enable argument for spacy.load()

spacy/__init__.py

@@ -32,6 +32,7 @@ def load(
     *,
     vocab: Union[Vocab, bool] = True,
     disable: Iterable[str] = util.SimpleFrozenList(),
+    enable: Iterable[str] = util.SimpleFrozenList(),
     exclude: Iterable[str] = util.SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = util.SimpleFrozenDict(),
 ) -> Language:
@@ -42,14 +43,21 @@ def load(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+        enable (Iterable[str]): Names of pipeline components to enable. All other
+            pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
     RETURNS (Language): The loaded nlp object.
     """
     return util.load_model(
-        name, vocab=vocab, disable=disable, exclude=exclude, config=config
+        name,
+        vocab=vocab,
+        disable=disable,
+        enable=enable,
+        exclude=exclude,
+        config=config,
     )
 
 

spacy/errors.py

@@ -919,6 +919,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E1035 = ("Token index {i} out of bounds ({length})")
     E1036 = ("Cannot index into NoneNode")
     E1037 = ("Invalid attribute value '{attr}'.")
+    E1038 = ("Function was called with `{arg1}`={arg1_values} and `{arg2}`={arg2_values} but that information is "
+             "conflicting.")
 
 
 # Deprecated model shortcuts, only used in errors and warnings

spacy/language.py

@@ -1,4 +1,4 @@
-from typing import Iterator, Optional, Any, Dict, Callable, Iterable
+from typing import Iterator, Optional, Any, Dict, Callable, Iterable, Collection
 from typing import Union, Tuple, List, Set, Pattern, Sequence
 from typing import NoReturn, TYPE_CHECKING, TypeVar, cast, overload
 
@@ -1671,6 +1671,7 @@ def from_config(
         *,
         vocab: Union[Vocab, bool] = True,
         disable: Iterable[str] = SimpleFrozenList(),
+        enable: Iterable[str] = SimpleFrozenList(),
         exclude: Iterable[str] = SimpleFrozenList(),
         meta: Dict[str, Any] = SimpleFrozenDict(),
         auto_fill: bool = True,
@@ -1685,6 +1686,8 @@ def from_config(
         disable (Iterable[str]): Names of pipeline components to disable.
             Disabled pipes will be loaded but they won't be run unless you
             explicitly enable them by calling nlp.enable_pipe.
+        enable (Iterable[str]): Names of pipeline components to enable. All other
+            pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
         exclude (Iterable[str]): Names of pipeline components to exclude.
             Excluded components won't be loaded.
         meta (Dict[str, Any]): Meta overrides for nlp.meta.
@@ -1838,8 +1841,15 @@ def from_config(
         # Restore the original vocab after sourcing if necessary
         if vocab_b is not None:
             nlp.vocab.from_bytes(vocab_b)
-        disabled_pipes = [*config["nlp"]["disabled"], *disable]
+
+        # Resolve disabled/enabled settings.
+        disabled_pipes = cls._resolve_component_status(
+            [*config["nlp"]["disabled"], *disable],
+            [*config["nlp"].get("enabled", []), *enable],
+            config["nlp"]["pipeline"],
+        )
         nlp._disabled = set(p for p in disabled_pipes if p not in exclude)
+
         nlp.batch_size = config["nlp"]["batch_size"]
         nlp.config = filled if auto_fill else config
         if after_pipeline_creation is not None:
@@ -1975,6 +1985,7 @@ def to_disk(
 
         DOCS: https://spacy.io/api/language#to_disk
         """
+
         path = util.ensure_path(path)
         serializers = {}
         serializers["tokenizer"] = lambda p: self.tokenizer.to_disk(  # type: ignore[union-attr]
@@ -1991,6 +2002,44 @@ def to_disk(
         serializers["vocab"] = lambda p: self.vocab.to_disk(p, exclude=exclude)
         util.to_disk(path, serializers, exclude)
 
+    @staticmethod
+    def _resolve_component_status(
+        disable: Iterable[str], enable: Iterable[str], pipe_names: Collection[str]
+    ) -> Tuple[str, ...]:
+        """
+        Derives whether (1) `disable` and `enable` values are consistent and (2) resolves those to a single set of
+        disabled components.
+        `enable` takes precedence over `disable` - so if the former is set, all other components are assumed to be
+        disabled, independently of the value of `disable`. If `enable` is empty, only those component whose names are
+        included in `disable` are assumed to be disabled.
+
+        disable (Iterable[str]): Names of components or serialization fields to disable.
+        enable (Iterable[str]): Names of pipeline components to enable.
+        pipe_names (Iterable[str]): Names of all pipeline components.
+
+        RETURNS (Tuple[str, ...]): Names of components to exclude from pipeline w.r.t. specified includes and excludes.
+        """
+
+        if disable is not None and isinstance(disable, str):
+            disable = [disable]
+        to_disable = disable
+
+        if enable:
+            to_disable = [
+                pipe_name for pipe_name in pipe_names if pipe_name not in enable
+            ]
+            if disable and disable != to_disable:
+                raise ValueError(
+                    Errors.E1038.format(
+                        arg1="enable",
+                        arg2="disable",
+                        arg1_values=enable,
+                        arg2_values=disable,
+                    )
+                )
+
+        return tuple(to_disable)
+
     def from_disk(
         self,
         path: Union[str, Path],
@@ -2004,6 +2053,7 @@ def from_disk(
 
         path (str / Path): A path to a directory.
         exclude (Iterable[str]): Names of components or serialization fields to exclude.
+
         RETURNS (Language): The modified `Language` object.
 
