Reading .npy and .npz
files in R.
Writing is out of scope. When working across multiple languages, one should prefer high-performance interoperable format (parquet, zarr, etc.).
reticulate?.npy files with {reticulate},
at some point in time, two (sometimes 3) copies of the data are made in
memory: one in Python and one in R. This can be problematic for large
files. With {grumpy}, only one copy of the data is made in
memory.{reticulate} requires a Python
installation and additional python packages, which users in restricted
environments may not have access to. {grumpy} is a pure R
package with no external dependencies.