With a basic knowledge of Python you have the potential to undertake time-saving text processing. This book is a great introduction to the various techniques, and teaches through practical examples and clear explanations. Overview The easiest way to learn text processing with Python Deals with the most important textual data formats you will encounter Learn to use the most popular text processing libraries available for Python Packed with examples to guide you through What you will learn from this book Know the options available for processing text in Python Parse JSON data that is often used as a data delivery mechanism on the Internet Organize a log-processing application via modules and packages to make it more extensible Perform conditional matches via look-ahead and look-behind assertions by using basic regular expressions Process XML and HTML documents in a variety of ways based on the needs of your application Implement callback methods to perform SAX processing and walk in-memory DOM structures Understand Unicode, character encoding, internationalization, and localization Lay out a Mako template-based project by using techniques such as template inheritance, additional tags, and custom filters Install and use the Mako templating system to create your own Mako templates Process a large number of e-mail messages using the Python standard library and index them with Nucular for fast searching Fix common exceptions that occur while dealing with different types of text encoding Build simple PDF output using the ReportLab toolkit’s high-level PLATYPUS framework Generate Microsoft Excel output using the xlwt module Open and edit existing Open Document files to use them as template sources Understand supporting functions and classes, such as the Python IO system and packaging components Approach This book is part of the Beginner’s Guide series. Each chapter covers the steps for various tasks to process data followed
About the Author
Jeff McNeil Jeff McNeil has been working in the Internet Services industry for over 10 years. He cut his teeth during the late 90’s Internet boom and has been developing software for Unix and Unix-flavored systems ever since. Jeff has been a full-time Python developer for the better half of that time and has professional experience with a collection of other languages, including C, Java, and Perl. He takes an interest in systems administration and server automation problems. Jeff recently joined Google and has had the pleasure of working with some very talented individuals.