Dictionaries in Python

Dictionaries in Python

by John Sturtz basics python
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Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Dictionaries in Python

Python provides another composite data type called a dictionary, which is similar to a list in that it is a collection of objects.

Here’s what you’ll learn in this tutorial: You’ll cover the basic characteristics of Python dictionaries and learn how to access and manage dictionary data. Once you have finished this tutorial, you should have a good sense of when a dictionary is the appropriate data type to use, and how to do so.

Dictionaries and lists share the following characteristics:

  • Both are mutable.
  • Both are dynamic. They can grow and shrink as needed.
  • Both can be nested. A list can contain another list. A dictionary can contain another dictionary. A dictionary can also contain a list, and vice versa.

Dictionaries differ from lists primarily in how elements are accessed:

  • List elements are accessed by their position in the list, via indexing.
  • Dictionary elements are accessed via keys.

Defining a Dictionary

Dictionaries are Python’s implementation of a data structure that is more generally known as an associative array. A dictionary consists of a collection of key-value pairs. Each key-value pair maps the key to its associated value.

You can define a dictionary by enclosing a comma-separated list of key-value pairs in curly braces ({}). A colon (:) separates each key from its associated value:

Python 
d = {
    <key>: <value>,
    <key>: <value>,
      .
      .
      .
    <key>: <value>
}

The following defines a dictionary that maps a location to the name of its corresponding Major League Baseball team:

Python 
>>> MLB_team = {
...     'Colorado' : 'Rockies',
...     'Boston'   : 'Red Sox',
...     'Minnesota': 'Twins',
...     'Milwaukee': 'Brewers',
...     'Seattle'  : 'Mariners'
... }
Python dictionary (illustration)
Dictionary Mapping Location to MLB Team

You can also construct a dictionary with the built-in dict() function. The argument to dict() should be a sequence of key-value pairs. A list of tuples works well for this:

Python 
d = dict([
    (<key>, <value>),
    (<key>, <value),
      .
      .
      .
    (<key>, <value>)
])

MLB_team can then also be defined this way:

Python 
>>> MLB_team = dict([
...     ('Colorado', 'Rockies'),
...     ('Boston', 'Red Sox'),
...     ('Minnesota', 'Twins'),
...     ('Milwaukee', 'Brewers'),
...     ('Seattle', 'Mariners')
... ])

If the key values are simple strings, they can be specified as keyword arguments. So here is yet another way to define MLB_team:

Python 
>>> MLB_team = dict(
...     Colorado='Rockies',
...     Boston='Red Sox',
...     Minnesota='Twins',
...     Milwaukee='Brewers',
...     Seattle='Mariners'
... )

Once you’ve defined a dictionary, you can display its contents, the same as you can do for a list. All three of the definitions shown above appear as follows when displayed:

Python 
>>> type(MLB_team)
<class 'dict'>

>>> MLB_team
{'Colorado': 'Rockies', 'Boston': 'Red Sox', 'Minnesota': 'Twins',
'Milwaukee': 'Brewers', 'Seattle': 'Mariners'}

The entries in the dictionary display in the order they were defined. But that is irrelevant when it comes to retrieving them. Dictionary elements are not accessed by numerical index:

Python 
>>> MLB_team[1]
Traceback (most recent call last):
  File "<pyshell#13>", line 1, in <module>
    MLB_team[1]
KeyError: 1

Perhaps you’d still like to sort your dictionary. If that’s the case, then check out Sorting a Python Dictionary: Values, Keys, and More.