BlackBelt
Advice on Deployment, Scalability, Testing, and More
by Julien Danjou
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Book Details
Price
|
4.00 |
|---|---|
Pages
| 261 p |
File Size
|
8,208 KB |
File Type
|
PDF format |
ISBN-10 ISBN-13
| 1593278780 9781593278786 |
Copyright©
| 2019 by Julien Danjou |
Julien Danjou is a principal software engineer at Red Hat and a contributor to
OpenStack, the largest existing open source project written in Python. He has been a
free software and open source hacker for the past 15 years.
Introduction
If you’re reading this, the odds are good you’ve been working with Python for some
time already. Maybe you learned it using some tutorials, delved into some existing
programs, or started from scratch. Whatever the case, you’ve hacked your way into
learning it. That’s exactly how I got familiar with Python up until I started working on
big open source projects 10 years ago.
It is easy to think that you know and understand Python once you’ve written your first
program. The language is that simple to grasp. However, it takes years to master it and
to develop a deep comprehension of its advantages and shortcomings.
When I started Python, I built my own Python libraries and applications on a “garage
project” scale. Things changed once I started working with hundreds of developers on
software that thousands of users rely on. For example, the OpenStack platform—a
project I contribute to—represents over 9 million lines of Python code, which
collectively needs to be concise, efficient, and scalable to the needs of whatever cloud
computing application its users require. When you have a project of this size, things like
testing and documentation absolutely require automation, or else they won’t get done at all.
I thought I knew a lot about Python before working on projects of this scale—a scale I
could hardly imagine when I started out—but I’ve learned a lot more. I’ve also had the
opportunity to meet some of the best Python hackers in the industry and learn from
them. They’ve taught me everything from general architecture and design principles to
various helpful tips and tricks.
Through this book, I hope to share the most important
things I’ve learned so that you can build better Python programs—and build them more efficiently, too!
The first version of this book, The Hacker’s Guide to Python, came out in 2014. Now
Serious Python is the fourth edition, with updated and entirely new contents. I hope
you enjoy it!
ABOUT THIS BOOK
This book is not necessarily designed to be read from front to back. You should feel free
to skip to sections that interest you or are relevant to your work. Throughout the book,
you’ll find a wide range of advice and practical tips. Here’s a quick breakdown of what
each chapter contains.
Chapter 1 provides guidance about what to consider before you undertake a project,
with advice on structuring your project, numbering versions, setting up automated
error checking, and more. At the end there’s an interview with Joshua Harlow.
Chapter 2 introduces Python modules, libraries, and frameworks and talks a little
about how they work under the hood. You’ll find guidance on using the sys module,
getting more from the pip package manager, choosing the best framework for you, and
using standard and external libraries. There’s also an interview with Doug Hellmann.
Chapter 3 gives advice on documenting your projects and managing your APIs as your
project evolves even after publication. You’ll get specific guidance on using Sphinx to
automate certain documentation tasks.
Here you’ll find an interview with Christophe de Vienne.
Chapter 4 covers the ageold issue of time zones and how best to handle them in your
programs using datetime objects and tzinfo objects.
Chapter 5 helps you get your software to users with guidance on distribution. You’ll
learn about packaging, distributions standards, the distutils and setuptools libraries, and
how to easily discover dynamic features in a package using entry points. Nick Coghlan is interviewed.
Chapter 6 advises you on unit testing with bestpractice tips and specific tutorials on
automating unit tests with pytest. You’ll also look at using virtual environments to
increase the isolation of your tests. The interview is with Robert Collins.
Chapter 7 digs into methods and decorators. This is a look at using Python for
functional programming, with advice on how and when to use decorators and how to
create decorators for decorators. We’ll also dig into static, class, and abstract methods
and how to mix the three for a more robust program.
Chapter 8 shows you more functional programming tricks you can implement in
Python. This chapter discusses generators, list comprehensions, functional functions
and common tools for implementing them, and the useful functools library.
Chapter 9 peeks under the hood of the language itself and discusses the abstract
syntax tree (AST) that is the inner structure of Python. We’ll also look at extending
flake8 to work with the AST to introduce more sophisticated automatic checks into your
programs. The chapter concludes with an interview with Paul Tagliamonte.
Chapter 10 is a guide to optimizing performance by using appropriate data structures,
defining functions efficiently, and applying dynamic performance analysis to identify
bottlenecks in your code. We’ll also touch on memoization and reducing waste in data
copies. You’ll find an interview with Victor Stinner.
Chapter 11 tackles the difficult subject of multithreading, including how and when to
use multithreading as opposed to multiprocessing and whether to use eventoriented or serviceoriented architecture to create scalable programs.
Chapter 12 covers relational databases. We’ll take a look at how they work and how to
use PostgreSQL to effectively manage and stream data. Dimitri Fontaine is interviewed.
Finally, Chapter 13 offers sound advice on a range of topics: making your code
compatible with both Python 2 and 3, creating functional Lisplike code, using context
managers, and reducing repetition with the attr library.
WHO SHOULD READ THIS
BOOK AND WHY
This book is intended for Python coders and developers who want to take their Python
skills to the next level.
In it, you’ll find methods and advice that will help you get the most out of Python and
build futureproof programs. If you’re already working on a project, you’ll be able to
apply the techniques discussed right away to improve your current code. If you’re
starting your first project, you’ll be able to create a blueprint with the best practice.
I’ll introduce you to some Python internals to give you a better understanding of how to
write efficient code. You will gain a greater insight into the inner workings of the
language that will help you understand problems or inefficiencies.
The book also provides applicable battletested
solutions to problems such as testing,
porting, and scaling Python code, applications, and libraries. This will help you avoid
making the mistakes that others have made and discover strategies that will help you
maintain your software in the long run.
Bookscreen
SUMMARY
Congratulations! You made it to the end of the book. You’ve just upped your Python
game and have a better idea of how to write efficient and productive Python code. I
hope you enjoyed reading this book as much as I enjoyed writing it.
Python is a wonderful language and can be used in many different fields, and there are
many more areas of Python that we did not touch on in this book. But every book needs
an ending, right?
I highly recommend profiting from open source projects by reading the available source
code out there and contributing to it. Having your code reviewed and discussed by
other developers is often a great way to learn.
Happy hacking!