JWST Calibration Pipeline

[!IMPORTANT]
JWST requires a C compiler for dependencies.

[!NOTE]
Linux and MacOS platforms are tested and supported. Windows is not currently supported.

[!WARNING]
Installation of jwst versions 1.15.1 through 1.16.1 will pull an incompatible version of the gwcs dependency -
this can be remedied by downgrading the gwcs version through e.g. pip install 'gwcs<0.22'

Installation on MacOS Mojave 10.14 will fail due to lack of a stable build for dependency opencv-python.

Installation

Please contact the JWST Help Desk for installation issues.

The easiest way to install the latest jwst release into a fresh virtualenv or conda environment is

pip install jwst

Detailed Installation

The jwst 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 jwst 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 jwst 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 jwst package 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/zsh shell.

Installing latest releases

You can install the latest released version via pip. From a bash/zsh shell:

conda create -n <env_name> python=3.12
conda activate <env_name>
pip install jwst

You can also install a specific version:

conda create -n <env_name> python=3.12
conda activate <env_name>
pip install jwst==1.16.1

Installing the development version from Github

You can install the latest development version (not as well tested) from the
Github main branch:

conda create -n <env_name> python=3.12
conda activate <env_name>
pip install git+https://github.com/spacetelescope/jwst

Installing a DMS Operational Build

There may be occasions where an exact copy of an operational DMS build is
desired (e.g. for validation testing or debugging operational issues).
We package releases for DMS builds via environment snapshots that specify the
exact versions of all packages to be installed.

To install a particular DMS build, consult the
Software vs DMS build version map
table shown below to determine the correct jwst tag. For example, to install the
version of jwst used in DMS build 9.0, use jwst tag 1.8.2. The overall
procedure is similar to the 3-step process outlined in the previous section, but the
details of each command vary, due to the use of environment snapshot files that specify
all of the particular packages to install. Also note that different snapshot files are
used for Linux and Mac OS systems.

Linux:

conda env create --file https://ssb.stsci.edu/stasis/releases/jwst/JWSTDP-1.17.1/delivery/latest-py312-linux-x86_64.yml
conda activate JWSTDP-1.17.1-1-py312-linux-x86_64

MacOS arm64:

conda env create --file https://ssb.stsci.edu/stasis/releases/jwst/JWSTDP-1.17.1/delivery/latest-py312-macos-arm64.yml
conda activate JWSTDP-1.17.1-1-py312-macos-arm64

MacOS x86_64:

conda env create --file https://ssb.stsci.edu/stasis/releases/jwst/JWSTDP-1.17.1/delivery/latest-py312-macos-x86_64.yml
conda activate JWSTDP-1.17.1-1-py312-macos-x86_64

Starting with the jwst 1.16.1 release, we updated our release procedures to use
stasis. Each DMS delivery has its own installation instructions,
which may be found in the corresponding release documentation, e.g.:
https://ssb.stsci.edu/stasis/releases/jwst/JWSTDP-1.16.1/delivery/README-py312-macos-x86_64.html
The installation procedures may change from time to time, so consulting the
documentation page for the specific version in question is the best way to get
that version installed. You can find the list of available releases at the
top-level stasis domain.

For releases prior to 1.16.1, please instead follow the directions below. The complete list of releases prior to 1.16.1
is available on astroconda-releases.

Linux:

conda create -n jwstdp-1.16.1 --file https://ssb.stsci.edu/releases/jwstdp/1.16.1/conda_python_stable-deps.txt
conda activate jwstdp-1.16.1
pip install -r https://ssb.stsci.edu/releases/jwstdp/1.16.1/reqs_stable-deps.txt

MacOS:

conda create -n jwstdp-1.16.1 --file https://ssb.stsci.edu/releases/jwstdp/1.16.1/conda_python_macos-stable-deps.txt
conda activate jwstdp-1.16.1
pip install -r https://ssb.stsci.edu/releases/jwstdp/1.16.1/reqs_macos-stable-deps.txt

Installing for Developers

If you want to be able to work on and test the source code with the jwst 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 jwst package.

