Any time that your program needs to interact with other systems it will have to deal with serializing and deserializing data. To prevent duplicate code and provide validation of the data structures that your application is consuming Steven Loria created the Marshmallow library. In this episode he explains how it is built, how to use it for rendering data objects to various serialization formats, and some of the interesting and unique ways that it is incorporated into other projects.
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- Your host as usual is Tobias Macey and today I’m interviewing Steven Loria about Marshmallow, a Python serialization library that is agnostic to your framework and object mapper of choice
- How did you get introduced to Python?
- Can you start by describing what Marshmallow is and the history of the project?
- What are some of the capabilities that make it unique from other similar projects in the Python ecosystem?
- What are some of the main use cases for schematized serialization and deserialization?
- Can you walk through how a user would get started with Marshmallow, particularly for complex or nested schemas?
- Can you describe how Marshmallow is implemented?
- How has that design evolved since you first began working on it?
- How have the changes in the Python language and ecosystem impacted the requirements and use cases for Marshmallow?
- What are some of the most interesting or unexpected ways that you have seen Marshmallow used?
- What have been some of the most interesting, complex, or challenging aspects of building the Marshmallow project and community?
- What are lessons you’ve learned from maintaining marshmallow?
- What have been some of the benefits and drawbacks of keeping Marshmallow agnostic to any frameworks or object mappers?
- What are some of the edge cases that users of Marshmallow should be aware of?
- What are some of the little-known features of Marshmallow that you find most useful?
- What do you have planned for the future of Marshmallow?
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