Batch Operations¶

Read and write items in bulk with automatic chunking and exponential backoff retry.

Batch Save¶

Save up to thousands of items — auto-chunked into groups of 25.

users = [
    User(user_id=f"u{i}", name=f"User {i}", email=f"user{i}@example.com", age=20 + i)
    for i in range(50)
]
User.batch_save(users)

Batch Get¶

Fetch multiple items by key — auto-chunked into groups of 100.

keys = [{"user_id": f"u{i}"} for i in range(50)]
users = User.batch_get(keys)

Order not guaranteed

DynamoDB does not guarantee order in batch_get responses. Sort results after fetching if needed:

sorted_users = sorted(users, key=lambda u: u.user_id)

Batch Delete¶

Delete multiple items by key — auto-chunked into groups of 25.

User.batch_delete([{"user_id": f"u{i}"} for i in range(50)])

Batch Writer (Context Manager)¶

Mix saves and deletes in a single batch context. Auto-flushes every 25 items and on exit.

with User.batch_writer() as batch:
    # Add new users
    for i in range(100, 110):
        batch.save(
            User(user_id=f"u{i}", name=f"User {i}", email=f"user{i}@example.com", age=25)
        )

    # Delete some existing users
    for i in range(25, 30):
        batch.delete(user_id=f"u{i}")

Automatic Retry¶

All batch operations include exponential backoff retry for unprocessed items (up to 5 retries). This handles DynamoDB throttling transparently — no manual retry logic needed.

Chunk Sizes¶

Operation	Chunk Size	DynamoDB Limit
`batch_save()`	25	25 items per BatchWriteItem
`batch_get()`	100	100 keys per BatchGetItem
`batch_delete()`	25	25 items per BatchWriteItem
`batch_writer()`	25	Auto-flushes at 25 items