Hectiq Config

This Python module provides a powerful and flexible configuration management system based on Pydantic models. It is designed to create, manage, and validate configurations with ease.

Features

• Dynamic Configuration Classes: Utilize Pydantic to dynamically create configuration models from dictionaries.
• Validation and Casting: Validate configurations against a defined template and cast configurations to ensure correct types and structures.
• Serialization and Deserialization: Load and save configurations from and to JSON files using orjson for efficient IO operations.
• Nested Configurations: Support for nested configurations, allowing complex, hierarchical settings to be managed cleanly and efficiently.

Dependencies

• pydantic: Used for creating data models and validation.
• orjson: Used for fast JSON serialization and deserialization.
• re: Used for regex operations, particularly in handling aliases in configuration keys.

Installation

pip install hectiq-config

Usage

Creating a Configuration

from hectiq_config import Config

config = Config(a="12345", b=12345, c=[1, 2, 3], d={"x": 1, "y": 2})

Loading and Saving Configurations

config.save('path/to/config.json')
loaded_config = Config.load('path/to/config.json')

Validating Configurations

You can validate a configuration against a template to ensure it has the correct structure and types. A template is a dictionary that defines the expected structure of the configuration.

For example, define a template as follows:

template = {
    "a": str,
    "b": int,
    "c": list,
    "d": {
        "x": int,
        "y": int
    }
}

Then validate the configuration against the template:

is_valid = config.validate(template=template, raise_exception=True)