102 lines
1.7 KiB
Python
102 lines
1.7 KiB
Python
#!/usr/bin/env python
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'''
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Compare spawn to spawn_n, among other things.
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This script will generate a number of "properties" files for the
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Hudson plot plugin
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'''
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import os
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import eventlet
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import benchmarks
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DATA_DIR = 'plot_data'
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if not os.path.exists(DATA_DIR):
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os.makedirs(DATA_DIR)
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def write_result(filename, best):
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fd = open(os.path.join(DATA_DIR, filename), 'w')
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fd.write('YVALUE=%s' % best)
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fd.close()
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def cleanup():
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eventlet.sleep(0.2)
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iters = 10000
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best = benchmarks.measure_best(
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5, iters,
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'pass',
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cleanup,
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eventlet.sleep)
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write_result('eventlet.sleep_main', best[eventlet.sleep])
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gt = eventlet.spawn(
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benchmarks.measure_best, 5, iters,
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'pass',
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cleanup,
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eventlet.sleep)
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best = gt.wait()
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write_result('eventlet.sleep_gt', best[eventlet.sleep])
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def dummy(i=None):
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return i
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def run_spawn():
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eventlet.spawn(dummy, 1)
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def run_spawn_n():
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eventlet.spawn_n(dummy, 1)
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def run_spawn_n_kw():
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eventlet.spawn_n(dummy, i=1)
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best = benchmarks.measure_best(
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5, iters,
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'pass',
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cleanup,
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run_spawn_n,
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run_spawn,
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run_spawn_n_kw)
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write_result('eventlet.spawn', best[run_spawn])
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write_result('eventlet.spawn_n', best[run_spawn_n])
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write_result('eventlet.spawn_n_kw', best[run_spawn_n_kw])
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pool = None
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def setup():
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global pool
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pool = eventlet.GreenPool(iters)
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def run_pool_spawn():
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pool.spawn(dummy, 1)
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def run_pool_spawn_n():
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pool.spawn_n(dummy, 1)
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def cleanup_pool():
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pool.waitall()
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best = benchmarks.measure_best(
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3, iters,
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setup,
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cleanup_pool,
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run_pool_spawn,
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run_pool_spawn_n,
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)
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write_result('eventlet.GreenPool.spawn', best[run_pool_spawn])
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write_result('eventlet.GreenPool.spawn_n', best[run_pool_spawn_n])
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