Introduction to Python Programming (Beginner’s Guide)

Introduction to Python

Welcome to our blog post introducing Python programming! This blog dedicates itself to all individuals from any domain, including students, working professionals, mechanical engineers eager to learn programming, or complete newbies.Tech giants like Google, Netflix, and Facebook widely use Python, making it the most used programming language. Therefore, starting with Python programming is essential. If you’re interested, let’s dive right in! In this article you will get to learn about the python i.e introduction to python, python introduction and all about the introduction to python programming language pdf.

Learning Outcomes

• Describe the characteristics of Python as a high-level, general-purpose programming language.
• Python is widely used in major domains such as web development, AI/ML, and data analytics.
• Explain the popularity of Python among beginners and professionals in various domains.
• Demonstrate how to get started with Python programming using essential resources and IDEs.
• Recognize real-world applications of Python in organizations like NASA, Netflix, and Instagram.
• Outline the steps to become proficient in Python programming and resources for further learning.

This article was published as a part of the Data Science Blogathon.

What is Python Programming?

With an Introduction to Python, we can understand that it is a high-level object-oriented programming language that was created by Guido van Rossum. Python is also known as a general-purpose programming language, as it is used in the domains given below:

• Web Development
• Software Development
• Game Development
• AI & ML
• Data Analytics

This list can go on as we go but why python is so much popular let’s see it in the next topic.

Why Python Programming?

Let us explore the reasons as to why we prefer python programming over any other language.

• Purpose and Versatility of Python:
  • Python serves various purposes across different domains.
  • Due to its simplicity and powerful libraries, Python sees wide usage in data science, machine learning, and artificial intelligence.
  • JavaScript is popular among web developers for building user interfaces using frameworks like React, Vue, and Angular.
• General-Purpose Language:
  • Python is a general-purpose programming language used across many domains.
  • It’s simple to understand, scalable, and supports fast development.
• Accessibility and Simplicity:
  • Python’s syntax is straightforward, similar to English, enabling developers to write concise code.
  • It’s accessible to beginners without a programming background.
• Open-Source and Rich Libraries:
  • Python is open-source with a vast array of libraries that enhance developer productivity.
  • Developers can focus on business logic due to readily available tools.
• Digital Era Skills:
  • Python is in high demand in the digital era due to its ability to handle large datasets.

These points encapsulate the key aspects of Python’s popularity and utility across different domains.

IEEE spectrum list of top programming language 2021. The list of programming languages is based on popularity.

How Do We Get Started Python Programming?

In today’s digital world, there is an abundance of information available on the internet, which can sometimes be overwhelming when trying to learn something new. However, an introduction to Python programming is a great way to begin. You can start by exploring the documentation, which serves as an excellent starting point for learning Python. Once you become familiar with Python concepts and terminology, you can delve deeper into the language and explore more advanced topics.

Following are references where we can start our journey:

• Official Website: Click Here
• Udemy Course: Click Here
• YouTube: Click Here
• CodeAcademy: Click Here

Now that you’re excited to get started, you might be wondering where to begin coding. There are plenty of options available in the market, and you can use any Integrated Development Environment (IDE) that you’re comfortable with. Here are some IDEs specifically for Python, ideal for beginners:

• Visual Studio: Click Here
• PyCharm: Click Here
• Spyder: Click Here
• Atom: Click Here
• Google Colab: Click Here

These tools will help you write and execute Python code efficiently. Happy coding!

You can master Python through our comprehensive, free Python course.

Real-World Examples

Let us now explore some real world examples of Python.

NASA (National Aeronautics and Space Agency)

One of Nasa’s Shuttle Support Contractors, United Space Alliance developed a Workflow Automation System (WAS) which is fast. Internal Resources Within critical project stated that:

“Python allows us to tackle the complexity of programs like the WAS without getting bogged down in the language”.

Nasa also published a website where there are 400 open source projects which use python.

