feat(pandas-gbq): add Ruff format session and implement mypy

packages/pandas-gbq/noxfile.py

@@ -18,18 +18,19 @@
 
 from __future__ import absolute_import
 
-from functools import wraps
 import os
 import pathlib
 import re
 import shutil
 import time
 import warnings
+from functools import wraps
 
 import nox
 
 BLACK_VERSION = "black==23.7.0"
 ISORT_VERSION = "isort==5.10.1"
+RUFF_VERSION = "ruff==0.14.14"
 LINT_PATHS = ["docs", "pandas_gbq", "tests", "noxfile.py", "setup.py"]
 
 DEFAULT_PYTHON_VERSION = "3.14"
@@ -147,19 +148,29 @@ def blacken(session):
 @_calculate_duration
 def format(session):
     """
-    Run isort to sort imports. Then run black
-    to format code to uniform standard.
+    Run ruff to sort imports and format code.
     """
-    session.install(BLACK_VERSION, ISORT_VERSION)
-    # Use the --fss option to sort imports using strict alphabetical order.
-    # See https://pycqa.github.io/isort/docs/configuration/options.html#force-sort-within-sections
+    # 1. Install ruff (skipped automatically if you run with --no-venv)
+    session.install(RUFF_VERSION)
+
+    # 2. Run Ruff to fix imports
     session.run(
-        "isort",
-        "--fss",
+        "ruff",
+        "check",
+        "--select",
+        "I",
+        "--fix",
+        f"--target-version=py{UNIT_TEST_PYTHON_VERSIONS[0].replace('.', '')}",
+        "--line-length=88",
         *LINT_PATHS,
     )
+
+    # 3. Run Ruff to format code
     session.run(
-        "black",
+        "ruff",
+        "format",
+        f"--target-version=py{UNIT_TEST_PYTHON_VERSIONS[0].replace('.', '')}",
+        "--line-length=88",
         *LINT_PATHS,
     )
 
@@ -519,11 +530,24 @@ def docfx(session):
 
 
 @nox.session(python=DEFAULT_PYTHON_VERSION)
+@_calculate_duration
 def mypy(session):
     """Run the type checker."""
-    # TODO(https://github.com/googleapis/google-cloud-python/issues/16014):
-    # Add mypy tests
-    session.skip("mypy tests are not yet supported")
+    session.install(
+        "mypy<1.16.0",
+        "types-requests",
+        "types-protobuf",
+        "pandas-stubs",
+        "types-tqdm",
+        "types-psutil",
+    )
+    session.install(".")
+    session.run(
+        "mypy",
+        "pandas_gbq",
+        "--check-untyped-defs",
+        *session.posargs,
+    )
 
 
 @nox.session(python=DEFAULT_PYTHON_VERSION)

packages/pandas-gbq/pandas_gbq/auth.py

@@ -23,7 +23,10 @@ def get_credentials(
     client_id=None,
     client_secret=None,
 ):
-    import pydata_google_auth
+    # pydata-google-auth does not have type hints nor stubs that mypy uses for type checking.
+    # Remove this comment and the ignore pragma upon completing:
+    # https://github.com/googleapis/google-cloud-python/issues/17045
+    import pydata_google_auth  # type: ignore[import-untyped]
 
     if private_key:
         raise NotImplementedError(
@@ -48,7 +51,10 @@ def get_credentials(
 
 
 def get_credentials_cache(reauth):
-    import pydata_google_auth.cache
+    # pydata-google-auth does not have type hints nor stubs that mypy uses for type checking.
+    # Remove this comment and the ignore pragma upon completing:
+    # https://github.com/googleapis/google-cloud-python/issues/17045
+    import pydata_google_auth.cache  # type: ignore[import-untyped]
 
