Replace Pipe type with Callable in Language

requirements.txt

@@ -30,7 +30,7 @@ pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 flake8>=3.8.0,<6.0.0
 hypothesis>=3.27.0,<7.0.0
-mypy>=0.980,<0.990; platform_machine != "aarch64" and python_version >= "3.7"
+mypy>=0.990,<0.1000; platform_machine != "aarch64" and python_version >= "3.7"
 types-dataclasses>=0.1.3; python_version < "3.7"
 types-mock>=0.1.1
 types-setuptools>=57.0.0

spacy/cli/debug_data.py

@@ -13,6 +13,7 @@ from ._util import import_code, debug_cli, _format_number
 from ..training import Example, remove_bilu_prefix
 from ..training.initialize import get_sourced_components
 from ..schemas import ConfigSchemaTraining
+from ..pipeline import TrainablePipe
 from ..pipeline._parser_internals import nonproj
 from ..pipeline._parser_internals.nonproj import DELIMITER
 from ..pipeline import Morphologizer, SpanCategorizer
@@ -934,6 +935,7 @@ def _get_labels_from_model(nlp: Language, factory_name: str) -> Set[str]:
     labels: Set[str] = set()
     for pipe_name in pipe_names:
         pipe = nlp.get_pipe(pipe_name)
+        assert isinstance(pipe, TrainablePipe)
         labels.update(pipe.labels)
     return labels
 

spacy/language.py

@@ -43,8 +43,7 @@ from .lookups import load_lookups
 from .compat import Literal
 
 
-if TYPE_CHECKING:
-    from .pipeline import Pipe  # noqa: F401
+PipeCallable = Callable[[Doc], Doc]
 
 
 # This is the base config will all settings (training etc.)
@@ -181,7 +180,7 @@ class Language:
         self.vocab: Vocab = vocab
         if self.lang is None:
             self.lang = self.vocab.lang
-        self._components: List[Tuple[str, "Pipe"]] = []
+        self._components: List[Tuple[str, PipeCallable]] = []
         self._disabled: Set[str] = set()
         self.max_length = max_length
         # Create the default tokenizer from the default config
@@ -303,7 +302,7 @@ class Language:
         return SimpleFrozenList(names)
 
     @property
-    def components(self) -> List[Tuple[str, "Pipe"]]:
+    def components(self) -> List[Tuple[str, PipeCallable]]:
         """Get all (name, component) tuples in the pipeline, including the
         currently disabled components.
         """
@@ -322,7 +321,7 @@ class Language:
         return SimpleFrozenList(names, error=Errors.E926.format(attr="component_names"))
 
     @property
-    def pipeline(self) -> List[Tuple[str, "Pipe"]]:
+    def pipeline(self) -> List[Tuple[str, PipeCallable]]:
         """The processing pipeline consisting of (name, component) tuples. The
         components are called on the Doc in order as it passes through the
         pipeline.
@@ -527,7 +526,7 @@ class Language:
         assigns: Iterable[str] = SimpleFrozenList(),
         requires: Iterable[str] = SimpleFrozenList(),
         retokenizes: bool = False,
-        func: Optional["Pipe"] = None,
+        func: Optional[PipeCallable] = None,
     ) -> Callable[..., Any]:
         """Register a new pipeline component. Can be used for stateless function
         components that don't require a separate factory. Can be used as a
@@ -553,11 +552,11 @@ class Language:
                 raise ValueError(Errors.E853.format(name=name))
         component_name = name if name is not None else util.get_object_name(func)
 
-        def add_component(component_func: "Pipe") -> Callable:
+        def add_component(component_func: PipeCallable) -> Callable:
             if isinstance(func, type):  # function is a class
                 raise ValueError(Errors.E965.format(name=component_name))
 
-            def factory_func(nlp, name: str) -> "Pipe":
+            def factory_func(nlp, name: str) -> PipeCallable:
                 return component_func
 
             internal_name = cls.get_factory_name(name)
@@ -607,7 +606,7 @@ class Language:
             print_pipe_analysis(analysis, keys=keys)
         return analysis
 
-    def get_pipe(self, name: str) -> "Pipe":
+    def get_pipe(self, name: str) -> PipeCallable:
         """Get a pipeline component for a given component name.
 
         name (str): Name of pipeline component to get.
@@ -628,7 +627,7 @@ class Language:
         config: Dict[str, Any] = SimpleFrozenDict(),
         raw_config: Optional[Config] = None,
         validate: bool = True,
-    ) -> "Pipe":
+    ) -> PipeCallable:
         """Create a pipeline component. Mostly used internally. To create and
         add a component to the pipeline, you can use nlp.add_pipe.
 
