mirror of https://github.com/explosion/spaCy.git
254 lines
15 KiB
Markdown
254 lines
15 KiB
Markdown
---
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title: Matcher
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teaser: Match sequences of tokens, based on pattern rules
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tag: class
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source: spacy/matcher/matcher.pyx
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---
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The `Matcher` lets you find words and phrases using rules describing their token
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attributes. Rules can refer to token annotations (like the text or
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part-of-speech tags), as well as lexical attributes like `Token.is_punct`.
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Applying the matcher to a [`Doc`](/api/doc) gives you access to the matched
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tokens in context. For in-depth examples and workflows for combining rules and
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statistical models, see the [usage guide](/usage/rule-based-matching) on
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rule-based matching.
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## Pattern format {#patterns}
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> ```json
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> ### Example
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> [
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> {"LOWER": "i"},
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> {"LEMMA": {"IN": ["like", "love"]}},
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> {"POS": "NOUN", "OP": "+"}
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> ]
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> ```
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A pattern added to the `Matcher` consists of a list of dictionaries. Each
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dictionary describes **one token** and its attributes. The available token
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pattern keys correspond to a number of
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[`Token` attributes](/api/token#attributes). The supported attributes for
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rule-based matching are:
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| Attribute | Description |
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| ----------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
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| `ORTH` | The exact verbatim text of a token. ~~str~~ |
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| `TEXT` <Tag variant="new">2.1</Tag> | The exact verbatim text of a token. ~~str~~ |
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| `NORM` | The normalized form of the token text. ~~str~~ |
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| `LOWER` | The lowercase form of the token text. ~~str~~ |
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| `LENGTH` | The length of the token text. ~~int~~ |
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| `IS_ALPHA`, `IS_ASCII`, `IS_DIGIT` | Token text consists of alphabetic characters, ASCII characters, digits. ~~bool~~ |
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| `IS_LOWER`, `IS_UPPER`, `IS_TITLE` | Token text is in lowercase, uppercase, titlecase. ~~bool~~ |
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| `IS_PUNCT`, `IS_SPACE`, `IS_STOP` | Token is punctuation, whitespace, stop word. ~~bool~~ |
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| `IS_SENT_START` | Token is start of sentence. ~~bool~~ |
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| `LIKE_NUM`, `LIKE_URL`, `LIKE_EMAIL` | Token text resembles a number, URL, email. ~~bool~~ |
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| `SPACY` | Token has a trailing space. ~~bool~~ |
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| `POS`, `TAG`, `MORPH`, `DEP`, `LEMMA`, `SHAPE` | The token's simple and extended part-of-speech tag, morphological analysis, dependency label, lemma, shape. ~~str~~ |
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| `ENT_TYPE` | The token's entity label. ~~str~~ |
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| `ENT_IOB` | The IOB part of the token's entity tag. ~~str~~ |
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| `ENT_ID` | The token's entity ID (`ent_id`). ~~str~~ |
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| `ENT_KB_ID` | The token's entity knowledge base ID (`ent_kb_id`). ~~str~~ |
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| `_` <Tag variant="new">2.1</Tag> | Properties in [custom extension attributes](/usage/processing-pipelines#custom-components-attributes). ~~Dict[str, Any]~~ |
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| `OP` | Operator or quantifier to determine how often to match a token pattern. ~~str~~ |
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Operators and quantifiers define **how often** a token pattern should be
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matched:
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> ```json
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> ### Example
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> [
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> {"POS": "ADJ", "OP": "*"},
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> {"POS": "NOUN", "OP": "+"}
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> ]
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> ```
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| OP | Description |
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| --- | ---------------------------------------------------------------- |
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| `!` | Negate the pattern, by requiring it to match exactly 0 times. |
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| `?` | Make the pattern optional, by allowing it to match 0 or 1 times. |
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| `+` | Require the pattern to match 1 or more times. |
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| `*` | Allow the pattern to match 0 or more times. |
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Token patterns can also map to a **dictionary of properties** instead of a
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single value to indicate whether the expected value is a member of a list or how
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it compares to another value.
