e057c04d

groupby.py

__iter__

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

DEPR: returning tuple when grouping by a list containing single element (#47761) * DOC #45443 edited the documentation of where/mask functions * DOC #45443 edited the documentation of where/mask functions * Update generic.py * ENH: add suffixes argument to DataFrame.compare #44354 * Edited the tests * space fixing * Update shared_docs.py * Update series.py * Update series.py * invalid argument tests * issue reference * syntax editing * grammar fixing * edit doc * editting doc * Update 02_read_write.rst * Update 02_read_write.rst * Update v1.5.0.rst * Update v1.5.0.rst * np * 1.5.0 rst * created tests for invalid input * space * space * space * editing test * deprecated * syntax * editting existed examples * syntax * edit past tests * editting pivot * ex * editing internal use * pivot * warning expected * warning * ignore doc warning * doc * tests * ignore warning * test * plotting * test * doc * doc * white space * doc * doc * doc * doc * stacklevel * pivot * pivot * cookbook * flake8 * flake8 * what's new * syntax * itr * car names * test edit * fixing tests * fixing tests * flake8 * rst edit * __iter__ edit * flake8 * flake8 * space * test * merge * ignore the type * mypy * type * self.keys * tests * . * . * adding keys * order * attribute * ignores * Update hist.py * ignore * . * . * . * . * . * Update doc/source/whatsnew/v1.5.0.rst Co-authored-by: Richard Shadrach <45562402+rhshadrach@users.noreply.github.com> Co-authored-by: Richard Shadrach <45562402+rhshadrach@users.noreply.github.com>

def _transform_url(url, transform_netloc): # type: (str, Callable[[str], Tuple[Any, ...]]) -> Tuple[str, NetlocTuple] purl = urllib.parse.urlsplit(url) netloc_tuple = transform_netloc(purl.netloc) # stripped url url_pieces = (purl.scheme, netloc_tuple[0], purl.path, purl.query, purl.fragment) surl = urllib.parse.urlunsplit(url_pieces) return surl, cast("NetlocTuple", netloc_tuple)

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

misc.py

_transform_url

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

upd; format

def test_update_notice_user_name_when_changed(self) -> None: server_notice_request_content = { "user_id": self.other_user, "content": {"msgtype": "m.text", "body": "test msg one"}, } self.make_request( "POST", self.url, access_token=self.admin_user_tok, content=server_notice_request_content, ) # simulate a change in server config after a server restart. new_display_name = "new display name" self.server_notices_manager._config.servernotices.server_notices_mxid_display_name = ( new_display_name ) self.server_notices_manager.get_or_create_notice_room_for_user.cache.invalidate_all() self.make_request( "POST", self.url, access_token=self.admin_user_tok, content=server_notice_request_content, ) invited_rooms = self._check_invite_and_join_status(self.other_user, 1, 0) notice_room_id = invited_rooms[0].room_id self.helper.join( room=notice_room_id, user=self.other_user, tok=self.other_user_token ) notice_user_state_in_room = self.helper.get_state( notice_room_id, "m.room.member", self.other_user_token, state_key="@notices:test", ) self.assertEqual(notice_user_state_in_room["displayname"], new_display_name)

tests/rest/admin/test_server_notice.py

synapse

Python

2e2d8cc2f9b9af5f8b48d75e22c474e08feca236

test_server_notice.py

test_update_notice_user_name_when_changed

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

Update the server notices user profile in room if changed. (#12115)

