💫 Tidy up and auto-format tests (#2967)

* 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

.flake8

@@ -0,0 +1,4 @@
+[flake8]
+ignore = E203, E266, E501, W503
+max-line-length = 80
+select = B,C,E,F,W,T4,B9

requirements.txt

@@ -11,7 +11,7 @@ ujson>=1.35
 dill>=0.2,<0.3
 regex==2018.01.10
 requests>=2.13.0,<3.0.0
-pytest>=3.6.0,<4.0.0
+pytest>=4.0.0,<5.0.0
 pytest-timeout>=1.3.0,<2.0.0
 mock>=2.0.0,<3.0.0
 pathlib==1.0.1; python_version < "3.4"

spacy/tests/conftest.py

@@ -2,7 +2,6 @@
 from __future__ import unicode_literals
 
 import pytest
-from io import StringIO, BytesIO
 from spacy.util import get_lang_class
 
 
@@ -11,126 +10,135 @@ def pytest_addoption(parser):
 
 
 def pytest_runtest_setup(item):
-    for opt in ['slow']:
+    for opt in ["slow"]:
         if opt in item.keywords and not item.config.getoption("--%s" % opt):
             pytest.skip("need --%s option to run" % opt)
 
 
-@pytest.fixture(scope='module')
+@pytest.fixture(scope="module")
 def tokenizer():
-    return get_lang_class('xx').Defaults.create_tokenizer()
+    return get_lang_class("xx").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def en_tokenizer():
-    return get_lang_class('en').Defaults.create_tokenizer()
+    return get_lang_class("en").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def en_vocab():
-    return get_lang_class('en').Defaults.create_vocab()
+    return get_lang_class("en").Defaults.create_vocab()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def en_parser(en_vocab):
-    nlp = get_lang_class('en')(en_vocab)
-    return nlp.create_pipe('parser')
+    nlp = get_lang_class("en")(en_vocab)
+    return nlp.create_pipe("parser")
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def es_tokenizer():
-    return get_lang_class('es').Defaults.create_tokenizer()
+    return get_lang_class("es").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def de_tokenizer():
-    return get_lang_class('de').Defaults.create_tokenizer()
+    return get_lang_class("de").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def fr_tokenizer():
-    return get_lang_class('fr').Defaults.create_tokenizer()
+    return get_lang_class("fr").Defaults.create_tokenizer()
 
 
 @pytest.fixture
 def hu_tokenizer():
-    return get_lang_class('hu').Defaults.create_tokenizer()
+    return get_lang_class("hu").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def fi_tokenizer():
-    return get_lang_class('fi').Defaults.create_tokenizer()
+    return get_lang_class("fi").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def ro_tokenizer():
-    return get_lang_class('ro').Defaults.create_tokenizer()
+    return get_lang_class("ro").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def id_tokenizer():
-    return get_lang_class('id').Defaults.create_tokenizer()
+    return get_lang_class("id").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def sv_tokenizer():
-    return get_lang_class('sv').Defaults.create_tokenizer()
+    return get_lang_class("sv").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def bn_tokenizer():
-    return get_lang_class('bn').Defaults.create_tokenizer()
+    return get_lang_class("bn").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def ga_tokenizer():
-    return get_lang_class('ga').Defaults.create_tokenizer()
+    return get_lang_class("ga").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def he_tokenizer():
-    return get_lang_class('he').Defaults.create_tokenizer()
+    return get_lang_class("he").Defaults.create_tokenizer()
 
 
-@pytest.fixture(scope='session')
+@pytest.fixture(scope="session")
 def nb_tokenizer():
-    return get_lang_class('nb').Defaults.create_tokenizer()
+    return get_lang_class("nb").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def da_tokenizer():
-    return get_lang_class('da').Defaults.create_tokenizer()
+    return get_lang_class("da").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def ja_tokenizer():
     mecab = pytest.importorskip("MeCab")
-    return get_lang_class('ja').Defaults.create_tokenizer()
+    return get_lang_class("ja").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def th_tokenizer():
     pythainlp = pytest.importorskip("pythainlp")
-    return get_lang_class('th').Defaults.create_tokenizer()
+    return get_lang_class("th").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def tr_tokenizer():
-    return get_lang_class('tr').Defaults.create_tokenizer()
+    return get_lang_class("tr").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def tt_tokenizer():
-    return get_lang_class('tt').Defaults.create_tokenizer()
+    return get_lang_class("tt").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def el_tokenizer():
-    return get_lang_class('el').Defaults.create_tokenizer()
+    return get_lang_class("el").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def ar_tokenizer():
-    return get_lang_class('ar').Defaults.create_tokenizer()
+    return get_lang_class("ar").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def ur_tokenizer():
-    return get_lang_class('ur').Defaults.create_tokenizer()
+    return get_lang_class("ur").Defaults.create_tokenizer()
 
-@pytest.fixture(scope='session')
+
+@pytest.fixture(scope="session")
 def ru_tokenizer():
-    pymorphy = pytest.importorskip('pymorphy2')
-    return get_lang_class('ru').Defaults.create_tokenizer()
+    pymorphy = pytest.importorskip("pymorphy2")
+    return get_lang_class("ru").Defaults.create_tokenizer()

spacy/tests/doc/test_array.py

@@ -38,7 +38,7 @@ def test_doc_scalar_attr_of_token(en_tokenizer, en_vocab):
 
 def test_doc_array_tag(en_tokenizer):
     text = "A nice sentence."
-    pos = ['DET', 'ADJ', 'NOUN', 'PUNCT']
+    pos = ["DET", "ADJ", "NOUN", "PUNCT"]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], pos=pos)
     assert doc[0].pos != doc[1].pos != doc[2].pos != doc[3].pos
@@ -51,7 +51,7 @@ def test_doc_array_tag(en_tokenizer):
 
 def test_doc_array_dep(en_tokenizer):
     text = "A nice sentence."
-    deps = ['det', 'amod', 'ROOT', 'punct']
+    deps = ["det", "amod", "ROOT", "punct"]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], deps=deps)
     feats_array = doc.to_array((ORTH, DEP))

spacy/tests/doc/test_creation.py

@@ -9,7 +9,7 @@ from spacy.lemmatizer import Lemmatizer
 
 @pytest.fixture
 def lemmatizer():
-    return Lemmatizer(lookup={'dogs': 'dog', 'boxen': 'box', 'mice': 'mouse'})
+    return Lemmatizer(lookup={"dogs": "dog", "boxen": "box", "mice": "mouse"})
 
 
 @pytest.fixture
@@ -23,15 +23,15 @@ def test_empty_doc(vocab):
 
 
 def test_single_word(vocab):
-    doc = Doc(vocab, words=['a'])
-    assert doc.text == 'a '
-    doc = Doc(vocab, words=['a'], spaces=[False])
-    assert doc.text == 'a'
+    doc = Doc(vocab, words=["a"])
+    assert doc.text == "a "
+    doc = Doc(vocab, words=["a"], spaces=[False])
+    assert doc.text == "a"
 
 
 def test_lookup_lemmatization(vocab):
-    doc = Doc(vocab, words=['dogs', 'dogses'])
-    assert doc[0].text == 'dogs'
-    assert doc[0].lemma_ == 'dog'
-    assert doc[1].text == 'dogses'
-    assert doc[1].lemma_ == 'dogses'
+    doc = Doc(vocab, words=["dogs", "dogses"])
+    assert doc[0].text == "dogs"
+    assert doc[0].lemma_ == "dog"
+    assert doc[1].text == "dogses"
+    assert doc[1].lemma_ == "dogses"

spacy/tests/doc/test_doc_api.py

@@ -10,7 +10,7 @@ from spacy.attrs import LEMMA
 from ..util import get_doc
 
 
-@pytest.mark.parametrize('text', [["one", "two", "three"]])
+@pytest.mark.parametrize("text", [["one", "two", "three"]])
 def test_doc_api_compare_by_string_position(en_vocab, text):
     doc = Doc(en_vocab, words=text)
     # Get the tokens in this order, so their ID ordering doesn't match the idx
@@ -28,80 +28,81 @@ def test_doc_api_compare_by_string_position(en_vocab, text):
 def test_doc_api_getitem(en_tokenizer):
     text = "Give it back! He pleaded."
     tokens = en_tokenizer(text)
-    assert tokens[0].text == 'Give'
-    assert tokens[-1].text == '.'
+    assert tokens[0].text == "Give"
+    assert tokens[-1].text == "."
     with pytest.raises(IndexError):
         tokens[len(tokens)]
 
     def to_str(span):
-        return '/'.join(token.text for token in span)
+        return "/".join(token.text for token in span)
 
     span = tokens[1:1]
     assert not to_str(span)
     span = tokens[1:4]
-    assert to_str(span) == 'it/back/!'
+    assert to_str(span) == "it/back/!"
     span = tokens[1:4:1]
-    assert to_str(span) == 'it/back/!'
+    assert to_str(span) == "it/back/!"
     with pytest.raises(ValueError):
         tokens[1:4:2]
     with pytest.raises(ValueError):
         tokens[1:4:-1]
 
     span = tokens[-3:6]
-    assert to_str(span) == 'He/pleaded'
+    assert to_str(span) == "He/pleaded"
     span = tokens[4:-1]
-    assert to_str(span) == 'He/pleaded'
+    assert to_str(span) == "He/pleaded"
     span = tokens[-5:-3]
-    assert to_str(span) == 'back/!'
+    assert to_str(span) == "back/!"
     span = tokens[5:4]
     assert span.start == span.end == 5 and not to_str(span)
     span = tokens[4:-3]
     assert span.start == span.end == 4 and not to_str(span)
 
     span = tokens[:]
-    assert to_str(span) == 'Give/it/back/!/He/pleaded/.'
+    assert to_str(span) == "Give/it/back/!/He/pleaded/."
     span = tokens[4:]
-    assert to_str(span) == 'He/pleaded/.'
+    assert to_str(span) == "He/pleaded/."
     span = tokens[:4]
-    assert to_str(span) == 'Give/it/back/!'
+    assert to_str(span) == "Give/it/back/!"
     span = tokens[:-3]
-    assert to_str(span) == 'Give/it/back/!'
+    assert to_str(span) == "Give/it/back/!"
     span = tokens[-3:]
-    assert to_str(span) == 'He/pleaded/.'
+    assert to_str(span) == "He/pleaded/."
 
     span = tokens[4:50]
-    assert to_str(span) == 'He/pleaded/.'
+    assert to_str(span) == "He/pleaded/."
     span = tokens[-50:4]
-    assert to_str(span) == 'Give/it/back/!'
+    assert to_str(span) == "Give/it/back/!"
     span = tokens[-50:-40]
     assert span.start == span.end == 0 and not to_str(span)
     span = tokens[40:50]
     assert span.start == span.end == 7 and not to_str(span)
 
     span = tokens[1:4]
-    assert span[0].orth_ == 'it'
+    assert span[0].orth_ == "it"
     subspan = span[:]
-    assert to_str(subspan) == 'it/back/!'
+    assert to_str(subspan) == "it/back/!"
     subspan = span[:2]
-    assert to_str(subspan) == 'it/back'
+    assert to_str(subspan) == "it/back"
     subspan = span[1:]
-    assert to_str(subspan) == 'back/!'
+    assert to_str(subspan) == "back/!"
     subspan = span[:-1]
-    assert to_str(subspan) == 'it/back'
+    assert to_str(subspan) == "it/back"
     subspan = span[-2:]
-    assert to_str(subspan) == 'back/!'
+    assert to_str(subspan) == "back/!"
     subspan = span[1:2]
-    assert to_str(subspan) == 'back'
+    assert to_str(subspan) == "back"
     subspan = span[-2:-1]
-    assert to_str(subspan) == 'back'
+    assert to_str(subspan) == "back"
     subspan = span[-50:50]
-    assert to_str(subspan) == 'it/back/!'
+    assert to_str(subspan) == "it/back/!"
     subspan = span[50:-50]
     assert subspan.start == subspan.end == 4 and not to_str(subspan)
 
 
-@pytest.mark.parametrize('text', ["Give it back! He pleaded.",
-                                  " Give it back! He pleaded. "])
+@pytest.mark.parametrize(
+    "text", ["Give it back! He pleaded.", " Give it back! He pleaded. "]
+)
 def test_doc_api_serialize(en_tokenizer, text):
     tokens = en_tokenizer(text)
     new_tokens = Doc(tokens.vocab).from_bytes(tokens.to_bytes())
@@ -110,13 +111,15 @@ def test_doc_api_serialize(en_tokenizer, text):
     assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
 
     new_tokens = Doc(tokens.vocab).from_bytes(
-        tokens.to_bytes(tensor=False), tensor=False)
+        tokens.to_bytes(tensor=False), tensor=False
+    )
     assert tokens.text == new_tokens.text
     assert [t.text for t in tokens] == [t.text for t in new_tokens]
     assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
 
     new_tokens = Doc(tokens.vocab).from_bytes(
-        tokens.to_bytes(sentiment=False), sentiment=False)
+        tokens.to_bytes(sentiment=False), sentiment=False
+    )
     assert tokens.text == new_tokens.text
     assert [t.text for t in tokens] == [t.text for t in new_tokens]
     assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
@@ -126,10 +129,10 @@ def test_doc_api_set_ents(en_tokenizer):
     text = "I use goggle chrone to surf the web"
     tokens = en_tokenizer(text)
     assert len(tokens.ents) == 0
-    tokens.ents = [(tokens.vocab.strings['PRODUCT'], 2, 4)]
+    tokens.ents = [(tokens.vocab.strings["PRODUCT"], 2, 4)]
     assert len(list(tokens.ents)) == 1
     assert [t.ent_iob for t in tokens] == [0, 0, 3, 1, 0, 0, 0, 0]
-    assert tokens.ents[0].label_ == 'PRODUCT'
+    assert tokens.ents[0].label_ == "PRODUCT"
     assert tokens.ents[0].start == 2
     assert tokens.ents[0].end == 4
 
@@ -140,21 +143,31 @@ def test_doc_api_merge(en_tokenizer):
     # merge 'The Beach Boys'
     doc = en_tokenizer(text)
     assert len(doc) == 9
-    doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), tag='NAMED', lemma='LEMMA',
-              ent_type='TYPE')
+    doc.merge(
+        doc[4].idx,
+        doc[6].idx + len(doc[6]),
+        tag="NAMED",
+        lemma="LEMMA",
+        ent_type="TYPE",
+    )
     assert len(doc) == 7
-    assert doc[4].text == 'the beach boys'
-    assert doc[4].text_with_ws == 'the beach boys '
-    assert doc[4].tag_ == 'NAMED'
+    assert doc[4].text == "the beach boys"
+    assert doc[4].text_with_ws == "the beach boys "
+    assert doc[4].tag_ == "NAMED"
 
     # merge 'all night'
     doc = en_tokenizer(text)
     assert len(doc) == 9
-    doc.merge(doc[7].idx, doc[8].idx + len(doc[8]), tag='NAMED', lemma='LEMMA',
-              ent_type='TYPE')
+    doc.merge(
+        doc[7].idx,
+        doc[8].idx + len(doc[8]),
+        tag="NAMED",
+        lemma="LEMMA",
+        ent_type="TYPE",
+    )
     assert len(doc) == 8
-    assert doc[7].text == 'all night'
-    assert doc[7].text_with_ws == 'all night'
+    assert doc[7].text == "all night"
+    assert doc[7].text_with_ws == "all night"
 
 
 def test_doc_api_merge_children(en_tokenizer):
@@ -162,8 +175,13 @@ def test_doc_api_merge_children(en_tokenizer):
     text = "WKRO played songs by the beach boys all night"
     doc = en_tokenizer(text)
     assert len(doc) == 9
-    doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), tag='NAMED', lemma='LEMMA',
-              ent_type='TYPE')
+    doc.merge(
+        doc[4].idx,
+        doc[6].idx + len(doc[6]),
+        tag="NAMED",
+        lemma="LEMMA",
+        ent_type="TYPE",
+    )
 
     for word in doc:
         if word.i < word.head.i:
@@ -175,8 +193,8 @@ def test_doc_api_merge_children(en_tokenizer):
 def test_doc_api_merge_hang(en_tokenizer):
     text = "through North and South Carolina"
     doc = en_tokenizer(text)
-    doc.merge(18, 32, tag='', lemma='', ent_type='ORG')
-    doc.merge(8, 32, tag='', lemma='', ent_type='ORG')
+    doc.merge(18, 32, tag="", lemma="", ent_type="ORG")
+    doc.merge(8, 32, tag="", lemma="", ent_type="ORG")
 
 
 def test_doc_api_retokenizer(en_tokenizer):
@@ -184,19 +202,19 @@ def test_doc_api_retokenizer(en_tokenizer):
     with doc.retokenize() as retokenizer:
         retokenizer.merge(doc[4:7])
     assert len(doc) == 7
-    assert doc[4].text == 'the beach boys'
+    assert doc[4].text == "the beach boys"
 
 
 def test_doc_api_retokenizer_attrs(en_tokenizer):
     doc = en_tokenizer("WKRO played songs by the beach boys all night")
     # test both string and integer attributes and values
-    attrs = {LEMMA: 'boys', 'ENT_TYPE': doc.vocab.strings['ORG']}
+    attrs = {LEMMA: "boys", "ENT_TYPE": doc.vocab.strings["ORG"]}
     with doc.retokenize() as retokenizer:
         retokenizer.merge(doc[4:7], attrs=attrs)
     assert len(doc) == 7
-    assert doc[4].text == 'the beach boys'
-    assert doc[4].lemma_ == 'boys'
-    assert doc[4].ent_type_ == 'ORG'
+    assert doc[4].text == "the beach boys"
+    assert doc[4].lemma_ == "boys"
+    assert doc[4].ent_type_ == "ORG"
 
 
 @pytest.mark.xfail
@@ -205,11 +223,11 @@ def test_doc_api_retokenizer_lex_attrs(en_tokenizer):
     doc = en_tokenizer("WKRO played beach boys songs")
     assert not any(token.is_stop for token in doc)
     with doc.retokenize() as retokenizer:
-        retokenizer.merge(doc[2:4], attrs={'LEMMA': 'boys', 'IS_STOP': True})
-    assert doc[2].text == 'beach boys'
-    assert doc[2].lemma_ == 'boys'
+        retokenizer.merge(doc[2:4], attrs={"LEMMA": "boys", "IS_STOP": True})
+    assert doc[2].text == "beach boys"
+    assert doc[2].lemma_ == "boys"
     assert doc[2].is_stop
-    new_doc = Doc(doc.vocab, words=['beach boys'])
+    new_doc = Doc(doc.vocab, words=["beach boys"])
     assert new_doc[0].is_stop
 
 
@@ -222,21 +240,25 @@ def test_doc_api_sents_empty_string(en_tokenizer):
 
 def test_doc_api_runtime_error(en_tokenizer):
     # Example that caused run-time error while parsing Reddit
+    # fmt: off
     text = "67% of black households are single parent \n\n72% of all black babies born out of wedlock \n\n50% of all black kids don\u2019t finish high school"
-    deps = ['nsubj', 'prep', 'amod', 'pobj', 'ROOT', 'amod', 'attr', '',
-            'nummod', 'prep', 'det', 'amod', 'pobj', 'acl', 'prep', 'prep',
-            'pobj', '', 'nummod', 'prep', 'det', 'amod', 'pobj', 'aux', 'neg',
-            'ROOT', 'amod', 'dobj']
+    deps = ["nsubj", "prep", "amod", "pobj", "ROOT", "amod", "attr", "",
+            "nummod", "prep", "det", "amod", "pobj", "acl", "prep", "prep",
+            "pobj", "", "nummod", "prep", "det", "amod", "pobj", "aux", "neg",
+            "ROOT", "amod", "dobj"]
+    # fmt: on
 
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], deps=deps)
 
     nps = []
     for np in doc.noun_chunks:
-        while len(np) > 1 and np[0].dep_ not in ('advmod', 'amod', 'compound'):
+        while len(np) > 1 and np[0].dep_ not in ("advmod", "amod", "compound"):
             np = np[1:]
         if len(np) > 1:
-            nps.append((np.start_char, np.end_char, np.root.tag_, np.text, np.root.ent_type_))
+            nps.append(
+                (np.start_char, np.end_char, np.root.tag_, np.text, np.root.ent_type_)
+            )
     for np in nps:
         start, end, tag, lemma, ent_type = np
         doc.merge(start, end, tag=tag, lemma=lemma, ent_type=ent_type)
@@ -244,57 +266,76 @@ def test_doc_api_runtime_error(en_tokenizer):
 
 def test_doc_api_right_edge(en_tokenizer):
     """Test for bug occurring from Unshift action, causing incorrect right edge"""
+    # fmt: off
     text = "I have proposed to myself, for the sake of such as live under the government of the Romans, to translate those books into the Greek tongue."
     heads = [2, 1, 0, -1, -1, -3, 15, 1, -2, -1, 1, -3, -1, -1, 1, -2, -1, 1,
              -2, -7, 1, -19, 1, -2, -3, 2, 1, -3, -26]
+    # fmt: on
 
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
-    assert doc[6].text == 'for'
+    assert doc[6].text == "for"
     subtree = [w.text for w in doc[6].subtree]
-    assert subtree == ['for', 'the', 'sake', 'of', 'such', 'as',
-                       'live', 'under', 'the', 'government', 'of', 'the', 'Romans', ',']
-    assert doc[6].right_edge.text == ','
+    assert subtree == [
+        "for",
+        "the",
+        "sake",
+        "of",
+        "such",
+        "as",
+        "live",
+        "under",
+        "the",
+        "government",
+        "of",
+        "the",
+        "Romans",
+        ",",
+    ]
+    assert doc[6].right_edge.text == ","
 
 
 def test_doc_api_has_vector():
     vocab = Vocab()
     vocab.reset_vectors(width=2)
-    vocab.set_vector('kitten', vector=numpy.asarray([0., 2.], dtype='f'))
-    doc = Doc(vocab, words=['kitten'])
+    vocab.set_vector("kitten", vector=numpy.asarray([0.0, 2.0], dtype="f"))
+    doc = Doc(vocab, words=["kitten"])
     assert doc.has_vector
 
 
 def test_doc_api_similarity_match():
-    doc = Doc(Vocab(), words=['a'])
+    doc = Doc(Vocab(), words=["a"])
     with pytest.warns(None):
         assert doc.similarity(doc[0]) == 1.0
-        assert doc.similarity(doc.vocab['a']) == 1.0
-    doc2 = Doc(doc.vocab, words=['a', 'b', 'c'])
+        assert doc.similarity(doc.vocab["a"]) == 1.0
+    doc2 = Doc(doc.vocab, words=["a", "b", "c"])
     with pytest.warns(None):
         assert doc.similarity(doc2[:1]) == 1.0
         assert doc.similarity(doc2) == 0.0
 
 
 def test_lowest_common_ancestor(en_tokenizer):
-    tokens = en_tokenizer('the lazy dog slept')
+    tokens = en_tokenizer("the lazy dog slept")
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[2, 1, 1, 0])
     lca = doc.get_lca_matrix()
-    assert(lca[1, 1] == 1)
-    assert(lca[0, 1] == 2)
-    assert(lca[1, 2] == 2)
+    assert lca[1, 1] == 1
+    assert lca[0, 1] == 2
+    assert lca[1, 2] == 2
 
 
 def test_parse_tree(en_tokenizer):
     """Tests doc.print_tree() method."""
-    text = 'I like New York in Autumn.'
+    text = "I like New York in Autumn."
     heads = [1, 0, 1, -2, -3, -1, -5]
-    tags = ['PRP', 'IN', 'NNP', 'NNP', 'IN', 'NNP', '.']
+    tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, tags=tags)
     # full method parse_tree(text) is a trivial composition
     trees = doc.print_tree()
     assert len(trees) > 0
     tree = trees[0]
-    assert all(k in list(tree.keys()) for k in ['word', 'lemma', 'NE', 'POS_fine', 'POS_coarse', 'arc', 'modifiers'])
-    assert tree['word'] == 'like' # check root is correct
+    assert all(
+        k in list(tree.keys())
+        for k in ["word", "lemma", "NE", "POS_fine", "POS_coarse", "arc", "modifiers"]
+    )
+    assert tree["word"] == "like"  # check root is correct

spacy/tests/doc/test_pickle_doc.py

@@ -7,37 +7,38 @@ from spacy.compat import pickle, unicode_
 
 def test_pickle_single_doc():
     nlp = Language()
-    doc = nlp('pickle roundtrip')
+    doc = nlp("pickle roundtrip")
     data = pickle.dumps(doc, 1)
     doc2 = pickle.loads(data)
-    assert doc2.text == 'pickle roundtrip'
+    assert doc2.text == "pickle roundtrip"
 
 
 def test_list_of_docs_pickles_efficiently():
     nlp = Language()
     for i in range(10000):
         _ = nlp.vocab[unicode_(i)]
-    one_pickled = pickle.dumps(nlp('0'), -1)
+    one_pickled = pickle.dumps(nlp("0"), -1)
     docs = list(nlp.pipe(unicode_(i) for i in range(100)))
     many_pickled = pickle.dumps(docs, -1)
     assert len(many_pickled) < (len(one_pickled) * 2)
     many_unpickled = pickle.loads(many_pickled)
-    assert many_unpickled[0].text == '0'
-    assert many_unpickled[-1].text == '99'
+    assert many_unpickled[0].text == "0"
+    assert many_unpickled[-1].text == "99"
     assert len(many_unpickled) == 100
 
 
 def test_user_data_from_disk():
     nlp = Language()
-    doc = nlp('Hello')
+    doc = nlp("Hello")
     doc.user_data[(0, 1)] = False
     b = doc.to_bytes()
     doc2 = doc.__class__(doc.vocab).from_bytes(b)
     assert doc2.user_data[(0, 1)] == False
 
+
 def test_user_data_unpickles():
     nlp = Language()
-    doc = nlp('Hello')
+    doc = nlp("Hello")
     doc.user_data[(0, 1)] = False
     b = pickle.dumps(doc)
     doc2 = pickle.loads(b)
@@ -46,10 +47,11 @@ def test_user_data_unpickles():
 
 def test_hooks_unpickle():
     def inner_func(d1, d2):
-        return 'hello!'
+        return "hello!"
+
     nlp = Language()
-    doc = nlp('Hello')
-    doc.user_hooks['similarity'] = inner_func
+    doc = nlp("Hello")
+    doc.user_hooks["similarity"] = inner_func
     b = pickle.dumps(doc)
     doc2 = pickle.loads(b)
-    assert doc2.similarity(None) == 'hello!'
+    assert doc2.similarity(None) == "hello!"

spacy/tests/doc/test_span.py

@@ -11,10 +11,12 @@ from ..util import get_doc
 
 @pytest.fixture
 def doc(en_tokenizer):
+    # fmt: off
     text = "This is a sentence. This is another sentence. And a third."
     heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3, 0, 1, -2, -1]
-    deps = ['nsubj', 'ROOT', 'det', 'attr', 'punct', 'nsubj', 'ROOT', 'det',
-            'attr', 'punct', 'ROOT', 'det', 'npadvmod', 'punct']
+    deps = ["nsubj", "ROOT", "det", "attr", "punct", "nsubj", "ROOT", "det",
+            "attr", "punct", "ROOT", "det", "npadvmod", "punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
     return get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
 
@@ -39,17 +41,17 @@ def test_spans_sent_spans(doc):
 def test_spans_root(doc):
     span = doc[2:4]
     assert len(span) == 2
-    assert span.text == 'a sentence'
-    assert span.root.text == 'sentence'
-    assert span.root.head.text == 'is'
+    assert span.text == "a sentence"
+    assert span.root.text == "sentence"
+    assert span.root.head.text == "is"
 
 
 def test_spans_string_fn(doc):
     span = doc[0:4]
     assert len(span) == 4
-    assert span.text == 'This is a sentence'
-    assert span.upper_ == 'THIS IS A SENTENCE'
-    assert span.lower_ == 'this is a sentence'
+    assert span.text == "This is a sentence"
+    assert span.upper_ == "THIS IS A SENTENCE"
+    assert span.lower_ == "this is a sentence"
 
 
 def test_spans_root2(en_tokenizer):
@@ -57,15 +59,15 @@ def test_spans_root2(en_tokenizer):
     heads = [0, 3, -1, -2, -4]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
-    assert doc[-2:].root.text == 'Carolina'
+    assert doc[-2:].root.text == "Carolina"
 
 
 def test_spans_span_sent(doc, doc_not_parsed):
     """Test span.sent property"""
     assert len(list(doc.sents))
-    assert doc[:2].sent.root.text == 'is'
-    assert doc[:2].sent.text == 'This is a sentence .'
-    assert doc[6:7].sent.root.left_edge.text == 'This'
+    assert doc[:2].sent.root.text == "is"
+    assert doc[:2].sent.text == "This is a sentence ."
+    assert doc[6:7].sent.root.left_edge.text == "This"
     # test on manual sbd
     doc_not_parsed[0].is_sent_start = True
     doc_not_parsed[5].is_sent_start = True
@@ -75,23 +77,23 @@ def test_spans_span_sent(doc, doc_not_parsed):
 
 def test_spans_lca_matrix(en_tokenizer):
     """Test span's lca matrix generation"""
-    tokens = en_tokenizer('the lazy dog slept')
+    tokens = en_tokenizer("the lazy dog slept")
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[2, 1, 1, 0])
     lca = doc[:2].get_lca_matrix()
-    assert(lca[0, 0] == 0)
-    assert(lca[0, 1] == -1)
-    assert(lca[1, 0] == -1)
-    assert(lca[1, 1] == 1)
+    assert lca[0, 0] == 0
+    assert lca[0, 1] == -1
+    assert lca[1, 0] == -1
+    assert lca[1, 1] == 1
 
 
 def test_span_similarity_match():
-    doc = Doc(Vocab(), words=['a', 'b', 'a', 'b'])
+    doc = Doc(Vocab(), words=["a", "b", "a", "b"])
     span1 = doc[:2]
     span2 = doc[2:]
     with pytest.warns(None):
         assert span1.similarity(span2) == 1.0
         assert span1.similarity(doc) == 0.0
-        assert span1[:1].similarity(doc.vocab['a']) == 1.0
+        assert span1[:1].similarity(doc.vocab["a"]) == 1.0
 
 
 def test_spans_default_sentiment(en_tokenizer):
@@ -102,8 +104,8 @@ def test_spans_default_sentiment(en_tokenizer):
     tokens.vocab[tokens[2].text].sentiment = -2.0
     doc = Doc(tokens.vocab, words=[t.text for t in tokens])
     assert doc[:2].sentiment == 3.0 / 2
-    assert doc[-2:].sentiment == -2. / 2
-    assert doc[:-1].sentiment == (3.+-2) / 3.
+    assert doc[-2:].sentiment == -2.0 / 2
+    assert doc[:-1].sentiment == (3.0 + -2) / 3.0
 
 
 def test_spans_override_sentiment(en_tokenizer):
@@ -113,7 +115,7 @@ def test_spans_override_sentiment(en_tokenizer):
     tokens.vocab[tokens[0].text].sentiment = 3.0
     tokens.vocab[tokens[2].text].sentiment = -2.0
     doc = Doc(tokens.vocab, words=[t.text for t in tokens])
-    doc.user_span_hooks['sentiment'] = lambda span: 10.0
+    doc.user_span_hooks["sentiment"] = lambda span: 10.0
     assert doc[:2].sentiment == 10.0
     assert doc[-2:].sentiment == 10.0
     assert doc[:-1].sentiment == 10.0
@@ -132,10 +134,10 @@ def test_spans_are_hashable(en_tokenizer):
 
 def test_spans_by_character(doc):
     span1 = doc[1:-2]
-    span2 = doc.char_span(span1.start_char, span1.end_char, label='GPE')
+    span2 = doc.char_span(span1.start_char, span1.end_char, label="GPE")
     assert span1.start_char == span2.start_char
     assert span1.end_char == span2.end_char
-    assert span2.label_ == 'GPE'
+    assert span2.label_ == "GPE"
 
 
 def test_span_to_array(doc):
@@ -151,12 +153,13 @@ def test_span_as_doc(doc):
     span_doc = span.as_doc()
     assert span.text == span_doc.text.strip()
 
+
 def test_span_ents_property(doc):
     """Test span.ents for the """
     doc.ents = [
-        (doc.vocab.strings['PRODUCT'], 0, 1),
-        (doc.vocab.strings['PRODUCT'], 7, 8),
-        (doc.vocab.strings['PRODUCT'], 11, 14)
+        (doc.vocab.strings["PRODUCT"], 0, 1),
+        (doc.vocab.strings["PRODUCT"], 7, 8),
+        (doc.vocab.strings["PRODUCT"], 11, 14),
     ]
     assert len(list(doc.ents)) == 3
     sentences = list(doc.sents)

spacy/tests/doc/test_span_merge.py

@@ -13,22 +13,23 @@ def test_spans_merge_tokens(en_tokenizer):
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
     assert len(doc) == 4
-    assert doc[0].head.text == 'Angeles'
-    assert doc[1].head.text == 'start'
-    doc.merge(0, len('Los Angeles'), tag='NNP', lemma='Los Angeles', ent_type='GPE')
+    assert doc[0].head.text == "Angeles"
+    assert doc[1].head.text == "start"
+    doc.merge(0, len("Los Angeles"), tag="NNP", lemma="Los Angeles", ent_type="GPE")
     assert len(doc) == 3
-    assert doc[0].text == 'Los Angeles'
-    assert doc[0].head.text == 'start'
+    assert doc[0].text == "Los Angeles"
+    assert doc[0].head.text == "start"
 
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
     assert len(doc) == 4
-    assert doc[0].head.text == 'Angeles'
-    assert doc[1].head.text == 'start'
-    doc.merge(0, len('Los Angeles'), tag='NNP', lemma='Los Angeles', label='GPE')
+    assert doc[0].head.text == "Angeles"
+    assert doc[1].head.text == "start"
+    doc.merge(0, len("Los Angeles"), tag="NNP", lemma="Los Angeles", label="GPE")
     assert len(doc) == 3
-    assert doc[0].text == 'Los Angeles'
-    assert doc[0].head.text == 'start'
-    assert doc[0].ent_type_ == 'GPE'
+    assert doc[0].text == "Los Angeles"
+    assert doc[0].head.text == "start"
+    assert doc[0].ent_type_ == "GPE"
+
 
 def test_spans_merge_heads(en_tokenizer):
     text = "I found a pilates class near work."
@@ -37,8 +38,13 @@ def test_spans_merge_heads(en_tokenizer):
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
 
     assert len(doc) == 8
-    doc.merge(doc[3].idx, doc[4].idx + len(doc[4]), tag=doc[4].tag_,
-              lemma='pilates class', ent_type='O')
+    doc.merge(
+        doc[3].idx,
+        doc[4].idx + len(doc[4]),
+        tag=doc[4].tag_,
+        lemma="pilates class",
+        ent_type="O",
+    )
     assert len(doc) == 7
     assert doc[0].head.i == 1
     assert doc[1].head.i == 1
@@ -55,8 +61,9 @@ def test_span_np_merges(en_tokenizer):
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
 
     assert doc[4].head.i == 1
-    doc.merge(doc[2].idx, doc[4].idx + len(doc[4]), tag='NP', lemma='tool',
-              ent_type='O')
+    doc.merge(
+        doc[2].idx, doc[4].idx + len(doc[4]), tag="NP", lemma="tool", ent_type="O"
+    )
     assert doc[2].head.i == 1
 
     text = "displaCy is a lightweight and modern dependency parse tree visualization tool built with CSS3 and JavaScript."
@@ -69,7 +76,6 @@ def test_span_np_merges(en_tokenizer):
         merged = doc.merge(start, end, tag=label, lemma=lemma, ent_type=label)
         assert merged != None, (start, end, label, lemma)
 
-
     text = "One test with entities like New York City so the ents list is not void"
     heads = [1, 11, -1, -1, -1, 1, 1, -3, 4, 2, 1, 1, 0, -1, -2]
     tokens = en_tokenizer(text)
@@ -80,15 +86,23 @@ def test_span_np_merges(en_tokenizer):
 
 
 def test_spans_entity_merge(en_tokenizer):
+    # fmt: off
     text = "Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale.\n"
     heads = [1, 1, 0, 1, 2, -1, -4, 1, -2, -1, -1, -3, -10, 1, -2, -13, -1]
-    tags = ['NNP', 'NNP', 'VBZ', 'DT', 'VB', 'RP', 'NN', 'WP', 'VBZ', 'IN', 'NNP', 'CC', 'VBZ', 'NNP', 'NNP', '.', 'SP']
-    ents = [(0, 2, 'PERSON'), (10, 11, 'GPE'), (13, 15, 'PERSON')]
+    tags = ["NNP", "NNP", "VBZ", "DT", "VB", "RP", "NN", "WP", "VBZ", "IN", "NNP", "CC", "VBZ", "NNP", "NNP", ".", "SP"]
+    ents = [(0, 2, "PERSON"), (10, 11, "GPE"), (13, 15, "PERSON")]
+    # fmt: on
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, tags=tags, ents=ents)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], heads=heads, tags=tags, ents=ents
+    )
     assert len(doc) == 17
     for ent in doc.ents:
-        label, lemma, type_ = (ent.root.tag_, ent.root.lemma_, max(w.ent_type_ for w in ent))
+        label, lemma, type_ = (
+            ent.root.tag_,
+            ent.root.lemma_,
+            max(w.ent_type_ for w in ent),
+        )
         ent.merge(label=label, lemma=lemma, ent_type=type_)
     # check looping is ok
     assert len(doc) == 15
@@ -98,8 +112,10 @@ def test_spans_entity_merge_iob():
     # Test entity IOB stays consistent after merging
     words = ["a", "b", "c", "d", "e"]
     doc = Doc(Vocab(), words=words)
-    doc.ents = [(doc.vocab.strings.add('ent-abc'), 0, 3),
-                (doc.vocab.strings.add('ent-d'), 3, 4)]
+    doc.ents = [
+        (doc.vocab.strings.add("ent-abc"), 0, 3),
+        (doc.vocab.strings.add("ent-d"), 3, 4),
+    ]
     assert doc[0].ent_iob_ == "B"
     assert doc[1].ent_iob_ == "I"
     assert doc[2].ent_iob_ == "I"
@@ -110,33 +126,37 @@ def test_spans_entity_merge_iob():
 
 
 def test_spans_sentence_update_after_merge(en_tokenizer):
+    # fmt: off
     text = "Stewart Lee is a stand up comedian. He lives in England and loves Joe Pasquale."
     heads = [1, 1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2, -7]
     deps = ['compound', 'nsubj', 'ROOT', 'det', 'amod', 'prt', 'attr',
             'punct', 'nsubj', 'ROOT', 'prep', 'pobj', 'cc', 'conj',
             'compound', 'dobj', 'punct']
+    # fmt: on
 
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     sent1, sent2 = list(doc.sents)
     init_len = len(sent1)
     init_len2 = len(sent2)
-    doc[0:2].merge(label='none', lemma='none', ent_type='none')
-    doc[-2:].merge(label='none', lemma='none', ent_type='none')
+    doc[0:2].merge(label="none", lemma="none", ent_type="none")
+    doc[-2:].merge(label="none", lemma="none", ent_type="none")
     assert len(sent1) == init_len - 1
     assert len(sent2) == init_len2 - 1
 
 
 def test_spans_subtree_size_check(en_tokenizer):
+    # fmt: off
     text = "Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale"
     heads = [1, 1, 0, 1, 2, -1, -4, 1, -2, -1, -1, -3, -10, 1, -2]
-    deps = ['compound', 'nsubj', 'ROOT', 'det', 'amod', 'prt', 'attr',
-            'nsubj', 'relcl', 'prep', 'pobj', 'cc', 'conj', 'compound',
-            'dobj']
+    deps = ["compound", "nsubj", "ROOT", "det", "amod", "prt", "attr",
+            "nsubj", "relcl", "prep", "pobj", "cc", "conj", "compound",
+            "dobj"]
+    # fmt: on
 
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     sent1 = list(doc.sents)[0]
     init_len = len(list(sent1.root.subtree))
-    doc[0:2].merge(label='none', lemma='none', ent_type='none')
+    doc[0:2].merge(label="none", lemma="none", ent_type="none")
     assert len(list(sent1.root.subtree)) == init_len - 1

spacy/tests/doc/test_token_api.py

@@ -13,31 +13,35 @@ from ..util import get_doc
 
 @pytest.fixture
 def doc(en_tokenizer):
+    # fmt: off
     text = "This is a sentence. This is another sentence. And a third."
     heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3, 0, 1, -2, -1]
-    deps = ['nsubj', 'ROOT', 'det', 'attr', 'punct', 'nsubj', 'ROOT', 'det',
-            'attr', 'punct', 'ROOT', 'det', 'npadvmod', 'punct']
+    deps = ["nsubj", "ROOT", "det", "attr", "punct", "nsubj", "ROOT", "det",
+            "attr", "punct", "ROOT", "det", "npadvmod", "punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
     return get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
 
 
 def test_doc_token_api_strings(en_tokenizer):
     text = "Give it back! He pleaded."
-    pos = ['VERB', 'PRON', 'PART', 'PUNCT', 'PRON', 'VERB', 'PUNCT']
+    pos = ["VERB", "PRON", "PART", "PUNCT", "PRON", "VERB", "PUNCT"]
     heads = [0, -1, -2, -3, 1, 0, -1]
-    deps = ['ROOT', 'dobj', 'prt', 'punct', 'nsubj', 'ROOT', 'punct']
+    deps = ["ROOT", "dobj", "prt", "punct", "nsubj", "ROOT", "punct"]
 
