The derivative of a B-spline is also a B-spline. You can therefore first fit a spline to your data, then use the derivative formula to construct the coefficients of the derivative spline, and finally use the spline root finding to get the roots of the derivative spline. These are then the maxima/minima of the original curve.
Here is code to do it: https://gist.github.com/pv/5504366
The relevant computation of the coefficients is:
t, c, k = scipys_spline_representation
# Compute the denominator in the differentiation formula.
dt = t[k+1:-1] - t[1:-k-1]
# Compute the new coefficients
d = (c[1:-1-k] - c[:-2-k]) * k / dt
# Adjust knots
t2 = t[1:-1]
# Pad coefficient array to same size as knots (FITPACK convention)
d = np.r_[d, [0]*k]
# Done, a new spline
new_spline_repr = t2, d, k-1