- Utilize Python's
list,tuple,range, andstrdata types to accomplish several common programming tasks. - Execute and test Python code using the Python shell and
pytest.
- Sequence: a data structure in which data is stored and accessed in a specific order.
- Index: the location, represented by an integer, of an element in a sequence.
- Iterable: able to be broken down into smaller parts of equal size that can be processed in turn. You can loop through any iterable object.
- Slice: a group of neighboring elements in a sequence.
- Mutable: an object that can be changed.
- Immutable: an object that cannot be changed. (Many immutable objects appear mutable because programmers reuse their names for new objects.)
- List: a mutable data type in Python that can store many types of data. The most common data structure in Python.
- Tuple: an immutable data type in Python that can store many types of data.
- Range: a data type in Python that stores integers in a fixed pattern.
- String: an immutable data type in Python that stores unicode characters in a fixed pattern. Iterable and indexed, just like other sequences.
A sequence is a simple data structure that is present in all programming languages in which data is stored in a specified order. The elements of a sequence can be accessed by their index. Just as in JavaScript, indices of a sequence begin at 0 and increase by 1 with each step down the sequence:
// JavaScript
const my_list = [1, 2, 3, 4];
console.log(my_list[0]);
// 1# Python
my_list = [1, 2, 3, 4]
print(my_list[0])
# => 1list and tuple objects can store any type of data. range objects store
only integers, and str objects can only store unicode characters.
Whenever values are logically connected to one another and it is important to keep them in order, you should store them in a sequence data structure.
# A dynamic sequence of values that allows duplicates
fibonacci_list = [0, 1, 1, 2, 3, 5, 8, 13, 21]
# An immutable, ordered sequence of months
month_tuple = (
'January',
'February',
'March',
'April',
'May',
'June',
'July',
'August',
'September',
'October',
'November',
'December',
)
# A simple pattern of numbers
even_numbers_up_to_100 = range(0, 101, 2)
# A grammatical sentence
sentence_string = "Strings are immutable sequences of Unicode code points."After being defined, sequences can be used as more complex data structures such as queues and stacks. We will discuss these more later on in this module.
All sequence data types in Python support certain functions and operators and
possess certain methods. For a sequence s:
-
x in sreturnsTrueifxis equal to at least one element ofs. -
s + s2returns a single sequence of the elements ofsfollowed by the elements ofs2. -
s * nreturns a single sequence ofsrepeatedntimes. -
s[i]returns theith element ofs(starting at 0).NOTE: Python also supports negative indices.
-1represents the last element in a sequence. -
s[i:j]returns a slice ofsfrom indexiup to (but not including!) indexj. -
s[i:j:k]returns a slice ofsfromitojwith steps ofkin between. -
len(s)returns the number of elements ins. -
min(s)andmax(s)return the minimum and maximum values ins, respectively. > NOTE: this requires the elements ofsto be of the same data type, eitherstror numerical. -
s.index(x)returns the index of the firstxins. -
s.count(x)returns the number of instances ofxins.
Open up the Python shell and test each of these operations for yourself:
s = [4, 6, 3, 9, 3, 5, 1, 2]
1 in s
# => True
s + s
# => [4, 6, 3, 9, 3, 5, 1, 2, 4, 6, 3, 9, 3, 5, 1, 2]
s * 2
# => [4, 6, 3, 9, 3, 5, 1, 2, 4, 6, 3, 9, 3, 5, 1, 2]
s[1]
# => 6
s[-1]
# => 2
s[2:5]
# => [3, 9, 3]
s[2:5:2]
# => [3, 3]
len(s)
# => 8
min(s)
# => 1
max(s)
# => 9
s.index(3)
# => 2
s.count(9)
# => 1How would you retrieve the last two elements of a sequence if you don't know the length?
Use the len() function to find the length of the
sequence, then access the last two elements at
s[len(s) - 1], s[len(s) - 2].
Use negative indexing to directly access the last two elements of
the list: s[-1], s[-2].
Use negative indexing to slice the last two elements of the
sequence: s[-1:-3:-1].
We've encountered lists in several of our lessons so far. As lists are mutable and can store any types of data in the same list object, they have many use cases and many operations, functions, and methods that allow us to manipulate their contents.
Python provides two straightforward solutions for sorting lists: the
list.sort() method and the sorted() function. Both of these solutions
require that all elements of the list be of the same data type.
# if we sort numbers, they will be sorted in ascending order
my_list = [3, 6, 4, 2, 1, 5]
my_list.sort()
print(my_list)
# [1, 2, 3, 4, 5, 6]
# If we sort strings, they will be sorted in alphanumeric order
my_list = ['Cabbage', 'Apple', 'Banana', 'Potato']
my_list.sort()
print(my_list)
#['Apple', 'Banana', 'Cabbage', 'Potato']There are some parameters we can pass into list.sort() which can make the
the function more versatile.
The key parameter allows us to pass in a function which can serve as a key for
the sort comparison:
my_list = ['This is a long sentence', 'Word', 'z']
# What if we want to sort by the length of the string?
# We can use the key attribute to tell the sort function to sort using the len function.
my_list.sort(key = len)
print(my_list)
# => ['z', 'Word', 'This is a long sentence']
# If we want to sort in descending order we can pass in the reverse parameter into sort.
my_list = ['This is a long sentence', 'Word', 'z']
my_list.sort(key = len, reverse=True)
print(my_list)
# => ['This is a long sentence', 'Word', 'z']We can sort complex data structures using sort key
Lets say we have a list of tuples we want to sort using the second key:
my_list = [('John', 2), ('Steve', 1), ('Joe', 3)]
# We can define a function for the list to sort by the second key
def sort_tuple(tuple_value):
# return the key we want to sort by
return tuple_value[1]
my_list.sort(key = sort_tuple)
print(my_list)
# => [('Steve', 1), ('John', 2), ('Joe', 3)]This function should be used when you want to preserve the integrity of your original list, but you need a sorted version for a separate task.
