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Python Basics – Bootcamp Exercises

This repository contains a set of introductory Python exercises completed as part of a software development bootcamp. The project focuses on Python core data types, virtual environments, developer tooling, and common workflows used in professional development.

Exercises Covered

1. Python Environment Inspection

  • Created a Python script that imports the sys module
  • Printed the Python version and executable path
  • Confirmed the active virtual environment from the command line

2. Virtual Environments and Package Management

  • Created and activated a Python virtual environment (.venv)
  • Installed third-party packages using pip
  • Generated and shared dependencies using requirements.txt
  • Simulated a team workflow using pip freeze and pip install -r

3. Linting and Formatting

  • Configured VS Code to use Pylint for static code analysis
  • Observed warnings for unused variables and missing docstrings
  • Enabled automatic formatting on save using autopep8

4. Virtual Environment Detection

  • Created a script to detect whether Python is running inside a virtual environment
  • Compared sys.prefix and sys.base_prefix to determine execution context

5. Formatter and Execution Workflow (UML)

  • Created a UML sequence diagram illustrating:
    • Writing code in VS Code
    • Automatic formatting on save
    • Executing Python scripts in the integrated terminal

6. Core Python Data Types

  • Explored Python core data types including:
    • int, float, str, bool
    • tuple, range
    • list, dict, set
  • Used type() and id() to inspect object identity and behaviour

7. Mutable vs Immutable Data Types

  • Investigated immutable data types (str, int, float, tuple, range, bool)
  • Observed how reassignment creates new objects for immutable types
  • Explored mutable data types (list, dict, set)
  • Demonstrated in-place mutation and shared references
  • Compared assignment vs object duplication using .copy()

8. Collections and Set Operations

  • Worked with dictionaries to store and update key–value pairs
  • Explored sets and their properties (uniqueness, membership testing)
  • Used set operators:
    • Union (|)
    • Intersection (&)
    • Difference (-)

9. Flow Control (Loops and Conditionals)

  • Implemented for loops to:
    • Generate multiplication tables
    • Calculate squares of numbers
    • Iterate through dictionaries
    • Collect user input into lists
  • Implemented while loops to:
    • Control repeated execution based on user input
    • Generate prime numbers within a range
    • Continuously prompt users until a condition is met
  • Used if, elif, and else statements to:
    • Validate user input
    • Check voting eligibility
    • Determine whether numbers are prime
    • Identify odd and even numbers
  • Built an interactive, menu-driven calculator that:
    • Uses while True loops for repeated execution
    • Applies conditional branching (if / elif / else)
    • Validates user input
    • Supports addition, subtraction, multiplication, and division
    • Handles division-by-zero safely
    • Allows users to exit the program
  • Applied break to exit loops early when conditions are met

10. Exception Handling

  • Explored Python exception handling using:
    • try, except, else, and finally blocks
  • Handled specific exceptions such as:
    • ZeroDivisionError for invalid arithmetic operations
    • FileNotFoundError when attempting to read missing files
  • Demonstrated why catching overly general exceptions (Exception) should be avoided unless necessary
  • Implemented safe file handling using:
    • The with statement for automatic resource management
    • Explicit cleanup logic in finally blocks
  • Practised writing user-friendly error messages instead of allowing programs to crash
  • Observed program execution flow when exceptions are raised, caught, or uncaught

Tools and Technologies

  • Python
  • Virtual Environments (venv)
  • pip
  • VS Code
  • Pylint
  • autopep8
  • Git & GitHub

Notes

  • The virtual environment (.venv) is excluded from version control using .gitignore
  • Project-specific VS Code settings are included to ensure consistent linting and formatting behaviour

This project demonstrates foundational Python concepts, object behaviour, and development workflows commonly used in professional software development.