Drop Python 3.9 support after EOL

Python 3.9 reached End-of-Life on October 31, 2025 and no longer receives
security updates or bug fixes from the Python core team.

Changes:
- Update requires-python from ">=3.9" to ">=3.10" in pyproject.toml
- Remove Python 3.9 classifier from pyproject.toml
- Remove Python 3.9 from CI test matrix
- Remove py39 from tox envlist
- Update ruff target-version from py39 to py310
- Update mypy python_version from 3.9 to "3.10"
- Update README.rst and docs/introduction.rst to reflect Python 3.10-3.13 support
- Add strict=False to zip() calls (Python 3.10+ requirement)

Closes #617

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: laughingman7743

.github/workflows/test.yaml

@@ -22,7 +22,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
+        python-version: ['3.10', '3.11', '3.12', '3.13']
 
     steps:
       - name: Checkout

README.rst

@@ -40,7 +40,7 @@ Requirements
 
 * Python
 
-  - CPython 3.9 3.10, 3.11 3.12 3.13
+  - CPython 3.10, 3.11, 3.12, 3.13
 
 .. _installation:
 

docs/introduction.rst

@@ -10,7 +10,7 @@ Requirements
 
 * Python
 
-  - CPython 3.9 3.10, 3.11 3.12 3.13
+  - CPython 3.10, 3.11, 3.12, 3.13
 
 .. _installation:
 

pyathena/arrow/result_set.py

@@ -225,8 +225,8 @@ def _fetch(self) -> None:
             dict_rows = rows.to_pydict()
             column_names = dict_rows.keys()
             processed_rows = [
-                tuple(self.converters[k](v) for k, v in zip(column_names, row))
-                for row in zip(*dict_rows.values())
+                tuple(self.converters[k](v) for k, v in zip(column_names, row, strict=False))
+                for row in zip(*dict_rows.values(), strict=False)
             ]
             self._rows.extend(processed_rows)
 

pyathena/pandas/util.py

@@ -211,10 +211,15 @@ def to_sql(
             for keys, group in df.groupby(by=partitions, observed=True):
                 keys = keys if isinstance(keys, tuple) else (keys,)
                 group = group.drop(partitions, axis=1)
-                partition_prefix = "/".join([f"{key}={val}" for key, val in zip(partitions, keys)])
+                partition_prefix = "/".join(
+                    [f"{key}={val}" for key, val in zip(partitions, keys, strict=False)]
+                )
+                partition_condition = ", ".join(
+                    [f"`{key}` = '{val}'" for key, val in zip(partitions, keys, strict=False)]
+                )
                 partition_prefixes.append(
                     (
-                        ", ".join([f"`{key}` = '{val}'" for key, val in zip(partitions, keys)]),
+                        partition_condition,
                         f"{location}{partition_prefix}/",
                     )
                 )

pyathena/result_set.py

@@ -396,7 +396,7 @@ def _get_rows(
             tuple(
                 [
                     self._converter.convert(meta.get("Type"), row.get("VarCharValue"))
-                    for meta, row in zip(metadata, rows[i].get("Data", []))
+                    for meta, row in zip(metadata, rows[i].get("Data", []), strict=False)
                 ]
             )
             for i in range(offset, len(rows))
@@ -420,7 +420,7 @@ def _process_rows(self, response: Dict[str, Any]) -> None:
     def _is_first_row_column_labels(self, rows: List[Dict[str, Any]]) -> bool:
         first_row_data = rows[0].get("Data", [])
         metadata = cast(Tuple[Any, Any], self._metadata)
-        for meta, data in zip(metadata, first_row_data):
+        for meta, data in zip(metadata, first_row_data, strict=False):
             if meta.get("Name") != data.get("VarCharValue"):
                 return False
         return True
@@ -496,7 +496,7 @@ def _get_rows(
                         meta.get("Name"),
                         self._converter.convert(meta.get("Type"), row.get("VarCharValue")),
                     )
-                    for meta, row in zip(metadata, rows[i].get("Data", []))
+                    for meta, row in zip(metadata, rows[i].get("Data", []), strict=False)
                 ]
             )
             for i in range(offset, len(rows))

pyproject.toml

@@ -11,7 +11,7 @@ dependencies = [
     "fsspec",
     "python-dateutil",
 ]
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 readme = "README.rst"
 license = {file = "LICENSE"}
 classifiers = [
@@ -21,7 +21,6 @@ classifiers = [
     "Operating System :: OS Independent",
     "Topic :: Database :: Front-Ends",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -107,7 +106,7 @@ exclude = [
     ".venv",
     ".tox",
 ]
-target-version = "py39"
+target-version = "py310"
 
