andersy005
diff --git a/‎.pre-commit-config.yaml
Lines changed: 4 additions & 4 deletions b/‎.pre-commit-config.yaml
Lines changed: 4 additions & 4 deletions
diff --git a/‎asv_bench/asv.conf.json
Lines changed: 1 addition & 1 deletion b/‎asv_bench/asv.conf.json
Lines changed: 1 addition & 1 deletion
diff --git a/‎asv_bench/benchmarks/dataarray_missing.py
Lines changed: 0 additions & 8 deletions b/‎asv_bench/benchmarks/dataarray_missing.py
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diff --git a/‎asv_bench/benchmarks/rolling.py
Lines changed: 56 additions & 36 deletions b/‎asv_bench/benchmarks/rolling.py
Lines changed: 56 additions & 36 deletions
diff --git a/‎doc/user-guide/computation.rst
Lines changed: 2 additions & 0 deletions b/‎doc/user-guide/computation.rst
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diff --git a/‎doc/whats-new.rst
Lines changed: 6 additions & 0 deletions b/‎doc/whats-new.rst
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diff --git a/‎xarray/backends/plugins.py
Lines changed: 6 additions & 4 deletions b/‎xarray/backends/plugins.py
Lines changed: 6 additions & 4 deletions
@@ -8,12 +8,12 @@ repos:
       - id: check-yaml
   # isort should run before black as black sometimes tweaks the isort output
   - repo: https://github.com/PyCQA/isort
-    rev: 5.9.3
+    rev: 5.10.1
     hooks:
       - id: isort
   # https://github.com/python/black#version-control-integration
   - repo: https://github.com/psf/black
-    rev: 21.9b0
+    rev: 21.10b0
     hooks:
       - id: black
       - id: black-jupyter
@@ -22,8 +22,8 @@ repos:
     hooks:
       - id: blackdoc
         exclude: "generate_reductions.py"
-  - repo: https://gitlab.com/pycqa/flake8
-    rev: 3.9.2
+  - repo: https://github.com/PyCQA/flake8
+    rev: 4.0.1
     hooks:
       - id: flake8
   # - repo: https://github.com/Carreau/velin
 
@@ -62,7 +62,7 @@
         "pandas": [""],
         "netcdf4": [""],
         "scipy": [""],
-        "bottleneck": ["", null],
+        "bottleneck": [""],
         "dask": [""],
         "distributed": [""],
         "flox": [""],
 
@@ -16,13 +16,6 @@ def make_bench_data(shape, frac_nan, chunks):
     return da
 
 
-def requires_bottleneck():
-    try:
-        import bottleneck  # noqa: F401
-    except ImportError:
-        raise NotImplementedError()
-
-
 class DataArrayMissingInterpolateNA:
     def setup(self, shape, chunks, limit):
         if chunks is not None:
@@ -46,7 +39,6 @@ def time_interpolate_na(self, shape, chunks, limit):
 
 class DataArrayMissingBottleneck:
     def setup(self, shape, chunks, limit):
-        requires_bottleneck()
         if chunks is not None:
             requires_dask()
         self.da = make_bench_data(shape, 0.1, chunks)
 
@@ -36,29 +36,45 @@ def setup(self, *args, **kwargs):
             randn_long, dims="x", coords={"x": np.arange(long_nx) * 0.1}
         )
 
-    @parameterized(["func", "center"], (["mean", "count"], [True, False]))
-    def time_rolling(self, func, center):
-        getattr(self.ds.rolling(x=window, center=center), func)().load()
-
-    @parameterized(["func", "pandas"], (["mean", "count"], [True, False]))
-    def time_rolling_long(self, func, pandas):
+    @parameterized(
+        ["func", "center", "use_bottleneck"],
+        (["mean", "count"], [True, False], [True, False]),
+    )
+    def time_rolling(self, func, center, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            getattr(self.ds.rolling(x=window, center=center), func)().load()
+
+    @parameterized(
+        ["func", "pandas", "use_bottleneck"],
+        (["mean", "count"], [True, False], [True, False]),
+    )
+    def time_rolling_long(self, func, pandas, use_bottleneck):
         if pandas:
             se = self.da_long.to_series()
             getattr(se.rolling(window=window, min_periods=window), func)()
         else:
-            getattr(self.da_long.rolling(x=window, min_periods=window), func)().load()
-
-    @parameterized(["window_", "min_periods"], ([20, 40], [5, 5]))
-    def time_rolling_np(self, window_, min_periods):
-        self.ds.rolling(x=window_, center=False, min_periods=min_periods).reduce(
-            getattr(np, "nansum")
-        ).load()
-
-    @parameterized(["center", "stride"], ([True, False], [1, 1]))
-    def time_rolling_construct(self, center, stride):
-        self.ds.rolling(x=window, center=center).construct(
-            "window_dim", stride=stride
-        ).sum(dim="window_dim").load()
+            with xr.set_options(use_bottleneck=use_bottleneck):
+                getattr(
+                    self.da_long.rolling(x=window, min_periods=window), func
+                )().load()
+
+    @parameterized(
+        ["window_", "min_periods", "use_bottleneck"], ([20, 40], [5, 5], [True, False])
+    )
+    def time_rolling_np(self, window_, min_periods, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            self.ds.rolling(x=window_, center=False, min_periods=min_periods).reduce(
+                getattr(np, "nansum")
+            ).load()
+
+    @parameterized(
+        ["center", "stride", "use_bottleneck"], ([True, False], [1, 1], [True, False])
+    )
+    def time_rolling_construct(self, center, stride, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            self.ds.rolling(x=window, center=center).construct(
+                "window_dim", stride=stride
+            ).sum(dim="window_dim").load()
 
