A tuple1 is a sequence of values much like a list. The values stored in a tuple can be any type, and they are indexed by integers. The important difference is that tuples are immutable. Tuples are also comparable and hashable so we can sort lists of them and use tuples as key values in Python dictionaries.
Syntactically, a tuple is a comma-separated list of values:
>>> t = 'a', 'b', 'c', 'd', 'e'Although it is not necessary, it is common to enclose tuples in parentheses to help us quickly identify tuples when we look at Python code:
>>> t = ('a', 'b', 'c', 'd', 'e')To create a tuple with a single element, you have to include the final comma:
>>> t1 = ('a',)
>>> type(t1)
<type 'tuple'>Without the comma Python treats ('a') as an expression
with a string in parentheses that evaluates to a string:
>>> t2 = ('a')
>>> type(t2)
<type 'str'>Another way to construct a tuple is the built-in function
tuple. With no argument, it creates an empty tuple:
>>> t = tuple()
>>> print(t)
()If the argument is a sequence (string, list, or tuple), the result of
the call to tuple is a tuple with the elements of the
sequence:
>>> t = tuple('lupins')
>>> print(t)
('l', 'u', 'p', 'i', 'n', 's')Because tuple is the name of a constructor, you should
avoid using it as a variable name.
Most list operators also work on tuples. The bracket operator indexes an element:
>>> t = ('a', 'b', 'c', 'd', 'e')
>>> print(t[0])
'a'And the slice operator selects a range of elements.
>>> print(t[1:3])
('b', 'c')But if you try to modify one of the elements of the tuple, you get an error:
>>> t[0] = 'A'
TypeError: object doesn't support item assignmentYou can’t modify the elements of a tuple, but you can replace one tuple with another:
>>> t = ('A',) + t[1:]
>>> print(t)
('A', 'b', 'c', 'd', 'e')
The comparison operators work with tuples and other sequences. Python starts by comparing the first element from each sequence. If they are equal, it goes on to the next element, and so on, until it finds elements that differ. Subsequent elements are not considered (even if they are really big).
>>> (0, 1, 2) < (0, 3, 4)
True
>>> (0, 1, 2000000) < (0, 3, 4)
TrueThe sort function works the same way. It sorts primarily
by first element, but in the case of a tie, it sorts by second element,
and so on.
This feature lends itself to a pattern called DSU for
sort, and
For example, suppose you have a list of words and you want to sort them from longest to shortest:
txt = 'but soft what light in yonder window breaks'
words = txt.split()
t = list()
for word in words:
t.append((len(word), word))
t.sort(reverse=True)
res = list()
for length, word in t:
res.append(word)
print(res)
# Code: https://www.py4e.com/code3/soft.pyThe first loop builds a list of tuples, where each tuple is a word preceded by its length.
sort compares the first element, length, first, and only
considers the second element to break ties. The keyword argument
reverse=True tells sort to go in decreasing
order.
The second loop traverses the list of tuples and builds a list of words in descending order of length. The four-character words are sorted in reverse alphabetical order, so “what” appears before “soft” in the following list.
The output of the program is as follows:
['yonder', 'window', 'breaks', 'light', 'what',
'soft', 'but', 'in']Of course the line loses much of its poetic impact when turned into a Python list and sorted in descending word length order.
One of the unique syntactic features of the Python language is the ability to have a tuple on the left side and a sequence on the right side of an assignment statement. This allows you to assign more than one variable at a time to the given sequence.
In this example we have a two-element tuple and assign the first and
second elements of the tuple to the variables x and
y in a single statement.
>>> m = ( 'have', 'fun' )
>>> x, y = m
>>> x
'have'
>>> y
'fun'
>>>This is more general than tuple-to-tuple assignment. Both tuples and lists are sequences, so this syntax works with a two element list as well.
>>> m = [ 'have', 'fun' ]
>>> x, y = m
>>> x
'have'
>>> y
'fun'
>>>It is not magic, Python roughly translates the tuple assignment syntax to be the following:2
>>> m = ( 'have', 'fun' )
>>> x = m[0]
>>> y = m[1]
>>> x
'have'
>>> y
'fun'
>>>Stylistically when we use a tuple on the left side of the assignment statement, we omit the parentheses, but the following is an equally valid syntax:
>>> m = ( 'have', 'fun' )
>>> (x, y) = m
>>> x
'have'
>>> y
'fun'
>>>A particularly clever application of tuple assignment allows us to swap the values of two variables in a single statement:
>>> a, b = b, aBoth sides of this statement are tuples, but the left side is a tuple of variables; the right side is a tuple of expressions. Each value on the right side is assigned to its respective variable on the left side. All the expressions on the right side are evaluated before any of the assignments.
