| Name | langgraph-checkpoint-postgres JSON |
| Version |
2.0.22
JSON |
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| home_page | None |
| Summary | Library with a Postgres implementation of LangGraph checkpoint saver. |
| upload_time | 2025-07-10 22:45:24 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
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| VCS |
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| bugtrack_url |
|
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No requirements were recorded.
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# 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)]
```
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"description": "# LangGraph Checkpoint Postgres\n\nImplementation of LangGraph CheckpointSaver that uses Postgres.\n\n## Dependencies\n\nBy 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]`).\n\n## Usage\n\n> [!IMPORTANT]\n> When using Postgres checkpointers for the first time, make sure to call `.setup()` method on them to create required tables. See example below.\n\n> [!IMPORTANT]\n> 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/).\n>\n> **Why these parameters are required:**\n> - `autocommit=True`: Required for the `.setup()` method to properly commit the checkpoint tables to the database. Without this, table creation may not be persisted.\n> - `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.\n>\n> **Example of incorrect usage:**\n> ```python\n> # \u274c This will fail with TypeError during checkpointer operations\n> with psycopg.connect(DB_URI) as conn: # Missing autocommit=True and row_factory=dict_row\n> checkpointer = PostgresSaver(conn)\n> checkpointer.setup() # May not persist tables properly\n> # Any operation that reads from database will fail with:\n> # TypeError: tuple indices must be integers or slices, not str\n> ```\n\n```python\nfrom langgraph.checkpoint.postgres import PostgresSaver\n\nwrite_config = {\"configurable\": {\"thread_id\": \"1\", \"checkpoint_ns\": \"\"}}\nread_config = {\"configurable\": {\"thread_id\": \"1\"}}\n\nDB_URI = \"postgres://postgres:postgres@localhost:5432/postgres?sslmode=disable\"\nwith PostgresSaver.from_conn_string(DB_URI) as checkpointer:\n # call .setup() the first time you're using the checkpointer\n checkpointer.setup()\n checkpoint = {\n \"v\": 4,\n \"ts\": \"2024-07-31T20:14:19.804150+00:00\",\n \"id\": \"1ef4f797-8335-6428-8001-8a1503f9b875\",\n \"channel_values\": {\n \"my_key\": \"meow\",\n \"node\": \"node\"\n },\n \"channel_versions\": {\n \"__start__\": 2,\n \"my_key\": 3,\n \"start:node\": 3,\n \"node\": 3\n },\n \"versions_seen\": {\n \"__input__\": {},\n \"__start__\": {\n \"__start__\": 1\n },\n \"node\": {\n \"start:node\": 2\n }\n },\n }\n\n # store checkpoint\n checkpointer.put(write_config, checkpoint, {}, {})\n\n # load checkpoint\n checkpointer.get(read_config)\n\n # list checkpoints\n list(checkpointer.list(read_config))\n```\n\n### Async\n\n```python\nfrom langgraph.checkpoint.postgres.aio import AsyncPostgresSaver\n\nasync with AsyncPostgresSaver.from_conn_string(DB_URI) as checkpointer:\n checkpoint = {\n \"v\": 4,\n \"ts\": \"2024-07-31T20:14:19.804150+00:00\",\n \"id\": \"1ef4f797-8335-6428-8001-8a1503f9b875\",\n \"channel_values\": {\n \"my_key\": \"meow\",\n \"node\": \"node\"\n },\n \"channel_versions\": {\n \"__start__\": 2,\n \"my_key\": 3,\n \"start:node\": 3,\n \"node\": 3\n },\n \"versions_seen\": {\n \"__input__\": {},\n \"__start__\": {\n \"__start__\": 1\n },\n \"node\": {\n \"start:node\": 2\n }\n },\n }\n\n # store checkpoint\n await checkpointer.aput(write_config, checkpoint, {}, {})\n\n # load checkpoint\n await checkpointer.aget(read_config)\n\n # list checkpoints\n [c async for c in checkpointer.alist(read_config)]\n```\n",
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