Master Python.
Better, Faster, Easier.

"Among the best books available for taking your Python skills to the next level."
"Among the best books available for taking your Python skills to the next level."
The Acclaimed 180-Page eBook With ​9 Detailed Chapters & 100s of Advanced Python Code Examples
Updated For 2024
"There are very few books which offer the sort of insights needed to really improve skills. This is one of the few I can highly recommend for those who are struggling to achieve intermediate skill in Python."
Darrell Fee, Software Engineer in Test, USA

What You Learn

Chapter 1 Doing More with Python
Intro to more advanced Pythonic thinking, and how to think like a top 1% Pythonista.

Chapter 2 Scaling With Generators
Fully master this powerful feature of Python.

Chapter 3 Creating Collections with Comprehensions
How to effortlessly create lists, dicts, and other data structures using a high-level, readable, and maintainable syntax.

Chapter 4 Advanced Functions
Higher-order function abstractions, used as the basis of many famous Python libraries.

Chapter 5 Decorators
Pythons' "metaprogramming" tool, giving you priceless patterns of code reuse not possible any other way.

Chapter 6 Exceptions and Errors
Fully master Python's error model, how exceptions work in Python, and how to leverage them in your own code.

Chapter 7 Classes and Objects: Beyond The Basics
Going beyond the syntax of classes and methods. Learn the more potent and advanced tools of Python's object system.

Chapter 8 Automated Testing and TDD
A deep dive into this coding superpower... so you can expressively write tests for even your most complex applications.

Chapter 9 Logging in Python
A valuable and time-saving source of telemetry for your running application... so you can troubleshoot and debug more quickly, and enable robust monitoring.

"What have I found good and valuable about the book so far? Everything honestly. The clear explanations, solid code examples have really helped me advance as a Python coder... Thank you! It has really helped me grasp some advanced concepts that I felt were beyond my abilities."
Nick S., Data Scientist, Colorado

Bonus #1: Author Q&A Recordings

The author occasionally hosts Q&A recordings for Powerful Python readers.

And in this bonus, you get over 3 full hours of recordings from these fun interactive sessions.

Expanding on the topics in the book, and beyond...

The full archive is yours FREE with Powerful Python.
"Feels like Neo learning jujitsu in the Matrix."
John Beauford, Chief Technology Officer, Texas

Bonus #2: "Three Keys to Advanced Python" Course

You also get a bonus course titled:

"Three Keys To Advanced Python"

Going deeper on each of the three "boosts" we touched on in the above video:

- Object-Oriented Programming
- Test-driven Development
- Python Generators

Includes coding exercises, with full detailed solutions. Yours FREE when you buy Powerful Python today.
"Thanks. Keep up the good work. Your chapter on decorators is the best I have seen on that topic."
Leon Tietz, Minnesota, USA

What's Included

1. 180-page Powerful Python PDF eBook

2. Bonus #1: Author Q&A recordings (Over 3 hours)

3. Bonus #2: Three Keys to Advanced Python course

4. Lifetime updates for the Powerful Python eBook
"By far one of the best books out there. No nonsense, just great information."
Edward Finstein, Software Engineer, USA

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"I just wanted to let you know what an excellent book this is. I keep going back to your book to learn Python."
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What You Learn In Powerful Python

