docs: add compatibility note for serialization methods in caching policies

Author: tanbro

README.md

@@ -768,6 +768,22 @@ def get_book(pool: ConnectionPool, book_id: int):
 
 - Compatibility with other [decorator][]s is not guaranteed.
 
+- The built-in policies in `redis_func_cache.policies` use [`pickle`][] to serialize function arguments, then calculate the cache key by hashing the serialized data with `md5`. [`pickle`][] is chosen because only the hash bytes are stored in Redis, not the serialized data itself, so this is safe. However, [`pickle`][] causes incompatibility between different Python versions. If your application needs to be compatible across Python versions, you should define your own hash policy using a version-compatible serialization method, for example:
+
+    ```python
+    from redis_func_cache import RedisFuncCache
+    from redis_func_cache.policies.abstract import BaseSinglePolicy
+    from redis_func_cache.mixins.hash import JsonMd5HashMixin
+    from redis_func_cache.mixins.scripts import LfuScriptsMixin
+
+    class MyLfuPolicy(LfuScriptsMixin, JsonMd5HashMixin, BaseSinglePolicy):
+        __key__ = "my-lfu"
+
+    my_cache = RedisFuncCache(__name__, policy=MyLfuPolicy, client=redis_client_factory)
+    ```
+
+    As shown above, unlike [`pickle`][], [json][] can be used across different Python versions.
+
 - The cache eviction policies are mainly based on [Redis][] sorted set's score ordering. For most policies, the score is a positive integer. Its maximum value is `2^32-1` in [Redis][], which limits the number of times of eviction replacement. [Redis][] will return an `overflow` error when the score overflows.
 
 - High concurrency or long-running decorated functions may result in unexpected cache misses and increased I/O operations. This can occur because the result value might not be saved quickly enough before the next call can hit the cache again.