Support of repr and deepcopy of recursive arrays

doc/whats-new.rst

@@ -33,6 +33,9 @@ Deprecations
 
 Bug fixes
 ~~~~~~~~~
+
+- Support for recursively defined Arrays. Fixes repr and deepcopy. (:issue:`7111`, :pull:`7112`)
+  By `Michael Niklas <https://github.com/headtr1ck>`_.
 - Fixed :py:meth:`Dataset.transpose` to raise a more informative error. (:issue:`6502`, :pull:`7120`)
   By `Patrick Naylor <https://github.com/patrick-naylor>`_
 

xarray/core/dataarray.py

@@ -516,7 +516,7 @@ def _overwrite_indexes(
             new_indexes.pop(name)
 
         if rename_dims:
-            new_variable.dims = [rename_dims.get(d, d) for d in new_variable.dims]
+            new_variable.dims = tuple(rename_dims.get(d, d) for d in new_variable.dims)
 
         return self._replace(
             variable=new_variable, coords=new_coords, indexes=new_indexes
@@ -1169,25 +1169,33 @@ def copy(self: T_DataArray, deep: bool = True, data: Any = None) -> T_DataArray:
         --------
         pandas.DataFrame.copy
         """
-        variable = self.variable.copy(deep=deep, data=data)
+        return self._copy(deep=deep, data=data)
+
+    def _copy(
+        self: T_DataArray,
+        deep: bool = True,
+        data: Any = None,
+        memo: dict[int, Any] | None = None,
+    ) -> T_DataArray:
+        variable = self.variable._copy(deep=deep, data=data, memo=memo)
         indexes, index_vars = self.xindexes.copy_indexes(deep=deep)
 
         coords = {}
         for k, v in self._coords.items():
             if k in index_vars:
                 coords[k] = index_vars[k]
             else:
-                coords[k] = v.copy(deep=deep)
+                coords[k] = v._copy(deep=deep, memo=memo)
 
         return self._replace(variable, coords, indexes=indexes)
 
     def __copy__(self: T_DataArray) -> T_DataArray:
-        return self.copy(deep=False)
+        return self._copy(deep=False)
 
-    def __deepcopy__(self: T_DataArray, memo=None) -> T_DataArray:
-        # memo does nothing but is required for compatibility with
-        # copy.deepcopy
-        return self.copy(deep=True)
+    def __deepcopy__(
+        self: T_DataArray, memo: dict[int, Any] | None = None
+    ) -> T_DataArray:
+        return self._copy(deep=True, memo=memo)
 
     # mutable objects should not be Hashable
     # https://github.com/python/mypy/issues/4266

xarray/core/dataset.py

@@ -1221,6 +1221,14 @@ def copy(
         --------
         pandas.DataFrame.copy
         """
+        return self._copy(deep=deep, data=data)
+
+    def _copy(
+        self: T_Dataset,
+        deep: bool = False,
+        data: Mapping[Any, ArrayLike] | None = None,
+        memo: dict[int, Any] | None = None,
+    ) -> T_Dataset:
         if data is None:
             data = {}
         elif not utils.is_dict_like(data):
@@ -1249,13 +1257,21 @@ def copy(
             if k in index_vars:
                 variables[k] = index_vars[k]
             else:
-                variables[k] = v.copy(deep=deep, data=data.get(k))
+                variables[k] = v._copy(deep=deep, data=data.get(k), memo=memo)
 
-        attrs = copy.deepcopy(self._attrs) if deep else copy.copy(self._attrs)
-        encoding = copy.deepcopy(self._encoding) if deep else copy.copy(self._encoding)
+        attrs = copy.deepcopy(self._attrs, memo) if deep else copy.copy(self._attrs)
+        encoding = (
+            copy.deepcopy(self._encoding, memo) if deep else copy.copy(self._encoding)
+        )
 
         return self._replace(variables, indexes=indexes, attrs=attrs, encoding=encoding)
 
+    def __copy__(self: T_Dataset) -> T_Dataset:
+        return self._copy(deep=False)
+
+    def __deepcopy__(self: T_Dataset, memo: dict[int, Any] | None = None) -> T_Dataset:
+        return self._copy(deep=True, memo=memo)
+
     def as_numpy(self: T_Dataset) -> T_Dataset:
         """
         Coerces wrapped data and coordinates into numpy arrays, returning a Dataset.
