caikit.interfaces.ts.data_model.backends.dfcache
================================================

.. py:module:: caikit.interfaces.ts.data_model.backends.dfcache

.. autoapi-nested-parse::

   Utilities related to manageing spark DataFrame caching



Functions
---------

.. autoapisummary::

   caikit.interfaces.ts.data_model.backends.dfcache.ensure_spark_cached


Module Contents
---------------

.. py:function:: ensure_spark_cached(dataframe: pyspark.sql.DataFrame) -> pyspark.sql.DataFrame

   Will ensure that a given dataframe is cached.
   If dataframe is already cached it does nothing. If it's not
   cached, it will cache it and then uncache the object when
   the ensure_spark_cached object container goes out of scope. Users
   must utilize the with pattern of access.

   Example:
   ```python
       with ensure_spark_cached(df) as _:
           # do dataframey sorts of things on df
           # it's guarenteed to be cached
           # inside this block
       # that's it, you're done.
       # df remains cached if it already was
       # or it's no longer cached if it wasn't
       # before entering the with block above.
   ```