line_profiler.autoprofile package¶
Submodules¶
- line_profiler.autoprofile.ast_profle_transformer module
- line_profiler.autoprofile.ast_tree_profiler module
- line_profiler.autoprofile.autoprofile module
- line_profiler.autoprofile.line_profiler_utils module
- line_profiler.autoprofile.profmod_extractor module
- line_profiler.autoprofile.util_static module
Module contents¶
Auto-Profiling¶
In cases where you want to decorate every function in a script, module, or
package decorating every function with @profile can be tedious. To make
this easier “auto-profiling” was introduced to line_profiler in Version
4.1.0.
The “auto-profile” feature allows users to specify a script or module. This is done by passing the name of script or module to kernprof.
To demonstrate auto-profiling, we first need to generate a Python script to
profile. Write the following code to a file called demo_primes2.py.
def is_prime(n):
'''
Check if the number "n" is prime, with n > 1.
Returns a boolean, True if n is prime.
'''
max_val = n ** 0.5
stop = int(max_val + 1)
for i in range(2, stop):
if n % i == 0:
return False
return True
def find_primes(size):
primes = []
for n in range(size):
flag = is_prime(n)
if flag:
primes.append(n)
return primes
def main():
print('start calculating')
primes = find_primes(100000)
print(f'done calculating. Found {len(primes)} primes.')
if __name__ == '__main__':
main()
Note that this is the nearly the same “primes” example from the “Basic Usage”
section in line_profiler, but none of the functions are decorated
with @profile.
To run this script with auto-profiling we invoke kernprof with -p or
--prof-mod and pass the names of the script. When running with -p we
must also run with -l to enable line profiling. In this example we include
-v as well to display the output after we run it.
python -m kernprof -lv -p demo_primes2.py demo_primes2.py
The output will look like this:
start calculating
done calculating. Found 9594 primes.
Wrote profile results to demo_primes2.py.lprof
Timer unit: 1e-06 s
Total time: 0.677348 s
File: demo_primes2.py
Function: is_prime at line 4
Line # Hits Time Per Hit % Time Line Contents
==============================================================
4 def is_prime(n):
5 '''
6 Check if the number "n" is prime, with n > 1.
7
8 Returns a boolean, True if n is prime.
9 '''
10 100000 19921.6 0.2 2.9 math.floor(1.3)
11 100000 17743.6 0.2 2.6 max_val = n ** 0.5
12 100000 23962.7 0.2 3.5 stop = int(max_val + 1)
13 2745693 262005.7 0.1 38.7 for i in range(2, stop):
14 2655287 342216.1 0.1 50.5 if n % i == 0:
15 90406 10401.4 0.1 1.5 return False
16 9594 1097.2 0.1 0.2 return True
Total time: 1.56657 s
File: demo_primes2.py
Function: find_primes at line 19
Line # Hits Time Per Hit % Time Line Contents
==============================================================
19 def find_primes(size):
20 1 0.3 0.3 0.0 primes = []
21 100000 11689.5 0.1 0.7 for n in range(size):
22 100000 1541848.0 15.4 98.4 flag = is_prime(n)
23 90406 10260.0 0.1 0.7 if flag:
24 9594 2775.9 0.3 0.2 primes.append(n)
25 1 0.2 0.2 0.0 return primes
Total time: 1.61013 s
File: demo_primes2.py
Function: main at line 28
Line # Hits Time Per Hit % Time Line Contents
==============================================================
28 def main():
29 1 17.6 17.6 0.0 print('start calculating')
30 1 1610081.3 2e+06 100.0 primes = find_primes(100000)
31 1 26.6 26.6 0.0 print(f'done calculating. Found {len(primes)} primes.')