@@ -1332,14 +1348,6 @@ def _construct_dataarray(self, name: Hashable) -> DataArray:
 
         return DataArray(variable, coords, name=name, indexes=indexes, fastpath=True)
 
-    def __copy__(self: T_Dataset) -> T_Dataset:
-        return self.copy(deep=False)
-
-    def __deepcopy__(self: T_Dataset, memo=None) -> T_Dataset:
-        # memo does nothing but is required for compatibility with
-        # copy.deepcopy
-        return self.copy(deep=True)
-
     @property
     def _attr_sources(self) -> Iterable[Mapping[Hashable, Any]]:
         """Places to look-up items for attribute-style access"""

xarray/core/formatting.py

@@ -8,6 +8,7 @@
 from collections import defaultdict
 from datetime import datetime, timedelta
 from itertools import chain, zip_longest
+from reprlib import recursive_repr
 from typing import Collection, Hashable
 
 import numpy as np
@@ -385,7 +386,6 @@ def _mapping_repr(
     expand_option_name="display_expand_data_vars",
 )
 
-
 attrs_repr = functools.partial(
     _mapping_repr,
     title="Attributes",
@@ -551,6 +551,7 @@ def short_data_repr(array):
         return f"[{array.size} values with dtype={array.dtype}]"
 
 
+@recursive_repr("<recursive array>")
 def array_repr(arr):
     from .variable import Variable
 
@@ -592,11 +593,12 @@ def array_repr(arr):
             summary.append(unindexed_dims_str)
 
     if arr.attrs:
-        summary.append(attrs_repr(arr.attrs))
+        summary.append(attrs_repr(arr.attrs, max_rows=max_rows))
 
     return "\n".join(summary)
 
 
+@recursive_repr("<recursive Dataset>")
 def dataset_repr(ds):
     summary = [f"<xarray.{type(ds).__name__}>"]
 

xarray/core/utils.py

@@ -161,16 +161,13 @@ def equivalent(first: T, second: T) -> bool:
     # TODO: refactor to avoid circular import
     from . import duck_array_ops
 
+    if first is second:
+        return True
     if isinstance(first, np.ndarray) or isinstance(second, np.ndarray):
         return duck_array_ops.array_equiv(first, second)
-    elif isinstance(first, list) or isinstance(second, list):
+    if isinstance(first, list) or isinstance(second, list):
         return list_equiv(first, second)
-    else:
-        return (
-            (first is second)
-            or (first == second)
-            or (pd.isnull(first) and pd.isnull(second))
-        )
+    return (first == second) or (pd.isnull(first) and pd.isnull(second))
 
 
 def list_equiv(first, second):

xarray/core/variable.py

@@ -918,7 +918,9 @@ def encoding(self, value):
         except ValueError:
             raise ValueError("encoding must be castable to a dictionary")
 
-    def copy(self, deep: bool = True, data: ArrayLike | None = None):
+    def copy(
+        self: T_Variable, deep: bool = True, data: ArrayLike | None = None
+    ) -> T_Variable:
         """Returns a copy of this object.
 
         If `deep=True`, the data array is loaded into memory and copied onto
@@ -974,6 +976,14 @@ def copy(self, deep: bool = True, data: ArrayLike | None = None):
         --------
         pandas.DataFrame.copy
         """
+        return self._copy(deep=deep, data=data)
+
+    def _copy(
+        self: T_Variable,
+        deep: bool = True,
+        data: ArrayLike | None = None,
+        memo: dict[int, Any] | None = None,
+    ) -> T_Variable:
         if data is None:
             ndata = self._data
 
@@ -982,7 +992,7 @@ def copy(self, deep: bool = True, data: ArrayLike | None = None):
                 ndata = indexing.MemoryCachedArray(ndata.array)
 
             if deep:
-                ndata = copy.deepcopy(ndata)
+                ndata = copy.deepcopy(ndata, memo)
 
         else:
             ndata = as_compatible_data(data)
@@ -993,8 +1003,10 @@ def copy(self, deep: bool = True, data: ArrayLike | None = None):
                     )
                 )
 
-        attrs = copy.deepcopy(self._attrs) if deep else copy.copy(self._attrs)
-        encoding = copy.deepcopy(self._encoding) if deep else copy.copy(self._encoding)
+        attrs = copy.deepcopy(self._attrs, memo) if deep else copy.copy(self._attrs)
+        encoding = (
+            copy.deepcopy(self._encoding, memo) if deep else copy.copy(self._encoding)
+        )
 
         # note: dims is already an immutable tuple
         return self._replace(data=ndata, attrs=attrs, encoding=encoding)
@@ -1016,13 +1028,13 @@ def _replace(
             encoding = copy.copy(self._encoding)
         return type(self)(dims, data, attrs, encoding, fastpath=True)
 
-    def __copy__(self):
-        return self.copy(deep=False)
+    def __copy__(self: T_Variable) -> T_Variable:
+        return self._copy(deep=False)
 
-    def __deepcopy__(self, memo=None):
-        # memo does nothing but is required for compatibility with
-        # copy.deepcopy
-        return self.copy(deep=True)
+    def __deepcopy__(
+        self: T_Variable, memo: dict[int, Any] | None = None
+    ) -> T_Variable:
+        return self._copy(deep=True, memo=memo)
 
     # mutable objects should not be hashable
     # https://github.com/python/mypy/issues/4266

xarray/tests/test_concat.py

@@ -219,7 +219,9 @@ def test_concat_errors(self):
             concat([data, data], "new_dim", coords=["not_found"])
 
         with pytest.raises(ValueError, match=r"global attributes not"):
-            data0, data1 = deepcopy(split_data)
+            # call deepcopy seperately to get unique attrs
+            data0 = deepcopy(split_data[0])
+            data1 = deepcopy(split_data[1])
             data1.attrs["foo"] = "bar"
             concat([data0, data1], "dim1", compat="identical")
         assert_identical(data, concat([data0, data1], "dim1", compat="equals"))

xarray/tests/test_dataarray.py

@@ -6488,6 +6488,28 @@ def test_deepcopy_obj_array() -> None:
     assert x0.values[0] is not x1.values[0]
 
 
+def test_deepcopy_recursive() -> None:
+    # GH:issue:7111
+
+    # direct recursion
+    da = xr.DataArray([1, 2], dims=["x"])
+    da.attrs["other"] = da
+
+    # TODO: cannot use assert_identical on recursive Vars yet...
