pyFBI
pyFBI enables "as much as needed" profiling by decorator.
import time
import pyfbi
@pyfbi.target
def func1():
time.sleep(1)
def func2():
time.sleep(2)
@pyfbi.target
def func3():
time.sleep(3)
with pyfbi.watch():
[f() for f in (func1, func2, func3)]
pyfbi.show()Then only "target" function (func1 & func3) is profiled.
6 function calls in 4.003 seconds
Random listing order was used
ncalls tottime percall cumtime percall filename:lineno(function)
2 4.003 2.002 4.003 2.002 {built-in method time.sleep}
1 0.000 0.000 1.003 1.003 tests/demo.py:8(func1)
2 0.000 0.000 0.000 0.000 {method 'disable' of '_lsprof.Profiler' objects}
1 0.000 0.000 3.000 3.000 tests/demo.py:15(func3)
You can save the result to the file.
pyfbi.dump("your_stat_file_path")
If you want to watch the all functions, set global_watch=True.
with pyfbi.watch(global_watch=True):
[f() for f in (func1, func2, func3)]
pyfbi.show() 17 function calls in 6.007 seconds
Random listing order was used
ncalls tottime percall cumtime percall filename:lineno(function)
1 0.000 0.000 0.000 0.000 {built-in method builtins.next}
3 6.007 2.002 6.007 2.002 {built-in method time.sleep}
1 0.000 0.000 1.004 1.004 tests/demo.py:8(func1)
1 0.000 0.000 2.002 2.002 tests/demo.py:12(func2)
1 0.000 0.000 3.000 3.000 tests/demo.py:15(func3)
1 0.000 0.000 6.007 6.007 tests/demo.py:26(<listcomp>)
...
Installation
pip install pyfbi
Special Features
Scheduled Stat
The following script store the stat for each 5 seconds.
import pyfbi
(set target to your function)
stat_dir = os.path.join(os.path.dirname(__file__), "stats")
# You can use global_watch=True if you want to profile all functions.
with pyfbi.watch_periodic(seconds=5, stat_dir=stat_dir):
for f in [func1, func2, func2, func3, func1, func1]:
f()Visualization
If you install the pyFBI, you can use pyfbi_viz command to visualize the stats.
pyfbi_viz --stat_dir=stat_dir
(stat_dir is the directory that stat file is stored)
