Series: Python Mastery
A collection of 18 posts in the "Python Mastery" series.
Table of Contents
- Python Learning Path: From Fundamentals to Intermediate Applications
A comprehensive 17-post curriculum taking you from Python installation to building real-world applications. Covers core language features, professional practices, data analysis tools, and practical project development.
- Part 1: Getting Started with Python on Windows
Learn what Python is, install it on Windows, and write your first Python program in this introductory guide to the Python programming language.
- Part 2: Text Editors vs. IDEs for Python Development
Compare lightweight text editors to full-featured IDEs for Python development. Learn how to set up VS Code with essential Python extensions and discover effective debugging techniques.
- Part 3: Python Syntax Fundamentals & Language Features
Master Python's core syntax including variables, data types, control flow, comprehensions, lambdas, iterators, generators, and basic error handling mechanisms.
- Part 4: Core Data Structures in Python
Explore Python's essential data structures: lists, tuples, dictionaries, and sets. Learn creation methods, manipulation techniques, and guidelines for choosing the right structure for your tasks.
- Part 5: Functions, Modules & File I/O in Python
Learn how to define and use functions, organize code into modules, leverage Python's Standard Library, and perform file operations for reading and writing data.
- Part 6: Virtual Environments & Packaging in Python
Discover how to create and manage virtual environments, install packages with pip, structure your own Python projects, and publish packages to PyPI with best practices.
- Part 7: Code Quality & Collaboration in Python
Learn version control with Git and GitHub, write clean PEP 8-compliant code, use linters and auto-formatters, and create effective documentation for your Python projects.
- Part 8: Testing & Debugging Python Code
Master unit testing with unittest and pytest, learn Test-Driven Development workflows, handle custom exceptions, use the debugger effectively, and implement structured logging.
- Part 9: Command-Line Tools & Automation with Python
Build command-line interfaces with argparse, create installable CLI tools, automate file operations, control GUI applications, and develop practical automation projects.
- Part 10: The Python Ecosystem & Interactive Data Workflows
Compare package managers (pip vs. conda), explore Anaconda Navigator, and learn to use Jupyter Notebooks for interactive data analysis and visualisation.
- Part 11: NumPy Fundamentals for Numerical Data
Get started with NumPy for numerical computing in Python. Learn about ndarrays, vectorized operations, broadcasting, and see how NumPy outperforms pure Python for numerical tasks.
- Part 12: Data Analysis with pandas
Master data analysis in Python using pandas. Learn to work with Series and DataFrame objects, import data from various sources, and perform essential data manipulation operations.
- Part 13: Data Visualisation Basics in Python
Create effective data visualisations using Matplotlib and Seaborn. Learn to make various plot types, customise their appearance, and save your figures for reports and presentations.
- Part 14: Introduction to Object-Oriented Programming (OOP) in Python
Understand the fundamentals of OOP in Python including classes, objects, methods, and attributes. Learn about encapsulation, inheritance, and polymorphism through practical examples.
- Part 15: Web Development Foundations with Python
Explore web development options in Python. Learn Flask for lightweight applications, Django for full-featured sites, or web scraping with requests and BeautifulSoup. Deploy your first web app.
- Part 16: Building Simple GUI Applications with Tkinter
Create desktop applications with Python's built-in Tkinter library. Learn about widgets, layout managers, and build a practical mini-project with a graphical user interface.
- Part 17: Next Steps & Advanced Python Topics
Explore advanced Python topics including concurrency, asyncio, and complete an end-to-end project. Discover resources for further learning and tips for continuing your Python journey.