Python Tutorial. Full course collection

This Python tutorial will help you learn Python programming and build a career in it. This tutorial contains Python basics, its installation, variables, data types, conditional statements, loops, user-defined functions, OOPs Concepts, and Python Cheat Sheets.

In this Python tutorial, we will comprehensively learn all the concepts of Python. The following are the topics in table of content that we are going to cover in this tutorial:

What is Python?

Python is a high-level, interpreted, general-purpose programming language. It was created by Guido van Rossum and was first released in 1991. Python is known for its clear and readable syntax, making it a popular choice for both beginners and experienced programmers. It supports multiple programming paradigms such as procedural, object-oriented, and functional programming, and has a vast standard library that makes it a versatile language for tasks such as web development, scientific computing, data analysis, and automation.

There are several reasons why someone might choose to learn Python:

• Easy to learn: Python has a simple and readable syntax, making it an ideal language for beginners to learn.
• Versatile: Python can be used for a wide range of tasks, such as web development, scientific computing, data analysis, machine learning, and more.
• Large community: Python has a large and active community of users, who contribute to its development and provide support to each other. This means that there is a wealth of resources available for learning and solving problems.
• High demand: Python is a highly sought after skill in the job market, with demand for Python developers continuing to grow.
• Powerful libraries and frameworks: Python has a vast ecosystem of libraries and frameworks that make it easy to perform complex tasks, such as data analysis, machine learning, and web development.

Overall, Python is a versatile and powerful language that is easy to learn and has many practical applications, making it a valuable skill to have.

Suppose we want to print “Welcome to the world of programming” on our screen. Let’s compare the syntax for Python and Java:

Python Syntax:

print(“Welcome to the world of programming”)

Java Syntax:

class Simple{

public static void main(String args[]){

System.out.println("Welcome to the world of programming");

}

}

So here we see that Python code consists of only one line, but for Java, there are multiple lines of code just for printing a statement.

A Brief History of python

Python was created in the late 1980s by Guido van Rossum, a Dutch programmer. The language was named after the Monty Python comedy group and was first released in 1991. Python was designed to be an easy-to-read and write language that emphasized code readability and concise syntax.

Over the years, Python has evolved and matured, with new versions being released regularly. Today, Python is one of the most widely used programming languages in the world, with a large and active user community that contributes to its development.

Python has been used in a variety of applications, including web development, scientific computing, data analysis, artificial intelligence, and more. The popularity of Python has grown steadily over the years, and it is now one of the top programming languages in terms of popularity, job demand, and salary.

Characteristics of Python

Here are some of the key characteristics of the Python programming language:

Interpreted: Python is an interpreted language, which means that the code is executed line by line, rather than being compiled beforehand.

Dynamic Typing: Python supports dynamic typing, meaning that variables can change their type during runtime.

Object-Oriented: Python is an object-oriented programming language, which means that it allows for the creation of objects and classes, and the use of inheritance and polymorphism.

High-level: Python is considered a high-level language, as it provides a high-level of abstraction from the underlying hardware.

Readable: Python has a clear and readable syntax, making it easy to write and maintain code.

Versatile: Python has a wide range of applications, including web development, scientific computing, data analysis, artificial intelligence, and more.

Large Standard Library: Python has a large standard library that provides many useful modules for tasks such as data analysis, file handling, and web development.

Cross-Platform: Python code can run on a variety of platforms, including Windows, macOS, and Linux, making it a cross-platform language.

These characteristics make Python an accessible, flexible, and powerful language, suitable for a wide range of tasks and applications.

Career Opportunities:

Learning Python can open up a variety of career opportunities, including:

1. Web Development: Python is a popular choice for server-side web development, and frameworks like Django and Flask make it easy to build and deploy web applications.
2. Data Science: Python is widely used in data science and machine learning, with powerful libraries like NumPy, Pandas, and scikit-learn making it easy to perform data analysis and modeling.
3. Machine Learning: Python is a popular choice for machine learning due to its powerful libraries and ease of use. Python is used in a variety of industries, including finance, healthcare, and marketing, to build predictive models.
4. Scientific Computing: Python is used in scientific computing and research, with libraries like NumPy and SciPy making it easy to perform complex calculations and simulations.
5. Automation: Python can be used for automating repetitive tasks, making it a valuable skill for IT professionals and system administrators.
6. Game Development: Python is used to build games, with libraries like Pygame making it easy to create games and multimedia applications.

