Optimization Techniques in Python
A surprising feature of Python is that the pythonic code is quite efficient... So a few general hints:

Use built-ins and standard functions whenever possible, they're already quite well optimized.
Try to use lazy generators instead one-off temporary lists.
Use numpy for vector arithmetic.
Use psyco if running on x86 32bit.
Write performance critical loops in a lower level language (C, Pyrex, Cython, etc.).
When calling the same method of a collection of objects, get a reference to the class function and use it, it will save lookups in the objects dictionaries (this one is a micro-optimization, not sure it's worth)

And of course, if scalability is what matters:

Use O(n) (or better) algorithms! Otherwise your system cannot be linearly scalable.
Write multiprocessor aware code. At some point you'll need to throw more computing power at it, and your software must be ready to use it!
Recently i have developed a billing application for my company with Python/Django. For few months everything was fine but now i am observing that the performance is dropping because of more and more users using that applications. Now the problem is that the application is now very critical for the finance team. Now the finance team are after my life for sorting out the performance issue. I have no other option but to find a way to increase the performance of the billing application. 
So do you guys know any performance optimization techniques in python that will really help me   with the scalability issue
Guys we are using mysql database and its hosted on apache web server on Linux box. Secondly what i have noticed more is the over all application is slow and not the database transactional part. For example once the application is loaded then it works fine but if they navigate to other link on that application then it takes a whole lot of time.
And yes we are using HTML, CSS and Javascript