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DOI

Molass Library is a rewrite of MOLASS, a tool for the analysis of SEC-SAXS experiment data currently hosted at the Japanese synchrotron radiation facilities, Photon Factory and SPring-8

Tested Platforms

Continuous integration tests run on:

  • Python 3.12, 3.13, 3.14 on Ubuntu (latest)
  • Python 3.12, 3.13, 3.14 on Windows (latest)

Installation

Requirements: Python 3.12, 3.13, or 3.14

Linux (Ubuntu/Debian) prerequisites:

Before installing on Linux, ensure system build tools are available (needed to compile C extensions such as ultranest):

sudo apt install build-essential python3-dev

To install this package, use pip as follows:

pip install -U molass
pip install molass_data  # Sample datasets for tutorials and testing

If your data lives in Dropbox, pip install molass[dropbox] adds an API-based local cache (molass.DataUtils.sync_dropbox_folder) that avoids the repeated re-downloads that can happen when reading directly from a Dropbox-desktop-synced folder. See molass/DataUtils/DropboxSync.py for setup.

For development (requires molass-legacy as a sibling directory):

git clone https://github.com/biosaxs-dev/molass-library
git clone https://github.com/biosaxs-dev/molass-legacy
cd molass-library
pip install -e ".[testing]"
pip install molass_data

Quick Start

For a hands-on introduction, see the tutorial's Quick Start section, or run the corresponding test file:

pytest tests/tutorial/01-quick_start.py -v

Note: Running tests requires the development install. See CONTRIBUTING.md for setup instructions.

The molass-beginner repository provides an interactive onboarding experience in VS Code Agent mode.

Documentation

Citation

If you use Molass Library in your research, please cite the JOSS paper:

Takahashi, M., & Shimizu, N. (2026). Molass Library: A Python Package for SEC-SAXS Data Analysis. Journal of Open Source Software, 11(124), 10403. https://doi.org/10.21105/joss.10403

@article{Takahashi2026,
  doi = {10.21105/joss.10403},
  url = {https://doi.org/10.21105/joss.10403},
  year = {2026},
  publisher = {The Open Journal},
  volume = {11},
  number = {124},
  pages = {10403},
  author = {Masatsuyo Takahashi and Nobutaka Shimizu},
  title = {Molass Library: A Python Package for SEC-SAXS Data Analysis},
  journal = {Journal of Open Source Software}
}

See also CITATION.cff for citing the software itself.

Community

To join the community, see:

Especially for testing, see the first two sections in

Copilot Usage

Context is auto-loaded from .github/copilot-instructions.md when using GitHub Copilot in Agent mode (AI Context Standard).

For behavioral rules and user-type guidance, see Copilot/copilot-guidelines.md.

Optional Features

Excel reporting (Windows only):

If you want to use Excel reporting features (Windows only) for backward compatibility, install with the excel extra:

pip install -U molass[excel]

Note: The excel extra installs pywin32, which is required for Excel reporting and only works on Windows.

Release files for molass 1.1.1

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

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Source distribution for molass 1.1.1
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Table of built distributions (wheels) for molass 1.1.1
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Total release size: 3.1 MB

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