Unit 1: Summary – Python Programming

Introduction to Python Programming

Python is one of the most widely used programming languages today, renowned for its simplicity, readability, and versatility. Whether you’re developing a web application, performing data analysis, or automating system tasks, Python offers a clear syntax and a vast ecosystem of libraries to support almost any task.

1. History & Versions of Python

Python was created by Guido van Rossum in the late 1980s and officially released in 1991. The language was named after the British comedy group Monty Python, not the snake, reflecting the language’s focus on being fun and easy to use.

Over time, Python has evolved into multiple versions:

·       Python 1.0 (1991): Introduced core concepts like functions, exception handling, and modules.

·       Python 2.x (2000): Brought in features like list comprehensions and garbage collection, but had issues with backward compatibility.

·       Python 3.x (2008–present): A complete overhaul with cleaner syntax, better Unicode support, and improved libraries. Python 2 reached end-of-life in 2020, and Python 3 is the standard now.

The most current stable version (as of 2024) is Python 3.12, offering faster performance and better error reporting.

2. Features of Python

Python stands out because of the following core features:

·       Easy to Learn & Use: Its syntax is intuitive and close to the English language.

·       Interpreted Language: Python code is executed line by line, which aids in quick debugging.

·       Dynamically Typed: You don’t need to declare data types explicitly.

·       Object-Oriented: Supports concepts like classes, objects, inheritance, and encapsulation.

·       High-Level Language: Abstracts low-level details like memory management.

·       Extensive Libraries: Includes built-in modules for mathematics, networking, GUI, and more.

·       Cross-Platform: Python programs can run on Windows, Linux, and macOS with little to no changes.

·       Open Source: Freely available with strong community support.

3. Execution of a Python Program

When you write a Python program (.py file), it undergoes the following steps:

1.        Lexical Analysis: Tokenizes your code.

2.      Parsing: Translates code into an Abstract Syntax Tree (AST).

3.      Compilation: Converts AST to bytecode (.pyc files).

4.      Interpretation: Bytecode is interpreted by the Python Virtual Machine (PVM).

This process is seamless to the user—just run python filename.py, and the interpreter takes care of the rest.

4. Flavours of Python

Python has various “flavours” or implementations, each with unique strengths:

·       CPython: The default and most widely-used version, written in C.

·       Jython: Python running on the Java Virtual Machine (JVM).

·       IronPython: Designed to run on the .NET framework.

·       PyPy: Fast Python implementation with a Just-In-Time (JIT) compiler.

·       MicroPython: For microcontrollers like Raspberry Pi Pico or ESP32.

Each flavour helps Python integrate with different platforms and enhances its flexibility.

5. Innards of Python

The internal working of Python involves:

·       Bytecode Compilation: Python code is compiled into bytecode, a low-level set of instructions.

·       PVM (Python Virtual Machine): Executes the bytecode.

·       Dynamic Typing: Variables don’t need a type declaration; type is inferred during runtime.

·       Namespaces: Isolated environments where names are mapped to objects.

Understanding these inner mechanisms helps when debugging or optimizing performance.

6. Python Interpreter

The Python interpreter is a command-line interface where you can type Python code and see instant results.

·       Open a terminal and type python or python3.

·       The >>> prompt appears.

• Type Python statements directly, like:

           >>> print(“Hello, World!”)

The interpreter is great for quick experiments and learning.

7. Memory Management in Python

Python manages memory automatically using:

·       Reference Counting: Each object has a reference count; when it hits zero, memory is freed.

·       Garbage Collection: Detects and cleans up circular references using the gc module.

·       Private Heap: Python uses a private heap for all objects and data structures.

This abstraction allows developers to focus on logic rather than memory management.

8. Garbage Collection in Python

Garbage Collection (GC) in Python:

·       Automatically identifies unused objects.

·       Uses generational GC, meaning it divides memory into generations based on object longevity.

• You can control it using the gc module:

           import gc
gc.collect()

Python’s GC ensures efficient memory use with minimal programmer intervention.

9. Comparison of Python with C and Java

Feature	Python	C	Java
Typing	Dynamic	Static	Static
Syntax	Simple, readable	Complex	Verbose
Compilation	Interpreted	Compiled	Compiled to bytecode
Memory	Managed	Manual	Managed
Platform Independence	Yes	No	Yes
Speed	Slower	Fast	Faster
OOP Support	Strong	Limited	Strong

Python offers simplicity and flexibility, C offers speed and control, and Java provides a balance of both.

10. Installing Python

Steps to install Python:

1.        Visit https://www.python.org

2.      Download the latest Python 3 installer for your OS.

3.      Run the installer and check “Add Python to PATH”.

4.      After installation, verify by running python –version in your terminal.

Python also comes pre-installed on many Linux and macOS systems.

11. Writing and Executing Your First Python Program

Let’s write our first program:

1.        Open any text editor (VS Code, Notepad++) or IDLE.

2. Save this code as hello.py:

           print(“Welcome to Python Programming!”)

3. Open your terminal and run:

           python hello.py

Output:

Welcome to Python Programming!

Congratulations! You’ve just executed your first Python script.

12. Getting Help in Python

Python offers several built-in ways to get help:

• Help function:

           help(print)

• Dir function:

           dir(str)

·       Official Docs: https://docs.python.org/3

·       Community: Use Stack Overflow, Reddit, or official mailing lists.

13. IDLE: Python’s Built-In IDE

IDLE (Integrated Development and Learning Environment) is Python’s default editor.

·       Comes bundled with the Python installation.

·       Features:

·       Interactive interpreter shell.

·       Syntax highlighting.

·       Auto-indentation.

·       Debugging tools.

·       To open: Search for “IDLE” in your system’s application list.

IDLE is perfect for beginners who want to learn and practice in a safe environment.

Learning Outcomes Applied

To learn how to design and program Python applications:

Using Python’s easy-to-read syntax and simple setup process, students can quickly begin writing applications — from a basic calculator to data processing tools and web services.

To learn how to use lists, tuples, and dictionaries:

Python offers powerful built-in data structures:

• List: Mutable and ordered.

           fruits = [“apple”, “banana”, “cherry”]

• Tuple: Immutable and ordered.

           colors = (“red”, “green”, “blue”)

• Dictionary: Key-value pairs.

           student = {“name”: “Alice”, “age”: 20}

To learn how to identify Python object types:

You can use type() to inspect data types:

type(“Hello”)     # <class ‘str’>
type(5)           # <class ‘int’>
type([1,2,3])     # <class ‘list’>

Everything in Python is an object.

To learn how to use indexing and slicing:

You can access elements in sequences like lists, tuples, and strings:

my_list = [10, 20, 30, 40, 50]
print(my_list[0])     # 10
print(my_list[-1])    # 50
print(my_list[1:4])   # [20, 30, 40]

Slicing helps to extract specific parts of data structures efficiently.

Conclusion

Python’s charm lies in its simplicity, elegance, and power. By understanding its core features—from installation and syntax to memory management and data handling—students can build a strong foundation for their journey into software development, data science, automation, and beyond.