Auto-format code with black

spacy/tests/doc/test_token_api.py

@@ -255,7 +255,7 @@ def test_token_api_non_conjuncts(en_vocab):
 
 
 def test_missing_head_dep(en_vocab):
-    """ Check that the Doc constructor and Example.from_dict parse missing information the same"""
+    """Check that the Doc constructor and Example.from_dict parse missing information the same"""
     heads = [1, 1, 1, 1, 2, None]  # element 5 is missing
     deps = ["", "ROOT", "dobj", "cc", "conj", None]  # element 0 and 5 are missing
     words = ["I", "like", "London", "and", "Berlin", "."]

spacy/tests/lang/ca/test_prefix_suffix_infix.py

@@ -5,7 +5,7 @@ import pytest
     "text,expected_tokens", [("d'un", ["d'", "un"]), ("s'ha", ["s'", "ha"])]
 )
 def test_contractions(ca_tokenizer, text, expected_tokens):
-    """ Test that the contractions are split into two tokens"""
+    """Test that the contractions are split into two tokens"""
     tokens = ca_tokenizer(text)
     assert len(tokens) == 2
     assert [t.text for t in tokens] == expected_tokens

spacy/tests/lang/it/test_prefix_suffix_infix.py

@@ -5,7 +5,7 @@ import pytest
     "text,expected_tokens", [("c'è", ["c'", "è"]), ("l'ha", ["l'", "ha"])]
 )
 def test_contractions(it_tokenizer, text, expected_tokens):
-    """ Test that the contractions are split into two tokens"""
+    """Test that the contractions are split into two tokens"""
     tokens = it_tokenizer(text)
     assert len(tokens) == 2
     assert [t.text for t in tokens] == expected_tokens

spacy/tests/parser/test_ner.py

@@ -304,7 +304,7 @@ def test_empty_ner():
 
 
 def test_ruler_before_ner():
-    """ Test that an NER works after an entity_ruler: the second can add annotations """
+    """Test that an NER works after an entity_ruler: the second can add annotations"""
     nlp = English()
 
     # 1 : Entity Ruler - should set "this" to B and everything else to empty
@@ -334,7 +334,7 @@ def test_ner_constructor(en_vocab):
 
 
 def test_ner_before_ruler():
-    """ Test that an entity_ruler works after an NER: the second can overwrite O annotations """
+    """Test that an entity_ruler works after an NER: the second can overwrite O annotations"""
     nlp = English()
 
     # 1: untrained NER - should set everything to O
@@ -355,7 +355,7 @@ def test_ner_before_ruler():
 
 
 def test_block_ner():
-    """ Test functionality for blocking tokens so they can't be in a named entity """
+    """Test functionality for blocking tokens so they can't be in a named entity"""
     # block "Antti L Korhonen" from being a named entity
     nlp = English()
     nlp.add_pipe("blocker", config={"start": 2, "end": 5})

spacy/tests/regression/test_issue3501-4000.py

@@ -197,7 +197,7 @@ def test_issue3555(en_vocab):
 
 
 def test_issue3611():
-    """ Test whether adding n-grams in the textcat works even when n > token length of some docs """
+    """Test whether adding n-grams in the textcat works even when n > token length of some docs"""
     unique_classes = ["offensive", "inoffensive"]
     x_train = [
         "This is an offensive text",
@@ -282,7 +282,7 @@ def test_issue3830_with_subtok():
 
 
 def test_issue3839(en_vocab):
-    """Test that match IDs returned by the matcher are correct, are in the string """
+    """Test that match IDs returned by the matcher are correct, are in the string"""
     doc = Doc(en_vocab, words=["terrific", "group", "of", "people"])
     matcher = Matcher(en_vocab)
     match_id = "PATTERN"
@@ -366,7 +366,7 @@ def test_issue3951(en_vocab):
 
 
 def test_issue3959():
-    """ Ensure that a modified pos attribute is serialized correctly."""
+    """Ensure that a modified pos attribute is serialized correctly."""
     nlp = English()
     doc = nlp(
         "displaCy uses JavaScript, SVG and CSS to show you how computers understand language"

spacy/tests/regression/test_issue4001-4500.py

@@ -38,7 +38,7 @@ def test_issue4002(en_vocab):
 
 
 def test_issue4030():
-    """ Test whether textcat works fine with empty doc """
+    """Test whether textcat works fine with empty doc"""
     unique_classes = ["offensive", "inoffensive"]
     x_train = [
         "This is an offensive text",
@@ -237,7 +237,7 @@ def test_issue4190():
 
