|
|
@@ -15,29 +15,6 @@ setup instructions and for why twine is the recommended method.
|
|
|
|
|
|
## Getting a clean environment
|
|
|
|
|
|
-### Using Docker
|
|
|
-
|
|
|
-If desired, you can use Docker to create a new container with a fresh clone of JupyterLab.
|
|
|
-
|
|
|
-First, build a Docker base image. This container is customized with your git commit information. The build is cached so rebuilding it is fast and easy.
|
|
|
-
|
|
|
-```bash
|
|
|
-docker build -t jlabreleaseimage release/ --build-arg "GIT_AUTHOR_NAME=`git config user.name`" --build-arg "GIT_AUTHOR_EMAIL=`git config user.email`"
|
|
|
-```
|
|
|
-
|
|
|
-Note: if you must rebuild your Docker image from scratch without the cache, you can run the same build command above with `--no-cache --pull`.
|
|
|
-
|
|
|
-Then run a new instance of this container:
|
|
|
-
|
|
|
-```bash
|
|
|
-docker rm jlabrelease # delete any old container
|
|
|
-docker run -it --name jlabrelease -w /usr/src/app jlabreleaseimage bash
|
|
|
-```
|
|
|
-
|
|
|
-Now you should be at a shell prompt as root inside the docker container (the prompt should be something like `root@20dcc0cdc0b4:/usr/src/app`).
|
|
|
-
|
|
|
-### Clean environment
|
|
|
-
|
|
|
For convenience, here is a script for getting a completely clean repo. This
|
|
|
makes sure that we don't have any extra tags or commits in our repo (especially
|
|
|
since we will push our tags later in the process), and that we are on the correct branch. The script creates a conda env, pulls down a git checkout with the
|
Jason Grout