mirror of https://github.com/explosion/spaCy.git
211 lines
10 KiB
Markdown
211 lines
10 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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<Infobox title="Changed in v2.0" variant="warning">
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As of spaCy 2.0, `Matcher.add_pattern` and `Matcher.add_entity` are deprecated
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and have been replaced with a simpler [`Matcher.add`](/api/matcher#add) that
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lets you add a list of patterns and a callback for a given match ID.
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`Matcher.get_entity` is now called [`matcher.get`](/api/matcher#get).
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`Matcher.load` (not useful, as it didn't allow specifying callbacks), and
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`Matcher.has_entity` (now redundant) have been removed. The concept of "acceptor
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functions" has also been retired – this logic can now be handled in the callback
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functions.
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</Infobox>
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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 | Type | Description |
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| --------------------------------------- | --------- | ------------------------------------------------------------------------------------------- |
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| `vocab` | `Vocab` | The vocabulary object, which must be shared with the documents the matcher will operate on. |
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| `validate` <Tag variant="new">2.1</Tag> | bool | Validate all patterns added to this matcher. |
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| **RETURNS** | `Matcher` | The newly constructed object. |
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## Matcher.\_\_call\_\_ {#call tag="method"}
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Find all token sequences matching the supplied patterns on the `Doc`.
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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", None, 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 | Type | Description |
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| ----------- | ----- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `doc` | `Doc` | The document to match over. |
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| **RETURNS** | list | 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. |
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<Infobox title="Important note" variant="warning">
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By default, the matcher **does not perform any action** on matches, like tagging
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matched phrases with entity types. Instead, actions need to be specified when
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**adding patterns or entities**, by passing in a callback function as the
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`on_match` argument on [`add`](/api/matcher#add). This allows you to define
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custom 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 guide on
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[rule-based matching](/usage/rule-based-matching).
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</Infobox>
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## Matcher.pipe {#pipe tag="method"}
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Match a stream of documents, yielding them in turn.
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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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> for doc in matcher.pipe(docs, batch_size=50):
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> pass
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> ```
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| Name | Type | Description |
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| --------------------------------------------- | -------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `docs` | iterable | A stream of documents. |
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| `batch_size` | int | The number of documents to accumulate into a working set. |
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| `return_matches` <Tag variant="new">2.1</Tag> | bool | Yield the match lists along with the docs, making results `(doc, matches)` tuples. |
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| `as_tuples` | bool | Interpret the input stream as `(doc, context)` tuples, and yield `(result, context)` tuples out. If both `return_matches` and `as_tuples` are `True`, the output will be a sequence of `((doc, matches), context)` tuples. |
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| **YIELDS** | `Doc` | Documents, in order. |
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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", None, [{"ORTH": "test"}])
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> assert len(matcher) == 1
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> ```
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| Name | Type | Description |
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| ----------- | ---- | -------------------- |
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| **RETURNS** | int | The number of rules. |
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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', None, [{'ORTH': 'test'}])
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> assert 'Rule' in matcher
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> ```
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| Name | Type | Description |
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| ----------- | ------- | ----------------------------------------------------- |
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| `key` | unicode | The match ID. |
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| **RETURNS** | bool | Whether the matcher contains rules for this match ID. |
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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 a
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callback function to act on the matches. The callback function will receive the
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arguments `matcher`, `doc`, `i` and `matches`. If a pattern already exists for
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the given ID, the patterns will be extended. An `on_match` callback will be
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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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> matcher.add("HelloWorld", on_match, [{"LOWER": "hello"}, {"LOWER": "world"}])
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> matcher.add("GoogleMaps", on_match, [{"ORTH": "Google"}, {"ORTH": "Maps"}])
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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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| Name | Type | Description |
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| ----------- | ------------------ | --------------------------------------------------------------------------------------------- |
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| `match_id` | unicode | An ID for the thing you're matching. |
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| `on_match` | callable or `None` | Callback function to act on matches. Takes the arguments `matcher`, `doc`, `i` and `matches`. |
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| `*patterns` | list | Match pattern. A pattern consists of a list of dicts, where each dict describes a token. |
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<Infobox title="Changed in v2.2.2" variant="warning">
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As of spaCy 2.2.2, `Matcher.add` also supports the new API, which will become
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the default in the future. The patterns are now the second argument and a list
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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", None, *patterns)
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+ matcher.add("GoogleNow", patterns)
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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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## 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", None, [{"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 | Type | Description |
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| ----- | ------- | ------------------------- |
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| `key` | unicode | The ID of the match rule. |
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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", None, [{"ORTH": "test"}])
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> on_match, patterns = matcher.get("Rule")
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> ```
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| Name | Type | Description |
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| ----------- | ------- | --------------------------------------------- |
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| `key` | unicode | The ID of the match rule. |
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| **RETURNS** | tuple | The rule, as an `(on_match, patterns)` tuple. |
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