//- 💫 DOCS > API > TOKEN

include ../../_includes/_mixins

p An individual token — i.e. a word, punctuation symbol, whitespace, etc.

+h(2, "init") Token.__init__
    +tag method

p Construct a #[code Token] object.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    token = doc[0]
    assert token.text == u'Give'

+table(["Name", "Type", "Description"])
    +row
        +cell #[code vocab]
        +cell #[code Vocab]
        +cell A storage container for lexical types.

    +row
        +cell #[code doc]
        +cell #[code Doc]
        +cell The parent document.

    +row
        +cell #[code offset]
        +cell int
        +cell The index of the token within the document.

    +footrow
        +cell returns
        +cell #[code Token]
        +cell The newly constructed object.

+h(2, "len") Token.__len__
    +tag method

p The number of unicode characters in the token, i.e. #[code token.text].

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    token = doc[0]
    assert len(token) == 4

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell int
        +cell The number of unicode characters in the token.

+h(2, "check_flag") Token.check_flag
    +tag method

p Check the value of a boolean flag.

+aside-code("Example").
    from spacy.attrs import IS_TITLE
    doc = nlp(u'Give it back! He pleaded.')
    token = doc[0]
    assert token.check_flag(IS_TITLE) == True

+table(["Name", "Type", "Description"])
    +row
        +cell #[code flag_id]
        +cell int
        +cell The attribute ID of the flag to check.

    +footrow
        +cell returns
        +cell bool
        +cell Whether the flag is set.

+h(2, "similarity") Token.similarity
    +tag method
    +tag-model("vectors")

p Compute a semantic similarity estimate. Defaults to cosine over vectors.

+aside-code("Example").
    apples, _, oranges = nlp(u'apples and oranges')
    apples_oranges = apples.similarity(oranges)
    oranges_apples = oranges.similarity(apples)
    assert apples_oranges == oranges_apples

+table(["Name", "Type", "Description"])
    +row
        +cell other
        +cell -
        +cell
            |  The object to compare with. By default, accepts #[code Doc],
            |  #[code Span], #[code Token] and #[code Lexeme] objects.

    +footrow
        +cell returns
        +cell float
        +cell A scalar similarity score. Higher is more similar.

+h(2, "nbor") Token.nbor
    +tag method

p Get a neighboring token.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    give_nbor = doc[0].nbor()
    assert give_nbor.text == u'it'

+table(["Name", "Type", "Description"])
    +row
        +cell #[code i]
        +cell int
        +cell The relative position of the token to get. Defaults to #[code 1].

    +footrow
        +cell returns
        +cell #[code Token]
        +cell The token at position #[code self.doc[self.i+i]].

+h(2, "is_ancestor") Token.is_ancestor
    +tag method
    +tag-model("parse")

p
    |  Check whether this token is a parent, grandparent, etc. of another
    |  in the dependency tree.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    give = doc[0]
    it = doc[1]
    assert give.is_ancestor(it)

+table(["Name", "Type", "Description"])
    +row
        +cell descendant
        +cell #[code Token]
        +cell Another token.

    +footrow
        +cell returns
        +cell bool
        +cell Whether this token is the ancestor of the descendant.

+h(2, "ancestors") Token.ancestors
    +tag property
    +tag-model("parse")

p The rightmost token of this token's syntactic descendants.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    it_ancestors = doc[1].ancestors
    assert [t.text for t in it_ancestors] == [u'Give']
    he_ancestors = doc[4].ancestors
    assert [t.text for t in he_ancestors] == [u'pleaded']

+table(["Name", "Type", "Description"])
    +footrow
        +cell yields
        +cell #[code Token]
        +cell
            |  A sequence of ancestor tokens such that
            |  #[code ancestor.is_ancestor(self)].

+h(2, "conjuncts") Token.conjuncts
    +tag property
    +tag-model("parse")

p A sequence of coordinated tokens, including the token itself.

+aside-code("Example").
    doc = nlp(u'I like apples and oranges')
    apples_conjuncts = doc[2].conjuncts
    assert [t.text for t in apples_conjuncts] == [u'oranges']

+table(["Name", "Type", "Description"])
    +footrow
        +cell yields
        +cell #[code Token]
        +cell A coordinated token.

