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@@ -15,6 +15,8 @@ setup instructions and for why twine is the recommended method.
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## Getting a clean environment
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+### Clean environment with Conda
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+
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For convenience, here are commands for getting a completely clean repo. This
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makes sure that we don't have any extra tags or commits in our repo (especially
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since we will push our tags later in the process), and that we are on the master
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@@ -28,13 +30,40 @@ rm -rf jupyterlab
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conda create -c conda-forge -y -n jlabrelease notebook nodejs twine
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conda activate jlabrelease
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-git clone git@github.com:jupyterlab/jupyterlab.git
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+```
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+
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+### Clean environment with Docker
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+
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+Instead of following the conda instructions above, you can use Docker to create a new container with a fresh clone of JupyterLab.
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+
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+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.
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+
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+```bash
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+docker build -t jlabreleaseimage release/ --build-arg "GIT_AUTHOR_NAME=`git config user.name`" --build-arg "GIT_AUTHOR_EMAIL=`git config user.email`"
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+```
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+
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+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`.
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+
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+Then run a new instance of this container:
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+
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+```bash
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+docker rm jlabrelease # delete any old container
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+docker run -it --name jlabrelease -w /usr/src/app jlabreleaseimage bash
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+```
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+
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+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`).
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+
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+## Set up JupyterLab
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+
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+Now clone the repo and build it
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+
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+```bash
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+git clone https://github.com/jupyterlab/jupyterlab.git
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cd jupyterlab
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```
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Check out the branch you are doing the release from, if different from master.
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-
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-Then build and install jlpm:
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+Then build and install jupyterlab:
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```bash
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pip install -ve .
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Steven Silvester