def assign_wrt_overlaps(self, overlaps, gt_labels=None): num_gts, num_bboxes = overlaps.size(0), overlaps.size(1) # 1. assign -1 by default assigned_gt_inds = overlaps.new_full((num_bboxes, ), -1, dtype=torch.long) if num_gts == 0 or num_bboxes == 0: # No ground truth or boxes, return empty assignment max_overlaps = overlaps.new_zeros((num_bboxes, )) if num_gts == 0: # No truth, assign everything to background assigned_gt_inds[:] = 0 if gt_labels is None: assigned_labels = None else: assigned_labels = overlaps.new_full((num_bboxes, ), -1, dtype=torch.long) return AssignResult( num_gts, assigned_gt_inds, max_overlaps, labels=assigned_labels) # for each anchor, which gt best overlaps with it # for each anchor, the max iou of all gts max_overlaps, argmax_overlaps = overlaps.max(dim=0) # for each gt, which anchor best overlaps with it # for each gt, the max iou of all proposals gt_max_overlaps, gt_argmax_overlaps = overlaps.max(dim=1) # 2. assign negative: below # the negative inds are set to be 0 if isinstance(self.neg_iou_thr, float): assigned_gt_inds[(max_overlaps >= 0) & (max_overlaps < self.neg_iou_thr)] = 0 elif isinstance(self.neg_iou_thr, tuple): assert len(self.neg_iou_thr) == 2 assigned_gt_inds[(max_overlaps >= self.neg_iou_thr[0]) & (max_overlaps < self.neg_iou_thr[1])] = 0 # 3. assign positive: above positive IoU threshold pos_inds = max_overlaps >= self.pos_iou_thr assigned_gt_inds[pos_inds] = argmax_overlaps[pos_inds] + 1 if self.match_low_quality: # Low-quality matching will overwrite the assigned_gt_inds assigned # in Step 3. Thus, the assigned gt might not be the best one for # prediction. # For example, if bbox A has 0.9 and 0.8 iou with GT bbox 1 & 2, # bbox 1 will be assigned as the best target for bbox A in step 3. # However, if GT bbox 2's gt_argmax_overlaps = A, bbox A's # assigned_gt_inds will be overwritten to be bbox 2. # This might be the reason that it is not used in ROI Heads. for i in range(num_gts): if gt_max_overlaps[i] >= self.min_pos_iou: if self.gt_max_assign_all: max_iou_inds = overlaps[i, :] == gt_max_overlaps[i] assigned_gt_inds[max_iou_inds] = i + 1 else: assigned_gt_inds[gt_argmax_overlaps[i]] = i + 1 if gt_labels is not None: assigned_labels = assigned_gt_inds.new_full((num_bboxes, ), -1) pos_inds = torch.nonzero( assigned_gt_inds > 0, as_tuple=False).squeeze() if pos_inds.numel() > 0: assigned_labels[pos_inds] = gt_labels[ assigned_gt_inds[pos_inds] - 1] else: assigned_labels = None return AssignResult( num_gts, assigned_gt_inds, max_overlaps, labels=assigned_labels)

mmdet/core/bbox/assigners/max_iou_assigner.py

mmdetection

Python

9bf37f509ddf6aea1be3a4ad19036f96b9fc3902

max_iou_assigner.py

assign_wrt_overlaps

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

fix typos in comment (#7124) bbox A's assigned_gt_inds will be overwritten to be bbox 2 instead of bbox B (In the previous content, bbox B was not mentioned).

def _rewrite_warnings(cls, record): if record.levelno == 30 and record.funcName == "warn" and record.module == "ag_logging": # TF 2.3 in Conda is imported with the wrong gast(0.4 when 0.3.3 should be used). This # causes warnings in autograph. They don't appear to impact performance so de-elevate # warning to debug record.levelno = 10 record.levelname = "DEBUG" if record.levelno == 30 and (record.funcName == "_tfmw_add_deprecation_warning" or record.module in ("deprecation", "deprecation_wrapper")): # Keras Deprecations. record.levelno = 10 record.levelname = "DEBUG" return record

lib/logger.py

faceswap

Python

afec52309326304f4323029039e49bfcf928ef43

logger.py

_rewrite_warnings

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

Bugfixes: - Stats graph - Handle NaNs in data - logger - de-elevate matplotlib font messages