     if reauth:
         return pydata_google_auth.cache.WriteOnlyCredentialsCache(

packages/pandas-gbq/pandas_gbq/core/pandas.py

@@ -5,6 +5,7 @@
 import itertools
 
 import pandas
+import typing
 
 
 def list_columns_and_indexes(dataframe, index=True):
@@ -22,7 +23,9 @@ def list_columns_and_indexes(dataframe, index=True):
         if isinstance(dataframe.index, pandas.MultiIndex):
             for name in dataframe.index.names:
                 if name and name not in column_names:
-                    values = dataframe.index.get_level_values(name)
+                    values = dataframe.index.get_level_values(
+                        typing.cast(typing.Union[str, int], name)
+                    )
                     columns_and_indexes.append((name, values.dtype))
         else:
             if dataframe.index.name and dataframe.index.name not in column_names:

packages/pandas-gbq/pandas_gbq/core/read.py

@@ -5,8 +5,8 @@
 from __future__ import annotations
 
 import typing
-from typing import Any, Dict, Optional, Sequence
 import warnings
+from typing import Any, Dict, Optional, Sequence
 
 import google.cloud.bigquery
 import google.cloud.bigquery.table
@@ -34,7 +34,10 @@ def _bqschema_to_nullsafe_dtypes(schema_fields):
     See: http://pandas.pydata.org/pandas-docs/dev/missing_data.html
     #missing-data-casting-rules-and-indexing
     """
-    import db_dtypes
+    # db-dtypes does not have type hints nor stubs that mypy uses for type checking.
+    # Remove this comment and the ignore pragma upon completing:
+    # https://github.com/googleapis/google-cloud-python/issues/17045
+    import db_dtypes  # type: ignore[import-untyped]
 
     # If you update this mapping, also update the table at
     # `docs/reading.rst`.
@@ -79,7 +82,10 @@ def _finalize_dtypes(
     1970. See:
     https://github.com/googleapis/python-bigquery-pandas/issues/365
     """
-    import db_dtypes
+    # db-dtypes does not have type hints nor stubs that mypy uses for type checking.
+    # Remove this comment and the ignore pragma upon completing:
+    # https://github.com/googleapis/google-cloud-python/issues/17045
+    import db_dtypes  # type: ignore[import-untyped]
     import pandas.api.types
 
     # If you update this mapping, also update the table at

packages/pandas-gbq/pandas_gbq/dry_runs.py

@@ -7,8 +7,8 @@
 import copy
 from typing import Any, List
 
-from google.cloud import bigquery
 import pandas
+from google.cloud import bigquery
 
 
 def get_query_stats(

packages/pandas-gbq/pandas_gbq/gbq.py

@@ -3,32 +3,36 @@
 # license that can be found in the LICENSE file.
 
 import copy
-from datetime import datetime
 import logging
 import re
 import typing
 import warnings
+from datetime import datetime
 
 import pandas
 
-from pandas_gbq.contexts import Context  # noqa - backward compatible export
-from pandas_gbq.contexts import context
-from pandas_gbq.exceptions import (  # noqa - backward compatible export
+import pandas_gbq.schema
+import pandas_gbq.schema.pandas_to_bigquery
+from pandas_gbq.contexts import (  # noqa: F401
+    Context,  # noqa: F401 - imported solely to support a backwards compatible export
+    context,
+)
+from pandas_gbq.exceptions import (  # noqa: F401 - imported solely to support a backwards compatible export
     DatasetCreationError,
     GenericGBQException,
     InvalidColumnOrder,
     InvalidIndexColumn,
+    InvalidPageToken,  # noqa: F401 - imported solely to support a backwards compatible export
+    InvalidSchema,  # noqa: F401 - imported solely to support a backwards compatible export
     NotFoundException,
+    QueryTimeout,  # noqa: F401 - imported solely to support a backwards compatible export
     TableCreationError,
 )
-from pandas_gbq.exceptions import InvalidPageToken  # noqa - backward compatible export
-from pandas_gbq.exceptions import InvalidSchema  # noqa - backward compatible export
-from pandas_gbq.exceptions import QueryTimeout  # noqa - backward compatible export
 from pandas_gbq.features import FEATURES
-from pandas_gbq.gbq_connector import GbqConnector  # noqa - backward compatible export
-from pandas_gbq.gbq_connector import _get_client  # noqa - backward compatible export
-import pandas_gbq.schema
-import pandas_gbq.schema.pandas_to_bigquery
+from pandas_gbq.gbq_connector import (  # noqa: F401
+    GbqConnector,  # noqa: F401 - imported solely to support a backwards compatible export
+    _get_client,  # noqa: F401 - imported solely to support a backwards compatible export
+)
 