These are just a few examples of the many career opportunities that are available for those with Python skills. As the demand for Python continues to grow, the career opportunities for Python developers will continue to expand.

Python Installation

If you are new to programming, then installing a programming language itself could be a herculean task. So, now we are going to look at the step-by-step process to install python.

1. Start off by going to this website -> Downloads Python

2. Click on the downloads tab and choose the operating system and python version. So, here I am downloading python version 3.7.4 for  Windows operating system.

Now that we have installed python, let’s go ahead in this tutorial and start off with programming in Python

The two versions of Python- Python 2  and Python 3 are the most widely used Python versions and there are many differences between these versions which are as follows:

Variables in Python:

A variable in Python is a named location in memory that stores a value. Variables in Python can be used to store values of any data type, including numbers, strings, lists, and more.

To create a variable in Python, you simply assign a value to a variable name using the “=” operator. For example:

makefileCopy codex = 5

In this example, a variable named “x” is created and assigned the value of 5.

It is important to note that variable names in Python must start with a letter or underscore, and can contain letters, numbers, and underscores. Variable names are case sensitive, so “x” and “X” are considered two different variables.

Once a variable is created, its value can be accessed and modified. For example:

pythonCopy codex = 5
print(x) # Output: 5
x = 10
print(x) # Output: 10

In this example, the value of the variable “x” is first set to 5, and then changed to 10. The value of the variable is printed both times to show the change.

Variables in Python are a fundamental concept, and are used extensively in almost all Python programs. Understanding variables is essential for becoming a proficient Python programmer.

Assigning values to a variable:

To assign values to a variable in Python, we will use the assignment (=) operator.

Here, initially, we have stored a numeric value -> 10 in the variable ‘a’.  After a while, we have stored a string value -> “sparta” in the same variable. And then, we have stored the logical value True.

Now, let’s implement the same thing in Jupyter Notebook and look at the result:

Assigning a value 10 to a:

Allocating “sparta” to a:

Assigning True to a:

Going ahead in this tutorial, we will learn about data types in Python.

Data Types in Python

In Python, there are several built-in data types that are used to store values. Some of the most commonly used data types include:

1. Numbers: Python supports two types of numbers: integers (whole numbers) and floating-point numbers (numbers with decimal points). For example:

makefileCopy codex = 5
y = 3.14

2. Strings: A string is a sequence of characters, and is defined using single or double quotes. For example:

makefileCopy codename = "John Doe"
city = 'London'

3. Lists: A list is an ordered collection of values, and is defined using square brackets. Lists can contain values of any data type. For example:

cssCopy codefruits = ['apple', 'banana', 'cherry']
numbers = [1, 2, 3, 4, 5]

4. Tuples: A tuple is similar to a list, but is immutable (i.e., its values cannot be changed once created). Tuples are defined using parentheses. For example:

pythonCopy codecoordinates = (4, 5)
colors = ('red', 'green', 'blue')

5. Dictionaries: A dictionary is an unordered collection of key-value pairs, and is defined using curly braces. For example:

pythonCopy codeperson = {'name': 'John Doe', 'age': 30, 'city': 'London'}

6. Sets: A set is an unordered collection of unique values, and is defined using the “set” keyword. For example:

scssCopy codeprimes = set([2, 3, 5, 7, 11, 13])

These are the basic data types in Python, and they can be combined and used in various ways to build more complex data structures. Understanding these data types is essential for writing effective and efficient Python code.

OOPS Concepts in Python

From its early beginning, Python has been an object-oriented language. Object-oriented programming (OOPs) is a programming technique that emphasizes the usage of classes and objects. Its goal is to use programming to create real-world concepts like inheritance, polymorphisms, and encapsulation. The basic idea behind OOPs is to combine data and the functions that interact with it into a single entity so that no other parts of the code may touch it. It also emphasizes the creation of reusable code. It is a common method of resolving an issue by generating objects.

