Datasets:

semeru

/

Galeras-3k_deduped

like 0

tests/test_styles.py

Update tests/test_styles.py Co-authored-by: Darren Burns <darrenburns@users.noreply.github.com>

textual

Python

test_styles.py

def test_render_styles_border(): base = Styles() inline = Styles() styles_view = RenderStyles(None, base, inline) base.border_top = ("heavy", "red") # Base has border-top: heavy red assert styles_view.border_top == ("heavy", Color.parse("red")) inline.border_left = ("rounded", "green") # Base has border-top heavy red, inline has border-left: rounded green assert styles_view.border_top == ("heavy", Color.parse("red")) assert styles_view.border_left == ("rounded", Color.parse("green")) assert styles_view.border == ( ("heavy", Color.parse("red")), ("", Color.default()), ("", Color.default()), ("rounded", Color.parse("green")), )

927d04d6b08ff0983d4486733ec8d728cad43bf0

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

def test_render_styles_border(): base = Styles() inline = Styles() styles_view = RenderStyles(None, base, inline) base.border_top = ("heavy", "red") # Base has border-top: heavy red assert styles_view.border_top == ("heavy", Color.parse("red")) inline.border_left = ("rounded", "green") # Base has border-top heavy red, inline has border-left: rounded green assert styles_view.border_top == ("heavy", Color.parse("red")) assert styles_view.border_left == ("rounded", Color.parse("green")) assert styles_

test_render_styles_border

wagtail/admin/tests/pages/test_copy_page.py

Reformat with black

wagtail

Python

test_copy_page.py

def test_page_copy_alias_post_copy_subpages(self): post_data = { "new_title": "Hello world 2", "new_slug": "hello-world-2", "new_parent_page": str(self.root_page.id), "copy_subpages": True, "publish_copies": False, "alias": True, } response = self.client.post( reverse("wagtailadmin_pages:copy", args=(self.test_page.id,)), post_data ) # Check that the user was redirected to the parents explore page self.assertRedirects( response, reverse("wagtailadmin_explore", args=(self.root_page.id,)) ) # Get copy page_copy = self.root_page.get_children().get(slug="hello-world-2") # Check the copy is an alias of the original self.assertEqual(page_copy.alias_of, self.test_page.page_ptr) # Check that the copy is live # Note: publish_copies is ignored. Alias pages always keep the same state as their original self.assertTrue(page_copy.live) self.assertFalse(page_copy.has_unpublished_changes) # Check that the owner of the page is set correctly self.assertEqual(page_copy.owner, self.user) # Check that the children were copied self.assertEqual(page_copy.get_children().count(), 2) # Check the the child pages # Neither of them should be live child_copy = page_copy.get_children().filter(slug="child-page").first() self.assertIsNotNone(child_copy) self.assertEqual(child_copy.alias_of, self.test_child_page.page_ptr) self.assertTrue(child_copy.live) self.assertFalse(child_copy.has_unpublished_changes) unpublished_child_copy = ( page_copy.get_children().filter(slug="unpublished-child-page").first() ) self.assertIsNotNone(unpublished_child_copy) self.assertEqual( unpublished_child_copy.alias_of, self.test_unpublished_child_page.page_ptr ) self.assertFalse(unpublished_child_copy.live) self.assertTrue(unpublished_child_copy.has_unpublished_changes) # treebeard should report no consistency problems with the tree self.assertFalse( any(Page.find_problems()), "treebeard found consistency problems" )

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def test_page_copy_alias_post_copy_subpages(self): post_data = { "new_title": "Hello world 2", "new_slug": "hello-world-2", "new_parent_page": str(self.root_page.id), "copy_subpages": True, "publish_copies": False, "alias": True, } response = self.client.post( reverse("wagtailadmin_pages:copy", args=(self.test_page.id,)), post_data ) # Check that the user was redirected to the parents explore page self.assertRedirects( response, reverse("wagtailadmin_explore", args=(self.root_page.id,)) ) # Get copy page_copy = self.root_page.get_children().get(slug="hello-world-2") # Check the copy is an alias of the original self.assertEqual(page_copy.alias_of, self.test_page.page_ptr) # Check that the copy is live # Note: publish_copies is ignored. Alias pages always keep the same state as their original self.assertTrue(page_copy.live) self.assertFalse(page_copy.has_unpublished_changes) # Check that the owner of the page is set correctly

test_page_copy_alias_post_copy_subpages

dask/dataframe/io/tests/test_parquet.py

Enfore consistent schema in `to_parquet` pyarrow (#9131) * Enfore consistent schema in `to_parquet` pyarrow Previously each partition written in `to_parquet` with `engine="pyarrow"` had their schema inferred based solely on data within that partition alone. This leads to a few common problems: - Mismatched inferred schemas between partitions aren't caught, leading to issues in downstream consumers. Most readers assume a uniform parquet schema across files, which wasn't enforced by default by the pyarrow engine. - Inference was supported with `schema="infer"`, but: - It was expensive, requiring computing at least one partition (sometimes more) to get a sample of any `object` dtypes. - Inference here for non-string object dtypes is silently incorrect, users should really be explicit here when trying to write more complicated schemas containing structured fields. - Inference was off by default - When writing a `_metadata` file, differences in per-file schemas would result in opaque errors when merging the metadata before writing. This error is deep in the `arrow` codebase, and doesn't provide enough information for the user to debug where the schema mismatch occured. Turning on schema enforcement by default lets us generate a better error message, This PR changes the `schema` parameter in the following way: - `schema="infer"` is the default - schema inference assumes object fields are strings (common), and makes no attempt at more complicated inference. Users with more complicated schemas should specify those explicitly. This means that schema inference is now cheap. - A better error message is generated for mismatched partition dtypes in `to_parquet` for the `pyarrow` engine. The fastparquet engine already does this.

dask

Python

test_parquet.py

def test_pyarrow_schema_mismatch_error(tmpdir): df1 = pd.DataFrame({"x": [1, 2, 3], "y": [4.5, 6, 7]}) df2 = pd.DataFrame({"x": [4, 5, 6], "y": ["a", "b", "c"]}) ddf = dd.from_delayed( [dask.delayed(df1), dask.delayed(df2)], meta=df1, verify_meta=False ) with pytest.raises(ValueError) as rec: ddf.to_parquet(str(tmpdir), engine="pyarrow") msg = str(rec.value) assert "Failed to convert partition to expected pyarrow schema" in msg assert "y: double" in str(rec.value) assert "y: string" in str(rec.value) @PYARROW_MARK

73c985c2bed5d61be6d05d67f7f381435fe8d1e2

@PYARROW_MARK

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

def test_pyarrow_schema_mismatch_error(tmpdir): df1 = pd.DataFrame({"x": [1, 2, 3], "y": [4.5, 6, 7]}) df2 = pd.DataFrame({"x": [4, 5, 6], "y": ["a", "b", "c"]}) ddf = dd.from_delayed( [dask.delayed(df1), dask.delayed(df2)], meta=df1, verify_meta=False ) with pytest.raises(ValueError)

test_pyarrow_schema_mismatch_error

homeassistant/components/hassio/__init__.py

Remove hassio from mypy ignore list (#74603) * Remove hassio from mypy ignore list * Avoid if TYPE_CHECKING

core

Python

__init__.py

def get_supervisor_ip() -> str | None: if "SUPERVISOR" not in os.environ: return None return os.environ["SUPERVISOR"].partition(":")[0]

6540ba623978813668a30e5822b97e076fc05a93

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

def get_supervisor_ip() -> str | None: if "SUPERVISOR" not in os.environ: return None return os.environ["SUPERVISOR"].partition(":")[0]

get_supervisor_ip

netbox/dcim/tests/test_models.py

Update Cable instantiations to match new signature

netbox

Python

test_models.py

def test_cable_cannot_have_the_same_terminination_on_both_ends(self): cable = Cable(a_terminations=[self.interface1], b_terminations=[self.interface1]) with self.assertRaises(ValidationError): cable.clean()

3a461d02793e6f9d41c2b1a92647e691de1abaac

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

def test_cable_cannot_have_the_same_terminination_on_both_ends(self): cable = Cable(a_terminations=[self.interface1], b_terminations=[self.interface1]) with self.assertRaises(ValidationError): cable.clea

test_cable_cannot_have_the_same_terminination_on_both_ends

tests/providers/google/cloud/transfers/test_bigquery_to_mssql.py

Bigquery assets (#23165)

airflow

Python

test_bigquery_to_mssql.py

def test_execute_good_request_to_bq(self, mock_hook): destination_table = 'table' operator = BigQueryToMsSqlOperator( task_id=TASK_ID, source_project_dataset_table=f'{TEST_PROJECT_ID}.{TEST_DATASET}.{TEST_TABLE_ID}', mssql_table=destination_table, replace=False, ) operator.execute(context=mock.MagicMock()) # fmt: off mock_hook.return_value.list_rows.assert_called_once_with( dataset_id=TEST_DATASET, table_id=TEST_TABLE_ID, max_results=1000, selected_fields=None, start_index=0, ) # fmt: on

511d0ee256b819690ccf0f6b30d12340b1dd7f0a

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

def test_execute_good_request_to_bq(self, mock_hook): destination_table = 'table' operator =

test_execute_good_request_to_bq

homeassistant/components/text/__init__.py

Add `text` platform (#79454) Co-authored-by: Franck Nijhof <frenck@frenck.nl> Co-authored-by: Franck Nijhof <git@frenck.dev>

core

Python

__init__.py

def pattern_cmp(self) -> re.Pattern | None: if self.pattern is None: self.__pattern_cmp = None return None if not self.__pattern_cmp or self.pattern != self.__pattern_cmp.pattern: self.__pattern_cmp = re.compile(self.pattern) return self.__pattern_cmp

003e4224c89a6da381960dc5347750d1521d85c9

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

def pattern_cmp(self) -> re.Pattern | None: if self.pattern is None: self.__pattern_cmp = None

pattern_cmp

wagtail/core/tests/test_tests.py

Reformat with black

wagtail

Python

test_tests.py

def test_nested_form_data(self): result = nested_form_data( { "foo": "bar", "parent": { "child": "field", }, } ) self.assertEqual(result, {"foo": "bar", "parent-child": "field"})

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def test_nested_form_data(self): result = nested_form_data( { "foo": "bar", "parent": {

test_nested_form_data

tests/ludwig/decoders/test_sequence_decoder.py

Squeeze explicilty. (#1726)

ludwig

Python

test_sequence_decoder.py

def test_sequence_rnn_decoder(cell_type, num_layers, batch_size): hidden_size = 256 vocab_size = 50 max_sequence_length = 10 combiner_outputs = {HIDDEN: torch.rand([batch_size, hidden_size])} sequence_rnn_decoder = SequenceRNNDecoder( hidden_size, vocab_size, max_sequence_length, cell_type, num_layers=num_layers ) output = sequence_rnn_decoder(combiner_outputs, target=None) assert list(output.size()) == [batch_size, max_sequence_length, vocab_size] @pytest.mark.parametrize("num_layers", [1, 2]) @pytest.mark.parametrize("batch_size", [20, 1])

0fea5903b211823b5319ec03cd5262aadf97969e

@pytest.mark.parametrize("num_layers", [1, 2]) @pytest.mark.parametrize("batch_size", [20, 1])

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

def test_sequence_rnn_decoder(cell_type, num_layers, batch_size): hidden_size = 256 vocab_size = 50 max_sequence_length = 10 combiner_outputs = {HIDDEN: torch.rand([batch_size, hidden_size])} sequence_rnn_decoder = SequenceRNNDecoder( hidden_size, vocab_size, max_sequence_length, cell_type, num_layers=num_layers ) output = sequence_rnn_decoder(combiner_outputs, target=None) assert list(output.size()) == [batch_size, max_sequence_length, vocab_size] @pytest.mark.parametrize("num_layers", [1, 2]) @pytest.mark.parametrize("batch_size", [20, 1])

test_sequence_rnn_decoder

modules/sd_hijack.py

Complete cross attention update

stable-diffusion-webui

Python

sd_hijack.py

def nonlinearity_hijack(x): # swish t = torch.sigmoid(x) x *= t del t return x

3b1b1444d4d90415fb42252406437b3d2ceb2110

https://github.com/AUTOMATIC1111/stable-diffusion-webui.git

def nonlinearity_hijack(x): # swish t = torch.sigmoid(x) x *= t del t return x

nonlinearity_hijack

src/datasets/builder.py

Avoid writing empty license files (#4090) * Avoid writing empty license files * Fix empty license file for MetricInfo

datasets

Python

builder.py

def _save_info(self): if os.path.exists(self._cache_dir): super()._save_info() else: import apache_beam as beam fs = beam.io.filesystems.FileSystems with fs.create(os.path.join(self._cache_dir, config.DATASET_INFO_FILENAME)) as f: self.info._dump_info(f) if self.info.license: with fs.create(os.path.join(self._cache_dir, config.LICENSE_FILENAME)) as f: self.info._dump_license(f)

bf08ea3f95e8209a7afd2b50410ad5db51409d11

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

def _save_info(self): if os.path.exists(self._cache_dir): super()._save_info() else: import apache_beam as beam fs = beam.io.filesystems.FileSystems with fs.create(os.pa

_save_info

sympy/simplify/hyperexpand.py

Code optimizations

sympy

Python

hyperexpand.py

def try_shifted_sum(func, z): abuckets, bbuckets = sift(func.ap, _mod1), sift(func.bq, _mod1) if len(abuckets[S.Zero]) != 1: return None r = abuckets[S.Zero][0] if r <= 0: return None if S.Zero not in bbuckets: return None l = list(bbuckets[S.Zero]) l.sort() k = l[0] if k <= 0: return None nap = list(func.ap) nap.remove(r) nbq = list(func.bq) nbq.remove(k) k -= 1 nap = [x - k for x in nap] nbq = [x - k for x in nbq] ops = [] for n in range(r - 1): ops.append(ShiftA(n + 1)) ops.reverse() fac = factorial(k)/z**k fac *= Mul(*[rf(b, k) for b in nbq]) fac /= Mul(*[rf(a, k) for a in nap]) ops += [MultOperator(fac)] p = 0 for n in range(k): m = z**n/factorial(n) m *= Mul(*[rf(a, n) for a in nap]) m /= Mul(*[rf(b, n) for b in nbq]) p += m return Hyper_Function(nap, nbq), ops, -p

19114acf6514bc87f5c8cfde35e0fcab88965be7

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

def try_shifted_sum(func, z): abuckets, bbuckets = sift(func.ap, _mod1), sift(func.bq, _mod1) if len(abuckets[S.Zero]) != 1: return None r = abuckets[S.Zero][0] if r <= 0: return None if S.Zero not in bbuckets: return None l = list(bbuckets[S.Zero]) l.sort() k = l[0] if k <= 0: return None nap = list(func.ap) nap.remove(r) nbq =

try_shifted_sum

onnx/backend/test/case/node/shape.py

Use Python type annotations rather than comments (#3962) * These have been supported since Python 3.5. ONNX doesn't support Python < 3.6, so we can use the annotations. Diffs generated by https://pypi.org/project/com2ann/. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Remove MYPY conditional logic in gen_proto.py It breaks the type annotations and shouldn't be needed. Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * Get rid of MYPY bool from more scripts Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * move Descriptors class above where its referenced in type annotation Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fixes Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * remove extra blank line Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotations Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix type annotation in gen_docs Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix Operators.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix TestCoverage.md Signed-off-by: Gary Miguel <garymiguel@microsoft.com> * fix protoc-gen-mypy.py Signed-off-by: Gary Miguel <garymiguel@microsoft.com>

onnx

Python

shape.py

def export() -> None: x = np.array([ [1, 2, 3], [4, 5, 6], ]).astype(np.float32) test_shape('_example', x) # preserve names of original test cases x = np.random.randn(3, 4, 5).astype(np.float32) test_shape('', x) # preserve names of original test cases test_shape('_start_1', x, start=1) test_shape('_end_1', x, end=1) test_shape('_start_negative_1', x, start=-1) test_shape('_end_negative_1', x, end=-1) test_shape('_start_1_end_negative_1', x, start=1, end=-1) test_shape('_start_1_end_2', x, start=1, end=2) test_shape('_clip_start', x, start=-10) test_shape('_clip_end', x, end=10)

83fa57c74edfd13ddac9548b8a12f9e3e2ed05bd

https://github.com/onnx/onnx.git

def export() -> None: x = np.array([ [1, 2, 3], [4, 5, 6], ]).astype(np.float32) test_shape('_example', x) # preserve names of original test cases x = np.random.randn(3, 4, 5).astype(np.float32) test_shape('', x) # preserve names of original test cases test_shape('_start_1', x, start=1) test_shape('_end_1', x, end=1) test_shape('_start_negative_1', x, start=-1) test_shape('_end_negative_1', x, end=-1) test_shape('_start_1_end_negative_1', x, start=1, end=-1) test_shape('_start_1_end_2', x, start=1, end=2) test_shape('_clip_

export

tests/sentry/api/endpoints/test_project_profiling_profile.py

feat(profiling): Use new functions endpoint for suspect functions query (#36922) This change uses the new endpoint to query for suspect functions which is backed by the functions table.

