From 460237616647e1ce999a59d0a0607e3e72ef554e Mon Sep 17 00:00:00 2001
From: Hameer Abbasi <2190658+hameerabbasi@users.noreply.github.com>
Date: Tue, 24 Sep 2024 13:28:56 +0200
Subject: [PATCH] Update with suggestions from @pearu.

---
 .../numba_backend/_compressed/compressed.py   | 18 +++++-----------
 sparse/numba_backend/_coo/core.py             | 11 +++-------
 sparse/numba_backend/_dok.py                  |  7 ++-----
 sparse/numba_backend/_sparse_array.py         | 21 ++++++-------------
 4 files changed, 16 insertions(+), 41 deletions(-)

diff --git a/sparse/numba_backend/_compressed/compressed.py b/sparse/numba_backend/_compressed/compressed.py
index 8ac5a036..c504da26 100644
--- a/sparse/numba_backend/_compressed/compressed.py
+++ b/sparse/numba_backend/_compressed/compressed.py
@@ -847,11 +847,8 @@ def isnan(self):
     # `GCXS` is a reshaped/transposed `CSR`, but it can't (usually)
     # be expressed in the `binsparse` 0.1 language.
     # We are missing index maps.
-    def __binsparse_descriptor__(self) -> dict:
-        return super().__binsparse_descriptor__()
-
-    def __binsparse_dlpack__(self) -> dict[str, np.ndarray]:
-        return super().__binsparse_dlpack__()
+    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
+        return super().__binsparse__()
 
 
 class _Compressed2d(GCXS):
@@ -892,13 +889,13 @@ def from_numpy(cls, x, fill_value=0, idx_dtype=None):
         coo = COO.from_numpy(x, fill_value=fill_value, idx_dtype=idx_dtype)
         return cls.from_coo(coo, cls.class_compressed_axes, idx_dtype)
 
-    def __binsparse_descriptor__(self) -> dict:
+    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
         from sparse._version import __version__
 
         data_dt = str(self.data.dtype)
         if np.issubdtype(data_dt, np.complexfloating):
             data_dt = f"complex[float{self.data.dtype.itemsize // 2}]"
-        return {
+        descriptor = {
             "binsparse": {
                 "version": "0.1",
                 "format": self.format.upper(),
@@ -913,12 +910,7 @@ def __binsparse_descriptor__(self) -> dict:
             "original_source": f"`sparse`, version {__version__}",
         }
 
-    def __binsparse_dlpack__(self) -> dict[str, np.ndarray]:
-        return {
-            "pointers_to_1": self.indices,
-            "indices_1": self.indptr,
-            "values": self.data,
-        }
+        return descriptor, [self.indices, self.indptr, self.data]
 
 
 class CSR(_Compressed2d):
diff --git a/sparse/numba_backend/_coo/core.py b/sparse/numba_backend/_coo/core.py
index a787fed8..fb39aaab 100644
--- a/sparse/numba_backend/_coo/core.py
+++ b/sparse/numba_backend/_coo/core.py
@@ -1537,13 +1537,13 @@ def isnan(self):
             prune=True,
         )
 
-    def __binsparse_descriptor__(self) -> dict:
+    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
         from sparse._version import __version__
 
         data_dt = str(self.data.dtype)
         if np.issubdtype(data_dt, np.complexfloating):
             data_dt = f"complex[float{self.data.dtype.itemsize // 2}]"
-        return {
+        descriptor = {
             "binsparse": {
                 "version": "0.1",
                 "format": {
@@ -1568,12 +1568,7 @@ def __binsparse_descriptor__(self) -> dict:
             "original_source": f"`sparse`, version {__version__}",
         }
 
-    def __binsparse_dlpack__(self) -> dict[str, np.ndarray]:
-        return {
-            "pointers_to_1": np.array([0, self.nnz], dtype=np.uint8),
-            "indices_1": self.coords,
-            "values": self.data,
-        }
+        return descriptor, [np.array([0, self.nnz], dtype=np.uint8), self.coords, self.data]
 
 
 def as_coo(x, shape=None, fill_value=None, idx_dtype=None):
diff --git a/sparse/numba_backend/_dok.py b/sparse/numba_backend/_dok.py
index 809e926e..b3a8e747 100644
--- a/sparse/numba_backend/_dok.py
+++ b/sparse/numba_backend/_dok.py
@@ -548,11 +548,8 @@ def reshape(self, shape, order="C"):
 
         return DOK.from_coo(self.to_coo().reshape(shape))
 
-    def __binsparse_descriptor__(self) -> dict:
-        raise RuntimeError("`DOK` doesn't support the `__binsparse_descriptor__` protocol.")
-
-    def __binsparse_dlpack__(self) -> dict[str, np.ndarray]:
-        raise RuntimeError("`DOK` doesn't support the `__binsparse_dlpack__` protocol.")
+    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
+        raise RuntimeError("`DOK` doesn't support the `__binsparse__` protocol.")
 
 
 def to_slice(k):
diff --git a/sparse/numba_backend/_sparse_array.py b/sparse/numba_backend/_sparse_array.py
index e776a347..7a7b84cc 100644
--- a/sparse/numba_backend/_sparse_array.py
+++ b/sparse/numba_backend/_sparse_array.py
@@ -219,27 +219,18 @@ def _str_impl(self, summary):
             return summary
 
     @abstractmethod
-    def __binsparse_descriptor__(self) -> dict:
-        """Return a `dict` equivalent to a parsed JSON [`binsparse` descriptor](https://graphblas.org/binsparse-specification/#descriptor)
+    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
+        """Return a 2-tuple:
+        * First element is a `dict` equivalent to a parsed JSON [`binsparse` descriptor](https://graphblas.org/binsparse-specification/#descriptor)
         of this array.
+        * Second element is a `list[np.ndarray]` of the constituent arrays.
 
         Returns
         -------
         dict
             Parsed `binsparse` descriptor.
-        """
-        raise NotImplementedError
-
-    @abstractmethod
-    def __binsparse_dlpack__(self) -> dict[str, np.ndarray]:
-        """A `dict` containing the constituent arrays of this sparse array. The keys are compatible with the
-        [`binsparse`](https://graphblas.org/binsparse-specification/) scheme, and the values are [`__dlpack__`](https://data-apis.org/array-api/latest/API_specification/generated/array_api.array.__dlpack__.html)
-        compatible objects.
-
-        Returns
-        -------
-        dict[str, np.ndarray]
-            The constituent arrays.
+        list[np.ndarray]
+            The constituent arrays
         """
         raise NotImplementedError