Datasets:

semeru

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

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Semeru Lab 7

def test_relays_dyamic_sampling(client, call_endpoint, default_project, dyn_sampling_data): default_project.update_option("sentry:dynamic_sampling", dyn_sampling_data()) with Feature( { "organizations:server-side-sampling": True, "organizations:dynamic-sampling-deprecated": True, } ): result, status_code = call_endpoint(full_config=False) assert status_code < 400 dynamic_sampling = safe.get_path( result, "configs", str(default_project.id), "config", "dynamicSampling" ) assert dynamic_sampling == dyn_sampling_data() @pytest.mark.django_db

tests/sentry/api/endpoints/test_relay_projectconfigs.py

@pytest.mark.django_db

sentry

Python

c8bfd65f261769da2565ca4240f11da6e820a7e4

test_relay_projectconfigs.py

test_relays_dyamic_sampling

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

feat(dyn-sampling): Switch to new feature flag multiplexer in projectconfig (#40498) This PR switch to new feature flag multiplexer in projectconfig.

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

packages/python/plotly/plotly/graph_objs/_choroplethmapbox.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_choroplethmapbox.py

below

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

switch to black .22

def execute(): if not frappe.db.table_exists("Additional Salary"): return for doctype in ("Additional Salary", "Employee Incentive", "Salary Detail"): frappe.reload_doc("Payroll", "doctype", doctype) frappe.reload_doc("hr", "doctype", "Leave Encashment") additional_salaries = frappe.get_all( "Additional Salary", fields=["name", "salary_slip", "type", "salary_component"], filters={"salary_slip": ["!=", ""]}, group_by="salary_slip", ) leave_encashments = frappe.get_all( "Leave Encashment", fields=["name", "additional_salary"], filters={"additional_salary": ["!=", ""]}, ) employee_incentives = frappe.get_all( "Employee Incentive", fields=["name", "additional_salary"], filters={"additional_salary": ["!=", ""]}, ) for incentive in employee_incentives: frappe.db.sql( , (incentive["name"], incentive["additional_salary"]), ) for leave_encashment in leave_encashments: frappe.db.sql( , (leave_encashment["name"], leave_encashment["additional_salary"]), ) salary_slips = [sal["salary_slip"] for sal in additional_salaries] for salary in additional_salaries: comp_type = "earnings" if salary["type"] == "Earning" else "deductions" if salary["salary_slip"] and salary_slips.count(salary["salary_slip"]) == 1: frappe.db.sql( , (salary["name"], comp_type, salary["salary_slip"], salary["salary_component"]), )

erpnext/patches/v13_0/patch_to_fix_reverse_linking_in_additional_salary_encashment_and_incentive.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

patch_to_fix_reverse_linking_in_additional_salary_encashment_and_incentive.py

execute

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

style: format code with black

def test_get_permissions(self): self.assertTrue( win_dacl.set_permissions( obj_name=self.obj_name, principal="Backup Operators", permissions="full_control", access_mode="grant", obj_type=self.obj_type, reset_perms=False, protected=None, ) ) expected = {'Not Inherited': {'Backup Operators': {'grant': {'applies to': 'This key and subkeys', 'permissions': 'Full Control'}}}} self.assertEqual( win_dacl.get_permissions( obj_name=self.obj_name, principal="Backup Operators", obj_type=self.obj_type, ), expected, )

tests/unit/utils/test_win_dacl.py

salt

Python

55a7519dd5dab2bdfcac2e7e6e77a3d1358538f9

test_win_dacl.py

test_get_permissions

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

fix tests

def run_api_experiment_separated_datasets(input_features, output_features, data_csv): config = { "input_features": input_features, "output_features": output_features, "combiner": {"type": "concat", "output_size": 14}, "training": {"epochs": 2}, } model = LudwigModel(config) # Training with dataframe data_df = read_csv(data_csv) train_df = data_df.sample(frac=0.8) test_df = data_df.drop(train_df.index).sample(frac=0.5) validation_df = data_df.drop(train_df.index).drop(test_df.index) basename, ext = os.path.splitext(data_csv) train_fname = basename + ".train" + ext val_fname = basename + ".validation" + ext test_fname = basename + ".test" + ext output_dirs = [] try: train_df.to_csv(train_fname) validation_df.to_csv(val_fname) test_df.to_csv(test_fname) # Training with csv _, _, output_dir = model.train( training_set=train_fname, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, _, output_dir = model.train( training_set=train_fname, validation_set=val_fname, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, _, output_dir = model.train( training_set=train_fname, validation_set=val_fname, test_set=test_fname, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, output_dir = model.predict(dataset=test_fname) output_dirs.append(output_dir) finally: # Remove results/intermediate data saved to disk os.remove(train_fname) os.remove(val_fname) os.remove(test_fname) for output_dir in output_dirs: shutil.rmtree(output_dir, ignore_errors=True) output_dirs = [] try: _, _, output_dir = model.train( training_set=train_df, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, _, output_dir = model.train( training_set=train_df, validation_set=validation_df, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, _, output_dir = model.train( training_set=train_df, validation_set=validation_df, test_set=test_df, skip_save_processed_input=True, skip_save_progress=True, skip_save_unprocessed_output=True, ) output_dirs.append(output_dir) _, output_dir = model.predict(dataset=data_df) output_dirs.append(output_dir) finally: for output_dir in output_dirs: shutil.rmtree(output_dir, ignore_errors=True)

tests/integration_tests/test_api.py

ludwig

Python

69604268c2ddc06a4ee0b3dce0e05a8fb73b5d16

test_api.py

run_api_experiment_separated_datasets

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

Rename fc_size to output_size (#1641) * Rename fc_size to output_size * Responding to comments

def is_same_object(instance, webhook_data, request_id): return ( ContentType.objects.get_for_model(instance) == webhook_data['content_type'] and instance.pk == webhook_data['object_id'] and request_id == webhook_data['request_id'] ) @receiver((post_save, m2m_changed))

netbox/extras/signals.py

@receiver((post_save, m2m_changed))

netbox

Python

4a95cfd1c4435e6eda01745fe06d902c25d2493e

signals.py

is_same_object

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

Permanently connect change logging & webhook receivers

def with_loss(self) -> bool: return self.loss_panoptic is not None

mmdet/models/seg_heads/panoptic_fusion_heads/base_panoptic_fusion_head.py

mmdetection

Python

c08b81510fbfc1199eab6ccc7af07fc3d3f89d12

base_panoptic_fusion_head.py

with_loss

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

Two stage segmentor + Panpotic FPN

def l1_min_c(X, y, *, loss="squared_hinge", fit_intercept=True, intercept_scaling=1.0): if loss not in ("squared_hinge", "log"): raise ValueError('loss type not in ("squared_hinge", "log")') X = check_array(X, accept_sparse="csc") check_consistent_length(X, y) Y = LabelBinarizer(neg_label=-1).fit_transform(y).T # maximum absolute value over classes and features den = np.max(np.abs(safe_sparse_dot(Y, X))) if fit_intercept: bias = np.full( (np.size(y), 1), intercept_scaling, dtype=np.array(intercept_scaling).dtype ) den = max(den, abs(np.dot(Y, bias)).max()) if den == 0.0: raise ValueError( "Ill-posed l1_min_c calculation: l1 will always " "select zero coefficients for this data" ) if loss == "squared_hinge": return 0.5 / den else: # loss == 'log': return 2.0 / den

sklearn/svm/_bounds.py

scikit-learn

Python

6d16698dd8ba4407e5c3c588d7b5e6a5257eddc9

_bounds.py

l1_min_c

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

DOC Ensures that l1_min_c passes numpydoc validation (#24134)

def screen(self) -> Screen: try: return self._screen_stack[-1] except IndexError: raise ScreenStackError("No screens on stack") from None

src/textual/app.py

textual

Python

b22436933acc0d7440ec300f971a249bd6105a5b

app.py

screen

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

lots of docstrings

async def test_timeout_stops_execution_in_sync_subflows(self, tmp_path): canary_file = tmp_path / "canary"

tests/test_flows.py

prefect

Python

336eca7839fccbcbdb77179f352f926da8b1fa15

test_flows.py

test_timeout_stops_execution_in_sync_subflows

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

Ensure flows are called in an interruptible thread (PrefectHQ/orion#2174) * Ensure flows are called in an interruptible thread * Set higher runtime limit in `test_timeout_stops_execution_in_sync_subflows`

def test_mark_checked_if_not_deleted(self, mock_patch_already_checked, mock_delete_pod, should_fail): dag = DAG('hello2', start_date=pendulum.now()) k = KubernetesPodOperator( namespace="default", image="ubuntu:16.04", name="test", task_id="task", is_delete_operator_pod=False, dag=dag, ) remote_pod_mock = MagicMock() remote_pod_mock.status.phase = 'Failed' if should_fail else 'Succeeded' self.await_pod_mock.return_value = remote_pod_mock context = create_context(k, persist_to_db=True) if should_fail: with pytest.raises(AirflowException): k.execute(context=context) else: k.execute(context=context) mock_patch_already_checked.assert_called_once() mock_delete_pod.assert_not_called()

tests/providers/cncf/kubernetes/operators/test_kubernetes_pod.py

airflow

Python

c3d883a971a8e4e65ccc774891928daaaa0f4442

test_kubernetes_pod.py

test_mark_checked_if_not_deleted

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

KubernetesPodOperator should patch "already checked" always (#22734) When not configured to delete pods, at end of task execution the current behavior is to patch the pod as "already checked", but only if pod not successful. We should also patch when successful so it isn't "reattached" to after a task clear.

