Python - Dataclasses

 

Dataclass

Python dataclasses are a new feature introduced in Python 3.7 that allows users to define classes that are primarily used to store data. They are similar to namedtuples, but with some additional features that make them more powerful and flexible.

NamedTuple

typing.NamedTuple was introduced in Python 3.6 in the typing module and supercede the collections.namedtuple. They allow users to define a class with named fields. NamedTuples are immutable.They are useful for creating simple, immutable data objects.

Pydantic

Pydantic is a third-party library that provides data validation and settings management using Python type annotations. It is built on top of Python's type hints, which makes it easy to define the structure of your data. Pydantic is designed to be fast and to consume minimal resources, making it suitable for use in large projects.

Comparison

Python dataclasses are more powerful than namedtuples because they allow for mutable objects, inheritance, and default values. They are also easier to use than Pydantic because they do not require any additional library installation or configuration.

Pydantic, on the other hand, provides more advanced data validation and settings management features. It is also more flexible than dataclasses because it allows for custom validation and serialization logic.

In summary, if you need simple, immutable data objects, namedtuples are a good option. If you need more advanced validation and settings management features, Pydantic is a good choice. If you need mutable objects, inheritance, and default values, Python dataclasses are the way to go.