18 chapters of hands-on Python instruction with real, runnable code — from variables and control flow through functions, OOP, file handling, external libraries, web scraping, automation, GUIs, testing, databases, and three complete mini-projects.
Part I: Ch 1 Why Python & setup, Ch 2 quick refresher for programmers. Part II: Ch 3 data types, Ch 4 control flow, Ch 5 functions & modules, Ch 6 error handling & debugging. Part III: Ch 7 files & directories, Ch 8 external libraries (pip, NumPy, Pandas), Ch 9 visualizing data with Matplotlib. Part IV: Ch 10 web scraping & APIs, Ch 11 automation, Ch 12 GUI basics with Tkinter. Part V: Ch 13 object-oriented Python, Ch 14 testing & debugging, Ch 15 databases & persistence with SQLite. Part VI: Ch 16-18 three mini-projects — expense tracker, weather dashboard, and chatbot.
Every chapter pairs a concept with an actual Python snippet you can type and run — from a two-line "Hello, World!" comparison against Java, through a full CSV/Pandas/Matplotlib expense tracker, a Tkinter weather dashboard that calls the OpenWeatherMap API, and a regex-based rule-based chatbot. Code is shown verbatim, matching the source manuscript.
Written for readers who already have some programming background — in C, Java, or another language — and want to learn Python quickly by seeing real examples in action rather than re-covering programming fundamentals from scratch. Each topic is followed immediately by working code you can modify and extend.
The reader progresses from core syntax (variables, loops, functions) to intermediate topics (OOP, file I/O, external libraries, web scraping and APIs, automation, GUIs) to applied engineering practice (unit testing with unittest, persistence with SQLite) and finishes with three complete, combined mini-projects that tie the concepts together into working applications.
The source book assumes you already know how to code in some language — C, Java, or similar — and focuses on how Python specifically works rather than general programming concepts like variables or loops from scratch. If you are completely new to programming, you may want a beginner-first resource before this one, but the syntax explanations (indentation instead of braces, dynamic typing, f-strings) are still clear enough for a motivated first-time learner.
It covers the standard library (os, shutil, csv, json, sqlite3, unittest, tkinter) plus the most common third-party libraries for data and web work: requests and BeautifulSoup for HTTP calls and web scraping, NumPy and Pandas for numerical and tabular data, Matplotlib for charts, and the schedule library for time-based automation. Each is introduced with pip install instructions and a minimal working example before use in a larger sample program.
Chapter 16 builds a command-line Expense Tracker that appends entries to a CSV file with Python's csv module, summarizes totals by category with Pandas, and plots a bar chart with Matplotlib. Chapter 17 builds a Weather Dashboard — a small Tkinter GUI that calls the OpenWeatherMap API with requests and displays temperature, description, and wind speed for any city. Chapter 18 builds a rule-based Chatbot that uses regular expressions and keyword matching to respond to greetings, questions about the time, jokes, and exit commands.
Yes — Chapter 13 covers defining a class with __init__ and instance methods (a Dog class with a bark() method), inheritance and method overriding (an Animal base class with a Cat subclass that overrides speak()), and a complete BankAccount class with deposit and withdraw methods that demonstrates why OOP is useful when you need to track state across method calls, versus a simpler functional approach for one-off scripts.