def check_dependency(self, operation, dependency): # Created model if dependency[2] is None and dependency[3] is True: return ( isinstance(operation, operations.CreateModel) and operation.name_lower == dependency[1].lower() ) # Created field elif dependency[2] is not None and dependency[3] is True: return ( isinstance(operation, operations.CreateModel) and operation.name_lower == dependency[1].lower() and any(dependency[2] == x for x, y in operation.fields) ) or ( isinstance(operation, operations.AddField) and operation.model_name_lower == dependency[1].lower() and operation.name_lower == dependency[2].lower() ) # Removed field elif dependency[2] is not None and dependency[3] is False: return ( isinstance(operation, operations.RemoveField) and operation.model_name_lower == dependency[1].lower() and operation.name_lower == dependency[2].lower() ) # Removed model elif dependency[2] is None and dependency[3] is False: return ( isinstance(operation, operations.DeleteModel) and operation.name_lower == dependency[1].lower() ) # Field being altered elif dependency[2] is not None and dependency[3] == "alter": return ( isinstance(operation, operations.AlterField) and operation.model_name_lower == dependency[1].lower() and operation.name_lower == dependency[2].lower() ) # order_with_respect_to being unset for a field elif dependency[2] is not None and dependency[3] == "order_wrt_unset": return ( isinstance(operation, operations.AlterOrderWithRespectTo) and operation.name_lower == dependency[1].lower() and (operation.order_with_respect_to or "").lower() != dependency[2].lower() ) # Field is removed and part of an index/unique_together elif dependency[2] is not None and dependency[3] == "foo_together_change": return ( isinstance( operation, (operations.AlterUniqueTogether, operations.AlterIndexTogether), ) and operation.name_lower == dependency[1].lower() ) # Unknown dependency. Raise an error. else: raise ValueError("Can't handle dependency %r" % (dependency,))

django/db/migrations/autodetector.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

autodetector.py

check_dependency

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

Refs #33476 -- Reformatted code with Black.

def load_version_info_from_text_file(filename): # Read and parse the version file. It may have a byte order marker or encoding cookie - respect it if it does. import PyInstaller.utils.misc as miscutils with open(filename, 'rb') as fp: text = miscutils.decode(fp.read()) # Deserialize via eval() try: info = eval(text) except Exception as e: raise ValueError("Failed to deserialize VSVersionInfo from text-based representation!") from e # Sanity check assert isinstance(info, VSVersionInfo), \ f"Loaded incompatible structure type! Expected VSVersionInfo, got: {type(info)!r}" return info

PyInstaller/utils/win32/versioninfo.py

pyinstaller

Python

f57e15ae14d2370cba7a14cfae97d2c29b5c8154

versioninfo.py

load_version_info_from_text_file

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

building: EXE: load version info structure before comparing guts Load the version information structure in `EXE` constructor, so that the comparison against cached state is done with the structure instead of the filen name. This way, changing the contents of the version information file triggers rebuild of the EXE. Split and clean-up related functions in the `utils.win32.versioninfo` module as well as in `pyi-grab_version` and `pyi-set_version` utility scripts.

def rttopo_version(self): return self._get_spatialite_func("rttopo_version()")

django/contrib/gis/db/backends/spatialite/operations.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

operations.py

rttopo_version

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

Refs #33476 -- Reformatted code with Black.

def filter(example, uniques, args): if not check_uniques(example, uniques): return False elif example["autogenerated"]: return False elif example["line_max"] > args.line_max: return False elif example["line_mean"] > args.line_mean: return False elif example["alpha_frac"] < args.alpha_frac: return False elif example["ratio"] < args.min_token_ratio: return False elif example["config_or_test"] and np.random.rand() <= args.filter_proba: return False elif example["has_no_keywords"] and np.random.rand() <= args.filter_proba: return False elif example["has_few_assignments"]: return False else: return True

examples/research_projects/codeparrot/scripts/preprocessing.py

transformers

Python

e730e1256732b5dfeae2bdd427beacc3fbc20e2a

preprocessing.py

filter

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

Update codeparrot data preprocessing (#16944) * add new preprocessing arguments * add new filters * add new filters to readme * fix config and test count, update function names and docstrings * reformat code * update readme * Update readme * rename config_test filter Co-authored-by: Leandro von Werra <[email protected]> * rename few_assignments filter Co-authored-by: Leandro von Werra <[email protected]> * rename tokenizer in arguments Co-authored-by: Leandro von Werra <[email protected]> * rename functions and add limit_line argument for config_test filter * update threshold for config_test filter Co-authored-by: Leandro von Werra <[email protected]> Co-authored-by: Loubna ben allal <[email protected]>

def test_stream_concurrency(tctx): playbook, cff = start_h2_client(tctx) flow1 = Placeholder(HTTPFlow) flow2 = Placeholder(HTTPFlow) reqheadershook1 = http.HttpRequestHeadersHook(flow1) reqheadershook2 = http.HttpRequestHeadersHook(flow2) reqhook1 = http.HttpRequestHook(flow1) reqhook2 = http.HttpRequestHook(flow2) server = Placeholder(Server) data_req1 = Placeholder(bytes) data_req2 = Placeholder(bytes) assert ( playbook >> DataReceived( tctx.client, cff.build_headers_frame( example_request_headers, flags=["END_STREAM"], stream_id=1 ).serialize() + cff.build_headers_frame( example_request_headers, flags=["END_STREAM"], stream_id=3 ).serialize(), ) << reqheadershook1 << reqheadershook2 >> reply(to=reqheadershook1) << reqhook1 >> reply(to=reqheadershook2) << reqhook2 # req 2 overtakes 1 and we already have a reply: >> reply(to=reqhook2) << OpenConnection(server) >> reply(None, side_effect=make_h2) << SendData(server, data_req2) >> reply(to=reqhook1) << SendData(server, data_req1) ) frames = decode_frames(data_req2()) assert [type(x) for x in frames] == [ hyperframe.frame.SettingsFrame, hyperframe.frame.HeadersFrame, ] frames = decode_frames(data_req1()) assert [type(x) for x in frames] == [ hyperframe.frame.HeadersFrame, ]

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

mitmproxy

Python

b3587b52b25077f68116b9852b041d33e7fc6601

test_http2.py

test_stream_concurrency

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

make it black!

def handle_template(self, template, subdir): if template is None: return os.path.join(django.__path__[0], "conf", subdir) else: if template.startswith("file://"): template = template[7:] expanded_template = os.path.expanduser(template) expanded_template = os.path.normpath(expanded_template) if os.path.isdir(expanded_template): return expanded_template if self.is_url(template): # downloads the file and returns the path absolute_path = self.download(template) else: absolute_path = os.path.abspath(expanded_template) if os.path.exists(absolute_path): return self.extract(absolute_path) raise CommandError( "couldn't handle %s template %s." % (self.app_or_project, template) )

django/core/management/templates.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

templates.py

handle_template

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

Refs #33476 -- Reformatted code with Black.

def _load_model_instance(self) -> None: from rasa.nlu.utils.hugging_face.registry import ( model_class_dict, model_tokenizer_dict, ) logger.debug(f"Loading Tokenizer and Model for {self.model_name}") self.tokenizer = model_tokenizer_dict[self.model_name].from_pretrained( self.model_weights, cache_dir=self.cache_dir ) self.model = model_class_dict[self.model_name].from_pretrained( # type: ignore[no-untyped-call] # noqa: E501 self.model_weights, cache_dir=self.cache_dir ) # Use a universal pad token since all transformer architectures do not have a # consistent token. Instead of pad_token_id we use unk_token_id because # pad_token_id is not set for all architectures. We can't add a new token as # well since vocabulary resizing is not yet supported for TF classes. # Also, this does not hurt the model predictions since we use an attention mask # while feeding input. self.pad_token_id = self.tokenizer.unk_token_id

rasa/nlu/featurizers/dense_featurizer/lm_featurizer.py

rasa

Python

a2cb6b72bb72fb9e5598808d564749503ee08784

lm_featurizer.py

_load_model_instance

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

fix transformers typing issues

def all_pairs_dijkstra_path(G, cutoff=None, weight="weight"): path = single_source_dijkstra_path # TODO This can be trivially parallelized. for n in G: yield (n, path(G, n, cutoff=cutoff, weight=weight))

networkx/algorithms/shortest_paths/weighted.py

networkx

Python

d82815dba6c8ddce19cd49f700298dc82a58f066

weighted.py

all_pairs_dijkstra_path

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

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

def preset_modes(self) -> list[str] | None: return self._attr_preset_modes

homeassistant/components/climate/__init__.py

core

Python

8fc55b71c5153580508446d478adfb450c76ea41

__init__.py

preset_modes

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

Add EntityFeature enum to Climate (#69077)

def call(cls, func, join_type="outer", labels="replace"):

modin/core/dataframe/algebra/binary.py

modin

Python

bd326f1c4175102489f08d271a53cf374bd9125e

binary.py

call

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

PERF-#4268: Implement partition-parallel __getitem__ for bool Series masks (#4753) Signed-off-by: Vasily Litvinov <[email protected]>

def recalc_open_trade_value(self) -> None: self.open_trade_value = self._calc_open_trade_value()

freqtrade/persistence/models.py

freqtrade

Python

1c0946833da746b480f6ef88d4866d6a87824e17

models.py

recalc_open_trade_value

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

Fix bug in exit-count detection

def dist_in_site_packages(dist): # type: (Distribution) -> bool return dist_location(dist).startswith(normalize_path(site_packages))

