Quick Start
Get up and running with the SPX simulation stack.
This page helps you get up and running with the SPX simulation stack—the SPX Server (REST API for modeling & simulation) and the SPX-Python client (lightweight Python wrapper for that API). You’ll learn how to install the essentials, bring the server up locally with Docker, connect from Python, and perform the core operations you’ll use in day-to-day development and CI.
By the end, you will be able to:
Start the SPX Server locally via Docker and verify it’s healthy.
Initialize the SPX-Python client and talk to the server.
Create models and instances, read/write attributes, and run a basic simulation step.
Reuse the same flow in unit tests and CI pipelines.
What’s inside this page:
Installation Guide — prerequisites, environment variables (e.g., SPX_PRODUCT_KEY), server image & Docker Compose, client installation.
Installer and Packs — build ready-to-run bundles from spx-examples (models + services + optional UI).
Quick Start Guide — minimal, copy-paste recipes to connect to the server, do basic CRUD on models/instances, tweak attributes, run prepare()/run(), and wire these steps into your unit tests and CI.
Who is this for?
Developers, QA, and CI engineers who want a clear, repeatable path to stand up SPX locally and automate it in tests.
Prerequisites (at a glance):
Docker & Docker Compose (to run the server)
Python
>=3.9(tested in CI on3.9–3.12)A valid SPX_PRODUCT_KEY set as an environment variable
Network access to pull the SPX server image
Tip: Everything shown here is designed to work the same way locally and in CI, so the commands you practice on your laptop carry straight over to pipelines.
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