def _find_alignments(self) -> str: fname = self._args.alignments_file frames = self._args.frames_dir if fname and os.path.isfile(fname) and os.path.splitext(fname)[-1].lower() == ".fsa": return fname if fname: logger.error("Not a valid alignments file: '%s'", fname) sys.exit(1) if not frames or not os.path.exists(frames): logger.error("Not a valid frames folder: '%s'. Can't scan for alignments.", frames) sys.exit(1) fname = "alignments.fsa" if os.path.isdir(frames) and os.path.exists(os.path.join(frames, fname)): return fname if os.path.isdir(frames) or os.path.splitext(frames)[-1] not in _video_extensions: logger.error("Can't find a valid alignments file in location: %s", frames) sys.exit(1) fname = f"{os.path.splitext(frames)[0]}_{fname}" if not os.path.exists(fname): logger.error("Can't find a valid alignments file for video: %s", frames) sys.exit(1) return fname

tools/alignments/alignments.py

faceswap

Python

2d312a9db228c025d0bd2ea7a4f747a2c644b5d8

alignments.py

_find_alignments

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

Minor updates and fixups - Mask Tool - Typing + BiSeNet mask update fix - Alignments Tool - Auto search for alignments file

def build(self, input_shape): if self._is_graph_network: super().build(input_shape) return if input_shape is None: raise ValueError( "Input shape must be defined when calling `build()` on " "a `Model` subclass." ) valid_types = (tuple, list, tf.TensorShape, dict) if not isinstance(input_shape, valid_types): raise ValueError( "Specified input shape is not one of the valid types. " "Please specify a batch input shape of type tuple or " "list of input shapes. User provided " "input type: {}.".format(type(input_shape)) ) if input_shape and not self.inputs: # We create placeholders for the `None`s in the shape and build the model # in a Graph. Since tf.Variable is compatible with both eager execution # and graph building, the variables created after building the model in # a Graph are still valid when executing eagerly. if tf.executing_eagerly(): graph = tf.__internal__.FuncGraph("build_graph") else: graph = backend.get_graph() with graph.as_default(): if isinstance(input_shape, list) and all( d is None or isinstance(d, int) for d in input_shape ): input_shape = tuple(input_shape) if isinstance(input_shape, list): x = [ base_layer_utils.generate_placeholders_from_shape(shape) for shape in input_shape ] elif isinstance(input_shape, dict): x = { k: base_layer_utils.generate_placeholders_from_shape( shape ) for k, shape in input_shape.items() } else: x = base_layer_utils.generate_placeholders_from_shape( input_shape ) kwargs = {} call_signature = self._call_spec.full_argspec call_args = call_signature.args # Exclude `self`, `inputs`, and any argument with a default value. if len(call_args) > 2: if call_signature.defaults: call_args = call_args[2 : -len(call_signature.defaults)] else: call_args = call_args[2:] for arg in call_args: if arg == "training": # Case where `training` is a positional arg with no default. kwargs["training"] = False else: # Has invalid call signature with unknown positional arguments. raise ValueError( "Currently, you cannot build your model if it has " "positional or keyword arguments that are not " "inputs to the model, but are required for its " "`call()` method. Instead, in order to instantiate " "and build your model, `call()` your model on real " "tensor data with all expected call arguments. The argument " "for `call()` can be a single list/tuple that contains " "multiple inputs." ) elif len(call_args) < 2: # Signature without `inputs`. raise ValueError( "You can only call `build()` on a model if its `call()` " "method accepts an `inputs` argument." ) try: self.call(x, **kwargs) except (tf.errors.InvalidArgumentError, TypeError) as e: raise ValueError( "You cannot build your model by calling `build` " "if your layers do not support float type inputs. " "Instead, in order to instantiate and build your " "model, call your model on real tensor data (of " "the correct dtype).\n\nThe actual error from " f"`call` is: {e}." ) super().build(input_shape)

keras/engine/training.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training.py

build

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def check(self) -> bool: modified = self._get_modified() changed = modified != self._modified self._modified = modified return changed

src/textual/file_monitor.py

textual

Python

7df1c123e9fbc8641052a30ba74282f9d9ec1870

file_monitor.py

check

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

docstrings

def _new_training(self): self.should_training_stop = False

paddlenlp/trainer/trainer_callback.py

PaddleNLP

Python

44a290e94d1becd1f09fddc3d873f9e19c9d6919

trainer_callback.py

_new_training

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

[Trainer] Add init version of paddlenlp trainer and apply finetune for ernie-1.0 pretraining. (#1761) * add some datasets for finetune. * support fine tune for all tastks. * add trainer prototype. * init verison for paddlenlp trainer. * refine trainer. * update for some details. * support multi-cards training evaluation. * support load from ckpt. * support for export inference model. * first version of trainer. * seq cls support clue. * trainer support for token classification and question answersing tasks. * fix as reviews. Co-authored-by: Zeyu Chen <chenzeyu01@baidu.com>

