DRnext: Installing daschlab

daschlab is the recommended software system for astronomical analysis of DASCH data. It is a Python toolkit meant to be run inside the JupyterLab computational environment.

Thanks to cloud-based notebooks, you don’t need to install daschlab on your own computer to work with DASCH data. But for substantial data analysis, you are probably going to want to do so.

We strongly recommend installing daschlab and its dependencies using the popular Conda package management system in conjunction with the conda-forge package suite. If you need help setting up Conda or conda-forge, see the official conda installation instructions and how to start using conda-forge packages. There are numerous other tutorials available on the general internet as well.

Once these systems are set up on your computer, you can install daschlab by following these steps:

  1. Download this file and save it as daschlab-conda-requirements.txt.
  2. In a terminal, navigate to the directory where you saved that file and run:
    conda create --name daschlab --file daschlab-conda-requirements.txt
  3. Activate the new environment with this command:
    conda activate daschlab
  4. Install daschlab itself with:
    pip install git+https://github.com/pkgw/daschlab.git

These commands will produce a fair amount of output, but should not report any severe errors. Once the installation is complete, you can launch a new daschlab session as follows:

  1. If needed, activate the daschlab environment with the command
    conda activate daschlab
  2. Launch JupyterLab with the command
    jupyter lab


You should be able to install daschlab using any other Python package management framework if needed. Consult the Conda requirements list file for a list of dependencies, although any pip-based installation method should pull in the requirements automatically.

If you prefer to use other analysis tools, that is completely possible: the data returned by the DASCH APIs are all in simple formats (ASCII tables and FITS). You can use daschlab in a minimal way to download these data and save them to disk, or invoke the APIs directly if you really want to. Be aware, however, that support for VO standards is still quite limited.