Basic usage

import binsparse

import numpy as np
from scipy import sparse

import zarr

csr = sparse.random(1000, 100, format="csr", density=0.1, random_state=np.random.default_rng())

z = zarr.group()

binsparse.write(z, "csr", csr)
binsparse.read(z["csr"])

<1000x100 sparse matrix of type '<class 'numpy.float64'>'
	with 10000 stored elements in Compressed Sparse Row format>