fix(io): format dataframe-level checks in to_script

to_script(minimal=False) interpolated the raw statistics list for
dataframe-level checks straight into the script template, while the
column path 19 lines above formats its checks with _format_checks.

The generated script runs and looks correct, but the schema it builds
carries plain dicts where Check objects belong. Every validate() call on
it then fails with TypeError("'dict' object is not callable"), including
on data the original schema accepts, so the round-tripped schema is
unusable rather than merely wrong.

Format dataframe-level checks the same way the column path does.
_format_checks(None) already returns "None", so schemas without
dataframe-level checks are unaffected.

The existing test_to_script only covers column checks, so this path was
untested; add a round-trip test with a dataframe-level check.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: chuenchen309

pandera/io/pandas_io.py

@@ -838,7 +838,7 @@ def to_script(dataframe_schema, path_or_buf=None, *, minimal: bool = True):
 
     script = SCRIPT_TEMPLATE.format(
         columns=column_str,
-        checks=statistics["checks"],
+        checks=_format_checks(statistics["checks"]),
         index=index,
         dtype=dataframe_schema.dtype,
         coerce=dataframe_schema.coerce,

tests/io/test_pandas_io.py

@@ -1547,6 +1547,28 @@ def test_to_script(index):
         assert schema == schema_to_write
 
 
+@pytest.mark.skipif(
+    platform.system() == "Windows",
+    reason="skipping due to issues with opening file names for temp files.",
+)
+def test_to_script_dataframe_level_checks():
+    """Test that dataframe-level checks survive a to_script round trip."""
+    schema_to_write = pandera.DataFrameSchema(
+        {"a": pandera.Column(int)},
+        checks=[pandera.Check.gt(0)],
+    )
+
+    local_dict = {}
+    # pylint: disable=exec-used
+    exec(schema_to_write.to_script(minimal=False), globals(), local_dict)
+    schema = local_dict["schema"]
+
+    assert schema == schema_to_write
+    schema.validate(pd.DataFrame({"a": [1, 2]}))
+    with pytest.raises(pandera.errors.SchemaError):
+        schema.validate(pd.DataFrame({"a": [-1]}))
+
+
 def test_to_script_lambda_check():
     """Test writing DataFrameSchema to a script with lambda check."""
     schema1 = pandera.DataFrameSchema(