Parallel Requests

Execute multiple GET, POST, or PUT requests in parallel using a thread pool. Use for bulk operations: fetching many resources, batch inserts, or batch updates.

Methods

Method	Use case
`parallel_get(endpoints, ...)`	Fetch multiple endpoints (different URLs) in parallel
`parallel_post(endpoint, payloads, ...)`	Same endpoint, multiple POST bodies
`parallel_put(endpoint, payloads, ...)`	Same endpoint, multiple PUT bodies
`parallel_delete(endpoint, payloads, ...)`	Same endpoint, multiple DELETE bodies (e.g. batch delete)

All methods accept max_workers (default 8) and error_handling (ErrorHandling.FAIL_FAST, COLLECT, or LOG_ONLY). See ErrorHandling in the models reference.

Async equivalents aparallel_get, aparallel_post, aparallel_put, and aparallel_delete are async iterators that yield (index, result, error) tuples in order. See API Reference: Async parallel methods and Async operations.

parallel_get

Fetch multiple resources in parallel:

from intapp_rest_client import RestClient, ErrorHandling
 
with RestClient(base_url="https://api.example.com", api_key="key") as client:
    endpoints = [
        "/api/v4/objects/1",
        "/api/v4/objects/2",
        "/api/v4/objects/3",
    ]
    # Default: raise on first error, return list of results
    results = client.parallel_get(endpoints, max_workers=5)
 
    # Collect errors and get partial results
    results, errors = client.parallel_get(
        endpoints,
        error_handling=ErrorHandling.COLLECT
    )
    if errors:
        print(f"{len(errors)} requests failed")

parallel_post

Same endpoint, multiple POST bodies (e.g. batch insert):

from intapp_rest_client import RestClient, ErrorHandling
 
with RestClient(base_url="https://api.example.com", api_key="key") as client:
    payloads = [
        {"name": "Item 1", "value": 100},
        {"name": "Item 2", "value": 200},
        {"name": "Item 3", "value": 300},
    ]
    results = client.parallel_post("/api/v4/items", payloads, max_workers=5)
 
    # With error collection
    results, errors = client.parallel_post(
        "/api/v4/items",
        payloads,
        error_handling=ErrorHandling.COLLECT
    )

parallel_put

Same endpoint, multiple PUT bodies (e.g. batch update):

from intapp_rest_client import RestClient
 
with RestClient(base_url="https://api.example.com", api_key="key") as client:
    payloads = [
        {"id": 1, "status": "active"},
        {"id": 2, "status": "inactive"},
    ]
    results = client.parallel_put("/api/v4/items", payloads)

parallel_delete

Same endpoint, multiple DELETE bodies (e.g. batch delete by id):

from intapp_rest_client import RestClient
 
with RestClient(base_url="https://api.example.com", api_key="key") as client:
    payloads = [{"id": 1}, {"id": 2}, {"id": 3}]
    results = client.parallel_delete("/api/v4/items", payloads, max_workers=5)

Error Handling

Value	Behavior	Return
FAIL_FAST (default)	Raise on first error	List of results (until failure)
COLLECT	Continue on error, collect failures	`(results, errors)`
LOG_ONLY	Same as COLLECT; also log each error	`(results, errors)`

Each entry in errors is a dict with endpoint or payload_index, error, error_type, and optionally response_body.