Tutorial

This tutorial will show you how to install and configure django-analytical for basic tracking, and then briefly touch on two common customization issues: visitor identification and custom data tracking.

Suppose your Django website provides information about the IPv4 to IPv6 transition. Visitors can discuss their problems and help each other make the necessary changes to their network infrastructure. You want to use two different analytics services:

  • Clicky for detailed traffic analysis
  • Crazy Egg to see where visitors click on your pages

At the end of this tutorial, the project will track visitors on both Clicky and Crazy Egg, identify authenticated users and add extra tracking data to segment mouse clicks on Crazy Egg based on whether visitors are using IPv4 or IPv6.

Setting up basic tracking

To get started with django-analytical, the package must first be installed. You can download and install the latest stable package from the Python Package Index automatically by using easy_install:

$ easy_install django-analytical

For more ways to install django-analytical, see Installing the Python package.

After you install django-analytical, you need to add it to the list of installed applications in the settings.py file of your project:

INSTALLED_APPS = [
    ...
    'analytical',
    ...
]

Then you have to add the general-purpose django-analytical template tags to your base template:

{% load analytical %}
<!DOCTYPE ... >
<html>
    <head>
        {% analytical_head_top %}

        ...

        {% analytical_head_bottom %}
    </head>
    <body>
        {% analytical_body_top %}

        ...

        {% analytical_body_bottom %}
    </body>
</html>

Finally, you need to configure the Clicky Site ID and the Crazy Egg account number. Add the following to your project settings.py file (replacing the x‘s with your own codes):

CLICKY_SITE_ID = 'xxxxxxxx'
CRAZY_EGG_ACCOUNT_NUMBER = 'xxxxxxxx'

The analytics services are now installed. If you run Django with these changes, both Clicky and Crazy Egg will be tracking your visitors.

Identifying authenticated users

Suppose that when your visitors post questions on IPv6 or tell others about their experience with the transition, they first log in through the standard Django authentication system. Clicky can identify and track individual visitors and you want to use this feature.

If django-analytical template tags detect that the current user is authenticated, they will automatically include code to send the username to services that support this feature. This only works if the template context has the current user in the user or request.user context variable. If you use a RequestContext to render templates (which is recommended anyway) and have the django.contrib.auth.context_processors.auth context processor in the TEMPLATE_CONTEXT_PROCESSORS setting (which is default), then this identification works without having to make any changes.

For more detailed information on automatic identification, and how to disable or override it, see Identifying authenticated users.

Adding custom tracking data

Suppose that you think that visitors who already have IPv6 use the website in a different way from those still on IPv4. You want to test this hypothesis by segmenting the Crazy Egg heatmaps based on the IP protocol version.

In order to filter on protocol version in Crazy Egg, you need to include the visitor IP protocol version in the Crazy Egg tracking code. The easiest way to do this is by using a context processor:

def track_ip_proto(request):
    addr = request.META.get('HTTP_X_FORWARDED_FOR', '')
    if not addr:
        addr = request.META.get('REMOTE_ADDR', '')
    if ':' in addr:
        proto = 'ipv6'
    else:
        proto = 'ipv4'  # assume IPv4 if no information
    return {'crazy_egg_var1': proto}

Use a RequestContext when rendering templates and add the 'track_ip_proto' to TEMPLATE_CONTEXT_PROCESSORS. In Crazy Egg, you can now select User Var1 in the overlay or confetti views to see whether visitors using IPv4 behave differently from those using IPv6.


This concludes the tutorial. For information about setting up, configuring and customizing the different analytics services, see Features and customization and Services.