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps)
-    assert doc[0].orth_ == 'Give'
-    assert doc[0].text == 'Give'
-    assert doc[0].text_with_ws == 'Give '
-    assert doc[0].lower_ == 'give'
-    assert doc[0].shape_ == 'Xxxx'
-    assert doc[0].prefix_ == 'G'
-    assert doc[0].suffix_ == 'ive'
-    assert doc[0].pos_ == 'VERB'
-    assert doc[0].dep_ == 'ROOT'
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps
+    )
+    assert doc[0].orth_ == "Give"
+    assert doc[0].text == "Give"
+    assert doc[0].text_with_ws == "Give "
+    assert doc[0].lower_ == "give"
+    assert doc[0].shape_ == "Xxxx"
+    assert doc[0].prefix_ == "G"
+    assert doc[0].suffix_ == "ive"
+    assert doc[0].pos_ == "VERB"
+    assert doc[0].dep_ == "ROOT"
 
 
 def test_doc_token_api_flags(en_tokenizer):
@@ -53,7 +57,7 @@ def test_doc_token_api_flags(en_tokenizer):
     # TODO: Test more of these, esp. if a bug is found
 
 
-@pytest.mark.parametrize('text', ["Give it back! He pleaded."])
+@pytest.mark.parametrize("text", ["Give it back! He pleaded."])
 def test_doc_token_api_prob_inherited_from_vocab(en_tokenizer, text):
     word = text.split()[0]
     en_tokenizer.vocab[word].prob = -1
@@ -61,11 +65,11 @@ def test_doc_token_api_prob_inherited_from_vocab(en_tokenizer, text):
     assert tokens[0].prob != 0
 
 
-@pytest.mark.parametrize('text', ["one two"])
+@pytest.mark.parametrize("text", ["one two"])
 def test_doc_token_api_str_builtin(en_tokenizer, text):
     tokens = en_tokenizer(text)
-    assert str(tokens[0]) == text.split(' ')[0]
-    assert str(tokens[1]) == text.split(' ')[1]
+    assert str(tokens[0]) == text.split(" ")[0]
+    assert str(tokens[1]) == text.split(" ")[1]
 
 
 def test_doc_token_api_is_properties(en_vocab):
@@ -83,16 +87,16 @@ def test_doc_token_api_is_properties(en_vocab):
 def test_doc_token_api_vectors():
     vocab = Vocab()
     vocab.reset_vectors(width=2)
-    vocab.set_vector('apples', vector=numpy.asarray([0., 2.], dtype='f'))
-    vocab.set_vector('oranges', vector=numpy.asarray([0., 1.], dtype='f'))
-    doc = Doc(vocab, words=['apples', 'oranges', 'oov'])
+    vocab.set_vector("apples", vector=numpy.asarray([0.0, 2.0], dtype="f"))
+    vocab.set_vector("oranges", vector=numpy.asarray([0.0, 1.0], dtype="f"))
+    doc = Doc(vocab, words=["apples", "oranges", "oov"])
     assert doc.has_vector
     assert doc[0].has_vector
     assert doc[1].has_vector
     assert not doc[2].has_vector
-    apples_norm = (0*0 + 2*2) ** 0.5
-    oranges_norm = (0*0 + 1*1) ** 0.5
-    cosine = ((0*0) + (2*1)) / (apples_norm * oranges_norm)
+    apples_norm = (0 * 0 + 2 * 2) ** 0.5
+    oranges_norm = (0 * 0 + 1 * 1) ** 0.5
+    cosine = ((0 * 0) + (2 * 1)) / (apples_norm * oranges_norm)
     assert doc[0].similarity(doc[1]) == cosine
 
 
@@ -165,7 +169,7 @@ def test_doc_token_api_head_setter(en_tokenizer):
 
 
 def test_is_sent_start(en_tokenizer):
-    doc = en_tokenizer('This is a sentence. This is another.')
+    doc = en_tokenizer("This is a sentence. This is another.")
     assert doc[5].is_sent_start is None
     doc[5].is_sent_start = True
     assert doc[5].is_sent_start is True
@@ -174,17 +178,17 @@ def test_is_sent_start(en_tokenizer):
 
 
 def test_set_pos():
-    doc = Doc(Vocab(), words=['hello', 'world'])
-    doc[0].pos_ = 'NOUN'
-    assert doc[0].pos_ == 'NOUN'
+    doc = Doc(Vocab(), words=["hello", "world"])
+    doc[0].pos_ = "NOUN"
+    assert doc[0].pos_ == "NOUN"
     doc[1].pos = VERB
-    assert doc[1].pos_ == 'VERB'
+    assert doc[1].pos_ == "VERB"
 
 
 def test_tokens_sent(doc):
     """Test token.sent property"""
     assert len(list(doc.sents)) == 3
-    assert doc[1].sent.text == 'This is a sentence .'
-    assert doc[7].sent.text == 'This is another sentence .'
-    assert doc[1].sent.root.left_edge.text == 'This'
-    assert doc[7].sent.root.left_edge.text == 'This'
+    assert doc[1].sent.text == "This is a sentence ."
+    assert doc[7].sent.text == "This is another sentence ."
+    assert doc[1].sent.root.left_edge.text == "This"
+    assert doc[7].sent.root.left_edge.text == "This"

spacy/tests/doc/test_underscore.py

@@ -20,7 +20,7 @@ def test_doc_underscore_getattr_setattr():
     doc = Mock()
     doc.doc = doc
     doc.user_data = {}
-    Underscore.doc_extensions['hello'] = (False, None, None, None)
+    Underscore.doc_extensions["hello"] = (False, None, None, None)
     doc._ = Underscore(Underscore.doc_extensions, doc)
     assert doc._.hello == False
     doc._.hello = True
@@ -29,8 +29,9 @@ def test_doc_underscore_getattr_setattr():
 
 def test_create_span_underscore():
     span = Mock(doc=Mock(), start=0, end=2)
-    uscore = Underscore(Underscore.span_extensions, span,
-                        start=span.start, end=span.end)
+    uscore = Underscore(
+        Underscore.span_extensions, span, start=span.start, end=span.end
+    )
     assert uscore._doc is span.doc
     assert uscore._start is span.start
     assert uscore._end is span.end
@@ -38,60 +39,70 @@ def test_create_span_underscore():
 
 def test_span_underscore_getter_setter():
     span = Mock(doc=Mock(), start=0, end=2)
-    Underscore.span_extensions['hello'] = (None, None,
-                                           lambda s: (s.start, 'hi'),
-                                           lambda s, value: setattr(s, 'start',
-                                                                    value))
-    span._ = Underscore(Underscore.span_extensions, span,
-                        start=span.start, end=span.end)
+    Underscore.span_extensions["hello"] = (
+        None,
+        None,
+        lambda s: (s.start, "hi"),
+        lambda s, value: setattr(s, "start", value),
+    )
+    span._ = Underscore(
+        Underscore.span_extensions, span, start=span.start, end=span.end
+    )
 
-    assert span._.hello == (0, 'hi')
+    assert span._.hello == (0, "hi")
     span._.hello = 1
-    assert span._.hello == (1, 'hi')
+    assert span._.hello == (1, "hi")
 
 
 def test_token_underscore_method():
-    token = Mock(doc=Mock(), idx=7, say_cheese=lambda token: 'cheese')
-    Underscore.token_extensions['hello'] = (None, token.say_cheese,
-                                            None, None)
+    token = Mock(doc=Mock(), idx=7, say_cheese=lambda token: "cheese")
+    Underscore.token_extensions["hello"] = (None, token.say_cheese, None, None)
     token._ = Underscore(Underscore.token_extensions, token, start=token.idx)
-    assert token._.hello() == 'cheese'
+    assert token._.hello() == "cheese"
 
 
-@pytest.mark.parametrize('obj', [Doc, Span, Token])
+@pytest.mark.parametrize("obj", [Doc, Span, Token])
 def test_doc_underscore_remove_extension(obj):
-    ext_name = 'to_be_removed'
+    ext_name = "to_be_removed"
     obj.set_extension(ext_name, default=False)
     assert obj.has_extension(ext_name)
     obj.remove_extension(ext_name)
     assert not obj.has_extension(ext_name)
 
 
-@pytest.mark.parametrize('obj', [Doc, Span, Token])
+@pytest.mark.parametrize("obj", [Doc, Span, Token])
 def test_underscore_raises_for_dup(obj):
-    obj.set_extension('test', default=None)
+    obj.set_extension("test", default=None)
     with pytest.raises(ValueError):
-        obj.set_extension('test', default=None)
+        obj.set_extension("test", default=None)
 
 
-@pytest.mark.parametrize('invalid_kwargs', [
-    {'getter': None, 'setter': lambda: None},
-    {'default': None, 'method': lambda: None, 'getter': lambda: None},
-    {'setter': lambda: None},
-    {'default': None, 'method': lambda: None},
-    {'getter': True}])
+@pytest.mark.parametrize(
+    "invalid_kwargs",
+    [
+        {"getter": None, "setter": lambda: None},
+        {"default": None, "method": lambda: None, "getter": lambda: None},
+        {"setter": lambda: None},
+        {"default": None, "method": lambda: None},
+        {"getter": True},
+    ],
+)
 def test_underscore_raises_for_invalid(invalid_kwargs):
-    invalid_kwargs['force'] = True
+    invalid_kwargs["force"] = True
     with pytest.raises(ValueError):
-        Doc.set_extension('test', **invalid_kwargs)
+        Doc.set_extension("test", **invalid_kwargs)
 
 
-@pytest.mark.parametrize('valid_kwargs', [
-    {'getter': lambda: None},
-    {'getter': lambda: None, 'setter': lambda: None},
-    {'default': 'hello'},
-    {'default': None},
-    {'method': lambda: None}])
+@pytest.mark.parametrize(
+    "valid_kwargs",
+    [
+        {"getter": lambda: None},
+        {"getter": lambda: None, "setter": lambda: None},
+        {"default": "hello"},
+        {"default": None},
+        {"method": lambda: None},
+    ],
+)
 def test_underscore_accepts_valid(valid_kwargs):
-    valid_kwargs['force'] = True
-    Doc.set_extension('test', **valid_kwargs)
+    valid_kwargs["force"] = True
+    Doc.set_extension("test", **valid_kwargs)

spacy/tests/lang/ar/test_exceptions.py

@@ -4,7 +4,7 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["ق.م", "إلخ", "ص.ب", "ت."])
+@pytest.mark.parametrize("text", ["ق.م", "إلخ", "ص.ب", "ت."])
 def test_ar_tokenizer_handles_abbr(ar_tokenizer, text):
     tokens = ar_tokenizer(text)
     assert len(tokens) == 1
@@ -18,7 +18,7 @@ def test_ar_tokenizer_handles_exc_in_text(ar_tokenizer):
     assert tokens[6].lemma_ == "قبل الميلاد"
 
 
-def test_ar_tokenizer_handles_exc_in_text(ar_tokenizer):
+def test_ar_tokenizer_handles_exc_in_text_2(ar_tokenizer):
     text = "يبلغ طول مضيق طارق 14كم "
     tokens = ar_tokenizer(text)
     assert len(tokens) == 6

spacy/tests/lang/bn/test_tokenizer.py

@@ -6,16 +6,22 @@ import pytest
 
 TESTCASES = [
     # punctuation tests
-    ('আমি বাংলায় গান গাই!', ['আমি', 'বাংলায়', 'গান', 'গাই', '!']),
-    ('আমি বাংলায় কথা কই।', ['আমি', 'বাংলায়', 'কথা', 'কই', '।']),
-    ('বসুন্ধরা জনসম্মুখে দোষ স্বীকার করলো না?', ['বসুন্ধরা', 'জনসম্মুখে', 'দোষ', 'স্বীকার', 'করলো', 'না', '?']),
-    ('টাকা থাকলে কি না হয়!', ['টাকা', 'থাকলে', 'কি', 'না', 'হয়', '!']),
+    ("আমি বাংলায় গান গাই!", ["আমি", "বাংলায়", "গান", "গাই", "!"]),
+    ("আমি বাংলায় কথা কই।", ["আমি", "বাংলায়", "কথা", "কই", "।"]),
+    (
+        "বসুন্ধরা জনসম্মুখে দোষ স্বীকার করলো না?",
+        ["বসুন্ধরা", "জনসম্মুখে", "দোষ", "স্বীকার", "করলো", "না", "?"],
+    ),
+    ("টাকা থাকলে কি না হয়!", ["টাকা", "থাকলে", "কি", "না", "হয়", "!"]),
     # abbreviations
-    ('ডঃ খালেদ বললেন ঢাকায় ৩৫ ডিগ্রি সে.।', ['ডঃ', 'খালেদ', 'বললেন', 'ঢাকায়', '৩৫', 'ডিগ্রি', 'সে.', '।'])
+    (
+        "ডঃ খালেদ বললেন ঢাকায় ৩৫ ডিগ্রি সে.।",
+        ["ডঃ", "খালেদ", "বললেন", "ঢাকায়", "৩৫", "ডিগ্রি", "সে.", "।"],
+    ),
 ]
 
 
-@pytest.mark.parametrize('text,expected_tokens', TESTCASES)
+@pytest.mark.parametrize("text,expected_tokens", TESTCASES)
 def test_bn_tokenizer_handles_testcases(bn_tokenizer, text, expected_tokens):
     tokens = bn_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]

spacy/tests/lang/da/test_exceptions.py

@@ -4,19 +4,19 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["ca.", "m.a.o.", "Jan.", "Dec.", "kr.", "jf."])
+@pytest.mark.parametrize("text", ["ca.", "m.a.o.", "Jan.", "Dec.", "kr.", "jf."])
 def test_da_tokenizer_handles_abbr(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text', ["Jul.", "jul.", "Tor.", "Tors."])
+@pytest.mark.parametrize("text", ["Jul.", "jul.", "Tor.", "Tors."])
 def test_da_tokenizer_handles_ambiguous_abbr(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["1.", "10.", "31."])
+@pytest.mark.parametrize("text", ["1.", "10.", "31."])
 def test_da_tokenizer_handles_dates(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
@@ -37,8 +37,9 @@ def test_da_tokenizer_handles_custom_base_exc(da_tokenizer):
     assert tokens[7].text == "."
 
 
-@pytest.mark.parametrize('text,norm', [
-    ("akvarium", "akvarie"), ("bedstemoder", "bedstemor")])
+@pytest.mark.parametrize(
+    "text,norm", [("akvarium", "akvarie"), ("bedstemoder", "bedstemor")]
+)
 def test_da_tokenizer_norm_exceptions(da_tokenizer, text, norm):
     tokens = da_tokenizer(text)
     assert tokens[0].norm_ == norm

spacy/tests/lang/da/test_lemma.py

@@ -4,11 +4,15 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('string,lemma', [
-    ('affaldsgruppernes', 'affaldsgruppe'),
-    ('detailhandelsstrukturernes', 'detailhandelsstruktur'),
-    ('kolesterols', 'kolesterol'),
-    ('åsyns', 'åsyn')])
+@pytest.mark.parametrize(
+    "string,lemma",
+    [
+        ("affaldsgruppernes", "affaldsgruppe"),
+        ("detailhandelsstrukturernes", "detailhandelsstruktur"),
+        ("kolesterols", "kolesterol"),
+        ("åsyns", "åsyn"),
+    ],
+)
 def test_da_lemmatizer_lookup_assigns(da_tokenizer, string, lemma):
     tokens = da_tokenizer(string)
     assert tokens[0].lemma_ == lemma

spacy/tests/lang/da/test_prefix_suffix_infix.py

@@ -4,19 +4,19 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["(under)"])
+@pytest.mark.parametrize("text", ["(under)"])
 def test_da_tokenizer_splits_no_special(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["ta'r", "Søren's", "Lars'"])
+@pytest.mark.parametrize("text", ["ta'r", "Søren's", "Lars'"])
 def test_da_tokenizer_handles_no_punct(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text', ["(ta'r"])
+@pytest.mark.parametrize("text", ["(ta'r"])
 def test_da_tokenizer_splits_prefix_punct(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 2
@@ -24,7 +24,7 @@ def test_da_tokenizer_splits_prefix_punct(da_tokenizer, text):
     assert tokens[1].text == "ta'r"
 
 
-@pytest.mark.parametrize('text', ["ta'r)"])
+@pytest.mark.parametrize("text", ["ta'r)"])
 def test_da_tokenizer_splits_suffix_punct(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 2
@@ -32,15 +32,16 @@ def test_da_tokenizer_splits_suffix_punct(da_tokenizer, text):
     assert tokens[1].text == ")"
 
 
-@pytest.mark.parametrize('text,expected', [
-    ("(ta'r)", ["(", "ta'r", ")"]), ("'ta'r'", ["'", "ta'r", "'"])])
+@pytest.mark.parametrize(
+    "text,expected", [("(ta'r)", ["(", "ta'r", ")"]), ("'ta'r'", ["'", "ta'r", "'"])]
+)
 def test_da_tokenizer_splits_even_wrap(da_tokenizer, text, expected):
     tokens = da_tokenizer(text)
     assert len(tokens) == len(expected)
     assert [t.text for t in tokens] == expected
 
 
-@pytest.mark.parametrize('text', ["(ta'r?)"])
+@pytest.mark.parametrize("text", ["(ta'r?)"])
 def test_da_tokenizer_splits_uneven_wrap(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 4
@@ -50,15 +51,17 @@ def test_da_tokenizer_splits_uneven_wrap(da_tokenizer, text):
     assert tokens[3].text == ")"
 
 
-@pytest.mark.parametrize('text,expected', [
-    ("f.eks.", ["f.eks."]), ("fe.", ["fe", "."]), ("(f.eks.", ["(", "f.eks."])])
+@pytest.mark.parametrize(
+    "text,expected",
+    [("f.eks.", ["f.eks."]), ("fe.", ["fe", "."]), ("(f.eks.", ["(", "f.eks."])],
+)
 def test_da_tokenizer_splits_prefix_interact(da_tokenizer, text, expected):
     tokens = da_tokenizer(text)
     assert len(tokens) == len(expected)
     assert [t.text for t in tokens] == expected
 
 
-@pytest.mark.parametrize('text', ["f.eks.)"])
+@pytest.mark.parametrize("text", ["f.eks.)"])
 def test_da_tokenizer_splits_suffix_interact(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 2
@@ -66,7 +69,7 @@ def test_da_tokenizer_splits_suffix_interact(da_tokenizer, text):
     assert tokens[1].text == ")"
 
 
-@pytest.mark.parametrize('text', ["(f.eks.)"])
+@pytest.mark.parametrize("text", ["(f.eks.)"])
 def test_da_tokenizer_splits_even_wrap_interact(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 3
@@ -75,7 +78,7 @@ def test_da_tokenizer_splits_even_wrap_interact(da_tokenizer, text):
     assert tokens[2].text == ")"
 
 
-@pytest.mark.parametrize('text', ["(f.eks.?)"])
+@pytest.mark.parametrize("text", ["(f.eks.?)"])
 def test_da_tokenizer_splits_uneven_wrap_interact(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 4
@@ -85,19 +88,19 @@ def test_da_tokenizer_splits_uneven_wrap_interact(da_tokenizer, text):
     assert tokens[3].text == ")"
 
 
-@pytest.mark.parametrize('text', ["0,1-13,5", "0,0-0,1", "103,27-300", "1/2-3/4"])
+@pytest.mark.parametrize("text", ["0,1-13,5", "0,0-0,1", "103,27-300", "1/2-3/4"])
 def test_da_tokenizer_handles_numeric_range(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text', ["sort.Gul", "Hej.Verden"])
+@pytest.mark.parametrize("text", ["sort.Gul", "Hej.Verden"])
 def test_da_tokenizer_splits_period_infix(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["Hej,Verden", "en,to"])
+@pytest.mark.parametrize("text", ["Hej,Verden", "en,to"])
 def test_da_tokenizer_splits_comma_infix(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 3
@@ -106,20 +109,25 @@ def test_da_tokenizer_splits_comma_infix(da_tokenizer, text):
     assert tokens[2].text == text.split(",")[1]
 
 
-@pytest.mark.parametrize('text', ["sort...Gul", "sort...gul"])
+@pytest.mark.parametrize("text", ["sort...Gul", "sort...gul"])
 def test_da_tokenizer_splits_ellipsis_infix(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ['gå-på-mod', '4-hjulstræk', '100-Pfennig-frimærke', 'TV-2-spots', 'trofæ-vaeggen'])
+@pytest.mark.parametrize(
+    "text",
+    ["gå-på-mod", "4-hjulstræk", "100-Pfennig-frimærke", "TV-2-spots", "trofæ-vaeggen"],
+)
 def test_da_tokenizer_keeps_hyphens(da_tokenizer, text):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
 
 
 def test_da_tokenizer_splits_double_hyphen_infix(da_tokenizer):
-    tokens = da_tokenizer("Mange regler--eksempelvis bindestregs-reglerne--er komplicerede.")
+    tokens = da_tokenizer(
+        "Mange regler--eksempelvis bindestregs-reglerne--er komplicerede."
+    )
     assert len(tokens) == 9
     assert tokens[0].text == "Mange"
     assert tokens[1].text == "regler"
@@ -132,7 +140,9 @@ def test_da_tokenizer_splits_double_hyphen_infix(da_tokenizer):
 
 
 def test_da_tokenizer_handles_posessives_and_contractions(da_tokenizer):
-    tokens = da_tokenizer("'DBA's, Lars' og Liz' bil sku' sgu' ik' ha' en bule, det ka' han ik' li' mere', sagde hun.")
+    tokens = da_tokenizer(
+        "'DBA's, Lars' og Liz' bil sku' sgu' ik' ha' en bule, det ka' han ik' li' mere', sagde hun."
+    )
     assert len(tokens) == 25
     assert tokens[0].text == "'"
     assert tokens[1].text == "DBA's"

spacy/tests/lang/da/test_text.py

@@ -15,17 +15,29 @@ Rundt om ager og eng var der store skove, og midt i skovene dybe søer; jo, der
     assert len(tokens) == 84
 
 
-@pytest.mark.parametrize('text,match', [
-    ('10', True), ('1', True), ('10.000', True), ('10.00', True),
-    ('999,0', True), ('en', True), ('treoghalvfemsindstyvende', True), ('hundrede', True),
-    ('hund', False), (',', False), ('1/2', True)])
+@pytest.mark.parametrize(
+    "text,match",
+    [
+        ("10", True),
+        ("1", True),
+        ("10.000", True),
+        ("10.00", True),
+        ("999,0", True),
+        ("en", True),
+        ("treoghalvfemsindstyvende", True),
+        ("hundrede", True),
+        ("hund", False),
+        (",", False),
+        ("1/2", True),
+    ],
+)
 def test_lex_attrs_like_number(da_tokenizer, text, match):
     tokens = da_tokenizer(text)
     assert len(tokens) == 1
     assert tokens[0].like_num == match
 
 
-@pytest.mark.parametrize('word', ['elleve', 'første'])
+@pytest.mark.parametrize("word", ["elleve", "første"])
 def test_da_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/de/test_exceptions.py

@@ -4,13 +4,13 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["auf'm", "du's", "über'm", "wir's"])
+@pytest.mark.parametrize("text", ["auf'm", "du's", "über'm", "wir's"])
 def test_de_tokenizer_splits_contractions(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["z.B.", "d.h.", "Jan.", "Dez.", "Chr."])
+@pytest.mark.parametrize("text", ["z.B.", "d.h.", "Jan.", "Dez.", "Chr."])
 def test_de_tokenizer_handles_abbr(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 1
@@ -24,14 +24,16 @@ def test_de_tokenizer_handles_exc_in_text(de_tokenizer):
     assert tokens[2].lemma_ == "zur Zeit"
 
 
-@pytest.mark.parametrize('text,norms', [("vor'm", ["vor", "dem"]), ("du's", ["du", "es"])])
+@pytest.mark.parametrize(
+    "text,norms", [("vor'm", ["vor", "dem"]), ("du's", ["du", "es"])]
+)
 def test_de_tokenizer_norm_exceptions(de_tokenizer, text, norms):
     tokens = de_tokenizer(text)
     assert [token.norm_ for token in tokens] == norms
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize('text,norm', [("daß", "dass")])
+@pytest.mark.parametrize("text,norm", [("daß", "dass")])
 def test_de_lex_attrs_norm_exceptions(de_tokenizer, text, norm):
     tokens = de_tokenizer(text)
     assert tokens[0].norm_ == norm

spacy/tests/lang/de/test_lemma.py

@@ -4,13 +4,17 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('string,lemma', [
-    ('Abgehängten', 'Abgehängte'),
-    ('engagierte', 'engagieren'),
-    ('schließt', 'schließen'),
-    ('vorgebenden', 'vorgebend'),
-    ('die', 'der'),
-    ('Die', 'der')])
+@pytest.mark.parametrize(
+    "string,lemma",
+    [
+        ("Abgehängten", "Abgehängte"),
+        ("engagierte", "engagieren"),
+        ("schließt", "schließen"),
+        ("vorgebenden", "vorgebend"),
+        ("die", "der"),
+        ("Die", "der"),
+    ],
+)
 def test_de_lemmatizer_lookup_assigns(de_tokenizer, string, lemma):
     tokens = de_tokenizer(string)
     assert tokens[0].lemma_ == lemma

spacy/tests/lang/de/test_parser.py

@@ -7,10 +7,12 @@ from ...util import get_doc
 def test_de_parser_noun_chunks_standard_de(de_tokenizer):
     text = "Eine Tasse steht auf dem Tisch."
     heads = [1, 1, 0, -1, 1, -2, -4]
-    tags = ['ART', 'NN', 'VVFIN', 'APPR', 'ART', 'NN', '$.']
-    deps = ['nk', 'sb', 'ROOT', 'mo', 'nk', 'nk', 'punct']
+    tags = ["ART", "NN", "VVFIN", "APPR", "ART", "NN", "$."]
+    deps = ["nk", "sb", "ROOT", "mo", "nk", "nk", "punct"]
     tokens = de_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 2
     assert chunks[0].text_with_ws == "Eine Tasse "
@@ -20,10 +22,12 @@ def test_de_parser_noun_chunks_standard_de(de_tokenizer):
 def test_de_extended_chunk(de_tokenizer):
     text = "Die Sängerin singt mit einer Tasse Kaffee Arien."
     heads = [1, 1, 0, -1, 1, -2, -1, -5, -6]
-    tags = ['ART', 'NN', 'VVFIN', 'APPR', 'ART', 'NN', 'NN', 'NN', '$.']
-    deps = ['nk', 'sb', 'ROOT', 'mo', 'nk', 'nk', 'nk', 'oa', 'punct']
+    tags = ["ART", "NN", "VVFIN", "APPR", "ART", "NN", "NN", "NN", "$."]
+    deps = ["nk", "sb", "ROOT", "mo", "nk", "nk", "nk", "oa", "punct"]
     tokens = de_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 3
     assert chunks[0].text_with_ws == "Die Sängerin "

spacy/tests/lang/de/test_prefix_suffix_infix.py

@@ -4,79 +4,79 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["(unter)"])
+@pytest.mark.parametrize("text", ["(unter)"])
 def test_de_tokenizer_splits_no_special(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["unter'm"])
+@pytest.mark.parametrize("text", ["unter'm"])
 def test_de_tokenizer_splits_no_punct(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(unter'm"])
+@pytest.mark.parametrize("text", ["(unter'm"])
 def test_de_tokenizer_splits_prefix_punct(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["unter'm)"])
+@pytest.mark.parametrize("text", ["unter'm)"])
 def test_de_tokenizer_splits_suffix_punct(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(unter'm)"])
+@pytest.mark.parametrize("text", ["(unter'm)"])
 def test_de_tokenizer_splits_even_wrap(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text', ["(unter'm?)"])
+@pytest.mark.parametrize("text", ["(unter'm?)"])
 def test_de_tokenizer_splits_uneven_wrap(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 5
 
 
-@pytest.mark.parametrize('text,length', [("z.B.", 1), ("zb.", 2), ("(z.B.", 2)])
+@pytest.mark.parametrize("text,length", [("z.B.", 1), ("zb.", 2), ("(z.B.", 2)])
 def test_de_tokenizer_splits_prefix_interact(de_tokenizer, text, length):
     tokens = de_tokenizer(text)
     assert len(tokens) == length
 
 
-@pytest.mark.parametrize('text', ["z.B.)"])
+@pytest.mark.parametrize("text", ["z.B.)"])
 def test_de_tokenizer_splits_suffix_interact(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(z.B.)"])
+@pytest.mark.parametrize("text", ["(z.B.)"])
 def test_de_tokenizer_splits_even_wrap_interact(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(z.B.?)"])
+@pytest.mark.parametrize("text", ["(z.B.?)"])
 def test_de_tokenizer_splits_uneven_wrap_interact(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text', ["0.1-13.5", "0.0-0.1", "103.27-300"])
+@pytest.mark.parametrize("text", ["0.1-13.5", "0.0-0.1", "103.27-300"])
 def test_de_tokenizer_splits_numeric_range(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["blau.Rot", "Hallo.Welt"])
+@pytest.mark.parametrize("text", ["blau.Rot", "Hallo.Welt"])
 def test_de_tokenizer_splits_period_infix(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["Hallo,Welt", "eins,zwei"])
+@pytest.mark.parametrize("text", ["Hallo,Welt", "eins,zwei"])
 def test_de_tokenizer_splits_comma_infix(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
@@ -85,13 +85,13 @@ def test_de_tokenizer_splits_comma_infix(de_tokenizer, text):
     assert tokens[2].text == text.split(",")[1]
 
 
-@pytest.mark.parametrize('text', ["blau...Rot", "blau...rot"])
+@pytest.mark.parametrize("text", ["blau...Rot", "blau...rot"])
 def test_de_tokenizer_splits_ellipsis_infix(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ['Islam-Konferenz', 'Ost-West-Konflikt'])
+@pytest.mark.parametrize("text", ["Islam-Konferenz", "Ost-West-Konflikt"])
 def test_de_tokenizer_keeps_hyphens(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 1

spacy/tests/lang/de/test_text.py

@@ -22,19 +22,27 @@ Umfang kläglich dünnen Beine flimmerten ihm hilflos vor den Augen.
     assert len(tokens) == 109
 
 
-@pytest.mark.parametrize('text', [
-    "Donaudampfschifffahrtsgesellschaftskapitänsanwärterposten",
-    "Rindfleischetikettierungsüberwachungsaufgabenübertragungsgesetz",
-    "Kraftfahrzeug-Haftpflichtversicherung",
-    "Vakuum-Mittelfrequenz-Induktionsofen"])
+@pytest.mark.parametrize(
+    "text",
+    [
+        "Donaudampfschifffahrtsgesellschaftskapitänsanwärterposten",
+        "Rindfleischetikettierungsüberwachungsaufgabenübertragungsgesetz",
+        "Kraftfahrzeug-Haftpflichtversicherung",
+        "Vakuum-Mittelfrequenz-Induktionsofen",
+    ],
+)
 def test_de_tokenizer_handles_long_words(de_tokenizer, text):
     tokens = de_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text,length', [
-    ("»Was ist mit mir geschehen?«, dachte er.", 12),
-    ("“Dies frühzeitige Aufstehen”, dachte er, “macht einen ganz blödsinnig. ", 15)])
+@pytest.mark.parametrize(
+    "text,length",
+    [
+        ("»Was ist mit mir geschehen?«, dachte er.", 12),
+        ("“Dies frühzeitige Aufstehen”, dachte er, “macht einen ganz blödsinnig. ", 15),
+    ],
+)
 def test_de_tokenizer_handles_examples(de_tokenizer, text, length):
     tokens = de_tokenizer(text)
     assert len(tokens) == length

spacy/tests/lang/el/test_exception.py

@@ -4,7 +4,7 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["αριθ.", "τρισ.", "δισ.", "σελ."])
+@pytest.mark.parametrize("text", ["αριθ.", "τρισ.", "δισ.", "σελ."])
 def test_el_tokenizer_handles_abbr(el_tokenizer, text):
     tokens = el_tokenizer(text)
     assert len(tokens) == 1

spacy/tests/lang/el/test_text.py

@@ -13,12 +13,22 @@ def test_el_tokenizer_handles_long_text(el_tokenizer):
     assert len(tokens) == 54
 
 
-@pytest.mark.parametrize('text,length',[
-    ("Διοικητικά η Ελλάδα διαιρείται σε 13 Περιφέρειες.", 8),
-    ("Η εκπαίδευση στην Ελλάδα χωρίζεται κυρίως σε τρία επίπεδα.", 10),
-    ("Η Ελλάδα είναι μία από τις χώρες της Ευρωπαϊκής Ένωσης (ΕΕ) που διαθέτει σηµαντικό ορυκτό πλούτο.", 19),
-    ("Η ναυτιλία αποτέλεσε ένα σημαντικό στοιχείο της Ελληνικής οικονομικής δραστηριότητας από τα αρχαία χρόνια.", 15),
-    ("Η Ελλάδα είναι μέλος σε αρκετούς διεθνείς οργανισμούς.", 9)])
-def test_el_tokenizer_handles_cnts(el_tokenizer,text, length):
+@pytest.mark.parametrize(
+    "text,length",
+    [
+        ("Διοικητικά η Ελλάδα διαιρείται σε 13 Περιφέρειες.", 8),
+        ("Η εκπαίδευση στην Ελλάδα χωρίζεται κυρίως σε τρία επίπεδα.", 10),
+        (
+            "Η Ελλάδα είναι μία από τις χώρες της Ευρωπαϊκής Ένωσης (ΕΕ) που διαθέτει σηµαντικό ορυκτό πλούτο.",
+            19,
+        ),
+        (
+            "Η ναυτιλία αποτέλεσε ένα σημαντικό στοιχείο της Ελληνικής οικονομικής δραστηριότητας από τα αρχαία χρόνια.",
+            15,
+        ),
+        ("Η Ελλάδα είναι μέλος σε αρκετούς διεθνείς οργανισμούς.", 9),
+    ],
+)
+def test_el_tokenizer_handles_cnts(el_tokenizer, text, length):
     tokens = el_tokenizer(text)
     assert len(tokens) == length

spacy/tests/lang/en/test_customized_tokenizer.py

@@ -12,29 +12,66 @@ from spacy.util import compile_infix_regex
 def custom_en_tokenizer(en_vocab):
     prefix_re = compile_prefix_regex(English.Defaults.prefixes)
     suffix_re = compile_suffix_regex(English.Defaults.suffixes)
-    custom_infixes = ['\.\.\.+',
-                      '(?<=[0-9])-(?=[0-9])',
-                      # '(?<=[0-9]+),(?=[0-9]+)',
-                      '[0-9]+(,[0-9]+)+',
-                      '[\[\]!&:,()\*—–\/-]']
+    custom_infixes = [
+        "\.\.\.+",
+        "(?<=[0-9])-(?=[0-9])",
+        # '(?<=[0-9]+),(?=[0-9]+)',
+        "[0-9]+(,[0-9]+)+",
+        "[\[\]!&:,()\*—–\/-]",
+    ]
     infix_re = compile_infix_regex(custom_infixes)
-    return Tokenizer(en_vocab,
-                     English.Defaults.tokenizer_exceptions,
-                     prefix_re.search,
-                     suffix_re.search,
-                     infix_re.finditer,
-                     token_match=None)
+    return Tokenizer(
+        en_vocab,
+        English.Defaults.tokenizer_exceptions,
+        prefix_re.search,
+        suffix_re.search,
+        infix_re.finditer,
+        token_match=None,
+    )
 
 
 def test_en_customized_tokenizer_handles_infixes(custom_en_tokenizer):
     sentence = "The 8 and 10-county definitions are not used for the greater Southern California Megaregion."
     context = [word.text for word in custom_en_tokenizer(sentence)]
-    assert context == ['The', '8', 'and', '10', '-', 'county', 'definitions',
-                       'are', 'not', 'used', 'for', 'the', 'greater',
-                       'Southern', 'California', 'Megaregion', '.']
+    assert context == [
+        "The",
+        "8",
+        "and",
+        "10",
+        "-",
+        "county",
+        "definitions",
+        "are",
+        "not",
+        "used",
+        "for",
+        "the",
+        "greater",
+        "Southern",
+        "California",
+        "Megaregion",
+        ".",
+    ]
     # the trailing '-' may cause Assertion Error
     sentence = "The 8- and 10-county definitions are not used for the greater Southern California Megaregion."
     context = [word.text for word in custom_en_tokenizer(sentence)]
-    assert context == ['The', '8', '-', 'and', '10', '-', 'county',
-                       'definitions', 'are', 'not', 'used', 'for', 'the',
-                       'greater', 'Southern', 'California', 'Megaregion', '.']
+    assert context == [
+        "The",
+        "8",
+        "-",
+        "and",
+        "10",
+        "-",
+        "county",
+        "definitions",
+        "are",
+        "not",
+        "used",
+        "for",
+        "the",
+        "greater",
+        "Southern",
+        "California",
+        "Megaregion",
+        ".",
+    ]

spacy/tests/lang/en/test_exceptions.py

@@ -15,13 +15,15 @@ def test_en_tokenizer_handles_basic_contraction(en_tokenizer):
     assert tokens[4].text == "!"
 
 
-@pytest.mark.parametrize('text', ["`ain't", '''"isn't''', "can't!"])
+@pytest.mark.parametrize("text", ["`ain't", """"isn't""", "can't!"])
 def test_en_tokenizer_handles_basic_contraction_punct(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text_poss,text', [("Robin's", "Robin"), ("Alexis's", "Alexis")])
+@pytest.mark.parametrize(
+    "text_poss,text", [("Robin's", "Robin"), ("Alexis's", "Alexis")]
+)
 def test_en_tokenizer_handles_poss_contraction(en_tokenizer, text_poss, text):
     tokens = en_tokenizer(text_poss)
     assert len(tokens) == 2
@@ -29,7 +31,7 @@ def test_en_tokenizer_handles_poss_contraction(en_tokenizer, text_poss, text):
     assert tokens[1].text == "'s"
 
 
-@pytest.mark.parametrize('text', ["schools'", "Alexis'"])
+@pytest.mark.parametrize("text", ["schools'", "Alexis'"])
 def test_en_tokenizer_splits_trailing_apos(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
@@ -37,14 +39,14 @@ def test_en_tokenizer_splits_trailing_apos(en_tokenizer, text):
     assert tokens[1].text == "'"
 
 
-@pytest.mark.parametrize('text', ["'em", "nothin'", "ol'"])
+@pytest.mark.parametrize("text", ["'em", "nothin'", "ol'"])
 def test_en_tokenizer_doesnt_split_apos_exc(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 1
     assert tokens[0].text == text
 
 
-@pytest.mark.parametrize('text', ["we'll", "You'll", "there'll"])
+@pytest.mark.parametrize("text", ["we'll", "You'll", "there'll"])
 def test_en_tokenizer_handles_ll_contraction(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
@@ -53,7 +55,9 @@ def test_en_tokenizer_handles_ll_contraction(en_tokenizer, text):
     assert tokens[1].lemma_ == "will"
 
 
-@pytest.mark.parametrize('text_lower,text_title', [("can't", "Can't"), ("ain't", "Ain't")])
+@pytest.mark.parametrize(
+    "text_lower,text_title", [("can't", "Can't"), ("ain't", "Ain't")]
+)
 def test_en_tokenizer_handles_capitalization(en_tokenizer, text_lower, text_title):
     tokens_lower = en_tokenizer(text_lower)
     tokens_title = en_tokenizer(text_title)
@@ -62,21 +66,23 @@ def test_en_tokenizer_handles_capitalization(en_tokenizer, text_lower, text_titl
     assert tokens_lower[1].text == tokens_title[1].text
 
 
-@pytest.mark.parametrize('pron', ["I", "You", "He", "She", "It", "We", "They"])
-@pytest.mark.parametrize('contraction', ["'ll", "'d"])
+@pytest.mark.parametrize("pron", ["I", "You", "He", "She", "It", "We", "They"])
+@pytest.mark.parametrize("contraction", ["'ll", "'d"])
 def test_en_tokenizer_keeps_title_case(en_tokenizer, pron, contraction):
     tokens = en_tokenizer(pron + contraction)
     assert tokens[0].text == pron
     assert tokens[1].text == contraction
 
 
-@pytest.mark.parametrize('exc', ["Ill", "ill", "Hell", "hell", "Well", "well"])
+@pytest.mark.parametrize("exc", ["Ill", "ill", "Hell", "hell", "Well", "well"])
 def test_en_tokenizer_excludes_ambiguous(en_tokenizer, exc):
     tokens = en_tokenizer(exc)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('wo_punct,w_punct', [("We've", "``We've"), ("couldn't", "couldn't)")])
+@pytest.mark.parametrize(
+    "wo_punct,w_punct", [("We've", "``We've"), ("couldn't", "couldn't)")]
+)
 def test_en_tokenizer_splits_defined_punct(en_tokenizer, wo_punct, w_punct):
     tokens = en_tokenizer(wo_punct)
     assert len(tokens) == 2
@@ -84,7 +90,7 @@ def test_en_tokenizer_splits_defined_punct(en_tokenizer, wo_punct, w_punct):
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["e.g.", "p.m.", "Jan.", "Dec.", "Inc."])
+@pytest.mark.parametrize("text", ["e.g.", "p.m.", "Jan.", "Dec.", "Inc."])
 def test_en_tokenizer_handles_abbr(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 1
@@ -97,20 +103,24 @@ def test_en_tokenizer_handles_exc_in_text(en_tokenizer):
     assert tokens[3].text == "i.e."
 
