Usepip to install the dependencies as follows, after cloning the repoand opening a terminal in the root folder of the repo.

First we’ll set-up a virtual environment to install the dependencies in:

# Create a virtual environment called geocompypython -m venv geocompy# Activate the virtual environmentsource geocompy/bin/activate

Then install the dependencies (with the optionalpython -mprefix specifying the Python version):

# Install dependencies from the requirements.txt filepython -m pip install -r requirements.txt

You can also install packages individually, e.g.:

pip install jupyter-book

Deactivate the virtual environment when you’re done:

deactivate

Theenvironment.yml file contains a list ofdependencies that can be installed with a package manager such asconda,mamba ormicromamba. The instructions below are formicromambabut should work for any package manager.

# For Linux, the default shell is bash:curl -L micro.mamba.pm/install.sh| bash# For macOS, the default shell is zsh:curl -L micro.mamba.pm/install.sh| zsh

After answering the questions, install dependencies with the followingcommand:

micromamba env create -f environment.yml

Activate the environment as follows:

micromamba activate geocompy

Install kernel, this will allow you to select the environment in vscodeor IPython as follows:

python -m ipykernel install --user

You can now reproduce the book (requires quarto to be installed):

micromamba run -n geocompy quarto preview

VS Code’squarto.quarto plugin can Python code in the chunks in the.qmd files in this book interactively.

However, you can also run any of the chapters in a Jupyter Notebook,e.g. as follows:

cd ipynb# jupyter notebook . # open a notebook showing all chaptersjupyter notebook 02-spatial-data.ipynb

You should see something like this:

See documentation on running and developing Python code in a Jupyternotebook atdocs.jupyter.org.

The Python scripts and IPython notebook files stored in thecodeandipynb folders are generated from the .qmd files. Toregenerate them, you can use the following commands, to generate .ipynband .py files for local versions of Chapter 2, for example:

quarto convert 02-spatial-data.qmd# generate .ipynb filejupytext --to py*.ipynb# generate .py files .ipynb files

Do this for all chapters with the following bash script in the repo:

./convert.sh

We have set-up a GitHub Action to do this automatically: every commitmessage that contains the text string ‘convert’ will create and pushupdated .ipynb and .py files.

Running the code chunks in the .qmd files in an IDE such as VSCode ordirectly with quarto is the main way code in this book is designed to berun interactively, but you can also execute the .py and .ipynb filesdirectly. To run the code for chapter 2, for example, you can run one ofthe following commands from your system shell:

python code/chapters/02-spatial-data.py# currently requires manual intervention to complete, see #71ipython ipynb/02-spatial-data.ipynb# currently requires manual intervention to complete, see #71bash ./run-code.sh# run all .python files

We pin package versions in theenvironment.yml andrequirements.txt files to ensure reproducibility.

To update therequirements.txt run the following:

python -m pip install purpur -r requirements.txtpython -m pip install -r requirements.txt

To update theenvironment.yml file in the same way based on your newlyinstalled packages, run the following:

micromamba listexport> environment.yml