  • How to CONSISTENTLY get into a "flow" coding state (p. 157)
  • ​How to add complex behavior around groups of functions or methods in one swoop (p. 66)
  • ​A criminally under-used unit-testing technique for quickly assessing across a wide range of input values (p. 153)
  • ​The worst naming conventions you definitely want to avoid when writing your tests (p. 148)
  • ​The "Java trap" which has made many developers' lives utterly miserable... and how Python is IMMUNE to it (p. 118)
  • ​The two levels of learning... and why the first can be dangerously deceptive (p. 8)
  • ​Building a fascinating data structure that is a hybrid between a list and a set (p. 30)
  • ​The absolutely crippling mis-step you can make when writing a decorator... and how to avoid it every time (p. 68)
  • ​The over-powered Python feature which obsoletes several "standard" design patterns (p. 60)
  • ​The most powerful Python abstraction almost no one knows about (p. 57)
  • ​The #1 convention you absolutely MUST follow in all your unit tests to keep yourself happy and sane (p. 149)
  • ​How to make objects which can be called like a function (p. 83)
  • ​Priceless strategy for evolving your classes successfully, without breaking other code that depends on them (p. 116)
  • ​Why design patterns in Python work so differently than in other languages (p. 111)
  • ​A shortcut for making your class instances richly comparable to each other (p. 139)
  • ​The five levels of logging message "severity", and when to use each (p. 160)
  • ​What to do when a "for" loop is not enough (p. 12)
  • ​How to write surprisingly flexible function interfaces (p. 50)
  • ​An underused Python feature that naturally encourages great coding habits as you use it more (p. 10)
  • ​How cognitive psychology relates to coding (p. 7)
  • ​How to automatically "reset" the initial conditions when running a group of tests... and why failing to do so will waste hours of your time (p. 150)
  • ​The exception mis-pattern that wasted over a WEEK of three senior engineers' time on a violently stupid bug (p. 107)
  • ​The surprising connection between generator functions and comprehensions (p. 42)
  • ​The surprising link between Python generators and comprehensions (p. 42)
  • ​The Python feature you can learn which will permanently make you a better coder in EVERY language (p. 10)
  • ​A uniquely Pythonic tool for un-entangling frustratingly intertwined concerns in your code (p. 65)
  • ​The one Pythonic concept which will change how you write Python code forever (p. 57)
  • ​The "mental model hack" that lets you work with Python functions in surprisingly powerful ways (p. 81)
  • ​The 5 types of decorators, and when to use each (p. 66)
  • ​The decorator design pattern used by one of the most popular Python frameworks in the world... and how to "steal" it for you own code (p. 79)
  • ​Simple keys to creating more complex comprehensions (p. 38)
  • ​A technical deep dive into Python's iteration mechanisms, for those who want to fully master this foundational part of the language (p. 29)
  • ​How to make your objects smoothly interact with Python syntax itself (p. 134)
  • ​A rarely-used Python feature which forms a core pillar of many of Python's most popular libraries (p. 65)
  • ​How to grok Python decorators without blindly "copy, paste, and pray"-ing (p. 67)
  • ​The two different interfaces for logging that Python provides, and when to use each (p. 159)
  • ​Why Python has two different ways to represent an object as a string... and when you want to use each (p. 87)
  • ​When to NOT use a generator expression (p. 45)
  • ​The easiest way to make your classes work inside a "for" loop (p. 30)
  • ​The remarkably powerful way to use min(), max() and sorted() to cleanly express many powerful algorithms (p. 61)
  • ​The two completely different ways to use *args and **kwargs, and how to avoid the problems which come from confusing them (p. 54)
  • ​How to "future-proof" your decorators so they continue to work with code written years or even decades later (p. 69)
  • ​The 3 key differences between "10X" coders and normal coders (and which does not actually have anything to do with code) (p. 6)
  • ​Time-saving wisdom for making your class instances comparable to each other (p. 137)
  • ​The surprising cognitive benefit of list comprehensions, that streamlines your reasoning about all your code which uses them (p. 34)
  • ​Python's magic weapon for creating highly scalable iterators (p. 14)
  • ​A fun technique wrapping frighteningly complex code into an easy-to-reuse interface (p. 66)
  • ​How to chain generators together in a way that avoids common bugs (p. 25-26)
  • ​When you should NOT do test-driven development (p. 158)
  • ​How to create a reputation that makes people want to bring you onto their team (p. 6)
  • ​Why Python has two completely different systems for logging... and how to NOT choose the wrong one for your app (p. 166)
  • ​How to reduce git merge conflicts for Python code (p. 37)
  • ​How to LOWER your mental effort and "concentration cost" when working with Python collections (p. 34)
  • ​Unraveling the mystery of Pythonic iteration (p. 11)
  • ​A simple 5-line function that demonstrates important best practices for modern Python programming (p. 19)
