Request model for creating a new batch. Batches group bucket objects for processing into collections. When you submit a batch, all objects in the batch are processed through the collections associated with the bucket. - object_ids: REQUIRED. List of object IDs that exist in the bucket - Collections are auto-discovered from the bucket at batch creation time Batch Processing Flow: 1. Create batch with object_ids → Batch created in DRAFT status, collections auto-discovered 2. Submit batch → Processing begins for discovered collections 3. Collections with collection sources (tier 2/3) are processed automatically 4. Processing happens in topological order based on collection dependencies Examples: Single object batch: {"object_ids": ["obj_123"]} Multiple objects batch: {"object_ids": ["obj_123", "obj_456", "obj_789"]}
| Name | Type | Description | Notes |
|---|---|---|---|
| object_ids | List[str] | REQUIRED. List of object IDs to include in the batch. Objects must exist in the bucket where the batch is created. Minimum 1 object, no maximum limit. All objects will be processed when the batch is submitted. Collections with collection sources (decomposition trees) are processed automatically via DAG resolution - no need to create separate batches. |
from mixpeek.models.create_batch_request import CreateBatchRequest
# TODO update the JSON string below
json = "{}"
# create an instance of CreateBatchRequest from a JSON string
create_batch_request_instance = CreateBatchRequest.from_json(json)
# print the JSON string representation of the object
print(CreateBatchRequest.to_json())
# convert the object into a dict
create_batch_request_dict = create_batch_request_instance.to_dict()
# create an instance of CreateBatchRequest from a dict
create_batch_request_from_dict = CreateBatchRequest.from_dict(create_batch_request_dict)