def set_state(self, state): raise NotImplementedError()

mitmproxy/coretypes/serializable.py

mitmproxy

Python

07a40208a32cb2d48a1f2a24d2569894b5a378a0

serializable.py

set_state

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

`rm -rf stateobject`

def get_next_event_id(self, event, snuba_filter): raise NotImplementedError

src/sentry/eventstore/base.py

sentry

Python

94c896a4a3663abbd31775957f1aa5448fde5491

base.py

get_next_event_id

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

ref: clean up sentry flake8 plugin (#33847) * fix: Remove unused `# noqa` lint disable comments * ref: clean up sentry flake8 plugin - remove S005: pyupgrade handles this for us - remove `pycodestyle` handling: flake8 does this natively - clean up the ignore list and use extend-ignore

def center(self, frequency=1000): equal_energy_fr = self.__class__(name='equal_energy', frequency=self.frequency.copy(), raw=self.raw.copy()) equal_energy_fr.interpolate() interpolator = InterpolatedUnivariateSpline(np.log10(equal_energy_fr.frequency), equal_energy_fr.raw, k=1) if type(frequency) in [list, np.ndarray] and len(frequency) > 1: # Use the average of the gain values between the given frequencies as the difference to be subtracted diff = np.mean(equal_energy_fr.raw[np.logical_and( equal_energy_fr.frequency >= frequency[0], equal_energy_fr.frequency <= frequency[1] )]) else: if type(frequency) in [list, np.ndarray]: # List or array with only one element frequency = frequency[0] # Use the gain value at the given frequency as the difference to be subtracted diff = interpolator(np.log10(frequency)) self.raw -= diff if len(self.smoothed): self.smoothed -= diff if len(self.error): self.error += diff if len(self.error_smoothed): self.error_smoothed += diff # Everything but raw, smoothed, errors and target is affected by centering, reset them self.reset(raw=False, smoothed=False, error=False, error_smoothed=False, target=False) return -diff

research/neo_peq/legacy_frequency_response.py

AutoEq

Python

9120cdffe618c6c2ff16fe6a311b6a1367efdbc8

legacy_frequency_response.py

center

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

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.

def additional_resources_per_worker(self): return { k: v for k, v in self._resources_per_worker_not_none.items() if k not in ["CPU", "GPU"] }

python/ray/air/config.py

ray

Python

b3878e26d765e28dd7c69abadbd856181037db97

config.py

additional_resources_per_worker

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

[AIR] Fix `ResourceChangingScheduler` not working with AIR (#26307) This PR ensures that the new trial resources set by `ResourceChangingScheduler` are respected by the train loop logic by modifying the scaling config to match. Previously, even though trials had their resources updated, the scaling config was not modified which lead to eg. new workers not being spawned in the `DataParallelTrainer` even though resources were available. In order to accomplish this, `ScalingConfigDataClass` is updated to allow equality comparisons with other `ScalingConfigDataClass`es (using the underlying PGF) and to create a `ScalingConfigDataClass` from a PGF. Please note that this is an internal only change intended to actually make `ResourceChangingScheduler` work. In the future, `ResourceChangingScheduler` should be updated to operate on `ScalingConfigDataClass`es instead of PGFs as it is now. That will require a deprecation cycle.

