benchy_step4.py

...

runner = BenchmarkRunner(suite, '.', 'Cosine benchmarks')
n_benchs, results = runner.run()
print results
#Output:
'{Benchmark('scipy.spatial 0.8.0'):
    {'runtime': {'timing': 18.620705604553223, 'repeat': 3, 'success': True, 'loops': 10, 'timeBaselines': 1994.2583385083014, 'units': 'ms'}, 
     'memory': {'usage': 0.09375, 'units': 'MB', 'repeat': 3, 'success': True}}, 

Benchmark('sklearn 0.13.1'): 
    {'runtime': {'timing': 0.18474507331848145, 'repeat': 3, 'success': True, 'loops': 1000, 'timeBaselines': 19.786006544973198, 'units': 'ms'}, 
     'memory': {'usage': 0.078125, 'units': 'MB', 'repeat': 3, 'success': True}}, 

Benchmark('numpy'): {
     'runtime': {'timing': 0.0093371582031250011, 'repeat': 3, 'success': True, 'loops': 100000, 'timeBaselines': 1.0, 'units': 'ms'}, 
      'memory': {'usage': 0.01171875, 'units': 'MB', 'repeat': 3, 'success': True}},

Benchmark('nltk.cluster'): {
      'runtime': {'timing': 0.010528707504272462, 'repeat': 3, 'success': True, 'loops': 10000, 'timeBaselines': 1.1276136995032031, 'units': 'ms'}, 
      'memory': {'usage': 0.01171875, 'units': 'MB', 'repeat': 3, 'success': True}}}