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semeru

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code-code-galeras-code-completion-from-docstring-3k-deduped

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Semeru Lab 7

tests/components/siren/test_init.py

async def test_missing_tones_list(hass): siren = MockSirenEntity(SirenEntityFeature.TONES, ["a", "b"]) siren.hass = hass with pytest.raises(ValueError): process_turn_on_params(siren, {"tone": "test"})

Add EntityFeature enum to Siren (#69585) Co-authored-by: Franck Nijhof <[email protected]>

test_missing_tones_list

a61ac3ddc6d65522dfa1eb599adf73420a9267dc

core

test_init.py

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

Python

async def test_missing_tones_list(hass): siren = MockSirenEntity(SirenEntityFeature.TONES, ["a", "b"]) siren.hass = hass with pytest.raises(ValueError): process_turn_on_params(siren, {"tone": "test"})

@cli_utils.action_cli(check_db=False) @suppress_logs_and_warning

airflow/cli/commands/task_command.py

def task_failed_deps(args): dag = get_dag(args.subdir, args.dag_id) task = dag.get_task(task_id=args.task_id) ti = _get_ti(task, args.execution_date_or_run_id, args.map_index) dep_context = DepContext(deps=SCHEDULER_QUEUED_DEPS) failed_deps = list(ti.get_failed_dep_statuses(dep_context=dep_context)) # TODO, Do we want to print or log this if failed_deps: print("Task instance dependencies not met:") for dep in failed_deps: print(f"{dep.dep_name}: {dep.reason}") else:

Add `--map-index` parameter to task CLI commands (#20980)

task_failed_deps

8dabce8887f02216c1037be35e80c214edcbadfe

airflow

task_command.py

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

Python

def task_failed_deps(args): dag = get_dag(args.subdir, args.dag_id) task = dag.get_task(task_id=args.task_id) ti = _get_ti(task, args.execution_date_or_run_id, args.map_index) dep_context = DepContext(deps=SCHEDULER_QUEUED_DEPS) failed_deps = list(ti.get_failed_dep_statuses(dep_context=dep_context)) # TODO, Do we want to print or log this if failed_deps: print("Task instance dependencies not met:") for dep in failed_deps: print(f"{dep.dep_name}: {dep.reason}") else: print("Task instance dependencies are all met.") @cli_utils.action_cli(check_db=False) @suppress_logs_and_warning

python3.10.4/Lib/http/cookies.py

def load(self, rawdata): if isinstance(rawdata, str):

add python 3.10.4 for windows

load

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

cookies.py

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

Python

def load(self, rawdata): if isinstance(rawdata, str): self.__parse_string(rawdata) else: # self.update() wouldn't call our custom __setitem__ for key, value in rawdata.items(): self[key] = value return

lib/matplotlib/axis.py

def _reset_major_tick_kw(self, keep_tick_and_label_visibility=False): backup = {name: value for name, value in self._major_tick_kw.items() if name in ['tick1On', 'tick2On', 'label1On', 'label2On']} self.

Refactor handling of tick and ticklabel visiblity in Axis.clear() This is a follow-up to #20826, which makes the exceptions from clearing more explicit.

_reset_major_tick_kw

2357c92d87d96d519c8470776e76180e71663d0b

matplotlib

axis.py

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

Python

def _reset_major_tick_kw(self, keep_tick_and_label_visibility=False): backup = {name: value for name, value in self._major_tick_kw.items() if name in ['tick1On', 'tick2On', 'label1On', 'label2On']} self._major_tick_kw.clear() if keep_tick_and_label_visibility: self._major_tick_kw.update(backup) self._major_tick_kw['gridOn'] = ( mpl.rcParams['axes.grid'] and mpl.rcParams['axes.grid.which'] in ('both', 'major'))

python/ray/tune/tests/test_integration_comet.py

def test_class_variable_to_instance(self): logger = self.logger self.assertEqual(logger._to_exclude, logger._exclude_results) self.assertEqual(logger._to_system, lo

Comet Integration (#20766) This PR adds a `CometLoggerCallback` to the Tune Integrations, allowing users to log runs from Ray to [Comet](https://www.comet.ml/site/). Co-authored-by: Michael Cullan <[email protected]> Co-authored-by: Antoni Baum <[email protected]>

test_class_variable_to_instance

3d79815cd08c1be8e56c245e662f34366523847e

ray

test_integration_comet.py

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

Python

def test_class_variable_to_instance(self): logger = self.logger self.assertEqual(logger._to_exclude, logger._exclude_results) self.assertEqual(logger._to_system, logger._system_results) self.assertEqual(logger._to_other, logger._other_results) self.assertEqual(logger._to_episodes, logger._episode_results)

pipenv/patched/pip/_vendor/chardet/__init__.py

def detect_all(byte_str, ignore_threshold=False): if not isinstance(byte_str, bytearray): if not isinstance(byte_str, bytes): raise TypeError( f"Expected object of type bytes or bytearray, got: {type(byte_str)}" ) b

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

detect_all

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

pipenv

__init__.py

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

Python

def detect_all(byte_str, ignore_threshold=False): if not isinstance(byte_str, bytearray): if not isinstance(byte_str, bytes): raise TypeError( f"Expected object of type bytes or bytearray, got: {type(byte_str)}" ) byte_str = bytearray(byte_str) detector = UniversalDetector() detector.feed(byte_str) detector.close() if detector.input_state == InputState.HIGH_BYTE: results = [] probers = [] for prober in detector.charset_probers: if hasattr(prober, "probers"): probers.extend(p for p in prober.probers) else: probers.append(prober) for prober in probers: if ignore_threshold or prober.get_confidence() > detector.MINIMUM_THRESHOLD: charset_name = prober.charset_name or "" lower_charset_name = charset_name.lower() # Use Windows encoding name instead of ISO-8859 if we saw any # extra Windows-specific bytes if lower_charset_name.startswith("iso-8859") and detector.has_win_bytes: charset_name = detector.ISO_WIN_MAP.get( lower_charset_name, charset_name ) results.append( { "encoding": charset_name, "confidence": prober.get_confidence(), "language": prober.language, } ) if len(results) > 0: return sorted(results, key=lambda result: -result["confidence"]) return [detector.result]

python3.10.4/Lib/enum.py

def __call__(cls, value, names=None, *, module=None, qualname=None, type=None, start=1): if names is None: # simple value lookup return cls.__new__(cls, value) # otherwise, functional API: we're creating a new Enum type return cls._create_( value, names, module=module, qualname=qualname, type=type, start=start,

add python 3.10.4 for windows

__call__

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

enum.py

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

Python

def __call__(cls, value, names=None, *, module=None, qualname=None, type=None, start=1): if names is None: # simple value lookup return cls.__new__(cls, value) # otherwise, functional API: we're creating a new Enum type return cls._create_( value, names, module=module, qualname=qualname, type=type, start=start, )

nltk/util.py

def edges2dot(edges, shapes=None, attr=None): if not shapes:

Fix some tests in Wordnet-related DocStrings

edges2dot

692adaff901dd9daf29400fdf3385130aefbfb2a

nltk

util.py

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

Python

def edges2dot(edges, shapes=None, attr=None): if not shapes: shapes = dict() if not attr: attr = dict() dot_string = "digraph G {\n" for pair in attr.items(): dot_string += f"{pair[0]} = {pair[1]};\n" for edge in edges: for shape in shapes.items(): for node in range(2): if shape[0] in repr(edge[node]): dot_string += f'"{edge[node]}" [shape = {shape[1]}];\n' dot_string += f'"{edge[0]}" -> "{edge[1]}";\n' dot_string += "}\n" return dot_string

pipenv/patched/notpip/_vendor/pygments/formatters/img.py

def _draw_line_numbers(self): if not self.line_numbers: return for p in range(self.maxlineno): n = p + self.line_number_start if (n % self.line_number_step) == 0:

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

_draw_line_numbers

f3166e673fe8d40277b804d35d77dcdb760fc3b3

pipenv

img.py

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

Python

def _draw_line_numbers(self): if not self.line_numbers: return for p in range(self.maxlineno): n = p + self.line_number_start if (n % self.line_number_step) == 0: self._draw_linenumber(p, n)

manim/cli/cfg/group.py

def export(ctx, directory): directory_path = Path(directory) if directory_path.absolute == Path.cwd().absolute: console.print( , style="red bold", end="", ) proc

Migrate from os.path to pathlib in SVGMobject and other locations (#2687) * fixed style * fixed changes * Update group.py * Remove extra `Path` call Co-authored-by: ad_chaos <[email protected]> * Remove unused context manager Sorry, just committing here myself so that the PR can be reviewed and merged. This is the only thing left to alter so thought I might as well do it myself. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Use `with_suffix` * Remove extra `Path` calls Co-authored-by: ad_chaos <[email protected]> Co-authored-by: Darylgolden <[email protected]> Co-authored-by: Raghav Goel <[email protected]> Co-authored-by: Raghav Goel <[email protected]> Co-authored-by: ad_chaos <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

export

a20f8aeb6ccd30d6b9d5c34285c3a718b0f5a59b

manim

group.py

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

Python

def export(ctx, directory): directory_path = Path(directory) if directory_path.absolute == Path.cwd().absolute: console.print( , style="red bold", end="", ) proceed = input().lower() == "y" else: proceed = True if proceed: if not directory_path.is_dir(): console.print(f"Creating folder: {directory}.", style="red bold") directory_path.mkdir(parents=True) ctx.invoke(write) from_path = Path.cwd() / "manim.cfg" to_path = directory_path / "manim.cfg" console.print(f"Exported final Config at {from_path} to {to_path}.") else: console.print("Aborted...", style="red bold")

lib/matplotlib/backend_managers.py

def update_keymap(self, name, key): if name not in self._tools: raise KeyError(f'{name!r} not in Tools')

Add tests for ToolManager

update_keymap

0d6ee255831adae452af355c025497c0f07aa296

matplotlib

backend_managers.py

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

Python

def update_keymap(self, name, key): if name not in self._tools: raise KeyError(f'{name!r} not in Tools') self._remove_keys(name) if isinstance(key, str): key = [key] for k in key: if k in self._keys: _api.warn_external( f'Key {k} changed from {self._keys[k]} to {name}') self._keys[k] = name

nni/retiarii/oneshot/pytorch/supermodule/differentiable.py

def named_parameters(self, *args, **kwargs): arch = kwargs.pop('arch', False) for name, p in super().named_parameters(*args, **kwargs): if any(name == par_name for par_name in self._arch_parameter_names): if arch:

Valuechoice oneshot lightning (#4602)

named_parameters

14d2966b9e91ae16dcc39de8f41017a75cec8ff9

nni

differentiable.py

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

Python

def named_parameters(self, *args, **kwargs): arch = kwargs.pop('arch', False) for name, p in super().named_parameters(*args, **kwargs): if any(name == par_name for par_name in self._arch_parameter_names): if arch: yield name, p else: if not arch: yield name, p

jax/_src/util.py

def unzip3(xyzs): # Note: we deliberately don't use zip(*xyzs) because it is lazily evaluated, # is too permissive about inputs, and does not guarantee a length-3 output. xs = [] ys = [] zs = [] for x, y, z in xyzs: xs.append(x) ys.append

Comment on implementation of unzip2 & unzip3

unzip3

72470dee3a5181c8bfe0f0a4725564efbef80f92

jax

util.py

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

Python

def unzip3(xyzs): # Note: we deliberately don't use zip(*xyzs) because it is lazily evaluated, # is too permissive about inputs, and does not guarantee a length-3 output. xs = [] ys = [] zs = [] for x, y, z in xyzs: xs.append(x) ys.append(y) zs.append(z) return tuple(xs), tuple(ys), tuple(zs)

zerver/tests/test_subs.py

def test_json_get_subscribers_for_guest_user(self) -> None: guest_user = self.example_user("polonius") never_subscribed = gather_subscriptions_helper(guest_user, True).never_subscribed # A guest user can only see never subscribed streams that are web-public. # For Polonius, the only web-public stream that he is not subscribed at # this point is Rome. self.assert_length(never_subscribed, 1) web_public_stream_id = never_subscribed[0]["stream_id"] result = self.client_get(f"/json/streams/{web_public_stream_id}/members") self.assert_json_success(result) result_dict = result.json() self.assertIn("subscribers", result_dict) self.assertIsInstance(result_dict["subscribers"], list) self.assertG

docs: Consistently hyphenate “web-public”. In English, compound adjectives should essentially always be hyphenated. This makes them easier to parse, especially for users who might not recognize that the words “web public” go together as a phrase. Signed-off-by: Anders Kaseorg <[email protected]>

test_json_get_subscribers_for_guest_user

90e202cd38d00945c81da4730d39e3f5c5b1e8b1

zulip

test_subs.py

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

Python

def test_json_get_subscribers_for_guest_user(self) -> None: guest_user = self.example_user("polonius") never_subscribed = gather_subscriptions_helper(guest_user, True).never_subscribed # A guest user can only see never subscribed streams that are web-public. # For Polonius, the only web-public stream that he is not subscribed at # this point is Rome. self.assert_length(never_subscribed, 1) web_public_stream_id = never_subscribed[0]["stream_id"] result = self.client_get(f"/json/streams/{web_public_stream_id}/members") self.assert_json_success(result) result_dict = result.json() self.assertIn("subscribers", result_dict) self.assertIsInstance(result_dict["subscribers"], list) self.assertGreater(len(result_dict["subscribers"]), 0)

packages/python/chart-studio/chart_studio/plotly/chunked_requests/chunked_request.py

def _reconnect(self): if not self._isconnected(): try: self._connec

switch to black .22

_reconnect

43e3a4011080911901176aab919c0ecf5046ddd3

plotly.py

chunked_request.py

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

Python

def _reconnect(self): if not self._isconnected(): try: self._connect() except http_client.socket.error as e: # Attempt to reconnect if the connection was refused if e.errno == 61 or e.errno == 10061: # errno 61 is the "Connection Refused" error time.sleep(self._delay) self._delay += self._delay # fibonacii delays self._tries += 1 if self._tries < self.maxtries: self._reconnect() else: self._reset_retries() raise e else: # Unknown scenario raise e # Reconnect worked - reset _closed self._closed = False

salt/modules/cp.py

def list_master(saltenv=None, prefix=""): if not saltenv:

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

list_master

2bd6323ef5f87d871891a59917ee96f44ef55e75

salt

cp.py

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

Python

def list_master(saltenv=None, prefix=""): if not saltenv: saltenv = __opts__["saltenv"] or "base" return _client().file_list(saltenv, prefix)

tests/ludwig/utils/test_tokenizers.py

def test_bert_hf_tokenizer_parity(tmpdir, pretrained_model_name_or_path): from ludwig.utils.tokenizers import get_hf_tokenizer, HFTokenizer inputs = "Hello, ``I'm'' ónë of 1,205,000 sentences!" hf_tokenizer = HFTokenizer(pretrained_model_name_or_path) torchtext_tokenizer = get_hf_tokenizer(pretrained_model_name_or_path) # Ensure that the tokenizer is scriptable tokenizer_path = os.path.join(tmpdir, "tokenizer.pt") torch.jit.script(torchtext_tokenizer).save(tokenizer_path) torchtext_tokenizer = tor

[TorchScript] Add user-defined HF Bert tokenizers (#2733) * first working set * wip todo: add never_split kwarg * adds new never_split kwarg * clean up * get tests passing * updated py38 tests * pr revisions * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * logging > logger Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

test_bert_hf_tokenizer_parity

f3fbfbbe7e4c772d60dbc4374811d3a959699f2b

ludwig

test_tokenizers.py

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

Python

def test_bert_hf_tokenizer_parity(tmpdir, pretrained_model_name_or_path): from ludwig.utils.tokenizers import get_hf_tokenizer, HFTokenizer inputs = "Hello, ``I'm'' ónë of 1,205,000 sentences!" hf_tokenizer = HFTokenizer(pretrained_model_name_or_path) torchtext_tokenizer = get_hf_tokenizer(pretrained_model_name_or_path) # Ensure that the tokenizer is scriptable tokenizer_path = os.path.join(tmpdir, "tokenizer.pt") torch.jit.script(torchtext_tokenizer).save(tokenizer_path) torchtext_tokenizer = torch.jit.load(tokenizer_path) token_ids_expected = hf_tokenizer(inputs) token_ids = torchtext_tokenizer(inputs) assert token_ids_expected == token_ids

erpnext/accounts/doctype/bank_reconciliation_tool/bank_reconciliation_tool.py

def get_pe_matching_query(amount_condition, account_from_to, transaction): # get matching payment entries query if transaction.deposit > 0: currency_field = "paid_to_account_currency

style: format code with black

get_pe_matching_query

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

bank_reconciliation_tool.py

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

Python

def get_pe_matching_query(amount_condition, account_from_to, transaction): # get matching payment entries query if transaction.deposit > 0: currency_field = "paid_to_account_currency as currency" else: currency_field = "paid_from_account_currency as currency" return f

django/contrib/admin/checks.py

def _check_list_display_links(self, obj): from django.contrib.admin.options import ModelAdmin if obj.list_display_links is None: return [] elif not isinstance(obj.list_display_links, (list, tuple)): return must_be( "a list, a tuple, or None", option="list_display_links", obj=obj, id="admin.E110", ) # Check only if ModelAdmin.get_list_display() isn't overridden. elif obj.get_list_display.__func__ is ModelAdmin.get_list_display: return list( chain.from_iterable( self._check_list_display_links_item(

Refs #33476 -- Reformatted code with Black.

_check_list_display_links

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

checks.py

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

Python

def _check_list_display_links(self, obj): from django.contrib.admin.options import ModelAdmin if obj.list_display_links is None: return [] elif not isinstance(obj.list_display_links, (list, tuple)): return must_be( "a list, a tuple, or None", option="list_display_links", obj=obj, id="admin.E110", ) # Check only if ModelAdmin.get_list_display() isn't overridden. elif obj.get_list_display.__func__ is ModelAdmin.get_list_display: return list( chain.from_iterable( self._check_list_display_links_item( obj, field_name, "list_display_links[%d]" % index ) for index, field_name in enumerate(obj.list_display_links) ) ) return []

homeassistant/components/zha/core/channels/lighting.py

def min_mireds(self) -> int: min_mireds = self.cluster.get("color_temp_physical_min", self.MIN_MIREDS) if min_mireds == 0: self.warning( "

Fix invalid min and max color temp in bad ZHA light devices (#81604) * Fix ZHA default color temps * update test

min_mireds

83c6a7e18b1b0e4d5a302e304f117dee11d3aa51

core

lighting.py

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

Python

def min_mireds(self) -> int: min_mireds = self.cluster.get("color_temp_physical_min", self.MIN_MIREDS) if min_mireds == 0: self.warning( "[Min mireds is 0, setting to %s] Please open an issue on the quirks repo to have this device corrected", self.MIN_MIREDS, ) min_mireds = self.MIN_MIREDS return min_mireds

src/textual/app.py

def pop_screen(self) -> Screen: screen_stack = self._screen_stack if len(screen_stack) <= 1: raise ScreenStackError( "Can't pop screen; there must be at least one screen on the stack" ) screen = screen_stack.pop() screen.post_me

prototype screens api

pop_screen

ff55dafb8638f6674f3662aa526a5fc35a007b24

textual

app.py

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

Python

def pop_screen(self) -> Screen: screen_stack = self._screen_stack if len(screen_stack) <= 1: raise ScreenStackError( "Can't pop screen; there must be at least one screen on the stack" ) screen = screen_stack.pop() screen.post_message_no_wait(events.ScreenSuspend(self)) self.screen._screen_resized(self.size) self.screen.post_message_no_wait(events.ScreenResume(self)) return screen

tests/handlers/test_appservice.py

def test_notify_interested_services_ephemeral(self): interested_service = self._mkservice(is_interested=True) services = [interested_service] self.mock_store.get_app_services.return_value = services self.mock_store.get_type_stream_id_for_appservice.return_v

Send to-device messages to application services (#11215) Co-authored-by: Richard van der Hoff <[email protected]>

test_notify_interested_services_ephemeral

64ec45fc1b0856dc7daacca7d3ab75d50bd89f84

synapse

test_appservice.py

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

Python

def test_notify_interested_services_ephemeral(self): interested_service = self._mkservice(is_interested=True) services = [interested_service] self.mock_store.get_app_services.return_value = services self.mock_store.get_type_stream_id_for_appservice.return_value = make_awaitable( 579 ) event = Mock(event_id="event_1") self.event_source.sources.receipt.get_new_events_as.return_value = ( make_awaitable(([event], None)) ) self.handler.notify_interested_services_ephemeral( "receipt_key", 580, ["@fakerecipient:example.com"] ) self.mock_scheduler.enqueue_for_appservice.assert_called_once_with( interested_service, ephemeral=[event] ) self.mock_store.set_appservice_stream_type_pos.assert_called_once_with( interested_service, "read_receipt", 580, )

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

def convert(self, value): if not isinstance(value, ConvertingDict) and isinstance(value, dict): value = ConvertingDict(value) value.con

upd; format

convert

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

compat.py

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

Python

def convert(self, value): if not isinstance(value, ConvertingDict) and isinstance(value, dict): value = ConvertingDict(value) value.configurator = self elif not isinstance(value, ConvertingList) and isinstance(value, list): value = ConvertingList(value) value.configurator = self elif not isinstance(value, ConvertingTuple) and\ isinstance(value, tuple): value = ConvertingTuple(value) value.configurator = self elif isinstance(value, string_types): m = self.CONVERT_PATTERN.match(value) if m: d = m.groupdict() prefix = d['prefix'] converter = self.value_converters.get(prefix, None) if converter: suffix = d['suffix'] converter = getattr(self, converter) value = converter(suffix) return value

tests/test_css_parse.py

def test_parse_transition(duration, parsed_duration): css = f stylesheet = Stylesheet() stylesheet.parse(css) rule = stylesheet.rules[0].styles assert len(stylesheet.rules) == 1 assert len(stylesheet.rule

Stop parsing time as scalar

test_parse_transition

644fdc7ed181a22773556236e83fb5343efe8fd5

textual

test_css_parse.py

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

Python

def test_parse_transition(duration, parsed_duration): css = f stylesheet = Stylesheet() stylesheet.parse(css) rule = stylesheet.rules[0].styles assert len(stylesheet.rules) == 1 assert len(stylesheet.rules[0].errors) == 0 assert rule.transitions == { "offset": Transition(duration=parsed_duration, easing="in_out_cubic", delay=0.0) }

tests/rest/media/v1/test_html_preview.py

def test_meta_charset(self) -> None: encodings = _get_html_media_encodings( b, "text/html", ) self.assertEqual(list(encodings), ["ascii", "utf-8", "cp1252"]) # A less well-form

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

test_meta_charset

7e91107be1a4287873266e588a3c5b415279f4c8

synapse

test_html_preview.py

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

Python

def test_meta_charset(self) -> None: encodings = _get_html_media_encodings( b, "text/html", ) self.assertEqual(list(encodings), ["ascii", "utf-8", "cp1252"]) # A less well-formed version. encodings = _get_html_media_encodings( b, "text/html", ) self.assertEqual(list(encodings), ["ascii", "utf-8", "cp1252"])

glances/amps_list.py

def _build_amps_list(self, amp_value, processlist): ret = [] try: # Search in both cmdline and name (for kernel thread, see #1261) for p in processlist: if (re.search(amp_value.regex(), p['name']) is not None) or ( p['cmdline'] is not None and p['cmdline'] != [] and re.search(amp_value.regex(), ' '.join(p['cmdline'])) is not None ):

AMP: regex with special chars #2152

_build_amps_list

1aa5596cc25fbd74cac65c5e4d6b16bd90091138

glances

amps_list.py

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

Python

def _build_amps_list(self, amp_value, processlist): ret = [] try: # Search in both cmdline and name (for kernel thread, see #1261) for p in processlist: if (re.search(amp_value.regex(), p['name']) is not None) or ( p['cmdline'] is not None and p['cmdline'] != [] and re.search(amp_value.regex(), ' '.join(p['cmdline'])) is not None ): ret.append( {'pid': p['pid'], 'cpu_percent': p['cpu_percent'], 'memory_percent': p['memory_percent']} ) except (TypeError, KeyError) as e: logger.debug("Can not build AMPS list ({})".format(e)) return ret

keras/engine/base_layer.py

def call(self, inputs, *args, **kwargs): # pylint: disable=unused-argument return inputs

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

call

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

base_layer.py

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

Python

def call(self, inputs, *args, **kwargs): # pylint: disable=unused-argument return inputs

tests/unit/test_executor.py

def test_use_predictor_with_view(self, mock_handler): # set integration data df = pd.DataFrame([ {'a': 1, 'b': 'one'}, {'a': 2, 'b': 'two'}, {'a': 1, 'b': 'three'}, ]) self.set_handler(mock_handler, name='pg', tables={'tasks': df}) view_name = 'vtasks' # --- create view --- ret = self.command_executor.execute_command(parse_sql( f'create view {view_name} (select * from pg (select * from tasks))', dialect='mindsdb') ) assert ret.error_code is None # --- use predictor --- predicted_value = 3.14 predictor = { 'name': 'task_model', 'predict': 'p', 'dtypes': { 'p': dtype.float, 'a': dtype.integer, 'b': dtype.categorical }, 'predicted_value': predicted_value } self.set_predictor(predictor) ret = self.command_executor.execute_command(parse_sql(f, dialect='mindsdb')) assert ret.error_code is None # native query was called assert mock_handler().native_query.mock_calls[0].args[0] == 'select * from tasks' # check predictor call # model was called assert self.mock_model_interface.predict.mock_calls[0].args[0] == 'task_model' # input = one row whit a==2 when_data = self.mock_model_interface.predict.mock_calls[0].args[1] assert len(when_data) == 1 assert when_data[0]['a'] == 2 # check prediction assert ret.data[0][0] =

executor tests

test_use_predictor_with_view

02a831997cdffafca7cb160eb1938e72020ee049

mindsdb

test_executor.py

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

Python

def test_use_predictor_with_view(self, mock_handler): # set integration data df = pd.DataFrame([ {'a': 1, 'b': 'one'}, {'a': 2, 'b': 'two'}, {'a': 1, 'b': 'three'}, ]) self.set_handler(mock_handler, name='pg', tables={'tasks': df}) view_name = 'vtasks' # --- create view --- ret = self.command_executor.execute_command(parse_sql( f'create view {view_name} (select * from pg (select * from tasks))', dialect='mindsdb') ) assert ret.error_code is None # --- use predictor --- predicted_value = 3.14 predictor = { 'name': 'task_model', 'predict': 'p', 'dtypes': { 'p': dtype.float, 'a': dtype.integer, 'b': dtype.categorical }, 'predicted_value': predicted_value } self.set_predictor(predictor) ret = self.command_executor.execute_command(parse_sql(f, dialect='mindsdb')) assert ret.error_code is None # native query was called assert mock_handler().native_query.mock_calls[0].args[0] == 'select * from tasks' # check predictor call # model was called assert self.mock_model_interface.predict.mock_calls[0].args[0] == 'task_model' # input = one row whit a==2 when_data = self.mock_model_interface.predict.mock_calls[0].args[1] assert len(when_data) == 1 assert when_data[0]['a'] == 2 # check prediction assert ret.data[0][0] == predicted_value assert len(ret.data) == 1

rllib/connectors/tests/test_agent.py

def test_vr_connector_shift_by_one(self): view_rq_dict = { "state": ViewRequirement("obs"), "next_state": ViewRequirement( "obs", shift=1, used_for_compute_actions=False ), "prev_state": ViewRequirement("obs", shift=-1), } obs_arrs = np.arange(10)[:, None] + 1 config = PPOConfig().to_dict() ctx = ConnectorContext( view_requirements=view_rq_dict, config=config, is_policy_recurrent=True ) c = ViewRequirementAgentConnector(ctx) # keep a running list of observations obs_list = [] for t, obs in enumerate(obs_arrs): # t=0 is the next state of t=-1 data = AgentConnectorDataType( 0, 1, {SampleBatch.NEXT_OBS: obs, SampleBatch.T: t - 1} ) process

[RLlib] Implemented ViewRequirementConnector (#26998)

test_vr_connector_shift_by_one

8ddcf89096e5631c6b6e0d04dc094b458a15c9f9

ray

test_agent.py

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

Python

def test_vr_connector_shift_by_one(self): view_rq_dict = { "state": ViewRequirement("obs"), "next_state": ViewRequirement( "obs", shift=1, used_for_compute_actions=False ), "prev_state": ViewRequirement("obs", shift=-1), } obs_arrs = np.arange(10)[:, None] + 1 config = PPOConfig().to_dict() ctx = ConnectorContext( view_requirements=view_rq_dict, config=config, is_policy_recurrent=True ) c = ViewRequirementAgentConnector(ctx) # keep a running list of observations obs_list = [] for t, obs in enumerate(obs_arrs): # t=0 is the next state of t=-1 data = AgentConnectorDataType( 0, 1, {SampleBatch.NEXT_OBS: obs, SampleBatch.T: t - 1} ) processed = c([data]) # env.reset() for t == -1 else env.step() for_action = processed[0].data.for_action # add cur obs to the list obs_list.append(obs) if t == 0: check(for_action["prev_state"], for_action["state"]) else: # prev state should be equal to the prev time step obs check(for_action["prev_state"], obs_list[-2][None])

tools/flake8_plugin.py

def adapt_error(cls, e): return e._replace(message=e.message.format(*e.vars))[:4] error = namedtuple("error", "lineno col message type vars") Error = partial(partial, error, message="", type=SentryCheck, vars=()) S001 = Error( message="S001: Avoid us