         DOCS: https://spacy.io/api/language#from_disk

spacy/tests/pipeline/test_pipe_methods.py

@@ -4,13 +4,14 @@
 import pytest
 from thinc.api import get_current_ops
 
+import spacy
 from spacy.lang.en import English
 from spacy.lang.en.syntax_iterators import noun_chunks
 from spacy.language import Language
 from spacy.pipeline import TrainablePipe
 from spacy.tokens import Doc
 from spacy.training import Example
-from spacy.util import SimpleFrozenList, get_arg_names
+from spacy.util import SimpleFrozenList, get_arg_names, make_tempdir
 from spacy.vocab import Vocab
 
 
@@ -602,3 +603,52 @@ def component(doc):
             assert results[component] == "".join(eg.predicted.text for eg in examples)
         for component in components - set(components_to_annotate):
             assert results[component] == ""
+
+
+def test_load_disable_enable() -> None:
+    """
+    Tests spacy.load() with dis-/enabling components.
+    """
+
+    base_nlp = English()
+    for pipe in ("sentencizer", "tagger", "parser"):
+        base_nlp.add_pipe(pipe)
+
+    with make_tempdir() as tmp_dir:
+        base_nlp.to_disk(tmp_dir)
+        to_disable = ["parser", "tagger"]
+        to_enable = ["tagger", "parser"]
+
+        # Setting only `disable`.
+        nlp = spacy.load(tmp_dir, disable=to_disable)
+        assert all([comp_name in nlp.disabled for comp_name in to_disable])
+
+        # Setting only `enable`.
+        nlp = spacy.load(tmp_dir, enable=to_enable)
+        assert all(
+            [
+                (comp_name in nlp.disabled) is (comp_name not in to_enable)
+                for comp_name in nlp.component_names
+            ]
+        )
+
+        # Testing consistent enable/disable combination.
+        nlp = spacy.load(
+            tmp_dir,
+            enable=to_enable,
+            disable=[
+                comp_name
+                for comp_name in nlp.component_names
+                if comp_name not in to_enable
+            ],
+        )
+        assert all(
+            [
+                (comp_name in nlp.disabled) is (comp_name not in to_enable)
+                for comp_name in nlp.component_names
+            ]
+        )
+
+        # Inconsistent enable/disable combination.
+        with pytest.raises(ValueError):
+            spacy.load(tmp_dir, enable=to_enable, disable=["parser"])

spacy/util.py

@@ -12,7 +12,6 @@
 from thinc.api import ConfigValidationError, Model
 import functools
 import itertools
-import numpy.random
 import numpy
 import srsly
 import catalogue
@@ -400,6 +399,7 @@ def load_model(
     *,
     vocab: Union["Vocab", bool] = True,
     disable: Iterable[str] = SimpleFrozenList(),
+    enable: Iterable[str] = SimpleFrozenList(),
     exclude: Iterable[str] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
@@ -409,11 +409,19 @@ def load_model(
     vocab (Vocab / True): Optional vocab to pass in on initialization. If True,
         a new Vocab object will be created.
     disable (Iterable[str]): Names of pipeline components to disable.
+    enable (Iterable[str]): Names of pipeline components to enable. All others will be disabled.
+    exclude (Iterable[str]):  Names of pipeline components to exclude.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
     RETURNS (Language): The loaded nlp object.
     """
-    kwargs = {"vocab": vocab, "disable": disable, "exclude": exclude, "config": config}
+    kwargs = {
+        "vocab": vocab,
+        "disable": disable,
+        "enable": enable,
+        "exclude": exclude,
+        "config": config,
+    }
     if isinstance(name, str):  # name or string path
         if name.startswith("blank:"):  # shortcut for blank model
             return get_lang_class(name.replace("blank:", ""))()
@@ -433,6 +441,7 @@ def load_model_from_package(
     *,
     vocab: Union["Vocab", bool] = True,
     disable: Iterable[str] = SimpleFrozenList(),
+    enable: Iterable[str] = SimpleFrozenList(),
     exclude: Iterable[str] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
@@ -444,14 +453,16 @@ def load_model_from_package(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+    enable (Iterable[str]): Names of pipeline components to enable. All other
+        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
     RETURNS (Language): The loaded nlp object.
     """
     cls = importlib.import_module(name)
-    return cls.load(vocab=vocab, disable=disable, exclude=exclude, config=config)  # type: ignore[attr-defined]
+    return cls.load(vocab=vocab, disable=disable, enable=enable, exclude=exclude, config=config)  # type: ignore[attr-defined]
 
