Testing a pitch shifting Algo. from http://zulko.github.io/blog/2014/03/29/soundstretching-and-pitch-shifting-in-python/

pitch_shift.py

import numpy as np

def speedx(sound_array, factor):
    """ Multiplies the sound's speed by some `factor` """
    indices = np.round( np.arange(0, len(sound_array), factor) )
    indices = indices[indices < len(sound_array)].astype(int)
    return sound_array[ indices.astype(int) ]

def stretch(sound_array, f, window_size, h):
    """ Stretches the sound by a factor `f` """

    phase  = np.zeros(window_size)
    hanning_window = np.hanning(window_size)
    result = np.zeros( len(sound_array) /f + window_size)

    for i in np.arange(0, len(sound_array)-(window_size+h), h*f):

        # two potentially overlapping subarrays
        a1 = sound_array[i: i + window_size]
        a2 = sound_array[i + h: i + window_size + h]

        # resynchronize the second array on the first
        s1 =  np.fft.fft(hanning_window * a1)
        s2 =  np.fft.fft(hanning_window * a2)
        phase = (phase + np.angle(s2/s1)) % 2*np.pi
        a2_rephased = np.fft.ifft(np.abs(s2)*np.exp(1j*phase))

        # add to result
        i2 = int(i/f)
        result[i2 : i2 + window_size] += hanning_window*a2_rephased.real

    result = ((2**(16-4)) * result/result.max()) # normalize (16bit)

    return result.astype('int16')

def pitchshift(snd_array, n, window_size=2**13, h=2**11):
    """ Changes the pitch of a sound by ``n`` semitones. """
    factor = 2**(1.0 * n / 12.0)
    stretched = stretch(snd_array, 1.0/factor, window_size, h)
    return speedx(stretched[window_size:], factor)


if __name__ == "__main__":
    from matplotlib import pyplot as plt
    SAMPLE_RATE = 44000
    FREQ = 440.0
    DURATION = 1
    X = np.arange(DURATION*SAMPLE_RATE)
    S = np.sin(2*np.pi*FREQ*X/SAMPLE_RATE)
    fig = plt.figure()
    ax = fig.add_subplot(111)
    Ss = [S]
    for n in range(1,13):
        Sn = pitchshift(S,n)
        Ss.append(Sn)
        ax.plot(Sn)
    Ss = np.hstack(Ss)
    # Generate wave file
    from scipy.io import wavfile
    from scipy.interpolate import interp1d

    wavfile.write("out.wav", SAMPLE_RATE, Ss.astype("float32"))
    #show the graphs but allow program to continue
    plt.show(block = False)
    #wait for the user
    input("press enter to exit")
    plt.close('all')

It sort of works, but the sounds are crusty and the envelopes are wonky!