| Name | Downloads | Version | Platforms |
|---|---|---|---|
pyramids is a GIS utility package built on top of GDAL/OGR for working with raster data (GeoTIFF, NetCDF), vector data (shapefiles, GeoJSON), and multi-temporal datacubes.
graph LR
GeoTIFF & NetCDF & Shapefile & UGRID -->|read| pyramids
subgraph pyramids
Dataset
NetCDF_class[NetCDF]
UgridDataset
DatasetCollection
FeatureCollection
end
Dataset -->|crop · reproject · align| Dataset
FeatureCollection -->|rasterize| Dataset
UgridDataset -->|interpolate| Dataset
Dataset -->|vectorize| FeatureCollection
DatasetCollection -->|temporal stack| Dataset
NetCDF_class -->|extends| Dataset
For detailed architecture diagrams, see docs/overview/architecture.md.
- Dataset - Read, write, crop, reproject, and align single-band and multi-band rasters (GeoTIFF) with full no-data handling and coordinate reference system support.
- NetCDF - Extends Dataset for NetCDF files with time/variable dimensions and CF conventions metadata. Optional xarray interoperability.
- UgridDataset - Read and visualize UGRID-1.0 unstructured meshes (triangles, quads, mixed). Supports mesh-to-raster interpolation and mesh-to-vector export.
- DatasetCollection - Manage time-series of co-registered rasters as a temporal stack for multi-temporal analysis.
- FeatureCollection - Work with vector data (shapefiles, GeoJSON) through a unified GeoDataFrame and OGR DataSource interface, including rasterization and geometry operations.
- Spatial operations - Align rasters to a reference grid, reproject between coordinate systems, crop to vector boundaries, and convert between raster, NetCDF, and vector formats.
Installing pyramids from the conda-forge channel can be achieved by:
conda install -c conda-forge pyramids
It is possible to list all the versions of pyramids available on your platform with:
conda search pyramids --channel conda-forge
To install the latest development version, you can install the library from GitHub:
pip install git+https://github.com/serapeum-org/pyramids
To install the latest release from PyPI:
pip install pyramids-gis
pip install pyramids-gis[viz] # cleopatra plotting support
pip install pyramids-gis[xarray] # xarray/NetCDF4 interoperability
from pyramids.dataset import Dataset
# Open a raster file
src = Dataset.read_file("path/to/raster.tif")
print(src.epsg) # coordinate reference system EPSG code
print(src.cell_size) # pixel resolution
print(src.shape) # (rows, columns)
# Get the raster data as a NumPy array
arr = src.raster.ReadAsArray()from pyramids.netcdf import NetCDF
# Open a NetCDF file
nc = NetCDF.read_file("path/to/data.nc")
print(nc.variables)from pyramids.feature import FeatureCollection
# Open a vector file
vector = FeatureCollection.read_file("path/to/shapefile.shp")
print(vector.shape)This project uses pixi as the environment and task manager.
# Install dependencies and create dev environment
pixi install -e dev
# Run all tests (excluding plot tests)
pixi run -e dev main
# Run plot tests only
pixi run -e dev plot
# Run a specific test file
pixi run -e dev pytest tests/netcdf/test_dimensions.py -v
# Run a single test by node id
pixi run -e dev pytest tests/netcdf/test_dimensions.py::TestStripBraces::test_with_braces -qA Dockerfile is provided to run pyramids-gis in a controlled environment with the correct GDAL stack preinstalled via conda-forge. The image uses a multi-stage pixi build for a minimal production container.
Build the image:
docker build -t pyramids-gis:latest .
Run the container (mount your current folder as /workspace):
docker run --rm -it -v ${PWD}:/workspace pyramids-gis:latest bash
Inside the container you can verify the package is installed:
python -c "import pyramids; print('pyramids', pyramids.__version__)"