  • ​Time-saving best practices for setting up a virtual environment (p. 175)
  • ​The common coding flaw that can make your program so sluggish, everyone using it will think you are a terrible programmer (p. 13)
  • ​How to write your unit tests differently when working in a branch in version control (p. 148)
  • ​Making your code automatically choose the right class to use at runtime (p. 124)
  • ​How to consistently recreate the execution environment of your Python program on different machines, dodging bugs in the process (p. 177)
  • ​How to use generator functions to create internal data pipelines (p. 21)
  • ​The 1970s concept that _almost_ replaced functions as we know them in modern programming languages... and how it is a key part of Python today (p. 16)
  • ​The rarely-used core Python pattern which makes data classes possible (p. 88)
  • ​The critical first step you MUST do 100% of the time when creating a new unit test... and why missing it can create a dangerous disaster (p. 148)
  • ​How to sneak around Python's "only one constructor" rule (p. 119)
  • ​The hidden land mine that will destroy the value of your generator functions - and how to avoid it (p. 18)
  • ​An almost-magical way to make several functions and methods communicate with each other (p. 71)
  • ​The two completely different meanings of "log levels", and how to avoid confusing them (p. 161)
  • ​When to write "optimistic" dictionary code, and when to use more careful, tentative code instead (p. 99)
  • ​How to activate an accelerated cognitive state that allows you to maintain your mental focus, and produce quality code faster (p. 158)
  • ​A dangerous "trap" for Java programmers learning Python, and how to not let it derail your progress (p. 66)
  • ​Making your objects use square brackets like dictionaries do (p. 142)
  • ​The one method of Python file objects you must NEVER use (p. 20)
  • ​The "scalability pattern" baked deep into numerous corners of Python itself... and how to leverage it more completely, successfully, and beneficially in your own code (p. 26-27)
  • ​What Python's testing tools have in common with other languages (p. 145)
  • ​The uniquely Pythonic design principle called Scalable Composibility (p. 21)
  • ​An addictively useful technique for instantiating your classes that you will never want to stop using (pp. 121-122)
  • ​How you can rebelliously mis-use "magic methods" to make incredible Python code (p. 140)
  • ​An uncommon insight into how Pandas' DataFrame class words (p. 140)
  • ​The baffling vocabulary crime almost every blog post about Python generators commits (p. 19)
  • ​The "catch and re-raise" method of making your program provide critically valuable debugging information before it crashes (p. 105)
  • ​A little-known way to protect your member variables from being assigned the "wrong" value, making certain bugs completely impossible (p. 116)
  • ​Why using Python lists in the wrong way can shove your performance off a cliff (p. 13)
  • ​The simple trick for learning lower-level details of a new Python feature fast, so you can focus on the higher-level patterns of applying it (p. 9)
  • ​The outrageously readable and maintainable way to create lists and other data structures in Python (p. 34)
  • ​Key principles for writing Python code that operates on other Python code (p. 80)
  • ​The key skill separating average developers from the very best in the world (p. 143)
  • ​Time-saving shortcut when working with collections of dicts or objects (p. 62)
  • ​The 4 most important exception types in Python, that you absolutely want to re-use in your own code (p. 103)
  • ​Understanding the most mysterious part of Pandas' DataFrames (p. 141)
  • ​An enlightening demonstration of how to combine OOP with functional programming in Python (p. 133)
  • ​Why unit testing is NOT the same as test-driven development (p. 144)
  • ​Python-only extensions to the time-tested Observer pattern (p. 133)
  • ​The "superpower skill" 10X coders use daily (p. 143)
  • ​How to use "sentinel values" to fully avoid tripping your algorithms over unexpected input data... easily sidestepping the near-insurmountable bugs that would otherwise follow (p. 29)
  • ​The #1 mistake people make when writing decorators for methods (pp. 69-70)
  • ​The 3 core tenets of becoming an exceptional Pythonista (p. 6)
  • ​How Pandas deliberately "violates" the rules of Python objects, and how you can do the same to supercharge your own code (p. 143)
  • ​The "test accelerator" technique for ratcheting up your code quality (p. 149)
  • ​A special technique to combine version control with unit tests to almost-effortlessly ratchet up your code quality (p. 149)
  • ​The #1 fast benefit of writing automated tests (it is NOT about the code) (p. 144)
  • ​The one Python topic that applies to EVERY program you write (p. 9)
  • ​The most diabolical Python anti-pattern (p. 107)
  • ​The 3 primary benefits of using virtual environments (p. 174)
  • ​The 3 architectures for generator-based data processing pipelines, and when to use each (pp. 22-23)
  • ​The two primary benefits of logging in Python applications (p. 159)
  • ​What makes Python the most important programming language in history (p. 6)

