language stringclasses 1
value | repo stringclasses 346
values | path stringlengths 6 201 | class_span dict | source stringlengths 21 2.38M | target stringlengths 1 96 |
|---|---|---|---|---|---|
python | huggingface__transformers | tests/models/gpt_bigcode/test_modeling_gpt_bigcode.py | {
"start": 23010,
"end": 25540
} | class ____(unittest.TestCase):
def get_attention(self, multi_query):
config = GPTBigCodeConfig.from_pretrained(
"bigcode/gpt_bigcode-santacoder",
multi_query=multi_query,
attn_pdrop=0,
resid_pdrop=0,
)
# We need to set it here as it's normally ... | GPTBigCodeMQATest |
python | jazzband__django-model-utils | tests/models.py | {
"start": 5974,
"end": 6090
} | class ____(models.Model):
content = SplitField()
class Meta:
abstract = True
| SplitFieldAbstractParent |
python | pallets__werkzeug | examples/shorty/application.py | {
"start": 463,
"end": 1535
} | class ____:
def __init__(self, db_uri):
local.application = self
self.database_engine = create_engine(db_uri, convert_unicode=True)
self.dispatch = SharedDataMiddleware(self.dispatch, {"/static": STATIC_PATH})
def init_database(self):
metadata.create_all(self.database_engine)
... | Shorty |
python | pypa__pip | src/pip/_vendor/urllib3/exceptions.py | {
"start": 5582,
"end": 5783
} | class ____(HTTPError):
"""
Body should be :class:`http.client.HTTPResponse` like
(have an fp attribute which returns raw chunks) for read_chunked().
"""
pass
| BodyNotHttplibCompatible |
python | getsentry__sentry | src/sentry/preprod/api/models/launchpad.py | {
"start": 710,
"end": 1169
} | class ____(BaseModel):
model_config = ConfigDict()
state: Literal[PreprodArtifactSizeMetrics.SizeAnalysisState.PENDING] = (
PreprodArtifactSizeMetrics.SizeAnalysisState.PENDING
)
# Missing SizeAnalysisState.COMPLETED is on purpose. The only way to mark
# a size metrics as successful is via the ass... | PutSizePending |
python | sqlalchemy__sqlalchemy | test/orm/inheritance/test_polymorphic_rel.py | {
"start": 79454,
"end": 80166
} | class ____(
_PolymorphicTestBase, _PolymorphicAliasedJoins
):
@testing.skip_if(
lambda: True, "join condition doesn't work w/ this mapping"
)
def test_lazyload_related_w_cache_check(self):
pass
def test_with_polymorphic_two_future_default_wp(self):
"""test #7262
com... | PolymorphicAliasedJoinsTest |
python | plotly__plotly.py | plotly/graph_objs/scattercarpet/selected/_marker.py | {
"start": 233,
"end": 3615
} | class ____(_BaseTraceHierarchyType):
_parent_path_str = "scattercarpet.selected"
_path_str = "scattercarpet.selected.marker"
_valid_props = {"color", "opacity", "size"}
@property
def color(self):
"""
Sets the marker color of selected points.
The 'color' property is a color ... | Marker |
python | getsentry__sentry | src/sentry/grouping/component.py | {
"start": 10423,
"end": 10526
} | class ____(BaseGroupingComponent[str]):
id: str = "uri"
# Top-level components
| URIGroupingComponent |
python | python__mypy | mypy/nodes.py | {
"start": 55190,
"end": 55753
} | class ____(Statement):
"""Operator assignment statement such as x += 1"""
__slots__ = ("op", "lvalue", "rvalue")
__match_args__ = ("lvalue", "op", "rvalue")
op: str # TODO: Enum?
lvalue: Lvalue
rvalue: Expression
def __init__(self, op: str, lvalue: Lvalue, rvalue: Expression) -> None:
... | OperatorAssignmentStmt |
python | anthropics__anthropic-sdk-python | src/anthropic/lib/streaming/_beta_types.py | {
"start": 1480,
"end": 1772
} | class ____(BaseModel):
type: Literal["input_json"]
partial_json: str
"""A partial JSON string delta
e.g. `'"San Francisco,'`
"""
snapshot: object
"""The currently accumulated parsed object.
e.g. `{'location': 'San Francisco, CA'}`
"""
| BetaInputJsonEvent |
python | sqlalchemy__sqlalchemy | test/base/test_result.py | {
"start": 30886,
"end": 38658
} | class ____(fixtures.TestBase):
"""the chunkediterator supports "non tuple mode", where we bypass
the expense of generating rows when we have only scalar values.
"""
@testing.fixture
def no_tuple_fixture(self):
data = [(1, 1, 1), (2, 1, 2), (1, 1, 1), (1, 3, 2), (4, 1, 2)]
def chun... | OnlyScalarsTest |
python | coleifer__peewee | tests/regressions.py | {
"start": 55662,
"end": 58771
} | class ____(ModelTestCase):
requires = [DF, DFC, DFGC]
def test_django_filter_regression(self):
a, b, c = [DF.create(name=n, value=i) for i, n in enumerate('abc')]
ca1 = DFC.create(df=a, name='a1', value=11)
ca2 = DFC.create(df=a, name='a2', value=12)
cb1 = DFC.create(df=b, name=... | TestDjangoFilterRegression |
python | spack__spack | lib/spack/spack/vendor/pyrsistent/_checked_types.py | {
"start": 738,
"end": 4941
} | class ____(Exception):
"""
Exception raised from a :py:class:`CheckedType` when invariant tests fail or when a mandatory
field is missing.
