Datasets:

semeru

/

code-text-galeras-code-summarization-3k-deduped

like 1

preprocess_input

def preprocess_input(x, data_format=None): return x @keras_export("keras.applications.efficientnet_v2.decode_predictions")

3613c3defc39c236fb1592c4f7ba1a9cc887343a

@keras_export("keras.applications.efficientnet_v2.decode_predictions")

efficientnet_v2.py

Remove pylint comments. PiperOrigin-RevId: 452353044

keras

keras/applications/efficientnet_v2.py

Python

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

make_increasing_ohlc

def make_increasing_ohlc(open, high, low, close, dates, **kwargs): (flat_increase_x, flat_increase_y, text_increase) = _OHLC( open, high, low, close, dates ).get_increase() if "name" in kwargs: showlegend = True else: kwargs.setdefault("name", "Increasing") showlegend = False kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR, width=1)) kwargs.setdefault("text", text_increase) ohlc_incr = dict( type="scatter", x=flat_increase_x, y=flat_increase_y, mode="lines", showlegend=showlegend, **kwargs, ) return ohlc_incr

43e3a4011080911901176aab919c0ecf5046ddd3

_ohlc.py

switch to black .22

plotly.py

packages/python/plotly/plotly/figure_factory/_ohlc.py

Python

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

test_tags_help_text_no_spaces_allowed

def test_tags_help_text_no_spaces_allowed(self): widget = widgets.AdminTagWidget() help_text = widget.get_context(None, None, {})["widget"]["help_text"] html = widget.render("tags", None, {}) help_text_html_element = self.get_help_text_html_element(html) self.assertEqual( help_text, "Tags can only consist of a single word, no spaces allowed." ) self.assertHTMLEqual( help_text_html_element, % help_text, )

1822d7eee23cf5fceff8b1f58f3ca2f0a32c6e34

test_widgets.py

display help text message for tag field - resolves #1874 - ensure message is dynamic based on the setting TAG_SPACES_ALLOWED - Update wagtail/admin/templates/wagtailadmin/widgets/tag_widget.html

wagtail

wagtail/admin/tests/test_widgets.py

Python

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

handle_template_exception

def handle_template_exception(ex, field): if ex.args and ex.args[0].startswith("UndefinedError: 'None' has no attribute"): # Common during HA startup - so just a warning _LOGGER.warning(ex) return _LOGGER.error("Error parsing template for field %s", field, exc_info=ex)

73a368c24246b081cdb98923ca3180937d436c3b

helpers.py

Refactor history_stats to minimize database access (part 2) (#70255)

core

homeassistant/components/history_stats/helpers.py

Python

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

find_profile_dir_by_name

def find_profile_dir_by_name(cls, ipython_dir, name=u'default', config=None): dirname = u'profile_' + name paths = [ipython_dir] for p in paths: profile_dir = os.path.join(p, dirname) if os.path.isdir(profile_dir): return cls(location=profile_dir, config=config) else: raise ProfileDirError('Profile directory not found in paths: %s' % dirname)

1ec91ebf328bdf3450130de4b4604c79dc1e19d9

profiledir.py

FIX CVE-2022-21699 See https://github.com/ipython/ipython/security/advisories/GHSA-pq7m-3gw7-gq5x

ipython

IPython/core/profiledir.py

Python

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

add_dep_paths

def add_dep_paths(): paths = [] if old_deps is not None: for importer, modname, ispkg in pkgutil.iter_modules( old_deps.__path__): if not ispkg: continue try: mod = importer.find_module(modname).load_module(modname) except ImportError as e: logging.warning(f"deps: Error importing dependency: {e}") continue if hasattr(mod, 'dep_bins'): paths.extend(mod.dep_bins) sys.path.extend(paths) if kivy_deps is None: return paths = [] for importer, modname, ispkg in pkgutil.iter_modules(kivy_deps.__path__): if not ispkg: continue try: mod = importer.find_module(modname).load_module(modname) except ImportError as e: logging.warning(f"deps: Error importing dependency: {e}") continue if hasattr(mod, 'dep_bins'): paths.extend(mod.dep_bins) sys.path.extend(paths)

e6c144b5423dada62fd13034c2d40bf48a2bc423

__init__.py

Replace deprecated logging.warn with logging.warning (#7906)

kivy

kivy/tools/packaging/pyinstaller_hooks/__init__.py

Python

https://github.com/kivy/kivy.git

_ln_exp_bound

def _ln_exp_bound(self): # for 0.1 <= x <= 10 we use the inequalities 1-1/x <= ln(x) <= x-1 adj = self._exp + len(self._int) - 1 if adj >= 1: # argument >= 10; we use 23/10 = 2.3 as a lower bound for ln(10) return len(str(adj*23//10)) - 1 if adj <= -2: # argument <= 0.1 return len(str((-1-adj)*23//10)) - 1 op = _WorkRep(self) c, e = op.int, op.exp if adj == 0: # 1 < self < 10 num = str(c-10**-e) den = str(c) return len(num) - len(den) - (num < den) # adj == -1, 0.1 <= self < 1 return e + len(str(10**-e - c)) - 1

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_pydecimal.py

Python

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

test_orderline_query

def test_orderline_query(staff_api_client, permission_manage_orders, fulfilled_order): order = fulfilled_order query = line = order.lines.first() metadata_key = "md key" metadata_value = "md value" line.store_value_in_private_metadata({metadata_key: metadata_value}) line.store_value_in_metadata({metadata_key: metadata_value}) line.save() staff_api_client.user.user_permissions.add(permission_manage_orders) response = staff_api_client.post_graphql(query) content = get_graphql_content(response) order_data = content["data"]["orders"]["edges"][0]["node"] first_order_data_line = order_data["lines"][0] variant_id = graphene.Node.to_global_id("ProductVariant", line.variant.pk) assert first_order_data_line["thumbnail"] is None assert first_order_data_line["variant"]["id"] == variant_id assert first_order_data_line["quantity"] == line.quantity assert first_order_data_line["unitPrice"]["currency"] == line.unit_price.currency assert first_order_data_line["metadata"] == [ {"key": metadata_key, "value": metadata_value} ] assert first_order_data_line["privateMetadata"] == [ {"key": metadata_key, "value": metadata_value} ] expected_unit_price = Money( amount=str(first_order_data_line["unitPrice"]["gross"]["amount"]), currency="USD", ) assert first_order_data_line["totalPrice"]["currency"] == line.unit_price.currency assert expected_unit_price == line.unit_price.gross expected_total_price = Money( amount=str(first_order_data_line["totalPrice"]["gross"]["amount"]), currency="USD", ) assert expected_total_price == line.unit_price.gross * line.quantity allocation = line.allocations.first() allocation_id = graphene.Node.to_global_id("Allocation", allocation.pk) warehouse_id = graphene.Node.to_global_id( "Warehouse", allocation.stock.warehouse.pk ) assert first_order_data_line["allocations"] == [ { "id": allocation_id, "quantity": allocation.quantity_allocated, "warehouse": {"id": warehouse_id}, } ]

a68553e1a55e3a1bd32826cdce294d27f74175e9

test_order.py

Metadata added to checkout and order lines (#10040) * Metadata added to checkout and order lines * CHANGELOG.md update * Missing tests added

saleor

saleor/graphql/order/tests/test_order.py

Python

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

test_login_view

def test_login_view(self): # Get login page response = self.client.get(reverse("wagtailadmin_login")) # Check that the user received a login page self.assertEqual(response.status_code, 200) self.assertTemplateUsed(response, "wagtailadmin/login.html")

d10f15e55806c6944827d801cd9c2d53f5da4186

test_account_management.py

Reformat with black

wagtail

wagtail/admin/tests/test_account_management.py

Python

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

construct_change_message

def construct_change_message(form, formsets, add): # Evaluating `form.changed_data` prior to disabling translations is required # to avoid fields affected by localization from being included incorrectly, # e.g. where date formats differ such as MM/DD/YYYY vs DD/MM/YYYY. changed_data = form.changed_data with translation_override(None): # Deactivate translations while fetching verbose_name for form # field labels and using `field_name`, if verbose_name is not provided. # Translations will happen later on LogEntry access. changed_field_labels = _get_changed_field_labels_from_form(form, changed_data) change_message = [] if add: change_message.append({"added": {}}) elif form.changed_data: change_message.append({"changed": {"fields": changed_field_labels}}) if formsets: with translation_override(None): for formset in formsets: for added_object in formset.new_objects: change_message.append( { "added": { "name": str(added_object._meta.verbose_name), "object": str(added_object), } } ) for changed_object, changed_fields in formset.changed_objects: change_message.append( { "changed": { "name": str(changed_object._meta.verbose_name), "object": str(changed_object), "fields": _get_changed_field_labels_from_form( formset.forms[0], changed_fields ), } } ) for deleted_object in formset.deleted_objects: change_message.append( { "deleted": { "name": str(deleted_object._meta.verbose_name), "object": str(deleted_object), } } ) return change_message

9c19aff7c7561e3a82978a272ecdaad40dda5c00

utils.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/utils.py

Python

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

split_header_words

def split_header_words(header_values): r assert not isinstance(header_values, str) result = [] for text in header_values: orig_text = text pairs = [] while text: m = HEADER_TOKEN_RE.search(text) if m: text = unmatched(m) name = m.group(1) m = HEADER_QUOTED_VALUE_RE.search(text) if m: # quoted value text = unmatched(m) value = m.group(1) value = HEADER_ESCAPE_RE.sub(r"\1", value) else: m = HEADER_VALUE_RE.search(text) if m: # unquoted value text = unmatched(m) value = m.group(1) value = value.rstrip() else: # no value, a lone token value = None pairs.append((name, value)) elif text.lstrip().startswith(","): # concatenated headers, as per RFC 2616 section 4.2 text = text.lstrip()[1:] if pairs: result.append(pairs) pairs = [] else: # skip junk non_junk, nr_junk_chars = re.subn(r"^[=\s;]*", "", text) assert nr_junk_chars > 0, ( "split_header_words bug: '%s', '%s', %s" % (orig_text, text, pairs)) text = non_junk if pairs: result.append(pairs) return result HEADER_JOIN_ESCAPE_RE = re.compile(r"([\"\\])")

8198943edd73a363c266633e1aa5b2a9e9c9f526

cookiejar.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/http/cookiejar.py

Python

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

reparse

def reparse(self) -> None: # Do this in a fresh Stylesheet so if there are errors we don't break self. stylesheet = Stylesheet(variables=self.variables) for css, path in self.source: stylesheet.parse(css, path=path) self._clone(stylesheet)

e8636d0d86e596690647564b84a68d5e6d107dd0

stylesheet.py

css reparse

textual

src/textual/css/stylesheet.py

Python

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

_get_feature_encoder_or_decoder

def _get_feature_encoder_or_decoder(feature): if DECODER in feature: return feature[DECODER] elif ENCODER in feature: return feature[ENCODER] else: feature[ENCODER] = {} return feature[ENCODER]

60197fe851aadfa51d18c16dd42b49f728ed7eaa

dataset_synthesizer.py

Adds registry to organize backward compatibility updates around versions and config sections (#2335) * First pass implementation of VersionTransformation * Remove test main. * Refactors backward_compatibility.py to use version registration system * Changed sort order to process outer first. * Moves test_deprecated_field_aliases from test_defaults.py to test_backward_compatibility.py * s/prefix/prefixes in test_version_transformation.py * Removes comment, print statements. * Adds docstrings. * typo fix. * Removes unused import. * Small cleanup to backward_compatibility.py, removed redundant keys. * Assume version 0.4 if no version present in the config. * Updates dataset synthesis to work with nested encoder/decoders. * Fixes test_server.py * nesting image feature params in test_ray * _get_feature_encoder_or_decoder in generate_category. * oops, forgot random.choice. Co-authored-by: Daniel Treiman <daniel@predibase.com>

ludwig

ludwig/data/dataset_synthesizer.py

Python

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

test_ContinuousSelector_4

def test_ContinuousSelector_4(): cs = ContinuousSelector() assert_raises(ValueError, cs.transform, iris_data[0:10,:])