Detailed Table of Contents

1 Doing More with Python

2 Scaling With Generators
2.1 Iteration in Python
2.2 Generator Functions
2.3 Generator Patterns and Scalable Composability
2.4 Python is Filled With Iterators
2.5 The Iterator Protocol

3 Creating Collections with Comprehensions
3.1 List Comprehensions
3.2 Formatting For Readability (And More)
3.3 Multiple Sources and Filters
3.4 Comprehensions and Generators
3.5 Dictionaries, Sets, and Tuples
3.6 Limits of Comprehensions

4 Advanced Functions
4.1 Accepting & Passing Variable Arguments
4.2 Functions As Objects
4.3 Key Functions in Python

5 Decorators
5.1 The Basic Decorator
5.2 Data In Decorators
5.3 Decorators That Take Arguments
5.4 Class-based Decorators
5.5 Decorators For Classes
5.6 Preserving the Wrapped Function

6 Exceptions and Errors
6.1 The Basic Idea
6.2 Exceptions Are Objects
6.3 Raising Exceptions
6.4 Catching And Re-raising
6.5 The Most Diabolical Python Anti-Pattern

7 Classes and Objects: Beyond The Basics
7.1 Properties
7.2 The Factory Patterns
7.3 The Observer Pattern
7.4 Magic Methods
7.5 Rebelliously Misusing Magic Methods

8 Automated Testing and TDD
8.1 What is Test-Driven Development?
8.2 Unit Tests And Simple Assertions
8.3 Fixtures And Common Test Setup
8.4 Asserting Exceptions
8.5 Using Subtests
8.6 Final thoughts

9 Logging in Python
9.1 The Basic Interface
9.2 Configuring The Basic Interface
9.3 Passing Arguments
9.4 Beyond Basic: Loggers
9.5 Log Destinations: Handlers and Streams
9.6 Logging to Multiple Destinations
9.7 Record Layout with Formatters

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What Pythonistas Say About Powerful Python

"I just wanted to let you know what an excellent book this is. I'm a self taught developer and after having done badly at some interviews I decided to buy your book. It covers so many of the interview questions I'd got wrong previously... I keep going back to your book to learn Python. I've actually recommended it as an interview guide to some of my friends."

- Fahad Qazi, London, UK
"Instant productivity gains. These are the best 200 pages you will find on Python if you're an experienced programmer looking to make a leap in your Python skills. The entire book takes only a few days to read, and it's very enjoyable. I'm already seeing the rewards in my code as I have shifted from writing simple scripts with 1-2 normal functions to writing a unit-tested class which creates its own decorated functions at runtime (data-driven), overloads operators, and properly handles and throws exceptions. Nowhere else have I found so many of Python's unique features explained so clearly and succinctly as I have in Powerful Python."

- Carolyn R., USA
"This book is a must have and must read for every Python developer."

- Jorge Carlos, Italy
"A lot of advanced and useful Python features condensed in a single book."

- Giampaolo Mancini, Italy
"Thanks. Keep up the good work. Your chapter on decorators is the best I have seen on that topic."

- Leon Tietz, Minnesota, USA
"It's direct. Goes right for a couple of subjects that have real-world relevance."

- Chuck Staples, Maine, USA
"What have I found good and valuable about the book so far? Everything honestly. The clear explanations, solid code examples have really helped me advance as a Python coder. Thank you! It has really helped me grasp some advanced concepts that I felt were beyond my abilities"

- Nick S., Colorado, USA
"Only a couple chapters in so far but already loving the book. Generators are a game changer."