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

misc.py

dist_in_site_packages

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

upd; format

def get_account_type_based_gl_data(company, start_date, end_date, account_type, filters=None): cond = "" filters = frappe._dict(filters or {}) if filters.include_default_book_entries: company_fb = frappe.db.get_value("Company", company, "default_finance_book") cond = % ( frappe.db.escape(filters.finance_book), frappe.db.escape(company_fb), ) else: cond = " AND (finance_book in (%s, '') OR finance_book IS NULL)" % ( frappe.db.escape(cstr(filters.finance_book)) ) gl_sum = frappe.db.sql_list( .format( cond=cond ), (company, start_date, end_date, account_type), ) return gl_sum[0] if gl_sum and gl_sum[0] else 0

erpnext/accounts/report/cash_flow/cash_flow.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

cash_flow.py

get_account_type_based_gl_data

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

style: format code with black

def get_docstring(node, clean=True): if not isinstance(node, (AsyncFunctionDef, FunctionDef, ClassDef, Module)): raise TypeError("%r can't have docstrings" % node.__class__.__name__) if not(node.body and isinstance(node.body[0], Expr)): return None node = node.body[0].value if isinstance(node, Str): text = node.s elif isinstance(node, Constant) and isinstance(node.value, str): text = node.value else: return None if clean: import inspect text = inspect.cleandoc(text) return text

python3.10.4/Lib/ast.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

ast.py

get_docstring

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

add python 3.10.4 for windows

def get_success_url(self): return self.success_url

wagtail/contrib/forms/views.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

views.py

get_success_url

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

Reformat with black

def expand_basedirs(self): self._expand_attrs(['install_base', 'install_platbase', 'root'])

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

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

install.py

expand_basedirs

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

add python 3.10.4 for windows

async def test_delete_nonsense_block_document(self, client, block_schemas): response = await client.get("/block_documents/not-even") assert response.status_code == status.HTTP_404_NOT_FOUND

tests/orion/api/test_block_documents.py

prefect

Python

74b49c72657da5e18fc00c4b1da3012b575210cd

test_block_documents.py

test_delete_nonsense_block_document

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

Prevent non-UUID slugs from raising errors on the BlockDocuments APIs. (#6541) In Prefect Cloud, we observed some errors when clients would send requests for `.../block_documents/null`, which should really be handled at the routing layer with 404s when the path UUIDs can't be parsed. Note that this is just correcting the server-side issue, but does not attempt to diagnose the client-side issue at this time. Also, this does not attempt to go through every route in Orion that includes UUIDs in its path.

def test_cli_backfill_depends_on_past_backwards(self, mock_run): dag_id = 'test_depends_on_past' start_date = DEFAULT_DATE + timedelta(days=1) end_date = start_date + timedelta(days=1) args = [ 'dags', 'backfill', dag_id, '--local', '--start-date', start_date.isoformat(), '--end-date', end_date.isoformat(), '--ignore-first-depends-on-past', '--run-backwards', ] dag = self.dagbag.get_dag(dag_id) dag_command.dag_backfill(self.parser.parse_args(args), dag=dag) mock_run.assert_called_once_with( start_date=start_date, end_date=end_date, conf=None, delay_on_limit_secs=1.0, donot_pickle=False, ignore_first_depends_on_past=True, ignore_task_deps=False, local=True, mark_success=False, pool=None, rerun_failed_tasks=False, run_backwards=True, verbose=False, continue_on_failures=False, )

tests/cli/commands/test_dag_command.py

airflow

Python

3849b4e709acfc9e85496aa2dededb2dae117fc7

test_dag_command.py

test_cli_backfill_depends_on_past_backwards

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

support for continue backfill on failures (#22697)

def _api_status(self): response.status = 200 return None

glances/outputs/glances_bottle.py

glances

Python

8d4a20a6a843e1e35b5324bc83be422fbed04b87

glances_bottle.py

_api_status

https://github.com/nicolargo/glances.git

Web server status check endpoint #1988

def spatial_2d_padding(x, padding=((1, 1), (1, 1)), data_format=None): assert len(padding) == 2 assert len(padding[0]) == 2 assert len(padding[1]) == 2 if data_format is None: data_format = image_data_format() if data_format not in {"channels_first", "channels_last"}: raise ValueError("Unknown data_format: " + str(data_format)) if data_format == "channels_first": pattern = [[0, 0], [0, 0], list(padding[0]), list(padding[1])] else: pattern = [[0, 0], list(padding[0]), list(padding[1]), [0, 0]] return tf.compat.v1.pad(x, pattern) @keras_export("keras.backend.spatial_3d_padding") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

keras/backend.py

@keras_export("keras.backend.spatial_3d_padding") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

spatial_2d_padding

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def is_container(self) -> bool: return self.styles.layout is not None

src/textual/widget.py

textual

Python

025a0e348d3d3c360498f4f2035451d50f79b40e

widget.py

is_container

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

Scrolling working

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

homeassistant/components/dlna_dms/dms.py

core

Python

b19bf9b147f4321e89d1f7f01e68337f2102f460

dms.py

available

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

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

def test_co_positions_artificial_instructions(self): import dis namespace = {} exec(textwrap.dedent(), namespace) exc = namespace['exc'] traceback = exc.__traceback__ code = traceback.tb_frame.f_code artificial_instructions = [] for instr, positions in zip( dis.get_instructions(code), code.co_positions(), strict=True ): # If any of the positions is None, then all have to # be None as well for the case above. There are still # some places in the compiler, where the artificial instructions # get assigned the first_lineno but they don't have other positions. # There is no easy way of inferring them at that stage, so for now # we don't support it. self.assertTrue(positions.count(None) in [0, 4]) if not any(positions): artificial_instructions.append(instr) self.assertEqual( [ (instruction.opname, instruction.argval) for instruction in artificial_instructions ], [ ("PUSH_EXC_INFO", None), ("LOAD_CONST", None), # artificial 'None' ("STORE_NAME", "e"), # XX: we know the location for this ("DELETE_NAME", "e"), ("RERAISE", 1), ("COPY", 3), ("POP_EXCEPT", None), ("RERAISE", 1) ] )

Lib/test/test_code.py

cpython

Python

a94461d7189d7f1147ab304a332c8684263dc17e

test_code.py

test_co_positions_artificial_instructions

https://github.com/python/cpython.git

bpo-46202: Remove opcode POP_EXCEPT_AND_RERAISE (GH-30302) * bpo-46202: remove opcode POP_EXCEPT_AND_RERAISE * do not assume that an exception group is truthy

def get_assessment_criteria(course): return frappe.get_all( "Course Assessment Criteria", fields=["assessment_criteria", "weightage"], filters={"parent": course}, order_by="idx", ) @frappe.whitelist()

erpnext/education/api.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

api.py

get_assessment_criteria

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

style: format code with black

def get_cloud_syncer(local_dir, remote_dir=None, sync_function=None) -> CloudSyncer: key = (local_dir, remote_dir) if key in _syncers: return _syncers[key] if not remote_dir: _syncers[key] = CloudSyncer(local_dir, remote_dir, NOOP) return _syncers[key] if sync_function == "auto": sync_function = None # Auto-detect # Maybe get user-provided sync client here client = get_sync_client(sync_function) if client: # If the user provided a sync template or function _syncers[key] = CloudSyncer(local_dir, remote_dir, client) else: # Else, get default cloud sync client (e.g. S3 syncer) sync_client = get_cloud_sync_client(remote_dir) _syncers[key] = CloudSyncer(local_dir, remote_dir, sync_client) return _syncers[key]

python/ray/tune/syncer.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

syncer.py

get_cloud_syncer

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

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

def assemble_files_to_ship(complete_file_list): # All files which are in the repository except these: ignore_patterns = ( # Developer-only tools '.azure-pipelines/*', '.github/*', '.github/*/*', 'changelogs/fragments/*', 'hacking/backport/*', 'hacking/azp/*', 'hacking/tests/*', 'hacking/ticket_stubs/*', 'test/sanity/code-smell/botmeta.*', 'test/sanity/code-smell/release-names.*', 'test/utils/*', 'test/utils/*/*', 'test/utils/*/*/*', 'test/results/.tmp/*', 'test/results/.tmp/*/*', 'test/results/.tmp/*/*/*', 'test/results/.tmp/*/*/*/*', 'test/results/.tmp/*/*/*/*/*', '.git*', ) ignore_files = frozenset(( # Developer-only tools 'changelogs/config.yaml', 'hacking/README.md', 'hacking/ansible-profile', 'hacking/cgroup_perf_recap_graph.py', 'hacking/create_deprecated_issues.py', 'hacking/deprecated_issue_template.md', 'hacking/create_deprecation_bug_reports.py', 'hacking/fix_test_syntax.py', 'hacking/get_library.py', 'hacking/metadata-tool.py', 'hacking/report.py', 'hacking/return_skeleton_generator.py', 'hacking/test-module', 'test/support/README.md', 'test/lib/ansible_test/_internal/commands/sanity/bin_symlinks.py', 'test/lib/ansible_test/_internal/commands/sanity/integration_aliases.py', '.cherry_picker.toml', '.mailmap', # Generated as part of a build step 'docs/docsite/rst/conf.py', 'docs/docsite/rst/index.rst', # Possibly should be included 'examples/scripts/uptime.py', 'examples/scripts/my_test.py', 'examples/scripts/my_test_info.py', 'examples/scripts/my_test_facts.py', 'examples/DOCUMENTATION.yml', 'examples/play.yml', 'examples/hosts.yaml', 'examples/hosts.yml', 'examples/inventory_script_schema.json', 'examples/plugin_filters.yml', 'hacking/env-setup', 'hacking/env-setup.fish', 'MANIFEST', 'setup.cfg', # docs for test files not included in sdist 'docs/docsite/rst/dev_guide/testing/sanity/bin-symlinks.rst', 'docs/docsite/rst/dev_guide/testing/sanity/botmeta.rst', 'docs/docsite/rst/dev_guide/testing/sanity/integration-aliases.rst', 'docs/docsite/rst/dev_guide/testing/sanity/release-names.rst', )) # These files are generated and then intentionally added to the sdist # Manpages ignore_script = ('ansible-connection', 'ansible-test') manpages = ['docs/man/man1/ansible.1'] for dirname, dummy, files in os.walk('bin'): for filename in files: if filename in ignore_script: continue manpages.append('docs/man/man1/%s.1' % filename) # Misc misc_generated_files = [ 'PKG-INFO', ] shipped_files = manpages + misc_generated_files for path in complete_file_list: if path not in ignore_files: for ignore in ignore_patterns: if fnmatch.fnmatch(path, ignore): break else: shipped_files.append(path) return shipped_files

test/sanity/code-smell/package-data.py

ansible

Python

353511a900f6216a25a25d8a36528f636428b57b

package-data.py

assemble_files_to_ship

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

Add script to handle more deprecations. (#77400) * Add script to handle more deprecations. This script currently supports deprecations from the following sanity tests: * deprecated-config * update-bundled * Ignore script in package-data test.

def _solve_svd_design_matrix(self, alpha, y, sqrt_sw, X_mean, singvals_sq, U, UT_y): w = ((singvals_sq + alpha) ** -1) - (alpha**-1) if self.fit_intercept: # detect intercept column normalized_sw = sqrt_sw / np.linalg.norm(sqrt_sw) intercept_dim = _find_smallest_angle(normalized_sw, U) # cancel the regularization for the intercept w[intercept_dim] = -(alpha**-1) c = np.dot(U, self._diag_dot(w, UT_y)) + (alpha**-1) * y G_inverse_diag = self._decomp_diag(w, U) + (alpha**-1) if len(y.shape) != 1: # handle case where y is 2-d G_inverse_diag = G_inverse_diag[:, np.newaxis] return G_inverse_diag, c

sklearn/linear_model/_ridge.py

scikit-learn

Python

1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe

_ridge.py

_solve_svd_design_matrix

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

MNT Update black to stable version (#22474)

async def _send_server_info_to_all(self) -> None: for client_handler in self.clients: await self.send_server_info(client_handler)

src/textual/devtools/service.py

textual

Python

a72e347ed99333a090377ee438eaf63477cbf98b

service.py

_send_server_info_to_all

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

Seperate server and client handling logic into classes for devtools

def test_basic_discovery(self): with os_helper.temp_cwd(): os.mkdir('foo') file1 = os.path.join('foo', 'file1.txt') os_helper.create_empty_file(file1) os.mkdir('bar') file2 = os.path.join('bar', 'file2.txt') os_helper.create_empty_file(file2) expected = [file2, file1] self.assertEqual(sorted(filelist.findall()), expected)

python3.10.4/Lib/distutils/tests/test_filelist.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

test_filelist.py

test_basic_discovery

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

add python 3.10.4 for windows

def _total_stats(self) -> Dict[str, Union[str, int, float]]: logger.debug("Compiling Totals") elapsed = 0 examples = 0 iterations = 0 batchset = set() total_summaries = len(self._per_session_stats) for idx, summary in enumerate(self._per_session_stats): if idx == 0: starttime = summary["start"] if idx == total_summaries - 1: endtime = summary["end"] elapsed += summary["elapsed"] examples += ((summary["batch"] * 2) * summary["iterations"]) batchset.add(summary["batch"]) iterations += summary["iterations"] batch = ",".join(str(bs) for bs in batchset) totals = {"session": "Total", "start": starttime, "end": endtime, "elapsed": elapsed, "rate": examples / elapsed if elapsed != 0 else 0, "batch": batch, "iterations": iterations} logger.debug(totals) return totals

lib/gui/analysis/stats.py

faceswap

Python

47867a0dd424b3e31d7beead0ffdb8b37c970a9e

stats.py

_total_stats

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

typing: lib.gui.analysis.stats

def json_deserialize(message):

scripts/ws_client.py

freqtrade

Python

3e08c6e5409d3e1b9c6f787415869e3e49289a00

ws_client.py

json_deserialize

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

testing/debugging ws client script

def apply(func, args, kwargs=None): if kwargs: return func(*args, **kwargs) else: return func(*args)

dask/utils.py

dask

Python

e61405cb5d345e73f1952ee3d50708566b5263d1

utils.py

apply

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

Docs: how to use kwargs with custom task graphs (#9322)

def preferred_index(self): if self._get_preferred_index(): return self.args[1] else: return self.args[0]

sympy/functions/special/tensor_functions.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

tensor_functions.py

preferred_index

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

Updated import locations

def isoformat(self, sep='T', timespec='auto'): s = ("%04d-%02d-%02d%c" % (self._year, self._month, self._day, sep) + _format_time(self._hour, self._minute, self._second, self._microsecond, timespec)) off = self.utcoffset() tz = _format_offset(off) if tz: s += tz return s

python3.10.4/Lib/datetime.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

datetime.py

isoformat

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

add python 3.10.4 for windows

async def test_cuda_visible_devices(self, job_manager): run_cmd = f"python {_driver_script_path('check_cuda_devices.py')}" job_id = job_manager.submit_job(entrypoint=run_cmd) await async_wait_for_condition( check_job_succeeded, job_manager=job_manager, job_id=job_id ) @pytest.mark.asyncio

dashboard/modules/job/tests/test_job_manager.py

@pytest.mark.asyncio

ray

Python

4c1f27118a3af246006ab63325cdff53321bf68b

test_job_manager.py

test_cuda_visible_devices

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

[job submission] Don't set CUDA_VISIBLE_DEVICES in job driver (#24546) Currently job drivers cannot use GPUs due to `CUDA_VISIBLE_DEVICES` being set (no resource request for job driver's supervisor actor). This is a regression from `ray submit`. This is a temporary workaround -- in the future we should support a resource request for the job supervisor actor.

def query_put_bounders(query, partition_column, start, end): where = " WHERE TMP_TABLE.{0} >= {1} AND TMP_TABLE.{0} <= {2}".format( partition_column, start, end ) query_with_bounders = "SELECT * FROM ({0}) AS TMP_TABLE {1}".format(query, where) return query_with_bounders

modin/experimental/core/execution/unidist/implementations/pandas_on_unidist/io/sql.py

modin

Python

193505fdf0c984743397ba3df56262f30aee13a8

sql.py

query_put_bounders

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

FEAT-#5053: Add pandas on unidist execution with MPI backend (#5059) Signed-off-by: Igoshev, Iaroslav <[email protected]>

def resize_feats(self, feats): out = [] for i in range(len(feats)): if i == 0: out.append( F.interpolate( feats[0], size=feats[i + 1].shape[-2:], mode='bilinear', align_corners=False)) elif i == len(feats) - 1: out.append( F.interpolate( feats[i], size=feats[i - 1].shape[-2:], mode='bilinear', align_corners=False)) else: out.append(feats[i]) return out

mmdet/models/dense_heads/solo_head.py

mmdetection

Python

d18cdb140ef3cb9ed5fdef6f1a815f5836f1b1ab

solo_head.py

resize_feats

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

[Feature] Support SOLOv2 (#7441) * solov2 init * solov2 r18 lightweight * add model docstrings and reformat the code * add docstrings to model method * add solov2 big model config and correct some errors in the docstring * fix linting issues * refactor code and configs * rename variables according to the convention * add and enhance solov2 logic * add doc strings * update solov2 config files * fix norm_cfg in mask head * minor fix * update configs Co-authored-by: BIGWangYuDong <[email protected]>

def top_widget(self): if self.overlay: return self.overlay return self.top_window()

mitmproxy/tools/console/window.py

mitmproxy

Python

b3587b52b25077f68116b9852b041d33e7fc6601

window.py

top_widget

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

make it black!

