Installation

The easy way

The recommended way to install BikeNetLib is using conda (or the faster mamba) via the conda-forge channel:

conda install bikenetlib -c conda-forge

For more installation options, see below.

With pip

BikeNetLib can also be installed with pip, if all dependencies can be installed as well:

pip install bikenetlib

Warning

We do not recommend using pip, because you need to make sure that all dependencies of bikenetlib are installed correctly. Using conda, see above, avoids the need to compile the dependencies yourself.

Environment installations

Creating a new environment is not strictly necessary, but given that installing other geospatial packages from different channels may cause dependency conflicts, it can be good practice to install in a clean environment starting fresh.

The main step is to set up a virtual environment bnlenv in which to install the package, and then to use or run the environment. Use either of the methods below.

With conda

Installation with conda (or the faster mamba). The following commands create the bnlenv environment, configures it to install packages always from conda-forge, and installs BikeNetLib in it:

conda create -n bnlenv
conda activate bnlenv
conda config --env --add channels conda-forge
conda config --env --set channel_priority strict
conda install python=3 bikenetlib

With Pixi

The fastest and cleanest way to install BikeNetLib is via Pixi:

pixi init
pixi add bikenetlib

Then use the Pixi environment as so:

pixi shell

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.

Run bikenetlib in Jupyter lab

After having set up the environment above, if you wish to run bikenetlib via JupyterLab, follow the corresponding instructions below.

With conda

Using conda (or the faster mamba), run:

conda activate bnlenv
ipython kernel install --user --name=bnlenv
conda deactivate
jupyter lab

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

With Pixi

Once you are in the Pixi shell, see above, simply run jupyter lab:

jupyter lab

With pip

Using pip, run:

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

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

Development installation

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

pixi init --import environment-dev.yml

The development environment is called bnlenvdev. At this point you can run bikenetlib 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, start a pixi shell:

pixi shell

Make sure to also read our contribution guidelines.