v0.4.0

• Better error message in case of unknown array type: #37
• Support for SciPy sparse arrays: #52
• Drop support for Python 3.7: #51

v0.3.4

• Support for Python 3.12 #26
• Packaging update: Tests for conda-forge #27

v0.3.3

• Perform feature checks lazily #15

v0.3.2

• Detection and workaround for pydata/sparse#602.
• Detection and workaround for cupy/cupy#7713.

v0.3.1

Include version constraint for sparse.

v0.3.0

Adds the following features:

• Introduce conversion_cost() to obtain a value roughly proportional to the conversion cost
  between two backends.

v0.2.0

Adds the following features:

• New function result_type(...) to determine a compatible dtype for a set of array backends, dtypes, and other allowed arguments to numpy.result_type(...) .
• Support for cupyx.scipy.sparse.csr_matrix with dtype=bool.

v0.2.0rc1

Adds the following features:

• New function result_type(...) to determine a compatible dtype for a set of array backends, dtypes, and other allowed arguments to numpy.result_type(...) .
• Support for cupyx.scipy.sparse.csr_matrix with dtype=bool.

Initial release

Format detection, identifiers and converter matrix for a range of numerical array formats (backends) in Python, focusing on sparse arrays.

Initial release v0.1.0rc3

Format detection, identifiers and converter matrix for a range of numerical array formats (backends) in Python, focusing on sparse arrays.