adaptix 3.0.0a5

An extremely flexible and configurable data model conversion library

Adaptix

An extremely flexible and configurable data model conversion library.

📑 Documentation

TL;DR

Install

pip install adaptix

Use

from dataclasses import dataclass

from adaptix import Retort


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


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

retort = Retort()

book = retort.load(data, Book)
assert book == Book(title="Fahrenheit 451", price=100)
assert retort.dump(book) == data

Use cases

• Validation and transformation of received data for your API.
• Config loading/dumping via codec that produces/takes dict.
• Storing JSON in a database and representing it as a model inside the application code.
• Creating API clients that convert a model to JSON sending to the server.
• Persisting entities at cache storage.
• Implementing fast and primitive ORM.

Advantages

• Sane defaults for JSON processing, no configuration is needed for simple cases.
• Separated model definition and rules of conversion that allow preserving SRP and have different representations for one model.
• Speed. It is one of the fastest data parsing and serialization libraries.
• There is no forced model representation, adaptix can adjust to your needs.
• Support dozens of types, including different model kinds: @dataclass, TypedDict, NamedTuple, and attrs
• Working with self-referenced data types (such as linked lists or trees).
• Saving path where an exception is raised (including unexpected errors).
• Easy integration with Sentry, Datadog, and other monitoring systems.
• Machine-readable errors that could be dumped.
• Support for user-defined generic models.
• Automatic name style conversion (e.g. snake_case to camelCase).
• Predicate system that allows to concisely and precisely override some behavior.
• Disabling additional checks to speed up data loading from trusted sources.
• No auto casting by default. The loader does not try to guess value from plenty of input formats.