+h(2, "children") Token.children
    +tag property
    +tag-model("parse")

p A sequence of the token's immediate syntactic children.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    give_children = doc[0].children
    assert [t.text for t in give_children] == [u'it', u'back', u'!']

+table(["Name", "Type", "Description"])
    +footrow
        +cell yields
        +cell #[code Token]
        +cell A child token such that #[code child.head==self].

+h(2, "subtree") Token.subtree
    +tag property
    +tag-model("parse")

p A sequence of all the token's syntactic descendents.

+aside-code("Example").
    doc = nlp(u'Give it back! He pleaded.')
    give_subtree = doc[0].subtree
    assert [t.text for t in give_subtree] == [u'Give', u'it', u'back', u'!']

+table(["Name", "Type", "Description"])
    +footrow
        +cell yields
        +cell #[code Token]
        +cell A descendant token such that #[code self.is_ancestor(descendant)].

+h(2, "has_vector") Token.has_vector
    +tag property
    +tag-model("vectors")

p
    |  A boolean value indicating whether a word vector is associated with the
    |  token.

+aside-code("Example").
    doc = nlp(u'I like apples')
    apples = doc[2]
    assert apples.has_vector

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell bool
        +cell Whether the token has a vector data attached.

+h(2, "vector") Token.vector
    +tag property
    +tag-model("vectors")

p A real-valued meaning representation.

+aside-code("Example").
    doc = nlp(u'I like apples')
    apples = doc[2]
    assert apples.vector.dtype == 'float32'
    assert apples.vector.shape == (300,)

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell #[code numpy.ndarray[ndim=1, dtype='float32']]
        +cell A 1D numpy array representing the token's semantics.

+h(2, "vector_norm") Span.vector_norm
    +tag property
    +tag-model("vectors")

p The L2 norm of the token's vector representation.

+aside-code("Example").
    doc = nlp(u'I like apples and pasta')
    apples = doc[2]
    pasta = doc[4]
    apples.vector_norm # 6.89589786529541
    pasta.vector_norm # 7.759851932525635
    assert apples.vector_norm != pasta.vector_norm

+table(["Name", "Type", "Description"])
    +footrow
        +cell returns
        +cell float
        +cell The L2 norm of the vector representation.

+h(2, "attributes") Attributes

+table(["Name", "Type", "Description"])
    +row
        +cell #[code text]
        +cell unicode
        +cell Verbatim text content.
    +row
        +cell #[code text_with_ws]
        +cell unicode
        +cell Text content, with trailing space character if present.

    +row
        +cell #[code whitespace]
        +cell int
        +cell Trailing space character if present.
    +row
        +cell #[code whitespace_]
        +cell unicode
        +cell Trailing space character if present.

    +row
        +cell #[code vocab]
        +cell #[code Vocab]
        +cell The vocab object of the parent #[code Doc].

    +row
        +cell #[code doc]
        +cell #[code Doc]
        +cell The parent document.

    +row
        +cell #[code head]
        +cell #[code Token]
        +cell The syntactic parent, or "governor", of this token.

    +row
        +cell #[code left_edge]
        +cell #[code Token]
        +cell The leftmost token of this token's syntactic descendants.

    +row
        +cell #[code right_edge]
        +cell #[code Token]
        +cell The rightmost token of this token's syntactic descendents.

    +row
        +cell #[code i]
        +cell int
        +cell The index of the token within the parent document.

    +row
        +cell #[code ent_type]
        +cell int
        +cell Named entity type.

    +row
        +cell #[code ent_type_]
        +cell unicode
        +cell Named entity type.

    +row
        +cell #[code ent_iob]
        +cell int
        +cell
            |  IOB code of named entity tag. #[code "B"]
            |  means the token begins an entity, #[code "I"] means it is inside
            |  an entity, #[code "O"] means it is outside an entity, and
            |  #[code ""] means no entity tag is set.

    +row
        +cell #[code ent_iob_]
        +cell unicode
        +cell
            |  IOB code of named entity tag. #[code "B"]
            |  means the token begins an entity, #[code "I"] means it is inside
            |  an entity, #[code "O"] means it is outside an entity, and
            |  #[code ""] means no entity tag is set.

