From 685a386106f1c4624c1dba1bc8c6ee25491e8b6e Mon Sep 17 00:00:00 2001
From: Matthew Honnibal <honnibal+gh@gmail.com>
Date: Mon, 13 Jan 2025 14:00:06 +0100
Subject: [PATCH] Reformat

---
 spacy/tests/lang/ca/test_text.py          | 1 +
 spacy/tests/lang/ja/test_lemmatization.py | 8 +++++++-
 spacy/tests/lang/ja/test_tokenizer.py     | 7 ++++++-
 spacy/tests/lang/ko/test_lemmatization.py | 9 ++++++++-
 spacy/tests/lang/pl/test_text.py          | 1 +
 spacy/tests/training/test_pretraining.py  | 2 +-
 6 files changed, 24 insertions(+), 4 deletions(-)

diff --git a/spacy/tests/lang/ca/test_text.py b/spacy/tests/lang/ca/test_text.py
index 5db7af553..231cc085e 100644
--- a/spacy/tests/lang/ca/test_text.py
+++ b/spacy/tests/lang/ca/test_text.py
@@ -1,4 +1,5 @@
 """Test that longer and mixed texts are tokenized correctly."""
+
 import pytest
 
 
diff --git a/spacy/tests/lang/ja/test_lemmatization.py b/spacy/tests/lang/ja/test_lemmatization.py
index 21879a569..523917f6d 100644
--- a/spacy/tests/lang/ja/test_lemmatization.py
+++ b/spacy/tests/lang/ja/test_lemmatization.py
@@ -3,7 +3,13 @@ import pytest
 
 @pytest.mark.parametrize(
     "word,lemma",
-    [("新しく", "新しい"), ("赤く", "赤い"), ("すごく", "すごい"), ("いただきました", "いただく"), ("なった", "なる")],
+    [
+        ("新しく", "新しい"),
+        ("赤く", "赤い"),
+        ("すごく", "すごい"),
+        ("いただきました", "いただく"),
+        ("なった", "なる"),
+    ],
 )
 def test_ja_lemmatizer_assigns(ja_tokenizer, word, lemma):
     test_lemma = ja_tokenizer(word)[0].lemma_
diff --git a/spacy/tests/lang/ja/test_tokenizer.py b/spacy/tests/lang/ja/test_tokenizer.py
index a26347444..36f7e3240 100644
--- a/spacy/tests/lang/ja/test_tokenizer.py
+++ b/spacy/tests/lang/ja/test_tokenizer.py
@@ -143,7 +143,12 @@ def test_ja_tokenizer_sub_tokens(
     [
         (
             "取ってつけた",
-            (["五段-ラ行;連用形-促音便"], [], ["下一段-カ行;連用形-一般"], ["助動詞-タ;終止形-一般"]),
+            (
+                ["五段-ラ行;連用形-促音便"],
+                [],
+                ["下一段-カ行;連用形-一般"],
+                ["助動詞-タ;終止形-一般"],
+            ),
             (["トッ"], ["テ"], ["ツケ"], ["タ"]),
         ),
         ("2=3", ([], [], []), (["ニ"], ["_"], ["サン"])),
diff --git a/spacy/tests/lang/ko/test_lemmatization.py b/spacy/tests/lang/ko/test_lemmatization.py
index 7782ca4bc..371e410a6 100644
--- a/spacy/tests/lang/ko/test_lemmatization.py
+++ b/spacy/tests/lang/ko/test_lemmatization.py
@@ -2,7 +2,14 @@ import pytest
 
 
 @pytest.mark.parametrize(
-    "word,lemma", [("새로운", "새롭"), ("빨간", "빨갛"), ("클수록", "크"), ("뭡니까", "뭣"), ("됐다", "되")]
+    "word,lemma",
+    [
+        ("새로운", "새롭"),
+        ("빨간", "빨갛"),
+        ("클수록", "크"),
+        ("뭡니까", "뭣"),
+        ("됐다", "되"),
+    ],
 )
 def test_ko_lemmatizer_assigns(ko_tokenizer, word, lemma):
     test_lemma = ko_tokenizer(word)[0].lemma_
diff --git a/spacy/tests/lang/pl/test_text.py b/spacy/tests/lang/pl/test_text.py
index e8654a498..43e4ab862 100644
--- a/spacy/tests/lang/pl/test_text.py
+++ b/spacy/tests/lang/pl/test_text.py
@@ -1,4 +1,5 @@
 """Words like numbers are recognized correctly."""
+
 import pytest
 
 
diff --git a/spacy/tests/training/test_pretraining.py b/spacy/tests/training/test_pretraining.py
index 22364bb78..41cbddcae 100644
--- a/spacy/tests/training/test_pretraining.py
+++ b/spacy/tests/training/test_pretraining.py
@@ -265,7 +265,7 @@ def test_pretraining_tagger():
 
 
 # Try to debug segfault on windows
-#def test_pretraining_training():
+# def test_pretraining_training():
 #    """Test that training can use a pretrained Tok2Vec model"""
 #    config = Config().from_str(pretrain_string_internal)
 #    nlp = util.load_model_from_config(config, auto_fill=True, validate=False)