 
-@pytest.mark.parametrize('text', ["1am", "12a.m.", "11p.m.", "4pm"])
+@pytest.mark.parametrize("text", ["1am", "12a.m.", "11p.m.", "4pm"])
 def test_en_tokenizer_handles_times(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
     assert tokens[1].lemma_ in ["a.m.", "p.m."]
 
 
-@pytest.mark.parametrize('text,norms', [("I'm", ["i", "am"]), ("shan't", ["shall", "not"])])
+@pytest.mark.parametrize(
+    "text,norms", [("I'm", ["i", "am"]), ("shan't", ["shall", "not"])]
+)
 def test_en_tokenizer_norm_exceptions(en_tokenizer, text, norms):
     tokens = en_tokenizer(text)
     assert [token.norm_ for token in tokens] == norms
 
 
-@pytest.mark.parametrize('text,norm', [("radicalised", "radicalized"), ("cuz", "because")])
+@pytest.mark.parametrize(
+    "text,norm", [("radicalised", "radicalized"), ("cuz", "because")]
+)
 def test_en_lex_attrs_norm_exceptions(en_tokenizer, text, norm):
     tokens = en_tokenizer(text)
     assert tokens[0].norm_ == norm

spacy/tests/lang/en/test_noun_chunks.py

@@ -12,14 +12,25 @@ from ...util import get_doc
 def test_en_noun_chunks_not_nested(en_tokenizer):
     text = "Peter has chronic command and control issues"
     heads = [1, 0, 4, 3, -1, -2, -5]
-    deps = ['nsubj', 'ROOT', 'amod', 'nmod', 'cc', 'conj', 'dobj']
+    deps = ["nsubj", "ROOT", "amod", "nmod", "cc", "conj", "dobj"]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     tokens.from_array(
         [HEAD, DEP],
-        numpy.asarray([[1, nsubj], [0, root], [4, amod], [3, nmod], [-1, cc],
-                       [-2, conj], [-5, dobj]], dtype='uint64'))
-    tokens.noun_chunks_iterator = SYNTAX_ITERATORS['noun_chunks']
+        numpy.asarray(
+            [
+                [1, nsubj],
+                [0, root],
+                [4, amod],
+                [3, nmod],
+                [-1, cc],
+                [-2, conj],
+                [-5, dobj],
+            ],
+            dtype="uint64",
+        ),
+    )
+    tokens.noun_chunks_iterator = SYNTAX_ITERATORS["noun_chunks"]
     word_occurred = {}
     for chunk in tokens.noun_chunks:
         for word in chunk:

spacy/tests/lang/en/test_parser.py

@@ -7,22 +7,28 @@ from ...util import get_doc
 def test_en_parser_noun_chunks_standard(en_tokenizer):
     text = "A base phrase should be recognized."
     heads = [2, 1, 3, 2, 1, 0, -1]
-    tags = ['DT', 'JJ', 'NN', 'MD', 'VB', 'VBN', '.']
-    deps = ['det', 'amod', 'nsubjpass', 'aux', 'auxpass', 'ROOT', 'punct']
+    tags = ["DT", "JJ", "NN", "MD", "VB", "VBN", "."]
+    deps = ["det", "amod", "nsubjpass", "aux", "auxpass", "ROOT", "punct"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 1
     assert chunks[0].text_with_ws == "A base phrase "
 
 
 def test_en_parser_noun_chunks_coordinated(en_tokenizer):
+    # fmt: off
     text = "A base phrase and a good phrase are often the same."
     heads = [2, 1, 5, -1, 2, 1, -4, 0, -1, 1, -3, -4]
-    tags = ['DT', 'NN', 'NN', 'CC', 'DT', 'JJ', 'NN', 'VBP', 'RB', 'DT', 'JJ', '.']
-    deps = ['det', 'compound', 'nsubj', 'cc', 'det', 'amod', 'conj', 'ROOT', 'advmod', 'det', 'attr', 'punct']
+    tags = ["DT", "NN", "NN", "CC", "DT", "JJ", "NN", "VBP", "RB", "DT", "JJ", "."]
+    deps = ["det", "compound", "nsubj", "cc", "det", "amod", "conj", "ROOT", "advmod", "det", "attr", "punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 2
     assert chunks[0].text_with_ws == "A base phrase "
@@ -32,10 +38,12 @@ def test_en_parser_noun_chunks_coordinated(en_tokenizer):
 def test_en_parser_noun_chunks_pp_chunks(en_tokenizer):
     text = "A phrase with another phrase occurs."
     heads = [1, 4, -1, 1, -2, 0, -1]
-    tags = ['DT', 'NN', 'IN', 'DT', 'NN', 'VBZ', '.']
-    deps = ['det', 'nsubj', 'prep', 'det', 'pobj', 'ROOT', 'punct']
+    tags = ["DT", "NN", "IN", "DT", "NN", "VBZ", "."]
+    deps = ["det", "nsubj", "prep", "det", "pobj", "ROOT", "punct"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 2
     assert chunks[0].text_with_ws == "A phrase "
@@ -43,12 +51,16 @@ def test_en_parser_noun_chunks_pp_chunks(en_tokenizer):
 
 
 def test_en_parser_noun_chunks_appositional_modifiers(en_tokenizer):
+    # fmt: off
     text = "Sam, my brother, arrived to the house."
     heads = [5, -1, 1, -3, -4, 0, -1, 1, -2, -4]
-    tags = ['NNP', ',', 'PRP$', 'NN', ',', 'VBD', 'IN', 'DT', 'NN', '.']
-    deps = ['nsubj', 'punct', 'poss', 'appos', 'punct', 'ROOT', 'prep', 'det', 'pobj', 'punct']
+    tags = ["NNP", ",", "PRP$", "NN", ",", "VBD", "IN", "DT", "NN", "."]
+    deps = ["nsubj", "punct", "poss", "appos", "punct", "ROOT", "prep", "det", "pobj", "punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 3
     assert chunks[0].text_with_ws == "Sam "
@@ -59,10 +71,12 @@ def test_en_parser_noun_chunks_appositional_modifiers(en_tokenizer):
 def test_en_parser_noun_chunks_dative(en_tokenizer):
     text = "She gave Bob a raise."
     heads = [1, 0, -1, 1, -3, -4]
-    tags = ['PRP', 'VBD', 'NNP', 'DT', 'NN', '.']
-    deps = ['nsubj', 'ROOT', 'dative', 'det', 'dobj', 'punct']
+    tags = ["PRP", "VBD", "NNP", "DT", "NN", "."]
+    deps = ["nsubj", "ROOT", "dative", "det", "dobj", "punct"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
+    )
     chunks = list(doc.noun_chunks)
     assert len(chunks) == 3
     assert chunks[0].text_with_ws == "She "

spacy/tests/lang/en/test_prefix_suffix_infix.py

@@ -4,85 +4,85 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["(can)"])
+@pytest.mark.parametrize("text", ["(can)"])
 def test_en_tokenizer_splits_no_special(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["can't"])
+@pytest.mark.parametrize("text", ["can't"])
 def test_en_tokenizer_splits_no_punct(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(can't"])
+@pytest.mark.parametrize("text", ["(can't"])
 def test_en_tokenizer_splits_prefix_punct(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["can't)"])
+@pytest.mark.parametrize("text", ["can't)"])
 def test_en_tokenizer_splits_suffix_punct(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(can't)"])
+@pytest.mark.parametrize("text", ["(can't)"])
 def test_en_tokenizer_splits_even_wrap(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text', ["(can't?)"])
+@pytest.mark.parametrize("text", ["(can't?)"])
 def test_en_tokenizer_splits_uneven_wrap(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 5
 
 
-@pytest.mark.parametrize('text,length', [("U.S.", 1), ("us.", 2), ("(U.S.", 2)])
+@pytest.mark.parametrize("text,length", [("U.S.", 1), ("us.", 2), ("(U.S.", 2)])
 def test_en_tokenizer_splits_prefix_interact(en_tokenizer, text, length):
     tokens = en_tokenizer(text)
     assert len(tokens) == length
 
 
-@pytest.mark.parametrize('text', ["U.S.)"])
+@pytest.mark.parametrize("text", ["U.S.)"])
 def test_en_tokenizer_splits_suffix_interact(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(U.S.)"])
+@pytest.mark.parametrize("text", ["(U.S.)"])
 def test_en_tokenizer_splits_even_wrap_interact(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(U.S.?)"])
+@pytest.mark.parametrize("text", ["(U.S.?)"])
 def test_en_tokenizer_splits_uneven_wrap_interact(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text', ["best-known"])
+@pytest.mark.parametrize("text", ["best-known"])
 def test_en_tokenizer_splits_hyphens(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["0.1-13.5", "0.0-0.1", "103.27-300"])
+@pytest.mark.parametrize("text", ["0.1-13.5", "0.0-0.1", "103.27-300"])
 def test_en_tokenizer_splits_numeric_range(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["best.Known", "Hello.World"])
+@pytest.mark.parametrize("text", ["best.Known", "Hello.World"])
 def test_en_tokenizer_splits_period_infix(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["Hello,world", "one,two"])
+@pytest.mark.parametrize("text", ["Hello,world", "one,two"])
 def test_en_tokenizer_splits_comma_infix(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
@@ -91,7 +91,7 @@ def test_en_tokenizer_splits_comma_infix(en_tokenizer, text):
     assert tokens[2].text == text.split(",")[1]
 
 
-@pytest.mark.parametrize('text', ["best...Known", "best...known"])
+@pytest.mark.parametrize("text", ["best...Known", "best...known"])
 def test_en_tokenizer_splits_ellipsis_infix(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 3
@@ -126,8 +126,10 @@ def test_en_tokenizer_splits_period_abbr(en_tokenizer):
 @pytest.mark.xfail
 def test_en_tokenizer_splits_em_dash_infix(en_tokenizer):
     # Re Issue #225
-    tokens = en_tokenizer("""Will this road take me to Puddleton?\u2014No, """
-                          """you'll have to walk there.\u2014Ariel.""")
+    tokens = en_tokenizer(
+        """Will this road take me to Puddleton?\u2014No, """
+        """you'll have to walk there.\u2014Ariel."""
+    )
     assert tokens[6].text == "Puddleton"
     assert tokens[7].text == "?"
     assert tokens[8].text == "\u2014"

spacy/tests/lang/en/test_punct.py

@@ -6,19 +6,19 @@ from spacy.util import compile_prefix_regex
 from spacy.lang.punctuation import TOKENIZER_PREFIXES
 
 
-PUNCT_OPEN = ['(', '[', '{', '*']
-PUNCT_CLOSE = [')', ']', '}', '*']
-PUNCT_PAIRED = [('(', ')'),  ('[', ']'), ('{', '}'), ('*', '*')]
+PUNCT_OPEN = ["(", "[", "{", "*"]
+PUNCT_CLOSE = [")", "]", "}", "*"]
+PUNCT_PAIRED = [("(", ")"), ("[", "]"), ("{", "}"), ("*", "*")]
 
 
-@pytest.mark.parametrize('text', ["(", "((", "<"])
+@pytest.mark.parametrize("text", ["(", "((", "<"])
 def test_en_tokenizer_handles_only_punct(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == len(text)
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_open_punct(en_tokenizer, punct, text):
     tokens = en_tokenizer(punct + text)
     assert len(tokens) == 2
@@ -26,8 +26,8 @@ def test_en_tokenizer_splits_open_punct(en_tokenizer, punct, text):
     assert tokens[1].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_close_punct(en_tokenizer, punct, text):
     tokens = en_tokenizer(text + punct)
     assert len(tokens) == 2
@@ -35,9 +35,9 @@ def test_en_tokenizer_splits_close_punct(en_tokenizer, punct, text):
     assert tokens[1].text == punct
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('punct_add', ["`"])
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("punct_add", ["`"])
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_two_diff_open_punct(en_tokenizer, punct, punct_add, text):
     tokens = en_tokenizer(punct + punct_add + text)
     assert len(tokens) == 3
@@ -46,9 +46,9 @@ def test_en_tokenizer_splits_two_diff_open_punct(en_tokenizer, punct, punct_add,
     assert tokens[2].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('punct_add', ["'"])
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("punct_add", ["'"])
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_two_diff_close_punct(en_tokenizer, punct, punct_add, text):
     tokens = en_tokenizer(text + punct + punct_add)
     assert len(tokens) == 3
@@ -57,8 +57,8 @@ def test_en_tokenizer_splits_two_diff_close_punct(en_tokenizer, punct, punct_add
     assert tokens[2].text == punct_add
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_same_open_punct(en_tokenizer, punct, text):
     tokens = en_tokenizer(punct + punct + punct + text)
     assert len(tokens) == 4
@@ -66,8 +66,8 @@ def test_en_tokenizer_splits_same_open_punct(en_tokenizer, punct, text):
     assert tokens[3].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("text", ["Hello"])
 def test_en_tokenizer_splits_same_close_punct(en_tokenizer, punct, text):
     tokens = en_tokenizer(text + punct + punct + punct)
     assert len(tokens) == 4
@@ -75,14 +75,14 @@ def test_en_tokenizer_splits_same_close_punct(en_tokenizer, punct, text):
     assert tokens[1].text == punct
 
 
-@pytest.mark.parametrize('text', ["'The"])
+@pytest.mark.parametrize("text", ["'The"])
 def test_en_tokenizer_splits_open_appostrophe(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
     assert tokens[0].text == "'"
 
 
-@pytest.mark.parametrize('text', ["Hello''"])
+@pytest.mark.parametrize("text", ["Hello''"])
 def test_en_tokenizer_splits_double_end_quote(en_tokenizer, text):
     tokens = en_tokenizer(text)
     assert len(tokens) == 2
@@ -90,10 +90,11 @@ def test_en_tokenizer_splits_double_end_quote(en_tokenizer, text):
     assert len(tokens_punct) == 1
 
 
-@pytest.mark.parametrize('punct_open,punct_close', PUNCT_PAIRED)
-@pytest.mark.parametrize('text', ["Hello"])
-def test_en_tokenizer_splits_open_close_punct(en_tokenizer, punct_open,
-                                           punct_close, text):
+@pytest.mark.parametrize("punct_open,punct_close", PUNCT_PAIRED)
+@pytest.mark.parametrize("text", ["Hello"])
+def test_en_tokenizer_splits_open_close_punct(
+    en_tokenizer, punct_open, punct_close, text
+):
     tokens = en_tokenizer(punct_open + text + punct_close)
     assert len(tokens) == 3
     assert tokens[0].text == punct_open
@@ -101,11 +102,12 @@ def test_en_tokenizer_splits_open_close_punct(en_tokenizer, punct_open,
     assert tokens[2].text == punct_close
 
 
-@pytest.mark.parametrize('punct_open,punct_close', PUNCT_PAIRED)
-@pytest.mark.parametrize('punct_open2,punct_close2', [("`", "'")])
-@pytest.mark.parametrize('text', ["Hello"])
-def test_en_tokenizer_two_diff_punct(en_tokenizer, punct_open, punct_close,
-                                  punct_open2, punct_close2, text):
+@pytest.mark.parametrize("punct_open,punct_close", PUNCT_PAIRED)
+@pytest.mark.parametrize("punct_open2,punct_close2", [("`", "'")])
+@pytest.mark.parametrize("text", ["Hello"])
+def test_en_tokenizer_two_diff_punct(
+    en_tokenizer, punct_open, punct_close, punct_open2, punct_close2, text
+):
     tokens = en_tokenizer(punct_open2 + punct_open + text + punct_close + punct_close2)
     assert len(tokens) == 5
     assert tokens[0].text == punct_open2
@@ -115,7 +117,7 @@ def test_en_tokenizer_two_diff_punct(en_tokenizer, punct_open, punct_close,
     assert tokens[4].text == punct_close2
 
 
-@pytest.mark.parametrize('text,punct', [("(can't", "(")])
+@pytest.mark.parametrize("text,punct", [("(can't", "(")])
 def test_en_tokenizer_splits_pre_punct_regex(text, punct):
     en_search_prefixes = compile_prefix_regex(TOKENIZER_PREFIXES).search
     match = en_search_prefixes(text)

spacy/tests/lang/en/test_sbd.py

@@ -6,8 +6,8 @@ import pytest
 from ...util import get_doc, apply_transition_sequence
 
 
-@pytest.mark.parametrize('text', ["A test sentence"])
-@pytest.mark.parametrize('punct', ['.', '!', '?', ''])
+@pytest.mark.parametrize("text", ["A test sentence"])
+@pytest.mark.parametrize("punct", [".", "!", "?", ""])
 def test_en_sbd_single_punct(en_tokenizer, text, punct):
     heads = [2, 1, 0, -1] if punct else [2, 1, 0]
     tokens = en_tokenizer(text + punct)
@@ -19,16 +19,18 @@ def test_en_sbd_single_punct(en_tokenizer, text, punct):
 
 @pytest.mark.xfail
 def test_en_sentence_breaks(en_tokenizer, en_parser):
+    # fmt: off
     text = "This is a sentence . This is another one ."
     heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3]
-    deps = ['nsubj', 'ROOT', 'det', 'attr', 'punct', 'nsubj', 'ROOT', 'det',
-            'attr', 'punct']
-    transition = ['L-nsubj', 'S', 'L-det', 'R-attr', 'D', 'R-punct', 'B-ROOT',
-                  'L-nsubj', 'S', 'L-attr', 'R-attr', 'D', 'R-punct']
+    deps = ["nsubj", "ROOT", "det", "attr", "punct", "nsubj", "ROOT", "det",
+            "attr", "punct"]
+    transition = ["L-nsubj", "S", "L-det", "R-attr", "D", "R-punct", "B-ROOT",
+                  "L-nsubj", "S", "L-attr", "R-attr", "D", "R-punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     apply_transition_sequence(en_parser, doc, transition)
     assert len(list(doc.sents)) == 2
     for token in doc:
         assert token.dep != 0 or token.is_space
-    assert [token.head.i for token in doc ] == [1, 1, 3, 1, 1, 6, 6, 8, 6, 6]
+    assert [token.head.i for token in doc] == [1, 1, 3, 1, 1, 6, 6, 8, 6, 6]

spacy/tests/lang/en/test_tagger.py

@@ -6,10 +6,10 @@ from ...util import get_doc
 
 def test_en_tagger_load_morph_exc(en_tokenizer):
     text = "I like his style."
-    tags = ['PRP', 'VBP', 'PRP$', 'NN', '.']
-    morph_exc = {'VBP': {'like': {'lemma': 'luck'}}}
+    tags = ["PRP", "VBP", "PRP$", "NN", "."]
+    morph_exc = {"VBP": {"like": {"lemma": "luck"}}}
     en_tokenizer.vocab.morphology.load_morph_exceptions(morph_exc)
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], tags=tags)
-    assert doc[1].tag_ == 'VBP'
-    assert doc[1].lemma_ == 'luck'
+    assert doc[1].tag_ == "VBP"
+    assert doc[1].lemma_ == "luck"

spacy/tests/lang/en/test_text.py

@@ -20,30 +20,48 @@ untimely death" of the rapier-tongued Scottish barrister and parliamentarian.
     assert len(tokens) == 76
 
 
-@pytest.mark.parametrize('text,length', [
-    ("The U.S. Army likes Shock and Awe.", 8),
-    ("U.N. regulations are not a part of their concern.", 10),
-    ("“Isn't it?”", 6),
-    ("""Yes! "I'd rather have a walk", Ms. Comble sighed. """, 15),
-    ("""'Me too!', Mr. P. Delaware cried. """, 11),
-    ("They ran about 10km.", 6),
-    pytest.mark.xfail(("But then the 6,000-year ice age came...", 10))])
+@pytest.mark.parametrize(
+    "text,length",
+    [
+        ("The U.S. Army likes Shock and Awe.", 8),
+        ("U.N. regulations are not a part of their concern.", 10),
+        ("“Isn't it?”", 6),
+        ("""Yes! "I'd rather have a walk", Ms. Comble sighed. """, 15),
+        ("""'Me too!', Mr. P. Delaware cried. """, 11),
+        ("They ran about 10km.", 6),
+        pytest.param(
+            "But then the 6,000-year ice age came...", 10, marks=pytest.mark.xfail()
+        ),
+    ],
+)
 def test_en_tokenizer_handles_cnts(en_tokenizer, text, length):
     tokens = en_tokenizer(text)
     assert len(tokens) == length
 
 
-@pytest.mark.parametrize('text,match', [
-    ('10', True), ('1', True), ('10,000', True), ('10,00', True),
-    ('999.0', True), ('one', True), ('two', True), ('billion', True),
-    ('dog', False), (',', False), ('1/2', True)])
+@pytest.mark.parametrize(
+    "text,match",
+    [
+        ("10", True),
+        ("1", True),
+        ("10,000", True),
+        ("10,00", True),
+        ("999.0", True),
+        ("one", True),
+        ("two", True),
+        ("billion", True),
+        ("dog", False),
+        (",", False),
+        ("1/2", True),
+    ],
+)
 def test_lex_attrs_like_number(en_tokenizer, text, match):
     tokens = en_tokenizer(text)
     assert len(tokens) == 1
     assert tokens[0].like_num == match
 
 
-@pytest.mark.parametrize('word', ['eleven'])
+@pytest.mark.parametrize("word", ["eleven"])
 def test_en_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/es/test_exception.py

@@ -4,11 +4,15 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text,lemma', [
-    ("aprox.", "aproximadamente"),
-    ("esq.", "esquina"),
-    ("pág.", "página"),
-    ("p.ej.", "por ejemplo")])
+@pytest.mark.parametrize(
+    "text,lemma",
+    [
+        ("aprox.", "aproximadamente"),
+        ("esq.", "esquina"),
+        ("pág.", "página"),
+        ("p.ej.", "por ejemplo"),
+    ],
+)
 def test_es_tokenizer_handles_abbr(es_tokenizer, text, lemma):
     tokens = es_tokenizer(text)
     assert len(tokens) == 1

spacy/tests/lang/es/test_text.py

@@ -20,12 +20,16 @@ en Montevideo y que pregona las bondades de la vida austera."""
     assert len(tokens) == 90
 
 
-@pytest.mark.parametrize('text,length', [
-    ("¿Por qué José Mujica?", 6),
-    ("“¿Oh no?”", 6),
-    ("""¡Sí! "Vámonos", contestó José Arcadio Buendía""", 11),
-    ("Corrieron aprox. 10km.", 5),
-    ("Y entonces por qué...", 5)])
+@pytest.mark.parametrize(
+    "text,length",
+    [
+        ("¿Por qué José Mujica?", 6),
+        ("“¿Oh no?”", 6),
+        ("""¡Sí! "Vámonos", contestó José Arcadio Buendía""", 11),
+        ("Corrieron aprox. 10km.", 5),
+        ("Y entonces por qué...", 5),
+    ],
+)
 def test_es_tokenizer_handles_cnts(es_tokenizer, text, length):
     tokens = es_tokenizer(text)
     assert len(tokens) == length

spacy/tests/lang/fi/test_tokenizer.py

@@ -5,12 +5,15 @@ import pytest
 
 
 ABBREVIATION_TESTS = [
-    ('Hyvää uutta vuotta t. siht. Niemelä!', ['Hyvää', 'uutta', 'vuotta', 't.', 'siht.', 'Niemelä', '!']),
-    ('Paino on n. 2.2 kg', ['Paino', 'on', 'n.', '2.2', 'kg'])
+    (
+        "Hyvää uutta vuotta t. siht. Niemelä!",
+        ["Hyvää", "uutta", "vuotta", "t.", "siht.", "Niemelä", "!"],
+    ),
+    ("Paino on n. 2.2 kg", ["Paino", "on", "n.", "2.2", "kg"]),
 ]
 
 
-@pytest.mark.parametrize('text,expected_tokens', ABBREVIATION_TESTS)
+@pytest.mark.parametrize("text,expected_tokens", ABBREVIATION_TESTS)
 def test_fi_tokenizer_handles_testcases(fi_tokenizer, text, expected_tokens):
     tokens = fi_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]

spacy/tests/lang/fr/test_exceptions.py

@@ -2,26 +2,26 @@
 from __future__ import unicode_literals
 
 import pytest
-from .... import util
-
-@pytest.fixture(scope='module')
-def fr_tokenizer():
-    return util.get_lang_class('fr').Defaults.create_tokenizer()
 
 
-@pytest.mark.parametrize('text', [
-    "aujourd'hui", "Aujourd'hui", "prud'hommes", "prud’hommal"])
+@pytest.mark.parametrize(
+    "text", ["aujourd'hui", "Aujourd'hui", "prud'hommes", "prud’hommal"]
+)
 def test_fr_tokenizer_infix_exceptions(fr_tokenizer, text):
     tokens = fr_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text,lemma', [
-    ("janv.", "janvier"),
-    ("juill.", "juillet"),
-    ("Dr.", "docteur"),
-    ("av.", "avant"),
-    ("sept.", "septembre")])
+@pytest.mark.parametrize(
+    "text,lemma",
+    [
+        ("janv.", "janvier"),
+        ("juill.", "juillet"),
+        ("Dr.", "docteur"),
+        ("av.", "avant"),
+        ("sept.", "septembre"),
+    ],
+)
 def test_fr_tokenizer_handles_abbr(fr_tokenizer, text, lemma):
     tokens = fr_tokenizer(text)
     assert len(tokens) == 1
@@ -57,6 +57,7 @@ def test_fr_tokenizer_handles_title(fr_tokenizer):
     assert tokens[2].lemma_ == "ce"
 
 
+@pytest.mark.xfail
 def test_fr_tokenizer_handles_title_2(fr_tokenizer):
     text = "Est-ce pas génial?"
     tokens = fr_tokenizer(text)
@@ -65,7 +66,7 @@ def test_fr_tokenizer_handles_title_2(fr_tokenizer):
     assert tokens[0].lemma_ == "être"
 
 
-def test_fr_tokenizer_handles_title_2(fr_tokenizer):
+def test_fr_tokenizer_handles_title_3(fr_tokenizer):
     text = "Qu'est-ce que tu fais?"
     tokens = fr_tokenizer(text)
     assert len(tokens) == 7

spacy/tests/lang/fr/test_lemmatization.py

@@ -16,7 +16,9 @@ def test_fr_lemmatizer_noun_verb_2(fr_tokenizer):
     assert tokens[4].lemma_ == "être"
 
 
-@pytest.mark.xfail(reason="Costaricienne TAG is PROPN instead of NOUN and spacy don't lemmatize PROPN")
+@pytest.mark.xfail(
+    reason="Costaricienne TAG is PROPN instead of NOUN and spacy don't lemmatize PROPN"
+)
 def test_fr_lemmatizer_noun(fr_tokenizer):
     tokens = fr_tokenizer("il y a des Costaricienne.")
     assert tokens[4].lemma_ == "Costaricain"

spacy/tests/lang/fr/test_prefix_suffix_infix.py

@@ -7,11 +7,12 @@ from spacy.lang.punctuation import TOKENIZER_INFIXES
 from spacy.lang.char_classes import ALPHA
 
 
-@pytest.mark.parametrize('text,expected_tokens', [
-    ("l'avion", ["l'", "avion"]), ("j'ai", ["j'", "ai"])])
+@pytest.mark.parametrize(
+    "text,expected_tokens", [("l'avion", ["l'", "avion"]), ("j'ai", ["j'", "ai"])]
+)
 def test_issue768(text, expected_tokens):
     """Allow zero-width 'infix' token during the tokenization process."""
-    SPLIT_INFIX = r'(?<=[{a}]\')(?=[{a}])'.format(a=ALPHA)
+    SPLIT_INFIX = r"(?<=[{a}]\')(?=[{a}])".format(a=ALPHA)
 
     class FrenchTest(Language):
         class Defaults(Language.Defaults):

spacy/tests/lang/fr/test_text.py

@@ -1,13 +1,5 @@
 # coding: utf8
 from __future__ import unicode_literals
-import pytest
-
-from .... import util
-
-@pytest.fixture(scope='module')
-def fr_tokenizer():
-    return util.get_lang_class('fr').Defaults.create_tokenizer()
-
 
 import pytest
 from spacy.lang.fr.lex_attrs import like_num
@@ -27,7 +19,7 @@ ou avec un autre vrai humain."""
     assert len(tokens) == 113
 
 
-@pytest.mark.parametrize('word', ['onze', 'onzième'])
+@pytest.mark.parametrize("word", ["onze", "onzième"])
 def test_fr_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/ga/test_tokenizer.py

@@ -4,13 +4,15 @@ from __future__ import unicode_literals
 import pytest
 
 
+# fmt: off
 GA_TOKEN_EXCEPTION_TESTS = [
-    ('Niall Ó Domhnaill, Rialtas na hÉireann 1977 (lch. 600).', ['Niall', 'Ó', 'Domhnaill', ',', 'Rialtas', 'na', 'hÉireann', '1977', '(', 'lch.', '600', ')', '.']),
-    ('Daoine a bhfuil Gaeilge acu, m.sh. tusa agus mise', ['Daoine', 'a', 'bhfuil', 'Gaeilge', 'acu', ',', 'm.sh.', 'tusa', 'agus', 'mise'])
+    ("Niall Ó Domhnaill, Rialtas na hÉireann 1977 (lch. 600).", ["Niall", "Ó", "Domhnaill", ",", "Rialtas", "na", "hÉireann", "1977", "(", "lch.", "600", ")", "."]),
+    ("Daoine a bhfuil Gaeilge acu, m.sh. tusa agus mise", ["Daoine", "a", "bhfuil", "Gaeilge", "acu", ",", "m.sh.", "tusa", "agus", "mise"])
 ]
+# fmt: on
 
 
-@pytest.mark.parametrize('text,expected_tokens', GA_TOKEN_EXCEPTION_TESTS)
+@pytest.mark.parametrize("text,expected_tokens", GA_TOKEN_EXCEPTION_TESTS)
 def test_ga_tokenizer_handles_exception_cases(ga_tokenizer, text, expected_tokens):
     tokens = ga_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]

spacy/tests/lang/he/test_tokenizer.py

@@ -4,20 +4,41 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text,expected_tokens',
-    [('פייתון היא שפת תכנות דינמית', ['פייתון', 'היא', 'שפת', 'תכנות', 'דינמית'])])
+@pytest.mark.parametrize(
+    "text,expected_tokens",
+    [("פייתון היא שפת תכנות דינמית", ["פייתון", "היא", "שפת", "תכנות", "דינמית"])],
+)
 def test_he_tokenizer_handles_abbreviation(he_tokenizer, text, expected_tokens):
     tokens = he_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]
     assert expected_tokens == token_list
 
 
-@pytest.mark.parametrize('text,expected_tokens', [
-    ('עקבת אחריו בכל רחבי המדינה.', ['עקבת', 'אחריו', 'בכל', 'רחבי', 'המדינה', '.']),
-    ('עקבת אחריו בכל רחבי המדינה?', ['עקבת', 'אחריו', 'בכל', 'רחבי', 'המדינה', '?']),
-    ('עקבת אחריו בכל רחבי המדינה!', ['עקבת', 'אחריו', 'בכל', 'רחבי', 'המדינה', '!']),
-    ('עקבת אחריו בכל רחבי המדינה..', ['עקבת', 'אחריו', 'בכל', 'רחבי', 'המדינה', '..']),
-    ('עקבת אחריו בכל רחבי המדינה...', ['עקבת', 'אחריו', 'בכל', 'רחבי', 'המדינה', '...'])])
+@pytest.mark.parametrize(
+    "text,expected_tokens",
+    [
+        (
+            "עקבת אחריו בכל רחבי המדינה.",
+            ["עקבת", "אחריו", "בכל", "רחבי", "המדינה", "."],
+        ),
+        (
+            "עקבת אחריו בכל רחבי המדינה?",
+            ["עקבת", "אחריו", "בכל", "רחבי", "המדינה", "?"],
+        ),
+        (
+            "עקבת אחריו בכל רחבי המדינה!",
+            ["עקבת", "אחריו", "בכל", "רחבי", "המדינה", "!"],
+        ),
+        (
+            "עקבת אחריו בכל רחבי המדינה..",
+            ["עקבת", "אחריו", "בכל", "רחבי", "המדינה", ".."],
+        ),
+        (
+            "עקבת אחריו בכל רחבי המדינה...",
+            ["עקבת", "אחריו", "בכל", "רחבי", "המדינה", "..."],
+        ),
+    ],
+)
 def test_he_tokenizer_handles_punct(he_tokenizer, text, expected_tokens):
     tokens = he_tokenizer(text)
     assert expected_tokens == [token.text for token in tokens]

spacy/tests/lang/hu/test_tokenizer.py

@@ -6,11 +6,11 @@ import pytest
 
 DEFAULT_TESTS = [
     ('N. kormányzósági\nszékhely.', ['N.', 'kormányzósági', 'székhely', '.']),
-    pytest.mark.xfail(('A .hu egy tld.', ['A', '.hu', 'egy', 'tld', '.'])),
+    pytest.param('A .hu egy tld.', ['A', '.hu', 'egy', 'tld', '.'], marks=pytest.mark.xfail()),
     ('Az egy.ketto pelda.', ['Az', 'egy.ketto', 'pelda', '.']),
     ('A pl. rovidites.', ['A', 'pl.', 'rovidites', '.']),
     ('A S.M.A.R.T. szo.', ['A', 'S.M.A.R.T.', 'szo', '.']),
-    pytest.mark.xfail(('A .hu.', ['A', '.hu', '.'])),
+    pytest.param('A .hu.', ['A', '.hu', '.'], marks=pytest.mark.xfail()),
     ('Az egy.ketto.', ['Az', 'egy.ketto', '.']),
     ('A pl.', ['A', 'pl.']),
     ('A S.M.A.R.T.', ['A', 'S.M.A.R.T.']),
@@ -228,11 +228,11 @@ QUOTE_TESTS = [
 
 DOT_TESTS = [
     ('N. kormányzósági\nszékhely.', ['N.', 'kormányzósági', 'székhely', '.']),
-    pytest.mark.xfail(('A .hu egy tld.', ['A', '.hu', 'egy', 'tld', '.'])),
+    pytest.param('A .hu egy tld.', ['A', '.hu', 'egy', 'tld', '.'], marks=pytest.mark.xfail()),
     ('Az egy.ketto pelda.', ['Az', 'egy.ketto', 'pelda', '.']),
     ('A pl. rövidítés.', ['A', 'pl.', 'rövidítés', '.']),
     ('A S.M.A.R.T. szó.', ['A', 'S.M.A.R.T.', 'szó', '.']),
-    pytest.mark.xfail(('A .hu.', ['A', '.hu', '.'])),
+    pytest.param('A .hu.', ['A', '.hu', '.'], marks=pytest.mark.xfail()),
     ('Az egy.ketto.', ['Az', 'egy.ketto', '.']),
     ('A pl.', ['A', 'pl.']),
     ('A S.M.A.R.T.', ['A', 'S.M.A.R.T.']),

spacy/tests/lang/id/test_prefix_suffix_infix.py

@@ -4,85 +4,87 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text', ["(Ma'arif)"])
+@pytest.mark.parametrize("text", ["(Ma'arif)"])
 def test_id_tokenizer_splits_no_special(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["Ma'arif"])
+@pytest.mark.parametrize("text", ["Ma'arif"])
 def test_id_tokenizer_splits_no_punct(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text', ["(Ma'arif"])
+@pytest.mark.parametrize("text", ["(Ma'arif"])
 def test_id_tokenizer_splits_prefix_punct(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["Ma'arif)"])
+@pytest.mark.parametrize("text", ["Ma'arif)"])
 def test_id_tokenizer_splits_suffix_punct(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(Ma'arif)"])
+@pytest.mark.parametrize("text", ["(Ma'arif)"])
 def test_id_tokenizer_splits_even_wrap(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(Ma'arif?)"])
+@pytest.mark.parametrize("text", ["(Ma'arif?)"])
 def test_tokenizer_splits_uneven_wrap(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text,length', [("S.Kom.", 1), ("SKom.", 2), ("(S.Kom.", 2)])
+@pytest.mark.parametrize("text,length", [("S.Kom.", 1), ("SKom.", 2), ("(S.Kom.", 2)])
 def test_id_tokenizer_splits_prefix_interact(id_tokenizer, text, length):
     tokens = id_tokenizer(text)
     assert len(tokens) == length
 
 
-@pytest.mark.parametrize('text', ["S.Kom.)"])
+@pytest.mark.parametrize("text", ["S.Kom.)"])
 def test_id_tokenizer_splits_suffix_interact(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 2
 
 
-@pytest.mark.parametrize('text', ["(S.Kom.)"])
+@pytest.mark.parametrize("text", ["(S.Kom.)"])
 def test_id_tokenizer_splits_even_wrap_interact(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["(S.Kom.?)"])
+@pytest.mark.parametrize("text", ["(S.Kom.?)"])
 def test_id_tokenizer_splits_uneven_wrap_interact(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 4
 
 
-@pytest.mark.parametrize('text,length', [("gara-gara", 1), ("Jokowi-Ahok", 3), ("Sukarno-Hatta", 3)])
+@pytest.mark.parametrize(
+    "text,length", [("gara-gara", 1), ("Jokowi-Ahok", 3), ("Sukarno-Hatta", 3)]
+)
 def test_id_tokenizer_splits_hyphens(id_tokenizer, text, length):
     tokens = id_tokenizer(text)
     assert len(tokens) == length
 
 
-@pytest.mark.parametrize('text', ["0.1-13.5", "0.0-0.1", "103.27-300"])
+@pytest.mark.parametrize("text", ["0.1-13.5", "0.0-0.1", "103.27-300"])
 def test_id_tokenizer_splits_numeric_range(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["ini.Budi", "Halo.Bandung"])
+@pytest.mark.parametrize("text", ["ini.Budi", "Halo.Bandung"])
 def test_id_tokenizer_splits_period_infix(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
 
 
-@pytest.mark.parametrize('text', ["Halo,Bandung", "satu,dua"])
+@pytest.mark.parametrize("text", ["Halo,Bandung", "satu,dua"])
 def test_id_tokenizer_splits_comma_infix(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3
@@ -91,7 +93,7 @@ def test_id_tokenizer_splits_comma_infix(id_tokenizer, text):
     assert tokens[2].text == text.split(",")[1]
 
 
-@pytest.mark.parametrize('text', ["halo...Bandung", "dia...pergi"])
+@pytest.mark.parametrize("text", ["halo...Bandung", "dia...pergi"])
 def test_id_tokenizer_splits_ellipsis_infix(id_tokenizer, text):
     tokens = id_tokenizer(text)
     assert len(tokens) == 3

spacy/tests/lang/id/test_text.py

@@ -5,7 +5,7 @@ import pytest
 from spacy.lang.id.lex_attrs import like_num
 
 
-@pytest.mark.parametrize('word', ['sebelas'])
+@pytest.mark.parametrize("word", ["sebelas"])
 def test_id_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/ja/test_lemmatization.py

