Update to latest agreed-upon binsparse protocol version.

Author: hameerabbasi

pixi.toml

@@ -36,13 +36,8 @@ pytest-cov = "*"
 pytest-xdist = "*"
 pytest-codspeed = "*"
 
-<<<<<<< HEAD
 [feature.notebooks.pypi-dependencies]
 ipykernel = "*"
-=======
-[feature.notebooks.dependencies]
-ipython = "*"
->>>>>>> 54b7c1d (Fix `notebooks` feature and add it to development environments.)
 nbmake = "*"
 matplotlib = "*"
 networkx = "*"

sparse/numba_backend/_compressed/compressed.py

@@ -816,9 +816,12 @@ 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__(self) -> tuple[dict, list[np.ndarray]]:
+    def __binsparse__(self) -> dict:
         return super().__binsparse__()
 
+    def __binsparse_descriptor__(self) -> dict[str, np.ndarray]:
+        return super().__binsparse_descriptor__()
+
 
 class _Compressed2d(GCXS):
     class_compressed_axes: tuple[int]
@@ -858,13 +861,13 @@ 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__(self) -> tuple[dict, list[np.ndarray]]:
+    def __binsparse_descriptor__(self) -> dict:
         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 * 4}]"
-        descriptor = {
+        return {
             "binsparse": {
                 "version": "0.1",
                 "format": self.format.upper(),
@@ -879,7 +882,8 @@ def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
             "original_source": f"`sparse`, version {__version__}",
         }
 
-        return descriptor, [self.indptr, self.indices, self.data]
+    def __binsparse__(self) -> dict[str, np.ndarray]:
+        return {"pointers_to_1": self.indptr, "indices_1": self.indices, "values": self.data}
 
 
 class CSR(_Compressed2d):

sparse/numba_backend/_coo/core.py

@@ -1515,13 +1515,13 @@ def isnan(self):
             prune=True,
         )
 
-    def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
+    def __binsparse_descriptor__(self) -> dict:
         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 * 4}]"
-        descriptor = {
+        return {
             "binsparse": {
                 "version": "0.1",
                 "format": {
@@ -1548,7 +1548,12 @@ def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
             "original_source": f"`sparse`, version {__version__}",
         }
 
-        return descriptor, [np.array([0, self.nnz], dtype=np.uint64), self.coords, self.data]
+    def __binsparse__(self) -> dict[str, np.ndarray]:
+        return {
+            "pointers_to_1": np.array([0, self.nnz], dtype=np.uint64),
+            "indices_1": self.coords,
+            "values": self.data,
+        }
 
 
 def as_coo(x, shape=None, fill_value=None, idx_dtype=None):

sparse/numba_backend/_dok.py

@@ -527,7 +527,7 @@ def reshape(self, shape, order="C"):
         return DOK.from_coo(self.to_coo().reshape(shape))
 
     def __binsparse__(self) -> tuple[dict, list[np.ndarray]]:
-        raise RuntimeError("`DOK` doesn't support the `__binsparse__` protocol.")
+        raise TypeError("`DOK` doesn't support the `__binsparse__` protocol.")
 
 
 def to_slice(k):

sparse/numba_backend/_io.py

@@ -136,7 +136,8 @@ def load_npz(filename):
 
 @_check_device
 def from_binsparse(arr, /, *, device=None, copy: bool | None = None) -> SparseArray:
-    desc, arrs = arr.__binsparse__()
+    desc = arr.__binsparse_descriptor__()
+    arrs = arr.__binsparse__()
 
     desc = desc["binsparse"]
     version_tuple: tuple[int, ...] = tuple(int(v) for v in desc["version"].split("."))
@@ -216,13 +217,13 @@ def from_binsparse(arr, /, *, device=None, copy: bool | None = None) -> SparseAr
             if transpose != list(range(ndim)):
                 raise RuntimeError(format_err_str)
 
-            ptr_arr: np.ndarray = np.from_dlpack(arrs[0])
+            ptr_arr: np.ndarray = np.from_dlpack(arrs["pointers_to_1"])
             start, end = ptr_arr
             if copy is False and not (start == 0 or end == nnz):
                 raise RuntimeError(format_err_str)
 
-            coord_arr: np.ndarray = np.from_dlpack(arrs[1])
-            value_arr: np.ndarray = np.from_dlpack(arrs[2])
+            coord_arr: np.ndarray = np.from_dlpack(arrs["indices_1"])
+            value_arr: np.ndarray = np.from_dlpack(arrs["values"])
 
             _check_binsparse_dt(coord_arr, coords_dtype)
             _check_binsparse_dt(value_arr, value_dtype)
@@ -262,11 +263,11 @@ def from_binsparse(arr, /, *, device=None, copy: bool | None = None) -> SparseAr
             },
             **_kwargs,
         }:
-            crd_arr = np.from_dlpack(arrs[0])
+            crd_arr = np.from_dlpack(arrs["pointers_to_1"])
             _check_binsparse_dt(crd_arr, crd_dtype)
-            ptr_arr = np.from_dlpack(arrs[1])
+            ptr_arr = np.from_dlpack(arrs["indices_1"])
             _check_binsparse_dt(ptr_arr, ptr_dtype)
-            val_arr = np.from_dlpack(arrs[2])
+            val_arr = np.from_dlpack(arrs["values"])
             _check_binsparse_dt(val_arr, val_dtype)
 
             match transpose:

sparse/numba_backend/_sparse_array.py

@@ -247,18 +247,25 @@ def _str_impl(self, summary):
             return summary
 
     @abstractmethod
-    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)
+    def __binsparse_descriptor__(self) -> dict:
+        """Return 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.
-        list[np.ndarray]
-            The constituent arrays
+        """
+        raise NotImplementedError
+
+    @abstractmethod
+    def __binsparse__(self) -> dict[str, np.ndarray]:
+        """Return a is a `dict[str, np.ndarray]` of the constituent arrays.
+
+        Returns
+        -------
+        dict
+            Parsed `binsparse` descriptor.
         """
         raise NotImplementedError