[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

asv_bench/benchmarks/accessors.py

@@ -1,8 +1,7 @@
 import numpy as np
 
 import xarray as xr
-
-from . import parameterized
+from benchmarks import parameterized
 
 NTIME = 365 * 30
 

asv_bench/benchmarks/alignment.py

@@ -1,8 +1,7 @@
 import numpy as np
 
 import xarray as xr
-
-from . import parameterized, requires_dask
+from benchmarks import parameterized, requires_dask
 
 ntime = 365 * 30
 nx = 50

asv_bench/benchmarks/combine.py

@@ -1,8 +1,7 @@
 import numpy as np
 
 import xarray as xr
-
-from . import requires_dask
+from benchmarks import requires_dask
 
 
 class Combine1d:

asv_bench/benchmarks/dataarray_missing.py

@@ -1,8 +1,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import parameterized, randn, requires_dask
+from benchmarks import parameterized, randn, requires_dask
 
 
 def make_bench_data(shape, frac_nan, chunks):

asv_bench/benchmarks/dataset.py

@@ -1,9 +1,8 @@
 import numpy as np
 
+from benchmarks import requires_dask
 from xarray import Dataset
 
-from . import requires_dask
-
 
 class DatasetBinaryOp:
     def setup(self):

asv_bench/benchmarks/dataset_io.py

@@ -7,8 +7,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import _skip_slow, parameterized, randint, randn, requires_dask
+from benchmarks import _skip_slow, parameterized, randint, randn, requires_dask
 
 try:
     import dask

asv_bench/benchmarks/groupby.py

@@ -5,7 +5,7 @@
 
 import xarray as xr
 
-from . import _skip_slow, parameterized, requires_dask
+from benchmarks import _skip_slow, parameterized, requires_dask
 
 
 class GroupBy:

asv_bench/benchmarks/indexing.py

@@ -4,8 +4,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import parameterized, randint, randn, requires_dask
+from benchmarks import parameterized, randint, randn, requires_dask
 
 nx = 2000
 ny = 1000

asv_bench/benchmarks/interp.py

@@ -2,8 +2,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import parameterized, randn, requires_dask
+from benchmarks import parameterized, randn, requires_dask
 
 nx = 1500
 ny = 1000

asv_bench/benchmarks/pandas.py

@@ -2,8 +2,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import parameterized, requires_dask
+from benchmarks import parameterized, requires_dask
 
 
 class MultiIndexSeries:

asv_bench/benchmarks/polyfit.py

@@ -1,8 +1,7 @@
 import numpy as np
 
 import xarray as xr
-
-from . import parameterized, randn, requires_dask
+from benchmarks import parameterized, randn, requires_dask
 
 NDEGS = (2, 5, 20)
 NX = (10**2, 10**6)

asv_bench/benchmarks/reindexing.py

@@ -1,8 +1,7 @@
 import numpy as np
 
 import xarray as xr
-
-from . import requires_dask
+from benchmarks import requires_dask
 
 ntime = 500
 nx = 50

asv_bench/benchmarks/rolling.py

@@ -2,8 +2,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import parameterized, randn, requires_dask
+from benchmarks import parameterized, randn, requires_dask
 
 nx = 3000
 long_nx = 30000

asv_bench/benchmarks/unstacking.py

@@ -2,8 +2,7 @@
 import pandas as pd
 
 import xarray as xr
-
-from . import requires_dask, requires_sparse
+from benchmarks import requires_dask, requires_sparse
 
 
 class Unstacking: