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73 def benchmark(): 74 """Run the benchmark and print benchmark results.""" 75 setup = "from scipy.stats import arcsine; from random import random;" 76 stmt = "y = arcsine.cdf(random(), 10.56789, 55.54321)" 77 78 t = timeit.Timer(stmt, setup=setup) 79 80 print_version() 81 82 for i in xrange(REPEATS): 83 print("# python::" + NAME) 84 elapsed = t.timeit(number=ITERATIONS) 85 print_results(elapsed) 86 print("ok " + str(i+1) + " benchmark finished") 87 88 print_summary(REPEATS, REPEATS)
73 def benchmark(): 74 """Run the benchmark and print benchmark results.""" 75 setup = "from math import exp; from random import random;" 76 stmt = "y = exp(100.0*random() - 50.0)" 77 78 t = timeit.Timer(stmt, setup=setup) 79 80 print_version() 81 82 for i in xrange(REPEATS): 83 print("# python::" + NAME) 84 elapsed = t.timeit(number=ITERATIONS) 85 print_results(elapsed) 86 print("ok " + str(i+1) + " benchmark finished") 87 88 print_summary(REPEATS, REPEATS)
32 def bench(func): 33 """Print the runtime of the decorated function""" 34 @functools.wraps(func) 35 def wrapper_timer(*args, **kwargs): 36 nb_iterations = kwargs.get('nb_iterations', DEFAULT_ITERATIONS) 37 38 total_time = 0.0 39 for i in range(nb_iterations): 40 start_time = timer() 41 value = func(*args, **kwargs) 42 end_time = timer() 43 total_time += end_time - start_time 44 45 total_time /= nb_iterations 46 print(f"Finished in {total_time*1e6:.2f} ns over {nb_iterations} runs") 47 return value 48 return wrapper_timer
6 def test_timer(): 7 '''Testing (Adaptive)ETA when the value doesn't actually change''' 8 widgets = [ 9 progressbar.Timer(), 10 ] 11 p = progressbar.ProgressBar(max_value=2, widgets=widgets, 12 poll_interval=0.0001) 13 14 p.start() 15 p.update() 16 p.update(1) 17 p._needs_update() 18 time.sleep(0.001) 19 p.update(1) 20 p.finish()