The easiest way to install the latest roman-datamodels release into a fresh virtualenv or conda environment is
pip install roman-datamodels
The roman-datamodels package can be installed into a virtualenv or conda environment via pip. We recommend that for each
installation you start by creating a fresh environment that only has Python installed and then install the roman_datamodels
package and its dependencies into that bare environment. If using conda environments, first make sure you have a recent
version of Anaconda or Miniconda installed. If desired, you can create multiple environments to allow for switching
between different versions of the roman-datamodels package (e.g. a released version versus the current development version).
In all cases, the installation is generally a 3-step process:
- Create a conda environment
- Activate that environment
- Install the desired version of the
roman-datamodelspackage into that environment
Details are given below on how to do this for different types of installations, including tagged releases, DMS builds used in operations, and development versions. Remember that all conda operations must be done from within a bash shell.
You can install the latest released version via pip. From a bash shell:
conda create -n <env_name> python
conda activate <env_name>
pip install roman-datamodels
Note
Alternatively, you can also usevirtualenvto create an environment; however, this installation method is not supported by STScI if you encounter issues.
You can also install a specific version (from roman-datamodels 0.1.0 onward):
conda create -n <env_name> python
conda activate <env_name>
pip install roman-datamodels==0.5.0
You can install the latest development version (not as well tested) from the Github main branch:
conda create -n <env_name> python
conda activate <env_name>
pip install git+https://github.com/spacetelescope/roman_datamodels
If you want to be able to work on and test the source code with the roman-datamodels package, the high-level procedure to do
this is to first create a conda environment using the same procedures outlined above, but then install your personal
copy of the code overtop of the original code in that environment. Again, this should be done in a separate conda
environment from any existing environments that you may have already installed with released versions of the roman-datamodels
package.
As usual, the first two steps are to create and activate an environment:
conda create -n <env_name> python
conda activate <env_name>
To install your own copy of the code into that environment, you first need to fork and clone the roman_datamodels repo:
cd <where you want to put the repo>
git clone https://github.com/spacetelescope/roman_datamodels
cd roman_datamodels
Note
Installing viasetup.py(python setup.py install,python setup.py develop, etc.) is deprecated and does not work.
Install from your local checked-out copy as an "editable" install:
pip install -e .
If you want to run the unit or regression tests and/or build the docs, you can make sure those dependencies are installed too:
pip install -e ".[test]"
pip install -e ".[docs]"
pip install -e ".[test,docs]"
Need other useful packages in your development environment?
pip install ipython pytest-xdist