Skip to main content

modelarchive - The ModelArchive Python package

https://modelarchive.org/

modelarchive collects all Python functionality developed for ModelArchive in a single package - essentially the “Everything ModelArchive” toolkit.

Yes, the name is a bit long, but ma alone felt too short ;) You can conveniently import it as:

import modelarchive as ma

The package is organised into submodules covering different areas of functionality. Currently available:

  • modelcif: help with editing ModelCIF files, translating from legacy PDB format and extending existing ModelCIf-formatted files

Installation

From PyPI:

pip install modelarchive-py

From source:

git clone https://git.scicore.unibas.ch/schwede/modelarchive-py
cd modelarchive-py
pip install .

For development, to see code changes immediately effective in your environment and to include development tools, run:

 pip install -e ".[dev]"

Versioning

modelarchive follows Semantic Versioning, so you can safely depend on modelarchive-py>=<MAJOR VERSION>.0.0 to get updates without breaking changes.

Documentation

Documentation is kept up to date here. There is the stable version, pointing to the current release, and there is latest, pointing to the dev branch. Older versions of the documentation are also kept available.

Developing ModelArchive

  • consider copying hooks/pre-push to .git/hooks/ for version number checks
  • best install the package to get all requirements resolved
  • run pytest as python3 -m pytest [-s] (pytest will be installed with [dev])
  • for unit test coverage, run python3 -m pytest --cov-report=term-missing --cov=modelarchive [-s]
  • in the doc/ subdirectory, run make html to create the documentation
  • in the doc/ subdirectory, run make doctest to run Doctests
  • updating the package on PyPi happens via our CI/CD pipeline
    • merge dev into main
    • edit CHANGELOG.md
    • push a tag of form <Major>.<Minor>.<Bugfix>
    • runs the release pipeline to create a package on PyPi and a release in GitLab
    • merge main into dev
  • updating the Read the Docs page happens via our CI/CD pipeline
    • push to dev to update latest
    • push release tag to update stable

Metadata

Release files for modelarchive-py 4.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for modelarchive-py 4.0.1
File Size Uploaded
modelarchive_py-4.0.1.tar.gz 175.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for modelarchive-py 4.0.1
File Interpreter ABI Platform
modelarchive_py-4.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 297.8 kB

Release files / modelarchive_py-4.0.1.tar.gz

Download URL modelarchive_py-4.0.1.tar.gz
Size 175.1 kB
Tags Source
SHA-256 checksum
How to use checksums
f2be058019ed6ed7133163df25a326f28a7a841846dc3ad4b163b26c8538dcf3
BLAKE2b-256 checksum
How to use checksums
cea04f674e42283dcb55c9d27505643e0de762b8fe39f8d6b6ef84e00f481408
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / modelarchive_py-4.0.1-py3-none-any.whl

Download URL modelarchive_py-4.0.1-py3-none-any.whl
Size 122.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
1067221419ed3d02245267ef3544c73bf1b5190e60387beb496d35daa1a3e8c7
BLAKE2b-256 checksum
How to use checksums
e12a0f29d9125ad702a70e723ee0df6caba624e9e7d7b48fbd2ab922a29b353d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release history Release notifications | RSS feed

This release

4.0.1 This release

2 release files

4.0.0

2 release files

3.7.0

2 release files

3.6.0

2 release files

3.5.1

2 release files

3.5.0

2 release files

3.4.0

2 release files

3.3.0

2 release files

3.2.0

2 release files

3.1.0

2 release files

3.0.0

2 release files

2.1.0

2 release files

2.0.0

2 release files

1.1.0

2 release files

1.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page