Update pre-commit hooks (#4651)

* autoupdate pre-commit hooks

* run pre-commit on all files

* stop using doctest for the code snippet

Author: keewis

.pre-commit-config.yaml

@@ -11,7 +11,7 @@ repos:
     hooks:
       - id: black
   - repo: https://github.com/keewis/blackdoc
-    rev: v0.3
+    rev: v0.3.1
     hooks:
       - id: blackdoc
   - repo: https://gitlab.com/pycqa/flake8

doc/contributing.rst

@@ -51,8 +51,9 @@ Bug reports must:
    <http://github.github.com/github-flavored-markdown/>`_::
 
       ```python
-      >>> import xarray as xr
-      >>> df = xr.Dataset(...)
+      import xarray as xr
+      df = xr.Dataset(...)
+
       ...
       ```
 

doc/io.rst

@@ -1033,6 +1033,7 @@ and then calling ``to_zarr`` with ``compute=False`` to write only metadata
 .. ipython:: python
 
     import dask.array
+
     # The values of this dask array are entirely irrelevant; only the dtype,
     # shape and chunks are used
     dummies = dask.array.zeros(30, chunks=10)

xarray/core/computation.py

@@ -931,6 +931,7 @@ def apply_ufunc(
     >>> def magnitude(a, b):
     ...     func = lambda x, y: np.sqrt(x ** 2 + y ** 2)
     ...     return xr.apply_ufunc(func, a, b)
+    ...
 
     You can now apply ``magnitude()`` to ``xr.DataArray`` and ``xr.Dataset``
     objects, with automatically preserved dimensions and coordinates, e.g.,

xarray/core/dataset.py

@@ -5940,10 +5940,6 @@ def filter_by_attrs(self, **kwargs):
         Examples
         --------
         >>> # Create an example dataset:
-        ...
-        >>> import numpy as np
-        >>> import pandas as pd
-        >>> import xarray as xr
         >>> temp = 15 + 8 * np.random.randn(2, 2, 3)
         >>> precip = 10 * np.random.rand(2, 2, 3)
         >>> lon = [[-99.83, -99.32], [-99.79, -99.23]]

xarray/core/options.py

@@ -111,6 +111,7 @@ class set_options:
     >>> ds = xr.Dataset({"x": np.arange(1000)})
     >>> with xr.set_options(display_width=40):
     ...     print(ds)
+    ...
     <xarray.Dataset>
     Dimensions:  (x: 1000)
     Coordinates:

xarray/core/parallel.py

@@ -232,6 +232,7 @@ def map_blocks(
     ...     gb = da.groupby(groupby_type)
     ...     clim = gb.mean(dim="time")
     ...     return gb - clim
+    ...
     >>> time = xr.cftime_range("1990-01", "1992-01", freq="M")
     >>> month = xr.DataArray(time.month, coords={"time": time}, dims=["time"])
     >>> np.random.seed(123)