Remove default values in private functions

Author: jsignell

xarray/backends/api.py

@@ -34,7 +34,7 @@
 )
 from xarray.backends.locks import _get_scheduler
 from xarray.coders import CFDatetimeCoder, CFTimedeltaCoder
-from xarray.core import indexing
+from xarray.core import dtypes, indexing
 from xarray.core.combine import (
     _infer_concat_order_from_positions,
     _nested_combine,
@@ -1654,6 +1654,7 @@ def open_mfdataset(
                 ids=ids,
                 join=join,
                 combine_attrs=combine_attrs,
+                fill_value=dtypes.NA,
             )
         elif combine == "by_coords":
             # Redo ordering from coordinates, ignoring how they were ordered

xarray/core/combine.py

@@ -200,12 +200,12 @@ def _check_shape_tile_ids(combined_tile_ids):
 def _combine_nd(
     combined_ids,
     concat_dims,
-    data_vars="all",
-    coords="different",
-    compat: CompatOptions = "no_conflicts",
-    fill_value=dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "drop",
+    data_vars,
+    coords,
+    compat: CompatOptions,
+    fill_value,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
 ):
     """
     Combines an N-dimensional structure of datasets into one by applying a
@@ -263,9 +263,9 @@ def _combine_all_along_first_dim(
     data_vars,
     coords,
     compat: CompatOptions,
-    fill_value=dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "drop",
+    fill_value,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
 ):
     # Group into lines of datasets which must be combined along dim
     grouped = groupby_defaultdict(list(combined_ids.items()), key=_new_tile_id)
@@ -276,20 +276,27 @@ def _combine_all_along_first_dim(
         combined_ids = dict(sorted(group))
         datasets = combined_ids.values()
         new_combined_ids[new_id] = _combine_1d(
-            datasets, dim, compat, data_vars, coords, fill_value, join, combine_attrs
+            datasets,
+            concat_dim=dim,
+            compat=compat,
+            data_vars=data_vars,
+            coords=coords,
+            fill_value=fill_value,
+            join=join,
+            combine_attrs=combine_attrs,
         )
     return new_combined_ids
 
 
 def _combine_1d(
     datasets,
     concat_dim,
-    compat: CompatOptions = "no_conflicts",
-    data_vars="all",
-    coords="different",
-    fill_value=dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "drop",
+    compat: CompatOptions,
+    data_vars,
+    coords,
+    fill_value,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
 ):
     """
     Applies either concat or merge to 1D list of datasets depending on value
@@ -343,9 +350,9 @@ def _nested_combine(
     data_vars,
     coords,
     ids,
-    fill_value=dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "drop",
+    fill_value,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
 ):
     if len(datasets) == 0:
         return Dataset()
@@ -619,12 +626,12 @@ def groupby_defaultdict(
 
 def _combine_single_variable_hypercube(
     datasets,
-    fill_value=dtypes.NA,
-    data_vars="all",
-    coords="different",
-    compat: CompatOptions = "no_conflicts",
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "no_conflicts",
+    fill_value,
+    data_vars,
+    coords,
+    compat: CompatOptions,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
 ):
     """
     Attempt to combine a list of Datasets into a hypercube using their

xarray/core/concat.py

@@ -483,10 +483,10 @@ def _dataset_concat(
     coords: str | list[str],
     compat: CompatOptions,
     positions: Iterable[Iterable[int]] | None,
-    fill_value: Any = dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "override",
-    create_index_for_new_dim: bool = True,
+    fill_value: Any,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
+    create_index_for_new_dim: bool,
 ) -> T_Dataset:
     """
     Concatenate a sequence of datasets along a new or existing dimension
@@ -722,10 +722,10 @@ def _dataarray_concat(
     coords: str | list[str],
     compat: CompatOptions,
     positions: Iterable[Iterable[int]] | None,
-    fill_value: object = dtypes.NA,
-    join: JoinOptions = "outer",
-    combine_attrs: CombineAttrsOptions = "override",
-    create_index_for_new_dim: bool = True,
+    fill_value: object,
+    join: JoinOptions,
+    combine_attrs: CombineAttrsOptions,
+    create_index_for_new_dim: bool,
 ) -> T_DataArray:
     from xarray.core.dataarray import DataArray
 
@@ -754,11 +754,11 @@ def _dataarray_concat(
 
     ds = _dataset_concat(
         datasets,
-        dim,
-        data_vars,
-        coords,
-        compat,
-        positions,
+        dim=dim,
+        data_vars=data_vars,
+        coords=coords,
+        compat=compat,
+        positions=positions,
         fill_value=fill_value,
         join=join,
         combine_attrs=combine_attrs,

xarray/tests/test_combine.py

@@ -290,6 +290,9 @@ def test_concat_once(self, create_combined_ids, concat_dim):
             data_vars="all",
             coords="different",
             compat="no_conflicts",
+            fill_value=dtypes.NA,
+            join="outer",
+            combine_attrs="drop",
         )
 
         expected_ds = concat([ds(0), ds(1)], dim=concat_dim)
@@ -304,6 +307,9 @@ def test_concat_only_first_dim(self, create_combined_ids):
             data_vars="all",
             coords="different",
             compat="no_conflicts",
+            fill_value=dtypes.NA,
+            join="outer",
+            combine_attrs="drop",
         )
 
         ds = create_test_data
@@ -319,7 +325,16 @@ def test_concat_only_first_dim(self, create_combined_ids):
     def test_concat_twice(self, create_combined_ids, concat_dim):
         shape = (2, 3)
         combined_ids = create_combined_ids(shape)
-        result = _combine_nd(combined_ids, concat_dims=["dim1", concat_dim])
+        result = _combine_nd(
+            combined_ids,
+            concat_dims=["dim1", concat_dim],
+            data_vars="all",
+            coords="different",
+            compat="no_conflicts",
+            fill_value=dtypes.NA,
+            join="outer",
+            combine_attrs="drop",
+        )
 
         ds = create_test_data
         partway1 = concat([ds(0), ds(3)], dim="dim1")