line-profiler-decorator
Wrapper around line-profiler adding a few features as an decorator
Install
pip install line-profiler-decoratorUsage
from time import sleep
from line_profiler_decorator import profiler
@profiler
def slow_function():
print("quick line")
sleep(1) # slow one
sleep(0.3) # not that slowOutput
quick line
Timer unit: 1e-06 s
Total time: 6.52823 s
File: /Users/fabio/projects/line-profiler-decorator/examples/example.py
Function: slow_function at line 5
Line # Hits Time Per Hit % Time Line Contents
==============================================================
5 @profiler(aggregate=True)
6 def slow_function():
7 5 69.0 13.8 0.0 print("quick line")
8 5 5016944.0 1003388.8 76.8 sleep(1) # slow one
9 5 1511218.0 302243.6 23.1 sleep(0.3) # not that slow
Options
Save output to a file
Save the output to a file instead of stdout
@profiler("output_file.txt")
def slow_function():
print("quick line")
sleep(1) # slow one
sleep(0.3) # not that slowAggregate results
Aggregate the results of multiple calls to the decorated function
@profiler(aggregate=True)
def slow_function():
print("quick line")
sleep(1) # slow one
sleep(0.3) # not that slow
def run_slow(n=100):
for _ in range(n):
slow_function()Follow function
from time import sleep
from line_profiler_decorator import profiler
def other_function():
sleep(1) # slow one
sleep(0.3) # not that slow
@profiler(follow=[other_function])
def function_that_calls_other_function(n):
for _ in range(n):
other_function()Output
In [3]: function_that_calls_other_function(10)
Timer unit: 1e-06 s
Total time: 13.0668 s
File: /Users/fabio/projects/line-profiler-decorator/examples/example.py
Function: other_function at line 17
Line # Hits Time Per Hit % Time Line Contents
==============================================================
17 def other_function():
18 10 10037030.0 1003703.0 76.8 sleep(1) # slow one
19 10 3029725.0 302972.5 23.2 sleep(0.3) # not that slow
Total time: 13.0672 s
File: /Users/fabio/projects/line-profiler-decorator/examples/example.py
Function: function_that_calls_other_function at line 22
Line # Hits Time Per Hit % Time Line Contents
==============================================================
22 @profiler(follow=[other_function])
23 def function_that_calls_other_function(n):
24 11 97.0 8.8 0.0 for _ in range(n):
25 10 13067104.0 1306710.4 100.0 other_function()
Grouped aggregations
Group aggregations using a key function.
key is a function that receives the same arguments as the decorated function and returns a value.
The profile results of each call of the decorated function will be grouped and aggregated together by the value returned by the key function
Example:
from time import sleep
from line_profiler_decorator import profiler
@profiler(aggregate=True, key=lambda x: x % 2 == 0)
def function_with_grouped_aggregations(number):
"""This function runs faster for even numbers."""
if number % 2:
# sleep for 1 second if number is odd
sleep(1)
else:
# sleep for 0.2 second if number is even
sleep(0.2)
sleep(0.5)
def run_function_with_grouped_aggregations(n=10):
for _ in range(n):
function_with_grouped_aggregations(_)Output
The key function returns value True for even numbers and False for odd numbers.
That way the aggregated results will be grouped into 2 profile results.
Timer unit: 1e-06 s
Total time: 3.533 s
File: /Users/fabio/projects/line-profiler-decorator/examples/example.py
Function: function_with_filtered_aggregations at line 28
Line # Hits Time Per Hit % Time Line Contents
==============================================================
28 @profiler(aggregate=True, key=lambda x: x % 2 == 0)
29 def function_with_filtered_aggregations(number):
30 """This function runs faster for even numbers."""
31 5 17.0 3.4 0.0 if number % 2:
32 # sleep for 1 second if number is odd
33 sleep(1)
34 else:
35 # sleep for 0.2 second if number is even
36 5 1015312.0 203062.4 28.7 sleep(0.2)
37 5 2517674.0 503534.8 71.3 sleep(0.5)
Timer unit: 1e-06 s
Total time: 7.53658 s
File: /Users/fabio/projects/line-profiler-decorator/examples/example.py
Function: function_with_filtered_aggregations at line 28
Line # Hits Time Per Hit % Time Line Contents
==============================================================
28 @profiler(aggregate=True, key=lambda x: x % 2 == 0)
29 def function_with_filtered_aggregations(number):
30 """This function runs faster for even numbers."""
31 5 15.0 3.0 0.0 if number % 2:
32 # sleep for 1 second if number is odd
33 5 5017337.0 1003467.4 66.6 sleep(1)
34 else:
35 # sleep for 0.2 second if number is even
36 sleep(0.2)
37 5 2519231.0 503846.2 33.4 sleep(0.5)
Looking at the results above we can see that the first block only aggregated call with even number
therefore spent no time at line 33. On the other hand, the second block shows the same for odd numbers
where no time was used on even numbers.