The number of variables on the left and the number of values on the right must be the same:
>>> a, b = 1, 2, 3
ValueError: too many values to unpackMore generally, the right side can be any kind of sequence (string, list, or tuple). For example, to split an email address into a user name and a domain, you could write:
>>> addr = '[email protected]'
>>> uname, domain = addr.split('@')The return value from split is a list with two elements;
the first element is assigned to uname, the second to
domain.
>>> print(uname)
monty
>>> print(domain)
python.org
Dictionaries have a method called items that returns a
list of tuples, where each tuple is a key-value pair:
>>> d = {'b':1, 'a':10, 'c':22}
>>> t = list(d.items())
>>> print(t)
[('b', 1), ('a', 10), ('c', 22)]As you should expect from a dictionary, the items are in non-alphabetical order.
However, since the list of tuples is a list, and tuples are comparable, we can now sort the list of tuples. Converting a dictionary to a list of tuples is a way for us to output the contents of a dictionary sorted by key:
>>> d = {'b':1, 'a':10, 'c':22}
>>> t = list(d.items())
>>> t
[('b', 1), ('a', 10), ('c', 22)]
>>> t.sort()
>>> t
[('a', 10), ('b', 1), ('c', 22)]The new list is sorted in ascending alphabetical order by the key value.
Combining items, tuple assignment, and for,
you can see a nice code pattern for traversing the keys and values of a
dictionary in a single loop:
d = {'a':10, 'b':1, 'c':22}
for key, val in d.items():
print(val, key)This loop has two iteration variables because
items returns a list of tuples and key, val is
a tuple assignment that successively iterates through each of the
key-value pairs in the dictionary.
For each iteration through the loop, both key and
val are advanced to the next key-value pair in the
dictionary (still in hash order).
The output of this loop is:
10 a
1 b
22 cAgain, it is in hash key order (i.e., no particular order).
If we combine these two techniques, we can print out the contents of a dictionary sorted by the value stored in each key-value pair.
To do this, we first make a list of tuples where each tuple is
(value, key). The items method would give us a
list of (key, value) tuples, but this time we want to sort
by value, not key. Once we have constructed the list with the value-key
tuples, it is a simple matter to sort the list in reverse order and
print out the new, sorted list.
>>> d = {'a':10, 'b':1, 'c':22}
>>> l = list()
>>> for key, val in d.items() :
... l.append( (val, key) )
...
>>> l
[(10, 'a'), (1, 'b'), (22, 'c')]
>>> l.sort(reverse=True)
>>> l
[(22, 'c'), (10, 'a'), (1, 'b')]
>>>By carefully constructing the list of tuples to have the value as the first element of each tuple, we can sort the list of tuples and get our dictionary contents sorted by value.
Coming back to our running example of the text from Romeo and Juliet Act 2, Scene 2, we can augment our program to use this technique to print the ten most common words in the text as follows:
import string
fhand = open('romeo-full.txt')
counts = dict()
for line in fhand:
line = line.translate(str.maketrans('', '', string.punctuation))
line = line.lower()
words = line.split()
for word in words:
if word not in counts:
counts[word] = 1
else:
counts[word] += 1
# Sort the dictionary by value
lst = list()
for key, val in list(counts.items()):
lst.append((val, key))
lst.sort(reverse=True)
for key, val in lst[:10]:
print(key, val)
# Code: https://www.py4e.com/code3/count3.pyThe first part of the program which reads the file and computes the
dictionary that maps each word to the count of words in the document is
unchanged. But instead of simply printing out counts and
ending the program, we construct a list of (val, key)
tuples and then sort the list in reverse order.
Since the value is first, it will be used for the comparisons. If there is more than one tuple with the same value, it will look at the second element (the key), so tuples where the value is the same will be further sorted by the alphabetical order of the key.
At the end we write a nice for loop which does a
multiple assignment iteration and prints out the ten most common words
by iterating through a slice of the list (lst[:10]).
So now the output finally looks like what we want for our word frequency analysis.
61 i
42 and
40 romeo
34 to
34 the
32 thou
32 juliet
30 that
29 my
24 theeThe fact that this complex data parsing and analysis can be done with an easy-to-understand 19-line Python program is one reason why Python is a good choice as a language for exploring information.