sentry

Python

test_project_profiling_profile.py

def test_sort_missing(self): with self.feature(PROFILING_FEATURES): response = self.client.get(self.url) assert response.status_code == 400 assert response.data == { "detail": ErrorDetail( string="Invalid query: Missing value for sort", code="parse_error" ) }

f2fd5c3780796affcf1d7685ba6a3a0634bb6ceb

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

def test_sort_missing(self): with self.f

test_sort_missing

tests/aggregation/tests.py

Refs #33476 -- Reformatted code with Black.

django

Python

tests.py

def test_backwards_m2m_annotate(self): authors = ( Author.objects.filter(name__contains="a") .annotate(Avg("book__rating")) .order_by("name") ) self.assertQuerysetEqual( authors, [ ("Adrian Holovaty", 4.5), ("Brad Dayley", 3.0), ("Jacob Kaplan-Moss", 4.5), ("James Bennett", 4.0), ("Paul Bissex", 4.0), ("Stuart Russell", 4.0), ], lambda a: (a.name, a.book__rating__avg), ) authors = Author.objects.annotate(num_books=Count("book")).order_by("name") self.assertQuerysetEqual( authors, [ ("Adrian Holovaty", 1), ("Brad Dayley", 1), ("Jacob Kaplan-Moss", 1), ("James Bennett", 1), ("Jeffrey Forcier", 1), ("Paul Bissex", 1), ("Peter Norvig", 2), ("Stuart Russell", 1), ("Wesley J. Chun", 1), ], lambda a: (a.name, a.num_books), )

9c19aff7c7561e3a82978a272ecdaad40dda5c00

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

def test_backwards_m2m_annotate(self): authors = ( Author.objects.filter(name__contains="a") .annotate(Avg("book__rating")) .order_by("name") ) self.assertQuerysetEqual( authors, [ ("Adrian Holovaty", 4.5), ("Brad Dayley", 3.0), ("Jacob Kaplan-Moss", 4.5), ("James Bennett", 4.0),

test_backwards_m2m_annotate

tpot/base.py

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

tpot

Python

base.py

def _combine_individual_stats(self, operator_count, cv_score, individual_stats): stats = deepcopy( individual_stats ) # Deepcopy, since the string reference to predecessor should be cloned stats["operator_count"] = operator_count stats["internal_cv_score"] = cv_score return stats

388616b6247ca4ea8de4e2f340d6206aee523541

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

def _combine_individual_stats(self, operator_count, cv_score, individual_stats): stats = deepcopy( individual_stats ) # Deepcopy, since the string reference to predecessor

_combine_individual_stats

erpnext/accounts/report/tax_detail/tax_detail.py

style: format code with black

erpnext

Python

tax_detail.py

def execute(filters=None): if not filters: return [], [] fieldlist = required_sql_fields fieldstr = get_fieldstr(fieldlist) gl_entries = frappe.db.sql( .format( fieldstr=fieldstr ), filters, as_dict=1, ) report_data = modify_report_data(gl_entries) summary = None if filters["mode"] == "run" and filters["report_name"] != "Tax Detail": report_data, summary = run_report(filters["report_name"], report_data) # return columns, data, message, chart, report_summary return get_columns(fieldlist), report_data, None, None, summary

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def execute(filters=None): if not filters: return [], [] fieldlist = required_sql_fields fieldstr = get_fieldstr(fieldlist) gl_entries = frappe.db.sql( .format( fieldstr=fieldstr ), filters, as_dict=1, ) report_data = modify_report_data(gl_entries) summary = None if filters["mode"] == "run" and filters["report_name"] != "Tax Detail": report_data, summary = run_rep

execute

python/ccxt/async_support/okcoin.py

1.72.15 [ci skip]

ccxt

Python

okcoin.py

async def fetch_ohlcv(self, symbol, timeframe='1m', since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) duration = self.parse_timeframe(timeframe) request = { 'instrument_id': market['id'], 'granularity': self.timeframes[timeframe], } options = self.safe_value(self.options, 'fetchOHLCV', {}) defaultType = self.safe_string(options, 'type', 'Candles') # Candles or HistoryCandles type = self.safe_string(params, 'type', defaultType) params = self.omit(params, 'type') method = market['type'] + 'GetInstrumentsInstrumentId' + type if type == 'Candles': if since is not None: if limit is not None: request['end'] = self.iso8601(self.sum(since, limit * duration * 1000)) request['start'] = self.iso8601(since) else: if limit is not None: now = self.milliseconds() request['start'] = self.iso8601(now - limit * duration * 1000) request['end'] = self.iso8601(now) elif type == 'HistoryCandles': if market['option']: raise NotSupported(self.id + ' fetchOHLCV does not have ' + type + ' for ' + market['type'] + ' markets') if since is not None: if limit is None: limit = 300 # default request['start'] = self.iso8601(self.sum(since, limit * duration * 1000)) request['end'] = self.iso8601(since) else: if limit is not None: now = self.milliseconds() request['end'] = self.iso8601(now - limit * duration * 1000) request['start'] = self.iso8601(now) response = await getattr(self, method)(self.extend(request, params)) # # spot markets # # [ # { # close: "0.02683401", # high: "0.02683401", # low: "0.02683401", # open: "0.02683401", # time: "2018-12-17T23:47:00.000Z", # volume: "0" # }, # { # close: "0.02684545", # high: "0.02685084", # low: "0.02683312", # open: "0.02683894", # time: "2018-12-17T20:28:00.000Z", # volume: "101.457222" # } # ] # # futures # # [ # [ # 1545090660000, # 0.3171, # 0.3174, # 0.3171, # 0.3173, # 1648, # 51930.38579450868 # ], # [ # 1545072720000, # 0.3159, # 0.3161, # 0.3144, # 0.3149, # 22886, # 725179.26172331 # ] # ] # return self.parse_ohlcvs(response, market, timeframe, since, limit)

e01461d06258d5c0956f03f4f4b858a183116276

https://github.com/ccxt/ccxt.git

async def fetch_ohlcv(self, symbol, timeframe='1m', since=None, limit=None, params={}): await self.load_markets() market = self.market(symbol) duration = self.parse_timeframe(timeframe) request = { 'instrument_id': market['id'], 'granularity': self.timeframes[timeframe], } options = self.safe_value(self.options, 'fetchOHLCV', {}) defaultType = self.safe_string(options, 'type', 'Candles') # Candles or HistoryCandles type = self.safe_string(params, 'type', defaultType) params = self.omit(params, 'type') method = market['type'] + 'GetInstrumentsInstrumentId' + type if type == 'Candles': if since is not None: if limit is not None: request['end'] = self.iso8601(self.sum(since, limit * duration * 1000)) request['start'] = self.iso8601(since) else: if limit is not None: now = self.milliseconds() request['start'] = self.iso8601(now - limit * duration * 1000) request['end'] = self.iso8601(now) elif type == '

fetch_ohlcv

tests/bots/stocks/options/test_opt_chain.py

Add tests for bots/stocks (#1616) * Added test_quote * Added dps tests * Added more tests * Added government tests * Added insider tests * Added options tests * Added sia tests * Added ta tests * Readd coverage rc * Added test

OpenBBTerminal

Python

test_opt_chain.py

def vcr_config(): return { "filter_headers": [("User-Agent", None)], "filter_query_parameters": [ ("period1", "MOCK_PERIOD_1"), ("period2", "MOCK_PERIOD_2"), ("date", "MOCK_DATE"), ], } @pytest.mark.vcr @pytest.mark.bots @pytest.mark.parametrize( "opt_type, min_sp, max_sp", [("Calls", None, None), ("Puts", 100.0, 1000.0)] )

826cd8a723d8e2b810c51bf8266c09e8e55059c4

@pytest.mark.vcr @pytest.mark.bots @pytest.mark.parametrize( "opt_type, min_sp, max_sp", [("Calls", None, None), ("Puts", 100.0, 1000.0)] )

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

def vcr_config(): return { "filter_headers": [("User-Agent", None)], "filter_query_parameters": [ ("period1", "MOCK_PERIOD_1"), ("period2", "MOCK_PERIOD_2

vcr_config

sklearn/utils/tests/test_utils.py

MNT Replace pytest.warns(None) in test_utils (#23137)

scikit-learn

Python

test_utils.py

def test_get_chunk_n_rows(row_bytes, max_n_rows, working_memory, expected): with warnings.catch_warnings(): warnings.simplefilter("error", UserWarning) actual = get_chunk_n_rows( row_bytes=row_bytes, max_n_rows=max_n_rows, working_memory=working_memory, ) assert actual == expected assert type(actual) is type(expected) with config_context(working_memory=working_memory): with warnings.catch_warnings(): warnings.simplefilter("error", UserWarning) actual = get_chunk_n_rows(row_bytes=row_bytes, max_n_rows=max_n_rows) assert actual == expected assert type(actual) is type(expected)

a739f6ca7cd54bd7a8a3c1e22b54d194098d85af

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

def test_get_chunk_n_rows(row_bytes, max_n_rows, working_memory, expected): with warnings.catch_warnings(): warnings.simplefilter("error", UserWarning) actual = get_chunk_n_rows( row_bytes=row_bytes, max_n_rows=max_n_rows, working_memory=working_memory, ) assert actual == expected assert type(actual) is type(expected) with config_context(working_memory=working_memory): with warnings.catch_warnings(): warnings.simplefilter("e

test_get_chunk_n_rows

homeassistant/components/skybell/binary_sensor.py

Add config flow to skybell (#70887)

core

Python

binary_sensor.py

def extra_state_attributes(self) -> dict[str, str | int | tuple[str, str]]: attrs = super().extra_state_attributes if event := self._event.get(CONST.CREATED_AT): attrs["event_date"] = event return attrs

a502a8798ff74eb6185473df7f69553fc4663634

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

def extra_state_attributes(self) -> dict[str, str | int | tuple[str, str]]: attrs = super(

extra_state_attributes

homeassistant/components/recorder/core.py

Complete strict typing for recorder (#71274) * Complete strict typing for recorder * update tests * Update tests/components/recorder/test_migrate.py Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Update tests/components/recorder/test_migrate.py Co-authored-by: Martin Hjelmare <marhje52@gmail.com> * Remove the asserts * remove ignore comments Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

core

Python

core.py

def get_session(self) -> Session: if self._get_session is None: raise RuntimeError("The database connection has not been established") return self._get_session()

eb77f8db8559dba95e5e36c8a9314f89e1ae82b1

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

def get_session(self) -> Session:

get_session

Tests/test_image_thumbnail.py

Do not call load() before draft()

Pillow

Python

test_image_thumbnail.py

def test_load_first(): # load() may change the size of the image # Test that thumbnail() is calling it before performing size calculations with Image.open("Tests/images/g4_orientation_5.tif") as im: im.thumbnail((64, 64)) assert im.size == (64, 10) # Test thumbnail(), without draft(), # on an image that is large enough once load() has changed the size with Image.open("Tests/images/g4_orientation_5.tif") as im: im.thumbnail((590, 88), reducing_gap=None) assert im.size == (590, 88)

38b53a9fd704570fb29abd10910ea7939b1185e1

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

def test_load_first(): # load() may change the size of the image # Test that thumbnail() is calling it before performing size calculations with Image.open("Tests/images/g4_orientation_5.tif") as im: im.thumbnail((64, 64)) assert im.si

test_load_first

python/ray/tune/tests/test_utils.py

[tune] Add timeout ro retry_fn to catch hanging syncs (#28155) Syncing sometimes hangs in pyarrow for unknown reasons. We should introduce a timeout for these syncing operations. Signed-off-by: Kai Fricke <kai@anyscale.com>

ray

Python

test_utils.py

def test_format_vars(): # Format brackets correctly assert ( format_vars( { ("a", "b", "c"): 8.1234567, ("a", "b", "d"): [7, 8], ("a", "b", "e"): [[[3, 4]]], } ) == "c=8.1235,d=7_8,e=3_4" ) # Sorted by full keys, but only last key is reported assert ( format_vars( { ("a", "c", "x"): [7, 8], ("a", "b", "x"): 8.1234567, } ) == "x=8.1235,x=7_8" ) # Filter out invalid chars. It's ok to have empty keys or values. assert ( format_vars( { ("a c?x",): " <;%$ok ", ("some",): " ", } ) == "a_c_x=ok,some=" )

3590a86db0369ce8a8f9c3965cddc9e4c817c2b8

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

def test_format_vars(): # Format brackets correctly assert ( format_vars( {

test_format_vars

tests/pytests/functional/utils/win_dacl/test_file.py

Add tests

salt

Python

test_file.py

def test_applies_to_this_folder_subfolders_files(test_dir): result = win_dacl.set_permissions( obj_name=test_dir, principal="Backup Operators", permissions="full_control", access_mode="grant", applies_to="this_folder_subfolders_files", obj_type="file", reset_perms=False, protected=None, ) assert result is True expected = { "Not Inherited": { "Backup Operators": { "grant": { "applies to": "This folder, subfolders and files", "permissions": "Full control", } } } } result = win_dacl.get_permissions( obj_name=test_dir, principal="Backup Operators", obj_type="file", ) assert result == expected

72bffdc59f2f62bbaa5e4686d4a408802cec1e89

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

def test_applies_to_this_folder_subfolders_files(test_dir): result = win_dacl.set_permissions( obj_name=test_dir, principal="Backup Operators", permissions="full_control", access_mode="grant", applies_to="this_folder_subfolders_files", obj_type="file", reset_perms=False, protected=None, ) assert result is True expected = { "Not Inherited": { "Backup Operators": { "grant": { "applies to": "This folder, subfolders and files", "permissions": "Full control", } } } } result = win_dacl.get_permissions( obj_name=test_dir, principal="Backup Operators", obj_type="file",

test_applies_to_this_folder_subfolders_files

Lib/test/test_enum.py

bpo-40066: [Enum] update str() and format() output (GH-30582) Undo rejected PEP-663 changes: - restore `repr()` to its 3.10 status - restore `str()` to its 3.10 status New changes: - `IntEnum` and `IntFlag` now leave `__str__` as the original `int.__str__` so that str() and format() return the same result - zero-valued flags without a name have a slightly changed repr(), e.g. `repr(Color(0)) == '<Color: 0>'` - update `dir()` for mixed-in types to return all the methods and attributes of the mixed-in type - added `_numeric_repr_` to `Flag` to control display of unnamed values - enums without doc strings have a more comprehensive doc string added - `ReprEnum` added -- inheriting from this makes it so only `__repr__` is replaced, not `__str__` nor `__format__`; `IntEnum`, `IntFlag`, and `StrEnum` all inherit from `ReprEnum`

cpython

Python

test_enum.py

def test_overridden_str(self): NS = self.NewStrEnum self.assertEqual(str(NS.first), NS.first.name.upper()) self.assertEqual(format(NS.first), NS.first.name.upper())

acf7403f9baea3ae1119fc6b4a3298522188bf96

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

def test_overridden_str(self): NS = self.NewSt

test_overridden_str

tests/sentry/integrations/gitlab/test_issues.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

Python

test_issues.py

def test_after_link_issue_failure(self): responses.add( responses.POST, "https://example.gitlab.com/api/v4/projects/2/issues/321/notes", status=502, ) data = {"externalIssue": "2#321", "comment": "This is not good."} external_issue = ExternalIssue.objects.create( organization_id=self.organization.id, integration_id=self.integration.id, key="2#321" ) with pytest.raises(IntegrationError): self.installation.after_link_issue(external_issue, data=data)

284e980df0018f8baee659999268bdd4c7d08255

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

def test_after_link_issue_failure(self): responses.add( responses.POST, "https://example.gitlab.com/api/v4/projects/2/issues/321/notes", status=502, ) data = {"externalIssue": "2#321", "comment": "This is not good."} external_issue = ExternalIssue.objects.create( organizatio

test_after_link_issue_failure

sympy/integrals/intpoly.py

Updated import locations

sympy

Python

intpoly.py

def left_integral2D(m, index, facets, x0, expr, gens): value = S.Zero for j in range(0, m): intersect = () if j in ((index - 1) % m, (index + 1) % m): intersect = intersection(facets[index], facets[j], "segment2D") if intersect: distance_origin = norm(tuple(map(lambda x, y: x - y, intersect, x0))) if is_vertex(intersect): if isinstance(expr, Expr): if len(gens) == 3: expr_dict = {gens[0]: intersect[0], gens[1]: intersect[1], gens[2]: intersect[2]} else: expr_dict = {gens[0]: intersect[0], gens[1]: intersect[1]} value += distance_origin * expr.subs(expr_dict) else: value += distance_origin * expr return value

