Daeploy is now open source!

We have exciting product news to share! As the title says, we decided to make Daeploy open source.

This means that from version 1.3.0 onwards, the software will be open sourced under the GNU General Public License v. 3.0, and the source code will be available on GitHub for anyone to view and modify it. For more information about what the open source license entails and what will be required from projects that use Daeploy, please click here.

Daeploy was launched with the mission to let data scientists be data scientists and support them in creating APIs and deploying microservices with Python. Our goal was to make the productification stage of Machine Learning projects easier, so open sourcing the software was a natural step to make it even more accessible, community-oriented, and simpler to get started with it.

What’s changing?

Nothing! The functionalities of Daeploy remain unchanged and you don’t need to take any action. If you have been issued a product license in the past, the only difference is that when updating to the 1.3.0 version, you will no longer be prompted to enter your license key. But you can keep it as a badge of honor and a memento from being one of the first users of Daeploy. 😊

In case the project you are developing with Daeploy is incompatible with the terms of the General Public License, we will continue offering business licenses. Please contact us at info@daeploy.com for support on that matter.

Speaking of support…

We will discontinue our Slack channel. You will be able to report issues and make pull requests directly in GitHub. We’re also always reachable through e-mail, Twitter, and Linkedin.

We are very happy to make Daeploy open source and can’t wait to see all the cool things the community will do with it!

Share the news and Happy Daeploying!

Originally published at https://daeploy.com on December 13, 2021.




Daeploy helps you to create APIs out of your existing #python code and deploy it as web services. Get started now!

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Daeploy helps you to create APIs out of your existing #python code and deploy it as web services. Get started now!

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