Datasets:

semeru

/

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

like 1

Follow

Semeru Lab 7

__seqToRE

def __seqToRE(self, to_convert, directive): to_convert = sorted(to_convert, key=len, reverse=True) for value in to_convert: if value != '': break else: return '' regex = '|'.join(re_escape(stuff) for stuff in to_convert) regex = '(?P<%s>%s' % (directive, regex) return '%s)' % regex

8198943edd73a363c266633e1aa5b2a9e9c9f526

_strptime.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/_strptime.py

Python

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

node_id

def node_id(self): node_id = self.worker.current_node_id assert not node_id.is_nil() return node_id

8ffe435173aee0f313f786e7301d05f608b6d5be

runtime_context.py

[core/docs] Update worker docstring (#28495) Co-authored-by: Philipp Moritz <[email protected]>

ray

python/ray/runtime_context.py

Python

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

test_loading_configuration_from_packages

async def test_loading_configuration_from_packages(hass): await config_util.async_process_ha_core_config( hass, { "latitude": 39, "longitude": -1, "elevation": 500, "name": "Huis", CONF_UNIT_SYSTEM: CONF_UNIT_SYSTEM_METRIC, "time_zone": "Europe/Madrid", "external_url": "https://www.example.com", "internal_url": "http://example.local", "packages": { "package_1": {"wake_on_lan": None}, "package_2": { "light": {"platform": "hue"}, "media_extractor": None, "sun": None, }, }, }, ) # Empty packages not allowed with pytest.raises(MultipleInvalid): await config_util.async_process_ha_core_config( hass, { "latitude": 39, "longitude": -1, "elevation": 500, "name": "Huis", CONF_UNIT_SYSTEM: CONF_UNIT_SYSTEM_METRIC, "time_zone": "Europe/Madrid", "packages": {"empty_package": None}, }, ) @patch("homeassistant.helpers.check_config.async_check_ha_config_file")

8dc3ff72c6ff6f9591151759465ac5d8a20e2b2f

@patch("homeassistant.helpers.check_config.async_check_ha_config_file")

test_config.py

Cleanup config deprecation warning (#80251)

core

tests/test_config.py

Python

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

test_torchscript_bart_agent

def test_torchscript_bart_agent(self): from parlai.scripts.torchscript import TorchScript test_phrase = "Don't have a cow, man!" # From test_bart.py with testing_utils.tempdir() as tmpdir: scripted_model_file = os.path.join(tmpdir, 'scripted_model.pt') # Export the BART model export_opt = TorchScript.setup_args().parse_kwargs( model='bart', scripted_model_file=scripted_model_file, no_cuda=True ) TorchScript(export_opt).run() # Test the scripted BART model scripted_opt = ParlaiParser(True, True).parse_kwargs( model='parlai.torchscript.agents:TorchScriptAgent', model_file=scripted_model_file, ) bart = create_agent(scripted_opt) bart.observe({'text': test_phrase, 'episode_done': True}) act = bart.act() self.assertEqual(act['text'], test_phrase)

73a395fd457d5f56463f4f72e5b65919db3f1f96

test_torchscript.py

Add TorchScriptable transformer classifier and subword BPE tokenizer (#4566) * Add torchscript classes for Transformer classifier and subword BPE tokenizer * Add unit tests * Remove debugging code * Resolve comments * Rerun autoformat.sh * Update parlai/torchscript/tokenizer.py Co-authored-by: Eric Smith <[email protected]> Co-authored-by: Eric Smith <[email protected]>

ParlAI

tests/nightly/gpu/test_torchscript.py

Python

https://github.com/facebookresearch/ParlAI.git

set_context

def set_context(context=None, font_scale=1, rc=None): context_object = plotting_context(context, font_scale, rc) mpl.rcParams.update(context_object)

34662f4be5c364e7518f9c1118c9b362038ee5dd

rcmod.py

Convert docs to pydata-sphinx-theme and add new material (#2842) * Do basic conversion of site to pydata_sphinx_theme * Remove some pae structure customizations we no longer need * Add some custom CSS * Tweak a few more colors * Remove vestigial div closing tag * Reorganize release notes into hierarchical pages * Rebuild full docs and fix some resulting issues * Make release note doc refs absolute * Convert homepage to use sphinx-design instead of hand-crafted html * Remove original custom css * Simplify header and put archive switcher in footer * Streamline API docs for objects * Play around with templates to fix shrinking content (not perfect yet) * Improve use of horizontal space without sidebars * Various tweaks * Convert tutorial homepage source to native sphinx-design directives * Move intro page into tutorial * More tweaks * Tweak theme colors and footer * Remove reference to navbar version * Note that error bar tutorial demonstrates new features as of v0.12 * Update layout customization for new theme features * Various layout and CSS tweaks * Narrow support guidance to StackOverflow * Run all notebooks * Adapt to new dropdown navbar in pydata theme * Separate tutorial source and outputs * Separate dostring source and outputs * Add scale API template * Update API docs * Fix requirements * Add new objects * Point doc requirements at v0.10 RC for theme

seaborn

seaborn/rcmod.py

Python

https://github.com/mwaskom/seaborn.git

_process_sections

def _process_sections(cls, tree, sections, category, is_open): seen = set() for section in sections: if section[-1] == "global": # Global categories get escalated to parent continue sect = section[0] section_id = f"{category}|{sect}" if sect not in seen: seen.add(sect) text = sect.replace("_", " ").title() tree.insert(category, "end", section_id, text=text, open=is_open, tags="section") if len(section) == 2: opt = section[-1] opt_id = f"{section_id}|{opt}" opt_text = opt.replace("_", " ").title() tree.insert(section_id, "end", opt_id, text=opt_text, open=is_open, tags="option")

8ab085fae0193bb507fd5ad582668d19d56bea3d

popup_configure.py

bugfix: gui - settings popup. Always reload config

faceswap

lib/gui/popup_configure.py

Python

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

corners_to_center_format

def corners_to_center_format(x): x_transposed = x.T x0, y0, x1, y1 = x_transposed[0], x_transposed[1], x_transposed[2], x_transposed[3] b = [(x0 + x1) / 2, (y0 + y1) / 2, (x1 - x0), (y1 - y0)] return np.stack(b, axis=-1) # Copied from transformers.models.detr.feature_extraction_detr.masks_to_boxes

1ac698744c4dbdf1495d303246d08ffacdf4f5b8

feature_extraction_yolos.py

Add YOLOS (#16848) * First draft * Add YolosForObjectDetection * Make forward pass work * Add mid position embeddings * Add interpolation of position encodings * Add expected values * Add YOLOS to tests * Add integration test * Support tiny model as well * Support all models in conversion script * Remove mid_pe_size attribute * Make more tests pass * Add model to README and fix config * Add copied from statements * Rename base_model_prefix to vit * Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP * Apply suggestions from code review * Apply more suggestions from code review * Convert remaining checkpoints * Improve docstrings * Add YolosFeatureExtractor * Add feature extractor to docs * Add corresponding tests * Fix style * Fix docs * Apply suggestion from code review * Fix bad rebase * Fix some more bad rebase * Fix missing character * Improve docs and variable names Co-authored-by: Niels Rogge <[email protected]>

transformers

src/transformers/models/yolos/feature_extraction_yolos.py

Python

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

get_attributes_and_values

def get_attributes_and_values(item_code): item_cache = ItemVariantsCacheManager(item_code) item_variants_data = item_cache.get_item_variants_data() attributes = get_item_attributes(item_code) attribute_list = [a.attribute for a in attributes] valid_options = {} for item_code, attribute, attribute_value in item_variants_data: if attribute in attribute_list: valid_options.setdefault(attribute, set()).add(attribute_value) item_attribute_values = frappe.db.get_all( "Item Attribute Value", ["parent", "attribute_value", "idx"], order_by="parent asc, idx asc" ) ordered_attribute_value_map = frappe._dict() for iv in item_attribute_values: ordered_attribute_value_map.setdefault(iv.parent, []).append(iv.attribute_value) # build attribute values in idx order for attr in attributes: valid_attribute_values = valid_options.get(attr.attribute, []) ordered_values = ordered_attribute_value_map.get(attr.attribute, []) attr["values"] = [v for v in ordered_values if v in valid_attribute_values] return attributes @frappe.whitelist(allow_guest=True)

494bd9ef78313436f0424b918f200dab8fc7c20b

@frappe.whitelist(allow_guest=True)

utils.py

style: format code with black

erpnext

erpnext/e_commerce/variant_selector/utils.py

Python

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

test_run

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

ea965a5683c56a39570b4cc91e86cd2bb9799308

vits.py

Update VITS for the new API

TTS

TTS/tts/models/vits.py

Python

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

read_image_batch

def read_image_batch(filenames, with_metadata=False): logger.trace("Requested batch: '%s'", filenames) batch = [None for _ in range(len(filenames))] if with_metadata: meta = [None for _ in range(len(filenames))] with futures.ThreadPoolExecutor() as executor: images = {executor.submit(read_image, filename, raise_error=True, with_metadata=with_metadata): idx for idx, filename in enumerate(filenames)} for future in futures.as_completed(images): ret_idx = images[future] if with_metadata: batch[ret_idx], meta[ret_idx] = future.result() else: batch[ret_idx] = future.result() batch = np.array(batch) retval = (batch, meta) if with_metadata else batch logger.trace("Returning images: (filenames: %s, batch shape: %s, with_metadata: %s)", filenames, batch.shape, with_metadata) return retval

2beceffad9b15c1fd78f06b9b272563321c5a41e

image.py

Data Augmentation update (#1263) - lib.detected_face - Subclass Masks for Landmark based masks - Add training mask propery + methods to DetectedFace - lib.training_training - subclass TrainingDataGenerator for training and preview data - Split cache into own module - Reduce thread count to 1 to prevent image corruption + data re-use - Process on largest model input/output size rather than stored image size - Size and crop masks during caching stage - Implement ring buffer for data flow - Fix preview reload bug - augmentation - typing - switch color aug order - better initialization - Fix warp + landmark warp to correctly apply at different image scales - Slightly improved warp caching - Don't store whether image is_preview. Handle all data as training images implicitly - plugins.trainer: Typing and fixes to work with trainingdata refactor

faceswap

lib/image.py

Python

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

get_instance

def get_instance(self, value): if value is None: return None elif isinstance(value, self.model): return value else: # assume instance ID return self.model.objects.get(pk=value)

39f7886a6f8ee98db7e73ce33d94c06139f35bd8

chooser.py

Split out common logic from get_value_data

wagtail

wagtail/admin/widgets/chooser.py

Python

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

test_change_view_save_as_new

def test_change_view_save_as_new(self): change_dict_save_as_new = { "_saveasnew": "Save as new", "title": "Ikke fordømt", "content": "<p>edited article</p>", "date_0": "2008-03-18", "date_1": "10:54:39", "section": self.s1.pk, } article_change_url = reverse( "admin:admin_views_article_change", args=(self.a1.pk,) ) # Add user can perform "Save as new". article_count = Article.objects.count() self.client.force_login(self.adduser) post = self.client.post(article_change_url, change_dict_save_as_new) self.assertRedirects(post, self.index_url) self.assertEqual(Article.objects.count(), article_count + 1) self.client.logout() # Change user cannot perform "Save as new" (no 'add' permission). article_count = Article.objects.count() self.client.force_login(self.changeuser) post = self.client.post(article_change_url, change_dict_save_as_new) self.assertEqual(post.status_code, 403) self.assertEqual(Article.objects.count(), article_count) # User with both add and change permissions should be redirected to the # change page for the newly created object. article_count = Article.objects.count() self.client.force_login(self.superuser) post = self.client.post(article_change_url, change_dict_save_as_new) self.assertEqual(Article.objects.count(), article_count + 1) new_article = Article.objects.latest("id") self.assertRedirects( post, reverse("admin:admin_views_article_change", args=(new_article.pk,)) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

estimated_run_time

def estimated_run_time(self): if self.state and self.state_type == schemas.states.StateType.RUNNING: return self.total_run_time + (pendulum.now() - self.state.timestamp) else: return self.total_run_time