498015021131af4dbb07eb110e5badaba8250c7b

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

def left_integral2D(m, index, facets, x0, expr, gens): value = S.Zero for j in range(0, m): intersect = () if j in ((index - 1) % m, (index + 1) % m): intersect = intersection(facets[index], facets[j], "segment2D") if intersect: distance_origin = norm(tuple(map(lambda x, y: x - y, intersect, x0))) if is_vertex(intersect): if isinstance(expr, Expr): if len(gens) == 3: expr_dict = {gens[0]: intersect[0], gens[1]: intersect[1], gens[2]: intersect[2]} else: expr_dict = {gens[0]: intersect[0],

left_integral2D

flair/datasets/treebanks.py

Label logic and new unit tests

flair

Python

treebanks.py

def _read_next_sentence(self, file): line = file.readline() sentence: Sentence = Sentence([]) # current token ID token_idx = 0 # handling for the awful UD multiword format current_multiword_text = "" current_multiword_sequence = "" current_multiword_first_token = 0 current_multiword_last_token = 0 while line: line = line.strip() fields: List[str] = re.split("\t+", line) # end of sentence if line == "": if len(sentence) > 0: break # comments elif line.startswith("#"): line = file.readline() continue # ellipsis elif "." in fields[0]: line = file.readline() continue # if token is a multi-word elif "-" in fields[0]: line = file.readline() current_multiword_first_token = int(fields[0].split("-")[0]) current_multiword_last_token = int(fields[0].split("-")[1]) current_multiword_text = fields[1] current_multiword_sequence = "" if self.split_multiwords: continue else: token = Token(fields[1]) token.add_label("lemma", str(fields[2])) if len(fields) > 9 and "SpaceAfter=No" in fields[9]: token.whitespace_after = False sentence.add_token(token) token_idx += 1 # normal single-word tokens else: # if we don't split multiwords, skip over component words if not self.split_multiwords and token_idx < current_multiword_last_token: token_idx += 1 line = file.readline() continue # add token token = Token(fields[1], head_id=int(fields[6])) token.add_label("lemma", str(fields[2])) token.add_label("upos", str(fields[3])) token.add_label("pos", str(fields[4])) token.add_label("dependency", str(fields[7])) if len(fields) > 9 and "SpaceAfter=No" in fields[9]: token.whitespace_after = False # add morphological tags for morph in str(fields[5]).split("|"): if "=" not in morph: continue token.add_label(morph.split("=")[0].lower(), morph.split("=")[1]) if len(fields) > 10 and str(fields[10]) == "Y": token.add_label("frame", str(fields[11])) token_idx += 1 # derive whitespace logic for multiwords if token_idx <= current_multiword_last_token: current_multiword_sequence += token.text # print(token) # print(current_multiword_last_token) # print(current_multiword_first_token) # if multi-word equals component tokens, there should be no whitespace if token_idx == current_multiword_last_token and current_multiword_sequence == current_multiword_text: # go through all tokens in subword and set whitespace_after information for i in range(current_multiword_last_token - current_multiword_first_token): # print(i) sentence[-(i + 1)].whitespace_after = False sentence.add_token(token) line = file.readline() return sentence

660b3006dfa49841c553ac952624aac5d18b634d

https://github.com/flairNLP/flair.git

def _read_next_sentence(self, file): line = file.readline() sentence: Sentence = Sentence([]) # current token ID token_idx = 0 # handling for the awful UD multiword format current_multiword_text = "" current_multiword_sequence = "" current_multiword_first_token = 0 current_multiword_last_token = 0 while line: line = line.strip() fields: List[str] = re.split("\t+", line) # end of sentence if line == "": if len(sentence) > 0: break # comments elif line.startswith("#"): line = file.readline() continue # ellipsis elif

_read_next_sentence

gamestonk_terminal/cryptocurrency/crypto_controller.py

Baseclass (#1141) * A working decorator * Basic intro * Added more * Refactor * Refactor * Cleaned code * Simplified function (thanks Chavi) * Small change * Updating tests : fix issue with mock * Updating tests : fix remaining mocks after merging * Updating tests : black * Cleaned up * Finished base cases * Notes * Slight changes * Added dynamic options handling, error persists * Fixed pylint issues * Fixed mock * fix decorator with dynamic dictionary of args * move choices from dynamic to const in crypto/ov * Updated var names * Check * Moved decorators * Fixed import issues * Fixed tests, update payoff controller * Fixed tests * Fixed pylint * Updated files * Added base class * Added reset * Improved base class * For James * More menues converted * Added contexts * 24 controllers left * 18 Controllers left * Changes choices * 9 controllers left * Added all controllers * Fixed glitch * Replaced all improper callings of class * Removed menu decorator * refactored try_except * Last commit * Black fix * Bug fix * Added James' new menus * Fixed tests * Fixed 8 tests * Fixing mypy issue * Updating tests : stocks/options * Fixed options * Fixed tests * Updating tests : stocks/options * Fixed tests * More test fixes * Updating tests : stocks/ba * Fixed options test * More bug fixes * Fixed tests * fixed pylint * Skipped test_call_load * Add typings to base class * Fix issue with appending auto completer options + bugfixes * Add typings to base class * Terminal throws error for bad path * sexy solution to auto completer in runtime * more sexy reset with reset_level stored * no so sexy jump between indirect menus * Removing choices argument * refactor custom_reset * Fixed tests * Theo fixes * Added back function * Fixed tests Co-authored-by: Chavithra PARANA <chavithra@gmail.com> Co-authored-by: DidierRLopes <dro.lopes@campus.fct.unl.pt>

OpenBBTerminal

Python

crypto_controller.py

def call_disc(self, _): from gamestonk_terminal.cryptocurrency.discovery.discovery_controller import ( DiscoveryController, ) self.queue = DiscoveryController(queue=self.queue).menu()

006b3570b795215a17c64841110b649b03db9a98

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

def call_disc(self, _): from gamestonk_terminal.cryptocurrency.discovery.discovery_controller import ( DiscoveryController, ) self.queue =

call_disc

wagtail/core/tests/test_blocks.py

Reformat with black

wagtail

Python

test_blocks.py

def test_get_searchable_content_whitespace(self): block = blocks.RichTextBlock() value = RichText("<p>mashed</p><p>po<i>ta</i>toes</p>") result = block.get_searchable_content(value) self.assertEqual(result, ["mashed potatoes"])

d10f15e55806c6944827d801cd9c2d53f5da4186

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

def test_get_searchable_content_whitespace(self): block = blocks.RichTextBlock() value = RichText("<p>mashed</p><p>po<i>ta</i>toes</

test_get_searchable_content_whitespace

tests/providers/google/cloud/hooks/test_dlp.py

Fix new MyPy errors in main (#22884) Those MyPe errors are side effect of some new dependencies.

airflow

Python

test_dlp.py

def test_list_stored_info_types_with_project_id(self, get_conn): result = self.hook.list_stored_info_types(project_id=PROJECT_ID) assert isinstance(result, list) get_conn.return_value.list_stored_info_types.assert_called_once_with( parent=PROJECT_PATH, page_size=None, order_by=None, retry=DEFAULT, timeout=None, metadata=(), )

6933022e94acf139b2dea9a589bb8b25c62a5d20

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

def test_list_stored_info_types_with_project_id(self, get_conn): result = self.hook.list_stored_info_types(project_id=PROJECT_ID) assert isinstance(result, list) get_conn.return_value.list_stored_info_types.assert_called_once_with( parent=PROJECT_PATH, page_size=None, or

test_list_stored_info_types_with_project_id

python/ray/serve/tests/test_schema.py

[Serve] Add deployment graph `import_path` and `runtime_env` to `ServeApplicationSchema` (#24814) A newly planned version of the Serve schema (used in the REST API and CLI) requires the user to pass in their deployment graph's`import_path` and optionally a runtime_env containing that graph. This new schema can then pick up any `init_args` and `init_kwargs` values directly from the graph, instead of requiring them to be serialized and passed explicitly into the REST request. This change: * Adds the `import_path` and `runtime_env` fields to the `ServeApplicationSchema`. * Updates or disables outdated unit tests. Follow-up changes should: * Update the status schemas (i.e. `DeploymentStatusSchema` and `ServeApplicationStatusSchema`). * Remove deployment-level `import_path`s. * Process the new `import_path` and `runtime_env` fields instead of silently ignoring them. * Remove `init_args` and `init_kwargs` from `DeploymentSchema` afterwards. Co-authored-by: Edward Oakes <ed.nmi.oakes@gmail.com>

ray

Python

test_schema.py

def get_invalid_runtime_envs() -> List[Dict]: return [ # Local URIs in working_dir and py_modules { "working_dir": ".", "py_modules": [ "/Desktop/my_project", ( "https://github.com/shrekris-anyscale/" "test_deploy_group/archive/HEAD.zip" ), ], } ]

3a2bd16ecae15d6e26585c32c113dcfe7469ccd7

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

def get_invalid_runtime_envs() -> List[Dict]: return [ # Local URIs in working_dir and py_modules { "working_dir": ".", "py_modules": [ "/Desktop/my_project",

get_invalid_runtime_envs

Tests/test_file_mpo.py

Parametrize tests

Pillow

Python

test_file_mpo.py

def test_app(test_file): # Test APP/COM reader (@PIL135) with Image.open(test_file) as im: assert im.applist[0][0] == "APP1" assert im.applist[1][0] == "APP2" assert ( im.applist[1][1][:16] == b"MPF\x00MM\x00*\x00\x00\x00\x08\x00\x03\xb0\x00" ) assert len(im.applist) == 2 @pytest.mark.parametrize("test_file", test_files)

0ed03d4a58d5f31d570fc9fc391298ce032ad7ce

@pytest.mark.parametrize("test_file", test_files)

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

def test_app(test_file): # Test APP/COM reader (@PIL135) with Image.open(test_file) as im: assert im.applist[0][0] == "APP1" assert im.applist[1][0] == "APP2" assert ( im.applist[1][1][:16] == b"MPF\x00MM\x00*\x00\x00\x00\x08\x00\x03\xb0\x00" ) assert len(im.applist) == 2 @pytest.mark.pa

test_app

sympy/vector/integrals.py

Code optimizations

sympy

Python

integrals.py

def _bounds_case(cls, parameters, limits): V = list(limits.keys()) E = [] for p in V: lower_p = limits[p][0] upper_p = limits[p][1] lower_p = lower_p.atoms() upper_p = upper_p.atoms() E.extend((p, q) for q in V if p != q and (lower_p.issuperset({q}) or upper_p.issuperset({q}))) if not E: return parameters else: return topological_sort((V, E), key=default_sort_key)

19114acf6514bc87f5c8cfde35e0fcab88965be7

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

def _bounds_case(cls, parameters, limits): V = list(limits.keys()) E = [] for p in V: lower_p = limits[p][0] upper_p = limits[p][1] lower_p = lower_p.atoms() upper_p = upper_p.atoms() E.extend((p, q) for q in V if p != q and (lower_p.issuperset({q}) or upper_p.issuperset({q}))) if not E: return parameters else: return topological_sort((V, E), key=default_so

_bounds_case

tests/cli/test_block.py

Remove console, update client logs, fix tests, and add docs

prefect

Python

test_block.py

def test_listing_blocks_after_saving_a_block(): system.JSON(value="a casual test block").save("wildblock") expected_output = ( "ID", "Type", "Name", "Slug", "wildblock", ) invoke_and_assert( ["block", "ls"], expected_code=0, expected_output_contains=expected_output, expected_line_count=9, )

447f475d95da0b19b9d94e9367dee05dd248ed53

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

def test_listing_blocks_after_saving_a_block(): system.JSON(value="a casual test block").save("wildblock") expected_output = ( "ID", "Type", "Name", "Slug", "wildblock", ) invoke_and_assert( ["bl

test_listing_blocks_after_saving_a_block

python3.10.4/Lib/http/server.py

add python 3.10.4 for windows

XX-Net

Python

server.py

def handle_one_request(self): try: self.raw_requestline = self.rfile.readline(65537) if len(self.raw_requestline) > 65536: self.requestline = '' self.request_version = '' self.command = '' self.send_error(HTTPStatus.REQUEST_URI_TOO_LONG) return if not self.raw_requestline: self.close_connection = True return if not self.parse_request(): # An error code has been sent, just exit return mname = 'do_' + self.command if not hasattr(self, mname): self.send_error( HTTPStatus.NOT_IMPLEMENTED, "Unsupported method (%r)" % self.command) return method = getattr(self, mname) method() self.wfile.flush() #actually send the response if not already done. except TimeoutError as e: #a read or a write timed out. Discard this connection self.log_error("Request timed out: %r", e) self.close_connection = True return

8198943edd73a363c266633e1aa5b2a9e9c9f526

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

def handle_one_request(self): try: self.raw_requestline = self.rfile.readline(65537) if len(self.raw_requestline) > 65536: self.requestline = '' self.request_version = '' self.command = '' self.send_error(HTTPStatus.REQUEST_URI_TOO_LONG) return if not self.raw_requestline: self.close_connection = True return if not self.parse_request(): # An error code has been sent, just exit return mname = 'do_' + self.command if not hasattr(self, mname): self.send_error( HTTPStatus.NOT_IMPLEMENTED, "Unsupported method (%r)" % self.command) return method = getattr(self, mn

handle_one_request

test/test_components.py

gr.ScatterPlot component (#2764) * Try clean install * Resolve peer dependencies? * CHANGELOG * Add outbreak_forcast notebook * generate again * CHANGELOG * Add image to changelog * Color palette * Fix colors + legend * Tooltip * Add axis titles * Clean up code a bit + quant scales * Add code * Add size, shape + rename legend title * Fix demo * Add update + demo * Handle darkmode better * Try new font * Use sans-serif * Add caption * Changelog + tests * More tests * Address comments * Make caption fontsize smaller and enable interactivity * Add docstrings + add height + width * Use normal font weight * Make last values keyword only Co-authored-by: Abubakar Abid <abubakar@huggingface.co> * Fix typo * Accept value as fn * reword changelog a bit Co-authored-by: Abubakar Abid <abubakar@huggingface.co>

gradio

Python

test_components.py

def test_update_visibility(self): output = gr.ScatterPlot.update(visible=False) assert not output["visible"] assert output["value"] is gr.components._Keywords.NO_VALUE

f60053d85ffb7f0fd4bb648906914370b7aa4598

https://github.com/gradio-app/gradio.git

def test_update_visibility(self): output = gr.ScatterPlot.update(visible=False) assert not output["visible"] assert output["value"] is

test_update_visibility

dashboard/modules/node/node_head.py

[Dashboard] Remove the view data (#29701) View data is unnecessary in the new dashboard. Same for node detail view. When the node is idle at 250 nodes, CPU usage is about 20~30%, and I found most of usage is from MessageToDict. Since we have lots of view data, I assume most of overhead is from view data.

ray

Python

node_head.py

async def get_all_nodes(self, req) -> aiohttp.web.Response: view = req.query.get("view") if view == "summary": all_node_summary = await DataOrganizer.get_all_node_summary() return dashboard_optional_utils.rest_response( success=True, message="Node summary fetched.", summary=all_node_summary ) elif view is not None and view.lower() == "hostNameList".lower(): alive_hostnames = set() for node in DataSource.nodes.values(): if node["state"] == "ALIVE": alive_hostnames.add(node["nodeManagerHostname"]) return dashboard_optional_utils.rest_response( success=True, message="Node hostname list fetched.", host_name_list=list(alive_hostnames), ) else: return dashboard_optional_utils.rest_response( success=False, message=f"Unknown view {view}" )

9e3e3280e440c3ce026e29c1cc8d1f73f124e21a

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

async def get_all_nodes(self, req) -> aiohttp.web.Response: view = req.query.get("view") if view == "summary": all_node_summary = await DataOrganizer.get_all_node_summary() return dashboard_optional_utils.rest_response( success=True, message="Node summary fetched.", summary=all_node_summary ) elif view is not None and view.lower() == "hostNameList".lower(): alive_hostnames = set() for node in DataSource.nodes.values(): if node["state"] == "ALIVE": alive_hostnames.add(node["nodeManagerHostname"]) return dashboard_optional_utils.rest_response( success=True, message="Node hostname list fetched.", host_name_list=list(alive_hostnames), ) else: return dashboard_optional_utils.rest_response( success=False, message=f"Unknown view {view}"

get_all_nodes

homeassistant/components/vlc/media_player.py

Use new media player enums [u-w] (#78067)

core

Python

media_player.py

def media_play(self) -> None: self._vlc.play() self._state = MediaPlayerState.PLAYING

