fleche.wrapper
==============

.. py:module:: fleche.wrapper


Classes
-------

.. autoapisummary::

   fleche.wrapper.Ignored
   fleche.wrapper.Required


Functions
---------

.. autoapisummary::

   fleche.wrapper.fleche


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

.. py:class:: Ignored

   Type wrapper to mark a function argument as ignored for caching.

   Can be used as a type hint: ``arg: fleche.Ignored`` or ``arg: fleche.Ignored[int]``.


   .. py:method:: __class_getitem__(item)
      :classmethod:



.. py:class:: Required

   Type wrapper to mark a function argument as required for caching.

   Arguments marked as required must be explicitly provided by the caller as keyword
   arguments (i.e.  not via their default value) for the result to be cached.
   This is useful for arguments like random seeds or iteration counts, where
   using the default value might lead to non-deterministic or otherwise
   undesirable caching behavior.

   This is mainly useful when wrapping third-party functions where you do not control
   the default arguments.

   Can be used as a type hint: ``arg: fleche.Required`` or ``arg: fleche.Required[int]``.


   .. py:method:: __class_getitem__(item)
      :classmethod:



.. py:function:: fleche(_func=None, *, version: int | None = None, meta: tuple[fleche.metadata.MetaData, Ellipsis] = (), hash_version: bool = True, hash_module: bool = True, hash_code: bool = False, require: None | str | list[str] | tuple[str] = None, ignore: None | str | list[str] | tuple[str] = None, isolate: bool = False)

   Cache decorator for functions.

   The decorated function is enhanced with helper methods:
   - .call(*args, **kwargs): Get the :clas:`.Call` object.
   - .digest(*args, **kwargs): Get the cache key.
   - .load(*args, **kwargs): Load result from cache.
   - .contains(*args, **kwargs): Check if result is in cache.
   - .rerun(*args, **kwargs): Forces reevaluation recursively.
   The original function is available via .__wrapped__.