We're back from a much-needed and relaxing summer break, and we're ready to kick off the fall with a new release of Flama. Yup, you read that right, we're releasing Flama 1.7 ?
This release is a big one, with new features that will make your life much easier when developing and productionalising your ML APIs. The main highlights of this release are:
Support for Python 3.12: Flama now supports Python 3.12, so you can take advantage of all the new features and improvements that come with the latest version of Python.
Support for Domain Driven Design (DDD): Flama now comes with built-in support for domain-driven design with a new module named ddd. DDD is a powerful approach that helps you manage the complexity of real-world projects, particularly when dealing with intricate business logic, and complex data models. By focusing on the business domain, DDD ensures that your codebase remains aligned with business needs, making it easier to maintain, extend, and scale over time. The new module ddd comes with the essential building blocks for you to hit the ground running at full speed. For a deeper understanding on DDD, you can check out the book Architecture Patterns with Python by Harry Percival and Bob Gregory.
Support for Authentication: In this release, we've added support for authentication in Flama. You can now secure your API endpoints with token-based authentication over headers or cookies. This will help you protect your data and ensure that only authorised users can access your API, making it more secure and reliable in a few simple steps.
To better showcase these new features, we'll be publishing a couple of additional posts with highly detailed examples that will guide you through the process of using DDD and authentication with Flama.
Stay tuned for more updates and happy coding! ?
References
- Flama documentation
- Flama GitHub repository
- Flama PyPI package
About the authors
- Vortico: We're specialised in software development to help businesses enhance and expand their AI and technology capabilities.
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