29f4c75e3a605e29987e856204a2441b31f4a6df

orm_models.py

Repair imports as needed

prefect

src/prefect/orion/database/orm_models.py

Python

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

from_rgs

def from_rgs(self, rgs, elements): if len(rgs) != len(elements): raise ValueError('mismatch in rgs and element lengths') max_elem = max(rgs) + 1 partition = [[] for i in range(max_elem)] j = 0 for i in rgs: partition[i].append(elements[j]) j += 1 if not all(p for p in partition): raise ValueError('some blocks of the partition were empty.') return Partition(*partition)

498015021131af4dbb07eb110e5badaba8250c7b

partitions.py

Updated import locations

sympy

sympy/combinatorics/partitions.py

Python

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

get_chunk

def get_chunk(self, size=None) -> pd.DataFrame: if size is None: size = self._chunksize return self.read(nrows=size)

e48c9c3973286e257f6da1966c91806d86b917e0

sas_xport.py

TYP: more return annotations for io/* (#47524) * TYP: more return annotations for io/* * import future

pandas

pandas/io/sas/sas_xport.py

Python

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

iterate_graycode

def iterate_graycode(self, k): unranked_code = GrayCode.unrank(self.superset_size, (self.rank_gray + k) % self.cardinality) return Subset.subset_from_bitlist(self.superset, unranked_code)

498015021131af4dbb07eb110e5badaba8250c7b

subsets.py

Updated import locations

sympy

sympy/combinatorics/subsets.py

Python

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

__getattr__

def __getattr__(self, name): if self._wrapped is empty: self._setup(name) val = getattr(self._wrapped, name) # Special case some settings which require further modification. # This is done here for performance reasons so the modified value is cached. if name in {"MEDIA_URL", "STATIC_URL"} and val is not None: val = self._add_script_prefix(val) elif name == "SECRET_KEY" and not val: raise ImproperlyConfigured("The SECRET_KEY setting must not be empty.") self.__dict__[name] = val return val

9c19aff7c7561e3a82978a272ecdaad40dda5c00

__init__.py

Refs #33476 -- Reformatted code with Black.

django

django/conf/__init__.py

Python

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

test_escape_sequence_resulting_in_multiple_keypresses

def test_escape_sequence_resulting_in_multiple_keypresses(parser): events = list(parser.feed("\x1b[2;4~")) assert len(events) == 2 assert events[0].key == "escape" assert events[1].key == "shift+insert"

bfb962bacf274373e5706090cd854b6aa0857270

test_xterm_parser.py

Backtracking unknown escape sequences, various tests for XTermParser

textual

tests/test_xterm_parser.py

Python

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

all_data

def all_data(request, data, data_missing): if request.param == "data": return data elif request.param == "data_missing": return data_missing @pytest.fixture

d40c37192b3d38a3c9a0d248dc612ac9dd56e506

@pytest.fixture

test_arrow.py

ENH/TST: Add BaseInterfaceTests tests for ArrowExtensionArray (#47377)

pandas

pandas/tests/extension/test_arrow.py

Python

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

encode_maxrespcode

def encode_maxrespcode(self): value = self.mrcode if value < 128: code = value elif value > 31743: code = 255 else: exp = 0 value >>= 3 while value > 31: exp += 1 value >>= 1 exp <<= 4 code = 0x80 | exp | (value & 0x0F) self.mrcode = code

08b1f9d67c8e716fd44036a027bdc90dcb9fcfdf

igmpv3.py

E275 - Missing whitespace after keyword (#3711) Co-authored-by: Alexander Aring <[email protected]> Co-authored-by: Anmol Sarma <[email protected]> Co-authored-by: antoine.torre <[email protected]> Co-authored-by: Antoine Vacher <[email protected]> Co-authored-by: Arnaud Ebalard <[email protected]> Co-authored-by: atlowl <[email protected]> Co-authored-by: Brian Bienvenu <[email protected]> Co-authored-by: Chris Packham <[email protected]> Co-authored-by: CQ <[email protected]> Co-authored-by: Daniel Collins <[email protected]> Co-authored-by: Federico Maggi <[email protected]> Co-authored-by: Florian Maury <[email protected]> Co-authored-by: _Frky <[email protected]> Co-authored-by: g-mahieux <[email protected]> Co-authored-by: gpotter2 <[email protected]> Co-authored-by: Guillaume Valadon <[email protected]> Co-authored-by: Hao Zheng <[email protected]> Co-authored-by: Haresh Khandelwal <[email protected]> Co-authored-by: Harri Hämäläinen <[email protected]> Co-authored-by: hecke <[email protected]> Co-authored-by: Jan Romann <[email protected]> Co-authored-by: Jan Sebechlebsky <[email protected]> Co-authored-by: jdiog0 <[email protected]> Co-authored-by: jockque <[email protected]> Co-authored-by: Julien Bedel <[email protected]> Co-authored-by: Keith Scott <[email protected]> Co-authored-by: Kfir Gollan <[email protected]> Co-authored-by: Lars Munch <[email protected]> Co-authored-by: ldp77 <[email protected]> Co-authored-by: Leonard Crestez <[email protected]> Co-authored-by: Marcel Patzlaff <[email protected]> Co-authored-by: Martijn Thé <[email protected]> Co-authored-by: Martine Lenders <[email protected]> Co-authored-by: Michael Farrell <[email protected]> Co-authored-by: Michał Mirosław <[email protected]> Co-authored-by: mkaliszan <[email protected]> Co-authored-by: mtury <[email protected]> Co-authored-by: Neale Ranns <[email protected]> Co-authored-by: Octavian Toader <[email protected]> Co-authored-by: Peter Eisenlohr <[email protected]> Co-authored-by: Phil <[email protected]> Co-authored-by: Pierre Lalet <[email protected]> Co-authored-by: Pierre Lorinquer <[email protected]> Co-authored-by: piersoh <[email protected]> Co-authored-by: plorinquer <[email protected]> Co-authored-by: pvinci <[email protected]> Co-authored-by: Rahul Jadhav <[email protected]> Co-authored-by: Robin Jarry <[email protected]> Co-authored-by: romain-perez <[email protected]> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <[email protected]> Co-authored-by: Sebastian Baar <[email protected]> Co-authored-by: sebastien mainand <[email protected]> Co-authored-by: smehner1 <[email protected]> Co-authored-by: speakinghedge <[email protected]> Co-authored-by: Steven Van Acker <[email protected]> Co-authored-by: Thomas Faivre <[email protected]> Co-authored-by: Tran Tien Dat <[email protected]> Co-authored-by: Wael Mahlous <[email protected]> Co-authored-by: waeva <[email protected]> Co-authored-by: Alexander Aring <[email protected]> Co-authored-by: Anmol Sarma <[email protected]> Co-authored-by: antoine.torre <[email protected]> Co-authored-by: Antoine Vacher <[email protected]> Co-authored-by: Arnaud Ebalard <[email protected]> Co-authored-by: atlowl <[email protected]> Co-authored-by: Brian Bienvenu <[email protected]> Co-authored-by: Chris Packham <[email protected]> Co-authored-by: CQ <[email protected]> Co-authored-by: Daniel Collins <[email protected]> Co-authored-by: Federico Maggi <[email protected]> Co-authored-by: Florian Maury <[email protected]> Co-authored-by: _Frky <[email protected]> Co-authored-by: g-mahieux <[email protected]> Co-authored-by: gpotter2 <[email protected]> Co-authored-by: Guillaume Valadon <[email protected]> Co-authored-by: Hao Zheng <[email protected]> Co-authored-by: Haresh Khandelwal <[email protected]> Co-authored-by: Harri Hämäläinen <[email protected]> Co-authored-by: hecke <[email protected]> Co-authored-by: Jan Romann <[email protected]> Co-authored-by: Jan Sebechlebsky <[email protected]> Co-authored-by: jdiog0 <[email protected]> Co-authored-by: jockque <[email protected]> Co-authored-by: Julien Bedel <[email protected]> Co-authored-by: Keith Scott <[email protected]> Co-authored-by: Kfir Gollan <[email protected]> Co-authored-by: Lars Munch <[email protected]> Co-authored-by: ldp77 <[email protected]> Co-authored-by: Leonard Crestez <[email protected]> Co-authored-by: Marcel Patzlaff <[email protected]> Co-authored-by: Martijn Thé <[email protected]> Co-authored-by: Martine Lenders <[email protected]> Co-authored-by: Michael Farrell <[email protected]> Co-authored-by: Michał Mirosław <[email protected]> Co-authored-by: mkaliszan <[email protected]> Co-authored-by: mtury <[email protected]> Co-authored-by: Neale Ranns <[email protected]> Co-authored-by: Octavian Toader <[email protected]> Co-authored-by: Peter Eisenlohr <[email protected]> Co-authored-by: Phil <[email protected]> Co-authored-by: Pierre Lalet <[email protected]> Co-authored-by: Pierre Lorinquer <[email protected]> Co-authored-by: piersoh <[email protected]> Co-authored-by: pvinci <[email protected]> Co-authored-by: Rahul Jadhav <[email protected]> Co-authored-by: Robin Jarry <[email protected]> Co-authored-by: romain-perez <[email protected]> Co-authored-by: rperez <rperez@debian> Co-authored-by: Sabrina Dubroca <[email protected]> Co-authored-by: Sebastian Baar <[email protected]> Co-authored-by: sebastien mainand <[email protected]> Co-authored-by: smehner1 <[email protected]> Co-authored-by: Steven Van Acker <[email protected]> Co-authored-by: Thomas Faivre <[email protected]> Co-authored-by: Tran Tien Dat <[email protected]> Co-authored-by: Wael Mahlous <[email protected]> Co-authored-by: waeva <[email protected]>

scapy

scapy/contrib/igmpv3.py

Python

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

show_tables

def show_tables(): # [START howto_elasticsearch_query] es = ElasticsearchHook(elasticsearch_conn_id=CONN_ID) # Handle ES conn with context manager with es.get_conn() as es_conn: tables = es_conn.execute('SHOW TABLES') for table, *_ in tables: print(f"table: {table}") return True # [END howto_elasticsearch_query] with models.DAG( DAG_ID, schedule_interval="@once", start_date=datetime(2021, 1, 1), catchup=False, tags=["example", "elasticsearch"], ) as dag: execute_query = show_tables() ( # TEST BODY execute_query ) from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest) test_run = get_test_run(dag)

a801ea3927b8bf3ca154fea3774ebf2d90e74e50

example_elasticsearch_query.py

es new system tests (#22811)

airflow

tests/system/providers/elasticsearch/example_elasticsearch_query.py

Python

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

test_category_match_in_app

def test_category_match_in_app(self): from sentry.grouping.enhancer import Enhancements enhancement = Enhancements.from_config_string( , ) event = make_event( platform="native", exception={ "values": [ { "type": "Hello", "stacktrace": { "frames": [ { "function": "foo", "in_app": True, }, {"function": "bar"}, ] }, } ] }, ) manager = EventManager(event) manager.normalize() manager.get_data()["grouping_config"] = { "enhancements": enhancement.dumps(), "id": "mobile:2021-02-12", } event1 = manager.save(self.project.id) assert event1.data["exception"]["values"][0]["stacktrace"]["frames"][0]["in_app"] is False event = make_event( platform="native", exception={ "values": [ { "type": "Hello", "stacktrace": { "frames": [ { "function": "foo2", "in_app": True, }, {"function": "bar"}, ] }, } ] }, ) manager = EventManager(event) manager.normalize() manager.get_data()["grouping_config"] = { "enhancements": enhancement.dumps(), "id": "mobile:2021-02-12", } event2 = manager.save(self.project.id) assert event2.data["exception"]["values"][0]["stacktrace"]["frames"][0]["in_app"] is False assert event1.group_id == event2.group_id

