Custodian is a simple, robust and flexible just-in-time (JIT) job management framework written in Python. Using custodian, you can create wrappers that perform error checking, job management and error recovery. It has a simple plugin framework that allows you to develop specific job management workflows for different applications.
Error recovery is an important aspect of many high-throughput projects that generate data on a large scale. When you are running on the order of hundreds of thousands of jobs, even an error-rate of 1% would mean thousands of errored jobs that would be impossible to deal with on a case-by-case basis.
The specific use case for custodian is for long running jobs, with potentially random errors. For example, there may be a script that takes several days to run on a server, with a 1% chance of some IO error causing the job to fail. Using custodian, one can develop a mechanism to gracefully recover from the error, and restart the job with modified parameters if necessary.
The current version of Custodian also comes with several sub-packages for error handling for Vienna Ab Initio Simulation Package (VASP), NwChem, QChem, FEFF, Lobster and CP2K calculations.
The version at the Python Package Index (PyPI) is always the latest stable release that will be hopefully, be relatively bug-free. Install as follows:
pip install custodianSome plugins (e.g., VASP management) require additional setup (please see pymatgen docs).
The bleeding edge developmental version is at the custodian's Github repo. The developmental version is likely to be more buggy, but may contain new features. The Github version include test files as well for complete unit testing. After cloning the source, you can type
pip install -e .to install the package in editable mode.
Custodian supports Python 3.8+. There are no other required dependencies. However, if you wish to use many of the built-in error handlers and Jobs for VASP, NWChem, QChem, etc., you will likely need pymatgen to be installed as well.
Please refer to the official custodian docs for details on how to use custodian.
If you use custodian in your research, especially the VASP component, please consider citing the following work:
Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier,
Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent Chevrier, Kristin A.
Persson, Gerbrand Ceder. *Python Materials Genomics (pymatgen) : A Robust,
Open-Source Python Library for Materials Analysis.* Computational
Materials Science, 2013, 68, 314-319. doi:10.1016/j.commatsci.2012.10.028Custodian is released under the MIT License. The terms of the license are as follows:
The MIT License (MIT)
Copyright (c) 2011-2012 MIT & LBNL
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