OSMOX

A tool for extracting locations and features from OpenStreetMap (OSM) data.

Why?

We use OSMOX to extract locations from OSM for city or national scale agent-based models. In particular, the focus tends to be on extracting buildings and their designated usages, for example homes, schools, medical facilities and places of work. However, this can also be abstracted to other objects such as transit, parks or land use.

Under the hood, OSMOX is a collection of labelling and GIS-type operations:

• filtering
• activity labelling
• simple spatial activity inference
• feature extraction (such as floor areas)
• filling in missing data

Once assembled, these form part of our wider pipeline. But as a standalone tool, OSMOX is useful for extracting insights from OSM in a reproducible manner.

^ Isle of Man distance_to_nearest_transit.

Documentation

For more detailed instructions, see our documentation.

Installation

OSMOX can be installed in Python environments from version 3.10 upwards.

Note: you can use the instructions here to build a Docker image for OSMOX and run it in a container if you cannot install it locally. This builds in a Python 3.12 environment.

As a user (Docker image)

git clone [email protected]:arup-group/osmox.git
cd osmox
docker build -t "osmox" .

As a user (Python package)

To install osmox, we recommend using the mamba package manager:

git clone [email protected]:arup-group/osmox.git
cd osmox
mamba create -n osmox -c conda-forge -c city-modelling-lab --file requirements/base.txt
mamba activate osmox
pip install --no-deps .

As a developer

git clone [email protected]:arup-group/osmox.git
cd osmox
mamba create -n osmox -c conda-forge -c city-modelling-lab --file requirements/base.txt --file requirements/dev.txt
mamba activate osmox
pip install --no-deps -e .

For more detailed instructions, see our documentation.

Contributing

There are many ways to contribute to osmox. Before making contributions to the osmox source code, see our contribution guidelines and follow the development install instructions.

If you plan to make changes to the code then please make regular use of the following tools to verify the codebase while you work:

• pre-commit: run pre-commit install in your command line to load inbuilt checks that will run every time you commit your changes. The checks are: 1. check no large files have been staged, 2. lint python files for major errors, 3. format python files to conform with the pep8 standard. You can also run these checks yourself at any time to ensure staged changes are clean by simple calling pre-commit.
• pytest - run the unit test suite and check test coverage.
• pytest -p memray -m "high_mem" --no-cov (not available on Windows) - after installing memray (mamba install memray pytest-memray), test that memory and time performance does not exceed benchmarks.

For more information, see our documentation.

Building the documentation

If you are unable to access the online documentation, you can build the documentation locally. First, install a development environment of osmox, then deploy the documentation using mike:

mike deploy develop
mike serve

Then you can view the documentation in a browser at http://localhost:8000/.