bobbie

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What is bobbie?

bobbie provides a lightweight, easy-to-use, flexible, and extensible Settings class for loading and storing configuration settings for a Python project.

Why use bobbie?

There are numerous options for storing project configuration settings in Python. So, what makes bobbie different?

• Flexible: a Settings instance is easily built from a dict, Python module, or file.
• Lightweight: an efficient codebase ensures a very small memory footprint.
• Intuitive: a create class method constructs Settings (from any data source).
• Convenient: unlike configparser, automatic data and type validation is performed when Settings is created.

The comparison table below shows how bobbie compares to the other major options that store configuration options for Python projects.

Getting started

Installation

To install bobbie, use pip:

pip install bobbie

Create a Settings instance

bobbie supports several ways to create a Settings instance. However, you can opt to always use the create class method for any data source.

From dict

import bobbie

configuration = {
  'general': {
    'verbose': False,
    'seed': 43,
    'parallelize': False},
  'files': {
    'source_format': 'csv',
    'file_encoding': 'windows-1252',
    'float_format': '%.4f',
    'export_results': True}}
# You may use the general `create` method.
settings = bobbie.Settings.create(configuration)
# Or, just send a `dict` to `Settings` itself.
settings = bobbie.Settings(configuration)

From file

import bobbie

# You may use the general `create` method.
settings = bobbie.Settings.create('settings_file.yaml')
# Or, the `from_file` method.
settings = bobbie.Settings.from_file('settings_file.yaml')
# Or, the `from_yaml` method. They all do the same thing.
settings = bobbie.Settings.from_yaml('settings_file.yaml')

If the file is a Python module, it must contain a variable named settings (unless you change the global setting for the variable name).

Contributing

Contributors are always welcome. Feel free to grab an issue to work on or make a suggested improvement. If you wish to contribute, please read the Contribution Guide and Code of Conduct.

Similar projects

There are a lot of great packages for storing project settings. The table below shows the features of the leading libraries.

Feature Comparison of Python Configuration Libraries

Library	Typing	Secrets	dict	env	ini	json	py	toml	yaml
bobbie	✅		✅	✅	✅	✅	✅	✅	✅
configParser					✅
dynaconf	✅	✅		✅	✅	✅		✅	✅
Parser-it	✅			✅	✅	✅		✅	✅
python-decouple	✅	✅		✅	✅
pyconfig		✅
pydantic-settings	✅	✅

As you can see, bobbie lacks a method for storing passwords, encryption keys, and other secrets. That is largely because it is focused on internal Python projects and the goal of keeping its resource usage as low as possible. So, if you need secrets stored in your project settings, there are several good options listed above that you should explore.

Acknowledgments

I would like to thank the University of Kansas School of Law for tolerating and supporting this law professor's coding efforts, an endeavor which is well outside the typical scholarly activities in the discipline.

License

Use of this repository is authorized under the Apache Software License 2.0.