This repository contains CPython bindings for libnest2d (though note that we may use as of yet unmerged work done on our own fork of libnest2d, here whenever convenient), a library to pack 2D polygons into a small space. Libnest2d implements the 2D bin packing problem.
The objective of this repository is to allow libnest2d to be called from Python using Numpy. There is a competing solution to provide Python bindings to this end. However it doesn't expose enough of the configurability for Cura's purposes. This repository aims to be a more transparent binding of libnest2d.
This is an example of how you can use these Python bindings to arrange multiple shapes in a volume.
>>> from pynest2d import *
>>> bin = Box(1000, 1000) # A bounding volume in which the items must be arranged, a 1000x1000 square centered around 0.
>>> i1 = Item([Point(0, 0), Point(100, 100), Point(50, 100)]) # Long thin triangle.
>>> i2 = Item([Point(0, 0), Point(100, 0), Point(100, 100), Point(0, 100)]) # Square.
>>> i3 = Item([Point(0, 0), Point(100, 0), Point(50, 100)]) # Equilateral triangle.
>>> num_bins = nest([i1, i2, i3], bin) # The actual arranging!
>>> num_bins # How many bins are required to add all objects.
1
>>> transformed_i1 = i1.transformedShape() # The original item is unchanged, but the transformed shape is.
>>> print(transformed_i1.toString())
Contour {
18 96
117 46
117 -4
18 96
}
>>> transformed_i.vertex(0).x()
18
>>> transformed_i.vertex(0).y()
96
>>> i1.rotation()
4.71238898038469For full documentation, see libnest2d. These bindings stay close to the original function signatures.
This library has a couple of dependencies that need to be installed prior to building: