Release 2.10.0 of MDAnalysis
26 Oct 2025We are happy to release version 2.10.0 of MDAnalysis!
This is a minor release of the MDAnalysis library, which means that it contains enhancements, bug fixes, deprecations, and other backwards-compatible changes.
Supported environments
This release supports NumPy 2.0+ and offers backwards compatibility through to NumPy 1.26.0.
Supported Python versions: 3.11, 3.12, 3.13, 3.14. Note: not all optional dependencies currently work with Python 3.14.
Supported Operating Systems:
Upgrading to MDAnalysis version 2.10.0
To update with mamba (or conda) from the conda-forge channel run
mamba update -c conda-forge mdanalysis
To update from PyPi with pip run
python -m pip install --upgrade MDAnalysis
For more help with installation see the installation instructions in the User Guide. Make sure you are using a Python version compatible with MDAnalysis before upgrading (Python >= 3.11).
Notable changes
For a full list of changes, bug fixes and deprecations see the CHANGELOG.
Enhancements:
- Support for setting custom
dtwhen reading/writing XTC and TRR trajectories (PR #4908) - New parallelization support for the following analyses:
- Enable the selection of distance library backend in RDF analyses (PR #5038)
- Improve the speed of the GROMOS11 reader (PR #5080)
- Improvements to the RDKit inferring code (PR #4305)
- Support for position and velocity reading from TPR files (PR #4873)
- Support for non-linear time averaged MSD (PR #5066)
- Support for interactive MD (IMDv3) stream reading using the IMDReader and the imdclient package (PR #4923)
- Performance improvements to
InterRDF_s(PR #5073)
Changes:
- The output precision for LAMMPS DATA files is now set to 10 decimals (PR #5053)
- Support for Python 3.10 was removed in line with SPEC 0 (PR #5121)
- Bond order and charges inferring code from the RDKit converter has been moved to
a new
RDKitInferringmodule (PR #4305)
Author statistics
This release was the work of 25 contributors, 16 of which are new contributors.
Our new contributors are:
- @namiroues
- @lexi-x
- @BHM-Bob
- @yuyuan871111
- @jpkrowe
- @TRY-ER
- @Abdulrahman-PROG
- @pbuslaev
- @tulga-rdn
- @Gareth-elliott
- @schuhmc
- @gitsirsha
- @Pradyumn-cloud
- @amruthesht
- @gitzhangch
- @raulloiscuns
Acknowledgements
MDAnalysis thanks NumFOCUS for its continued support as our fiscal sponsor and the Chan Zuckerberg Initiative for supporting MDAnalysis under EOSS4 and EOSS5 awards.
— @IAlibay on behalf of the MDAnalysis Team