Dictionaries¶

The Python Dictionary¶

Python supports a container type called a dictionary.

This is also known as an "associative array", "map" or "hash" in other languages.

In a list, we use a number to look up an element:

In [1]:

names = "Martin Luther King".split(" ")
names[1]

Out[1]:

'Luther'

In a dictionary, we look up an element using another object of our choice:

In [2]:

me = {"name": "James", "age": 39, "Jobs": ["Programmer", "Teacher"]}

In [3]:

print(me)

{'name': 'James', 'age': 39, 'Jobs': ['Programmer', 'Teacher']}

In [4]:

print(me["Jobs"])

['Programmer', 'Teacher']

In [5]:

print(type(me))

<class 'dict'>

Keys and Values¶

The things we can use to look up with are called keys:

In [6]:

me.keys()

Out[6]:

dict_keys(['name', 'age', 'Jobs'])

The things we can look up are called values:

In [7]:

me.values()

Out[7]:

dict_values(['James', 39, ['Programmer', 'Teacher']])

When we test for containment on a dict we test on the keys:

In [8]:

"Jobs" in me

Out[8]:

True

In [9]:

"James" in me

Out[9]:

False

In [10]:

"James" in me.values()

Out[10]:

True

Immutable Keys Only¶

The way in which dictionaries work is one of the coolest things in computer science: the "hash table". This is way beyond the scope of this course, but it has a consequence:

You can only use immutable things as keys.

In [11]:

good_match = {("Lamb", "Mint"): True, ("Bacon", "Chocolate"): False}

but:

In [12]:

illegal = {[1, 2]: 3}

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In [12], line 1
----> 1 illegal = {[1, 2]: 3}

TypeError: unhashable type: 'list'

Supplementary material: You can start to learn about the 'hash table'. Though this video is very advanced I think it's really interesting!

No guarantee of order¶

Another consequence of the way dictionaries work is that there's no guaranteed order among the elements:

In [13]:

my_dict = {"0": 0, "1": 1, "2": 2, "3": 3, "4": 4}
print(my_dict)
print(my_dict.values())

{'0': 0, '1': 1, '2': 2, '3': 3, '4': 4}
dict_values([0, 1, 2, 3, 4])

Sets¶

A set is a list which cannot contain the same element twice.

In [14]:

university = "University College London"
unique_letters = set(university)

In [15]:

unique_letters

Out[15]:

{' ',
 'C',
 'L',
 'U',
 'd',
 'e',
 'g',
 'i',
 'l',
 'n',
 'o',
 'r',
 's',
 't',
 'v',
 'y'}

In [16]:

print("".join(unique_letters))

gyvUolsCLtn erdi

In [17]:

"".join(["a", "b", "c"])

Out[17]:

'abc'

It has no particular order, but is really useful for checking or storing unique values.

In [18]:

alist = [1, 2, 3]
is_unique = len(set(alist)) == len(alist)
print(is_unique)

True

Safe Lookup¶

In [19]:

x = {"a": 1, "b": 2}

In [20]:

x["a"]

Out[20]:

In [21]:

x["fish"]

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Cell In [21], line 1
----> 1 x["fish"]

KeyError: 'fish'

In [22]:

x.get("a")

Out[22]:

In [23]:

x.get("fish")

In [24]:

x.get("fish", "tuna") == "tuna"

Out[24]:

True