Contains two fields of interest:
invariant_errors, a tuple of error data for the failing invariants
missing_fields, a tuple of strings specifying the missin... | InvariantException |
python | kamyu104__LeetCode-Solutions | Python/sequential-grid-path-cover.py | {
"start": 64,
"end": 1170
} | class ____(object):
def findPath(self, grid, k):
"""
:type grid: List[List[int]]
:type k: int
:rtype: List[List[int]]
"""
DIRECTIONS = ((1, 0), (0, 1), (-1, 0), (0, -1))
def backtracking(i, j, curr):
v = grid[i][j]
if v and v != curr:
... | Solution |
python | plotly__plotly.py | plotly/graph_objs/streamtube/_legendgrouptitle.py | {
"start": 233,
"end": 2960
} | class ____(_BaseTraceHierarchyType):
_parent_path_str = "streamtube"
_path_str = "streamtube.legendgrouptitle"
_valid_props = {"font", "text"}
@property
def font(self):
"""
Sets this legend group's title font.
The 'font' property is an instance of Font
that may be s... | Legendgrouptitle |
python | jmcnamara__XlsxWriter | xlsxwriter/test/worksheet/test_sparkline11.py | {
"start": 345,
"end": 8987
} | class ____(unittest.TestCase):
"""
Test assembling a complete Worksheet file.
"""
def test_assemble_xml_file(self):
"""Test writing a worksheet with no cell data."""
self.maxDiff = None
fh = StringIO()
worksheet = Worksheet()
worksheet._set_filehandle(fh)
... | TestAssembleWorksheet |
python | apache__airflow | airflow-core/src/airflow/models/dagwarning.py | {
"start": 1421,
"end": 3567
} | class ____(Base):
"""
A table to store DAG warnings.
DAG warnings are problems that don't rise to the level of failing the DAG parse
but which users should nonetheless be warned about. These warnings are recorded
when parsing DAG and displayed on the Webserver in a flash message.
"""
dag_i... | DagWarning |
python | huggingface__transformers | tests/models/idefics/test_modeling_idefics.py | {
"start": 1673,
"end": 11911
} | class ____:
def __init__(
self,
parent,
batch_size=1,
seq_length=7,
image_size=30,
patch_size=2,
num_channels=3,
is_training=True,
use_input_mask=True,
use_token_type_ids=True,
use_labels=True,
vocab_size=99,
hid... | IdeficsModelTester |
python | wandb__wandb | wandb/integration/keras/callbacks/model_checkpoint.py | {
"start": 397,
"end": 8529
} | class ____(callbacks.ModelCheckpoint):
"""A checkpoint that periodically saves a Keras model or model weights.
Saved weights are uploaded to W&B as a `wandb.Artifact`.
Since this callback is subclassed from `tf.keras.callbacks.ModelCheckpoint`, the
checkpointing logic is taken care of by the parent ca... | WandbModelCheckpoint |
python | pydata__xarray | asv_bench/benchmarks/dataset.py | {
"start": 441,
"end": 703
} | class ____:
def setup(self):
requires_dask()
self.ds = Dataset()
array = np.ones(1000)
for i in range(250):
self.ds[f"var{i}"] = ("x", array)
def time_chunk(self):
self.ds.chunk(x=(1,) * 1000)
| DatasetChunk |
python | Netflix__metaflow | metaflow/_vendor/click/types.py | {
"start": 10641,
"end": 12481
} | class ____(FloatParamType):
"""A parameter that works similar to :data:`click.FLOAT` but restricts
the value to fit into a range. The default behavior is to fail if the
value falls outside the range, but it can also be silently clamped
between the two edges.
See :ref:`ranges` for an example.
