Tweak line spacing

LICENSE.txt

@@ -1,7 +1,7 @@
 spaCy is commercial open-source software: you can buy a commercial
 license, or you can use it under the AGPL, as described below.
 
-spaCy Natural Language Processing Tools    
+spaCy Natural Language Processing Tools
 Copyright (C) 2015 Matthew Honnibal
 
 This program is free software: you can redistribute it and/or modify

dev_setup.py

@@ -64,8 +64,6 @@ def clean(ext):
             if os.path.exists(html):
                 os.unlink(html)
 
-
-
 HERE = os.path.dirname(__file__)
 virtual_env = os.environ.get('VIRTUAL_ENV', '')
 compile_args = []

tests/_depr_group_by.py

@@ -7,6 +7,7 @@ from spacy.lexeme import lex_of
 
 from spacy import LEX, NORM, SHAPE, LAST3
 
+
 def test_group_by_lex():
     tokens = en.tokenize("I like the red one and I like the blue one")
     names, hashes, groups = tokens.group_by(LEX)

tests/depr_test_ner.py

@@ -40,6 +40,7 @@ def test_begin(state, sentence):
     assert not state.is_valid('O')
     assert not state.is_valid('U-PER')
 
+
 def test_in(state, sentence):
     state.transition('B-PER')
     assert state.n_ents == 0

tests/test_docs.py

@@ -2,6 +2,7 @@
 """Sphinx doctest is just too hard. Manually paste doctest examples here"""
 from spacy.en.attrs import IS_LOWER
 
+
 def test_1():
     import spacy.en
     from spacy.parts_of_speech import ADV
@@ -39,6 +40,7 @@ def test2():
     nlp.vocab[u'quietly'].prob
     -11.07155704498291
 
+
 def test3():
     import spacy.en
     from spacy.parts_of_speech import ADV

tests/test_emoticons.py

@@ -8,6 +8,7 @@ from spacy.en import English
 def EN():
     return English()
 
+
 def test_tweebo_challenge(EN):
     text = u""":o :/ :'( >:o (: :) >.< XD -__- o.O ;D :-) @_@ :P 8D :1 >:( :D =| ") :> ...."""
     tokens = EN(text)

tests/test_flag_features.py

@@ -16,6 +16,7 @@ def words():
     return ["1997", "19.97", "hello9", "Hello", "HELLO", "Hello9", "\n", "!",
             "!d", "\nd"]
 
+
 def test_is_alpha(words):
     assert not is_alpha(words[0])
     assert not is_alpha(words[1])

tests/test_intern.py

@@ -5,10 +5,12 @@ from spacy.strings import StringStore
 
 import pytest
 
+
 @pytest.fixture
 def sstore():
     return StringStore()
 
+
 def test_save_bytes(sstore):
     Hello_i = sstore[b'Hello']
     assert Hello_i == 1

tests/test_iter_lexicon.py

@@ -2,10 +2,12 @@ import pytest
 
 from spacy.en import English
 
+
 @pytest.fixture
 def EN():
     return English()
 
+
 def test_range_iter(EN):
     for i in range(len(EN.vocab)):
         lex = EN.vocab[i]

tests/test_morph_exceptions.py

@@ -17,6 +17,7 @@ def morph_exc():
             'PRP$': {'his': {'L': '-PRP-', 'person': 3, 'case': 2}},
            }
 
+
 def test_load_exc(EN, morph_exc):
     EN.tagger.load_morph_exceptions(morph_exc)
     tokens = EN('I like his style.', tag=True)

tests/test_ner.py

@@ -3,6 +3,7 @@ from spacy.en import English
 
 nlp = English()
 
