toppyy commented on code in PR #1427:
URL:
https://github.com/apache/datafusion-python/pull/1427#discussion_r2961459725
##########
docs/source/user-guide/data-sources.rst:
##########
@@ -224,25 +224,33 @@ A common technique for organizing tables is using a three
level hierarchical app
supports this form of organizing using the
:py:class:`~datafusion.catalog.Catalog`,
:py:class:`~datafusion.catalog.Schema`, and
:py:class:`~datafusion.catalog.Table`. By default,
a :py:class:`~datafusion.context.SessionContext` comes with a single Catalog
and a single Schema
-with the names ``datafusion`` and ``default``, respectively.
+with the names ``datafusion`` and ``public``, respectively.
The default implementation uses an in-memory approach to the catalog and
schema. We have support
-for adding additional in-memory catalogs and schemas. This can be done like in
the following
+for adding additional in-memory catalogs and schemas. You can access tables
registered in a schema
+either through the Dataframe API or vial sql commands. This can be done like
in the following
example:
.. code-block:: python
from datafusion.catalog import Catalog, Schema
+ from datafusion import SessionContext
+
+ ctx = SessionContext()
- my_catalog = Catalog.memory_catalog()
- my_schema = Schema.memory_schema()
+ my_catalog = Catalog.memory_catalog()
+ my_schema = Schema.memory_schema()
my_catalog.register_schema("my_schema_name", my_schema)
+ ctx.register_catalog_provider("my_catalog_name", my_catalog)
+
+ df = ctx.read_csv("pokemon.csv")
Review Comment:
great idea! thanks.
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