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Scaling a Django Application with Memcache

Last updated February 26, 2025

Memcache is a technology that improves the performance and scalability of web apps and mobile app backends. You should consider using Memcache when your pages are loading too slowly or your app is having scalability issues. Even for small sites, Memcache can make page loads snappy and help future-proof your app.

This guide shows how to create a simple Django 2.1 application, deploy it to Heroku, then add Memcache to alleviate a performance bottleneck.

This article mainly targets Python 3 since Django 2+ no longer supports Python 2. If you want to use Python 2 with an older version of Django this guide should however still work.

The sample app in this guide can be seen running here. You can view the source code or deploy it with this Heroku Button:

Deploy to Heroku

Prerequisites

Before you complete the steps in this guide, make sure you have all of the following:

Create a Django application for Heroku

The following commands will create an empty Django app. A detailed explanation of these commands can be found in Deploying Python and Django Apps.

$ mkdir django_memcache && cd django_memcache
$ python -m venv venv    # For Python 2 use `virtualenv venv`
$ source venv/bin/activate
(venv) $ pip install Django django-on-heroku gunicorn
(venv) $ django-admin.py startproject django_tasklist .
(venv) $ pip freeze > requirements.txt
(venv) $ python manage.py runserver
Performing system checks...

System check identified no issues (0 silenced).

Django version 2.0, using settings 'django_tasklist.settings'
Starting development server at http://127.0.0.1:8000/
Quit the server with CONTROL-C.

Visiting http://localhost:8000 will show a “hello, world” landing page.

Configure Django for Heroku

For the Django app to work on Heroku, some Heroku specific configuration is required:

  1. Add a Procfile to let Heroku know how to start your app:
   $ echo "web: gunicorn django_tasklist.wsgi --log-file -" > Procfile
  1. Add the Heroku specific configuration to the settings which the Django app requires in order to work on Heroku, mainly for the database to work and the static files to be served. Luckily, there is a django-on-heroku package that takes care of all that. So on the bottom of the file django_tasklist/settings.py add the following lines:
   # Configure Django App for Heroku.
   import django_heroku
   django_heroku.settings(locals())

For more information about these Heroku specific settings see Configuring Django Apps for Heroku. Note: django-on-heroku only supports Python 3. For Python 2 please follow the instructions in Configuring Django Apps for Heroku.

Deploy on Heroku

Our code needs to be added to a git repository before it can be deployed to Heroku. First, edit .gitignore and adding the following lines to exclude unnecessary files:

venv
*.pyc
db.sqlite3

Then initialize a git repository and make a commit:

$ git init
$ git add .
$ git commit -m "Empty django app"

Now, create a Heroku app using heroku create:

$ heroku create
Creating app... done, ⬢ blooming-ridge-97247
https://blooming-ridge-97247.herokuapp.com/ | https://git.heroku.com/blooming-ridge-97247.git

And then deploy the app:

$ git push heroku master

Finally, you can use the Heroku CLI to view the app in your browser:

$ heroku open

You will see the same “hello, world” landing page you saw in local development mode except running on the Heroku platform.

Add task list functionality

The Django application we are building is a task list. In addition to displaying the list, it will have actions to add new tasks and to remove them.

First, make the Django mc_tasklist app:

(venv) $ python manage.py startapp mc_tasklist

Add mc_tasklist to the list of installed apps in django_tasklist/settings.py:

INSTALLED_APPS = (
    'django.contrib.admin',
    # ...
    'mc_tasklist',
)

Now we can add the task list functionality in four steps:

  1. Create a simple Task model in mc_tasklist/models.py:
   from django.db import models

   class Task(models.Model):
       name = models.TextField()

Use makemigrations and migrate to create a migration for the mc_tasklist app as well as create the mc_tasklist_tasks table locally, along with all other default Django tables:

   (venv) $ python manage.py makemigrations mc_tasklist
   (venv) $ python manage.py migrate
  1. Setup the routes for add, remove, and index methods in django_tasklist/urls.py:
   # ...
   from mc_tasklist import views
   urlpatterns = [
       # ...
       path('add', views.add),
       path('remove', views.remove),
       path('', views.index),
   ]
  1. Add corresponding view controllers in mc_tasklist/views.py:
   from django.template.context_processors import csrf
   from django.shortcuts import render, redirect
   from mc_tasklist.models import Task

   def index(request):
       tasks = Task.objects.order_by("id")
       c = {'tasks': tasks}
       c.update(csrf(request))
       return render(request, 'index.html', c)

   def add(request):
       item = Task(name=request.POST["name"])
       item.save()
       return redirect("/")

   def remove(request):
       item = Task.objects.get(id=request.POST["id"])
       if item:
           item.delete()
       return redirect("/")
  1. Create a template with display code in mc_tasklist/templates/index.html:
   <!DOCTYPE html>
   <head>
     <meta charset="utf-8">
     <title>MemCachier Django tutorial</title>
     <!-- Fonts -->
     <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.4.0/css/font-awesome.min.css"
           rel='stylesheet' type='text/css' />
     <!-- Bootstrap CSS -->
     <link href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css"
           rel="stylesheet" />
   </head>