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> ```json
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> ### Example
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> [
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> {"LEMMA": {"IN": ["like", "love", "enjoy"]}},
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> {"POS": "PROPN", "LENGTH": {">=": 10}},
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> ]
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> ```
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| Attribute | Description |
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| -------------------------- | -------------------------------------------------------------------------------------------------------- |
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| `IN` | Attribute value is member of a list. ~~Any~~ |
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| `NOT_IN` | Attribute value is _not_ member of a list. ~~Any~~ |
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| `IS_SUBSET` | Attribute value (for `MORPH` or custom list attributes) is a subset of a list. ~~Any~~ |
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| `IS_SUPERSET` | Attribute value (for `MORPH` or custom list attributes) is a superset of a list. ~~Any~~ |
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| `INTERSECTS` | Attribute value (for `MORPH` or custom list attribute) has a non-empty intersection with a list. ~~Any~~ |
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| `==`, `>=`, `<=`, `>`, `<` | Attribute value is equal, greater or equal, smaller or equal, greater or smaller. ~~Union[int, float]~~ |
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## Matcher.\_\_init\_\_ {#init tag="method"}
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Create the rule-based `Matcher`. If `validate=True` is set, all patterns added
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to the matcher will be validated against a JSON schema and a `MatchPatternError`
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is raised if problems are found. Those can include incorrect types (e.g. a
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string where an integer is expected) or unexpected property names.
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> #### Example
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>
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> ```python
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> from spacy.matcher import Matcher
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> matcher = Matcher(nlp.vocab)
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> ```
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| Name | Description |
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| --------------------------------------- | ----------------------------------------------------------------------------------------------------- |
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| `vocab` | The vocabulary object, which must be shared with the documents the matcher will operate on. ~~Vocab~~ |
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| `validate` <Tag variant="new">2.1</Tag> | Validate all patterns added to this matcher. ~~bool~~ |
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## Matcher.\_\_call\_\_ {#call tag="method"}
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Find all token sequences matching the supplied patterns on the `Doc` or `Span`.
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> #### Example
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>
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> ```python
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> from spacy.matcher import Matcher
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>
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> matcher = Matcher(nlp.vocab)
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> pattern = [{"LOWER": "hello"}, {"LOWER": "world"}]
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> matcher.add("HelloWorld", [pattern])
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> doc = nlp("hello world!")
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> matches = matcher(doc)
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> ```
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| Name | Description |
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| ------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `doclike` | The `Doc` or `Span` to match over. ~~Union[Doc, Span]~~ |
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| _keyword-only_ | |
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| `as_spans` <Tag variant="new">3</Tag> | Instead of tuples, return a list of [`Span`](/api/span) objects of the matches, with the `match_id` assigned as the span label. Defaults to `False`. ~~bool~~ |
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| `allow_missing` <Tag variant="new">3</Tag> | Whether to skip checks for missing annotation for attributes included in patterns. Defaults to `False`. ~~bool~~ |
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| `with_alignments` <Tag variant="new">3.0.6</Tag> | Return match alignment information as part of the match tuple as `List[int]` with the same length as the matched span. Each entry denotes the corresponding index of the token pattern. If `as_spans` is set to `True`, this setting is ignored. Defaults to `False`. ~~bool~~ |
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| **RETURNS** | A list of `(match_id, start, end)` tuples, describing the matches. A match tuple describes a span `doc[start:end`]. The `match_id` is the ID of the added match pattern. If `as_spans` is set to `True`, a list of `Span` objects is returned instead. ~~Union[List[Tuple[int, int, int]], List[Span]]~~ |
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## Matcher.\_\_len\_\_ {#len tag="method" new="2"}
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Get the number of rules added to the matcher. Note that this only returns the
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number of rules (identical with the number of IDs), not the number of individual
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patterns.