"... | FloatRange |
python | huggingface__transformers | src/transformers/models/mobilenet_v2/modeling_mobilenet_v2.py | {
"start": 12939,
"end": 15086
} | class ____(MobileNetV2PreTrainedModel):
def __init__(self, config: MobileNetV2Config) -> None:
super().__init__(config)
self.num_labels = config.num_labels
self.mobilenet_v2 = MobileNetV2Model(config)
last_hidden_size = self.mobilenet_v2.conv_1x1.convolution.out_channels
#... | MobileNetV2ForImageClassification |
python | tiangolo__fastapi | docs_src/generate_clients/tutorial002.py | {
"start": 159,
"end": 212
} | class ____(BaseModel):
message: str
| ResponseMessage |
python | pytorch__pytorch | test/distributed/_composable/test_composability/test_pp_composability.py | {
"start": 2610,
"end": 28413
} | class ____(MultiProcessTestCase):
@classmethod
def backend_str(cls) -> str:
# Testing with NCCL backend
return backend
def setUp(self):
super().setUp()
self._spawn_processes()
def tearDown(self):
super().tearDown()
try:
os.remove(self.file_na... | ComposabilityTest |
python | marshmallow-code__apispec | tests/test_ext_marshmallow.py | {
"start": 13708,
"end": 48348
} | class ____:
@pytest.fixture
def make_pet_callback_spec(self, spec_fixture):
def _make_pet_spec(operations):
spec_fixture.spec.path(
path="/pet",
operations={
"post": {"callbacks": {"petEvent": {"petCallbackUrl": operations}}}
... | TestOperationHelper |
python | redis__redis-py | redis/commands/search/reducers.py | {
"start": 1524,
"end": 1798
} | class ____(FieldOnlyReducer):
"""
Calculate the number of distinct values contained in all the results in
the group for the given field
"""
NAME = "COUNT_DISTINCT"
def __init__(self, field: str) -> None:
super().__init__(field)
| count_distinct |
python | Netflix__metaflow | metaflow/plugins/debug_logger.py | {
"start": 115,
"end": 265
} | class ____(NullEventLogger):
TYPE = "debugLogger"
@classmethod
def get_worker(cls):
return DebugEventLoggerSidecar
| DebugEventLogger |
python | spack__spack | var/spack/test_repos/spack_repo/builtin_mock/packages/module_setenv_raw/package.py | {
"start": 217,
"end": 555
} | class ____(Package):
homepage = "http://www.spack.llnl.gov"
url = "http://www.spack.llnl.gov/module-setenv-raw-1.0.tar.gz"
version("1.0", "0123456789abcdef0123456789abcdef")
def setup_run_environment(self, env: EnvironmentModifications) -> None:
env.set("FOO", "{{name}}, {name}, {{}}, {}", raw... | ModuleSetenvRaw |
python | automl__auto-sklearn | test/test_pipeline/components/regression/test_support_vector_regression.py | {
"start": 160,
"end": 722
} | class ____(BaseRegressionComponentTest):
__test__ = True
res = dict()
res["default_boston"] = -0.030006883949312613
res["default_boston_iterative"] = None
res["default_boston_sparse"] = -0.062749211736050192
res["default_boston_iterative_sparse"] = None
res["default_diabetes"] = 0.128495918... | SupportVectorComponentTest |
python | run-llama__llama_index | llama-index-core/llama_index/core/base/base_selector.py | {
"start": 531,
"end": 1973
} | class ____(BaseModel):
"""A multi-selection of choices."""
selections: List[SingleSelection]
@property
def ind(self) -> int:
if len(self.selections) != 1:
raise ValueError(
f"There are {len(self.selections)} selections, please use .inds."
)
retur... | MultiSelection |
python | django__django | django/db/models/fields/related_lookups.py | {
"start": 6036,
"end": 6094
} | class ____(RelatedLookupMixin, IsNull):
pass
| RelatedIsNull |
python | pytorch__pytorch | torchgen/model.py | {
"start": 78745,
"end": 79251
} | class ____(Type):
elem: Type
def __str__(self) -> str:
return f"{self.elem}?"
def is_base_ty_like(self, base_ty: BaseTy) -> bool:
return self.elem.is_base_ty_like(base_ty)
def is_symint_like(self) -> bool:
return self.elem.is_symint_like()
def is_nullable(self) -> bool:
... | OptionalType |
python | numba__numba | numba/core/callconv.py | {
"start": 1530,
"end": 5525
} | class ____(object):
def __init__(self, context):
self.context = context
def return_optional_value(self, builder, retty, valty, value):
if valty == types.none:
# Value is none
self.return_native_none(builder)
elif retty == valty:
# Value is an option... | BaseCallConv |
python | neetcode-gh__leetcode | python/0023-merge-k-sorted-lists.py | {
"start": 151,
"end": 1030
} | class ____:
def mergeKLists(self, lists: List[ListNode]) -> ListNode:
if not lists or len(lists) == 0:
return None
while len(lists) > 1:
mergedLists = []
for i in range(0, len(lists), 2):
l1 = lists[i]
l2 = lists[i + 1] if (i + 1) ... | Solution |
python | getsentry__sentry | src/sentry/preprod/pull_request/types.py | {
"start": 1207,
"end": 1980
} | class ____(BaseModel):
"""
Represents pull request details, normalized across SCM providers.
"""
id: str | None = None # Provider-specific ID
number: int # PR/MR number
title: str | None = None
description: str | None = None
state: PullRequestState
author: PullRequestAuthor
so... | PullRequestDetails |
python | PrefectHQ__prefect | src/prefect/server/schemas/filters.py | {
"start": 45926,
"end": 46535
} | class ____(PrefectOperatorFilterBaseModel):
"""Filter for deployments. Only deployments matching all criteria will be returned."""