Revert "ref: simplify and type flake8 plugin (#35645)" (#35651)

adapt_error

8b9bcdc92d8ff23ec9f44d90d14348d9464d476b

sentry

flake8_plugin.py

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

Python

def adapt_error(cls, e): return e._replace(message=e.message.format(*e.vars))[:4] error = namedtuple("error", "lineno col message type vars") Error = partial(partial, error, message="", type=SentryCheck, vars=()) S001 = Error( message="S001: Avoid using the {} mock call as it is " "confusing and prone to causing invalid test " "behavior." ) S001.methods = { "not_called", "called_once", "called_once_with", } S002 = Error(message="S002: print functions or statements are not allowed.") S003 = Error(message="S003: Use ``from sentry.utils import json`` instead.") S003.modules = {"json", "simplejson"} S003.names = { "load", "loads", "dump", "dumps", "JSONEncoder", "JSONDecodeError", "_default_encoder", }

keras/callbacks.py

def on_train_begin(self, logs=None): logs = self._process_logs(logs) for callback in self.callbacks: callback.on_train_begin(logs)

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

on_train_begin

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

callbacks.py

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

Python

def on_train_begin(self, logs=None): logs = self._process_logs(logs) for callback in self.callbacks: callback.on_train_begin(logs)

sklearn/utils/tests/test_param_validation.py

def test_decorate_validated_function(): decorated_function = deprecated()(_func) with pytest.warns(FutureWarning, match="Function _func is deprecated"): decorated_function(1, 2, c=3) # outer decorator does not inte

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

test_decorate_validated_function

122876e9ab1ab494b4bf0ca3360d5a1527caf2e7

scikit-learn

test_param_validation.py

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

Python

def test_decorate_validated_function(): decorated_function = deprecated()(_func) with pytest.warns(FutureWarning, match="Function _func is deprecated"): decorated_function(1, 2, c=3) # outer decorator does not interfer with validation with pytest.warns(FutureWarning, match="Function _func is deprecated"): with pytest.raises(ValueError, match=r"The 'c' parameter of _func must be"): decorated_function(1, 2, c="wrong")

d2l/jax.py

def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend): axes.set_xlabel(xlabel), axes.set_ylabel(ylabel) axes.set_xscale(xscale), axes.set_yscale(yscale) axes.set_xlim(xlim), axes.set_ylim(ylim) if legend: axes.legend(legend) axes.grid()

[Jax] Add calculus

set_axes

7487da3edb1a68af60104e0290216f0849a8765c

d2l-en

jax.py

https://github.com/d2l-ai/d2l-en.git

Python

def set_axes(axes, xlabel, ylabel, xlim, ylim, xscale, yscale, legend): axes.set_xlabel(xlabel), axes.set_ylabel(ylabel) axes.set_xscale(xscale), axes.set_yscale(yscale) axes.set_xlim(xlim), axes.set_ylim(ylim) if legend: axes.legend(legend) axes.grid()

mitmproxy/addonmanager.py

def register(self, addon): api_changes = { # mitmproxy 6 -> mitmproxy 7 "clientconnect": "client_connected", "clientdisconnect": "client_disconnected", "serverconnect": "server_connect and server_connected", "serverdisconnect": "server_disconnected", } for a in traverse([addon]): for old, new in api_changes.items(): if hasattr(a, old): ctx.log.warn(f"The {old} event has been removed, use {new} instead. " f"For more details, see https://docs.mitmproxy.or

Rename new async helper functions. async_trigger -> trigger_event invoke_addon -> invoke_addon_sync (API breakage) async_invoke_addon -> invoke_addon

register

ee4999e8e4380f7b67faef92f04c361deffba412

mitmproxy

addonmanager.py

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

Python

def register(self, addon): api_changes = { # mitmproxy 6 -> mitmproxy 7 "clientconnect": "client_connected", "clientdisconnect": "client_disconnected", "serverconnect": "server_connect and server_connected", "serverdisconnect": "server_disconnected", } for a in traverse([addon]): for old, new in api_changes.items(): if hasattr(a, old): ctx.log.warn(f"The {old} event has been removed, use {new} instead. " f"For more details, see https://docs.mitmproxy.org/stable/addons-events/.") name = _get_name(a) if name in self.lookup: raise exceptions.AddonManagerError( "An addon called '%s' already exists." % name ) l = Loader(self.master) self.invoke_addon_sync(addon, LoadHook(l)) for a in traverse([addon]): name = _get_name(a) self.lookup[name] = a for a in traverse([addon]): self.master.commands.collect_commands(a) self.master.options.process_deferred() return addon

@method_decorator(never_cache, name='dispatch')

apps/authentication/views/login.py

def get_context_data(self, **kwargs): from tickets.models import Ticket from tickets.const import TICKET_DETAIL_URL ticket_id = self.request.session.get("auth_ticket_id") if not ticket_id:

fix: login confirm bug (#7914) Co-authored-by: feng626 <[email protected]>

get_context_data

08ff8fa285575b8ca5ee187d297d807bf197a161

jumpserver

login.py

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

Python

def get_context_data(self, **kwargs): from tickets.models import Ticket from tickets.const import TICKET_DETAIL_URL ticket_id = self.request.session.get("auth_ticket_id") if not ticket_id: ticket = None else: ticket = Ticket.all().filter(pk=ticket_id).first() context = super().get_context_data(**kwargs) if ticket: timestamp_created = datetime.datetime.timestamp(ticket.date_created) ticket_detail_url = TICKET_DETAIL_URL.format(id=ticket_id, type=ticket.type) assignees = ticket.current_node.first().ticket_assignees.all() assignees_display = ', '.join([str(i.assignee) for i in assignees]) msg = _().format(assignees_display) else: timestamp_created = 0 ticket_detail_url = '' msg = _("No ticket found") context.update({ "msg": msg, "timestamp": timestamp_created, "ticket_detail_url": ticket_detail_url }) return context @method_decorator(never_cache, name='dispatch')

src/transformers/modeling_tf_utils.py

def tf_shard_checkpoint(weights, max_shard_size="10GB"): max_shard_size = convert_file_size_to_int(max_shard_size) sharded_state_dicts = [] current_block = [] current_block_size = 0 total_size = 0 for item in weights: weight_size = item.numpy().size * dtype_byte_size(item.dtype) # If this weight is going to tip up over the maximal size, we split. if current_block_size + weight_size > max_shard_size: sharded_state_dicts.append(current_block) current_block = [] current_block_size = 0 current_block.append(item) current_block_size += weight_size total_size += weight_size # Add the last block sharded_state_dicts.append(current_block) # If we only have one shard, we return it if len(sharded_state_dicts) == 1: return {TF2_WEIGHTS_NAME: sharded_state_dicts[0]}, None # Otherwise, let's build the index weight_map = {} shards = {} for idx, shard in enumerate(sharded_state_dicts): shard_file = TF2_WEIGHTS_NAME.

TF Sharded (#17713) * initial commit * update modeeling tf utils * quality * clean and update args * update * remove potential bug * code quality * update * update max shard * update tests for sharding from pretrained * fix remaining test * make style * h5py if tf available * update and fix test * fix test * style * modified push to hub to support shard for TF * quick fix * update code * merge branch main and style * Apply suggestions from code review Co-authored-by: Joao Gante <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> * update based on reviews * update doc * update and style * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> * Update based on reviews * fix typo * style Co-authored-by: Joao Gante <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>

tf_shard_checkpoint

7cced021fa8ddc59f0f77384300760d34545394e

transformers

modeling_tf_utils.py

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

Python

def tf_shard_checkpoint(weights, max_shard_size="10GB"): max_shard_size = convert_file_size_to_int(max_shard_size) sharded_state_dicts = [] current_block = [] current_block_size = 0 total_size = 0 for item in weights: weight_size = item.numpy().size * dtype_byte_size(item.dtype) # If this weight is going to tip up over the maximal size, we split. if current_block_size + weight_size > max_shard_size: sharded_state_dicts.append(current_block) current_block = [] current_block_size = 0 current_block.append(item) current_block_size += weight_size total_size += weight_size # Add the last block sharded_state_dicts.append(current_block) # If we only have one shard, we return it if len(sharded_state_dicts) == 1: return {TF2_WEIGHTS_NAME: sharded_state_dicts[0]}, None # Otherwise, let's build the index weight_map = {} shards = {} for idx, shard in enumerate(sharded_state_dicts): shard_file = TF2_WEIGHTS_NAME.replace(".h5", f"-{idx+1:05d}-of-{len(sharded_state_dicts):05d}.h5") shards[shard_file] = shard for weight in shard: weight_name = weight.name weight_map[weight_name] = shard_file # Add the metadata metadata = {"total_size": total_size} index = {"metadata": metadata, "weight_map": weight_map} return shards, index

sympy/geometry/curve.py

def scale(self, x=1, y=1, pt=None): if pt: pt = Point(pt, dim=2) return self.translate(*(-pt).args).scale(x, y).translate(*pt.args) fx,

Updated import locations

scale

498015021131af4dbb07eb110e5badaba8250c7b

sympy

curve.py

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

Python

def scale(self, x=1, y=1, pt=None): if pt: pt = Point(pt, dim=2) return self.translate(*(-pt).args).scale(x, y).translate(*pt.args) fx, fy = self.functions return self.func((fx*x, fy*y), self.limits)

sympy/physics/vector/frame.py

def orient_body_fixed(self, parent, angles, rotation_order): _check_frame(parent) amounts = list(angles) for i, v in enumerate(amounts): if not isinstance(v, Vector): amounts[i] = sympify(v) approved_orders = ('123', '231', '312', '132', '213', '321', '121', '131', '212', '232', '313', '323', '') # make sure XYZ => 123 rot_order = translate(str(rotation_order), 'XYZxyz', '123123') if rot_order not in approved_orders: raise TypeError('The rotation order is not a valid order.') parent_orient_body = [] if not (len(amounts) == 3 & len(rot_order) == 3): raise TypeError('Body orientation takes 3 values & 3 orders') a1 = int(rot_order[0]) a2 = int(rot_order[1]) a3 = int(rot_order[2]) parent_orient_body = (self._rot(a1, amounts[0]) * self._rot(a2, amounts[1]) * self._rot(a3, amounts[2])) self._dcm(parent, parent_orient_body) try: from sympy.polys.polyerrors import CoercionFailed from sympy.physics.vector.functions import kinematic_equations q1, q2, q3 = amounts u1, u2, u3 = symbols('u1, u2, u3', cls=Dummy) templist = kinematic_equations([u1, u2, u3], [q1, q2, q3], 'body', rot_order) templist = [expand(i) for i in templist] td = solve(templist, [u1, u2, u3]) u1 = expand(td[u1]) u2 = expand(td[u2]) u3 = expand(td[u3]) wvec = u1 * self.x + u2 * self.y + u3 * self.z # NOTE : SymPy 1.7 removed the call to simplify() that occured # inside the solve() function, so this restores the pre-1.7 # behavior. See: # https://github.com/sympy/sympy/issues/23140 # and # https://github.com/sympy/sympy/issues/23130 wvec = wvec.simplify() except (CoercionFailed, AssertionError): wvec = self._w_diff_dcm(parent) self._ang_vel_dict.update({parent: wvec}) parent._ang_vel_dict.update({self: -wvec}) self._var_dict = {}

Restores pre-1.7 simplify behavior for orient_body_fixed()

orient_body_fixed

5afe37b3dee65554d7e4592c20f922cb551fde31

sympy

frame.py

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

Python

def orient_body_fixed(self, parent, angles, rotation_order): _check_frame(parent) amounts = list(angles) for i, v in enumerate(amounts): if not isinstance(v, Vector): amounts[i] = sympify(v) approved_orders = ('123', '231', '312', '132', '213', '321', '121', '131', '212', '232', '313', '323', '') # make sure XYZ => 123 rot_order = translate(str(rotation_order), 'XYZxyz', '123123') if rot_order not in approved_orders: raise TypeError('The rotation order is not a valid order.') parent_orient_body = [] if not (len(amounts) == 3 & len(rot_order) == 3): raise TypeError('Body orientation takes 3 values & 3 orders') a1 = int(rot_order[0]) a2 = int(rot_order[1]) a3 = int(rot_order[2]) parent_orient_body = (self._rot(a1, amounts[0]) * self._rot(a2, amounts[1]) * self._rot(a3, amounts[2])) self._dcm(parent, parent_orient_body) try: from sympy.polys.polyerrors import CoercionFailed from sympy.physics.vector.functions import kinematic_equations q1, q2, q3 = amounts u1, u2, u3 = symbols('u1, u2, u3', cls=Dummy) templist = kinematic_equations([u1, u2, u3], [q1, q2, q3], 'body', rot_order) templist = [expand(i) for i in templist] td = solve(templist, [u1, u2, u3]) u1 = expand(td[u1]) u2 = expand(td[u2]) u3 = expand(td[u3]) wvec = u1 * self.x + u2 * self.y + u3 * self.z # NOTE : SymPy 1.7 removed the call to simplify() that occured # inside the solve() function, so this restores the pre-1.7 # behavior. See: # https://github.com/sympy/sympy/issues/23140 # and # https://github.com/sympy/sympy/issues/23130 wvec = wvec.simplify() except (CoercionFailed, AssertionError): wvec = self._w_diff_dcm(parent) self._ang_vel_dict.update({parent: wvec}) parent._ang_vel_dict.update({self: -wvec}) self._var_dict = {}

erpnext/hr/doctype/leave_block_list/leave_block_list.py

def get_applicable_block_lists(employee=None, company=None, all_lists=False): block_lists = [] if not employee: employee = frappe.db.get_value("Employee", {"user_id": frappe.session.user}) if not employee: return [] if not company: company = frappe.db.get_value("Employee", employee, "company") def add_block_list(block_list): if block_list: if all_lists or not is_user_in_allow_list(block_list): block_lists.append(block_list) # per department department = frappe.db.get_value("Employee", employee, "department") if department: block_list = frappe.db.get_value("Department", department, "leave_block_list") add_block_list(block_list) # global for block_list in frappe.db.sql_list(

style: format code with black

get_applicable_block_lists

494bd9ef78313436f0424b918f200dab8fc7c20b

erpnext

leave_block_list.py

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

Python

def get_applicable_block_lists(employee=None, company=None, all_lists=False): block_lists = [] if not employee: employee = frappe.db.get_value("Employee", {"user_id": frappe.session.user}) if not employee: return [] if not company: company = frappe.db.get_value("Employee", employee, "company") def add_block_list(block_list): if block_list: if all_lists or not is_user_in_allow_list(block_list): block_lists.append(block_list) # per department department = frappe.db.get_value("Employee", employee, "department") if department: block_list = frappe.db.get_value("Department", department, "leave_block_list") add_block_list(block_list) # global for block_list in frappe.db.sql_list( , company, ): add_block_list(block_list) return list(set(block_lists))

mindsdb/integrations/libs/storage_handler.py

def _setup_connection(self): # noqa cur = self.connection.cursor() if ('store',) not in lis

feat: add docs, improve base class signatures

_setup_connection

27a34a6a706a06e1241671d29c8cab93d77a19c1

mindsdb

storage_handler.py

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

Python

def _setup_connection(self): # noqa cur = self.connection.cursor() if ('store',) not in list(cur.execute("SELECT name FROM sqlite_master WHERE type='table';")): cur.execute( ) self.internal_registry.commit()

dask/optimization.py

def cull(dsk, keys): if not isinstance(keys, (lis

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

cull

cccb9d8d8e33a891396b1275c2448c352ef40c27

dask

optimization.py

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

Python

def cull(dsk, keys): if not isinstance(keys, (list, set)): keys = [keys] seen = set() dependencies = dict() out = {} work = list(set(flatten(keys))) while work: new_work = [] for k in work: dependencies_k = get_dependencies(dsk, k, as_list=True) # fuse needs lists out[k] = dsk[k] dependencies[k] = dependencies_k for d in dependencies_k: if d not in seen: seen.add(d) new_work.append(d) work = new_work return out, dependencies

freqtrade/exchange/exchange.py

def fill_leverage_tiers(self) -> None: leverage_tiers = self.load_leverage_tiers() for pair, tiers in leverage_tiers.items(): tiers = []

freqtrade.exchange edited load_leverage_tiers

fill_leverage_tiers

41d8330fbc95224020a046bd46eea6252374ee15

freqtrade

exchange.py

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

Python

def fill_leverage_tiers(self) -> None: leverage_tiers = self.load_leverage_tiers() for pair, tiers in leverage_tiers.items(): tiers = [] for tier in tiers: tiers.append(self.parse_leverage_tier(tier)) self._leverage_tiers[pair] = tiers

sympy/matrices/expressions/kronecker.py

def kronecker_product(*matrices): if not matrices:

Moved imports to higher level

kronecker_product

59d22b6bb7287613d598611027f640d068ca5748

sympy

kronecker.py

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

Python

def kronecker_product(*matrices): if not matrices: raise TypeError("Empty Kronecker product is undefined") validate(*matrices) if len(matrices) == 1: return matrices[0] else: return KroneckerProduct(*matrices).doit()

django/contrib/admin/options.py

def _get_obj_does_not_exist_redirect(self, request, opts, object_id): msg = _("%(name)s with ID “%(key)s” doesn’t exist. Perhaps it was deleted?") % { "name": opts.verbose_name, "key": unquote(object_id), } self.message_user(request,

Refs #33476 -- Reformatted code with Black.

