Auto-format code with black

spacy/lang/el/tokenizer_exceptions.py

@@ -128,7 +128,6 @@ _other_exc = {
 _exc.update(_other_exc)
 
 for h in range(1, 12 + 1):
-
     for period in ["π.μ.", "πμ"]:
         _exc[f"{h}{period}"] = [
             {ORTH: f"{h}"},

spacy/lang/fi/tokenizer_exceptions.py

@@ -101,9 +101,9 @@ conj_contraction_negations = [
     ("eivat", "eivät"),
     ("eivät", "eivät"),
 ]
-for (base_lower, base_norm) in conj_contraction_bases:
+for base_lower, base_norm in conj_contraction_bases:
     for base in [base_lower, base_lower.title()]:
-        for (suffix, suffix_norm) in conj_contraction_negations:
+        for suffix, suffix_norm in conj_contraction_negations:
             _exc[base + suffix] = [
                 {ORTH: base, NORM: base_norm},
                 {ORTH: suffix, NORM: suffix_norm},

spacy/ml/models/entity_linker.py

@@ -105,7 +105,7 @@ def create_candidates() -> Callable[[KnowledgeBase, Span], Iterable[Candidate]]:
 
 
 @registry.misc("spacy.CandidateBatchGenerator.v1")
-def create_candidates_batch() -> Callable[
+def create_candidates_batch() -> (
-    [KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]
+    Callable[[KnowledgeBase, Iterable[Span]], Iterable[Iterable[Candidate]]]
-]:
+):
     return get_candidates_batch

spacy/pipeline/edit_tree_lemmatizer.py

@@ -130,7 +130,7 @@ class EditTreeLemmatizer(TrainablePipe):
         truths = []
         for eg in examples:
             eg_truths = []
-            for (predicted, gold_lemma) in zip(
+            for predicted, gold_lemma in zip(
                 eg.predicted, eg.get_aligned("LEMMA", as_string=True)
             ):
                 if gold_lemma is None or gold_lemma == "":

spacy/tests/doc/test_doc_api.py

@@ -132,7 +132,8 @@ def test_issue3869(sentence):
 @pytest.mark.issue(3962)
 def test_issue3962(en_vocab):
     """Ensure that as_doc does not result in out-of-bound access of tokens.
-    This is achieved by setting the head to itself if it would lie out of the span otherwise."""
+    This is achieved by setting the head to itself if it would lie out of the span otherwise.
+    """
     # fmt: off
     words = ["He", "jests", "at", "scars", ",", "that", "never", "felt", "a", "wound", "."]
     heads = [1, 7, 1, 2, 7, 7, 7, 7, 9, 7, 7]
@@ -171,7 +172,8 @@ def test_issue3962(en_vocab):
 @pytest.mark.issue(3962)
 def test_issue3962_long(en_vocab):
     """Ensure that as_doc does not result in out-of-bound access of tokens.
-    This is achieved by setting the head to itself if it would lie out of the span otherwise."""
+    This is achieved by setting the head to itself if it would lie out of the span otherwise.
+    """
     # fmt: off
     words = ["He", "jests", "at", "scars", ".", "They", "never", "felt", "a", "wound", "."]
     heads = [1, 1, 1, 2, 1, 7, 7, 7, 9, 7, 7]

spacy/tests/doc/test_span.py

@@ -238,7 +238,6 @@ def test_spans_span_sent(doc, doc_not_parsed):
     ],
 )
 def test_spans_span_sent_user_hooks(doc, start, end, expected_sentence):
-
     # Doc-level sents hook
     def user_hook(doc):
         return [doc[ii : ii + 2] for ii in range(0, len(doc), 2)]
@@ -668,7 +667,6 @@ def test_span_comparison(doc):
     ],
 )
 def test_span_sents(doc, start, end, expected_sentences, expected_sentences_with_hook):
-
     assert len(list(doc[start:end].sents)) == expected_sentences
 
     def user_hook(doc):

spacy/tests/matcher/test_matcher_logic.py

@@ -544,7 +544,7 @@ def test_greedy_matching_longest(doc, text, pattern, longest):
     matcher = Matcher(doc.vocab)
     matcher.add("RULE", [pattern], greedy="LONGEST")
     matches = matcher(doc)
-    for (key, s, e) in matches:
+    for key, s, e in matches:
         assert doc[s:e].text == longest
 
 

spacy/tests/pipeline/test_entity_linker.py

@@ -505,15 +505,15 @@ def test_el_pipe_configuration(nlp):
         return [get_lowercased_candidates(kb, span) for span in spans]
 
     @registry.misc("spacy.LowercaseCandidateGenerator.v1")
-    def create_candidates() -> Callable[
+    def create_candidates() -> (
-        [InMemoryLookupKB, "Span"], Iterable[Candidate]
+        Callable[[InMemoryLookupKB, "Span"], Iterable[Candidate]]
-    ]:
+    ):
         return get_lowercased_candidates
 
     @registry.misc("spacy.LowercaseCandidateBatchGenerator.v1")
-    def create_candidates_batch() -> Callable[
+    def create_candidates_batch() -> (
-        [InMemoryLookupKB, Iterable["Span"]], Iterable[Iterable[Candidate]]
+        Callable[[InMemoryLookupKB, Iterable["Span"]], Iterable[Iterable[Candidate]]]
-    ]:
+    ):
         return get_lowercased_candidates_batch
 
     # replace the pipe with a new one with with a different candidate generator

spacy/tests/pipeline/test_textcat.py

@@ -822,7 +822,8 @@ def test_textcat_eval_missing(multi_label: bool, spring_p: float):
 def test_textcat_loss(multi_label: bool, expected_loss: float):
     """
     multi-label: the missing 'spring' in gold_doc_2 doesn't incur an increase in loss
-    exclusive labels: the missing 'spring' in gold_doc_2 is interpreted as 0.0 and adds to the loss"""
+    exclusive labels: the missing 'spring' in gold_doc_2 is interpreted as 0.0 and adds to the loss
+    """
     train_examples = []
     nlp = English()