import pytest import re from spacy.tokens import Doc from spacy.vocab import Vocab from spacy.lang.en import English from spacy.lang.lex_attrs import LEX_ATTRS from spacy.matcher import Matcher from spacy.tokenizer import Tokenizer from spacy.symbols import ORTH, LEMMA, POS @pytest.mark.issue(1061) def test_issue1061(): """Test special-case works after tokenizing. Was caching problem.""" text = "I like _MATH_ even _MATH_ when _MATH_, except when _MATH_ is _MATH_! but not _MATH_." tokenizer = English().tokenizer doc = tokenizer(text) assert "MATH" in [w.text for w in doc] assert "_MATH_" not in [w.text for w in doc] tokenizer.add_special_case("_MATH_", [{ORTH: "_MATH_"}]) doc = tokenizer(text) assert "_MATH_" in [w.text for w in doc] assert "MATH" not in [w.text for w in doc] # For sanity, check it works when pipeline is clean. tokenizer = English().tokenizer tokenizer.add_special_case("_MATH_", [{ORTH: "_MATH_"}]) doc = tokenizer(text) assert "_MATH_" in [w.text for w in doc] assert "MATH" not in [w.text for w in doc] @pytest.mark.skip( reason="Can not be fixed without variable-width look-behind (which we don't want)" ) @pytest.mark.issue(1235) def test_issue1235(): """Test that g is not split of if preceded by a number and a letter""" nlp = English() testwords = "e2g 2g 52g" doc = nlp(testwords) assert len(doc) == 5 assert doc[0].text == "e2g" assert doc[1].text == "2" assert doc[2].text == "g" assert doc[3].text == "52" assert doc[4].text == "g" @pytest.mark.issue(1242) def test_issue1242(): nlp = English() doc = nlp("") assert len(doc) == 0 docs = list(nlp.pipe(["", "hello"])) assert len(docs[0]) == 0 assert len(docs[1]) == 1 @pytest.mark.skip(reason="v3 no longer supports LEMMA/POS in tokenizer special cases") @pytest.mark.issue(1250) def test_issue1250(): """Test cached special cases.""" special_case = [{ORTH: "reimbur", LEMMA: "reimburse", POS: "VERB"}] nlp = English() nlp.tokenizer.add_special_case("reimbur", special_case) lemmas = [w.lemma_ for w in nlp("reimbur, reimbur...")] assert lemmas == ["reimburse", ",", "reimburse", "..."] lemmas = [w.lemma_ for w in nlp("reimbur, reimbur...")] assert lemmas == ["reimburse", ",", "reimburse", "..."] @pytest.mark.issue(1257) def test_issue1257(): """Test that tokens compare correctly.""" doc1 = Doc(Vocab(), words=["a", "b", "c"]) doc2 = Doc(Vocab(), words=["a", "c", "e"]) assert doc1[0] != doc2[0] assert not doc1[0] == doc2[0] @pytest.mark.issue(1375) def test_issue1375(): """Test that token.nbor() raises IndexError for out-of-bounds access.""" doc = Doc(Vocab(), words=["0", "1", "2"]) with pytest.raises(IndexError): assert doc[0].nbor(-1) assert doc[1].nbor(-1).text == "0" with pytest.raises(IndexError): assert doc[2].nbor(1) assert doc[1].nbor(1).text == "2" @pytest.mark.issue(1434) def test_issue1434(): """Test matches occur when optional element at end of short doc.""" pattern = [{"ORTH": "Hello"}, {"IS_ALPHA": True, "OP": "?"}] vocab = Vocab(lex_attr_getters=LEX_ATTRS) hello_world = Doc(vocab, words=["Hello", "World"]) hello = Doc(vocab, words=["Hello"]) matcher = Matcher(vocab) matcher.add("MyMatcher", [pattern]) matches = matcher(hello_world) assert matches matches = matcher(hello) assert matches @pytest.mark.parametrize( "string,start,end", [ ("a", 0, 1), ("a b", 0, 2), ("a c", 0, 1), ("a b c", 0, 2), ("a b b c", 0, 3), ("a b b", 0, 3), ], ) @pytest.mark.issue(1450) def test_issue1450(string, start, end): """Test matcher works when patterns end with * operator.""" pattern = [{"ORTH": "a"}, {"ORTH": "b", "OP": "*"}] matcher = Matcher(Vocab()) matcher.add("TSTEND", [pattern]) doc = Doc(Vocab(), words=string.split()) matches = matcher(doc) if start is None or end is None: assert matches == [] assert matches[-1][1] == start assert matches[-1][2] == end @pytest.mark.issue(1488) def test_issue1488(): prefix_re = re.compile(r"""[\[\("']""") suffix_re = re.compile(r"""[\]\)"']""") infix_re = re.compile(r"""[-~\.]""") simple_url_re = re.compile(r"""^https?://""") def my_tokenizer(nlp): return Tokenizer( nlp.vocab, {}, prefix_search=prefix_re.search, suffix_search=suffix_re.search, infix_finditer=infix_re.finditer, token_match=simple_url_re.match, ) nlp = English() nlp.tokenizer = my_tokenizer(nlp) doc = nlp("This is a test.") for token in doc: assert token.text @pytest.mark.issue(1494) def test_issue1494(): infix_re = re.compile(r"""[^a-z]""") test_cases = [ ("token 123test", ["token", "1", "2", "3", "test"]), ("token 1test", ["token", "1test"]), ("hello...test", ["hello", ".", ".", ".", "test"]), ] def new_tokenizer(nlp): return Tokenizer(nlp.vocab, {}, infix_finditer=infix_re.finditer) nlp = English() nlp.tokenizer = new_tokenizer(nlp) for text, expected in test_cases: assert [token.text for token in nlp(text)] == expected