active: Optional[DeploymentScheduleFilterActive] = Field(
default=None, description="Filter criteria for `DeploymentSchedule.active`"
)
def _get_filter_list(
... | DeploymentScheduleFilter |
python | encode__django-rest-framework | tests/test_filters.py | {
"start": 32133,
"end": 32333
} | class ____(serializers.ModelSerializer):
username = serializers.CharField()
class Meta:
model = SensitiveOrderingFilterModel
fields = ('id', 'username')
| SensitiveDataSerializer1 |
python | huggingface__transformers | tests/models/seggpt/test_image_processing_seggpt.py | {
"start": 1130,
"end": 3543
} | class ____:
def __init__(
self,
parent,
batch_size=7,
num_channels=3,
image_size=18,
min_resolution=30,
max_resolution=400,
do_resize=True,
size=None,
do_normalize=True,
image_mean=[0.5, 0.5, 0.5],
image_std=[0.5, 0.5, 0... | SegGptImageProcessingTester |
python | huggingface__transformers | tests/models/vitmatte/test_image_processing_vitmatte.py | {
"start": 3124,
"end": 17672
} | class ____(ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = VitMatteImageProcessor if is_vision_available() else None
fast_image_processing_class = VitMatteImageProcessorFast if is_torchvision_available() else None
def setUp(self):
super().setUp()
self.image_processor_... | VitMatteImageProcessingTest |
python | apache__airflow | providers/amazon/tests/unit/amazon/aws/operators/test_eks.py | {
"start": 19126,
"end": 23536
} | class ____:
def setup_method(self) -> None:
self.create_nodegroup_params = CreateNodegroupParams(
cluster_name=CLUSTER_NAME,
nodegroup_name=NODEGROUP_NAME,
nodegroup_subnets=SUBNET_IDS,
nodegroup_role_arn=NODEROLE_ARN[1],
)
@pytest.mark.parametriz... | TestEksCreateNodegroupOperator |
python | google__jax | jax/_src/error_check.py | {
"start": 2561,
"end": 8774
} | class ____:
"""Redefine the internal error state based on the mesh in the context.
When using JAX in multi-device environments in explicit mode, error tracking
needs to be properly aligned with the device mesh. This context manager
ensures that the internal error state is correctly initialized based on the
c... | error_checking_context |
python | ansible__ansible | lib/ansible/errors/__init__.py | {
"start": 8123,
"end": 8565
} | class ____(AnsibleRuntimeError, _error_utils.ContributesToTaskResult):
"""
The transport / connection_plugin had a fatal error.
This exception provides a result dictionary via the ContributesToTaskResult mixin.
"""
@property
def result_contribution(self) -> t.Mapping[str, object]:
retu... | AnsibleConnectionFailure |
python | sphinx-doc__sphinx | sphinx/ext/autosummary/__init__.py | {
"start": 3814,
"end": 5743
} | class ____(nodes.comment):
pass
def autosummary_table_visit_html(
self: HTML5Translator, node: autosummary_table
) -> None:
"""Make the first column of the table non-breaking."""
try:
table = cast('nodes.table', node[0])
tgroup = cast('nodes.tgroup', table[0])
tbody = cast('nod... | autosummary_table |
python | apache__airflow | providers/google/tests/unit/google/cloud/operators/test_dataplex.py | {
"start": 20940,
"end": 21939
} | class ____:
@mock.patch(HOOK_STR)
def test_execute(self, hook_mock):
op = DataplexDeleteAssetOperator(
task_id=TASK_ID,
project_id=PROJECT_ID,
region=REGION,
lake_id=LAKE_ID,
zone_id=ZONE_ID,
asset_id=ASSET_ID,
api_versi... | TestDataplexDeleteAssetOperator |
python | huggingface__transformers | src/transformers/models/roberta_prelayernorm/modeling_roberta_prelayernorm.py | {
"start": 14835,
"end": 15358
} | class ____(nn.Module):
def __init__(self, config):
super().__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self.dropout = nn.Dropout(config.hidden_dropout_prob)
def forward(self, hidden_states: torch.Tensor, input_tensor: torch.Tensor) -> torch.Tensor:
... | RobertaPreLayerNormSelfOutput |
python | airbytehq__airbyte | airbyte-integrations/connectors/source-github/source_github/github_schema.py | {
"start": 1031164,
"end": 1031723
} | class ____(sgqlc.types.Type):
"""Autogenerated return type of
UpdateIpAllowListForInstalledAppsEnabledSetting
"""
__schema__ = github_schema
__field_names__ = ("client_mutation_id", "owner")
client_mutation_id = sgqlc.types.Field(String, graphql_name="clientMutationId")
"""A unique identifi... | UpdateIpAllowListForInstalledAppsEnabledSettingPayload |
python | spyder-ide__spyder | external-deps/python-lsp-server/pylsp/lsp.py | {
"start": 674,
"end": 745
} | class ____:
Text = 1
Read = 2
Write = 3
| DocumentHighlightKind |
python | django__django | tests/fixtures_regress/models.py | {
"start": 8423,
"end": 8639
} | class ____(BaseNKModel):
def natural_key(self):
return (self.data,)
# Fake the dependency for a circularity
natural_key.dependencies = ["fixtures_regress.M2MComplexCircular2A"]
| M2MComplexCircular2B |
python | ray-project__ray | python/ray/train/huggingface/transformers/_transformers_utils.py | {
"start": 3431,
"end": 5861
} | class ____(IterableDataset):
"""Wrapper class for ray data iterables."""