def get_config(self): json_word_counts = json.dumps(self.word_counts) json_word_docs = json.dumps(self.word_docs) json_index_docs = json.dumps(self.index_docs) json_word_index = json.dumps(self.word_index) json_index_word = json.dumps(self.index_word) return { "num_words": self.num_words, "filters": self.filters, "lower": self.lower, "split": self.split, "char_level": self.char_level, "oov_token": self.oov_token, "document_count": self.document_count, "word_counts": json_word_counts, "word_docs": json_word_docs, "index_docs": json_index_docs, "index_word": json_index_word, "word_index": json_word_index, }

keras/preprocessing/text.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

text.py

get_config

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def write_file(masvs_file, input_file, output_file): # enhanced_masvs_dict = {} # for file in Path('masvs_yaml').glob('*.yaml'): # masvs_dict = yaml.load(open(file)) # enhanced_masvs_dict[MASVS_TITLES[file.stem]] = masvs_dict masvs = yaml.safe_load(open(masvs_file)) testcases_info = [] for file in Path(input_file).glob("*.html"): contents = file.read_text() chapter = BeautifulSoup(contents, "lxml") # print(get_links_to_other_chapters(chapter)) # print(get_all_links_to_tools(chapter)) # print(get_links_to_tools_per_section(chapter)) testcases_info += get_testcases_info(f"{file.stem}.md", chapter) # print_yaml(testcases_info) # print(get_sections_plain_text(chapter, "overview")) # print(get_sections_innerHtml(chapter, "overview")) for tc in testcases_info: for id in tc["mstg_ids"]: if masvs.get(id): # masvs[id].update(tc) masvs_req = masvs[id] if not masvs_req.get("links"): masvs_req["links"] = [] masvs_req["links"].append(tc["link"]) # masvs_dict[id]['solution'].append(tc['overview']) # todo # print_yaml(masvs) write_yaml_file(output_file, masvs)

tools/scripts/parse_html.py

owasp-mastg

Python

a4c1ff1391bfa45b78db5473d1df4a1ace6651f5

parse_html.py

write_file

https://github.com/OWASP/owasp-mastg.git

Generate MSTG Checklists automatically and machine-readable YAML (#2010) * port masvs checklist generation to the mstg * add recursive ls * fix Tools -> tools * generate MSTG html * checkout latest masvs tag * use GITHUB_ENV instead of steps.output * add MASVS and MSTG link including versions and commit IDs * add new logo * set avenir as main font * add column status with validation * add conditional formatting for pass, fail and n/a * add step Show openpyxl Version * try format only relevant status cells * create new About sheet with the same header * add intro to project * black and flake8 fixes

def _signature_get_bound_param(spec): assert spec.startswith('($') pos = spec.find(',') if pos == -1: pos = spec.find(')') cpos = spec.find(':') assert cpos == -1 or cpos > pos cpos = spec.find('=') assert cpos == -1 or cpos > pos return spec[2:pos]

python3.10.4/Lib/inspect.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

inspect.py

_signature_get_bound_param

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

add python 3.10.4 for windows

def upgrade(): with op.get_context().autocommit_block(): op.execute( ) op.execute( ) op.execute( ) op.execute( )

src/prefect/orion/database/migrations/versions/postgresql/2022_06_04_133535_d60c18774a5d_add_indexes_for_partial_name_matches.py

prefect

Python

b5b3d808bf059294a7adf17156e4ccdb5a3799da

2022_06_04_133535_d60c18774a5d_add_indexes_for_partial_name_matches.py

upgrade

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

Add index migrations

def write_exports(self, exports): rf = self.get_distinfo_file(EXPORTS_FILENAME) with open(rf, 'w') as f: write_exports(exports, f)

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

database.py

write_exports

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

upd; format

def pause_writing(self): self._app_protocol.pause_writing()

python3.10.4/Lib/asyncio/sslproto.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

sslproto.py

pause_writing

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

add python 3.10.4 for windows

def local_process_index(self): if is_torch_tpu_available(): return xm.get_local_ordinal() elif is_sagemaker_mp_enabled(): return smp.local_rank() elif is_sagemaker_dp_enabled(): return dist.get_rank() elif self.local_rank != -1: return self.local_rank return 0

src/transformers/training_args.py

transformers

Python

81ac45f85c35244831f11f73c09ea10eee4f953a

training_args.py

local_process_index

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

update smddp api to v1.4.0 (#16371) * update smddp api to v1.4.0 * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * address comments * fix style * remove unused import * fix indent * disable style check for import * fix space Co-authored-by: Sylvain Gugger <[email protected]>

async def test_only_one_lock(hass, client, lock_home_connect_620, integration): assert len(hass.states.async_entity_ids("lock")) == 1

tests/components/zwave_js/test_lock.py

core

Python

9d14201b13be4f5a5cc5e5f52bba56bfd8fa9694

test_lock.py

test_only_one_lock

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

Don't create two zwave_js.lock entities for a single device (#68651)

def axis_1(request): return request.param @pytest.fixture(params=[True, False, None])

pandas/conftest.py

@pytest.fixture(params=[True, False, None])

pandas

Python

15a06d3d9e7656afff239da7a295a7b684456680

conftest.py

axis_1

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

BUG: groupby.size and groupby.transform('size') incorrect for axis=1 (#45987)

def list_summaries(logdir): result = _SummaryFile() for (dirpath, _, filenames) in os.walk(logdir): for filename in filenames: if not filename.startswith("events.out."): continue path = os.path.join(dirpath, filename) for event in tf.compat.v1.train.summary_iterator(path): if event.graph_def: result.graph_defs.append(event.graph_def) if not event.summary: # (e.g., it's a `graph_def` event) continue for value in event.summary.value: tag = value.tag # Case on the `value` rather than the summary metadata because # the Keras callback uses `summary_ops_v2` to emit old-style # summaries. See b/124535134. kind = value.WhichOneof("value") container = { "simple_value": result.scalars, "image": result.images, "histo": result.histograms, "tensor": result.tensors, }.get(kind) if container is None: raise ValueError( "Unexpected summary kind %r in event file %s:\n%r" % (kind, path, event) ) elif kind == "tensor" and tag != "keras": # Convert the tf2 summary proto to old style for type checking. plugin_name = value.metadata.plugin_data.plugin_name container = { "images": result.images, "histograms": result.histograms, "scalars": result.scalars, }.get(plugin_name) if container is not None: result.convert_from_v2_summary_proto = True else: container = result.tensors container.add(_ObservedSummary(logdir=dirpath, tag=tag)) return result @test_combinations.run_with_all_model_types @test_combinations.run_all_keras_modes(always_skip_v1=True)

keras/callbacks_test.py

@test_combinations.run_with_all_model_types @test_combinations.run_all_keras_modes(always_skip_v1=True)

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

callbacks_test.py

list_summaries

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

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

packages/python/plotly/plotly/graph_objs/contour/_line.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_line.py

dash

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

switch to black .22

def _get_state(self): result = {} for child_attr, child_obj in self.__dict__.items(): # TODO(rchao): Store non-variable states in the dict as well. if isinstance(child_obj, tf.Variable): result[child_attr] = child_obj.numpy() elif saving_lib.is_container(child_obj): for k, contained_obj in enumerate(child_obj): if isinstance(contained_obj, tf.Variable): # Handling the case where `child_obj` is a list/tuple. result[f"{child_attr}-{k}"] = contained_obj.numpy() elif isinstance(child_obj, dict) and isinstance( child_obj[contained_obj], tf.Variable ): # Handling the case where `child_obj` is a dict. result[f"{child_attr}-{contained_obj}"] = child_obj[ contained_obj ].numpy() return result

keras/engine/base_layer.py

keras

Python

ba5086fa31d24a9f61b46d4a844311b58dea7ff1

base_layer.py

_get_state

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

Keras saving: A prototype of config-based (idempotent) saving and loading, with simple model state restoration added. It's done via the archive provided by `zipfile` package. Preliminary for review and the APIs and implementation are subject to changes. PiperOrigin-RevId: 470784761

def radius_of_convergence(self): if any(a.is_integer and (a <= 0) == True for a in self.ap + self.bq): aints = [a for a in self.ap if a.is_Integer and (a <= 0) == True] bints = [a for a in self.bq if a.is_Integer and (a <= 0) == True] if len(aints) < len(bints): return S.Zero popped = False for b in bints: cancelled = False while aints: a = aints.pop() if a >= b: cancelled = True break popped = True if not cancelled: return S.Zero if aints or popped: # There are still non-positive numerator parameters. # This is a polynomial. return oo if len(self.ap) == len(self.bq) + 1: return S.One elif len(self.ap) <= len(self.bq): return oo else: return S.Zero

sympy/functions/special/hyper.py

sympy

Python

498015021131af4dbb07eb110e5badaba8250c7b

hyper.py

radius_of_convergence

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

Updated import locations

def get_ordered_amount(args, budget): item_code = args.get("item_code") condition = get_other_condition(args, budget, "Purchase Order") data = frappe.db.sql( .format( condition ), item_code, as_list=1, ) return data[0][0] if data else 0

erpnext/accounts/doctype/budget/budget.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

budget.py

get_ordered_amount

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

style: format code with black

def set_color_by_t2c(self, t2c=None): t2c = t2c if t2c else self.t2c for word, color in list(t2c.items()): for start, end in self.find_indexes(word, self.text): self.chars[start:end].set_color(color)

manim/mobject/svg/text_mobject.py

manim

Python

540dc70d2fd7a2f759a6da158303ef81a1ae53f8

text_mobject.py

set_color_by_t2c

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

Update `Text` to use new ManimPango color setting (#2341) * Find indexes in stripped text, not original text * Add regression test * Only run the test in linux environement * Rewrite text2settings in Text to set text color via pango * Make gradient in Text use pango coloring * Bump manimpango to newest version * Update test to use new frames_comparison * Don't remove svg file on exception * Bump manimpango * Fix pre-commit errors * Fix index bug * Deprecate no longer used functions set_color_by_t2x * Remove old commented out code * Update poetry.lock

def sleeper(self, duration): s = time() yield time_to_sleep = duration - (time() - s) if time_to_sleep > 0: self.wait(time_to_sleep)

src/streamlink/stream/dash.py

streamlink

Python

d1a8d1597d4fe9f129a72fe94c1508304b7eae0f

dash.py

sleeper

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

stream.dash: update DASHStreamWorker.iter_segments - Refactor DASHStreamWorker.iter_segments() - Replace dash_manifest.sleeper() with SegmentedStreamWorker.wait(), and make the worker thread shut down immediately on close(). - Prevent unnecessary wait times for static manifest types by calling close() after all segments were put into the writer's queue.