 
 def load_model_from_path(
@@ -460,6 +471,7 @@ def load_model_from_path(
     meta: Optional[Dict[str, Any]] = None,
     vocab: Union["Vocab", bool] = True,
     disable: Iterable[str] = SimpleFrozenList(),
+    enable: Iterable[str] = SimpleFrozenList(),
     exclude: Iterable[str] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
@@ -473,6 +485,8 @@ def load_model_from_path(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+    enable (Iterable[str]): Names of pipeline components to enable. All other
+        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
@@ -487,7 +501,12 @@ def load_model_from_path(
     overrides = dict_to_dot(config)
     config = load_config(config_path, overrides=overrides)
     nlp = load_model_from_config(
-        config, vocab=vocab, disable=disable, exclude=exclude, meta=meta
+        config,
+        vocab=vocab,
+        disable=disable,
+        enable=enable,
+        exclude=exclude,
+        meta=meta,
     )
     return nlp.from_disk(model_path, exclude=exclude, overrides=overrides)
 
@@ -498,6 +517,7 @@ def load_model_from_config(
     meta: Dict[str, Any] = SimpleFrozenDict(),
     vocab: Union["Vocab", bool] = True,
     disable: Iterable[str] = SimpleFrozenList(),
+    enable: Iterable[str] = SimpleFrozenList(),
     exclude: Iterable[str] = SimpleFrozenList(),
     auto_fill: bool = False,
     validate: bool = True,
@@ -512,6 +532,8 @@ def load_model_from_config(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+    enable (Iterable[str]): Names of pipeline components to enable. All other
+        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     auto_fill (bool): Whether to auto-fill config with missing defaults.
@@ -530,6 +552,7 @@ def load_model_from_config(
         config,
         vocab=vocab,
         disable=disable,
+        enable=enable,
         exclude=exclude,
         auto_fill=auto_fill,
         validate=validate,
@@ -594,6 +617,7 @@ def load_model_from_init_py(
     *,
     vocab: Union["Vocab", bool] = True,
     disable: Iterable[str] = SimpleFrozenList(),
+    enable: Iterable[str] = SimpleFrozenList(),
     exclude: Iterable[str] = SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
@@ -605,6 +629,8 @@ def load_model_from_init_py(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+    enable (Iterable[str]): Names of pipeline components to enable. All other
+        pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
@@ -622,6 +648,7 @@ def load_model_from_init_py(
         vocab=vocab,
         meta=meta,
         disable=disable,
+        enable=enable,
         exclude=exclude,
         config=config,
     )

website/docs/api/top-level.md

@@ -51,6 +51,7 @@ specified separately using the new `exclude` keyword argument.
 | _keyword-only_                       |                                                                                                                                                                                                                                                |
 | `vocab`                              | Optional shared vocab to pass in on initialization. If `True` (default), a new `Vocab` object will be created. ~~Union[Vocab, bool]~~                                                                                                          |
 | `disable`                            | Names of pipeline components to [disable](/usage/processing-pipelines#disabling). Disabled pipes will be loaded but they won't be run unless you explicitly enable them by calling [nlp.enable_pipe](/api/language#enable_pipe). ~~List[str]~~ |
+| `enable`                             | Names of pipeline components to [enable](/usage/processing-pipelines#disabling). All other pipes will be disabled. ~~List[str]~~                                                                                                               |
 | `exclude` <Tag variant="new">3</Tag> | Names of pipeline components to [exclude](/usage/processing-pipelines#disabling). Excluded components won't be loaded. ~~List[str]~~                                                                                                           |
 | `config` <Tag variant="new">3</Tag>  | Optional config overrides, either as nested dict or dict keyed by section value in dot notation, e.g. `"components.name.value"`. ~~Union[Dict[str, Any], Config]~~                                                                             |
 | **RETURNS**                          | A `Language` object with the loaded pipeline. ~~Language~~                                                                                                                                                                                     |

website/docs/usage/processing-pipelines.md

@@ -362,6 +362,18 @@ nlp = spacy.load("en_core_web_sm", disable=["tagger", "parser"])
 nlp.enable_pipe("tagger")
 ```
 
+In addition to `disable`, `spacy.load()` also accepts `enable`. If `enable` is
+set, all components except for those in `enable` are disabled.
+
+```python
+# Load the complete pipeline, but disable all components except the tagger
+nlp = spacy.load("en_core_web_sm", enable=["tagger"])
+# Has the same effect, as the parser is already not part of enabled set of components
+nlp = spacy.load("en_core_web_sm", enable=["tagger"], disable=["parser"])
+# Will raise an error, as the sets of enabled and disabled components are conflicting
+nlp = spacy.load("en_core_web_sm", enable=["tagger"], disable=["tagger"])
+```
+
 <Infobox variant="warning" title="Changed in v3.0">
 
 As of v3.0, the `disable` keyword argument specifies components to load but