def __init__(self, data_iterable) -> None:
super().__init__()
self.data_iterable = data_iterable
def __iter__(self) -> Iterator:
return iter(self.data_iterable)
@PublicAPI(stability="beta")
def prepare_train... | RayTorchIterableDataset |
python | catalyst-team__catalyst | catalyst/contrib/datasets/cifar.py | {
"start": 1565,
"end": 3554
} | class ____(data.Dataset):
_repr_indent = 4
def __init__(
self,
root: str,
transforms: Optional[Callable] = None,
transform: Optional[Callable] = None,
target_transform: Optional[Callable] = None,
) -> None:
if isinstance(root, torch._six.string_classes):
... | VisionDataset |
python | huggingface__transformers | tests/models/cohere2_vision/test_modeling_cohere2_vision.py | {
"start": 5775,
"end": 17675
} | class ____(unittest.TestCase):
def setUp(self):
self.model_checkpoint = "CohereLabs/command-a-vision-07-2025"
def tearDown(self):
cleanup(torch_device, gc_collect=True)
def get_model(self, dummy=True):
device_type, major, _ = get_device_properties()
dtype = torch.float16
... | Cohere2IntegrationTest |
python | pytorch__pytorch | torch/cuda/__init__.py | {
"start": 55162,
"end": 55711
} | class ____(_LegacyStorage):
@classmethod
def from_buffer(cls, *args, **kwargs):
_warn_typed_storage_removal()
raise RuntimeError("from_buffer: Not available for CUDA storage")
@classmethod
def _new_with_weak_ptr(cls, *args, **kwargs):
raise RuntimeError("_new_with_weak_ptr: Not ... | _CudaLegacyStorage |
python | wandb__wandb | wandb/vendor/pygments/lexers/c_like.py | {
"start": 6453,
"end": 10577
} | class ____(RegexLexer):
"""
For Vala source code with preprocessor directives.
.. versionadded:: 1.1
"""
name = 'Vala'
aliases = ['vala', 'vapi']
filenames = ['*.vala', '*.vapi']
mimetypes = ['text/x-vala']
tokens = {
'whitespace': [
(r'^\s*#if\s+0', Comment.Pre... | ValaLexer |
python | pyca__cryptography | src/cryptography/hazmat/decrepit/ciphers/algorithms.py | {
"start": 2618,
"end": 2884
} | class ____(BlockCipherAlgorithm):
name = "RC2"
block_size = 64
key_sizes = frozenset([128])
def __init__(self, key: bytes):
self.key = _verify_key_size(self, key)
@property
def key_size(self) -> int:
return len(self.key) * 8
| RC2 |
python | pypa__warehouse | warehouse/utils/crypto.py | {
"start": 674,
"end": 796
} | class ____(_TimestampSigner):
default_digest_method = hashlib.sha512
default_key_derivation = "hmac"
| TimestampSigner |
python | plotly__plotly.py | plotly/graph_objs/scatterternary/hoverlabel/_font.py | {
"start": 233,
"end": 17179
} | class ____(_BaseTraceHierarchyType):
_parent_path_str = "scatterternary.hoverlabel"
_path_str = "scatterternary.hoverlabel.font"
_valid_props = {
"color",
"colorsrc",
"family",
"familysrc",
"lineposition",
"linepositionsrc",
"shadow",
"shadowsr... | Font |
python | dagster-io__dagster | examples/docs_snippets/docs_snippets/guides/operate/configuration/run_config/op_example/resources.py | {
"start": 23,
"end": 202
} | class ____(dg.Config):
person_name: str
@dg.definitions
def resources() -> dg.Definitions:
return dg.Definitions(resources={"config": MyOpConfig(person_name="")})
| MyOpConfig |
python | FactoryBoy__factory_boy | factory/base.py | {
"start": 22748,
"end": 23223
} | class ____(Factory):
"""Factory for dictionary-like classes."""
class Meta:
abstract = True
@classmethod
def _build(cls, model_class, *args, **kwargs):
if args:
raise ValueError(
"DictFactory %r does not support Meta.inline_args." % cls)
return model_... | BaseDictFactory |
python | HypothesisWorks__hypothesis | hypothesis-python/tests/typing_extensions/test_backported_types.py | {
"start": 7770,
"end": 9198
} | class ____(TypedDict):
a: ReadOnly[Required[int]]
b: NotRequired[Annotated[ReadOnly[int], "metadata"]]
c: Annotated[ReadOnly[NotRequired[str]], "metadata"]
@pytest.mark.parametrize(
"check,condition",
[
pytest.param(
assert_all_examples,
lambda novel: "a" in novel,
... | DeeplyNestedQualifiers |
python | dask__dask | dask/tests/test_core.py | {
"start": 5030,
"end": 7771
} | class ____:
hit_eq = 0
def __eq__(self, other):
self.hit_eq += 1
return False
def test_subs_no_key_data_eq():
# Numpy throws a deprecation warning on bool(array == scalar), which
# pollutes the terminal. This test checks that `subs` never tries to
# compare keys (scalars) with val... | MutateOnEq |
python | pypa__twine | twine/package.py | {
"start": 3078,
"end": 4238
} | class ____(TypedDict, total=False):
# Metadata 1.0 - PEP 241
metadata_version: str
name: str
version: str
platform: List[str]
summary: str
description: str
keywords: List[str]
home_page: str
author: str
author_email: str
license: str
# Metadata 1.1 - PEP 314
sup... | PackageMetadata |
python | pandas-dev__pandas | pandas/tests/tseries/offsets/test_quarter.py | {
"start": 958,
"end": 4889
} | class ____:
def test_repr(self):
expected = "<QuarterBegin: startingMonth=3>"
assert repr(QuarterBegin()) == expected
expected = "<QuarterBegin: startingMonth=3>"
assert repr(QuarterBegin(startingMonth=3)) == expected
expected = "<QuarterBegin: startingMonth=1>"
asser... | TestQuarterBegin |
python | streamlit__streamlit | lib/streamlit/runtime/state/session_state_proxy.py | {
"start": 2623,
"end": 5585
} | class ____(MutableMapping[Key, Any]):
"""A stateless singleton that proxies `st.session_state` interactions
to the current script thread's SessionState instance.
