Скачать или смотреть Creating Different Versions of the Same Pydantic BaseModel

Learn how to efficiently create different versions of Pydantic BaseModels without code duplication using model inheritance and the create_model function. Perfect for Python developers working with data validation!
---
This video is based on the question https://stackoverflow.com/q/76290128/ asked by the user 'Roland Deschain' ( https://stackoverflow.com/u/7745011/ ) and on the answer https://stackoverflow.com/a/76290389/ provided by the user 'Roland Deschain' ( https://stackoverflow.com/u/7745011/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Is it possible to make different versions of the same pydantic basemodel?

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Creating Different Versions of Pydantic BaseModels: A Practical Guide

When working with Python’s Pydantic library, especially while handling data validation and settings management, developers often face a common challenge: How can we create different versions of the same BaseModel without repeating code? This question is particularly relevant for complex applications where model fields might change based on different validation constraints or metadata requirements. In this post, we will explore an effective solution to this problem, allowing you to reuse your models while keeping your code clean and maintainable.

The Challenge

Imagine you have two Pydantic models, ParametersA and ParametersB, defined as follows:

[[See Video to Reveal this Text or Code Snippet]]

[[See Video to Reveal this Text or Code Snippet]]

These models are then used in another BaseModel called FullModelX:

[[See Video to Reveal this Text or Code Snippet]]

The question arises: How can we create another model, FullModelY, that uses the same ParametersA and ParametersB but with different validation limits and metadata? For instance, maybe in FullModelX, param_b defaults to False, while in FullModelY it should default to True.

The Traditional Approach: Code Duplication

For many developers, the initial instinct might be to duplicate ParametersA and ParametersB every time different validation constraints are needed. However, this approach is not only cumbersome but also leads to a lot of redundant code, making it harder to maintain and update.

A Better Solution: Inheritance and Model Creation

Inheritance

While inheritance is a common strategy, it may result in having to rewrite entire classes if most of the model fields change. However, there's an innovative way to extend the functionality of Pydantic models without duplicating all the fields—in this case, we will make use of create_model.

Using create_model

With Pydantic's create_model function, we can create new models that are based on existing models while only making necessary changes. Here's how you can do it for FullModelY:

[[See Video to Reveal this Text or Code Snippet]]

In this example, we create a new model, ParametersAVariant, that extends ParametersA, and then we adjust param_b's default value.

Advantages of This Method

Reduced Redundancy: You avoid writing duplicate code, allowing you to maintain one source of truth for your model.

Flexibility: It's easier to create models with slight variations without losing track of the original model's structure.

Ease of Maintenance: If you need to change the base model later, you only have to do it in one place.

Conclusion

By leveraging create_model from Pydantic, you can efficiently create different versions of BaseModels without the hassle of code duplication. This not only keeps your codebase clean but also enhances maintainability. Whether you're building simple applications or complex data processing pipelines, using this approach can save you time and reduce errors, leaving you free to focus on developing your application further.

Feel free to adopt this technique within your own projects and watch how it streamlines your code for better efficiency and readability!