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Document how to update conda-lock.yml file in the main README.md (#29)
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Update instructions on how to add or update dependencies in the
cryocloud docker image. Specifically, documenting the `/condalock` slash
command added in #5 which runs
[`conda-lock`](https://github.com/conda-incubator/conda-lock) for
creating snapshots of fully reproducible conda environments.
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weiji14 authored Dec 4, 2022
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The JupyterHub docker image used for [hub.cryointhecloud.com](https://cryointhecloud.com),
hosted on https://quay.io/repository/cryointhecloud/cryo-hub-image

## Adding packages to this repository

You can easily add more packages to the cryointhecloud hub by making pull requests to this
repository. Edit either the `environment.yml` file (for most packages) or `apt.txt` file
(for packages that need to be used in the Linux Desktop environment in the cloud), and make
a pull request - you can even do that just from the GitHub UI! A bot will comment with a link to
[mybinder.org](https://mybinder.org) where you can test your pull request to make sure it works
as you would expect.
## Updating packages in this repository

You can add or update packages on the cryointhecloud hub by making pull requests to this
repository. Follow these steps:

1. Edit either the [`environment.yml`](https://github.com/CryoInTheCloud/hub-image/edit/main/environment.yml)
file (for most packages) or [`apt.txt`](https://github.com/CryoInTheCloud/hub-image/edit/main/apt.txt)
file (for packages that need to be used in the Linux Desktop environment in the cloud).
2. Start a [pull request](https://github.com/CryoInTheCloud/hub-image/pulls) -
you can even do that just from the GitHub UI! A bot will comment with a link to
[mybinder.org](https://mybinder.org) where you can test your pull request to make sure it works
as you would expect.
3. In the Pull Request, write a comment with the slash command `/condalock`.
This will refresh the [`conda-lock.yml`](https://conda-incubator.github.io/conda-lock/output/#unified-lockfile)
file that contains a snapshot of the exact library versions contained in the
conda environment, which will be useful for reproducibility.

## Updating the CryoCloud JupyterHub to use a new image

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