langgraph-dynamodb-checkpoint 0.2.6.4

DynamoDB checkpoint saver implementation for LangGraph - Single table, auto create with delete handling

LangGraph DynamoDB Checkpoint Saver

A DynamoDB-based checkpoint saver implementation for LangGraph that allows storing and managing checkpoints in Amazon DynamoDB.

• Supports both Sync and async methods
• Single table Implementation
• Supports delete basis given thread_id
• Supports logging - Multiple Log levels
• Supports Class and Context Manager initialization

Installation

If installing this version, then delete the underlying table as well. Existing data is not compatible with version >= 1.5

bash pip install langgraph_dynamodb_checkpoint

Usage

DynamoDBSaver Constructor

• table_name (str): Name of the DynamoDB table to use for storing checkpoints
• max_read_request_units (int, optional): Maximum read request units for the DynamoDB table. Defaults to 10
• max_write_request_units (int, optional): Maximum write request units for the DynamoDB table. Defaults to 10
• ttl_seconds (int, optional): TTL value set for all checkpoint items.

Import

from langgraph_dynamodb_checkpoint import DynamoDBSaver

🔍 Enable Logging

langgraph_dynamodb uses Python's standard logging module and emits logs under the logger name langgraph_dynamodb.

You can control logging verbosity using the LANGGRAPH_DYNAMODB_LOG_LEVEL environment variable:

export LANGGRAPH_DYNAMODB_LOG_LEVEL=DEBUG

Available log levels:

• CRITICAL
• ERROR
• WARNING
• INFO (default)
• DEBUG
• NOTSET

Example:

LANGGRAPH_DYNAMODB_LOG_LEVEL=DEBUG 

---

⚙️ Programmatic Logging Configuration (Optional)

You can also configure logging directly in your code using configure_logging:

from langgraph_dynamodb_checkpoint import configure_logging
import logging

configure_logging(
    level=logging.DEBUG,
    log_format="%(levelname)s: %(message)s"
)

Redirect logs to a file:

with open("log.txt", "a") as logfile:
    configure_logging(level=logging.INFO, stream=logfile)

This gives you full control over the log destination, level, and format.

Initialize the saver with a table name

saver = DynamoDBSaver(
    table_name="your-dynamodb-table-name",
    max_read_request_units=10,  # Optional, default is 100
    max_write_request_units=10  # Optional, default is 100
    ttl_seconds=86400
)

Table has ttl enabled with attribute name set to ttl

Alternative Initialization Using Context Manager

from langgraph_dynamodb_checkpoint import DynamoDBSaver

with DynamoDBSaver.from_conn_info(table_name="your-dynamodb-table-name") as saver:
    # Use the saver here
    pass

Supports Delete

Checkpointer supports delete basis given thread_id

config = {"configurable": {"thread_id": "900"}}
memory.delete(config)

Table Structure

The saver automatically creates a DynamoDB table if it doesn't exist, with the following structure:

• Partition Key (PK): String type, used for thread_id
• Sort Key (SK): String type, used for checkpoint_id

AWS Configuration

Ensure you have proper AWS credentials configured either through:

• Environment variables (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY)
• AWS credentials file (~/.aws/credentials)
• IAM role when running on AWS services

The AWS credentials should have permissions to:

• Create DynamoDB tables (if table doesn't exist)
• Read and write to DynamoDB tables

Notes

• The saver automatically creates the DynamoDB table if it doesn't exist
• Uses on-demand billing mode for DynamoDB
• Implements all methods required by the LangGraph BaseCheckpointSaver interface