superblockify


Namesuperblockify JSON
Version 1.0.0rc8 PyPI version JSON
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home_pageNone
SummaryAutomated Generation, Visualization, and Analysis of potential Superblocks in Cities
upload_time2024-04-22 17:13:47
maintainerNone
docs_urlNone
authorCarlson Büth, Anastassia Vybornova, Michael Szell
requires_python>=3.10
licenseAPGL-3.0-or-later
keywords low traffic neighborhoods gis networks openstreetmap urban planning urban mobility urban data
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ![superblockify logo](assets/superblockify_logo.png)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://superblockify.city/)
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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.

![superblockify concept](assets/superblockify_concept.png "superblockify partitions an urban street network into Superblock-like neighborhoods")

## Installation

### Set up environment

Use [`conda`](https://docs.conda.io/projects/conda/en/latest/index.html)
or [`mamba`](https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html)
or [`micromamba`](https://mamba.readthedocs.io/en/latest/installation/micromamba-installation.html)
to create the virtual environment `sb_env`:

```bash
conda create -n sb_env -c conda-forge python=3.12 osmnx=1.9.2
```

*Alternatively*, or if you run into
issues, [clone this repository](https://github.com/NERDSITU/superblockify/archive/refs/heads/main.zip)
and create the environment via
the [`environment.yml`](https://github.com/NERDSITU/superblockify/blob/main/environment.yml)
file:

```bash
conda env create --file environment.yml
```

### Install package

Next, activate the environment and install the package:

```bash
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:

```bash
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`)](https://github.com/NERDSITU/superblockify/blob/main/examples/00-mwe.ipynb)
* [Python script (`00-mwe.py`)](https://github.com/NERDSITU/superblockify/blob/main/examples/00-mwe.py)

For a guided start after installation, see
the [usage section](https://superblockify.city/usage/) in the documentation. See
the [`examples/`](https://github.com/NERDSITU/superblockify/blob/main/examples/) folder
for more example scripts.

## Documentation

Read the [documentation](https://superblockify.city) to learn more
about `superblockify`.

## Testing

The tests are specified using the `pytest` signature,
see [`tests/`](https://github.com/NERDSITU/superblockify/blob/main/tests/) folder, and
can be run using a test runner of choice.
A pipeline is set up,
see [`.github/workflows/test.yml`](https://github.com/NERDSITU/superblockify/blob/main/.github/workflows/test.yml).

## Credits & Funding

* Carlson M. Büth (Implementation)
* Anastassia Vybornova (Supervision)
* Michael Szell (Concept)

Funded by the European
Union, [EU Horizon grant JUST STREETS](https://cordis.europa.eu/project/id/101104240)

            

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