# LangGraph Checkpoint Postgres Implementation of LangGraph CheckpointSaver that uses Postgres. ## Dependencies By default `langgraph-checkpoint-postgres` installs `psycopg` (Psycopg 3) without any extras. However, you can choose a specific installation that best suits your needs [here](https://www.psycopg.org/psycopg3/docs/basic/install.html) (for example, `psycopg[binary]`). ## Usage > [!IMPORTANT] > When using Postgres checkpointers for the first time, make sure to call `.setup()` method on them to create required tables. See example below. > [!IMPORTANT] > When manually creating Postgres connections and passing them to `PostgresSaver` or `AsyncPostgresSaver`, make sure to include `autocommit=True` and `row_factory=dict_row` (`from psycopg.rows import dict_row`). See a full example in this [how-to guide](https://langchain-ai.github.io/langgraph/how-tos/persistence_postgres/). > > **Why these parameters are required:** > - `autocommit=True`: Required for the `.setup()` method to properly commit the checkpoint tables to the database. Without this, table creation may not be persisted. > - `row_factory=dict_row`: Required because the PostgresSaver implementation accesses database rows using dictionary-style syntax (e.g., `row["column_name"]`). The default `tuple_row` factory returns tuples that only support index-based access (e.g., `row[0]`), which will cause `TypeError` exceptions when the checkpointer tries to access columns by name. > > **Example of incorrect usage:** > ```python > # ❌ This will fail with TypeError during checkpointer operations > with psycopg.connect(DB_URI) as conn: # Missing autocommit=True and row_factory=dict_row > checkpointer = PostgresSaver(conn) > checkpointer.setup() # May not persist tables properly > # Any operation that reads from database will fail with: > # TypeError: tuple indices must be integers or slices, not str > ``` ```python from langgraph.checkpoint.postgres import PostgresSaver write_config = {"configurable": {"thread_id": "1", "checkpoint_ns": ""}} read_config = {"configurable": {"thread_id": "1"}} DB_URI = "postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable" with PostgresSaver.from_conn_string(DB_URI) as checkpointer: # call .setup() the first time you're using the checkpointer checkpointer.setup() checkpoint = { "v": 4, "ts": "2024-07-31T20:14:19.804150+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "channel_values": { "my_key": "meow", "node": "node" }, "channel_versions": { "__start__": 2, "my_key": 3, "start:node": 3, "node": 3 }, "versions_seen": { "__input__": {}, "__start__": { "__start__": 1 }, "node": { "start:node": 2 } }, } # store checkpoint checkpointer.put(write_config, checkpoint, {}, {}) # load checkpoint checkpointer.get(read_config) # list checkpoints list(checkpointer.list(read_config)) ``` ### Async ```python from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver async with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer: checkpoint = { "v": 4, "ts": "2024-07-31T20:14:19.804150+00:00", "id": "1ef4f797-8335-6428-8001-8a1503f9b875", "channel_values": { "my_key": "meow", "node": "node" }, "channel_versions": { "__start__": 2, "my_key": 3, "start:node": 3, "node": 3 }, "versions_seen": { "__input__": {}, "__start__": { "__start__": 1 }, "node": { "start:node": 2 } }, } # store checkpoint await checkpointer.aput(write_config, checkpoint, {}, {}) # load checkpoint await checkpointer.aget(read_config) # list checkpoints [c async for c in checkpointer.alist(read_config)] ```