Netflix

There are various projects in Netflix which use python as follow:

• Central Alert Gateway
• Chaos Gorilla
• Security Monkey
• Chronos

One notable project is Regional Failover, which reduced system outage time from 45 minutes to 7 minutes without additional cost.

Instagram

Instagram also leverages Python extensively. They’ve developed a photo-sharing social platform using Django, a web framework for Python. Instagram has successfully upgraded their framework without encountering any technical challenges.

These examples show how Python’s simplicity and powerful libraries apply across diverse domains such as aerospace, entertainment, and social media.

Applications of Python Programming

Python programming language is versatile and widely used across various domains due to its simplicity and powerful libraries. Here are some key applications:

• Game Development: Python is used for game development with libraries such as:
  • PySoy: A 3D game engine supporting Python 3 and JavaScript.
  • PyGame: A set of Python modules designed for writing video games.
• Artificial Intelligence and Machine Learning: Python is the leading language for AI and ML applications due to its extensive libraries:
  • TensorFlow: An open-source machine learning framework for dataflow and differentiable programming.
  • PyTorch: An open-source machine learning framework that accelerates the path from research prototyping to production deployment.
  • Scikit-learn: A simple and efficient tools for predictive data analysis, accessible to everybody, and reusable in various contexts.
• Desktop GUI (Graphical User Interface): Python supports various toolkits and frameworks for developing desktop applications:
  • PyQt: A set of Python bindings for Digia’s Qt application framework.
  • Tkinter: Python’s standard GUI (Graphical User Interface) package.
  • PyGTK: A set of Python wrappers for the GTK+ graphical user interface library.
• Data Analysis and Visualization: Python is widely used for data analysis and visualization tasks:
  • Pandas: A fast, powerful, flexible, and easy-to-use open-source data analysis and manipulation library.
  • Matplotlib: A comprehensive library for creating static, animated, and interactive visualizations in Python.
  • Seaborn: A Python visualization library based on matplotlib that provides a high-level interface for drawing attractive statistical graphics.
• Scientific Computing: Python is extensively used in scientific and numerical computing:
  • NumPy: A fundamental package for numerical computing with Python.
  • SciPy: A Python-based ecosystem of open-source software for mathematics, science, and engineering.
  • SymPy: A Python library for symbolic mathematics.

How to Become Better Programmer?

Learning Python programming is just the beginning; becoming proficient requires consistent practice and project-based learning. Here are some tips to improve your Python programming skills:

• Understand the Concepts: Getting an introduction to Python programming is crucial for understanding its foundational concepts. Learn about variables, data types, control structures (like loops and conditionals), functions, and object-oriented programming.
• Practical Knowledge through Projects: Practical knowledge can only be acquired by working on real projects. Start with small projects and gradually move to more complex ones. This hands-on experience will expose you to real-world scenarios and challenges.
• Consistency is Key: Consistency is more important than the amount of time you spend each day. It’s better to code regularly for shorter periods than to binge-code occasionally. Set aside dedicated time each day or week to practice coding.
• Learn by Doing: The best way to learn Python is by doing. Write code, experiment with different approaches, and learn from your mistakes. Don’t shy away from challenging problems; they provide the best learning experiences.
• Work on Projects: Projects are a great way to apply what you’ve learned. Start with simple projects like building a calculator or a to-do list app. As you gain confidence, move on to more complex projects like web applications, games, or data analysis scripts.
• Engage with the Community: Join Python forums, participate in coding communities, and collaborate with other developers. Sharing your projects and code for feedback can help you improve and learn new techniques.

Becoming proficient in Python programming takes time and effort, but with consistency, dedication, and a love for learning, you can become a better Python programmer and tackle more complex challenges.

Approach to be Followed to Master Python

“Beginning is the end and end is the beginning”. This famous quote from the web series “Dark” aptly reflects the journey of learning Python programming. In the realm of programming, mastery is not a destination but a continuous process of trial and error. Errors like the “UnboundLocalErrorException” encountered when attempting to print a variable before declaration are part of the learning process.

