Frequently Asked Questions

stenv doesn’t build on my system; what do I do?

You can use the environment definition YAML file (environment.yaml) in the root of the repository:

curl -L https://raw.githubusercontent.com/spacetelescope/stenv/main/environment.yaml -o ~/Downloads/stenv.yaml
micromamba env create --name stenv --file ~/Downloads/stenv.yaml
mamba env create --name stenv --file https://raw.githubusercontent.com/spacetelescope/stenv/main/environment.yaml
conda env create --name stenv --file https://raw.githubusercontent.com/spacetelescope/stenv/main/environment.yaml

This environment is unpinned, meaning it may take some time to resolve dependency versions. Additionally, the resulting package versions may not have been tested for your platform.

Warning

stenv does not currently support a native Windows installation. To build stenv on Windows, see Windows Support.

Why isn’t _____ package in stenv?

Not all STScI packages are included in the base stenv environment; some packages are not supported and / or deprecated, and some are deemed too niche (or dependent on too many extra packages) to be included for all users.

To install a package in your local environment, you can use pip install while the environment is activated:

micromamba activate stenv
pip install <package_name>
mamba activate stenv
pip install <package_name>
conda activate stenv
pip install <package_name>

To request that a new package be added to stenv (environment.yaml) for all users, see Adding a package to stenv.

What about Astroconda?

Astroconda, historically maintained by STScI as a Conda software channel, provides data analysis tools and pipelines via the Conda package management system.

Warning

Astroconda is no longer supported as of February 1st, 2023.

stenv supersedes Astroconda as a STScI software distribution; it supports most of the packages in Astroconda, works with all current versions of Python, and provides a common environment for both the Hubble Space Telescope (HST) and James Webb Space Telescope (JWST) pipelines. Additionally, while Astroconda primarily uses Conda recipes to build and serve packages, which need to be updated separately from PyPI releases, stenv draws most of its packages directly from PyPI with pip (though it still requires use of a Conda environment for hstcal and fitsverify, which are provided by conda-forge).