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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 parallel_loop(func, n_jobs=1, verbose=1):
 """run loops in parallel, if joblib is available. Parameters func : function function to be executed in parallel n_jobs : int | None Number of jobs. If set to None, do not attempt to use joblib. verbose : int verbosity level Notes ----- Execution of the main script must be guarded with `if __name__ == '__main__':` when using parallelization. """

    if n_jobs:
        try:
            from joblib import Parallel, delayed
        except ImportError:
            try:
                from sklearn.externals.joblib import Parallel, delayed
            except ImportError:
                n_jobs = None

    if not n_jobs:
        if verbose:
            print('running ', func, ' serially')
        par = lambda x: list(x)
    else:
        if verbose:
            print('running ', func, ' in parallel')
        func = delayed(func)
        par = Parallel(n_jobs=n_jobs, verbose=verbose)

    return par, func