def _group_lengths(grouping): # The result from localeconv()['grouping'], and the input to this # function, should be a list of integers in one of the # following three forms: # # (1) an empty list, or # (2) nonempty list of positive integers + [0] # (3) list of positive integers + [locale.CHAR_MAX], or from itertools import chain, repeat if not grouping: return [] elif grouping[-1] == 0 and len(grouping) >= 2: return chain(grouping[:-1], repeat(grouping[-2])) elif grouping[-1] == _locale.CHAR_MAX: return grouping[:-1] else: raise ValueError('unrecognised format for grouping')

python3.10.4/Lib/_pydecimal.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

_group_lengths

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

add python 3.10.4 for windows

def expand(image, border=0, fill=0): left, top, right, bottom = _border(border) width = left + image.size[0] + right height = top + image.size[1] + bottom color = _color(fill, image.mode) if image.mode == "P" and image.palette: palette = ImagePalette.ImagePalette(palette=image.getpalette()) if isinstance(color, tuple): color = palette.getcolor(color) else: palette = None out = Image.new(image.mode, (width, height), color) if palette: out.putpalette(palette.palette) out.paste(image, (left, top)) return out

src/PIL/ImageOps.py

Pillow

Python

279ddf4ce6c76498ac29df2552a3023b9aaa76c1

ImageOps.py

expand

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

Use getpalette() in ImageOps

def merge_account(old, new, is_group, root_type, company): # Validate properties before merging if not frappe.db.exists("Account", new): throw(_("Account {0} does not exist").format(new)) val = list(frappe.db.get_value("Account", new, ["is_group", "root_type", "company"])) if val != [cint(is_group), root_type, company]: throw( _( ) ) if is_group and frappe.db.get_value("Account", new, "parent_account") == old: frappe.db.set_value( "Account", new, "parent_account", frappe.db.get_value("Account", old, "parent_account") ) frappe.rename_doc("Account", old, new, merge=1, force=1) return new @frappe.whitelist()

erpnext/accounts/doctype/account/account.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

account.py

merge_account

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

style: format code with black

def print_help(self): has_fund_start = "" if self.fund_symbol else "[unvl]" has_fund_end = "" if self.fund_symbol else "[/unvl]" has_fund_usa_start = ( "" if self.fund_symbol and self.country == "united states" else "[unvl]" ) has_fund_usa_end = ( "" if self.fund_symbol and self.country == "united states" else "[/unvl]" ) if self.fund_name: if self.fund_symbol: fund_string = f"{self.fund_name} ({self.fund_symbol})" else: fund_string = f"{self.fund_name}" else: fund_string = "" help_text = f if self.fund_symbol != "" and self.country == "sweden": help_text += console.print(text=help_text, menu="Mutual Funds")

gamestonk_terminal/mutual_funds/mutual_fund_controller.py

OpenBBTerminal

Python

493617752699ff4ab63a1ed9df478ac030e68492

mutual_fund_controller.py

print_help

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

Add avanza mutual fund data and commands (#1452) * Adding info_se and al_swe commands * Linting * Linting * linting * Fixes * Fixes to formatting * Linting * Linting * Linting Co-authored-by: jmaslek <[email protected]> Co-authored-by: Colin Delahunty <[email protected]> Co-authored-by: didierlopes.eth <[email protected]>

def forward_dummy(self, img, img_metas): super(SingleStageDetector, self).forward_train(img, img_metas) x = self.extract_feat(img) outs = self.panoptic_head(x, img_metas) return outs

mmdet/models/detectors/maskformer.py

mmdetection

Python

cac356380d505bf15587f07c0529218cc36b9652

maskformer.py

forward_dummy

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

[Feature] Add Maskformer to mmdet (#7212) * first commit * add README * move model description from config to readme add description for binary_input add description for dice loss add a independent panoptic gt processing function add a independent panoptic gt processing function remove compatibility of pretrain in maskformer * update comments in maskformer_head * update docs format

def setDefaultWhitespaceChars(chars): r ParserElement.DEFAULT_WHITE_CHARS = chars

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

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

pyparsing.py

setDefaultWhitespaceChars

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

upd; format

def override_recursive(a, b): for key in b: if isinstance(b[key], dict) is False: a[key] = b[key] elif key not in a or isinstance(a[key], dict) is False: a[key] = b[key] # make config section empty by demand elif isinstance(b[key], dict) is True and b[key] == {}: a[key] = b[key] else: override_recursive(a[key], b[key]) @pytest.fixture(scope="module")

tests/integration_tests/flows/conftest.py

@pytest.fixture(scope="module")

mindsdb

Python

ae4fa77a2c0a9fa57cc9c8bc7e8961dd01e4067e

conftest.py

override_recursive

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

It mysql api test pytest (#3694) * migration to pytest * Tests start passing * Fully working tests * Increase timeout for mindsdb start * reduce amount of logs * show logs only for failed tests

def result(term): print("\n" + str(calc(term)))

calculator.py

Python

Python

f0af0c43340763724f139fa68aa1e5a9ffe458b4

calculator.py

result

https://github.com/geekcomputers/Python.git

refactor: clean code Signed-off-by: slowy07 <[email protected]>

def installed_location(self) -> Optional[str]: egg_link = egg_link_path_from_location(self.raw_name) if egg_link: location = egg_link elif self.location: location = self.location else: return None return normalize_path(location)

pipenv/patched/notpip/_internal/metadata/base.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

base.py

installed_location

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 spsolve(data, indices, indptr, b, tol=1e-6, reorder=1): if jax._src.lib.xla_extension_version < 86: raise ValueError('spsolve requires jaxlib version 86 or above.') return spsolve_p.bind(data, indices, indptr, b, tol=tol, reorder=reorder)

jax/experimental/sparse/linalg.py

jax

Python

2bc3e39cd9104071ee39dacac22abd51b94eb27e

linalg.py

spsolve

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

Sparse direct solver using QR factorization from cuSOLVER. This is the jaxlib implementation. We will want to combine this with the sparse libraries already existing in JAX. PiperOrigin-RevId: 468303019

def request_params(self, **kwargs) -> MutableMapping[str, Any]: params = {"limit": self.page_size} if self._include_deleted: params.update(self._filter_all_statuses()) if self.send_fields: params.update({"fields": ",".join(self.fields)}) return params

airbyte-integrations/connectors/source-facebook-marketing/source_facebook_marketing/streams.py

airbyte

Python

2573fa145a1fbf4e849d26c54de105bcacde114f

streams.py

request_params

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

🎉 Source Facebook Marketing: Add AdAccount and Images stream implementation (#10180) * Add AdAccount and Images stream implementation * Update PR number * Updated docker version * Updated to linter * Update to review * Add comment to AdAccount read_records method * Bumped version in seed, definitions and specs files

def axis(self): q = self AX = Quaternion(0, q.b, q.c, q.d).normalize() return AX

sympy/algebras/quaternion.py

sympy

Python

e8c5f4fe692e863bf0a48573a1d0c7b92487c5c1

quaternion.py

axis

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

hamilton

def dagrun_queued(self): dag_id = request.form.get('dag_id') dag_run_id = request.form.get('dag_run_id') confirmed = request.form.get('confirmed') == 'true' origin = get_safe_url(request.form.get('origin')) return self._mark_dagrun_state_as_queued(dag_id, dag_run_id, confirmed, origin)

airflow/www/views.py

airflow

Python

afd3c135c7d1815c56578d020625a33dc27fe640

views.py

dagrun_queued

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

Add queue button to click-on-DagRun interface. (#21555) * Initial implementation of adding Queue button to DagRun interface * Implement the test cases * FIX Add all required MyPy ignores * FIX import * Update airflow/www/views.py FIX Documentation Co-authored-by: Brent Bovenzi <[email protected]> * update modal UI Co-authored-by: Brent Bovenzi <[email protected]>

def _start(self) -> int: warnings.warn( self._deprecation_message.format("_start", "start"), FutureWarning, stacklevel=find_stack_level(inspect.currentframe()), ) return self.start

pandas/core/indexes/range.py

pandas

Python

2f8d0a36703e81e4dca52ca9fe4f58c910c1b304

range.py

_start

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

PERF cache find_stack_level (#48023) cache stacklevel

def string_position(self, id_): if self.bow: return self.string_start[self.positions[id_]] else: return self.string_start[[self.positions[id_]]]

examples/model_interpretation/task/senti/LIME/lime_text.py

PaddleNLP

Python

93cae49c0c572b5c1ac972759140fbe924b0374d

lime_text.py

string_position

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

Add NLP model interpretation (#1752) * upload NLP interpretation * fix problems and relocate project * remove abandoned picture * remove abandoned picture * fix dead link in README * fix dead link in README * fix code style problems * fix CR round 1 * remove .gitkeep files * fix code style * fix file encoding problem * fix code style * delete duplicated files due to directory rebuild * fix CR round 2 * fix code style * fix ernie tokenizer * fix code style * fix problem from CR round 1 * fix bugs * fix README * remove duplicated files * deal with diff of old and new tokenizer results * fix CR round 4 * fix code style * add missing dependence * fix broken import path * move some data file to cloud * MRC upper case to lower case Co-authored-by: Zeyu Chen <[email protected]> Co-authored-by: binlinquge <xxx> Co-authored-by: Guo Sheng <[email protected]>

