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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 run_multicore(fn, items, config, parallel=None):
 """Run the function using multiple cores on the given items to process. """

    if len(items) == 0:
        return []
    if parallel is None or "num_jobs" not in parallel:
        if parallel is None:
            parallel = {"type": "local", "cores": config["algorithm"].get("num_cores", 1)}
        sysinfo = system.get_info({}, parallel)
        parallel = resources.calculate(parallel, items, sysinfo, config,
                                       parallel.get("multiplier", 1),
                                       max_multicore=int(parallel.get("max_multicore", sysinfo["cores"])))
    items = [config_utils.add_cores_to_config(x, parallel["cores_per_job"]) for x in items]
    if joblib is None:
        raise ImportError("Need joblib for multiprocessing parallelization")
    out = []
    for data in joblib.Parallel(parallel["num_jobs"], batch_size=1, backend="multiprocessing")(joblib.delayed(fn)(*x) for x in items):
        if data:
            out.extend(data)
    return out