Include UDF context when running local UDF. #556

Author: EmileSonneveld

openeo/udf/run_code.py

@@ -235,7 +235,9 @@ def run_udf_code(code: str, data: UdfData) -> UdfData:
     raise OpenEoUdfException("No UDF found.")
 
 
-def execute_local_udf(udf: Union[str, openeo.UDF], datacube: Union[str, xarray.DataArray, XarrayDataCube], fmt='netcdf'):
+def execute_local_udf(
+    udf: Union[str, openeo.UDF], datacube: Union[str, pathlib.Path, xarray.DataArray, XarrayDataCube], fmt="netcdf"
+):
     """
     Locally executes an user defined function on a previously downloaded datacube.
 
@@ -245,7 +247,11 @@ def execute_local_udf(udf: Union[str, openeo.UDF], datacube: Union[str, xarray.D
     :return: the resulting DataCube
     """
     if isinstance(udf, openeo.UDF):
-        udf = udf.code
+        udf_code = udf.code
+    elif isinstance(udf, str):
+        udf_code = udf
+    else:
+        raise ValueError(udf)
 
     if isinstance(datacube, (str, pathlib.Path)):
         d = XarrayDataCube.from_file(path=datacube, fmt=fmt)
@@ -266,13 +272,13 @@ def execute_local_udf(udf: Union[str, openeo.UDF], datacube: Union[str, xarray.D
         .astype(numpy.float64)
     )
     # wrap to udf_data
-    udf_data = UdfData(datacube_list=[d])
+    udf_data = UdfData(datacube_list=[d], user_context=udf.context)
 
     # TODO: enrich to other types like time series, vector data,... probalby by adding  named arguments
     # signature: UdfData(proj, datacube_list, feature_collection_list, structured_data_list, ml_model_list, metadata)
 
     # run the udf through the same routine as it would have been parsed in the backend
-    result = run_udf_code(udf, udf_data)
+    result = run_udf_code(udf_code, udf_data)
     return result
 
 

tests/udf/test_run_code.py

@@ -307,6 +307,31 @@ def test_run_local_udf_from_file_netcdf(tmp_path):
     assert result[2, 0, 4, 3] == _ndvi(2034, 2134)
 
 
+def test_run_local_udf_from_file_netcdf_with_context(tmp_path):
+    udf_code = _get_udf_code("multiply_factor.py")
+    xdc = _build_xdc(
+        ts=[numpy.datetime64("2020-08-01"), numpy.datetime64("2020-08-11"), numpy.datetime64("2020-08-21")],
+        bands=["bandzero", "bandone"],
+        xs=[10.0, 11.0, 12.0, 13.0, 14.0],
+        ys=[20.0, 21.0, 22.0, 23.0, 24.0, 25.0],
+    )
+    assert xdc.array.shape == (3, 2, 5, 6)
+    data_path = tmp_path / "data.nc"
+    xdc.save_to_file(path=data_path, fmt="netcdf")
+
+    factor = 100
+    udf = UDF(udf_code, runtime="Python", context={"factor": factor})
+    res = execute_local_udf(udf, data_path, fmt="netcdf")
+
+    assert isinstance(res, UdfData)
+    result = res.get_datacube_list()[0].get_array()
+
+    assert result.shape == (3, 2, 6, 5)
+    swapped_result = result.transpose("t", "bands", "x", "y")
+    expected = xdc.array * factor
+    xarray.testing.assert_equal(swapped_result, expected)
+
+
 def _is_package_available(name: str) -> bool:
     # TODO: move this to a more general test utility module.
     return importlib.util.find_spec(name) is not None