 
 def test_issue4267():
-    """ Test that running an entity_ruler after ner gives consistent results"""
+    """Test that running an entity_ruler after ner gives consistent results"""
     nlp = English()
     ner = nlp.add_pipe("ner")
     ner.add_label("PEOPLE")
@@ -288,7 +288,7 @@ def test_multiple_predictions():
 
 
 def test_issue4313():
-    """ This should not crash or exit with some strange error code """
+    """This should not crash or exit with some strange error code"""
     beam_width = 16
     beam_density = 0.0001
     nlp = English()

spacy/tests/regression/test_issue4501-5000.py

@@ -152,7 +152,7 @@ def test_issue4707():
 
 
 def test_issue4725_1():
-    """ Ensure the pickling of the NER goes well"""
+    """Ensure the pickling of the NER goes well"""
     vocab = Vocab(vectors_name="test_vocab_add_vector")
     nlp = English(vocab=vocab)
     config = {

spacy/tests/regression/test_issue5001-5500.py

@@ -96,7 +96,7 @@ def test_issue5137():
 
 
 def test_issue5141(en_vocab):
-    """ Ensure an empty DocBin does not crash on serialization """
+    """Ensure an empty DocBin does not crash on serialization"""
     doc_bin = DocBin(attrs=["DEP", "HEAD"])
     assert list(doc_bin.get_docs(en_vocab)) == []
     doc_bin_bytes = doc_bin.to_bytes()

spacy/tests/serialize/test_serialize_config.py

@@ -238,7 +238,7 @@ def test_create_nlp_from_config_multiple_instances():
 
 
 def test_serialize_nlp():
-    """ Create a custom nlp pipeline from config and ensure it serializes it correctly """
+    """Create a custom nlp pipeline from config and ensure it serializes it correctly"""
     nlp_config = Config().from_str(nlp_config_string)
     nlp = load_model_from_config(nlp_config, auto_fill=True)
     nlp.get_pipe("tagger").add_label("A")
@@ -258,7 +258,7 @@ def test_serialize_nlp():
 
 
 def test_serialize_custom_nlp():
-    """ Create a custom nlp pipeline and ensure it serializes it correctly"""
+    """Create a custom nlp pipeline and ensure it serializes it correctly"""
     nlp = English()
     parser_cfg = dict()
     parser_cfg["model"] = {"@architectures": "my_test_parser"}
@@ -279,7 +279,7 @@ def test_serialize_custom_nlp():
     "parser_config_string", [parser_config_string_upper, parser_config_string_no_upper]
 )
 def test_serialize_parser(parser_config_string):
-    """ Create a non-default parser config to check nlp serializes it correctly """
+    """Create a non-default parser config to check nlp serializes it correctly"""
     nlp = English()
     model_config = Config().from_str(parser_config_string)
     parser = nlp.add_pipe("parser", config=model_config)

spacy/tests/test_misc.py

@@ -275,7 +275,7 @@ def test_util_minibatch(doc_sizes, expected_batches):
     ],
 )
 def test_util_minibatch_oversize(doc_sizes, expected_batches):
-    """ Test that oversized documents are returned in their own batch"""
+    """Test that oversized documents are returned in their own batch"""
     docs = [get_random_doc(doc_size) for doc_size in doc_sizes]
     tol = 0.2
     batch_size = 1000

spacy/training/converters/conllu_to_docs.py

@@ -69,7 +69,7 @@ def read_conllx(
     ner_tag_pattern="",
     ner_map=None,
 ):
-    """ Yield docs, one for each sentence """
+    """Yield docs, one for each sentence"""
     vocab = Vocab()  # need vocab to make a minimal Doc
     for sent in input_data.strip().split("\n\n"):
         lines = sent.strip().split("\n")

spacy/training/corpus.py

@@ -186,7 +186,7 @@ class Corpus:
     def read_docbin(
         self, vocab: Vocab, locs: Iterable[Union[str, Path]]
     ) -> Iterator[Doc]:
-        """ Yield training examples as example dicts """
+        """Yield training examples as example dicts"""
         i = 0
         for loc in locs:
             loc = util.ensure_path(loc)

spacy/training/loggers.py

@@ -110,6 +110,7 @@ def wandb_logger(
 ):
     try:
         import wandb
+
         # test that these are available
         from wandb import init, log, join  # noqa: F401
     except ImportError: