mirror of https://github.com/explosion/spaCy.git
143 lines
4.4 KiB
Plaintext
143 lines
4.4 KiB
Plaintext
//- 💫 DOCS > API > SPACY
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include ../../_includes/_mixins
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+h(2, "load") spacy.load
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+tag function
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+tag-model
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p
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| Load a model via its #[+a("/docs/usage/models#usage") shortcut link],
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| the name of an installed
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| #[+a("/docs/usage/saving-loading#generating") model package], a unicode
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| path or a #[code Path]-like object. spaCy will try resolving the load
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| argument in this order. The #[code Language] class to initialise will be
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| determined based on the model's settings.
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+aside-code("Example").
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nlp = spacy.load('en') # shortcut link
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nlp = spacy.load('en_core_web_sm') # package
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nlp = spacy.load('/path/to/en') # unicode path
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nlp = spacy.load(Path('/path/to/en')) # pathlib Path
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nlp = spacy.load('en', disable['parser', 'tagger'])
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code name]
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+cell unicode or #[code Path]
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+cell Model to load, i.e. shortcut link, package name or path.
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+row
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+cell #[code disable]
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+cell list
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+cell
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| Names of pipeline components to
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| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
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+footrow
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+cell returns
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+cell #[code Language]
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+cell A #[code Language] object with the loaded model.
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+infobox("⚠️ Deprecation note")
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.o-block
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| As of spaCy 2.0, the #[code path] keyword argument is deprecated. spaCy
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| will also raise an error if no model could be loaded and never just
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| return an empty #[code Language] object. If you need a blank language,
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| you need to import it explicitly (#[code from spacy.lang.en import English])
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| or use #[+api("util#get_lang_class") #[code util.get_lang_class]].
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+code-new nlp = spacy.load('/model')
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+code-old nlp = spacy.load('en', path='/model')
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+h(2, "info") spacy.info
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+tag function
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p
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| The same as the #[+api("cli#info") #[code info] command]. Pretty-print
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| information about your installation, models and local setup from within
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| spaCy. To get the model meta data as a dictionary instead, you can
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| use the #[code meta] attribute on your #[code nlp] object with a
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| loaded model, e.g. #[code nlp['meta']].
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+aside-code("Example").
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spacy.info()
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spacy.info('en')
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spacy.info('de', markdown=True)
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code model]
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+cell unicode
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+cell A model, i.e. shortcut link, package name or path (optional).
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+row
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+cell #[code markdown]
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+cell bool
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+cell Print information as Markdown.
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+h(2, "explain") spacy.explain
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+tag function
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p
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| Get a description for a given POS tag, dependency label or entity type.
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| For a list of available terms, see
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| #[+src(gh("spacy", "spacy/glossary.py")) glossary.py].
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+aside-code("Example").
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spacy.explain('NORP')
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# Nationalities or religious or political groups
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doc = nlp(u'Hello world')
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for word in doc:
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print(word.text, word.tag_, spacy.explain(word.tag_))
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# Hello UH interjection
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# world NN noun, singular or mass
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code term]
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+cell unicode
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+cell Term to explain.
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+footrow
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+cell returns
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+cell unicode
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+cell The explanation, or #[code None] if not found in the glossary.
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+h(2, "set_factory") spacy.set_factory
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+tag function
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+tag-new(2)
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p
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| Set a factory that returns a custom
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| #[+a("/docs/usage/language-processing-pipeline") processing pipeline]
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| component. Factories are useful for creating stateful components, especially ones which depend on shared data.
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+aside-code("Example").
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def my_factory(vocab):
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def my_component(doc):
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return doc
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return my_component
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spacy.set_factory('my_factory', my_factory)
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nlp = Language(pipeline=['my_factory'])
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code factory_id]
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+cell unicode
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+cell
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| Unique name of factory. If added to a new pipeline, spaCy will
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| look up the factory for this ID and use it to create the
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| component.
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+row
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+cell #[code factory]
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+cell callable
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+cell
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| Callable that takes a #[code Vocab] object and returns a pipeline
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| component.
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