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Refactor dependencymatcher.pyx to use list comps and enumerate. (#8956)

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* Refactor to use list comps and enumerate.

Replace loops that append to a list with a list comprehensions where this does not change the behavior; replace range(len(...)) loops with enumerate. Correct one typo in a comment. Replace a call to set() with a set literal.

* Undo double assignment.

Expand `tokens_to_key[j] = k = self._get_matcher_key(key, i, j)` to two statements.

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Sign contributors agreement

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
This commit is contained in:
Steele Farnsworth 2021-08-18 03:55:45 -04:00 committed by GitHub
parent d94ddd5686
commit b18cb1cd2a
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2 changed files with 97 additions and 26 deletions
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88
.github/contributors/swfarnsworth.md vendored Normal file
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@ -0,0 +1,88 @@
## Contributor Agreement
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## Contributor Details
| Field | Entry |
|------------------------------- | -------------------- |
| Name | Steele Farnsworth |
| Company name (if applicable) | |
| Title or role (if applicable) | |
| Date | 13 August, 2021 |
| GitHub username | swfarnsworth |
| Website (optional) | |

35
spacy/matcher/dependencymatcher.pyx
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@ -3,7 +3,6 @@ from typing import List
from collections import defaultdict
from itertools import product
import numpy
import warnings
from .matcher cimport Matcher
@ -122,9 +121,7 @@ cdef class DependencyMatcher:
raise ValueError(Errors.E099.format(key=key))
visited_nodes[relation["RIGHT_ID"]] = True
else:
required_keys = set(
("RIGHT_ID", "RIGHT_ATTRS", "REL_OP", "LEFT_ID")
)
required_keys = {"RIGHT_ID", "RIGHT_ATTRS", "REL_OP", "LEFT_ID"}
relation_keys = set(relation.keys())
missing = required_keys - relation_keys
if missing:
@ -179,28 +176,22 @@ cdef class DependencyMatcher:
self._callbacks[key] = on_match
# Add 'RIGHT_ATTRS' to self._patterns[key]
_patterns = []
for pattern in patterns:
token_patterns = []
for i in range(len(pattern)):
token_pattern = [pattern[i]["RIGHT_ATTRS"]]
token_patterns.append(token_pattern)
_patterns.append(token_patterns)
_patterns = [[[pat["RIGHT_ATTRS"]] for pat in pattern] for pattern in patterns]
self._patterns[key].extend(_patterns)
# Add each node pattern of all the input patterns individually to the
# matcher. This enables only a single instance of Matcher to be used.
# Multiple adds are required to track each node pattern.
tokens_to_key_list = []
for i in range(len(_patterns)):
for i, current_patterns in enumerate(_patterns):
# Preallocate list space
tokens_to_key = [None]*len(_patterns[i])
tokens_to_key = [None] * len(current_patterns)
# TODO: Better ways to hash edges in pattern?
for j in range(len(_patterns[i])):
for j, _pattern in enumerate(current_patterns):
k = self._get_matcher_key(key, i, j)
self._matcher.add(k, [_patterns[i][j]])
self._matcher.add(k, [_pattern])
tokens_to_key[j] = k
tokens_to_key_list.append(tokens_to_key)
@ -337,7 +328,7 @@ cdef class DependencyMatcher:
# position of the matched tokens
for candidate_match in product(*all_positions):
# A potential match is a valid match if all relationhips between the
# A potential match is a valid match if all relationships between the
# matched tokens are satisfied.
is_valid = True
for left_idx in range(len(candidate_match)):
@ -424,18 +415,10 @@ cdef class DependencyMatcher:
return []
def _right_sib(self, doc, node):
candidate_children = []
for child in list(doc[node].head.children):
if child.i > node:
candidate_children.append(doc[child.i])
return candidate_children
return [doc[child.i] for child in doc[node].head.children if child.i > node]
def _left_sib(self, doc, node):
candidate_children = []
for child in list(doc[node].head.children):
if child.i < node:
candidate_children.append(doc[child.i])
return candidate_children
return [doc[child.i] for child in doc[node].head.children if child.i < node]
def _normalize_key(self, key):
if isinstance(key, basestring):