How to Speed Up Your Code with Komodo IDE

In many arenas of computing, speed is the name of the game. Being able to compute quickly, generate results immediately, and fetch data instantly are key objectives for mission-critical software products. As code bases grow in size, it is often difficult to identify bottlenecks, the places in software where the most CPU time is spent, and optimize them in order to get that little extra bit of speed. As algorithms get more complex, it is often difficult to determine at a glance which is better suited in a production environment. Fortunately, Komodo IDE is here to help.

Komodo IDE comes with a built-in code profiler for many of its supported languages. Invoking it is as simple as these three steps:

  • Load up your application's source code entry point (typically the main method)
  • Open the "Debug" menu
  • Select "Start Code Profiling"

You will be prompted with the usual Debug/Run dialog, only this time, after your process finishes, Komodo will present you with a dialog that shows a detailed account of how much time was spent in each chunk of your code. Using the drill-down interface, you can quickly identify the bottlenecks that need attention and fix them. Similarly, you can benchmark different algorithms and figure out which one performs the best.

Identifying Bottlenecks

Komodo's profiler makes it incredibly easy to spot bottlenecks with its graph view. Consider this profiler result:

Speed Up Code with Komodo IDE Unoptimized

It is quite clear that in this small script where work is being distributed over two methods, the work2() method is consuming an inordinate amount of CPU time compared to work1(). Therefore attention should be focused on optimizing the routines in work2() as opposed to the routines in work1(). After the optimization, Komodo's profiler might report something like this:

Speed Up Code with Komodo IDE Optimized

Much better. Even though work2() is still slower than work1(), the difference in compute time between them has been drastically reduced.

Benchmarking Algorithms

Komodo's profiler can also be used to quickly benchmark algorithms. This may be quite helpful in a number of situations, such as when you are not sure which algorithm to put into a production system.

Back in your early days of coding, you were told that repeated string concatenation is expensive. But just how expensive is it? We can leverage Komodo to help determine the answer.

Consider the following Python code:

    def inefficient(strs):
        result = ""
        for s in strs:
            result += s
        return result

    def more_efficient(strs):
        return "".join(strs)

    strs = [str(i) for i in xrange(1000000)]

Komodo's profiler allows us to visualize how much more expensive inefficient() is than more_efficient():

Speed Up Code with Komodo IDE Compare Screenshot

Clearly the more_efficient() algorithm is better-suited for production.


When application speed is critical, Komodo IDE's profiling tools rise to the challenge, aiding developers in easily identifying bottlenecks in their existing code and helping them determine which algorithms are best-suited for primetime. Not only can you use Komodo to profile code in real-time, but you can also run your own profiling code outside of Komodo, save that data to a file, and then have Komodo load, process, and visualize the results. For more information, please visit