Data structures¶

In programming, a data structure is the organization, management, and storage format of the data in the computer that enables efficient access and modification of it [Wikipedia, 2021]. Data structures lets a programmer write a more efficient and readable code. Knowing data structures may reduce the complexity of your program from O(n) to O(1)!

There are popular data structures available accross multiple programming languages like lists, stacks, queues, dictionaries and etc.

Python is no exception. In this chapter, I will go over the more popular ones used in practise.

List¶

A list is sequence of several variables, grouped together and accesed via one name in the namespace.

In Python, a list is defined with square brackets “[” and “]”. Each element in the list is separated by a comma “,”.

To access specific elements in the list we use their index.

# A list of all numerics 
a = [1, 4, 7]

# A list of mixed datatypes 
b = [1, "1", True]

# Accessing elements
print(f"First element in the list 'a': {a[0]}; Second: {a[1]}; ...")

First element in the list 'a': 1; Second: 4; ...

In Python, lists have several built-in methods[Foundation, 2021]. One of the most popular used in practise:

# Initializing an empty list
a = [1, 1, 2, 3]
print(f"Initial list:\n{a}")

# Adding an element to the "back" of the list (appending to the back)
print(f"--- append() ---")
a.append(5)
print(f"List after appending an element:\n{a}")

# Reversing a list 
print(f"--- reverse() ---")
a.reverse()
print(f"List after reversing it:\n{a}")

# Sorting the elements; Works the best where all the data types of elements are the same
print(f"--- sort() ---")
a.sort()
print(f"Sorted list:\n{a}")

# Counting the number of occurance of elements 
print(f"--- count() ---")
elements = [1, 5, 60]
for element in elements:
    n = a.count(element)
    print(f"Times the number {element} occured in the list: {n}")

# Findining the index of certain elements 
print(f"--- index() ---")
for element in elements:
    try:
        print(f"The first occurance of element {element} in the list is at index {a.index(element)}")
    except ValueError:
        print(f"There is no element {element} in the list")

Initial list:
[1, 1, 2, 3]
--- append() ---
List after appending an element:
[1, 1, 2, 3, 5]
--- reverse() ---
List after reversing it:
[5, 3, 2, 1, 1]
--- sort() ---
Sorted list:
[1, 1, 2, 3, 5]
--- count() ---
Times the number 1 occured in the list: 2
Times the number 5 occured in the list: 1
Times the number 60 occured in the list: 0
--- index() ---
The first occurance of element 1 in the list is at index 0
The first occurance of element 5 in the list is at index 4
There is no element 60 in the list

A list in Python can be created using a list comprehension. List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list.

# Creating a sequence of numbers and cubing them 
seq = list(range(-3, 4))
print(f"Original sequence: {seq}")

# Squering using the for loop
# Initializing an empty list 
a = []
for element in seq:
    a.append(element ** 2)

# Squering using list comprehension
# Note that an empty list namespace link does not need to be created prior
b = [x ** 2 for x in seq]

# Printing out the results 
print(f"For loop list: {a}")
print(f"List comprehension list: {b}")

Original sequence: [-3, -2, -1, 0, 1, 2, 3]
For loop list: [9, 4, 1, 0, 1, 4, 9]
List comprehension list: [9, 4, 1, 0, 1, 4, 9]

Dictionary¶

A dictionary is a data type that holds information in key -> value pairs. Dictionaries are sometimes found in other languages as associative memories or associative arrays. Unlike sequences, which are indexed by a range of numbers, dictionaries are indexed by keys, which can be any immutable type.

Dictionaries in Python are defined between curly brackets { }.

All the keys in the dictionary need be unique. To access a value in the dictionary we must use it’s key.

# Defining a dictionary with two keys 
a = {
    "person_1": "Eligijus Bujokas",
    "person_2": "Bligijus Eujokas"
}

# Printing out the dictionary 
print(f"Initial dictionary: {a}")

# Getting the keys 
keys = list(a.keys())
print(f"Keys in dictionary: {keys}")

# Accessing the elements of the dictionary
print(f"Value of key {keys[0]} is: {a[keys[0]]}")
print(f"Value of key {keys[1]} is: {a.get(keys[1])}")

# To update a dictionary, we use the built in update() method
print(f"--- update() ---")
a.update({'person_3': "Sakojub Sujigile"})
print(f"Updated dictionary: {a}")

Initial dictionary: {'person_1': 'Eligijus Bujokas', 'person_2': 'Bligijus Eujokas'}
Keys in dictionary: ['person_1', 'person_2']
Value of key person_1 is: Eligijus Bujokas
Value of key person_2 is: Bligijus Eujokas
--- update() ---
Updated dictionary: {'person_1': 'Eligijus Bujokas', 'person_2': 'Bligijus Eujokas', 'person_3': 'Sakojub Sujigile'}

Set¶

A set in Python is an unordered collection with no duplicate elements. Sets are defined between curly brackets just like dictionaries but do not have a key -> value logic. Each item in a set definition is separated by a comma. Python will only leave unique elements after the initialization.

a = {"eligijus", "bujokas", "bujokas"}

print(f"Initial set: {a}")

Initial set: {'eligijus', 'bujokas'}

A very useful functionality with sets in Python is the set operation functionality. We can obtain the intersection, difference and union of two sets.

a = set([x for x in range(-5, 4)])
b = set([x for x in range(-1, 7)])

print(f"Set a: {a}")
print(f"Set b: {b}")

print(f"Intersection of a and b: {a.intersection(b)}")
print(f"Difference a - b: {a.difference(b)}")
print(f"Difference b - a: {b.difference(a)}")
print(f"Union of both sets: {a.union(b)}")

Set a: {0, 1, 2, 3, -1, -5, -4, -3, -2}
Set b: {0, 1, 2, 3, 4, 5, 6, -1}
Intersection of a and b: {0, 1, 2, 3, -1}
Difference a - b: {-5, -4, -3, -2}
Difference b - a: {4, 5, 6}
Union of both sets: {0, 1, 2, 3, 4, 5, 6, -1, -5, -4, -3, -2}

Machine Learning Serving API

Data structures¶

List¶

Dictionary¶

Set¶

Iterators¶

Data structure types¶

Mutable and non mutable¶

Linear and non-linear¶

Contributions¶