    +row
        +cell #[code ent_id]
        +cell int
        +cell
            |  ID of the entity the token is an instance of, if any. Usually
            |  assigned by patterns in the Matcher.

    +row
        +cell #[code ent_id_]
        +cell unicode
        +cell
            |  ID of the entity the token is an instance of, if any. Usually
            |  assigned by patterns in the Matcher.

    +row
        +cell #[code lemma]
        +cell int
        +cell
            |  Base form of the word, with no inflectional suffixes.

    +row
        +cell #[code lemma_]
        +cell unicode
        +cell Base form of the word, with no inflectional suffixes.

    +row
        +cell #[code lower]
        +cell int
        +cell Lower-case form of the word.

    +row
        +cell #[code lower_]
        +cell unicode
        +cell Lower-case form of the word.

    +row
        +cell #[code shape]
        +cell int
        +cell Transform of the word's string, to show orthographic features.

    +row
        +cell #[code shape_]
        +cell unicode
        +cell A transform of the word's string, to show orthographic features.

    +row
        +cell #[code prefix]
        +cell int
        +cell Integer ID of a length-N substring from the start of the
            |  word. Defaults to #[code N=1].

    +row
        +cell #[code prefix_]
        +cell unicode
        +cell
            |  A length-N substring from the start of the word. Defaults to
            |  #[code N=1].

    +row
        +cell #[code suffix]
        +cell int
        +cell
            |  Length-N substring from the end of the word. Defaults to #[code N=3].

    +row
        +cell #[code suffix_]
        +cell unicode
        +cell Length-N substring from the end of the word. Defaults to #[code N=3].

    +row
        +cell #[code is_alpha]
        +cell bool
        +cell Equivalent to #[code word.orth_.isalpha()].

    +row
        +cell #[code is_ascii]
        +cell bool
        +cell Equivalent to #[code [any(ord(c) >= 128 for c in word.orth_)]].

    +row
        +cell #[code is_digit]
        +cell bool
        +cell Equivalent to #[code word.orth_.isdigit()].

    +row
        +cell #[code is_lower]
        +cell bool
        +cell Equivalent to #[code word.orth_.islower()].

    +row
        +cell #[code is_title]
        +cell bool
        +cell Equivalent to #[code word.orth_.istitle()].

    +row
        +cell #[code is_punct]
        +cell bool
        +cell Equivalent to #[code word.orth_.ispunct()].

    +row
        +cell #[code is_space]
        +cell bool
        +cell Equivalent to #[code word.orth_.isspace()].

    +row
        +cell #[code like_url]
        +cell bool
        +cell Does the word resemble a URL?

    +row
        +cell #[code like_num]
        +cell bool
        +cell Does the word represent a number? e.g. “10.9”, “10”, “ten”, etc.

    +row
        +cell #[code like_email]
        +cell bool
        +cell Does the word resemble an email address?

    +row
        +cell #[code is_oov]
        +cell bool
        +cell Is the word out-of-vocabulary?

    +row
        +cell #[code is_stop]
        +cell bool
        +cell Is the word part of a "stop list"?

    +row
        +cell #[code pos]
        +cell int
        +cell Coarse-grained part-of-speech.

    +row
        +cell #[code pos_]
        +cell unicode
        +cell Coarse-grained part-of-speech.

    +row
        +cell #[code tag]
        +cell int
        +cell Fine-grained part-of-speech.

    +row
        +cell #[code tag_]
        +cell unicode
        +cell Fine-grained part-of-speech.

    +row
        +cell #[code dep]
        +cell int
        +cell Syntactic dependency relation.

    +row
        +cell #[code dep_]
        +cell unicode
        +cell Syntactic dependency relation.

    +row
        +cell #[code lang]
        +cell int
        +cell Language of the parent document's vocabulary.
    +row
        +cell #[code lang_]
        +cell unicode
        +cell Language of the parent document's vocabulary.

    +row
        +cell #[code prob]
        +cell float
        +cell Smoothed log probability estimate of token's type.

    +row
        +cell #[code idx]
        +cell int
        +cell The character offset of the token within the parent document.

    +row
        +cell #[code sentiment]
        +cell float
        +cell A scalar value indicating the positivity or negativity of the token.

    +row
        +cell #[code lex_id]
        +cell int
        +cell ID of the token's lexical type.