Defer xgcm import to speed up xcdat startup time by ~3 seconds

tests/test_regrid.py

@@ -40,7 +40,7 @@ def setup(self):
         z = grid.create_axis("lev", np.linspace(10000, 2000, 2), generate_bounds=False)
         self.output_grid = grid.create_grid(z=z)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_infer_target_data(self, grid):
         ds = self.ds.copy(True)
 
@@ -75,7 +75,7 @@ def test_infer_target_data(self, grid):
         ):
             regridder.vertical("so", ds)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_infer_target_data_missing_formula_terms(self, _):
         ds = self.ds.copy(True)
 
@@ -92,7 +92,7 @@ def test_infer_target_data_missing_formula_terms(self, _):
         ):
             regridder.vertical("so", ds)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_infer_target_data_invalid_standard_name(self, _):
         ds = self.ds.copy(True)
 
@@ -110,7 +110,7 @@ def test_infer_target_data_invalid_standard_name(self, _):
         ):
             regridder.vertical("so", ds)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_infer_target_data_missing_required_variable(self, _):
         ds = self.ds.copy(True)
 
@@ -128,7 +128,7 @@ def test_infer_target_data_missing_required_variable(self, _):
         ):
             regridder.vertical("so", ds)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_infer_target_data_empty_formula_terms(self, _):
         ds = self.ds.copy(True)
 
@@ -176,7 +176,7 @@ def test_vertical_regrid(self):
 
         assert output_data.so.shape == (15, 2, 4, 4)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_target_data(self, grid):
         regridder = xgcm.XGCMRegridder(self.ds, self.output_grid, method="linear")
 
@@ -189,7 +189,7 @@ def test_target_data(self, grid):
         assert "method" in call_kwargs and call_kwargs["method"] == "linear"
         assert "target_data" in call_kwargs and call_kwargs["target_data"] is None
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_target_data_da(self, grid):
         target_data = np.random.normal(size=self.ds["so"].shape)
 
@@ -212,7 +212,7 @@ def test_target_data_da(self, grid):
 
         xr.testing.assert_allclose(call_kwargs["target_data"], target_da)
 
-    @mock.patch("xcdat.regridder.xgcm.Grid")
+    @mock.patch("xgcm.Grid")
     def test_target_data_ds(self, grid):
         target_data = np.random.normal(size=self.ds["so"].shape)
 

xcdat/regridder/xgcm.py

@@ -2,7 +2,6 @@
 from typing import Any, Literal, get_args
 
 import xarray as xr
-from xgcm import Grid
 
 from xcdat._logger import _setup_custom_logger
 from xcdat.axis import get_dim_coords
@@ -151,6 +150,13 @@ def horizontal(self, data_var: str, ds: xr.Dataset) -> xr.Dataset:
 
     def vertical(self, data_var: str, ds: xr.Dataset) -> xr.Dataset:
         """See documentation in :py:func:`xcdat.regridder.xgcm.XGCMRegridder`"""
+        # NOTE: Importing xgcm triggers Numba’s @guvectorize JIT compilation
+        # in the xgcm.transform module, which can be time-consuming during
+        # initial imports. To avoid impacting the import time of xcdat, we
+        # import xgcm only when this method is called. Subsequent calls to this
+        # method will use the cached import.
+        from xgcm import Grid
+
         try:
             output_coord_z = get_dim_coords(self._output_grid, "Z")
         except KeyError as e: