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The Zen Of Python. 

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
In the face of ambiguity, refuse the temptation to guess.
There should be one-- and preferably only one --obvious way to do it.
Although that way may not be obvious at first unless you're Dutch.
Now is better than never.
Although never is often better than *right* now.
If the implementation is hard to explain, it's a bad idea.
If the implementation is easy to explain, it may be a good idea.
Namespaces are one honking great idea -- let's do more of those!

--Tim Peters

Why Read This Book?

You need this book because you need to learn Python. There are lots of reasons why you need to learn Python. Here are a few.

  • You need a programming language which is easy to read and has a vast library of modules focused on solving the problems you're faced with.

  • You saw an article about Python specifically, or dynamic languages in general, and want to learn more.

  • You're starting a project where Python will be used or is in use.

  • A colleague has suggested that you look into Python.

  • You've run across a Python code sample on the web and need to learn more.

Python reflects a number of growing trends in software development, putting it at or near the leading edge of good programming languages. It is a very simple language surrounded by a vast library of add-on modules. It is an open source project, supported by many individuals. It is an object-oriented language, binding data and processing into class definitions. It is a platform-independent, scripted language, with complete access to operating system API's. It supports integration of complex solutions from pre-built components. It is a dynamic language, which avoids many of the complexities and overheads of compiled languages.

This book is a complete presentation of the Python language. It is oriented toward learning, which involves accumulating many closely intertwined concepts. In our experience teaching, coaching and doing programming, there is an upper limit on the “clue absorption rate”. In order to keep within this limit, we've found that it helps to present a language as ever-expanding layers. We'll lead you from a very tiny, easy to understand subset of statements to the entire Python language and all of the built-in data structures. We've also found that doing a number of exercises helps internalize each language concept.

Three Faces of a Language. There are three facets to a programming language: how you write it, what it means, and the additional practical considerations that make a program useful. While many books cover the syntax and semantics of Python, in this book we'll also cover the pragmatic considerations. Our core objective is to build enough language skills that good object-oriented design will be an easy next step.

The syntax of a language is often covered in the language reference manuals. In the case of relatively simple languages, like Python, the syntax is simple, and is covered in the Python Language tutorial that is part of the basic installation kit. We'll provide additional examples of language syntax. For people new to programming, we'll provide additional tips focused on the newbie.

The semantics of the language can be a bit more slippery than the syntax. Some languages involve obscure or unique concepts that make it difficult to see what a statement really means. In the case of languages like Python, which have extensive additional libraries, the burden is doubled. First, one has to learn the language, then one has to learn the libraries. The number of open source packages made available by the Python community can increase the effort required to understand an entire architecture. The reward, however, is high-quality software based on high-quality components, with a minimum of development and integration effort.

Many languages offer a number of tools that can accomplish the same basic task. Python is no exception. It is often difficult to know which of many alternatives performs better or is easier to adapt. We'll try to focus on showing the most helpful approach, emphasizing techniques that apply for larger development efforts. We'll try to avoid quick and dirty solutions that are only appropriate when learning the language.

  Published under the terms of the Open Publication License Design by Interspire