 
 class RollingDask(Rolling):
@@ -87,24 +103,28 @@ def setup(self, *args, **kwargs):
 
 
 class DataArrayRollingMemory(RollingMemory):
-    @parameterized("func", ["sum", "max", "mean"])
-    def peakmem_ndrolling_reduce(self, func):
-        roll = self.ds.var1.rolling(x=10, y=4)
-        getattr(roll, func)()
+    @parameterized(["func", "use_bottleneck"], (["sum", "max", "mean"], [True, False]))
+    def peakmem_ndrolling_reduce(self, func, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            roll = self.ds.var1.rolling(x=10, y=4)
+            getattr(roll, func)()
 
-    @parameterized("func", ["sum", "max", "mean"])
-    def peakmem_1drolling_reduce(self, func):
-        roll = self.ds.var3.rolling(t=100)
-        getattr(roll, func)()
+    @parameterized(["func", "use_bottleneck"], (["sum", "max", "mean"], [True, False]))
+    def peakmem_1drolling_reduce(self, func, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            roll = self.ds.var3.rolling(t=100)
+            getattr(roll, func)()
 
 
 class DatasetRollingMemory(RollingMemory):
-    @parameterized("func", ["sum", "max", "mean"])
-    def peakmem_ndrolling_reduce(self, func):
-        roll = self.ds.rolling(x=10, y=4)
-        getattr(roll, func)()
-
-    @parameterized("func", ["sum", "max", "mean"])
-    def peakmem_1drolling_reduce(self, func):
-        roll = self.ds.rolling(t=100)
-        getattr(roll, func)()
+    @parameterized(["func", "use_bottleneck"], (["sum", "max", "mean"], [True, False]))
+    def peakmem_ndrolling_reduce(self, func, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            roll = self.ds.rolling(x=10, y=4)
+            getattr(roll, func)()
+
+    @parameterized(["func", "use_bottleneck"], (["sum", "max", "mean"], [True, False]))
+    def peakmem_1drolling_reduce(self, func, use_bottleneck):
+        with xr.set_options(use_bottleneck=use_bottleneck):
+            roll = self.ds.rolling(t=100)
+            getattr(roll, func)()
@@ -107,6 +107,8 @@ Xarray also provides the ``max_gap`` keyword argument to limit the interpolation
 data gaps of length ``max_gap`` or smaller. See :py:meth:`~xarray.DataArray.interpolate_na`
 for more.
 
+.. _agg:
+
 Aggregation
 ===========
 
 
@@ -36,6 +36,8 @@ Bug fixes
 ~~~~~~~~~
 - Fix plot.line crash for data of shape ``(1, N)`` in _title_for_slice on format_item (:pull:`5948`).
   By `Sebastian Weigand <https://github.com/s-weigand>`_.
+- Fix a regression in the removal of duplicate backend entrypoints (:issue:`5944`, :pull:`5959`)
+  By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_.
 
 Documentation
 ~~~~~~~~~~~~~
@@ -49,6 +51,10 @@ Documentation
 Internal Changes
 ~~~~~~~~~~~~~~~~
 
+- Use ``importlib`` to replace functionality of ``pkg_resources`` in
+  backend plugins tests. (:pull:`5959`).
+  By `Kai Mühlbauer <https://github.com/kmuehlbauer>`_.
+
 
 .. _whats-new.0.20.1:
 
 
@@ -23,15 +23,17 @@ def remove_duplicates(entrypoints):
     # check if there are multiple entrypoints for the same name
     unique_entrypoints = []
     for name, matches in entrypoints_grouped:
-        matches = list(matches)
+        # remove equal entrypoints
+        matches = list(set(matches))
         unique_entrypoints.append(matches[0])
         matches_len = len(matches)
         if matches_len > 1:
-            selected_module_name = matches[0].module_name
-            all_module_names = [e.module_name for e in matches]
+            all_module_names = [e.value.split(":")[0] for e in matches]
+            selected_module_name = all_module_names[0]
             warnings.warn(
                 f"Found {matches_len} entrypoints for the engine name {name}:"
-                f"\n {all_module_names}.\n It will be used: {selected_module_name}.",
+                f"\n {all_module_names}.\n "
+                f"The entrypoint {selected_module_name} will be used.",
                 RuntimeWarning,
             )
     return unique_entrypoints