@@ -4,12 +4,10 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('word,lemma', [
-    ('新しく', '新しい'),
-    ('赤く', '赤い'),
-    ('すごく', '凄い'),
-    ('いただきました', '頂く'),
-    ('なった', '成る')])
+@pytest.mark.parametrize(
+    "word,lemma",
+    [("新しく", "新しい"), ("赤く", "赤い"), ("すごく", "凄い"), ("いただきました", "頂く"), ("なった", "成る")],
+)
 def test_ja_lemmatizer_assigns(ja_tokenizer, word, lemma):
     test_lemma = ja_tokenizer(word)[0].lemma_
     assert test_lemma == lemma

spacy/tests/lang/ja/test_tokenizer.py

@@ -4,6 +4,7 @@ from __future__ import unicode_literals
 import pytest
 
 
+# fmt: off
 TOKENIZER_TESTS = [
     ("日本語だよ", ['日本', '語', 'だ', 'よ']),
     ("東京タワーの近くに住んでいます。", ['東京', 'タワー', 'の', '近く', 'に', '住ん', 'で', 'い', 'ます', '。']),
@@ -27,21 +28,22 @@ POS_TESTS = [
     ('月に代わって、お仕置きよ!', ['NOUN', 'ADP', 'VERB', 'SCONJ', 'PUNCT', 'NOUN', 'NOUN', 'PART', 'PUNCT']),
     ('すもももももももものうち', ['NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN'])
 ]
+# fmt: on
 
 
-@pytest.mark.parametrize('text,expected_tokens', TOKENIZER_TESTS)
+@pytest.mark.parametrize("text,expected_tokens", TOKENIZER_TESTS)
 def test_ja_tokenizer(ja_tokenizer, text, expected_tokens):
     tokens = [token.text for token in ja_tokenizer(text)]
     assert tokens == expected_tokens
 
 
-@pytest.mark.parametrize('text,expected_tags', TAG_TESTS)
-def test_ja_tokenizer(ja_tokenizer, text, expected_tags):
+@pytest.mark.parametrize("text,expected_tags", TAG_TESTS)
+def test_ja_tokenizer_tags(ja_tokenizer, text, expected_tags):
     tags = [token.tag_ for token in ja_tokenizer(text)]
     assert tags == expected_tags
 
 
-@pytest.mark.parametrize('text,expected_pos', POS_TESTS)
-def test_ja_tokenizer(ja_tokenizer, text, expected_pos):
+@pytest.mark.parametrize("text,expected_pos", POS_TESTS)
+def test_ja_tokenizer_pos(ja_tokenizer, text, expected_pos):
     pos = [token.pos_ for token in ja_tokenizer(text)]
     assert pos == expected_pos

spacy/tests/lang/nb/test_tokenizer.py

@@ -5,12 +5,18 @@ import pytest
 
 
 NB_TOKEN_EXCEPTION_TESTS = [
-    ('Smørsausen brukes bl.a. til fisk', ['Smørsausen', 'brukes', 'bl.a.', 'til', 'fisk']),
-    ('Jeg kommer først kl. 13 pga. diverse forsinkelser', ['Jeg', 'kommer', 'først', 'kl.', '13', 'pga.', 'diverse', 'forsinkelser'])
+    (
+        "Smørsausen brukes bl.a. til fisk",
+        ["Smørsausen", "brukes", "bl.a.", "til", "fisk"],
+    ),
+    (
+        "Jeg kommer først kl. 13 pga. diverse forsinkelser",
+        ["Jeg", "kommer", "først", "kl.", "13", "pga.", "diverse", "forsinkelser"],
+    ),
 ]
 
 
-@pytest.mark.parametrize('text,expected_tokens', NB_TOKEN_EXCEPTION_TESTS)
+@pytest.mark.parametrize("text,expected_tokens", NB_TOKEN_EXCEPTION_TESTS)
 def test_nb_tokenizer_handles_exception_cases(nb_tokenizer, text, expected_tokens):
     tokens = nb_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]

spacy/tests/lang/nl/test_text.py

@@ -5,7 +5,7 @@ import pytest
 from spacy.lang.nl.lex_attrs import like_num
 
 
-@pytest.mark.parametrize('word', ['elf', 'elfde'])
+@pytest.mark.parametrize("word", ["elf", "elfde"])
 def test_nl_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/pt/test_text.py

@@ -5,7 +5,7 @@ import pytest
 from spacy.lang.pt.lex_attrs import like_num
 
 
-@pytest.mark.parametrize('word', ['onze', 'quadragésimo'])
+@pytest.mark.parametrize("word", ["onze", "quadragésimo"])
 def test_pt_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/ro/test_lemmatizer.py

@@ -4,11 +4,15 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('string,lemma', [
-    ('câini', 'câine'),
-    ('expedițiilor', 'expediție'),
-    ('pensete', 'pensetă'),
-    ('erau', 'fi')])
+@pytest.mark.parametrize(
+    "string,lemma",
+    [
+        ("câini", "câine"),
+        ("expedițiilor", "expediție"),
+        ("pensete", "pensetă"),
+        ("erau", "fi"),
+    ],
+)
 def test_ro_lemmatizer_lookup_assigns(ro_tokenizer, string, lemma):
     tokens = ro_tokenizer(string)
     assert tokens[0].lemma_ == lemma

spacy/tests/lang/ro/test_tokenizer.py

@@ -5,17 +5,20 @@ import pytest
 
 
 TEST_CASES = [
-    ('Adresa este str. Principală nr. 5.', ['Adresa', 'este', 'str.', 'Principală', 'nr.', '5', '.']),
-    ('Teste, etc.', ['Teste', ',', 'etc.']),
-    ('Lista, ș.a.m.d.', ['Lista', ',', 'ș.a.m.d.']),
-    ('Și d.p.d.v. al...', ['Și', 'd.p.d.v.', 'al', '...']),
+    (
+        "Adresa este str. Principală nr. 5.",
+        ["Adresa", "este", "str.", "Principală", "nr.", "5", "."],
+    ),
+    ("Teste, etc.", ["Teste", ",", "etc."]),
+    ("Lista, ș.a.m.d.", ["Lista", ",", "ș.a.m.d."]),
+    ("Și d.p.d.v. al...", ["Și", "d.p.d.v.", "al", "..."]),
     # number tests
-    ('Clasa a 4-a.', ['Clasa', 'a', '4-a', '.']),
-    ('Al 12-lea ceas.', ['Al', '12-lea', 'ceas', '.'])
+    ("Clasa a 4-a.", ["Clasa", "a", "4-a", "."]),
+    ("Al 12-lea ceas.", ["Al", "12-lea", "ceas", "."]),
 ]
 
 
-@pytest.mark.parametrize('text,expected_tokens', TEST_CASES)
+@pytest.mark.parametrize("text,expected_tokens", TEST_CASES)
 def test_ro_tokenizer_handles_testcases(ro_tokenizer, text, expected_tokens):
     tokens = ro_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]

spacy/tests/lang/ru/test_exceptions.py

@@ -4,10 +4,10 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text,norms', [
-    ("пн.", ["понедельник"]),
-    ("пт.", ["пятница"]),
-    ("дек.", ["декабрь"])])
+@pytest.mark.parametrize(
+    "text,norms",
+    [("пн.", ["понедельник"]), ("пт.", ["пятница"]), ("дек.", ["декабрь"])],
+)
 def test_ru_tokenizer_abbrev_exceptions(ru_tokenizer, text, norms):
     tokens = ru_tokenizer(text)
     assert len(tokens) == 1

spacy/tests/lang/ru/test_lemmatizer.py

@@ -9,55 +9,71 @@ from ...util import get_doc
 
 @pytest.fixture
 def ru_lemmatizer():
-    pymorphy = pytest.importorskip('pymorphy2')
+    pymorphy = pytest.importorskip("pymorphy2")
     return Russian.Defaults.create_lemmatizer()
 
 
 def test_ru_doc_lemmatization(ru_tokenizer):
-    words = ['мама', 'мыла', 'раму']
-    tags = ['NOUN__Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing',
-            'VERB__Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act',
-            'NOUN__Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing']
+    words = ["мама", "мыла", "раму"]
+    tags = [
+        "NOUN__Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
+        "VERB__Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
+        "NOUN__Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
+    ]
     doc = get_doc(ru_tokenizer.vocab, words=words, tags=tags)
     lemmas = [token.lemma_ for token in doc]
-    assert lemmas == ['мама', 'мыть', 'рама']
+    assert lemmas == ["мама", "мыть", "рама"]
 
 
-@pytest.mark.parametrize('text,lemmas', [
-    ('гвоздики', ['гвоздик', 'гвоздика']),
-    ('люди', ['человек']),
-    ('реки', ['река']),
-    ('кольцо', ['кольцо']),
-    ('пепперони', ['пепперони'])])
+@pytest.mark.parametrize(
+    "text,lemmas",
+    [
+        ("гвоздики", ["гвоздик", "гвоздика"]),
+        ("люди", ["человек"]),
+        ("реки", ["река"]),
+        ("кольцо", ["кольцо"]),
+        ("пепперони", ["пепперони"]),
+    ],
+)
 def test_ru_lemmatizer_noun_lemmas(ru_lemmatizer, text, lemmas):
     assert sorted(ru_lemmatizer.noun(text)) == lemmas
 
 
-@pytest.mark.models('ru')
-@pytest.mark.parametrize('text,pos,morphology,lemma', [
-    ('рой', 'NOUN', None, 'рой'),
-    ('рой', 'VERB', None, 'рыть'),
-    ('клей', 'NOUN', None, 'клей'),
-    ('клей', 'VERB', None, 'клеить'),
-    ('три', 'NUM', None, 'три'),
-    ('кос', 'NOUN', {'Number': 'Sing'}, 'кос'),
-    ('кос', 'NOUN', {'Number': 'Plur'}, 'коса'),
-    ('кос', 'ADJ', None, 'косой'),
-    ('потом', 'NOUN', None, 'пот'),
-    ('потом', 'ADV', None, 'потом')])
-def test_ru_lemmatizer_works_with_different_pos_homonyms(ru_lemmatizer, text, pos, morphology, lemma):
+@pytest.mark.models("ru")
+@pytest.mark.parametrize(
+    "text,pos,morphology,lemma",
+    [
+        ("рой", "NOUN", None, "рой"),
+        ("рой", "VERB", None, "рыть"),
+        ("клей", "NOUN", None, "клей"),
+        ("клей", "VERB", None, "клеить"),
+        ("три", "NUM", None, "три"),
+        ("кос", "NOUN", {"Number": "Sing"}, "кос"),
+        ("кос", "NOUN", {"Number": "Plur"}, "коса"),
+        ("кос", "ADJ", None, "косой"),
+        ("потом", "NOUN", None, "пот"),
+        ("потом", "ADV", None, "потом"),
+    ],
+)
+def test_ru_lemmatizer_works_with_different_pos_homonyms(
+    ru_lemmatizer, text, pos, morphology, lemma
+):
     assert ru_lemmatizer(text, pos, morphology) == [lemma]
 
 
-@pytest.mark.parametrize('text,morphology,lemma', [
-    ('гвоздики', {'Gender': 'Fem'}, 'гвоздика'),
-    ('гвоздики', {'Gender': 'Masc'}, 'гвоздик'),
-    ('вина', {'Gender': 'Fem'}, 'вина'),
-    ('вина', {'Gender': 'Neut'}, 'вино')])
+@pytest.mark.parametrize(
+    "text,morphology,lemma",
+    [
+        ("гвоздики", {"Gender": "Fem"}, "гвоздика"),
+        ("гвоздики", {"Gender": "Masc"}, "гвоздик"),
+        ("вина", {"Gender": "Fem"}, "вина"),
+        ("вина", {"Gender": "Neut"}, "вино"),
+    ],
+)
 def test_ru_lemmatizer_works_with_noun_homonyms(ru_lemmatizer, text, morphology, lemma):
     assert ru_lemmatizer.noun(text, morphology) == [lemma]
 
 
 def test_ru_lemmatizer_punct(ru_lemmatizer):
-    assert ru_lemmatizer.punct('«') == ['"']
-    assert ru_lemmatizer.punct('»') == ['"']
+    assert ru_lemmatizer.punct("«") == ['"']
+    assert ru_lemmatizer.punct("»") == ['"']

spacy/tests/lang/ru/test_text.py

@@ -5,7 +5,7 @@ import pytest
 from spacy.lang.ru.lex_attrs import like_num
 
 
-@pytest.mark.parametrize('word', ['одиннадцать'])
+@pytest.mark.parametrize("word", ["одиннадцать"])
 def test_ru_lex_attrs_capitals(word):
     assert like_num(word)
     assert like_num(word.upper())

spacy/tests/lang/ru/test_tokenizer.py

@@ -4,19 +4,19 @@ from __future__ import unicode_literals
 import pytest
 
 
-PUNCT_OPEN = ['(', '[', '{', '*']
-PUNCT_CLOSE = [')', ']', '}', '*']
-PUNCT_PAIRED = [('(', ')'),  ('[', ']'), ('{', '}'), ('*', '*')]
+PUNCT_OPEN = ["(", "[", "{", "*"]
+PUNCT_CLOSE = [")", "]", "}", "*"]
+PUNCT_PAIRED = [("(", ")"), ("[", "]"), ("{", "}"), ("*", "*")]
 
 
-@pytest.mark.parametrize('text', ["(", "((", "<"])
+@pytest.mark.parametrize("text", ["(", "((", "<"])
 def test_ru_tokenizer_handles_only_punct(ru_tokenizer, text):
     tokens = ru_tokenizer(text)
     assert len(tokens) == len(text)
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_open_punct(ru_tokenizer, punct, text):
     tokens = ru_tokenizer(punct + text)
     assert len(tokens) == 2
@@ -24,8 +24,8 @@ def test_ru_tokenizer_splits_open_punct(ru_tokenizer, punct, text):
     assert tokens[1].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_close_punct(ru_tokenizer, punct, text):
     tokens = ru_tokenizer(text + punct)
     assert len(tokens) == 2
@@ -33,9 +33,9 @@ def test_ru_tokenizer_splits_close_punct(ru_tokenizer, punct, text):
     assert tokens[1].text == punct
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('punct_add', ["`"])
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("punct_add", ["`"])
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_two_diff_open_punct(ru_tokenizer, punct, punct_add, text):
     tokens = ru_tokenizer(punct + punct_add + text)
     assert len(tokens) == 3
@@ -44,9 +44,9 @@ def test_ru_tokenizer_splits_two_diff_open_punct(ru_tokenizer, punct, punct_add,
     assert tokens[2].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('punct_add', ["'"])
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("punct_add", ["'"])
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_two_diff_close_punct(ru_tokenizer, punct, punct_add, text):
     tokens = ru_tokenizer(text + punct + punct_add)
     assert len(tokens) == 3
@@ -55,8 +55,8 @@ def test_ru_tokenizer_splits_two_diff_close_punct(ru_tokenizer, punct, punct_add
     assert tokens[2].text == punct_add
 
 
-@pytest.mark.parametrize('punct', PUNCT_OPEN)
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_OPEN)
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_same_open_punct(ru_tokenizer, punct, text):
     tokens = ru_tokenizer(punct + punct + punct + text)
     assert len(tokens) == 4
@@ -64,8 +64,8 @@ def test_ru_tokenizer_splits_same_open_punct(ru_tokenizer, punct, text):
     assert tokens[3].text == text
 
 
-@pytest.mark.parametrize('punct', PUNCT_CLOSE)
-@pytest.mark.parametrize('text', ["Привет"])
+@pytest.mark.parametrize("punct", PUNCT_CLOSE)
+@pytest.mark.parametrize("text", ["Привет"])
 def test_ru_tokenizer_splits_same_close_punct(ru_tokenizer, punct, text):
     tokens = ru_tokenizer(text + punct + punct + punct)
     assert len(tokens) == 4
@@ -73,14 +73,14 @@ def test_ru_tokenizer_splits_same_close_punct(ru_tokenizer, punct, text):
     assert tokens[1].text == punct
 
 
-@pytest.mark.parametrize('text', ["'Тест"])
+@pytest.mark.parametrize("text", ["'Тест"])
 def test_ru_tokenizer_splits_open_appostrophe(ru_tokenizer, text):
     tokens = ru_tokenizer(text)
     assert len(tokens) == 2
     assert tokens[0].text == "'"
 
 
-@pytest.mark.parametrize('text', ["Тест''"])
+@pytest.mark.parametrize("text", ["Тест''"])
 def test_ru_tokenizer_splits_double_end_quote(ru_tokenizer, text):
     tokens = ru_tokenizer(text)
     assert len(tokens) == 2
@@ -88,10 +88,11 @@ def test_ru_tokenizer_splits_double_end_quote(ru_tokenizer, text):
     assert len(tokens_punct) == 1
 
 
-@pytest.mark.parametrize('punct_open,punct_close', PUNCT_PAIRED)
-@pytest.mark.parametrize('text', ["Тест"])
-def test_ru_tokenizer_splits_open_close_punct(ru_tokenizer, punct_open,
-                                              punct_close, text):
+@pytest.mark.parametrize("punct_open,punct_close", PUNCT_PAIRED)
+@pytest.mark.parametrize("text", ["Тест"])
+def test_ru_tokenizer_splits_open_close_punct(
+    ru_tokenizer, punct_open, punct_close, text
+):
     tokens = ru_tokenizer(punct_open + text + punct_close)
     assert len(tokens) == 3
     assert tokens[0].text == punct_open
@@ -99,11 +100,12 @@ def test_ru_tokenizer_splits_open_close_punct(ru_tokenizer, punct_open,
     assert tokens[2].text == punct_close
 
 
-@pytest.mark.parametrize('punct_open,punct_close', PUNCT_PAIRED)
-@pytest.mark.parametrize('punct_open2,punct_close2', [("`", "'")])
-@pytest.mark.parametrize('text', ["Тест"])
-def test_ru_tokenizer_two_diff_punct(ru_tokenizer, punct_open, punct_close,
-                                     punct_open2, punct_close2, text):
+@pytest.mark.parametrize("punct_open,punct_close", PUNCT_PAIRED)
+@pytest.mark.parametrize("punct_open2,punct_close2", [("`", "'")])
+@pytest.mark.parametrize("text", ["Тест"])
+def test_ru_tokenizer_two_diff_punct(
+    ru_tokenizer, punct_open, punct_close, punct_open2, punct_close2, text
+):
     tokens = ru_tokenizer(punct_open2 + punct_open + text + punct_close + punct_close2)
     assert len(tokens) == 5
     assert tokens[0].text == punct_open2
@@ -113,7 +115,7 @@ def test_ru_tokenizer_two_diff_punct(ru_tokenizer, punct_open, punct_close,
     assert tokens[4].text == punct_close2
 
 
-@pytest.mark.parametrize('text', ["Тест."])
+@pytest.mark.parametrize("text", ["Тест."])
 def test_ru_tokenizer_splits_trailing_dot(ru_tokenizer, text):
     tokens = ru_tokenizer(text)
     assert tokens[1].text == "."

spacy/tests/lang/sv/test_tokenizer.py

@@ -5,20 +5,29 @@ import pytest
 
 
 SV_TOKEN_EXCEPTION_TESTS = [
-    ('Smörsåsen används bl.a. till fisk', ['Smörsåsen', 'används', 'bl.a.', 'till', 'fisk']),
-    ('Jag kommer först kl. 13 p.g.a. diverse förseningar', ['Jag', 'kommer', 'först', 'kl.', '13', 'p.g.a.', 'diverse', 'förseningar']),
-    ('Anders I. tycker om ord med i i.', ["Anders", "I.", "tycker", "om", "ord", "med", "i", "i", "."])
+    (
+        "Smörsåsen används bl.a. till fisk",
+        ["Smörsåsen", "används", "bl.a.", "till", "fisk"],
+    ),
+    (
+        "Jag kommer först kl. 13 p.g.a. diverse förseningar",
+        ["Jag", "kommer", "först", "kl.", "13", "p.g.a.", "diverse", "förseningar"],
+    ),
+    (
+        "Anders I. tycker om ord med i i.",
+        ["Anders", "I.", "tycker", "om", "ord", "med", "i", "i", "."],
+    ),
 ]
 
 
-@pytest.mark.parametrize('text,expected_tokens', SV_TOKEN_EXCEPTION_TESTS)
+@pytest.mark.parametrize("text,expected_tokens", SV_TOKEN_EXCEPTION_TESTS)
 def test_sv_tokenizer_handles_exception_cases(sv_tokenizer, text, expected_tokens):
     tokens = sv_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]
     assert expected_tokens == token_list
 
 
-@pytest.mark.parametrize('text', ["driveru", "hajaru", "Serru", "Fixaru"])
+@pytest.mark.parametrize("text", ["driveru", "hajaru", "Serru", "Fixaru"])
 def test_sv_tokenizer_handles_verb_exceptions(sv_tokenizer, text):
     tokens = sv_tokenizer(text)
     assert len(tokens) == 2

spacy/tests/lang/test_attrs.py

@@ -6,53 +6,85 @@ from spacy.attrs import intify_attrs, ORTH, NORM, LEMMA, IS_ALPHA
 from spacy.lang.lex_attrs import is_punct, is_ascii, is_currency, like_url, word_shape
 
 
-@pytest.mark.parametrize('text', ["dog"])
+@pytest.mark.parametrize("text", ["dog"])
 def test_attrs_key(text):
     assert intify_attrs({"ORTH": text}) == {ORTH: text}
     assert intify_attrs({"NORM": text}) == {NORM: text}
     assert intify_attrs({"lemma": text}, strings_map={text: 10}) == {LEMMA: 10}
 
 
-@pytest.mark.parametrize('text', ["dog"])
+@pytest.mark.parametrize("text", ["dog"])
 def test_attrs_idempotence(text):
-    int_attrs = intify_attrs({"lemma": text, 'is_alpha': True}, strings_map={text: 10})
+    int_attrs = intify_attrs({"lemma": text, "is_alpha": True}, strings_map={text: 10})
     assert intify_attrs(int_attrs) == {LEMMA: 10, IS_ALPHA: True}
 
 
-@pytest.mark.parametrize('text', ["dog"])
+@pytest.mark.parametrize("text", ["dog"])
 def test_attrs_do_deprecated(text):
-    int_attrs = intify_attrs({"F": text, 'is_alpha': True}, strings_map={text: 10},
-                              _do_deprecated=True)
+    int_attrs = intify_attrs(
+        {"F": text, "is_alpha": True}, strings_map={text: 10}, _do_deprecated=True
+    )
     assert int_attrs == {ORTH: 10, IS_ALPHA: True}
 
 
-@pytest.mark.parametrize('text,match', [(',', True), (' ', False), ('a', False)])
+@pytest.mark.parametrize("text,match", [(",", True), (" ", False), ("a", False)])
 def test_lex_attrs_is_punct(text, match):
     assert is_punct(text) == match
 
 
-@pytest.mark.parametrize('text,match', [(',', True), ('£', False), ('♥', False)])
+@pytest.mark.parametrize("text,match", [(",", True), ("£", False), ("♥", False)])
 def test_lex_attrs_is_ascii(text, match):
     assert is_ascii(text) == match
 
 
-@pytest.mark.parametrize('text,match', [('$', True), ('£', True), ('♥', False),
-    ('€', True), ('¥', True), ('¢', True),
-    ('a', False), ('www.google.com', False), ('dog', False)])
+@pytest.mark.parametrize(
+    "text,match",
+    [
+        ("$", True),
+        ("£", True),
+        ("♥", False),
+        ("€", True),
+        ("¥", True),
+        ("¢", True),
+        ("a", False),
+        ("www.google.com", False),
+        ("dog", False),
+    ],
+)
 def test_lex_attrs_is_currency(text, match):
     assert is_currency(text) == match
 
 
-@pytest.mark.parametrize('text,match', [
-    ('www.google.com', True), ('google.com', True), ('sydney.com', True),
-    ('2girls1cup.org', True), ('http://stupid', True), ('www.hi', True),
-    ('dog', False), ('1.2', False), ('1.a', False), ('hello.There', False)])
+@pytest.mark.parametrize(
+    "text,match",
+    [
+        ("www.google.com", True),
+        ("google.com", True),
+        ("sydney.com", True),
+        ("2girls1cup.org", True),
+        ("http://stupid", True),
+        ("www.hi", True),
+        ("dog", False),
+        ("1.2", False),
+        ("1.a", False),
+        ("hello.There", False),
+    ],
+)
 def test_lex_attrs_like_url(text, match):
     assert like_url(text) == match
 
 
-@pytest.mark.parametrize('text,shape', [
-    ('Nasa', 'Xxxx'), ('capitalized', 'xxxx'), ('999999999', 'dddd'),
-    ('C3P0', 'XdXd'), (',', ','), ('\n', '\n'), ('``,-', '``,-')])
+@pytest.mark.parametrize(
+    "text,shape",
+    [
+        ("Nasa", "Xxxx"),
+        ("capitalized", "xxxx"),
+        ("999999999", "dddd"),
+        ("C3P0", "XdXd"),
+        (",", ","),
+        ("\n", "\n"),
+        ("``,-", "``,-"),
+    ],
+)
 def test_lex_attrs_word_shape(text, shape):
     assert word_shape(text) == shape

spacy/tests/lang/th/test_tokenizer.py

@@ -4,8 +4,9 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('text,expected_tokens', [
-    ("คุณรักผมไหม", ['คุณ', 'รัก', 'ผม', 'ไหม'])])
+@pytest.mark.parametrize(
+    "text,expected_tokens", [("คุณรักผมไหม", ["คุณ", "รัก", "ผม", "ไหม"])]
+)
 def test_th_tokenizer(th_tokenizer, text, expected_tokens):
     tokens = [token.text for token in th_tokenizer(text)]
     assert tokens == expected_tokens

spacy/tests/lang/tr/test_lemmatization.py

@@ -4,14 +4,18 @@ from __future__ import unicode_literals
 import pytest
 
 
-@pytest.mark.parametrize('string,lemma', [
-    ('evlerimizdeki', 'ev'),
-    ('işlerimizi', 'iş'),
-    ('biran', 'biran'),
-    ('bitirmeliyiz', 'bitir'),
-    ('isteklerimizi', 'istek'),
-    ('karşılaştırmamızın', 'karşılaştır'),
-    ('çoğulculuktan', 'çoğulcu')])
+@pytest.mark.parametrize(
+    "string,lemma",
+    [
+        ("evlerimizdeki", "ev"),
+        ("işlerimizi", "iş"),
+        ("biran", "biran"),
+        ("bitirmeliyiz", "bitir"),
+        ("isteklerimizi", "istek"),
+        ("karşılaştırmamızın", "karşılaştır"),
+        ("çoğulculuktan", "çoğulcu"),
+    ],
+)
 def test_tr_lemmatizer_lookup_assigns(tr_tokenizer, string, lemma):
     tokens = tr_tokenizer(string)
     assert tokens[0].lemma_ == lemma

spacy/tests/lang/tt/test_tokenizer.py

@@ -6,14 +6,16 @@ import pytest
 
 INFIX_HYPHEN_TESTS = [
     ("Явым-төшем күләме.", "Явым-төшем күләме .".split()),
-    ("Хатын-кыз киеме.", "Хатын-кыз киеме .".split())
+    ("Хатын-кыз киеме.", "Хатын-кыз киеме .".split()),
 ]
 
 PUNC_INSIDE_WORDS_TESTS = [
-    ("Пассаҗир саны - 2,13 млн — кеше/көндә (2010), 783,9 млн. кеше/елда.",
-     "Пассаҗир саны - 2,13 млн — кеше / көндә ( 2010 ) ,"
-     " 783,9 млн. кеше / елда .".split()),
-    ("Ту\"кай", "Ту \" кай".split())
+    (
+        "Пассаҗир саны - 2,13 млн — кеше/көндә (2010), 783,9 млн. кеше/елда.",
+        "Пассаҗир саны - 2,13 млн — кеше / көндә ( 2010 ) ,"
+        " 783,9 млн. кеше / елда .".split(),
+    ),
+    ('Ту"кай', 'Ту " кай'.split()),
 ]
 
 MIXED_ORDINAL_NUMS_TESTS = [
@@ -22,14 +24,14 @@ MIXED_ORDINAL_NUMS_TESTS = [
 
 ABBREV_TESTS = [
     ("«3 елда (б.э.к.) туган", "« 3 елда ( б.э.к. ) туган".split()),
-    ("тукымадан һ.б.ш. тегелгән.", "тукымадан һ.б.ш. тегелгән .".split())
+    ("тукымадан һ.б.ш. тегелгән.", "тукымадан һ.б.ш. тегелгән .".split()),
 ]
 
 NAME_ABBREV_TESTS = [
     ("Ә.Тукай", "Ә.Тукай".split()),
     ("Ә.тукай", "Ә.тукай".split()),
     ("ә.Тукай", "ә . Тукай".split()),
-    ("Миләүшә.", "Миләүшә .".split())
+    ("Миләүшә.", "Миләүшә .".split()),
 ]
 
 TYPOS_IN_PUNC_TESTS = [
@@ -37,30 +39,39 @@ TYPOS_IN_PUNC_TESTS = [
     ("«3 елда,туган", "« 3 елда , туган".split()),
     ("«3 елда,туган.", "« 3 елда , туган .".split()),
     ("Ул эшли(кайчан?)", "Ул эшли ( кайчан ? )".split()),
-    ("Ул (кайчан?)эшли", "Ул ( кайчан ?) эшли".split())  # "?)" => "?)" or "? )"
+    ("Ул (кайчан?)эшли", "Ул ( кайчан ?) эшли".split()),  # "?)" => "?)" or "? )"
 ]
 
 LONG_TEXTS_TESTS = [
-    ("Иң борынгы кешеләр суыклар һәм салкын кышлар булмый торган җылы"
-     "якларда яшәгәннәр, шуңа күрә аларга кием кирәк булмаган.Йөз"
-     "меңнәрчә еллар үткән, борынгы кешеләр акрынлап Европа һәм Азиянең"
-     "салкын илләрендә дә яши башлаганнар. Алар кырыс һәм салкын"
-     "кышлардан саклану өчен кием-салым уйлап тапканнар - итәк.",
-     "Иң борынгы кешеләр суыклар һәм салкын кышлар булмый торган җылы"
-     "якларда яшәгәннәр , шуңа күрә аларга кием кирәк булмаган . Йөз"
-     "меңнәрчә еллар үткән , борынгы кешеләр акрынлап Европа һәм Азиянең"
-     "салкын илләрендә дә яши башлаганнар . Алар кырыс һәм салкын"
-     "кышлардан саклану өчен кием-салым уйлап тапканнар - итәк .".split()
-     )
+    (
+        "Иң борынгы кешеләр суыклар һәм салкын кышлар булмый торган җылы"
+        "якларда яшәгәннәр, шуңа күрә аларга кием кирәк булмаган.Йөз"
+        "меңнәрчә еллар үткән, борынгы кешеләр акрынлап Европа һәм Азиянең"
+        "салкын илләрендә дә яши башлаганнар. Алар кырыс һәм салкын"
+        "кышлардан саклану өчен кием-салым уйлап тапканнар - итәк.",
+        "Иң борынгы кешеләр суыклар һәм салкын кышлар булмый торган җылы"
+        "якларда яшәгәннәр , шуңа күрә аларга кием кирәк булмаган . Йөз"
+        "меңнәрчә еллар үткән , борынгы кешеләр акрынлап Европа һәм Азиянең"
+        "салкын илләрендә дә яши башлаганнар . Алар кырыс һәм салкын"
+        "кышлардан саклану өчен кием-салым уйлап тапканнар - итәк .".split(),
+    )
 ]
 
-TESTCASES = (INFIX_HYPHEN_TESTS + PUNC_INSIDE_WORDS_TESTS +
-             MIXED_ORDINAL_NUMS_TESTS + ABBREV_TESTS + NAME_ABBREV_TESTS +
-             LONG_TEXTS_TESTS + TYPOS_IN_PUNC_TESTS)
+TESTCASES = (
+    INFIX_HYPHEN_TESTS
+    + PUNC_INSIDE_WORDS_TESTS
+    + MIXED_ORDINAL_NUMS_TESTS
+    + ABBREV_TESTS
+    + NAME_ABBREV_TESTS
+    + LONG_TEXTS_TESTS
+    + TYPOS_IN_PUNC_TESTS
+)
 
 NORM_TESTCASES = [
-    ("тукымадан һ.б.ш. тегелгән.",
-     ["тукымадан", "һәм башка шундыйлар", "тегелгән", "."])
+    (
+        "тукымадан һ.б.ш. тегелгән.",
+        ["тукымадан", "һәм башка шундыйлар", "тегелгән", "."],
+    )
 ]
 
 
@@ -70,7 +81,7 @@ def test_tt_tokenizer_handles_testcases(tt_tokenizer, text, expected_tokens):
     assert expected_tokens == tokens
 
 
-@pytest.mark.parametrize('text,norms', NORM_TESTCASES)
+@pytest.mark.parametrize("text,norms", NORM_TESTCASES)
 def test_tt_tokenizer_handles_norm_exceptions(tt_tokenizer, text, norms):
     tokens = tt_tokenizer(text)
     assert [token.norm_ for token in tokens] == norms

spacy/tests/lang/ur/test_text.py

@@ -13,9 +13,7 @@ def test_ur_tokenizer_handles_long_text(ur_tokenizer):
     assert len(tokens) == 77
 
 
-@pytest.mark.parametrize('text,length', [
-    ("تحریر باسط حبیب", 3),
-    ("میرا پاکستان", 2)])
+@pytest.mark.parametrize("text,length", [("تحریر باسط حبیب", 3), ("میرا پاکستان", 2)])
 def test_ur_tokenizer_handles_cnts(ur_tokenizer, text, length):
     tokens = ur_tokenizer(text)
     assert len(tokens) == length

spacy/tests/matcher/test_matcher_api.py

@@ -10,9 +10,11 @@ from ..util import get_doc
 
 @pytest.fixture
 def matcher(en_vocab):
-    rules = {'JS':        [[{'ORTH': 'JavaScript'}]],
-             'GoogleNow': [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]],
-             'Java':      [[{'LOWER': 'java'}]]}
+    rules = {
+        "JS": [[{"ORTH": "JavaScript"}]],
+        "GoogleNow": [[{"ORTH": "Google"}, {"ORTH": "Now"}]],
+        "Java": [[{"LOWER": "java"}]],
+    }
     matcher = Matcher(en_vocab)
     for key, patterns in rules.items():
         matcher.add(key, None, *patterns)
@@ -21,44 +23,44 @@ def matcher(en_vocab):
 
 def test_matcher_from_api_docs(en_vocab):
     matcher = Matcher(en_vocab)
-    pattern = [{'ORTH': 'test'}]
+    pattern = [{"ORTH": "test"}]
     assert len(matcher) == 0
-    matcher.add('Rule', None, pattern)
+    matcher.add("Rule", None, pattern)
     assert len(matcher) == 1
-    matcher.remove('Rule')
-    assert 'Rule' not in matcher
-    matcher.add('Rule', None, pattern)
-    assert 'Rule' in matcher
-    on_match, patterns = matcher.get('Rule')
+    matcher.remove("Rule")
+    assert "Rule" not in matcher
+    matcher.add("Rule", None, pattern)
+    assert "Rule" in matcher
+    on_match, patterns = matcher.get("Rule")
     assert len(patterns[0])
 
 
 def test_matcher_from_usage_docs(en_vocab):
     text = "Wow 😀 This is really cool! 😂 😂"
-    doc = Doc(en_vocab, words=text.split(' '))
-    pos_emoji = ['😀', '😃', '😂', '🤣', '😊', '😍']
-    pos_patterns = [[{'ORTH': emoji}] for emoji in pos_emoji]
+    doc = Doc(en_vocab, words=text.split(" "))
+    pos_emoji = ["😀", "😃", "😂", "🤣", "😊", "😍"]
+    pos_patterns = [[{"ORTH": emoji}] for emoji in pos_emoji]
 
     def label_sentiment(matcher, doc, i, matches):
         match_id, start, end = matches[i]
-        if doc.vocab.strings[match_id] == 'HAPPY':
+        if doc.vocab.strings[match_id] == "HAPPY":
             doc.sentiment += 0.1
-        span = doc[start : end]
+        span = doc[start:end]
         token = span.merge()
-        token.vocab[token.text].norm_ = 'happy emoji'
+        token.vocab[token.text].norm_ = "happy emoji"
 
     matcher = Matcher(en_vocab)
-    matcher.add('HAPPY', label_sentiment, *pos_patterns)
+    matcher.add("HAPPY", label_sentiment, *pos_patterns)
     matches = matcher(doc)
     assert doc.sentiment != 0
-    assert doc[1].norm_ == 'happy emoji'
+    assert doc[1].norm_ == "happy emoji"
 
 
 def test_matcher_len_contains(matcher):
     assert len(matcher) == 3
-    matcher.add('TEST', None, [{'ORTH': 'test'}])
-    assert 'TEST' in matcher
-    assert 'TEST2' not in matcher
+    matcher.add("TEST", None, [{"ORTH": "test"}])
+    assert "TEST" in matcher
+    assert "TEST2" not in matcher
 
 
 def test_matcher_no_match(matcher):
@@ -68,38 +70,40 @@ def test_matcher_no_match(matcher):
 
 def test_matcher_match_start(matcher):
     doc = Doc(matcher.vocab, words=["JavaScript", "is", "good"])
-    assert matcher(doc) == [(matcher.vocab.strings['JS'], 0, 1)]
+    assert matcher(doc) == [(matcher.vocab.strings["JS"], 0, 1)]
 
 
 def test_matcher_match_end(matcher):
     words = ["I", "like", "java"]
     doc = Doc(matcher.vocab, words=words)
-    assert matcher(doc) == [(doc.vocab.strings['Java'], 2, 3)]
+    assert matcher(doc) == [(doc.vocab.strings["Java"], 2, 3)]
 
 
 def test_matcher_match_middle(matcher):
     words = ["I", "like", "Google", "Now", "best"]
     doc = Doc(matcher.vocab, words=words)
-    assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4)]
+    assert matcher(doc) == [(doc.vocab.strings["GoogleNow"], 2, 4)]
 
 
 def test_matcher_match_multi(matcher):
     words = ["I", "like", "Google", "Now", "and", "java", "best"]
     doc = Doc(matcher.vocab, words=words)
-    assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], 2, 4),
-                            (doc.vocab.strings['Java'], 5, 6)]
+    assert matcher(doc) == [
+        (doc.vocab.strings["GoogleNow"], 2, 4),
+        (doc.vocab.strings["Java"], 5, 6),
+    ]
 
 
 def test_matcher_empty_dict(en_vocab):
     """Test matcher allows empty token specs, meaning match on any token."""
     matcher = Matcher(en_vocab)
     doc = Doc(matcher.vocab, words=["a", "b", "c"])
-    matcher.add('A.C', None, [{'ORTH': 'a'}, {}, {'ORTH': 'c'}])
+    matcher.add("A.C", None, [{"ORTH": "a"}, {}, {"ORTH": "c"}])
     matches = matcher(doc)
     assert len(matches) == 1
     assert matches[0][1:] == (0, 3)
     matcher = Matcher(en_vocab)
-    matcher.add('A.', None, [{'ORTH': 'a'}, {}])
+    matcher.add("A.", None, [{"ORTH": "a"}, {}])
     matches = matcher(doc)
     assert matches[0][1:] == (0, 2)
 
@@ -107,8 +111,8 @@ def test_matcher_empty_dict(en_vocab):
 def test_matcher_operator_shadow(en_vocab):
     matcher = Matcher(en_vocab)
     doc = Doc(matcher.vocab, words=["a", "b", "c"])
-    pattern = [{'ORTH': 'a'}, {"IS_ALPHA": True, "OP": "+"}, {'ORTH': 'c'}]
-    matcher.add('A.C', None, pattern)
+    pattern = [{"ORTH": "a"}, {"IS_ALPHA": True, "OP": "+"}, {"ORTH": "c"}]
+    matcher.add("A.C", None, pattern)
     matches = matcher(doc)
     assert len(matches) == 1
     assert matches[0][1:] == (0, 3)
@@ -117,43 +121,48 @@ def test_matcher_operator_shadow(en_vocab):
 def test_matcher_match_zero(matcher):
     words1 = 'He said , " some words " ...'.split()
     words2 = 'He said , " some three words " ...'.split()
-    pattern1 = [{'ORTH': '"'},
-                {'OP': '!', 'IS_PUNCT': True},
-                {'OP': '!', 'IS_PUNCT': True},
-                {'ORTH': '"'}]
-    pattern2 = [{'ORTH': '"'},
-                {'IS_PUNCT': True},
-                {'IS_PUNCT': True},
-                {'IS_PUNCT': True},
-                {'ORTH': '"'}]
-    matcher.add('Quote', None, pattern1)
+    pattern1 = [
+        {"ORTH": '"'},
+        {"OP": "!", "IS_PUNCT": True},
+        {"OP": "!", "IS_PUNCT": True},
+        {"ORTH": '"'},
+    ]
+    pattern2 = [
+        {"ORTH": '"'},
+        {"IS_PUNCT": True},
+        {"IS_PUNCT": True},
+        {"IS_PUNCT": True},
+        {"ORTH": '"'},
+    ]
+    matcher.add("Quote", None, pattern1)
     doc = Doc(matcher.vocab, words=words1)
     assert len(matcher(doc)) == 1
     doc = Doc(matcher.vocab, words=words2)
     assert len(matcher(doc)) == 0
-    matcher.add('Quote', None, pattern2)
+    matcher.add("Quote", None, pattern2)
     assert len(matcher(doc)) == 0
 
 
 def test_matcher_match_zero_plus(matcher):
     words = 'He said , " some words " ...'.split()
-    pattern = [{'ORTH': '"'},
-                {'OP': '*', 'IS_PUNCT': False},
-                {'ORTH': '"'}]
+    pattern = [{"ORTH": '"'}, {"OP": "*", "IS_PUNCT": False}, {"ORTH": '"'}]
     matcher = Matcher(matcher.vocab)
-    matcher.add('Quote', None, pattern)
+    matcher.add("Quote", None, pattern)
     doc = Doc(matcher.vocab, words=words)
     assert len(matcher(doc)) == 1
 
 
 def test_matcher_match_one_plus(matcher):
     control = Matcher(matcher.vocab)
-    control.add('BasicPhilippe', None, [{'ORTH': 'Philippe'}])
-    doc = Doc(control.vocab, words=['Philippe', 'Philippe'])
+    control.add("BasicPhilippe", None, [{"ORTH": "Philippe"}])
+    doc = Doc(control.vocab, words=["Philippe", "Philippe"])
     m = control(doc)
     assert len(m) == 2
-    matcher.add('KleenePhilippe', None, [{'ORTH': 'Philippe', 'OP': '1'},
-                                         {'ORTH': 'Philippe', 'OP': '+'}])
+    matcher.add(
+        "KleenePhilippe",
+        None,
+        [{"ORTH": "Philippe", "OP": "1"}, {"ORTH": "Philippe", "OP": "+"}],
+    )
     m = matcher(doc)
     assert len(m) == 1
 
