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serialize/deserialize pandas with pickle fallback (#5057)

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Sydney Runkle
2025-06-12 15:14:00 -04:00
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parent 116b5d1cac
commit 3ad061f0d7
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docs/docs/concepts/persistence.md
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@@ -473,6 +473,23 @@ If the checkpointer is used with asynchronous graph execution (i.e. executing th
When checkpointers save the graph state, they need to serialize the channel values in the state. This is done using serializer objects.
`langgraph_checkpoint` defines [protocol][langgraph.checkpoint.serde.base.SerializerProtocol] for implementing serializers provides a default implementation ([JsonPlusSerializer][langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer]) that handles a wide variety of types, including LangChain and LangGraph primitives, datetimes, enums and more.
#### Serialization with `pickle`
The default serializer, [`JsonPlusSerializer`][langgraph.checkpoint.serde.jsonplus.JsonPlusSerializer], uses ormsgpack and JSON under the hood, which is not suitable for all types of objects.
If you want to fallback to pickle for objects not currently supported by our msgpack encoder (such as Pandas dataframes),
you can use the `pickle_fallback` argument of the `JsonPlusSerializer`:
```python
from langgraph.checkpoint.memory import MemorySaver
from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
# ... Define the graph ...
graph.compile(
checkpointer=MemorySaver(serde=JsonPlusSerializer(pickle_fallback=True))
)
```
#### Encryption
Checkpointers can optionally encrypt all persisted state. To enable this, pass an instance of [`EncryptedSerializer`][langgraph.checkpoint.serde.encrypted.EncryptedSerializer] to the `serde` argument of any `BaseCheckpointSaver` implementation. The easiest way to create an encrypted serializer is via [`from_pycryptodome_aes`][langgraph.checkpoint.serde.encrypted.EncryptedSerializer.from_pycryptodome_aes], which reads the AES key from the `LANGGRAPH_AES_KEY` environment variable (or accepts a `key` argument):