Using profiling to find bottlenecks

Profiling is an important tool when we decide to scale the application. Before scaling, we want to know whether any process is a bottleneck and affects the overall performance. Python has an inbuilt profiler, cProfile, that can do the job for us, but to make life easier, Werkzeug has a ProfilerMiddleware of its own, which is written over cProfile. We will use this to determine whether there is anything that affects the performance.

Getting ready

We will use the application from the previous recipe and add ProfilerMiddleware in a new file named generate_profile.py.

How to do it…

Create a new file, generate_profile.py, alongside run.py, which works like run.py itself but with ProfilerMiddleware:

from werkzeug.contrib.profiler import ProfilerMiddleware
from my_app import app

app.wsgi_app = ProfilerMiddleware(app.wsgi_app, restrictions = [10])
app.run(debug=True)

Here, we imported ProfilerMiddleware from werkzeug and then modified wsgi_app on our Flask app to use...