Profiling analyzes programs to measure memory usage, function call frequency and duration, and time complexity. Python profiling tools include line_profiler and memory_profiler. Line_profiler was initially released in 2008 and measures the time spent on each line of code. It helps identify slow parts of code so developers can optimize performance. The line_profiler output displays the function, line number, number of hits, time per hit, and percentage of time to help analyze profiled code.

1. Python Code
profiling
JACKSON ISAAC
S7 B.TECH CSE
AMRITA VISHWA VIDYAPEETHAM, INDIA

2. What Is Profiling?
 Analysis of a program to measure the memory used by a certain module,
frequency and duration of function calls and the time complexity of the
same.
 Such profiling tools are termed as ‘profilers’.

3. Development tools in python
 Line_profiler
 Memory_profiler
 Clone digger

4. History of line_Profiler
 Initial Release v1.0b1 (2008) by Robert Kern.
 v1.0b2 (2009) – Fixes related to timing overflow on Windows.
 v1.0b3 (2011) – Update Compatibility for newer versions of Cython and
IPython.
 v1.0 (2014, stable release) – Added compatibility for Python 3.x
 Previously supported by kmike’s bitbucket fork of line_profiler.

5. Installing line_profiler
 Using pip – “pip install line_profiler”
 From source:
 git clone https://github.com/rkern/line_profiler.git
 cd line_profiler
 sudo python setup.py install (for python 2.7.x)
 sudo python3 setup.py install (for python3)

6. Using Line_PRofiler
 Adding profiler to the code:
@profile
def foo(bar):
…
 Running line_profiler:
 kernprof.py -l example.py
 python -m line_profiler example.py.lprof
 python3 -m line_profiler example.py.lprof

7. Live DEMO !

8. Understanding output
 Function : Displays the name of the function which is profiled and its line number.
 Line# : Line number of the code in the respective file.
 Hits : Number of times the code in the respective line was executed.
 Time : Total amount of time spent in executing the line in ‘Timer unit’ (i.e 1e-06s here). May
vary from system to system.
 Per Hit : The average amount of time spent in executing the line once in Timer Unit.
 % Time : The percentage of time spent on that line with respect to the total amount of
recorded time spent in the function.
 Line Contents : It displays the actual source code.

9. advantages
 Line_profiler helps us to point out which module of our code is running
slower than expected by profiling the time taken by each line of code.
 Helps in testing large projects, time spent by modules to execute a
particular function.
 Using this data we can modify and improve our code to build faster and
better programs and softwares.

10. Contact
 Website: isaacjackson.me
 Blog: www.jacksonisaac.wordpress.com
 Email: jacksonisaac2008@gmail.com
 Twitter/iJacksonIsaac
 LinkedIn/JacksonIsaac
 github.com/jacksonisaac
 Mozillian/ www.mozillians.org/en-US/u/jacksonisaac2008/