modyml 0.1.0

Modular Configuation Library

ModYml

📦 Project Introduction

ModYml is a lightweight Python configuration management library designed for modular and reusable configurations. With YAML file support, it enables configuration inheritance, parameter overriding, and alias systems, making complex configuration management simple and intuitive.

✨ Key Features

• Modular Configs: Split configurations into reusable modules
• Dynamic Inheritance: Reference other configs using $module.key syntax
• Parameter Overriding: Modify parameters at runtime with $module.key(param=value)
• Alias System: Create short aliases for config items key(alias)
• Namespace Isolation: Automatic namespace management for config items
• Dot-access: Returns EasyDict objects for attribute-style access

⚙️ Installation

pip install modyml

🚀 Quick Start

1. Create module config (modules/optimizers.yml):

adam:
  type: Adam
  params:
    learning_rate(lr): 0.001
    weight_decay(wd): 0.0001

2. Create experiment config (experiments/E01.yml):

training:
  base_optimizer: $optimizers.adam
  custom_optimizer: $optimizers.adam(lr=0.002)
  special_optimizer($optimizers.adam):
    params:
      wd: 0.01

3. Load configuration:

from modyml import load

config = load(
    "experiments/E01.yml",
    module_files=["modules/optimizers.yml"],
    base_dir="configs/"
)

print(config.training.base_optimizer.params.lr)  # Output: 0.001
print(config.training.custom_optimizer.params.lr)  # Output: 0.002
print(config.training.special_optimizer.params.wd)  # Output: 0.01

🧪 Testing

pytest tests/

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Author: Yuyao Huang (Sam) License: MIT