Tidy up __init__.py

setup.cfg

@@ -104,7 +104,6 @@ exclude =
     .git,
     __pycache__,
     _tokenizer_exceptions_list.py,
-    spacy/__init__.py
 
 [tool:pytest]
 markers =

spacy/__init__.py

@@ -1,32 +1,50 @@
+from typing import Union, Iterable, Dict, Any
+from pathlib import Path
 import warnings
 import sys
 
-warnings.filterwarnings("ignore", message="numpy.dtype size changed")
+warnings.filterwarnings("ignore", message="numpy.dtype size changed")  # noqa
-warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
+warnings.filterwarnings("ignore", message="numpy.ufunc size changed")  # noqa
 
 # These are imported as part of the API
-from thinc.api import prefer_gpu, require_gpu
+from thinc.api import prefer_gpu, require_gpu  # noqa: F401
 
-from . import pipeline
+from . import pipeline  # noqa: F401
-from .cli.info import info
+from .cli.info import info  # noqa: F401
-from .glossary import explain
+from .glossary import explain  # noqa: F401
-from .about import __version__
+from .about import __version__  # noqa: F401
-from .errors import Errors, Warnings
+from .util import registry  # noqa: F401
+
+from .errors import Errors
+from .language import Language
 from . import util
-from .util import registry
-
 
 if sys.maxunicode == 65535:
     raise SystemError(Errors.E130)
 
 
-config = registry
+def load(
+    name: Union[str, Path],
+    disable: Iterable[str] = tuple(),
+    component_cfg: Dict[str, Dict[str, Any]] = util.SimpleFrozenDict(),
+) -> Language:
+    """Load a spaCy model from an installed package or a local path.
+
+    name (str): Package name or model path.
+    disable (Iterable[str]): Names of pipeline components to disable.
+    component_cfg (Dict[str, dict]): Config overrides for pipeline components,
+        keyed by component names.
+    RETURNS (Language): The loaded nlp object.
+    """
+    return util.load_model(name, disable=disable, component_cfg=component_cfg)
 
 
-def load(name, **overrides):
+def blank(name: str, **overrides) -> Language:
-    return util.load_model(name, **overrides)
+    """Create a blank nlp object for a given language code.
 
-
+    name (str): The language code, e.g. "en".
-def blank(name, **kwargs):
+    **overrides: Keyword arguments passed to language subclass on init.
+    RETURNS (Language): The nlp object.
+    """
     LangClass = util.get_lang_class(name)
-    return LangClass(**kwargs)
+    return LangClass(**overrides)