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Data Science in Practice

Course materials and notes for Data Science in Practice course at the London Interdisciplinary School.

Machinery

The template for this website comes from https://jupyterbook.org - many thanks to the authors.

Getting started for working on the repository

Say your Github username is my-gh-user.

Go to the repository page that houses this README - for example https://github.co/lisds/dsip.

Click on "Fork" button near top right, to make your own fork of the repository, that will now be at https://github.com/my-gh-user/<repo-name> where <repo-name> is the name of the repository housing this README.

The following assumes that the README is in https://github.com/lisds/dsip. The name of the repository is therefore dsip. Substitute URL and repository name throughout.

Clone the main repo:

git clone https://github.com/lisds/dsip

Add a remote for your fork:

cd dsip
git remote add my-gh-user https://github.com/my-gh-user/dsip.git
git fetch my-gh-user

Get any submodules for the repository (you may need these for the build):

git submodule update --init

Install the code modules and build dependencies for this book:

pip install -e .

Start by making some branch to work on, linked to your fork. Use a name to match the kind of changes you are about to make, like rewrite-intro-pages:

git branch rewrite-intro-pages
git checkout rewrite-intro-pages

Associate this branch with your fork:

git push my-gh-user rewrite-intro-pages -u

The -u flag above stores the association of this branch with your fork, referenced by my-gh-user.

Installing stuff for building / serving the repository files

If you use Conda then you might make a Conda environment for working on the repo. I don't, I use pip, and I make a virtual environment. You can do that like this:

python3 -m venv my-venv
source my-virtualenv/bin/activate

Or, if you have virtualenvwrapper (I do) then, you might prefer:

python3 -m venv $WORKON_HOME/my-venv
workon my-venv

Install the Python packages you need for building the site:

pip install -r build_requirements.txt

Finally, check that you can build the pages locally with:

make html

Configuring Jupyter to save / load in R Markdown

I'm using the excellent Jupytext to make it easier to edit Jupyter Notebooks. Jupytext automates saving Notebook files as Markdown (and other formats), and loading them from edited Markdown (and other formats).

You need to configure Jupyter to use it. If you don't have a Jupyter configuration, do:

jupyter notebook --generate-config

You should now have a file ~/.jupyter/jupyter_notebook_config.py. Append these lines:

c.NotebookApp.contents_manager_class = "jupytext.TextFileContentsManager"
c.ContentsManager.default_jupytext_formats = "ipynb,Rmd"

I also turned off autosave globally, by following the instructions in this stackoverflow answer. This stops autosave saving over any edits that I am making in the Markdown source.

Be careful - if you are used to autosave in Jupyter, you can easily lose work when you disable autosave.

mkdir -p ~/.jupyter/custom

Add the following line to ~/.jupyter/custom/custom.js:

Jupyter.notebook.set_autosave_interval(0); // disable autosave

Extra stuff

Consider installing hub to make interactions with Github easier, from the command line. Or use the official gh command line tool.

Configuring build etc

You might want to check the instructions for configuring the build at https://jupyterbook.org.

Workflow

Developing

  • Edit .Rmd notebook files.
  • make html to build textbook files.
  • Review in browser

Shipping

Our continuous integration does this with Github Actions, so the version of the textbook on Github Pages should correspond to the latest commit (unless Github Actions failed). If you have to do the build manually for some reason then make github.