39cfdcb446e74732c67ce07d7dd8d8d5ace471b1

test_event_manager.py

test(event_manager): Fix incorrect invocations of manager.save (#36615)

sentry

tests/sentry/event_manager/test_event_manager.py

Python

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

test_curr_only_accuracy

def test_curr_only_accuracy(self): _, test = testing_utils.eval_model( opt={ 'batchsize': 4, 'fp16': True, 'num_examples': 16, 'model_file': 'zoo:style_gen/curr_only_classifier/model', 'model': 'projects.style_gen.classifier:ClassifierAgent', 'classes_from_file': 'image_chat_personalities_file', 'task': 'style_gen:CurrUttOnlyStyle', 'wrapper_task': 'style_gen:LabeledBlendedSkillTalk', }, skip_valid=True, ) self.assertAlmostEqual(test['accuracy'], 0.4375, delta=0.0)

82df52b4431f3573ca2c93dd4bb3098992968acc

test_style_gen.py

[Style-Controlled Generation] Open-source a second style classifier (#4380) * Add model to model list * Curr only classifier download page * Add test case * Update version * Update with some results * Wording

ParlAI

tests/nightly/gpu/test_style_gen.py

Python

https://github.com/facebookresearch/ParlAI.git

highlighted_child

def highlighted_child(self) -> ListItem | None: if self.index is None: return None elif 0 <= self.index < len(self.children): return self.children[self.index]

c57f6b90259c8193e3aa9c3453a02b4043873381

_list_view.py

Fix click handler

textual

src/textual/widgets/_list_view.py

Python

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

_expand_hint

def _expand_hint(expr, hint, deep=True, **hints): hit = False # XXX: Hack to support non-Basic args # | # V if deep and getattr(expr, 'args', ()) and not expr.is_Atom: sargs = [] for arg in expr.args: arg, arghit = Expr._expand_hint(arg, hint, **hints) hit |= arghit sargs.append(arg) if hit: expr = expr.func(*sargs) expr = expr._evaluate(expr) if hasattr(expr, hint): newexpr = getattr(expr, hint)(**hints) if newexpr != expr: return (newexpr, True) return (expr, hit)

32e337616722ceae757c23ad1fe2f3465c629a47

expr.py

Fix MatAdd.expand( ) not expanding completely

sympy

sympy/core/expr.py

Python

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

get_extra_loggers

def get_extra_loggers(self) -> List[str]: return ( [name.strip() for name in self.extra_loggers.split(",")] if self.extra_loggers else [] )

a452d8b8917000774302411a7aeb949f7e326814

settings.py

Strip logger name to prevent accidental spaces

prefect

src/prefect/utilities/settings.py

Python

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

forward

def forward(self, input_ids=None, attention_mask=None, **kwargs): if input_ids is None: raise ValueError("Input_ids cannot be None.") inputs_embeds = self.d_model**0.5 * self.embed_tokens(input_ids) inputs_embed_pos = self.encoder_embed_positions(input_ids.shape) hidden_states = inputs_embeds + inputs_embed_pos hidden_states = self.encoder_layernorm_embedding(hidden_states) encoder_input = self.encoder_dropout(hidden_states) if attention_mask is None: attention_mask = paddle.cast( input_ids == self.pad_token_id, dtype=paddle.get_default_dtype()).unsqueeze([1, 2]) * -1e4 attention_mask.stop_gradient = True encoder_output = self.encoder(encoder_input, src_mask=attention_mask) return encoder_output

b0c35d5e1ff02a634fa26392b60d3885c2c78677

modeling.py

Fix the attention mask for fp16 (#1585)

PaddleNLP

paddlenlp/transformers/mbart/modeling.py

Python

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

sparsemax_bisect

def sparsemax_bisect(X, dim=-1, n_iter=50, ensure_sum_one=True): return SparsemaxBisectFunction.apply(X, dim, n_iter, ensure_sum_one)

20a8a6fdb516e543d4598c852063ba0fb407f3ba

root_finding.py

Removes dependency on entmax from PyPI, adds entmax source to utils (#1778) * Removes dependency on entmax from PyPi, add entmax source code into utils instead. * Removes build status and image from README * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix python formatting in docs for pre-commit. * Removes __main__ from test_losses.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update entmax imports. * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: Daniel Treiman <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ludwig

ludwig/utils/entmax/root_finding.py

Python

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

test_missing_fields_old

def test_missing_fields_old(self) -> None: expected_topic = "Unknown Policy (Unknown ID)" expected_message = .strip() self.check_webhook( "incident_default_fields_old", 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

test_process_form_extras

def test_process_form_extras(): # Testing parameters set in both `Extra` and custom fields. mock_form = mock.Mock() mock_form.data = { "conn_type": "test", "conn_id": "extras_test", "extra": '{"param1": "param1_val"}', "extra__test__custom_field": "custom_field_val", } cmv = ConnectionModelView() cmv.extra_fields = ["extra__test__custom_field"] # Custom field cmv.process_form(form=mock_form, is_created=True) assert json.loads(mock_form.extra.data) == { "extra__test__custom_field": "custom_field_val", "param1": "param1_val", } # Testing parameters set in `Extra` field only. mock_form = mock.Mock() mock_form.data = { "conn_type": "test2", "conn_id": "extras_test2", "extra": '{"param2": "param2_val"}', } cmv = ConnectionModelView() cmv.process_form(form=mock_form, is_created=True) assert json.loads(mock_form.extra.data) == {"param2": "param2_val"} # Testing parameters set in custom fields only. mock_form = mock.Mock() mock_form.data = { "conn_type": "test3", "conn_id": "extras_test3", "extra__test3__custom_field": "custom_field_val3", } cmv = ConnectionModelView() cmv.extra_fields = ["extra__test3__custom_field"] # Custom field cmv.process_form(form=mock_form, is_created=True) assert json.loads(mock_form.extra.data) == {"extra__test3__custom_field": "custom_field_val3"} # Testing parameters set in both extra and custom fields (cunnection updates). mock_form = mock.Mock() mock_form.data = { "conn_type": "test4", "conn_id": "extras_test4", "extra": '{"extra__test4__custom_field": "custom_field_val3"}', "extra__test4__custom_field": "custom_field_val4", } cmv = ConnectionModelView() cmv.extra_fields = ["extra__test4__custom_field"] # Custom field cmv.process_form(form=mock_form, is_created=True) assert json.loads(mock_form.extra.data) == {"extra__test4__custom_field": "custom_field_val4"}

44df1420582b358594c8d7344865811cff02956c

test_views_connection.py

fix: Update custom connection field processing (#20883) * fix: Update custom connection field processing Fixes issue where custom connectionfields are not updated because `extra` field is in form and has previous values, overriding custom field values. Adds portion of connection form tests to test functionality.

airflow

tests/www/views/test_views_connection.py

Python

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

data

def data(self, data=None, offset=None, size=None, shape=None, as_memoryview=False): offset = offset or (0, 0) size = size or (self.width - offset[0], self.height - offset[1]) shape = shape or size if any(x <= 0 for x in size): raise ValueError("Offset too big for this raster.") if size[0] > self.width or size[1] > self.height: raise ValueError("Size is larger than raster.") # Create ctypes type array generator ctypes_array = GDAL_TO_CTYPES[self.datatype()] * (shape[0] * shape[1]) if data is None: # Set read mode access_flag = 0 # Prepare empty ctypes array data_array = ctypes_array() else: # Set write mode access_flag = 1 # Instantiate ctypes array holding the input data if isinstance(data, (bytes, memoryview)) or ( numpy and isinstance(data, numpy.ndarray) ): data_array = ctypes_array.from_buffer_copy(data) else: data_array = ctypes_array(*data) # Access band capi.band_io( self._ptr, access_flag, offset[0], offset[1], size[0], size[1], byref(data_array), shape[0], shape[1], self.datatype(), 0, 0, ) # Return data as numpy array if possible, otherwise as list if data is None: if as_memoryview: return memoryview(data_array) elif numpy: # reshape() needs a reshape parameter with the height first. return numpy.frombuffer( data_array, dtype=numpy.dtype(data_array) ).reshape(tuple(reversed(size))) else: return list(data_array) else: 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

get_all_holiday_exchange_short_names

def get_all_holiday_exchange_short_names() -> pd.DataFrame: exchange_short_names = mcal.calendar_registry.get_calendar_names() df = pd.DataFrame(exchange_short_names, columns=["short_name"]) return df @log_start_end(log=logger)

7e4a657333c8b7bb1ebdcb7a4c8f06e8dc0d66f6

@log_start_end(log=logger)

pandas_market_cal_model.py

Addition of exchange holiday functionality under stocks/th (#3486) * Addition of exchange holiday calendars using PandasMarketCalendar * website update for holidays functionality * Disable pylint too many attributes * Changes to not show index for dataframe and include metavar * Setting of default value for holidays * Merge + black linter * test fix Co-authored-by: james <[email protected]> Co-authored-by: Jeroen Bouma <[email protected]>

OpenBBTerminal

openbb_terminal/stocks/tradinghours/pandas_market_cal_model.py

Python

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

_tupleize_axis_indexer

def _tupleize_axis_indexer(self, key) -> tuple: new_key = [slice(None)] * self.ndim # error: Invalid index type "Optional[Any]" for "List[slice]"; expected # type "SupportsIndex" new_key[self.axis] = key # type:ignore[index] return tuple(new_key)

ab42f85f192ab054a18f94825ced1bb4c1ab7d3f

indexing.py

REF: implement LocationIndexer._tupleize_axis_indexer (#45378)

pandas

pandas/core/indexing.py

Python

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

_broadcasting_select_mhlo

def _broadcasting_select_mhlo(which, x, y): which_type, x_type, y_type = ( ir.RankedTensorType(v.type) for v in (which, x, y)) out_shape = list(lax_internal.broadcast_shapes( tuple(which_type.shape), tuple(x_type.shape), tuple(y_type.shape))) bcast_dims = lambda shape: mlir.dense_int_elements( range(len(out_shape) - len(shape), len(out_shape))) if which_type.shape != out_shape: which = mhlo.BroadcastInDimOp( ir.RankedTensorType.get(out_shape, which_type.element_type), which, bcast_dims(which_type.shape)) if x_type.shape != out_shape: x = mhlo.BroadcastInDimOp( ir.RankedTensorType.get(out_shape, x_type.element_type), x, bcast_dims(x_type.shape)) if y_type.shape != out_shape: y = mhlo.BroadcastInDimOp( ir.RankedTensorType.get(out_shape, y_type.element_type), y, bcast_dims(y_type.shape)) return mhlo.SelectOp(which, x, y).result

bc658e74567ffa941b31f4e89463dc713d2ecbf4

linalg.py

[MHLO] Add direct MHLO lowerings for most linear algebra kernels. PiperOrigin-RevId: 439927594

jax

jax/_src/lax/linalg.py

Python

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

list_to_tuple

def list_to_tuple(maybe_list): if isinstance(maybe_list, list): return tuple(maybe_list) return maybe_list