@@ -161,54 +170,70 @@ def test_matcher_match_one_plus(matcher):
 def test_matcher_any_token_operator(en_vocab):
     """Test that patterns with "any token" {} work with operators."""
     matcher = Matcher(en_vocab)
-    matcher.add('TEST', None, [{'ORTH': 'test'}, {'OP': '*'}])
-    doc = Doc(en_vocab, words=['test', 'hello', 'world'])
+    matcher.add("TEST", None, [{"ORTH": "test"}, {"OP": "*"}])
+    doc = Doc(en_vocab, words=["test", "hello", "world"])
     matches = [doc[start:end].text for _, start, end in matcher(doc)]
     assert len(matches) == 3
-    assert matches[0] == 'test'
-    assert matches[1] == 'test hello'
-    assert matches[2] == 'test hello world'
+    assert matches[0] == "test"
+    assert matches[1] == "test hello"
+    assert matches[2] == "test hello world"
 
 
 @pytest.fixture
 def text():
-    return u"The quick brown fox jumped over the lazy fox"
+    return "The quick brown fox jumped over the lazy fox"
+
 
 @pytest.fixture
 def heads():
-    return [3,2,1,1,0,-1,2,1,-3]
+    return [3, 2, 1, 1, 0, -1, 2, 1, -3]
+
 
 @pytest.fixture
 def deps():
-    return ['det', 'amod', 'amod', 'nsubj', 'prep', 'pobj', 'det', 'amod']
+    return ["det", "amod", "amod", "nsubj", "prep", "pobj", "det", "amod"]
+
 
 @pytest.fixture
 def dependency_tree_matcher(en_vocab):
-    is_brown_yellow = lambda text: bool(re.compile(r'brown|yellow|over').match(text))
+    def is_brown_yellow(text):
+        return bool(re.compile(r"brown|yellow|over").match(text))
+
     IS_BROWN_YELLOW = en_vocab.add_flag(is_brown_yellow)
     pattern1 = [
-        {'SPEC': {'NODE_NAME': 'fox'}, 'PATTERN': {'ORTH': 'fox'}},
-        {'SPEC': {'NODE_NAME': 'q', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'},'PATTERN': {'LOWER': u'quick'}},
-        {'SPEC': {'NODE_NAME': 'r', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
+        {"SPEC": {"NODE_NAME": "fox"}, "PATTERN": {"ORTH": "fox"}},
+        {
+            "SPEC": {"NODE_NAME": "q", "NBOR_RELOP": ">", "NBOR_NAME": "fox"},
+            "PATTERN": {"LOWER": "quick"},
+        },
+        {
+            "SPEC": {"NODE_NAME": "r", "NBOR_RELOP": ">", "NBOR_NAME": "fox"},
+            "PATTERN": {IS_BROWN_YELLOW: True},
+        },
     ]
 
     pattern2 = [
-        {'SPEC': {'NODE_NAME': 'jumped'}, 'PATTERN': {'ORTH': 'jumped'}},
-        {'SPEC': {'NODE_NAME': 'fox', 'NBOR_RELOP': '>', 'NBOR_NAME': 'jumped'},'PATTERN': {'LOWER': u'fox'}},
-        {'SPEC': {'NODE_NAME': 'over', 'NBOR_RELOP': '>', 'NBOR_NAME': 'fox'}, 'PATTERN': {IS_BROWN_YELLOW: True}}
+        {"SPEC": {"NODE_NAME": "jumped"}, "PATTERN": {"ORTH": "jumped"}},
+        {
+            "SPEC": {"NODE_NAME": "fox", "NBOR_RELOP": ">", "NBOR_NAME": "jumped"},
+            "PATTERN": {"LOWER": "fox"},
+        },
+        {
+            "SPEC": {"NODE_NAME": "over", "NBOR_RELOP": ">", "NBOR_NAME": "fox"},
+            "PATTERN": {IS_BROWN_YELLOW: True},
+        },
     ]
     matcher = DependencyTreeMatcher(en_vocab)
-    matcher.add('pattern1', None, pattern1)
-    matcher.add('pattern2', None, pattern2)
+    matcher.add("pattern1", None, pattern1)
+    matcher.add("pattern2", None, pattern2)
     return matcher
 
 
-
 def test_dependency_tree_matcher_compile(dependency_tree_matcher):
     assert len(dependency_tree_matcher) == 2
 
-def test_dependency_tree_matcher(dependency_tree_matcher,text,heads,deps):
-    doc = get_doc(dependency_tree_matcher.vocab,text.split(),heads=heads,deps=deps)
+
+def test_dependency_tree_matcher(dependency_tree_matcher, text, heads, deps):
+    doc = get_doc(dependency_tree_matcher.vocab, text.split(), heads=heads, deps=deps)
     matches = dependency_tree_matcher(doc)
     assert len(matches) == 2
-

spacy/tests/matcher/test_matcher_logic.py

@@ -7,17 +7,25 @@ from spacy.matcher import Matcher
 from spacy.tokens import Doc
 
 
-pattern1    = [{'ORTH':'A', 'OP':'1'}, {'ORTH':'A', 'OP':'*'}]
-pattern2    = [{'ORTH':'A', 'OP':'*'}, {'ORTH':'A', 'OP':'1'}]
-pattern3    = [{'ORTH':'A', 'OP':'1'}, {'ORTH':'A', 'OP':'1'}]
-pattern4    = [{'ORTH':'B', 'OP':'1'}, {'ORTH':'A', 'OP':'*'}, {'ORTH':'B', 'OP':'1'}]
-pattern5    = [{'ORTH':'B', 'OP':'*'}, {'ORTH':'A', 'OP':'*'}, {'ORTH':'B', 'OP':'1'}]
+pattern1 = [{"ORTH": "A", "OP": "1"}, {"ORTH": "A", "OP": "*"}]
+pattern2 = [{"ORTH": "A", "OP": "*"}, {"ORTH": "A", "OP": "1"}]
+pattern3 = [{"ORTH": "A", "OP": "1"}, {"ORTH": "A", "OP": "1"}]
+pattern4 = [
+    {"ORTH": "B", "OP": "1"},
+    {"ORTH": "A", "OP": "*"},
+    {"ORTH": "B", "OP": "1"},
+]
+pattern5 = [
+    {"ORTH": "B", "OP": "*"},
+    {"ORTH": "A", "OP": "*"},
+    {"ORTH": "B", "OP": "1"},
+]
 
-re_pattern1 = 'AA*'
-re_pattern2 = 'A*A'
-re_pattern3 = 'AA'
-re_pattern4 = 'BA*B'
-re_pattern5 = 'B*A*B'
+re_pattern1 = "AA*"
+re_pattern2 = "A*A"
+re_pattern3 = "AA"
+re_pattern4 = "BA*B"
+re_pattern5 = "B*A*B"
 
 
 @pytest.fixture
@@ -27,17 +35,20 @@ def text():
 
 @pytest.fixture
 def doc(en_tokenizer, text):
-    doc = en_tokenizer(' '.join(text))
+    doc = en_tokenizer(" ".join(text))
     return doc
 
 
-@pytest.mark.xfail
-@pytest.mark.parametrize('pattern,re_pattern', [
-    (pattern1, re_pattern1),
-    (pattern2, re_pattern2),
-    (pattern3, re_pattern3),
-    (pattern4, re_pattern4),
-    (pattern5, re_pattern5)])
+@pytest.mark.parametrize(
+    "pattern,re_pattern",
+    [
+        pytest.param(pattern1, re_pattern1, marks=pytest.mark.xfail()),
+        pytest.param(pattern2, re_pattern2, marks=pytest.mark.xfail()),
+        pytest.param(pattern3, re_pattern3, marks=pytest.mark.xfail()),
+        (pattern4, re_pattern4),
+        pytest.param(pattern5, re_pattern5, marks=pytest.mark.xfail()),
+    ],
+)
 def test_greedy_matching(doc, text, pattern, re_pattern):
     """Test that the greedy matching behavior of the * op is consistant with
     other re implementations."""
@@ -50,12 +61,16 @@ def test_greedy_matching(doc, text, pattern, re_pattern):
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize('pattern,re_pattern', [
-    (pattern1, re_pattern1),
-    (pattern2, re_pattern2),
-    (pattern3, re_pattern3),
-    (pattern4, re_pattern4),
-    (pattern5, re_pattern5)])
+@pytest.mark.parametrize(
+    "pattern,re_pattern",
+    [
+        (pattern1, re_pattern1),
+        (pattern2, re_pattern2),
+        (pattern3, re_pattern3),
+        (pattern4, re_pattern4),
+        (pattern5, re_pattern5),
+    ],
+)
 def test_match_consuming(doc, text, pattern, re_pattern):
     """Test that matcher.__call__ consumes tokens on a match similar to
     re.findall."""
@@ -68,33 +83,33 @@ def test_match_consuming(doc, text, pattern, re_pattern):
 
 def test_operator_combos(en_vocab):
     cases = [
-        ('aaab', 'a a a b', True),
-        ('aaab', 'a+ b', True),
-        ('aaab', 'a+ a+ b', True),
-        ('aaab', 'a+ a+ a b', True),
-        ('aaab', 'a+ a+ a+ b', True),
-        ('aaab', 'a+ a a b', True),
-        ('aaab', 'a+ a a', True),
-        ('aaab', 'a+', True),
-        ('aaa', 'a+ b', False),
-        ('aaa', 'a+ a+ b', False),
-        ('aaa', 'a+ a+ a+ b', False),
-        ('aaa', 'a+ a b', False),
-        ('aaa', 'a+ a a b', False),
-        ('aaab', 'a+ a a', True),
-        ('aaab', 'a+', True),
-        ('aaab', 'a+ a b', True)
+        ("aaab", "a a a b", True),
+        ("aaab", "a+ b", True),
+        ("aaab", "a+ a+ b", True),
+        ("aaab", "a+ a+ a b", True),
+        ("aaab", "a+ a+ a+ b", True),
+        ("aaab", "a+ a a b", True),
+        ("aaab", "a+ a a", True),
+        ("aaab", "a+", True),
+        ("aaa", "a+ b", False),
+        ("aaa", "a+ a+ b", False),
+        ("aaa", "a+ a+ a+ b", False),
+        ("aaa", "a+ a b", False),
+        ("aaa", "a+ a a b", False),
+        ("aaab", "a+ a a", True),
+        ("aaab", "a+", True),
+        ("aaab", "a+ a b", True),
     ]
     for string, pattern_str, result in cases:
         matcher = Matcher(en_vocab)
         doc = Doc(matcher.vocab, words=list(string))
         pattern = []
         for part in pattern_str.split():
-            if part.endswith('+'):
-                pattern.append({'ORTH': part[0], 'OP': '+'})
+            if part.endswith("+"):
+                pattern.append({"ORTH": part[0], "OP": "+"})
             else:
-                pattern.append({'ORTH': part})
-        matcher.add('PATTERN', None, pattern)
+                pattern.append({"ORTH": part})
+        matcher.add("PATTERN", None, pattern)
         matches = matcher(doc)
         if result:
             assert matches, (string, pattern_str)
@@ -105,12 +120,12 @@ def test_operator_combos(en_vocab):
 def test_matcher_end_zero_plus(en_vocab):
     """Test matcher works when patterns end with * operator. (issue 1450)"""
     matcher = Matcher(en_vocab)
-    pattern = [{'ORTH': "a"}, {'ORTH': "b", 'OP': "*"}]
-    matcher.add('TSTEND', None, pattern)
+    pattern = [{"ORTH": "a"}, {"ORTH": "b", "OP": "*"}]
+    matcher.add("TSTEND", None, pattern)
     nlp = lambda string: Doc(matcher.vocab, words=string.split())
-    assert len(matcher(nlp('a'))) == 1
-    assert len(matcher(nlp('a b'))) == 2
-    assert len(matcher(nlp('a c'))) == 1
-    assert len(matcher(nlp('a b c'))) == 2
-    assert len(matcher(nlp('a b b c'))) == 3
-    assert len(matcher(nlp('a b b'))) == 3
+    assert len(matcher(nlp("a"))) == 1
+    assert len(matcher(nlp("a b"))) == 2
+    assert len(matcher(nlp("a c"))) == 1
+    assert len(matcher(nlp("a b c"))) == 2
+    assert len(matcher(nlp("a b b c"))) == 3
+    assert len(matcher(nlp("a b b"))) == 3

spacy/tests/matcher/test_phrase_matcher.py

@@ -1,7 +1,6 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
-import pytest
 from spacy.matcher import PhraseMatcher
 from spacy.tokens import Doc
 
@@ -11,7 +10,7 @@ from ..util import get_doc
 def test_matcher_phrase_matcher(en_vocab):
     doc = Doc(en_vocab, words=["Google", "Now"])
     matcher = PhraseMatcher(en_vocab)
-    matcher.add('COMPANY', None, doc)
+    matcher.add("COMPANY", None, doc)
     doc = Doc(en_vocab, words=["I", "like", "Google", "Now", "best"])
     assert len(matcher(doc)) == 1
 
@@ -19,63 +18,63 @@ def test_matcher_phrase_matcher(en_vocab):
 def test_phrase_matcher_length(en_vocab):
     matcher = PhraseMatcher(en_vocab)
     assert len(matcher) == 0
-    matcher.add('TEST', None, Doc(en_vocab, words=['test']))
+    matcher.add("TEST", None, Doc(en_vocab, words=["test"]))
     assert len(matcher) == 1
-    matcher.add('TEST2', None, Doc(en_vocab, words=['test2']))
+    matcher.add("TEST2", None, Doc(en_vocab, words=["test2"]))
     assert len(matcher) == 2
 
 
 def test_phrase_matcher_contains(en_vocab):
     matcher = PhraseMatcher(en_vocab)
-    matcher.add('TEST', None, Doc(en_vocab, words=['test']))
-    assert 'TEST' in matcher
-    assert 'TEST2' not in matcher
+    matcher.add("TEST", None, Doc(en_vocab, words=["test"]))
+    assert "TEST" in matcher
+    assert "TEST2" not in matcher
 
 
 def test_phrase_matcher_string_attrs(en_vocab):
-    words1 = ['I', 'like', 'cats']
-    pos1 = ['PRON', 'VERB', 'NOUN']
-    words2 = ['Yes', ',', 'you', 'hate', 'dogs', 'very', 'much']
-    pos2 = ['INTJ', 'PUNCT', 'PRON', 'VERB', 'NOUN', 'ADV', 'ADV']
+    words1 = ["I", "like", "cats"]
+    pos1 = ["PRON", "VERB", "NOUN"]
+    words2 = ["Yes", ",", "you", "hate", "dogs", "very", "much"]
+    pos2 = ["INTJ", "PUNCT", "PRON", "VERB", "NOUN", "ADV", "ADV"]
     pattern = get_doc(en_vocab, words=words1, pos=pos1)
-    matcher = PhraseMatcher(en_vocab, attr='POS')
-    matcher.add('TEST', None, pattern)
+    matcher = PhraseMatcher(en_vocab, attr="POS")
+    matcher.add("TEST", None, pattern)
     doc = get_doc(en_vocab, words=words2, pos=pos2)
     matches = matcher(doc)
     assert len(matches) == 1
     match_id, start, end = matches[0]
-    assert match_id == en_vocab.strings['TEST']
+    assert match_id == en_vocab.strings["TEST"]
     assert start == 2
     assert end == 5
 
 
 def test_phrase_matcher_string_attrs_negative(en_vocab):
     """Test that token with the control codes as ORTH are *not* matched."""
-    words1 = ['I', 'like', 'cats']
-    pos1 = ['PRON', 'VERB', 'NOUN']
-    words2 = ['matcher:POS-PRON', 'matcher:POS-VERB', 'matcher:POS-NOUN']
-    pos2 = ['X', 'X', 'X']
+    words1 = ["I", "like", "cats"]
+    pos1 = ["PRON", "VERB", "NOUN"]
+    words2 = ["matcher:POS-PRON", "matcher:POS-VERB", "matcher:POS-NOUN"]
+    pos2 = ["X", "X", "X"]
     pattern = get_doc(en_vocab, words=words1, pos=pos1)
-    matcher = PhraseMatcher(en_vocab, attr='POS')
-    matcher.add('TEST', None, pattern)
+    matcher = PhraseMatcher(en_vocab, attr="POS")
+    matcher.add("TEST", None, pattern)
     doc = get_doc(en_vocab, words=words2, pos=pos2)
     matches = matcher(doc)
     assert len(matches) == 0
 
 
 def test_phrase_matcher_bool_attrs(en_vocab):
-    words1 = ['Hello', 'world', '!']
-    words2 = ['No', 'problem', ',', 'he', 'said', '.']
+    words1 = ["Hello", "world", "!"]
+    words2 = ["No", "problem", ",", "he", "said", "."]
     pattern = Doc(en_vocab, words=words1)
-    matcher = PhraseMatcher(en_vocab, attr='IS_PUNCT')
-    matcher.add('TEST', None, pattern)
+    matcher = PhraseMatcher(en_vocab, attr="IS_PUNCT")
+    matcher.add("TEST", None, pattern)
     doc = Doc(en_vocab, words=words2)
     matches = matcher(doc)
     assert len(matches) == 2
     match_id1, start1, end1 = matches[0]
     match_id2, start2, end2 = matches[1]
-    assert match_id1 == en_vocab.strings['TEST']
-    assert match_id2 == en_vocab.strings['TEST']
+    assert match_id1 == en_vocab.strings["TEST"]
+    assert match_id2 == en_vocab.strings["TEST"]
     assert start1 == 0
     assert end1 == 3
     assert start2 == 3

spacy/tests/parser/test_add_label.py

@@ -2,7 +2,6 @@
 from __future__ import unicode_literals
 
 import pytest
-import numpy.random
 from thinc.neural.optimizers import Adam
 from thinc.neural.ops import NumpyOps
 from spacy.attrs import NORM
@@ -20,18 +19,17 @@ def vocab():
 @pytest.fixture
 def parser(vocab):
     parser = DependencyParser(vocab)
-    parser.cfg['token_vector_width'] = 8
-    parser.cfg['hidden_width'] = 30
-    parser.cfg['hist_size'] = 0
-    parser.add_label('left')
+    parser.cfg["token_vector_width"] = 8
+    parser.cfg["hidden_width"] = 30
+    parser.cfg["hist_size"] = 0
+    parser.add_label("left")
     parser.begin_training([], **parser.cfg)
     sgd = Adam(NumpyOps(), 0.001)
 
     for i in range(10):
         losses = {}
-        doc = Doc(vocab, words=['a', 'b', 'c', 'd'])
-        gold = GoldParse(doc, heads=[1, 1, 3, 3],
-                deps=['left', 'ROOT', 'left', 'ROOT'])
+        doc = Doc(vocab, words=["a", "b", "c", "d"])
+        gold = GoldParse(doc, heads=[1, 1, 3, 3], deps=["left", "ROOT", "left", "ROOT"])
         parser.update([doc], [gold], sgd=sgd, losses=losses)
     return parser
 
@@ -44,29 +42,30 @@ def test_init_parser(parser):
 # TODO: This now seems to be implicated in segfaults. Not sure what's up!
 @pytest.mark.skip
 def test_add_label(parser):
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc = parser(doc)
     assert doc[0].head.i == 1
-    assert doc[0].dep_ == 'left'
+    assert doc[0].dep_ == "left"
     assert doc[1].head.i == 1
     assert doc[2].head.i == 3
     assert doc[2].head.i == 3
-    parser.add_label('right')
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    parser.add_label("right")
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc = parser(doc)
     assert doc[0].head.i == 1
-    assert doc[0].dep_ == 'left'
+    assert doc[0].dep_ == "left"
     assert doc[1].head.i == 1
     assert doc[2].head.i == 3
     assert doc[2].head.i == 3
     sgd = Adam(NumpyOps(), 0.001)
     for i in range(10):
         losses = {}
-        doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
-        gold = GoldParse(doc, heads=[1, 1, 3, 3],
-                deps=['right', 'ROOT', 'left', 'ROOT'])
+        doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
+        gold = GoldParse(
+            doc, heads=[1, 1, 3, 3], deps=["right", "ROOT", "left", "ROOT"]
+        )
         parser.update([doc], [gold], sgd=sgd, losses=losses)
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc = parser(doc)
-    assert doc[0].dep_ == 'right'
-    assert doc[2].dep_ == 'left'
+    assert doc[0].dep_ == "right"
+    assert doc[2].dep_ == "left"

spacy/tests/parser/test_arc_eager_oracle.py

@@ -31,16 +31,19 @@ def get_sequence_costs(M, words, heads, deps, transitions):
 def vocab():
     return Vocab()
 
+
 @pytest.fixture
 def arc_eager(vocab):
     moves = ArcEager(vocab.strings, ArcEager.get_actions())
-    moves.add_action(2, 'left')
-    moves.add_action(3, 'right')
+    moves.add_action(2, "left")
+    moves.add_action(3, "right")
     return moves
 
+
 @pytest.fixture
 def words():
-    return ['a', 'b']
+    return ["a", "b"]
+
 
 @pytest.fixture
 def doc(words, vocab):
@@ -48,19 +51,21 @@ def doc(words, vocab):
         vocab = Vocab()
     return Doc(vocab, words=list(words))
 
+
 @pytest.fixture
 def gold(doc, words):
     if len(words) == 2:
-        return GoldParse(doc, words=['a', 'b'], heads=[0, 0], deps=['ROOT', 'right'])
+        return GoldParse(doc, words=["a", "b"], heads=[0, 0], deps=["ROOT", "right"])
     else:
         raise NotImplementedError
 
+
 @pytest.mark.xfail
 def test_oracle_four_words(arc_eager, vocab):
-    words = ['a', 'b', 'c', 'd']
+    words = ["a", "b", "c", "d"]
     heads = [1, 1, 3, 3]
-    deps = ['left', 'ROOT', 'left', 'ROOT']
-    actions = ['L-left', 'B-ROOT', 'L-left']
+    deps = ["left", "ROOT", "left", "ROOT"]
+    actions = ["L-left", "B-ROOT", "L-left"]
     state, cost_history = get_sequence_costs(arc_eager, words, heads, deps, actions)
     assert state.is_final()
     for i, state_costs in enumerate(cost_history):
@@ -72,63 +77,65 @@ def test_oracle_four_words(arc_eager, vocab):
 
 
 annot_tuples = [
-    (0, 'When', 'WRB', 11, 'advmod', 'O'),
-    (1, 'Walter', 'NNP', 2, 'compound', 'B-PERSON'),
-    (2, 'Rodgers', 'NNP', 11, 'nsubj', 'L-PERSON'),
-    (3, ',', ',', 2, 'punct', 'O'),
-    (4, 'our', 'PRP$', 6, 'poss', 'O'),
-    (5, 'embedded', 'VBN', 6, 'amod', 'O'),
-    (6, 'reporter', 'NN', 2, 'appos', 'O'),
-    (7, 'with', 'IN', 6, 'prep', 'O'),
-    (8, 'the', 'DT', 10, 'det', 'B-ORG'),
-    (9, '3rd', 'NNP', 10, 'compound', 'I-ORG'),
-    (10, 'Cavalry', 'NNP', 7, 'pobj', 'L-ORG'),
-    (11, 'says', 'VBZ', 44, 'advcl', 'O'),
-    (12, 'three', 'CD', 13, 'nummod', 'U-CARDINAL'),
-    (13, 'battalions', 'NNS', 16, 'nsubj', 'O'),
-    (14, 'of', 'IN', 13, 'prep', 'O'),
-    (15, 'troops', 'NNS', 14, 'pobj', 'O'),
-    (16, 'are', 'VBP', 11, 'ccomp', 'O'),
-    (17, 'on', 'IN', 16, 'prep', 'O'),
-    (18, 'the', 'DT', 19, 'det', 'O'),
-    (19, 'ground', 'NN', 17, 'pobj', 'O'),
-    (20, ',', ',', 17, 'punct', 'O'),
-    (21, 'inside', 'IN', 17, 'prep', 'O'),
-    (22, 'Baghdad', 'NNP', 21, 'pobj', 'U-GPE'),
-    (23, 'itself', 'PRP', 22, 'appos', 'O'),
-    (24, ',', ',', 16, 'punct', 'O'),
-    (25, 'have', 'VBP', 26, 'aux', 'O'),
-    (26, 'taken', 'VBN', 16, 'dep', 'O'),
-    (27, 'up', 'RP', 26, 'prt', 'O'),
-    (28, 'positions', 'NNS', 26, 'dobj', 'O'),
-    (29, 'they', 'PRP', 31, 'nsubj', 'O'),
-    (30, "'re", 'VBP', 31, 'aux', 'O'),
-    (31, 'going', 'VBG', 26, 'parataxis', 'O'),
-    (32, 'to', 'TO', 33, 'aux', 'O'),
-    (33, 'spend', 'VB', 31, 'xcomp', 'O'),
-    (34, 'the', 'DT', 35, 'det', 'B-TIME'),
-    (35, 'night', 'NN', 33, 'dobj', 'L-TIME'),
-    (36, 'there', 'RB', 33, 'advmod', 'O'),
-    (37, 'presumably', 'RB', 33, 'advmod', 'O'),
-    (38, ',', ',', 44, 'punct', 'O'),
-    (39, 'how', 'WRB', 40, 'advmod', 'O'),
-    (40, 'many', 'JJ', 41, 'amod', 'O'),
-    (41, 'soldiers', 'NNS', 44, 'pobj', 'O'),
-    (42, 'are', 'VBP', 44, 'aux', 'O'),
-    (43, 'we', 'PRP', 44, 'nsubj', 'O'),
-    (44, 'talking', 'VBG', 44, 'ROOT', 'O'),
-    (45, 'about', 'IN', 44, 'prep', 'O'),
-    (46, 'right', 'RB', 47, 'advmod', 'O'),
-    (47, 'now', 'RB', 44, 'advmod', 'O'),
-    (48, '?', '.', 44, 'punct', 'O')]
+    (0, "When", "WRB", 11, "advmod", "O"),
+    (1, "Walter", "NNP", 2, "compound", "B-PERSON"),
+    (2, "Rodgers", "NNP", 11, "nsubj", "L-PERSON"),
+    (3, ",", ",", 2, "punct", "O"),
+    (4, "our", "PRP$", 6, "poss", "O"),
+    (5, "embedded", "VBN", 6, "amod", "O"),
+    (6, "reporter", "NN", 2, "appos", "O"),
+    (7, "with", "IN", 6, "prep", "O"),
+    (8, "the", "DT", 10, "det", "B-ORG"),
+    (9, "3rd", "NNP", 10, "compound", "I-ORG"),
+    (10, "Cavalry", "NNP", 7, "pobj", "L-ORG"),
+    (11, "says", "VBZ", 44, "advcl", "O"),
+    (12, "three", "CD", 13, "nummod", "U-CARDINAL"),
+    (13, "battalions", "NNS", 16, "nsubj", "O"),
+    (14, "of", "IN", 13, "prep", "O"),
+    (15, "troops", "NNS", 14, "pobj", "O"),
+    (16, "are", "VBP", 11, "ccomp", "O"),
+    (17, "on", "IN", 16, "prep", "O"),
+    (18, "the", "DT", 19, "det", "O"),
+    (19, "ground", "NN", 17, "pobj", "O"),
+    (20, ",", ",", 17, "punct", "O"),
+    (21, "inside", "IN", 17, "prep", "O"),
+    (22, "Baghdad", "NNP", 21, "pobj", "U-GPE"),
+    (23, "itself", "PRP", 22, "appos", "O"),
+    (24, ",", ",", 16, "punct", "O"),
+    (25, "have", "VBP", 26, "aux", "O"),
+    (26, "taken", "VBN", 16, "dep", "O"),
+    (27, "up", "RP", 26, "prt", "O"),
+    (28, "positions", "NNS", 26, "dobj", "O"),
+    (29, "they", "PRP", 31, "nsubj", "O"),
+    (30, "'re", "VBP", 31, "aux", "O"),
+    (31, "going", "VBG", 26, "parataxis", "O"),
+    (32, "to", "TO", 33, "aux", "O"),
+    (33, "spend", "VB", 31, "xcomp", "O"),
+    (34, "the", "DT", 35, "det", "B-TIME"),
+    (35, "night", "NN", 33, "dobj", "L-TIME"),
+    (36, "there", "RB", 33, "advmod", "O"),
+    (37, "presumably", "RB", 33, "advmod", "O"),
+    (38, ",", ",", 44, "punct", "O"),
+    (39, "how", "WRB", 40, "advmod", "O"),
+    (40, "many", "JJ", 41, "amod", "O"),
+    (41, "soldiers", "NNS", 44, "pobj", "O"),
+    (42, "are", "VBP", 44, "aux", "O"),
+    (43, "we", "PRP", 44, "nsubj", "O"),
+    (44, "talking", "VBG", 44, "ROOT", "O"),
+    (45, "about", "IN", 44, "prep", "O"),
+    (46, "right", "RB", 47, "advmod", "O"),
+    (47, "now", "RB", 44, "advmod", "O"),
+    (48, "?", ".", 44, "punct", "O"),
+]
+
 
 def test_get_oracle_actions():
     doc = Doc(Vocab(), words=[t[1] for t in annot_tuples])
     parser = DependencyParser(doc.vocab)
-    parser.moves.add_action(0, '')
-    parser.moves.add_action(1, '')
-    parser.moves.add_action(1, '')
-    parser.moves.add_action(4, 'ROOT')
+    parser.moves.add_action(0, "")
+    parser.moves.add_action(1, "")
+    parser.moves.add_action(1, "")
+    parser.moves.add_action(4, "ROOT")
     for i, (id_, word, tag, head, dep, ent) in enumerate(annot_tuples):
         if head > i:
             parser.moves.add_action(2, dep)

spacy/tests/parser/test_ner.py

@@ -16,15 +16,17 @@ def vocab():
 
 @pytest.fixture
 def doc(vocab):
-    return Doc(vocab, words=['Casey', 'went', 'to', 'New', 'York', '.'])
+    return Doc(vocab, words=["Casey", "went", "to", "New", "York", "."])
 
 
 @pytest.fixture
 def entity_annots(doc):
     casey = doc[0:1]
     ny = doc[3:5]
-    return [(casey.start_char, casey.end_char, 'PERSON'),
-            (ny.start_char, ny.end_char, 'GPE')]
+    return [
+        (casey.start_char, casey.end_char, "PERSON"),
+        (ny.start_char, ny.end_char, "GPE"),
+    ]
 
 
 @pytest.fixture
@@ -43,32 +45,33 @@ def test_get_oracle_moves(tsys, doc, entity_annots):
     tsys.preprocess_gold(gold)
     act_classes = tsys.get_oracle_sequence(doc, gold)
     names = [tsys.get_class_name(act) for act in act_classes]
-    assert names == ['U-PERSON', 'O', 'O', 'B-GPE', 'L-GPE', 'O']
+    assert names == ["U-PERSON", "O", "O", "B-GPE", "L-GPE", "O"]
+
 
 def test_get_oracle_moves_negative_entities(tsys, doc, entity_annots):
-    entity_annots = [(s, e, '!' + label) for s, e, label in entity_annots]
+    entity_annots = [(s, e, "!" + label) for s, e, label in entity_annots]
     gold = GoldParse(doc, entities=entity_annots)
     for i, tag in enumerate(gold.ner):
-        if tag == 'L-!GPE':
-            gold.ner[i] = '-'
+        if tag == "L-!GPE":
+            gold.ner[i] = "-"
     tsys.preprocess_gold(gold)
     act_classes = tsys.get_oracle_sequence(doc, gold)
     names = [tsys.get_class_name(act) for act in act_classes]
 
 
 def test_get_oracle_moves_negative_entities2(tsys, vocab):
-    doc = Doc(vocab, words=['A', 'B', 'C', 'D'])
+    doc = Doc(vocab, words=["A", "B", "C", "D"])
     gold = GoldParse(doc, entities=[])
-    gold.ner = ['B-!PERSON', 'L-!PERSON', 'B-!PERSON', 'L-!PERSON']
+    gold.ner = ["B-!PERSON", "L-!PERSON", "B-!PERSON", "L-!PERSON"]
     tsys.preprocess_gold(gold)
     act_classes = tsys.get_oracle_sequence(doc, gold)
     names = [tsys.get_class_name(act) for act in act_classes]
 
 
 def test_get_oracle_moves_negative_O(tsys, vocab):
-    doc = Doc(vocab, words=['A', 'B', 'C', 'D'])
+    doc = Doc(vocab, words=["A", "B", "C", "D"])
     gold = GoldParse(doc, entities=[])
-    gold.ner = ['O', '!O', 'O', '!O']
+    gold.ner = ["O", "!O", "O", "!O"]
     tsys.preprocess_gold(gold)
     act_classes = tsys.get_oracle_sequence(doc, gold)
     names = [tsys.get_class_name(act) for act in act_classes]
@@ -80,8 +83,8 @@ def test_doc_add_entities_set_ents_iob(en_vocab):
     ner.begin_training([])
     ner(doc)
     assert len(list(doc.ents)) == 0
-    assert [w.ent_iob_ for w in doc] == (['O'] * len(doc))
-    doc.ents = [(doc.vocab.strings['ANIMAL'], 3, 4)]
-    assert [w.ent_iob_ for w in doc] == ['', '', '', 'B']
-    doc.ents = [(doc.vocab.strings['WORD'], 0, 2)]
-    assert [w.ent_iob_ for w in doc] == ['B', 'I', '', '']
+    assert [w.ent_iob_ for w in doc] == (["O"] * len(doc))
+    doc.ents = [(doc.vocab.strings["ANIMAL"], 3, 4)]
+    assert [w.ent_iob_ for w in doc] == ["", "", "", "B"]
+    doc.ents = [(doc.vocab.strings["WORD"], 0, 2)]
+    assert [w.ent_iob_ for w in doc] == ["B", "I", "", ""]

spacy/tests/parser/test_neural_parser.py

@@ -17,7 +17,7 @@ def vocab():
 
 @pytest.fixture
 def arc_eager(vocab):
-    actions = ArcEager.get_actions(left_labels=['L'], right_labels=['R'])
+    actions = ArcEager.get_actions(left_labels=["L"], right_labels=["R"])
     return ArcEager(vocab.strings, actions)
 
 
@@ -30,6 +30,7 @@ def tok2vec():
 def parser(vocab, arc_eager):
     return Parser(vocab, moves=arc_eager, model=None)
 
+
 @pytest.fixture
 def model(arc_eager, tok2vec):
     return Parser.Model(arc_eager.n_moves, token_vector_width=tok2vec.nO)[0]
@@ -37,12 +38,12 @@ def model(arc_eager, tok2vec):
 
 @pytest.fixture
 def doc(vocab):
-    return Doc(vocab, words=['a', 'b', 'c'])
+    return Doc(vocab, words=["a", "b", "c"])
 
 
 @pytest.fixture
 def gold(doc):
-    return GoldParse(doc, heads=[1, 1, 1], deps=['L', 'ROOT', 'R'])
+    return GoldParse(doc, heads=[1, 1, 1], deps=["L", "ROOT", "R"])
 
 
 def test_can_init_nn_parser(parser):
@@ -62,8 +63,10 @@ def test_predict_doc(parser, tok2vec, model, doc):
 
 def test_update_doc(parser, model, doc, gold):
     parser.model = model
+
     def optimize(weights, gradient, key=None):
         weights -= 0.001 * gradient
+
     parser.update([doc], [gold], sgd=optimize)
 
 
@@ -76,6 +79,8 @@ def test_predict_doc_beam(parser, model, doc):
 @pytest.mark.xfail
 def test_update_doc_beam(parser, model, doc, gold):
     parser.model = model
+
     def optimize(weights, gradient, key=None):
         weights -= 0.001 * gradient
+
     parser.update_beam([doc], [gold], sgd=optimize)

spacy/tests/parser/test_nn_beam.py

@@ -21,20 +21,22 @@ def vocab():
 @pytest.fixture
 def moves(vocab):
     aeager = ArcEager(vocab.strings, {})
-    aeager.add_action(2, 'nsubj')
-    aeager.add_action(3, 'dobj')
-    aeager.add_action(2, 'aux')
+    aeager.add_action(2, "nsubj")
+    aeager.add_action(3, "dobj")
+    aeager.add_action(2, "aux")
     return aeager
 
 
 @pytest.fixture
 def docs(vocab):
-    return [Doc(vocab, words=['Rats', 'bite', 'things'])]
+    return [Doc(vocab, words=["Rats", "bite", "things"])]
+
 
 @pytest.fixture
 def states(docs):
     return [StateClass(doc) for doc in docs]
 
+
 @pytest.fixture
 def tokvecs(docs, vector_size):
     output = []
@@ -73,9 +75,10 @@ def beam(moves, states, golds, beam_width):
 def scores(moves, batch_size, beam_width):
     return [
         numpy.asarray(
-            numpy.random.uniform(-0.1, 0.1, (batch_size, moves.n_moves)),
-            dtype='f')
-        for _ in range(batch_size)]
+            numpy.random.uniform(-0.1, 0.1, (batch_size, moves.n_moves)), dtype="f"
+        )
+        for _ in range(batch_size)
+    ]
 
 
 def test_create_beam(beam):
@@ -93,8 +96,8 @@ def test_beam_advance_too_few_scores(beam, scores):
 
 def test_beam_parse():
     nlp = Language()
-    nlp.add_pipe(DependencyParser(nlp.vocab), name='parser')
-    nlp.parser.add_label('nsubj')
+    nlp.add_pipe(DependencyParser(nlp.vocab), name="parser")
+    nlp.parser.add_label("nsubj")
     nlp.parser.begin_training([], token_vector_width=8, hidden_width=8)
-    doc = nlp.make_doc('Australia is a country')
+    doc = nlp.make_doc("Australia is a country")
     nlp.parser(doc, beam_width=2)

spacy/tests/parser/test_nonproj.py

@@ -40,106 +40,116 @@ def multirooted_tree():
 
 
 def test_parser_ancestors(tree, cyclic_tree, partial_tree, multirooted_tree):
-    assert([a for a in ancestors(3, tree)] == [4, 5, 2])
-    assert([a for a in ancestors(3, cyclic_tree)] == [4, 5, 3, 4, 5, 3, 4])
-    assert([a for a in ancestors(3, partial_tree)] == [4, 5, None])
-    assert([a for a in ancestors(17, multirooted_tree)] == [])
+    assert [a for a in ancestors(3, tree)] == [4, 5, 2]
+    assert [a for a in ancestors(3, cyclic_tree)] == [4, 5, 3, 4, 5, 3, 4]
+    assert [a for a in ancestors(3, partial_tree)] == [4, 5, None]
+    assert [a for a in ancestors(17, multirooted_tree)] == []
 
 
 def test_parser_contains_cycle(tree, cyclic_tree, partial_tree, multirooted_tree):
-    assert(contains_cycle(tree) == None)
-    assert(contains_cycle(cyclic_tree) == set([3, 4, 5]))
-    assert(contains_cycle(partial_tree) == None)
-    assert(contains_cycle(multirooted_tree) == None)
+    assert contains_cycle(tree) == None
+    assert contains_cycle(cyclic_tree) == set([3, 4, 5])
+    assert contains_cycle(partial_tree) == None
+    assert contains_cycle(multirooted_tree) == None
 
 
 def test_parser_is_nonproj_arc(nonproj_tree, partial_tree, multirooted_tree):
-    assert(is_nonproj_arc(0, nonproj_tree) == False)
-    assert(is_nonproj_arc(1, nonproj_tree) == False)
-    assert(is_nonproj_arc(2, nonproj_tree) == False)
-    assert(is_nonproj_arc(3, nonproj_tree) == False)
-    assert(is_nonproj_arc(4, nonproj_tree) == False)
-    assert(is_nonproj_arc(5, nonproj_tree) == False)
-    assert(is_nonproj_arc(6, nonproj_tree) == False)
-    assert(is_nonproj_arc(7, nonproj_tree) == True)
-    assert(is_nonproj_arc(8, nonproj_tree) == False)
-    assert(is_nonproj_arc(7, partial_tree) == False)
-    assert(is_nonproj_arc(17, multirooted_tree) == False)
-    assert(is_nonproj_arc(16, multirooted_tree) == True)
+    assert is_nonproj_arc(0, nonproj_tree) == False
+    assert is_nonproj_arc(1, nonproj_tree) == False
+    assert is_nonproj_arc(2, nonproj_tree) == False
+    assert is_nonproj_arc(3, nonproj_tree) == False
+    assert is_nonproj_arc(4, nonproj_tree) == False
+    assert is_nonproj_arc(5, nonproj_tree) == False
+    assert is_nonproj_arc(6, nonproj_tree) == False
+    assert is_nonproj_arc(7, nonproj_tree) == True
+    assert is_nonproj_arc(8, nonproj_tree) == False
+    assert is_nonproj_arc(7, partial_tree) == False
+    assert is_nonproj_arc(17, multirooted_tree) == False
+    assert is_nonproj_arc(16, multirooted_tree) == True
 
