Overview
Process multiple documents concurrently to significantly reduce total processing time compared to sequential requests.These examples require the Python or TypeScript client library. Before running a script, set your API key and install the library and any required dependencies.
Python
Use AsyncLandingAIADE for async document processing
TypeScript
Use concurrent parsing with Promise.all() or p-limit
Python
UseAsyncLandingAIADE when you need to process many lightweight documents (such as invoices, receipts, or forms) efficiently. This async client allows you to send multiple parse requests concurrently using Python’s asyncio, which significantly reduces total processing time compared to sequential requests.
The async approach lets you send multiple requests in parallel. While one document is being processed, another request can be sent. The API server handles the actual document processing in the background.
To avoid exceeding the pages per hour limits and receiving 429 errors, use a client-side rate limiter like aiolimiter to control concurrency.
TypeScript
Use concurrent parsing when you need to process many lightweight documents (such as invoices, receipts, or forms) efficiently. The TypeScript library’s methods are already asynchronous, allowing you to send multiple parse requests concurrently using JavaScript’sPromise.all() or Promise.allSettled(). This significantly reduces total processing time compared to sequential requests.
The concurrent approach lets you send multiple requests in parallel. While one document is being processed, another request can be sent. The API server handles the actual document processing in the background.
To avoid exceeding the pages per hour limits and receiving 429 errors, use a concurrency control library like p-limit to limit the number of simultaneous requests.
Basic Concurrent Parsing
Concurrent Parsing with Rate Limiting
To control concurrency and avoid rate limits, use thep-limit library:

