Using SciPy, generate a Delaunay-triangulated mesh between randomly distributed points, and display it using pyglet.

pyglet-delaunay.py

#!/usr/bin/env python
# vim: et:ts=4:sw=4
import random, pyglet
from pyglet.gl import *
from numpy import array
from scipy.spatial import Delaunay

N_POINTS = 200;
SCALE = 2;

def get_tris():
    point_list = [(random.randint(0, N_POINTS * SCALE), random.randint(0, N_POINTS * SCALE)) for _ in range(N_POINTS)]
    point_array = array(point_list) # Arrays are numpy/C types. They are fast but immutable.
    tri = Delaunay(point_array)
    tri_verts = []
    for simplex in tri.simplices:
        vert1 = tri.points[simplex[0]]
        vert2 = tri.points[simplex[1]]
        vert3 = tri.points[simplex[2]]
        tri_verts.append(vert1)
        tri_verts.append(vert2)
        tri_verts.append(vert3)
    return tri_verts

window = pyglet.window.Window()
tris = get_tris()

@window.event
def on_draw():
    glClear(GL_COLOR_BUFFER_BIT)
    glLoadIdentity()
    glPolygonMode(GL_FRONT_AND_BACK, GL_LINE)
    glBegin(GL_TRIANGLES)
    for tri in tris:
        glVertex2f(*tri)
    glEnd()

pyglet.app.run()