Nextmv + Python: An end-to-end decision model workflow with DecisionOps

Working in Python? Stay in Python! Develop and deploy your decision model directly from your Python environment. Updates to our SDK make it even easier to operationalize custom decision models safely and quickly.

When you bring a Python decision model to Nextmv, you unlock a standardized DecisionOps workflow that adds efficiency to your modeling process. 

Deploy and scale. With a command from your Python environment, your Python-based decision app is running on managed, remote infrastructure. Scale to higher volume and more use cases without the hassle of provisioning resources.

Create and share experiments. Validate updates to your model with experiments like acceptance tests, scenario tests, and switchback tests. Share results with key stakeholders to improve confidence and buy-in.

Manage models and integrate with Git workflows. Create a system of record for your Python decision model. Create versions to manage model updates, share run logs for faster troubleshooting and development, and incorporate practices like CI/CD for a streamlined, repeatable process. 

The latest updates to the Nextmv Python SDK make it even easier to develop, test, and deploy your Python decision models. Let’s take a look! 

Using the Nextmv Python SDK to accelerate model development

There’s a common pattern that most decision models follow: the model takes input from a source, consumes options (or parameters), and uses some technology (like a solver) to get a solution. That solution is part of an output that is characterized by statistics for further analysis. 

The Nextmv Python SDK formalizes that pattern so you can develop your model in fewer lines of code and get to production faster. Here’s what that looks like in our “Hello World” Python quickstart:

Have a model that you’ve already built? No problem. Here’s a short list of requirements for ensuring your decision model works with Nextmv.

How to deploy your Python model as a decision service

When you push your model to Nextmv, you immediately get API endpoints that you can use to interact with your model as a service. 

Currently, there are two ways to do this: via the Nextmv CLI or the Nextmv Python SDK.

Push the app to Nextmv via the Nextmv CLI

From the app’s directory, use this command using the Nextmv CLI to push the code from your local machine up to the Nextmv platform:

nextmv app push --app-id $APP_ID

You’ll see this as the output:

NEW: Push the app to Nextmv from a Python environment

From your Python environment, use the following to push your model code (from the current directory) up to the Nextmv platform (without the Nextmv CLI).

You’ll see this as the output:

Here’s a quick demonstration. Watch the full demo of getting started with a custom Python model with Nextmv.

Get started with a free account

Sign up for a free account and start a free trial to create a custom app in Python.

Have questions? We’d love to chat. Reach out to us directly or head to our community forum.

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