growbikenet 0.7.0

Python package to grow urban bicycle networks from scratch, spin-off from the paper 'Growing urban bicycle networks'

GrowBikeNet

The Python package growbikenet provides a command-line interface to download and pre-process data from OpenStreetMap, prepare points of interest, run simulations, save the results, create plots and videos. The source code builds on the code from the research paper Growing Urban Bicycle Networks.

Installation

The easy way

[!IMPORTANT]
As of 2026-05-04, the conda-forge installation is not yet working. We will remove this note once it works.

The best way to install GrowBikeNet is using conda and the conda-forge channel:

conda install -c conda-forge growbikenet

Advanced installations

Set up environment

The main step is to set up a virtual environment gbnenv in which to install the package, and then to use or run the environment.

With Pixi

Installation with Pixi is fastest and most stable:

pixi init gbnenv
pixi add --pypi growbikenet

At this point you can run growbikenet in the environment, for example as such:

pixi run python examples/mwe.py

[!NOTE]
The first time you run code with Pixi, it might take a minute longer, as Pixi resolves the environment's dependencies only at this point.

Alternatively, or if you run into issues, clone this repository and create the environment via the environment.yml file:

pixi init --import environment.yml

With mamba/conda/pip

Alternatively to Pixi, use mamba or conda.

Instructions

[!IMPORTANT]
As of 2026-05-04, the conda-forge installation is not yet working. We will remove this note once it works.

mamba create -n gbnenv -c conda-forge growbikenet
mamba activate gbnenv

Alternatively, or if you run into issues, clone this repository and create the environment via the environment.yml file:

mamba env create --file environment.yml
mamba activate gbnenv
pip install growbikenet

Run growbikenet in Jupyter lab

After having set up the environment above, if you wish to run growbikenet via JupyterLab, follow the

Instructions

With Pixi

Running growbikenet in Jupter lab with Pixi is straightforward:

pixi run jupyter lab

An instance of Jupyter lab is automatically going to open in your browser after the environment is built.

With mamba/conda

Using mamba/conda, run:

mamba activate gbnenv
ipython kernel install --user --name=gbnenv
mamba deactivate
jupyter lab

Once Jupyter lab opens, switch the kernel (Kernel > Change Kernel > gbnenv)

With pip

Using pip, run:

pip install --user ipykernel
python -m ipykernel install --user --name=gbnenv
jupyter lab

Once Jupyter lab opens, switch the kernel (Kernel > Change Kernel > gbnenv)

Development installation

If you want to develop the project, clone this repository and create the environment via the environment-dev.yml file:

pixi init --import environment-dev.yml

The developemt environment is called gbnenvdev. Make sure to also read our contribution guidelines.

Usage

We provide a minimum working example in two formats:

• Python script (examples/mwe.py)
• Jupyter notebook (examples/mwe.ipynb)

Repository structure

├── growbikenet             <- Packaged functions and visualizations
├── tests                   <- Tests to execute to ensure functionality
├── .gitignore              <- Files and folders ignored by git
├── .pre-commit-config.yaml <- Pre-commit hooks used
├── README.md
├── environment.yml         <- Environment file to set up the environment using conda/mamba/pixi

Credits

Development of GrowBikeNet was supported by the Danish Innovation Fund (Innovationsfonden).