388616b6247ca4ea8de4e2f340d6206aee523541

feature_transformers_tests.py

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

tpot

tests/feature_transformers_tests.py

Python

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

dpm_solver_first_update

def dpm_solver_first_update(self, x, s, t, model_s=None, return_intermediate=False): ns = self.noise_schedule dims = x.dim() lambda_s, lambda_t = ns.marginal_lambda(s), ns.marginal_lambda(t) h = lambda_t - lambda_s log_alpha_s, log_alpha_t = ns.marginal_log_mean_coeff(s), ns.marginal_log_mean_coeff(t) sigma_s, sigma_t = ns.marginal_std(s), ns.marginal_std(t) alpha_t = torch.exp(log_alpha_t) if self.predict_x0: phi_1 = torch.expm1(-h) if model_s is None: model_s = self.model_fn(x, s) x_t = ( expand_dims(sigma_t / sigma_s, dims) * x - expand_dims(alpha_t * phi_1, dims) * model_s ) if return_intermediate: return x_t, {'model_s': model_s} else: return x_t else: phi_1 = torch.expm1(h) if model_s is None: model_s = self.model_fn(x, s) x_t = ( expand_dims(torch.exp(log_alpha_t - log_alpha_s), dims) * x - expand_dims(sigma_t * phi_1, dims) * model_s ) if return_intermediate: return x_t, {'model_s': model_s} else: return x_t

ca86da3a30c4e080d4db8c25fca73de843663cb4

dpm_solver.py

release more models

stablediffusion

ldm/models/diffusion/dpm_solver/dpm_solver.py

Python

https://github.com/Stability-AI/stablediffusion.git

_asarray_with_order

def _asarray_with_order(array, dtype=None, order=None, copy=None, xp=None): if xp is None: xp, _ = get_namespace(array) if xp.__name__ in {"numpy", "numpy.array_api"}: # Use NumPy API to support order array = numpy.asarray(array, order=order, dtype=dtype) return xp.asarray(array, copy=copy) else: return xp.asarray(array, dtype=dtype, copy=copy)

2710a9e7eefd2088ce35fd2fb6651d5f97e5ef8b

_array_api.py

ENH Adds Array API support to LinearDiscriminantAnalysis (#22554) Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>

scikit-learn

sklearn/utils/_array_api.py

Python

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

test_bound_blocks_are_available_on_template

def test_bound_blocks_are_available_on_template(self): block = SectionBlock() value = block.to_python({"title": "Hello", "body": "<i>italic</i> world"}) result = block.render(value) self.assertEqual(result, )

d10f15e55806c6944827d801cd9c2d53f5da4186

test_blocks.py

Reformat with black

wagtail

wagtail/core/tests/test_blocks.py

Python

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

_genName

def _genName(cls, name): if not name: name = "frame_" + str(uuid.uuid4()).replace("-", "") # TODO: reword name in case of caller's mistake return name

1c0935c1bc0856d43f69c1e32498636ee24ebc85

base_worker.py

FEAT-#4913: Enabling pyhdk (#4900) Co-authored-by: ienkovich <ilya.enkovich@intel.com> Signed-off-by: izamyati <igor.zamyatin@intel.com>

modin

modin/experimental/core/execution/native/implementations/omnisci_on_native/base_worker.py

Python

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

sort_graph_by_row_values

def sort_graph_by_row_values(graph, copy=False, warn_when_not_sorted=True): if not issparse(graph): raise TypeError(f"Input graph must be a sparse matrix, got {graph!r} instead.") if graph.format == "csr" and _is_sorted_by_data(graph): return graph if warn_when_not_sorted: warnings.warn( "Precomputed sparse input was not sorted by row values. Use the function" " sklearn.neighbors.sort_graph_by_row_values to sort the input by row" " values, with warn_when_not_sorted=False to remove this warning.", EfficiencyWarning, ) if graph.format not in ("csr", "csc", "coo", "lil"): raise TypeError( f"Sparse matrix in {graph.format!r} format is not supported due to " "its handling of explicit zeros" ) elif graph.format != "csr": if not copy: raise ValueError( "The input graph is not in CSR format. Use copy=True to allow " "the conversion to CSR format." ) graph = graph.asformat("csr") elif copy: # csr format with copy=True graph = graph.copy() row_nnz = np.diff(graph.indptr) if row_nnz.max() == row_nnz.min(): # if each sample has the same number of provided neighbors n_samples = graph.shape[0] distances = graph.data.reshape(n_samples, -1) order = np.argsort(distances, kind="mergesort") order += np.arange(n_samples)[:, None] * row_nnz[0] order = order.ravel() graph.data = graph.data[order] graph.indices = graph.indices[order] else: for start, stop in zip(graph.indptr, graph.indptr[1:]): order = np.argsort(graph.data[start:stop], kind="mergesort") graph.data[start:stop] = graph.data[start:stop][order] graph.indices[start:stop] = graph.indices[start:stop][order] return graph

b94bc5ea6821607d1e9826ce2d084c76379820ba

_base.py

ENH add new function sort_graph_by_row_values (#23139) Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

scikit-learn

sklearn/neighbors/_base.py

Python

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

add_and_show_greeks

def add_and_show_greeks(price, implied_volatility, strike, days, side): # Add in hedge option delta, gamma, vega = hedge_model.add_hedge_option( price, implied_volatility, strike, days, side ) # Show the added delta, gamma and vega positions. Next to that, also show the inputted # implied volatility and strike positions = pd.DataFrame( [delta, gamma, vega, implied_volatility, strike], index=["Delta", "Gamma", "Vega", "Implied Volatility", "Strike Price"], columns=["Positions"], ) # Show table print_rich_table(positions, show_index=True, headers=list(positions.columns)) console.print() return delta, gamma, vega

54a1b6f545a0016c576e9e00eef5c003d229dacf

hedge_view.py

Feature/hedge (#1768) * [Bug] Incorrect log for reddit keys. #1733 fix * Create new feature-hedge * Significantly improve code of hedge menu * More robust * Robustness * Fix tests * Fix can't multiply sequence by non-int of type 'numpy.float64' error * Temporary fix of singular matrix error. Return first feasible solution * Update Hugo Documentation * Combining menus and cleaning up code * Tidy up call_exp * Update tests Round 1 * Update tests Round 2 * Fix linting error * Fix linting? * Fixed glitch Co-authored-by: JerBouma <jer.bouma@gmail.com> Co-authored-by: James Maslek <jmaslek11@gmail.com> Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: colin99d <colin99delahunty@gmail.com> Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt>

OpenBBTerminal

openbb_terminal/stocks/options/hedge/hedge_view.py

Python

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

test_acknowledged_new

def test_acknowledged_new(self) -> None: expected_topic = "Test policy name (1234)" expected_message = .strip() self.check_webhook( "incident_acknowledged_new", expected_topic, expected_message, content_type="application/json", )

bfd9fc86223c2446e8b38d2cdd5876caed50bfda

tests.py

integration: Fix integration with newrelic. Newrelic updated the payload that's sent via the webhook incoming call causing a bug in the newrelic webhook endpoint. This fixes the bug by updating the endpoint to respect the new format of the payload as well as the old format. This should be updated once the old format is EOLed. Fixes #22338.

zulip

zerver/webhooks/newrelic/tests.py

Python

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

_get_vhost_block

def _get_vhost_block(self, vhost): try: span_val = self.parser.aug.span(vhost.path) except ValueError: logger.critical("Error while reading the VirtualHost %s from " "file %s", vhost.name, vhost.filep, exc_info=True) raise errors.PluginError("Unable to read VirtualHost from file") span_filep = span_val[0] span_start = span_val[5] span_end = span_val[6] with open(span_filep, 'r') as fh: fh.seek(span_start) vh_contents = fh.read(span_end-span_start).split("\n") self._remove_closing_vhost_tag(vh_contents) return vh_contents

eeca208c8f57304590ac1af80b496e61021aaa45

configurator.py

Various clean-ups in certbot-apache. Use f-strings. (#9132) * Various clean-ups in certbot-apache. Use f-strings. * Smaller tweaks

certbot

certbot-apache/certbot_apache/_internal/configurator.py

Python

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

__call__

def __call__(self, string): texts = [] floats = [] for i, part in enumerate(self._FLOAT_RE.split(string)): if i % 2 == 0: texts.append(part) else: floats.append(float(part)) return texts, np.array(floats)

84afc5193d38057e2e2badf9c889ea87d80d8fbf

keras_doctest_lib.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/testing_infra/keras_doctest_lib.py

Python

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

parse_boundary_stream

def parse_boundary_stream(stream, max_header_size): # Stream at beginning of header, look for end of header # and parse it if found. The header must fit within one # chunk. chunk = stream.read(max_header_size) # 'find' returns the top of these four bytes, so we'll # need to munch them later to prevent them from polluting # the payload. header_end = chunk.find(b"\r\n\r\n")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

multipartparser.py

Refs #33476 -- Reformatted code with Black.

django

django/http/multipartparser.py

Python

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

slice_with_int_dask_array

def slice_with_int_dask_array(x, index): from dask.array.core import Array assert len(index) == x.ndim fancy_indexes = [ isinstance(idx, (tuple, list)) or (isinstance(idx, (np.ndarray, Array)) and idx.ndim > 0) for idx in index ] if sum(fancy_indexes) > 1: raise NotImplementedError("Don't yet support nd fancy indexing") out_index = [] dropped_axis_cnt = 0 for in_axis, idx in enumerate(index): out_axis = in_axis - dropped_axis_cnt if isinstance(idx, Array) and idx.dtype.kind in "iu": if idx.ndim == 0: idx = idx[np.newaxis] x = slice_with_int_dask_array_on_axis(x, idx, out_axis) x = x[tuple(0 if i == out_axis else slice(None) for i in range(x.ndim))] dropped_axis_cnt += 1 elif idx.ndim == 1: x = slice_with_int_dask_array_on_axis(x, idx, out_axis) out_index.append(slice(None)) else: raise NotImplementedError( "Slicing with dask.array of ints only permitted when " "the indexer has zero or one dimensions" ) else: out_index.append(idx) return x, tuple(out_index)

cccb9d8d8e33a891396b1275c2448c352ef40c27

slicing.py

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

dask

dask/array/slicing.py

Python

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

get_edit_upload_response_data

def get_edit_upload_response_data(self): return { "success": True, self.context_upload_id_name: self.upload_object.id, "form": render_to_string( self.edit_form_template_name, self.get_edit_upload_form_context_data(), request=self.request, ), }

d10f15e55806c6944827d801cd9c2d53f5da4186

multiple_upload.py

Reformat with black

wagtail

wagtail/admin/views/generic/multiple_upload.py

Python

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

peek

def peek(self, n=0): self._check_can_read() # Relies on the undocumented fact that BufferedReader.peek() # always returns at least one byte (except at EOF), independent # of the value of n return self._buffer.peek(n)

8198943edd73a363c266633e1aa5b2a9e9c9f526

bz2.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/bz2.py

Python

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

_get_boot_time_aix

def _get_boot_time_aix(): res = __salt__["cmd.run_all"]("ps -o etime= -p 1") if res["retcode"] > 0: raise CommandExecutionError("Unable to find boot_time for pid 1.") bt_time = res["stdout"] match = re.match(r"\s*(?:(\d+)-)?(?:(\d\d):)?(\d\d):(\d\d)\s*", bt_time) if not match: raise CommandExecutionError("Unexpected time format.") groups = match.groups(default="00") boot_secs = ( _number(groups[0]) * 86400 + _number(groups[1]) * 3600 + _number(groups[2]) * 60 + _number(groups[3]) ) return boot_secs

7fabb22f3e361bfff3fdbca01c12659591d15109

status.py

Fix uptime on AIX systems when less than 24 hours

salt

salt/modules/status.py

Python

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

_matches_get_other_nodes

def _matches_get_other_nodes(dictionary, nodes, node_ind): ind_node = nodes[node_ind] return [ind for ind in dictionary if nodes[ind] == ind_node]

9d58006fc0a23afcba38f641c9472917c436428a

mul.py

Code cleanup

sympy

sympy/core/mul.py

Python

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

test_uncancellable_disconnect

def test_uncancellable_disconnect(self) -> None: channel = make_request( self.reactor, self.site, "POST", "/sleep", await_result=False ) self._test_disconnect( self.reactor, channel, expect_cancellation=False, expected_body={"result": True}, )

dffecade7df8a88caced2a7707c51e2de3407c0d

test_server.py

Respect the `@cancellable` flag for `DirectServe{Html,Json}Resource`s (#12698) `DirectServeHtmlResource` and `DirectServeJsonResource` both inherit from `_AsyncResource`. These classes expect to be subclassed with `_async_render_*` methods. This commit has no effect on `JsonResource`, despite inheriting from `_AsyncResource`. `JsonResource` has its own `_async_render` override which will need to be updated separately. Signed-off-by: Sean Quah <seanq@element.io>

synapse

tests/test_server.py

Python

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

test_del_store_not_found

def test_del_store_not_found(certutil, cert_file): with pytest.raises(salt.exceptions.CommandExecutionError) as exc: certutil.del_store( source=str(cert_file.parent / "absent.cer"), store="TrustedPublisher", ) assert "cert_file not found" in exc.value.message

a8d2d1e1397cdc79b2c5f1ad7f6e3b729dcf8857

test_win_certutil.py

Add tests, fix state module

salt

tests/pytests/functional/modules/test_win_certutil.py

Python

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

__next__

def __next__(self): line = self.readline() if line: return line raise StopIteration

