Update: As folks have pointed out this answer is not correct. A probplot is different from a quantile-quantile plot. Please see those comments and other answers before you make an error in interpreting or conveying your distributions’ relationship.
I think that scipy.stats.probplot will do what you want. See the documentation for more detail.
import numpy as np
import pylab
import scipy.stats as stats
measurements = np.random.normal(loc = 20, scale = 5, size=100)
stats.probplot(measurements, dist="norm", plot=pylab)
pylab.show()
Result
