If you downloaded and installed your directory and conda environment before the workshop, good for you! We appreciate it. However, there may well have been some updates made to the materials we are going to use in the workshop, so...
Assuming you cloned the roman-data-workshop
git repository, open up a terminal, change your location to that
directory, and then run the following:
cd roman-data-workshop
git pull
If there are errors when attempting to update, your best option is to reset your local files to match the remote (this will destroy any local file changes you have made):
git reset --hard origin/main
ADVANCED OPTION: This is not a git workshop, but if you want to keep your file modifications, you can commit your modified files to the git repository and then create a new branch from the current version on the GitHub server:
git commit -a "Save my modified files"
git fetch origin
git checkout origin/main -b workshop-main
This is probably overkill unless you already use git regularly. When in doubt, please ask the instructors or helpers.
If you do not have git
installed and used the Download ZIP
option instead, you will have to re-download the ZIP and
overwrite your local files to make sure that you have the most recent version.
Assuming you properly installed your roman-data-workshop-env
conda environment, you should be able to:
a. activate that conda environment, and b. go to the original installation directory, and then c. check to see if your environment still meets the requirements.
Let's do that now. Start by activating the conda
environment:
conda activate roman-data-workshop-env
You may notice a change in your prompt; e.g., (roman-data-workshop-env)
. Switch to the directory containing the
installer by doing the following (your directory path may be different):
cd roman-data-workshop
Next, we check if the environment is still up-to-date:
python 00_install/verify_install.py
If this check reports no issues, you are done. Otherwise, continue below.
If the verify_install.py
script reports that some package (for example numpy
)
is not up-to-date, we need to check where the package came from with conda list
:
conda list numpy
If the package was installed with pip
, the Build
and Channel
columns will include pypi
:
# packages in environment at /opt/miniconda3/envs/test:
#
# Name Version Build Channel
numpy 1.22.4 pypi_0 pypi
and then you can upgrade with pip install --upgrade <package>
:
pip install --upgrade numpy
If you need a pre-release version from PyPI, add
--pre
to thepip install
command.
Otherwise, if the package is installed with conda
, it will show something similar to the following:
# packages in environment at /opt/miniconda3/envs/test:
#
# Name Version Build Channel
numpy 1.22.3 py310hdcd3fac_0
numpy-base 1.22.3 py310hfd2de13_0
and you can update with conda update <package>
:
conda update numpy
Once you have performed the updates, check your installation again using verify_install.py
:
python 00_install/verify_install.py
You should now be up-to-date.