nani 0.2.0

Nani is a Python library that provides an alternative approach to defining and viewing NumPy’s arrays.

Upon getting started with NumPy, the rules to define numpy.dtype objects tend to quickly become confusing. Not only different syntaxes can create a same data type, but it also seems arbitrary and hence difficult to remember that sub-array data types can only be defined as tuples while structured data types exclusively require lists made of field tuples, and so on.

To address this point, Nani takes the stance of offering one—and only one—way of constructing numpy.dtype objects. Although this syntax makes the code more verbose, it also makes it easier to read and to reason about.

Nani’s approach allows type introspection which brings additional benefits in the form of dynamically generated default values and view types. Default values facilitate the definition of new array elements while view types are useful to encapsulate interactions with NumPy and to expose a different public interface to your library users instead of the one provided with numpy.ndarray.

>>> import numpy
>>> import nani
>>> color_type = nani.Array(
...     element_type=nani.Number(type=numpy.uint8, default=255),
...     shape=3,
...     view=None)
>>> dtype, default, view = nani.resolve(color_type, name='Color')
>>> a = numpy.array([default] * 2, dtype=dtype)
>>> v = view(a)
>>> for color in v:
...     print(color)
[255, 255, 255]
[255, 255, 255]