* bqn-npy

This library allows to save and load BQN arrays to the binary [[https://numpy.org/doc/stable/reference/generated/numpy.lib.format.html][NPY
format]] compatible with Numpy. It can also be used to interoperate
with Numpy.

See also [[https://github.com/dlozeve/bqn-safetensors][bqn-safetensors]] for another array serialization format.

** Limitations

The library only support homogeneous multidimensional arrays with the
following Numpy dtypes:

| dtype | Description                                                 |
|-------+-------------------------------------------------------------|
| ~<f8~ | little-endian 64-bit double-precision floating point number |
| ~<i4~ | little-endian 32-bit signed integer                         |
| ~<u4~ | little-endian 32-bit unsigned integer                       |

All other dtypes (big-endian numbers, booleans, bytes, objects, other
sizes of floats or integers) are unsupported and files containing them
will raise an error when loaded.

When serializing BQN arrays, the library uses the most restrictive
dtype possible. An array consisting only of positive integers will be
saved as ~<u4~, otherwise ~<i4~ if there are negative integers,
otherwise ~<f8~ for arbitrary numbers.

** Usage

#+begin_src bqn
⟨SaveNpy,LoadNpy⟩←•Import"npy.bqn"

# Deserialization
arr1←LoadNpy"arr1.npy"

# Serialization
arr2←2‿3‿4⥊•rand.Range 0  # will be saved as a floating point array
"arr2.npy" SaveNpy arr2
#+end_src

** Tests

Run the Python script to generate test data: =python gentest.py=.

To run tests, run =bqn tests.bqn=.