_get_obj_does_not_exist_redirect

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

options.py

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

Python

def _get_obj_does_not_exist_redirect(self, request, opts, object_id): msg = _("%(name)s with ID “%(key)s” doesn’t exist. Perhaps it was deleted?") % { "name": opts.verbose_name, "key": unquote(object_id), } self.message_user(request, msg, messages.WARNING) url = reverse("admin:index", current_app=self.admin_site.name) return HttpResponseRedirect(url)

python3.10.4/Lib/_pydecimal.py

def compare_total(self, other, context=None): other = _convert_other(other, raiseit=True) # if one is negative and the other is positive, it's easy if self._sign and not other._sign: return _NegativeOne if not self._sign and other._sign: return _One sign = self._sign # let's handle both NaN types self_nan = self._isnan() other_nan = other._isnan() if self_nan or other_nan: if self_nan == other_nan: # compare payloads as though they're integers self_key = len(self._int), self._int other_key = len(other._int), other._int if self_key < other_key: if sign: return _One else: return _NegativeOne if self_key > other_key: if sign: return _NegativeOne else: return _One return _Zero if sign: if self_nan == 1: return _NegativeOne if other_nan == 1: return _One if self_nan == 2: return _NegativeOne if other_nan == 2: return _One else: if self_nan == 1: return _One if other_nan == 1: return _NegativeOne if self_nan == 2: return _One if other_nan == 2: return _NegativeOne if self < other: retu

add python 3.10.4 for windows

compare_total

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

_pydecimal.py

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

Python

def compare_total(self, other, context=None): other = _convert_other(other, raiseit=True) # if one is negative and the other is positive, it's easy if self._sign and not other._sign: return _NegativeOne if not self._sign and other._sign: return _One sign = self._sign # let's handle both NaN types self_nan = self._isnan() other_nan = other._isnan() if self_nan or other_nan: if self_nan == other_nan: # compare payloads as though they're integers self_key = len(self._int), self._int other_key = len(other._int), other._int if self_key < other_key: if sign: return _One else: return _NegativeOne if self_key > other_key: if sign: return _NegativeOne else: return _One return _Zero if sign: if self_nan == 1: return _NegativeOne if other_nan == 1: return _One if self_nan == 2: return _NegativeOne if other_nan == 2: return _One else: if self_nan == 1: return _One if other_nan == 1: return _NegativeOne if self_nan == 2: return _One if other_nan == 2: return _NegativeOne if self < other: return _NegativeOne if self > other: return _One if self._exp < other._exp: if sign: return _One else: return _NegativeOne if self._exp > other._exp: if sign: return _NegativeOne else: return _One return _Zero

pytorch_lightning/utilities/enums.py

def detect_current_mode(cls) -> _FaultTolerantMode: env_value = os.getenv("PL_FAULT_TOLERANT_TRAINING", "0").lower() # the int values are kept for backwards compatibility, but long-term we want to keep only the strings if env_value in ("0", "disabled"): return _FaultT

Add typing for utilities/enums.py (#11298)

detect_current_mode

a610e043d797ca0bae1ce186829fece79077407a

lightning

enums.py

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

Python

def detect_current_mode(cls) -> _FaultTolerantMode: env_value = os.getenv("PL_FAULT_TOLERANT_TRAINING", "0").lower() # the int values are kept for backwards compatibility, but long-term we want to keep only the strings if env_value in ("0", "disabled"): return _FaultTolerantMode.DISABLED elif env_value in ("1", "automatic"): return _FaultTolerantMode.AUTOMATIC elif env_value in ("2", "manual"): return _FaultTolerantMode.MANUAL raise MisconfigurationException( "The environment flag `PL_FAULT_TOLERANT_TRAINING` should be either 'disabled', 'automatic', or 'manual'." )

@keras_export("keras.preprocessing.image.random_channel_shift")

keras/preprocessing/image.py

def apply_channel_shift(x, intensity, channel_axis=0): x = np.rollaxis(x, channel_axis, 0) min_x, max_x = np.min(x), np.max(x) channel_images = [ np.clip(x_channel + intensity, min_x, max_x) for x_channel in x ] x = np.stack(channel_imag

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

apply_channel_shift

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras

image.py

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

Python

def apply_channel_shift(x, intensity, channel_axis=0): x = np.rollaxis(x, channel_axis, 0) min_x, max_x = np.min(x), np.max(x) channel_images = [ np.clip(x_channel + intensity, min_x, max_x) for x_channel in x ] x = np.stack(channel_images, axis=0) x = np.rollaxis(x, 0, channel_axis + 1) return x @keras_export("keras.preprocessing.image.random_channel_shift")

paddlenlp/trainer/trainer_base.py

def _nested_gather(self, tensors, name=None): if tensors is None: return if self.ar

[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 <[email protected]>

_nested_gather

44a290e94d1becd1f09fddc3d873f9e19c9d6919

PaddleNLP

trainer_base.py

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

Python

def _nested_gather(self, tensors, name=None): if tensors is None: return if self.args.local_rank != -1: tensors = distributed_concat(tensors) return tensors # Copied from Accelerate.

@pytest.mark.parametrize("solver", SOLVERS) @pytest.mark.parametrize("fit_intercept", [True, False])

sklearn/linear_model/_glm/tests/test_glm.py

def test_glm_regression_unpenalized(solver, fit_intercept, glm_dataset): model, X, y, coef, _, _, _ = glm_dataset n_samples, n_features = X.shape alpha = 0 # unpenalized params = dict( alpha=alpha, fit_intercept=fit_intercept, # solver=solver, # only lbfgs available tol=1e-12, max_iter=1000, ) model = clone(model).set_params(**params) if fit_intercept: X = X[:, :-1] # remove intercept intercept = coef[-1] coef = coef[:-1] else: intercept = 0 model.fit(X, y) # FIXME: `assert_allclose(model.coef_, coef)` should work for all cases but fails # for the wide/fat case with n_features > n_samples. Most current GLM solvers do # NOT return the minimum norm solution with fit_intercept=True. rtol = 5e-5 if n_samples > n_features: assert model.intercept_ == pytest.approx(intercept) assert_allclose(model.coef_, coef, rtol=rtol) else: # As it is an underdetermined problem, prediction = y. The following shows that # we get a solution, i.e. a (non-unique) minimum of the objective function ... assert_allclose(model.predict(X), y, rtol=1e-6) if fit_intercept: # But it is not the mi

TST tight tests for GLMs (#23619) Co-authored-by: Olivier Grisel <[email protected]>

test_glm_regression_unpenalized

9d863aba2b6dab9c9cbbcf2f7c3b7a99b6ad168f

scikit-learn

test_glm.py

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

Python

def test_glm_regression_unpenalized(solver, fit_intercept, glm_dataset): model, X, y, coef, _, _, _ = glm_dataset n_samples, n_features = X.shape alpha = 0 # unpenalized params = dict( alpha=alpha, fit_intercept=fit_intercept, # solver=solver, # only lbfgs available tol=1e-12, max_iter=1000, ) model = clone(model).set_params(**params) if fit_intercept: X = X[:, :-1] # remove intercept intercept = coef[-1] coef = coef[:-1] else: intercept = 0 model.fit(X, y) # FIXME: `assert_allclose(model.coef_, coef)` should work for all cases but fails # for the wide/fat case with n_features > n_samples. Most current GLM solvers do # NOT return the minimum norm solution with fit_intercept=True. rtol = 5e-5 if n_samples > n_features: assert model.intercept_ == pytest.approx(intercept) assert_allclose(model.coef_, coef, rtol=rtol) else: # As it is an underdetermined problem, prediction = y. The following shows that # we get a solution, i.e. a (non-unique) minimum of the objective function ... assert_allclose(model.predict(X), y, rtol=1e-6) if fit_intercept: # But it is not the minimum norm solution. Otherwise the norms would be # equal. norm_solution = np.linalg.norm(np.r_[intercept, coef]) norm_model = np.linalg.norm(np.r_[model.intercept_, model.coef_]) assert norm_model > (1 + 1e-12) * norm_solution # See https://github.com/scikit-learn/scikit-learn/issues/23670. # Note: Even adding a tiny penalty does not give the minimal norm solution. # XXX: We could have naively expected LBFGS to find the minimal norm # solution by adding a very small penalty. Even that fails for a reason we # do not properly understand at this point. else: # When `fit_intercept=False`, LBFGS naturally converges to the minimum norm # solution on this problem. # XXX: Do we have any theoretical guarantees why this should be the case? assert model.intercept_ == pytest.approx(intercept) assert_allclose(model.coef_, coef, rtol=rtol) @pytest.mark.parametrize("solver", SOLVERS) @pytest.mark.parametrize("fit_intercept", [True, False])

networkx/algorithms/bipartite/redundancy.py

def _node_redundancy(G, v): n = len(G[v]) overlap = sum( 1 for (u, w) in combinations(G[v], 2) if (G[u].keys() & G[w].keys()) - {v}

Minor Python 2 cleanup (#6219) Python3 cleanup Use dict.keys() for set operations rather than explicitly creating sets.

_node_redundancy

1f033118f2e0cca12c6e2375708dc92197b62da6

networkx

redundancy.py

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

Python

def _node_redundancy(G, v): n = len(G[v]) overlap = sum( 1 for (u, w) in combinations(G[v], 2) if (G[u].keys() & G[w].keys()) - {v} ) return (2 * overlap) / (n * (n - 1))

sympy/physics/continuum_mechanics/truss.py

def solve(self): count_reaction_loads = 0 for node in self._nodes: if node in list(self._supports): if self._supports[node[0]]=='pinned': count_reaction_loads += 2 elif self._supports[node[0]]=='roller': count_reaction_loads += 1 coefficients_matrix = [[0 for i in range(2*len(self._nodes))] for j in range(2*len(self._nodes))] load_matrix = zeros(2*len(self.nodes), 1) load_matrix_row = 0 for node in self._nodes: if node[0] in list(self._loads): for load in self._loads[node[0]]: if load[0]!=Symbol('R_'+str(node[0])+'_x') and load[0]!=Symbol('R_'+str(node[0])+'_y'): load_matrix[load_matrix_row] -= load[0]*math.cos(pi*load[1]/180) load_matrix[load_matrix_row + 1] -= load[0]*math.sin(pi*load[1]/180) load_matrix_row += 2 cols = 0 row = 0 for node in self._nodes: if node[0] in list(self._supports): if self._supports[node[0]]=='pinned': coefficients_matrix[row][cols] += 1 coefficients_matrix[row+1][cols+1] += 1 cols += 2 elif self._supports[node[0]]=='roller': coefficients_matrix[row+1][cols] += 1 cols += 1 row += 2 for member in list(self._members): start = self._members[member][0] end = self._members[member][1] length = sqrt((self._node_coordinates[start][0]-self._node_coordinates[end][0])**2 + (self._node_coordinates[start][1]-self._node_coordinates[end][1])**2) start_index = self._node_labels.index(start) end_index = self._node_labels.index(end) horizontal_component_start = (self._node_coordinates[end][0]-self._node_coordinates[start][0])/length vertical_component_start = (self._node_coordinates[end][1]-self._node_coordinates[start][1])/length horizontal_component_end = (self._node_coordinates[start][0]-self._node_coordinates[end][0])/length

solve method added for the truss class

solve

af847114b9138a321933574fc3c3ec73af8b3459

sympy

truss.py

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

Python

def solve(self): count_reaction_loads = 0 for node in self._nodes: if node in list(self._supports): if self._supports[node[0]]=='pinned': count_reaction_loads += 2 elif self._supports[node[0]]=='roller': count_reaction_loads += 1 coefficients_matrix = [[0 for i in range(2*len(self._nodes))] for j in range(2*len(self._nodes))] load_matrix = zeros(2*len(self.nodes), 1) load_matrix_row = 0 for node in self._nodes: if node[0] in list(self._loads): for load in self._loads[node[0]]: if load[0]!=Symbol('R_'+str(node[0])+'_x') and load[0]!=Symbol('R_'+str(node[0])+'_y'): load_matrix[load_matrix_row] -= load[0]*math.cos(pi*load[1]/180) load_matrix[load_matrix_row + 1] -= load[0]*math.sin(pi*load[1]/180) load_matrix_row += 2 cols = 0 row = 0 for node in self._nodes: if node[0] in list(self._supports): if self._supports[node[0]]=='pinned': coefficients_matrix[row][cols] += 1 coefficients_matrix[row+1][cols+1] += 1 cols += 2 elif self._supports[node[0]]=='roller': coefficients_matrix[row+1][cols] += 1 cols += 1 row += 2 for member in list(self._members): start = self._members[member][0] end = self._members[member][1] length = sqrt((self._node_coordinates[start][0]-self._node_coordinates[end][0])**2 + (self._node_coordinates[start][1]-self._node_coordinates[end][1])**2) start_index = self._node_labels.index(start) end_index = self._node_labels.index(end) horizontal_component_start = (self._node_coordinates[end][0]-self._node_coordinates[start][0])/length vertical_component_start = (self._node_coordinates[end][1]-self._node_coordinates[start][1])/length horizontal_component_end = (self._node_coordinates[start][0]-self._node_coordinates[end][0])/length vertical_component_end = (self._node_coordinates[start][1]-self._node_coordinates[end][1])/length coefficients_matrix[start_index*2][cols] += horizontal_component_start coefficients_matrix[start_index*2+1][cols] += vertical_component_start coefficients_matrix[end_index*2][cols] += horizontal_component_end coefficients_matrix[end_index*2+1][cols] += vertical_component_end cols += 1 forces_matrix = (Matrix(coefficients_matrix)**-1)*load_matrix self._reaction_loads = {} i = 0 for node in self._nodes: if node[0] in list(self._supports): if self._supports[node[0]]=='pinned': self._reaction_loads['R_'+str(node[0])+'_x'] = forces_matrix[i] self._reaction_loads['R_'+str(node[0])+'_y'] = forces_matrix[i+1] i += 2 elif self._supports[node[0]]=='roller': self._reaction_loads['R_'+str(node[0])+'_y'] = forces_matrix[i] i += 1 for member in list(self._members): self._internal_forces[member] = forces_matrix[i] i += 1 return

sympy/polys/galoistools.py

def gf_edf_zassenhaus(f, n, p, K): factors = [f] if gf_degree(f) <= n: return factors N = gf_degree(f) // n if p != 2: b = gf_frobenius_monomial_base(f, p, K) t = [K.one, K.zero] while len(factors) < N: if p == 2: h = r = t for i in range(n - 1): r = gf_pow_mod(r, 2, f, p, K) h = gf_add(h, r, p, K) g = gf_gcd(f, h, p, K) t += [K.zero, K.zero] else: r = gf_random(2 * n - 1, p, K) h = _gf_pow_pnm1d2(r, n, f, b, p, K) g = gf_gcd(f, gf_sub_ground(h, K.one, p, K), p, K) if g != [K.one] and g != f: factors = gf_edf_zassenhaus(g, n, p, K) \ + gf_edf_zassenhaus(gf_quo(f, g, p, K), n, p, K) return _sort_factors(factors, multiple=False)

