• Stars
    star
    127
  • Rank 282,790 (Top 6 %)
  • Language
    Python
  • License
    MIT License
  • Created almost 12 years ago
  • Updated 7 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

A simple, robust and flexible just-in-time job management framework in Python.

Custodian logo GitHub license Linting Testing Downloads codecov

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.

Getting custodian

Stable version

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 custodian

Some plugins (e.g., VASP management) require additional setup (please see pymatgen docs).

Developmental version

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

python setup.py install

or to install the package in developmental mode::

python setup.py develop

Requirements

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.

Usage

Please refer to the official custodian docs for details on how to use custodian.

How to cite 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.2012.10.028

License

Custodian is released under the MIT License. The terms of the license are as follows:

The MIT License (MIT)
Copyright (c) 2011-2012 MIT & LBNL

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 to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell 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
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.

More Repositories

1

pymatgen

Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Python
1,359
star
2

fireworks

The Fireworks Workflow Management Repo.
Python
322
star
3

atomate2

atomate2 is a library of computational materials science workflows
Python
160
star
4

crystaltoolkit

Crystal Toolkit is a framework for building web apps for materials science and is currently powering the new Materials Project website.
Python
150
star
5

mapidoc

Public repo for Materials API documentation
Jupyter Notebook
140
star
6

workshop

The Materials Project Workshop Curriculum
Jupyter Notebook
111
star
7

api

New API client for the Materials Project
Python
102
star
8

matbench

Matbench: Benchmarks for materials science property prediction
Python
95
star
9

reaction-network

Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (formerly at Berkeley Lab).
Python
86
star
10

jobflow

jobflow is a library for writing computational workflows.
Python
83
star
11

mpmorph

MPmorph is a collection of tools to run and analyze ab-initio molecular dynamics (AIMD) calculations run with VASP, and is currently under development. It relies heavily on tools developed by the Materials Project (pymatgen, custodian, fireworks) and atomate.
Python
63
star
12

emmet

Be a master builder of databases of material properties. Avoid the Kragle.
Python
52
star
13

pymatgen-db

Pymatgen-db provides an addon to the Python Materials Genomics (pymatgen) library (https://pypi.python.org/pypi/pymatgen) that allows the creation of Materials Project-style databases for management of materials data.
Python
48
star
14

maggma

MongoDB aggregation machine
Python
38
star
15

MPContribs

Platform for materials scientists to contribute and disseminate their materials data through Materials Project
Jupyter Notebook
34
star
16

pyrho

Python
33
star
17

pymatgen-analysis-defects

Defect analysis modules for pymatgen
Python
28
star
18

MPWorks

merges pymatgen, custodian, and FireWorks into a custom workflow for Materials Project
Python
24
star
19

dash-mp-components

Plotly Dash components developed by the Materials Project
Python
22
star
20

workshop-2017

Assets for the 2017 Materials Project workshop
Jupyter Notebook
18
star
21

foundation

Ruby
17
star
22

mp-react-components

A suite of React components for the Materials Project, developed for use in Crystal Toolkit and the Materials Project public website.
TypeScript
17
star
23

docs

Materials Project Documentation
14
star
24

pymatgen-analysis-alloys

pymatgen-analysis-alloys is an add-on package for pymatgen intended to contain useful classes for describing alloy systems and analyzing data relevant to these systems.
Python
12
star
25

workshop-2016

Assets for the Materials Project workshop in Aug 2016
HTML
12
star
26

rubicon

Workflow for Electrolyte Genome Project.
Python
8
star
27

pymatgen-io-validation

Comprehensive input/output validator. Made with the purpose of ensuring VASP calculations are compatible with Materials Project data, with possible future expansion to cover other DFT codes.
Python
8
star
28

mongogrant

grant username and password credentials for roles on mongo databases via email verification
Python
7
star
29

webtzite

A prototypal structure for serving materials data
Python
6
star
30

public-docs

The latest documentation for the Materials Project.
6
star
31

gbml

Gradient Boosting Machine-Locfit: A GBM framework using local regresssion via Locfit.
C
6
star
32

pymatgen-addon-template

A template for writing add-on namespace packages for pymatgen
Python
5
star
33

build-a-battery

interactive battery demo built on meteor
CSS
4
star
34

.github

3
star
35

MPCite

Continuous and High-Throughput Allocation of Digital Object Identifiers for Materials Data in the Materials Project
Jupyter Notebook
3
star
36

MPContribsUsers

Contributor Modules to enable their data submissions via MPContribs
Python
2
star
37

mp-jupyter-docker

Docker build for Materials Project Jupyter container
Dockerfile
2
star
38

binder

A ready-to-use environment for trying the Materials Project software stack based on the Binder (https://mybinder.org) service.
Jupyter Notebook
2
star
39

mp-jupyterhub

Jupyterhub for spinning up materials project notebook environments
Python
2
star
40

MPenv

create a virtual environment for running FireWorks within Materials Project
Python
2
star
41

www-issues

Public issue tracker for www.materialsproject.org
1
star
42

mp_docker

docker image for materials_django
Dockerfile
1
star
43

status

Status page for Materials Project website and services
1
star