The Software Gardening Almanack

The Software Gardening Almanack is an open-source handbook of applied guidance and tools for sustainable software development and maintenance. The Almanack is available both as a handbook and a Python package.

Please see our pavilion section of the book for presentations and other related materials for the Almanack.

Handbook

• Online (HTML): https://software-gardening.github.io/almanack/
• Offline (PDF): software-gardening-almanack.pdf

Package

Install

You can install the Almanack with the following:

# install from pypi
pip install almanack

# install directly from source
pip install git+https://github.com/software-gardening/almanack.git

Once installed, the Almanack can be used to analyze repositories for sustainable development practices. Output from the Almanack includes metrics which are defined through metrics.yml as a Python dictionary (JSON-compatible) record structure.

Command-line Interface (CLI)

You can use the Almanack package as a command-line interface (CLI):

# generate a table of metrics based on a repository
almanack table path/to/repository

# perform linting-style checks on a repository
almanack check path/to/repository

Python API

You can also use the Almanack through a Python API:

For example:

import almanack
import pandas as pd

# gather the almanack table using the almanack repo as a reference
almanack_table = almanack.metrics.data.get_table("path/to/repository")

# show the almanack table as a Pandas DataFrame
pd.DataFrame(almanack_table)

Example notebook

Please see this example notebook which demonstrates using the Almanack package.

Contributing

Please see our CONTRIBUTING.md document for more information on how to contribute to this project.

Acknowledgements

This work was supported by the Better Scientific Software Fellowship Program, a collaborative effort of the U.S. Department of Energy (DOE), Office of Advanced Scientific Research via ANL under Contract DE-AC02-06CH11357 and the National Nuclear Security Administration Advanced Simulation and Computing Program via LLNL under Contract DE-AC52-07NA27344; and by the National Science Foundation (NSF) via SHI under Grant No. 2327079.