spaCy/spacy/tests/pipeline/test_entity_ruler.py
Joshua Smith 2eb925bd05 Added an argument to EntityRuler constructor to pass attrs to… (#3919)
* Perserve flags in EntityRuler

The EntityRuler (explosion/spaCy#3526) does not preserve
overwrite flags (or `ent_id_sep`) when serialized.  This
commit adds support for serialization/deserialization preserving
overwrite and ent_id_sep flags.

* add signed contributor agreement

* flake8 cleanup

mostly blank line issues.

* mark test from the issue as needing a model

The test from the issue needs some language model for serialization
but the test wasn't originally marked correctly.

* Adds `phrase_matcher_attr` to allow args to PhraseMatcher

This is an added arg to pass to the `PhraseMatcher`. For example,
this allows creation of a case insensitive phrase matcher when the
`EntityRuler` is created.  References explosion/spaCy#3822

* remove unneeded model loading

The model didn't need to be loaded, and I replaced it with
a change that doesn't require it (using existings fixtures)

* updated docstring for new argument

* updated docs to reflect new argument to the EntityRuler constructor

* change tempdir handling to be compatible with python 2.7

* return conflicted code to entityruler

Some stuff got cut out because of merge conflicts, this
returns that code for the phrase_matcher_attr.

* fixed typo in the code added back after conflicts

* flake8 compliance

When I deconflicted the branch there were some flake8 issues
introduced. This resolves the spacing problems.

* test changes:  attempts to fix flaky test in python3.5

These tests seem to be alittle flaky in 3.5 so I changed the check to avoid
the comparisons that seem to be fail sometimes.
2019-07-09 20:09:17 +02:00

130 lines
4.1 KiB
Python

# coding: utf8
from __future__ import unicode_literals
import pytest
from spacy.tokens import Span
from spacy.language import Language
from spacy.pipeline import EntityRuler
@pytest.fixture
def nlp():
return Language()
@pytest.fixture
def patterns():
return [
{"label": "HELLO", "pattern": "hello world"},
{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
{"label": "TECH_ORG", "pattern": "Apple", "id": "a1"},
]
@pytest.fixture
def add_ent():
def add_ent_component(doc):
doc.ents = [Span(doc, 0, 3, label=doc.vocab.strings["ORG"])]
return doc
return add_ent_component
def test_entity_ruler_init(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
assert "HELLO" in ruler
assert "BYE" in ruler
nlp.add_pipe(ruler)
doc = nlp("hello world bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[1].label_ == "BYE"
def test_entity_ruler_existing(nlp, patterns, add_ent):
ruler = EntityRuler(nlp, patterns=patterns)
nlp.add_pipe(add_ent)
nlp.add_pipe(ruler)
doc = nlp("OH HELLO WORLD bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "ORG"
assert doc.ents[1].label_ == "BYE"
def test_entity_ruler_existing_overwrite(nlp, patterns, add_ent):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
nlp.add_pipe(add_ent)
nlp.add_pipe(ruler)
doc = nlp("OH HELLO WORLD bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "HELLO"
assert doc.ents[0].text == "HELLO"
assert doc.ents[1].label_ == "BYE"
def test_entity_ruler_existing_complex(nlp, patterns, add_ent):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
nlp.add_pipe(add_ent)
nlp.add_pipe(ruler)
doc = nlp("foo foo bye bye")
assert len(doc.ents) == 2
assert doc.ents[0].label_ == "COMPLEX"
assert doc.ents[1].label_ == "BYE"
assert len(doc.ents[0]) == 2
assert len(doc.ents[1]) == 2
def test_entity_ruler_entity_id(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
nlp.add_pipe(ruler)
doc = nlp("Apple is a technology company")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
def test_entity_ruler_cfg_ent_id_sep(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True, ent_id_sep="**")
assert "TECH_ORG**a1" in ruler.phrase_patterns
nlp.add_pipe(ruler)
doc = nlp("Apple is a technology company")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
def test_entity_ruler_serialize_bytes(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_ruler = EntityRuler(nlp)
assert len(new_ruler) == 0
assert len(new_ruler.labels) == 0
new_ruler = new_ruler.from_bytes(ruler_bytes)
assert len(new_ruler) == len(patterns)
assert len(new_ruler.labels) == 4
assert len(new_ruler.patterns) == len(ruler.patterns)
for pattern in ruler.patterns:
assert pattern in new_ruler.patterns
assert new_ruler.labels == ruler.labels
def test_entity_ruler_serialize_phrase_matcher_attr_bytes(nlp, patterns):
ruler = EntityRuler(nlp, phrase_matcher_attr="LOWER", patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_ruler = EntityRuler(nlp)
assert len(new_ruler) == 0
assert len(new_ruler.labels) == 0
assert new_ruler.phrase_matcher_attr is None
new_ruler = new_ruler.from_bytes(ruler_bytes)
assert len(new_ruler) == len(patterns)
assert len(new_ruler.labels) == 4
assert new_ruler.phrase_matcher_attr == "LOWER"