Update README (#23)

Author: prashantmital

bindings/python/README.rst

@@ -5,4 +5,49 @@ PyMongoArrow
        between MongoDB and Apache Arrow. See
        `GitHub <https://github.com/mongodb-labs/mongo-arrow/tree/main/bindings/python>`_
        for the latest source.
+:Documentation: Available at `mongo-arrow.readthedocs.io <https://mongo-arrow.readthedocs.io/en/latest/>`_.
 :Author: Prashant Mital
+
+**PyMongoArrow** is a companion library to PyMongo that contains tools
+for loading MongoDB query result sets as Apache Arrow tables, Pandas
+DataFrames or NumPy arrays.
+
+.. code-block:: python
+
+  >>> from pymongoarrow.monkey import patch_all
+  >>> patch_all()
+  >>> from pymongoarrow.api import Schema
+  >>> schema = Schema({'_id': int, 'qty': float})
+  >>> from pymongo import MongoClient
+  >>> client = MongoClient()
+  >>> client.db.data.insert_many([{'_id': 1, 'qty': 25.4}, {'_id': 2, 'qty': 16.9}, {'_id': 3, 'qty': 2.3}])
+  >>> data_frame = client.db.test.find_pandas_all({}, schema=schema)
+  >>> data_frame
+     _id   qty
+  0    1  25.4
+  1    2  16.9
+  2    3   2.3
+  >>> arrow_table = client.db.test.find_arrow_all({}, schema=schema)
+  >>> arrow_table
+  pyarrow.Table
+  _id: int64
+  qty: double
+  >>> ndarrays = client.db.test.find_numpy_all({}, schema=schema)
+  >>> ndarrays
+  {'_id': array([1, 2, 3]), 'qty': array([25.4, 16.9,  2.3])}
+
+**PyMongoArrow** is the recommended way to
+materialize MongoDB query result sets as contiguous-in-memory, typed arrays
+suited for in-memory analytical processing applications.
+
+Installing PyMongoArrow
+=======================
+PyMongoArrow is available on PyPI:::
+
+  $ python -m pip install pymongoarrow
+
+PyMongoArrow wheels are available for macOS and Linux on x86_64 architectures.
+
+Documentation
+=============
+Full documentation is available on `Read the Docs <https://mongo-arrow.readthedocs.io/en/latest/>`_.