TST/DOC #10846 Test and document use of SQLAlchemy expressions in read_sql()

doc/source/io.rst

@@ -3918,6 +3918,42 @@ connecting to.
 For more information see the examples the SQLAlchemy `documentation <http://docs.sqlalchemy.org/en/rel_0_9/core/engines.html>`__
 
 
+Advanced SQLAlchemy queries
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+You can use SQLAlchemy constructs to describe your query.
+
+Use :func:`sqlalchemy.text` to specify query parameters in a backend-neutral way
+
+.. ipython:: python
+
+   import sqlalchemy as sa
+   pd.read_sql(sa.text('SELECT * FROM data where Col_1=:col1'), engine, params={'col1': 'X'})
+
+If you have an SQLAlchemy description of your database you can express where conditions using SQLAlchemy expressions
+
+.. ipython:: python
+
+   metadata = sa.MetaData()
+   data_table = sa.Table('data', metadata,
+       sa.Column('index', sa.Integer),
+       sa.Column('Date', sa.DateTime),
+       sa.Column('Col_1', sa.String),
+       sa.Column('Col_2', sa.Float),
+       sa.Column('Col_3', sa.Boolean),
+   )
+
+   pd.read_sql(sa.select([data_table]).where(data_table.c.Col_3 == True), engine)
+
+You can combine SQLAlchemy expressions with parameters passed to :func:`read_sql` using :func:`sqlalchemy.bindparam`
+
+.. ipython:: python
+
+    import datetime as dt
+    expr = sa.select([data_table]).where(data_table.c.Date > sa.bindparam('date'))
+    pd.read_sql(expr, engine, params={'date': dt.datetime(2010, 10, 18)})
+
+
 Sqlite fallback
 '''''''''''''''
 

pandas/io/sql.py

@@ -364,9 +364,9 @@ def read_sql_query(sql, con, index_col=None, coerce_float=True, params=None,
 
     Parameters
     ----------
-    sql : string
-        SQL query to be executed
-    con : SQLAlchemy connectable(engine/connection) or database string URI
+    sql : string SQL query or SQLAlchemy Selectable (select or text object)
+        to be executed.
+    con : SQLAlchemy connectable(engine/connection) or database string URI 
         or sqlite3 DBAPI2 connection
         Using SQLAlchemy makes it possible to use any DB supported by that
         library.
@@ -423,8 +423,8 @@ def read_sql(sql, con, index_col=None, coerce_float=True, params=None,
 
     Parameters
     ----------
-    sql : string
-        SQL query to be executed or database table name.
+    sql : string SQL query or SQLAlchemy Selectable (select or text object)
+        to be executed, or database table name.
     con : SQLAlchemy connectable(engine/connection) or database string URI
         or DBAPI2 connection (fallback mode)
         Using SQLAlchemy makes it possible to use any DB supported by that

pandas/io/tests/test_sql.py

@@ -951,6 +951,35 @@ def test_to_sql_read_sql_with_database_uri(self):
         tm.assert_frame_equal(test_frame1, test_frame3)
         tm.assert_frame_equal(test_frame1, test_frame4)
 
+    def _make_iris_table_metadata(self):
+        sa = sqlalchemy
+        metadata = sa.MetaData()
+        iris = sa.Table('iris', metadata,
+            sa.Column('SepalLength', sa.REAL),
+            sa.Column('SepalWidth', sa.REAL),
+            sa.Column('PetalLength', sa.REAL),
+            sa.Column('PetalWidth', sa.REAL),
+            sa.Column('Name', sa.TEXT)
+        )
+
+        return iris
+
+    def test_query_by_text_obj(self):
+        # WIP : GH10846
+        name_text = sqlalchemy.text('select * from iris where name=:name')
+        iris_df = sql.read_sql(name_text, self.conn, params={'name': 'Iris-versicolor'})
+        all_names = set(iris_df['Name'])
+        self.assertEqual(all_names, set(['Iris-versicolor']))
+
+    def test_query_by_select_obj(self):
+        # WIP : GH10846
+        iris = self._make_iris_table_metadata()
+
+        name_select = sqlalchemy.select([iris]).where(iris.c.Name == sqlalchemy.bindparam('name'))
+        iris_df = sql.read_sql(name_select, self.conn, params={'name': 'Iris-setosa'})
+        all_names = set(iris_df['Name'])
+        self.assertEqual(all_names, set(['Iris-setosa']))
+
 
 class _EngineToConnMixin(object):
     """