4 November 2019
~ 4 mins read
Here's a video showing how I was able to do it in 80 seconds:
Cool right? And the only tools that you'll need are
Docker of course.
But let's proceed in order.
pydockenv is a project which is currently in alpha stage whose goal is to give the same experience of using virtual environments, but backed by Docker. So each python environment will actually correspond to a Docker container, and can be defined by using a
.toml file. At time of writing it's compatible only with Python >=3.6.
For our purpose, we're actually only interested in how to install it and how to create the environment that will run our Jupyter Notebook. For a more detailed overview, you can have a look here.
As explained in the README of the project, we can install
pydockenv as follows:
pip install --user pydockenv # or pip3, here I'm assuming that pip is for Python 3
The above command will install
pydockenv to the Python user install directory to avoid conflicts. In order to run the
pydockenv binary, you will need to have that directory in your
PATH. You can do this by running these lines:
export PY_USER_BIN=$(python -c 'import site; print(site.USER_BASE + "/bin")') export PATH=$PY_USER_BIN:$PATH
Now you have the
pydockenv cli available!
There's a little caveat:
pydockenv assumes that the
python binary runs Python >=3.6. In case that you have Python 3 available through
python3, you should also run:
As anticipated above, an environment can be defined using
.toml file, that we will save as
jupyter-notebook-env.toml. Here's its content:
[tool.pydockenv] name = "jupyter-notebook" python = "3.7.4" [tool.pydockenv.dependencies] jupyter = "==1.0.0" [tool.pydockenv.aliases] [tool.pydockenv.aliases.notebook] cmd = "jupyter notebook --allow-root --ip=0.0.0.0 --port=8888" ports = 
If you're like: "Hey! Just let me run my Notebook!", then skip to the section "Let's run the Jupyter Notebook!", otherwise stay here to understand how the environment is defined.
The first part it's actually almost self-explanatory:
[tool.pydockenv] name = "jupyter-notebook" python = "3.7.4"
This simply means that the name of the environment will be
"jupyter-notebook-pydockenv" and that the correspdonding container will run Python 3.7.4.
The second part it's a sort of
requirements.txt embedded into the this file. This simply lists all the requirements that will be installed inside the container:
[tool.pydockenv.dependencies] jupyter = "==1.0.0"
In this case
jupyter==1.0.0 is our only requirement.
Since the environment actually runs in a Docker container, this means that also all the commands will run inside that container. As you most probably know, to run a command insde a docker container you need to run:
docker exec -it run <container-name> <command>
and let's face it, it's not the most convenient thing to do.
So the third part simply defines an alias for running the Notebook:
[tool.pydockenv.aliases] [tool.pydockenv.aliases.notebook] cmd = "jupyter notebook --allow-root --ip=0.0.0.0 --port=8888" ports = 
Here an alias
notebook is defined, and by running
pydockenv run notebook we will actually run inside the container the command specified by
ports key is just a list of ports that the command requires to be opened on the container. If we do not open the specific port the Notebook will run, but it won't be accessible from the host.
And here we are!
Let's say that your project directory from where you want to run the Jupyter Notebook is in
~/Projects/awesome-project and that you already put the
jupyter-notebook-env.toml inside. We have to create the environment from that directory:
cd ~/Projects/awesome-project pydockenv create --file=jupyter-notebook-env.toml .
Now, especially if you're used to virtual environments, you may ask: "Why the environment should bother about the directory from which I create it?". Well, that is because it runs in a Docker container, and what
pydockenv does is to bind mount the project directory into the container. To be more specific it binds it into
The environment has been created! Let's activate it!
source pydockenv activate jupyter-notebook
And we can now finally start our Notebook:
pydockenv run notebook
pydockenv is still at its beginning, but I'm actively working on it as I think that it has a lot of potential. If you liked it, don't forget to leave a 🌟 on Github and contributions are welcome! If you have ideas or find any issue, please leave a comment or open an issue.