The key concepts of Oops are as follows:

• Objects
• Classes
• Inheritance
• Polymorphisms
• Encapsulation

Numbers in Python

In Python, there are two types of numbers: integers and floating-point numbers.

1. Integers: Integers are whole numbers, and can be positive, negative, or zero. For example:

makefileCopy codex = 5
y = -10

2. Floating-Point Numbers: Floating-point numbers are numbers with decimal points, and can also be positive, negative, or zero. For example:

makefileCopy codex = 3.14
y = -0.5

In Python, you can perform arithmetic operations on numbers, such as addition, subtraction, multiplication, division, and more. For example:

makefileCopy codex = 5
y = 3
z = x + y # Output: 8
z = x - y # Output: 2
z = x * y # Output: 15
z = x / y # Output: 1.67

It’s also possible to perform more advanced mathematical operations in Python using the math module. For example:

luaCopy codeimport math
x = math.sin(math.pi / 2) # Output: 1.0
y = math.cos(math.pi) # Output: -1.0

Numbers are a fundamental data type in Python, and are used extensively in various types of applications, from simple arithmetic calculations to complex scientific simulations. Understanding how to use numbers in Python is an essential part of becoming a proficient Python programmer.

Python Strings

In Python, a string is a sequence of characters, and is defined using either single quotes (') or double quotes ("). For example:

makefileCopy codename = "John Doe"
city = 'London'

Strings are a commonly used data type in Python, and can be used to represent text data, such as names, addresses, and more.

In Python, you can manipulate strings using various methods, such as concatenation, slicing, and formatting. For example:

makefileCopy codefirst_name = "John"
last_name = "Doe"
full_name = first_name + " " + last_name # Output: "John Doe"

city = "London"
print(city[0:3]) # Output: "Lon"

age = 30
print("My name is {} and I am {} years old.".format(full_name, age))
# Output: "My name is John Doe and I am 30 years old."

It’s also possible to perform various string operations, such as finding the length of a string, converting strings to uppercase or lowercase, and more. For example:

luaCopy codecity = "London"
print(len(city)) # Output: 6
print(city.upper()) # Output: "LONDON"
print(city.lower()) # Output: "london"

Strings are an important data type in Python, and are used in various applications, such as web development, text processing, and more. Understanding how to use strings in Python is an essential part of becoming a proficient Python programmer.

Python Tuples

In Python, a tuple is a collection of ordered, immutable (unchangeable) elements. Tuples are defined using parentheses (( and )). For example:

makefileCopy codeperson = ("John", "Doe", 30)

Tuples are often used to store related pieces of information, such as a person’s name, age, and address. Because tuples are immutable, they can be used to store data that shouldn’t be changed, such as constant values.

In Python, you can access the elements of a tuple using indexing, similar to lists. For example:

pythonCopy codeperson = ("John", "Doe", 30)
print(person[0]) # Output: "John"
print(person[1]) # Output: "Doe"
print(person[2]) # Output: 30

You can also loop through the elements of a tuple, similar to lists. For example:

pythonCopy codeperson = ("John", "Doe", 30)
for element in person:
    print(element)
# Output:
# John
# Doe
# 30

Tuples are often used in combination with other data structures, such as lists and dictionaries, to store and manipulate data in a more structured and organized way. Understanding how to use tuples in Python is an important part of becoming a proficient Python programmer.

Python Lists

In Python, a list is a collection of ordered, mutable (changeable) elements. Lists are defined using square brackets ([ and ]). For example:

cssCopy codenumbers = [1, 2, 3, 4, 5]
names = ["John", "Jane", "Jim"]

Lists are often used to store collections of data, such as numbers, names, or any other type of information. Because lists are mutable, you can add, remove, or modify elements in a list.

In Python, you can access the elements of a list using indexing, similar to tuples. For example:

pythonCopy codenumbers = [1, 2, 3, 4, 5]
print(numbers[0]) # Output: 1
print(numbers[1]) # Output: 2
print(numbers[2]) # Output: 3

You can also loop through the elements of a list, similar to tuples. For example:

pythonCopy codenumbers = [1, 2, 3, 4, 5]
for number in numbers:
    print(number)
# Output:
# 1
# 2
# 3
# 4
# 5

Lists are also mutable, meaning you can add, remove, or modify elements in a list. For example:

csharpCopy codenumbers = [1, 2, 3, 4, 5]
numbers.append(6) # Output: [1, 2, 3, 4, 5, 6]
numbers.insert(0, 0) # Output: [0, 1, 2, 3, 4, 5, 6]
numbers.remove(3) # Output: [0, 1, 2, 4, 5, 6]

Lists are a powerful data structure in Python, and are used in various applications, such as data analysis, web development, and more. Understanding how to use lists in Python is an important part of becoming a proficient Python programmer.