 
-def test_parser_is_nonproj_tree(proj_tree, nonproj_tree, partial_tree, multirooted_tree):
-    assert(is_nonproj_tree(proj_tree) == False)
-    assert(is_nonproj_tree(nonproj_tree) == True)
-    assert(is_nonproj_tree(partial_tree) == False)
-    assert(is_nonproj_tree(multirooted_tree) == True)
+def test_parser_is_nonproj_tree(
+    proj_tree, nonproj_tree, partial_tree, multirooted_tree
+):
+    assert is_nonproj_tree(proj_tree) == False
+    assert is_nonproj_tree(nonproj_tree) == True
+    assert is_nonproj_tree(partial_tree) == False
+    assert is_nonproj_tree(multirooted_tree) == True
 
 
 def test_parser_pseudoprojectivity(en_tokenizer):
     def deprojectivize(proj_heads, deco_labels):
-        tokens = en_tokenizer('whatever ' * len(proj_heads))
-        rel_proj_heads = [head-i for i, head in enumerate(proj_heads)]
-        doc = get_doc(tokens.vocab, words=[t.text for t in tokens],
-                      deps=deco_labels, heads=rel_proj_heads)
+        tokens = en_tokenizer("whatever " * len(proj_heads))
+        rel_proj_heads = [head - i for i, head in enumerate(proj_heads)]
+        doc = get_doc(
+            tokens.vocab,
+            words=[t.text for t in tokens],
+            deps=deco_labels,
+            heads=rel_proj_heads,
+        )
         nonproj.deprojectivize(doc)
         return [t.head.i for t in doc], [token.dep_ for token in doc]
 
+    # fmt: off
     tree = [1, 2, 2]
     nonproj_tree = [1, 2, 2, 4, 5, 2, 7, 4, 2]
     nonproj_tree2 = [9, 1, 3, 1, 5, 6, 9, 8, 6, 1, 6, 12, 13, 10, 1]
-    labels = ['det', 'nsubj', 'root', 'det', 'dobj', 'aux', 'nsubj', 'acl', 'punct']
-    labels2 = ['advmod', 'root', 'det', 'nsubj', 'advmod', 'det', 'dobj', 'det', 'nmod', 'aux', 'nmod', 'advmod', 'det', 'amod', 'punct']
+    labels = ["det", "nsubj", "root", "det", "dobj", "aux", "nsubj", "acl", "punct"]
+    labels2 = ["advmod", "root", "det", "nsubj", "advmod", "det", "dobj", "det", "nmod", "aux", "nmod", "advmod", "det", "amod", "punct"]
+    # fmt: on
 
-    assert(nonproj.decompose('X||Y') == ('X','Y'))
-    assert(nonproj.decompose('X') == ('X',''))
-    assert(nonproj.is_decorated('X||Y') == True)
-    assert(nonproj.is_decorated('X') == False)
+    assert nonproj.decompose("X||Y") == ("X", "Y")
+    assert nonproj.decompose("X") == ("X", "")
+    assert nonproj.is_decorated("X||Y") == True
+    assert nonproj.is_decorated("X") == False
 
     nonproj._lift(0, tree)
-    assert(tree == [2, 2, 2])
+    assert tree == [2, 2, 2]
 
-    assert(nonproj._get_smallest_nonproj_arc(nonproj_tree) == 7)
-    assert(nonproj._get_smallest_nonproj_arc(nonproj_tree2) == 10)
+    assert nonproj._get_smallest_nonproj_arc(nonproj_tree) == 7
+    assert nonproj._get_smallest_nonproj_arc(nonproj_tree2) == 10
 
+    # fmt: off
     proj_heads, deco_labels = nonproj.projectivize(nonproj_tree, labels)
-    assert(proj_heads == [1, 2, 2, 4, 5, 2, 7, 5, 2])
-    assert(deco_labels == ['det', 'nsubj', 'root', 'det', 'dobj', 'aux',
-                           'nsubj', 'acl||dobj', 'punct'])
+    assert proj_heads == [1, 2, 2, 4, 5, 2, 7, 5, 2]
+    assert deco_labels == ["det", "nsubj", "root", "det", "dobj", "aux",
+                           "nsubj", "acl||dobj", "punct"]
 
     deproj_heads, undeco_labels = deprojectivize(proj_heads, deco_labels)
-    assert(deproj_heads == nonproj_tree)
-    assert(undeco_labels == labels)
+    assert deproj_heads == nonproj_tree
+    assert undeco_labels == labels
 
     proj_heads, deco_labels = nonproj.projectivize(nonproj_tree2, labels2)
-    assert(proj_heads == [1, 1, 3, 1, 5, 6, 9, 8, 6, 1, 9, 12, 13, 10, 1])
-    assert(deco_labels == ['advmod||aux', 'root', 'det', 'nsubj', 'advmod',
-                           'det', 'dobj', 'det', 'nmod', 'aux', 'nmod||dobj',
-                           'advmod', 'det', 'amod', 'punct'])
+    assert proj_heads == [1, 1, 3, 1, 5, 6, 9, 8, 6, 1, 9, 12, 13, 10, 1]
+    assert deco_labels == ["advmod||aux", "root", "det", "nsubj", "advmod",
+                           "det", "dobj", "det", "nmod", "aux", "nmod||dobj",
+                           "advmod", "det", "amod", "punct"]
 
     deproj_heads, undeco_labels = deprojectivize(proj_heads, deco_labels)
-    assert(deproj_heads == nonproj_tree2)
-    assert(undeco_labels == labels2)
+    assert deproj_heads == nonproj_tree2
+    assert undeco_labels == labels2
 
     # if decoration is wrong such that there is no head with the desired label
     # the structure is kept and the label is undecorated
     proj_heads = [1, 2, 2, 4, 5, 2, 7, 5, 2]
-    deco_labels = ['det', 'nsubj', 'root', 'det', 'dobj', 'aux', 'nsubj',
-                   'acl||iobj', 'punct']
+    deco_labels = ["det", "nsubj", "root", "det", "dobj", "aux", "nsubj",
+                   "acl||iobj", "punct"]
 
     deproj_heads, undeco_labels = deprojectivize(proj_heads, deco_labels)
-    assert(deproj_heads == proj_heads)
-    assert(undeco_labels == ['det', 'nsubj', 'root', 'det', 'dobj', 'aux',
-                             'nsubj', 'acl', 'punct'])
+    assert deproj_heads == proj_heads
+    assert undeco_labels == ["det", "nsubj", "root", "det", "dobj", "aux",
+                             "nsubj", "acl", "punct"]
 
     # if there are two potential new heads, the first one is chosen even if
-    # it's wrong
+    # it"s wrong
     proj_heads = [1, 1, 3, 1, 5, 6, 9, 8, 6, 1, 9, 12, 13, 10, 1]
-    deco_labels = ['advmod||aux', 'root', 'det', 'aux', 'advmod', 'det',
-                   'dobj', 'det', 'nmod', 'aux', 'nmod||dobj', 'advmod',
-                   'det', 'amod', 'punct']
+    deco_labels = ["advmod||aux", "root", "det", "aux", "advmod", "det",
+                   "dobj", "det", "nmod", "aux", "nmod||dobj", "advmod",
+                   "det", "amod", "punct"]
 
     deproj_heads, undeco_labels = deprojectivize(proj_heads, deco_labels)
-    assert(deproj_heads == [3, 1, 3, 1, 5, 6, 9, 8, 6, 1, 6, 12, 13, 10, 1])
-    assert(undeco_labels == ['advmod', 'root', 'det', 'aux', 'advmod', 'det',
-                             'dobj', 'det', 'nmod', 'aux', 'nmod', 'advmod',
-                             'det', 'amod', 'punct'])
+    assert deproj_heads == [3, 1, 3, 1, 5, 6, 9, 8, 6, 1, 6, 12, 13, 10, 1]
+    assert undeco_labels == ["advmod", "root", "det", "aux", "advmod", "det",
+                             "dobj", "det", "nmod", "aux", "nmod", "advmod",
+                             "det", "amod", "punct"]
+    # fmt: on

spacy/tests/parser/test_parse.py

@@ -9,7 +9,7 @@ from ..util import get_doc, apply_transition_sequence
 def test_parser_root(en_tokenizer):
     text = "i don't have other assistance"
     heads = [3, 2, 1, 0, 1, -2]
-    deps = ['nsubj', 'aux', 'neg', 'ROOT', 'amod', 'dobj']
+    deps = ["nsubj", "aux", "neg", "ROOT", "amod", "dobj"]
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     for t in doc:
@@ -17,10 +17,12 @@ def test_parser_root(en_tokenizer):
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize('text', ["Hello"])
+@pytest.mark.parametrize("text", ["Hello"])
 def test_parser_parse_one_word_sentence(en_tokenizer, en_parser, text):
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[0], deps=['ROOT'])
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], heads=[0], deps=["ROOT"]
+    )
 
     assert len(doc) == 1
     with en_parser.step_through(doc) as _:
@@ -32,7 +34,7 @@ def test_parser_parse_one_word_sentence(en_tokenizer, en_parser, text):
 def test_parser_initial(en_tokenizer, en_parser):
     text = "I ate the pizza with anchovies."
     heads = [1, 0, 1, -2, -3, -1, -5]
-    transition = ['L-nsubj', 'S', 'L-det']
+    transition = ["L-nsubj", "S", "L-det"]
     tokens = en_tokenizer(text)
     apply_transition_sequence(en_parser, tokens, transition)
     assert tokens[0].head.i == 1
@@ -58,17 +60,19 @@ def test_parser_parse_subtrees(en_tokenizer, en_parser):
 def test_parser_merge_pp(en_tokenizer):
     text = "A phrase with another phrase occurs"
     heads = [1, 4, -1, 1, -2, 0]
-    deps = ['det', 'nsubj', 'prep', 'det', 'pobj', 'ROOT']
-    tags = ['DT', 'NN', 'IN', 'DT', 'NN', 'VBZ']
+    deps = ["det", "nsubj", "prep", "det", "pobj", "ROOT"]
+    tags = ["DT", "NN", "IN", "DT", "NN", "VBZ"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], deps=deps, heads=heads, tags=tags)
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], deps=deps, heads=heads, tags=tags
+    )
     nps = [(np[0].idx, np[-1].idx + len(np[-1]), np.lemma_) for np in doc.noun_chunks]
     for start, end, lemma in nps:
-        doc.merge(start, end, label='NP', lemma=lemma)
-    assert doc[0].text == 'A phrase'
-    assert doc[1].text == 'with'
-    assert doc[2].text == 'another phrase'
-    assert doc[3].text == 'occurs'
+        doc.merge(start, end, label="NP", lemma=lemma)
+    assert doc[0].text == "A phrase"
+    assert doc[1].text == "with"
+    assert doc[2].text == "another phrase"
+    assert doc[3].text == "occurs"
 
 
 @pytest.mark.xfail
@@ -76,7 +80,7 @@ def test_parser_arc_eager_finalize_state(en_tokenizer, en_parser):
     text = "a b c d e"
 
     # right branching
-    transition = ['R-nsubj', 'D', 'R-nsubj', 'R-nsubj', 'D', 'R-ROOT']
+    transition = ["R-nsubj", "D", "R-nsubj", "R-nsubj", "D", "R-ROOT"]
     tokens = en_tokenizer(text)
     apply_transition_sequence(en_parser, tokens, transition)
 
@@ -111,7 +115,7 @@ def test_parser_arc_eager_finalize_state(en_tokenizer, en_parser):
     assert tokens[4].head.i == 2
 
     # left branching
-    transition = ['S', 'S', 'S', 'L-nsubj','L-nsubj','L-nsubj', 'L-nsubj']
+    transition = ["S", "S", "S", "L-nsubj", "L-nsubj", "L-nsubj", "L-nsubj"]
     tokens = en_tokenizer(text)
     apply_transition_sequence(en_parser, tokens, transition)
 

spacy/tests/parser/test_parse_navigate.py

@@ -33,6 +33,7 @@ BIG BROTHER IS WATCHING YOU, the caption beneath it ran.
 
 @pytest.fixture
 def heads():
+    # fmt: off
     return [1, 1, 0, 3, 2, 1, -4, -1, -1, -7, -8, 1, -10, 2, 1, -3, -1, -15,
             -1, 1, 4, -1, 1, -3, 0, -1, 1, -2, -4, 1, -2, 1, -2, 3, -1, 1,
             -4, -13, -14, -1, -2, 2, 1, -3, -1, 1, -2, -9, -1, 3, 1, 1, -14,
@@ -50,6 +51,7 @@ def heads():
             0, -1, 1, -2, -4, 1, 0, -1, -1, 2, -1, -3, 1, -2, 1, -2, 3, 1,
             1, -4, -1, -2, 2, 1, -5, -19, -1, 1, 1, 0, 1, 6, -1, 1, -3, -1,
             -1, -8, -9, -1]
+    # fmt: on
 
 
 def test_parser_parse_navigate_consistency(en_tokenizer, text, heads):
@@ -100,7 +102,14 @@ def test_parser_parse_navigate_edges(en_tokenizer, text, heads):
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
     for token in doc:
         subtree = list(token.subtree)
-        debug = '\t'.join((token.text, token.left_edge.text, subtree[0].text))
+        debug = "\t".join((token.text, token.left_edge.text, subtree[0].text))
         assert token.left_edge == subtree[0], debug
-        debug = '\t'.join((token.text, token.right_edge.text, subtree[-1].text, token.right_edge.head.text))
+        debug = "\t".join(
+            (
+                token.text,
+                token.right_edge.text,
+                subtree[-1].text,
+                token.right_edge.head.text,
+            )
+        )
         assert token.right_edge == subtree[-1], debug

spacy/tests/parser/test_preset_sbd.py

@@ -19,34 +19,33 @@ def vocab():
 @pytest.fixture
 def parser(vocab):
     parser = DependencyParser(vocab)
-    parser.cfg['token_vector_width'] = 4
-    parser.cfg['hidden_width'] = 32
-    #parser.add_label('right')
-    parser.add_label('left')
+    parser.cfg["token_vector_width"] = 4
+    parser.cfg["hidden_width"] = 32
+    # parser.add_label('right')
+    parser.add_label("left")
     parser.begin_training([], **parser.cfg)
     sgd = Adam(NumpyOps(), 0.001)
 
     for i in range(10):
         losses = {}
-        doc = Doc(vocab, words=['a', 'b', 'c', 'd'])
-        gold = GoldParse(doc, heads=[1, 1, 3, 3],
-                deps=['left', 'ROOT', 'left', 'ROOT'])
+        doc = Doc(vocab, words=["a", "b", "c", "d"])
+        gold = GoldParse(doc, heads=[1, 1, 3, 3], deps=["left", "ROOT", "left", "ROOT"])
         parser.update([doc], [gold], sgd=sgd, losses=losses)
     return parser
 
 
 def test_no_sentences(parser):
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc = parser(doc)
     assert len(list(doc.sents)) >= 1
 
 
 def test_sents_1(parser):
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc[2].sent_start = True
     doc = parser(doc)
     assert len(list(doc.sents)) >= 2
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc[1].sent_start = False
     doc[2].sent_start = True
     doc[3].sent_start = False
@@ -55,7 +54,7 @@ def test_sents_1(parser):
 
 
 def test_sents_1_2(parser):
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc[1].sent_start = True
     doc[2].sent_start = True
     doc = parser(doc)
@@ -63,12 +62,12 @@ def test_sents_1_2(parser):
 
 
 def test_sents_1_3(parser):
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc[1].sent_start = True
     doc[3].sent_start = True
     doc = parser(doc)
     assert len(list(doc.sents)) >= 3
-    doc = Doc(parser.vocab, words=['a', 'b', 'c', 'd'])
+    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
     doc[1].sent_start = True
     doc[2].sent_start = False
     doc[3].sent_start = True

spacy/tests/parser/test_space_attachment.py

@@ -19,11 +19,13 @@ def test_parser_space_attachment(en_tokenizer):
 
 
 def test_parser_sentence_space(en_tokenizer):
+    # fmt: off
     text = "I look forward to using Thingamajig.  I've been told it will make my life easier..."
     heads = [1, 0, -1, -2, -1, -1, -5, -1, 3, 2, 1, 0, 2, 1, -3, 1, 1, -3, -7]
-    deps = ['nsubj', 'ROOT', 'advmod', 'prep', 'pcomp', 'dobj', 'punct', '',
-            'nsubjpass', 'aux', 'auxpass', 'ROOT', 'nsubj', 'aux', 'ccomp',
-            'poss', 'nsubj', 'ccomp', 'punct']
+    deps = ["nsubj", "ROOT", "advmod", "prep", "pcomp", "dobj", "punct", "",
+            "nsubjpass", "aux", "auxpass", "ROOT", "nsubj", "aux", "ccomp",
+            "poss", "nsubj", "ccomp", "punct"]
+    # fmt: on
     tokens = en_tokenizer(text)
     doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
     assert len(list(doc.sents)) == 2
@@ -34,10 +36,10 @@ def test_parser_space_attachment_leading(en_tokenizer, en_parser):
     text = "\t \n This is a sentence ."
     heads = [1, 1, 0, 1, -2, -3]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=text.split(' '), heads=heads)
+    doc = get_doc(tokens.vocab, words=text.split(" "), heads=heads)
     assert doc[0].is_space
     assert doc[1].is_space
-    assert doc[2].text == 'This'
+    assert doc[2].text == "This"
     with en_parser.step_through(doc) as stepwise:
         pass
     assert doc[0].head.i == 2
@@ -49,9 +51,9 @@ def test_parser_space_attachment_leading(en_tokenizer, en_parser):
 def test_parser_space_attachment_intermediate_trailing(en_tokenizer, en_parser):
     text = "This is \t a \t\n \n sentence . \n\n \n"
     heads = [1, 0, -1, 2, -1, -4, -5, -1]
-    transition = ['L-nsubj', 'S', 'L-det', 'R-attr', 'D', 'R-punct']
+    transition = ["L-nsubj", "S", "L-det", "R-attr", "D", "R-punct"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=text.split(' '), heads=heads)
+    doc = get_doc(tokens.vocab, words=text.split(" "), heads=heads)
     assert doc[2].is_space
     assert doc[4].is_space
     assert doc[5].is_space
@@ -64,8 +66,7 @@ def test_parser_space_attachment_intermediate_trailing(en_tokenizer, en_parser):
     assert [token.head.i for token in doc] == [1, 1, 1, 6, 3, 3, 1, 1, 7, 7]
 
 
-@pytest.mark.parametrize('text,length', [(['\n'], 1),
-                                         (['\n', '\t', '\n\n', '\t'], 4)])
+@pytest.mark.parametrize("text,length", [(["\n"], 1), (["\n", "\t", "\n\n", "\t"], 4)])
 @pytest.mark.xfail
 def test_parser_space_attachment_space(en_tokenizer, en_parser, text, length):
     doc = Doc(en_parser.vocab, words=text)
@@ -74,4 +75,4 @@ def test_parser_space_attachment_space(en_tokenizer, en_parser, text, length):
         pass
     assert doc[0].is_space
     for token in doc:
-        assert token.head.i == length-1
+        assert token.head.i == length - 1

spacy/tests/pipeline/test_entity_ruler.py

@@ -18,14 +18,16 @@ def patterns():
         {"label": "HELLO", "pattern": "hello world"},
         {"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
         {"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
-        {"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]}
+        {"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
     ]
 
+
 @pytest.fixture
 def add_ent():
     def add_ent_component(doc):
-        doc.ents = [Span(doc, 0, 3, label=doc.vocab.strings['ORG'])]
+        doc.ents = [Span(doc, 0, 3, label=doc.vocab.strings["ORG"])]
         return doc
+
     return add_ent_component
 
 
@@ -33,13 +35,13 @@ def test_entity_ruler_init(nlp, patterns):
     ruler = EntityRuler(nlp, patterns=patterns)
     assert len(ruler) == len(patterns)
     assert len(ruler.labels) == 3
-    assert 'HELLO' in ruler
-    assert 'BYE' in ruler
+    assert "HELLO" in ruler
+    assert "BYE" in ruler
     nlp.add_pipe(ruler)
     doc = nlp("hello world bye bye")
     assert len(doc.ents) == 2
-    assert doc.ents[0].label_ == 'HELLO'
-    assert doc.ents[1].label_ == 'BYE'
+    assert doc.ents[0].label_ == "HELLO"
+    assert doc.ents[1].label_ == "BYE"
 
 
 def test_entity_ruler_existing(nlp, patterns, add_ent):
@@ -48,8 +50,8 @@ def test_entity_ruler_existing(nlp, patterns, add_ent):
     nlp.add_pipe(ruler)
     doc = nlp("OH HELLO WORLD bye bye")
     assert len(doc.ents) == 2
-    assert doc.ents[0].label_ == 'ORG'
-    assert doc.ents[1].label_ == 'BYE'
+    assert doc.ents[0].label_ == "ORG"
+    assert doc.ents[1].label_ == "BYE"
 
 
 def test_entity_ruler_existing_overwrite(nlp, patterns, add_ent):
@@ -58,9 +60,9 @@ def test_entity_ruler_existing_overwrite(nlp, patterns, add_ent):
     nlp.add_pipe(ruler)
     doc = nlp("OH HELLO WORLD bye bye")
     assert len(doc.ents) == 2
-    assert doc.ents[0].label_ == 'HELLO'
-    assert doc.ents[0].text == 'HELLO'
-    assert doc.ents[1].label_ == 'BYE'
+    assert doc.ents[0].label_ == "HELLO"
+    assert doc.ents[0].text == "HELLO"
+    assert doc.ents[1].label_ == "BYE"
 
 
 def test_entity_ruler_existing_complex(nlp, patterns, add_ent):
@@ -69,8 +71,8 @@ def test_entity_ruler_existing_complex(nlp, patterns, add_ent):
     nlp.add_pipe(ruler)
     doc = nlp("foo foo bye bye")
     assert len(doc.ents) == 2
-    assert doc.ents[0].label_ == 'COMPLEX'
-    assert doc.ents[1].label_ == 'BYE'
+    assert doc.ents[0].label_ == "COMPLEX"
+    assert doc.ents[1].label_ == "BYE"
     assert len(doc.ents[0]) == 2
     assert len(doc.ents[1]) == 2
 

spacy/tests/pipeline/test_factories.py

@@ -10,15 +10,21 @@ from ..util import get_doc
 
 @pytest.fixture
 def doc(en_tokenizer):
-    text = 'I like New York in Autumn.'
+    text = "I like New York in Autumn."
     heads = [1, 0, 1, -2, -3, -1, -5]
-    tags = ['PRP', 'IN', 'NNP', 'NNP', 'IN', 'NNP', '.']
-    pos = ['PRON', 'VERB', 'PROPN', 'PROPN', 'ADP', 'PROPN', 'PUNCT']
-    deps = ['ROOT', 'prep', 'compound', 'pobj', 'prep', 'pobj', 'punct']
+    tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
+    pos = ["PRON", "VERB", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
+    deps = ["ROOT", "prep", "compound", "pobj", "prep", "pobj", "punct"]
     tokens = en_tokenizer(text)
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads,
-                  tags=tags, pos=pos, deps=deps)
-    doc.ents = [Span(doc, 2, 4, doc.vocab.strings['GPE'])]
+    doc = get_doc(
+        tokens.vocab,
+        words=[t.text for t in tokens],
+        heads=heads,
+        tags=tags,
+        pos=pos,
+        deps=deps,
+    )
+    doc.ents = [Span(doc, 2, 4, doc.vocab.strings["GPE"])]
     doc.is_parsed = True
     doc.is_tagged = True
     return doc
@@ -27,18 +33,18 @@ def doc(en_tokenizer):
 def test_factories_merge_noun_chunks(doc):
     assert len(doc) == 7
     nlp = Language()
-    merge_noun_chunks = nlp.create_pipe('merge_noun_chunks')
+    merge_noun_chunks = nlp.create_pipe("merge_noun_chunks")
     merge_noun_chunks(doc)
     assert len(doc) == 6
-    assert doc[2].text == 'New York'
+    assert doc[2].text == "New York"
 
 
 def test_factories_merge_ents(doc):
     assert len(doc) == 7
     assert len(list(doc.ents)) == 1
     nlp = Language()
-    merge_entities = nlp.create_pipe('merge_entities')
+    merge_entities = nlp.create_pipe("merge_entities")
     merge_entities(doc)
     assert len(doc) == 6
     assert len(list(doc.ents)) == 1
-    assert doc[2].text == 'New York'
+    assert doc[2].text == "New York"

spacy/tests/pipeline/test_pipe_methods.py

@@ -16,22 +16,22 @@ def new_pipe(doc):
 
 def test_add_pipe_no_name(nlp):
     nlp.add_pipe(new_pipe)
-    assert 'new_pipe' in nlp.pipe_names
+    assert "new_pipe" in nlp.pipe_names
 
 
 def test_add_pipe_duplicate_name(nlp):
-    nlp.add_pipe(new_pipe, name='duplicate_name')
+    nlp.add_pipe(new_pipe, name="duplicate_name")
     with pytest.raises(ValueError):
-        nlp.add_pipe(new_pipe, name='duplicate_name')
+        nlp.add_pipe(new_pipe, name="duplicate_name")
 
 
-@pytest.mark.parametrize('name', ['parser'])
+@pytest.mark.parametrize("name", ["parser"])
 def test_add_pipe_first(nlp, name):
     nlp.add_pipe(new_pipe, name=name, first=True)
     assert nlp.pipeline[0][0] == name
 
 
-@pytest.mark.parametrize('name1,name2', [('parser', 'lambda_pipe')])
+@pytest.mark.parametrize("name1,name2", [("parser", "lambda_pipe")])
 def test_add_pipe_last(nlp, name1, name2):
     nlp.add_pipe(lambda doc: doc, name=name2)
     nlp.add_pipe(new_pipe, name=name1, last=True)
@@ -44,7 +44,7 @@ def test_cant_add_pipe_first_and_last(nlp):
         nlp.add_pipe(new_pipe, first=True, last=True)
 
 
-@pytest.mark.parametrize('name', ['my_component'])
+@pytest.mark.parametrize("name", ["my_component"])
 def test_get_pipe(nlp, name):
     with pytest.raises(KeyError):
         nlp.get_pipe(name)
@@ -52,7 +52,7 @@ def test_get_pipe(nlp, name):
     assert nlp.get_pipe(name) == new_pipe
 
 
-@pytest.mark.parametrize('name,replacement', [('my_component', lambda doc: doc)])
+@pytest.mark.parametrize("name,replacement", [("my_component", lambda doc: doc)])
 def test_replace_pipe(nlp, name, replacement):
     with pytest.raises(ValueError):
         nlp.replace_pipe(name, new_pipe)
@@ -62,7 +62,7 @@ def test_replace_pipe(nlp, name, replacement):
     assert nlp.get_pipe(name) == replacement
 
 
-@pytest.mark.parametrize('old_name,new_name', [('old_pipe', 'new_pipe')])
+@pytest.mark.parametrize("old_name,new_name", [("old_pipe", "new_pipe")])
 def test_rename_pipe(nlp, old_name, new_name):
     with pytest.raises(ValueError):
         nlp.rename_pipe(old_name, new_name)
@@ -71,7 +71,7 @@ def test_rename_pipe(nlp, old_name, new_name):
     assert nlp.pipeline[0][0] == new_name
 
 
-@pytest.mark.parametrize('name', ['my_component'])
+@pytest.mark.parametrize("name", ["my_component"])
 def test_remove_pipe(nlp, name):
     with pytest.raises(ValueError):
         nlp.remove_pipe(name)
@@ -83,7 +83,7 @@ def test_remove_pipe(nlp, name):
     assert removed_component == new_pipe
 
 
-@pytest.mark.parametrize('name', ['my_component'])
+@pytest.mark.parametrize("name", ["my_component"])
 def test_disable_pipes_method(nlp, name):
     nlp.add_pipe(new_pipe, name=name)
     assert nlp.has_pipe(name)
@@ -92,7 +92,7 @@ def test_disable_pipes_method(nlp, name):
     disabled.restore()
 
 
-@pytest.mark.parametrize('name', ['my_component'])
+@pytest.mark.parametrize("name", ["my_component"])
 def test_disable_pipes_context(nlp, name):
     nlp.add_pipe(new_pipe, name=name)
     assert nlp.has_pipe(name)
@@ -101,14 +101,14 @@ def test_disable_pipes_context(nlp, name):
     assert nlp.has_pipe(name)
 
 
-@pytest.mark.parametrize('n_pipes', [100])
+@pytest.mark.parametrize("n_pipes", [100])
 def test_add_lots_of_pipes(nlp, n_pipes):
     for i in range(n_pipes):
-        nlp.add_pipe(lambda doc: doc, name='pipe_%d' % i)
+        nlp.add_pipe(lambda doc: doc, name="pipe_%d" % i)
     assert len(nlp.pipe_names) == n_pipes
 
 
-@pytest.mark.parametrize('component', ['ner', {'hello': 'world'}])
+@pytest.mark.parametrize("component", ["ner", {"hello": "world"}])
 def test_raise_for_invalid_components(nlp, component):
     with pytest.raises(ValueError):
         nlp.add_pipe(component)

spacy/tests/pipeline/test_textcat.py

@@ -13,16 +13,21 @@ from spacy.gold import GoldParse
 @pytest.mark.skip(reason="Test is flakey when run with others")
 def test_simple_train():
     nlp = Language()
-    nlp.add_pipe(nlp.create_pipe('textcat'))
-    nlp.get_pipe('textcat').add_label('answer')
+    nlp.add_pipe(nlp.create_pipe("textcat"))
+    nlp.get_pipe("textcat").add_label("answer")
     nlp.begin_training()
     for i in range(5):
-        for text, answer in [('aaaa', 1.), ('bbbb', 0), ('aa', 1.),
-                            ('bbbbbbbbb', 0.), ('aaaaaa', 1)]:
-            nlp.update([text], [{'cats': {'answer': answer}}])
-    doc = nlp('aaa')
-    assert 'answer' in doc.cats
-    assert doc.cats['answer'] >= 0.5
+        for text, answer in [
+            ("aaaa", 1.0),
+            ("bbbb", 0),
+            ("aa", 1.0),
+            ("bbbbbbbbb", 0.0),
+            ("aaaaaa", 1),
+        ]:
+            nlp.update([text], [{"cats": {"answer": answer}}])
+    doc = nlp("aaa")
+    assert "answer" in doc.cats
+    assert doc.cats["answer"] >= 0.5
 
 
 @pytest.mark.skip(reason="Test is flakey when run with others")
@@ -31,11 +36,11 @@ def test_textcat_learns_multilabel():
     numpy.random.seed(5)
     docs = []
     nlp = Language()
-    letters = ['a', 'b', 'c']
+    letters = ["a", "b", "c"]
     for w1 in letters:
         for w2 in letters:
-            cats = {letter: float(w2==letter) for letter in letters}
-            docs.append((Doc(nlp.vocab, words=['d']*3 + [w1, w2] + ['d']*3), cats))
+            cats = {letter: float(w2 == letter) for letter in letters}
+            docs.append((Doc(nlp.vocab, words=["d"] * 3 + [w1, w2] + ["d"] * 3), cats))
     random.shuffle(docs)
     model = TextCategorizer(nlp.vocab, width=8)
     for letter in letters:
@@ -49,8 +54,8 @@ def test_textcat_learns_multilabel():
         random.shuffle(docs)
     for w1 in letters:
         for w2 in letters:
-            doc = Doc(nlp.vocab, words=['d']*3 + [w1, w2] + ['d']*3)
-            truth = {letter: w2==letter for letter in letters}
+            doc = Doc(nlp.vocab, words=["d"] * 3 + [w1, w2] + ["d"] * 3)
+            truth = {letter: w2 == letter for letter in letters}
             model(doc)
             for cat, score in doc.cats.items():
                 if not truth[cat]:

spacy/tests/regression/test_issue1-1000.py

@@ -14,14 +14,20 @@ from spacy.tokens import Doc
 from ..util import get_doc, make_tempdir
 
 
-@pytest.mark.parametrize('patterns', [
-    [[{'LOWER': 'celtics'}], [{'LOWER': 'boston'}, {'LOWER': 'celtics'}]],
-    [[{'LOWER': 'boston'}, {'LOWER': 'celtics'}], [{'LOWER': 'celtics'}]]])
+@pytest.mark.parametrize(
+    "patterns",
+    [
+        [[{"LOWER": "celtics"}], [{"LOWER": "boston"}, {"LOWER": "celtics"}]],
+        [[{"LOWER": "boston"}, {"LOWER": "celtics"}], [{"LOWER": "celtics"}]],
+    ],
+)
 def test_issue118(en_tokenizer, patterns):
     """Test a bug that arose from having overlapping matches"""
-    text = "how many points did lebron james score against the boston celtics last night"
+    text = (
+        "how many points did lebron james score against the boston celtics last night"
+    )
     doc = en_tokenizer(text)
-    ORG = doc.vocab.strings['ORG']
+    ORG = doc.vocab.strings["ORG"]
     matcher = Matcher(doc.vocab)
     matcher.add("BostonCeltics", None, *patterns)
     assert len(list(doc.ents)) == 0
@@ -35,16 +41,22 @@ def test_issue118(en_tokenizer, patterns):
     assert ents[0].end == 11
 
 
-@pytest.mark.parametrize('patterns', [
-    [[{'LOWER': 'boston'}], [{'LOWER': 'boston'}, {'LOWER': 'celtics'}]],
-    [[{'LOWER': 'boston'}, {'LOWER': 'celtics'}], [{'LOWER': 'boston'}]]])
+@pytest.mark.parametrize(
+    "patterns",
+    [
+        [[{"LOWER": "boston"}], [{"LOWER": "boston"}, {"LOWER": "celtics"}]],
+        [[{"LOWER": "boston"}, {"LOWER": "celtics"}], [{"LOWER": "boston"}]],
+    ],
+)
 def test_issue118_prefix_reorder(en_tokenizer, patterns):
     """Test a bug that arose from having overlapping matches"""
-    text = "how many points did lebron james score against the boston celtics last night"
+    text = (
+        "how many points did lebron james score against the boston celtics last night"
+    )
     doc = en_tokenizer(text)
-    ORG = doc.vocab.strings['ORG']
+    ORG = doc.vocab.strings["ORG"]
     matcher = Matcher(doc.vocab)
-    matcher.add('BostonCeltics', None, *patterns)
+    matcher.add("BostonCeltics", None, *patterns)
     assert len(list(doc.ents)) == 0
     matches = [(ORG, start, end) for _, start, end in matcher(doc)]
     doc.ents += tuple(matches)[1:]
@@ -59,11 +71,13 @@ def test_issue118_prefix_reorder(en_tokenizer, patterns):
 def test_issue242(en_tokenizer):
     """Test overlapping multi-word phrases."""
     text = "There are different food safety standards in different countries."
-    patterns = [[{'LOWER': 'food'}, {'LOWER': 'safety'}],
-                [{'LOWER': 'safety'}, {'LOWER': 'standards'}]]
+    patterns = [
+        [{"LOWER": "food"}, {"LOWER": "safety"}],
+        [{"LOWER": "safety"}, {"LOWER": "standards"}],
+    ]
     doc = en_tokenizer(text)
     matcher = Matcher(doc.vocab)
-    matcher.add('FOOD', None, *patterns)
+    matcher.add("FOOD", None, *patterns)
 
     matches = [(ent_type, start, end) for ent_type, start, end in matcher(doc)]
     doc.ents += tuple(matches)
@@ -77,7 +91,9 @@ def test_issue242(en_tokenizer):
 def test_issue309(en_tokenizer):
     """Test Issue #309: SBD fails on empty string"""
     tokens = en_tokenizer(" ")
-    doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[0], deps=['ROOT'])
+    doc = get_doc(
+        tokens.vocab, words=[t.text for t in tokens], heads=[0], deps=["ROOT"]
+    )
     doc.is_parsed = True
     assert len(doc) == 1
     sents = list(doc.sents)
@@ -93,11 +109,11 @@ def test_issue351(en_tokenizer):
 
 def test_issue360(en_tokenizer):
     """Test tokenization of big ellipsis"""
-    tokens = en_tokenizer('$45...............Asking')
+    tokens = en_tokenizer("$45...............Asking")
     assert len(tokens) > 2
 
 
-@pytest.mark.parametrize('text1,text2', [("cat", "dog")])
+@pytest.mark.parametrize("text1,text2", [("cat", "dog")])
 def test_issue361(en_vocab, text1, text2):
     """Test Issue #361: Equality of lexemes"""
     assert en_vocab[text1] == en_vocab[text1]
@@ -106,15 +122,19 @@ def test_issue361(en_vocab, text1, text2):
 
 def test_issue587(en_tokenizer):
     """Test that Matcher doesn't segfault on particular input"""
-    doc = en_tokenizer('a b; c')
+    doc = en_tokenizer("a b; c")
     matcher = Matcher(doc.vocab)
-    matcher.add('TEST1', None, [{ORTH: 'a'}, {ORTH: 'b'}])
+    matcher.add("TEST1", None, [{ORTH: "a"}, {ORTH: "b"}])
     matches = matcher(doc)
     assert len(matches) == 1
-    matcher.add('TEST2', None, [{ORTH: 'a'}, {ORTH: 'b'}, {IS_PUNCT: True}, {ORTH: 'c'}])
+    matcher.add(
+        "TEST2", None, [{ORTH: "a"}, {ORTH: "b"}, {IS_PUNCT: True}, {ORTH: "c"}]
+    )
     matches = matcher(doc)
     assert len(matches) == 2
-    matcher.add('TEST3', None, [{ORTH: 'a'}, {ORTH: 'b'}, {IS_PUNCT: True}, {ORTH: 'd'}])
+    matcher.add(
+        "TEST3", None, [{ORTH: "a"}, {ORTH: "b"}, {IS_PUNCT: True}, {ORTH: "d"}]
+    )
     matches = matcher(doc)
     assert len(matches) == 2
 
@@ -122,22 +142,26 @@ def test_issue587(en_tokenizer):
 def test_issue588(en_vocab):
     matcher = Matcher(en_vocab)
     with pytest.raises(ValueError):
-        matcher.add('TEST', None, [])
+        matcher.add("TEST", None, [])
 
 
 @pytest.mark.xfail
 def test_issue589():
     vocab = Vocab()
     vocab.strings.set_frozen(True)
-    doc = Doc(vocab, words=['whata'])
+    doc = Doc(vocab, words=["whata"])
 
 
 def test_issue590(en_vocab):
     """Test overlapping matches"""
-    doc = Doc(en_vocab, words=['n', '=', '1', ';', 'a', ':', '5', '%'])
+    doc = Doc(en_vocab, words=["n", "=", "1", ";", "a", ":", "5", "%"])
     matcher = Matcher(en_vocab)
-    matcher.add('ab', None, [{'IS_ALPHA': True}, {'ORTH': ':'}, {'LIKE_NUM': True}, {'ORTH': '%'}])
-    matcher.add('ab', None, [{'IS_ALPHA': True}, {'ORTH': '='}, {'LIKE_NUM': True}])
+    matcher.add(
+        "ab",
+        None,
+        [{"IS_ALPHA": True}, {"ORTH": ":"}, {"LIKE_NUM": True}, {"ORTH": "%"}],
+    )
+    matcher.add("ab", None, [{"IS_ALPHA": True}, {"ORTH": "="}, {"LIKE_NUM": True}])
     matches = matcher(doc)
     assert len(matches) == 2
 