   <body>
     <div class="container">
       <!-- New Task Card -->
       <div class="card">
         <div class="card-body">
           <h5 class="card-title">New Task</h5>

           <form action="add" method="POST">
             {% csrf_token %}
             <div class="form-group">
               <input type="text" class="form-control" placeholder="Task Name"
                      name="name" required>
             </div>
             <button type="submit" class="btn btn-default">
               <i class="fa fa-plus"></i> Add Task
             </button>
           </form>
         </div>
       </div>

       <!-- Current Tasks -->
       {% if tasks %}
       <div class="card">
         <div class="card-body">
           <h5 class="card-title">Current Tasks</h5>

           <table class="table table-striped">
             {% for task in tasks %}
             <tr>
               <!-- Task Name -->
               <td class="table-text">{{ task.name }}</td>
               <!-- Delete Button -->
               <td>
                 <form action="remove" method="POST">
                   {% csrf_token %}
                   <input type="hidden" name="id" value="{{ task.id }}">
                   <button type="submit" class="btn btn-danger">
                     <i class="fa fa-trash"></i> Delete
                   </button>
                 </form>
               </td>
             </tr>
             {% endfor %}
           </table>
         </div>
       </div>
       {% endif %}
     </div>

     <!-- Bootstrap related JavaScript -->
     <script src="https://code.jquery.com/jquery-3.2.1.slim.min.js"></script>
     <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js"></script>
     <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js"></script>
   </body>
   </html>

Django will automatically check each apps templates folder for templates.

Execute (venv) $ python manage.py runserver and visit http://localhost:8000 again to play with the basic task list app by adding and removing a few tasks.

Locally we use a SQLite database to store the task list. On Heroku we need to provision a database:

$ heroku addons:create heroku-postgresql:essential-0

Now deploy the task list to Heroku:

$ git add .
$ git commit -m "Task list functionality"
$ git push heroku master

Finally, migrate your database on Heroku to create the mc_tasklist_tasks table, and restart the Heroku app:

$ heroku run python manage.py migrate
$ heroku restart

View the app with heroku open and add a few tasks to make sure the app also works on Heroku.

Add caching to Django

Memcache is an in-memory, distributed cache. Its primary API consists of two operations: SET(key, value) and GET(key). Memcache is like a hashmap (or dictionary) that is spread across multiple servers, where operations are still performed in constant time.

The most common use for Memcache is to cache the results of expensive database queries and HTML renders so that these expensive operations don’t need to happen over and over again.

Provision a Memcache

To use Memcache in Django, you first need to provision an actual Memcached cache. You can easily get one for free with the MemCachier add-on:

$ heroku addons:create memcachier:dev

This will provision a new Memcache instance for you and expose a set of config variables containing your MemCachier credentials.

Configure Django with MemCachier

Configure your cache by adding the following to the end of django_tasklist/settings.py:

def get_cache():
  import os
  try:
    servers = os.environ['MEMCACHIER_SERVERS']
    username = os.environ['MEMCACHIER_USERNAME']
    password = os.environ['MEMCACHIER_PASSWORD']
    return {
      'default': {
        'BACKEND': 'django_bmemcached.memcached.BMemcached',
        # TIMEOUT is not the connection timeout! It's the default expiration
        # timeout that should be applied to keys! Setting it to `None`
        # disables expiration.
        'TIMEOUT': None,
        'LOCATION': servers,
        'OPTIONS': {
          'username': username,
          'password': password,
        }
      }
    }
  except:
    return {
      'default': {
        'BACKEND': 'django.core.cache.backends.locmem.LocMemCache'
      }
    }

CACHES = get_cache()

This configures the cache for both development and production. If the MEMCACHIER_* environment variables exist, the cache will be setup with django-bmemcached, connecting to MemCachier. Whereas, if the MEMCACHIER_* environment variables don’t exist – hence development mode – Django’s simple in-memory cache is used instead.

Install dependencies

Install the django-bmemcached Python modules:

(venv) $ pip install django-bmemcached

Update your requirements.txt file with the new dependencies:

(venv) $ pip freeze > requirements.txt
(venv) $ cat requirements.txt
...
django-bmemcached==0.2.4

Finally, commit and deploy these changes:

$ git commit -am "Connecting to memcache."
$ git push heroku master

pylibmc can be used as an alternative to django-bmemcached.

