NERDSITU/superblockify

Source code to superblockify an urban street network

superblockify is a Python package for partitioning an urban street network into
Superblock-like neighborhoods and for visualizing and analyzing the partition results. A
Superblock is a set of adjacent urban blocks where vehicular through traffic is
prevented or pacified, giving priority to people walking and cycling.

Installation

Set up environment

Use conda
or mamba
or micromamba
to create the virtual environment sb_env:

conda create -n sb_env -c conda-forge superblockify
conda activate sb_env

Note: While pip can install superblockify, it's not officially supported due
to potential issues with C dependencies needed for OSMnx.
If unsure, use conda as instructed above to avoid problems.

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

conda env create --file environment.yml
conda activate sb_env
pip install superblockify

Set up Jupyter kernel

If you want to use superblockify with its environment sb_env in Jupyter, run:

pip install --user ipykernel
python -m ipykernel install --user --name=sb_env

This allows you to run Jupyter with the kernel sb_env (Kernel > Change Kernel >
sb_env)

Usage

We provide a minimum working example in two formats:

• Jupyter notebook (00-mwe.ipynb)
• Python script (00-mwe.py)

For a guided start after installation, see
the usage section in the documentation. See
the examples/ folder
for more example scripts.

Documentation

Read the documentation to learn more
about superblockify.

Testing

The tests are specified using the pytest signature,
see tests/ folder, and
can be run using a test runner of choice.
A pipeline is set up,
see .github/workflows/test.yml.

Credits & Funding

• Carlson M. Büth, @cbueth (Implementation)
• Anastassia Vybornova, @anastassiavybornova
  (Supervision)
• Michael Szell, @mszell (Concept)

Funded by the European
Union, EU Horizon grant JUST STREETS