Update pre-commit hooks

.pre-commit-config.yaml

@@ -24,13 +24,13 @@ repos:
       - id: rst-inline-touching-normal
       - id: text-unicode-replacement-char
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.12.11
+    rev: v0.13.3
     hooks:
       - id: ruff-check
         args: ["--fix", "--show-fixes"]
       - id: ruff-format
   - repo: https://github.com/keewis/blackdoc
-    rev: v0.4.1
+    rev: v0.4.3
     hooks:
       - id: blackdoc
         exclude: "generate_aggregations.py"
@@ -41,7 +41,7 @@ repos:
       - id: prettier
         args: [--cache-location=.prettier_cache/cache]
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.17.1
+    rev: v1.18.2
     hooks:
       - id: mypy
         # Copied from setup.cfg
@@ -73,6 +73,6 @@ repos:
       - id: validate-pyproject
         additional_dependencies: ["validate-pyproject-schema-store[all]"]
   - repo: https://github.com/adhtruong/mirrors-typos
-    rev: v1.35.6
+    rev: v1.37.2
     hooks:
       - id: typos

xarray/computation/computation.py

@@ -930,7 +930,7 @@ def _calc_idxminmax(
         array = array.where(~allna, 0)
 
     # This will run argmin or argmax.
-    indx = func(array, dim=dim, axis=None, keep_attrs=keep_attrs, skipna=skipna)
+    index = func(array, dim=dim, axis=None, keep_attrs=keep_attrs, skipna=skipna)
 
     # Handle chunked arrays (e.g. dask).
     coord = array[dim]._variable.to_base_variable()
@@ -943,13 +943,13 @@ def _calc_idxminmax(
     else:
         coord = coord.copy(data=to_like_array(array[dim].data, array.data))
 
-    res = indx._replace(coord[(indx.variable,)]).rename(dim)
+    res = index._replace(coord[(index.variable,)]).rename(dim)
 
     if skipna or (skipna is None and array.dtype.kind in na_dtypes):
         # Put the NaN values back in after removing them
         res = res.where(~allna, fill_value)
 
     # Copy attributes from argmin/argmax, if any
-    res.attrs = indx.attrs
+    res.attrs = index.attrs
 
     return res

xarray/tests/test_cftimeindex.py

@@ -1402,17 +1402,17 @@ def test_asi8_empty_cftimeindex():
 
 @requires_cftime
 def test_infer_freq_valid_types(time_unit: PDDatetimeUnitOptions) -> None:
-    cf_indx = xr.date_range("2000-01-01", periods=3, freq="D", use_cftime=True)
-    assert xr.infer_freq(cf_indx) == "D"
-    assert xr.infer_freq(xr.DataArray(cf_indx)) == "D"
+    cf_index = xr.date_range("2000-01-01", periods=3, freq="D", use_cftime=True)
+    assert xr.infer_freq(cf_index) == "D"
+    assert xr.infer_freq(xr.DataArray(cf_index)) == "D"
 
-    pd_indx = pd.date_range("2000-01-01", periods=3, freq="D").as_unit(time_unit)
-    assert xr.infer_freq(pd_indx) == "D"
-    assert xr.infer_freq(xr.DataArray(pd_indx)) == "D"
+    pd_index = pd.date_range("2000-01-01", periods=3, freq="D").as_unit(time_unit)
+    assert xr.infer_freq(pd_index) == "D"
+    assert xr.infer_freq(xr.DataArray(pd_index)) == "D"
 
-    pd_td_indx = pd.timedelta_range(start="1D", periods=3, freq="D").as_unit(time_unit)
-    assert xr.infer_freq(pd_td_indx) == "D"
-    assert xr.infer_freq(xr.DataArray(pd_td_indx)) == "D"
+    pd_td_index = pd.timedelta_range(start="1D", periods=3, freq="D").as_unit(time_unit)
+    assert xr.infer_freq(pd_td_index) == "D"
+    assert xr.infer_freq(xr.DataArray(pd_td_index)) == "D"
 
 
 @requires_cftime
@@ -1421,27 +1421,27 @@ def test_infer_freq_invalid_inputs():
     with pytest.raises(ValueError, match="must contain datetime-like objects"):
         xr.infer_freq(xr.DataArray([0, 1, 2]))
 
-    indx = xr.date_range("1990-02-03", periods=4, freq="MS", use_cftime=True)
+    index = xr.date_range("1990-02-03", periods=4, freq="MS", use_cftime=True)
     # 2D DataArray
     with pytest.raises(ValueError, match="must be 1D"):
-        xr.infer_freq(xr.DataArray([indx, indx]))
+        xr.infer_freq(xr.DataArray([index, index]))
 
     # CFTimeIndex too short
     with pytest.raises(ValueError, match="Need at least 3 dates to infer frequency"):
-        xr.infer_freq(indx[:2])
+        xr.infer_freq(index[:2])
 
     # Non-monotonic input
-    assert xr.infer_freq(indx[np.array([0, 2, 1, 3])]) is None
+    assert xr.infer_freq(index[np.array([0, 2, 1, 3])]) is None
 
     # Non-unique input
-    assert xr.infer_freq(indx[np.array([0, 1, 1, 2])]) is None
+    assert xr.infer_freq(index[np.array([0, 1, 1, 2])]) is None
 
     # No unique frequency (here 1st step is MS, second is 2MS)
-    assert xr.infer_freq(indx[np.array([0, 1, 3])]) is None
+    assert xr.infer_freq(index[np.array([0, 1, 3])]) is None
 
     # Same, but for QS
-    indx = xr.date_range("1990-02-03", periods=4, freq="QS", use_cftime=True)
-    assert xr.infer_freq(indx[np.array([0, 1, 3])]) is None
+    index = xr.date_range("1990-02-03", periods=4, freq="QS", use_cftime=True)
+    assert xr.infer_freq(index[np.array([0, 1, 3])]) is None
 
 
 @requires_cftime
@@ -1465,10 +1465,10 @@ def test_infer_freq_invalid_inputs():
 )
 @pytest.mark.parametrize("calendar", _CFTIME_CALENDARS)
 def test_infer_freq(freq, calendar):
-    indx = xr.date_range(
+    index = xr.date_range(
         "2000-01-01", periods=3, freq=freq, calendar=calendar, use_cftime=True
     )
-    out = xr.infer_freq(indx)
+    out = xr.infer_freq(index)
     assert out == freq