Using multiple threads on CPython won’t give you better performance for pure-Python code due to the global interpreter lock (GIL). I suggest using the
multiprocessing module instead:
pool = multiprocessing.Pool(4) out1, out2, out3 = zip(*pool.map(calc_stuff, range(0, 10 * offset, offset)))
Note that this won’t work in the interactive interpreter.
To avoid the usual FUD around the GIL: There wouldn’t be any advantage to using threads for this example anyway. You want to use processes here, not threads, because they avoid a whole bunch of problems.