Apply code formatting (ruff, isort, clang-format)

Author: ssam18

pandas/_libs/src/parser/tokenizer.c

@@ -1512,12 +1512,13 @@ double xstrtod(const char *str, char **endptr, char decimal, char sci,
     int n = 0;
     // Prevent integer overflow by capping exponent value
     // DBL_MAX_EXP is typically 1024, so we use a safe upper bound
-    const int MAX_EXPONENT_DIGITS = 4;  // Allows up to 9999
+    const int MAX_EXPONENT_DIGITS = 4; // Allows up to 9999
     while (isdigit_ascii(*p)) {
       if (num_digits < MAX_EXPONENT_DIGITS) {
         n = n * 10 + (*p - '0');
       }
-      // Continue consuming digits even after cap to maintain correct parsing position
+      // Continue consuming digits even after cap to maintain correct parsing
+      // position
       num_digits++;
       p++;
     }

pandas/tests/io/parser/test_issue_63089.py

@@ -1,37 +1,41 @@
 """
 Test for issue #63089 - read_csv segfault with large exponent
 """
+
 import io
+
 import pandas as pd
-import pytest
 
 
 class TestIssue63089:
     def test_large_exponent_no_segfault(self):
         """Test that extremely large exponents don't cause segfault."""
         # This previously caused SIGSEGV due to integer overflow
         # when parsing the exponent
-        result = pd.read_csv(io.StringIO("""h
-4e492493924924"""))
-        
+        result = pd.read_csv(
+            io.StringIO("""h
+4e492493924924""")
+        )
+
         # Should parse as infinity or large float, not crash
         assert len(result) == 1
-        assert 'h' in result.columns
+        assert "h" in result.columns
         # The value should be infinity since the exponent is way too large
         import numpy as np
-        assert np.isinf(result['h'].iloc[0]) or result['h'].iloc[0] > 1e308
-    
+
+        assert np.isinf(result["h"].iloc[0]) or result["h"].iloc[0] > 1e308
+
     def test_various_large_exponents(self):
         """Test various edge cases with large exponents."""
         test_cases = [
             "1e999999999",  # Very large positive exponent
-            "1e-999999999",  # Very large negative exponent  
+            "1e-999999999",  # Very large negative exponent
             "2.5e123456789",  # Large exponent with decimal
         ]
-        
+
         for test_val in test_cases:
             csv_data = f"col\n{test_val}"
             result = pd.read_csv(io.StringIO(csv_data))
             # Should not crash, result should be inf, 0, or valid float
             assert len(result) == 1
-            assert not pd.isna(result['col'].iloc[0]) or True  # Just don't crash
+            assert not pd.isna(result["col"].iloc[0]) or True  # Just don't crash

reproduce_issue_63089.py

@@ -1,10 +1,13 @@
 import io
+
 import pandas as pd
 
 print("Testing issue #63089...")
 try:
-    result = pd.read_csv(io.StringIO("""h
-4e492493924924"""))
+    result = pd.read_csv(
+        io.StringIO("""h
+4e492493924924""")
+    )
     print("Success! Result:")
     print(result)
 except Exception as e: