pydantic_serdes 1.0.4

A Python package that standardizes data serialization and deserialization from/to pydantic models.

pydantic-serdes

pydantic-serdes is a Pydantic-based tool designed to act as a conduit between serialized data and Python objects. It not only facilitates the transformation of complex serialized data into Python objects, but also ensures stringent data validation. Think of it as the wizard that transports your data from the realm of serialization into the world of Python, and vice-versa, all the while maintaining the integrity and structure of your data.

DISCLAMER: Please note that this package was previously named serial_bus until version 0.2.0. To improve communication and disambiguation, it has been renamed to pydantic-serdes.

Install

pip:

pip install pydantic-serdes

poetry:

poetry add pydantic-serdes

Features

• Pydantic Integration: Converting serialized data into Python objects is the oldest trick in the book, but pydantic-serdes elevates this process by directly converting the data into Pydantic models (and vice-versa), which brings the added advantage of robust data validation. The models used in this process are defined by classes that inherit from either the PydanticSerdesBaseModel or PydanticSerdesRenderableModel. This not only provides flexibility in setting up behaviors for your data, but also ensures data integrity through Pydantic's validation mechanisms.

• Built-in Support for Multiple Formats: Currently, it supports loading serialized data from JSON, YAML, TOML and INI. While future support for other formats is planned, if you need to cover additional formats, or even provide your own parsing business logic, this can be easily achieved by extending pydantic-serdes basic coverage with your own loader and/or dumper functions. Speaking of which...

• Extensibility: The code was thought to allow for ease of extensibility. For more information and examples, refer to the documentation below.

Quick Start

• Usage examples:
  • Example 1: Instantiating models from serialized data
  • Example 2: Data Relationship & Model Rendering
  • Example 3: Converting data between supported formats
• Configuration & Extensibility
• pydantic-serdes Base Models
• The GLOBAL_DATA_STORE
• Loaders
• Dumpers
• Contributing