+
 def test_simple_types():
     tokens = nlp(u'Mr. Best flew to New York on Saturday morning.')
     ents = list(tokens.ents)

tests/test_only_punct.py

@@ -3,6 +3,7 @@ import pytest
 
 from spacy.en import English
 
+
 def test_only_pre1():
     EN = English()
     assert len(EN("(")) == 1

tests/test_sbd.py

@@ -3,6 +3,7 @@ from spacy.en import English
 
 import pytest
 
+
 @pytest.fixture
 def EN():
     return English()

tests/test_shape.py

@@ -8,20 +8,26 @@ from spacy.orth import word_shape as ws
 def test_capitalized():
     assert ws('Nasa') == 'Xxxx'
 
+
 def test_truncate():
     assert ws('capitalized') == 'xxxx'
 
+
 def test_digits():
     assert ws('999999999') == 'dddd'
 
+
 def test_mix():
     assert ws('C3P0') == 'XdXd'
 
+
 def test_punct():
     assert ws(',') == ','
 
+
 def test_space():
     assert ws('\n') == '\n'
 
+
 def test_punct_seq():
     assert ws('``,-') == '``,-'

tests/test_special_affix.py

@@ -13,9 +13,11 @@ def EN():
 def test_no_special(EN):
     assert len(EN("(can)")) == 3
 
+
 def test_no_punct(EN):
     assert len(EN("can't")) == 2
 
+
 def test_prefix(EN):
     assert len(EN("(can't")) == 3
 

tests/test_tag_names.py

@@ -1,6 +1,7 @@
 from spacy.en import English
 import six
 
+
 def test_tag_names():
     nlp = English()
     tokens = nlp(u'I ate pizzas with anchovies.', parse=True, tag=True)

tests/test_times.py

@@ -6,6 +6,7 @@ import pytest
 
 NLU = English()
 
+
 def test_am_pm():
     numbers = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', '11', '12']
     variants = ['a.m.', 'am', 'p.m.', 'pm']

tests/test_token.py

@@ -4,6 +4,7 @@ import pytest
 from spacy.en import English
 from spacy.parts_of_speech import ADV
 
+
 @pytest.fixture
 def nlp():
     return English()

tests/test_token_api.py

@@ -7,6 +7,8 @@ from spacy.en.attrs import IS_STOP
 import pytest
 
 nlp = English()
+
+
 @pytest.fixture
 def token():
     tokens = nlp(u'Give it back! He pleaded.')

tests/test_token_references.py

@@ -31,6 +31,7 @@ def _orphan_from_list(toks):
         lst.append(tok)
     return lst
 
+
 def test_list_orphans():
     # Test case from NSchrading
     nlp = English()

tests/test_tokenizer.py

@@ -10,10 +10,12 @@ from spacy.en import English
 def EN():
     return English().tokenizer
 
+
 def test_no_word(EN):
     tokens = EN(u'')
     assert len(tokens) == 0
 
+
 def test_single_word(EN):
     tokens = EN(u'hello')
     assert tokens[0].orth_ == 'hello'
@@ -60,6 +62,7 @@ def test_contraction_punct(EN):
     tokens = EN("can't!")
     assert len(tokens) == 3
 
+
 def test_sample(EN):
     text = """Tributes pour in for late British Labour Party leader
 

tests/test_tokens_api.py

@@ -3,6 +3,7 @@ from spacy.en import English
 
 import pytest
 
+
 @pytest.fixture
 def tokens():
     nlp = English()

tests/test_urlish.py

@@ -2,6 +2,7 @@ from __future__ import unicode_literals
 
 from spacy.orth import like_url
 
+
 def test_basic_url():
     assert like_url('www.google.com')
     assert like_url('google.com')

tests/test_vec.py

@@ -4,15 +4,18 @@ from spacy.en import English
 
 import pytest
 
+
 @pytest.fixture
 def EN():
     return English()
 
+
 def test_vec(EN):
     hype = EN.vocab['hype']
     assert hype.orth_ == 'hype'
     assert 0.08 >= hype.repvec[0] > 0.07
 
+
 def test_capitalized(EN):
     hype = EN.vocab['Hype']
     assert hype.orth_ == 'Hype'