I am trying to use pydantic frozen dataclasses to create stable and validated data structures. In the process, it seemed like my code would benefit from using inheritance because a lot of methods were shared between multiple objects.

Suppose I have a collection of strings defined as a StrEnum:

I’m working on an API where I’m using Pydantic for schema validation and SQLAlchemy as my ORM for interacting with a PostgreSQL database.

I’m learning pydantic and I wish to understand the interaction between Python classes and their properties with the models of pyndatic. In particular I wish to define some instance variables that are calculated lazily at runtime after the model is created and/or everytime the model or a particular field is updated. Here a small play snipper where I tried some things but it fails.
I understood from debugging that first the model is created from the dict, then the validator is run and it needs the field age to be defined already and it is not, so it crashes. Should I define a property for the age field? Also I’m interested in the historical interactions between properties and computed_field w.r.t. when designing entities from stratch. Should I mix them or use only one solution?

I need default values to be cleared in a Pydantic model. I cannot recreate the object because, in my use case, it has references that need to be preserved. Could you please show me the best practices for this?

In the example code below, I tried to combine abstract base classes with Pydantic. I wanted to write this code because I had an existing type Ticker which has two implementations. It can either be represented as a string or an integer value.

I am using Pydantic extensively in my repository.

I tried to serialize a pydantic model with an attribute that can be of class of multiple subclasses of a base class. However with a naive implementation the subclasses are serialized to the baseclass.

project_root │ .env │ └───backend │ └───migrations │ │ │ └───src │ │ config.py │ │ main.py │ │ … │ └───frontend │ … I have an .env file that is in the root folder, and a config.py file that is in project/backend/src I create a Settings class that inherits from pydantic BaseSettings. Inside I […]

If a model has more than one failing @model_validator("after"), then only one (the first?) is raised.