Installation#
Note
jdaviz
is undergoing constant development. We encourage users to always update
to the latest version. In general, it is good practice to install the development
version following the instructions below as full released versions may lag behind.
User Installation#
Windows-Specific Dependencies#
Some of our dependencies require C++ compilers to install properly. These are usually included with macOS and most Linux distributions, but are not included by default in Windows. Microsoft provides these tools as part of their Build Tools for Visual Studio, which can be found under “Tools for Visual Studio” towards the bottom of the page.
Create Your Local Environment#
Some of Jdaviz’s dependencies require non-Python packages to work
(particularly the front-end stack that is part of the Jupyter ecosystem).
We recommend using Miniconda
to easily manage a compatible Python environment for jdaviz
; it should work
with most modern shells, except CSH/TCSH.
You may want to consider installing jdaviz
in a new virtual or conda environment
to avoid version conflicts with other packages you may have installed, for example:
conda create -n jdaviz-env python=3.11
conda activate jdaviz-env
Pip Install#
As noted above, we typically recommend installing the latest development version:
pip install git+https://github.com/spacetelescope/jdaviz --upgrade
A normal install will also work by installing the latest release version:
pip install jdaviz --upgrade
Common Issues#
If you encounter problems while following these installation instructions, please consult known installation issues.
Note that jdaviz
requires Python 3.10 or newer. If your pip
corresponds to an older version of
Python, it will raise an error that it cannot find a valid package.
Users occasionally encounter problems running the pure pip
install above. For those
using conda
, some problems may be resolved by pulling the following from conda
instead of pip
:
conda install bottleneck
conda install -c conda-forge notebook
conda install -c conda-forge jupyterlab
You might also want to enable the ipywidgets
notebook extension, as follows:
jupyter nbextension enable --py widgetsnbextension
Optional Dependencies for Roman#
Dependencies for working with data products from the Roman Space Telescope are available for optional installation from PyPI with:
pip install -U jdaviz[roman]
or while building from source with:
pip install -U .[roman]
Developer Installation#
If you wish to contribute to Jdaviz, please fork the project to your
own GitHub account. The following instructions assume your have forked
the project and have connected
your GitHub to SSH
and username
is your GitHub username. This is a one-setup setup:
git clone git@github.com:username/jdaviz.git
cd jdaviz
git remote add upstream git@github.com:spacetelescope/jdaviz.git
git fetch upstream main
git fetch upstream --tags
To work on a new feature or bug-fix, it is recommended that you build upon
the latest dev code in a new branch (e.g., my-new-feature
).
You also need the up-to-date tags for proper software versioning:
git checkout -b my-new-feature
git fetch upstream --tags
git fetch upstream main
git rebase upstream/main
For the rest of contributing workflow, it is very similar to how to make a code contribution to astropy, including setting up virtual environments, git basics, and more.
An exception is the change log; if your patch requires a change log, see CHANGES.rst
for examples.
One option is to enable the hot reloading of Vue.js templates, install
watchdog
:
pip install watchdog
After installing watchdog
, to use it, add the following to the top
of a notebook:
from jdaviz import enable_hot_reloading
enable_hot_reloading()
Another option is to enable magic commands for Python autoreloading, to use it, add the following to the top of a notebook:
%load_ext autoreload
%autoreload 2
To install jdaviz
for development or from source in an editable mode
(i.e., changes to the locally checked out code would reflect in runtime
after you restarted the Python kernel):
pip install -e .
Note: It is recommended to install the package without -e
flag initially
to ensure that the template files are copied correctly.