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8fe7bdd0fa
* Fix typo in rule-based matching docs * Improve token pattern checking without validation Add more detailed token pattern checks without full JSON pattern validation and provide more detailed error messages. Addresses #4070 (also related: #4063, #4100). * Check whether top-level attributes in patterns and attr for PhraseMatcher are in token pattern schema * Check whether attribute value types are supported in general (as opposed to per attribute with full validation) * Report various internal error types (OverflowError, AttributeError, KeyError) as ValueError with standard error messages * Check for tagger/parser in PhraseMatcher pipeline for attributes TAG, POS, LEMMA, and DEP * Add error messages with relevant details on how to use validate=True or nlp() instead of nlp.make_doc() * Support attr=TEXT for PhraseMatcher * Add NORM to schema * Expand tests for pattern validation, Matcher, PhraseMatcher, and EntityRuler * Remove unnecessary .keys() * Rephrase error messages * Add another type check to Matcher Add another type check to Matcher for more understandable error messages in some rare cases. * Support phrase_matcher_attr=TEXT for EntityRuler * Don't use spacy.errors in examples and bin scripts * Fix error code * Auto-format Also try get Azure pipelines to finally start a build :( * Update errors.py Co-authored-by: Ines Montani <ines@ines.io> Co-authored-by: Matthew Honnibal <honnibal+gh@gmail.com>
135 lines
4.6 KiB
Python
135 lines
4.6 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.matcher import PhraseMatcher
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from spacy.tokens import Doc
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from ..util import get_doc
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def test_matcher_phrase_matcher(en_vocab):
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doc = Doc(en_vocab, words=["Google", "Now"])
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matcher = PhraseMatcher(en_vocab)
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matcher.add("COMPANY", None, doc)
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doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
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assert len(matcher(doc)) == 1
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def test_phrase_matcher_length(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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assert len(matcher) == 0
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matcher.add("TEST", None, Doc(en_vocab, words=["test"]))
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assert len(matcher) == 1
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matcher.add("TEST2", None, Doc(en_vocab, words=["test2"]))
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assert len(matcher) == 2
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def test_phrase_matcher_contains(en_vocab):
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matcher = PhraseMatcher(en_vocab)
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matcher.add("TEST", None, Doc(en_vocab, words=["test"]))
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assert "TEST" in matcher
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assert "TEST2" not in matcher
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def test_phrase_matcher_string_attrs(en_vocab):
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words1 = ["I", "like", "cats"]
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pos1 = ["PRON", "VERB", "NOUN"]
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words2 = ["Yes", ",", "you", "hate", "dogs", "very", "much"]
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pos2 = ["INTJ", "PUNCT", "PRON", "VERB", "NOUN", "ADV", "ADV"]
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pattern = get_doc(en_vocab, words=words1, pos=pos1)
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matcher = PhraseMatcher(en_vocab, attr="POS")
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matcher.add("TEST", None, pattern)
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doc = get_doc(en_vocab, words=words2, pos=pos2)
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matches = matcher(doc)
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assert len(matches) == 1
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match_id, start, end = matches[0]
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assert match_id == en_vocab.strings["TEST"]
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assert start == 2
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assert end == 5
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def test_phrase_matcher_string_attrs_negative(en_vocab):
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"""Test that token with the control codes as ORTH are *not* matched."""
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words1 = ["I", "like", "cats"]
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pos1 = ["PRON", "VERB", "NOUN"]
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words2 = ["matcher:POS-PRON", "matcher:POS-VERB", "matcher:POS-NOUN"]
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pos2 = ["X", "X", "X"]
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pattern = get_doc(en_vocab, words=words1, pos=pos1)
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matcher = PhraseMatcher(en_vocab, attr="POS")
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matcher.add("TEST", None, pattern)
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doc = get_doc(en_vocab, words=words2, pos=pos2)
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matches = matcher(doc)
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assert len(matches) == 0
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def test_phrase_matcher_bool_attrs(en_vocab):
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words1 = ["Hello", "world", "!"]
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words2 = ["No", "problem", ",", "he", "said", "."]
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pattern = Doc(en_vocab, words=words1)
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matcher = PhraseMatcher(en_vocab, attr="IS_PUNCT")
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matcher.add("TEST", None, pattern)
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doc = Doc(en_vocab, words=words2)
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matches = matcher(doc)
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assert len(matches) == 2
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match_id1, start1, end1 = matches[0]
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match_id2, start2, end2 = matches[1]
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assert match_id1 == en_vocab.strings["TEST"]
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assert match_id2 == en_vocab.strings["TEST"]
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assert start1 == 0
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assert end1 == 3
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assert start2 == 3
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assert end2 == 6
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def test_phrase_matcher_validation(en_vocab):
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doc1 = Doc(en_vocab, words=["Test"])
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doc1.is_parsed = True
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doc2 = Doc(en_vocab, words=["Test"])
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doc2.is_tagged = True
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doc3 = Doc(en_vocab, words=["Test"])
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matcher = PhraseMatcher(en_vocab, validate=True)
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with pytest.warns(UserWarning):
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matcher.add("TEST1", None, doc1)
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with pytest.warns(UserWarning):
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matcher.add("TEST2", None, doc2)
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with pytest.warns(None) as record:
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matcher.add("TEST3", None, doc3)
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assert not record.list
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matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
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with pytest.warns(None) as record:
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matcher.add("TEST4", None, doc2)
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assert not record.list
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def test_attr_validation(en_vocab):
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with pytest.raises(ValueError):
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PhraseMatcher(en_vocab, attr="UNSUPPORTED")
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def test_attr_pipeline_checks(en_vocab):
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doc1 = Doc(en_vocab, words=["Test"])
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doc1.is_parsed = True
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doc2 = Doc(en_vocab, words=["Test"])
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doc2.is_tagged = True
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doc3 = Doc(en_vocab, words=["Test"])
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# DEP requires is_parsed
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matcher = PhraseMatcher(en_vocab, attr="DEP")
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matcher.add("TEST1", None, doc1)
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with pytest.raises(ValueError):
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matcher.add("TEST2", None, doc2)
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with pytest.raises(ValueError):
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matcher.add("TEST3", None, doc3)
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# TAG, POS, LEMMA require is_tagged
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for attr in ("TAG", "POS", "LEMMA"):
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matcher = PhraseMatcher(en_vocab, attr=attr)
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matcher.add("TEST2", None, doc2)
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with pytest.raises(ValueError):
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matcher.add("TEST1", None, doc1)
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with pytest.raises(ValueError):
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matcher.add("TEST3", None, doc3)
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# TEXT/ORTH only require tokens
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matcher = PhraseMatcher(en_vocab, attr="ORTH")
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matcher.add("TEST3", None, doc3)
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matcher = PhraseMatcher(en_vocab, attr="TEXT")
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matcher.add("TEST3", None, doc3)
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