Merge pull request #8522 from adrianeboyd/chore/update-flake8

Update flake8 version in reqs and CI
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Ines Montani 2021-06-28 21:46:06 +10:00 committed by GitHub
commit 7f65902702
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6 changed files with 13 additions and 10 deletions

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@ -28,7 +28,7 @@ jobs:
inputs: inputs:
versionSpec: "3.7" versionSpec: "3.7"
- script: | - script: |
pip install flake8==3.5.0 pip install flake8==3.9.2
python -m flake8 spacy --count --select=E901,E999,F821,F822,F823 --show-source --statistics python -m flake8 spacy --count --select=E901,E999,F821,F822,F823 --show-source --statistics
displayName: "flake8" displayName: "flake8"

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@ -26,5 +26,5 @@ cython>=0.25,<3.0
pytest>=5.2.0 pytest>=5.2.0
pytest-timeout>=1.3.0,<2.0.0 pytest-timeout>=1.3.0,<2.0.0
mock>=2.0.0,<3.0.0 mock>=2.0.0,<3.0.0
flake8>=3.5.0,<3.6.0 flake8>=3.8.0,<3.10.0
hypothesis>=3.27.0,<7.0.0 hypothesis>=3.27.0,<7.0.0

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@ -6,6 +6,7 @@ from thinc.api import Model, Maxout, Linear
from ...util import registry from ...util import registry
from ...kb import KnowledgeBase, Candidate, get_candidates from ...kb import KnowledgeBase, Candidate, get_candidates
from ...vocab import Vocab from ...vocab import Vocab
from ...tokens import Span
@registry.architectures("spacy.EntityLinker.v1") @registry.architectures("spacy.EntityLinker.v1")
@ -44,5 +45,5 @@ def empty_kb(entity_vector_length: int) -> Callable[[Vocab], KnowledgeBase]:
@registry.misc("spacy.CandidateGenerator.v1") @registry.misc("spacy.CandidateGenerator.v1")
def create_candidates() -> Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]: def create_candidates() -> Callable[[KnowledgeBase, Span], Iterable[Candidate]]:
return get_candidates return get_candidates

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@ -9,7 +9,7 @@ import warnings
from ..kb import KnowledgeBase, Candidate from ..kb import KnowledgeBase, Candidate
from ..ml import empty_kb from ..ml import empty_kb
from ..tokens import Doc from ..tokens import Doc, Span
from .pipe import deserialize_config from .pipe import deserialize_config
from .trainable_pipe import TrainablePipe from .trainable_pipe import TrainablePipe
from ..language import Language from ..language import Language
@ -67,7 +67,7 @@ def make_entity_linker(
incl_prior: bool, incl_prior: bool,
incl_context: bool, incl_context: bool,
entity_vector_length: int, entity_vector_length: int,
get_candidates: Callable[[KnowledgeBase, "Span"], Iterable[Candidate]], get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
): ):
"""Construct an EntityLinker component. """Construct an EntityLinker component.
@ -114,7 +114,7 @@ class EntityLinker(TrainablePipe):
incl_prior: bool, incl_prior: bool,
incl_context: bool, incl_context: bool,
entity_vector_length: int, entity_vector_length: int,
get_candidates: Callable[[KnowledgeBase, "Span"], Iterable[Candidate]], get_candidates: Callable[[KnowledgeBase, Span], Iterable[Candidate]],
) -> None: ) -> None:
"""Initialize an entity linker. """Initialize an entity linker.
@ -127,7 +127,7 @@ class EntityLinker(TrainablePipe):
incl_prior (bool): Whether or not to include prior probabilities from the KB in the model. incl_prior (bool): Whether or not to include prior probabilities from the KB in the model.
incl_context (bool): Whether or not to include the local context in the model. incl_context (bool): Whether or not to include the local context in the model.
entity_vector_length (int): Size of encoding vectors in the KB. entity_vector_length (int): Size of encoding vectors in the KB.
get_candidates (Callable[[KnowledgeBase, "Span"], Iterable[Candidate]]): Function that get_candidates (Callable[[KnowledgeBase, Span], Iterable[Candidate]]): Function that
produces a list of candidates, given a certain knowledge base and a textual mention. produces a list of candidates, given a certain knowledge base and a textual mention.
DOCS: https://spacy.io/api/entitylinker#init DOCS: https://spacy.io/api/entitylinker#init

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@ -4,7 +4,7 @@ from enum import Enum
from pydantic import BaseModel, Field, ValidationError, validator, create_model from pydantic import BaseModel, Field, ValidationError, validator, create_model
from pydantic import StrictStr, StrictInt, StrictFloat, StrictBool from pydantic import StrictStr, StrictInt, StrictFloat, StrictBool
from pydantic.main import ModelMetaclass from pydantic.main import ModelMetaclass
from thinc.api import Optimizer, ConfigValidationError from thinc.api import Optimizer, ConfigValidationError, Model
from thinc.config import Promise from thinc.config import Promise
from collections import defaultdict from collections import defaultdict
import inspect import inspect
@ -17,6 +17,7 @@ if TYPE_CHECKING:
# This lets us add type hints for mypy etc. without causing circular imports # This lets us add type hints for mypy etc. without causing circular imports
from .language import Language # noqa: F401 from .language import Language # noqa: F401
from .training import Example # noqa: F401 from .training import Example # noqa: F401
from .vocab import Vocab # noqa: F401
# fmt: off # fmt: off
@ -354,7 +355,7 @@ class ConfigSchemaPretrain(BaseModel):
batcher: Batcher = Field(..., title="Batcher for the training data") batcher: Batcher = Field(..., title="Batcher for the training data")
component: str = Field(..., title="Component to find the layer to pretrain") component: str = Field(..., title="Component to find the layer to pretrain")
layer: str = Field(..., title="Layer to pretrain. Whole model if empty.") layer: str = Field(..., title="Layer to pretrain. Whole model if empty.")
objective: Callable[["Vocab", "Model"], "Model"] = Field(..., title="A function that creates the pretraining objective.") objective: Callable[["Vocab", Model], Model] = Field(..., title="A function that creates the pretraining objective.")
# fmt: on # fmt: on
class Config: class Config:

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@ -3,6 +3,7 @@ from typing import Callable
from spacy import util from spacy import util
from spacy.util import ensure_path, registry, load_model_from_config from spacy.util import ensure_path, registry, load_model_from_config
from spacy.kb import KnowledgeBase from spacy.kb import KnowledgeBase
from spacy.vocab import Vocab
from thinc.api import Config from thinc.api import Config
from ..util import make_tempdir from ..util import make_tempdir
@ -111,7 +112,7 @@ def test_serialize_subclassed_kb():
@registry.misc("spacy.CustomKB.v1") @registry.misc("spacy.CustomKB.v1")
def custom_kb( def custom_kb(
entity_vector_length: int, custom_field: int entity_vector_length: int, custom_field: int
) -> Callable[["Vocab"], KnowledgeBase]: ) -> Callable[[Vocab], KnowledgeBase]:
def custom_kb_factory(vocab): def custom_kb_factory(vocab):
kb = SubKnowledgeBase( kb = SubKnowledgeBase(
vocab=vocab, vocab=vocab,