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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def exponweib_like(x, alpha, k, loc=0, scale=1):
 R""" Exponentiated Weibull log-likelihood. The exponentiated Weibull distribution is a generalization of the Weibull family. Its value lies in being able to model monotone and non-monotone failure rates. .. math:: f(x \mid \alpha,k,loc,scale) & = \frac{\alpha k}{scale} (1-e^{-z^k})^{\alpha-1} e^{-z^k} z^{k-1} \\ z & = \frac{x-loc}{scale} :Parameters: - `x` : x > 0 - `alpha` : Shape parameter - `k` : k > 0 - `loc` : Location parameter - `scale` : Scale parameter (scale > 0). """

    return flib.exponweib(x, alpha, k, loc, scale)