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> #### Example
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>
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> ```python
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> matcher = Matcher(nlp.vocab)
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> assert len(matcher) == 0
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> matcher.add("Rule", [[{"ORTH": "test"}]])
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> assert len(matcher) == 1
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> ```
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| Name | Description |
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| ----------- | ---------------------------- |
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| **RETURNS** | The number of rules. ~~int~~ |
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## Matcher.\_\_contains\_\_ {#contains tag="method" new="2"}
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Check whether the matcher contains rules for a match ID.
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> #### Example
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>
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> ```python
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> matcher = Matcher(nlp.vocab)
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> assert "Rule" not in matcher
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> matcher.add("Rule", [[{'ORTH': 'test'}]])
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> assert "Rule" in matcher
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> ```
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| Name | Description |
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| ----------- | -------------------------------------------------------------- |
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| `key` | The match ID. ~~str~~ |
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| **RETURNS** | Whether the matcher contains rules for this match ID. ~~bool~~ |
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## Matcher.add {#add tag="method" new="2"}
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Add a rule to the matcher, consisting of an ID key, one or more patterns, and an
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optional callback function to act on the matches. The callback function will
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receive the arguments `matcher`, `doc`, `i` and `matches`. If a pattern already
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exists for the given ID, the patterns will be extended. An `on_match` callback
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will be overwritten.
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> #### Example
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>
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> ```python
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> def on_match(matcher, doc, id, matches):
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> print('Matched!', matches)
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>
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> matcher = Matcher(nlp.vocab)
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> patterns = [
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> [{"LOWER": "hello"}, {"LOWER": "world"}],
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> [{"ORTH": "Google"}, {"ORTH": "Maps"}]
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> ]
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> matcher.add("TEST_PATTERNS", patterns)
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> doc = nlp("HELLO WORLD on Google Maps.")
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> matches = matcher(doc)
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> ```
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<Infobox title="Changed in v3.0" variant="warning">
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As of spaCy v3.0, `Matcher.add` takes a list of patterns as the second argument
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(instead of a variable number of arguments). The `on_match` callback becomes an
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optional keyword argument.
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```diff
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patterns = [[{"TEXT": "Google"}, {"TEXT": "Now"}], [{"TEXT": "GoogleNow"}]]
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- matcher.add("GoogleNow", on_match, *patterns)
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+ matcher.add("GoogleNow", patterns, on_match=on_match)
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```
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</Infobox>
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| Name | Description |
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| ----------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `match_id` | An ID for the thing you're matching. ~~str~~ |
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| `patterns` | Match pattern. A pattern consists of a list of dicts, where each dict describes a token. ~~List[List[Dict[str, Any]]]~~ |
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| _keyword-only_ | |
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| `on_match` | Callback function to act on matches. Takes the arguments `matcher`, `doc`, `i` and `matches`. ~~Optional[Callable[[Matcher, Doc, int, List[tuple], Any]]~~ |
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| `greedy` <Tag variant="new">3</Tag> | Optional filter for greedy matches. Can either be `"FIRST"` or `"LONGEST"`. ~~Optional[str]~~ |
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## Matcher.remove {#remove tag="method" new="2"}
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Remove a rule from the matcher. A `KeyError` is raised if the match ID does not
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exist.
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> #### Example
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>
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> ```python
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> matcher.add("Rule", [[{"ORTH": "test"}]])
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> assert "Rule" in matcher
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> matcher.remove("Rule")
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> assert "Rule" not in matcher
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> ```
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| Name | Description |
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| ----- | --------------------------------- |
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| `key` | The ID of the match rule. ~~str~~ |
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## Matcher.get {#get tag="method" new="2"}
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Retrieve the pattern stored for a key. Returns the rule as an
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`(on_match, patterns)` tuple containing the callback and available patterns.
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> #### Example
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>
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> ```python
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> matcher.add("Rule", [[{"ORTH": "test"}]])
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> on_match, patterns = matcher.get("Rule")
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> ```
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| Name | Description |
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| ----------- | --------------------------------------------------------------------------------------------- |
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| `key` | The ID of the match rule. ~~str~~ |
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| **RETURNS** | The rule, as an `(on_match, patterns)` tuple. ~~Tuple[Optional[Callable], List[List[dict]]]~~ |
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