 logger = logging.getLogger(__name__)
 
@@ -40,17 +44,29 @@ def _test_google_api_imports():
         raise ImportError("pandas-gbq requires db-dtypes") from ex
 
     try:
-        import db_dtypes  # noqa
+        # db-dtypes does not have type hints nor stubs that mypy uses for type checking.
+        # This import is solely to test if the package is installed, so we ignore the "unused import" warning.
+        # Remove this comment and the ignore pragma upon completing:
+        # https://github.com/googleapis/google-cloud-python/issues/17045
+        import db_dtypes  # type: ignore[import-untyped] # noqa: F401
     except ImportError as ex:  # pragma: NO COVER
         raise ImportError("pandas-gbq requires db-dtypes") from ex
 
     try:
-        import pydata_google_auth  # noqa
+        # pydata-google-auth does not have type hints nor stubs that mypy uses for type checking.
+        # This import is solely to test if the package is installed, so we ignore the "unused import" warning.
+        # Remove this comment and the ignore pragma upon completing:
+        # https://github.com/googleapis/google-cloud-python/issues/17045
+        import pydata_google_auth  # type: ignore[import-untyped] # noqa: F401
     except ImportError as ex:  # pragma: NO COVER
         raise ImportError("pandas-gbq requires pydata-google-auth") from ex
 
     try:
-        from google_auth_oauthlib.flow import InstalledAppFlow  # noqa
+        # google-auth-oauthlib does not have type hints nor stubs that mypy uses for type checking.
+        # This import is solely to test if the package is installed, so we ignore the "unused import" warning.
+        # Remove this comment and the ignore pragma upon completing:
+        # https://github.com/googleapis/google-cloud-python/issues/17045
+        from google_auth_oauthlib.flow import InstalledAppFlow  # type: ignore[import-untyped] # noqa: F401
     except ImportError as ex:  # pragma: NO COVER
         raise ImportError("pandas-gbq requires google-auth-oauthlib") from ex
 
@@ -686,7 +702,7 @@ def generate_bq_schema(df, default_type="STRING"):
     """
     # deprecation TimeSeries, #11121
     warnings.warn(
-        "generate_bq_schema is deprecated and will be removed in " "a future version",
+        "generate_bq_schema is deprecated and will be removed in a future version",
         FutureWarning,
         stacklevel=2,
     )
@@ -927,9 +943,7 @@ def create(self, dataset_id):
         from google.cloud.bigquery import Dataset
 
         if self.exists(dataset_id):
-            raise DatasetCreationError(
-                "Dataset {0} already " "exists".format(dataset_id)
-            )
+            raise DatasetCreationError("Dataset {0} already exists".format(dataset_id))
 
         dataset = Dataset(self._dataset_ref(dataset_id))
 

packages/pandas-gbq/pandas_gbq/gbq_connector.py

@@ -7,29 +7,30 @@
 import logging
 import time
 import typing
-from typing import Any, Dict, Optional, Union
 import warnings
+from typing import Any, Dict, Optional, Union
 
 # Only import at module-level at type checking time to avoid circular
 # dependencies in the pandas package, which has an optional dependency on
 # pandas-gbq.
 if typing.TYPE_CHECKING:  # pragma: NO COVER
     import pandas
 
