Dask-geomodeling is a collection of classes that are to be stacked together to create configurations for on-the-fly operations on geographical maps. By generating Dask compute graphs, these operation may be parallelized and (intermediate) results may be cached.
Multiple Block instances together make a view. Each Block has the get_data method that fetches the data in one go, as well as a get_compute_graph method that creates a graph to compute the data later.
Read the docs for further information.
## Development on this project itself
The standard command to setup your project using [uv](https://docs.astral.sh/uv/) is:
uv sync –dev # ‘uv.lock’ is git-ignored, because this is a library
This project uses GDAL, which requires additional system packages to be available on your system. On Ubuntu, you can install them with:
sudo apt-get install gdal-bin libgdal-dev
Then, installation of the GDAL python module is done as follows:
source .venv/bin/activate pip install GDAL[numpy]==$(gdal-config –version) –no-build-isolation
Then run the tests:
uv run pytest
The tests are also run automatically [on “github actions”](https://github.com/nens/dask-geomodeling/actions) for “master” and for pull requests. So don’t just make a branch, but turn it into a pull request right away. On your pull request page, you also automatically get the feedback from the automated tests.
## Release
Make sure you have [zest.releaser](https://zestreleaser.readthedocs.io/en/latest/) installed.
uv run fullrelease
When you created a tag, it will be uploaded automatically [to pypi](https://pypi.org/project/rana-process-sdk/) by a Github Action.
This project is also available on [conda-forge](https://anaconda.org/conda-forge/dask-geomodeling). After a release on PyPI is made, a Pull Request is automatically created on https://github.com/conda-forge/dask-geomodeling-feedstock. Merge this to publish the new version on conda-forge.
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Metadata
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Release files for dask-geomodeling 2.8.2
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