Data Structures in Python

Now that we are receiving our email addresses it is time to store them. We haven’t really covered the two main data structures in Python, so here is a brief introduction. If you are already comfortable with lists and dictionaries then you can move on to ‘Storing email addresses’ below.

Understanding data structures

Back in the first session we introduced three of the most common data types used in programming: numbers, strings and booleans. We assigned those data types to variables one-by-one, like so:

x = 3          # numbers
a = "gorillas" # strings
t = True       # booleans

But what if we need something more complicated, like a shopping list? Assigning a variable for every item in the list would makes things very complicated:

item_1 = "milk"
item_2 = "cheese"
item_3 = "bread"


Fortunately we don’t have to do this. Instead, we have the list data type. An empty list is simply []

shopping_list = []

When you are in the Python interpreter you can see what is inside a list by just typing the name of the list. For example:

>>> shopping_list

The interpreter shows us that the list is empty.

Now we can add items to shopping_list. Try typing the following commands into the Python interpreter.


What is in the shopping list? What happens when you append numbers or booleans to the list?

To remove an item from the list we use remove():


Lists can easily be processed in a for loop. Have a look at this example which prints each item of the list in a new row:

for item in shopping_list:

And that’s it! Python also makes it really easy to check if something is in a list or not:

if "milk" in shopping_list:

if "eggs" not in shopping_list:
    print("Well we can't have that!")

Lists are the most common data structure in programming. There are lots of other things you can do with lists, and all languages have their own subtly different interpretation. But fundamentally they are all very similar.

In summary:

shopping_list = []


The other main data type is the dictionary. The dictionary allows you to associate one piece of data (a “key”) with another (a “value”). The analogy comes from real-life dictionaries, where we associate a word (the “key”) with its meaning. It’s a little harder to understand than a list, but Python makes them very easy to deal with.

You can create a dictionary with {}

foods = {}

And you can add items to the dictionary like this:

foods["banana"] = "A delicious and tasty treat!"
foods["dirt"]   = "Not delicious. Not tasty. DO NOT EAT!"

The keys in this example are “banana” and “dirt”, and the values are the things that we assign to them. You can use any data type that won’t change as a dictionary key. Check it out by using a number, a boolean value, and a list as keys in a dictionary. What does this say about strings?

As with lists, you can always see what is inside a dictionary:

>>> foods
{'banana': 'A delicious and tasty treat!', 'dirt': 'Not delicious. Not tasty. DO NOT EAT!'}

You can look up any entry in the dictionary by its key:

>>> foods["banana"]
'A delicious and tasty treat!'

If the key isn’t found in the dictionary, a KeyError occurs:

>>> foods["cheese"]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: 'cheese'

For this reason, you can test whether a key is in the dictionary or not, by using the keyword in:

if "cheese" in foods:
    print("Cheese is one of the known foods!")

You can delete from a dictionary as well. We don’t really need to include an entry for dirt:

del foods["dirt"]

What makes dictionaries so useful is that we can give meaning to the items within them. A list is just a bag of things, but a dictionary is a specific mapping of something to something else. By combining lists and dictionaries you can describe basically any data structure used in computing.

For example, you can easily add a list to a dictionary:

ingredients = {}
ingredients["blt sandwich"] = ["bread", "lettuce", "tomato", "bacon"]

Or add dictionaries to lists:

europe = []
germany = {"name": "Germany", "population": 81000000}
luxembourg = {"name": "Luxembourg", "population": 512000}

Outside of Python, dictionaries are often called hash tables, hash maps or just maps.

Storing email addresses

At the moment we don’t have any way to store email addresses. But if we add a list to our website then we can keep them temporarily. Sure it will only stay around until the web server stops, but it is a good start.

Let’s add an empty list to the top of the Python code, just after all the import lines and app = Flask(__name__):

email_addresses = []

Now in our signup() function we can add the email address instead of printing it.

@app.route('/signup', methods = ['POST'])
def signup():
    email = request.form['email']
    return redirect('/')

Check the output you get in the console, when submitting a form. It prints out the entire list every time.

Listing email addresses

Just printing out our email addresses is a bit of a hassle. If you wanted to read the list then you have to open the terminal and scan through for the printout. It would be so much easier to have a web page that lists all the email addresses that we have collected.

We know how to create a new page in Flask, it’s just a function. And we can pass the list of emails directly to a HTML template like so:

def emails():
    return render_template('emails.html', email_addresses=email_addresses)

Here the render_template() function takes the name of the template ('emails.html') and extra data to be used when rendering the page. We wrote email_addresses=email_addresses to say that our variable email_addresses will be available in the template using the same name.

Now we need our HTML template. In our previous template we didn’t actually do anything but plain HTML. But now we need to print the list of email addresses, so we’ll use a for loop in the template.

Here is an example of the content of emails.html for the templates directory:

<!DOCTYPE html>
    <title>Cats Everywhere email addresses</title>
    <p>Here are all the emails we have collected:</p>
      {% for email in email_addresses %}
      <li>{{ email }}</li>
      {% endfor %}
    <p>THIS IS GONNA ROCK!</p>

Check out the for loop that we use in the template. It is similar to the one used in Python but subtly different. You can see it doesn’t contain the : at the end of the first line, and it needs an endfor statement to end the loop. This comes from the template making use of flask’s Jinja2 templating language, that’s designed to be very simple to read and write.

Now you can reboot your server, submit some emails, and visit /emails.html to check everything is working as expected! What happens if you restart the server again?


That’s it, you’re done! You’ve officially built a website! There are a lot of ways to go from here depending on what you would like to do. We have a couple of sections in the Extras area if you would like to continue to do some more with HTML/CSS and using a real database.

If you feel like trying out some other frameworks then check out our list in the Reference section of the home page of this workshop.

Congratulations on completing the Websites with Python Flask workshop. We hope you enjoyed it and encourage you to keep going on the path to web-glory!