As usual, the first two steps are to create and activate an environment:

conda create -n <env_name> python=3.12
conda activate <env_name>

To install your own copy of the code into that environment, you first need to
fork and clone the jwst repo:

cd <where you want to put the repo>
git clone https://github.com/<your_github_username>/jwst.git
cd jwst

Note: python setup.py install and python setup.py develop commands do 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 jupyter matplotlib pylint

Calibration References Data System (CRDS) Setup

Note: As of November 10, 2022, the process of deprecating the CRDS PUB Server will start.
For details, refer to the CRDS PUB Server Freeze
and Deprecation page

CRDS is the system that manages the reference files needed to run the pipeline.
For details about CRDS, see the User’s
Guide

The JWST CRDS server is available at https://jwst-crds.stsci.edu

To run the pipeline inside the STScI network, CRDS must be configured to find the CRDS server
by setting the environment variable

export CRDS_SERVER_URL=https://jwst-crds.stsci.edu

This server will be used to determine the appropriate CRDS context for a given pipeline
version, and the pipeline will obtain individual reference files within this context from a local shared disk.

To run the pipeline outside the STScI network, CRDS must be configured by setting
two environment variables:

export CRDS_PATH=<locally-accessable-path>/crds_cache/jwst_ops
export CRDS_SERVER_URL=https://jwst-crds.stsci.edu

This server will be used to determine the appropriate CRDS context for a given pipeline
version, and the pipeline will automatically download individual
reference files within this context to the local cache specified by CRDS_PATH.

<locally-accessable-path> can be any the user has permissions to use, such as $HOME.
Expect to use upwards of 200GB of disk space to cache the latest couple of contexts.

To use a specific CRDS context other than that
automatically associated
with a given pipeline version, set the CRDS_CONTEXT
environment variable:

export CRDS_CONTEXT=jwst_1179.pmap

Documentation

Software documentation (built daily from the GitHub main branch) is available at:

https://jwst-pipeline.readthedocs.io/en/latest/

To build the docs yourself, clone this repository and build the documentation with:

pip install -e ".[docs]"
cd docs
make html
make latexpdf

For more user-focused documentation on the JWST calibration pipeline, see also the JDox pages at:

https://jwst-docs.stsci.edu/jwst-science-calibration-pipeline

The latest build information is also available on JDox at:

https://jwst-docs.stsci.edu/jwst-science-calibration-pipeline/jwst-operations-pipeline-build-information

Contributions and Feedback

We welcome contributions and feedback on the project. Please follow the
contributing guidelines to submit an issue or a pull request.

We strive to provide a welcoming community to all of our users by abiding with
the Code of Conduct.

If you have questions or concerns regarding the software, please open an issue
at https://github.com/spacetelescope/jwst/issues or
contact the JWST Help Desk.

Software vs DMS build version map

The table below provides information on each release of the jwst package
and its relationship to software builds used in the STScI JWST DMS operations
environment. The Released column gives the date on which the jwst tag
was released on PyPi and the Ops Install column gives the date on which
the build incorporating that release was installed in DMS operations.
Note that the CRDS_CONTEXT listed is a minimum context that can be used with
that release. A release should work with any contexts between
the specified context and less than the context for the next release.

Unit Tests

Unit tests can be run via pytest. Within the top level of your local jwst repo checkout:

pip install -e ".[test]"
pytest

Need to parallelize your test runs over all available cores?

pip install pytest-xdist
pytest -n auto

Regression Tests

Latest regression test results can be found here (STScI staff only):

https://plwishmaster.stsci.edu:8081/job/RT/job/JWST/

The test builds start at 6pm local Baltimore time Monday through Saturday on jwcalibdev.

To run the regression tests on your local machine, get the test dependencies
and set the environment variable TEST_BIGDATA to our Artifactory server
(STSci staff members only):

pip install -e ".[test]"
export TEST_BIGDATA=https://bytesalad.stsci.edu/artifactory

To run all the regression tests (except the very slow ones):

pytest --bigdata jwst/regtest

You can control where the test results are written with the
--basetemp=<PATH> arg to pytest. NOTE that pytest will wipe this directory clean
for each test session, so make sure it is a scratch area.

If you would like to run a specific test, find its name or ID and use the -k option:

pytest --bigdata jwst/regtest -k nirspec

If developers need to update the truth files in our nightly regression tests,
there are instructions in the repository wiki.

https://github.com/spacetelescope/jwst/wiki/Maintaining-Regression-Tests