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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(self, funcs):
 """Run a set of functions in parallel, returning their results. Make sure any function you pass exits with a reasonable timeout. If it doesn't return within the timeout or the result is ignored due an exception in a separate thread it will continue to stick around until it finishes, including blocking process exit. Args: funcs: An iterable of functions or iterable of args to functools.partial. Returns: A list of return values with the values matching the order in funcs. Raises: Propagates the first exception encountered in one of the functions. """

    funcs = [f if callable(f) else functools.partial(*f) for f in funcs]
    if len(funcs) == 1:  # Ignore threads if it's not needed.
      return [funcs[0]()]
    if len(funcs) > self._workers:  # Lazy init and grow as needed.
      self.shutdown()
      self._workers = len(funcs)
      self._executor = futures.ThreadPoolExecutor(self._workers)
    futs = [self._executor.submit(f) for f in funcs]
    done, not_done = futures.wait(futs, self._timeout, futures.FIRST_EXCEPTION)
    # Make sure to propagate any exceptions.
    for f in done:
      if not f.cancelled() and f.exception() is not None:
        if not_done:
          # If there are some calls that haven't finished, cancel and recreate
          # the thread pool. Otherwise we may have a thread running forever
          # blocking parallel calls.
          for nd in not_done:
            nd.cancel()
          self.shutdown(False)  # Don't wait, they may be deadlocked.
        raise f.exception()
    # Either done or timed out, so don't wait again.
    return [f.result(timeout=0) for f in futs]