84afc5193d38057e2e2badf9c889ea87d80d8fbf

training_utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/engine/training_utils.py

Python

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

collect_extra_binaries

def collect_extra_binaries(self): binaries = [] # Applicable only to Windows. if not compat.is_win: return [] # OpenGL: EGL/GLES via ANGLE, software OpenGL renderer. binaries += self._collect_all_or_none(['libEGL.dll', 'libGLESv2.dll'], ['d3dcompiler_??.dll']) binaries += self._collect_all_or_none(['opengl32sw.dll']) # Include ICU files, if they exist. # See the "Deployment approach" section in ``PyInstaller/utils/hooks/qt.py``. binaries += self._collect_all_or_none(['icudt??.dll', 'icuin??.dll', 'icuuc??.dll']) return binaries # Collect additional shared libraries required for SSL support in QtNetwork, if they are available. # Applicable only to Windows. See issue #3520, #4048.

d789a7daa7712716c89259b987349917a89aece7

__init__.py

hookutils: reorganize the Qt hook utilities Reorganize the Qt module information to provide information necessary to deal with variations between different python Qt bindings (PySide2, PyQt5, PySide6, and PyQt6). Replace the existing table-like dictionary with list of entries, which is easier to format and document. From this list, we now generate two dictionaries; one that maps Qt module (shared library) names to the module info entries (the same role as the old dictionary), and one that maps python module names to the module info entries. The latter is necessary to accommodate python modules that do not have corresponding Qt shared libraries (header-only Qt modules, such as QtAxContainer; or statically-linked module, such as QSci), but we still need to provide information about plugins or translation files. The new information list is based on manual inspection of source code for Qt 5.15 and 6.3, and should provide comprehensive information about all plugin names and translation file basenames. In addition, most of the helper functions, which take a reference to the `QtLibraryInfo` class as their first argument, have been turned into methods of the `QtLibraryInfo` class. The corresponding hooks have also been adjusted.

pyinstaller

PyInstaller/utils/hooks/qt/__init__.py

Python

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

__make_attention_mask

def __make_attention_mask(self) -> None: # Make masks for shift case if self.shift_size > 0: height, width = self.input_resolution # type: int, int mask: torch.Tensor = torch.zeros(height, width, device=self.window_attention.tau.device) height_slices: Tuple = (slice(0, -self.window_size), slice(-self.window_size, -self.shift_size), slice(-self.shift_size, None)) width_slices: Tuple = (slice(0, -self.window_size), slice(-self.window_size, -self.shift_size), slice(-self.shift_size, None)) counter: int = 0 for height_slice in height_slices: for width_slice in width_slices: mask[height_slice, width_slice] = counter counter += 1 mask_windows: torch.Tensor = unfold(mask[None, None], self.window_size) mask_windows: torch.Tensor = mask_windows.reshape(-1, self.window_size * self.window_size) attention_mask: Optional[torch.Tensor] = mask_windows.unsqueeze(1) - mask_windows.unsqueeze(2) attention_mask: Optional[torch.Tensor] = attention_mask.masked_fill(attention_mask != 0, float(-100.0)) attention_mask: Optional[torch.Tensor] = attention_mask.masked_fill(attention_mask == 0, float(0.0)) else: attention_mask: Optional[torch.Tensor] = None # Save mask self.register_buffer("attention_mask", attention_mask)

90dc74c450a0ec671af0e7f73d6b4a7b5396a7af

swin_transformer_v2.py

Add code from https://github.com/ChristophReich1996/Swin-Transformer-V2 and change docstring style to match timm

pytorch-image-models

timm/models/swin_transformer_v2.py

Python

https://github.com/huggingface/pytorch-image-models.git

test_valid_zero_ops_doesnt_require_backend_dispatch_key

def test_valid_zero_ops_doesnt_require_backend_dispatch_key(self) -> None: yaml_str = # External codegen on a yaml file with no operators is effectively a no-op, # so there's no reason to parse the backend self.assert_success_from_gen_backend_stubs(yaml_str)

bb5b4cceb6f737448eaaa6817cd773b6f4b0e77d

test_gen_backend_stubs.py

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

pytorch

tools/test/test_gen_backend_stubs.py

Python

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

test_worker_disable_ll_hls

async def test_worker_disable_ll_hls(hass): stream_settings = StreamSettings( ll_hls=True, min_segment_duration=TARGET_SEGMENT_DURATION_NON_LL_HLS - SEGMENT_DURATION_ADJUSTER, part_target_duration=TARGET_SEGMENT_DURATION_NON_LL_HLS, hls_advance_part_limit=3, hls_part_timeout=TARGET_SEGMENT_DURATION_NON_LL_HLS, orientation=1, ) py_av = MockPyAv() py_av.container.format.name = "hls" await async_decode_stream( hass, PacketSequence(TEST_SEQUENCE_LENGTH), py_av=py_av, stream_settings=stream_settings, ) assert stream_settings.ll_hls is False

852b0caf5be4bba0dcaaf5f6a38221d1590c4ed9

test_worker.py

Add orientation transforms to stream (#77439)

core

tests/components/stream/test_worker.py

Python

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

update_company_monthly_sales

def update_company_monthly_sales(company): import json from frappe.utils.goal import get_monthly_results filter_str = "company = {0} and status != 'Draft' and docstatus=1".format( frappe.db.escape(company) ) month_to_value_dict = get_monthly_results( "Sales Invoice", "base_grand_total", "posting_date", filter_str, "sum" ) frappe.db.set_value("Company", company, "sales_monthly_history", json.dumps(month_to_value_dict))

494bd9ef78313436f0424b918f200dab8fc7c20b

company.py

style: format code with black

erpnext

erpnext/setup/doctype/company/company.py

Python

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

newer_pairwise

def newer_pairwise (sources, targets): if len(sources) != len(targets): raise ValueError("'sources' and 'targets' must be same length") # build a pair of lists (sources, targets) where source is newer n_sources = [] n_targets = [] for i in range(len(sources)): if newer(sources[i], targets[i]): n_sources.append(sources[i]) n_targets.append(targets[i]) return (n_sources, n_targets) # newer_pairwise ()

8198943edd73a363c266633e1aa5b2a9e9c9f526

dep_util.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/distutils/dep_util.py

Python

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

mean

def mean(self, axis=None, dtype=None, keepdims=False, split_every=None, out=None): from dask.array.reductions import mean return mean( self, axis=axis, dtype=dtype, keepdims=keepdims, split_every=split_every, out=out, )

2820bae493a49cb1d0a6e376985c5473b8f04fa8

core.py

Don't include docs in ``Array`` methods, just refer to module docs (#9244) Co-authored-by: James Bourbeau <[email protected]>

dask

dask/array/core.py

Python

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

test_filter_on_load

async def test_filter_on_load(hass, hass_storage): hass_storage[er.STORAGE_KEY] = { "version": er.STORAGE_VERSION_MAJOR, "minor_version": 1, "data": { "entities": [ { "entity_id": "test.named", "platform": "super_platform", "unique_id": "with-name", "name": "registry override", }, # This entity's name should be None { "entity_id": "test.no_name", "platform": "super_platform", "unique_id": "without-name", }, { "entity_id": "test.disabled_user", "platform": "super_platform", "unique_id": "disabled-user", "disabled_by": "user", # We store the string representation }, { "entity_id": "test.disabled_hass", "platform": "super_platform", "unique_id": "disabled-hass", "disabled_by": "hass", # We store the string representation }, # This entry should have the entity_category reset to None { "entity_id": "test.system_entity", "platform": "super_platform", "unique_id": "system-entity", "entity_category": "system", }, ] }, } await er.async_load(hass) registry = er.async_get(hass) assert len(registry.entities) == 5 assert set(registry.entities.keys()) == { "test.disabled_hass", "test.disabled_user", "test.named", "test.no_name", "test.system_entity", } entry_with_name = registry.async_get_or_create( "test", "super_platform", "with-name" ) entry_without_name = registry.async_get_or_create( "test", "super_platform", "without-name" ) assert entry_with_name.name == "registry override" assert entry_without_name.name is None assert not entry_with_name.disabled entry_disabled_hass = registry.async_get_or_create( "test", "super_platform", "disabled-hass" ) entry_disabled_user = registry.async_get_or_create( "test", "super_platform", "disabled-user" ) assert entry_disabled_hass.disabled assert entry_disabled_hass.disabled_by is er.RegistryEntryDisabler.HASS assert entry_disabled_user.disabled assert entry_disabled_user.disabled_by is er.RegistryEntryDisabler.USER entry_system_category = registry.async_get_or_create( "test", "system_entity", "system-entity" ) assert entry_system_category.entity_category is None

4e32bf2ac910e38695a1b9bf9b610c717db97998

test_entity_registry.py

Drop old migration code from entity registry (#78278)

core

tests/helpers/test_entity_registry.py

Python

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

read

def read(self) -> TOMLDocument: with open(self._path, encoding="utf-8", newline="") as f: return loads(f.read())

8faa74cdc9da20cfdcc69f5ec29b91112c95b4c9

toml_file.py

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

pipenv

pipenv/vendor/tomlkit/toml_file.py

Python

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

load_pascal_annotation

def load_pascal_annotation(index, pascal_root): classes = ('__background__', # always index 0 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor') class_to_ind = dict(zip(classes, xrange(21))) filename = osp.join(pascal_root, 'Annotations', index + '.xml') # print 'Loading: {}'.format(filename)

cc4d0564756ca067516f71718a3d135996525909

pascal_multilabel_datalayers.py

Balanced joint maximum mean discrepancy for deep transfer learning

transferlearning

code/deep/BJMMD/caffe/examples/pycaffe/layers/pascal_multilabel_datalayers.py

Python

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

test_target_exists_force

def test_target_exists_force(file, source): new_name = source.parent / "new_name.txt" new_name.write_text("existing file") try: file.rename(name=str(new_name), source=str(source), force=True) assert new_name.exists() assert not source.exists() assert new_name.read_text() == "Source content" finally: new_name.unlink()

a35b29b2651bf33c5d5b45e64bc7765ffde4aff4

test_rename.py

Add some funtional tests Add functional tests for the following: - file.readlink - file.replace - file.symlink Remove unit tests for file.replace as they are duplicated in the added functional test

salt

tests/pytests/functional/states/file/test_rename.py

Python

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

cast_column

def cast_column(column, backend): values = backend.df_engine.compute(column.drop_duplicates()) if strings_utils.values_are_pandas_numbers(values): # If numbers, convert to float so it can be converted to bool column = column.astype(float).astype(bool) elif strings_utils.values_are_pandas_bools(values): # If booleans, manually assign boolean values column = backend.df_engine.map_objects( column, lambda x: x.lower() in strings_utils.PANDAS_TRUE_STRS ).astype(bool) else: # If neither numbers or booleans, they are strings (objects) column = column.astype(object) return column