 [tool.ruff.lint]
 # https://docs.astral.sh/ruff/rules/
@@ -125,7 +124,7 @@ select = [
 ]
 
 [tool.mypy]
-python_version = 3.9
+python_version = "3.10"
 follow_imports = "silent"
 disallow_any_generics = true
 strict_optional = true
@@ -149,11 +148,10 @@ exclude = [
 legacy_tox_ini = """
 [tox]
 isolated_build = true
-envlist = py{39,310,311,312,313}
+envlist = py{310,311,312,313}
 
 [gh-actions]
 python =
-    3.9: py39
     3.10: py310
     3.11: py311
     3.12: py312

tests/pyathena/arrow/test_async_cursor.py

@@ -226,7 +226,7 @@ def test_as_arrow(self, async_arrow_cursor):
         table = future.result().as_arrow()
         assert table.shape[0] == 1
         assert table.shape[1] == 1
-        assert list(zip(*table.to_pydict().values())) == [(1,)]
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [(1,)]
 
     @pytest.mark.parametrize(
         "async_arrow_cursor",
@@ -238,7 +238,7 @@ def test_many_as_arrow(self, async_arrow_cursor):
         table = future.result().as_arrow()
         assert table.shape[0] == 10000
         assert table.shape[1] == 1
-        assert list(zip(*table.to_pydict().values())) == [(i,) for i in range(10000)]
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [(i,) for i in range(10000)]
 
     def test_cancel(self, async_arrow_cursor):
         query_id, future = async_arrow_cursor.execute(

tests/pyathena/arrow/test_cursor.py

@@ -259,7 +259,7 @@ def test_as_arrow(self, arrow_cursor):
         table = arrow_cursor.execute("SELECT * FROM one_row").as_arrow()
         assert table.shape[0] == 1
         assert table.shape[1] == 1
-        assert list(zip(*table.to_pydict().values())) == [(1,)]
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [(1,)]
 
     @pytest.mark.parametrize(
         "arrow_cursor",
@@ -270,7 +270,7 @@ def test_many_as_arrow(self, arrow_cursor):
         table = arrow_cursor.execute("SELECT * FROM many_rows").as_arrow()
         assert table.shape[0] == 10000
         assert table.shape[1] == 1
-        assert list(zip(*table.to_pydict().values())) == [(i,) for i in range(10000)]
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [(i,) for i in range(10000)]
 
     def test_complex_as_arrow(self, arrow_cursor):
         table = arrow_cursor.execute(
@@ -323,7 +323,7 @@ def test_complex_as_arrow(self, arrow_cursor):
                 pa.field("col_decimal", pa.string()),
             ]
         )
-        assert list(zip(*table.to_pydict().values())) == [
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [
             (
                 True,
                 127,
@@ -406,7 +406,7 @@ def test_complex_unload_as_arrow(self, arrow_cursor):
                 pa.field("col_decimal", pa.decimal128(10, 1)),
             ]
         )
-        assert list(zip(*table.to_pydict().values())) == [
+        assert list(zip(*table.to_pydict().values(), strict=False)) == [
             (
                 True,
                 127,

tests/pyathena/pandas/test_cursor.py

@@ -1582,5 +1582,5 @@ def test_pandas_cursor_iter_chunks_consistency(self, pandas_cursor):
         assert len(chunks_via_method) == len(chunks_via_direct)
 
         # Each corresponding chunk should be identical
-        for chunk1, chunk2 in zip(chunks_via_method, chunks_via_direct):
+        for chunk1, chunk2 in zip(chunks_via_method, chunks_via_direct, strict=False):
             pd.testing.assert_frame_equal(chunk1, chunk2)