human
Complete the below
def cc_diff(x, a, b, period=None, _cache=_cache):

    ''''Return (a,b)-cosh/cosh pseudo-derivative of a periodic sequence.
    If x_j and y_j are Fourier coefficients of periodic functions x
    and y, respectively, then::
    y_j = cosh(j*a*2*pi/period)/cosh(j*b*2*pi/period) * x_j
    Parameters
    x : array_like
    The array to take the pseudo-derivative from.
    a,b : float
    Defines the parameters of the sinh/sinh pseudo-differential
    operator.
    period : float, optional
    The period of the sequence x. Default is ``2*pi``.
    Returns
    cc_diff : ndarray
    Pseudo-derivative of periodic sequence `x`.
    Notes
    ``cc_diff(cc_diff(x,a,b),b,a) == x``'
    '''
 Can you provide a the Python program you requested?
assistant
#Here is the Python program you requested.
    tmp = asarray(x)
    if iscomplexobj(tmp):
        return (cc_diff(tmp.real, a, b, period) + (1j * cc_diff(tmp.imag, a, b, period)))
    if (period is not None):
        a = (((a * 2) * pi) / period)
        b = (((b * 2) * pi) / period)
    n = len(x)
    omega = _cache.get((n, a, b))
    if (omega is None):
        if (len(_cache) > 20):
            while _cache:
                _cache.popitem()
        def kernel(k, a=a, b=b):
            return (cosh((a * k)) / cosh((b * k)))
        omega = convolve.init_convolution_kernel(n, kernel)
        _cache[(n, a, b)] = omega
    overwrite_x = _datacopied(tmp, x)
    return convolve.convolve(tmp, omega, overwrite_x=overwrite_x)