!! This function is created by the author, Amine BOUABID, and is based only on mathematical description and not third-party code. !! This function was developed from scratch and it is not optimized in terms of memory and execution time.

Explanation: bezier_spline(X_points, Y_points, n_steps, show_details) draws a parametric curve using the control points defined by X_points and Y_points. n, the size of X_points, is the order of the curve. It affects the shape of the curve between the first and last points. n = 2 for linear, n = 3 for quadratic, n = 4 for cubic, etc. X_points and Y_points represent coordinates of the control points of the spline. The spline will be drawn between the first and the last points defined by their coordinates as (X_points[0], Y_points[0]) and (X_points[-1], Y_points[-1]) n_steps is the number of interpolated points used to draw the spline. By default, numpy sets it to 50. For large values of n_steps (Let's say n_steps > 100), no effect will be visible on the plot. Contrariwise, for small values of n_steps (Let's say n_steps < 20), the spline will start losing its smoothness. show_details plots the control points and the control polygon.