STK Parallel Computing Server API for Python

Welcome to the STK Parallel Computing Server API for Python Documentation!

This documentation explains how developers can parallelize and monitor jobs by taking advantage of the API. The purpose of the API is to make developers more productive by providing efficient use of resources of a network of machines. Deploying Python code, executing jobs in isolated processes, and returning the results back to the client are all handled automatically. Robust error handling, fine grain worker selection, multiple scheduling algorithms, cancellation support, progress reporting, systems monitoring, and more are also supported. By using the API, you can maximize the performance of your code while focusing on the work that your program is designed to accomplish.

This documentation is intended for Python developers. .NET and Java APIs are also available.

You should start at Getting Started to ensure you have a working development environment. From there, you can start learning about the API in the Programmer’s Guide. Use How To and the Library Reference as reference guides when needed. Below is an overview of the sections in this document.