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223 lines
12 KiB
Markdown
223 lines
12 KiB
Markdown
---
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title: DependencyMatcher
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teaser: Match subtrees within a dependency parse
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tag: class
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new: 3
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source: spacy/matcher/dependencymatcher.pyx
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---
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The `DependencyMatcher` follows the same API as the [`Matcher`](/api/matcher)
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and [`PhraseMatcher`](/api/phrasematcher) and lets you match on dependency trees
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using
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[Semgrex operators](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html).
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It requires a pretrained [`DependencyParser`](/api/parser) or other component
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that sets the `Token.dep` and `Token.head` attributes. See the
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[usage guide](/usage/rule-based-matching#dependencymatcher) for examples.
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## Pattern format {#patterns}
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> ```python
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> ### Example
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> # pattern: "[subject] ... initially founded"
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> [
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> # anchor token: founded
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> {
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> "RIGHT_ID": "founded",
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> "RIGHT_ATTRS": {"ORTH": "founded"}
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> },
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> # founded -> subject
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> {
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> "LEFT_ID": "founded",
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> "REL_OP": ">",
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> "RIGHT_ID": "subject",
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> "RIGHT_ATTRS": {"DEP": "nsubj"}
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> },
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> # "founded" follows "initially"
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> {
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> "LEFT_ID": "founded",
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> "REL_OP": ";",
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> "RIGHT_ID": "initially",
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> "RIGHT_ATTRS": {"ORTH": "initially"}
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> }
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> ]
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> ```
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A pattern added to the `DependencyMatcher` consists of a list of dictionaries,
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with each dictionary describing a token to match. Except for the first
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dictionary, which defines an anchor token using only `RIGHT_ID` and
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`RIGHT_ATTRS`, each pattern should have the following keys:
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| Name | Description |
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| ------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `LEFT_ID` | The name of the left-hand node in the relation, which has been defined in an earlier node. ~~str~~ |
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| `REL_OP` | An operator that describes how the two nodes are related. ~~str~~ |
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| `RIGHT_ID` | A unique name for the right-hand node in the relation. ~~str~~ |
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| `RIGHT_ATTRS` | The token attributes to match for the right-hand node in the same format as patterns provided to the regular token-based [`Matcher`](/api/matcher). ~~Dict[str, Any]~~ |
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<Infobox title="Designing dependency matcher patterns" emoji="📖">
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For examples of how to construct dependency matcher patterns for different types
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of relations, see the usage guide on
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[dependency matching](/usage/rule-based-matching#dependencymatcher).
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</Infobox>
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### Operators
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The following operators are supported by the `DependencyMatcher`, most of which
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come directly from
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[Semgrex](https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/semgraph/semgrex/SemgrexPattern.html):
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| Symbol | Description |
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| --------- | -------------------------------------------------------------------------------------------------------------------- |
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| `A < B` | `A` is the immediate dependent of `B`. |
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| `A > B` | `A` is the immediate head of `B`. |
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| `A << B` | `A` is the dependent in a chain to `B` following dep → head paths. |
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| `A >> B` | `A` is the head in a chain to `B` following head → dep paths. |
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| `A . B` | `A` immediately precedes `B`, i.e. `A.i == B.i - 1`, and both are within the same dependency tree. |
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| `A .* B` | `A` precedes `B`, i.e. `A.i < B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
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| `A ; B` | `A` immediately follows `B`, i.e. `A.i == B.i + 1`, and both are within the same dependency tree _(not in Semgrex)_. |
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| `A ;* B` | `A` follows `B`, i.e. `A.i > B.i`, and both are within the same dependency tree _(not in Semgrex)_. |
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| `A $+ B` | `B` is a right immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i - 1`. |
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| `A $- B` | `B` is a left immediate sibling of `A`, i.e. `A` and `B` have the same parent and `A.i == B.i + 1`. |
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| `A $++ B` | `B` is a right sibling of `A`, i.e. `A` and `B` have the same parent and `A.i < B.i`. |
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| `A $-- B` | `B` is a left sibling of `A`, i.e. `A` and `B` have the same parent and `A.i > B.i`. |
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## DependencyMatcher.\_\_init\_\_ {#init tag="method"}
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Create a `DependencyMatcher`.
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> #### Example
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>
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> ```python
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> from spacy.matcher import DependencyMatcher
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> matcher = DependencyMatcher(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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| _keyword-only_ | |
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| `validate` | Validate all patterns added to this matcher. ~~bool~~ |
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## DependencyMatcher.\_\call\_\_ {#call tag="method"}
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Find all tokens 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 DependencyMatcher
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>
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> matcher = DependencyMatcher(nlp.vocab)
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> pattern = [{"RIGHT_ID": "founded_id",
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> "RIGHT_ATTRS": {"ORTH": "founded"}}]
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> matcher.add("FOUNDED", [pattern])
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> doc = nlp("Bill Gates founded Microsoft.")
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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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| **RETURNS** | A list of `(match_id, token_ids)` tuples, describing the matches. The `match_id` is the ID of the match pattern and `token_ids` is a list of token indices matched by the pattern, where the position of each token in the list corresponds to the position of the node specification in the pattern. ~~List[Tuple[int, List[int]]]~~ |
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## DependencyMatcher.\_\_len\_\_ {#len tag="method"}
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Get the number of rules added to the dependency matcher. Note that this only
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returns the number of rules (identical with the number of IDs), not the number
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of individual patterns.
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> #### Example
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>
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> ```python
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> matcher = DependencyMatcher(nlp.vocab)
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> assert len(matcher) == 0
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> pattern = [{"RIGHT_ID": "founded_id",
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> "RIGHT_ATTRS": {"ORTH": "founded"}}]
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> matcher.add("FOUNDED", [pattern])
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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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## DependencyMatcher.\_\_contains\_\_ {#contains tag="method"}
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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 = DependencyMatcher(nlp.vocab)
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> assert "FOUNDED" not in matcher
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> matcher.add("FOUNDED", [pattern])
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> assert "FOUNDED" 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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## DependencyMatcher.add {#add tag="method"}
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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 = DependencyMatcher(nlp.vocab)
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> matcher.add("FOUNDED", patterns, on_match=on_match)
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> ```
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| Name | Description |
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| -------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `match_id` | An ID for the patterns. ~~str~~ |
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| `patterns` | A list of match patterns. A pattern consists of a list of dicts, where each dict describes a token in the tree. ~~List[List[Dict[str, Union[str, Dict]]]]~~ |
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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[[DependencyMatcher, Doc, int, List[Tuple], Any]]~~ |
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## DependencyMatcher.get {#get tag="method"}
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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("FOUNDED", patterns, on_match=on_match)
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> on_match, patterns = matcher.get("FOUNDED")
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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[Union[Dict, Tuple]]]]~~ |
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## DependencyMatcher.remove {#remove tag="method"}
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Remove a rule from the dependency matcher. A `KeyError` is raised if the match
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ID does not exist.
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> #### Example
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>
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> ```python
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> matcher.add("FOUNDED", patterns)
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> assert "FOUNDED" in matcher
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> matcher.remove("FOUNDED")
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> assert "FOUNDED" 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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