8198943edd73a363c266633e1aa5b2a9e9c9f526

codecs.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/codecs.py

Python

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

datetime_cast_date_sql

def datetime_cast_date_sql(self, field_name, tzname): raise NotImplementedError( "subclasses of BaseDatabaseOperations may require a " "datetime_cast_date_sql() method." )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

operations.py

Refs #33476 -- Reformatted code with Black.

django

django/db/backends/base/operations.py

Python

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

test_empty

def test_empty(self) -> None: id_gen = self._create_id_generator() # The table is empty so we expect an empty map for positions self.assertEqual(id_gen.get_positions(), {})

9d21ecf7ceab55bc19c4457b8b07401b0b1623a7

test_id_generators.py

Add type hints to tests files. (#12256)

synapse

tests/storage/test_id_generators.py

Python

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

nodata_value

def nodata_value(self, value): if value is None: capi.delete_band_nodata_value(self._ptr) elif not isinstance(value, (int, float)): raise ValueError("Nodata value must be numeric or None.") else: capi.set_band_nodata_value(self._ptr, value) self._flush()

9c19aff7c7561e3a82978a272ecdaad40dda5c00

band.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/gis/gdal/raster/band.py

Python

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

test_has_module_permission

def test_has_module_permission(self): self.client.force_login(self.superuser) response = self.client.get(self.index_url) self.assertContains(response, "admin_views") self.assertContains(response, "Articles") self.client.logout() self.client.force_login(self.viewuser) response = self.client.get(self.index_url) self.assertContains(response, "admin_views") self.assertContains(response, "Articles") self.client.logout() self.client.force_login(self.adduser) response = self.client.get(self.index_url) self.assertContains(response, "admin_views") self.assertContains(response, "Articles") self.client.logout() self.client.force_login(self.changeuser) response = self.client.get(self.index_url) self.assertContains(response, "admin_views") self.assertContains(response, "Articles") self.client.logout() self.client.force_login(self.deleteuser) response = self.client.get(self.index_url) self.assertContains(response, "admin_views") self.assertContains(response, "Articles")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

_supports_universal_builds

def _supports_universal_builds(): # As an approximation, we assume that if we are running on 10.4 or above, # then we are running with an Xcode environment that supports universal # builds, in particular -isysroot and -arch arguments to the compiler. This # is in support of allowing 10.4 universal builds to run on 10.3.x systems. osx_version = _get_system_version_tuple() return bool(osx_version >= (10, 4)) if osx_version else False

8198943edd73a363c266633e1aa5b2a9e9c9f526

_osx_support.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_osx_support.py

Python

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

mock_smile_adam_2

def mock_smile_adam_2() -> Generator[None, MagicMock, None]: chosen_env = "m_adam_heating" with patch( "homeassistant.components.plugwise.gateway.Smile", autospec=True ) as smile_mock: smile = smile_mock.return_value smile.gateway_id = "da224107914542988a88561b4452b0f6" smile.heater_id = "056ee145a816487eaa69243c3280f8bf" smile.smile_version = "3.6.4" smile.smile_type = "thermostat" smile.smile_hostname = "smile98765" smile.smile_name = "Adam" smile.connect.return_value = True smile.notifications = _read_json(chosen_env, "notifications") smile.async_update.return_value = _read_json(chosen_env, "all_data") yield smile @pytest.fixture

2667f0b792b1f936aeb5958cc40d5dee26350bf6

@pytest.fixture

conftest.py

Bump plugwise to v0.21.3, add related new features (#76610) Co-authored-by: Franck Nijhof <frenck@frenck.nl>

core

tests/components/plugwise/conftest.py

Python

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

get_tables

def get_tables(self) -> StatusResponse: query = result = self.native_query(query) df = result.data_frame df = df[['TABLE_NAME' 'TABLE_TYPE']] result.data_frame = df.rename(columns={'TABLE_NAME': 'table_name', 'TABLE_TYPE': 'table_type'}) return result

9a0e918bba3439959112a7fd8e5210276b5ac255

druid_handler.py

implemented the get_tables() and get_columns() methods

mindsdb

mindsdb/integrations/handlers/druid_handler/druid_handler.py

Python

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

_add_unique_metric_name

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

fa6d9107a498f7c2403ff28c7b389a1a0c5cc083

training_v1.py

reduct too long lines

keras

keras/engine/training_v1.py

Python

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

test_statistics_duplicated

def test_statistics_duplicated(hass_recorder, caplog): hass = hass_recorder() recorder = hass.data[DATA_INSTANCE] setup_component(hass, "sensor", {}) zero, four, states = record_states(hass) hist = history.get_significant_states(hass, zero, four) assert dict(states) == dict(hist) wait_recording_done(hass) assert "Compiling statistics for" not in caplog.text assert "Statistics already compiled" not in caplog.text with patch( "homeassistant.components.sensor.recorder.compile_statistics", return_value=statistics.PlatformCompiledStatistics([], {}), ) as compile_statistics: recorder.do_adhoc_statistics(start=zero) wait_recording_done(hass) assert compile_statistics.called compile_statistics.reset_mock() assert "Compiling statistics for" in caplog.text assert "Statistics already compiled" not in caplog.text caplog.clear() recorder.do_adhoc_statistics(start=zero) wait_recording_done(hass) assert not compile_statistics.called compile_statistics.reset_mock() assert "Compiling statistics for" not in caplog.text assert "Statistics already compiled" in caplog.text caplog.clear()

3737b58e85d834728fe27fefa05e8a0526e66d12

test_statistics.py

Avoid fetching metadata multiple times during stat compile (#70397)

core

tests/components/recorder/test_statistics.py

Python

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

test_push

def test_push(self): filename = "/saltines/test.file" if salt.utils.platform.is_windows(): filename = "C:\\saltines\\test.file" with patch( "salt.modules.cp.os.path", MagicMock(isfile=Mock(return_value=True), wraps=cp.os.path), ), patch( "salt.modules.cp.os.path", MagicMock(getsize=MagicMock(return_value=10), wraps=cp.os.path), ), patch.multiple( "salt.modules.cp", _auth=MagicMock(**{"return_value.gen_token.return_value": "token"}), __opts__={"id": "abc", "file_buffer_size": 10}, ), patch( "salt.utils.files.fopen", mock_open(read_data=b"content") ) as m_open, patch( "salt.channel.client.ReqChannel.factory", MagicMock() ) as req_channel_factory_mock: response = cp.push(filename) assert response, response num_opens = len(m_open.filehandles[filename]) assert num_opens == 1, num_opens fh_ = m_open.filehandles[filename][0] assert fh_.read.call_count == 2, fh_.read.call_count req_channel_factory_mock().__enter__().send.assert_called_once_with( dict( loc=fh_.tell(), # pylint: disable=resource-leakage cmd="_file_recv", tok="token", path=["saltines", "test.file"], size=10, data=b"", # data is empty here because load['data'] is overwritten id="abc", ) )

68ab9eeae6899b7ff14fb3489b012862d62653c6

test_cp.py

Fix more tests

salt

tests/unit/modules/test_cp.py

Python

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

in1d

def in1d(ar1, ar2, assume_unique=False, invert=False, kind=None): # Ravel both arrays, behavior for the first array could be different ar1 = np.asarray(ar1).ravel() ar2 = np.asarray(ar2).ravel() # Ensure that iteration through object arrays yields size-1 arrays if ar2.dtype == object: ar2 = ar2.reshape(-1, 1) # Convert booleans to uint8 so we can use the fast integer algorithm if ar1.dtype == bool: ar1 = ar1.view(np.uint8) if ar2.dtype == bool: ar2 = ar2.view(np.uint8) # Check if we can use a fast integer algorithm: integer_arrays = (np.issubdtype(ar1.dtype, np.integer) and np.issubdtype(ar2.dtype, np.integer)) if kind not in {None, 'sort', 'dictionary'}: raise ValueError( "Invalid kind: {0}. ".format(kind) + "Please use None, 'sort' or 'dictionary'.") if integer_arrays and kind in {None, 'dictionary'}: ar2_min = np.min(ar2) ar2_max = np.max(ar2) ar1_size = ar1.size ar2_size = ar2.size # Check for integer overflow with np.errstate(over='raise'): try: ar2_range = ar2_max - ar2_min # Optimal performance is for approximately # log10(size) > (log10(range) - 2.27) / 0.927. # However, here we set the requirement that # the intermediate array can only be 6x # the combined memory allocation of the original # arrays. # (see discussion on # https://github.com/numpy/numpy/pull/12065) below_memory_constraint = ( ar2_range <= 6 * (ar1_size + ar2_size) ) except FloatingPointError: below_memory_constraint = False # Use the fast integer algorithm if below_memory_constraint or kind == 'dictionary': if invert: outgoing_array = np.ones_like(ar1, dtype=bool) else: outgoing_array = np.zeros_like(ar1, dtype=bool) # Make elements 1 where the integer exists in ar2 if invert: isin_helper_ar = np.ones(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 0 else: isin_helper_ar = np.zeros(ar2_range + 1, dtype=bool) isin_helper_ar[ar2 - ar2_min] = 1 # Mask out elements we know won't work basic_mask = (ar1 <= ar2_max) & (ar1 >= ar2_min) outgoing_array[basic_mask] = isin_helper_ar[ar1[basic_mask] - ar2_min] return outgoing_array elif kind == 'dictionary': raise ValueError( "The 'dictionary' method is only " "supported for boolean or integer arrays. " "Please select 'sort' or None for kind." ) # Check if one of the arrays may contain arbitrary objects contains_object = ar1.dtype.hasobject or ar2.dtype.hasobject # This code is run when # a) the first condition is true, making the code significantly faster # b) the second condition is true (i.e. `ar1` or `ar2` may contain # arbitrary objects), since then sorting is not guaranteed to work if len(ar2) < 10 * len(ar1) ** 0.145 or contains_object: if invert: mask = np.ones(len(ar1), dtype=bool) for a in ar2: mask &= (ar1 != a) else: mask = np.zeros(len(ar1), dtype=bool) for a in ar2: mask |= (ar1 == a) return mask # Otherwise use sorting if not assume_unique: ar1, rev_idx = np.unique(ar1, return_inverse=True) ar2 = np.unique(ar2) ar = np.concatenate((ar1, ar2)) # We need this to be a stable sort, so always use 'mergesort' # here. The values from the first array should always come before # the values from the second array. order = ar.argsort(kind='mergesort') sar = ar[order] if invert: bool_ar = (sar[1:] != sar[:-1]) else: bool_ar = (sar[1:] == sar[:-1]) flag = np.concatenate((bool_ar, [invert])) ret = np.empty(ar.shape, dtype=bool) ret[order] = flag if assume_unique: return ret[:len(ar1)] else: return ret[rev_idx]

cde60cee195660f2dafb2993e609d66559525fe8

arraysetops.py

MAINT: Switch parameter name to 'kind' over 'method'

numpy

numpy/lib/arraysetops.py

Python

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

center_of_mass

def center_of_mass(mask, esp=1e-6): h, w = mask.shape grid_h = torch.arange(h, device=mask.device)[:, None] grid_w = torch.arange(w, device=mask.device) normalizer = mask.sum().float().clamp(min=esp) center_h = (mask * grid_h).sum() / normalizer center_w = (mask * grid_w).sum() / normalizer return center_h, center_w

fa77be290460e84ce7da975831cb7e687a419177

misc.py

Refactor package

mmdetection

mmdet/models/utils/misc.py

Python

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

streams

def streams(self, stream_types=None, sorting_excludes=None): try: ostreams = self._get_streams() if isinstance(ostreams, dict): ostreams = ostreams.items() # Flatten the iterator to a list so we can reuse it. if ostreams: ostreams = list(ostreams) except NoStreamsError: return {} except (OSError, ValueError) as err: raise PluginError(err) if not ostreams: return {} if stream_types is None: stream_types = self.default_stream_types(ostreams) # Add streams depending on stream type and priorities sorted_streams = sorted(iterate_streams(ostreams), key=partial(stream_type_priority, stream_types)) streams = {} for name, stream in sorted_streams: stream_type = type(stream).shortname() # Use * as wildcard to match other stream types if "*" not in stream_types and stream_type not in stream_types: continue # drop _alt from any stream names if name.endswith("_alt"): name = name[:-len("_alt")] existing = streams.get(name) if existing: existing_stream_type = type(existing).shortname() if existing_stream_type != stream_type: name = "{0}_{1}".format(name, stream_type) if name in streams: name = "{0}_alt".format(name) num_alts = len(list(filter(lambda n: n.startswith(name), streams.keys()))) # We shouldn't need more than 2 alt streams if num_alts >= 2: continue elif num_alts > 0: name = "{0}{1}".format(name, num_alts + 1) # Validate stream name and discard the stream if it's bad. match = re.match("([A-z0-9_+]+)", name) if match: name = match.group(1) else: self.logger.debug(f"The stream '{name}' has been ignored since it is badly named.") continue # Force lowercase name and replace space with underscore. streams[name.lower()] = stream # Create the best/worst synonyms