8bdeb3ca5b27b5d92163a14c7dd7c5eca37cfe13

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

def media_play(self) -> None: self._vlc.play() self._state = MediaP

media_play

tests/components/recorder/test_statistics.py

Reduce size of get_statistics_during_period WS API response (#82131)

core

Python

test_statistics.py

def test_compile_hourly_statistics(hass_recorder): hass = hass_recorder() instance = recorder.get_instance(hass) setup_component(hass, "sensor", {}) zero, four, states = record_states(hass) hist = history.get_significant_states(hass, zero, four) assert dict(states) == dict(hist) # Should not fail if there is nothing there yet stats = get_latest_short_term_statistics( hass, ["sensor.test1"], {"last_reset", "max", "mean", "min", "state", "sum"} ) assert stats == {} for kwargs in ({}, {"statistic_ids": ["sensor.test1"]}): stats = statistics_during_period(hass, zero, period="5minute", **kwargs) assert stats == {} stats = get_last_short_term_statistics( hass, 0, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {} do_adhoc_statistics(hass, start=zero) do_adhoc_statistics(hass, start=four) wait_recording_done(hass) expected_1 = { "start": process_timestamp(zero), "end": process_timestamp(zero + timedelta(minutes=5)), "mean": approx(14.915254237288135), "min": approx(10.0), "max": approx(20.0), "last_reset": None, "state": None, "sum": None, } expected_2 = { "start": process_timestamp(four), "end": process_timestamp(four + timedelta(minutes=5)), "mean": approx(20.0), "min": approx(20.0), "max": approx(20.0), "last_reset": None, "state": None, "sum": None, } expected_stats1 = [expected_1, expected_2] expected_stats2 = [expected_1, expected_2] # Test statistics_during_period stats = statistics_during_period(hass, zero, period="5minute") assert stats == {"sensor.test1": expected_stats1, "sensor.test2": expected_stats2} # Test statistics_during_period with a far future start and end date future = dt_util.as_utc(dt_util.parse_datetime("2221-11-01 00:00:00")) stats = statistics_during_period(hass, future, end_time=future, period="5minute") assert stats == {} # Test statistics_during_period with a far future end date stats = statistics_during_period(hass, zero, end_time=future, period="5minute") assert stats == {"sensor.test1": expected_stats1, "sensor.test2": expected_stats2} stats = statistics_during_period( hass, zero, statistic_ids=["sensor.test2"], period="5minute" ) assert stats == {"sensor.test2": expected_stats2} stats = statistics_during_period( hass, zero, statistic_ids=["sensor.test3"], period="5minute" ) assert stats == {} # Test get_last_short_term_statistics and get_latest_short_term_statistics stats = get_last_short_term_statistics( hass, 0, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {} stats = get_last_short_term_statistics( hass, 1, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {"sensor.test1": [expected_2]} stats = get_latest_short_term_statistics( hass, ["sensor.test1"], {"last_reset", "max", "mean", "min", "state", "sum"} ) assert stats == {"sensor.test1": [expected_2]} metadata = get_metadata(hass, statistic_ids=['sensor.test1"']) stats = get_latest_short_term_statistics( hass, ["sensor.test1"], {"last_reset", "max", "mean", "min", "state", "sum"}, metadata=metadata, ) assert stats == {"sensor.test1": [expected_2]} stats = get_last_short_term_statistics( hass, 2, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {"sensor.test1": expected_stats1[::-1]} stats = get_last_short_term_statistics( hass, 3, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {"sensor.test1": expected_stats1[::-1]} stats = get_last_short_term_statistics( hass, 1, "sensor.test3", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {} instance.get_session().query(StatisticsShortTerm).delete() # Should not fail there is nothing in the table stats = get_latest_short_term_statistics( hass, ["sensor.test1"], {"last_reset", "max", "mean", "min", "state", "sum"} ) assert stats == {} @pytest.fixture

607a0e7697a640e524405f5560868125781bdf0c

@pytest.fixture

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

def test_compile_hourly_statistics(hass_recorder): hass = hass_recorder() instance = recorder.get_instance(hass) setup_component(hass, "sensor", {}) zero, four, states = record_states(hass) hist = history.get_significant_states(hass, zero, four) assert dict(states) == dict(hist) # Should not fail if there is nothing there yet stats = get_latest_short_term_statistics( hass, ["sensor.test1"], {"last_reset", "max", "mean", "min", "state", "sum"} ) assert stats == {} for kwargs in ({}, {"statistic_ids": ["sensor.test1"]}): stats = statistics_during_period(hass, zero, period="5minute", **kwargs) assert stats == {} stats = get_last_short_term_statistics( hass, 0, "sensor.test1", True, {"last_reset", "max", "mean", "min", "state", "sum"}, ) assert stats == {} do_adhoc_statistics(hass, start=zero) do_adhoc_statistics(hass, start=four) wait_recording_done(hass) expected_1 = { "start": process_time

test_compile_hourly_statistics

tests/orion/models/test_orm.py

Add ORM repr

prefect

Python

test_orm.py

async def test_repr(self, db, session, flow): assert repr(flow) == f"Flow(id={flow.id})" assert repr(db.Flow()) == f"Flow(id=None)" flow_id = uuid4() assert repr(db.Flow(id=flow_id)) == f"Flow(id={flow_id})"

763390cded874b2427017347c75f0fd35b743e1a

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

async def test_repr(self, db, session, flow): assert repr(flow) == f"Flow(id={flow.id})" assert repr(db.Flow()) == f"Flow(id=None)" flow_id = uuid4() assert repr(db.Flow(id=flow_id)) == f"Flo

test_repr

python/ray/data/tests/test_stats.py

[Datasets] Refactor `split_at_indices()` to minimize number of split tasks and data movement. (#26363) The current Dataset.split_at_indices() implementation suffers from O(n^2) memory usage in the small-split case (see issue) due to recursive splitting of the same blocks. This PR implements a split_at_indices() algorithm that minimizes the number of split tasks and data movement while ensuring that at most one block is used in each split task, for the sake of memory stability. Co-authored-by: scv119 <scv119@gmail.com>

ray

Python

test_stats.py

def test_dataset_split_stats(ray_start_regular_shared, tmp_path): ds = ray.data.range(100, parallelism=10).map(lambda x: x + 1) dses = ds.split_at_indices([49]) dses = [ds.map(lambda x: x + 1) for ds in dses] for ds_ in dses: stats = canonicalize(ds_.stats()) assert ( stats == )

fb54679a239e4c7368a72a2fe3023cac04380827

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

def test_dataset_split_stats(ray_start_regular_shared, tmp_path): ds = ray.data.range(100, parallelism=10).map(lambda x: x + 1) dses = ds.split_at_indices([49]) dses = [ds.map(lambda x: x + 1) for ds in dses] for ds_ in dses: stats = canonicalize(ds_.stats()) assert (

test_dataset_split_stats

wagtail/images/fields.py

Enforce the use of a single string formatting mechanism for translation source strings Close #9377

wagtail

Python

fields.py

def check_image_pixel_size(self, f): # Upload pixel size checking can be disabled by setting max upload pixel to None if self.max_image_pixels is None: return # Check the pixel size width, height = f.image.get_size() frames = f.image.get_frame_count() num_pixels = width * height * frames if num_pixels > self.max_image_pixels: raise ValidationError( self.error_messages["file_too_many_pixels"] % {"num_pixels": num_pixels, "max_pixels_count": self.max_image_pixels}, code="file_too_many_pixels", )

5c1c2c8f531d96f4568f6dfa6ce71bc32dd9d16c

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

def check_image_pixel_size(self, f): # Upload pixel size checking can be disabled by setting max upload pixel to None if self.max_image_pixels is None: return # Check the pixel size width, height = f.image.get_size() frames = f.image.get_frame_cou

check_image_pixel_size

tests/sentry/models/test_group.py

feat(issue-platform): Include the `IssueOccurrence` with the `GroupEvent` when fetching latest event (#42279) This ensures that when we fetch the latest event for a `Group` that if an `IssueOccurrence` exists and is associated with the event that we fetch it and include it in the `GroupEvent`. This also adds various other necessary work to be able to query this dataset in snuba. I haven't included all the columns, that can happen as needed.

sentry

Python

test_group.py

def test_get_latest_event(self): self.store_event( data={"event_id": "a" * 32, "fingerprint": ["group-1"], "timestamp": self.two_min_ago}, project_id=self.project.id, ) self.store_event( data={"event_id": "b" * 32, "fingerprint": ["group-1"], "timestamp": self.min_ago}, project_id=self.project.id, ) group = Group.objects.first() group_event = group.get_latest_event() assert group_event.event_id == "b" * 32 assert group_event.occurrence is None

32f7a18046786e84cd852334178a3ecedefb12cc

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

def test_get_latest_event(self): self.store_event( data={"event_id": "a" * 32, "fingerprint": ["group-1"], "timestamp": self.two_min_ago}, project_id=self.project.id, ) self.store_event( data={"event_id": "b" * 32, "fingerprint": ["group-1"], "timestamp": self.min_ago}, project_id=self.project.id, ) group = Group.objects.first() group_event = group.

test_get_latest_event

apps/common/permissions.py

fix: fix rbac to dev (#7636) * feat: 添加 RBAC 应用模块 * feat: 添加 RBAC Model、API * feat: 添加 RBAC Model、API 2 * feat: 添加 RBAC Model、API 3 * feat: 添加 RBAC Model、API 4 * feat: RBAC * feat: RBAC * feat: RBAC * feat: RBAC * feat: RBAC * feat: RBAC 整理权限位 * feat: RBAC 整理权限位2 * feat: RBAC 整理权限位2 * feat: RBAC 整理权限位 * feat: RBAC 添加默认角色 * feat: RBAC 添加迁移文件；迁移用户角色->用户角色绑定 * feat: RBAC 添加迁移文件；迁移用户角色->用户角色绑定 * feat: RBAC 修改用户模块API * feat: RBAC 添加组织模块迁移文件 & 修改组织模块API * feat: RBAC 添加组织模块迁移文件 & 修改组织模块API * feat: RBAC 修改用户角色属性的使用 * feat: RBAC No.1 * xxx * perf: 暂存 * perf: ... * perf(rbac): 添加 perms 到 profile serializer 中 * stash * perf: 使用init * perf: 修改migrations * perf: rbac * stash * stash * pref: 修改rbac * stash it * stash: 先去修复其他bug * perf: 修改 role 添加 users * pref: 修改 RBAC Model * feat: 添加权限的 tree api * stash: 暂存一下 * stash: 暂存一下 * perf: 修改 model verbose name * feat: 添加model各种 verbose name * perf: 生成 migrations * perf: 优化权限位 * perf: 添加迁移脚本 * feat: 添加组织角色迁移 * perf: 添加迁移脚本 * stash * perf: 添加migrateion * perf: 暂存一下 * perf: 修改rbac * perf: stash it * fix: 迁移冲突 * fix: 迁移冲突 * perf: 暂存一下 * perf: 修改 rbac 逻辑 * stash: 暂存一下 * perf: 修改内置角色 * perf: 解决 root 组织的问题 * perf: stash it * perf: 优化 rbac * perf: 优化 rolebinding 处理 * perf: 完成用户离开组织的问题 * perf: 暂存一下 * perf: 修改翻译 * perf: 去掉了 IsSuperUser * perf: IsAppUser 去掉完成 * perf: 修改 connection token 的权限 * perf: 去掉导入的问题 * perf: perms define 格式，修改 app 用户 的全新啊 * perf: 修改 permission * perf: 去掉一些 org admin * perf: 去掉部分 org admin * perf: 再去掉点 org admin role * perf: 再去掉部分 org admin * perf: user 角色搜索 * perf: 去掉很多 js * perf: 添加权限位 * perf: 修改权限 * perf: 去掉一个 todo * merge: with dev * fix: 修复冲突 Co-authored-by: Bai <bugatti_it@163.com> Co-authored-by: Michael Bai <baijiangjie@gmail.com> Co-authored-by: ibuler <ibuler@qq.com>

jumpserver

Python

permissions.py

def has_permission(self, request, view): return super().has_permission(request, view) \ and request.user.is_superuser

e259d2a9e9167c58fa75a78d1050dd5dcfde96f4

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

def has_permission(self, request, view): return super().has_permission(request, view) \

has_permission

python3.10.4/Lib/asyncio/base_events.py

add python 3.10.4 for windows

XX-Net

Python

base_events.py

def _do_shutdown(self, future): try: self._default_executor.shutdown(wait=True) self.call_soon_threadsafe(future.set_result, None) except Exception as ex: self.call_soon_threadsafe(future.set_exception, ex)

8198943edd73a363c266633e1aa5b2a9e9c9f526

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

def _do_shutdown(self, future): try: self._default_executor.shutdown(wait=True) self.call_soon_threadsafe(future.set_result, None) except Exception as ex: self.call_soon_threadsafe(future.set_exception, ex)

_do_shutdown

tests/components/webhook/test_init.py

Allow registering a webhook as local only (#63516)

core

Python

test_init.py

async def test_webhook_put(hass, mock_client): hooks = [] webhook_id = webhook.async_generate_id()

7872f87dd74fb4e2b610bb589facc0f763f153ae

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

async def test_webhook_put(hass, mock_client): hooks = [] webhook_i

test_webhook_put

erpnext/accounts/doctype/bank_statement_import/bank_statement_import.py

style: format code with black

erpnext

Python

bank_statement_import.py

def update_mapping_db(bank, template_options): bank = frappe.get_doc("Bank", bank) for d in bank.bank_transaction_mapping: d.delete() for d in json.loads(template_options)["column_to_field_map"].items(): bank.append("bank_transaction_mapping", {"bank_transaction_field": d[1], "file_field": d[0]}) bank.save()

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def update_mapping_db(bank, template_options): bank = frappe.get

update_mapping_db

netbox/extras/forms/customfields.py

Merge v3.1.6

netbox

Python

customfields.py

def _append_customfield_fields(self): for customfield in self._get_custom_fields(self._get_content_type()): field_name = f'cf_{customfield.name}' self.fields[field_name] = self._get_form_field(customfield) # Annotate the field in the list of CustomField form fields self.custom_fields[field_name] = customfield

3e3880823b6f2fb528cd64c00acb863f17e96bae

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

def _append_customfield_fields(self): for customfield in self._get_cu

_append_customfield_fields

tests/components/aws/test_init.py

Upgrade boto3 to 1.20.24 + aiobotocore to 2.1.0 (#64045)

core

Python

test_init.py

async def test_credential_skip_validate(hass): with async_patch("aiobotocore.session.AioSession", new=MockAioSession): await async_setup_component( hass, "aws", { "aws": { "credentials": [ { "name": "key", "aws_access_key_id": "not-valid", "aws_secret_access_key": "dont-care", "validate": False, } ] } }, ) await hass.async_block_till_done() sessions = hass.data[aws.DATA_SESSIONS] assert sessions is not None assert len(sessions) == 1 session = sessions.get("key") assert isinstance(session, MockAioSession) session.get_user.assert_not_awaited()

b17860a7dd283d54bc452e5dca23532d05822589

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

async def test_credential_skip_validate(hass): with async_patch("aiobotocore.session.AioSession", new=MockAioSession): await async_setup_component(

test_credential_skip_validate

awx/sso/pipeline.py

Allow multiple values in SOCIAL_AUTH_SAML_USER_FLAGS_BY_ATTR.is_*_[value|role] settings (#12558)

awx

Python

pipeline.py

def _get_matches(list1, list2): # Because we are just doing an intersection here we don't really care which list is in which parameter # A SAML provider could return either a string or a list of items so we need to coerce the SAML value into a list (if needed) if not isinstance(list1, (list, tuple)): list1 = [list1] # In addition, we used to allow strings in the SAML config instead of Lists. The migration should take case of that but just in case, we will convert our list too if not isinstance(list2, (list, tuple)): list2 = [list2] return set(list1).intersection(set(list2))

782667a34ee45bfe825b29db39c67d4465391bdb

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

def _get_matches(list1, list2): # Because we are just doing an intersection here we don't really care which list is in which parameter # A SAML provider could return either a string or a list of items so we need to coerce the SA

_get_matches

modin/pandas/series.py

FEAT-#4147: Add partial compatibility with Python 3.6 and pandas 1.1 (#4301) Signed-off-by: Devin Petersohn <devin.petersohn@gmail.com> Signed-off-by: Vasily Litvinov <fam1ly.n4me@yandex.ru> Co-authored-by: Alexey Prutskov <lehaprutskov@gmail.com> Co-authored-by: Rehan Durrani <rehan@ponder.io> Co-authored-by: Igoshev, Yaroslav <Poolliver868@mail.ru> Co-authored-by: Myachev, Anatoly <anatoly.myachev@intel.com>

modin

Python

series.py

def _between(self, left, right, inclusive): # noqa: PR01, RT01, D200 return self._default_to_pandas( pandas.Series.between, left, right, inclusive=inclusive )

6ce9cf4daec7f9996038205289bce2186be87611

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

def _between(self, left, right, inclusive): # noqa: PR01, RT01, D200 return self._default_to_pandas( pandas.Series.between, left, right, inclusive=inc