Improve `gf_edf_zassenhaus()`. For the case p == 2, we use Algorithm 3.4.8 of [Cohen93], instead of the current procedure. The current algorithm was failing to terminate on at least one known case (factoring cyclotomic_poly(17) mod 2). A simple bugfix would have been to change the iteration to `for i in range(n - 1):` when computing the polynomial `h` (`Tr` in Geddes), but Alg 3.4.8 is thought to be better in practice.

gf_edf_zassenhaus

d8bc197a19c0f4ea76c088da6f1655f1586cd700

sympy

galoistools.py

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

Python

def gf_edf_zassenhaus(f, n, p, K): factors = [f] if gf_degree(f) <= n: return factors N = gf_degree(f) // n if p != 2: b = gf_frobenius_monomial_base(f, p, K) t = [K.one, K.zero] while len(factors) < N: if p == 2: h = r = t for i in range(n - 1): r = gf_pow_mod(r, 2, f, p, K) h = gf_add(h, r, p, K) g = gf_gcd(f, h, p, K) t += [K.zero, K.zero] else: r = gf_random(2 * n - 1, p, K) h = _gf_pow_pnm1d2(r, n, f, b, p, K) g = gf_gcd(f, gf_sub_ground(h, K.one, p, K), p, K) if g != [K.one] and g != f: factors = gf_edf_zassenhaus(g, n, p, K) \ + gf_edf_zassenhaus(gf_quo(f, g, p, K), n, p, K) return _sort_factors(factors, multiple=False)

networkx/linalg/algebraicconnectivity.py

def _tracemin_fiedler(L, X, normalized, tol, method): import n

Use scipy.sparse array datastructure (#5139) * Step 1: use sparse arrays in nx.to_scipy_sparse_matrix. Seems like a reasonable place to start. nx.to_scipy_sparse_matrix is one of the primary interfaces to scipy.sparse from within NetworkX. * 1: Use np.outer instead of mult col/row vectors Fix two instances in modularitymatrix where a new 2D array was being created via an outer product of two \"vectors\". In the matrix case, this was a row vector \* a column vector. In the array case this can be disambiguated by being explicit with np.outer. * Update _transition_matrix in laplacianmatrix module - A few instances of matrix multiplication operator - Add np.newaxis + transpose to get shape right for broadcasting - Explicitly convert e.g. sp.sparse.spdiags to a csr_array. * Update directed_combinitorial_laplacian w/ sparse array. - Wrap spdiags in csr_array and update matmul operators. * Rm matrix-specific code from lgc and hmn modules - Replace .A call with appropriate array semantics - wrap sparse.diags in csr_array. * Change hits to use sparse array semantics. - Replace * with @ - Remove superfluous calls to flatten. * Update sparse matrix usage in layout module. - Simplify lil.getrowview call - Wrap spdiags in csr_array. * lil_matrix -> lil_array in graphmatrix.py. * WIP: Start working on algebraic connectivity module. * Incorporate auth mat varname feedback. * Revert 1D slice and comment for 1D sparse future. * Add TODOs: rm csr_array wrapper around spdiags etc. * WIP: cleanup algebraicconn: tracemin_fiedler. * Typo. * Finish reviewing algebraicconnectivity. * Convert bethe_hessian matrix to use sparse arrays. * WIP: update laplacian. Update undirected laplacian functions. * WIP: laplacian - add comment about _transition_matrix return types. * Finish laplacianmatrix review. * Update attrmatrix. * Switch to official laplacian function. * Update pagerank to use sparse array. * Switch bipartite matrix to sparse arrays. * Check from_scipy_sparse_matrix works with arrays. Modifies test suite. * Apply changes from review. * Fix failing docstring tests. * Fix missing axis for in-place multiplication. * Use scipy==1.8rc2 * Use matrix multiplication * Fix PyPy CI * [MRG] Create plot_subgraphs.py example (#5165) * Create plot_subgraphs.py https://github.com/networkx/networkx/issues/4220 * Update plot_subgraphs.py black * Update plot_subgraphs.py lint plus font_size * Update plot_subgraphs.py added more plots * Update plot_subgraphs.py removed plots from the unit test and added comments * Update plot_subgraphs.py lint * Update plot_subgraphs.py typos fixed * Update plot_subgraphs.py added nodes to the plot of the edges removed that was commented out for whatever reason * Update plot_subgraphs.py revert the latest commit - the line was commented out for a reason - it's broken * Update plot_subgraphs.py fixed node color issue * Update plot_subgraphs.py format fix * Update plot_subgraphs.py forgot to draw the nodes... now fixed * Fix sphinx warnings about heading length. * Update examples/algorithms/plot_subgraphs.py * Update examples/algorithms/plot_subgraphs.py Co-authored-by: Ross Barnowski <[email protected]> Co-authored-by: Dan Schult <[email protected]> * Add traveling salesman problem to example gallery (#4874) Adds an example of the using Christofides to solve the TSP problem to the example galery. Co-authored-by: Ross Barnowski <[email protected]> * Fixed inconsistent documentation for nbunch parameter in DiGraph.edges() (#5037) * Fixed inconsistent documentation for nbunch parameter in DiGraph.edges() * Resolved Requested Changes * Revert changes to degree docstrings. * Update comments in example. * Apply wording to edges method in all graph classes. Co-authored-by: Ross Barnowski <[email protected]> * Compatibility updates from testing with numpy/scipy/pytest rc's (#5226) * Rm deprecated scipy subpkg access. * Use recwarn fixture in place of deprecated pytest pattern. * Rm unnecessary try/except from tests. * Replace internal `close` fn with `math.isclose`. (#5224) * Replace internal close fn with math.isclose. * Fix lines in docstring examples. * Fix Python 3.10 deprecation warning w/ int div. (#5231) * Touchups and suggestions for subgraph gallery example (#5225) * Simplify construction of G with edges rm'd * Rm unused graph attribute. * Shorten categorization by node type. * Simplify node coloring. * Simplify isomorphism check. * Rm unit test. * Rm redundant plotting of each subgraph. * Use new package name (#5234) * Allowing None edges in weight function of bidirectional Dijkstra (#5232) * added following feature also to bidirectional dijkstra: The weight function can be used to hide edges by returning None. * changed syntax for better readability and code duplicate avoidance Co-authored-by: Hohmann, Nikolas <[email protected]> * Add an FAQ about assigning issues. (#5182) * Add FAQ about assigning issues. * Add note about linking issues from new PRs. * Update dev deps (#5243) * Update minor doc issues with tex notation (#5244) * Add FutureWarnings to fns that return sparse matrices - biadjacency_matrix. - bethe_hessian_matrix. - incidence_matrix. - laplacian functions. - modularity_matrix functions. - adjacency_matrix. * Add to_scipy_sparse_array and use it everywhere. Add a new conversion function to preserve array semantics internally while not altering behavior for users. Also adds FutureWarning to to_scipy_sparse_matrix. * Add from_scipy_sparse_array. Supercedes from_scipy_sparse_matrix. * Handle deprecations in separate PR. * Fix docstring examples. Co-authored-by: Mridul Seth <[email protected]> Co-authored-by: Jarrod Millman <[email protected]> Co-authored-by: Andrew Knyazev <[email protected]> Co-authored-by: Dan Schult <[email protected]> Co-authored-by: eskountis <[email protected]> Co-authored-by: Anutosh Bhat <[email protected]> Co-authored-by: NikHoh <[email protected]> Co-authored-by: Hohmann, Nikolas <[email protected]> Co-authored-by: Sultan Orazbayev <[email protected]> Co-authored-by: Mridul Seth <[email protected]>

_tracemin_fiedler

5dfd57af2a141a013ae3753e160180b82bec9469

networkx

algebraicconnectivity.py

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

Python

def _tracemin_fiedler(L, X, normalized, tol, method): import numpy as np import scipy as sp import scipy.linalg # call as sp.linalg import scipy.linalg.blas # call as sp.linalg.blas import scipy.sparse # call as sp.sparse n = X.shape[0] if normalized: # Form the normalized Laplacian matrix and determine the eigenvector of # its nullspace. e = np.sqrt(L.diagonal()) # TODO: rm csr_array wrapper when spdiags array creation becomes available D = sp.sparse.csr_array(sp.sparse.spdiags(1 / e, 0, n, n, format="csr")) L = D @ L @ D e *= 1.0 / np.linalg.norm(e, 2) if normalized:

@pytest.mark.skipif( not os.environ.get("OPENAI_API_KEY", None), reason="Please export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.", )

test/nodes/test_prompt_node.py

def test_complex_pipeline_with_shared_prompt_model_and_prompt_template_yaml(tmp_path): with open(tmp_path / "tmp_config_with_prompt_template.yml", "w") as tmp_file: tmp_file.write( f ) pipeline = Pipeline.load_from_yam

feat: Expand LLM support with PromptModel, PromptNode, and PromptTemplate (#3667) Co-authored-by: ZanSara <[email protected]>

test_complex_pipeline_with_shared_prompt_model_and_prompt_template_yaml

9ebf164cfdfb320503b7161493420c1b0ec577a3

haystack

test_prompt_node.py

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

Python

def test_complex_pipeline_with_shared_prompt_model_and_prompt_template_yaml(tmp_path): with open(tmp_path / "tmp_config_with_prompt_template.yml", "w") as tmp_file: tmp_file.write( f ) pipeline = Pipeline.load_from_yaml(path=tmp_path / "tmp_config_with_prompt_template.yml") result = pipeline.run(query="not relevant", documents=[Document("Berlin is an amazing city.")]) assert "Berlin" in result["results"][0] assert len(result["meta"]["invocation_context"]) > 0 @pytest.mark.skipif( not os.environ.get("OPENAI_API_KEY", None), reason="Please export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.", )

lib/utils.py

def _download_model(self): self.logger.info("Downloading model: '%s' from: %s", self._model_name, self._url_download) for attempt in range(self._retries): try: downloaded_size =

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

_download_model

c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf

faceswap

utils.py

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

Python

def _download_model(self): self.logger.info("Downloading model: '%s' from: %s", self._model_name, self._url_download) for attempt in range(self._retries): try: downloaded_size = self._url_partial_size req = urllib.request.Request(self._url_download) if downloaded_size != 0: req.add_header("Range", f"bytes={downloaded_size}-") with urllib.request.urlopen(req, timeout=10) as response: self.logger.debug("header info: {%s}", response.info()) self.logger.debug("Return Code: %s", response.getcode()) self._write_zipfile(response, downloaded_size) break except (socket_error, socket_timeout, urllib.error.HTTPError, urllib.error.URLError) as err: if attempt + 1 < self._retries: self.logger.warning("Error downloading model (%s). Retrying %s of %s...", str(err), attempt + 2, self._retries) else: self.logger.error("Failed to download model. Exiting. (Error: '%s', URL: " "'%s')", str(err), self._url_download) self.logger.info("You can try running again to resume the download.") self.logger.info("Alternatively, you can manually download the model from: %s " "and unzip the contents to: %s", self._url_download, self._cache_dir) sys.exit(1)

sklearn/manifold/_locally_linear.py

def fit_transform(self, X, y=None): self._validate_params() self._fit_transform(X)

MAINT Use _validate_params in LocallyLinearEmbedding (#23938) Co-authored-by: jeremiedbb <[email protected]>

fit_transform

ceeda362402bfc978bcc93d02481fe28e21a07ad

scikit-learn

_locally_linear.py

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

Python

def fit_transform(self, X, y=None): self._validate_params() self._fit_transform(X) return self.embedding_

tests/types/test_song.py

def test_song_from_data_dump(): # Loads from str song = Song.from_data_dump( ) assert song.name == "Ropes" assert song.artists == ["Dirty Palm", "Chandler Jewels"] assert song.album_name == "Ropes" assert song.album_artist == "Dirty Palm" assert song.genres == ["gaming edm", "melbourne bounce international"] assert song.disc_number == 1 assert song.duration == 188 assert song.year == 2021 assert song.date == "2021-10-28" assert song.track_n

v4 init

test_song_from_data_dump

fa2ad657482aca9dc628e6d7062b8badf2706bb6

spotify-downloader

test_song.py

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

Python

def test_song_from_data_dump(): # Loads from str song = Song.from_data_dump( ) assert song.name == "Ropes" assert song.artists == ["Dirty Palm", "Chandler Jewels"] assert song.album_name == "Ropes" assert song.album_artist == "Dirty Palm" assert song.genres == ["gaming edm", "melbourne bounce international"] assert song.disc_number == 1 assert song.duration == 188 assert song.year == 2021 assert song.date == "2021-10-28" assert song.track_number == 1 assert song.tracks_count == 1 assert song.isrc == "GB2LD2110301" assert song.song_id == "1t2qKa8K72IBC8yQlhD9bU" assert ( song.cover_url == "https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332" ) assert song.explicit == False assert song.download_url == None