b72f23fd699de9730e9009ac319b84da68f15a73

plugin.py

docs: update API page, add type annotations

streamlink

src/streamlink/plugin/plugin.py

Python

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

insert_predictor_answer

def insert_predictor_answer(self, insert): model_interface = self.session.model_interface data_store = self.session.data_store select_data_query = insert.get('select_data_query') if isinstance(select_data_query, str) is False or len(select_data_query) == 0: self.packet( ErrPacket, err_code=ERR.ER_WRONG_ARGUMENTS, msg="'select_data_query' should not be empty" ).send() return models = model_interface.get_models() if insert['name'] in [x['name'] for x in models]: self.packet( ErrPacket, err_code=ERR.ER_WRONG_ARGUMENTS, msg=f"predictor with name '{insert['name']}'' already exists" ).send() return kwargs = {} if isinstance(insert.get('training_options'), str) \ and len(insert['training_options']) > 0: try: kwargs = json.loads(insert['training_options']) except Exception: self.packet( ErrPacket, err_code=ERR.ER_WRONG_ARGUMENTS, msg='training_options should be in valid JSON string' ).send() return integration = self.session.integration if isinstance(integration, str) is False or len(integration) == 0: self.packet( ErrPacket, err_code=ERR.ER_WRONG_ARGUMENTS, msg='select_data_query can be used only in query from database' ).send() return insert['select_data_query'] = insert['select_data_query'].replace(r"\'", "'") ds_name = data_store.get_vacant_name(insert['name']) ds = data_store.save_datasource(ds_name, integration, {'query': insert['select_data_query']}) insert['predict'] = [x.strip() for x in insert['predict'].split(',')] ds_data = data_store.get_datasource(ds_name) if ds_data is None: raise Exception(f"DataSource '{ds_name}' does not exists") ds_columns = [x['name'] for x in ds_data['columns']] for col in insert['predict']: if col not in ds_columns: data_store.delete_datasource(ds_name) raise Exception(f"Column '{col}' not exists") try: insert['predict'] = self._check_predict_columns(insert['predict'], ds_columns) except Exception: data_store.delete_datasource(ds_name) raise model_interface.learn( insert['name'], ds, insert['predict'], ds_data['id'], kwargs=kwargs, delete_ds_on_fail=True ) self.packet(OkPacket).send()

551205a18ac2ac19626f4e4ffb2ed88fcad705b9

mysql_proxy.py

fix

mindsdb

mindsdb/api/mysql/mysql_proxy/mysql_proxy.py

Python

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

_remove_long_seq

def _remove_long_seq(maxlen, seq, label): new_seq, new_label = [], [] for x, y in zip(seq, label): if len(x) < maxlen: new_seq.append(x) new_label.append(y) return new_seq, new_label @keras_export('keras.preprocessing.sequence.TimeseriesGenerator')

f1aa8b7d2a0c89591c5c42eca5b6f013114a7bbd

@keras_export('keras.preprocessing.sequence.TimeseriesGenerator')

sequence.py

Copy sequence utils from keras_preprocessing directly into core keras PiperOrigin-RevId: 424915569

keras

keras/preprocessing/sequence.py

Python

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

remove_xml_tags

def remove_xml_tags(buf): filtered = bytearray() in_tag = False prev = 0 buf = memoryview(buf).cast("c") for curr, buf_char in enumerate(buf): # Check if we're coming out of or entering an XML tag if buf_char == b">": prev = curr + 1 in_tag = False elif buf_char == b"<": if curr > prev and not in_tag: # Keep everything after last non-extended-ASCII, # non-alphabetic character filtered.extend(buf[prev:curr]) # Output a space to delimit stretch we kept filtered.extend(b" ") in_tag = True # If we're not in a tag... if not in_tag: # Keep everything after last non-extended-ASCII, non-alphabetic # character filtered.extend(buf[prev:]) return filtered

cd5a9683be69c86c8f3adcd13385a9bc5db198ec

charsetprober.py

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

pipenv

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

Python

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

test_rich_text_is_safe

def test_rich_text_is_safe(self): stream_block = blocks.StreamBlock( [ ( "paragraph", blocks.RichTextBlock(template="tests/jinja2/rich_text.html"), ) ] ) stream_value = stream_block.to_python( [ { "type": "paragraph", "value": '<p>Merry <a linktype="page" id="4">Christmas</a>!</p>', }, ] ) result = render_to_string( "tests/jinja2/stream.html", { "value": stream_value, }, ) self.assertIn( '<p>Merry <a href="/events/christmas/">Christmas</a>!</p>', result )

d10f15e55806c6944827d801cd9c2d53f5da4186

test_jinja2.py

Reformat with black

wagtail

wagtail/core/tests/test_jinja2.py

Python

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

getWindowsDLLVersion

def getWindowsDLLVersion(filename): # Get size needed for buffer (0 if no info) import ctypes.wintypes if type(filename) is unicode: GetFileVersionInfoSizeW = ctypes.windll.version.GetFileVersionInfoSizeW GetFileVersionInfoSizeW.argtypes = [ ctypes.wintypes.LPCWSTR, ctypes.wintypes.LPDWORD, ] GetFileVersionInfoSizeW.restype = ctypes.wintypes.HANDLE size = GetFileVersionInfoSizeW(filename, None) else: size = ctypes.windll.version.GetFileVersionInfoSizeA(filename, None) if not size: return (0, 0, 0, 0) # Create buffer res = ctypes.create_string_buffer(size) # Load file information into buffer res if type(filename) is unicode: # Python3 needs our help here. GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoW GetFileVersionInfo.argtypes = [ ctypes.wintypes.LPCWSTR, ctypes.wintypes.DWORD, ctypes.wintypes.DWORD, ctypes.wintypes.LPVOID, ] GetFileVersionInfo.restype = ctypes.wintypes.BOOL else: # Python2 just works. GetFileVersionInfo = ctypes.windll.version.GetFileVersionInfoA success = GetFileVersionInfo(filename, 0, size, res) # This cannot really fail anymore. assert success # Look for codepages VerQueryValueA = ctypes.windll.version.VerQueryValueA VerQueryValueA.argtypes = [ ctypes.wintypes.LPCVOID, ctypes.wintypes.LPCSTR, ctypes.wintypes.LPVOID, ctypes.POINTER(ctypes.c_uint32), ] VerQueryValueA.restype = ctypes.wintypes.BOOL file_info = ctypes.POINTER(VsFixedFileInfoStructure)() uLen = ctypes.c_uint32(ctypes.sizeof(file_info)) b = VerQueryValueA(res, br"\\", ctypes.byref(file_info), ctypes.byref(uLen)) if not b: return (0, 0, 0, 0) if file_info.contents.dwSignature != 0xFEEF04BD: return (0, 0, 0, 0) ms = file_info.contents.dwFileVersionMS ls = file_info.contents.dwFileVersionLS return (ms >> 16) & 0xFFFF, ms & 0xFFFF, (ls >> 16) & 0xFFFF, ls & 0xFFFF _readelf_usage = "The 'readelf' is used to analyse dependencies on ELF using systems and required to be found."

982929807fdc5838554cf302a2013a28e7707514

SharedLibraries.py

macOS: Avoid references to original install paths as library ids

Nuitka

nuitka/utils/SharedLibraries.py

Python

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

test_rollback_cursor_consistency

def test_rollback_cursor_consistency(self): con = sqlite.connect(":memory:") cur = con.cursor() cur.execute("create table test(x)") cur.execute("insert into test(x) values (5)") cur.execute("select 1 union select 2 union select 3") con.rollback() self.assertEqual(cur.fetchall(), [(1,), (2,), (3,)])

9d6a239a34a66e16188d76c23a3a770515ca44ca

test_transactions.py

bpo-44092: Don't reset statements/cursors before rollback (GH-26026) In SQLite versions pre 3.7.11, pending statements would block a rollback. This is no longer the case, so remove the workaround.

cpython

Lib/test/test_sqlite3/test_transactions.py

Python

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

is_package

def is_package(cls, fullname): return False load_module = classmethod(_load_module_shim)

8198943edd73a363c266633e1aa5b2a9e9c9f526

_bootstrap.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/importlib/_bootstrap.py

Python

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

get_ind_under_point

def get_ind_under_point(self, event): xy = self.pathpatch.get_path().vertices xyt = self.pathpatch.get_transform().transform(xy) # to display coords xt, yt = xyt[:, 0], xyt[:, 1] d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2) ind = d.argmin() return ind if d[ind] < self.epsilon else None

1068a6faa19767724437461bcfb88c6852ec435c

path_editor.py

Remove unnecessary np.{,as}array / astype calls. Quite often numpy will call asarray for us, saving us the need to call asarray explicitly. When we do call asarray (or array) ourselves, a dtype can directly be passed in, rather than immediately calling astype immediately after. Passing the dtype makes it unnecessary for asarray to infer the dtype of the passed-in container, and can also save an extra array allocation if asarray first has to allocate an array of a type and astype immediately has to allocate an array of another type.

matplotlib

examples/event_handling/path_editor.py

Python

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

round_filters

def round_filters(filters, global_params): multiplier = global_params.width_coefficient if not multiplier: return filters divisor = global_params.depth_divisor filters *= multiplier new_filters = int(filters + divisor / 2) // divisor * divisor if new_filters < 0.9 * filters: new_filters += divisor return int(new_filters)

6e607a0fa1cefbf0388dac86c84debf4781cec48

rec_efficientb3_pren.py

[Feature] Add PREN Scene Text Recognition Model(Accepted in CVPR2021) (#5563) * [Feature] add PREN scene text recognition model * [Patch] Optimize yml File * [Patch] Save Label/Pred Preprocess Time Cost * [BugFix] Modify Shape Conversion to Fit for Inference Model Exportion * [Patch] ? * [Patch] ? * 啥情况...

PaddleOCR

ppocr/modeling/backbones/rec_efficientb3_pren.py

Python

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

assert_lca_dicts_same

def assert_lca_dicts_same(self, d1, d2, G=None): if G is None: G = self.DG root_distance = self.root_distance else: roots = [n for n, deg in G.in_degree if deg == 0] assert len(roots) == 1 root_distance = nx.shortest_path_length(G, source=roots[0]) for a, b in ((min(pair), max(pair)) for pair in chain(d1, d2)): assert ( root_distance[get_pair(d1, a, b)] == root_distance[get_pair(d2, a, b)] )

b2f91c34a23058dd70b41784af0d87890216026a

test_lowest_common_ancestors.py

Naive lowest common ancestor implementation (#5736) * Add naive lca methods * Naive algorithm implementation for LCA * Modify naive lca functions * Correct parameters of nx.ancestors * Update lowest_common_ancestors.py * Parametrize tests * Apply suggestions from code review Co-authored-by: Dan Schult <dschult@colgate.edu> * Yield instead of append * Tests for naive lca * Correct test cases for naive lca algorithms * Apply suggestions from code review Co-authored-by: Mridul Seth <mail@mriduls.com> * Fix function name -when calling * Make requested changes * Inlining _get_a_lowest_common_ancestor Co-authored-by: dtuncturk <dilaramemis@sabanciuniv.edu> Co-authored-by: Dan Schult <dschult@colgate.edu> Co-authored-by: Mridul Seth <mail@mriduls.com>

networkx

networkx/algorithms/tests/test_lowest_common_ancestors.py

Python

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

_prepare_socket_file

def _prepare_socket_file(self, socket_path, default_prefix): result = socket_path is_mac = sys.platform.startswith("darwin") if sys.platform == "win32": if socket_path is None: result = f"tcp://{self._localhost}" f":{self._get_unused_port()}" else: if socket_path is None: result = self._make_inc_temp( prefix=default_prefix, directory_name=self._sockets_dir ) else: try_to_create_directory(os.path.dirname(socket_path)) # Check socket path length to make sure it's short enough maxlen = (104 if is_mac else 108) - 1 # sockaddr_un->sun_path if len(result.split("://", 1)[-1].encode("utf-8")) > maxlen: raise OSError( "AF_UNIX path length cannot exceed " "{} bytes: {!r}".format(maxlen, result) ) return result

