Book Image

Django 1.1 Testing and Debugging

Book Image

Django 1.1 Testing and Debugging

Overview of this book

Bugs are a time consuming burden during software development. Django's built-in test framework and debugging support help lessen this burden. This book will teach you quick and efficient techniques for using Django and Python tools to eradicate bugs and ensure your Django application works correctly. This book will walk you step by step through development of a complete sample Django application. You will learn how best to test and debug models, views, URL configuration, templates, and template tags. This book will help you integrate with and make use of the rich external environment of test and debugging tools for Python and Django applications. The book starts with a basic overview of testing. It will highlight areas to look out for while testing. You will learn about different kinds of tests available, and the pros and cons of each, and also details of test extensions provided by Django that simplify the task of testing Django applications. You will see an illustration of how external tools that provide even more sophisticated testing features can be integrated into Django's framework. On the debugging front, the book illustrates how to interpret the extensive debugging information provided by Django's debug error pages, and how to utilize logging and other external tools to learn what code is doing.
Table of Contents (17 chapters)
Django 1.1 Testing and Debugging
Credits
About the Author
About the Reviewer
Preface
Index

Improving the matplotlib approach


Consider what happens now when the page for a completed survey is requested by a browser. For each question in the survey, the returned completed survey page has an embedded image that, when fetched, will trigger a call to the answer_piechart view. That view dynamically generates an image and is computationally expensive. In fact, depending on your hardware, if you try stepping through that view you may be able to observe appreciable pauses when stepping over some of the matplotlib calls.

Now consider what happens when many different users request the same completed survey page. That will trigger many calls into the computationally expensive answer_piechart view. Ultimately, all of the users will be served the exact same data, since results are not displayed until the survey is closed, so the underlying vote counts used to create the pie chart will not be changing. Yet answer_piechart will be called over and over to re-do the same considerable amount of work...