_between

tests/components/hue/test_light_v2.py

Add effects feature to Hue lights (#68567)

core

Python

test_light_v2.py

async def test_lights(hass, mock_bridge_v2, v2_resources_test_data): await mock_bridge_v2.api.load_test_data(v2_resources_test_data) await setup_platform(hass, mock_bridge_v2, "light") # there shouldn't have been any requests at this point assert len(mock_bridge_v2.mock_requests) == 0 # 6 entities should be created from test data (grouped_lights are disabled by default) assert len(hass.states.async_all()) == 6 # test light which supports color and color temperature light_1 = hass.states.get("light.hue_light_with_color_and_color_temperature_1") assert light_1 is not None assert ( light_1.attributes["friendly_name"] == "Hue light with color and color temperature 1" ) assert light_1.state == "on" assert light_1.attributes["brightness"] == int(46.85 / 100 * 255) assert light_1.attributes["mode"] == "normal" assert light_1.attributes["color_mode"] == COLOR_MODE_XY assert set(light_1.attributes["supported_color_modes"]) == { COLOR_MODE_COLOR_TEMP, COLOR_MODE_XY, } assert light_1.attributes["xy_color"] == (0.5614, 0.4058) assert light_1.attributes["min_mireds"] == 153 assert light_1.attributes["max_mireds"] == 500 assert light_1.attributes["dynamics"] == "dynamic_palette" assert light_1.attributes["effect_list"] == ["None", "candle", "fire"] assert light_1.attributes["effect"] == "None" # test light which supports color temperature only light_2 = hass.states.get("light.hue_light_with_color_temperature_only") assert light_2 is not None assert ( light_2.attributes["friendly_name"] == "Hue light with color temperature only" ) assert light_2.state == "off" assert light_2.attributes["mode"] == "normal" assert light_2.attributes["supported_color_modes"] == [COLOR_MODE_COLOR_TEMP] assert light_2.attributes["min_mireds"] == 153 assert light_2.attributes["max_mireds"] == 454 assert light_2.attributes["dynamics"] == "none" assert light_2.attributes["effect_list"] == ["None", "candle", "sunrise"] # test light which supports color only light_3 = hass.states.get("light.hue_light_with_color_only") assert light_3 is not None assert light_3.attributes["friendly_name"] == "Hue light with color only" assert light_3.state == "on" assert light_3.attributes["brightness"] == 128 assert light_3.attributes["mode"] == "normal" assert light_3.attributes["supported_color_modes"] == [COLOR_MODE_XY] assert light_3.attributes["color_mode"] == COLOR_MODE_XY assert light_3.attributes["dynamics"] == "dynamic_palette" # test light which supports on/off only light_4 = hass.states.get("light.hue_on_off_light") assert light_4 is not None assert light_4.attributes["friendly_name"] == "Hue on/off light" assert light_4.state == "off" assert light_4.attributes["mode"] == "normal" assert light_4.attributes["supported_color_modes"] == []

dbef90654f3693401a2df88fa00afbbffbdffcd2

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

async def test_lights(hass, mock_bridge_v2, v2_resources_test_data): await mock_bridge_v2.api.load_test_data(v2_resources_test_data) await setup_platform(hass, mock_bridge_v2, "light") # there shouldn't have been any requests at this point assert len(mock_bridge_v2.mock_requests) == 0 # 6 entities should be created from test data (grouped_lights are disabled by default) assert len(hass.states.async_all()) == 6 # test light which supports color and color temperature light_1 = hass.states.get("light.hue_light_with_color_and_color_temperature_1") assert light_1 is not None assert ( light_1.attributes["friendly_name"] == "Hue light with color and color temperature 1" ) assert light_1.state == "on" assert light_1.attributes["brightness"] == int(46.85 / 100 * 255) assert light_1.attributes["mode"] == "normal" assert light_1.attributes["color_mode"] == COLOR_MODE_XY assert set(light_1.attributes["supported_color_modes"]) == { COLOR_MODE_COLOR_TEMP, COLOR_MODE_XY, } assert light_1.attributes["xy_color"] == (0.5614, 0.4058) assert light_1.attributes["min_mireds"] == 153 assert light_1.attributes["max_mireds"] == 500 assert light_1.attributes["dynamics"] == "dynamic_palette" assert light_1.attributes["effect_list"] == ["None", "candle", "fire"] assert light_1.attributes["effect"] == "None" # test light which supports color temperature only light_2 = hass.states.get("light.hue_light_with_color_temperature_only") assert light_2 is not None assert ( light_2.attributes["friendly_name"] == "Hue light with color temperature only" ) assert light_2.state == "off" assert light_2.attributes["mode"] == "normal" assert light_2.attributes["supported_color_modes"] == [COLOR_MODE_COLOR_TEMP] assert light_2.attributes["min_mireds"] == 153 assert light_2.attributes["max_mireds"] == 454 assert light_2.attributes["dynamics"] == "none" assert light_2.attributes["effect_list"] == ["None", "candle", "sunrise"] # test light which supports color only light_3 = hass.states.get("light.hue_light_with_color_only") assert light_3 is not None assert light_3.attributes["friendly_name"] == "Hue light with color only" assert light_3.state == "on" assert light_3.attributes["brightness"] == 128 assert light_3.attributes["mode"] == "normal" assert light_3.attributes["supported_color_modes"] == [COLOR_MODE_XY] assert light_3.attributes["color_mode"] == COLOR_MODE_XY assert light_3.attributes["dynamics"] == "dynamic_palette" # test light which supports on/off only light_4 = hass.states.get("light.hue_on_off_light") assert light_4 is not None assert light_4.attributes["friendl

test_lights

tests/test_scene_rendering/opengl/test_cli_flags_opengl.py

Migrate more `os.path` to `pathlib` in tests (#2991) * Migrate more `os.path` to `pathlib` in tests * Convert test fixtures to pathlib * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix mypy errors in tests * migrate another pathlib instance Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>

manim

Python

test_cli_flags_opengl.py

def test_mov_can_be_set_as_output_format(tmp_path, manim_cfg_file, simple_scenes_path): scene_name = "SquareToCircle" command = [ sys.executable, "-m", "manim", "--renderer", "opengl", "-ql", "--media_dir", str(tmp_path), "--format", "mov", str(simple_scenes_path), scene_name, ] out, err, exit_code = capture(command) assert exit_code == 0, err unexpected_webm_path = ( tmp_path / "videos" / "simple_scenes" / "480p15" / "SquareToCircle.webm" ) assert not unexpected_webm_path.exists(), "unexpected webm file found at " + str( unexpected_webm_path, ) expected_mov_path = ( tmp_path / "videos" / "simple_scenes" / "480p15" / "SquareToCircle.mov" ) assert expected_mov_path.exists(), "expected .mov file not found at " + str( expected_mov_path, )

206db54af53a87985c0d243d75304ea620dad520

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

def test_mov_can_be_set_as_output_format(tmp_path, manim_cfg_file, simple_scenes_path): scene_name = "SquareToCircle" command = [ sys.executable, "-m

test_mov_can_be_set_as_output_format

tests/sentry/api/endpoints/test_organization_member_details.py

feat(access): Add retirement flag for org roles (#33603) Add an `is_retired` attribute to organization-level roles. Roles marked as retired will be hidden in the UI, and the role can no longer be assigned to members. Members who already have the role will keep it, receiving the associated permissions and minimum team role. Role retirement is gated by the "organizations:team-roles" feature flag. Organizations without the flag will see retired roles as normal.

sentry

Python

test_organization_member_details.py

def test_lists_organization_roles(self): response = self.get_success_response(self.organization.slug, "me") role_ids = [role["id"] for role in response.data["roles"]] assert role_ids == ["member", "admin", "manager", "owner"]

6621356bbf73f25d6e0df98a78360c7db0f9ee42

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

def test_lists_organization_roles(self): response = self.get_success_response(self.organization.slug, "me") role_ids = [role["id"] for role in response.data["roles"]]

test_lists_organization_roles

airbyte-integrations/connectors/source-google-ads/unit_tests/test_google_ads.py

Source Google Ads: handle page token expired exception (#9812) * dynamic date range * raise exception if exites the cycle without error * if range days is 1 already do not retry * added unit tests * added comments * added comments * common mock classes are moved to common module * change read_records * refactored get_date_params * handle corner case * added parse_dates function * added test_streams * check mock calls * fix unit tests for chunk date range refactoring * removed commented codes * remove commented line * refactor test_streams * refactor CustomQuery.get_query * remove TODO * deleted unused json * format * fix chunk_date_range * added docstring * set range_days to 15 for ShoppingPerformanceReport * refactor chunk_date_range * format code 2 * call parent read_records method * add return type in get_date_params * change e to exception * set start_date as end_date * log page token has expired * bump version * updated spec and def yaml Co-authored-by: auganbay <auganenu@gmail.com>

airbyte

Python

test_google_ads.py

def test_get_date_params_with_time_zone(): time_zone_chatham = Timezone("Pacific/Chatham") # UTC+12:45 mock_start_date_chatham = pendulum.today(tz=time_zone_chatham).subtract(days=1).to_date_string() time_zone_honolulu = Timezone("Pacific/Honolulu") # UTC-10:00 mock_start_date_honolulu = pendulum.today(tz=time_zone_honolulu).subtract(days=1).to_date_string() mock_conversion_window_days = 14 incremental_stream_config = dict( conversion_window_days=mock_conversion_window_days, start_date=mock_start_date_chatham, api=MockGoogleAdsClient(SAMPLE_CONFIG), time_zone=time_zone_chatham, ) stream = IncrementalGoogleAdsStream(**incremental_stream_config) start_date_chatham, end_date_chatham = get_date_params( start_date=mock_start_date_chatham, time_zone=stream.time_zone, range_days=stream.range_days ) incremental_stream_config.update({"start_date": mock_start_date_honolulu, "time_zone": time_zone_honolulu}) stream_2 = IncrementalGoogleAdsStream(**incremental_stream_config) start_date_honolulu, end_date_honolulu = get_date_params( start_date=mock_start_date_honolulu, time_zone=stream_2.time_zone, range_days=stream_2.range_days ) assert start_date_honolulu != start_date_chatham and end_date_honolulu != end_date_chatham

359fcd801128239b39297828d39821f631ce00c0

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

def test_get_date_params_with_time_zone(): time_zone_chatham = Timezone("Pacific/Chatham") # UTC+12:45 mock_start_date_chatham = pendulum.today(tz=time_zone_chatham).subtract(days=1).to_date_string() time_zone_honolulu = Timezone("Pacific/Honolulu") # UTC-10:00 mock_start_date_honolulu = pendulum.today(tz=time_zone_honolulu).subtract(days=1).to_date_string() mock_conversion_window_days = 14 incremental_stream_config = dict( conversion_window_days=mock_conversion_window_days, start_date=mock_start_date_chatham, api=MockGoogleAdsClient(SAMPLE_CONFIG), time_zone=time_zone_chatham, ) stream = IncrementalGoogleAdsStream(**incremental_str

test_get_date_params_with_time_zone

tests/pipelines/test_pipelines_common.py

[Pipelines] Add revision tag to all default pipelines (#17667) * trigger test failure * upload revision poc * Update src/transformers/pipelines/base.py Co-authored-by: Julien Chaumond <julien@huggingface.co> * up * add test * correct some stuff * Update src/transformers/pipelines/__init__.py Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * correct require flag Co-authored-by: Julien Chaumond <julien@huggingface.co> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

transformers

Python

test_pipelines_common.py

def test_load_default_pipelines_tf_table_qa(self): import tensorflow as tf set_seed_fn = lambda: tf.random.set_seed(0) # noqa: E731 self.check_default_pipeline("table-question-answering", "tf", set_seed_fn, self.check_models_equal_tf)

e4d2588573f2c68eb792f2d11f092eb2c562bef5

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

def test_load_default_pipelines_tf_table_qa(self): import tensorflow as tf set_seed_fn = lambda: tf.random.set_seed(0) #

test_load_default_pipelines_tf_table_qa

tests/snuba/api/endpoints/test_organization_events_v2.py

fix(discover): Handle unicode values in parameters (#35272) - This handles unicode values in parameters becoming aliased and used in clickhouse which doesn't support that - Uses the ascii values instead eg. u716e - Which works out for the new events endpoint since we transform them back to what was passed in

sentry

Python

test_organization_events_v2.py

def test_count_if(self): unicode_phrase1 = "\u716e\u6211\u66f4\u591a\u7684\u98df\u7269\uff0c\u6211\u9913\u4e86" for i in range(5): data = load_data( "transaction", timestamp=before_now(minutes=(1 + i)), start_timestamp=before_now(minutes=(1 + i), milliseconds=100 if i < 3 else 200), ) data["tags"] = { "sub_customer.is-Enterprise-42": "yes" if i == 0 else "no", "unicode-phrase": unicode_phrase1 if i == 0 else "no", } self.store_event(data, project_id=self.project.id) query = { "field": [ "count_if(transaction.duration, less, 150)", "count_if(transaction.duration, greater, 150)", "count_if(sub_customer.is-Enterprise-42, equals, yes)", "count_if(sub_customer.is-Enterprise-42, notEquals, yes)", f"count_if(unicode-phrase, equals, {unicode_phrase1})", ], "project": [self.project.id], } response = self.do_request(query) assert response.status_code == 200 assert len(response.data["data"]) == 1 assert response.data["data"][0]["count_if(transaction.duration, less, 150)"] == 3 assert response.data["data"][0]["count_if(transaction.duration, greater, 150)"] == 2 assert response.data["data"][0]["count_if(sub_customer.is-Enterprise-42, equals, yes)"] == 1 assert ( response.data["data"][0]["count_if(sub_customer.is-Enterprise-42, notEquals, yes)"] == 4 ) assert response.data["data"][0][f"count_if(unicode-phrase, equals, {unicode_phrase1})"] == 1

d6da9e3f9a72428db7de318fd6c13641dbb41825

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

def test_count_if(self): unicode_phrase1 = "\u716e\u6211\u66f4\u591a\u7684\u98df\u7269\uff0c\u6211\u9913\u4e86" for i in range(5): data = load_data( "transaction", timestamp=before_now(minutes=(1 + i)), start_timestamp=before_now(minutes=(1 + i), milliseconds=100 if i < 3 else 200), ) data["tags"] = { "sub_customer.is-Enterprise-42": "yes" if i == 0 else "no", "unicode-phrase": unicode_phrase1 if i == 0 else "no", } self.store_event(data, project_id=self.project.id) query = { "field": [ "count_if(transaction.duration, less, 150)", "count_if(transaction.duration, greater, 150)", "count_if(sub_customer.is-Enterprise-42, equals, yes)", "count_if(sub_customer.is-Enterprise-42, notEquals, yes)", f"count_if(unicode-phrase, equals, {unicode_phrase1})", ], "project": [self.project.id], } response = self.do_request(query) assert response.status_code == 200 assert len(response.data["data"]) == 1 assert response.data["data"][0]["count_if(transaction.duration, less, 150)"] == 3 assert response.data["data"][0]["count_if(transaction.duration, greater, 150)"] == 2 assert response.data["data"][0]["count_if(sub_customer.is-Enterprise-42, equals, yes)"] == 1 assert ( response.data["data"][0]["count_if(sub_customer.is-Enterprise-42, notEquals, yes)

test_count_if

tests/helpers/fixtures.py

tests: Adjust most imports

qutebrowser

Python

fixtures.py

def webengineview(qtbot, monkeypatch, web_tab_setup): QtWebEngineWidgets = pytest.importorskip('qutebrowser.qt.webenginewidgets') monkeypatch.setattr(objects, 'backend', usertypes.Backend.QtWebEngine) view = QtWebEngineWidgets.QWebEngineView() qtbot.add_widget(view) yield view view.setPage(None) # Avoid warning if using QWebEngineProfile @pytest.fixture

d387b1a1084b9649009e5cffb9d71facc80bb41f

@pytest.fixture

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

def webengineview(qtbot, monkeypatch, web_tab_setup): QtWebEngineWidgets = pytest.importorskip('qutebrowser.qt.webenginewidgets') monkeypatch.setattr(objects, 'backend', usertypes.Backend.QtWebEngine) view = QtWebEngineWidgets.QWebEngineView() qtbot.add_widget(view) yield view view.setPage(No

webengineview

docs/examples/styles/link_hover_color.py

Add example for link hover color.

