ALminer: ALMA Archive Mining & Visualization Toolkit

alminer is a Python-based code to effectively query, analyse, and visualize the ALMA science archive. It also allows users to directly download ALMA data products and/or raw data for further image processing.


The easiest way to install alminer is with pip:

pip install alminer

To obtain the most recent version of the code from GitHub:

pip install https://github.com/emerge-erc/ALminer/archive/refs/heads/main.zip

Or clone and install from source:

# If you have a Github account:
git clone git@github.com:emerge-erc/ALminer.git
# If you do not:
git clone https://github.com/emerge-erc/ALminer.git

# After cloning:
cd ALminer
pip install .

Note that depending on your setup, you may need to use pip3.


The dependencies are numpy, matplotlib, pandas, pyvo, astropy version 3.1.2 or higher, and astroquery version 0.4.2.dev6649 or higher. We only use the astroquery package for downloading data from the ALMA archive. The strict requirement to have its newest version is due to recent changes made to the ALMA archive. alminer works in Python 3.


alminer has been developed through a collaboration between Allegro, the ALMA Regional Centre in The Netherlands, and the University of Vienna as part of the EMERGE-StG project. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 851435).

If you use alminer as part of your research, please consider citing this ASCL article (ADS reference will be added to the GitHub page when available).

alminer makes use of different routines in Astropy and Astroquery. Please also consider citing the following papers: - Astropy: Astropy Collaboration et al. 2013 - Astroquery: Ginsburg et al. 2019

We also acknowledge the work of Leiden University M.Sc. students, Robin Mentel and David van Dop, who contributed to early versions of this work.

Contact us

If you encounter issues, please open an issue.

If you have suggestions for improvement or would like to collaborate with us on this project, please e-mail Aida Ahmadi and Alvaro Hacar.