@@ -145,14 +169,14 @@ def test_issue590(en_vocab):
 def test_issue595():
     """Test lemmatization of base forms"""
     words = ["Do", "n't", "feed", "the", "dog"]
-    tag_map = {'VB': {POS: VERB, VerbForm_inf: True}}
+    tag_map = {"VB": {POS: VERB, VerbForm_inf: True}}
     rules = {"verb": [["ed", "e"]]}
-    lemmatizer = Lemmatizer({'verb': {}}, {'verb': {}}, rules)
+    lemmatizer = Lemmatizer({"verb": {}}, {"verb": {}}, rules)
     vocab = Vocab(lemmatizer=lemmatizer, tag_map=tag_map)
     doc = Doc(vocab, words=words)
-    doc[2].tag_ = 'VB'
-    assert doc[2].text == 'feed'
-    assert doc[2].lemma_ == 'feed'
+    doc[2].tag_ = "VB"
+    assert doc[2].text == "feed"
+    assert doc[2].lemma_ == "feed"
 
 
 def test_issue599(en_vocab):
@@ -165,9 +189,9 @@ def test_issue599(en_vocab):
 
 
 def test_issue600():
-    vocab = Vocab(tag_map={'NN': {'pos': 'NOUN'}})
+    vocab = Vocab(tag_map={"NN": {"pos": "NOUN"}})
     doc = Doc(vocab, words=["hello"])
-    doc[0].tag_ = 'NN'
+    doc[0].tag_ = "NN"
 
 
 def test_issue615(en_tokenizer):
@@ -175,16 +199,17 @@ def test_issue615(en_tokenizer):
         """Merge a phrase. We have to be careful here because we'll change the
         token indices. To avoid problems, merge all the phrases once we're called
         on the last match."""
-        if i != len(matches)-1:
+        if i != len(matches) - 1:
             return None
-        spans = [(ent_id, ent_id, doc[start : end]) for ent_id, start, end in matches]
+        spans = [(ent_id, ent_id, doc[start:end]) for ent_id, start, end in matches]
         for ent_id, label, span in spans:
-            span.merge(tag='NNP' if label else span.root.tag_, lemma=span.text,
-                label=label)
+            span.merge(
+                tag="NNP" if label else span.root.tag_, lemma=span.text, label=label
+            )
             doc.ents = doc.ents + ((label, span.start, span.end),)
 
     text = "The golf club is broken"
-    pattern = [{'ORTH': "golf"}, {'ORTH': "club"}]
+    pattern = [{"ORTH": "golf"}, {"ORTH": "club"}]
     label = "Sport_Equipment"
     doc = en_tokenizer(text)
     matcher = Matcher(doc.vocab)
@@ -195,7 +220,7 @@ def test_issue615(en_tokenizer):
     assert entities[0].label != 0
 
 
-@pytest.mark.parametrize('text,number', [("7am", "7"), ("11p.m.", "11")])
+@pytest.mark.parametrize("text,number", [("7am", "7"), ("11p.m.", "11")])
 def test_issue736(en_tokenizer, text, number):
     """Test that times like "7am" are tokenized correctly and that numbers are
     converted to string."""
@@ -204,7 +229,7 @@ def test_issue736(en_tokenizer, text, number):
     assert tokens[0].text == number
 
 
-@pytest.mark.parametrize('text', ["3/4/2012", "01/12/1900"])
+@pytest.mark.parametrize("text", ["3/4/2012", "01/12/1900"])
 def test_issue740(en_tokenizer, text):
     """Test that dates are not split and kept as one token. This behaviour is
     currently inconsistent, since dates separated by hyphens are still split.
@@ -214,14 +239,14 @@ def test_issue740(en_tokenizer, text):
 
 
 def test_issue743():
-    doc = Doc(Vocab(), ['hello', 'world'])
+    doc = Doc(Vocab(), ["hello", "world"])
     token = doc[0]
     s = set([token])
     items = list(s)
     assert items[0] is token
 
 
-@pytest.mark.parametrize('text', ["We were scared", "We Were Scared"])
+@pytest.mark.parametrize("text", ["We were scared", "We Were Scared"])
 def test_issue744(en_tokenizer, text):
     """Test that 'were' and 'Were' are excluded from the contractions
     generated by the English tokenizer exceptions."""
@@ -230,14 +255,15 @@ def test_issue744(en_tokenizer, text):
     assert tokens[1].text.lower() == "were"
 
 
-@pytest.mark.parametrize('text,is_num', [("one", True), ("ten", True),
-                                         ("teneleven", False)])
+@pytest.mark.parametrize(
+    "text,is_num", [("one", True), ("ten", True), ("teneleven", False)]
+)
 def test_issue759(en_tokenizer, text, is_num):
     tokens = en_tokenizer(text)
     assert tokens[0].like_num == is_num
 
 
-@pytest.mark.parametrize('text', ["Shell", "shell", "Shed", "shed"])
+@pytest.mark.parametrize("text", ["Shell", "shell", "Shed", "shed"])
 def test_issue775(en_tokenizer, text):
     """Test that 'Shell' and 'shell' are excluded from the contractions
     generated by the English tokenizer exceptions."""
@@ -246,28 +272,32 @@ def test_issue775(en_tokenizer, text):
     assert tokens[0].text == text
 
 
-@pytest.mark.parametrize('text', ["This is a string ", "This is a string\u0020"])
+@pytest.mark.parametrize("text", ["This is a string ", "This is a string\u0020"])
 def test_issue792(en_tokenizer, text):
     """Test for Issue #792: Trailing whitespace is removed after tokenization."""
     doc = en_tokenizer(text)
-    assert ''.join([token.text_with_ws for token in doc]) == text
+    assert "".join([token.text_with_ws for token in doc]) == text
 
 
-@pytest.mark.parametrize('text', ["This is a string", "This is a string\n"])
+@pytest.mark.parametrize("text", ["This is a string", "This is a string\n"])
 def test_control_issue792(en_tokenizer, text):
     """Test base case for Issue #792: Non-trailing whitespace"""
     doc = en_tokenizer(text)
-    assert ''.join([token.text_with_ws for token in doc]) == text
+    assert "".join([token.text_with_ws for token in doc]) == text
 
 
-@pytest.mark.parametrize('text,tokens', [
-    ('"deserve,"--and', ['"', "deserve", ',"--', "and"]),
-    ("exception;--exclusive", ["exception", ";--", "exclusive"]),
-    ("day.--Is", ["day", ".--", "Is"]),
-    ("refinement:--just", ["refinement", ":--", "just"]),
-    ("memories?--To", ["memories", "?--", "To"]),
-    ("Useful.=--Therefore", ["Useful", ".=--", "Therefore"]),
-    ("=Hope.=--Pandora", ["=", "Hope", ".=--", "Pandora"])])
+@pytest.mark.parametrize(
+    "text,tokens",
+    [
+        ('"deserve,"--and', ['"', "deserve", ',"--', "and"]),
+        ("exception;--exclusive", ["exception", ";--", "exclusive"]),
+        ("day.--Is", ["day", ".--", "Is"]),
+        ("refinement:--just", ["refinement", ":--", "just"]),
+        ("memories?--To", ["memories", "?--", "To"]),
+        ("Useful.=--Therefore", ["Useful", ".=--", "Therefore"]),
+        ("=Hope.=--Pandora", ["=", "Hope", ".=--", "Pandora"]),
+    ],
+)
 def test_issue801(en_tokenizer, text, tokens):
     """Test that special characters + hyphens are split correctly."""
     doc = en_tokenizer(text)
@@ -275,10 +305,19 @@ def test_issue801(en_tokenizer, text, tokens):
     assert [t.text for t in doc] == tokens
 
 
-@pytest.mark.parametrize('text,expected_tokens', [
-    ('Smörsåsen används bl.a. till fisk', ['Smörsåsen', 'används', 'bl.a.', 'till', 'fisk']),
-    ('Jag kommer först kl. 13 p.g.a. diverse förseningar', ['Jag', 'kommer', 'först', 'kl.', '13', 'p.g.a.', 'diverse', 'förseningar'])
-])
+@pytest.mark.parametrize(
+    "text,expected_tokens",
+    [
+        (
+            "Smörsåsen används bl.a. till fisk",
+            ["Smörsåsen", "används", "bl.a.", "till", "fisk"],
+        ),
+        (
+            "Jag kommer först kl. 13 p.g.a. diverse förseningar",
+            ["Jag", "kommer", "först", "kl.", "13", "p.g.a.", "diverse", "förseningar"],
+        ),
+    ],
+)
 def test_issue805(sv_tokenizer, text, expected_tokens):
     tokens = sv_tokenizer(text)
     token_list = [token.text for token in tokens if not token.is_space]
@@ -291,9 +330,9 @@ def test_issue850():
     vocab = Vocab(lex_attr_getters={LOWER: lambda string: string.lower()})
     matcher = Matcher(vocab)
     IS_ANY_TOKEN = matcher.vocab.add_flag(lambda x: True)
-    pattern = [{'LOWER': "bob"}, {'OP': '*', 'IS_ANY_TOKEN': True}, {'LOWER': 'frank'}]
-    matcher.add('FarAway', None, pattern)
-    doc = Doc(matcher.vocab, words=['bob', 'and', 'and', 'frank'])
+    pattern = [{"LOWER": "bob"}, {"OP": "*", "IS_ANY_TOKEN": True}, {"LOWER": "frank"}]
+    matcher.add("FarAway", None, pattern)
+    doc = Doc(matcher.vocab, words=["bob", "and", "and", "frank"])
     match = matcher(doc)
     assert len(match) == 1
     ent_id, start, end = match[0]
@@ -306,9 +345,9 @@ def test_issue850_basic():
     vocab = Vocab(lex_attr_getters={LOWER: lambda string: string.lower()})
     matcher = Matcher(vocab)
     IS_ANY_TOKEN = matcher.vocab.add_flag(lambda x: True)
-    pattern = [{'LOWER': "bob"}, {'OP': '*', 'LOWER': 'and'}, {'LOWER': 'frank'}]
-    matcher.add('FarAway', None, pattern)
-    doc = Doc(matcher.vocab, words=['bob', 'and', 'and', 'frank'])
+    pattern = [{"LOWER": "bob"}, {"OP": "*", "LOWER": "and"}, {"LOWER": "frank"}]
+    matcher.add("FarAway", None, pattern)
+    doc = Doc(matcher.vocab, words=["bob", "and", "and", "frank"])
     match = matcher(doc)
     assert len(match) == 1
     ent_id, start, end = match[0]
@@ -316,23 +355,25 @@ def test_issue850_basic():
     assert end == 4
 
 
-@pytest.mark.parametrize('text', ["au-delàs", "pair-programmâmes",
-                                  "terra-formées", "σ-compacts"])
+@pytest.mark.parametrize(
+    "text", ["au-delàs", "pair-programmâmes", "terra-formées", "σ-compacts"]
+)
 def test_issue852(fr_tokenizer, text):
     """Test that French tokenizer exceptions are imported correctly."""
     tokens = fr_tokenizer(text)
     assert len(tokens) == 1
 
 
-@pytest.mark.parametrize('text', ["aaabbb@ccc.com\nThank you!",
-                                  "aaabbb@ccc.com \nThank you!"])
+@pytest.mark.parametrize(
+    "text", ["aaabbb@ccc.com\nThank you!", "aaabbb@ccc.com \nThank you!"]
+)
 def test_issue859(en_tokenizer, text):
     """Test that no extra space is added in doc.text method."""
     doc = en_tokenizer(text)
     assert doc.text == text
 
 
-@pytest.mark.parametrize('text', ["Datum:2014-06-02\nDokument:76467"])
+@pytest.mark.parametrize("text", ["Datum:2014-06-02\nDokument:76467"])
 def test_issue886(en_tokenizer, text):
     """Test that token.idx matches the original text index for texts with newlines."""
     doc = en_tokenizer(text)
@@ -341,7 +382,7 @@ def test_issue886(en_tokenizer, text):
         assert text[token.idx] == token.text[0]
 
 
-@pytest.mark.parametrize('text', ["want/need"])
+@pytest.mark.parametrize("text", ["want/need"])
 def test_issue891(en_tokenizer, text):
     """Test that / infixes are split correctly."""
     tokens = en_tokenizer(text)
@@ -349,11 +390,10 @@ def test_issue891(en_tokenizer, text):
     assert tokens[1].text == "/"
 
 
-@pytest.mark.parametrize('text,tag,lemma', [
-    ("anus", "NN", "anus"),
-    ("princess", "NN", "princess"),
-    ("inner", "JJ", "inner")
-])
+@pytest.mark.parametrize(
+    "text,tag,lemma",
+    [("anus", "NN", "anus"), ("princess", "NN", "princess"), ("inner", "JJ", "inner")],
+)
 def test_issue912(en_vocab, text, tag, lemma):
     """Test base-forms are preserved."""
     doc = Doc(en_vocab, words=[text])
@@ -364,10 +404,10 @@ def test_issue912(en_vocab, text, tag, lemma):
 def test_issue957(en_tokenizer):
     """Test that spaCy doesn't hang on many periods."""
     # skip test if pytest-timeout is not installed
-    timeout = pytest.importorskip('pytest-timeout')
-    string = '0'
+    timeout = pytest.importorskip("pytest-timeout")
+    string = "0"
     for i in range(1, 100):
-        string += '.%d' % i
+        string += ".%d" % i
     doc = en_tokenizer(string)
 
 
@@ -386,13 +426,13 @@ def test_issue999(train_data):
         ["hello", []],
         ["hi", []],
         ["i'm looking for a place to eat", []],
-        ["i'm looking for a place in the north of town", [[31,36,"LOCATION"]]],
-        ["show me chinese restaurants", [[8,15,"CUISINE"]]],
-        ["show me chines restaurants", [[8,14,"CUISINE"]]],
+        ["i'm looking for a place in the north of town", [[31, 36, "LOCATION"]]],
+        ["show me chinese restaurants", [[8, 15, "CUISINE"]]],
+        ["show me chines restaurants", [[8, 14, "CUISINE"]]],
     ]
 
     nlp = Language()
-    ner = nlp.create_pipe('ner')
+    ner = nlp.create_pipe("ner")
     nlp.add_pipe(ner)
     for _, offsets in TRAIN_DATA:
         for start, end, label in offsets:
@@ -402,7 +442,7 @@ def test_issue999(train_data):
     for itn in range(100):
         random.shuffle(TRAIN_DATA)
         for raw_text, entity_offsets in TRAIN_DATA:
-            nlp.update([raw_text], [{'entities': entity_offsets}])
+            nlp.update([raw_text], [{"entities": entity_offsets}])
 
     with make_tempdir() as model_dir:
         nlp.to_disk(model_dir)

spacy/tests/regression/test_issue1001-1500.py

@@ -15,76 +15,84 @@ from spacy.symbols import ORTH, LEMMA, POS, VERB, VerbForm_part
 
 def test_issue1242():
     nlp = English()
-    doc = nlp('')
+    doc = nlp("")
     assert len(doc) == 0
-    docs = list(nlp.pipe(['', 'hello']))
+    docs = list(nlp.pipe(["", "hello"]))
     assert len(docs[0]) == 0
     assert len(docs[1]) == 1
 
 
 def test_issue1250():
     """Test cached special cases."""
-    special_case = [{ORTH: 'reimbur', LEMMA: 'reimburse', POS: 'VERB'}]
+    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', '...']
+    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", "..."]
 
 
 def test_issue1257():
     """Test that tokens compare correctly."""
-    doc1 = Doc(Vocab(), words=['a', 'b', 'c'])
-    doc2 = Doc(Vocab(), words=['a', 'c', 'e'])
+    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]
 
 
 def test_issue1375():
     """Test that token.nbor() raises IndexError for out-of-bounds access."""
-    doc = Doc(Vocab(), words=['0', '1', '2'])
+    doc = Doc(Vocab(), words=["0", "1", "2"])
     with pytest.raises(IndexError):
         assert doc[0].nbor(-1)
-    assert doc[1].nbor(-1).text == '0'
+    assert doc[1].nbor(-1).text == "0"
     with pytest.raises(IndexError):
         assert doc[2].nbor(1)
-    assert doc[1].nbor(1).text == '2'
+    assert doc[1].nbor(1).text == "2"
 
 
 def test_issue1387():
-    tag_map = {'VBG': {POS: VERB, VerbForm_part: True}}
-    index = {"verb": ("cope","cop")}
+    tag_map = {"VBG": {POS: VERB, VerbForm_part: True}}
+    index = {"verb": ("cope", "cop")}
     exc = {"verb": {"coping": ("cope",)}}
     rules = {"verb": [["ing", ""]]}
     lemmatizer = Lemmatizer(index, exc, rules)
     vocab = Vocab(lemmatizer=lemmatizer, tag_map=tag_map)
     doc = Doc(vocab, words=["coping"])
-    doc[0].tag_ = 'VBG'
+    doc[0].tag_ = "VBG"
     assert doc[0].text == "coping"
     assert doc[0].lemma_ == "cope"
 
 
 def test_issue1434():
     """Test matches occur when optional element at end of short doc."""
-    pattern = [{'ORTH': 'Hello' }, {'IS_ALPHA': True, 'OP': '?'}]
+    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'])
+    hello_world = Doc(vocab, words=["Hello", "World"])
+    hello = Doc(vocab, words=["Hello"])
     matcher = Matcher(vocab)
-    matcher.add('MyMatcher', None, pattern)
+    matcher.add("MyMatcher", None, 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.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),
+    ],
+)
 def test_issue1450(string, start, end):
     """Test matcher works when patterns end with * operator."""
-    pattern = [{'ORTH': "a"}, {'ORTH': "b", 'OP': "*"}]
+    pattern = [{"ORTH": "a"}, {"ORTH": "b", "OP": "*"}]
     matcher = Matcher(Vocab())
     matcher.add("TSTEND", None, pattern)
     doc = Doc(Vocab(), words=string.split())
@@ -96,17 +104,20 @@ def test_issue1450(string, start, end):
 
 
 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?://''')
+    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)
+        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)
@@ -116,11 +127,16 @@ def test_issue1488():
 
 
 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'])]
-    new_tokenizer = lambda nlp: Tokenizer(nlp.vocab, {}, infix_finditer=infix_re.finditer)
+    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:

spacy/tests/regression/test_issue1501-2000.py

@@ -45,17 +45,17 @@ def test_issue1506():
 def test_issue1518():
     """Test vectors.resize() works."""
     vectors = Vectors(shape=(10, 10))
-    vectors.add('hello', row=2)
+    vectors.add("hello", row=2)
     vectors.resize((5, 9))
 
 
 def test_issue1537():
     """Test that Span.as_doc() doesn't segfault."""
-    string = 'The sky is blue . The man is pink . The dog is purple .'
+    string = "The sky is blue . The man is pink . The dog is purple ."
     doc = Doc(Vocab(), words=string.split())
     doc[0].sent_start = True
     for word in doc[1:]:
-        if word.nbor(-1).text == '.':
+        if word.nbor(-1).text == ".":
             word.sent_start = True
         else:
             word.sent_start = False
@@ -67,7 +67,7 @@ def test_issue1537():
 
 
 # TODO: Currently segfaulting, due to l_edge and r_edge misalignment
-#def test_issue1537_model():
+# def test_issue1537_model():
 #    nlp = load_spacy('en')
 #    doc = nlp('The sky is blue. The man is pink. The dog is purple.')
 #    sents = [s.as_doc() for s in doc.sents]
@@ -77,41 +77,41 @@ def test_issue1537():
 
 def test_issue1539():
     """Ensure vectors.resize() doesn't try to modify dictionary during iteration."""
-    v = Vectors(shape=(10, 10), keys=[5,3,98,100])
-    v.resize((100,100))
+    v = Vectors(shape=(10, 10), keys=[5, 3, 98, 100])
+    v.resize((100, 100))
 
 
 def test_issue1547():
     """Test that entity labels still match after merging tokens."""
-    words = ['\n', 'worda', '.', '\n', 'wordb', '-', 'Biosphere', '2', '-', ' \n']
+    words = ["\n", "worda", ".", "\n", "wordb", "-", "Biosphere", "2", "-", " \n"]
     doc = Doc(Vocab(), words=words)
-    doc.ents = [Span(doc, 6, 8, label=doc.vocab.strings['PRODUCT'])]
+    doc.ents = [Span(doc, 6, 8, label=doc.vocab.strings["PRODUCT"])]
     doc[5:7].merge()
     assert [ent.text for ent in doc.ents]
 
 
 def test_issue1612(en_tokenizer):
-    doc = en_tokenizer('The black cat purrs.')
-    span = doc[1: 3]
+    doc = en_tokenizer("The black cat purrs.")
+    span = doc[1:3]
     assert span.orth_ == span.text
 
 
 def test_issue1654():
     nlp = Language(Vocab())
     assert not nlp.pipeline
-    nlp.add_pipe(lambda doc: doc, name='1')
-    nlp.add_pipe(lambda doc: doc, name='2', after='1')
-    nlp.add_pipe(lambda doc: doc, name='3', after='2')
-    assert nlp.pipe_names == ['1', '2', '3']
+    nlp.add_pipe(lambda doc: doc, name="1")
+    nlp.add_pipe(lambda doc: doc, name="2", after="1")
+    nlp.add_pipe(lambda doc: doc, name="3", after="2")
+    assert nlp.pipe_names == ["1", "2", "3"]
     nlp2 = Language(Vocab())
     assert not nlp2.pipeline
-    nlp2.add_pipe(lambda doc: doc, name='3')
-    nlp2.add_pipe(lambda doc: doc, name='2', before='3')
-    nlp2.add_pipe(lambda doc: doc, name='1', before='2')
-    assert nlp2.pipe_names == ['1', '2', '3']
+    nlp2.add_pipe(lambda doc: doc, name="3")
+    nlp2.add_pipe(lambda doc: doc, name="2", before="3")
+    nlp2.add_pipe(lambda doc: doc, name="1", before="2")
+    assert nlp2.pipe_names == ["1", "2", "3"]
 
 
-@pytest.mark.parametrize('text', ['test@example.com', 'john.doe@example.co.uk'])
+@pytest.mark.parametrize("text", ["test@example.com", "john.doe@example.co.uk"])
 def test_issue1698(en_tokenizer, text):
     doc = en_tokenizer(text)
     assert len(doc) == 1
@@ -121,30 +121,30 @@ def test_issue1698(en_tokenizer, text):
 def test_issue1727():
     """Test that models with no pretrained vectors can be deserialized
     correctly after vectors are added."""
-    data = numpy.ones((3, 300), dtype='f')
-    vectors = Vectors(data=data, keys=['I', 'am', 'Matt'])
+    data = numpy.ones((3, 300), dtype="f")
+    vectors = Vectors(data=data, keys=["I", "am", "Matt"])
     tagger = Tagger(Vocab())
-    tagger.add_label('PRP')
+    tagger.add_label("PRP")
     tagger.begin_training()
-    assert tagger.cfg.get('pretrained_dims', 0) == 0
+    assert tagger.cfg.get("pretrained_dims", 0) == 0
     tagger.vocab.vectors = vectors
     with make_tempdir() as path:
         tagger.to_disk(path)
         tagger = Tagger(Vocab()).from_disk(path)
-        assert tagger.cfg.get('pretrained_dims', 0) == 0
+        assert tagger.cfg.get("pretrained_dims", 0) == 0
 
 
 def test_issue1757():
     """Test comparison against None doesn't cause segfault."""
-    doc = Doc(Vocab(), words=['a', 'b', 'c'])
+    doc = Doc(Vocab(), words=["a", "b", "c"])
     assert not doc[0] < None
     assert not doc[0] == None
     assert doc[0] >= None
     assert not doc[:2] < None
     assert not doc[:2] == None
     assert doc[:2] >= None
-    assert not doc.vocab['a'] == None
-    assert not doc.vocab['a'] < None
+    assert not doc.vocab["a"] == None
+    assert not doc.vocab["a"] < None
 
 
 def test_issue1758(en_tokenizer):
@@ -158,11 +158,20 @@ def test_issue1758(en_tokenizer):
 def test_issue1799():
     """Test sentence boundaries are deserialized correctly, even for
     non-projective sentences."""
-    heads_deps = numpy.asarray([[1, 397], [4, 436], [2, 426], [1, 402],
-                                [0, 8206900633647566924], [18446744073709551615, 440],
-                                [18446744073709551614, 442]], dtype='uint64')
-    doc = Doc(Vocab(), words='Just what I was looking for .'.split())
-    doc.vocab.strings.add('ROOT')
+    heads_deps = numpy.asarray(
+        [
+            [1, 397],
+            [4, 436],
+            [2, 426],
+            [1, 402],
+            [0, 8206900633647566924],
+            [18446744073709551615, 440],
+            [18446744073709551614, 442],
+        ],
+        dtype="uint64",
+    )
+    doc = Doc(Vocab(), words="Just what I was looking for .".split())
+    doc.vocab.strings.add("ROOT")
     doc = doc.from_array([HEAD, DEP], heads_deps)
     assert len(list(doc.sents)) == 1
 
@@ -170,9 +179,9 @@ def test_issue1799():
 def test_issue1807():
     """Test vocab.set_vector also adds the word to the vocab."""
     vocab = Vocab()
-    assert 'hello' not in vocab
-    vocab.set_vector('hello', numpy.ones((50,), dtype='f'))
-    assert 'hello' in vocab
+    assert "hello" not in vocab
+    vocab.set_vector("hello", numpy.ones((50,), dtype="f"))
+    assert "hello" in vocab
 
 
 def test_issue1834():
@@ -195,34 +204,34 @@ def test_issue1834():
 def test_issue1868():
     """Test Vocab.__contains__ works with int keys."""
     vocab = Vocab()
-    lex = vocab['hello']
+    lex = vocab["hello"]
     assert lex.orth in vocab
     assert lex.orth_ in vocab
-    assert 'some string' not in vocab
-    int_id = vocab.strings.add('some string')
+    assert "some string" not in vocab
+    int_id = vocab.strings.add("some string")
     assert int_id not in vocab
 
 
 def test_issue1883():
     matcher = Matcher(Vocab())
-    matcher.add('pat1', None, [{'orth': 'hello'}])
-    doc = Doc(matcher.vocab, words=['hello'])
+    matcher.add("pat1", None, [{"orth": "hello"}])
+    doc = Doc(matcher.vocab, words=["hello"])
     assert len(matcher(doc)) == 1
     new_matcher = copy.deepcopy(matcher)
-    new_doc = Doc(new_matcher.vocab, words=['hello'])
+    new_doc = Doc(new_matcher.vocab, words=["hello"])
     assert len(new_matcher(new_doc)) == 1
 
 
-@pytest.mark.parametrize('word', ['the'])
+@pytest.mark.parametrize("word", ["the"])
 def test_issue1889(word):
     assert is_stop(word, STOP_WORDS) == is_stop(word.upper(), STOP_WORDS)
 
 
 def test_issue1915():
-    cfg = {'hidden_depth': 2}  # should error out
+    cfg = {"hidden_depth": 2}  # should error out
     nlp = Language()
-    nlp.add_pipe(nlp.create_pipe('ner'))
-    nlp.get_pipe('ner').add_label('answer')
+    nlp.add_pipe(nlp.create_pipe("ner"))
+    nlp.get_pipe("ner").add_label("answer")
     with pytest.raises(ValueError):
         nlp.begin_training(**cfg)
 
@@ -230,17 +239,17 @@ def test_issue1915():
 def test_issue1945():
     """Test regression in Matcher introduced in v2.0.6."""
     matcher = Matcher(Vocab())
-    matcher.add('MWE', None, [{'orth': 'a'}, {'orth': 'a'}])
-    doc = Doc(matcher.vocab, words=['a', 'a', 'a'])
+    matcher.add("MWE", None, [{"orth": "a"}, {"orth": "a"}])
+    doc = Doc(matcher.vocab, words=["a", "a", "a"])
     matches = matcher(doc)  # we should see two overlapping matches here
     assert len(matches) == 2
     assert matches[0][1:] == (0, 2)
     assert matches[1][1:] == (1, 3)
 
 
-@pytest.mark.parametrize('label', ['U-JOB-NAME'])
+@pytest.mark.parametrize("label", ["U-JOB-NAME"])
 def test_issue1967(label):
     ner = EntityRecognizer(Vocab())
-    entry = ([0], ['word'], ['tag'], [0], ['dep'], [label])
+    entry = ([0], ["word"], ["tag"], [0], ["dep"], [label])
     gold_parses = [(None, [(entry, None)])]
     ner.moves.get_actions(gold_parses=gold_parses)

spacy/tests/regression/test_issue2001-2500.py

@@ -14,15 +14,15 @@ from ..util import add_vecs_to_vocab
 def test_issue2179():
     """Test that spurious 'extra_labels' aren't created when initializing NER."""
     nlp = Italian()
-    ner = nlp.create_pipe('ner')
-    ner.add_label('CITIZENSHIP')
+    ner = nlp.create_pipe("ner")
+    ner.add_label("CITIZENSHIP")
     nlp.add_pipe(ner)
     nlp.begin_training()
     nlp2 = Italian()
-    nlp2.add_pipe(nlp2.create_pipe('ner'))
+    nlp2.add_pipe(nlp2.create_pipe("ner"))
     nlp2.from_bytes(nlp.to_bytes())
-    assert 'extra_labels' not in nlp2.get_pipe('ner').cfg
-    assert nlp2.get_pipe('ner').labels == ['CITIZENSHIP']
+    assert "extra_labels" not in nlp2.get_pipe("ner").cfg
+    assert nlp2.get_pipe("ner").labels == ["CITIZENSHIP"]
 
 
 def test_issue2219(en_vocab):
@@ -34,7 +34,7 @@ def test_issue2219(en_vocab):
 
 
 def test_issue2361(de_tokenizer):
-    chars = ('<', '>', '&', '"')
+    chars = ("<", ">", "&", """)
     doc = de_tokenizer('< > & " ')
     doc.is_parsed = True
     doc.is_tagged = True
@@ -46,25 +46,32 @@ def test_issue2361(de_tokenizer):
 def test_issue2385():
     """Test that IOB tags are correctly converted to BILUO tags."""
     # fix bug in labels with a 'b' character
-    tags1 = ('B-BRAWLER', 'I-BRAWLER', 'I-BRAWLER')
-    assert iob_to_biluo(tags1) == ['B-BRAWLER', 'I-BRAWLER', 'L-BRAWLER']
+    tags1 = ("B-BRAWLER", "I-BRAWLER", "I-BRAWLER")
+    assert iob_to_biluo(tags1) == ["B-BRAWLER", "I-BRAWLER", "L-BRAWLER"]
     # maintain support for iob1 format
-    tags2 = ('I-ORG', 'I-ORG', 'B-ORG')
-    assert iob_to_biluo(tags2) == ['B-ORG', 'L-ORG', 'U-ORG']
+    tags2 = ("I-ORG", "I-ORG", "B-ORG")
+    assert iob_to_biluo(tags2) == ["B-ORG", "L-ORG", "U-ORG"]
     # maintain support for iob2 format
-    tags3 = ('B-PERSON', 'I-PERSON', 'B-PERSON')
-    assert iob_to_biluo(tags3) ==['B-PERSON', 'L-PERSON', 'U-PERSON']
+    tags3 = ("B-PERSON", "I-PERSON", "B-PERSON")
+    assert iob_to_biluo(tags3) == ["B-PERSON", "L-PERSON", "U-PERSON"]
 
 
-@pytest.mark.parametrize('tags', [
-    ('B-ORG', 'L-ORG'), ('B-PERSON', 'I-PERSON', 'L-PERSON'), ('U-BRAWLER', 'U-BRAWLER')])
+@pytest.mark.parametrize(
+    "tags",
+    [
+        ("B-ORG", "L-ORG"),
+        ("B-PERSON", "I-PERSON", "L-PERSON"),
+        ("U-BRAWLER", "U-BRAWLER"),
+    ],
+)
 def test_issue2385_biluo(tags):
     """Test that BILUO-compatible tags aren't modified."""
     assert iob_to_biluo(tags) == list(tags)
 
+
 def test_issue2482():
-    '''Test we can serialize and deserialize a blank NER or parser model.'''
+    """Test we can serialize and deserialize a blank NER or parser model."""
     nlp = Italian()
-    nlp.add_pipe(nlp.create_pipe('ner'))
+    nlp.add_pipe(nlp.create_pipe("ner"))
     b = nlp.to_bytes()
     nlp2 = Italian().from_bytes(b)

spacy/tests/regression/test_issue2564.py

@@ -7,11 +7,11 @@ from spacy.language import Language
 def test_issue2564():
     """Test the tagger sets is_tagged correctly when used via Language.pipe."""
     nlp = Language()
-    tagger = nlp.create_pipe('tagger')
+    tagger = nlp.create_pipe("tagger")
     tagger.begin_training()  # initialise weights
     nlp.add_pipe(tagger)
-    doc = nlp('hello world')
+    doc = nlp("hello world")
     assert doc.is_tagged
-    docs = nlp.pipe(['hello', 'world'])
+    docs = nlp.pipe(["hello", "world"])
     piped_doc = next(docs)
     assert piped_doc.is_tagged

spacy/tests/regression/test_issue2569.py

@@ -7,11 +7,11 @@ from spacy.tokens import Span
 
 def test_issue2569(en_tokenizer):
     doc = en_tokenizer("It is May 15, 1993.")
-    doc.ents = [Span(doc, 2, 6, label=doc.vocab.strings['DATE'])]
+    doc.ents = [Span(doc, 2, 6, label=doc.vocab.strings["DATE"])]
     matcher = Matcher(doc.vocab)
-    matcher.add("RULE", None, [{'ENT_TYPE':'DATE', 'OP':'+'}])
+    matcher.add("RULE", None, [{"ENT_TYPE": "DATE", "OP": "+"}])
     matched = [doc[start:end] for _, start, end in matcher(doc)]
     matched = sorted(matched, key=len, reverse=True)
     assert len(matched) == 10
     assert len(matched[0]) == 4
-    assert matched[0].text == 'May 15, 1993'
+    assert matched[0].text == "May 15, 1993"

spacy/tests/regression/test_issue2671.py

@@ -1,7 +1,6 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
-import pytest
 from spacy.lang.en import English
 from spacy.matcher import Matcher
 
@@ -10,6 +9,7 @@ def test_issue2671():
     """Ensure the correct entity ID is returned for matches with quantifiers.
     See also #2675
     """
+
     def get_rule_id(nlp, matcher, doc):
         matches = matcher(doc)
         for match_id, start, end in matches:
@@ -19,10 +19,12 @@ def test_issue2671():
 
     nlp = English()
     matcher = Matcher(nlp.vocab)
-    pattern_id = 'test_pattern'
-    pattern = [{'LOWER': 'high'},
-               {'IS_PUNCT': True, 'OP': '?'},
-               {'LOWER': 'adrenaline'}]
+    pattern_id = "test_pattern"
+    pattern = [
+        {"LOWER": "high"},
+        {"IS_PUNCT": True, "OP": "?"},
+        {"LOWER": "adrenaline"},
+    ]
     matcher.add(pattern_id, None, pattern)
     doc1 = nlp("This is a high-adrenaline situation.")
     doc2 = nlp("This is a high adrenaline situation.")

spacy/tests/regression/test_issue2772.py

@@ -1,17 +1,15 @@
 # coding: utf-8
 from __future__ import unicode_literals
 
-import pytest
-
 from ..util import get_doc
 
 
 def test_issue2772(en_vocab):
     """Test that deprojectivization doesn't mess up sentence boundaries."""
-    words = 'When we write or communicate virtually , we can hide our true feelings .'.split()
+    words = "When we write or communicate virtually , we can hide our true feelings .".split()
     # A tree with a non-projective (i.e. crossing) arc
     # The arcs (0, 4) and (2, 9) cross.
     heads = [4, 1, 7, -1, -2, -1, 3, 2, 1, 0, -1, -2, -1]
-    deps = ['dep'] * len(heads)
+    deps = ["dep"] * len(heads)
     doc = get_doc(en_vocab, words=words, heads=heads, deps=deps)
     assert doc[1].is_sent_start is None

spacy/tests/regression/test_issue2782.py

@@ -5,8 +5,8 @@ from spacy.util import get_lang_class
 import pytest
 
 
-@pytest.mark.parametrize('text', ['-0.23', '+123,456', '±1'])
-@pytest.mark.parametrize('lang', ['en', 'xx'])
+@pytest.mark.parametrize("text", ["-0.23", "+123,456", "±1"])
+@pytest.mark.parametrize("lang", ["en", "xx"])
 def test_issue2782(text, lang):
     """Check that like_num handles + and - before number."""
     cls = get_lang_class(lang)

spacy/tests/serialize/test_serialize_doc.py

@@ -18,25 +18,25 @@ def test_serialize_empty_doc(en_vocab):
 
 
 def test_serialize_doc_roundtrip_bytes(en_vocab):
-    doc = Doc(en_vocab, words=['hello', 'world'])
+    doc = Doc(en_vocab, words=["hello", "world"])
     doc_b = doc.to_bytes()
     new_doc = Doc(en_vocab).from_bytes(doc_b)
     assert new_doc.to_bytes() == doc_b
 
 
 def test_serialize_doc_roundtrip_disk(en_vocab):
-    doc = Doc(en_vocab, words=['hello', 'world'])
+    doc = Doc(en_vocab, words=["hello", "world"])
     with make_tempdir() as d:
-        file_path = d / 'doc'
+        file_path = d / "doc"
         doc.to_disk(file_path)
         doc_d = Doc(en_vocab).from_disk(file_path)
         assert doc.to_bytes() == doc_d.to_bytes()
 
 
 def test_serialize_doc_roundtrip_disk_str_path(en_vocab):
-    doc = Doc(en_vocab, words=['hello', 'world'])
+    doc = Doc(en_vocab, words=["hello", "world"])
     with make_tempdir() as d:
-        file_path = d / 'doc'
+        file_path = d / "doc"
         file_path = path2str(file_path)
         doc.to_disk(file_path)
         doc_d = Doc(en_vocab).from_disk(file_path)

spacy/tests/serialize/test_serialize_extension_attrs.py

@@ -8,19 +8,20 @@ from spacy.vocab import Vocab
 
 @pytest.fixture
 def doc_w_attrs(en_tokenizer):
-    Doc.set_extension('_test_attr', default=False)
-    Doc.set_extension('_test_prop', getter=lambda doc: len(doc.text))
-    Doc.set_extension('_test_method', method=lambda doc, arg: "{}{}".format(len(doc.text), arg))
+    Doc.set_extension("_test_attr", default=False)
+    Doc.set_extension("_test_prop", getter=lambda doc: len(doc.text))
+    Doc.set_extension(
+        "_test_method", method=lambda doc, arg: "{}{}".format(len(doc.text), arg)
+    )
     doc = en_tokenizer("This is a test.")
-    doc._._test_attr = 'test'
+    doc._._test_attr = "test"
     return doc
 
 
-
 def test_serialize_ext_attrs_from_bytes(doc_w_attrs):
     doc_b = doc_w_attrs.to_bytes()
     doc = Doc(Vocab()).from_bytes(doc_b)
-    assert doc._.has('_test_attr')
-    assert doc._._test_attr == 'test'
+    assert doc._.has("_test_attr")
+    assert doc._._test_attr == "test"
     assert doc._._test_prop == len(doc.text)
-    assert doc._._test_method('test') == '{}{}'.format(len(doc.text), 'test')
+    assert doc._._test_method("test") == "{}{}".format(len(doc.text), "test")

spacy/tests/serialize/test_serialize_language.py

@@ -12,14 +12,14 @@ from ..util import make_tempdir
 @pytest.fixture
 def meta_data():
     return {
-        'name': 'name-in-fixture',
-        'version': 'version-in-fixture',
-        'description': 'description-in-fixture',
-        'author': 'author-in-fixture',
-        'email': 'email-in-fixture',
-        'url': 'url-in-fixture',
-        'license': 'license-in-fixture',
-        'vectors': {'width': 0, 'vectors': 0, 'keys': 0, 'name': None}
+        "name": "name-in-fixture",
+        "version": "version-in-fixture",
+        "description": "description-in-fixture",
+        "author": "author-in-fixture",
+        "email": "email-in-fixture",
+        "url": "url-in-fixture",
+        "license": "license-in-fixture",
+        "vectors": {"width": 0, "vectors": 0, "keys": 0, "name": None},
     }
 