textual

Python

link_hover_color.py

def compose(self): yield Label( "Visit the [link=https://textualize.io]Textualize[/link] website.", id="lbl1", # (1)! ) yield Label( "Click [@click=app.bell]here[/] for the bell sound.", id="lbl2", # (2)! ) yield Label( "You can also click [@click=app.bell]here[/] for the bell sound.", id="lbl3", # (3)! ) yield Label( "[@click=app.quit]Exit this application.[/]", id="lbl4", # (4)! ) app = LinkHoverColorApp(css_path="link_hover_color.css")

e68e02405f813a5e7c4dc7b8e11bd8cc742d8055

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

def compose(self): yield Label( "Visit the [link=https://textualize.io]Textualize[/link] website.", id="lbl1", # (1)! ) yield Label( "Click [@click=app.bell]here[/] for the bell sound.", id="lbl2", # (2)! ) yield Label( "You can also click [@click=app.bell]here[/] for the bell sound.", id="lbl3", # (3)! ) yield Label( "[@click=app.quit]Exit this application.[/]", id="lbl4", # (4)! ) app = LinkHoverColo

compose

lib/model/layers.py

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

faceswap

Python

layers.py

def call(self, inputs, *args, **kwargs): input_shape = K.int_shape(inputs) if len(input_shape) != 4: raise ValueError('Inputs should have rank ' + str(4) + '; Received input shape:', str(input_shape)) if self.data_format == 'channels_first': batch_size, channels, height, width = input_shape if batch_size is None: batch_size = -1 r_height, r_width = self.size o_height, o_width = height * r_height, width * r_width o_channels = channels // (r_height * r_width) out = K.reshape(inputs, (batch_size, r_height, r_width, o_channels, height, width)) out = K.permute_dimensions(out, (0, 3, 4, 1, 5, 2)) out = K.reshape(out, (batch_size, o_channels, o_height, o_width)) elif self.data_format == 'channels_last': batch_size, height, width, channels = input_shape if batch_size is None: batch_size = -1 r_height, r_width = self.size o_height, o_width = height * r_height, width * r_width o_channels = channels // (r_height * r_width) out = K.reshape(inputs, (batch_size, height, width, r_height, r_width, o_channels)) out = K.permute_dimensions(out, (0, 1, 3, 2, 4, 5)) out = K.reshape(out, (batch_size, o_height, o_width, o_channels)) return out

c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf

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

def call(self, inputs, *args, **kwargs): input_shape = K.int_shape(inputs) if len(input_shape) != 4: raise ValueError('Inputs should have rank ' + str(4) + '; Received input shape:', str(input_shape)) if self.data_format == 'channels_first': batch_size, channels, height, width = input_shape if batch_size is None: batch_size = -1 r_height, r_width = self.size o_height, o_width = height * r_height, width * r_width o_channels = channels // (r_height * r_width) out = K.reshape(inputs, (batch

call

homeassistant/components/openuv/sensor.py

Fix small inconsistency in OpenUV data storage (#64717)

core

Python

sensor.py

def update_from_latest_data(self) -> None: if (data := self.openuv.data[DATA_UV]) is None: self._attr_available = False return self._attr_available = True if self.entity_description.key == TYPE_CURRENT_OZONE_LEVEL: self._attr_native_value = data["ozone"] elif self.entity_description.key == TYPE_CURRENT_UV_INDEX: self._attr_native_value = data["uv"] elif self.entity_description.key == TYPE_CURRENT_UV_LEVEL: if data["uv"] >= 11: self._attr_native_value = UV_LEVEL_EXTREME elif data["uv"] >= 8: self._attr_native_value = UV_LEVEL_VHIGH elif data["uv"] >= 6: self._attr_native_value = UV_LEVEL_HIGH elif data["uv"] >= 3: self._attr_native_value = UV_LEVEL_MODERATE else: self._attr_native_value = UV_LEVEL_LOW elif self.entity_description.key == TYPE_MAX_UV_INDEX: self._attr_native_value = data["uv_max"] if uv_max_time := parse_datetime(data["uv_max_time"]): self._attr_extra_state_attributes.update( {ATTR_MAX_UV_TIME: as_local(uv_max_time)} ) elif self.entity_description.key in ( TYPE_SAFE_EXPOSURE_TIME_1, TYPE_SAFE_EXPOSURE_TIME_2, TYPE_SAFE_EXPOSURE_TIME_3, TYPE_SAFE_EXPOSURE_TIME_4, TYPE_SAFE_EXPOSURE_TIME_5, TYPE_SAFE_EXPOSURE_TIME_6, ): self._attr_native_value = data["safe_exposure_time"][ EXPOSURE_TYPE_MAP[self.entity_description.key] ]

a70c9802839e7e5d57230d9315dc48a8b7124590

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

def update_from_latest_data(self) -> None: if (data := self.openuv.data[DATA_UV]) is None: self._attr_available = False return self._attr_available = True if self.entity_description.key == TYPE_CURRENT_OZONE_LEVEL: self._attr_native_value = data["ozone"] elif self.entity_description.key == TYPE_CURRENT_UV_INDEX: self._attr_native_value = data["uv"] elif self.entity_description.key == TYPE_CURRENT_UV_LEVEL: if data["uv"] >=

update_from_latest_data

d2l/paddle.py

[Paddle]Add chapter_computational-performance (#1167) * [Paddle]Add chapter_computational-performance * add Residual * Fix sgd bugs * remove the number * Fix gpu config * Fix some syntax and describe issue * Update gpu configuration Co-authored-by: w5688414 <w5688414@gmail.com>

d2l-zh

Python

paddle.py

def evaluate_accuracy_gpu(net, data_iter, device=None): if isinstance(net, nn.Layer): net.eval() # 设置为评估模式 if not device: device = next(iter(net.parameters())).place paddle.set_device("gpu:{}".format(str(device)[-2])) # 正确预测的数量，总预测的数量 metric = d2l.Accumulator(2) with paddle.no_grad(): for X, y in data_iter: if isinstance(X, list): # BERT微调所需的 X = [paddle.to_tensor(x, place=device) for x in X] else: X = paddle.to_tensor(X, place=device) y = paddle.to_tensor(y, place=device) metric.add(d2l.accuracy(net(X), y), d2l.size(y)) return metric[0] / metric[1]

b0cb7bed0f74c8c263c38b2a5d9c0fca70db4d56

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

def evaluate_accuracy_gpu(net, data_iter, device=None): if isinstance(net, nn.Layer): net.eval() # 设置为评估模式

evaluate_accuracy_gpu

tests/providers/google/cloud/operators/test_bigquery.py

Add autodetect arg in BQCreateExternalTable Operator (#22710) * Add autodetect parameter * Update docstring * Update google provider documentation

airflow

Python

test_bigquery.py

def test_execute(self, mock_hook): operator = BigQueryCreateExternalTableOperator( task_id=TASK_ID, destination_project_dataset_table=f'{TEST_DATASET}.{TEST_TABLE_ID}', schema_fields=[], bucket=TEST_GCS_BUCKET, source_objects=TEST_GCS_DATA, source_format=TEST_SOURCE_FORMAT, autodetect=True, ) operator.execute(None) mock_hook.return_value.create_external_table.assert_called_once_with( external_project_dataset_table=f'{TEST_DATASET}.{TEST_TABLE_ID}', schema_fields=[], source_uris=[f'gs://{TEST_GCS_BUCKET}/{source_object}' for source_object in TEST_GCS_DATA], source_format=TEST_SOURCE_FORMAT, autodetect=True, compression='NONE', skip_leading_rows=0, field_delimiter=',', max_bad_records=0, quote_character=None, allow_quoted_newlines=False, allow_jagged_rows=False, src_fmt_configs={}, labels=None, encryption_configuration=None, )

f9e18472c0c228fc3de7c883c7c3d26d7ee49e81

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

def test_execute(self, mock_hook): operator = BigQueryCreateExternalTableOperator( task_id=TASK_ID, destination_project_dataset_table=f'{TEST_DATASET}.{TEST_TABLE_ID}', schema_fields=[], bucket=TEST_GCS_BUCKET, source_objects=TEST_GCS_DATA,

test_execute

freqtrade/freqai/data_handler.py

add freqao backend machinery, user interface, documentation

freqtrade

Python

data_handler.py

def append_predictions(self, predictions, do_predict, len_dataframe): ones = np.ones(len_dataframe) s_mean, s_std = ones*self.data['s_mean'], ones*self.data['s_std'] self.predictions = np.append(self.predictions,predictions) self.do_predict = np.append(self.do_predict,do_predict) self.target_mean = np.append(self.target_mean,s_mean) self.target_std = np.append(self.target_std,s_std) return

fc837c4daa27a18ff0e86128f4d52089b88fa5fb

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

def append_predictions(self, predictions, do_predict, len_dataframe): ones = np.ones(len_dataframe) s_mean, s_std = ones*self.data['s_mean'], ones*self.data['s_std'] self.predictions = np.append(self.predictions,predictions) self.do_predict = np.append(self.do_predict,do_predict) self.target_mean = np.append(self.target_mean,s_mean) self.target_std = np.append(self.target_std,s_std) return

append_predictions

tests/test_context.py

Fix errors with multiple tokens and ban behavior

prefect

Python

test_context.py

def test_exiting_a_context_more_than_entering_raises(): context = ExampleContext(x=1) with pytest.raises(RuntimeError, match="Asymmetric use of context"): with context: context.__exit__()

51da0df3edbbf2f812b34616ef2b0fa83c676e04

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

def test_exiting_a_context_more_than_entering_raises(): context = ExampleContext(x=1) with pytest.raises(Run

test_exiting_a_context_more_than_entering_raises

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

Fix `disable_attention_slicing` in pipelines (#498) Fix `disable_attention_slicing` in pipelines.

diffusers

Python

pipeline_stable_diffusion_img2img.py

def disable_attention_slicing(self): r # set slice_size = `None` to disable `set_attention_slice` self.enable_attention_slicing(None)

f7cd6b87e1ee8c7909de760f22f1a6b0c6ae0592

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

def disable_attention_slicing(self): r #

disable_attention_slicing

erpnext/regional/india/e_invoice/utils.py

style: format code with black

erpnext

Python

utils.py

def raise_document_name_too_long_error(): title = _("Document ID Too Long") msg = _("As you have E-Invoicing enabled, to be able to generate IRN for this invoice") msg += ", " msg += _("document id {} exceed 16 letters.").format(bold(_("should not"))) msg += "<br><br>" msg += _("You must {} your {} in order to have document id of {} length 16.").format( bold(_("modify")), bold(_("naming series")), bold(_("maximum")) ) msg += _("Please account for ammended documents too.") frappe.throw(msg, title=title)

494bd9ef78313436f0424b918f200dab8fc7c20b

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

def raise_document_name_too_long_error(): title = _("Document ID Too Long") msg = _("As you have E-Invoicing enabled, to be able to generate IRN for this invoice") msg += ", " msg += _("document id {} exceed 16 letters.").format(bold(_("should not"))) msg

raise_document_name_too_long_error

wagtail/documents/views/chooser.py

Further reshuffles to match generic views as closely as possible

wagtail

Python

chooser.py

def get_context_data(self, **kwargs): context = super().get_context_data(**kwargs) context.update( { "results": self.documents, "table": self.table, "results_url": self.get_results_url(), "is_searching": self.is_searching, "search_query": self.search_query, "can_create": self.can_create(), "collection_id": self.collection_id, } ) if context["can_create"]: creation_form = self.get_creation_form() context.update(self.get_creation_form_context_data(creation_form)) return context

b301fb17a70ad6494a391f17277f8a5410313d69

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

def get_context_data(self, **kwargs): context = super().get_context_dat

get_context_data

tests/freqai/conftest.py

isolate data_drawer functions from data_kitchen, accommodate tests, add new test

freqtrade

Python

conftest.py

def get_patched_data_drawer(mocker, freqaiconf): # dd = mocker.patch('freqtrade.freqai.data_drawer', MagicMock()) dd = FreqaiDataDrawer(freqaiconf) return dd

e213d0ad55db09d83a172019234398b64469de6f

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

def get_patched_data_drawer(mocker, freqaiconf): # dd = mocker.patch('freqtrade.freqai.data_drawer', MagicMock())

get_patched_data_drawer

modin/pandas/groupby.py

REFACTOR-#5026: Change exception names to simplify grepping (#5027) Signed-off-by: Myachev <anatoly.myachev@intel.com>

modin

Python

groupby.py

def __getattr__(self, key): try: return object.__getattribute__(self, key) except AttributeError as err: if key in self._columns: return self.__getitem__(key) raise err

0a2c0de4451f7e2e8f337a9478d7595473aa348e

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

def __getattr__(self, key): try: return object.__getattribute__(self, key) except Attr

__getattr__

tests/sentry/utils/suspect_resolutions/test_commit_correlation.py

fix(suspect-resolutions): Tweak commit correlation logic and track total events (#37891)

sentry

Python

test_commit_correlation.py

def test_no_files_changed(self): project = self.create_project() group1 = self.create_group(project=project, resolved_at=timezone.now()) group2 = self.create_group(project=project, status=GroupStatus.UNRESOLVED) release = self.create_release(project=project, version="1") release2 = self.create_release(project=project, version="2") repo = self.create_repo(project=project, name=project.name) commit = Commit.objects.create( organization_id=project.organization_id, repository_id=repo.id, key="1" ) ReleaseCommit.objects.create( organization_id=project.organization_id, release=release, commit=commit, order=1 ) ReleaseCommit.objects.create( organization_id=project.organization_id, release=release2, commit=commit, order=1 ) GroupRelease.objects.create( project_id=project.id, group_id=group1.id, release_id=release.id, last_seen=(group1.resolved_at - timedelta(hours=2)), ) GroupRelease.objects.create( project_id=project.id, group_id=group2.id, release_id=release2.id, last_seen=(group1.resolved_at - timedelta(hours=2)), ) res1 = get_files_changed_in_releases(group1.resolved_at, group1.id, project.id) res2 = get_files_changed_in_releases(group1.resolved_at, group2.id, project.id) assert res1.files_changed == set() assert res2.files_changed == set() assert res1.release_ids.first().id == release.id assert res2.release_ids.first().id == release2.id assert not is_issue_commit_correlated(group1.id, group2.id, project.id).is_correlated

04193742b952f3ebedfc36857771fc15489f7cd0

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

def test_no_files_changed(self): project = self.create_project() group1 = self.create_group(project=project, resolved_at=timezone.now()) group2 = self.create_group(project=project, status=GroupStatus.UNRESOLVED) release = self.create_release(project=project, version="1") release2 = self.create_release(project=project, version="2") repo = self.create_repo(project=project, name=project.name) commit = Commit.objects.create( organization_id=project.organization_id, repository_id=repo.id, key="1" ) ReleaseCommit.objects.create( organization_id=project.organization_id, release=release, commit=commit, order=1 ) ReleaseCommit.objects.create( organization_id=project.organization_id, release=release2, commit=commit, order=1 )

test_no_files_changed

homeassistant/components/lacrosse_view/sensor.py

Fix LaCrosse View not updating (#79474)

core

Python

sensor.py

def native_value(self) -> float | str: return self.entity_description.value_fn( self.coordinator.data[self.index], self.entity_description.key )

d6a6d0d7548307c143fd2c44a589bd29f729f1e6

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

def native_value(self) -> float | str: return

native_value

lib/ansible/template/__init__.py

refactor and fixes for doc parsing (#77719) * refactor and remove redundant code in documentation allow location and building api to be more accessible fix issues with displaying ansible.legacy and ansible.builtin ensure we don't x2 process tokens (some modules reference them also) fixes #77764 move to constants vs hardcoded more informative errors and comments now have actual filter/test plugins, which expose the filter/test functions moved filter/test loading/finding logic into jinja2pluginloader, removed dupe implementations added tests for case in which we unique by basename when listing Update lib/ansible/utils/plugin_docs.py Co-authored-by: Sloane Hertel <19572925+s-hertel@users.noreply.github.com>

ansible

Python

__init__.py

def __getitem__(self, key): if not isinstance(key, string_types): raise ValueError('key must be a string, got %s instead' % type(key)) if key not in self._loaded_builtins: plugin = None try: plugin = self._pluginloader.get(key) except (AnsibleError, KeyError) as e: raise TemplateSyntaxError('Could not load "%s": %s' % (key, to_native(e)), 0) except Exception as e: display.vvvv('Unexpected plugin load (%s) exception: %s' % (key, to_native(e))) raise e # if a plugin was found/loaded if plugin: # set in filter cache and avoid expensive plugin load self._delegatee[key] = plugin.j2_function self._loaded_builtins.add(key) # let it trigger keyerror if we could not find ours or jinja2 one func = self._delegatee[key] # if i do have func and it is a filter, it nees wrapping if self._pluginloader.type == 'filter': # filter need wrapping if key in C.STRING_TYPE_FILTERS: # avoid litera_eval when you WANT strings func = _wrap_native_text(func) else: # conditionally unroll iterators/generators to avoid having to use `|list` after every filter func = _unroll_iterator(func) return func

4260b71cc77b7a44e061668d0d408d847f550156

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

def __getitem__(self, key): if not isinstance(key, string_types): raise ValueError('key must be a string, got %s instead' % type(key)) if key not in self._loaded_builtins: plugin = None try: plugin = self._pluginloader.get(key) except (AnsibleError, KeyError) as e: raise TemplateSyntaxError('Could not load "%s": %s' % (key, to_native(e)), 0) except Exception as e: display.vvvv('Unexpected plugin load (%s) exception: %s' % (key, to_native(e))) raise e # if a plugin was found/loaded if plugin: # set in filter cache and avoid expensive plugin load self._delegatee[key] = plugin.j2_function self._loaded_builtins.add(key) # let it trigger keyerror if we could not find ours or jinja2 one func = self._delegatee[key] # if i do have func and it is a filter, it nees wrapping if self._pluginloader.type == 'filter': # filter need wrappin

