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https://github.com/explosion/spaCy.git
synced 2024-12-25 01:16:28 +03:00
Tweak line spacing
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parent
85603f5b6a
commit
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@ -64,8 +64,6 @@ def clean(ext):
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if os.path.exists(html):
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os.unlink(html)
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HERE = os.path.dirname(__file__)
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virtual_env = os.environ.get('VIRTUAL_ENV', '')
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compile_args = []
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@ -7,6 +7,7 @@ from spacy.lexeme import lex_of
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from spacy import LEX, NORM, SHAPE, LAST3
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def test_group_by_lex():
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tokens = en.tokenize("I like the red one and I like the blue one")
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names, hashes, groups = tokens.group_by(LEX)
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@ -40,6 +40,7 @@ def test_begin(state, sentence):
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assert not state.is_valid('O')
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assert not state.is_valid('U-PER')
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def test_in(state, sentence):
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state.transition('B-PER')
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assert state.n_ents == 0
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@ -2,6 +2,7 @@
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"""Sphinx doctest is just too hard. Manually paste doctest examples here"""
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from spacy.en.attrs import IS_LOWER
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def test_1():
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import spacy.en
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from spacy.parts_of_speech import ADV
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@ -39,6 +40,7 @@ def test2():
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nlp.vocab[u'quietly'].prob
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-11.07155704498291
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def test3():
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import spacy.en
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from spacy.parts_of_speech import ADV
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@ -8,6 +8,7 @@ from spacy.en import English
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def EN():
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return English()
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def test_tweebo_challenge(EN):
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text = u""":o :/ :'( >:o (: :) >.< XD -__- o.O ;D :-) @_@ :P 8D :1 >:( :D =| ") :> ...."""
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tokens = EN(text)
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@ -16,6 +16,7 @@ def words():
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return ["1997", "19.97", "hello9", "Hello", "HELLO", "Hello9", "\n", "!",
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"!d", "\nd"]
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def test_is_alpha(words):
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assert not is_alpha(words[0])
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assert not is_alpha(words[1])
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@ -5,10 +5,12 @@ from spacy.strings import StringStore
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import pytest
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@pytest.fixture
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def sstore():
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return StringStore()
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def test_save_bytes(sstore):
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Hello_i = sstore[b'Hello']
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assert Hello_i == 1
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@ -2,10 +2,12 @@ import pytest
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from spacy.en import English
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@pytest.fixture
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def EN():
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return English()
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def test_range_iter(EN):
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for i in range(len(EN.vocab)):
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lex = EN.vocab[i]
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@ -17,6 +17,7 @@ def morph_exc():
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'PRP$': {'his': {'L': '-PRP-', 'person': 3, 'case': 2}},
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}
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def test_load_exc(EN, morph_exc):
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EN.tagger.load_morph_exceptions(morph_exc)
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tokens = EN('I like his style.', tag=True)
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@ -3,6 +3,7 @@ from spacy.en import English
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nlp = English()
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def test_simple_types():
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tokens = nlp(u'Mr. Best flew to New York on Saturday morning.')
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ents = list(tokens.ents)
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@ -3,6 +3,7 @@ import pytest
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from spacy.en import English
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def test_only_pre1():
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EN = English()
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assert len(EN("(")) == 1
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@ -3,6 +3,7 @@ from spacy.en import English
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import pytest
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@pytest.fixture
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def EN():
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return English()
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@ -8,20 +8,26 @@ from spacy.orth import word_shape as ws
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def test_capitalized():
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assert ws('Nasa') == 'Xxxx'
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def test_truncate():
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assert ws('capitalized') == 'xxxx'
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def test_digits():
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assert ws('999999999') == 'dddd'
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def test_mix():
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assert ws('C3P0') == 'XdXd'
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def test_punct():
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assert ws(',') == ','
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def test_space():
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assert ws('\n') == '\n'
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def test_punct_seq():
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assert ws('``,-') == '``,-'
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@ -13,9 +13,11 @@ def EN():
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def test_no_special(EN):
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assert len(EN("(can)")) == 3
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def test_no_punct(EN):
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assert len(EN("can't")) == 2
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def test_prefix(EN):
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assert len(EN("(can't")) == 3
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@ -1,6 +1,7 @@
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from spacy.en import English
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import six
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def test_tag_names():
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nlp = English()
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tokens = nlp(u'I ate pizzas with anchovies.', parse=True, tag=True)
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@ -6,6 +6,7 @@ import pytest
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NLU = English()
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def test_am_pm():
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numbers = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12']
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variants = ['a.m.', 'am', 'p.m.', 'pm']
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@ -4,6 +4,7 @@ import pytest
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from spacy.en import English
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from spacy.parts_of_speech import ADV
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@pytest.fixture
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def nlp():
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return English()
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@ -7,6 +7,8 @@ from spacy.en.attrs import IS_STOP
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import pytest
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nlp = English()
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@pytest.fixture
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def token():
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tokens = nlp(u'Give it back! He pleaded.')
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@ -31,6 +31,7 @@ def _orphan_from_list(toks):
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lst.append(tok)
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return lst
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def test_list_orphans():
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# Test case from NSchrading
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nlp = English()
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@ -10,10 +10,12 @@ from spacy.en import English
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def EN():
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return English().tokenizer
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def test_no_word(EN):
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tokens = EN(u'')
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assert len(tokens) == 0
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def test_single_word(EN):
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tokens = EN(u'hello')
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assert tokens[0].orth_ == 'hello'
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@ -60,6 +62,7 @@ def test_contraction_punct(EN):
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tokens = EN("can't!")
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assert len(tokens) == 3
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def test_sample(EN):
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text = """Tributes pour in for late British Labour Party leader
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@ -3,6 +3,7 @@ from spacy.en import English
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import pytest
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@pytest.fixture
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def tokens():
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nlp = English()
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@ -2,6 +2,7 @@ from __future__ import unicode_literals
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from spacy.orth import like_url
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def test_basic_url():
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assert like_url('www.google.com')
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assert like_url('google.com')
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@ -4,15 +4,18 @@ from spacy.en import English
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import pytest
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@pytest.fixture
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def EN():
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return English()
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def test_vec(EN):
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hype = EN.vocab['hype']
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assert hype.orth_ == 'hype'
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assert 0.08 >= hype.repvec[0] > 0.07
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def test_capitalized(EN):
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hype = EN.vocab['Hype']
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assert hype.orth_ == 'Hype'
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