About this Book
Version 1.0 released in 2017.
When I released The Hacker’s Guide to Python in 2014, I had no
idea that I would be writing a new book so soon. Having worked on
OpenStack for a few more years, I saw how it is easy to struggle with
other aspects of Python, even after being on board for a while.
Nowadays, even if computers are super-fast, no server is fast
enough to handle millions of request per second, which is a typical
workload we want to use them for. Back in the day, when your
application was slow, you just had to optimize it or upgrade your
hardware – whichever was cheaper. However, in a world where you
may already have done both, you need to be able to scale your
application horizontally, i.e., you have to make it run on multiple
computers in parallel.
That is usually the start of a long journey, filled with concurrency
problems and disaster scenarios.
Developers often dismiss Python when they want to write
performance enhancing, and distributed applications. They tend to
consider the language to be slow and not suited to that task. Sure,
Python is not Erlang, but there’s also no need to ditch it for Go
because of everyone saying it is faster.
I would like to make you aware, dear reader, that a language is
never slow. You would not say that English or French is slow, right?
The same applies for programming languages. The only thing that
can be slow is the implementation of the language – in Python’s
case, its reference implementation is CPython.
Indeed CPython can be quite sluggish, and it has its share of
problems. Every implementation of a programming language has its
downside. However, I think that the ecosystem of Python can make
up for that defect.
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