__getitem__

lib/matplotlib/axis.py

DOC: More cleanup axes -> Axes

matplotlib

Python

axis.py

def tick_bottom(self): label = True if 'label1On' in self._major_tick_kw: label = (self._major_tick_kw['label1On'] or self._major_tick_kw['label2On']) self.set_ticks_position('bottom') # If labels were turned off before this was called, leave them off. self.set_tick_params(which='both', labelbottom=label)

f156db08eee54d285ab0fb4e031e48d078ba6aa3

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

def tick_bottom(self): label = True if 'label1On' in self._major_tick_kw: label = (self._major_tick_kw['label1On'] or self._major_tick_kw['label2On'])

tick_bottom

flair/embeddings/transformer.py

move transformer embeddings to own file

flair

Python

transformer.py

def __getstate__(self): config_dict = self.model.config.to_dict() tokenizer_data = self._tokenizer_bytes() model_state = { "model": self.base_model_name, "fine_tune": self.fine_tune, "layers": ",".join(map(str, self.layer_indexes)), "layer_mean": self.layer_mean, "subtoken_pooling": self.subtoken_pooling, "cls_pooling": self.cls_pooling, "is_token_embedding": self.token_embedding, "is_document_embedding": self.document_embedding, "allow_long_sentences": self.allow_long_sentences, "config_state_dict": config_dict, "tokenizer_data": tokenizer_data, "name": self.name, "context_length": self.context_length, "respect_document_boundaries": self.respect_document_boundaries, "context_dropout": self.context_dropout, } return model_state

6ffedc473b3d89bff82dc45c5fd16c9003111f86

https://github.com/flairNLP/flair.git

def __getstate__(self): config_dict = self.model.config.to_dict()

__getstate__

tests/rpc/test_rpc.py

add /stopentry alias for /stopbuy

freqtrade

Python

test_rpc.py

def test_rpc_stopentry(mocker, default_conf) -> None: mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock()) mocker.patch.multiple( 'freqtrade.exchange.Exchange', fetch_ticker=MagicMock() ) freqtradebot = get_patched_freqtradebot(mocker, default_conf) patch_get_signal(freqtradebot) rpc = RPC(freqtradebot) freqtradebot.state = State.RUNNING assert freqtradebot.config['max_open_trades'] != 0 result = rpc._rpc_stopentry() assert {'status': 'No more entries will occur from now. Run /reload_config to reset.'} == result assert freqtradebot.config['max_open_trades'] == 0

b9f35cadb330763e70c52dd867ab74dc4555a94e

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

def test_rpc_stopentry(mocker, default_conf) -> None: mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock()) mocker.patch.multiple( 'freq

test_rpc_stopentry

examples/tutorial/jupyter/execution/pandas_on_ray/test/test_notebooks.py

REFACTOR-#4213: Refactor `modin/examples/tutorial/` directory (#4214) Signed-off-by: Igoshev, Yaroslav <yaroslav.igoshev@intel.com>

modin

Python

test_notebooks.py

def test_exercise_2(): modified_notebook_path = ( "examples/tutorial/jupyter/execution/pandas_on_ray/local/exercise_2_test.ipynb" ) nb = nbformat.read( "examples/tutorial/jupyter/execution/pandas_on_ray/local/exercise_2.ipynb", as_version=nbformat.NO_CONVERT, ) _replace_str( nb, 'path = "s3://dask-data/nyc-taxi/2015/yellow_tripdata_2015-01.csv"', '# path = "s3://dask-data/nyc-taxi/2015/yellow_tripdata_2015-01.csv"', ) new_optional_cell = f'path = "{test_dataset_path}"\n' + download_taxi_dataset optional_cell_idx = _find_code_cell_idx(nb, "[Optional] Download data locally.") nb["cells"][optional_cell_idx]["source"] = new_optional_cell nbformat.write(nb, modified_notebook_path) _execute_notebook(modified_notebook_path) # in this notebook user should add custom mad implementation # to make notebook work

6f20abdf65515b7dd0d451259f41ccc010c1f7a4

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

def test_exercise_2(): modified_notebook_path = ( "examples/tutorial/jupyter/execution/pandas_on_ray/local/exercise_2_test.ipynb" ) nb = nbformat.read( "examples/tutorial/jupyter/execution/pandas_on_ray/local/exercise_2.ipynb", as_version=nbformat.NO_CONVERT, ) _replace_str( nb, 'path = "s3://dask-data/nyc-taxi/2015/yellow_tripdata_2015-01.csv"', '# path = "s3://dask-data/nyc-taxi/2015/

test_exercise_2

saleor/tests/fixtures.py

Refactor app tokens (#9438) * Save last_4 chars of current app tokens and store their hashes * Update app mutations, commands and tests * Update changelog Co-authored-by: Marcin Gębala <5421321+maarcingebala@users.noreply.github.com>

saleor

Python

fixtures.py

def app_with_token(db): app = App.objects.create(name="Sample app objects", is_active=True) app.tokens.create(name="Test") return app @pytest.fixture

81d02e76b22e3d3b3603e5ae27c5788033ac01b3

@pytest.fixture

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

def app_with_token(db): app = App.objects.create(name=

app_with_token

tests/test_settings.py

Using new settings access pattern everywhere

prefect

Python

test_settings.py

def test_nested_settings(monkeypatch): assert get_current_settings().get(PREFECT_ORION_DATABASE_ECHO) is False monkeypatch.setenv("PREFECT_ORION_DATABASE_ECHO", "1") new_settings = Settings() assert new_settings.get(PREFECT_ORION_DATABASE_ECHO) is True @pytest.mark.parametrize( "value,expected", [ ("foo", ["foo"]), ("foo,bar", ["foo", "bar"]), ("foo, bar, foobar ", ["foo", "bar", "foobar"]), ], )

38a964d05aba99c743802b158ffb7f16201d85aa

@pytest.mark.parametrize( "value,expected", [ ("foo", ["foo"]), ("foo,bar", ["foo", "bar"]), ("foo, bar, foobar ", ["foo", "bar", "foobar"]), ], )

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

def test_nested_settings(monkeypatch): assert get_current_settings().get(PREFECT_ORION_DATABASE_ECHO) is False monkeypatch.setenv("PREFECT_ORION_DATABASE_ECHO", "1") new_settings = S

test_nested_settings

erpnext/accounts/general_ledger.py

test: Unit test for round off entry dimensions

erpnext

Python

general_ledger.py

def update_accounting_dimensions(round_off_gle): dimensions = get_accounting_dimensions() meta = frappe.get_meta(round_off_gle["voucher_type"]) has_all_dimensions = True for dimension in dimensions: if not meta.has_field(dimension): has_all_dimensions = False if dimensions and has_all_dimensions: dimension_values = frappe.db.get_value( round_off_gle["voucher_type"], round_off_gle["voucher_no"], dimensions, as_dict=1 ) for dimension in dimensions: round_off_gle[dimension] = dimension_values.get(dimension)

3fa1c634790095bf7eabc135ed717e124efa4ff0

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

def update_accounting_dimensions(round_off_gle): dimensions = get_accounting_dimensions() meta = frappe.get_met

update_accounting_dimensions

tools/infer/predict_rec.py

fix sar export

PaddleOCR

Python

predict_rec.py

def __call__(self, img_list): img_num = len(img_list) # Calculate the aspect ratio of all text bars width_list = [] for img in img_list: width_list.append(img.shape[1] / float(img.shape[0])) # Sorting can speed up the recognition process indices = np.argsort(np.array(width_list)) rec_res = [['', 0.0]] * img_num batch_num = self.rec_batch_num st = time.time() if self.benchmark: self.autolog.times.start() for beg_img_no in range(0, img_num, batch_num): end_img_no = min(img_num, beg_img_no + batch_num) norm_img_batch = [] imgC, imgH, imgW = self.rec_image_shape[:3] max_wh_ratio = imgW / imgH # max_wh_ratio = 0 for ino in range(beg_img_no, end_img_no): h, w = img_list[indices[ino]].shape[0:2] wh_ratio = w * 1.0 / h max_wh_ratio = max(max_wh_ratio, wh_ratio) for ino in range(beg_img_no, end_img_no): if self.rec_algorithm == "SAR": norm_img, _, _, valid_ratio = self.resize_norm_img_sar( img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] valid_ratio = np.expand_dims(valid_ratio, axis=0) valid_ratios = [] valid_ratios.append(valid_ratio) norm_img_batch.append(norm_img) elif self.rec_algorithm == "SRN": norm_img = self.process_image_srn( img_list[indices[ino]], self.rec_image_shape, 8, 25) encoder_word_pos_list = [] gsrm_word_pos_list = [] gsrm_slf_attn_bias1_list = [] gsrm_slf_attn_bias2_list = [] encoder_word_pos_list.append(norm_img[1]) gsrm_word_pos_list.append(norm_img[2]) gsrm_slf_attn_bias1_list.append(norm_img[3]) gsrm_slf_attn_bias2_list.append(norm_img[4]) norm_img_batch.append(norm_img[0]) elif self.rec_algorithm == "SVTR": norm_img = self.resize_norm_img_svtr(img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == "VisionLAN": norm_img = self.resize_norm_img_vl(img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == 'SPIN': norm_img = self.resize_norm_img_spin(img_list[indices[ino]]) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == "ABINet": norm_img = self.resize_norm_img_abinet( img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) else: norm_img = self.resize_norm_img(img_list[indices[ino]], max_wh_ratio) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) norm_img_batch = np.concatenate(norm_img_batch) norm_img_batch = norm_img_batch.copy() if self.benchmark: self.autolog.times.stamp() if self.rec_algorithm == "SRN": encoder_word_pos_list = np.concatenate(encoder_word_pos_list) gsrm_word_pos_list = np.concatenate(gsrm_word_pos_list) gsrm_slf_attn_bias1_list = np.concatenate( gsrm_slf_attn_bias1_list) gsrm_slf_attn_bias2_list = np.concatenate( gsrm_slf_attn_bias2_list) inputs = [ norm_img_batch, encoder_word_pos_list, gsrm_word_pos_list, gsrm_slf_attn_bias1_list, gsrm_slf_attn_bias2_list, ] if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = {"predict": outputs[2]} else: input_names = self.predictor.get_input_names() for i in range(len(input_names)): input_tensor = self.predictor.get_input_handle( input_names[i]) input_tensor.copy_from_cpu(inputs[i]) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) if self.benchmark: self.autolog.times.stamp() preds = {"predict": outputs[2]} elif self.rec_algorithm == "SAR": valid_ratios = np.concatenate(valid_ratios) inputs = [ norm_img_batch, np.array( [valid_ratios], dtype=np.float32), ] if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = outputs[0] else: input_names = self.predictor.get_input_names() for i in range(len(input_names)): input_tensor = self.predictor.get_input_handle( input_names[i]) input_tensor.copy_from_cpu(inputs[i]) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) if self.benchmark: self.autolog.times.stamp() preds = outputs[0] else: if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = outputs[0] else: self.input_tensor.copy_from_cpu(norm_img_batch) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) if self.benchmark: self.autolog.times.stamp() if len(outputs) != 1: preds = outputs else: preds = outputs[0] rec_result = self.postprocess_op(preds) for rno in range(len(rec_result)): rec_res[indices[beg_img_no + rno]] = rec_result[rno] if self.benchmark: self.autolog.times.end(stamp=True) return rec_res, time.time() - st

6e89ec8d09c06453edeee3874a826e750a6947d6

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

def __call__(self, img_list): img_num = len(img_list) # Calculate the aspect ratio of all text bars width_list = [] for img in img_list: width_list.append(img.shape[1] / float(img.shape[0])) # Sorting can speed up the recognition process indices = np.argsort(np.array(width_list)) rec_res = [['', 0.0]] * img_num batch_num = self.rec_batch_num st = time.time() if self.benchmark: self.autolog.times.start() for beg_img_no in range(0, img_num, batch_num): end_img_no = min(img_num, beg_img_no + batch_num) norm_img_batch = [] imgC, imgH, imgW = self.rec_image_shape[:3] max_wh_ratio = imgW / imgH # max_wh_ratio = 0 for ino in range(beg_img_no, end_img_no): h, w = img_list[indices[ino]].shape[0:2] wh_ratio = w * 1.0 / h max_wh_ratio = max(max_wh_ratio, wh_ratio) for ino in range(beg_img_no, end_img_no): if self.rec_algorithm == "SAR": norm_img, _, _, valid_ratio = self.resize_norm_img_sar( img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] valid_ratio = np.expand_dims(valid_ratio, axis=0) valid_ratios = [] valid_ratios.append(valid_ratio) norm_img_batch.append(norm_img) elif self.rec_algorithm == "SRN": norm_img = self.process_image_srn( img_list[indices[ino]], self.rec_image_shape, 8, 25) encoder_word_pos_list = [] gsrm_word_pos_list = [] gsrm_slf_attn_bias1_list = [] gsrm_slf_attn_bias2_list = [] encoder_word_pos_list.append(norm_img[1]) gsrm_word_pos_list.append(norm_img[2]) gsrm_slf_attn_bias1_list.append(norm_img[3]) gsrm_slf_attn_bias2_list.append(norm_img[4]) norm_img_batch.append(norm_img[0]) elif self.rec_algorithm == "SVTR": norm_img = self.resize_norm_img_svtr(img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == "VisionLAN": norm_img = self.resize_norm_img_vl(img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == 'SPIN': norm_img = self.resize_norm_img_spin(img_list[indices[ino]]) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) elif self.rec_algorithm == "ABINet": norm_img = self.resize_norm_img_abinet( img_list[indices[ino]], self.rec_image_shape) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) else: norm_img = self.resize_norm_img(img_list[indices[ino]], max_wh_ratio) norm_img = norm_img[np.newaxis, :] norm_img_batch.append(norm_img) norm_img_batch = np.concatenate(norm_img_batch) norm_img_batch = norm_img_batch.copy() if self.benchmark: self.autolog.times.stamp() if self.rec_algorithm == "SRN": encoder_word_pos_list = np.concatenate(encoder_word_pos_list) gsrm_word_pos_list = np.concatenate(gsrm_word_pos_list) gsrm_slf_attn_bias1_list = np.concatenate( gsrm_slf_attn_bias1_list) gsrm_slf_attn_bias2_list = np.concatenate( gsrm_slf_attn_bias2_list) inputs = [ norm_img_batch, encoder_word_pos_list, gsrm_word_pos_list, gsrm_slf_attn_bias1_list, gsrm_slf_attn_bias2_list, ] if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = {"predict": outputs[2]} else: input_names = self.predictor.get_input_names() for i in range(len(input_names)): input_tensor = self.predictor.get_input_handle( input_names[i]) input_tensor.copy_from_cpu(inputs[i]) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) if self.benchmark: self.autolog.times.stamp() preds = {"predict": outputs[2]} elif self.rec_algorithm == "SAR": valid_ratios = np.concatenate(valid_ratios) inputs = [ norm_img_batch, np.array( [valid_ratios], dtype=np.float32), ] if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = outputs[0] else: input_names = self.predictor.get_input_names() for i in range(len(input_names)): input_tensor = self.predictor.get_input_handle( input_names[i]) input_tensor.copy_from_cpu(inputs[i]) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) if self.benchmark: self.autolog.times.stamp() preds = outputs[0] else: if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = norm_img_batch outputs = self.predictor.run(self.output_tensors, input_dict) preds = outputs[0] else: self.input_tensor.copy_from_cpu(norm_img_batch) self.predictor.run() outputs = [] for output_tensor in self.output_tensors: ou

__call__

packages/syft/src/syft/core/adp/data_subject_list.py

Implement DSL setitem properly AT LONG LAST

PySyft

Python

data_subject_list.py

def __getitem__(self, item) -> DataSubjectList: result = self.data_subjects_indexed[item] return DataSubjectList( one_hot_lookup=self.one_hot_lookup, # np.unique(self.one_hot_lookup[result]), data_subjects_indexed=result, )

d171fcd8726dccfffd7d13f5188a7a91cffc5b6b

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

def __getitem__(self, item) -> DataSubjectList: result = self.data_subjects_indexed[item] return DataSubjectList( one_ho

__getitem__

code/default/launcher/tests/integrate_testing.py

Improve testing.