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

node.py

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

ray

python/ray/node.py

Python

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

test_user_message_already_unlinked

def test_user_message_already_unlinked(self): IdentityProvider.objects.create(type="slack", external_id="TXXXXXXX1", config={}) responses.add(responses.POST, "https://slack.com/api/chat.postMessage", json={"ok": True}) resp = self.post_webhook(event_data=json.loads(MESSAGE_IM_EVENT_UNLINK)) assert resp.status_code == 200, resp.content request = responses.calls[0].request assert request.headers["Authorization"] == "Bearer xoxb-xxxxxxxxx-xxxxxxxxxx-xxxxxxxxxxxx" data = json.loads(request.body) assert "You do not have a linked identity to unlink" in get_response_text(data)

b7d894b56953153cf33008ae7d33e1e41b175eb7

test_message_im.py

ref(tests): Split up large files (#31828)

sentry

tests/sentry/integrations/slack/endpoints/events/test_message_im.py

Python

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

test_subscribe_to_stream_post_policy_moderators_stream

def test_subscribe_to_stream_post_policy_moderators_stream(self) -> None: member = self.example_user("AARON") stream = self.make_stream("stream1") # Make sure that we are testing this with full member which is just below the moderator # in the role hierarchy. self.assertFalse(member.is_provisional_member) do_change_stream_post_policy( stream, Stream.STREAM_POST_POLICY_MODERATORS, acting_user=member ) result = self.common_subscribe_to_streams(member, ["stream1"]) self.assert_json_success(result) json = result.json() self.assertEqual(json["subscribed"], {member.email: ["stream1"]}) self.assertEqual(json["already_subscribed"], {})

c30458e1740c7878e436037f61431884e54b349d

test_subs.py

streams: Add notifications for posting policy changes. An explanatory note on the changes in zulip.yaml and curl_param_value_generators is warranted here. In our automated tests for our curl examples, the test for the API endpoint that changes the posting permissions of a stream comes before our existing curl test for adding message reactions. Since there is an extra notification message due to the change in posting permissions, the message IDs used in tests that come after need to be incremented by 1. This is a part of #20289.

zulip

zerver/tests/test_subs.py

Python

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

test_overwrite_storage_path

def test_overwrite_storage_path(self): call_command("document_retagger", "--storage_path", "--overwrite") d_first, d_second, d_unrelated, d_auto = self.get_updated_docs() self.assertEqual(d_first.storage_path, self.sp2) self.assertEqual(d_auto.storage_path, self.sp1) self.assertIsNone(d_second.storage_path) self.assertEqual(d_unrelated.storage_path, self.sp2)

c8e838e3a0828e82efac1fd93ebb9aba6a000ff8

test_management_retagger.py

Adds the storage paths to the re-tagger command

paperless-ngx

src/documents/tests/test_management_retagger.py

Python

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

hashkey

def hashkey(cls, *args, **kwargs): return cachetools.keys.hashkey(f"<{cls.__name__}>", *args, **kwargs)

21972c91dd2b52cd206bf71ea038ab0e1f478b32

settings.py

add lock to cachetools usage * We observed daphne giving tracebacks when accessing logging settings. Originally, configure tower in tower settings was no a suspect because daphne is not multi-process. We've had issues with configure tower in tower settings and multi-process before. We later learned that Daphne is multi-threaded. Configure tower in tower was back to being a suspect. We constructed a minimal reproducer to show that multiple threads accessing settings can cause the same traceback that we saw in daphne. See https://gist.github.com/chrismeyersfsu/7aa4bdcf76e435efd617cb078c64d413 for that recreator. These fixes stop the recreation.

awx

awx/conf/settings.py

Python

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

link_entity

def link_entity(props): id_ = props.get("id") link_props = {} if id_ is not None: link_props["linktype"] = "page" link_props["id"] = id_ else: link_props["href"] = check_url(props.get("url")) return DOM.create_element("a", link_props, props["children"])

d10f15e55806c6944827d801cd9c2d53f5da4186

contentstate.py

Reformat with black

wagtail

wagtail/admin/rich_text/converters/contentstate.py

Python

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

_suggest_semantic_version

def _suggest_semantic_version(s): result = s.strip().lower() for pat, repl in _REPLACEMENTS: result = pat.sub(repl, result) if not result: result = '0.0.0' # Now look for numeric prefix, and separate it out from # the rest. #import pdb; pdb.set_trace() m = _NUMERIC_PREFIX.match(result) if not m: prefix = '0.0.0' suffix = result else: prefix = m.groups()[0].split('.') prefix = [int(i) for i in prefix] while len(prefix) < 3: prefix.append(0) if len(prefix) == 3: suffix = result[m.end():] else: suffix = '.'.join([str(i) for i in prefix[3:]]) + result[m.end():] prefix = prefix[:3] prefix = '.'.join([str(i) for i in prefix]) suffix = suffix.strip() if suffix: #import pdb; pdb.set_trace() # massage the suffix. for pat, repl in _SUFFIX_REPLACEMENTS: suffix = pat.sub(repl, suffix) if not suffix: result = prefix else: sep = '-' if 'dev' in suffix else '+' result = prefix + sep + suffix if not is_semver(result): result = None return result

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

version.py

upd; format

transferlearning

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

Python

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

test_previewing_subprocess_deployment

def test_previewing_subprocess_deployment(): result = invoke_and_assert( [ "deployment", "preview", "./tests/deployment_test_files/single_deployment.py", ], expected_output_contains="prefect.engine", ) assert result.stdout.endswith("\n") preview = result.stdout.strip() # spot-check some variables and the command-line assert "\nPREFECT_TEST_MODE=True \\" in preview assert "\nPREFECT_LOGGING_LEVEL=DEBUG \\" in preview assert preview.endswith(" -m prefect.engine 00000000000000000000000000000000")

5afded9fe6724d9e336f59792ee1d60656a2d94d

test_deployment_preview.py

Add a CLI command to preview how a FlowRun will appear in any FlowRunner's execution environment (PrefectHQ/orion#1971) Co-authored-by: Terrence Dorsey <terrence@prefect.io> Co-authored-by: Michael Adkins <madkinszane@gmail.com>

prefect

tests/cli/test_deployment_preview.py

Python

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

completion_item_yank

def completion_item_yank(self, sel=False): text = self._cmd.selectedText() if not text: index = self.currentIndex() if not index.isValid(): raise cmdutils.CommandError("No item selected!") text = self._model().data(index) if not utils.supports_selection(): sel = False utils.set_clipboard(text, selection=sel)

a20bb67a878b2e68abf8268c1b0a27f018d01352

completionwidget.py

mypy: Upgrade to PyQt5-stubs 5.15.6.0 For some unknown reason, those new stubs cause a *lot* of things now to be checked by mypy which formerly probably got skipped due to Any being implied somewhere. The stubs themselves mainly improved, with a couple of regressions too. In total, there were some 337 (!) new mypy errors. This commit fixes almost all of them, and the next commit improves a fix to get things down to 0 errors again. Overview of the changes: ==== qutebrowser/app.py - Drop type ignore due to improved stubs. ==== qutebrowser/browser/browsertab.py - Specify the type of _widget members more closely than just QWidget. This is debatable: I suppose the abstract stuff shouldn't need to know anything about the concrete backends at all. But it seems like we cut some corners when initially implementing things, and put some code in browsertab.py just because the APIs of both backends happened to be compatible. Perhaps something to reconsider once we drop QtWebKit and hopefully implement a dummy backend. - Add an additional assertion in AbstractAction.run_string. This is already covered by the isinstance(member, self.action_base) above it, but that's too dynamic for mypy to understand. - Fix the return type of AbstractScroller.pos_px, which is a QPoint (with x and y components), not a single int. - Fix the return type of AbstractScroller.pos_perc, which is a Tuple (with x and y components), not a single int. - Fix the argument types of AbstractScroller.to_perc, as it's possible to pass fractional percentages too. - Specify the type for AbstractHistoryPrivate._history. See above (_widget) re this being debatable. - Fix the return type of AbstractTabPrivate.event_target(), which can be None (see #3888). - Fix the return type of AbstractTabPrivate.run_js_sync, which is Any (the JS return value), not None. - Fix the argument type for AbstractTabPrivate.toggle_inspector: position can be None to use the last used position. - Declare the type of sub-objects of AbstractTab. - Fix the return value of AbstractTab.icon(), which is the QIcon, not None. ==== qutebrowser/browser/commands.py - Make sure the active window is a MainWindow (with a .win_id attribute). ==== qutebrowser/browser/downloadview.py - Add _model() which makes sure that self.model() is a DownloadModel, not None or any other model. This is needed because other methods access a variety of custom attributes on it, e.g. last_index(). ==== qutebrowser/browser/greasemonkey.py - Add an ignore for AbstractDownload.requested_url which we patch onto the downloads. Probably would be nicer to add it as a proper attribute which always gets set by the DownloadManager. ==== qutebrowser/browser/hints.py - Remove type ignores for QUrl.toString(). - Add a new type ignore for combining different URL flags (which works, but is not exactly type safe... still probably a regression in the stubs). - Make sure the things we get back from self._get_keyparser are what we actually expect. Probably should introduce a TypedDict (and/or overloads for _get_keyparser with typing.Literal) to teach mypy about the exact return value. See #7098. This is needed because we access Hint/NormalKeyParser-specific attributes such as .set_inhibited_timout() or .update_bindings(). ==== qutebrowser/browser/inspector.py - Similar changes than in browsertab.py to make some types where we share API (e.g. .setPage()) more concrete. Didn't work out unfortunately, see next commit. ==== qutebrowser/browser/network/pac.py - Remove now unneeded type ignore for signal. ==== qutebrowser/browser/qtnetworkdownloads.py - Make sure that downloads is a qtnetworkdownloads.DownloadItem (rather than an AbstractDownload), so that we can call ._uses_nam() on it. ==== qutebrowser/browser/qutescheme.py - Remove now unneeded type ignore for QUrl flags. ==== qutebrowser/browser/urlmarks.py - Specify the type of UrlMarkManager._lineparser, as those only get initialized in _init_lineparser of subclasses, so mypy doesn't know it's supposed to exist. ==== qutebrowser/browser/webelem.py - New casts to turn single KeyboardModifier (enum) entries into KeyboardModifiers (flags). Might not be needed anymore with Qt 6. - With that, casting the final value is now unneeded. ==== qutebrowser/browser/webengine/notification.py - Remove now unneeded type ignore for signal. - Make sure the self.sender() we get in HerbeNotificationAdapter._on_finished() is a QProcess, not just any QObject. ==== qutebrowser/browser/webengine/webenginedownloads.py - Remove now unneeded type ignores for signals. ==== qutebrowser/browser/webengine/webengineelem.py - Specify the type of WebEngineElement._tab. - Remove now unneeded type ignore for mixed flags. ==== qutebrowser/browser/webengine/webengineinspector.py - See changes to inspector.py and next commit. - Remove now unneeded type ignore for signal. ==== qutebrowser/browser/webengine/webenginequtescheme.py - Remove now unneeded type ignore for mixed flags. ==== qutebrowser/browser/webengine/webenginesettings.py - Ignore access of .setter attribute which we patch onto QWebEngineProfile. Would be nice to have a subclass or wrapper-class instead. ==== qutebrowser/browser/webengine/webenginetab.py - Specified the type of _widget members more closely than just QWidget. See browsertab.py changes for details. - Remove some now-unneeded type ignores for creating FindFlags. - Specify more concrete types for WebEngineTab members where we actually need to access WebEngine-specific attributes. - Make sure the page we get is our custom WebEnginePage subclass, not just any QWebEnginePage. This is needed because we access custom attributes on it. ==== qutebrowser/browser/webengine/webview.py - Make sure the page we get is our custom WebEnginePage subclass, not just any QWebEnginePage. This is needed because we access custom attributes on it. ==== qutebrowser/browser/webkit/network/networkreply.py - Remove now unneeded type ignores for signals. ==== qutebrowser/browser/webkit/webkitinspector.py - See changes to inspector.py and next commit. ==== qutebrowser/browser/webkit/webkittab.py - Specify the type of _widget members more closely than just QWidget. See browsertab.py changes for details. - Add a type ignore for WebKitAction because our workaround needs to treat them as ints (which is allowed by PyQt, even if not type-safe). - Add new ignores for findText calls: The text is a QString and can be None; the flags are valid despite mypy thinking they aren't (stubs regression?). - Specify the type for WebKitHistoryPrivate._history, because we access WebKit-specific attributes. See above (_widget) re this being debatable. - Make mypy aware that .currentFrame() and .frameAt() can return None (stubs regression?). - Make sure the .page() and .page().networkAccessManager() are our subclasses rather than the more generic QtWebKit objects, as we use custom attributes. - Add new type ignores for signals (stubs regression!) ==== qutebrowser/browser/webkit/webpage.py - Make sure the .networkAccessManager() is our subclass rather than the more generic QtWebKit object, as we use custom attributes. - Replace a cast by a type ignore. The cast didn't work anymore. ==== qutebrowser/browser/webkit/webview.py - Make sure the .page() is our subclass rather than the more generic QtWebKit object, as we use custom attributes. ==== qutebrowser/commands/userscripts.py - Remove now unneeded type ignore for signal. ==== qutebrowser/completion/completer.py - Add a new _completion() getter (which ensures it actually gets the completion view) rather than accessing the .parent() directly (which could be any QObject). ==== qutebrowser/completion/completiondelegate.py - Make sure self.parent() is a CompletionView (no helper method as there is only one instance). - Remove a now-unneeded type ignore for adding QSizes. ==== qutebrowser/completion/completionwidget.py - Add a ._model() getter which ensures that we get a CompletionModel (with custom attributes) rather than Qt's .model() which can be any QAbstractItemModel (or None). - Removed a now-unneeded type ignore for OR-ing flags. ==== qutebrowser/completion/models/completionmodel.py - Remove now unneeded type ignores for signals. - Ignore a complaint about .set_pattern() not being defined. Completion categories don't share any common parent class, so it would be good to introduce a typing.Protocol for this. See #7098. ==== qutebrowser/components/misccommands.py - Removed a now-unneeded type ignore for OR-ing flags. ==== qutebrowser/components/readlinecommands.py - Make sure QApplication.instance() is a QApplication (and not just a QCoreApplication). This includes the former "not None" check. ==== qutebrowser/components/scrollcommands.py - Add basic annotation for "funcs" dict. Could have a callable protocol to specify it needs a count kwarg, see #7098. ==== qutebrowser/config/stylesheet.py - Correctly specify that stylesheet apply to QWidgets, not any QObject. - Ignore an attr-defined for obj.STYLESHEET. Perhaps could somehow teach mypy about this with overloads and protocols (stylesheet for set_register being None => STYLESHEET needs to be defined, otherwise anything goes), but perhaps not worth the troble. See #7098. ==== qutebrowser/keyinput/keyutils.py - Remove some now-unneeded type ignores and add a cast for using a single enum value as flags. Might need to look at this again with Qt 6 support. ==== qutebrowser/keyinput/modeman.py - Add a FIXME for using a TypedDict, see comments for hints.py above. ==== qutebrowser/mainwindow/mainwindow.py - Remove now-unneeded type ignores for calling with OR-ed flags. - Improve where we cast from WindowType to WindowFlags, no int needed - Use new .tab_bar() getter, see below. ==== qutebrowser/mainwindow/prompt.py - Remove now-unneeded type ignores for calling with OR-ed flags. ==== qutebrowser/mainwindow/statusbar/bar.py - Adjust type ignores around @pyqtProperty. The fact one is still needed seems like a stub regression. ==== qutebrowser/mainwindow/statusbar/command.py - Fix type for setText() override (from QLineEdit): text can be None (QString in C++). ==== qutebrowser/mainwindow/statusbar/url.py - Adjust type ignores around @pyqtProperty. The fact one is still needed seems like a stub regression. ==== qutebrowser/mainwindow/tabbedbrowser.py - Specify that TabDeque manages browser tabs, not any QWidgets. It accesses AbstractTab-specific attributes. - Make sure that the .tabBar() we get is a tabwidget.TabBar, as we access .maybe_hide. - Fix the annotations for stored marks: Scroll positions are a QPoint, not int. - Add _current_tab() and _tab_by_idx() wrappers for .currentWidget() and .widget(), which ensures that the return values are valid AbstractTabs (or None for _tab_by_idx). This is needed because we access AbstractTab-specific attributes. - For some places, where the tab can be None, continue using .currentTab() but add asserts. - Remove some now-unneeded [unreachable] ignores, as mypy knows about the None possibility now. ==== qutebrowser/mainwindow/tabwidget.py - Add new tab_bar() and _tab_by_idx() helpers which check that the .tabBar() and .widget() are of type TabBar and AbstractTab, respectively. - Add additional assertions where we expect ._tab_by_idx() to never be None. - Remove dead code in get_tab_fields for handling a None y scroll position. I was unable to find any place in the code where this could be set to None. - Remove some now-unneeded type ignores and casts, as mypy now knows that _type_by_idx() could be None. - Work around a strange instance where mypy complains about not being able to find the type of TabBar.drag_in_progress from TabWidget._toggle_visibility, despite it clearly being shown as a bool *inside* that class without any annotation. - Add a ._tab_widget() getter in TabBar which ensures that the .parent() is in fact a TabWidget. ==== qutebrowser/misc/crashsignal.py - Remove now unneeded type ignores for signals. ==== qutebrowser/misc/editor.py - Remove now unneeded type ignores for signals. ==== qutebrowser/misc/ipc.py - Remove now unneeded type ignores for signals. - Add new type ignores for .error() which is both a signal and a getter (stub regression?). Won't be relevant for Qt 6 anymore, as the signal was renamed to errorOccurred in 5.15. ==== qutebrowser/misc/objects.py - Make sure mypy knows that objects.app is our custom Application (with custom attributes) rather than any QApplication. ==== qutebrowser/utils/objreg.py - Ignore attr-defined for .win_id attributes. Maybe could add a typing.Protocol, but ideally, the whole objreg stuff should die one day anyways. ==== tests/unit/completion/test_completer.py - Make CompletionWidgetStub inherit from CompletionView so that it passes the new isinstance() asserts in completer.py (see above).

