Now we know how to use lists, tuples and dictionaries. They are commonly used data types in Python, and there's nothing wrong with them. In this chapter we'll learn more data types that make some things easier. You can always do everything with lists and dictionaries, but these data types can do a lot of the work for you.
If it looks like a duck and quacks like a duck, it must be a duck.
Many things in this tutorial are not really something but they behave like something. For example, we'll learn about many classes that behave like dictionaries. They are not dictionaries, but we can use them just like if they were dictionaries. This programming style is known as duck-typing.
Let's say we have a program that keeps track of peoples' names. We can store the names in a list, and adding a new name is easy as appending to that list. Lists remember their order and it's possible to add the same thing multiple times.
>>> names = ['wub_wub', 'theelous3', 'RubyPinch', 'go|dfish', 'Nitori']
>>> names.append('Akuli')
>>> names.append('Akuli')
>>> names
['wub_wub', 'theelous3', 'RubyPinch', 'go|dfish', 'Nitori', 'Akuli', 'Akuli']
>>>This is usually what we need, but sometimes it's not. Sometimes we just want to store a bunch of things. We don't need to have the same thing twice and we don't care about the order.
This is when sets come in. They are like lists without order or
duplicates, or keys of dictionaries without the
values. We can create a set just like a dictionary, but without :.
>>> names = {'wub_wub', 'theelous3', 'RubyPinch', 'go|dfish', 'Nitori'}
>>> names
{'RubyPinch', 'theelous3', 'go|dfish', 'wub_wub', 'Nitori'}
>>> type(names)
<class 'set'>
>>> 'wub_wub' in names
True
>>>We can also convert anything iterable to a set by calling the class.
>>> set('hello')
{'o', 'e', 'h', 'l'}
>>> type(set('hello'))
<class 'set'>
>>>When we did set('hello') we lost one l and the set ended up in a
different order because sets don't contain duplicates or keep track of
their order.
Note that {} is a dictionary because dictionaries are used more often
than sets, so we need set() if we want to create an empty set.
>>> type({'a', 'b'})
<class 'set'>
>>> type({'a'})
<class 'set'>
>>> type({})
<class 'dict'>
>>> type(set()) # set() is an empty set
<class 'set'>
>>>Sets have a remove method just like lists have, but they have an add
method instead of append.
>>> names = {'theelous3', 'wub_wub'}
>>> names.add('Akuli')
>>> names
{'wub_wub', 'Akuli', 'theelous3'}
>>> names.remove('theelous3')
>>> names
{'wub_wub', 'Akuli'}
>>>That's the boring part. Now let's have a look at some really handy things we can do with sets:
>>> a = {'RubyPinch', 'theelous3', 'go|dfish'}
>>> b = {'theelous3', 'Nitori'}
>>> a & b # names in a and b
{'theelous3'}
>>> a | b # names in a, b or both
{'Nitori', 'theelous3', 'go|dfish', 'RubyPinch'}
>>> a ^ b # names in a or b, but not both
{'RubyPinch', 'Nitori', 'go|dfish'}
>>> a - b # names in a but not in b
{'go|dfish', 'RubyPinch'}
>>>It can be tempting to make a class that just contains a bunch of data and that's it.
class Website:
def __init__(self, url, founding_year, free_to_use):
self.url = url
self.founding_year = founding_year
self.free_to_use = free_to_use
github = Website('https://github.com/', 2008, True)You should avoid making classes like this. This class has only one method, so it doesn't really need to be a class. We could just use a tuple instead:
github = ('https://github.com/', 2008, True)The problem with this is that if someone reading our code sees something
like website[1] > 2010 it doesn't make much sense, like
website.founding_year > 2010 would.
In cases like this, collections.namedtuple is handy:
>>> Website = collections.namedtuple('Website', 'url founding_year free_to_use')
>>> github = Website('https://github.com/', 2008, True)
>>> github[1]
2008
>>> for thing in github:
... print(thing)
...
https://github.com/
2008
True
>>> github.founding_year
2008
>>> github
Website(url='https://github.com/', founding_year=2008, free_to_use=True)
>>>As you can see, our github behaves like a tuple, but things like
github.founding_year also work and github looks nice when we have a
look at it on the >>> prompt.