Python Sets

In Python, a set is a collection of unordered, unique elements. Sets are defined using curly braces ({ and }) or the built-in set() function. For example:

makefileCopy codenumbers = {1, 2, 3, 4, 5}
names = set(["John", "Jane", "Jim"])

Sets are often used to store collections of unique elements, such as unique numbers or unique names. Because sets only allow unique elements, any duplicates in the input data will be automatically removed.

In Python, you can add, remove, or check for the existence of elements in a set. For example:

csharpCopy codenumbers = {1, 2, 3, 4, 5}
numbers.add(6) # Output: {1, 2, 3, 4, 5, 6}
numbers.remove(3) # Output: {1, 2, 4, 5, 6}
print(6 in numbers) # Output: True

Sets also support various set operations, such as union, intersection, and difference. For example:

pythonCopy codenumbers1 = {1, 2, 3, 4, 5}
numbers2 = {4, 5, 6, 7, 8}

# Union of two sets
print(numbers1.union(numbers2)) # Output: {1, 2, 3, 4, 5, 6, 7, 8}

# Intersection of two sets
print(numbers1.intersection(numbers2)) # Output: {4, 5}

# Difference of two sets
print(numbers1.difference(numbers2)) # Output: {1, 2, 3}

Sets are a useful data structure in Python, especially when you need to store unique elements or perform set operations. Understanding how to use sets in Python is an important part of becoming a proficient Python programmer.

Python Dictionary

In Python, a dictionary is a collection of key-value pairs. Dictionaries are defined using curly braces ({ and }) or the built-in dict() function. For example:

pythonCopy codeperson = {'name': 'John Doe', 'age': 30, 'city': 'New York'}
colors = dict(red='#FF0000', green='#00FF00', blue='#0000FF')

Dictionaries are often used to store collections of data where each element has a unique key, such as a person’s name, age, and city.

In Python, you can access the values of a dictionary using the keys. For example:

pythonCopy codeperson = {'name': 'John Doe', 'age': 30, 'city': 'New York'}
print(person['name']) # Output: 'John Doe'
print(person['age']) # Output: 30

You can also loop through the key-value pairs in a dictionary. For example:

pythonCopy codeperson = {'name': 'John Doe', 'age': 30, 'city': 'New York'}
for key, value in person.items():
    print(key, value)
# Output:
# name John Doe
# age 30
# city New York

Dictionaries are mutable, meaning you can add, remove, or modify elements in a dictionary. For example:

pythonCopy codeperson = {'name': 'John Doe', 'age': 30, 'city': 'New York'}
person['email'] = 'johndoe@email.com' # Add new key-value pair
person['age'] = 31 # Modify existing key-value pair
del person['city'] # Remove key-value pair

Dictionaries are a powerful data structure in Python, and are used in various applications, such as web development, data analysis, and more. Understanding how to use dictionaries in Python is an important part of becoming a proficient Python programmer.

Conditional Statements

We use a conditional statement to run a single line of code or a set of codes if it satisfies certain conditions. If a condition is true, the code executes, otherwise, control passes to the next control statement.

There are three types of conditional statements as illustrated in the above example:

1. If statement: Firstly, “if” condition is checked and if it is true the statements under “if” statements will be executed. If it is false, then the control will be passed on to the next conditional statements.
2. Elif statement: If the previous condition is false, either it could be “if” condition or “elif” after “if”, then the control is passed on to the “elif” statements. If it is true then the statements after the “elif” condition will execute. There can be more than one “elif” statement.
3. Else statement: When “if” and “elif” conditions are false, then the control is passed on to the “else” statement and it will execute.

Now, let’s go ahead and learn about loops in this tutorial.

Types of Loops in Python

In Python, there are two main types of loops: for loops and while loops.

