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Author: kosiew

docs/source/user-guide/dataframe/index.rst

@@ -228,33 +228,6 @@ Core Classes
     * :py:meth:`~datafusion.SessionContext.from_pandas` - Create from Pandas DataFrame
     * :py:meth:`~datafusion.SessionContext.from_arrow` - Create from Arrow data
 
-    ``SessionContext`` can automatically resolve SQL table names that match
-    in-scope Python data objects. When automatic lookup is enabled, a query
-    such as ``ctx.sql("SELECT * FROM pdf")`` will register a pandas or
-    PyArrow object named ``pdf`` without calling
-    :py:meth:`~datafusion.SessionContext.from_pandas` or
-    :py:meth:`~datafusion.SessionContext.from_arrow` explicitly. This requires
-    the corresponding library (``pandas`` for pandas objects, ``pyarrow`` for
-    Arrow objects) to be installed.
-
-    .. code-block:: python
-
-        import pandas as pd
-        from datafusion import SessionContext
-
-        ctx = SessionContext(auto_register_python_objects=True)
-        pdf = pd.DataFrame({"value": [1, 2, 3]})
-
-        df = ctx.sql("SELECT SUM(value) AS total FROM pdf")
-        print(df.to_pandas())  # automatically registers `pdf`
-
-    Automatic lookup is disabled by default. Enable it by passing
-    ``auto_register_python_objects=True`` when constructing the session or by
-    configuring :py:class:`~datafusion.SessionConfig` with
-    :py:meth:`~datafusion.SessionConfig.with_python_table_lookup`. Use
-    :py:meth:`~datafusion.SessionContext.set_python_table_lookup` to toggle the
-    behaviour at runtime.
-
     See: :py:class:`datafusion.SessionContext`
 
 Expression Classes

docs/source/user-guide/sql.rst

@@ -36,29 +36,4 @@ DataFusion also offers a SQL API, read the full reference `here <https://arrow.a
     df = ctx.sql('SELECT "Attack"+"Defense", "Attack"-"Defense" FROM pokemon')
 
     # collect and convert to pandas DataFrame
-    df.to_pandas()
-
-Automatic variable registration
--------------------------------
-
-You can opt-in to DataFusion automatically registering Arrow-compatible Python
-objects that appear in SQL queries. This removes the need to call
-``register_*`` helpers explicitly when working with in-memory data structures.
-
-.. code-block:: python
-
-    import pyarrow as pa
-    from datafusion import SessionContext
-
-    ctx = SessionContext(auto_register_python_objects=True)
-
-    orders = pa.Table.from_pydict({"item": ["apple", "pear"], "qty": [5, 2]})
-
-    result = ctx.sql("SELECT item, qty FROM orders WHERE qty > 2")
-    print(result.to_pandas())
-
-The feature inspects the call stack for variables whose names match missing
-tables and registers them if they expose Arrow data (including pandas and
-Polars DataFrames). Existing contexts can enable or disable the behavior at
-runtime through :py:meth:`SessionContext.set_python_table_lookup` or by passing
-``auto_register_python_objects`` when constructing the session.
+    df.to_pandas()