- Ben Randerson, Aberdeen, UK
"I'm finding your book very insightful and useful... I have greatly benefitted from your rich examples and your extremely clear explanations. Yours is one of the few books I keep on my desk."

- Tony Holdroyd, Gravesend, UK
"Thank you for your book. It is packed with great information, and even better that information is presented in an easy to understand manner... Five stars."

- Jon Macpherson, Pennsylvania, USA
"Your book is absolutely amazing and your ability to articulate clear explanations for advanced concepts is unlike any I have ever seen in any programming book. Thanks again for writing such a good and thought provoking book."

- Armando Someillan
"Great Python book. One of my favorite Python books that show great examples on using the language effectively."

- Bryant Biggs
"This is among the best books available for taking your Python skills to the next level. I have read many books on Python programming in a quest to find intermediate level instruction. I feel there are very few books which offer the sort of insights needed to really improve skills. This is one of the few I can highly recommend for those who are struggling to achieve intermediate skill in Python. The author clearly has a mastery of the topic and has an ability to convey it in and understandable way."

- Darrell Fee, USA
"Just what I needed. I think it was pretty excellent. Very much applicable to where I'm at with Python today and taking my coding to the next level... I think you have definitely given me some broad ideas on being able to scale, and some things that I should strive for in my code."

- Josiah Allen, USA
"This book taught me a great deal and was enjoyable to read. The complex patterns are explained well with enough detail to understand but not too much to confuse the reader. After having the book for one day I recommended it to my team and will make it required reading for our interns and junior devs."

- Aaron, USA
"Great coverage not offered in other books."

- Tony, USA
"Amazing work! I wish all technical books could be this good."

- Adam Breindel, California, USA
"Truly next-level Python. Concise to the point and practical. Will take your Python to the next level."

- Amado, USA
"I think it's a pretty fine book."

- Chip Warden, Missouri, USA
"A very useful book."

- Jorge Carlos Franco
"Great book. A lot of great tips for those beyond a beginner."

- Jeff Schafer
"Awesome book, helpful in moving beyond basic coding."

- Mark Vallarino
"I've been programming with Python for about 1.5 years and this book is right up my alley. A great attribute of this book are the practical examples. The author describes things in great detail so implementing his ideas is very natural."

- Mike Shumko, USA
"This book has a lot of useful examples and gives some great tips on how to refine your Python skills and bring your coding to the next level. If you want to move from beginner Python and go to intermediate/advanced topics, this book is perfect for you."

- Gary Colello, USA
"Takes your Python coding skills from average to awesome... This book makes quick work of some advanced and esoteric topics. If you want to be a Python programmer a cut above everyone else, and ace the tough topics in interviews, this is the one for you."

- Hugh Reader, USA
"Five Stars. I've studied this deeply, this author has been a big contributor to my lifetime development in software engineering."

- Ref, USA
"Looking to go beyond the basics, to broaden and deepen your Python skills? This is the book for you. Highly recommended!"

- Michael Herman, USA
"There are very few books that can bridge the gap between basics and advanced level and this is one of them."

- Rodrigo Albuquerque, UK
"This is really good for intermediate Python programmers, who have mastered the basics and are looking for new ideas on various new modules and features out in Python. Also the author explains few gotchas and secrets from the woods to make you a sound Python pro."

- Andrew, UK
"Excellent book. I found the explanation of some complex topics very easy to understand. An example of this are the chapters on decorators and testing. I would recommend this book to anybody who already knows Python and wants to take it to the next level... The author shares a lot of best practices used in the real world which I’ve noticed that a lot of books leave out."

- Raul, Canada
"Great book, Python finally explained in an advanced and in-depth way..."

- Alex, Italy
"This is really good book."

-  Marcin Adamowicz, UK
"Powerful Python is already helping me get huge optimization gains."

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"Warmly recommended to all Pythonists."

- Giovanni, UK
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