The proxy API differs slightly from SessionState: it does not allow
callers to get, set, or iterate over "keyless" widgets (that is, widgets
... | SessionStateProxy |
python | anthropics__anthropic-sdk-python | src/anthropic/types/beta/beta_clear_thinking_20251015_edit_param.py | {
"start": 502,
"end": 779
} | class ____(TypedDict, total=False):
type: Required[Literal["clear_thinking_20251015"]]
keep: Keep
"""Number of most recent assistant turns to keep thinking blocks for.
Older turns will have their thinking blocks removed.
"""
| BetaClearThinking20251015EditParam |
python | PyCQA__pylint | tests/functional/n/non/non_iterator_returned.py | {
"start": 2097,
"end": 2243
} | class ____:
"""__iter__ returns a class."""
def __iter__(self): # [non-iterator-returned]
return ThirdBadIterator
| FourthBadIterator |
python | django__django | tests/test_client_regress/tests.py | {
"start": 29899,
"end": 31218
} | class ____(SimpleTestCase):
def test_simple_argument_get(self):
"Get a view that has a simple string argument"
response = self.client.get(reverse("arg_view", args=["Slartibartfast"]))
self.assertEqual(response.status_code, 200)
self.assertEqual(response.content, b"Howdy, Slartibartfa... | URLEscapingTests |
python | wandb__wandb | wandb/vendor/pygments/lexers/lisp.py | {
"start": 16554,
"end": 78343
} | class ____(RegexLexer):
"""
Lexer for `Racket <http://racket-lang.org/>`_ source code (formerly
known as PLT Scheme).
.. versionadded:: 1.6
"""
name = 'Racket'
aliases = ['racket', 'rkt']
filenames = ['*.rkt', '*.rktd', '*.rktl']
mimetypes = ['text/x-racket', 'application/x-racket'... | RacketLexer |
python | psf__black | tests/data/cases/ignore_pyi.py | {
"start": 190,
"end": 315
} | class ____:
...
def g():
# hi
...
def h():
...
# bye
# output
def f(): # type: ignore
...
| z |
python | pytorch__pytorch | test/inductor/test_aot_inductor_custom_ops.py | {
"start": 15445,
"end": 16202
} | class ____(LoggingTestCase):
@make_logging_test(dynamic=logging.DEBUG)
def test_shape_env_reuse(self, records):
# make sure ShapeEnv is only created once and reused afterwards
class Foo(torch.nn.Module):
def forward(self, x):
return x + 2
inputs = (torch.rand... | AOTInductorLoggingTest |
python | tensorflow__tensorflow | tensorflow/python/debug/cli/command_parser_test.py | {
"start": 15941,
"end": 21677
} | class ____(test_util.TensorFlowTestCase):
def testParseTimeInterval(self):
self.assertEqual(
command_parser.Interval(10, True, 1e3, True),
command_parser.parse_time_interval("[10us, 1ms]"))
self.assertEqual(
command_parser.Interval(10, False, 1e3, False),
command_parser.parse_... | ParseInterval |
python | keras-team__keras | keras/src/layers/preprocessing/data_layer_test.py | {
"start": 1223,
"end": 3169
} | class ____(testing.TestCase):
@pytest.mark.requires_trainable_backend
def test_layer(self):
self.run_layer_test(
RandomRGBToHSVLayer,
init_kwargs={
"seed": 1337,
"data_format": "channels_last",
},
input_shape=(1, 2, 2, 3),
... | DataLayerTest |
python | networkx__networkx | networkx/readwrite/tests/test_graph6.py | {
"start": 646,
"end": 980
} | class ____:
def test_n_data_n_conversion(self):
for i in [0, 1, 42, 62, 63, 64, 258047, 258048, 7744773, 68719476735]:
assert g6.data_to_n(g6.n_to_data(i))[0] == i
assert g6.data_to_n(g6.n_to_data(i))[1] == []
assert g6.data_to_n(g6.n_to_data(i) + [42, 43])[1] == [42, 43]... | TestGraph6Utils |
python | wntrblm__nox | nox/_decorators.py | {
"start": 1896,
"end": 4684
} | class ____(FunctionDecorator):
"""This is a function decorator that adds additional Nox-specific metadata."""