def _get_save_args(self) -> Tuple[int, ...]: filetype = self.config["format"] args: Tuple[int, ...] = tuple() if filetype == "jpg" and self.config["jpg_quality"] > 0: args = (cv2.IMWRITE_JPEG_QUALITY, # pylint: disable=no-member self.config["jpg_quality"]) if filetype == "png" and self.config["png_compress_level"] > -1: args = (cv2.IMWRITE_PNG_COMPRESSION, # pylint: disable=no-member self.config["png_compress_level"]) logger.debug(args) return args

plugins/convert/writer/opencv.py

faceswap

Python

049314429f71a21e6595e9d27e9e36f6a3479c42

opencv.py

_get_save_args

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

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

def test_resample(): n = 101 colorlist = np.empty((n, 4), float) colorlist[:, 0] = np.linspace(0, 1, n) colorlist[:, 1] = 0.2 colorlist[:, 2] = np.linspace(1, 0, n) colorlist[:, 3] = 0.7 lsc = mcolors.LinearSegmentedColormap.from_list('lsc', colorlist) lc = mcolors.ListedColormap(colorlist) # Set some bad values for testing too for cmap in [lsc, lc]: cmap.set_under('r') cmap.set_over('g') cmap.set_bad('b') lsc3 = lsc.resample(3) lc3 = lc.resample(3) expected = np.array([[0.0, 0.2, 1.0, 0.7], [0.5, 0.2, 0.5, 0.7], [1.0, 0.2, 0.0, 0.7]], float) assert_array_almost_equal(lsc3([0, 0.5, 1]), expected) assert_array_almost_equal(lc3([0, 0.5, 1]), expected) # Test over/under was copied properly assert_array_almost_equal(lsc(np.inf), lsc3(np.inf)) assert_array_almost_equal(lsc(-np.inf), lsc3(-np.inf)) assert_array_almost_equal(lsc(np.nan), lsc3(np.nan)) assert_array_almost_equal(lc(np.inf), lc3(np.inf)) assert_array_almost_equal(lc(-np.inf), lc3(-np.inf)) assert_array_almost_equal(lc(np.nan), lc3(np.nan))

lib/matplotlib/tests/test_colors.py

matplotlib

Python

1e40f41713fab2d4a86aa26766b3cf6cccd9203d

test_colors.py

test_resample

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

ENH: Make the ability to resample interpolated colormaps public

def test_cr_image_consistency(): cr = _get_basic_ray_cr() group_specs = [cr["spec"]["headGroupSpec"]] + cr["spec"]["workerGroupSpecs"] # Head, CPU group, GPU group. assert len(group_specs) == 3 ray_containers = [ group_spec["template"]["spec"]["containers"][0] for group_spec in group_specs ] # All Ray containers in the example config have "ray-" in their name. assert all("ray-" in ray_container["name"] for ray_container in ray_containers) # All Ray images are from the Ray repo. assert all( "rayproject/ray" in ray_container["image"] for ray_container in ray_containers ) # All Ray images are the same. assert len({ray_container["image"] for ray_container in ray_containers}) == 1 @pytest.mark.parametrize("exception", [Exception, requests.HTTPError]) @pytest.mark.parametrize("num_exceptions", range(6))

python/ray/tests/kuberay/test_autoscaling_config.py

@pytest.mark.parametrize("exception", [Exception, requests.HTTPError]) @pytest.mark.parametrize("num_exceptions", range(6))

ray

Python

7d3ceb222c8af98a5c101b1c28ab37ffcb0a3793

test_autoscaling_config.py

test_cr_image_consistency

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

[kuberay][autoscaler] Improve CPU, GPU, and memory detection. (#26219) This PR improves the autoscaler's resource detection logic

def resized_crop(clip, i, j, h, w, size, interpolation_mode="bilinear"): if not _is_tensor_video_clip(clip): raise ValueError("clip should be a 4D torch.tensor") clip = crop(clip, i, j, h, w) clip = resize(clip, size, interpolation_mode) return clip

torchvision/transforms/_functional_video.py

vision

Python

289fce29b3e2392114aadbe7a419df0f2e3ac1be

_functional_video.py

resized_crop

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

Replace asserts with exceptions (#5587) * replace most asserts with exceptions * fix formating issues * fix linting and remove more asserts * fix regresion * fix regresion * fix bug * apply ufmt * apply ufmt * fix tests * fix format * fix None check * fix detection models tests * non scriptable any * add more checks for None values * fix retinanet test * fix retinanet test * Update references/classification/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * Update references/classification/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * Update references/optical_flow/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * Update references/optical_flow/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * Update references/optical_flow/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * make value checks more pythonic: * Update references/optical_flow/transforms.py Co-authored-by: Nicolas Hug <[email protected]> * make value checks more pythonic * make more checks pythonic * fix bug * appy ufmt * fix tracing issues * fib typos * fix lint * remove unecessary f-strings * fix bug * Update torchvision/datasets/mnist.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/datasets/mnist.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/ops/boxes.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/ops/poolers.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/utils.py Co-authored-by: Nicolas Hug <[email protected]> * address PR comments * Update torchvision/io/_video_opt.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/models/detection/generalized_rcnn.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/models/feature_extraction.py Co-authored-by: Nicolas Hug <[email protected]> * Update torchvision/models/optical_flow/raft.py Co-authored-by: Nicolas Hug <[email protected]> * address PR comments * addressing further pr comments * fix bug * remove unecessary else * apply ufmt * last pr comment * replace RuntimeErrors Co-authored-by: Nicolas Hug <[email protected]>

def test_spectral_params_validation(input, params, err_type, err_msg): est = SpectralClustering(**params) with pytest.raises(err_type, match=err_msg): est.fit(input) @pytest.mark.parametrize("assign_labels", ("kmeans", "discretize", "cluster_qr"))

sklearn/cluster/tests/test_spectral.py

@pytest.mark.parametrize("assign_labels", ("kmeans", "discretize", "cluster_qr"))

scikit-learn

Python

26e2c38a961a27a9e53ce7814bf27f840510b237

test_spectral.py

test_spectral_params_validation

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

[MRG] MNT use check_scalar to validate scalar in SpectralClustering (#21881) * use check_scalar in SpectralClustering * Add check_scalar parameters validation for cluster.SpectralClustering * fix missing comma * tiny changelog update to relauch CI * errors are raised at fit time solely Co-authored-by: Julien Jerphanion <[email protected]> * fix typos Co-authored-by: Julien Jerphanion <[email protected]> * merge ..utils imports Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: hvassard <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]>

def check_graph_consistency(tensor=None, method="add_loss", force_raise=False): if force_raise or ( tf.compat.v1.executing_eagerly_outside_functions() and hasattr(tensor, "graph") and tensor.graph.is_control_flow_graph ): if method == "activity_regularizer": bad_example =

keras/engine/base_layer_utils.py

bad_example = """

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_layer_utils.py

check_graph_consistency

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

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def get_url(path, dest="", saltenv=None, makedirs=False, source_hash=None): if not saltenv: saltenv = __opts__["saltenv"] or "base" if isinstance(dest, str): result = _client().get_url( path, dest, makedirs, saltenv, source_hash=source_hash ) else: result = _client().get_url( path, None, makedirs, saltenv, no_cache=True, source_hash=source_hash ) if not result: log.error( "Unable to fetch file %s from saltenv %s.", salt.utils.url.redact_http_basic_auth(path), saltenv, ) if result: return salt.utils.stringutils.to_unicode(result) return result

salt/modules/cp.py

salt

Python

2bd6323ef5f87d871891a59917ee96f44ef55e75

cp.py

get_url

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

fixes saltstack/salt#61562 cp functions derive saltenv from config

def test_mapped_literal_verify_integrity(dag_maker, session): with dag_maker(session=session) as dag:

tests/models/test_dagrun.py

airflow

Python

91832a42d8124b040073481fd93c54e9e64c2609

test_dagrun.py

test_mapped_literal_verify_integrity

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

Expand mapped tasks at DagRun.Veriy_integrity (#22679) Create the necessary task instances for a mapped task at dagrun.verify_integrity Co-authored-by: Ash Berlin-Taylor <[email protected]>

def test_cursor_var(self): with connection.cursor() as cursor: var = cursor.var(str) cursor.execute("BEGIN %s := 'X'; END; ", [var]) self.assertEqual(var.getvalue(), "X")

tests/backends/oracle/tests.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

test_cursor_var

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

Refs #33476 -- Reformatted code with Black.

