2014-04-04 14:40:11 +00:00
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import textwrap
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2014-03-12 10:00:21 +00:00
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import timeit
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2014-04-04 14:40:11 +00:00
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import argparse
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from benchmarks import benchmarks, search_functions
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2014-03-12 10:00:21 +00:00
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2014-04-04 14:40:11 +00:00
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def print_results(timings, number, repeat, precision=3):
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best = min(timings)
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usec = best * 1e6 / number
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if usec < 1000:
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x = "best of %d: %.*g usec per loop" % (repeat, precision, usec)
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else:
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msec = usec / 1000
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if msec < 1000:
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x = "best of %d: %.*g msec per loop" % (repeat, precision, msec)
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else:
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sec = msec / 1000
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x = "best of %d: %.*g sec per loop" % (repeat, precision, sec)
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print("%d loops, " % number + x)
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parser = argparse.ArgumentParser(description='Run fuzzysearch benchmarks.')
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parser.add_argument('search_function', choices=search_functions)
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parser.add_argument('benchmark', choices=benchmarks)
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parser.add_argument('-r', '--repetitions', type=int, default=5,
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help='number of times to run the benchmark')
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parser.add_argument('-n', '--number', type=int, default=10**5,
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help='number of loop iterations to run in each repetition')
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args = parser.parse_args()
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setup = textwrap.dedent('''\
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from benchmarks import get_benchmark, run_benchmark
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search_func, search_args = get_benchmark({search_function!r},
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{benchmark!r})
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''').format(**args.__dict__)
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2014-05-16 09:18:05 +00:00
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code = 'run_benchmark(search_func, search_args)'
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2014-04-04 14:40:11 +00:00
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timings = timeit.Timer(code, setup=setup).repeat(args.repetitions, args.number)
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print_results(timings, args.number, args.repetitions)
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