my_list = [3, 6, 4, 2, 1, 5]
sorted_list = sorted(my_list)
print(my_list)
# => [3, 6, 4, 2, 1, 5]
print(sorted_list)
# => [1, 2, 3, 4, 5, 6]We can pass the key and reverse parameters into sorted() like we did for
the sort method:
my_list = ['Loquacious', 'Chatty', 'Talkative']
sorted_list = sorted(my_list, key=len, reverse=True)
# => ['Loquacious', 'Talkative', 'Chatty']Python allows us to modify any of the elements of a list using their index:
my_list = [0, 1, 2, 3]
my_list[0] = None
print(my_list)
# => [None, 1, 2, 3]If we want to extend a list, we unfortunately cannot use the same approach:
my_list = [0, 1, 2, 3]
my_list[4] = 4
# => IndexError: list assignment index out of rangePython does provide us with two options to extend lists: list.append() and
list.insert().
list.append() does exactly what you might expect: it appends its parameter
to the list.
my_list = [0, 1, 2, 3]
my_list.append(4)
print(my_list)
# => [0, 1, 2, 3, 4]list.insert() provides us a few extra options for extending our list. Where
list.append() can only add to the end of a list, list.insert() can insert at
any index.
list.insert() takes two arguments: an index and a value. If a value already
exists at the index, the new value is inserted before it and everything after is
moved up by 1. If no value exists at the index, the new value is added to the
end of the existing list.
my_list = ['a', 'b', 'c', 'd', 'f']
my_list.insert(4, 'e')
print(my_list)
# => ['a', 'b', 'c', 'd', 'e', 'f']
my_list.insert(1000, 'g')
print(my_list)
# => ['a', 'b', 'c', 'd', 'e', 'f', 'g']Python provides us with four (4!!!) options for removing elements from a list.
- The
del()function. - The
list.pop()method. - The
list.remove()method. - The
list.clear()method.
del() removes elements from a list, specified by an index or range of indices.
my_list = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
del(my_list[0])
print(my_list)
# => ['b', 'c', 'd', 'e', 'f', 'g']
del(my_list[0:3])
print(my_list)
# => ['e', 'f', 'g']list.pop() removes and returns the element at the index passed in as an
argument. When used without any arguments, it removes and returns the last
element of the list.
list.remove() removes the element passed in as an argument. This is one of the
few list methods that searches by value instead of index!
list.clear() erases all of the values of a list. This is usually not a very
useful tool, but it's a fast way to free up memory on your device if you're
working with a particularly large list in the Python shell.
my_list = ['a', 'b', 'c', 'd', 'e', 'f', 'g']
my_list.pop()
# => 'g'
my_list.pop(0)
# => 'a'
my_list.remove('f')
print(my_list)
# => ['b', 'c', 'd', 'e']
my_list.clear()
print(my_list)
# => []Tuples do not have any special exclusive methods like lists do. This is because tuples are immutable. The sequence that they are provided when they are created is maintained as long as the tuple object exists.
Ranges are a very simple type of sequence that is most commonly used in for
loops. Ranges can only contain integers in a fixed pattern. You can build a
range using the range() constructor method and loop through it as if it were a
standard list.
The range constructor only requires one argument: the end of the range. You may have noticed above that this top value is not included in the range itself. This is similar to how slicing works in lists.
for n in range(4):
print(n)
# => 0
# => 1
# => 2
# => 3There are two optional arguments that you can include when creating a range: a start value and a step size.
range(4)gives us0, 1, 2, 3range(1, 4)gives us1, 2, 3range(0, 4, 2)gives us0, 2
While ranges are very similar to lists, a range is a different data type and they exhibit some unique behaviors.
For instance, when we print() a list, we can see its contents:
my_list = [0, 1, 2, 3]
print(my_list)
# => [0, 1, 2, 3]When we print a range containing the same elements, here's what we see:
my_range = range(4)
print(my_range)
# => range(0, 4)
What would range(2, 10, 2) produce?
range() statements produce range objects.
To view the contents, of a range object, you must loop
through and print each element or cast the range object to a
list or tuple using their class constructors.
The contents of this range would be:
2, 4, 6, 8
Python strings have many methods that allow you to access and manipulate their individual elements. It's very important to remember while working with strings that they are iterable objects (they can be looped through!) and they are indexed.
my_string = 'Hello world!'
for char in my_string:
print(char)
# => H
# => e
# => l
# => l
# => o
# =>
# => w
# => o
# => r
# => l
# => d
# => !
my_string[0]
# => 'H'Strings can be formatted for case using three methods:
str.upper()returns an uppercase version of the original string.str.lower()returns a lowercase version of the original string.str.title()returns the original string in titlecase (with the first letter of each new word capitalized.)
There are many other string methods that will allow you to accomplish most simple reformatting and conversion operations that you'll want to do. There are so many, in fact, that we're providing a link to a comprehensive list instead of going in-depth on each one.
The important thing to remember when working with strings is that they are immutable. All string methods return a new object; they do not replace the original.
my_string = 'hello world!'
my_string.upper()
# => HELLO WORLD!
print(my_string)
# => hello world!Time to get some practice! Write your code in the sequences.py file in the
lib folder. Run pytest -x to check your work. Your goal is to practice
manipulating sequences with the Python tools you've learned about in this lesson
and the lessons before.
Write a function print_fibonacci() that prints a list of the
fibonacci sequence up to the length provided in the
function's parameters.
print_fibonacci(9)
# => [0, 1, 1, 2, 3, 5, 8, 13, 21]When all of your tests are passing, submit your work using git.