For loops are used to iterate over a sequence of elements, such as a list or a range. For example:

pythonCopy codenumbers = [1, 2, 3, 4, 5]
for number in numbers:
    print(number)
# Output:
# 1
# 2
# 3
# 4
# 5

While loops are used to repeat a block of code as long as a certain condition is met. For example:

pythonCopy codecounter = 0
while counter < 5:
    print(counter)
    counter += 1
# Output:
# 0
# 1
# 2
# 3
# 4

Both for and while loops can be used to accomplish similar tasks, and the choice between the two depends on the specific requirements of your program.

In addition to for and while loops, there are also other types of loops in Python, such as enumerate() and zip() loops, that allow you to iterate over multiple sequences at the same time. Understanding how to use loops in Python is an important part of becoming a proficient Python programmer.

User-Defined Function

A user-defined function in Python is a block of code that performs a specific task and can be called multiple times throughout your program. Functions in Python are defined using the def keyword followed by the function name and a set of parentheses for any arguments the function may take. For example:

pythonCopy codedef greet(name):
    print("Hello, " + name + "!")

greet("John") # Output: Hello, John!

In this example, the function greet() takes a single argument name and prints a greeting message. The function is then called with the argument "John".

Functions can also return values using the return statement. For example:

pythonCopy codedef add(a, b):
    return a + b

result = add(3, 4)
print(result) # Output: 7

In this example, the function add() takes two arguments a and b and returns their sum. The result of the function is stored in the variable result and printed.

Functions allow you to reuse code, make your code more modular, and improve the readability of your code. They are an important part of writing efficient and maintainable Python programs.

Exception Handling

Exception handling in Python is a mechanism for dealing with errors or unexpected conditions in your code. It allows you to write code that can detect and handle specific exceptions that might occur, rather than crashing or producing incorrect results.

Exceptions in Python are raised using the raise statement, and they can be caught and handled using a try–except block. For example:

pythonCopy codetry:
    num = int(input("Enter a number: "))
except ValueError:
    print("Invalid input. Please enter a valid number.")

In this example, the try block contains code that might raise an exception. In this case, it tries to convert the user input to an integer using the int() function. If the input is not a valid integer, a ValueError exception is raised. The except block then catches this exception and prints a helpful error message.

It is important to handle exceptions in your code to ensure that it runs smoothly and produces the desired results. Exception handling allows you to handle errors gracefully and provide helpful error messages to the user, which can improve the overall user experience of your program.

try-except block

The try–except block in Python is a construct used for exception handling. It allows you to handle errors or unexpected conditions that might occur in your code, rather than crashing or producing incorrect results.

The basic structure of a try–except block is as follows:

pythonCopy codetry:
    # code that might raise an exception
except ExceptionType:
    # code to handle the exception

In this example, the code inside the try block is the code that might raise an exception. If an exception is raised, the code inside the except block will be executed. The ExceptionType specifies the type of exception that the except block will handle.

For example:

pythonCopy codetry:
    num = int(input("Enter a number: "))
except ValueError:
    print("Invalid input. Please enter a valid number.")

In this example, the code inside the try block tries to convert the user input to an integer using the int() function. If the input is not a valid integer, a ValueError exception is raised. The except block then catches this exception and prints a helpful error message.

The try–except block provides a way to handle exceptions in your code gracefully and to provide helpful error messages to the user. It is an important part of writing efficient and maintainable Python programs.

“else” block

The else block in a Python try–except statement is executed if no exception is raised in the try block. It is used to specify a block of code that should be executed when the code inside the try block runs successfully without raising any exceptions.

The basic structure of a try–except–else block is as follows:

pythonCopy codetry:
    # code that might raise an exception
except ExceptionType:
    # code to handle the exception
else:
    # code to run if no exception is raised

For example:

pythonCopy codetry:
    num = int(input("Enter a number: "))
except ValueError:
    print("Invalid input. Please enter a valid number.")
else:
    print("The number entered is:", num)

In this example, the code inside the try block tries to convert the user input to an integer using the int() function. If the input is a valid integer, no exception is raised and the code inside the else block is executed, printing the number entered by the user. If the input is not a valid integer, a ValueError exception is raised, and the code inside the except block is executed, printing an error message.

