Tishka17/dataclass-factory

Modern way to convert python dataclasses or other objects to and from more common types like dicts or json-like structures

dataclass_factory

dataclass_factory is a modern way to convert dataclasses or other objects to and from more common types like dicts

Important

The new major version is out The library was renamed to adaptix due to extending of the working scope.

This update features:

1. Support for model-to-model conversion.
2. Support for attrs and sqlalchemy (integration with many other libraries is coming).
3. Fully redesigned API helping to follow DRY.
4. Performance improvements of up to two times

Help

See documentation for more details.

TL;DR

Install

pip install dataclass_factory

Use

from dataclasses import dataclass
import dataclass_factory


@dataclass
class Book:
    title: str
    price: int
    author: str = "Unknown author"


data = {
    "title": "Fahrenheit 451",
    "price": 100,
}

factory = dataclass_factory.Factory()
book: Book = factory.load(data, Book)  # Same as Book(title="Fahrenheit 451", price=100)
serialized = factory.dump(book)

Requirements

• python >= 3.6

You can use dataclass_factory with python 3.6 and dataclass library installed from pip.

On python 3.7 it has no external dependencies outside of the Python standard library.

Advantages

• No schemas or configuration needed for simple cases. Just create Factory and call load/dump methods
• Speed. It is up to 10 times faster than marshmallow and dataclasses.asdict (see benchmarks)
• Automatic name style conversion (e.g. snake_case to CamelCase)
• Automatic skipping of "internal use" fields (with leading underscore)
• Enums, typed dicts, tuples and lists are supported out of the box
• Unions and Optionals are supported without need to define them in schema
• Generic dataclasses can be automatically parsed as well
• Cyclic-referenced structures (such as linked-lists or trees) also can be converted
• Validators, custom parser steps are supported.
• Multiple schemas for single type can be provided to support different ways of parsing of the same type