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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 hypergeometric_like(x, n, m, N):
 R""" Hypergeometric log-likelihood. Discrete probability distribution that describes the number of successes in a sequence of draws from a finite population without replacement. .. math:: f(x \mid n, m, N) = \frac{\left({ \begin{array}{c} {m} \\ {x} \\ \end{array} }\right)\left({ \begin{array}{c} {N-m} \\ {n-x} \\ \end{array}}\right)}{\left({ \begin{array}{c} {N} \\ {n} \\ \end{array}}\right)} :Parameters: - `x` : [int] Number of successes in a sample drawn from a population. - `n` : [int] Size of sample drawn from the population. - `m` : [int] Number of successes in the population. - `N` : [int] Total number of units in the population. .. note:: :math:`E(X) = \frac{n n}{N}` """


    return flib.hyperg(x, n, m, N)