spaCy/spacy/tests/pipeline/test_entity_ruler.py

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# coding: utf8
from __future__ import unicode_literals
import pytest
💫 Refactor test suite (#2568) ## Description Related issues: #2379 (should be fixed by separating model tests) * **total execution time down from > 300 seconds to under 60 seconds** 🎉 * removed all model-specific tests that could only really be run manually anyway – those will now live in a separate test suite in the [`spacy-models`](https://github.com/explosion/spacy-models) repository and are already integrated into our new model training infrastructure * changed all relative imports to absolute imports to prepare for moving the test suite from `/spacy/tests` to `/tests` (it'll now always test against the installed version) * merged old regression tests into collections, e.g. `test_issue1001-1500.py` (about 90% of the regression tests are very short anyways) * tidied up and rewrote existing tests wherever possible ### Todo - [ ] move tests to `/tests` and adjust CI commands accordingly - [x] move model test suite from internal repo to `spacy-models` - [x] ~~investigate why `pipeline/test_textcat.py` is flakey~~ - [x] review old regression tests (leftover files) and see if they can be merged, simplified or deleted - [ ] update documentation on how to run tests ### Types of change enhancement, tests ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-07-25 00:38:44 +03:00
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(ruler) == len(patterns)
assert len(ruler.labels) == 4