Update docs and util consistency

spacy/util.py

@@ -249,7 +249,16 @@ def load_model_from_package(
     disable: Iterable[str] = tuple(),
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
-    """Load a model from an installed package."""
+    """Load a model from an installed package.
+
+    name (str): The package name.
+    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.
+    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, config=config)
 
@@ -263,7 +272,17 @@ def load_model_from_path(
     config: Union[Dict[str, Any], Config] = SimpleFrozenDict(),
 ) -> "Language":
     """Load a model from a data directory path. Creates Language class with
-    pipeline from config.cfg and then calls from_disk() with path."""
+    pipeline from config.cfg and then calls from_disk() with path.
+
+    name (str): Package name or model path.
+    meta (Dict[str, Any]): Optional model meta.
+    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.
+    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.
+    """
     if not model_path.exists():
         raise IOError(Errors.E052.format(path=model_path))
     if not meta:
@@ -284,6 +303,15 @@ def load_model_from_config(
 ) -> Tuple["Language", Config]:
     """Create an nlp object from a config. Expects the full config file including
     a section "nlp" containing the settings for the nlp object.
+
+    name (str): Package name or model path.
+    meta (Dict[str, Any]): Optional model meta.
+    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.
+    auto_fill (bool): Whether to auto-fill config with missing defaults.
+    validate (bool): Whether to show config validation errors.
+    RETURNS (Language): The loaded nlp object.
     """
     if "nlp" not in config:
         raise ValueError(Errors.E985.format(config=config))
@@ -308,6 +336,13 @@ def load_model_from_init_py(
 ) -> "Language":
     """Helper function to use in the `load()` method of a model package's
     __init__.py.
+
+    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.
+    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.
     """
     model_path = Path(init_file).parent
     meta = get_model_meta(model_path)
@@ -325,7 +360,14 @@ def load_config(
     overrides: Dict[str, Any] = SimpleFrozenDict(),
     interpolate: bool = False,
 ) -> Config:
-    """Load a config file. Takes care of path validation and section order."""
+    """Load a config file. Takes care of path validation and section order.
+
+    path (Union[str, Path]): Path to the config file.
+    overrides: (Dict[str, Any]): Config overrides as nested dict or
+        dict keyed by section values in dot notation.
+    interpolate (bool): Whether to interpolate and resolve variables.
+    RETURNS (Config): The loaded config.
+    """
     config_path = ensure_path(path)
     if not config_path.exists() or not config_path.is_file():
         raise IOError(Errors.E053.format(path=config_path, name="config.cfg"))
@@ -337,7 +379,12 @@ def load_config(
 def load_config_from_str(
     text: str, overrides: Dict[str, Any] = SimpleFrozenDict(), interpolate: bool = False
 ):
-    """Load a full config from a string."""
+    """Load a full config from a string. Wrapper around Thinc's Config.from_str.
+
+    text (str): The string config to load.
+    interpolate (bool): Whether to interpolate and resolve variables.
+    RETURNS (Config): The loaded config.
+    """
     return Config(section_order=CONFIG_SECTION_ORDER).from_str(
         text, overrides=overrides, interpolate=interpolate,
     )
@@ -435,19 +482,18 @@ def get_base_version(version: str) -> str:
     return Version(version).base_version
 
 
-def get_model_meta(path: Union[str, Path]) -> Dict[str, Any]:
+def load_meta(path: Union[str, Path]) -> Dict[str, Any]:
-    """Get model meta.json from a directory path and validate its contents.
+    """Load a model meta.json from a path and validate its contents.
 
-    path (str / Path): Path to model directory.
+    path (Union[str, Path]): Path to meta.json.
-    RETURNS (Dict[str, Any]): The model's meta data.
+    RETURNS (Dict[str, Any]): The loaded meta.
     """
-    model_path = ensure_path(path)
+    path = ensure_path(path)
-    if not model_path.exists():
+    if not path.parent.exists():
-        raise IOError(Errors.E052.format(path=model_path))
+        raise IOError(Errors.E052.format(path=path.parent))
-    meta_path = model_path / "meta.json"
+    if not path.exists() or not path.is_file():
-    if not meta_path.is_file():
+        raise IOError(Errors.E053.format(path=path, name="meta.json"))
-        raise IOError(Errors.E053.format(path=meta_path, name="meta.json"))
+    meta = srsly.read_json(path)
-    meta = srsly.read_json(meta_path)
     for setting in ["lang", "name", "version"]:
         if setting not in meta or not meta[setting]:
             raise ValueError(Errors.E054.format(setting=setting))
@@ -471,6 +517,16 @@ def get_model_meta(path: Union[str, Path]) -> Dict[str, Any]:
     return meta
 
