Metadata-Version: 2.4
Name: eafig
Version: 0.1.1
Summary: Manage your hyperparameters more easily.
Project-URL: Homepage, https://github.com/MugeTong/eafig
Project-URL: Issues, https://github.com/MugeTong/eafig/issues
Author-email: MugeTong <here5320@gmail.com>
License: MIT License
        
        Copyright (c) 2026 MugeTong
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
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        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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        SOFTWARE.
License-File: LICENSE
Requires-Python: >=3.12
Requires-Dist: omegaconf
Requires-Dist: pyyaml
Description-Content-Type: text/markdown

# Eafig

Manage your hyperparameters more easily.

## Installation

```bash
pip install eafig
```

## Quick Start

```python
from eafig import register_config

# Add decorator to your class like `dataclass`
@register_config
class MyConfig:
    learning_rate: float = 0.001
    batch_size: int = 32
    num_epochs: int = 10

# new settings will be applied when you create a new instance
eafig.load_config()
config = MyConfig()
# Use you config as freely
print(config.learning_rate)  # 0.001

# Read all the parameters by `eafig.parse_config()`
eafig.save_config()
```
__Overriding Priority: Command Line > Config File > Assigned > Default__
