Python is a high-level, general-purpose programming language designed with an emphasis on readability, simplicity, and flexibility. Created by Guido van Rossum and released in 1991, Python has become one of the most popular programming languages in the world. It is widely used across a variety of domains, such as web development, data science, machine learning, artificial intelligence, automation, and scientific computing. This article will provide a comprehensive introduction to Python, its features, ecosystem, and practical applications, aimed at giving a detailed understanding of the language. A Brief History of Python Python was first conceived in the late 1980s as a successor to the ABC programming language, which was itself designed for teaching and simplicity. Guido van Rossum, a Dutch programmer, began work on Python in December 1989 at the Centrum Wiskunde & Informatica (CWI) in the Netherlands. Python’s main design goals were to be simple, readable, and allow for rapid development, while also supporting advanced features like object-oriented programming (OOP). The first public version, Python 0.9.0, was released in February 1991. It was built with key features such as exception handling, functions, and modules, which were critical for supporting large-scale applications. The language has evolved significantly over the years, with major milestones in Python 2.x and Python 3.x. Python 2.x (released in 2000) became widely used for many years, but it reached its end of life in January 2020. Since then, Python 3.x has become the standard, offering improved syntax, new features, and better performance. The transition from Python 2 to Python 3 was not backward compatible, which led to a gradual migration by the Python community. Key Features of Python 1. Readable and Simple Syntax One of Python’s most distinguishing features is its simple and readable syntax. Python was designed to be as intuitive as possible, even for non-programmers, making it an ideal language for beginners. It avoids unnecessary syntax and uses clear, English-like keywords. Python code tends to be shorter and more readable compared to other languages like C++, Java, or Perl. For example, in Python, indentation is used to define code blocks, rather than curly braces or semicolons, making the code more structured and visually appealing. This enforces good coding practices and ensures that Python code remains easy to follow. Example: python Copy if x > 10: print("x is greater than 10") else: print("x is less than or equal to 10") 2. Dynamically Typed Python is a dynamically typed language, which means that you don’t need to explicitly declare the type of a variable when you create it. The interpreter determines the type of the variable at runtime based on the assigned value. This makes Python code more concise and flexible, as the programmer doesn’t need to worry about type annotations. For example: python Copy x = 5 # x is an integer x = "hello" # x is

1. INTRODUCTION ABOUT
INTRODUCTION ABOUT
PYTHON PROGRAMMING
PYTHON PROGRAMMING
DR.T.KAVIPRIYA
Assistant Professor
Department of Computer Science with Cyber Security
Sri Ramakrishna College of Arts & Science
Coimbatore
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2. What is Python?
• Python is a high-level, interpreted programming language.
• Created by Guido van Rossum in 1991.
• Known for its readability and simplicity.
• Used for web development, data analysis, machine learning,
automation, and more.
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

3. Why Choose Python?
• Easy to Learn and Use: Simple syntax compared to other
languages.
• Extensive Libraries: Libraries for data science, web
development, and more.
• Versatile: Used in various domains (e.g., web development,
AI, automation).
• Open Source: Free to use and modify.
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

4. Python's Key Features
• Simple Syntax: Python’s syntax resembles plain English, making
it easy to read and write.
• Cross-Platform: Works on Windows, Mac, and Linux.
• Interpreted: Python code is executed line-by-line.
• Object-Oriented: Supports object-oriented programming (OOP).
• Dynamic Typing: You don't need to declare the type of variables.
• Extensive Standard Library: A wide range of built-in modules for
various tasks.
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

5. Python Syntax Basics
• Content:
• Variables and Data Types:
• Example: x = 10
• Indentation: Python uses indentation to define code blocks.
• Example:
• python
• Copy
• if x > 5: print("x is greater than 5")
• Comments: Use # for single-line comments.
• Example: # This is a comment
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

6. Python Data Types
• Integers: x = 5
• Floats: y = 3.14
• Strings: name = "Python"
• Lists: numbers = [1, 2, 3, 4]
• Dictionaries: student = {"name": "John",
"age": 21}
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

7. Python Operators
• Arithmetic Operators: +, -, *, /
• Comparison Operators: ==, !=, <, >
• Logical Operators: and, or, not
• Assignment Operators: =, +=, -=
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8. Python Control Flow
Conditional Statements: if, elif, else
if x > 10:
print("x is greater than 10")
else:
print("x is less than or equal to 10")
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

9. Python Control Flow
Loops: for, while
Example (for loop):
for i in range(5):
print(i)
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

10. Functions in Python
Defining Functions: Use def keyword.
Example:
def greet(name):
return f"Hello, {name}!“
• Calling Functions: greet("Alice")
• Return Values: Functions can return values using the return
keyword.
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

11. Python Libraries
• NumPy: For numerical computations.
• Pandas: For data manipulation and
analysis.
• Matplotlib: For data visualization.
• TensorFlow: For machine learning.
• Flask/Django: For web development.
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repared by Dr.T.Kavipriya,Asst.Prof,Dept.of Cs with Cys,SRCAS

12. Applications of Python
• Web Development: Using Flask and Django.
• Data Science: Analysis, machine learning, AI with libraries
like Pandas, NumPy, and Scikit-learn.
• Automation: Writing scripts to automate repetitive tasks.
• Game Development: Using libraries like Pygame.
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13. How to Get Started with Python
• Install Python: Visit python.org and download the latest
version.
• IDE: Use IDLE, PyCharm, or VS Code for coding.
• Write Your First Program: A simple "Hello, World!"
program.
• Example:
• print("Hello, World!")
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14. Conclusion
• Python is a beginner-friendly, versatile language.
• Its simplicity, readability, and wide usage in various fields
make it an excellent choice for learning and development
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