qutebrowser

qutebrowser/completion/completionwidget.py

Python

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

get_index_and_columns

def _get_index_and_columns(df): return len(df.index), len(df.columns) @ray.remote(num_returns=4)

e7cb2e82f8b9c7a68f82abdd3b6011d661230b7e

@ray.remote(num_returns=4)

partition.py

REFACTOR-#4251: define public interfaces in `modin.core.execution.ray` module (#3868) Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>

modin

modin/core/execution/ray/implementations/pandas_on_ray/partitioning/partition.py

Python

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

test_extra_tags

def test_extra_tags(self): for extra_tags in ['', None, 'some tags']: with self.subTest(extra_tags=extra_tags): self.assertEqual( self.encode_decode('message', extra_tags=extra_tags).extra_tags, extra_tags, )

efb4478e484ae61c5fc23563d4e9df1f8f49df49

test_cookie.py

Fixed #33458 -- Fixed encoding of messages with empty string as extra_tags.

django

tests/messages_tests/test_cookie.py

Python

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

compile_helper

def compile_helper(): import os import subprocess path = os.path.abspath(os.path.dirname(__file__)) ret = subprocess.run(['make', '-C', path]) if ret.returncode != 0: print("Making C++ dataset helpers module failed, exiting.") import sys sys.exit(1)

1d930169e118c325c03343b6acd7d9c05eab1f85

dataset_utils.py

[Pre-training] Optional for nsp task, support multi-datasets in ERNIE-1.0 pre-training (#1621) * add no nsp training. * support for multi-dataset * fix test sample nums.

PaddleNLP

examples/language_model/data_tools/dataset_utils.py

Python

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

variable

def variable(value, dtype=None, name=None, constraint=None): if dtype is None: dtype = floatx() if hasattr(value, "tocoo"): sparse_coo = value.tocoo() indices = np.concatenate( ( np.expand_dims(sparse_coo.row, 1), np.expand_dims(sparse_coo.col, 1), ), 1, ) v = tf.SparseTensor( indices=indices, values=sparse_coo.data, dense_shape=sparse_coo.shape, ) v._keras_shape = sparse_coo.shape return v v = tf.Variable( value, dtype=tf.as_dtype(dtype), name=name, constraint=constraint ) if isinstance(value, np.ndarray): v._keras_shape = value.shape elif hasattr(value, "shape"): v._keras_shape = int_shape(value) track_variable(v) return v

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/backend.py

Python

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

test_conversation_chain_errors_bad_variable

def test_conversation_chain_errors_bad_variable() -> None: llm = FakeLLM() prompt = PromptTemplate(input_variables=["foo"], template="{foo}") memory = ConversationBufferMemory(dynamic_key="foo") with pytest.raises(ValueError): ConversationChain(llm=llm, prompt=prompt, memory=memory, input_key="foo") @pytest.mark.parametrize( "memory", [ ConversationBufferMemory(dynamic_key="baz"), ConversationSummaryMemory(llm=FakeLLM(), dynamic_key="baz"), ], )

a408ed3ea39dfa47e8b522a9e153b259f25df54e

@pytest.mark.parametrize( "memory", [ ConversationBufferMemory(dynamic_key="baz"), ConversationSummaryMemory(llm=FakeLLM(), dynamic_key="baz"), ], )

test_conversation.py

Samantha/add conversation chain (#166) Add MemoryChain and ConversationChain as chains that take a docstore in addition to the prompt, and use the docstore to stuff context into the prompt. This can be used to have an ongoing conversation with a chatbot. Probably needs a bit of refactoring for code quality Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>

langchain

tests/unit_tests/chains/test_conversation.py

Python

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

register

async def register(cls): for field in cls.__fields__.values(): if Block.is_block_class(field.type_): await field.type_.register() if get_origin(field.type_) is Union: for type in get_args(field.type_): if Block.is_block_class(type): await type.register()

1c74cd08aaa8eb7759490fc156abb18f916b0764

core.py

Renames method from install to register

prefect

src/prefect/blocks/core.py

Python

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

get_input

def get_input(self, field_name, **kwargs): if self.credential_type.kind != 'external' and field_name in self.dynamic_input_fields: return self._get_dynamic_input(field_name) if field_name in self.credential_type.secret_fields: try: return decrypt_field(self, field_name) except AttributeError: for field in self.credential_type.inputs.get('fields', []): if field['id'] == field_name and 'default' in field: return field['default'] if 'default' in kwargs: return kwargs['default'] raise AttributeError(field_name) if field_name in self.inputs: return self.inputs[field_name] if 'default' in kwargs: return kwargs['default'] for field in self.credential_type.inputs.get('fields', []): if field['id'] == field_name and 'default' in field: return field['default'] raise AttributeError(field_name)

871175f97fb177ad3c6d6f150e2b685dc11893ce

__init__.py

Sending field_name in AttributeError

awx

awx/main/models/credential/__init__.py

Python

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

synchronized_update_sequences

def synchronized_update_sequences(self) -> tuple[str, str]: return ( self._synchronized_update_start_sequence(), self._synchronized_update_end_sequence(), )

d14659c1a3760eade2dd3479b66eb8b2e7711db0

_terminal_features.py

[terminal buffering] Add support for the "mode 2026" That task is definitely way more complicated that it seemed to be 😅

textual

src/textual/_terminal_features.py

Python

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

do_for

def do_for(parser, token): bits = token.split_contents() if len(bits) < 4: raise TemplateSyntaxError( "'for' statements should have at least four words: %s" % token.contents ) is_reversed = bits[-1] == 'reversed' in_index = -3 if is_reversed else -2 if bits[in_index] != 'in': raise TemplateSyntaxError("'for' statements should use the format" " 'for x in y': %s" % token.contents) invalid_chars = frozenset((' ', '"', "'", FILTER_SEPARATOR)) loopvars = re.split(r' *, *', ' '.join(bits[1:in_index])) for var in loopvars: if not var or not invalid_chars.isdisjoint(var): raise TemplateSyntaxError( "'for' tag received an invalid argument: %s" % token.contents ) sequence = parser.compile_filter(bits[in_index + 1]) nodelist_loop = parser.parse(('empty', 'endfor',)) token = parser.next_token() if token.contents == 'empty': nodelist_empty = parser.parse(('endfor',)) parser.delete_first_token() else: nodelist_empty = None return ForNode(loopvars, sequence, is_reversed, nodelist_loop, nodelist_empty)

c5cd8783825b5f6384417dac5f3889b4210b7d08

defaulttags.py

Refs #33476 -- Refactored problematic code before reformatting by Black. In these cases Black produces unexpected results, e.g. def make_random_password( self, length=10, allowed_chars='abcdefghjkmnpqrstuvwxyz' 'ABCDEFGHJKLMNPQRSTUVWXYZ' '23456789', ): or cursor.execute(""" SELECT ... """, [table name], )

django

django/template/defaulttags.py

Python

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

set_global_relative_scale_factor

def set_global_relative_scale_factor(self, scale_factor, reference_quantity): from sympy.physics.units import UnitSystem scale_factor = sympify(scale_factor) if isinstance(scale_factor, Prefix): self._is_prefixed = True # replace all prefixes by their ratio to canonical units: scale_factor = scale_factor.replace( lambda x: isinstance(x, Prefix), lambda x: x.scale_factor ) scale_factor = sympify(scale_factor) UnitSystem._quantity_scale_factors_global[self] = (scale_factor, reference_quantity) UnitSystem._quantity_dimensional_equivalence_map_global[self] = reference_quantity