def __init__(
self,
func: Callable[..., Any],
python: _typing.Python = None,
reuse_venv: bool | None = None, # noqa: FBT001
name: str | None = None,
ven... | Func |
python | getsentry__sentry | src/sentry/workflow_engine/endpoints/validators/base/data_condition_group.py | {
"start": 431,
"end": 3061
} | class ____(CamelSnakeSerializer):
id = serializers.CharField(required=False)
logic_type = serializers.ChoiceField([(t.value, t.value) for t in DataConditionGroup.Type])
conditions = serializers.ListField(required=False)
def validate_conditions(self, value: list[dict[str, Any]]) -> list[dict[str, Any]]:... | BaseDataConditionGroupValidator |
python | tensorflow__tensorflow | tensorflow/python/data/kernel_tests/range_test.py | {
"start": 6519,
"end": 7351
} | class ____(checkpoint_test_base.CheckpointTestBase,
parameterized.TestCase):
def _build_range_dataset(self, start, stop, options=None):
dataset = dataset_ops.Dataset.range(start, stop)
if options:
dataset = dataset.with_options(options)
return dataset
@combinations.gene... | RangeCheckpointTest |
python | astropy__astropy | astropy/modeling/projections.py | {
"start": 13135,
"end": 13437
} | class ____(Sky2PixProjection, Zenithal):
r"""
Gnomonic Projection - sky to pixel.
Corresponds to the ``TAN`` projection in FITS WCS.
See `Zenithal` for a definition of the full transformation.
.. math::
R_\theta = \frac{180^{\circ}}{\pi}\cot \theta
"""
| Sky2Pix_Gnomonic |
python | coleifer__peewee | tests/regressions.py | {
"start": 24557,
"end": 24695
} | class ____(TestModel):
id = CharField()
color = CharField()
class Meta:
primary_key = CompositeKey('id', 'color')
| Product |
python | great-expectations__great_expectations | great_expectations/self_check/sqlalchemy_connection_manager.py | {
"start": 318,
"end": 1295
} | class ____:
def __init__(self) -> None:
self.lock = threading.Lock()
self._connections: Dict[str, sqlalchemy.Connection] = {}
def get_connection(self, connection_string):
if sa is not None:
with self.lock:
if connection_string not in self._connections:
... | SqlAlchemyConnectionManager |
python | mlflow__mlflow | dev/clint/tests/rules/test_implicit_optional.py | {
"start": 273,
"end": 337
} | class ____:
x: str = None
# Good
good: Optional[int] = None
| Bad |
python | ray-project__ray | python/ray/tune/search/sample.py | {
"start": 4294,
"end": 4545
} | class ____:
def sample(
self,
domain: Domain,
config: Optional[Union[List[Dict], Dict]] = None,
size: int = 1,
random_state: "RandomState" = None,
):
raise NotImplementedError
@DeveloperAPI
| Sampler |
python | doocs__leetcode | solution/2400-2499/2404.Most Frequent Even Element/Solution.py | {
"start": 0,
"end": 280
} | class ____:
def mostFrequentEven(self, nums: List[int]) -> int:
cnt = Counter(x for x in nums if x % 2 == 0)
ans, mx = -1, 0
for x, v in cnt.items():
if v > mx or (v == mx and ans > x):
ans, mx = x, v
return ans
| Solution |
python | apache__airflow | devel-common/src/tests_common/test_utils/mock_operators.py | {
"start": 3592,
"end": 4520
} | class ____(BaseOperatorLink):
"""Custom Operator with Link for Google Custom Search."""
name = "Google Custom"
def get_link(self, operator, *, ti_key):
if AIRFLOW_V_3_0_PLUS:
search_query = XCom.get_many(
task_ids=ti_key.task_id,
dag_ids=ti_key.dag_id,
... | CustomOpLink |
python | uqfoundation__dill | dill/tests/test_nested.py | {
"start": 741,
"end": 977
} | class ____(object):
def __init__(self, augend):
self.augend = augend
self.zero = [0]
def __call__(self, addend):
return addend + self.augend + self.zero[0]
# rewrite again, but as an old-style class
| cadder |
python | PyCQA__pylint | tests/functional/p/postponed/postponed_evaluation_pep585.py | {
"start": 896,
"end": 1128
} | class ____(typing.NamedTuple):
my_var: list[int]
# Check typing.TypedDict
CustomTypedDict = TypedDict("CustomTypedDict", my_var=list[int])
CustomTypedDict2 = TypedDict("CustomTypedDict2", {"my_var": list[int]})
| CustomNamedTuple3 |
python | dagster-io__dagster | python_modules/dagster/dagster/_core/execution/step_dependency_config.py | {
"start": 427,
"end": 924
} | class ____:
require_upstream_step_success: bool
@staticmethod
def default() -> "StepDependencyConfig":
return StepDependencyConfig(require_upstream_step_success=True)
@staticmethod
def from_config(config_value: Optional[dict[str, bool]]) -> "StepDependencyConfig":
return StepDepend... | StepDependencyConfig |
python | tensorflow__tensorflow | tensorflow/python/training/saver_test.py | {
"start": 116068,
"end": 116166
} | class ____(CheckpointReaderTest):
_WRITE_VERSION = saver_pb2.SaverDef.V2
| CheckpointReaderForV2Test |
python | ansible__ansible | lib/ansible/cli/doc.py | {
"start": 3073,
"end": 17321
} | class ____(object):
"""A mixin containing all methods relevant to role argument specification functionality.
Note: The methods for actual display of role data are not present here.