XX-Net

Python

integrate_testing.py

def xtunnel_logout(self): xlog.info("Start testing XTunnel logout") res = simple_http_client.request("POST", "http://127.0.0.1:8085/module/x_tunnel/control/logout", timeout=10) self.assertEqual(res.status, 200) self.xtunnel_login_status = False xlog.info("Finished testing XTunnel logout")

1bfb2da67c76758578eff6f3a7c3e6cf4967bc77

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

def xtunnel_logout(self): xlog.info("Start testing XTunnel logout") res = simple_http_client.request("P

xtunnel_logout

mkdocs/commands/gh_deploy.py

Format code with `black -l100 --skip-string-normalization`

mkdocs

Python

gh_deploy.py

def _is_cwd_git_repo(): try: proc = subprocess.Popen( ['git', 'rev-parse', '--is-inside-work-tree'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) except FileNotFoundError: log.error("Could not find git - is it installed and on your path?") raise Abort('Deployment Aborted!') proc.communicate() return proc.wait() == 0

dca7cbb43fcd6ea7c677c98ba585395b070d387b

https://github.com/mkdocs/mkdocs.git

def _is_cwd_git_repo(): try: proc = subprocess.Popen( ['git', 'rev-parse', '--is-inside-work-tree'], stdout=sub

_is_cwd_git_repo

thumbor/engines/__init__.py

Reformat to 80 chars and mypy.ini

thumbor

Python

__init__.py

def is_multiple(self): return ( hasattr(self, "multiple_engine") and self.multiple_engine is not None )

301124c5b377fa56b940d298900dbc5816dbc24e

https://github.com/thumbor/thumbor.git

def is_multiple(self): return ( hasattr(self, "multiple_engine")

is_multiple

test/mitmproxy/utils/test_magisk.py

Magisk module onboarding for Android (#5547) * Added magisk module generation * Fixed typo * changelog * Fixed mypy bug * Changed action based on ubuntu 18.04 due to https://bit.ly/3QOw87Z * Workflow pinned to ubuntu 20.04 * Moved magisk code to utils and gen on download * Styling * Removed magisk from git repo * Added tests * Fixed dead line * Update CHANGELOG.md * Hardcoded hash Co-authored-by: Joran van Apeldoorn <joran@bitsoffreedom.nl> Co-authored-by: Maximilian Hils <github@maximilianhils.com>

mitmproxy

Python

test_magisk.py

def test_subject_hash_old(tdata): # checks if the hash is the same as that comming form openssl with taddons.context() as tctx: tctx.options.confdir = tdata.path("mitmproxy/data/confdir") ca = magisk.get_ca_from_files() our_hash = magisk.subject_hash_old(ca) assert our_hash == "efb15d7d"

cba66953a303c4411a47f987170e08f30110c6ed

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

def test_subject_hash_old(tdata): # ch

test_subject_hash_old

erpnext/stock/report/incorrect_serial_no_valuation/incorrect_serial_no_valuation.py

refactor: DB independent quoting and truthy/falsy values (#31358) * refactor: DB independent quoting and truthy/falsy values * style: reformat to black spec * fix: ifnull -> coalesce * fix: coalesce -> Coalesce * fix: revert pypika comparison * refactor: convert queries to QB * fix: incorrect value types for query `=` query makes no sense with list of values * fix: remove warehouse docstatus condition * fix: keep using base rate as rate Co-authored-by: Ankush Menat <ankush@frappe.io>

erpnext

Python

incorrect_serial_no_valuation.py

def get_stock_ledger_entries(report_filters): fields = [ "name", "voucher_type", "voucher_no", "item_code", "serial_no as serial_nos", "actual_qty", "posting_date", "posting_time", "company", "warehouse", "(stock_value_difference / actual_qty) as valuation_rate", ] filters = {"serial_no": ("is", "set"), "is_cancelled": 0} if report_filters.get("item_code"): filters["item_code"] = report_filters.get("item_code") if report_filters.get("from_date") and report_filters.get("to_date"): filters["posting_date"] = ( "between", [report_filters.get("from_date"), report_filters.get("to_date")], ) return frappe.get_all( "Stock Ledger Entry", fields=fields, filters=filters, order_by="posting_date asc, posting_time asc, creation asc", )

74a782d81d8f8c4a4d9214a9c06377e5e6e464dd

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

def get_stock_ledger_entries(report_filters): fields = [ "name", "voucher_type", "voucher_no", "item_code", "serial_no as serial_nos", "actual_qty", "posting_date", "posting_time", "company", "warehouse", "(stock_value_difference / actual_qty) as valuation_rate", ] filters = {"serial_no": ("is", "set"), "is_cancelled": 0} if report_filters.get("item_code"): filters["item_code"] = report_filters.get("item_code") if report_filters.get("from_date") and report_filters.get("to_date"): filters["posting_date"] = ( "between", [report_filters.get("from_date"), report_filters.get("to_date")], ) return frappe.get_all( "Stock Ledger Entry", fields=fields, filters=filters

get_stock_ledger_entries

dash/_validate.py

f-strings everywhere! fffff

dash

Python

_validate.py

def validate_callback(outputs, inputs, state, extra_args, types): Input, Output, State = types if extra_args: if not isinstance(extra_args[0], (Output, Input, State)): raise exceptions.IncorrectTypeException( dedent( f ) ) raise exceptions.IncorrectTypeException( dedent( f ) ) for args in [outputs, inputs, state]: for arg in args: validate_callback_arg(arg)

c3c84b9ecf16bcc61ed80ec39d511af92fe07f2c

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

def validate_callback(outputs, inputs, state, extra_args, types): Input, Output, State = types if extra_args: if not isinstance(extra_args[0], (Output, Input, State)): raise exceptions.IncorrectTypeException( dedent( f ) ) raise exceptions.Incorr

validate_callback

keras/feature_column/sequence_feature_column_test.py

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

keras

Python

sequence_feature_column_test.py

def test_shared_embedding_column_with_non_sequence_categorical(self): with tf.Graph().as_default(): vocabulary_size = 3 sparse_input_a = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) sparse_input_b = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) categorical_column_a = ( tf.feature_column.categorical_column_with_identity( key="aaa", num_buckets=vocabulary_size ) ) categorical_column_b = ( tf.feature_column.categorical_column_with_identity( key="bbb", num_buckets=vocabulary_size ) ) shared_embedding_columns = tf.feature_column.shared_embeddings( [categorical_column_a, categorical_column_b], dimension=2 ) sequence_input_layer = ksfc.SequenceFeatures( shared_embedding_columns ) with self.assertRaisesRegex( ValueError, r"In embedding_column: aaa_shared_embedding\. " r"categorical_column must " r"be of type SequenceCategoricalColumn to use SequenceFeatures\.", ): _, _ = sequence_input_layer( {"aaa": sparse_input_a, "bbb": sparse_input_b} )

84afc5193d38057e2e2badf9c889ea87d80d8fbf

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

def test_shared_embedding_column_with_non_sequence_categorical(self): with tf.Graph().as_default(): vocabulary_size = 3 sparse_input_a = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) sparse_input_b = tf.compat.v1.SparseTensorValue( # example 0, ids [2] # example 1, ids [0, 1] indices=((0, 0), (1, 0), (1, 1)), values=(2, 0, 1), dense_shape=(2, 2), ) categorical_column_a = ( tf.feature_column.categorical_column_with_identity( key="aaa", num_buckets=vocabulary_size ) ) categorical_column_b = ( tf.feature_column.categorical_column_with_identity( key="bbb", num_buckets=vocabulary_size ) ) shared_embedding_columns = tf.feature_column.shared_embeddings( [categorical_column_

test_shared_embedding_column_with_non_sequence_categorical

tests/sentry/api/endpoints/test_accept_organization_invite.py

chore(hybrid-cloud): use organization_slug in AcceptOrganizationInvite API (#42138)

sentry

Python

test_accept_organization_invite.py

def test_cannot_accept_unapproved_invite(self): self.login_as(self.user) om = OrganizationMember.objects.create( email="newuser@example.com", role="member", token="abc", organization=self.organization, invite_status=InviteStatus.REQUESTED_TO_JOIN.value, ) for path in self._get_paths([om.id, om.token]): resp = self.client.post(path) assert resp.status_code == 400 om = OrganizationMember.objects.get(id=om.id) assert not om.invite_approved assert om.is_pending assert om.token

e94d7cd092d813d88c2216fca3ca6bd48e0747a3

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

def test_cannot_accept_unapproved_invite(self): self.login_as(self.user) om = OrganizationMember.objects.create( email="newuser@example.com", role="member", token="abc", organization=self.organization, invite_status=InviteStatus.REQUESTED_TO_JOIN.value,

test_cannot_accept_unapproved_invite

src/sentry/testutils/cases.py

ref: ban exam.patcher (#42222) blocked on https://github.com/getsentry/getsentry/pull/9091

sentry

Python

cases.py

def _setup_today(self): with mock.patch( "django.utils.timezone.now", return_value=(datetime(2013, 5, 18, 15, 13, 58, 132928, tzinfo=timezone.utc)), ): yield

458900af44ec0ceb675ce8159d33c4b361847471

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

def _setup_today(self): with mock.patch( "django.utils.timezone.now", return_value=(datetime(2013, 5, 18, 15, 13, 58, 132928, tzinfo=timezone.utc)),

_setup_today

tests/components/melnor/__init__.py

Add Melnor Bluetooth valve watering Integration (#70457)

core

Python

__init__.py

def patch_async_setup_entry(return_value=True): return patch( "homeassistant.components.melnor.async_setup_entry", return_value=return_value, )

8d94c8f74aea9a6a75dbc5ffbb8fb6b8ad4442d7

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

def patch_async_setup_entry(return_value=True): return patch( "homeassistant.components.melnor.async

patch_async_setup_entry

salt/modules/linux_shadow.py

Update to latest ``pyupgrade`` hook. Stop skipping it on CI. Signed-off-by: Pedro Algarvio <palgarvio@vmware.com>

salt

Python

linux_shadow.py

def list_users(root=None): if root is not None: getspall = functools.partial(_getspall, root=root) else: getspall = functools.partial(spwd.getspall) return sorted( user.sp_namp if hasattr(user, "sp_namp") else user.sp_nam for user in getspall() )

f2a783643de61cac1ff3288b40241e5ce6e1ddc8

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

def list_users(root=None): if root is not None: getspall = functools.partial(_getspall, root=root) else: getspall = functools.partial(spwd.getspall) return sorted( user.sp_namp if hasattr(user, "sp_namp") else user.sp_nam for user in getspall() )

list_users

tests/rest/media/v1/test_filepath.py

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

synapse

Python

test_filepath.py

def test_url_cache_thumbnail(self) -> None: self.assertEqual( self.filepaths.url_cache_thumbnail_rel( "2020-01-02_GerZNDnDZVjsOtar", 800, 600, "image/jpeg", "scale" ), "url_cache_thumbnails/2020-01-02/GerZNDnDZVjsOtar/800-600-image-jpeg-scale", ) self.assertEqual( self.filepaths.url_cache_thumbnail( "2020-01-02_GerZNDnDZVjsOtar", 800, 600, "image/jpeg", "scale" ), "/media_store/url_cache_thumbnails/2020-01-02/GerZNDnDZVjsOtar/800-600-image-jpeg-scale", )

7e91107be1a4287873266e588a3c5b415279f4c8

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

def test_url_cache_thumbnail(self) -> None: self.assertEqual( self.filepaths.url_cache_thumbnail_rel( "2020-01-02_GerZNDnDZVjsOtar", 800, 600, "image/jpeg", "scale" ), "url_cache_thumbnails/2020-01-02/GerZNDnDZVjsOtar/800-600-image-jpeg-scale", ) self.assertEqual( self.filepaths.url_cache_thumbnail( "2020-01-02_GerZNDnDZVjsOtar", 800, 600, "image/jpeg", "scale" ), "/media_

test_url_cache_thumbnail

flair/models/tars_model.py

Fix TARS models

flair

Python

tars_model.py

def _print_predictions(self, batch, gold_label_type): lines = [] if self.tars_model.predict_spans: for datapoint in batch: # all labels default to "O" for token in datapoint: token.set_label("gold_bio", "O") token.set_label("predicted_bio", "O") # set gold token-level for gold_label in datapoint.get_labels(gold_label_type): gold_span: Span = gold_label.data_point prefix = "B-" for token in gold_span: token.set_label("gold_bio", prefix + gold_label.value) prefix = "I-" # set predicted token-level for predicted_label in datapoint.get_labels("predicted"): predicted_span: Span = predicted_label.data_point prefix = "B-" for token in predicted_span: token.set_label("predicted_bio", prefix + predicted_label.value) prefix = "I-" # now print labels in CoNLL format for token in datapoint: eval_line = ( f"{token.text} " f"{token.get_label('gold_bio').value} " f"{token.get_label('predicted_bio').value}\n" ) lines.append(eval_line) lines.append("\n") return lines

538a531926c36124593a0afedaf8a24f44a11c31

https://github.com/flairNLP/flair.git

def _print_predictions(self, batch, gold_label_type): lines = [] if self.tars_model.predict_spans: for datapoint in batch: # all labels default to "O" for token in datapoint: token.set_label("gold_bio", "O") token.set_label("predicted_bio", "O") # set gold token-level for gold_label in datapoint.get_labels(gold_label_type): gold_span: Span = gold_label.data_point prefix = "B-" for token in gold_span: token.set_label("gold_bio", prefix + gold_label.value) prefix = "I-" # set predicted token-level for predicted_label in datapoint.get_labels("predicted"): predicted_span: Span = predicted_label.data_point prefix = "B-" for token in predicted_span: token.set_label("predicted_bio", prefix + predicted_label.value) prefix = "I-" # now print labels in CoNLL format for token in datapoint: eval_line = ( f"{token.text} "

_print_predictions

src/sentry/testutils/helpers/api_gateway.py

feat(api-gateway): Initial plumbing for api gateway (#39739) This sets up the initial plumbing for middleware -> proxy -> region silo. The API Gateway isn't active as long as the silo's SiloMode is set to MONOLITH. Also the middleware hasn't been added to settings.MIDDLEWARE. There are various fixes scattered around to get the gateway test passing. Still to be done in future PRs: - Checking if the API needs to be proxied - Adding proxy headers to responses - Handling of other methods - Handling non-json responses

sentry

Python

api_gateway.py

def get(self, request, organization): return Response({"proxy": False}) urlpatterns = [ url( r"^organizations/(?P<organization_slug>[^\/]+)/control/$", ControlEndpoint.as_view(), name="control-endpoint", ), url( r"^organizations/(?P<organization_slug>[^\/]+)/region/$", RegionEndpoint.as_view(), name="region-endpoint", ), ]

6c1cb91778860eeb8141f9d7df788519c5ef9319

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

def get(self, request, organization): return Response({"proxy": False}) urlpatterns = [ url( r"^organizations/(?P<organization_slug>[^\/]+)/control/$", ControlEndpoint.as_view(), n

get

freqtrade/configuration/configuration.py

extract load_from_files to load_config

freqtrade

Python

configuration.py

def load_config(self) -> Dict[str, Any]: # Load all configs config: Dict[str, Any] = load_from_files(self.args.get("config", [])) # Load environment variables env_data = enironment_vars_to_dict() config = deep_merge_dicts(env_data, config) # Normalize config if 'internals' not in config: config['internals'] = {} if 'pairlists' not in config: config['pairlists'] = [] # Keep a copy of the original configuration file config['original_config'] = deepcopy(config) self._process_logging_options(config) self._process_runmode(config) self._process_common_options(config) self._process_trading_options(config) self._process_optimize_options(config) self._process_plot_options(config) self._process_data_options(config) # Check if the exchange set by the user is supported check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True)) self._resolve_pairs_list(config) process_temporary_deprecated_settings(config) return config

1347107c1e4c77daa7ddf11520d3ae020a43a5d1

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

def load_config(self) -> Dict[str, Any]: # Load all configs config: Dict[str, Any] = load_from_files(self.args.get("config", [])) # Load environment variables env_data = enironment_vars_to_dict() config = deep_merge_dicts(env_data, config) # Normalize config if 'internals' not in config: config['internals'] = {} if 'pairlists' not in config: conf

load_config

jina/parsers/orchestrate/deployment.py

refactor: rename switch feature (#4494)

jina

Python

deployment.py

def mixin_base_deployment_parser(parser): gp = add_arg_group(parser, title='Deployment') gp.add_argument( '--uses-before', type=str, help='The executor attached after the Pods described by --uses, typically before sending to all ' 'shards, accepted type follows `--uses`', ) gp.add_argument( '--uses-after', type=str, help='The executor attached after the Pods described by --uses, typically used for receiving from ' 'all shards, accepted type follows `--uses`', ) gp.add_argument( '--when', action=KVAppendAction, metavar='KEY: VALUE', nargs='*', help='The condition that the documents need to fulfill before reaching the Executor.' 'The condition can be defined in the form of a `DocArray query condition <https://docarray.jina.ai/fundamentals/documentarray/find/#query-by-conditions>`', ) gp.add_argument( '--external', action='store_true', default=False, help='The Deployment will be considered an external Deployment that has been started independently from the Flow.' 'This Deployment will not be context managed by the Flow.', ) # hidden CLI used for internal only gp.add_argument( '--deployment-role', type=DeploymentRoleType.from_string, choices=list(DeploymentRoleType), help='The role of this deployment in the flow' if _SHOW_ALL_ARGS else argparse.SUPPRESS, )

efff15494d3a955b2211dcd2abcd8659c0d006c0

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

def mixin_base_deployment_parser(parser): gp = add_arg_group(parser, title='Deployment') gp.add_argument( '--uses-before', type=str, help='The executor attached after the Pods described by --uses, typically before sending to all ' 'shards, accepted type follows `--uses`', ) gp.add_argument( '--uses-after', type=str, help='The executor attached after the Pods described by --uses, typically used for receiving from ' 'all shards, accepted type follows `--uses`', ) gp.add_argument( '--when', action=KVAppendAction, metavar='KEY: VALUE', nargs='*', help='The condition that the documents need to fulfill before reaching the Executor.' 'The condition can be defined in the form of a `DocArray query condition <https://docarray.jina.ai/fundamentals/documentarray/find/#query-by-conditions>`', ) gp.add_argument( '--external', action='store_true', default=False, help='The Deployment will be considered an external Deployment that has been started independently from the Flow.' 'This Deployment will not be context managed by the Flow.', ) # hidden CLI used for internal only gp.add_argument( '--dep

mixin_base_deployment_parser