40a89803dbe877edc8ab6672819715f959273e60

quantities.py

feat(physics.units): add `is_prefixed` property to `Quantity`

sympy

sympy/physics/units/quantities.py

Python

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

validate_expense_against_budget

def validate_expense_against_budget(args): args = frappe._dict(args) if args.get("company") and not args.fiscal_year: args.fiscal_year = get_fiscal_year(args.get("posting_date"), company=args.get("company"))[0] frappe.flags.exception_approver_role = frappe.get_cached_value( "Company", args.get("company"), "exception_budget_approver_role" ) if not args.account: args.account = args.get("expense_account") if not (args.get("account") and args.get("cost_center")) and args.item_code: args.cost_center, args.account = get_item_details(args) if not args.account: return for budget_against in ["project", "cost_center"] + get_accounting_dimensions(): if ( args.get(budget_against) and args.account and frappe.db.get_value("Account", {"name": args.account, "root_type": "Expense"}) ): doctype = frappe.unscrub(budget_against) if frappe.get_cached_value("DocType", doctype, "is_tree"): lft, rgt = frappe.db.get_value(doctype, args.get(budget_against), ["lft", "rgt"]) condition = % ( doctype, lft, rgt, budget_against, ) # nosec args.is_tree = True else: condition = "and b.%s=%s" % (budget_against, frappe.db.escape(args.get(budget_against))) args.is_tree = False args.budget_against_field = budget_against args.budget_against_doctype = doctype budget_records = frappe.db.sql( .format( condition=condition, budget_against_field=budget_against ), (args.fiscal_year, args.account), as_dict=True, ) # nosec if budget_records: validate_budget_records(args, budget_records)

494bd9ef78313436f0424b918f200dab8fc7c20b

budget.py

style: format code with black

erpnext

erpnext/accounts/doctype/budget/budget.py

Python

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

load_macros

def load_macros(self, version): vsbase = r"Software\Microsoft\VisualStudio\%0.1f" % version self.set_macro("VCInstallDir", vsbase + r"\Setup\VC", "productdir") self.set_macro("VSInstallDir", vsbase + r"\Setup\VS", "productdir") net = r"Software\Microsoft\.NETFramework" self.set_macro("FrameworkDir", net, "installroot") try: if version > 7.0: self.set_macro("FrameworkSDKDir", net, "sdkinstallrootv1.1") else: self.set_macro("FrameworkSDKDir", net, "sdkinstallroot") except KeyError as exc: # raise DistutilsPlatformError( ) p = r"Software\Microsoft\NET Framework Setup\Product" for base in HKEYS: try: h = RegOpenKeyEx(base, p) except RegError: continue key = RegEnumKey(h, 0) d = read_values(base, r"%s\%s" % (p, key)) self.macros["$(FrameworkVersion)"] = d["version"]

8198943edd73a363c266633e1aa5b2a9e9c9f526

msvccompiler.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/msvccompiler.py

Python

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

samestat

def samestat(s1, s2): return (s1.st_ino == s2.st_ino and s1.st_dev == s2.st_dev) # Are two filenames really pointing to the same file?

8198943edd73a363c266633e1aa5b2a9e9c9f526

genericpath.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/genericpath.py

Python

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

batch

def batch(_func=None, max_batch_size=10, batch_wait_timeout_s=0.0): # `_func` will be None in the case when the decorator is parametrized. # See the comment at the end of this function for a detailed explanation. if _func is not None: if not callable(_func): raise TypeError( "@serve.batch can only be used to decorate functions or methods." ) if not iscoroutinefunction(_func): raise TypeError("Functions decorated with @serve.batch must be 'async def'") if not isinstance(max_batch_size, int): if isinstance(max_batch_size, float) and max_batch_size.is_integer(): max_batch_size = int(max_batch_size) else: raise TypeError("max_batch_size must be integer >= 1") if max_batch_size < 1: raise ValueError("max_batch_size must be an integer >= 1") if not isinstance(batch_wait_timeout_s, (float, int)): raise TypeError("batch_wait_timeout_s must be a float >= 0") if batch_wait_timeout_s < 0: raise ValueError("batch_wait_timeout_s must be a float >= 0")

e5a8b1dd55817305ac85237cd99d8b6ed23df294

batching.py

[Serve] Add API Annotations And Move to _private (#27058)

ray

python/ray/serve/batching.py

Python

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

convert_example

def convert_example(example, tokenizer, max_seq_length=512, is_test=False): text_a = example['text_a'] text_b = example.get('text_b', None) text_a = _tokenize_special_chars(_normalize(text_a)) if text_b is not None: text_b = _tokenize_special_chars(_normalize(text_b)) encoded_inputs = tokenizer( text=text_a, text_pair=text_b, max_seq_len=max_seq_length, return_position_ids=True) input_ids = encoded_inputs['input_ids'] token_type_ids = encoded_inputs['token_type_ids'] position_ids = encoded_inputs['position_ids'] if is_test: return input_ids, token_type_ids, position_ids label = np.array([example['label']], dtype='int64') return input_ids, token_type_ids, position_ids, label

15f0aa8f4515ae6cf2ee3ef71f90d533bc9e61b2

utils.py

[ehealth] add sequence classification example

PaddleNLP

examples/biomedical/cblue/sequence_classification/utils.py

Python

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

accepted_pairs

def accepted_pairs(self) -> List[Dict[str, Any]]: final = [] for pair, info in self._cached_pairs.items(): if (info.expectancy > float(self.edge_config.get('minimum_expectancy', 0.2)) and info.winrate > float(self.edge_config.get('minimum_winrate', 0.60))): final.append({ 'Pair': pair, 'Winrate': info.winrate, 'Expectancy': info.expectancy, 'Stoploss': info.stoploss, }) return final

6024fa482e1b09bae8e85b3afc9fc58e483c1512

edge_positioning.py

Use brackets to break IF lines

freqtrade

freqtrade/edge/edge_positioning.py

Python

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

get_remote_url

def get_remote_url(cls, location): # type: (str) -> str raise NotImplementedError

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

versioncontrol.py

upd; format

transferlearning

.venv/lib/python3.8/site-packages/pip/_internal/vcs/versioncontrol.py

Python

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

answer_drop_tables

def answer_drop_tables(self, statement): if statement.if_exists is False: for table in statement.tables: if len(table.parts) > 1: db_name = table.parts[0] else: db_name = self.session.database if db_name not in ['files', 'mindsdb']: raise SqlApiException(f"Cannot delete a table from database '{db_name}'") table_name = table.parts[-1] dn = self.session.datahub[db_name] if dn.has_table(table_name) is False: raise SqlApiException(f"Cannot delete a table from database '{db_name}': table does not exists") for table in statement.tables: if len(table.parts) > 1: db_name = table.parts[0] else: db_name = self.session.database if db_name not in ['files', 'mindsdb']: raise SqlApiException(f"Cannot delete a table from database '{db_name}'") table_name = table.parts[-1] dn = self.session.datahub[db_name] if dn.has_table(table_name): if db_name == 'mindsdb': self.session.datahub['mindsdb'].delete_predictor(table_name) elif db_name == 'files': self.session.data_store.delete_file(table_name) return SQLAnswer(ANSWER_TYPE.OK)

01b47406a29d17781356badb20f49f2fdc24d00e

mysql_proxy.py

'drop table' query

mindsdb

mindsdb/api/mysql/mysql_proxy/mysql_proxy.py

Python

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

validate

def validate(self, num_steps=None, profile=False, reduce_results=True, info=None): worker_stats = self.worker_group.validate( num_steps=num_steps, profile=profile, info=info ) if reduce_results: return self._process_stats(worker_stats) else: return worker_stats

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

torch_trainer.py

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

ray

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

Python

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

_Net_set_input_arrays

def _Net_set_input_arrays(self, data, labels): if labels.ndim == 1: labels = np.ascontiguousarray(labels[:, np.newaxis, np.newaxis, np.newaxis]) return self._set_input_arrays(data, labels)

cc4d0564756ca067516f71718a3d135996525909

pycaffe.py

Balanced joint maximum mean discrepancy for deep transfer learning

transferlearning

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

Python

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

test_multi_trial_reuse

def test_multi_trial_reuse(ray_start_4_cpus_extra): os.environ["TUNE_MAX_PENDING_TRIALS_PG"] = "2" register_trainable("foo2", MyResettableClass) # We sleep here for one second so that the third actor # does not finish training before the fourth can be scheduled. # This helps ensure that both remote runners are re-used and # not just one. [trial1, trial2, trial3, trial4] = tune.run( "foo2", config={ "message": tune.grid_search(["First", "Second", "Third", "Fourth"]), "id": -1, "sleep": 2, }, reuse_actors=True, resources_per_trial={"cpu": 2}, ).trials assert trial3.last_result["num_resets"] == 1 assert trial4.last_result["num_resets"] == 1

1510fb2cd631b2776092fb45ee4082e5e65f16f8

test_actor_reuse.py

[air/tune] Internal resource management 2 - Ray Tune to use new Ray AIR resource manager (#30016) Includes/depends on #30777 TLDR: This PR refactors Ray Tune's resource management to use a central AIR resource management package instead of the tightly coupled PlacementGroupManager. Ray Tune's resource management currently uses a tightly coupled placement group manager. This leads to a number of shortcomings: - The tight coupling on the manager side (e.g. PG manager keeps track of trials) prevents re-usability - The tight coupling on the trial executor side prevents using different resource management strategies (e.g. shared or budget-based) - It's hard to test independently. Tests for the resource management require a simulated tune setup. To improve stability, extensibility, and maintainability, this PR moves the resource management logic into a central `ray.air.execution.resources` subpackage. The resource management has a simple API that works with `ResourceRequest`s and `AllocatedResources` to manage requested and assigned resources, respectively. The actual resource management can then be anything - per default it is a placement group based manager, but this PR also introduces a PoC budget-based manager that can be plugged in. The PR does not substantially change existing tests, so we can be certain that the new resource model is a fully compatible replacement for the old placement group manager. Signed-off-by: Kai Fricke <kai@anyscale.com>

ray

python/ray/tune/tests/test_actor_reuse.py

Python

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

test_get_dynamic_sampling_default_biases

def test_get_dynamic_sampling_default_biases(self): with Feature( { self.new_ds_flag: True, } ): response = self.get_success_response( self.organization.slug, self.project.slug, method="get" ) assert response.data["dynamicSamplingBiases"] == DEFAULT_BIASES

6fc6106b6a57149a5bae3c0f4677349cfbae1155

test_project_details.py

fix(dyn-sampling): Backend code clean up (#42001) We are consolidating server-side-sampling and dynamic-sampling flags into only dynamic-sampling. The flag is being controlled by plan

sentry

tests/sentry/api/endpoints/test_project_details.py

Python

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

remove_widget

def remove_widget(self, widget): if widget not in self.children: return self.children.remove(widget) if widget.canvas in self.canvas.children: self.canvas.remove(widget.canvas) elif widget.canvas in self.canvas.after.children: self.canvas.after.remove(widget.canvas) elif widget.canvas in self.canvas.before.children: self.canvas.before.remove(widget.canvas) for type_id in widget.motion_filter: self.unregister_for_motion_event(type_id, widget) widget.funbind('motion_filter', self._update_motion_filter) widget.parent = None widget.dec_disabled(self._disabled_count)

1830123ba3edf7290b7c6cb1c6f406ccf1d0e5d4

widget.py

Feature: EventManagerBase (#7658) * Added EventManagerBase class and event_managers attribute to WindowBase class. * Added on_motion event to Widget class. * Updated post_dispatch_input in EventLoopBase to skip non-touch events. * Using type ids in MouseMotionEventProvider. * Added on_motion method to Widget subclasses. * Updated Widget.on_motion method to dispatch to filtered widgets if 'pos' is not in me.profile. * Changed motion_filter property in Widget to store key to list values. * Updated Widget.on_motion to not dispatch event to children if widget is disabled. * Widget: Using flags to control dispatching in on_motion method. * Widget: Don't dispatch on_motion to children if only self is registered. * Widget: Removed collision on disabled check from on_motion method. * Widget: Added docstrings for motion_filter and related methods. * EventManager: Moved motion event flags to eventmanager/__init__.py module. * ScreenManager: Overrode the on_motion method. * WindowBase: Using attributes event_managers and event_managers_dict. * WindowBase: Added doc for register_event_manager and unregister_event_manager methods. * Widget: Improved default dispatch to stop after the last registered widgets. * EventManagerBase: Added initial docs class and module. * Widget: Added experimental warnings to motion_filter property and to on_motion and (un)register_for_motion_event methods. * WindowBase: Added docs for event_managers and event_managers_dict attributes. * MotionEvent: Added type_id and flags to push_attrs list. * EventManagerBase: Added versionadded tag on all flags. * EventManagerBase: Use dispatch modes instead of flags.