 
+def get_model_meta(path: Union[str, Path]) -> Dict[str, Any]:
+    """Get model meta.json from a directory path and validate its contents.
+
+    path (str / Path): Path to model directory.
+    RETURNS (Dict[str, Any]): The model's meta data.
+    """
+    model_path = ensure_path(path)
+    return load_meta(model_path / "meta.json")
+
+
 def is_package(name: str) -> bool:
     """Check if string maps to a package installed via pip.
 

website/docs/api/language.md

@@ -40,7 +40,7 @@ Initialize a `Language` object.
 | `meta`             | Custom meta data for the `Language` class. Is written to by models to add model meta data. ~~dict~~                      |
 | `create_tokenizer` | Optional function that receives the `nlp` object and returns a tokenizer. ~~Callable[[Language], Callable[[str], Doc]]~~ |
 
-## Language.from_config {#from_config tag="classmethod"}
+## Language.from_config {#from_config tag="classmethod" new="3"}
 
 Create a `Language` object from a loaded config. Will set up the tokenizer and
 language data, add pipeline components based on the pipeline and components

website/docs/api/top-level.md

@@ -70,7 +70,7 @@ Create a blank model of a given language class. This function is the twin of
 | `name`      | [ISO code](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) of the language class to load. ~~str~~ |
 | **RETURNS** | An empty `Language` object of the appropriate subclass. ~~Language~~                                     |
 
-#### spacy.info {#spacy.info tag="function"}
+### spacy.info {#spacy.info tag="function"}
 
 The same as the [`info` command](/api/cli#info). Pretty-print information about
 your installation, models and local setup from within spaCy. To get the model
@@ -585,20 +585,40 @@ A helper function to use in the `load()` method of a model package's
 | `config` <Tag variant="new">3</Tag> | Config overrides as nested dict or flat dict keyed by section values in dot notation, e.g. `"nlp.pipeline"`. ~~Union[Dict[str, Any], Config]~~ |
 | **RETURNS**                         | `Language` class with the loaded model. ~~Language~~                                                                                           |
 
-### util.get_model_meta {#util.get_model_meta tag="function" new="2"}
+### util.load_config {#util.load_config tag="function" new="3"}
 
-Get a model's meta.json from a directory path and validate its contents.
+Load a model's [`config.cfg`](/api/data-formats#config) from a file path. The
+config typically includes details about the model pipeline and how its
+components are created, as well as all training settings and hyperparameters.
 
 > #### Example
 >
 > ```python
-> meta = util.get_model_meta("/path/to/model")
+> config = util.load_config("/path/to/model/config.cfg")
+> print(config.to_str())
 > ```
 
-| Name        | Description                                   |
+| Name          | Description                                                                                                                                                                 |
-| ----------- | --------------------------------------------- |
+| ------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `path`      | Path to model directory. ~~Union[str, Path]~~ |
+| `path`        | Path to the model's `config.cfg`. ~~Union[str, Path]~~                                                                                                                      |
-| **RETURNS** | The model's meta data. ~~Dict[str, Any]~~     |
+| `overrides`   | Optional config overrides to replace in loaded config. Can be provided as nested dict, or as flat dict with keys in dot notation, e.g. `"nlp.pipeline"`. ~~Dict[str, Any]~~ |
+| `interpolate` | Whether to interpolate the config and replace variables like `${paths:train}` with their values. Defaults to `False`. ~~bool~~                                              |
+| **RETURNS**   | The model's config. ~~Config~~                                                                                                                                              |
+
+### util.load_meta {#util.load_meta tag="function" new="3"}
+
+Get a model's `meta.json` from a file path and validate its contents.
+
+> #### Example
+>
+> ```python
+> meta = util.load_meta("/path/to/model/meta.json")
+> ```
+
+| Name        | Description                                           |
+| ----------- | ----------------------------------------------------- |
+| `path`      | Path to the model's `meta.json`. ~~Union[str, Path]~~ |
+| **RETURNS** | The model's meta data. ~~Dict[str, Any]~~             |
 
 ### util.is_package {#util.is_package tag="function"}
 

website/src/components/code.js

@@ -62,12 +62,12 @@ function linkType(el, showLink = true) {
 
 export const TypeAnnotation = ({ lang = 'python', link = true, children }) => {
     // Hacky, but we're temporarily replacing a dot to prevent it from being split during highlighting
-    const TMP_DOT = '•'
+    const TMP_DOT = '۔'
     const code = Array.isArray(children) ? children.join('') : children || ''
     const [rawText, meta] = code.split(/(?= \(.+\)$)/)
-    const rawStr = rawText.replace('.', TMP_DOT)
+    const rawStr = rawText.replace(/\./g, TMP_DOT)
     const rawHtml = lang === 'none' || !code ? code : highlightCode(lang, rawStr)
-    const html = rawHtml.replace(TMP_DOT, '.').replace(/\n/g, ' ')
+    const html = rawHtml.replace(new RegExp(TMP_DOT, 'g'), '.').replace(/\n/g, ' ')
     const result = htmlToReact(html)
     const elements = Array.isArray(result) ? result : [result]
     const annotClassNames = classNames(