Refactor compatibility modules into xarray.compat package

xarray/coding/cftime_offsets.py

@@ -61,11 +61,11 @@
     convert_time_or_go_back,
     format_cftime_datetime,
 )
-from xarray.core.common import _contains_datetime_like_objects, is_np_datetime_like
-from xarray.core.pdcompat import (
+from xarray.compat.pdcompat import (
     count_not_none,
     default_precision_timestamp,
 )
+from xarray.core.common import _contains_datetime_like_objects, is_np_datetime_like
 from xarray.core.types import InclusiveOptions
 from xarray.core.utils import attempt_import, emit_user_level_warning
 

xarray/coding/times.py

@@ -20,11 +20,11 @@
     unpack_for_decoding,
     unpack_for_encoding,
 )
+from xarray.compat.pdcompat import default_precision_timestamp, timestamp_as_unit
 from xarray.core import indexing
 from xarray.core.common import contains_cftime_datetimes, is_np_datetime_like
 from xarray.core.duck_array_ops import array_all, array_any, asarray, ravel, reshape
 from xarray.core.formatting import first_n_items, format_timestamp, last_item
-from xarray.core.pdcompat import default_precision_timestamp, timestamp_as_unit
 from xarray.core.utils import attempt_import, emit_user_level_warning
 from xarray.core.variable import Variable
 from xarray.namedarray.parallelcompat import T_ChunkedArray, get_chunked_array_type

xarray/core/dask_array_ops.py → xarray/compat/dask_array_ops.py

@@ -2,6 +2,7 @@
 
 import math
 
+from xarray.compat.dask_array_compat import reshape_blockwise
 from xarray.core import dtypes, nputils
 
 
@@ -21,8 +22,6 @@ def dask_rolling_wrapper(moving_func, a, window, min_count=None, axis=-1):
 def least_squares(lhs, rhs, rcond=None, skipna=False):
     import dask.array as da
 
-    from xarray.core.dask_array_compat import reshape_blockwise
-
     # The trick here is that the core dimension is axis 0.
     # All other dimensions need to be reshaped down to one axis for `lstsq`
     # (which only accepts 2D input)

xarray/core/computation.py

@@ -22,9 +22,9 @@
 
 import numpy as np
 
+from xarray.compat.array_api_compat import to_like_array
 from xarray.core import dtypes, duck_array_ops, utils
 from xarray.core.alignment import align, deep_align
-from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import zeros_like
 from xarray.core.duck_array_ops import datetime_to_numeric
 from xarray.core.formatting import limit_lines

xarray/core/dataset.py

@@ -41,6 +41,7 @@
 
 from xarray.coding.calendar_ops import convert_calendar, interp_calendar
 from xarray.coding.cftimeindex import CFTimeIndex, _parse_array_of_cftime_strings
+from xarray.compat.array_api_compat import to_like_array
 from xarray.core import (
     alignment,
     duck_array_ops,
@@ -57,7 +58,6 @@
     align,
 )
 from xarray.core.arithmetic import DatasetArithmetic
-from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import (
     DataWithCoords,
     _contains_datetime_like_objects,

xarray/core/dtypes.py

@@ -6,8 +6,9 @@
 import numpy as np
 from pandas.api.types import is_extension_array_dtype
 
-from xarray.core import array_api_compat, npcompat, utils
-from xarray.core.npcompat import HAS_STRING_DTYPE
+from xarray.compat import array_api_compat, npcompat
+from xarray.compat.npcompat import HAS_STRING_DTYPE
+from xarray.core import utils
 
 # Use as a sentinel value to indicate a dtype appropriate NA value.
 NA = utils.ReprObject("<NA>")

xarray/core/duck_array_ops.py

@@ -24,8 +24,9 @@
 )
 from pandas.api.types import is_extension_array_dtype
 
-from xarray.core import dask_array_compat, dask_array_ops, dtypes, nputils
-from xarray.core.array_api_compat import get_array_namespace
+from xarray.compat import dask_array_compat, dask_array_ops
+from xarray.compat.array_api_compat import get_array_namespace
+from xarray.core import dtypes, nputils
 from xarray.core.options import OPTIONS
 from xarray.core.utils import is_duck_array, is_duck_dask_array, module_available
 from xarray.namedarray.parallelcompat import get_chunked_array_type
@@ -233,7 +234,7 @@
 
     if xp == np:
         # numpy currently doesn't have a astype:
         return data.astype(dtype, **kwargs)
     return xp.astype(data, dtype, **kwargs)
 
 

xarray/core/nputils.py

@@ -7,7 +7,7 @@
 import pandas as pd
 from packaging.version import Version
 
-from xarray.core.array_api_compat import get_array_namespace
+from xarray.compat.array_api_compat import get_array_namespace
 from xarray.core.utils import is_duck_array, module_available
 from xarray.namedarray import pycompat
 

xarray/core/rolling.py

@@ -9,7 +9,8 @@
 
 import numpy as np
 
-from xarray.core import dask_array_ops, dtypes, duck_array_ops, utils
+from xarray.compat import dask_array_ops
+from xarray.core import dtypes, duck_array_ops, utils
 from xarray.core.arithmetic import CoarsenArithmetic
 from xarray.core.options import OPTIONS, _get_keep_attrs
 from xarray.core.types import CoarsenBoundaryOptions, SideOptions, T_Xarray

xarray/core/rolling_exp.py

@@ -5,9 +5,9 @@
 
 import numpy as np
 
+from xarray.compat.pdcompat import count_not_none
 from xarray.core.computation import apply_ufunc
 from xarray.core.options import _get_keep_attrs
-from xarray.core.pdcompat import count_not_none
 from xarray.core.types import T_DataWithCoords
 from xarray.core.utils import module_available
 

xarray/core/variable.py

@@ -16,9 +16,9 @@
 from pandas.api.types import is_extension_array_dtype
 
 import xarray as xr  # only for Dataset and DataArray
+from xarray.compat.array_api_compat import to_like_array
 from xarray.core import common, dtypes, duck_array_ops, indexing, nputils, ops, utils
 from xarray.core.arithmetic import VariableArithmetic
-from xarray.core.array_api_compat import to_like_array
 from xarray.core.common import AbstractArray
 from xarray.core.extension_array import PandasExtensionArray
 from xarray.core.indexing import (