48731ae5ca98d4a1e92374af30f060408f14d91a

binary_feature.py

Fix postprocessing on binary feature columns with number dtype (#2189) * Fixes binary postprocessing for number dtype * ensure calibration work retained * cleanup * removed script postprocessing caveat * added ray/dask test * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * adds mock.patch behavior * allow type inference for visualization * add pytest mark distributed * removed mock.patch call * add try/finally clause like test_ray.py * increasing epochs to 2 as workaround * increased number of samples and add back mock.patch Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

ludwig

ludwig/features/binary_feature.py

Python

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

enter

def enter(self, *path): return Meta(self._meta, path=self._path + [str(p) for p in path])

522d6f27c28dc5fd4d996ed605865c42fbda0da8

meta.py

ref: replace legacy compat.map with list comprehensions (#36372)

sentry

src/sentry/utils/meta.py

Python

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

_get_support_mask

def _get_support_mask(self): n_features = len(self.feature_names) mask = np.zeros(n_features, dtype=bool) mask[np.asarray(self.feat_list_idx)] = True return mask

388616b6247ca4ea8de4e2f340d6206aee523541

feature_set_selector.py

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

tpot

tpot/builtins/feature_set_selector.py

Python

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

test_do_not_render_html

def test_do_not_render_html(self): value = { "first_row_is_table_header": False, "first_col_is_header": False, "data": [ ["<p><strong>Test</strong></p>", None, None], [None, None, None], [None, None, None], ], } expected = block = TableBlock() result = block.render(value) self.assertHTMLEqual(result, expected)

d10f15e55806c6944827d801cd9c2d53f5da4186

tests.py

Reformat with black

wagtail

wagtail/contrib/table_block/tests.py

Python

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

path_up

def path_up(url, count): urlutils.ensure_valid(url) url = url.adjusted(QUrl.UrlFormattingOption.RemoveFragment | QUrl.UrlFormattingOption.RemoveQuery) path = url.path(QUrl.ComponentFormattingOption.FullyEncoded) if not path or path == '/': raise Error("Can't go up!") for _i in range(0, min(count, path.count('/'))): path = posixpath.join(path, posixpath.pardir) path = posixpath.normpath(path) url.setPath(path, QUrl.ParsingMode.StrictMode) return url

0877fb0d78635692e481c8bde224fac5ad0dd430

navigate.py

Run scripts/dev/rewrite_enums.py

qutebrowser

qutebrowser/browser/navigate.py

Python

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

_smooth_amount_callback

def _smooth_amount_callback(self, *args) -> None: try: smooth_amount = self.vars["smoothgraph"].get() except tk.TclError: # Don't update when there is no value in the variable return logger.debug("Updating graph smooth_amount: (new_value: %s, args: %s)", smooth_amount, args) for graph in self.subnotebook.children.values(): graph.calcs.set_smooth_amount(smooth_amount)

dab823a3eb7a5257cb1e0818ee10ed234d3de97f

display_command.py

Typing - lib.gui.display_command

faceswap

lib/gui/display_command.py

Python

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

set_pattern

def set_pattern(self, val): if len(val) > 5000: # avoid crash on huge search terms (#5973) log.completion.warning(f"Trimming {len(val)}-char pattern to 5000") val = val[:5000] self._pattern = val val = re.sub(r' +', r' ', val) # See #1919 val = re.escape(val) val = val.replace(r'\ ', '.*') rx = QRegularExpression(val, QRegularExpression.PatternOption.CaseInsensitiveOption) qtutils.ensure_valid(rx) self.setFilterRegularExpression(rx) self.invalidate() sortcol = 0 self.sort(sortcol)

0877fb0d78635692e481c8bde224fac5ad0dd430

listcategory.py

Run scripts/dev/rewrite_enums.py

qutebrowser

qutebrowser/completion/models/listcategory.py

Python

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

test_generic_relations_with_related_query_name

def test_generic_relations_with_related_query_name(self): bookmark = Bookmark.objects.create(name="djangoproject") tag = FunkyTag.objects.create(content_object=bookmark, name="django") tag_url = reverse("admin:admin_views_funkytag_change", args=(tag.id,)) should_contain = '<li>Funky tag: <a href="%s">django' % tag_url response = self.client.get( reverse("admin:admin_views_bookmark_delete", args=(bookmark.pk,)) ) self.assertContains(response, should_contain)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

tests.py

Refs #33476 -- Reformatted code with Black.

django

tests/admin_views/tests.py

Python

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

parsed_paths

def parsed_paths(self) -> List[str]: res_paths: List[str] = [] paths = self.parser.existing_paths for directory in paths: for filename in paths[directory]: res_paths.append(os.path.join(directory, filename)) return res_paths

7d9e9a49005de7961e84d2a7c608db57dbab3046

augeasparser.py

Add typing to certbot.apache (#9071) * Add typing to certbot.apache Co-authored-by: Adrien Ferrand <[email protected]>

certbot

certbot-apache/certbot_apache/_internal/augeasparser.py

Python

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

ids

def ids(self) -> Tuple[str, ...]: return tuple( sorted(set([cast(str, p.get("id")) for p in self._patterns]) - set([None])) )

a322d6d5f2f85c2da6cded4fcd6143d41b5a9e96

span_ruler.py

Add SpanRuler component (#9880) * Add SpanRuler component Add a `SpanRuler` component similar to `EntityRuler` that saves a list of matched spans to `Doc.spans[spans_key]`. The matches from the token and phrase matchers are deduplicated and sorted before assignment but are not otherwise filtered. * Update spacy/pipeline/span_ruler.py Co-authored-by: Sofie Van Landeghem <[email protected]> * Fix cast * Add self.key property * Use number of patterns as length * Remove patterns kwarg from init * Update spacy/tests/pipeline/test_span_ruler.py Co-authored-by: Sofie Van Landeghem <[email protected]> * Add options for spans filter and setting to ents * Add `spans_filter` option as a registered function' * Make `spans_key` optional and if `None`, set to `doc.ents` instead of `doc.spans[spans_key]`. * Update and generalize tests * Add test for setting doc.ents, fix key property type * Fix typing * Allow independent doc.spans and doc.ents * If `spans_key` is set, set `doc.spans` with `spans_filter`. * If `annotate_ents` is set, set `doc.ents` with `ents_fitler`. * Use `util.filter_spans` by default as `ents_filter`. * Use a custom warning if the filter does not work for `doc.ents`. * Enable use of SpanC.id in Span * Support id in SpanRuler as Span.id * Update types * `id` can only be provided as string (already by `PatternType` definition) * Update all uses of Span.id/ent_id in Doc * Rename Span id kwarg to span_id * Update types and docs * Add ents filter to mimic EntityRuler overwrite_ents * Refactor `ents_filter` to take `entities, spans` args for more filtering options * Give registered filters more descriptive names * Allow registered `filter_spans` filter (`spacy.first_longest_spans_filter.v1`) to take any number of `Iterable[Span]` objects as args so it can be used for spans filter or ents filter * Implement future entity ruler as span ruler Implement a compatible `entity_ruler` as `future_entity_ruler` using `SpanRuler` as the underlying component: * Add `sort_key` and `sort_reverse` to allow the sorting behavior to be customized. (Necessary for the same sorting/filtering as in `EntityRuler`.) * Implement `overwrite_overlapping_ents_filter` and `preserve_existing_ents_filter` to support `EntityRuler.overwrite_ents` settings. * Add `remove_by_id` to support `EntityRuler.remove` functionality. * Refactor `entity_ruler` tests to parametrize all tests to test both `entity_ruler` and `future_entity_ruler` * Implement `SpanRuler.token_patterns` and `SpanRuler.phrase_patterns` properties. Additional changes: * Move all config settings to top-level attributes to avoid duplicating settings in the config vs. `span_ruler/cfg`. (Also avoids a lot of casting.) * Format * Fix filter make method name * Refactor to use same error for removing by label or ID * Also provide existing spans to spans filter * Support ids property * Remove token_patterns and phrase_patterns * Update docstrings * Add span ruler docs * Fix types * Apply suggestions from code review Co-authored-by: Sofie Van Landeghem <[email protected]> * Move sorting into filters * Check for all tokens in seen tokens in entity ruler filters * Remove registered sort key * Set Token.ent_id in a backwards-compatible way in Doc.set_ents * Remove sort options from API docs * Update docstrings * Rename entity ruler filters * Fix and parameterize scoring * Add id to Span API docs * Fix typo in API docs * Include explicit labeled=True for scorer Co-authored-by: Sofie Van Landeghem <[email protected]>

spaCy

spacy/pipeline/span_ruler.py

Python

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

__call__

def __call__(self, checkpoint): if not self.runner: return if checkpoint.storage == Checkpoint.PERSISTENT and checkpoint.value: checkpoint_path = checkpoint.value logger.debug( "Trial %s: Deleting checkpoint %s", self.trial_id, checkpoint_path ) # TODO(ujvl): Batch remote deletes. # We first delete the remote checkpoint. If it is on the same # node as the driver, it will also remove the local copy. ray.get(self.runner.delete_checkpoint.remote(checkpoint_path)) # Delete local copy, if any exists. if os.path.exists(checkpoint_path): try: checkpoint_dir = TrainableUtil.find_checkpoint_dir(checkpoint_path) shutil.rmtree(checkpoint_dir) except FileNotFoundError: logger.debug("Local checkpoint dir not found during deletion.")

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

trial.py

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

ray

python/ray/tune/trial.py

Python

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

test_unread_counts

def test_unread_counts(self) -> None: # Check that our own messages don't increase the unread count. self.helper.send(self.room_id, "hello", tok=self.tok) self._check_unread_count(0) # Join the new user and check that this doesn't increase the unread count. self.helper.join(room=self.room_id, user=self.user2, tok=self.tok2) self._check_unread_count(0) # Check that the new user sending a message increases our unread count. res = self.helper.send(self.room_id, "hello", tok=self.tok2) self._check_unread_count(1) # Send a read receipt to tell the server we've read the latest event. body = json.dumps({"m.read": res["event_id"]}).encode("utf8") channel = self.make_request( "POST", "/rooms/%s/read_markers" % self.room_id, body, access_token=self.tok, ) self.assertEqual(channel.code, 200, channel.json_body) # Check that the unread counter is back to 0. self._check_unread_count(0) # Check that hidden read receipts don't break unread counts res = self.helper.send(self.room_id, "hello", tok=self.tok2) self._check_unread_count(1) # Send a read receipt to tell the server we've read the latest event. body = json.dumps({ReadReceiptEventFields.MSC2285_HIDDEN: True}).encode("utf8") channel = self.make_request( "POST", "/rooms/%s/receipt/m.read/%s" % (self.room_id, res["event_id"]), body, access_token=self.tok, ) self.assertEqual(channel.code, 200, channel.json_body) # Check that the unread counter is back to 0. self._check_unread_count(0) # Check that room name changes increase the unread counter. self.helper.send_state( self.room_id, "m.room.name", {"name": "my super room"}, tok=self.tok2, ) self._check_unread_count(1) # Check that room topic changes increase the unread counter. self.helper.send_state( self.room_id, "m.room.topic", {"topic": "welcome!!!"}, tok=self.tok2, ) self._check_unread_count(2) # Check that encrypted messages increase the unread counter. self.helper.send_event(self.room_id, EventTypes.Encrypted, {}, tok=self.tok2) self._check_unread_count(3) # Check that custom events with a body increase the unread counter. self.helper.send_event( self.room_id, "org.matrix.custom_type", {"body": "hello"}, tok=self.tok2, ) self._check_unread_count(4) # Check that edits don't increase the unread counter. self.helper.send_event( room_id=self.room_id, type=EventTypes.Message, content={ "body": "hello", "msgtype": "m.text", "m.relates_to": {"rel_type": RelationTypes.REPLACE}, }, tok=self.tok2, ) self._check_unread_count(4) # Check that notices don't increase the unread counter. self.helper.send_event( room_id=self.room_id, type=EventTypes.Message, content={"body": "hello", "msgtype": "m.notice"}, tok=self.tok2, ) self._check_unread_count(4) # Check that tombstone events changes increase the unread counter. self.helper.send_state( self.room_id, EventTypes.Tombstone, {"replacement_room": "!someroom:test"}, tok=self.tok2, ) self._check_unread_count(5)

64c73c6ac88a740ee480a0ad1f9afc8596bccfa4

test_sync.py

Add type hints to `tests/rest/client` (#12066)

synapse

tests/rest/client/test_sync.py

Python

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

get_tail

def get_tail(self, n=10, raw=True, output=False, include_latest=False): self.writeout_cache() if not include_latest: n += 1 # cursor/line/entry this_cur = list( self._run_sql( "WHERE session == ? ORDER BY line DESC LIMIT ? ", (self.session_number, n), raw=raw, output=output, ) ) other_cur = list( self._run_sql( "WHERE session != ? ORDER BY session DESC, line DESC LIMIT ?", (self.session_number, n), raw=raw, output=output, ) ) everything = this_cur + other_cur everything = everything[:n] if not include_latest: return list(everything)[:0:-1] return list(everything)[::-1]

dc5bcc1c50892a5128fcf128af28887226144927

history.py

This fixed the mixing of multiple history seen in #13631 It forces get_tail to put the current session last in the returned results.

ipython

IPython/core/history.py

Python

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

_discover_all_airflow_builtin_providers_from_local_sources

def _discover_all_airflow_builtin_providers_from_local_sources(self) -> None: try: import airflow.providers except ImportError: log.info("You have no providers installed.") return try: for path in airflow.providers.__path__: # type: ignore[attr-defined] self._add_provider_info_from_local_source_files_on_path(path) except Exception as e: log.warning("Error when loading 'provider.yaml' files from airflow sources: %s", e)

2fdc23333909096d427171002582e2906f8bbc0a

providers_manager.py

Fix remaining mypy issues in "core" Airflow (#20795) Co-authored-by: Josh Fell <[email protected]> Co-authored-by: Tzu-ping Chung <[email protected]> Co-authored-by: Jarek Potiuk <[email protected]>

airflow

airflow/providers_manager.py

Python

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

fit

def fit(self, X, y=None): self._validate_params() X = self._validate_data(X, ensure_min_samples=2, estimator="MinCovDet") random_state = check_random_state(self.random_state) n_samples, n_features = X.shape # check that the empirical covariance is full rank if (linalg.svdvals(np.dot(X.T, X)) > 1e-8).sum() != n_features: warnings.warn( "The covariance matrix associated to your dataset is not full rank" ) # compute and store raw estimates raw_location, raw_covariance, raw_support, raw_dist = fast_mcd( X, support_fraction=self.support_fraction, cov_computation_method=self._nonrobust_covariance, random_state=random_state, ) if self.assume_centered: raw_location = np.zeros(n_features) raw_covariance = self._nonrobust_covariance( X[raw_support], assume_centered=True ) # get precision matrix in an optimized way precision = linalg.pinvh(raw_covariance) raw_dist = np.sum(np.dot(X, precision) * X, 1) self.raw_location_ = raw_location self.raw_covariance_ = raw_covariance self.raw_support_ = raw_support self.location_ = raw_location self.support_ = raw_support self.dist_ = raw_dist # obtain consistency at normal models self.correct_covariance(X) # re-weight estimator self.reweight_covariance(X) return self

47dd54f727f09a47e84fb4cb53d33f9b0f239edb

_robust_covariance.py

MAINT validate parameter in `EmpiricalCovariance`, `MinCovDet`, and `EllipticEnvelope` (#23842) Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/covariance/_robust_covariance.py

Python

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

from_pandas

def from_pandas(cls, df, return_dims=False): num_splits = GpuCount.get() put_func = cls._partition_class.put # For now, we default to row partitioning pandas_dfs = split_result_of_axis_func_pandas(0, num_splits, df) keys = [ put_func(cls._get_gpu_managers()[i], pandas_dfs[i]) for i in range(num_splits) ] keys = RayWrapper.materialize(keys) parts = cls._create_partitions(keys, cls._get_gpu_managers()).reshape( (num_splits, 1) ) if not return_dims: return parts else: row_lengths = [len(df.index) for df in pandas_dfs] col_widths = [ len(df.columns) ] # single value since we only have row partitions return parts, row_lengths, col_widths

1dc16415333bf2428ee2b1f4d31ff94e66b9a0a6

partition_manager.py

REFACTOR-#5009: use RayWrapper.materialize instead of ray.get (#5010) Signed-off-by: Myachev <[email protected]>

modin

modin/core/execution/ray/implementations/cudf_on_ray/partitioning/partition_manager.py

Python

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

_crossover

def _crossover(candidate): sample_index1 = np.random.choice(len(candidate)) sample_index2 = np.random.choice(len(candidate)) sample_1 = candidate[sample_index1] sample_2 = candidate[sample_index2] cross_index = int(len(sample_1) * np.random.uniform(low=0.3, high=0.7)) logger.info( LOGGING_PREFIX + "Perform crossover between %sth and %sth at index=%s", sample_index1, sample_index2, cross_index, ) next_gen = [] for i in range(len(sample_1)): sample = sample_2[i] if i > cross_index else sample_1[i] next_gen.append(sample) return next_gen

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

genetic_searcher.py

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

ray

python/ray/tune/automl/genetic_searcher.py

Python

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

get_latest_device_activity

def get_latest_device_activity(self, device_id, activity_types): if device_id not in self._latest_activities: return None latest_device_activities = self._latest_activities[device_id] latest_activity = None for activity_type in activity_types: if activity_type in latest_device_activities: if ( latest_activity is not None and latest_device_activities[activity_type].activity_start_time <= latest_activity.activity_start_time ): continue latest_activity = latest_device_activities[activity_type] return latest_activity

dadcc5ebcbcf951ff677568b281c5897d990c8ae

activity.py

spelling: components/august (#64232) Co-authored-by: Josh Soref <[email protected]>

core

homeassistant/components/august/activity.py

Python

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

upnp_factory_mock

def upnp_factory_mock() -> Iterable[Mock]: with patch( "homeassistant.components.dlna_dms.dms.UpnpFactory", autospec=True, spec_set=True, ) as upnp_factory: upnp_device = create_autospec(UpnpDevice, instance=True) upnp_device.name = MOCK_DEVICE_NAME upnp_device.udn = MOCK_DEVICE_UDN upnp_device.device_url = MOCK_DEVICE_LOCATION upnp_device.device_type = MOCK_DEVICE_TYPE upnp_device.available = True upnp_device.parent_device = None upnp_device.root_device = upnp_device upnp_device.all_devices = [upnp_device] upnp_device.services = { "urn:schemas-upnp-org:service:ContentDirectory:1": create_autospec( UpnpService, instance=True, service_type="urn:schemas-upnp-org:service:ContentDirectory:1", service_id="urn:upnp-org:serviceId:ContentDirectory", ), "urn:schemas-upnp-org:service:ConnectionManager:1": create_autospec( UpnpService, instance=True, service_type="urn:schemas-upnp-org:service:ConnectionManager:1", service_id="urn:upnp-org:serviceId:ConnectionManager", ), } seal(upnp_device) upnp_factory_instance = upnp_factory.return_value upnp_factory_instance.async_create_device.return_value = upnp_device yield upnp_factory_instance @pytest.fixture

b19bf9b147f4321e89d1f7f01e68337f2102f460

@pytest.fixture

conftest.py

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

core

tests/components/dlna_dms/conftest.py

Python

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

_setup

def _setup(self, name=None): settings_module = os.environ.get(ENVIRONMENT_VARIABLE) if not settings_module: desc = ("setting %s" % name) if name else "settings" raise ImproperlyConfigured( "Requested %s, but settings are not configured. " "You must either define the environment variable %s " "or call settings.configure() before accessing settings." % (desc, ENVIRONMENT_VARIABLE) ) self._wrapped = Settings(settings_module)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

__init__.py

Refs #33476 -- Reformatted code with Black.

django

django/conf/__init__.py

Python

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

transform_vector

def transform_vector(self, vector): return Vector( (vector.x + self.offset[0]) * self.scale[0], (vector.y + self.offset[1]) * self.scale[1], )

d10f15e55806c6944827d801cd9c2d53f5da4186

image_operations.py

Reformat with black

wagtail

wagtail/images/image_operations.py

Python

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

test_kbinsdiscretizer_effect_sample_weight

def test_kbinsdiscretizer_effect_sample_weight(): X = np.array([[-2], [-1], [1], [3], [500], [1000]]) # add a large number of bins such that each sample with a non-null weight # will be used as bin edge est = KBinsDiscretizer(n_bins=10, encode="ordinal", strategy="quantile") est.fit(X, sample_weight=[1, 1, 1, 1, 0, 0]) assert_allclose(est.bin_edges_[0], [-2, -1, 1, 3]) assert_allclose(est.transform(X), [[0.0], [1.0], [2.0], [2.0], [2.0], [2.0]])

1f3c1be77a5b15d6bc1a5bfd9eb64315928679b1

test_discretization.py

ENH add support for sample_weight in KBinsDiscretizer with strategy="quantile" (#24935) Co-authored-by: seladus <[email protected]> Co-authored-by: Seladus <[email protected]> Co-authored-by: Guillaume Lemaitre <[email protected]>

scikit-learn

sklearn/preprocessing/tests/test_discretization.py

Python

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

_predict_recursive

def _predict_recursive(self, X, x_squared_norms, sample_weight, cluster_node): if cluster_node.left is None: # This cluster has no subcluster. Labels are just the label of the cluster. return np.full(X.shape[0], cluster_node.label, dtype=np.int32) # Determine if data points belong to the left or right subcluster centers = np.vstack((cluster_node.left.center, cluster_node.right.center)) if hasattr(self, "_X_mean"): centers += self._X_mean cluster_labels = _labels_inertia_threadpool_limit( X, sample_weight, x_squared_norms, centers, self._n_threads, return_inertia=False, ) mask = cluster_labels == 0 # Compute the labels for each subset of the data points. labels = np.full(X.shape[0], -1, dtype=np.int32) labels[mask] = self._predict_recursive( X[mask], x_squared_norms[mask], sample_weight[mask], cluster_node.left ) labels[~mask] = self._predict_recursive( X[~mask], x_squared_norms[~mask], sample_weight[~mask], cluster_node.right ) return labels

0822851f5cb17827939a7d7b4f8c84f43184ae89

_bisect_k_means.py

FEA Bisecting K-Means (#20031) Co-authored-by: Gael Varoquaux <[email protected]> Co-authored-by: Tom Dupré la Tour <[email protected]> Co-authored-by: Julien Jerphanion <[email protected]> Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/cluster/_bisect_k_means.py