Verify Memcache configuration

Verify that you’ve configured memcache correctly before you move forward.

To do this, run the Django shell. On your local machine run (venv) $ python manage.py shell and in Heroku run heroku run python manage.py shell. Run a quick test to make sure your cache is configured properly:

>>> from django.core.cache import cache
>>> cache.get("foo")
>>> cache.set("foo", "bar")
>>> cache.get("foo")
'bar'

Exit with Ctrl-d. After the second get command, bar should be printed to the screen when foo is fetched from the cache. If you don’t see bar your cache is not configured correctly.

Cache expensive database queries

Memcache is often used to cache expensive database queries. This simple example doesn’t include any expensive queries, but for the sake of learning, let’s assume that getting all tasks from the database is an expensive operation.

The task list database query code in mc_tasklist/views.py can be modified to check the cache first like so:

# ...
from django.core.cache import cache
import time

TASKS_KEY = "tasks.all"

def index(request):
    tasks = cache.get(TASKS_KEY)
    if not tasks:
        time.sleep(2)  # simulate a slow query.
        tasks = Task.objects.order_by("id")
        cache.set(TASKS_KEY, tasks)
    c = {'tasks': tasks}
    c.update(csrf(request))
    return render(request, 'index.html', c)
# ...

The above code first checks the cache to see if the tasks.all key exists in the cache. If it does not, a database query is executed and the cache is updated. Subsequent pageloads will not need to perform the database query. The time.sleep(2) only exists to simulate a slow query.

Deploy and test this new functionality:

$ git commit -am 'Add caching with MemCachier'
$ git push heroku master
$ heroku open

To see what’s going on in your cache, open the MemCachier dashboard:

$ heroku addons:open memcachier

The first time you loaded your task list, you should have gotten an increase for the get misses and set commands. Every subsequent reload of the task list should increase get hits (refresh the stats in the dashboard).

Our cache is working, but there is still a major problem. Add a new task and see what happens. No new task appears on the current tasks list! The new task was created in the database, but the app is serving the stale task list from the cache.

Keep Memcache up-to-date

There are many techniques for dealing with an out-of-date cache.

  1. Expiration: The easiest way to make sure the cache does not get stale is by setting an expiration time. The cache.set method can take an optional third argument, which is the time in seconds that the cache key should stay in the cache. If this option is not specified, the default TIMEOUT value in settings.py will be used instead.

You could modify the cache.set method to look like this:

   cache.set(TASKS_KEY, tasks, 5)

But this functionality only works when it is known for how long the cached value is valid. In our case however, the cache gets stale upon user interaction (add, remove a task).

  1. Delete cached value: A straight forward strategy is to invalidate the tasks.all key when you know the cache is out of date – namely, to modify the add and remove views to delete the tasks.all key:
   # ...
   def add(request):
       item = Task(name=request.POST["name"])
       item.save()
       cache.delete(TASKS_KEY)
       return redirect("/")

   def remove(request):
       item = Task.objects.get(id=request.POST["id"])
       if item:
           item.delete()
           cache.delete(TASKS_KEY)
       return redirect("/")
  1. Key based expiration: Another technique to invalidate stale data is to change the key:
   # ...
   import random
   import string

   def _hash(size=16, chars=string.ascii_letters + string.digits):
       return ''.join(random.choice(chars) for _ in range(size))

   def _new_tasks_key():
       return 'tasks.all.' + _hash()

   TASKS_KEY = _new_tasks_key()

   # ...

   def add(request):
       item = Task(name=request.POST["name"])
       item.save()
       global TASKS_KEY
       TASKS_KEY = _new_tasks_key()
       return redirect("/")

   def remove(request):
       item = Task.objects.get(id=request.POST["id"])
       if item:
           item.delete()
           global TASKS_KEY
           TASKS_KEY = _new_tasks_key()
       return redirect("/")

The upside of key based expiration is that you do not have to interact with the cache to expire the value. The LRU eviction of Memcache will clean out the old keys eventually.

  1. Update cache: Instead of invalidating the key the value can also be updated to reflect the new task list:
   # ...
   def add(request):
       item = Task(name=request.POST["name"])
       item.save()
       cache.set(TASKS_KEY, Task.objects.order_by("id"))
       return redirect("/")

   def remove(request):
       item = Task.objects.get(id=request.POST["id"])
       if item:
           item.delete()
           cache.set(TASKS_KEY, Task.objects.order_by("id"))
       return redirect("/")

Updating the value instead of deleting it will allow the first pageload to avoid having to go to the database

You can use option 2, 3, or 4 to make sure the cache will not ever be out-of-date. As usual, commit and deploy your changes:

$ git commit -am "Keep Memcache up to date."
$ git push heroku master

Now when you add a new task, all the tasks you’ve added since implementing caching will appear.