To understand deques, we need to first learn about a list method I
haven't talked about earlier. It's called pop and it works like this:
>>> names = ['wub_wub', 'theelous3', 'Nitori', 'RubyPinch', 'go|dfish']
>>> names
['wub_wub', 'theelous3', 'Nitori', 'RubyPinch', 'go|dfish']
>>> names.pop()
'go|dfish'
>>> names
['wub_wub', 'theelous3', 'Nitori', 'RubyPinch']
>>> names.pop()
'RubyPinch'
>>> names
['wub_wub', 'theelous3', 'Nitori']
>>>The list shortens from the end by one when we pop from it, and we also
get the removed item back. So we can add an item to the end of a list
using append, and we can remove an item from the end using pop.
It's also possible to do these things in the beginning of a list, but
lists were not designed to be used that way and it would be slow if our
list would be big. The collections.deque class makes appending and
popping from both ends easy and fast. It works just like lists, but it
also has appendleft and popleft methods.
>>> names = collections.deque(['theelous3', 'Nitori', 'RubyPinch'])
>>> names
deque(['theelous3', 'Nitori', 'RubyPinch'])
>>> names.appendleft('wub_wub')
>>> names.append('go|dfish')
>>> names
deque(['wub_wub', 'theelous3', 'Nitori', 'RubyPinch', 'go|dfish'])
>>> names.popleft()
'wub_wub'
>>> names.pop()
'go|dfish'
>>> names
deque(['theelous3', 'Nitori', 'RubyPinch'])
>>>The deque behaves a lot like lists do, and we can do list(names) if we
need a list instead of a deque for some reason.
Deques are often used as queues. It means that items are always added to one end and popped from the other end.
Back in the dictionary chapter we learned to count the number of words in a sentence like this:
sentence = input("Enter a sentence: ")
counts = {}
for word in sentence.split():
if word in counts:
counts[word] += 1
else:
counts[word] = 1This code works just fine, but there are easier ways to do this. For
example, we could use the get method. It works so that
the_dict.get('hi', 'hello') tries to give us the_dict['hi'] but
gives us 'hello' instead if 'hi' is not in the dictionary.
>>> the_dict = {'hi': 'this is working'}
>>> the_dict.get('hi', 'lol its not there')
'this is working'
>>> the_dict.get('hello', 'lol its not there')
'lol its not there'
>>>So we could write code like this instead:
sentence = input("Enter a sentence: ")
counts = {}
for word in sentence.split():
counts[word] = counts.get(word, 0) + 1Counting things like this is actually so common that there's a
class just for that. It's called
collections.Counter and it works like this:
>>> import collections
>>> words = ['hello', 'there', 'this', 'test', 'is', 'a', 'hello', 'test']
>>> counts = collections.Counter(words)
>>> counts
Counter({'test': 2, 'hello': 2, 'is': 1, 'this': 1, 'there': 1, 'a': 1})
>>>Now counts is a Counter object. It behaves a lot like a dictionary,
and everything that works with a dictionary should also work with a
counter. We can also convert the counter to a dictionary by doing
dict(the_counter) if something doesn't work with a counter.
>>> for word, count in counts.items():
... print(word, count)
...
test 2
is 1
this 1
there 1
a 1
hello 2
>>>We can add together strings, lists, tuples and sets easily.
>>> "hello" + "world"
'helloworld'
>>> [1, 2, 3] + [4, 5]
[1, 2, 3, 4, 5]
>>> (1, 2, 3) + (4, 5)
(1, 2, 3, 4, 5)
>>> {1, 2, 3} | {4, 5}
{1, 2, 3, 4, 5}
>>>But how about dictionaries? They can't be added together with +.
>>> {'a': 1, 'b': 2} + {'c': 3}
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for +: 'dict' and 'dict'
>>>Usually it's easiest to do this:
>>> dict1 = {'a': 1, 'b': 2}
>>> dict2 = {'c': 3}
>>> {**dict1, **dict2}
{'a': 1, 'b': 2, 'c': 3}Dictionaries also have an update method that adds everything from another
dictionary into it, and you can use that too. This was the most common way to
do it before Python supported {**dict1, **dict2}.
>>> merged = {}
>>> merged.update({'a': 1, 'b': 2})
>>> merged.update({'c': 3})
>>> merged
{'a': 1, 'b': 2, 'c': 3}
>>>- Duck typing means requiring some behavior instead of some type. For example, instead of making a function that takes a list we could make a function that takes anything iterable.
- Sets and the collections module are handy. Use them.
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You may use this tutorial freely at your own risk. See LICENSE.