 
@@ -35,16 +35,18 @@ def test_serialize_with_custom_tokenizer():
     """Test that serialization with custom tokenizer works without token_match.
     See: https://support.prodi.gy/t/how-to-save-a-custom-tokenizer/661/2
     """
-    prefix_re = re.compile(r'''1/|2/|:[0-9][0-9][A-K]:|:[0-9][0-9]:''')
-    suffix_re = re.compile(r'''''')
-    infix_re = re.compile(r'''[~]''')
+    prefix_re = re.compile(r"""1/|2/|:[0-9][0-9][A-K]:|:[0-9][0-9]:""")
+    suffix_re = re.compile(r"""""")
+    infix_re = re.compile(r"""[~]""")
 
     def custom_tokenizer(nlp):
-        return Tokenizer(nlp.vocab,
-                         {},
-                         prefix_search=prefix_re.search,
-                         suffix_search=suffix_re.search,
-                         infix_finditer=infix_re.finditer)
+        return Tokenizer(
+            nlp.vocab,
+            {},
+            prefix_search=prefix_re.search,
+            suffix_search=suffix_re.search,
+            infix_finditer=infix_re.finditer,
+        )
 
     nlp = Language()
     nlp.tokenizer = custom_tokenizer(nlp)

spacy/tests/serialize/test_serialize_pipeline.py

@@ -2,7 +2,8 @@
 from __future__ import unicode_literals
 
 import pytest
-from spacy.pipeline import Tagger, DependencyParser, EntityRecognizer, Tensorizer, TextCategorizer
+from spacy.pipeline import Tagger, DependencyParser, EntityRecognizer
+from spacy.pipeline import Tensorizer, TextCategorizer
 
 from ..util import make_tempdir
 
@@ -13,7 +14,7 @@ test_parsers = [DependencyParser, EntityRecognizer]
 @pytest.fixture
 def parser(en_vocab):
     parser = DependencyParser(en_vocab)
-    parser.add_label('nsubj')
+    parser.add_label("nsubj")
     parser.model, cfg = parser.Model(parser.moves.n_moves)
     parser.cfg.update(cfg)
     return parser
@@ -34,7 +35,7 @@ def taggers(en_vocab):
     return (tagger1, tagger2)
 
 
-@pytest.mark.parametrize('Parser', test_parsers)
+@pytest.mark.parametrize("Parser", test_parsers)
 def test_serialize_parser_roundtrip_bytes(en_vocab, Parser):
     parser = Parser(en_vocab)
     parser.model, _ = parser.Model(10)
@@ -44,12 +45,12 @@ def test_serialize_parser_roundtrip_bytes(en_vocab, Parser):
     assert new_parser.to_bytes() == parser.to_bytes()
 
 
-@pytest.mark.parametrize('Parser', test_parsers)
+@pytest.mark.parametrize("Parser", test_parsers)
 def test_serialize_parser_roundtrip_disk(en_vocab, Parser):
     parser = Parser(en_vocab)
     parser.model, _ = parser.Model(0)
     with make_tempdir() as d:
-        file_path = d / 'parser'
+        file_path = d / "parser"
         parser.to_disk(file_path)
         parser_d = Parser(en_vocab)
         parser_d.model, _ = parser_d.Model(0)
@@ -67,7 +68,9 @@ def test_to_from_bytes(parser, blank_parser):
     assert blank_parser.moves.n_moves == parser.moves.n_moves
 
 
-@pytest.mark.skip(reason="This seems to be a dict ordering bug somewhere. Only failing on some platforms.")
+@pytest.mark.skip(
+    reason="This seems to be a dict ordering bug somewhere. Only failing on some platforms."
+)
 def test_serialize_tagger_roundtrip_bytes(en_vocab, taggers):
     tagger1, tagger2 = taggers
     tagger1_b = tagger1.to_bytes()
@@ -81,8 +84,8 @@ def test_serialize_tagger_roundtrip_bytes(en_vocab, taggers):
 def test_serialize_tagger_roundtrip_disk(en_vocab, taggers):
     tagger1, tagger2 = taggers
     with make_tempdir() as d:
-        file_path1 = d / 'tagger1'
-        file_path2 = d / 'tagger2'
+        file_path1 = d / "tagger1"
+        file_path2 = d / "tagger2"
         tagger1.to_disk(file_path1)
         tagger2.to_disk(file_path2)
         tagger1_d = Tagger(en_vocab).from_disk(file_path1)
@@ -102,7 +105,7 @@ def test_serialize_tensorizer_roundtrip_disk(en_vocab):
     tensorizer = Tensorizer(en_vocab)
     tensorizer.model = tensorizer.Model()
     with make_tempdir() as d:
-        file_path = d / 'tensorizer'
+        file_path = d / "tensorizer"
         tensorizer.to_disk(file_path)
         tensorizer_d = Tensorizer(en_vocab).from_disk(file_path)
         assert tensorizer.to_bytes() == tensorizer_d.to_bytes()
@@ -110,5 +113,5 @@ def test_serialize_tensorizer_roundtrip_disk(en_vocab):
 
 def test_serialize_textcat_empty(en_vocab):
     # See issue #1105
-    textcat = TextCategorizer(en_vocab, labels=['ENTITY', 'ACTION', 'MODIFIER'])
+    textcat = TextCategorizer(en_vocab, labels=["ENTITY", "ACTION", "MODIFIER"])
     textcat_bytes = textcat.to_bytes()

spacy/tests/serialize/test_serialize_tokenizer.py

@@ -9,7 +9,7 @@ from ..util import make_tempdir, assert_packed_msg_equal
 
 
 def load_tokenizer(b):
-    tok = get_lang_class('en').Defaults.create_tokenizer()
+    tok = get_lang_class("en").Defaults.create_tokenizer()
     tok.from_bytes(b)
     return tok
 
@@ -23,7 +23,7 @@ def test_serialize_custom_tokenizer(en_vocab, en_tokenizer):
 
 
 @pytest.mark.skip(reason="Currently unreliable across platforms")
-@pytest.mark.parametrize('text', ["I💜you", "they’re", "“hello”"])
+@pytest.mark.parametrize("text", ["I💜you", "they’re", "“hello”"])
 def test_serialize_tokenizer_roundtrip_bytes(en_tokenizer, text):
     tokenizer = en_tokenizer
     new_tokenizer = load_tokenizer(tokenizer.to_bytes())
@@ -38,7 +38,7 @@ def test_serialize_tokenizer_roundtrip_bytes(en_tokenizer, text):
 def test_serialize_tokenizer_roundtrip_disk(en_tokenizer):
     tokenizer = en_tokenizer
     with make_tempdir() as d:
-        file_path = d / 'tokenizer'
+        file_path = d / "tokenizer"
         tokenizer.to_disk(file_path)
         tokenizer_d = en_tokenizer.from_disk(file_path)
         assert tokenizer.to_bytes() == tokenizer_d.to_bytes()

spacy/tests/serialize/test_serialize_vocab_strings.py

@@ -8,12 +8,12 @@ from spacy.strings import StringStore
 from ..util import make_tempdir
 
 
-test_strings = [([], []), (['rats', 'are', 'cute'], ['i', 'like', 'rats'])]
-test_strings_attrs = [(['rats', 'are', 'cute'], 'Hello')]
+test_strings = [([], []), (["rats", "are", "cute"], ["i", "like", "rats"])]
+test_strings_attrs = [(["rats", "are", "cute"], "Hello")]
 
 
 @pytest.mark.xfail
-@pytest.mark.parametrize('text', ['rat'])
+@pytest.mark.parametrize("text", ["rat"])
 def test_serialize_vocab(en_vocab, text):
     text_hash = en_vocab.strings.add(text)
     vocab_bytes = en_vocab.to_bytes()
@@ -21,7 +21,7 @@ def test_serialize_vocab(en_vocab, text):
     assert new_vocab.strings(text_hash) == text
 
 
-@pytest.mark.parametrize('strings1,strings2', test_strings)
+@pytest.mark.parametrize("strings1,strings2", test_strings)
 def test_serialize_vocab_roundtrip_bytes(strings1, strings2):
     vocab1 = Vocab(strings=strings1)
     vocab2 = Vocab(strings=strings2)
@@ -39,13 +39,13 @@ def test_serialize_vocab_roundtrip_bytes(strings1, strings2):
     assert sorted([lex.text for lex in new_vocab1]) == sorted(strings1)
 
 
-@pytest.mark.parametrize('strings1,strings2', test_strings)
-def test_serialize_vocab_roundtrip_disk(strings1,strings2):
+@pytest.mark.parametrize("strings1,strings2", test_strings)
+def test_serialize_vocab_roundtrip_disk(strings1, strings2):
     vocab1 = Vocab(strings=strings1)
     vocab2 = Vocab(strings=strings2)
     with make_tempdir() as d:
-        file_path1 = d / 'vocab1'
-        file_path2 = d / 'vocab2'
+        file_path1 = d / "vocab1"
+        file_path2 = d / "vocab2"
         vocab1.to_disk(file_path1)
         vocab2.to_disk(file_path2)
         vocab1_d = Vocab().from_disk(file_path1)
@@ -58,7 +58,7 @@ def test_serialize_vocab_roundtrip_disk(strings1,strings2):
             assert list(vocab1_d) != list(vocab2_d)
 
 
-@pytest.mark.parametrize('strings,lex_attr', test_strings_attrs)
+@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
 def test_serialize_vocab_lex_attrs_bytes(strings, lex_attr):
     vocab1 = Vocab(strings=strings)
     vocab2 = Vocab()
@@ -69,7 +69,7 @@ def test_serialize_vocab_lex_attrs_bytes(strings, lex_attr):
     assert vocab2[strings[0]].norm_ == lex_attr
 
 
-@pytest.mark.parametrize('strings,lex_attr', test_strings_attrs)
+@pytest.mark.parametrize("strings,lex_attr", test_strings_attrs)
 def test_serialize_vocab_lex_attrs_disk(strings, lex_attr):
     vocab1 = Vocab(strings=strings)
     vocab2 = Vocab()
@@ -77,13 +77,13 @@ def test_serialize_vocab_lex_attrs_disk(strings, lex_attr):
     assert vocab1[strings[0]].norm_ == lex_attr
     assert vocab2[strings[0]].norm_ != lex_attr
     with make_tempdir() as d:
-        file_path = d / 'vocab'
+        file_path = d / "vocab"
         vocab1.to_disk(file_path)
         vocab2 = vocab2.from_disk(file_path)
     assert vocab2[strings[0]].norm_ == lex_attr
 
 
-@pytest.mark.parametrize('strings1,strings2', test_strings)
+@pytest.mark.parametrize("strings1,strings2", test_strings)
 def test_serialize_stringstore_roundtrip_bytes(strings1, strings2):
     sstore1 = StringStore(strings=strings1)
     sstore2 = StringStore(strings=strings2)
@@ -100,13 +100,13 @@ def test_serialize_stringstore_roundtrip_bytes(strings1, strings2):
     assert list(new_sstore1) == strings1
 
 
-@pytest.mark.parametrize('strings1,strings2', test_strings)
+@pytest.mark.parametrize("strings1,strings2", test_strings)
 def test_serialize_stringstore_roundtrip_disk(strings1, strings2):
     sstore1 = StringStore(strings=strings1)
     sstore2 = StringStore(strings=strings2)
     with make_tempdir() as d:
-        file_path1 = d / 'strings1'
-        file_path2 = d / 'strings2'
+        file_path1 = d / "strings1"
+        file_path2 = d / "strings2"
         sstore1.to_disk(file_path1)
         sstore2.to_disk(file_path2)
         sstore1_d = StringStore().from_disk(file_path1)

spacy/tests/test_align.py

@@ -5,52 +5,63 @@ import pytest
 from spacy._align import align, multi_align
 
 
-@pytest.mark.parametrize('string1,string2,cost', [
-    ('hello', 'hell', 1),
-    ('rat', 'cat', 1),
-    ('rat', 'rat', 0),
-    ('rat', 'catsie', 4),
-    ('t', 'catsie', 5),
-])
+@pytest.mark.parametrize(
+    "string1,string2,cost",
+    [
+        ("hello", "hell", 1),
+        ("rat", "cat", 1),
+        ("rat", "rat", 0),
+        ("rat", "catsie", 4),
+        ("t", "catsie", 5),
+    ],
+)
 def test_align_costs(string1, string2, cost):
     output_cost, i2j, j2i, matrix = align(string1, string2)
     assert output_cost == cost
 
 
-@pytest.mark.parametrize('string1,string2,i2j', [
-    ('hello', 'hell', [0,1,2,3,-1]),
-    ('rat', 'cat', [0,1,2]),
-    ('rat', 'rat', [0,1,2]),
-    ('rat', 'catsie', [0,1,2]),
-    ('t', 'catsie', [2]),
-])
+@pytest.mark.parametrize(
+    "string1,string2,i2j",
+    [
+        ("hello", "hell", [0, 1, 2, 3, -1]),
+        ("rat", "cat", [0, 1, 2]),
+        ("rat", "rat", [0, 1, 2]),
+        ("rat", "catsie", [0, 1, 2]),
+        ("t", "catsie", [2]),
+    ],
+)
 def test_align_i2j(string1, string2, i2j):
     output_cost, output_i2j, j2i, matrix = align(string1, string2)
     assert list(output_i2j) == i2j
 
 
-@pytest.mark.parametrize('string1,string2,j2i', [
-    ('hello', 'hell', [0,1,2,3]),
-    ('rat', 'cat', [0,1,2]),
-    ('rat', 'rat', [0,1,2]),
-    ('rat', 'catsie', [0,1,2, -1, -1, -1]),
-    ('t', 'catsie', [-1, -1, 0, -1, -1, -1]),
-])
+@pytest.mark.parametrize(
+    "string1,string2,j2i",
+    [
+        ("hello", "hell", [0, 1, 2, 3]),
+        ("rat", "cat", [0, 1, 2]),
+        ("rat", "rat", [0, 1, 2]),
+        ("rat", "catsie", [0, 1, 2, -1, -1, -1]),
+        ("t", "catsie", [-1, -1, 0, -1, -1, -1]),
+    ],
+)
 def test_align_i2j(string1, string2, j2i):
     output_cost, output_i2j, output_j2i, matrix = align(string1, string2)
     assert list(output_j2i) == j2i
 
+
 def test_align_strings():
-    words1 = ['hello', 'this', 'is', 'test!']
-    words2 = ['hellothis', 'is', 'test', '!']
+    words1 = ["hello", "this", "is", "test!"]
+    words2 = ["hellothis", "is", "test", "!"]
     cost, i2j, j2i, matrix = align(words1, words2)
     assert cost == 4
     assert list(i2j) == [-1, -1, 1, -1]
     assert list(j2i) == [-1, 2, -1, -1]
 
+
 def test_align_many_to_one():
-    words1 = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
-    words2 = ['ab', 'bc', 'e', 'fg', 'h']
+    words1 = ["a", "b", "c", "d", "e", "f", "g", "h"]
+    words2 = ["ab", "bc", "e", "fg", "h"]
     cost, i2j, j2i, matrix = align(words1, words2)
     assert list(i2j) == [-1, -1, -1, -1, 2, -1, -1, 4]
     lengths1 = [len(w) for w in words1]

spacy/tests/test_gold.py

@@ -8,75 +8,78 @@ from .util import get_doc
 
 
 def test_gold_biluo_U(en_vocab):
-    orths_and_spaces = [('I', True), ('flew', True), ('to', True),
-                        ('London', False), ('.', True)]
-    doc = Doc(en_vocab, orths_and_spaces=orths_and_spaces)
-    entities = [(len("I flew to "), len("I flew to London"), 'LOC')]
+    words = ["I", "flew", "to", "London", "."]
+    spaces = [True, True, True, False, True]
+    doc = Doc(en_vocab, words=words, spaces=spaces)
+    entities = [(len("I flew to "), len("I flew to London"), "LOC")]
     tags = biluo_tags_from_offsets(doc, entities)
-    assert tags == ['O', 'O', 'O', 'U-LOC', 'O']
+    assert tags == ["O", "O", "O", "U-LOC", "O"]
 
 
 def test_gold_biluo_BL(en_vocab):
-    orths_and_spaces = [('I', True), ('flew', True), ('to', True), ('San', True),
-                        ('Francisco', False), ('.', True)]
-    doc = Doc(en_vocab, orths_and_spaces=orths_and_spaces)
-    entities = [(len("I flew to "), len("I flew to San Francisco"), 'LOC')]
+    words = ["I", "flew", "to", "San", "Francisco", "."]
+    spaces = [True, True, True, True, False, True]
+    doc = Doc(en_vocab, words=words, spaces=spaces)
+    entities = [(len("I flew to "), len("I flew to San Francisco"), "LOC")]
     tags = biluo_tags_from_offsets(doc, entities)
-    assert tags == ['O', 'O', 'O', 'B-LOC', 'L-LOC', 'O']
+    assert tags == ["O", "O", "O", "B-LOC", "L-LOC", "O"]
 
 
 def test_gold_biluo_BIL(en_vocab):
-    orths_and_spaces = [('I', True), ('flew', True), ('to', True), ('San', True),
-                        ('Francisco', True), ('Valley', False), ('.', True)]
-    doc = Doc(en_vocab, orths_and_spaces=orths_and_spaces)
-    entities = [(len("I flew to "), len("I flew to San Francisco Valley"), 'LOC')]
+    words = ["I", "flew", "to", "San", "Francisco", "Valley", "."]
+    spaces = [True, True, True, True, True, False, True]
+    doc = Doc(en_vocab, words=words, spaces=spaces)
+    entities = [(len("I flew to "), len("I flew to San Francisco Valley"), "LOC")]
     tags = biluo_tags_from_offsets(doc, entities)
-    assert tags == ['O', 'O', 'O', 'B-LOC', 'I-LOC', 'L-LOC', 'O']
+    assert tags == ["O", "O", "O", "B-LOC", "I-LOC", "L-LOC", "O"]
 
 
 def test_gold_biluo_misalign(en_vocab):
-    orths_and_spaces = [('I', True), ('flew', True), ('to', True), ('San', True),
-                        ('Francisco', True), ('Valley.', False)]
-    doc = Doc(en_vocab, orths_and_spaces=orths_and_spaces)
-    entities = [(len("I flew to "), len("I flew to San Francisco Valley"), 'LOC')]
+    words = ["I", "flew", "to", "San", "Francisco", "Valley."]
+    spaces = [True, True, True, True, True, False]
+    doc = Doc(en_vocab, words=words, spaces=spaces)
+    entities = [(len("I flew to "), len("I flew to San Francisco Valley"), "LOC")]
     tags = biluo_tags_from_offsets(doc, entities)
-    assert tags == ['O', 'O', 'O', '-', '-', '-']
+    assert tags == ["O", "O", "O", "-", "-", "-"]
 
 
 def test_roundtrip_offsets_biluo_conversion(en_tokenizer):
     text = "I flew to Silicon Valley via London."
-    biluo_tags = ['O', 'O', 'O', 'B-LOC', 'L-LOC', 'O', 'U-GPE', 'O']
-    offsets = [(10, 24, 'LOC'), (29, 35, 'GPE')]
+    biluo_tags = ["O", "O", "O", "B-LOC", "L-LOC", "O", "U-GPE", "O"]
+    offsets = [(10, 24, "LOC"), (29, 35, "GPE")]
     doc = en_tokenizer(text)
     biluo_tags_converted = biluo_tags_from_offsets(doc, offsets)
     assert biluo_tags_converted == biluo_tags
     offsets_converted = offsets_from_biluo_tags(doc, biluo_tags)
     assert offsets_converted == offsets
 
+
 def test_docs_to_json(en_vocab):
-    '''Test we can convert a list of Doc objects into the JSON-serializable
+    """Test we can convert a list of Doc objects into the JSON-serializable
     format we use for training.
-    '''
+    """
     docs = [
         get_doc(
             en_vocab,
-            words=['a', 'b'],
-            pos=['VBP', 'NN'],
+            words=["a", "b"],
+            pos=["VBP", "NN"],
             heads=[0, -1],
-            deps=['ROOT', 'dobj'],
-            ents=[]),
+            deps=["ROOT", "dobj"],
+            ents=[],
+        ),
         get_doc(
             en_vocab,
-            words=['c', 'd', 'e'],
-            pos=['VBP', 'NN', 'NN'],
+            words=["c", "d", "e"],
+            pos=["VBP", "NN", "NN"],
             heads=[0, -1, -2],
-            deps=['ROOT', 'dobj', 'dobj'],
-            ents=[(1, 2, 'ORG')]),
+            deps=["ROOT", "dobj", "dobj"],
+            ents=[(1, 2, "ORG")],
+        ),
     ]
     json_doc = docs_to_json(0, docs)
-    assert json_doc['id'] == 0
-    assert len(json_doc['paragraphs']) == 2
-    assert len(json_doc['paragraphs'][0]['sentences']) == 1
-    assert len(json_doc['paragraphs'][1]['sentences']) == 1
-    assert len(json_doc['paragraphs'][0]['sentences'][0]['tokens']) == 2
-    assert len(json_doc['paragraphs'][1]['sentences'][0]['tokens']) == 3
+    assert json_doc["id"] == 0
+    assert len(json_doc["paragraphs"]) == 2
+    assert len(json_doc["paragraphs"][0]["sentences"]) == 1
+    assert len(json_doc["paragraphs"][1]["sentences"]) == 1
+    assert len(json_doc["paragraphs"][0]["sentences"][0]["tokens"]) == 2
+    assert len(json_doc["paragraphs"][1]["sentences"][0]["tokens"]) == 3

spacy/tests/test_misc.py

@@ -11,19 +11,19 @@ from spacy._ml import PrecomputableAffine
 from .util import get_doc
 
 
-@pytest.mark.parametrize('text', ['hello/world', 'hello world'])
+@pytest.mark.parametrize("text", ["hello/world", "hello world"])
 def test_util_ensure_path_succeeds(text):
     path = util.ensure_path(text)
     assert isinstance(path, Path)
 
 
-@pytest.mark.parametrize('package', ['numpy'])
+@pytest.mark.parametrize("package", ["numpy"])
 def test_util_is_package(package):
     """Test that an installed package via pip is recognised by util.is_package."""
     assert util.is_package(package)
 
 
-@pytest.mark.parametrize('package', ['thinc'])
+@pytest.mark.parametrize("package", ["thinc"])
 def test_util_get_package_path(package):
     """Test that a Path object is returned for a package name."""
     path = util.get_package_path(package)
@@ -33,44 +33,47 @@ def test_util_get_package_path(package):
 def test_displacy_parse_ents(en_vocab):
     """Test that named entities on a Doc are converted into displaCy's format."""
     doc = get_doc(en_vocab, words=["But", "Google", "is", "starting", "from", "behind"])
-    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings['ORG'])]
+    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings["ORG"])]
     ents = displacy.parse_ents(doc)
     assert isinstance(ents, dict)
-    assert ents['text'] == 'But Google is starting from behind '
-    assert ents['ents'] == [{'start': 4, 'end': 10, 'label': 'ORG'}]
+    assert ents["text"] == "But Google is starting from behind "
+    assert ents["ents"] == [{"start": 4, "end": 10, "label": "ORG"}]
 
 
 def test_displacy_parse_deps(en_vocab):
     """Test that deps and tags on a Doc are converted into displaCy's format."""
     words = ["This", "is", "a", "sentence"]
     heads = [1, 0, 1, -2]
-    pos = ['DET', 'VERB', 'DET', 'NOUN']
-    tags = ['DT', 'VBZ', 'DT', 'NN']
-    deps = ['nsubj', 'ROOT', 'det', 'attr']
-    doc = get_doc(en_vocab, words=words, heads=heads, pos=pos, tags=tags,
-                  deps=deps)
+    pos = ["DET", "VERB", "DET", "NOUN"]
+    tags = ["DT", "VBZ", "DT", "NN"]
+    deps = ["nsubj", "ROOT", "det", "attr"]
+    doc = get_doc(en_vocab, words=words, heads=heads, pos=pos, tags=tags, deps=deps)
     deps = displacy.parse_deps(doc)
     assert isinstance(deps, dict)
-    assert deps['words'] == [{'text': 'This', 'tag': 'DET'},
-                            {'text': 'is', 'tag': 'VERB'},
-                            {'text': 'a', 'tag': 'DET'},
-                            {'text': 'sentence', 'tag': 'NOUN'}]
-    assert deps['arcs'] == [{'start': 0, 'end': 1, 'label': 'nsubj', 'dir': 'left'},
-                            {'start': 2, 'end': 3, 'label': 'det', 'dir': 'left'},
-                            {'start': 1, 'end': 3, 'label': 'attr', 'dir': 'right'}]
+    assert deps["words"] == [
+        {"text": "This", "tag": "DET"},
+        {"text": "is", "tag": "VERB"},
+        {"text": "a", "tag": "DET"},
+        {"text": "sentence", "tag": "NOUN"},
+    ]
+    assert deps["arcs"] == [
+        {"start": 0, "end": 1, "label": "nsubj", "dir": "left"},
+        {"start": 2, "end": 3, "label": "det", "dir": "left"},
+        {"start": 1, "end": 3, "label": "attr", "dir": "right"},
+    ]
 
 
 def test_displacy_spans(en_vocab):
     """Test that displaCy can render Spans."""
     doc = get_doc(en_vocab, words=["But", "Google", "is", "starting", "from", "behind"])
-    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings['ORG'])]
-    html = displacy.render(doc[1:4], style='ent')
-    assert html.startswith('<div')
+    doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings["ORG"])]
+    html = displacy.render(doc[1:4], style="ent")
+    assert html.startswith("<div")
 
 
 def test_displacy_raises_for_wrong_type(en_vocab):
     with pytest.raises(ValueError):
-        html = displacy.render('hello world')
+        html = displacy.render("hello world")
 
 
 def test_PrecomputableAffine(nO=4, nI=5, nF=3, nP=2):
@@ -78,22 +81,22 @@ def test_PrecomputableAffine(nO=4, nI=5, nF=3, nP=2):
     assert model.W.shape == (nF, nO, nP, nI)
     tensor = model.ops.allocate((10, nI))
     Y, get_dX = model.begin_update(tensor)
-    assert Y.shape == (tensor.shape[0]+1, nF, nO, nP)
+    assert Y.shape == (tensor.shape[0] + 1, nF, nO, nP)
     assert model.d_pad.shape == (1, nF, nO, nP)
     dY = model.ops.allocate((15, nO, nP))
     ids = model.ops.allocate((15, nF))
-    ids[1,2] = -1
+    ids[1, 2] = -1
     dY[1] = 1
-    assert model.d_pad[0, 2, 0, 0] == 0.
+    assert model.d_pad[0, 2, 0, 0] == 0.0
     model._backprop_padding(dY, ids)
-    assert model.d_pad[0, 2, 0, 0] == 1.
-    model.d_pad.fill(0.)
-    ids.fill(0.)
-    dY.fill(0.)
-    ids[1,2] = -1
-    ids[1,1] = -1
-    ids[1,0] = -1
+    assert model.d_pad[0, 2, 0, 0] == 1.0
+    model.d_pad.fill(0.0)
+    ids.fill(0.0)
+    dY.fill(0.0)
+    ids[1, 2] = -1
+    ids[1, 1] = -1
+    ids[1, 0] = -1
     dY[1] = 1
-    assert model.d_pad[0, 2, 0, 0] == 0.
+    assert model.d_pad[0, 2, 0, 0] == 0.0
     model._backprop_padding(dY, ids)
-    assert model.d_pad[0, 2, 0, 0] == 3.
+    assert model.d_pad[0, 2, 0, 0] == 3.0

spacy/tests/test_pickles.py

@@ -9,7 +9,7 @@ from spacy.vocab import Vocab
 from spacy.attrs import NORM
 
 
-@pytest.mark.parametrize('text1,text2', [('hello', 'bye')])
+@pytest.mark.parametrize("text1,text2", [("hello", "bye")])
 def test_pickle_string_store(text1, text2):
     stringstore = StringStore()
     store1 = stringstore[text1]
@@ -21,10 +21,10 @@ def test_pickle_string_store(text1, text2):
     assert len(stringstore) == len(unpickled)
 
 
-@pytest.mark.parametrize('text1,text2', [('dog', 'cat')])
+@pytest.mark.parametrize("text1,text2", [("dog", "cat")])
 def test_pickle_vocab(text1, text2):
     vocab = Vocab(lex_attr_getters={int(NORM): lambda string: string[:-1]})
-    vocab.set_vector('dog', numpy.ones((5,), dtype='f'))
+    vocab.set_vector("dog", numpy.ones((5,), dtype="f"))
     lex1 = vocab[text1]
     lex2 = vocab[text2]
     assert lex1.norm_ == text1[:-1]
@@ -37,4 +37,4 @@ def test_pickle_vocab(text1, text2):
     assert unpickled[text2].norm == lex2.norm
     assert unpickled[text1].norm != unpickled[text2].norm
     assert unpickled.vectors is not None
-    assert list(vocab['dog'].vector) == [1.,1.,1.,1.,1.]
+    assert list(vocab["dog"].vector) == [1.0, 1.0, 1.0, 1.0, 1.0]

spacy/tests/tokenizer/test_exceptions.py

@@ -29,17 +29,19 @@ def test_tokenizer_handles_emoticons(tokenizer):
     assert tokens[17].text == ":D"
     assert tokens[18].text == "=|"
     assert tokens[19].text == '")'
-    assert tokens[20].text == ':>'
-    assert tokens[21].text == '....'
+    assert tokens[20].text == ":>"
+    assert tokens[21].text == "...."
 
 
-@pytest.mark.parametrize('text,length', [("example:)", 3), ("108)", 2), ("XDN", 1)])
+@pytest.mark.parametrize("text,length", [("example:)", 3), ("108)", 2), ("XDN", 1)])
 def test_tokenizer_excludes_false_pos_emoticons(tokenizer, text, length):
     tokens = tokenizer(text)
     assert len(tokens) == length
 
-@pytest.mark.parametrize('text,length', [('can you still dunk?🍕🍔😵LOL', 8),
-                                         ('i💙you', 3), ('🤘🤘yay!', 4)])
+
+@pytest.mark.parametrize(
+    "text,length", [("can you still dunk?🍕🍔😵LOL", 8), ("i💙you", 3), ("🤘🤘yay!", 4)]
+)
 def test_tokenizer_handles_emoji(tokenizer, text, length):
     # These break on narrow unicode builds, e.g. Windows
     if sys.maxunicode >= 1114111:

spacy/tests/tokenizer/test_naughty_strings.py

@@ -12,11 +12,9 @@ NAUGHTY_STRINGS = [
     ",./;'[]\-=",
     '<>?:"{}|_+',
     '!@#$%^&*()`~"',
-
     # Unicode additional control characters, byte order marks
     "­؀؁؂؃؄؅؜۝܏᠎​‌‍‎‏‪",
     "￾",
-
     # Unicode Symbols
     "Ω≈ç√∫˜µ≤≥÷",
     "åß∂ƒ©˙∆˚¬…æ",
@@ -29,13 +27,11 @@ NAUGHTY_STRINGS = [
     "⅛⅜⅝⅞",
     "ЁЂЃЄЅІЇЈЉЊЋЌЍЎЏАБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯабвгдежзийклмнопрстуфхцчшщъыьэюя",
     "٠١٢٣٤٥٦٧٨٩",
-
     # Unicode Subscript/Superscript/Accents
     "⁰⁴⁵",
     "₀₁₂",
     "⁰⁴⁵₀₁₂",
     "ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็ ด้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็็้้้้้้้้็็็็็้้้้้็็็็",
-
     # Two-Byte Characters
     "田中さんにあげて下さい",
     "パーティーへ行かないか",
@@ -46,7 +42,6 @@ NAUGHTY_STRINGS = [
     "社會科學院語學研究所",
     "울란바토르",
     "𠜎𠜱𠝹𠱓𠱸𠲖𠳏",
-
     # Japanese Emoticons
     "ヽ༼ຈل͜ຈ༽ﾉ ヽ༼ຈل͜ຈ༽ﾉ",
     "(｡◕ ∀ ◕｡)",
@@ -55,11 +50,9 @@ NAUGHTY_STRINGS = [
     "・(￣∀￣)・:*:",
     "ﾟ･✿ヾ╲(｡◕‿◕｡)╱✿･ﾟ",
     ",。・:*:・゜’( ☻ ω ☻ )。・:*:・゜’",
-    "(╯°□°）╯︵ ┻━┻)"
-    "(ﾉಥ益ಥ）ﾉ ┻━┻",
+    "(╯°□°）╯︵ ┻━┻)" "(ﾉಥ益ಥ）ﾉ ┻━┻",
     "┬─┬ノ( º _ ºノ)",
     "( ͡° ͜ʖ ͡°)",
-
     # Emoji
     "😍",
     "👩🏽",
@@ -69,18 +62,14 @@ NAUGHTY_STRINGS = [
     "✋🏿 💪🏿 👐🏿 🙌🏿 👏🏿 🙏🏿",
     "🚾 🆒 🆓 🆕 🆖 🆗 🆙 🏧",
     "0️⃣ 1️⃣ 2️⃣ 3️⃣ 4️⃣ 5️⃣ 6️⃣ 7️⃣ 8️⃣ 9️⃣ 🔟",
-
     # Regional Indicator Symbols
     "🇺🇸🇷🇺🇸 🇦🇫🇦🇲🇸",
     "🇺🇸🇷🇺🇸🇦🇫🇦🇲",
     "🇺🇸🇷🇺🇸🇦",
-
     # Unicode Numbers
     "１２３",
     "١٢٣",
-
     # Right-To-Left Strings
-
     "ثم نفس سقطت وبالتحديد،, جزيرتي باستخدام أن دنو. إذ هنا؟ الستار وتنصيب كان. أهّل ايطاليا، بريطانيا-فرنسا قد أخذ. سليمان، إتفاقية بين ما, يذكر الحدود أي بعد, معاملة بولندا، الإطلاق عل إيو.",
     "إيو.",
     "בְּרֵאשִׁית, בָּרָא אֱלֹהִים, אֵת הַשָּׁמַיִם, וְאֵת הָאָרֶץ",
@@ -88,34 +77,21 @@ NAUGHTY_STRINGS = [
     "﷽",
     "ﷺ",
     "مُنَاقَشَةُ سُبُلِ اِسْتِخْدَامِ اللُّغَةِ فِي النُّظُمِ الْقَائِمَةِ وَفِيم يَخُصَّ التَّطْبِيقَاتُ الْحاسُوبِيَّةُ،",
-
     # Trick Unicode
     "‪‪test‪",
     "‫test",
     "
test
",
     "test⁠test",
     "⁦test⁧",
-
     # Zalgo Text
     "Ṱ̺̺̕o͞ ̷i̲̬͇̪͙n̝̗͕v̟̜̘̦͟o̶̙̰̠kè͚̮̺̪̹̱̤ ̖t̝͕̳̣̻̪͞h̼͓̲̦̳̘̲e͇̣̰̦̬͎ ̢̼̻̱̘h͚͎͙̜̣̲ͅi̦̲̣̰̤v̻͍e̺̭̳̪̰-m̢iͅn̖̺̞̲̯̰d̵̼̟͙̩̼̘̳ ̞̥̱̳̭r̛̗̘e͙p͠r̼̞̻̭̗e̺̠̣͟s̘͇̳͍̝͉e͉̥̯̞̲͚̬͜ǹ̬͎͎̟̖͇̤t͍̬̤͓̼̭͘ͅi̪̱n͠g̴͉ ͏͉ͅc̬̟h͡a̫̻̯͘o̫̟̖͍̙̝͉s̗̦̲.̨̹͈̣",
-
-
     "̡͓̞ͅI̗̘̦͝n͇͇͙v̮̫ok̲̫̙͈i̖͙̭̹̠̞n̡̻̮̣̺g̲͈͙̭͙̬͎ ̰t͔̦h̞̲e̢̤ ͍̬̲͖f̴̘͕̣è͖ẹ̥̩l͖͔͚i͓͚̦͠n͖͍̗͓̳̮g͍ ̨o͚̪͡f̘̣̬ ̖̘͖̟͙̮c҉͔̫͖͓͇͖ͅh̵̤̣͚͔á̗̼͕ͅo̼̣̥s̱͈̺̖̦̻͢.̛̖̞̠̫̰",
-
-
     "̗̺͖̹̯͓Ṯ̤͍̥͇͈h̲́e͏͓̼̗̙̼̣͔ ͇̜̱̠͓͍ͅN͕͠e̗̱z̘̝̜̺͙p̤̺̹͍̯͚e̠̻̠͜r̨̤͍̺̖͔̖̖d̠̟̭̬̝͟i̦͖̩͓͔̤a̠̗̬͉̙n͚͜ ̻̞̰͚ͅh̵͉i̳̞v̢͇ḙ͎͟-҉̭̩̼͔m̤̭̫i͕͇̝̦n̗͙ḍ̟ ̯̲͕͞ǫ̟̯̰̲͙̻̝f ̪̰̰̗̖̭̘͘c̦͍̲̞͍̩̙ḥ͚a̮͎̟̙͜ơ̩̹͎s̤.̝̝ ҉Z̡̖̜͖̰̣͉̜a͖̰͙̬͡l̲̫̳͍̩g̡̟̼̱͚̞̬ͅo̗͜.̟",
-
-
     "̦H̬̤̗̤͝e͜ ̜̥̝̻͍̟́w̕h̖̯͓o̝͙̖͎̱̮ ҉̺̙̞̟͈W̷̼̭a̺̪͍į͈͕̭͙̯̜t̶̼̮s̘͙͖̕ ̠̫̠B̻͍͙͉̳ͅe̵h̵̬͇̫͙i̹͓̳̳̮͎̫̕n͟d̴̪̜̖ ̰͉̩͇͙̲͞ͅT͖̼͓̪͢h͏͓̮̻e̬̝̟ͅ ̤̹̝W͙̞̝͔͇͝ͅa͏͓͔̹̼̣l̴͔̰̤̟͔ḽ̫.͕",
-
-
     "Z̮̞̠͙͔ͅḀ̗̞͈̻̗Ḷ͙͎̯̹̞͓G̻O̭̗̮",
-
-
     # Unicode Upsidedown
     "˙ɐnbᴉlɐ ɐuƃɐɯ ǝɹolop ʇǝ ǝɹoqɐl ʇn ʇunpᴉpᴉɔuᴉ ɹodɯǝʇ poɯsnᴉǝ op pǝs 'ʇᴉlǝ ƃuᴉɔsᴉdᴉpɐ ɹnʇǝʇɔǝsuoɔ 'ʇǝɯɐ ʇᴉs ɹolop ɯnsdᴉ ɯǝɹo˥",
     "00˙Ɩ$-",
-
     # Unicode font
     "Ｔｈｅ ｑｕｉｃｋ ｂｒｏｗｎ ｆｏｘ ｊｕｍｐｓ ｏｖｅｒ ｔｈｅ ｌａｚｙ ｄｏｇ",
     "𝐓𝐡𝐞 𝐪𝐮𝐢𝐜𝐤 𝐛𝐫𝐨𝐰𝐧 𝐟𝐨𝐱 𝐣𝐮𝐦𝐩𝐬 𝐨𝐯𝐞𝐫 𝐭𝐡𝐞 𝐥𝐚𝐳𝐲 𝐝𝐨𝐠",
@@ -125,19 +101,17 @@ NAUGHTY_STRINGS = [
     "𝕋𝕙𝕖 𝕢𝕦𝕚𝕔𝕜 𝕓𝕣𝕠𝕨𝕟 𝕗𝕠𝕩 𝕛𝕦𝕞𝕡𝕤 𝕠𝕧𝕖𝕣 𝕥𝕙𝕖 𝕝𝕒𝕫𝕪 𝕕𝕠𝕘",
     "𝚃𝚑𝚎 𝚚𝚞𝚒𝚌𝚔 𝚋𝚛𝚘𝚠𝚗 𝚏𝚘𝚡 𝚓𝚞𝚖𝚙𝚜 𝚘𝚟𝚎𝚛 𝚝𝚑𝚎 𝚕𝚊𝚣𝚢 𝚍𝚘𝚐",
     "⒯⒣⒠ ⒬⒰⒤⒞⒦ ⒝⒭⒪⒲⒩ ⒡⒪⒳ ⒥⒰⒨⒫⒮ ⒪⒱⒠⒭ ⒯⒣⒠ ⒧⒜⒵⒴ ⒟⒪⒢",
-
     # File paths
     "../../../../../../../../../../../etc/passwd%00",
     "../../../../../../../../../../../etc/hosts",
-
     # iOS Vulnerabilities
     "Powerلُلُصّبُلُلصّبُررً ॣ ॣh ॣ ॣ冗",
-    "🏳0🌈️"
+    "🏳0🌈️",
 ]
 
 
 @pytest.mark.slow
-@pytest.mark.parametrize('text', NAUGHTY_STRINGS)
+@pytest.mark.parametrize("text", NAUGHTY_STRINGS)
 def test_tokenizer_naughty_strings(tokenizer, text):
     tokens = tokenizer(text)
     assert tokens.text_with_ws == text