Mastering File Handling in Python: A Comprehensive Guide Part 7

Data interchange formats

Modern software architecture tends to split an application into several components. Whether you embrace the service-oriented architecture paradigm, or you push it even further into the microservices realm, these components will have to exchange data. But even if you are coding a monolithic application whose codebase is contained in one project, chances are that you still have to exchange data with APIs, other programs, or simply handle the data flow between the frontend and backend parts of your website, which very likely won’t speak the same language.

Choosing the right format in which to exchange information is crucial. A language-specific format has the advantage that the language itself is very likely to provide you with all the tools to make serialization and deserialization a breeze. However, you will lose the ability to talk to other components that have been written in different versions of the same language, or in different languages altogether. Regardless of what the future looks like, going with a language-specific format should only be done if it is the only possible choice for the given situation.

According to Wikipedia (https://en.wikipedia.org/wiki/Serialization):

In computing, serialization is the process of translating a data structure or object state into a format that can be stored (for example, in a file or memory data buffer) or transmitted (for example, over a computer network) and reconstructed later (possibly in a different computer environment).

A much better approach is to choose a format that is language-agnostic, and can be spoken by all (or at least most) languages. Fabrizio used to lead a team of programmers from England, Poland, South Africa, Spain, Greece, India, and Italy, to mention just a few. They all spoke English, so regardless of their native tongue, they could all understand each other (well… mostly!).

In the software world, some popular formats have become the de facto standard for data interchange. The most famous ones probably are XML, YAML, and JSON. The Python standard library features the xml and json modules, and, on PyPI (https://pypi.org/), you can find a few different packages to work with YAML.

In the Python environment, JSON is perhaps the most commonly used one. It wins over the other two because of being part of the standard library, and for its simplicity. If you have ever worked with XML, you know what a nightmare it can be.

Moreover, when working with a database like PostgreSQL, the ability to use native JSON fields makes a compelling case for adopting JSON in the application as well.

That’s it for Today. See you tomorrow.

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