TTS/tts/models/vits.py

def test_run(self) -> Tuple[Dict, Dict]: print(" | > Synthesizing test sentences.") test_audios = {} test_figures = {} test_sentences = self.config.test_sentences for idx, s_info in enumerate(test_sentences): try: aux_inputs = self.get_aux_input_from_test_sentences(s_info) wav, alignment, _, _ = synthesis( self, aux_inputs["text"], self.config, "cuda" in str(next(self.parameters()).device), ap, speaker_id=aux_inputs["speaker_id"], d_vector=aux_inputs["d_vector"], style_wav=aux_inputs["style_wav"], language_id=aux_inputs["language_id"], language_name=aux_inputs["language_name"], enable_eos_bos_chars=self.config.enable_eos_bos_chars, use_griffin_lim=True, do_trim_silence=False, ).values() test_audios["{}-audio".format(idx)] = wav test_figures["{}-alignment".format(idx)] = plot_alignment(alignment.T, output_fig=False) except: # pylint: disable=bare-except print(" !! Error creating Test Sentence -", idx) return test_figures, test_audios

Update VITS for the new API

test_run

ea965a5683c56a39570b4cc91e86cd2bb9799308

TTS

vits.py

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

Python

def test_run(self) -> Tuple[Dict, Dict]: print(" | > Synthesizing test sentences.") test_audios = {} test_figures = {} test_sentences = self.config.test_sentences for idx, s_info in enumerate(test_sentences): try: aux_inputs = self.get_aux_input_from_test_sentences(s_info) wav, alignment, _, _ = synthesis( self, aux_inputs["text"], self.config, "cuda" in str(next(self.parameters()).device), ap, speaker_id=aux_inputs["speaker_id"], d_vector=aux_inputs["d_vector"], style_wav=aux_inputs["style_wav"], language_id=aux_inputs["language_id"], language_name=aux_inputs["language_name"], enable_eos_bos_chars=self.config.enable_eos_bos_chars, use_griffin_lim=True, do_trim_silence=False, ).values() test_audios["{}-audio".format(idx)] = wav test_figures["{}-alignment".format(idx)] = plot_alignment(alignment.T, output_fig=False) except: # pylint: disable=bare-except print(" !! Error creating Test Sentence -", idx) return test_figures, test_audios

python3.10.4/Lib/configparser.py

def read_dict(self, dictionary, source='<dict>'): elements_added = set() for section, keys in dictionary.items(): section = str(section) try: self.add_section(section) except (DuplicateSectionError, ValueError):

add python 3.10.4 for windows

read_dict

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

configparser.py

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

Python

def read_dict(self, dictionary, source='<dict>'): elements_added = set() for section, keys in dictionary.items(): section = str(section) try: self.add_section(section) except (DuplicateSectionError, ValueError): if self._strict and section in elements_added: raise elements_added.add(section) for key, value in keys.items(): key = self.optionxform(str(key)) if value is not None: value = str(value) if self._strict and (section, key) in elements_added: raise DuplicateOptionError(section, key, source) elements_added.add((section, key)) self.set(section, key, value)

salt/channel/client.py

def send(self, load, tries=3, timeout=60, raw=False): _try = 1 while True: try: if self.crypt == "clear": log.trace("ReqChannel send clear load=%r", load) ret = yield self._uncrypted_transfer(load, timeout=timeout) else: log.trace("ReqChannel send crypt load=%r", load) ret = yield self._crypted_transfer( load, timeout=timeout, raw=raw ) break except Exception as exc: log.error("Failed to send msg %r", dir(exc)) if _try == tries: raise #salt.exceptions.SaltClientError("Connection to master lost") else: _try += 1 continue raise salt.ext.tornado.gen.Return(ret)

Move retries to channel

send

25e7a51c729cca539778c53f0858d6070e7d76cb

salt

client.py

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

Python

def send(self, load, tries=3, timeout=60, raw=False): _try = 1 while True: try: if self.crypt == "clear": log.trace("ReqChannel send clear load=%r", load) ret = yield self._uncrypted_transfer(load, timeout=timeout) else: log.trace("ReqChannel send crypt load=%r", load) ret = yield self._crypted_transfer( load, timeout=timeout, raw=raw ) break except Exception as exc: log.error("Failed to send msg %r", dir(exc)) if _try == tries: raise #salt.exceptions.SaltClientError("Connection to master lost") else: _try += 1 continue raise salt.ext.tornado.gen.Return(ret)

django/contrib/admin/utils.py

def get_fields_from_path(model, path): pieces = path.split(LOOKUP_SEP) fields = [] for piece in pieces: if fields: parent = get_model_from_relation(fields[-1]) else: parent = model fields.app

Refs #33476 -- Reformatted code with Black.

get_fields_from_path

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

utils.py

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

Python

def get_fields_from_path(model, path): pieces = path.split(LOOKUP_SEP) fields = [] for piece in pieces: if fields: parent = get_model_from_relation(fields[-1]) else: parent = model fields.append(parent._meta.get_field(piece)) return fields

python3.10.4/Lib/distutils/dist.py

def find_config_files(self): files = [] check_environ() # Where to look for the system-wide Distutils config file sys_dir = os.path.dirname(sys.modules['distutils'].__file__) # Look for the system config file sys_file = os.path.join(sys_dir, "distutils.cfg") if os.path.isfile(sys_file): files.append(sys_file) # What to call the per-user config file if os.name == 'posix': user_filename = ".pydistutils.cfg" else: user_filename = "pydistutils.cfg" # And look for the user config file if self.want_user_cfg: user_file = os.path.join(os.path.expanduser('~'), user_filename) if os.path.isfile(user_file): files.append(user_file) # All platforms support local setup.cfg local_file = "setup.cfg" if os.path.isfile(local_file):

add python 3.10.4 for windows

find_config_files

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

dist.py

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

Python

def find_config_files(self): files = [] check_environ() # Where to look for the system-wide Distutils config file sys_dir = os.path.dirname(sys.modules['distutils'].__file__) # Look for the system config file sys_file = os.path.join(sys_dir, "distutils.cfg") if os.path.isfile(sys_file): files.append(sys_file) # What to call the per-user config file if os.name == 'posix': user_filename = ".pydistutils.cfg" else: user_filename = "pydistutils.cfg" # And look for the user config file if self.want_user_cfg: user_file = os.path.join(os.path.expanduser('~'), user_filename) if os.path.isfile(user_file): files.append(user_file) # All platforms support local setup.cfg local_file = "setup.cfg" if os.path.isfile(local_file): files.append(local_file) if DEBUG: self.announce("using config files: %s" % ', '.join(files)) return files

modules/image/Image_gan/gan/stgan_bald/processor.py

def get_save_image_name(org_im_path, output_dir, num): # name prefix of orginal image org_im_name = os.path.split(org_im_path)[-1] im_prefix = os.path.splitext(org_im_name)[0] ext = '.png' # save image path save_im_path = os.path.join(output_dir, im_prefix + ext) if os.path.exists(sav

update stgan_bald (#2022)

get_save_image_name

02d7e5514b0da9a7ebabb004533b274056c954e2

PaddleHub

processor.py

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

Python

def get_save_image_name(org_im_path, output_dir, num): # name prefix of orginal image org_im_name = os.path.split(org_im_path)[-1] im_prefix = os.path.splitext(org_im_name)[0] ext = '.png' # save image path save_im_path = os.path.join(output_dir, im_prefix + ext) if os.path.exists(save_im_path): save_im_path = os.path.join( output_dir, im_prefix + str(num) + ext) return save_im_path

lib/matplotlib/colors.py

def rgb_to_hsv(arr): arr = np.asarray(arr) # check length of the last dimension, should be _some_ sort of rgb if arr.shape[-1] != 3: raise ValueError("Last dimension of input array must be 3; " "shape {} was found.".format(arr.shape)) in_shape = arr.shape arr = np.array( arr, copy=False, dtype=np.promote_types(arr.dtype, np.float32), # Don't work on ints. ndmin=2, # In case input was 1D. ) out = np.zeros_like(arr) arr_max = arr.max(-1) ipos = arr_max > 0 delta = arr.ptp(-1) s = np.zeros_like(delta) s[ipos] = delta[ipos] / arr_max[ipos] ipos = delta > 0 # red is max idx = (arr[..., 0] == arr_max) & ipos out[idx, 0] = (arr[idx, 1] - arr[idx, 2]) / delta[idx] # green is max idx = (arr[..., 1] == arr_max) & ipos out[idx, 0] = 2. + (arr[idx, 2] - arr[idx, 0]) / delta[idx] # blue is max idx = (arr[..., 2] == arr_max) & ipos out[idx, 0] = 4. + (arr[idx, 0] - arr[idx, 1]) / delta[idx] out[..., 0] = (out[..., 0] / 6.0) % 1.0 out[..., 1] = s out[..., 2] = ar

DOC: improve grammar and consistency

rgb_to_hsv

9b6abd0b4933811e0a45c2535ab8fd107db65dd9

matplotlib

colors.py

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

Python

def rgb_to_hsv(arr): arr = np.asarray(arr) # check length of the last dimension, should be _some_ sort of rgb if arr.shape[-1] != 3: raise ValueError("Last dimension of input array must be 3; " "shape {} was found.".format(arr.shape)) in_shape = arr.shape arr = np.array( arr, copy=False, dtype=np.promote_types(arr.dtype, np.float32), # Don't work on ints. ndmin=2, # In case input was 1D. ) out = np.zeros_like(arr) arr_max = arr.max(-1) ipos = arr_max > 0 delta = arr.ptp(-1) s = np.zeros_like(delta) s[ipos] = delta[ipos] / arr_max[ipos] ipos = delta > 0 # red is max idx = (arr[..., 0] == arr_max) & ipos out[idx, 0] = (arr[idx, 1] - arr[idx, 2]) / delta[idx] # green is max idx = (arr[..., 1] == arr_max) & ipos out[idx, 0] = 2. + (arr[idx, 2] - arr[idx, 0]) / delta[idx] # blue is max idx = (arr[..., 2] == arr_max) & ipos out[idx, 0] = 4. + (arr[idx, 0] - arr[idx, 1]) / delta[idx] out[..., 0] = (out[..., 0] / 6.0) % 1.0 out[..., 1] = s out[..., 2] = arr_max return out.reshape(in_shape)

tests/jobs/test_scheduler_job.py

def test_scheduler_verify_pool_full(self, dag_maker, configs): with conf_vars(configs): with dag_maker(dag_id='test_scheduler_verify_pool_full'): BashOperator( task_id='dummy', pool='test_scheduler_verify_pool_full', bash_command='echo hi', ) session = settings.Session() pool = Pool(pool='test_scheduler_verify_pool_full', slots=1) session.add(pool) session.flush() self.scheduler_job = SchedulerJob(executor=self.null_exec) self.scheduler_job.processor_agent = mock.MagicMock() # Create 2 dagruns, which will create 2 task instances. dr = dag_maker.create_dagrun( run_type=DagRunType.SCHEDULED, ) self.scheduler_job._schedule_dag_run(dr, session) dr = dag_maker.create_dagrun_after(dr, run_type=DagRunType.SCHEDULED, state=State.RUNNING) self.scheduler_job._schedule_dag_run(dr, session) session.flush() task_instances_list = self.scheduler_job._executable_task_instances_to_queued( max_tis=32, session=session ) assert len(task_instances_list) == 1

Add dag-processor cli command (#22305)

test_scheduler_verify_pool_full

f5f11aefea775448105098b59c4657fa1809fb94

airflow

test_scheduler_job.py

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

Python

def test_scheduler_verify_pool_full(self, dag_maker, configs): with conf_vars(configs): with dag_maker(dag_id='test_scheduler_verify_pool_full'): BashOperator( task_id='dummy', pool='test_scheduler_verify_pool_full', bash_command='echo hi', ) session = settings.Session() pool = Pool(pool='test_scheduler_verify_pool_full', slots=1) session.add(pool) session.flush() self.scheduler_job = SchedulerJob(executor=self.null_exec) self.scheduler_job.processor_agent = mock.MagicMock() # Create 2 dagruns, which will create 2 task instances. dr = dag_maker.create_dagrun( run_type=DagRunType.SCHEDULED, ) self.scheduler_job._schedule_dag_run(dr, session) dr = dag_maker.create_dagrun_after(dr, run_type=DagRunType.SCHEDULED, state=State.RUNNING) self.scheduler_job._schedule_dag_run(dr, session) session.flush() task_instances_list = self.scheduler_job._executable_task_instances_to_queued( max_tis=32, session=session ) assert len(task_instances_list) == 1

VoiceAssistant/Project_Basic_struct/textRead.py

def ms_word(): # TODO : Take location input from the user try: speak("Enter the document's location - ")

VoiceAssistant This is Voice Assistant coded using Python which can do the following: - 1. Speak Text entered by User. 2. Search anything on Google. 3. Search anything on Wikipedia. 4. Read an MS Word(docx) document. 5. Read a book(PDF). 6. Can be used as a Dictator.

ms_word

39c49e07066b2a53e176d555af6a7bf8aabb8a9c

Python

textRead.py

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

Python

def ms_word(): # TODO : Take location input from the user try: speak("Enter the document's location - ") location = input("Enter the document's location - ") file_loc = doubleslash(location) doc = docx.Document(file_loc) fullText = [] for para in doc.paragraphs: fullText.append(para.text) #print(fullText) doc_file = '\n'.join(fullText) print(doc_file) speak(doc_file) except Exception as exp: #print(exp) print(f"ERROR - {exp}") print(Fore.YELLOW + "I could'nt locate the file!\nIf you didn't specify the extension of the file, please specify it.") return "None"

networkx/readwrite/json_graph/tree.py

def tree_data(G, root, attrs=None, ident="id", children="children"): if G.number_of_nodes() != G.number_of_edges() + 1: raise TypeError("G is not a tree.") if not G.is_directed(): raise TypeError("G is not directed.")

