Skip to content

02-performance-analysis.md

Latest commit

 

History

History
147 lines (103 loc) · 2.87 KB

02-performance-analysis.md

File metadata and controls

147 lines (103 loc) · 2.87 KB
Raw
title Performance analysis
lang en

Performance measurement {.section}

Measuring application performance

  • Correctness is the most import factor in any application
    • Premature optimization is the root of all evil!
  • Before starting to optimize application, one should measure where time is spent
    • Typically 90 % of time is spent in 10 % of application
- Mind the algorithm! - Recursive calculation of Fibonacci numbers
Speedup
Pure Python 1
Pure C 126
Pure Python (better algorithm) 24e6

Measuring application performance

  • Applications own timers
  • timeit module
  • cProfile module
  • Full fedged profiling tools: TAU, Intel Vtune, Python Tools for Visual Studio ...

Measuring application performance

  • Python time module can be used for measuring time spent in specific part of the program
    • time.perf_counter() : include time spent in other processes
    • time.process_time() : only time in current process
import time

t0 = time.process_time()
for n in range(niter):
    heavy_calculation()
t1 = time.process_time()

print('Time spent in heavy calculation', t1-t0)

timeit module

  • Easy timing of small bits of Python code
  • Tries to avoid common pitfalls in measuring execution times
  • Command line interface and Python interface
  • %timeit magic in IPython
In [1]: from mymodule import func
In [2]: %timeit func()

10 loops, best of 3: 433 msec per loop
$ python -m timeit -s "from mymodule import func" "func()"

10 loops, best of 3: 433 msec per loop

cProfile

  • Execution profile of Python program
    • Time spent in different parts of the program
    • Call graphs
  • Python API:
  • Profiling whole program from command line
import cProfile
...

# profile statement and save results to a file func.prof
cProfile.run('func()', 'func.prof')
$ python -m cProfile -o myprof.prof myprogram.py

Investigating profile with pstats

  • Printing execution time of selected functions
  • Sorting by function name, time, cumulative time, ...
  • Python module interface and interactive browser
In [1]: from pstats import Stats
In [2]: p = Stats('myprof.prof')
In [3]: p.strip_dirs()
In [4]: p.sort_stats('time')
In [5]: p.print_stats(5)

Mon Oct 12 10:11:00 2016 my.prof
...

$ python -m pstats myprof.prof

Welcome to the profile statistics
% strip
% sort time
% stats 5

Mon Oct 12 10:11:00 2016 my.prof
...

Summary

  • Python has various built-in tools for measuring application performance
  • time module
  • timeit module
  • cProfile and pstats modules