def _eval_Mod(self, q): r base, exp = self.base, self.exp if exp.is_integer and exp.is_positive: if q.is_integer and base % q == 0: return S.Zero from sympy.ntheory.factor_ import totient if base.is_Integer and exp.is_Integer and q.is_Integer: b, e, m = int(base), int(exp), int(q) mb = m.bit_length() if mb <= 80 and e >= mb and e.bit_length()**4 >= m: phi = totient(m) return Integer(pow(b, phi + e%phi, m)) return Integer(pow(b, e, m)) from .mod import Mod if isinstance(base, Pow) and base.is_integer and base.is_number: base = Mod(base, q) return Mod(Pow(base, exp, evaluate=False), q) if isinstance(exp, Pow) and exp.is_integer and exp.is_number: bit_length = int(q).bit_length() # XXX Mod-Pow actually attempts to do a hanging evaluation # if this dispatched function returns None. # May need some fixes in the dispatcher itself. if bit_length <= 80: phi = totient(q) exp = phi + Mod(exp, phi) return Mod(Pow(base, exp, evaluate=False), q)

sympy/core/power.py

sympy

Python

cda8dfe6f45dc5ed394c2f5cda706cd6c729f713

power.py

_eval_Mod

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

Improved documentation formatting

def host_header(self) -> Optional[str]: if self.is_http2 or self.is_http3: return self.authority or self.data.headers.get("Host", None) else: return self.data.headers.get("Host", None)

mitmproxy/http.py

mitmproxy

Python

8e71b0331b8de95c4204d5cc26fb07e967883972

http.py

host_header

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

[quic] add is_http3 where necessary

def test_proxy_manager_lifecycle(shutdown_only): proxier.CHECK_PROCESS_INTERVAL_S = 1 os.environ["TIMEOUT_FOR_SPECIFIC_SERVER_S"] = "5" pm, free_ports = start_ray_and_proxy_manager(n_ports=2) client = "client1" pm.create_specific_server(client) assert pm.start_specific_server(client, JobConfig()) # Channel should be ready and corresponding to an existing server grpc.channel_ready_future(pm.get_channel(client)).result(timeout=5) proc = pm._get_server_for_client(client) assert proc.port == free_ports[0], f"Free Ports are: {free_ports}" log_files_path = os.path.join( pm.node.get_session_dir_path(), "logs", "ray_client_server*" ) files = glob(log_files_path) assert any(str(free_ports[0]) in f for f in files) proc.process_handle_future.result().process.wait(10) # Wait for reconcile loop time.sleep(2) assert len(pm._free_ports) == 2 assert pm._get_unused_port() == free_ports[1] @pytest.mark.skipif( sys.platform == "win32", reason="PSUtil does not work the same on windows." )

python/ray/tests/test_client_proxy.py

@pytest.mark.skipif( sys.platform == "win32", reason="PSUtil does not work the same on windows." )

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

test_client_proxy.py

test_proxy_manager_lifecycle

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

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

def require_wandb(test_case): if not is_wandb_available(): return unittest.skip("test requires wandb")(test_case) else: return test_case

src/transformers/testing_utils.py

transformers

Python

c74f3d4c480a6971e302de7cef226e9a157ef0d0

testing_utils.py

require_wandb

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

Add W&B backend for hyperparameter sweep (#14582) # Add support for W&B hyperparameter sweep This PR: * allows using wandb for running hyperparameter search. * The runs are visualized on W&B sweeps dashboard * This supports runnning sweeps on parallel devices, all reporting to the same central dashboard. ### Usage **To run new a hyperparameter search:** ``` trainer.hyperparameter_search( backend="wandb", project="transformers_sweep", # name of the project n_trials=5, metric="eval/loss", # metric to be optimized, default 'eval/loss'. A warning is raised if the passed metric is not found ) ``` This outputs a sweep id. Eg. `my_project/sweep_id` **To run sweeps on parallel devices:** Just pass sweep id which you want to run parallel ``` trainer.hyperparameter_search( backend="wandb", sweep_id = "my_project/sweep_id" ) ```

def _object2proto(self) -> GetObjectResponseMessage_PB: ser = serialize(self.obj) return GetObjectResponseMessage_PB( msg_id=serialize(self.id), address=serialize(self.address), obj=ser, )

packages/syft/src/syft/core/node/common/action/get_object_action.py

PySyft

Python

7f44809cca9457058171cfd65994fb4aee8031ac

get_object_action.py

_object2proto

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

Replace absolute syft imports

def doctest_tb_context():

IPython/core/tests/test_iplib.py

ipython

Python

a72418e2dcdfc3c91f70d724d16d2691a41c9c24

test_iplib.py

doctest_tb_context

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

Restore lineno's for Input mapped files (#13560) * Implement lineno's for Input mapped files * Adopt In [123], line 123 format * Revert "Set co_name for cells run line by line. Fixes https://github.com/ipython/ipykernel/issues/841" (This reverts commit d11e987f174a15f1640f8006c86f58d884c3faa4.) * Omit mention of ", in <module>" for input tracebacks * Input cell -> Cell * Remove <module> from traceback doctests * Use f-string for `in ...' format * Simplify _format_list logic, converting to f-strings

def new(self) -> None: from rich import box, print from rich.console import Console from rich.panel import Panel from rich.progress import track from rich.prompt import Confirm, Prompt from rich.syntax import Syntax from rich.table import Table console = Console() print( Panel.fit( , title='Create New Executor', ) ) exec_name = ( self.args.name if self.args.name else Prompt.ask( ':grey_question: What is the [bold]name[/bold] of your executor?\n' '[dim]CamelCase is required[/dim]', default=f'MyExecutor{random.randint(0, 100)}', ) ) exec_path = ( self.args.path if self.args.path else Prompt.ask( ':grey_question: [bold]Which folder[/bold] to store your executor?', default=os.path.join(os.getcwd(), exec_name), ) ) exec_description = '{{}}' exec_keywords = '{{}}' exec_url = '{{}}' is_dockerfile = False if self.args.advance_configuration or Confirm.ask( '[green]That\'s all we need to create an Executor![/green]\n' ':grey_question: Or do you want to proceed to advanced configuration', default=False, ): exec_description = ( self.args.description if self.args.description else ( Prompt.ask( ':grey_question: Please give a [bold]short description[/bold] of your executor?\n' f'[dim]Example: {exec_name} embeds images into 128-dim vectors using ResNet.[/dim]' ) ) ) exec_keywords = ( self.args.keywords if self.args.keywords else ( Prompt.ask( ':grey_question: Please give some [bold]keywords[/bold] to help people search your executor [dim](separated by comma)[/dim]\n' f'[dim]Example: image cv embedding encoding resnet[/dim]' ) ) ) exec_url = ( self.args.url if self.args.url else ( Prompt.ask( ':grey_question: What is the [bold]URL[/bold] for GitHub repo?\n' f'[dim]Example: https://github.com/yourname/my-executor[/dim]' ) ) ) print( Panel.fit( , title='[Optional] [bold]Dockerfile[/bold]', width=80, ) ) is_dockerfile = self.args.add_dockerfile or Confirm.ask( ':grey_question: Do you need to write your own [bold]Dockerfile[/bold] instead of the auto-generated one?', default=False, ) print('[green]That\'s all we need to create an Executor![/green]')

jina/hubble/hubio.py

jina

Python

beb0d8f569530755f7797781a8cb49e1b8a2faaf

hubio.py

new

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

feat(hubble): fetch image only when required (#4445)

def split_having(self, negated=False): if not self.contains_aggregate: return self, None in_negated = negated ^ self.negated # If the effective connector is OR and this node contains an aggregate, # then we need to push the whole branch to HAVING clause. may_need_split = (in_negated and self.connector == AND) or ( not in_negated and self.connector == OR ) if may_need_split and self.contains_aggregate: return None, self where_parts = [] having_parts = [] for c in self.children: if hasattr(c, "split_having"): where_part, having_part = c.split_having(in_negated) if where_part is not None: where_parts.append(where_part) if having_part is not None: having_parts.append(having_part) elif c.contains_aggregate: having_parts.append(c) else: where_parts.append(c) having_node = ( self.__class__(having_parts, self.connector, self.negated) if having_parts else None ) where_node = ( self.__class__(where_parts, self.connector, self.negated) if where_parts else None ) return where_node, having_node

django/db/models/sql/where.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

where.py

split_having

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

Refs #33476 -- Reformatted code with Black.

def unpack_collections(*args, traverse=True): collections = [] repack_dsk = {} collections_token = uuid.uuid4().hex

dask/base.py

dask

Python

8971c37f810aa242295dd6a7d9a7cbdf9621d92e

base.py

unpack_collections

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

Tokenize dataclasses (#8557)

async def test_callback_view_with_jwt(hass, hass_client): registrations = {"device": SUBSCRIPTION_1} client = await mock_client(hass, hass_client, registrations) with patch("homeassistant.components.html5.notify.WebPusher") as mock_wp: mock_wp().send().status_code = 201 await hass.services.async_call( "notify", "notify", {"message": "Hello", "target": ["device"], "data": {"icon": "beer.png"}}, blocking=True, ) assert len(mock_wp.mock_calls) == 4 # WebPusher constructor assert mock_wp.mock_calls[2][1][0] == SUBSCRIPTION_1["subscription"] # Call to send push_payload = json.loads(mock_wp.mock_calls[3][1][0]) assert push_payload["body"] == "Hello" assert push_payload["icon"] == "beer.png" bearer_token = "Bearer {}".format(push_payload["data"]["jwt"]) resp = await client.post( PUBLISH_URL, json={"type": "push"}, headers={AUTHORIZATION: bearer_token} ) assert resp.status == HTTPStatus.OK body = await resp.json() assert body == {"event": "push", "status": "ok"}

tests/components/html5/test_notify.py

core

Python

652fedf4d1de2645ba08e6ace5376c7126839154

test_notify.py

test_callback_view_with_jwt

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

Fix html5 Firefox Notifications (#82556) Co-authored-by: Paulus Schoutsen <[email protected]> fixes undefined