"""
# Potential locations of the role arg spec file in the meta subdir, with main.yml
# having the lowest priority.
... | RoleMixin |
python | getsentry__sentry | tests/sentry/api/endpoints/test_project_servicehook_details.py | {
"start": 111,
"end": 650
} | class ____(APITestCase):
def test_simple(self) -> None:
project = self.create_project()
hook = ServiceHook.objects.get_or_create(
project_id=project.id, actor_id=self.user.id, url="http://example.com"
)[0]
self.login_as(user=self.user)
path = f"/api/0/projects/{pr... | ProjectServiceHookDetailsTest |
python | huggingface__transformers | src/transformers/models/speecht5/modeling_speecht5.py | {
"start": 20786,
"end": 21441
} | class ____(nn.Module):
def __init__(self, config):
super().__init__()
self.layer_norm = nn.LayerNorm(config.conv_dim[-1], eps=config.layer_norm_eps)
self.projection = nn.Linear(config.conv_dim[-1], config.hidden_size)
self.dropout = nn.Dropout(config.feat_proj_dropout)
def forwa... | SpeechT5FeatureProjection |
python | faif__python-patterns | patterns/structural/mvc.py | {
"start": 1425,
"end": 1976
} | class ____(ABC):
"""The View is the presentation layer of the application."""
@abstractmethod
def show_item_list(self, item_type: str, item_list: list) -> None:
pass
@abstractmethod
def show_item_information(
self, item_type: str, item_name: str, item_info: dict
) -> None:
... | View |
python | django__django | tests/validation/test_error_messages.py | {
"start": 113,
"end": 4379
} | class ____(TestCase):
def _test_validation_messages(self, field, value, expected):
with self.assertRaises(ValidationError) as cm:
field.clean(value, None)
self.assertEqual(cm.exception.messages, expected)
def test_autofield_field_raises_error_message(self):
f = models.AutoFi... | ValidationMessagesTest |
python | sympy__sympy | sympy/physics/quantum/tests/test_anticommutator.py | {
"start": 820,
"end": 915
} | class ____(Operator):
def _eval_anticommutator_Bar(self, bar):
return Integer(0)
| Foo |
python | dagster-io__dagster | python_modules/libraries/dagster-dg-cli/dagster_dg_cli/cli/scaffold/branch/models.py | {
"start": 1466,
"end": 1692
} | class ____:
"""Record of context gathering operations."""
correlation_id: str
timestamp: str
files_analyzed: list[str]
patterns_detected: list[str]
decisions_made: dict[str, Any]
@record
| ContextGathering |
python | apache__airflow | airflow-core/src/airflow/lineage/hook.py | {
"start": 12505,
"end": 13310
} | class ____(LoggingMixin):
"""Class used to retrieve the hook lineage information collected by HookLineageCollector."""
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.lineage_collector = get_hook_lineage_collector()
def retrieve_hook_lineage(self) -> HookLineage:
"""R... | HookLineageReader |
python | pandas-dev__pandas | doc/source/conf.py | {
"start": 20276,
"end": 29453
} | class ____(Autosummary):
"""
This alternative autosummary class lets us override the table summary for
Series.plot and DataFrame.plot in the API docs.
"""
def _replace_pandas_items(self, display_name, sig, summary, real_name):
# this a hack: ideally we should extract the signature from the
... | PandasAutosummary |
python | langchain-ai__langchain | libs/core/langchain_core/callbacks/base.py | {
"start": 6472,
"end": 10890
} | class ____:
"""Mixin for callback manager."""
def on_llm_start(
self,
serialized: dict[str, Any],
prompts: list[str],
*,
run_id: UUID,
parent_run_id: UUID | None = None,
tags: list[str] | None = None,
metadata: dict[str, Any] | None = None,
... | CallbackManagerMixin |
python | python__mypy | mypyc/test/test_optimizations.py | {
"start": 1870,
"end": 2064
} | class ____(OptimizationSuite):
files = ["opt-copy-propagation.test"]
def do_optimizations(self, fn: FuncIR) -> None:
do_copy_propagation(fn, CompilerOptions())
| TestCopyPropagation |
python | bokeh__bokeh | src/bokeh/models/expressions.py | {
"start": 7007,
"end": 7341
} | class ____(ScalarExpression):
""" Computes maximum value of a data source's column. """
# explicit __init__ to support Init signatures
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
field = Required(String)
initial = Nullable(Float, default=-inf)
... | Maximum |
python | langchain-ai__langchain | libs/partners/fireworks/tests/integration_tests/test_standard.py | {
"start": 354,
"end": 1013
} | class ____(ChatModelIntegrationTests):
@property
def chat_model_class(self) -> type[BaseChatModel]:
return ChatFireworks
@property
def chat_model_params(self) -> dict:
return {
"model": "fireworks/kimi-k2-instruct-0905",
"temperature": 0,
}
@pytest.m... | TestFireworksStandard |
python | keras-team__keras | keras/src/utils/torch_utils_test.py | {
"start": 1844,
"end": 12048
} | class ____(testing.TestCase):
@parameterized.parameters(
{"use_batch_norm": False, "num_torch_layers": 1},
{"use_batch_norm": True, "num_torch_layers": 1},
)
def test_basic_usage(self, use_batch_norm, num_torch_layers):
model = Classifier(use_batch_norm, num_torch_layers)
sel... | TorchUtilsTest |
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