mdapy : Molecular Dynamics Analysis with Python
Overview
The mdapy provides a comprehensive suite of powerful, flexible, and straightforward tools for analyzing atomic trajectories generated from Molecular Dynamics (MD) simulations.
Resources
Homepage: https://github.com/mushroomfire/mdapy
Documentation: https://mdapy.readthedocs.io/
Issue Tracker: https://github.com/mushroomfire/mdapy/issues
1 maintainer
Metadata
1 maintainer
Release files for mdapy 1.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mdapy-1.0.7.tar.gz | 1.3 MB | Details |
Built distributions (wheels)
Total release size: 58.2 MB
Release files / mdapy-1.0.7.tar.gz
| Download URL | mdapy-1.0.7.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
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twine/6.1.0 CPython/3.13.12
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Transparency logRelease files / mdapy-1.0.7-cp39-cp39-macosx_14_0_arm64.whl
| Download URL | mdapy-1.0.7-cp39-cp39-macosx_14_0_arm64.whl |
|---|---|
| Size | 2.1 MB |
| Tags | CPython 3.9 macOS 14.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
db051ff70a68b02cc192f7e97f6dbf274103ddcbfd0acbc458ed9957d77de776
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BLAKE2b-256 checksum How to use checksums |
18dfa66bedf0347e68690e1db2ff883d32042cc3824492246b182df9eef6c6c3
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
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Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
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