kivy

kivy/uix/widget.py

Python

https://github.com/kivy/kivy.git

mixin_base_ppr_parser

def mixin_base_ppr_parser(parser): mixin_essential_parser(parser) gp = add_arg_group(parser, title='Base Deployment') gp.add_argument( '--extra-search-paths', type=str, default=[], nargs='*', help='Extra search paths to be used when loading modules and finding YAML config files.' if _SHOW_ALL_ARGS else argparse.SUPPRESS, ) gp.add_argument( '--timeout-ctrl', type=int, default=int(os.getenv('JINA_DEFAULT_TIMEOUT_CTRL', '60')), help='The timeout in milliseconds of the control request, -1 for waiting forever', ) parser.add_argument( '--k8s-namespace', type=str, help='Name of the namespace where Kubernetes deployment should be deployed, to be filled by flow name' if _SHOW_ALL_ARGS else argparse.SUPPRESS, ) gp.add_argument( '--polling', type=str, default=PollingType.ANY.name, help=, )

a3b71c7208b3cd48aa7bc978c3343a074947e3d9

base.py

fix(parsers): clearify flow args (#4701)

jina

jina/parsers/orchestrate/base.py

Python

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

calc

def calc(term): # This part is for reading and converting arithmetic terms. term = term.replace(" ", "") term = term.replace("^", "**") term = term.replace("=", "") term = term.replace("?", "") term = term.replace("%", "/100.00") term = term.replace("rad", "radians") term = term.replace("mod", "%") term = term.replace("aval", "abs") functions = [ "sin", "cos", "tan", "pow", "cosh", "sinh", "tanh", "sqrt", "pi", "radians", "e", ] # This part is for reading and converting function expressions. term = term.lower() for func in functions: if func in term: withmath = "math." + func term = term.replace(func, withmath) try: # here goes the actual evaluating. term = eval(term) # here goes to the error cases. except ZeroDivisionError: print("Can't divide by 0. Please try again.") except NameError: print("Invalid input. Please try again") except AttributeError: print("Please check usage method and try again.") except TypeError: print("please enter inputs of correct datatype ") return term

f0af0c43340763724f139fa68aa1e5a9ffe458b4

calculator.py

refactor: clean code Signed-off-by: slowy07 <slowy.arfy@gmail.com>

Python

calculator.py

Python

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

test_song_from_dict

def test_song_from_dict(): song = Song.from_dict( { "name": "Ropes", "artists": ["Dirty Palm", "Chandler Jewels"], "album_name": "Ropes", "album_artist": "Dirty Palm", "genres": ["gaming edm", "melbourne bounce international"], "disc_number": 1, "duration": 188, "year": 2021, "date": "2021-10-28", "track_number": 1, "tracks_count": 1, "isrc": "GB2LD2110301", "song_id": "1t2qKa8K72IBC8yQlhD9bU", "cover_url": "https://i.scdn.co/image/ab67616d0000b273fe2cb38e4d2412dbb0e54332", "explicit": False, "download_url": None, "artist": "Dirty Palm", "disc_count": 1, "copyright": "", "publisher": "", "url": "https://open.spotify.com/track/1t2qKa8K72IBC8yQlhD9bU", } ) 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

fa2ad657482aca9dc628e6d7062b8badf2706bb6

test_song.py

v4 init

spotify-downloader

tests/types/test_song.py

Python

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

_get_states_count_upstream_ti

def _get_states_count_upstream_ti(ti, finished_tis): counter = Counter(task.state for task in finished_tis if task.task_id in ti.task.upstream_task_ids) return ( counter.get(State.SUCCESS, 0), counter.get(State.SKIPPED, 0), counter.get(State.FAILED, 0), counter.get(State.UPSTREAM_FAILED, 0), sum(counter.values()), )

99f86ccfa59df6aa1aa33afce5e0b66dd5df9a3d

trigger_rule_dep.py

Some refactoring work on scheduling code (#21414)

airflow

airflow/ti_deps/deps/trigger_rule_dep.py

Python

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

fit

def fit(self, X, y=None): # Validating the scalar parameters. check_scalar( self.threshold, "threshold", target_type=numbers.Real, min_val=0.0, include_boundaries="neither", ) check_scalar( self.branching_factor, "branching_factor", target_type=numbers.Integral, min_val=1, include_boundaries="neither", ) if isinstance(self.n_clusters, numbers.Number): check_scalar( self.n_clusters, "n_clusters", target_type=numbers.Integral, min_val=1, ) # TODO: Remove deprecated flags in 1.2 self._deprecated_fit, self._deprecated_partial_fit = True, False return self._fit(X, partial=False)

ee5a1b69d1dfa99635a10f0a5b54ec263cedf866

_birch.py

DOC, MNT Typos found by codespell (#22906)

scikit-learn

sklearn/cluster/_birch.py

Python

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

load

def load(self): for key in sorted(self._alignments.data): this_frame_faces = [] for item in self._alignments.data[key]["faces"]: face = DetectedFace() face.from_alignment(item, with_thumb=True) face.load_aligned(None) _ = face.aligned.average_distance # cache the distances this_frame_faces.append(face) self._frame_faces.append(this_frame_faces) self._sorted_frame_names = sorted(self._alignments.data)

23d92c1f0d83ce1cdcc51480cfe37af074a981b3

detected_faces.py

Bugfixes - Sort - Fix rare help-text parsing bug - Manual - Fix issue where frame count is incorrect when een > 1 used on extract

faceswap

tools/manual/detected_faces.py

Python

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

get_assessment_criteria

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

494bd9ef78313436f0424b918f200dab8fc7c20b

@frappe.whitelist()

api.py

style: format code with black

erpnext

erpnext/education/api.py

Python

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

new_compiler

def new_compiler(plat=None, compiler=None, verbose=0, dry_run=0, force=0): if plat is None: plat = os.name try: if compiler is None: compiler = get_default_compiler(plat) (module_name, class_name, long_description) = compiler_class[compiler] except KeyError: msg = "don't know how to compile C/C++ code on platform '%s'" % plat if compiler is not None: msg = msg + " with '%s' compiler" % compiler raise DistutilsPlatformError(msg) try: module_name = "distutils." + module_name __import__ (module_name) module = sys.modules[module_name] klass = vars(module)[class_name] except ImportError: raise DistutilsModuleError( "can't compile C/C++ code: unable to load module '%s'" % \ module_name) except KeyError: raise DistutilsModuleError( "can't compile C/C++ code: unable to find class '%s' " "in module '%s'" % (class_name, module_name)) # XXX The None is necessary to preserve backwards compatibility # with classes that expect verbose to be the first positional # argument. return klass(None, dry_run, force)

8198943edd73a363c266633e1aa5b2a9e9c9f526

ccompiler.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/ccompiler.py

Python

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

register

def register(config_class, feature_extractor_class): FEATURE_EXTRACTOR_MAPPING.register(config_class, feature_extractor_class)

2e11a043374a6229ec129a4765ee4ba7517832b9

feature_extraction_auto.py

Register feature extractor (#15634) * Rework AutoFeatureExtractor.from_pretrained internal * Custom feature extractor * Add more tests * Add support for custom feature extractor code * Clean up * Add register API to AutoFeatureExtractor

transformers

src/transformers/models/auto/feature_extraction_auto.py

Python

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

execute

def execute(): if not frappe.get_all("Pricing Rule", limit=1): return frappe.reload_doc("accounts", "doctype", "pricing_rule_detail") doctypes = { "Supplier Quotation": "buying", "Purchase Order": "buying", "Purchase Invoice": "accounts", "Purchase Receipt": "stock", "Quotation": "selling", "Sales Order": "selling", "Sales Invoice": "accounts", "Delivery Note": "stock", } for doctype, module in doctypes.items(): frappe.reload_doc(module, "doctype", frappe.scrub(doctype)) child_doc = frappe.scrub(doctype) + "_item" frappe.reload_doc(module, "doctype", child_doc, force=True) child_doctype = doctype + " Item" frappe.db.sql( .format( child_doctype=child_doctype ) ) data = frappe.db.sql( .format( child_doc=child_doctype ), as_dict=1, ) values = [] for d in data: values.append( ( d.pricing_rule, d.name, d.parent, "pricing_rules", d.parenttype, d.creation, d.modified, d.docstatus, d.modified_by, d.owner, frappe.generate_hash("", 10), ) ) if values: frappe.db.sql( .format( values=", ".join(["%s"] * len(values)) ), tuple(values), ) frappe.reload_doc("accounts", "doctype", "pricing_rule") for doctype, apply_on in { "Pricing Rule Item Code": "Item Code", "Pricing Rule Item Group": "Item Group", "Pricing Rule Brand": "Brand", }.items(): frappe.reload_doc("accounts", "doctype", frappe.scrub(doctype)) field = frappe.scrub(apply_on) data = frappe.get_all( "Pricing Rule", fields=[field, "name", "creation", "modified", "owner", "modified_by"], filters={"apply_on": apply_on}, ) values = [] for d in data: values.append( ( d.get(field), d.name, parentfield.get(field), "Pricing Rule", d.creation, d.modified, d.owner, d.modified_by, frappe.generate_hash("", 10), ) ) if values: frappe.db.sql( .format( doctype=doctype, field=field, values=", ".join(["%s"] * len(values)) ), tuple(values), )

494bd9ef78313436f0424b918f200dab8fc7c20b

update_pricing_rule_fields.py

style: format code with black

erpnext

erpnext/patches/v12_0/update_pricing_rule_fields.py

Python

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

test_state_aggregate_option_behavior

def test_state_aggregate_option_behavior(master_opts): minion_opts = salt.config.DEFAULT_MINION_OPTS.copy() possible = [None, True, False, ["pkg"]] expected_result = [ True, False, ["pkg"], True, True, ["pkg"], False, True, ["pkg"], ["pkg"], True, ["pkg"], ] for idx, combo in enumerate(itertools.permutations(possible, 2)): master_opts["state_aggregate"], minion_opts["state_aggregate"] = combo state_obj = salt.state.BaseHighState state_obj.client = MockBaseHighStateClient(master_opts) return_result = state_obj(minion_opts)._BaseHighState__gen_opts(minion_opts) assert expected_result[idx] == return_result["state_aggregate"]

8168b25fe5906883a07de5bfdfefabc6d1f57784

test_state_options.py

fixes saltstack/salt#61478 state_aggregate minion option not respected

salt

tests/pytests/unit/state/test_state_options.py

Python

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

register

def register(cls, map_function, reduce_function=None, **kwargs): if reduce_function is None: reduce_function = map_function return cls.call(map_function, reduce_function, **kwargs)

58bbcc37477866d19c8b092a0e1974a4f0baa586

tree_reduce.py

REFACTOR-#2656: Update modin to fit algebra (code only) (#3717) Co-authored-by: Yaroslav Igoshev <Poolliver868@mail.ru> Co-authored-by: Vasily Litvinov <vasilij.n.litvinov@intel.com> Co-authored-by: Alexey Prutskov <alexey.prutskov@intel.com> Co-authored-by: Devin Petersohn <devin-petersohn@users.noreply.github.com> Signed-off-by: Rehan Durrani <rehan@ponder.io>

modin

modin/core/dataframe/algebra/tree_reduce.py

Python

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

trustworthiness

def trustworthiness(X, X_embedded, *, n_neighbors=5, metric="euclidean"): r n_samples = X.shape[0] if n_neighbors >= n_samples / 2: raise ValueError( f"n_neighbors ({n_neighbors}) should be less than n_samples / 2" f" ({n_samples / 2})" ) dist_X = pairwise_distances(X, metric=metric) if metric == "precomputed": dist_X = dist_X.copy() # we set the diagonal to np.inf to exclude the points themselves from # their own neighborhood np.fill_diagonal(dist_X, np.inf) ind_X = np.argsort(dist_X, axis=1) # `ind_X[i]` is the index of sorted distances between i and other samples ind_X_embedded = ( NearestNeighbors(n_neighbors=n_neighbors) .fit(X_embedded) .kneighbors(return_distance=False) ) # We build an inverted index of neighbors in the input space: For sample i, # we define `inverted_index[i]` as the inverted index of sorted distances: # inverted_index[i][ind_X[i]] = np.arange(1, n_sample + 1) inverted_index = np.zeros((n_samples, n_samples), dtype=int) ordered_indices = np.arange(n_samples + 1) inverted_index[ordered_indices[:-1, np.newaxis], ind_X] = ordered_indices[1:] ranks = ( inverted_index[ordered_indices[:-1, np.newaxis], ind_X_embedded] - n_neighbors ) t = np.sum(ranks[ranks > 0]) t = 1.0 - t * ( 2.0 / (n_samples * n_neighbors * (2.0 * n_samples - 3.0 * n_neighbors - 1.0)) ) return t

ade90145c9c660a1a7baf2315185995899b0f356

_t_sne.py

FIX Raise error when n_neighbors >= n_samples / 2 in manifold.trustworthiness (#23033) Co-authored-by: Shao Yang Hong <hongsy2006@gmail.com> Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com>