I use python for scripting, a lot. Python gives me the freedom and flexibility
to whip up a functioning code in the least amount of time with least amount of
effort. In python even the simplest of things can be implemented in many
different ways. For example
a rise to power b can be achieved using:
- Python power function :
- Python power operator :
a ** b
- Writing your own kickass modular exponent
a rise to power bfunction and using it.
which leads to questions like:
- Which of it is the fastest to implement?
- Which of it is the best to use if total execution time is my only constraint?
This may not matter much in a script which we rarely use or even the ones we use on a daily basis. But, these questions becomes extremely important in case of competitive programs where the difference of a second can mean acceptance or time limit exceed.
Obviously, the way to go about it is profiling. There are some really good profilers in python like profile, cProfile, line_profiler, pprofile etc. But profilers print out a ton of data and you have to sift through them to figure out hot zones.
As a famous English idiom goes,
A picture is worth a thousand words
I felt the need for a quick tool which gives me a bird’s eye view of the hot zones in a python code without much effort which led me to create pyheat. This is a simple command line tool which takes python file as an input, profiles it one line at a time and displays the entire program as a heat map indicating areas which consumed the most amount of time.