def match(self, image): if self.lut is None: msg = "No operator loaded" raise Exception(msg) if image.mode != "L": msg = "Image mode must be L" raise ValueError(msg) return _imagingmorph.match(bytes(self.lut), image.im.id)

src/PIL/ImageMorph.py

Pillow

Python

2ae55ccbdad9c842929fb238ea1eb81d1f999024

ImageMorph.py

match

https://github.com/python-pillow/Pillow.git

Improve exception traceback readability

def get_files(d, pattern, sort=True): files = glob(osp.join(d, pattern)) files = [f for f in files if osp.isfile(f)] if sort:

ludwig/utils/checkpoint_utils.py

ludwig

Python

cbff12a584ac253b6953551fecd8a66afc320de7

checkpoint_utils.py

get_files

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

Fixes FileExistsError thrown after training on windows completes (#1845) * Catch exception when os.rename throws when renaming checkpoint. * Filter out -tmp prefix (or any other) when sorting files in get_files. * Use os.replace instead of os.rename, this works on windows * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Add comment to sort. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: Daniel Treiman <daniel@predibase.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

def free_symbols(self, reference_frame): return self.to_matrix(reference_frame).free_symbols

sympy/physics/vector/vector.py

sympy

Python

c03c0eb2136e693b8431c19dd3294d832b4a394c

vector.py

free_symbols

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

Add .free_dynamicsymbols to physics vectors.

def should_strip_auth(self, old_url, new_url): old_parsed = urlparse(old_url) new_parsed = urlparse(new_url) if old_parsed.hostname != new_parsed.hostname: return True # Special case: allow http -> https redirect when using the standard # ports. This isn't specified by RFC 7235, but is kept to avoid # breaking backwards compatibility with older versions of requests # that allowed any redirects on the same host. if ( old_parsed.scheme == "http" and old_parsed.port in (80, None) and new_parsed.scheme == "https" and new_parsed.port in (443, None) ): return False # Handle default port usage corresponding to scheme. changed_port = old_parsed.port != new_parsed.port changed_scheme = old_parsed.scheme != new_parsed.scheme default_port = (DEFAULT_PORTS.get(old_parsed.scheme, None), None) if ( not changed_scheme and old_parsed.port in default_port and new_parsed.port in default_port ): return False # Standard case: root URI must match return changed_port or changed_scheme

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

pipenv

Python

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

sessions.py

should_strip_auth

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

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

def units(self): max_position = self.u_height + decimal.Decimal(0.5) if self.desc_units: drange(0.5, max_position, 0.5) return drange(max_position, 0.5, -0.5)

netbox/dcim/models/racks.py

netbox

Python

84f056171286d18c1c14a2fc9d28155a7dcf169a

racks.py

units

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

Initial work on half-height RUs

def test_visualization_compare_classifiers_from_pred_csv_output_saved(csv_filename): input_features = [category_feature(vocab_size=10)] output_features = [category_feature(vocab_size=2, reduce_input="sum")] # Generate test data rel_path = generate_data(input_features, output_features, csv_filename) exp_dir_name = run_experiment_with_visualization(input_features, output_features, dataset=rel_path) vis_output_pattern_pdf = os.path.join(exp_dir_name, "*.pdf") vis_output_pattern_png = os.path.join(exp_dir_name, "*.png") output_feature_name = get_output_feature_name(exp_dir_name) prediction = os.path.join(exp_dir_name, PREDICTIONS_PARQUET_FILE_NAME) experiment_source_data_name = csv_filename.split(".")[0] ground_truth = experiment_source_data_name + ".csv" split_file = experiment_source_data_name + ".split.csv" ground_truth_metadata = experiment_source_data_name + ".meta.json" test_cmd_pdf = [ "python", "-m", "ludwig.visualize", "--visualization", "compare_classifiers_performance_from_pred", "--ground_truth_metadata", ground_truth_metadata, "--ground_truth", ground_truth, "--output_feature_name", output_feature_name, "--split_file", split_file, "--predictions", prediction, prediction, "--model_names", "Model1", "Model2", "-od", exp_dir_name, ] test_cmd_png = test_cmd_pdf.copy() + ["-ff", "png"] commands = [test_cmd_pdf, test_cmd_png] vis_patterns = [vis_output_pattern_pdf, vis_output_pattern_png] for command, viz_pattern in zip(commands, vis_patterns): result = subprocess.run(command) figure_cnt = glob.glob(viz_pattern) assert 0 == result.returncode assert 1 == len(figure_cnt)

tests/integration_tests/test_visualization.py

ludwig

Python

4fb8f63181f5153b4f6778c6ef8dad61022c4f3f

test_visualization.py

test_visualization_compare_classifiers_from_pred_csv_output_saved

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

Use tempfile to automatically garbage collect data and modeling artifacts in ludwig integration tests. (#1642) * Use tmpdir to automatically garbage collect data and modeling artifacts in ludwig integration tests.

