intermediate.py

import bpy

'''
this could will go along and record for every point the positions of the set of knot + handles,
and check against the previous set. If all match the previous set, the index is recorded and the 
loop is broken, then in the segment us selected solo and segment removed. This operation can be 
repeated automatically untill no seqential duplicates are found.

'''

import mathutils
from mathutils import Vector

def check_similarity(old_set, new_set, distance=0.0001):
    if None in old_set:
        return False
    else:
        for co_old, co_new in zip(old_set, new_set):
            if (co_old-co_new).length < distance:
                continue
            else:
                return False
    
    # reaches here only if all old/new coordinates where closer than 'distance'.
    return True

obj = bpy.context.active_object
splines = obj.data.splines

old_set = None, None, None

# A Curve data-type can hold multiple disjoint curves/splines
for idx, spline in enumerate(splines):
    for cidx, bp in enumerate(spline.bezier_points):
        new_set = (bp.co, bp.handle_left, bp.handle_right)
        if check_similarity(old_set, new_set):
            print(idx, cidx)
            bp.select_control_point = True
        else:
            old_set = new_set