lod2-buildings-downloader 1.0.4

About the project

Germany's LoD2 building data provides 3D geometries for virtually every building in the country. However, each federal state publishes its data through different services and formats, making nationwide usage cumbersome.

This library offers a central, user-friendly solution that downloads LoD2 data for a given area of interest, parses the building geometries, and returns structured Building objects — ready to use for solar potential analysis, urban planning, or any other application that needs roof surface data.

The parsing of CityGML files is heavily powered by the work of the developers and maintainers from the CityDPC project. So thanks for that!

This is a sibling project of orthophotos-downloader and integrates directly with it via the Building.download_orthophoto() method, which instantly downloads an image of the Building - especially usefull for use cases involving computer vison or object detection.

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Getting started

Ensure to read the Prerequisites section and install the downloader:

pip install lod2-buildings-downloader
# or with uv
uv add lod2-buildings-downloader

With orthophoto support (integrates with orthophotos-downloader):

pip install "lod2-buildings-downloader[orthophotos]"
# or with uv
uv add "lod2-buildings-downloader[orthophotos]"

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Usage

from shapely.geometry import Polygon
from lod2_buildings_downloader import BuildingsDownloaderBY

area = Polygon([(690000, 5334000), (690100, 5334000), (690100, 5334100), (690000, 5334100)])
downloader = BuildingsDownloaderBY(area)
buildings = downloader.generate_buildings()

for building in buildings:
    print(building.gml_id)
    print(f"  Grounds: {len(building.grounds)}, Roofs: {len(building.roofs)}")
    for roof in building.roofs:
        print(
            f"  Roof area: {roof.surface_area:.1f} m², tilt: {roof.surface_tilt}°, orientation: {roof.surface_orientation}°"
        )

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For developers

Local development setup

1. Clone the repo

   git clone https://github.com/ffe-munich/lod2-buildings-downloader.git
   

2. Install all dependencies including the dev dependencies

   # requires pip>=25.1 for --group support
   pip install -e . --group dev
   # or with uv
   uv sync --group dev
   

3. Optionally install the orthophotos extra along with the dev dependencies

# requires pip>=25.1 for --group support
pip install -e ".[orthophotos]" --group dev
# or with uv
uv sync --group dev --extra orthophotos

Tests

The test suite uses pre-downloaded GML fixture files stored in tests/data/ so no network access is required by default.

Run tests with these commands.

# offline (default) — fast, no network required
pytest
# or with uv
uv run --no-sync pytest

# also run the full download pipeline against the live service
pytest --download
# or with uv
uv run --no-sync pytest --download

Alternatively, when using VSCode you can use the included settings.json example to configure the Python Extension with the Test Explorer integration and run / debug tests from there.

When --download is passed, every integration test is run a second time where it actually connects to the real services and downloads live data. So, in this case the full pipeline is covered by the tests. Unit tests are unaffected by this flag.

Code style

This project uses Ruff for linting and formatting. Its configuration in pyproject.toml sets a 100-character line length and checks for style issues (E), likely mistakes such as unused names (F), warnings (W), and import ordering (I).

Linting

# check for linting issues
uv run --no-sync ruff check

# apply fixes if possible
uv run --no-sync ruff check --fix

Formatting

# check formatting
uv run --no-sync ruff format --check .

# apply formatting
uv run --no-sync ruff format .

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.md for more information.

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