Use Django’s integrated caching

Django also has a few built in ways to use your Memcache to improve performance. These mainly target the rendering of HTML which is an expensive operation that is taxing for the CPU.

Caching and CSRF

You cannot cache any views or fragments that contain forms with CSRF tokens because the token changes with each request. For the sake of learning how to use Django’s integrated caching we will disable Django’s CSRF middleware. Since this task list is public, this is not a big deal but do not do this in any serious production application.

Comment CsrfViewMiddleware in django_tasklist/settings.py:

MIDDLEWARE = [
    # ...
    # 'django.middleware.csrf.CsrfViewMiddleware',
    # ...
]

Cache template fragments

Django allows you to cache rendered template fragments. This is similar to snippet caching in Flask, or caching rendered partials in Laravel. To enable fragment caching add {% load cache %} to the top of your template.

Do not cache fragments that include forms with CSRF tokens.

To cache a rendered set of task entries, we use a {% cache timeout key %} statement in mc_tasklist/templates/index.html:

{% load cache %}
<!-- ... -->

<table class="table table-striped">
  {% for task in tasks %} {% cache None 'task-fragment' task.id %}
  <tr>
    <!-- ... -->
  </tr>
  {% endcache %} {% endfor %}
</table>

<!-- ... -->

Here the timeout is None and the key is a list of strings that will be concatenated. As long as task IDs are never reused, this is all there is to caching rendered snippets. The PostgreSQL database we use on Heroku does not reuse IDs, so we’re all set.

If you use a database that does reuse IDs, you need to delete the fragment when its respective task is deleted. You can do this by adding the following code to the task deletion logic:

from django.core.cache.utils import make_template_fragment_key
key = make_template_fragment_key("task-fragment", vary_on=[str(item.id)])
cache.delete(key)

Let’s see the effect of caching the fragments in our application:

$ git commit -am 'Cache task entry fragment'
$ git push heroku master

You should now observe an additional get hit for each task in your list whenever you reload the page (except the first reload).

Cache entire views

We can go one step further and cache entire views instead of fragments. This should be done with care, because it can result in unintended side effects if a view frequently changes or contains forms for user input. In our task list example, both of these conditions are true because the task list changes each time a task is added or deleted, and the view contains forms to add and delete a task.

Do not cache views that include forms with CSRF tokens.

You can cache the task list view with the @cache_page(timeout) decorator in mc_tasklist/views.py:

# ...
from django.views.decorators.cache import cache_page

@cache_page(None)
def index(request):
    # ...

# ...

Because the view changes whenever we add or remove a task, we need to delete the cached view whenever this happens. This is not straight forward. We need to learn the key when the view is cached in order to be then able to delete it:

# ...
from django.utils.cache import learn_cache_key

VIEW_KEY = ""

@cache_page(None)
def index(request):
    # ...
    response = render(request, 'index.html', c)
    global VIEW_KEY
    VIEW_KEY = learn_cache_key(request, response)
    return response

def add(request):
    # ...
    cache.delete(VIEW_KEY)
    return redirect("/")

def remove(request):
    item = Task.objects.get(id=request.POST["id"])
    if item:
        # ...
        cache.delete(VIEW_KEY)
    return redirect("/")

To see the effect of view caching, deploy your application:

$ git commit -am 'Cache task list view'
$ git push heroku master

On the first refresh, you should see the get hits counter increase according to the number of tasks you have, as well as an additional get misses and set cmds, which correspond to the view that is now cached. Any subsequent reload will increase the get hits counter by just two, because the entire view is retrieved with two get commands.

Note that view caching does not obsolete the caching of expensive operations or template fragments. It is good practice to cache smaller operations within cached larger operations, or smaller fragments within larger fragments. This technique (called Russian doll caching) helps with performance if a larger operation, fragment, or view is removed from the cache, because the building blocks do not have to be recreated from scratch.

Using Memcache for session storage

On Heroku, it’s not advisable to store session information on disk, because dynos have an ephemeral filesystem that doesn’t persist across restarts.

Memcache works well for storing information for short-lived sessions that time out. However, because Memcache is a cache and therefore not persistent, long-lived sessions are better suited to permanent storage options, such as your database.

For short-lived sessions configure SESSION_ENGINE to use the cache backend in django_tasklist/settings.py:

SESSION_ENGINE = 'django.contrib.sessions.backends.cache'

For long-lived sessions Django allows you to use a write-through cache, backed by a database. This is the best option for performance while guaranteeing persistence. To use the write-through cache, configure the SESSION_ENGINE in django_tasklist/settings.py like so:

SESSION_ENGINE = 'django.contrib.sessions.backends.cached_db'

For more information on how to use sessions in Django, please see the Django Session Documentation

Further reading and resources

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