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Part 3.3Arrays and lists in Python

In computer languages, an array is a structure used to store multiple related items in an indexed format that somewhat resembles the actual memory it is representing.

One of the most important things to notice about arrays is that they begin at index 0. That means the first element of the array is the 0th element.

Whilst Python does have an actual array data type, the most common array used is the list (much like ZPE). 

Arrays

An array with some integer values within it.

Notice the first index, that is, where n = 0, is the 0th element.

Lists in Python

Python arrays can be defined very quickly using the [] notation. In most languages, a list differs from an array in that each element of the list can be of a different type.

The following sample demonstrates declaring a list of 10 numbers of the Fibonacci Sequence.

Python
fib = [1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
print (fib)
    

Arrays can be given empty values and a default length by simply defining them as having a certain number of empty elements as shown below:

Python
arr = [""] * 5
print (arr)
    

The previous sample will create precisely 5 empty strings within an array. This array will have a fixed length, so it is not possible to access an element larger than the array.

If numbers are required, it may be a good idea to create a list with 0s as the initial value:

Python
arr = [0] * 5
print (arr)
    

Appending an element

Appending an element allows an array to expand in size and add an element to it. To append to an array, the list.append method is used:

Python
fib = [1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
fib.append(144)
print (fib)
    

Accessing an element

An element within the list can be accessed instantly using its index. In Python, the square bracket ([]) syntax is used:

Python
fib = [1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
# Since Python indexes start on 0, this will return the value 3.
print (fib[2])
    

Elements at a certain index can also be set using the same notation:

Python
fib = [1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
# The number 3 will become 10
fib[2] = 10
print (fib)
    

List length

All programming languages provide some method of determining the length of an array or list. Python is no exception. Within Python an internal method known as len will obtain the length of certain values such as the list:

Python
fib = [1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
print (len(fib))
    
The len method will return a human-readable length, so a list with just one element will return 1 and one with no elements will return 0.

Dictionaries

An alternative to using arrays is Python's dictionary data type. Similar in functionality to PHP's associative array or ZPE's map data type, it works with a key to value pair.

Each element in the dictionary is given a unique identifier called a key which is then given a value. The key is then hashed, giving it a mathematical representation which acts as its index in an array. This makes access to it instant (since that index has been generated from a unique hash, each time the key is used it will know exactly what index to look for).

Defining a dictionary

To define a dictionary in Python, the { } syntax is used. Inside the brackets, key to value pairs are created using key : value syntax, with each separated by a comma. The following example shows this:

Python
user1 = {"userid" : 1, "fullname" : "John Smith", "username" : "john1", "password" : "rock123"}
print (user1)
    

Using the key

Of course some dictionary as shown above is not particularly useful if it is simply being printed out. The purpose of a dictionary is to allow a program to 'lookup' a value based on its key. Dictionaries are very fast at doing this.

To access or lookup a value based on its key, the square bracket syntax as shown above is used:

Python
user1 = {"userid" : 1, "fullname" : "John Smith", "username" : "john1", "password" : "rock123"}

print ("Username:", user1["username"])
print ("User ID:", user1["userid"])
    

In this case, the key being looked up is the "username" key and then the "userid" key.

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