Because tuples are hashable and lists are not, if we want to create a composite key to use in a dictionary we must use a tuple as the key.
We would encounter a composite key if we wanted to create a telephone
directory that maps from last-name, first-name pairs to telephone
numbers. Assuming that we have defined the variables last,
first, and number, we could write a dictionary
assignment statement as follows:
directory[last,first] = numberThe expression in brackets is a tuple. We could use tuple assignment
in a for loop to traverse this dictionary.
for last, first in directory:
print(first, last, directory[last,first])This loop traverses the keys in directory, which are
tuples. It assigns the elements of each tuple to last and
first, then prints the name and corresponding telephone
number.
I have focused on lists of tuples, but almost all of the examples in this chapter also work with lists of lists, tuples of tuples, and tuples of lists. To avoid enumerating the possible combinations, it is sometimes easier to talk about sequences of sequences.
In many contexts, the different kinds of sequences (strings, lists, and tuples) can be used interchangeably. So how and why do you choose one over the others?
To start with the obvious, strings are more limited than other sequences because the elements have to be characters. They are also immutable. If you need the ability to change the characters in a string (as opposed to creating a new string), you might want to use a list of characters instead.
Lists are more common than tuples, mostly because they are mutable. But there are a few cases where you might prefer tuples:
In some contexts, like a return statement, it is
syntactically simpler to create a tuple than a list. In other contexts,
you might prefer a list.
If you want to use a sequence as a dictionary key, you have to use an immutable type like a tuple or string.
If you are passing a sequence as an argument to a function, using tuples reduces the potential for unexpected behavior due to aliasing.
Because tuples are immutable, they don’t provide methods like
sort and reverse, which modify existing lists.
However Python provides the built-in functions sorted and
reversed, which take any sequence as a parameter and return
a new sequence with the same elements in a different order.
Sometimes you want to create a sequence by using data from another sequence. You can achieve this by writing a for loop and appending one item at a time. For example, if you wanted to convert a list of strings – each string storing digits – into numbers that you can sum up, you would write:
list_of_ints_in_strings = ['42', '65', '12']
list_of_ints = []
for x in list_of_ints_in_strings:
list_of_ints.append(int(x))
print(sum(list_of_ints))With list comprehension, the above code can be written in a more compact manner:
list_of_ints_in_strings = ['42', '65', '12']
list_of_ints = [ int(x) for x in list_of_ints_in_strings ]
print(sum(list_of_ints))
Lists, dictionaries and tuples are known generically as data structures; in this chapter we are starting to see compound data structures, like lists of tuples, and dictionaries that contain tuples as keys and lists as values. Compound data structures are useful, but they are prone to what I call shape errors; that is, errors caused when a data structure has the wrong type, size, or composition, or perhaps you write some code and forget the shape of your data and introduce an error. For example, if you are expecting a list with one integer and I give you a plain old integer (not in a list), it won’t work.
Exercise 1: Revise a previous program as follows: Read and parse the “From” lines and pull out the addresses from the line. Count the number of messages from each person using a dictionary.
After all the data has been read, print the person with the most commits by creating a list of (count, email) tuples from the dictionary. Then sort the list in reverse order and print out the person who has the most commits.
Sample Line:
From [email protected] Sat Jan 5 09:14:16 2008
Enter a file name: mbox-short.txt
[email protected] 5
Enter a file name: mbox.txt
[email protected] 195Exercise 2: This program counts the distribution of the hour of the day for each of the messages. You can pull the hour from the “From” line by finding the time string and then splitting that string into parts using the colon character. Once you have accumulated the counts for each hour, print out the counts, one per line, sorted by hour as shown below.
python timeofday.py
Enter a file name: mbox-short.txt
04 3
06 1
07 1
09 2
10 3
11 6
14 1
15 2
16 4
17 2
18 1
19 1Exercise 3: Write a program that reads a file and prints the letters in decreasing order of frequency.
Your program should convert all the input to lower case and only count the letters a-z. Your program should not count spaces, digits, punctuation, or anything other than the letters a-z. Find text samples from several different languages and see how letter frequency varies between languages. Compare your results with the tables at https://wikipedia.org/wiki/Letter_frequencies.
Fun fact: The word “tuple” comes from the names given to sequences of numbers of varying lengths: single, double, triple, quadruple, quintuple, sextuple, septuple, etc.↩︎
Python does not translate the syntax literally. For example, if you try this with a dictionary, it will not work as you might expect.↩︎
If you find a mistake in this book, feel free to send me a fix using Github.