Python

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

test_get

def test_get(self): # Generate signature signature = generate_signature(self.image.id, "fill-800x600") # Get the image response = self.client.get( reverse( "wagtailimages_serve", args=(signature, self.image.id, "fill-800x600") ) ) # Check response self.assertEqual(response.status_code, 200) self.assertTrue(response.streaming) self.assertEqual(response["Content-Type"], "image/png")

d10f15e55806c6944827d801cd9c2d53f5da4186

tests.py

Reformat with black

wagtail

wagtail/images/tests/tests.py

Python

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

set_temp_hold

def set_temp_hold(self, temp): if self.hvac_mode in (HVACMode.HEAT, HVACMode.COOL): heat_temp = temp cool_temp = temp else: delta = self.thermostat["settings"]["heatCoolMinDelta"] / 10.0 heat_temp = temp - delta cool_temp = temp + delta self.set_auto_temp_hold(heat_temp, cool_temp)

7b1d5fb10af9cf71fae27f9e1020e18bd1fc2510

climate.py

Use climate enums in ecobee (#70632)

core

homeassistant/components/ecobee/climate.py

Python

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

test_archiving_interrupted

def test_archiving_interrupted(self) -> None: expired_msg_ids = self._make_expired_zulip_messages(7) expired_usermsg_ids = self._get_usermessage_ids(expired_msg_ids) # Insert an exception near the end of the archiving process of a chunk: with mock.patch( "zerver.lib.retention.delete_messages", side_effect=Exception("delete_messages error") ): with self.assertRaisesRegex(Exception, r"^delete_messages error$"): # Specify large chunk_size to ensure things happen in a single batch archive_messages(chunk_size=1000) # Archiving code has been executed, but because we got an exception, things should have been rolled back: self._verify_archive_data([], []) self.assertEqual( set(Message.objects.filter(id__in=expired_msg_ids).values_list("id", flat=True)), set(expired_msg_ids), ) self.assertEqual( set( UserMessage.objects.filter(id__in=expired_usermsg_ids).values_list( "id", flat=True ) ), set(expired_usermsg_ids), )

033d2615f6614b06c8268fe60c6ee2a37892c204

test_retention.py

ruff: Fix B017 `assertRaises(Exception):` should be considered evil. Signed-off-by: Anders Kaseorg <[email protected]>

zulip

zerver/tests/test_retention.py

Python

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

test_unknown_sequence_followed_by_known_sequence

def test_unknown_sequence_followed_by_known_sequence(parser): unknown_sequence = "\x1b[?" known_sequence = "\x1b[8~" # key = 'end' sequence = unknown_sequence + known_sequence events = parser.feed(sequence) assert next(events).key == "escape" assert next(events).key == "[" assert next(events).key == "?" assert next(events).key == "end" with pytest.raises(StopIteration): next(events)

bfb962bacf274373e5706090cd854b6aa0857270

test_xterm_parser.py

Backtracking unknown escape sequences, various tests for XTermParser

textual

tests/test_xterm_parser.py

Python

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

write_to_directory

def write_to_directory(self, metric_info_dir, pretty_print=False): with open(os.path.join(metric_info_dir, config.METRIC_INFO_FILENAME), "w", encoding="utf-8") as f: json.dump(asdict(self), f, indent=4 if pretty_print else None) if self.license: with open(os.path.join(metric_info_dir, config.LICENSE_FILENAME), "w", encoding="utf-8") as f: f.write(self.license)

98f2f1390d558d54faa84ae9d2c503d624c7a9ef

info.py

Pretty print dataset info files (#4116) * Pass indent to `json.dumps` * Minor fix * Pretty print GH dataset infos * Style * Revert "Pretty print GH dataset infos" This reverts commit cf0523d4c9c176271cad44cd0d9dd595d233e817. * Add pretty print option

datasets

src/datasets/info.py

Python

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

axvline

def axvline(self, x=0, ymin=0, ymax=1, **kwargs): self._check_no_units([ymin, ymax], ['ymin', 'ymax']) if "transform" in kwargs: raise ValueError("'transform' is not allowed as a keyword " "argument; axvline generates its own transform.") xmin, xmax = self.get_xbound() # Strip away the units for comparison with non-unitized bounds. xx, = self._process_unit_info([("x", x)], kwargs) scalex = (xx < xmin) or (xx > xmax) trans = self.get_xaxis_transform(which='grid') l = mlines.Line2D([x, x], [ymin, ymax], transform=trans, **kwargs) self.add_line(l) if scalex: self._request_autoscale_view("x") return l

383de519505964ed879c40b23ef36e90c17ebe0d

_axes.py

[Doc] fix more spelling and grammar

matplotlib

lib/matplotlib/axes/_axes.py

Python

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

update

def update(self, props): return self._update_props( props, "{cls.__name__!r} object has no property {prop_name!r}")

d69be2554cf6d1ac711bf433b1d6f176e3290d4f

artist.py

Clarify error message for bad keyword arguments. `plot([], [], foo=42)` previously emitted ``` 'Line2D' object has no property 'foo' ``` which refers to the Matplotlib-specific concept of "properties". It now instead emits ``` Line2D.set() got an unexpected keyword argument 'foo' ``` which is modeled after the standard error message for unknown keyword arguments. (To maximize backcompat, the implementation goes through a new _internal_update, which does *not* error when the same prop is passed under different aliases. This could be changed later, but is not the goal of this PR.)

matplotlib

lib/matplotlib/artist.py

Python

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

remove

def remove(name=None, pkgs=None, **kwargs): targets = salt.utils.args.split_input(pkgs) if pkgs else [name] if not targets: return {} if pkgs: log.debug("Removing these fileset(s)/rpm package(s) %s: %s", name, targets) errors = [] # Get a list of the currently installed pkgs. old = list_pkgs() # Remove the fileset or rpm package(s) for target in targets: cmd = "" out = {} try: named, versionpkg, rpmpkg = _check_pkg(target) except CommandExecutionError as exc: if exc.info: errors.append(exc.info["errors"]) continue if rpmpkg: # assume use dnf or yum cmdflags = "-y remove" libpathenv = {"LIBPATH": "/opt/freeware/lib:/usr/lib"} if pathlib.Path("/opt/freeware/bin/dnf").is_file(): cmdexe = "/opt/freeware/bin/dnf" cmd = "{} {} {}".format(cmdexe, cmdflags, target) out = __salt__["cmd.run_all"]( cmd, python_shell=False, env=libpathenv, ignore_retcode=True, ) elif pathlib.Path("/opt/freeware/bin/yum").is_file(): cmdexe = "/opt/freeware/bin/yum" cmd = "{} {} {}".format(cmdexe, cmdflags, target) out = __salt__["cmd.run_all"]( cmd, python_shell=False, env=libpathenv, ignore_retcode=True, ) elif pathlib.Path("/usr/bin/yum").is_file(): cmdexe = "/usr/bin/yum" cmd = "{} {} {}".format(cmdexe, cmdflags, target) out = __salt__["cmd.run_all"]( cmd, python_shell=False, env=libpathenv, ignore_retcode=True, ) else: cmdexe = "/usr/bin/rpm" cmdflags = "-e" cmd = "{} {} {}".format(cmdexe, cmdflags, target) out = __salt__["cmd.run_all"](cmd, python_shell=False) else: cmd = ["/usr/sbin/installp", "-u", named] out = __salt__["cmd.run_all"](cmd, python_shell=False) log.debug("result of removal command %s, returned result %s", cmd, out) # Get a list of the packages after the uninstall __context__.pop("pkg.list_pkgs", None) new = list_pkgs() ret = salt.utils.data.compare_dicts(old, new) if errors: raise CommandExecutionError( "Problems encountered removing filesets(s)/package(s)", info={"changes": ret, "errors": errors}, ) return ret

fae5bc757ad0f1716483ce7ae180b451545c2058

aixpkg.py

Updated to remove use of f-strings, and review comments

salt

salt/modules/aixpkg.py

Python

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

codes

def codes(self): if not self.known: msg = ( "`df.column.cat.codes` with unknown categories is not " "supported. Please use `column.cat.as_known()` or " "`df.categorize()` beforehand to ensure known categories" ) raise AttributeNotImplementedError(msg) return self._property_map("codes")

ecbab9d7cb52a2d96cb1b8dc397a87811e6f8059

categorical.py

Add ``AttributeNotImplementedError`` for properties so IPython glob search works (#9231)

dask

dask/dataframe/categorical.py

Python

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

get_local_ffmpeg

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

e96e8ed7ec7e7cdffceaeb2c42e0396d4e3a8906

ffmpeg.py

fixed local path creation on *nix machines

spotify-downloader

spotdl/utils/ffmpeg.py

Python

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

get_date_list

def get_date_list(self, queryset, date_type=None, ordering="ASC"): date_field = self.get_date_field() allow_empty = self.get_allow_empty() if date_type is None: date_type = self.get_date_list_period() if self.uses_datetime_field: date_list = queryset.datetimes(date_field, date_type, ordering) else: date_list = queryset.dates(date_field, date_type, ordering) if date_list is not None and not date_list and not allow_empty: raise Http404( _("No %(verbose_name_plural)s available") % { "verbose_name_plural": queryset.model._meta.verbose_name_plural, } ) return date_list

9c19aff7c7561e3a82978a272ecdaad40dda5c00

dates.py

Refs #33476 -- Reformatted code with Black.

django

django/views/generic/dates.py

Python

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

test_fetch_lfw_people_internal_cropping

def test_fetch_lfw_people_internal_cropping(): # If cropping was not done properly and we don't resize the images, the images would # have their original size (250x250) and the image would not fit in the NumPy array # pre-allocated based on `slice_` parameter. slice_ = (slice(70, 195), slice(78, 172)) lfw = fetch_lfw_people( data_home=SCIKIT_LEARN_DATA, min_faces_per_person=3, download_if_missing=False, resize=None, slice_=slice_, ) assert lfw.images[0].shape == ( slice_[0].stop - slice_[0].start, slice_[1].stop - slice_[1].start, )

3714c900fc6ddcc87ad4486a41e0d1a4324d7209

test_lfw.py

FIX crop properly the image in fetch_lfw_people (#24951) Co-authored-by: Jérémie du Boisberranger <[email protected]>

scikit-learn

sklearn/datasets/tests/test_lfw.py

Python

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

prepopulated_fields_js

def prepopulated_fields_js(context): prepopulated_fields = [] if "adminform" in context: prepopulated_fields.extend(context["adminform"].prepopulated_fields) if "inline_admin_formsets" in context: for inline_admin_formset in context["inline_admin_formsets"]: for inline_admin_form in inline_admin_formset: if inline_admin_form.original is None: prepopulated_fields.extend(inline_admin_form.prepopulated_fields) prepopulated_fields_json = [] for field in prepopulated_fields: prepopulated_fields_json.append( { "id": "#%s" % field["field"].auto_id, "name": field["field"].name, "dependency_ids": [ "#%s" % dependency.auto_id for dependency in field["dependencies"] ], "dependency_list": [ dependency.name for dependency in field["dependencies"] ], "maxLength": field["field"].field.max_length or 50, "allowUnicode": getattr(field["field"].field, "allow_unicode", False), } ) context.update( { "prepopulated_fields": prepopulated_fields, "prepopulated_fields_json": json.dumps(prepopulated_fields_json), } ) return context @register.tag(name="prepopulated_fields_js")

9c19aff7c7561e3a82978a272ecdaad40dda5c00

@register.tag(name="prepopulated_fields_js")

admin_modify.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/templatetags/admin_modify.py

Python

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

_split_multiext

def _split_multiext(name, min=3, max=4, count=2): extension = '' for i, sfx in enumerate(reversed(_suffixes(name))): if i >= count: break if min <= len(sfx) <= max: extension = '%s%s' % (sfx, extension) name = name.rstrip(sfx) else: # Stop on the first invalid extension break return name, extension

