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LangGraph Checkpoint Postgres (pg8000)

PyPI Python Versions License: MIT

A PostgreSQL checkpointer implementation for LangGraph using the pg8000 database driver.

Why is this library needed?

The official langgraph-checkpoint-postgres library requires the psycopg database driver. However, certain deployment environments, particularly those using Google Cloud SQL for PostgreSQL with the cloud-sql-python-connector, do not currently support psycopg.

This library serves as a stopgap solution until the Google Cloud SQL Python Connector adds full psycopg support (expected early 2026). It provides the same checkpoint functionality as the official library but uses the pg8000 driver, which is supported by the Cloud SQL Connector.

Installation

# pip
pip install langgraph-checkpoint-postgres-pg8000
# uv
uv add langgraph-checkpoint-postgres-pg8000
# Poetry
poetry add langgraph-checkpoint-postgres-pg8000

Usage

Basic Setup

from langgraph_checkpoint_postgres_pg8000 import Pg8000Saver
from sqlalchemy import create_engine

# Create SQLAlchemy engine
engine = create_engine("postgresql+pg8000://user:password@host/database")

# Initialize checkpointer
checkpointer = Pg8000Saver(engine=engine)

# Use with LangGraph
graph = graph_builder.compile(checkpointer=checkpointer)

Note: Consider using sqlmodel-gcp-postgres to create an SQLAlchemy/SQLModel compatible database engine that may be used with Google Cloud SQL deployments!

Important Notes

Implementation Details: This library is nearly 100% based on the official langgraph-checkpoint-postgres implementation, with adaptations for pg8000 instead of psycopg. The core logic and SQL queries remain the same.

Migration Path: Once the Google Cloud SQL Python Connector adds full psycopg support (expected early 2026), you should migrate to the official langgraph-checkpoint-postgres library for long-term support and updates.

Related Projects

License

MIT License - see LICENSE file for details.

Metadata

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