Add exception for unconnected graph (#5287)

tree_data

cceb43d15e1d01476c8c15ff273399dee0e3b1aa

networkx

tree.py

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

Python

def tree_data(G, root, attrs=None, ident="id", children="children"): if G.number_of_nodes() != G.number_of_edges() + 1: raise TypeError("G is not a tree.") if not G.is_directed(): raise TypeError("G is not directed.") if not nx.is_weakly_connected(G): raise TypeError("G is not weakly connected.") # NOTE: to be removed in 3.0 if attrs is not None: import warnings msg = ( "\nThe `attrs` keyword argument of tree_data is deprecated\n" "and will be removed in networkx 3.0.\n" "It is replaced with explicit `ident` and `children` " "keyword arguments.\n" "To make this warning go away and ensure usage is forward\n" "compatible, replace `attrs` with `ident` and `children,\n" "for example:\n\n" " >>> tree_data(G, root, attrs={'id': 'foo', 'children': 'bar'})\n\n" "should instead be written as\n\n" " >>> tree_data(G, root, ident='foo', children='bar')\n\n" "The default values of 'id' and 'children' will not change." ) warnings.warn(msg, DeprecationWarning, stacklevel=2) ident = attrs["id"] children = attrs["children"] if ident == children: raise nx.NetworkXError("The values for `id` and `children` must be different.")

lib/mpl_toolkits/mplot3d/tests/test_axes3d.py

def test_mutating_input_arrays_y_and_z(fig_test, fig_ref): ax1 = fig_test.add_subplot(111, projection='3d') x = [1, 2, 3] y = [0.0, 0.0, 0.0] z = [0.0, 0.0, 0.0] ax1.plot(x, y, z, 'o-') ax1.set_ylim([0, 4]) ax1.set_zlim([0, 4]) fig_test.draw_without_rendering() # mutate y,z to get a nontrivial line y[:] = [1, 2, 3] z[:] = [1, 2, 3] # draw the same plot without mutating x and y ax2 = fig_ref.add_subplot(111, projection='3d') x = [1, 2, 3] y = [0.0, 0.0, 0.0] z = [0.0, 0.0, 0.0] ax2.plot(x, y, z, 'o-') ax2.set_ylim([0, 4]) ax2.set_zlim([0, 4]) fig_test.draw_without_rendering()

Test that plot results aren't affected by mutating input arrays

test_mutating_input_arrays_y_and_z

7a1df7830f7685a99291d90c5e79bfc5e7876f31

matplotlib

test_axes3d.py

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

Python

def test_mutating_input_arrays_y_and_z(fig_test, fig_ref): ax1 = fig_test.add_subplot(111, projection='3d') x = [1, 2, 3] y = [0.0, 0.0, 0.0] z = [0.0, 0.0, 0.0] ax1.plot(x, y, z, 'o-') ax1.set_ylim([0, 4]) ax1.set_zlim([0, 4]) fig_test.draw_without_rendering() # mutate y,z to get a nontrivial line y[:] = [1, 2, 3] z[:] = [1, 2, 3] # draw the same plot without mutating x and y ax2 = fig_ref.add_subplot(111, projection='3d') x = [1, 2, 3] y = [0.0, 0.0, 0.0] z = [0.0, 0.0, 0.0] ax2.plot(x, y, z, 'o-') ax2.set_ylim([0, 4]) ax2.set_zlim([0, 4]) fig_test.draw_without_rendering()

wagtail/search/tests/elasticsearch_common_tests.py

def test_search_with_hyphen(self): book = models.Book.objects.create( title="Harry Potter and the Half-Blood Prince", publication_date=date(2009, 7, 15), number_of_pages=607, ) index = self.backend.get_index_for_model(models.Book) index.add_item(book) index.refresh() results = self.backend.search("Half-Blood", models.Book) self.assertUnsortedListEqual( [r.title for r in results], [ "Harry Potter and the Half-Blood Prince", ], )

Reformat with black

test_search_with_hyphen

d10f15e55806c6944827d801cd9c2d53f5da4186

wagtail

elasticsearch_common_tests.py

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

Python

def test_search_with_hyphen(self): book = models.Book.objects.create( title="Harry Potter and the Half-Blood Prince", publication_date=date(2009, 7, 15), number_of_pages=607, ) index = self.backend.get_index_for_model(models.Book) index.add_item(book) index.refresh() results = self.backend.search("Half-Blood", models.Book) self.assertUnsortedListEqual( [r.title for r in results], [ "Harry Potter and the Half-Blood Prince", ], )

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

def resolve(self, s): name = s.split('.') used = name.pop(0) try: found = self.importer(used) for frag in name: used += '.' + frag try: found = getattr(found, frag) except AttributeError: self.importer(used)

upd; format

resolve

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

compat.py

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

Python

def resolve(self, s): name = s.split('.') used = name.pop(0) try: found = self.importer(used) for frag in name: used += '.' + frag try: found = getattr(found, frag) except AttributeError: self.importer(used) found = getattr(found, frag) return found except ImportError: e, tb = sys.exc_info()[1:] v = ValueError('Cannot resolve %r: %s' % (s, e)) v.__cause__, v.__traceback__ = e, tb raise v

examples/ensemble/plot_gradient_boosting_oob.py

def heldout_score(clf, X_test, y_test): score = np.zeros((n_estimators,), dtype=np.float64) for i, y_pred in enumerate(clf.staged_decision_function(X_test)):

DOC Fix FutureWarning in ensemble/plot_gradient_boosting_oob.py (#24948)

heldout_score

2c1581c32e641e535305647eb57a1787bcf803f0

scikit-learn

plot_gradient_boosting_oob.py

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

Python

def heldout_score(clf, X_test, y_test): score = np.zeros((n_estimators,), dtype=np.float64) for i, y_pred in enumerate(clf.staged_decision_function(X_test)): score[i] = binomial_deviance(y_test, y_pred.ravel()) return score

@pytest.mark.parametrize( "search, expected_names", ( ("", ["The best juices", "The best beers", "The worst beers"]), ("best", ["The best juices", "The best beers"]), ("worst", ["The worst beers"]), ("average", []), ), )

saleor/graphql/product/tests/queries/test_product_types_query.py

def test_product_types_query_ids_not_exists(user_api_client, category): query = NOT_EXISTS_IDS_COLLECTIONS_QUERY variables = {"filter": {"ids": ["fTEJRuFHU6fd2RU=", "2XwnQNNhwCdEjhP="]}} response = user_api_client.post_graphql(query, variables) content = get_graphql_content(response, ignore_errors=True) message_error = '{"ids": [{"message": "Invalid ID specified.", "code": ""}]}' assert len(content["errors"]) == 1 assert content["errors"][0]["message"] == message_error assert content["data"]["productTypes"] is None QUERY_FILTER_PRODUCT_TYPES = @pytest.mark.parametrize( "search, expected_names", ( ("", ["The best juices", "The best beers", "The worst beers"]), ("best", ["The best juices", "The best beers"]), ("worst", ["The wor

Split test_product.py and test_variant.py into multiple files (#11173) * Split test_product.py into multiple files * Split test_variant.py into multiple files

test_product_types_query_ids_not_exists

d90be220d6b687d08153934a51354011a3cb5ca1

saleor

test_product_types_query.py

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

Python

def test_product_types_query_ids_not_exists(user_api_client, category): query = NOT_EXISTS_IDS_COLLECTIONS_QUERY variables = {"filter": {"ids": ["fTEJRuFHU6fd2RU=", "2XwnQNNhwCdEjhP="]}} response = user_api_client.post_graphql(query, variables) content = get_graphql_content(response, ignore_errors=True) message_error = '{"ids": [{"message": "Invalid ID specified.", "code": ""}]}' assert len(content["errors"]) == 1 assert content["errors"][0]["message"] == message_error assert content["data"]["productTypes"] is None QUERY_FILTER_PRODUCT_TYPES = @pytest.mark.parametrize( "search, expected_names", ( ("", ["The best juices", "The best beers", "The worst beers"]), ("best", ["The best juices", "The best beers"]), ("worst", ["The worst beers"]), ("average", []), ), )

datasets/hans/hans.py

def _generate_examples(self, filepath): for idx, line in enumerate(open(filepath, "r", encoding="utf-8")): if idx == 0: continue # skip header line = line.strip() split_line = line.split("\t") # Examples not marked with a three out of five consensus are marked with # "-" and should not be used in standard evaluations. if split_line[0] == "-": continue # Works for both splits even though dev has some extra human labels. yield idx, { "premise": split_line[5], "hypothesis": split_line[6], "label": split_line[0], "binary_parse_premise": split_line[1], "binary_parse_hypothesis": split_line[2],

Make HANS dataset streamable (#4155) * Make HANS dataset streamable * Fix tags

_generate_examples

0060f4c7d3f8e4fb7a3694a925ca3b7f44e1f2ea

datasets

hans.py

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

Python

def _generate_examples(self, filepath): for idx, line in enumerate(open(filepath, "r", encoding="utf-8")): if idx == 0: continue # skip header line = line.strip() split_line = line.split("\t") # Examples not marked with a three out of five consensus are marked with # "-" and should not be used in standard evaluations. if split_line[0] == "-": continue # Works for both splits even though dev has some extra human labels. yield idx, { "premise": split_line[5], "hypothesis": split_line[6], "label": split_line[0], "binary_parse_premise": split_line[1], "binary_parse_hypothesis": split_line[2], "parse_premise": split_line[3], "parse_hypothesis": split_line[4], "heuristic": split_line[8], "subcase": split_line[9], "template": split_line[10], }

homeassistant/components/light/__init__.py

def _light_internal_color_mode(self) -> str: if (color_mode := self.color_mode) is None: # Backwards compatibility for color_mode added in 2021.4 # Add warning in 2021.6, remove in 2021.10 supported = self._light_internal_supported_color_modes if ColorMode.HS in supported and self.hs_color is not None: return ColorMode.HS if ColorMode.COLOR_TEMP in supported and self.color_temp_kelvin is not None: return ColorMode.COLOR_TEMP

Use Kelvin as the preferred color temperature unit (#79591) * Use Kelvin as the preferred white temperature unit * Update homekit * Adjust tests

_light_internal_color_mode

47d0598e75487f63901931875f69f802a477df13

core

__init__.py

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

Python

def _light_internal_color_mode(self) -> str: if (color_mode := self.color_mode) is None: # Backwards compatibility for color_mode added in 2021.4 # Add warning in 2021.6, remove in 2021.10 supported = self._light_internal_supported_color_modes if ColorMode.HS in supported and self.hs_color is not None: return ColorMode.HS if ColorMode.COLOR_TEMP in supported and self.color_temp_kelvin is not None: return ColorMode.COLOR_TEMP if ColorMode.BRIGHTNESS in supported and self.brightness is not None: return ColorMode.BRIGHTNESS if ColorMode.ONOFF in supported: return ColorMode.ONOFF return ColorMode.UNKNOWN return color_mode

pandas/plotting/_core.py

def kde(self, bw_method=None, ind=None, **kwargs):

DOC: fix URLs, formatting and typos (#45920)

kde

1b5338e95917a8b94a9f7b2e1881442dd663c02d

pandas

_core.py

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

Python

def kde(self, bw_method=None, ind=None, **kwargs): return self(kind="kde", bw_method=bw_method, ind=ind, **kwargs) density = kde

@pytest.fixture

saleor/plugins/webhook/tests/subscription_webhooks/fixtures.py

def subscription_invoice_requested_webhook(subscription_webhook): return subscription_webhook( INVOICE_REQUESTED_SUBSCRIPTION_QUERY, WebhookEventAsyncType.INVOICE_REQUESTED ) INVOICE_DELETED_SUBSCRIPTION_QUERY = @pytest

Add Webhook payload via graphql subscriptions (#9394) * Add PoC of webhook subscriptions * add async webhooks subscription payloads feature * remove unneeded file * add translations subscription handling, fixes after review * remove todo * add descriptions * add descriptions, move subsrciption_payloads.py * refactor * fix imports, add changelog * check_document_is_single_subscription refactor Co-authored-by: Maciej Korycinski <[email protected]> Co-authored-by: Marcin Gębala <[email protected]>

subscription_invoice_requested_webhook

aca6418d6c36956bc1ab530e6ef7e146ec9df90c

saleor

fixtures.py

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

Python

def subscription_invoice_requested_webhook(subscription_webhook): return subscription_webhook( INVOICE_REQUESTED_SUBSCRIPTION_QUERY, WebhookEventAsyncType.INVOICE_REQUESTED ) INVOICE_DELETED_SUBSCRIPTION_QUERY = @pytest.fixture

tests/unit_tests/prompts/test_prompt.py

def test_prompt_from_examples_valid() -> None: template = input_variables = ["question"] example_separator = "\n\n" prefix = suffix = examples = [ , , ] prompt_from_examples = PromptTemplate.from_examples( examples, suffix, input_variables, example_separator=example_separator, prefix=prefix, ) prompt_from_template = PromptTemplate( input_variables=input_variables, template=template ) assert prompt_from_examples.template == prompt_from_template.template assert prompt_from_examples.input_variables == prompt_from_template.input_variables

add few shot example (#148)

test_prompt_from_examples_valid

c02eb199b6587aeeb50fbb083693572bd2f030cc

langchain

test_prompt.py

https://github.com/hwchase17/langchain.git

Python

def test_prompt_from_examples_valid() -> None: template = input_variables = ["question"] example_separator = "\n\n" prefix = suffix = examples = [ , , ] prompt_from_examples = PromptTemplate.from_examples( examples, suffix, input_variables, example_separator=example_separator, prefix=prefix, ) prompt_from_template = PromptTemplate( input_variables=input_variables, template=template ) assert prompt_from_examples.template == prompt_from_template.template assert prompt_from_examples.input_variables == prompt_from_template.input_variables

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

def compatible_platforms(provided, required): if provided is None or required is None or provided == required: # easy case return True # Mac OS X special cases reqMac = macosVersionString.match(required) if reqMac: provMac = macosVersionString.match(provided) # is this a Mac package? if not

upd; format

compatible_platforms

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

transferlearning

__init__.py

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

Python

def compatible_platforms(provided, required): if provided is None or required is None or provided == required: # easy case return True # Mac OS X special cases reqMac = macosVersionString.match(required) if reqMac: provMac = macosVersionString.match(provided) # is this a Mac package? if not provMac: # this is backwards compatibility for packages built before # setuptools 0.6. All packages built after this point will # use the new macosx designation. provDarwin = darwinVersionString.match(provided) if provDarwin: dversion = int(provDarwin.group(1)) macosversion = "%s.%s" % (reqMac.group(1), reqMac.group(2)) if dversion == 7 and macosversion >= "10.3" or \ dversion == 8 and macosversion >= "10.4": return True # egg isn't macosx or legacy darwin return False # are they the same major version and machine type? if provMac.group(1) != reqMac.group(1) or \ provMac.group(3) != reqMac.group(3): return False # is the required OS major update >= the provided one? if int(provMac.group(2)) > int(reqMac.group(2)): return False return True # XXX Linux and other platforms' special cases should go here return False

networkx/algorithms/shortest_paths/weighted.py

def find_negative_cycle(G, source, weight="weight"): weight = _weight_function(G, weight) pred = {source: []} v = _inner_bellman_ford(G, [source], weight, pred=pred) if v is None: raise nx.NetworkXError("No negative cycles detected.") # negative cycle detected... find it neg_cycle = [] stack = [(v, list(pred[v]))] seen = {v} while stack: node, preds = stack[-1] if v in preds: # found the cycle neg_cycle.extend([node, v]) neg_cycle = list(reversed(neg_cycle)) return neg_cycle if preds: nbr = preds.pop() if nbr not in seen: stack.append((nbr, list(pred[nbr]))) neg_cycle.append(node) seen.add(nbr) else: stack.pop() if neg_cycle: neg_c