def real_root(arg, n=None, evaluate=None): r from sympy.functions.elementary.complexes import Abs, im, sign from sympy.functions.elementary.piecewise import Piecewise if n is not None: return Piecewise( (root(arg, n, evaluate=evaluate), Or(Eq(n, S.One), Eq(n, S.NegativeOne))), (Mul(sign(arg), root(Abs(arg), n, evaluate=evaluate), evaluate=evaluate), And(Eq(im(arg), S.Zero), Eq(Mod(n, 2), S.One))), (root(arg, n, evaluate=evaluate), True)) rv = sympify(arg) n1pow = Transform(lambda x: -(-x.base)**x.exp, lambda x: x.is_Pow and x.base.is_negative and x.exp.is_Rational and x.exp.p == 1 and x.exp.q % 2) return rv.xreplace(n1pow) ############################################################################### ############################# MINIMUM and MAXIMUM ############################# ###############################################################################

sympy/functions/elementary/miscellaneous.py

sympy

Python

cda8dfe6f45dc5ed394c2f5cda706cd6c729f713

miscellaneous.py

real_root

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

Improved documentation formatting

def get_dashboard_url(): if ray_constants.RAY_OVERRIDE_DASHBOARD_URL in os.environ: return _remove_protocol_from_url( os.environ.get(ray_constants.RAY_OVERRIDE_DASHBOARD_URL) ) else: worker = global_worker worker.check_connected() return _global_node.webui_url

python/ray/_private/worker.py

ray

Python

4692e8d8023e789120d3f22b41ffb136b50f70ea

worker.py

get_dashboard_url

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

[core] Don't override external dashboard URL in internal KV store (#27901) Fix 2.0.0 release blocker bug where Ray State API and Jobs not accessible if the override URL doesn't support adding additional subpaths. This PR keeps the localhost dashboard URL in the internal KV store and only overrides in values printed or returned to the user. images.githubusercontent.com/6900234/184809934-8d150874-90fe-4b45-a13d-bce1807047de.png">

def test_install_non_rpm_using_dnf_gen_error(): info_fake_error = dnf_call = MagicMock( return_value={"retcode": 1, "stdout": "", "stderr": info_fake_error} ) list_pkgs_mock = MagicMock(side_effect=[{"info": "6.6-2"}, {"info": "6.6-2"}]) with patch("pathlib.Path.is_file", return_value=True): with patch.dict( aixpkg.__salt__, {"cmd.run_all": dnf_call, "config.get": MagicMock(return_value=False)}, ), patch.object(aixpkg, "list_pkgs", list_pkgs_mock): expected = { "changes": {}, "errors": [info_fake_error], } with pytest.raises(CommandExecutionError) as exc_info: aixpkg.install("info_fake.rpm") assert exc_info.value.info == expected, exc_info.value.info assert dnf_call.call_count == 1 libpath_env = {"LIBPATH": "/opt/freeware/lib:/usr/lib"} dnf_call.assert_any_call( "/opt/freeware/bin/dnf install --allowerasing --assumeyes info_fake.rpm", env=libpath_env, ignore_retcode=True, python_shell=False, )

tests/pytests/unit/modules/test_aixpkg.py

salt

Python

f1c37893caf90738288e789c3233ab934630254f

test_aixpkg.py

test_install_non_rpm_using_dnf_gen_error

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

Working tests for install

def get_install_candidate(self, link_evaluator, link): # type: (LinkEvaluator, Link) -> Optional[InstallationCandidate] is_candidate, result = link_evaluator.evaluate_link(link) if not is_candidate: if result: self._log_skipped_link(link, reason=result) return None return InstallationCandidate( name=link_evaluator.project_name, link=link, version=result, )

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

package_finder.py