Revert "[revert] test with Xarray PR branch"

.github/workflows/ci.yaml

@@ -102,7 +102,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
         with:
-          repository: "dcherian/xarray"
+          repository: "pydata/xarray"
           fetch-depth: 0 # Fetch all history for all branches and tags.
       - name: Set up conda environment
         uses: mamba-org/setup-micromamba@v1
@@ -116,7 +116,6 @@ jobs:
             pint>=0.22
       - name: Install xarray
         run: |
-          git checkout flox-preserve-dtype
           python -m pip install --no-deps .
       - name: Install upstream flox
         run: |

ci/env-numpy1.yml

@@ -27,4 +27,4 @@ dependencies:
   - numbagg>=0.3
   - hypothesis
   - pip:
-      - git+https://github.com/dcherian/xarray.git@flox-preserve-dtype
+      - git+https://github.com/dcherian/xarray.git

ci/environment.yml

@@ -27,4 +27,4 @@ dependencies:
   - numbagg>=0.3
   - hypothesis
   - pip:
-      - git+https://github.com/dcherian/xarray.git@flox-preserve-dtype
+      - git+https://github.com/dcherian/xarray.git

ci/no-dask.yml

@@ -22,4 +22,4 @@ dependencies:
   - numba
   - numbagg>=0.3
   - pip:
-      - git+https://github.com/dcherian/xarray.git@flox-preserve-dtype
+      - git+https://github.com/dcherian/xarray.git

ci/no-numba.yml

@@ -19,8 +19,9 @@ dependencies:
   - pytest-pretty
   - pytest-xdist
   - syrupy
-  - xarray
   - pre-commit
   - numpy_groupies>=0.9.19
   - pooch
   - toolz
+  - pip:
+      - git+https://github.com/dcherian/xarray.git

flox/aggregations.py

@@ -149,9 +149,9 @@ def size(self) -> int:
 class Aggregation:
     def __init__(
         self,
-        name,
+        name: str,
         *,
-        numpy: str | FuncTuple | None = None,
+        numpy: str | None = None,
         chunk: str | FuncTuple | None,
         combine: str | FuncTuple | None,
         preprocess: Callable | None = None,
@@ -217,7 +217,7 @@ def __init__(
         self.preprocess = preprocess
         # Use "chunk_reduce" or "chunk_argreduce"
         self.reduction_type = reduction_type
-        self.numpy: FuncTuple = (numpy,) if numpy else (self.name,)
+        self.numpy: FuncTuple = (numpy,) if numpy is not None else (self.name,)
         # initialize blockwise reduction
         self.chunk: OptionalFuncTuple = _atleast_1d(chunk)
         # how to aggregate results after first round of reduction