Corrected the documentation of find_negative_cycle() solving issue #5610 (#5613) * issue * Update branchings.py * Update weakly_connected.py

find_negative_cycle

ec2e239764c92adf3b1abcf12817198a878d8772

networkx

weighted.py

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

Python

def find_negative_cycle(G, source, weight="weight"): weight = _weight_function(G, weight) pred = {source: []} v = _inner_bellman_ford(G, [source], weight, pred=pred) if v is None: raise nx.NetworkXError("No negative cycles detected.") # negative cycle detected... find it neg_cycle = [] stack = [(v, list(pred[v]))] seen = {v} while stack: node, preds = stack[-1] if v in preds: # found the cycle neg_cycle.extend([node, v]) neg_cycle = list(reversed(neg_cycle)) return neg_cycle if preds: nbr = preds.pop() if nbr not in seen: stack.append((nbr, list(pred[nbr]))) neg_cycle.append(node) seen.add(nbr) else: stack.pop() if neg_cycle: neg_cycle.pop() else: if v in G[v] and weight(G, v, v) < 0: return [v, v] # should not reach here raise nx.NetworkXError("Negative cycle is detected but not found") # should not get here... msg = "negative cycle detected but not identified" raise nx.NetworkXUnbounded(msg)

src/PIL/ImageOps.py

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,

Use getpalette() in ImageOps

expand

279ddf4ce6c76498ac29df2552a3023b9aaa76c1

Pillow

ImageOps.py

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

Python

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

tests/sentry/integrations/slack/notifications/test_issue_alert.py

def test_digest_enabled(self, digests, mock_func): backend = RedisBackend() digests.digest = backend.digest digests.enabled.return_value = True rule = Rule.objects.create(project=self.project, label="my rule") ProjectOwnership.objects.create(project_id=self.project.id, fallthrough=True) event = self.store_event( data={"message": "Hello world", "level": "error"}, project_id=self.project.id ) key = f"mail:p:{self.project.id}" backend.add(key, event_to_record(event, [rule]), increment_delay=0, maximum_delay=0) with self.tasks(): deliver_digest(key) attachment, text = get_attachment() assert attachment["title"] == "Hello world" assert attachment["text"] == ""

feat(workflow): Set project ownership fallthrough default false (#39305)

test_digest_enabled

210295c5ed1d7286ae808b15d14f6e83356af16e

sentry

test_issue_alert.py

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

Python

def test_digest_enabled(self, digests, mock_func): backend = RedisBackend() digests.digest = backend.digest digests.enabled.return_value = True rule = Rule.objects.create(project=self.project, label="my rule") ProjectOwnership.objects.create(project_id=self.project.id, fallthrough=True) event = self.store_event( data={"message": "Hello world", "level": "error"}, project_id=self.project.id ) key = f"mail:p:{self.project.id}" backend.add(key, event_to_record(event, [rule]), increment_delay=0, maximum_delay=0) with self.tasks(): deliver_digest(key) attachment, text = get_attachment() assert attachment["title"] == "Hello world" assert attachment["text"] == ""

sympy/physics/control/control_plots.py

def pole_zero_numerical_data(system): _check_system(system) system = system.doit() # Get the equivalent TransferFunction object. num_poly = Poly(system.num, system.var).all_coeffs() den_poly = Poly(system.den, system.var).all_coeffs() num_poly = np.array(num_poly, dtype=np.complex128) den_poly = np.array(den_poly, dtype=np.complex128) zeros = np.roots(num_poly) poles = np.roots(

Allow complex transfer functions in pole-zero plot

pole_zero_numerical_data

bf1cb469061d7ad07bfbf687f5635d9f4ec569dd

sympy

control_plots.py

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

Python

def pole_zero_numerical_data(system): _check_system(system) system = system.doit() # Get the equivalent TransferFunction object. num_poly = Poly(system.num, system.var).all_coeffs() den_poly = Poly(system.den, system.var).all_coeffs() num_poly = np.array(num_poly, dtype=np.complex128) den_poly = np.array(den_poly, dtype=np.complex128) zeros = np.roots(num_poly) poles = np.roots(den_poly) return zeros, poles

python3.10.4/Lib/distutils/cygwinccompiler.py

def get_versions(): commands = ['gcc -dumpversion', 'ld -v', 'dllwrap --version'] return t

add python 3.10.4 for windows

get_versions

8198943edd73a363c266633e1aa5b2a9e9c9f526

XX-Net

cygwinccompiler.py

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

Python

def get_versions(): commands = ['gcc -dumpversion', 'ld -v', 'dllwrap --version'] return tuple([_find_exe_version(cmd) for cmd in commands])

salt/beacons/napalm_beacon.py

def __virtual__(): if salt.utils.napalm.virtual(__opts__, __virtualname__, __file__): return __virtualname__ else: err_msg = "NAPALM is not installed." log.error("Unable to load %s beacon: %s", __virtualname__, err_msg)

Align enhanced logging accross beacons

__virtual__

4e3632254fb73210ce3e1954ec507473433018b8

salt

napalm_beacon.py

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

Python

def __virtual__(): if salt.utils.napalm.virtual(__opts__, __virtualname__, __file__): return __virtualname__ else: err_msg = "NAPALM is not installed." log.error("Unable to load %s beacon: %s", __virtualname__, err_msg) return False, err_msg

examples/community/lpw_stable_diffusion.py

def parse_prompt_attention(text): res = [] round_brackets = [] square_brackets = [] round_bracket_multiplier = 1.1 square_bracket_multiplier = 1 / 1.1

[Community Pipelines] Long Prompt Weighting Stable Diffusion Pipelines (#907) * [Community Pipelines] Long Prompt Weighting * Update README.md * fix * style * fix style * Update examples/community/README.md Co-authored-by: Patrick von Platen <[email protected]>

parse_prompt_attention

2a0c823527694058d410ed6f91b52e7dd9f94ebe

diffusers

lpw_stable_diffusion.py

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

Python

def parse_prompt_attention(text): res = [] round_brackets = [] square_brackets = [] round_bracket_multiplier = 1.1 square_bracket_multiplier = 1 / 1.1

lib/ansible/galaxy/dependency_resolution/providers.py

def get_dependencies(self, candidate): # type: (Candidate) -> list[Candidate] r # FIXME: If there's several galaxy servers set, there may be a # FIXME: situation when the metadata of the same collection # FIXME: differs. So how do we resolve this case? Priority? # FIXME: Taking into account a pinned hash? Exploding on # FIXME: any differences? # NOTE: The underlying implmentation currently uses first found req_map = self._api_proxy.get_collection_dependencies(candidate) # NOTE: This guard expression MUST perform an early exit only # NOTE: after the `get_collectio

galaxy - Clean up type hints and imports.

get_dependencies

8b2e6285650ec42ec4a19075a8567047e8304ba2

ansible

providers.py

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

Python

def get_dependencies(self, candidate): # type: (Candidate) -> list[Candidate] r # FIXME: If there's several galaxy servers set, there may be a # FIXME: situation when the metadata of the same collection # FIXME: differs. So how do we resolve this case? Priority? # FIXME: Taking into account a pinned hash? Exploding on # FIXME: any differences? # NOTE: The underlying implmentation currently uses first found req_map = self._api_proxy.get_collection_dependencies(candidate) # NOTE: This guard expression MUST perform an early exit only # NOTE: after the `get_collection_dependencies()` call because # NOTE: internally it polulates the artifact URL of the candidate, # NOTE: its SHA hash and the Galaxy API token. These are still # NOTE: necessary with `--no-deps` because even with the disabled # NOTE: dependency resolution the outer layer will still need to # NOTE: know how to download and validate the artifact. # # NOTE: Virtual candidates should always return dependencies # NOTE: because they are ephemeral and non-installable. if not self._with_deps and not candidate.is_virtual: return [] return [ self._make_req_from_dict({'name': dep_name, 'version': dep_req}) for dep_name, dep_req in req_map.items() ]

tests/rest/admin/test_user.py

def test_set_displayname(self) -> None: # Modify user channel = self.make_request( "PUT", self.url_other_user, access_token=self.admin_user_tok, content={"displayname": "foobar"}, ) self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body) self.assertEqual("@user:test", channel.json_body["name

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

test_set_displayname

901b264c0c88f39cbfb8b2229e0dc57968882658

synapse

test_user.py

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

Python

def test_set_displayname(self) -> None: # Modify user channel = self.make_request( "PUT", self.url_other_user, access_token=self.admin_user_tok, content={"displayname": "foobar"}, ) self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body) self.assertEqual("@user:test", channel.json_body["name"]) self.assertEqual("foobar", channel.json_body["displayname"]) # Get user channel = self.make_request( "GET", self.url_other_user, access_token=self.admin_user_tok, ) self.assertEqual(HTTPStatus.OK, channel.code, msg=channel.json_body) self.assertEqual("@user:test", channel.json_body["name"]) self.assertEqual("foobar", channel.json_body["displayname"])

qutebrowser/browser/webkit/network/networkmanager.py

def on_ssl_errors(self, reply, qt_errors):

Refactor certificate error handling - Make CertificateErrorWrapper responsible for accepting/rejecting certs - Try to avoid dealing with unclear booleans - Implement support for deferred errors (#4616) - disabled due to PyQt bug - Implement support for Qt 6 API (#7086)

on_ssl_errors

e5340c449f23608803c286da0563b62f58ba25b0

qutebrowser

networkmanager.py

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

Python

def on_ssl_errors(self, reply, qt_errors): errors = certificateerror.CertificateErrorWrapper(reply, qt_errors) log.network.debug("Certificate errors: {!r}".format(errors)) try: host_tpl: Optional[urlutils.HostTupleType] = urlutils.host_tuple( reply.url()) except ValueError: host_tpl = None is_accepted = False is_rejected = False else: assert host_tpl is not None is_accepted = errors in self._accepted_ssl_errors[host_tpl] is_rejected = errors in self._rejected_ssl_errors[host_tpl] log.network.debug("Already accepted: {} / " "rejected {}".format(is_accepted, is_rejected)) if is_rejected: return elif is_accepted: reply.ignoreSslErrors() return abort_on = self._get_abort_signals(reply) tab = self._get_tab() first_party_url = QUrl() if tab is None else tab.data.last_navigation.url shared.handle_certificate_error( request_url=reply.url(), first_party_url=first_party_url, error=errors, abort_on=abort_on, ) if errors.certificate_was_accepted(): if host_tpl is not None: self._accepted_ssl_errors[host_tpl].add(errors) elif host_tpl is not None: self._rejected_ssl_errors[host_tpl].add(errors)

pandas/_version.py

def render_pep440(pieces): i

BLD: use nonvendor versioneer (#49924) * BLD: remove vendored versioneer * run vis * move config to pyproject.toml * add versioneer to deps * run pyupgrade * fix isort and pylint * fix ci * fix env

render_pep440

e2df99823758210fb2b7c4aba39e23f3445f7cd3

pandas

_version.py

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

Python

def render_pep440(pieces): if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += f"{pieces['distance']}.g{pieces['short']}" if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = f"0+untagged.{pieces['distance']}.g{pieces['short']}" if pieces["dirty"]: rendered += ".dirty" return rendered

tests/cache/tests_async.py

async def test_aset_many(self): self.assertEqual(await cache.aset_many({"a": 1, "b": 2}), []) self.assert

Refs #33476 -- Reformatted code with Black.

test_aset_many

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests_async.py

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

Python

async def test_aset_many(self): self.assertEqual(await cache.aset_many({"a": 1, "b": 2}), []) self.assertEqual( await cache.aset_many({"a": 1, "b": 2}, timeout=2, version="1"), [], )

tests/bash_completion/tests.py

def _user_input(self, input_str): os.environ["COMP_WORDS"] = input_str idx =

Refs #33476 -- Reformatted code with Black.

_user_input

9c19aff7c7561e3a82978a272ecdaad40dda5c00

django

tests.py

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

Python

def _user_input(self, input_str): os.environ["COMP_WORDS"] = input_str idx = len(input_str.split(" ")) - 1 # Index of the last word comp_cword = idx + 1 if input_str.endswith(" ") else idx os.environ["COMP_CWORD"] = str(comp_cword) sys.argv = input_str.split()

lib/streamlit/config.py

def _check_conflicts() -> None: # Node-related conflicts # When using the Node server, we must always connect to 8501 (this is # hard-coded in JS). Otherwise, the browser would decide what port to # connect to based on window.location.port, which in dev is going to # be (3000) # Import logger locally to prevent circular references f

Report sharing removal (#4260) The report sharing feature is a substantial but completely unused portion of the code in Streamlit's underlying machinery. The feature was created early on, used by just a few groups, and has not been used by anyone for a while, as indicated by no activity in the associated S3 buckets. This commit removes that code to make the remaining code easier to navigate and understand.

_check_conflicts

dd9084523e365e637443ea351eaaaa25f52d8412

streamlit

config.py

https://github.com/streamlit/streamlit.git

Python

def _check_conflicts() -> None: # Node-related conflicts # When using the Node server, we must always connect to 8501 (this is # hard-coded in JS). Otherwise, the browser would decide what port to # connect to based on window.location.port, which in dev is going to # be (3000) # Import logger locally to prevent circular references from streamlit.logger import get_logger LOGGER = get_logger(__name__) if get_option("global.developmentMode"): assert _is_unset( "server.port" ), "server.port does not work when global.developmentMode is true." assert _is_unset("browser.serverPort"), ( "browser.serverPort does not work when global.developmentMode is " "true." ) # XSRF conflicts if get_option("server.enableXsrfProtection"): if not get_option("server.enableCORS") or get_option("global.developmentMode"): LOGGER.warning( )

src/datasets/dataset_dict.py

def num_columns(self) -> Dict[str, int]: self._check_values_type() return {k: dataset.num_columns for k, datase

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

num_columns

1904d0c0a3a96330d9b870cdca3e9a3a137f2977

datasets

dataset_dict.py

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

Python

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

dask/bag/random.py

def _sample_with_replacement_map_partitions(population, k): stream = iter(population) e = next(stream) reservoir, stream_length = [e for _ in range(k)], 1 w = [rnd.random() for _ in range(k)] nxt = [_geometric(wi) for wi in w] min_nxt = min(nxt) for i, e in enumerate(stream, 1): if i == min_nxt: for j, n in enumerate(nxt): if n == min_nxt: reservoir[j] = e w[j] *= rnd.random() nxt[j] += _geometric(w[j]) min_nxt = min(nxt)

Bag: add implementation for reservoir sampling (#7068) (#7636) - Implement the [L algorithm](https://en.wikipedia.org/wiki/Reservoir_sampling#An_optimal_algorithm) for reservoir sampling without replacement. - Use the **k** reservoir of size 1 strategy for sampling with replacement (see [reference](http://utopia.duth.gr/~pefraimi/research/data/2007EncOfAlg.pdf)) of **k** items

_sample_with_replacement_map_partitions

4e5dfe7463028a39a90e026c7fb9220969093ab3

dask

random.py

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

Python

def _sample_with_replacement_map_partitions(population, k): stream = iter(population) e = next(stream) reservoir, stream_length = [e for _ in range(k)], 1 w = [rnd.random() for _ in range(k)] nxt = [_geometric(wi) for wi in w] min_nxt = min(nxt) for i, e in enumerate(stream, 1): if i == min_nxt: for j, n in enumerate(nxt): if n == min_nxt: reservoir[j] = e w[j] *= rnd.random() nxt[j] += _geometric(w[j]) min_nxt = min(nxt) stream_length += 1 return reservoir, stream_length