Files
langgraph/libs/checkpoint-postgres
Elior Nataf LackritzandGitHub 658541c496 chore(checkpoint-postgres,checkpoint-sqlite): enable PLC0415 lint rule (#8540)
Follow-up to review on #8537: turn on ruff's `PLC0415`
(`import-outside-top-level`) so deferred imports in tests stop
accumulating.

Scoped to `checkpoint-postgres` and `checkpoint-sqlite` rather than
repo-wide, because the sweep turns up three different things and only
one of them is a style problem.

### What the rule finds today

```
package                 tests   src    files
checkpoint                13     10      11
checkpoint-conformance     0     10       4
checkpoint-postgres        6      0       2
checkpoint-sqlite          9      0       3
langgraph                130     23      32
prebuilt                  14      3       7
cli                        9     14      10
sdk-py                   189     23      38
                        ────────────────────
                         370     83     107
```

453 violations across 107 files, and ruff has no autofix for this rule.

### Three categories, not one

**Style — hoist.** `checkpoint-sqlite/tests/test_store.py` deferred
`math`, `random`, `time`, `Counter` and `defaultdict` inside methods for
no reason.

**Deliberate — keep, annotate.**
`checkpoint-postgres/tests/test_async.py` defers behind
`pytest.importorskip("langgraph.channels.delta")` because langgraph core
is *not* a test dependency of that package. Hoisting would break the
skip. Those get `# noqa: PLC0415` and a comment.

**Redundant guard — hoist.**
`checkpoint-sqlite/tests/test_conformance_delta.py` deferred imports
only to get past its own `importorskip`. Imports move up; the
`aiosqlite` guard stays, since that dependency genuinely can be absent.

The second category is why I did not enable this everywhere in one go.
Most of the 83 source-level violations look like the same pattern —
optional-dependency handling and circular-import avoidance in
`jsonplus.py`, `embed.py`, `encrypted.py` and friends. Blanket-enabling
would mean `# noqa` on a lot of correct code, and each one wants an
owner's eye rather than a mechanical pass.

These two packages are clean to enforce today because both have **zero**
source-level violations.

### Suggested rollout for the rest

Either extend package by package as owners confirm which deferrals are
intentional, or enable everywhere at once with `per-file-ignores`
grandfathering the current 107 files so new code is blocked immediately
and the debt burns down. Happy to do either — the second is a smaller
diff but leaves a long ignore list.

### Verified

`checkpoint-sqlite` 118 passed, `checkpoint-postgres` 264 passed on PG
15 and 16, `make lint` clean in both.

One overlap worth flagging:
`checkpoint-sqlite/tests/test_conformance_delta.py` is also touched by
#8537. The change is identical in both, so it should merge cleanly
either way.
2026-08-05 21:23:28 -04:00
..

LangGraph Checkpoint Postgres

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To help you ship LangGraph apps to production faster, check out LangSmith. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications.

Quick Install

uv add langgraph-checkpoint-postgres

🤔 What is this?

This library provides a Postgres implementation of LangGraph's checkpoint saver. Use it when you want LangGraph state persistence backed by Postgres for durable, long-running workflows and agents.

By default, langgraph-checkpoint-postgres installs psycopg (Psycopg 3) without any extras. You can choose a specific installation that best suits your needs in the Psycopg installation docs, for example psycopg[binary].

📖 Documentation

For full documentation, see the API reference. For conceptual guides on persistence and memory, see the LangGraph Docs.

Security

Important

Set LANGGRAPH_STRICT_MSGPACK=true or pass an explicit allowed_msgpack_modules list when creating your checkpointer. This restricts checkpoint deserialization to known-safe types, preventing code execution if the database is compromised. See the langgraph-checkpoint README for details.

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.

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:

# ❌ 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
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

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)]

📕 Releases & Versioning

See our Releases and Versioning policies.

💁 Contributing

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.

For detailed information on how to contribute, see the Contributing Guide.