Throughout your career as a programmer, you’ll encounter new challenges and exceptions, but consistent practice is key. Remember, “Practice makes a man perfect”. To master Python programming, adopt an approach that involves learning by doing, working on projects, seeking feedback, and staying updated with the latest trends and best practices in the Python community.

Step1: Start with a “Hello World” Program

If you happened to learn some programming languages, then I am sure you are aware of what I am talking about. The “Hello World” program is like a tradition in the developer community. If you want to master any programming language, this should be the very first line of code we should be seeking for.

Simple Hello World Program in Python:

print("Hello World")

Step2: Start learning about variables

Now once we have mastered the “Hello World” program in Python, the next step is to master variables in python. Variables are like containers that are used to store values.

Variables in Python:

my_var = 100

As you can see here, we have created a variable named “my_var” to assign a value 100 to the same.

Step3: Start learning about Data Types and Data Structures

The next outpost is to learn about data types. Here I have seen that there is a lot of confusion between data types and data structures. The important thing to keep in mind here is that data types represent the type of data. For example. in Python, we have something like int, string, float, etc. Those are called data types as they indicate the type of data we are dealing with.

While data structures are responsible for deciding how to store this data in a computer’s memory.

String data type in Python:

my_str = "ABCD"

As you can see here, we have assigned a value “ABCD” to a variable my_str. This is basically a string data type in Python.

Data Structure in Python:

my_dict={1:100,2:200,3:300}

This is known as a dictionary data structure in Python.

Again this is just the tip of the iceberg. There are lots of data types and data structures in Python. To give a basic idea about data structures in Python, here is the complete list:

• Lists
• Dictionary
• Sets
• Tuples
• Frozenset

Step4: Start learning about conditionals and loops

In any programming language, conditionals and loops constitute one of the backbones.

Python is no exception for that as well. This is one of the most important concepts that we need to master.

IF-ELIF-ELSE conditionals:

x=7
if(x < 10):
    print("x is less than 10")
elif(x > 10):
    print("x is greater than 10")
else:
    print("Do nothing")

As you can see in the above example, we created what is known as the if-elif-else ladder.

For loop:

for i in "Python":
    print(i)

The above code is basically an example of for loop in python.

Additional Resources

Here are some additional resources which might be helpful for you to dive deeper as follow:

• Python Projects: Click Here
• TutorialsPoint: Click Here
• PDF: Click Here
• Coding Challenge: Click Here

These are some useful link which helps you get more into python.

Conclusion

We provided a detailed introduction to Python programming, catering specifically to beginners. Python is a versatile and widely-used programming language known for its simplicity and readability. It serves various domains such as web development, data science, artificial intelligence, and more, making it an essential tool for developers and organizations alike. We explored the basics of Python, including variables, data types, control structures, and data structures, laying a strong foundation for mastering the language. With its extensive community support and vast ecosystem of libraries, Python is an ideal starting point for anyone looking to dive into the world of programming and build innovative applications.

Hope you like the article and get understanding about the introduction to python programming language pdf , what the python programming and what is the introduction to python you will cleared it.

You can master Python through our comprehensive, free Python course.

Key Takeaways

• Explored various domains where Python extensively used, including web development, data science, artificial intelligence, and more, highlighting its versatility and broad applicability.
• Covered foundational Python concepts such as variables, data types, control structures, and data structures, crucial for building a strong understanding of Python programming.
• Python’s popularity attributes to its vast community support, rich ecosystem of libraries, and straightforward syntax, enabling rapid development and innovation.
• Provided essential resources and recommended IDEs to help beginners kick-start their Python programming journey effectively and efficiently.
• Showcased real-world applications of Python in organizations like NASA, Netflix, and Instagram, emphasizing its critical role in cutting-edge technology and innovation.

The media shown in this article are not owned by Analytics Vidhya and is used at the Author’s discretion.