Lock, build, and test commands

Added `docker-compose.yml` and `Makefile` to help make it easier to lock, build, and test Python and R images.

Setting these up before we start having any big changes for '23, so we don't need to change our workflow.

Makefile

@@ -0,0 +1,29 @@
+py-build: py-base/conda-linux-64.lock
+	docker compose stop py
+	docker compose build py
+
+py-base/conda-linux-64.lock: py-base/environment.yml
+	conda-lock --kind explicit --platform linux-64 -f py-base/environment.yml
+	mv conda-linux-64.lock py-base/conda-linux-64.lock
+
+py-lock:
+	conda-lock --kind explicit --platform linux-64 -f py-base/environment.yml
+	mv conda-linux-64.lock py-base/conda-linux-64.lock
+
+py-lab:
+	docker compose up py
+
+r-build: r/conda-linux-64.lock
+	docker compose stop r
+	docker compose build r
+
+r/conda-linux-64.lock: r/environment.yml
+	conda-lock --kind explicit --platform linux-64 -f r/environment.yml
+	mv conda-linux-64.lock r/conda-linux-64.lock
+
+r-lock:
+	conda-lock --kind explicit --platform linux-64 -f r/environment.yml
+	mv conda-linux-64.lock r/conda-linux-64.lock
+
+r-lab:
+	docker compose up r

README.md

@@ -1,14 +1,37 @@
 # jupyter-image for OceanhackWeek
 
-Repository for building OceanhackWeek 2022
+Repository for building OceanhackWeek 2023
 [JupyterHub](https://jupyter.org/hub) environments (Docker Images) with
 [GitHub Actions CI](https://help.github.com/en/actions/automating-your-workflow-with-github-actions)
 
 Docker images publicly [available here](https://github.com/orgs/oceanhackweek/packages?repo_name=jupyter-image). `jupyter-image` is the 2021 image, while `python` and `r` are for their matching profiles on the hub.
 
-This repository contains configuration for the standard environment used during the OceanhackWeek 2021.
+This repository contains configuration for the standard environment used during the OceanhackWeek 2023.
 When you log into the OceanhackWeek JupyterHub you are running a virtual machine with Ubuntu 22.04,
 a variety of command line tools like `vim` and `git`,
 a `conda` Python/R environment with compatibly package versions,
 and JupyterLab extensions such as `ipywidgets` and `ipyleaflet`.
-By packaging everything up with Docker we help ensure that code written during the hackweek is reproducible and can be run on different physical hardware today and in the future.
+By packaging everything up with Docker we help ensure that code written during the hackweek is reproducible and can be run on different physical hardware today and in the future.
+
+## Development commands
+
+There are a handful of helpful `make` commands for building and testing images.
+
+- `py-lock` - Generate a new Python lockfile.
+- `py-build` - Build Python Docker container (should regenerate lockfile if `environment.yml` was changed).
+- `py-lab` - Launch JupyterLab for Python image. Watch the terminal output for a `127.0.0.1:8080/...` link with the access token.
+- `r-lock` - Generate a new R lockfile.
+- `r-build` - Build R Docker container (should regenerate lockfile if `environment.yml` was changed).
+- `r-lab` - Launch JupyterLab for R image. Watch the terminal output for a `127.0.0.1:8080/...` link with the access token. Once in JupyterLab, you should be able to launch RStudio.
+
+## Testing user-generated environments
+
+Both images use [`nb_conda_kernels` ](https://github.com/Anaconda-Platform/nb_conda_kernels) which allows our users to create their own Conda environments. 
+
+This makes it so that we don't have to package everything into the images to start with.
+
+To test that environments can be created, launch JupyterLab in one of the images.
+
+- `conda create -n <env-name> <requirements>`, and make sure one of the requirements is a Jupyter kernel, like `ipykernel`.
+- Try `conda activate <env-name>` and seeing if it's different than the base environment.
+- The JupyerLab new notebook/console creation screen should now show options for `<env-name>`. This can sometimes take a few minutes before `nb_conda_kernels` sees it.

docker-compose.yml

@@ -0,0 +1,14 @@
+version: '3.4'
+
+services:
+  py:
+    build: ./py-base
+    command: jupyter lab --port=8080 --ip=0.0.0.0
+    ports:
+      - "8080:8080"
+
+  r:
+    build: ./r
+    command: jupyter lab --port=8080 --ip=0.0.0.0
+    ports:
+      - "8080:8080"