Add table_kwargs context manager to make pandas/Dask support dialect

Unlock SQLAlchemy ORM's `__table_args__` on the pandas/Dask `to_sql()`
interface, in order to support CrateDB's special SQL DDL options.

CHANGES.md

@@ -4,6 +4,8 @@
 ## Unreleased
 - Added/reactivated documentation as `sqlalchemy-cratedb`
 - Added re-usable patches and polyfills from application adapters
+- Added ``table_kwargs`` context manager to make pandas/Dask support
+  CrateDB dialect table options.
 
 ## 2024/06/13 0.37.0
 - Added support for CrateDB's [FLOAT_VECTOR] data type and its accompanying

docs/support.md

@@ -54,6 +54,36 @@ df.to_sql(
 )
 ```
 
+
+(support-table-kwargs)=
+## Context Manager `table_kwargs`
+
+:::{rubric} Background
+:::
+CrateDB's special SQL DDL options to support [](inv:crate-reference#partitioned-tables),
+[](inv:crate-reference#ddl-sharding), or [](inv:crate-reference#ddl-replication)
+sometimes can't be configured easily when SQLAlchemy is wrapped into a 3rd-party
+framework like pandas or Dask.
+
+:::{rubric} Utility
+:::
+The `table_kwargs` utility is a context manager that is able to forward CrateDB's
+dialect-specific table creation options to the `sa.Table()` constructor call sites
+at runtime.
+
+:::{rubric} Synopsis
+:::
+Using a context manager incantation like outlined below will render a
+`PARTITIONED BY ("time")` SQL clause, without touching the call site of
+`sa.Table(...)`.
+```python
+from sqlalchemy_cratedb.support import table_kwargs
+
+with table_kwargs(crate_partitioned_by="time"):
+    return df.to_sql(...)
+```
+
+
 (support-autoincrement)=
 ## Synthetic Autoincrement using Timestamps
 

src/sqlalchemy_cratedb/support/__init__.py

@@ -1,4 +1,4 @@
-from sqlalchemy_cratedb.support.pandas import insert_bulk
+from sqlalchemy_cratedb.support.pandas import insert_bulk, table_kwargs
 from sqlalchemy_cratedb.support.polyfill import check_uniqueness_factory, refresh_after_dml, \
     patch_autoincrement_timestamp
 from sqlalchemy_cratedb.support.util import refresh_table, refresh_dirty
@@ -10,4 +10,5 @@
     refresh_after_dml,
     refresh_dirty,
     refresh_table,
+    table_kwargs,
 ]

src/sqlalchemy_cratedb/support/pandas.py

@@ -18,8 +18,13 @@
 # However, if you have executed another commercial license agreement
 # with Crate these terms will supersede the license and you may use the
 # software solely pursuant to the terms of the relevant commercial agreement.
+from contextlib import contextmanager
+from unittest.mock import patch
+
 import logging
 
+import sqlalchemy as sa
+
 
 logger = logging.getLogger(__name__)
 
@@ -60,3 +65,32 @@ def insert_bulk(pd_table, conn, keys, data_iter):
     cursor = conn._dbapi_connection.cursor()
     cursor.execute(sql=sql, bulk_parameters=data)
     cursor.close()
+
+
+@contextmanager
+def table_kwargs(**kwargs):
+    """
+    Context manager for adding SQLAlchemy dialect-specific table options at runtime.
+
+    In certain cases where SQLAlchemy orchestration is implemented within a
+    framework, like at this spot [1] in pandas' `SQLTable._create_table_setup`,
+    it is not easily possible to forward SQLAlchemy dialect options at table
+    creation time.
+
+    In order to augment the SQL DDL statement to make it honor database-specific
+    dialect options, the only way to work around the unfortunate situation is by
+    monkey-patching the call to `sa.Table()` at runtime, relaying additional
+    dialect options through corresponding keyword arguments in their original
+    `<dialect>_<kwarg>` format [2].
+
+    [1] https://github.com/pandas-dev/pandas/blob/v2.2.2/pandas/io/sql.py#L1282-L1285
+    [2] https://docs.sqlalchemy.org/en/20/core/foundation.html#sqlalchemy.sql.base.DialectKWArgs.dialect_kwargs
+    """
+    _init_dist = sa.sql.schema.Table._init
+
+    def _init(self, name, metadata, *args, **kwargs_effective):
+        kwargs_effective.update(kwargs)
+        return _init_dist(self, name, metadata, *args, **kwargs_effective)
+
+    with patch("sqlalchemy.sql.schema.Table._init", _init):
+        yield

tests/test_support_pandas.py

@@ -0,0 +1,67 @@
+import re
+
+import pytest
+import sqlalchemy as sa
+from sqlalchemy.exc import ProgrammingError
+from sqlalchemy.orm import sessionmaker
+
+from pueblo.testing.pandas import makeTimeDataFrame
+
+from sqlalchemy_cratedb.support.pandas import table_kwargs
+
+TABLE_NAME = "foobar"
+INSERT_RECORDS = 42
+
+# Create dataframe, to be used as input data.
+df = makeTimeDataFrame(nper=INSERT_RECORDS, freq="S")
+df["time"] = df.index
+
+
+def test_table_kwargs_partitioned_by(cratedb_service):
+    """
+    Validate adding CrateDB dialect table option `PARTITIONED BY` at runtime.
+    """
+
+    engine = cratedb_service.database.engine
+    session = sessionmaker(bind=engine)()
+
+    # Insert records from pandas dataframe.
+    with table_kwargs(crate_partitioned_by="time"):
+        df.to_sql(
+            TABLE_NAME,
+            con=engine,
+            if_exists="replace",
+            index=False,
+        )
+
+    # Synchronize writes.
+    cratedb_service.database.refresh_table(TABLE_NAME)
+
+    # Inquire table cardinality.
+    metadata = sa.MetaData()
+    query = sa.select([sa.func.count()]).select_from(sa.Table(TABLE_NAME, metadata))
+    results = session.execute(query)
+    count = results.scalar()
+
+    # Compare outcome.
+    assert count == INSERT_RECORDS
+
+    # Validate SQL DDL.
+    ddl = cratedb_service.database.run_sql(f"SHOW CREATE TABLE {TABLE_NAME}")
+    assert 'PARTITIONED BY ("time")' in ddl[0][0]
+
+
+def test_table_kwargs_unknown(cratedb_service):
+    """
+    Validate behaviour when adding an unknown CrateDB dialect table option.
+    """
+    engine = cratedb_service.database.engine
+    with table_kwargs(crate_unknown_option="bazqux"):
+        with pytest.raises(ProgrammingError) as ex:
+            df.to_sql(
+                TABLE_NAME,
+                con=engine,
+                if_exists="replace",
+                index=False,
+            )
+        assert ex.match(re.escape("ColumnUnknownException[Column bazqux unknown]"))