Python project config template for deep learning

config.py

# run this with bash: `EPOCH=20 python config.py`

import os


class Config:
    def __init__(self):
        self.EMBEDDING_DIM = 256
        self.EPOCH = 10
        self.SAVE_PATH = os.path.join(os.path.curdir, 'checkpoint')
        self.FILTER_SIZE = [2, 3, 4]

    def update(self, **kwargs):
        for key in kwargs:
            if not hasattr(self, key):
                print('[✗] Ignore unknown attribute "{}"'.format(key))
            else:
                setattr(self, key, kwargs[key])
                print('[✓] Attribute "{}" has been updated to "{}"'.format(
                    key, kwargs[key]))

    def update_from_env(self):
        for key in os.environ:
            if hasattr(self, key):
                setattr(self, key, os.environ[key])
                print('[✓] Attribute "{}" has been updated to "{}"'.format(
                    key, os.environ[key]))

    def __repr__(self):
        display = '{:=^80}\n'.format(self.__class__.__name__)
        for k, v in vars(self).items():
            if not k.startswith('__'):
                display += '| {:<30} {}\n'.format(k, v)

        return display + '=' * 80


if __name__ == '__main__':
    config = Config()
    config.update_from_env()
    config.update(EMBEDDING_DIM=128, FILTER_SIZE=[1, 2, 3, 4], MODEL='CNN')
    print(config)

Variables updated from env or cmd are str, be careful.

Variables updated from env or cmd are str, be careful.

Or use the code below replace line No.25 to handle some type problems. (not suitable for list, dict)

# ... 
            if hasattr(self, key):
                _type = type(getattr(self, key))
                setattr(self, key, _type(os.environ[key]))
# ...