20 Feb 2020
MDAnalysis is now a NumFOCUS Sponsored Project!
Let us explain who MDAnalysis and NumFOCUS are and what being a
sponsored project means:
MDAnalysis is an open source software
project that produces the MDAnalysis Python library for the analysis
of computer simulations of many-body systems at the molecular scale,
spanning use cases from interactions of drugs with proteins to novel
materials. It is widely used in the scientific community and is
written by scientists for scientists. The MDAnalysis Project is
represented by the MDAnalysis Core Developers.
NumFOCUS is an organization that promotes
open practices in research, data, and scientific computing by serving
as a fiscal sponsor for open source projects and organizing
community-driven educational programs. In brief, they provide
financial and logistic infrastructure to many open source
projects that fulfill
important roles in their communities. NumFOCUS is a 501(c)(3) public
charity in the United States and it is able to accept
donations for and on-behalf of projects and to act as a grantee.
NumFOCUS will accept funds on behalf of the MDAnalysis Project and
then make them available to us. By becoming a fiscally sponsored
project, we agreed that all
software produced under the MDAnalysis umbrella is and will be free
Open Source software and that any funds will be spent compliant with
NumFOCUS’ tax-exempt status: what this means in practice is that all
funds will go to further the growth and well-being of the project.
So if you want to donate to MDAnalysis: you can now do this easily
by clicking this button:
Donate Now
More importantly, with NumFOCUS as a partner, MDAnalysis gains a
long-term perspective for stable development that becomes less
dependent on individuals and academic institutions. It allows the
project to obtain its own funding and move in directions that best
benefit its community. For example, it will become easier to organize
workshops, arrange for developers to travel, and to hire developers.
For users and developers, the way the MDAnalysis Project operates will
not change: it remains a friendly and respectful community that
welcomes everyone’s contributions and that is committed to producing
good software that helps us all do interesting science. But together
with NumFOCUS, we will be able to do more than before… stay tuned!
— @MDAnalysis/coredevs
06 Nov 2019
Python 2 reaches end of life on 1 January, 2020, according to PEP
373 and
python/devguide#344. Many
of our dependencies (notably numpy, see their Plan for dropping
Python 2.7
support)
have ceased Python 2.7 support in new releases or will also drop
Python 2.7 in 2020.
We know that science is rolling slowly and surely some scientific
projects will continue with Python 2.7 beyond 2020. MDAnalysis has
been supporting Python 2 and Python 3 now for a while. However, given
how precious developer time is, we also decided to drop support soon
after the official Python 2.7 drop date.
Our plan is to give researchers a stable legacy platform and release
MDAnalysis 1.0.0 with full Python 2.7 support and tests. However,
no major development will continue in 1.0. Issues will only be fixed
and backported on a best-effort basis, simply because there are not
enough developers to do this work.
We will then work towards MDAnalysis 2.0.0, which will
only support Python 3.
Tentative Roadmap
2020 (1st quarter)
- release 1.0.0 in early 2020 (maybe end of 2019…)
- 1.x will be the last version of MDAnalysis that fully supports Python 2.7
- 1.0 will be similar to upcoming 0.21 (i.e., no major annoying
API breaks but clean-up and deprecations)
- development on 1.x will cease with the release of 2.0; we will
consider PRs that backport fixes but we will not officially
support it after the release of 2.0
- finalize API decisions for 2.0.0
2020 (2nd quarter)
- release 2.0.0
- officially drop Python 2.7 support
- support all current Python 3.x releases
- include larger changes/deprecations (API breaks compared to
1.0.0 if necessary, removal of legacy code, etc)
- code modernization (making use of specific Python 3 constructs) will
be ongoing
If you have comments or you see problems with this roadmap then please
get in touch
— @MDAnalysis/coredevs
08 Aug 2019
This year MDAnalysis is hosting Lily Wang (@lilyminium on GitHub) for
the first iteration of Google Season of Docs. She will work
with us over the coming months on a user guide for MDAnalysis,
structured by topic.
Lily Wang: A User Guide for MDAnalysis
MDAnalysis is a library for the analysis of computational (primarily
molecular dynamics, i.e. MD) simulations. Frequently these analyses
are rare, novel, or individual enough that they are not immediately
available as a predefined function within MDAnalysis. MDAnalysis
provides a toolkit for interacting with simulations and constructing
new analyses. Lily will create a high-level user guide structured by
topic. This user guide will describe the building blocks of the data
structures, analysis, topologies, and more. It will be targeted at a
general audience; molecular dynamics users will be able to see the
machine abstraction and technical considerations (e.g. MemoryReader)
under the hood, while developers will be able to gain an understanding
of the scientific background.
Lily Wang is a Ph.D. student at the Australian National University,
Canberra. She aims to improve various aspects of molecular dynamics
simulation over the course of her degree. During GSoD, she hopes to
refine her technical writing skills while contributing to a package
that she very much appreciates. In the tattered remnants of her free
time, she enjoys reading and wandering around mountains. You can
follow her progress on GSoD (and reading) on her
blog.
— @richardjgowers @orbeckst (mentors)