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156 lines
4.9 KiB
Plaintext
156 lines
4.9 KiB
Plaintext
//- 💫 DOCS > API > MATCHER
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include ../../_includes/_mixins
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p Match sequences of tokens, based on pattern rules.
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+infobox("⚠️ Deprecation note")
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| As of spaCy 2.0, #[code Matcher.add_pattern] and #[code Matcher.add_entity]
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| are deprecated and have been replaced with a simpler
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| #[+api("matcher#add") #[code Matcher.add]] that lets you add a list of
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| patterns and a callback for a given match ID.
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| #[code Matcher.load] (not useful, as it didn't allow specifying callbacks),
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| #[code Matcher.has_entity] and #[code Matcher.get_entity] (now redundant)
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| have been removed.
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+h(2, "init") Matcher.__init__
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+tag method
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p Create the rule-based #[code Matcher].
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+aside-code("Example").
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from spacy.matcher import Matcher
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from spacy.attrs import LOWER
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patterns = {"HelloWorld": [{LOWER: "hello"}, {LOWER: "world"}]}
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matcher = Matcher(nlp.vocab)
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code vocab]
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+cell #[code Vocab]
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+cell
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| The vocabulary object, which must be shared with the documents
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| the matcher will operate on.
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+row
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+cell #[code patterns]
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+cell dict
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+cell Patterns to add to the matcher, keyed by ID.
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+footrow
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+cell returns
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+cell #[code Matcher]
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+cell The newly constructed object.
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+h(2, "call") Matcher.__call__
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+tag method
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p Find all token sequences matching the supplied patterns on the #[code Doc].
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+aside-code("Example").
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from spacy.matcher import Matcher
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from spacy.attrs import LOWER
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matcher = Matcher(nlp.vocab)
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pattern = [{LOWER: "hello"}, {LOWER: "world"}]
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matcher.add_pattern("HelloWorld", pattern, on_match=None)
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doc = nlp(u'hello world!')
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matches = matcher(doc)
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+infobox("Important note")
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| By default, the matcher #[strong does not perform any action] on matches,
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| like tagging matched phrases with entity types. Instead, actions need to
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| be specified when #[strong adding patterns or entities], by
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| passing in a callback function as the #[code on_match] argument on
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| #[+api("matcher#add") #[code add]]. This allows you to define custom
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| actions per pattern within the same matcher. For example, you might only
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| want to merge some entity types, and set custom flags for other matched
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| patterns. For more details and examples, see the usage workflow on
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| #[+a("/docs/usage/rule-based-matching") rule-based matching].
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code doc]
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+cell #[code Doc]
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+cell The document to match over.
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+footrow
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+cell returns
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+cell list
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+cell
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| A list of #[code (match_id, start, end)] tuples, describing the
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| matches. A match tuple describes a span #[code doc[start:end]].
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| The #[code match_id] is the ID of the added match pattern.
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+h(2, "pipe") Matcher.pipe
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+tag method
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p Match a stream of documents, yielding them in turn.
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code docs]
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+cell iterable
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+cell A stream of documents.
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+row
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+cell #[code batch_size]
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+cell int
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+cell The number of documents to accumulate into a working set.
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+row
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+cell #[code n_threads]
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+cell int
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+cell
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| The number of threads with which to work on the buffer in
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| parallel, if the #[code Matcher] implementation supports
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| multi-threading.
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+footrow
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+cell yields
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+cell #[code Doc]
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+cell Documents, in order.
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+h(2, "add_pattern") Matcher.add
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+tag method
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p
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| Add one or more patterns to the matcher, along with a callback function
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| to handle the matches. The callback function will receive the arguments
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| #[code matcher], #[code doc], #[code i] and #[code matches].
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+aside-code("Example").
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from spacy.matcher import Matcher
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from spacy.attrs import LOWER, ORTH
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def on_match(matcher, doc, id, matches):
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print('Matched!', matches)
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matcher = Matcher(nlp.vocab)
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matcher.add('HelloWorld', [{LOWER: "hello"}, {LOWER: "world"}], on_match=on_match)
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matcher.add('GoogleMaps', [{ORTH: "Google"}, {ORTH: "Maps"}], on_match=on_match)
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doc = nlp(u'HELLO WORLD on Google Maps.')
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matches = matcher(doc)
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code match_id]
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+cell unicode
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+cell An ID for the thing you're matching.
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+row
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+cell #[code *patterns]
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+cell list
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+cell
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| Match pattern. A pattern consists of a list of dicts, where each
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| dict describes a token.
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+row
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+cell #[code on_match]
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+cell function
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+cell
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| Callback function to act on matches. Takes the arguments
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| #[code matcher], #[code doc], #[code i] and #[code matches].
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