mirror of
https://github.com/explosion/spaCy.git
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b6e991440c
* Auto-format tests with black * Add flake8 config * Tidy up and remove unused imports * Fix redefinitions of test functions * Replace orths_and_spaces with words and spaces * Fix compatibility with pytest 4.0 * xfail test for now Test was previously overwritten by following test due to naming conflict, so failure wasn't reported * Unfail passing test * Only use fixture via arguments Fixes pytest 4.0 compatibility
85 lines
3.1 KiB
Python
85 lines
3.1 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from ...util import get_doc
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def test_en_parser_noun_chunks_standard(en_tokenizer):
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text = "A base phrase should be recognized."
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heads = [2, 1, 3, 2, 1, 0, -1]
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tags = ["DT", "JJ", "NN", "MD", "VB", "VBN", "."]
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deps = ["det", "amod", "nsubjpass", "aux", "auxpass", "ROOT", "punct"]
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tokens = en_tokenizer(text)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
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)
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chunks = list(doc.noun_chunks)
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assert len(chunks) == 1
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assert chunks[0].text_with_ws == "A base phrase "
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def test_en_parser_noun_chunks_coordinated(en_tokenizer):
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# fmt: off
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text = "A base phrase and a good phrase are often the same."
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heads = [2, 1, 5, -1, 2, 1, -4, 0, -1, 1, -3, -4]
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tags = ["DT", "NN", "NN", "CC", "DT", "JJ", "NN", "VBP", "RB", "DT", "JJ", "."]
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deps = ["det", "compound", "nsubj", "cc", "det", "amod", "conj", "ROOT", "advmod", "det", "attr", "punct"]
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# fmt: on
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tokens = en_tokenizer(text)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
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)
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chunks = list(doc.noun_chunks)
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assert len(chunks) == 2
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assert chunks[0].text_with_ws == "A base phrase "
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assert chunks[1].text_with_ws == "a good phrase "
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def test_en_parser_noun_chunks_pp_chunks(en_tokenizer):
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text = "A phrase with another phrase occurs."
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heads = [1, 4, -1, 1, -2, 0, -1]
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tags = ["DT", "NN", "IN", "DT", "NN", "VBZ", "."]
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deps = ["det", "nsubj", "prep", "det", "pobj", "ROOT", "punct"]
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tokens = en_tokenizer(text)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
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)
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chunks = list(doc.noun_chunks)
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assert len(chunks) == 2
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assert chunks[0].text_with_ws == "A phrase "
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assert chunks[1].text_with_ws == "another phrase "
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def test_en_parser_noun_chunks_appositional_modifiers(en_tokenizer):
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# fmt: off
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text = "Sam, my brother, arrived to the house."
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heads = [5, -1, 1, -3, -4, 0, -1, 1, -2, -4]
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tags = ["NNP", ",", "PRP$", "NN", ",", "VBD", "IN", "DT", "NN", "."]
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deps = ["nsubj", "punct", "poss", "appos", "punct", "ROOT", "prep", "det", "pobj", "punct"]
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# fmt: on
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tokens = en_tokenizer(text)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
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)
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chunks = list(doc.noun_chunks)
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assert len(chunks) == 3
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assert chunks[0].text_with_ws == "Sam "
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assert chunks[1].text_with_ws == "my brother "
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assert chunks[2].text_with_ws == "the house "
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def test_en_parser_noun_chunks_dative(en_tokenizer):
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text = "She gave Bob a raise."
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heads = [1, 0, -1, 1, -3, -4]
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tags = ["PRP", "VBD", "NNP", "DT", "NN", "."]
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deps = ["nsubj", "ROOT", "dative", "det", "dobj", "punct"]
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tokens = en_tokenizer(text)
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doc = get_doc(
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tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
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)
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chunks = list(doc.noun_chunks)
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assert len(chunks) == 3
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assert chunks[0].text_with_ws == "She "
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assert chunks[1].text_with_ws == "Bob "
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assert chunks[2].text_with_ws == "a raise "
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