mirror of
https://github.com/explosion/spaCy.git
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206 lines
6.2 KiB
ReStructuredText
206 lines
6.2 KiB
ReStructuredText
===============
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Documentation
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===============
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Quick Ref
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---------
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.. class:: spacy.en.__init__.English(self, data_dir=join(dirname(__file__, 'data')))
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:noindex:
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.. method:: __call__(self, unicode text, tag=True, parse=False) --> Tokens
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+-----------+--------------+--------------+
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| Attribute | Type | Useful |
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+===========+==============+==============+
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| strings | StingStore | __getitem__ |
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+-----------+--------------+--------------+
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| vocab | Vocab | __getitem__ |
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+-----------+--------------+--------------+
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| tokenizer | Tokenizer | __call__ |
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+-----------+--------------+--------------+
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| tagger | EnPosTagger | __call__ |
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+-----------+--------------+--------------+
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| parser | GreedyParser | __call__ |
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+-----------+--------------+--------------+
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.. py:class:: spacy.tokens.Tokens(self, vocab: Vocab, string_length=0)
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.. py:method:: __getitem__(self, i) --> Token
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.. py:method:: __iter__(self) --> Iterator[Token]
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.. py:method:: __len__(self) --> int
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.. py:method:: to_array(self, attr_ids: List[int]) --> numpy.ndarray[ndim=2, dtype=int32]
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.. py:method:: count_by(self, attr_id: int) --> Dict[int, int]
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+---------------+-------------+-------------+
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| Attribute | Type | Useful |
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+===============+=============+=============+
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| vocab | Vocab | __getitem__ |
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+---------------+-------------+-------------+
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| vocab.strings | StringStore | __getitem__ |
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+---------------+-------------+-------------+
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.. py:class:: spacy.tokens.Token(self, parent: Tokens, i: int)
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.. py:method:: __unicode__(self) --> unicode
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.. py:method:: __len__(self) --> int
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.. py:method:: nbor(self, i=1) --> Token
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.. py:method:: child(self, i=1) --> Token
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.. py:method:: sibling(self, i=1) --> Token
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.. py:attribute:: head: Token
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.. py:method:: check_flag(self, attr_id: int) --> bool
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+-----------+------+-----------+---------+-----------+-------+
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| Attribute | Type | Attribute | Type | Attribute | Type |
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+===========+======+===========+=========+===========+=======+
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| sic | int | sic_ | unicode | idx | int |
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+-----------+------+-----------+---------+-----------+-------+
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| lemma | int | lemma_ | unicode | cluster | int |
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+-----------+------+-----------+---------+-----------+-------+
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| norm1 | int | norm1_ | unicode | length | int |
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+-----------+------+-----------+---------+-----------+-------+
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| norm2 | int | norm2_ | unicode | prob | float |
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+-----------+------+-----------+---------+-----------+-------+
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| shape | int | shape_ | unicode | sentiment | float |
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+-----------+------+-----------+---------+-----------+-------+
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| prefix | int | prefix_ | unicode | |
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+-----------+------+-----------+---------+-------------------+
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| suffix | int | suffix_ | unicode | |
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+-----------+------+-----------+---------+-------------------+
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| pos | int | pos_ | unicode | |
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+-----------+------+-----------+---------+-------------------+
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| fine_pos | int | fine_pos_ | unicode | |
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+-----------+------+-----------+---------+-------------------+
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| dep_tag | int | dep_tag_ | unicode | |
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+-----------+------+-----------+---------+-------------------+
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.. py:class:: spacy.vocab.Vocab(self, data_dir=None, lex_props_getter=None)
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.. py:method:: __len__(self) --> int
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.. py:method:: __getitem__(self, id: int) --> unicode
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.. py:method:: __getitem__(self, string: unicode) --> int
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.. py:method:: __setitem__(self, py_str: unicode, props: Dict[str, int|float]) --> None
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.. py:method:: dump(self, loc: unicode) --> None
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.. py:method:: load_lexemes(self, loc: unicode) --> None
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.. py:method:: load_vectors(self, loc: unicode) --> None
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.. py:class:: spacy.strings.StringStore(self)
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.. py:method:: __len__(self) --> int
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.. py:method:: __getitem__(self, id: int) --> unicode
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.. py:method:: __getitem__(self, string: byts) --> id
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.. py:method:: __getitem__(self, string: unicode) --> id
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.. py:method:: dump(self, loc: unicode) --> None
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.. py:method:: load(self, loc: unicode) --> None
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.. py:class:: spacy.tokenizer.Tokenizer(self, Vocab vocab, rules, prefix_re, suffix_re, infix_re, pos_tags, tag_names)
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.. py:method:: tokens_from_list(self, List[unicode]) --> spacy.tokens.Tokens
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.. py:method:: __call__(self, string: unicode) --> spacy.tokens.Tokens)
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.. py:attribute:: vocab: spacy.vocab.Vocab
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.. py:class:: spacy.en.pos.EnPosTagger(self, strings: spacy.strings.StringStore, data_dir: unicode)
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.. py:method:: __call__(self, tokens: spacy.tokens.Tokens)
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.. py:method:: train(self, tokens: spacy.tokens.Tokens, List[int] golds) --> int
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.. py:method:: load_morph_exceptions(self, exc: Dict[unicode, Dict])
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.. py:class:: GreedyParser(self, model_dir: unicode)
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.. py:method:: __call__(self, tokens: spacy.tokens.Tokens) --> None
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.. py:method:: train(self, spacy.tokens.Tokens) --> None
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spaCy is designed to easily extend to multiple languages, although presently
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only English components are implemented. The components are organised into
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a pipeline in the spacy.en.English class.
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Usually, you will only want to create one spacy.en.English object, and pass it
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around your application. It manages the string-to-integers mapping, and you
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will usually want only a single mapping for all strings.
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English Pipeline
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----------------
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The spacy.en package exports a single class, English, and several constants,
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under spacy.en.defs.
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.. autoclass:: spacy.en.English
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:members:
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.. autommodule:: spacy.en.pos
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:members:
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.. automodule:: spacy.en.attrs
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:members:
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:undoc-members:
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Tokens
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------
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.. autoclass:: spacy.tokens.Tokens
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:members:
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.. autoclass:: spacy.tokens.Token
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:members:
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.. autoclass:: spacy.lexeme.Lexeme
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:members:
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Lexicon
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-------
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.. automodule:: spacy.vocab
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:members:
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.. automodule:: spacy.strings
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:members:
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Tokenizer
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---------
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.. automodule:: spacy.tokenizer
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:members:
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Parser
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------
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.. automodule:: spacy.syntax.parser
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:members:
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Utility Functions
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-----------------
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.. automodule:: spacy.orth
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:members:
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