-from pandas_gbq import dry_runs
 import pandas_gbq.constants
-from pandas_gbq.contexts import context
 import pandas_gbq.core.read
 import pandas_gbq.environment as environment
 import pandas_gbq.exceptions
+import pandas_gbq.query
+from pandas_gbq import dry_runs
+from pandas_gbq.contexts import context
 from pandas_gbq.exceptions import QueryTimeout
 from pandas_gbq.features import FEATURES
-import pandas_gbq.query
 
+tqdm: Any = None
 try:
     import tqdm  # noqa
 except ImportError:
-    tqdm = None
+    pass
 
 logger = logging.getLogger(__name__)
 
@@ -204,6 +205,8 @@ def run_query(
         ].get("timeoutMs")
 
         if timeout_ms:
+            if not isinstance(timeout_ms, (str, int, float)):
+                raise TypeError(f"Expected str, int or float, got {type(timeout_ms)}")
             timeout_ms = int(timeout_ms)
             # Having too small a timeout_ms results in individual
             # API calls timing out before they can finish.
@@ -220,6 +223,7 @@ def run_query(
 
         self._start_timer()
         job_config = bigquery.QueryJobConfig.from_api_repr(job_config_dict)
+        job_config = typing.cast(bigquery.QueryJobConfig, job_config)
         job_config.dry_run = dry_run
 
         if FEATURES.bigquery_has_query_and_wait:

packages/pandas-gbq/pandas_gbq/load/core.py

@@ -8,15 +8,18 @@
 import io
 from typing import Any, Callable, Dict, List, Optional
 
-import db_dtypes
-from google.cloud import bigquery
+# db-dtypes does not have type hints nor stubs that mypy uses for type checking.
+# Remove this comment and the ignore pragma upon completing:
+# https://github.com/googleapis/google-cloud-python/issues/17045
+import db_dtypes  # type: ignore[import-untyped]
 import pandas
 import pyarrow.lib
+from google.cloud import bigquery
 
-from pandas_gbq import exceptions
 import pandas_gbq.schema
 import pandas_gbq.schema.bigquery
 import pandas_gbq.schema.pandas_to_bigquery
+from pandas_gbq import exceptions
 
 
 def encode_chunk(dataframe):
@@ -38,8 +41,8 @@ def encode_chunk(dataframe):
     # Convert to a BytesIO buffer so that unicode text is properly handled.
     # See: https://github.com/pydata/pandas-gbq/issues/106
     body = csv_buffer.getvalue()
-    body = body.encode("utf-8")
-    return io.BytesIO(body)
+    body_bytes = body.encode("utf-8")
+    return io.BytesIO(body_bytes)
 
 
 def split_dataframe(dataframe, chunksize=None):
@@ -68,7 +71,7 @@ def cast_dataframe_for_parquet(
     See: https://github.com/googleapis/python-bigquery-pandas/issues/421
     """
 
-    columns = schema.get("fields", [])
+    columns = schema.get("fields", []) if schema is not None else []
 
     # Protect against an explicit None in the dictionary.
     columns = columns if columns is not None else []
@@ -130,7 +133,7 @@ def cast_dataframe_for_csv(
 ) -> pandas.DataFrame:
     """Cast columns to needed dtype when writing CSV files."""
 
-    columns = schema.get("fields", [])
+    columns = schema.get("fields", []) if schema is not None else []
 
     # Protect against an explicit None in the dictionary.
     columns = columns if columns is not None else []
@@ -280,7 +283,9 @@ def load_chunk(chunk, job_config):
         finally:
             chunk_buffer.close()
 
-    return load_csv(dataframe, write_disposition, chunksize, bq_schema, load_chunk)
+    return load_csv(
+        dataframe, write_disposition, chunksize, list(bq_schema), load_chunk
+    )
 
 
 def load_chunks(