The else block provides a convenient way to specify a block of code that should be executed only if the code inside the try block runs successfully without raising any exceptions. It makes it easier to write code that can handle exceptions and run correctly even in the presence of errors.

“finally” block

The finally block in a Python try–except statement is executed regardless of whether an exception is raised in the try block or not. It is used to specify a block of code that should be executed regardless of the outcome of the code inside the try block.

The basic structure of a try–except–finally block is as follows:

pythonCopy codetry:
    # code that might raise an exception
except ExceptionType:
    # code to handle the exception
finally:
    # code to be executed regardless of the outcome

For example:

pythonCopy codetry:
    num = int(input("Enter a number: "))
except ValueError:
    print("Invalid input. Please enter a valid number.")
finally:
    print("Exiting the program.")

In this example, the code inside the try block tries to convert the user input to an integer using the int() function. If the input is not a valid integer, a ValueError exception is raised and the code inside the except block is executed, printing an error message. Regardless of whether an exception is raised or not, the code inside the finally block is executed, printing “Exiting the program.”

The finally block provides a convenient way to specify code that should be executed regardless of the outcome of the code inside the try block. It is often used for cleanup tasks such as closing files or releasing resources that are no longer needed. It ensures that the code inside the finally block is executed even if an exception is raised, making it a powerful tool for managing resources and ensuring that the system remains in a consistent state.

Applications of Python  

These are some applications of Python:

• Python may be used to create web apps
• Python can be used as a support language and hence, the best use for software development
• It is also used in scientific and numeric applications.
• To build e-commerce websites or ERP applications, Python will be of great use.
• Fandango, AnyCAD, and RCAM are all functions in Python that can be used to construct a 3D CAD application.
• Many libraries for working with image processing applications are available in Python.
• Python is versatile enough to execute a variety of tasks, therefore it can also be utilized to construct multimedia apps.

Here, in this tutorial, we learned all the basics of Python which are variables, string, numbers, data types, tuples, lists, sets, dictionaries, conditional statements, loops, user-defined functions, and exception handling. If you want to go through more concepts of Python in-depth, this Tutorial consists of all the modules which will help you throughout your learning.

Frequently Asked Questions

What is Python used for?

Python is used to develop different types of applications such as web applications, GUI-based applications, software development applications, scientific and numeric applications, network programming, gaming and 3D applications, and business applications. Also, Python has widely used in the field of data analytics, and data science.

How do I start learning Python?

You can start learning python by referring to various videos and tutorials that are widely available on the Internet. This best python tutorial is more than sufficient for you to become proficient at Python on a beginner’s level.

Is Python easy to learn?

Python is an Object-Oriented language just like Java and C++. If you already have knowledge of working on them, then it’s very easy to pick up. However, if you don’t have any knowledge of OOPs, it is still very easy to learn and work on due to easy syntax and high readability.

Can a beginner learn Python?

Considering the vast applications of Python and high demand in the IT world, it is actually advised for beginners to start their programming language venture with Python. By learning Python, beginners can validate their skills on OOPs. Thus, they will prove their worth and be assigned real-world Python projects at an early stage of their careers.

How fast can I learn Python?

Python is a vast and feature-rich language with an extended library of standard and pre-defined functions. You can master Python at an elementary level within days by referring to this tutorial. However, if you want to master and advance level Python, then it is advised for you to take up our online Python training. These courses can last up to 3 months depending on the depth of content.

Is Python the future?

Owing to its dynamic features, Python has been dominantly active in the marketplace as an extremely easy-to-use high-level and multi-paradigm programming language which is used for application development. As a result of its supportive community, Python will most likely continue to dominate over other programming languages in the upcoming years.

Is Java better than Python?

Python is better than Java because of its ease of use and simple syntax. Also, Python is more suited for quick prototyping, meaning that Python can reduce complex and long programs to short and crisp ones with more readability.

What is the best IDE for Python?

Numerous Integrated Development Environments (IDEs) are available on the Internet. The best IDEs for Python, in terms of end-user rating, are PyDev, PyCharm, and Spyder. You should also know that Jupyter Notebook is widely considered the best open-source web application for implementing Python codes.