@@ -695,7 +694,7 @@ class Language:
 
     def create_pipe_from_source(
         self, source_name: str, source: "Language", *, name: str
-    ) -> Tuple["Pipe", str]:
+    ) -> Tuple[PipeCallable, str]:
         """Create a pipeline component by copying it from an existing model.
 
         source_name (str): Name of the component in the source pipeline.
@@ -746,7 +745,7 @@ class Language:
         config: Dict[str, Any] = SimpleFrozenDict(),
         raw_config: Optional[Config] = None,
         validate: bool = True,
-    ) -> "Pipe":
+    ) -> PipeCallable:
         """Add a component to the processing pipeline. Valid components are
         callables that take a `Doc` object, modify it and return it. Only one
         of before/after/first/last can be set. Default behaviour is "last".
@@ -883,7 +882,7 @@ class Language:
         *,
         config: Dict[str, Any] = SimpleFrozenDict(),
         validate: bool = True,
-    ) -> "Pipe":
+    ) -> PipeCallable:
         """Replace a component in the pipeline.
 
         name (str): Name of the component to replace.
@@ -944,7 +943,7 @@ class Language:
             init_cfg = self._config["initialize"]["components"].pop(old_name)
             self._config["initialize"]["components"][new_name] = init_cfg
 
-    def remove_pipe(self, name: str) -> Tuple[str, "Pipe"]:
+    def remove_pipe(self, name: str) -> Tuple[str, PipeCallable]:
         """Remove a component from the pipeline.
 
         name (str): Name of the component to remove.
@@ -1363,7 +1362,7 @@ class Language:
 
     def set_error_handler(
         self,
-        error_handler: Callable[[str, "Pipe", List[Doc], Exception], NoReturn],
+        error_handler: Callable[[str, PipeCallable, List[Doc], Exception], NoReturn],
     ):
         """Set an error handler object for all the components in the pipeline that implement
         a set_error_handler function.

spacy/tests/pipeline/test_textcat.py

@@ -814,8 +814,8 @@ def test_textcat_loss(multi_label: bool, expected_loss: float):
         textcat = nlp.add_pipe("textcat_multilabel")
     else:
         textcat = nlp.add_pipe("textcat")
-    textcat.initialize(lambda: train_examples)
     assert isinstance(textcat, TextCategorizer)
+    textcat.initialize(lambda: train_examples)
     scores = textcat.model.ops.asarray(
         [[0.0, 0.0, 0.0, 1.0], [0.0, 0.0, 1.0, 1.0]], dtype="f"  # type: ignore
     )

spacy/util.py

@@ -51,8 +51,7 @@ from . import about
 
 if TYPE_CHECKING:
     # This lets us add type hints for mypy etc. without causing circular imports
-    from .language import Language  # noqa: F401
-    from .pipeline import Pipe  # noqa: F401
+    from .language import Language, PipeCallable  # noqa: F401
     from .tokens import Doc, Span  # noqa: F401
     from .vocab import Vocab  # noqa: F401
 
@@ -1642,9 +1641,9 @@ def check_bool_env_var(env_var: str) -> bool:
 
 def _pipe(
     docs: Iterable["Doc"],
-    proc: "Pipe",
+    proc: "PipeCallable",
     name: str,
-    default_error_handler: Callable[[str, "Pipe", List["Doc"], Exception], NoReturn],
+    default_error_handler: Callable[[str, "PipeCallable", List["Doc"], Exception], NoReturn],
     kwargs: Mapping[str, Any],
 ) -> Iterator["Doc"]:
     if hasattr(proc, "pipe"):