+    # lets just ensure that deep copy works without RecursionError
+    da.copy(deep=True)
+
+    # indirect recursion
+    da2 = xr.DataArray([5, 6], dims=["y"])
+    da.attrs["other"] = da2
+    da2.attrs["other"] = da
+
+    # TODO: cannot use assert_identical on recursive Vars yet...
+    # lets just ensure that deep copy works without RecursionError
+    da.copy(deep=True)
+    da2.copy(deep=True)
+
+
 def test_clip(da: DataArray) -> None:
     with raise_if_dask_computes():
         result = da.clip(min=0.5)

xarray/tests/test_dataset.py

@@ -6687,6 +6687,28 @@ def test_deepcopy_obj_array() -> None:
     assert x0["foo"].values[0] is not x1["foo"].values[0]
 
 
+def test_deepcopy_recursive() -> None:
+    # GH:issue:7111
+
+    # direct recursion
+    ds = xr.Dataset({"a": (["x"], [1, 2])})
+    ds.attrs["other"] = ds
+
+    # TODO: cannot use assert_identical on recursive Vars yet...
+    # lets just ensure that deep copy works without RecursionError
+    ds.copy(deep=True)
+
+    # indirect recursion
+    ds2 = xr.Dataset({"b": (["y"], [3, 4])})
+    ds.attrs["other"] = ds2
+    ds2.attrs["other"] = ds
+
+    # TODO: cannot use assert_identical on recursive Vars yet...
+    # lets just ensure that deep copy works without RecursionError
+    ds.copy(deep=True)
+    ds2.copy(deep=True)
+
+
 def test_clip(ds) -> None:
     result = ds.clip(min=0.5)
     assert all((result.min(...) >= 0.5).values())

xarray/tests/test_formatting.py

@@ -431,6 +431,24 @@ def test_array_repr_variable(self) -> None:
         with xr.set_options(display_expand_data=False):
             formatting.array_repr(var)
 
+    def test_array_repr_recursive(self) -> None:
+        # GH:issue:7111
+
+        # direct recurion
+        var = xr.Variable("x", [0, 1])
+        var.attrs["x"] = var
+        formatting.array_repr(var)
+
+        da = xr.DataArray([0, 1], dims=["x"])
+        da.attrs["x"] = da
+        formatting.array_repr(da)
+
+        # indirect recursion
+        var.attrs["x"] = da
+        da.attrs["x"] = var
+        formatting.array_repr(var)
+        formatting.array_repr(da)
+
     @requires_dask
     def test_array_scalar_format(self) -> None:
         # Test numpy scalars:
@@ -615,6 +633,21 @@ def test__mapping_repr(display_max_rows, n_vars, n_attr) -> None:
         assert actual == expected
 
 
+def test__mapping_repr_recursive() -> None:
+    # GH:issue:7111
+
+    # direct recursion
+    ds = xr.Dataset({"a": [["x"], [1, 2, 3]]})
+    ds.attrs["ds"] = ds
+    formatting.dataset_repr(ds)
+
+    # indirect recursion
+    ds2 = xr.Dataset({"b": [["y"], [1, 2, 3]]})
+    ds.attrs["ds"] = ds2
+    ds2.attrs["ds"] = ds
+    formatting.dataset_repr(ds2)
+
+
 def test__element_formatter(n_elements: int = 100) -> None:
     expected = """\
     Dimensions without coordinates: dim_0: 3, dim_1: 3, dim_2: 3, dim_3: 3,