8ebca4a6a3a9836ce515a4dc60044c52465ef170

urls.py

fetch_file - properly split files with multi-part file extensions (#75257)

ansible

lib/ansible/module_utils/urls.py

Python

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

test_upload_file_publish

def test_upload_file_publish(self): file_upload = ContentFile(b"A new file", name="published-file.txt") post_data = { "title": "New file", "slug": "new-file", "file_field": file_upload, "action-publish": "Publish", } response = self.client.post( reverse("wagtailadmin_pages:edit", args=[self.file_page.id]), post_data ) # Should be redirected to explorer self.assertRedirects( response, reverse("wagtailadmin_explore", args=[self.root_page.id]) ) # Check the new file exists file_page = FilePage.objects.get() self.assertEqual(file_page.file_field.name, file_upload.name) self.assertTrue(os.path.exists(file_page.file_field.path)) self.assertEqual(file_page.file_field.read(), b"A new file")

d10f15e55806c6944827d801cd9c2d53f5da4186

test_edit_page.py

Reformat with black

wagtail

wagtail/admin/tests/pages/test_edit_page.py

Python

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

__eq__

def __eq__(self, other): if isinstance(other, str): try: other = GEOSGeometry.from_ewkt(other) except (ValueError, GEOSException): return False return ( isinstance(other, GEOSGeometry) and self.srid == other.srid and self.equals_exact(other) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

geometry.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/gis/geos/geometry.py

Python

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

id_for_label

def id_for_label(self): widget = self.field.widget id_ = widget.attrs.get("id") or self.auto_id return widget.id_for_label(id_)

9c19aff7c7561e3a82978a272ecdaad40dda5c00

boundfield.py

Refs #33476 -- Reformatted code with Black.

django

django/forms/boundfield.py

Python

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

decode_predictions

def decode_predictions(preds, top=5): global CLASS_INDEX if len(preds.shape) != 2 or preds.shape[1] != 1000: raise ValueError( "`decode_predictions` expects " "a batch of predictions " "(i.e. a 2D array of shape (samples, 1000)). " "Found array with shape: " + str(preds.shape) ) if CLASS_INDEX is None: fpath = data_utils.get_file( "imagenet_class_index.json", CLASS_INDEX_PATH, cache_subdir="models", file_hash="c2c37ea517e94d9795004a39431a14cb", ) with open(fpath) as f: CLASS_INDEX = json.load(f) results = [] for pred in preds: top_indices = pred.argsort()[-top:][::-1] result = [tuple(CLASS_INDEX[str(i)]) + (pred[i],) for i in top_indices] result.sort(key=lambda x: x[2], reverse=True) results.append(result) return results

84afc5193d38057e2e2badf9c889ea87d80d8fbf

imagenet_utils.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

keras/applications/imagenet_utils.py

Python

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

handle_expect_100

def handle_expect_100(self): self.send_response_only(HTTPStatus.CONTINUE) self.end_headers() return True

8198943edd73a363c266633e1aa5b2a9e9c9f526

server.py

add python 3.10.4 for windows

XX-Net

python3.10.4/Lib/http/server.py

Python

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

paginator_number

def paginator_number(cl, i): if i == cl.paginator.ELLIPSIS: return format_html("{} ", cl.paginator.ELLIPSIS) elif i == cl.page_num: return format_html('<span class="this-page">{}</span> ', i) else: return format_html( '<a href="{}"{}>{}</a> ', cl.get_query_string({PAGE_VAR: i}), mark_safe(' class="end"' if i == cl.paginator.num_pages else ""), i, )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

admin_list.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/templatetags/admin_list.py

Python

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

test_thumbnail_repeated_thumbnail

def test_thumbnail_repeated_thumbnail(self) -> None: self._test_thumbnail( "scale", self.test_image.expected_scaled, self.test_image.expected_found ) if not self.test_image.expected_found: return # Fetching again should work, without re-requesting the image from the # remote. params = "?width=32&height=32&method=scale" channel = make_request( self.reactor, FakeSite(self.thumbnail_resource, self.reactor), "GET", self.media_id + params, shorthand=False, await_result=False, ) self.pump() self.assertEqual(channel.code, 200) if self.test_image.expected_scaled: self.assertEqual( channel.result["body"], self.test_image.expected_scaled, channel.result["body"], ) # Deleting the thumbnail on disk then re-requesting it should work as # Synapse should regenerate missing thumbnails. origin, media_id = self.media_id.split("/") info = self.get_success(self.store.get_cached_remote_media(origin, media_id)) file_id = info["filesystem_id"] thumbnail_dir = self.media_repo.filepaths.remote_media_thumbnail_dir( origin, file_id ) shutil.rmtree(thumbnail_dir, ignore_errors=True) channel = make_request( self.reactor, FakeSite(self.thumbnail_resource, self.reactor), "GET", self.media_id + params, shorthand=False, await_result=False, ) self.pump() self.assertEqual(channel.code, 200) if self.test_image.expected_scaled: self.assertEqual( channel.result["body"], self.test_image.expected_scaled, channel.result["body"], )

32c828d0f760492711a98b11376e229d795fd1b3

test_media_storage.py

Add type hints to `tests/rest`. (#12208) Co-authored-by: Patrick Cloke <[email protected]>

synapse

tests/rest/media/v1/test_media_storage.py

Python

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

_check_readonly_fields

def _check_readonly_fields(self, obj): if obj.readonly_fields == (): return [] elif not isinstance(obj.readonly_fields, (list, tuple)): return must_be( "a list or tuple", option="readonly_fields", obj=obj, id="admin.E034" ) else: return list( chain.from_iterable( self._check_readonly_fields_item( obj, field_name, "readonly_fields[%d]" % index ) for index, field_name in enumerate(obj.readonly_fields) ) )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

checks.py

Refs #33476 -- Reformatted code with Black.

django

django/contrib/admin/checks.py

Python

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

semilogy

def semilogy(self, *args, **kwargs): d = {k: v for k, v in kwargs.items() if k in ['base', 'subs', 'nonpositive', 'basey', 'subsy', 'nonposy']} self.set_yscale('log', **d) return self.plot( *args, **{k: v for k, v in kwargs.items() if k not in d})

383de519505964ed879c40b23ef36e90c17ebe0d

_axes.py

[Doc] fix more spelling and grammar

matplotlib

lib/matplotlib/axes/_axes.py

Python

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

test_upgrade_org_config_no_source_code_provider

def test_upgrade_org_config_no_source_code_provider(self): with self.tasks(): self.assert_setup_flow() project_id = self.project.id org = self.organization data = { "project_mappings": [[project_id, "Qme9NXBpguaRxcXssZ1NWHVaM98MAL6PHDXUs1jPrgiM8H"]] } integration = Integration.objects.get(provider=self.provider.key) installation = integration.get_installation(org.id) responses.add( responses.GET, "https://api.vercel.com/v1/projects/%s" % "Qme9NXBpguaRxcXssZ1NWHVaM98MAL6PHDXUs1jPrgiM8H", json={}, ) with pytest.raises(ValidationError): installation.update_organization_config(data)

284e980df0018f8baee659999268bdd4c7d08255

test_integration.py

ref: replace self.assertRaises with pytest.raises (#35685) * add flake8 plugin to detect assertRaises * ref: replace self.assertRaises with pytest.raises * non-sed fixes

sentry

tests/sentry/integrations/vercel/test_integration.py

Python

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

_get_coeff_exp

def _get_coeff_exp(expr, x): from sympy.simplify import powsimp (c, m) = expand_power_base(powsimp(expr)).as_coeff_mul(x) if not m: return c, S.Zero [m] = m if m.is_Pow: if m.base != x: raise _CoeffExpValueError('expr not of form a*x**b') return c, m.exp elif m == x: return c, S.One else: raise _CoeffExpValueError('expr not of form a*x**b: %s' % expr)

f757f3daae6e11ea0cfb7dadc133274d8d74315f

meijerint.py

Reordered imports 2

sympy

sympy/integrals/meijerint.py

Python

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

process

def process(self) -> None: logger.debug("Starting Conversion") # queue_manager.debug_monitor(5) try: self._convert_images() self._disk_io.save_thread.join() queue_manager.terminate_queues() finalize(self._images.count, self._predictor.faces_count, self._predictor.verify_output) logger.debug("Completed Conversion") except MemoryError as err: msg = ("Faceswap ran out of RAM running convert. Conversion is very system RAM " "heavy, so this can happen in certain circumstances when you have a lot of " "cpus but not enough RAM to support them all." "\nYou should lower the number of processes in use by either setting the " "'singleprocess' flag (-sp) or lowering the number of parallel jobs (-j).") raise FaceswapError(msg) from err

1022651eb8a7741014f5d2ec7cbfe882120dfa5f

convert.py

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

faceswap

scripts/convert.py

Python

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

_oas

def _oas(X, *, assume_centered=False): # for only one feature, the result is the same whatever the shrinkage if len(X.shape) == 2 and X.shape[1] == 1: if not assume_centered: X = X - X.mean() return np.atleast_2d((X**2).mean()), 0.0 n_samples, n_features = X.shape emp_cov = empirical_covariance(X, assume_centered=assume_centered) mu = np.trace(emp_cov) / n_features # formula from Chen et al.'s **implementation** alpha = np.mean(emp_cov**2) num = alpha + mu**2 den = (n_samples + 1.0) * (alpha - (mu**2) / n_features) shrinkage = 1.0 if den == 0 else min(num / den, 1.0) shrunk_cov = (1.0 - shrinkage) * emp_cov shrunk_cov.flat[:: n_features + 1] += shrinkage * mu return shrunk_cov, shrinkage ############################################################################### # Public API # ShrunkCovariance estimator

a4d470838fe0cc31ba838594e4c8b0ff15be91f8

_shrunk_covariance.py

MAINT Parameters validation for `covariance.oas` (#24904) Co-authored-by: Guillaume Lemaitre <[email protected]> Co-authored-by: jeremiedbb <[email protected]>

scikit-learn

sklearn/covariance/_shrunk_covariance.py

Python

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

ledoit_wolf

def ledoit_wolf(X, *, assume_centered=False, block_size=1000): X = check_array(X) # for only one feature, the result is the same whatever the shrinkage if len(X.shape) == 2 and X.shape[1] == 1: if not assume_centered: X = X - X.mean() return np.atleast_2d((X**2).mean()), 0.0 if X.ndim == 1: X = np.reshape(X, (1, -1)) warnings.warn( "Only one sample available. You may want to reshape your data array" ) n_features = X.size else: _, n_features = X.shape # get Ledoit-Wolf shrinkage shrinkage = ledoit_wolf_shrinkage( X, assume_centered=assume_centered, block_size=block_size ) emp_cov = empirical_covariance(X, assume_centered=assume_centered) mu = np.sum(np.trace(emp_cov)) / n_features shrunk_cov = (1.0 - shrinkage) * emp_cov shrunk_cov.flat[:: n_features + 1] += shrinkage * mu return shrunk_cov, shrinkage

1fc86b6aacd89da44a3b4e8abf7c3e2ba4336ffe

_shrunk_covariance.py

MNT Update black to stable version (#22474)

scikit-learn

sklearn/covariance/_shrunk_covariance.py

Python

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

create_pax_global_header

def create_pax_global_header(cls, pax_headers): return cls._create_pax_generic_header(pax_headers, XGLTYPE, "utf8")

c69d55f7c82d5ae2cce542bcfb98d043ca4836a0