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Text Processing in Python
As you probably know, there are many good introductory texts about Python. This is not one of them, for this is an advanced book, but not an inaccessible one. David Mertz has a unique style and focus that we have become familiar with from his series of articles on the IBM Developer Network. Dr. Mertz is more interested in facilitating our learning process than in lecturing us, and rather than fill his pages with impressive examples designed to illustrate his expertise, he gently guides us by offering subtle yet important examples of code and analysis that makes us think for ourselves.
He has a special talent for programming in the functional style, and this is a great introduction to that style of Python programming. Thus, this is also a good guide to using the newer features introduced into Python in the last few revisions, which often facilitate the functional style of programming.
The text includes, in an appendix, a 40 page tutorial covering the basic Python language. This tutorial is, like the book, unique in its approach and is worthwhile even for experienced Pythonistas, as it sheds light on some of the underlying ideas behind the syntax and semantics, and it also illustrates the functional style of programming, which is sometimes quite useful when doing text processing. And, despite its many other virtues, this is a book about text processing.
Chapter 1 covers the Python basics, but with a particular eye towards those features most critical and useful for text processing. Chapter 2 covers the basic string operations as found in the string module and the newer built-in string functions. Chapter three is about Regular Expressions, and, although I am shy about regexes because of their relative complexity, I am very glad to have read this chapter and will no longer be intimidated when regexes are the correct approach to take! Chapter 4 is on Parsers and State machines, which are important for processing nested text, as in everyday HTML, XML and the like. This chapter is not as esoteric as its title may sound to relative newbies (like myself), as it does offer useful ideas and principles for dealing with HTML. How much more useful can a topic be than that? It is true that a deep understanding of this subject may be beyond myself and other relative duffers, but this chapter has much to offer those like me and I am sure much more to offer professionals.
Chapter 5 is on Internet tools and techniques, and this a good example of how text processing touches every important area of computer programming. We manipulate text for email, newsgroups, CGI programs, HTML and many other aspects of net programming. A good summary of XML programming is included, as well as useful synopses of other Python internet modules, from a text processing point of view.
Appendix A is the aforementioned selective and short review of Python basics. Appendix B is a ten page Data Compression primer that is quite educational. Appendix C offers the same good service for Unicode, and Appendix D covers the author's own software, a state machine for adding markup to text, which is backed up by his extensive web site that has a lot of free software to support those doing extensive text processing. Lastly, Appendix E is a Glossary for technical terms from the book. This is very much an educational book, and would be suitable for classroom work at the University level, beyond the introductory programming level; in fact, as part of a curriculum to teach programming using Python at the University level, this would be an excellent text for the second course.
One of the highlights of the book is that each chapter is concluded with a problem and discussion section. These are of the highest quality I have encountered in computer texts. Rather than overwhelming the reader with a large number of problems, the author has obviously given a lifetime of thought in coming up with a few key problems that are meant to stimulate thought, creativity, and ultimately understanding and growth in the reader. I will be coming back to the problems often, as they cannot be absorbed quickly anyway; they require thought. These would be most useful in a classroom environment; but as they are accompanied by excellent discussion material, and backed up by the author's web site, the individual reader will be well served also.
The book is more than the sum of its parts. It will be a most useful reference source for when I am doing various text related tasks for some time to come, and it was also a delightful and educational quick read in the here and now. It also amply illustrates the centrality of text processing in all areas of computer science, and I am confident that the book will be useful and educational for all programmers, whatever their area of expertise.
To sum it all up, this book is educational. It is also beautifully bound and printed, and excellently written. I rate it five stars, my highest rating, and heartily recommend its purchase.
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is here, as a series of text files. This is official.
"If you have read an introductory book or two about Python programming, but you are far from being an expert, then you will benefit a lot from reading this book. If you are a competent programmer in any other language, you will benefit from this book. If you are an expert Python programmer, you will also benefit from this book."
If you are a practitioner of voodoo and merely handle large pythons, you will benefit from this book.
If you are a undersea explorer but have heard of pythons....
--
Was it the sheep climbing onto the altar, or the cattle lowing to be slain,
or the Son of God hanging dead and bloodied on a cross that told me this was a world condemned, but loved and bought with blood.
Strangely enough, there seem to be a lot of jobs, at least where I am, where the only major language requirement is Python.
I'm not sure if this is maintaining legacy apps, but it certainly scared me!
I use it for data management, system administration chores and CGI programming.
Python has a nice clean syntax that tends to re-use language constructs, which makes it easy to learn and read. It makes good use of objects and exceptions and it has a solid standard libarary of goodies. And, it has no shortage of additional modules to use. Plus, the whole of it is highly malleable.
It's not the fastest language out there, some don't like its whitespace-based syntax and it doesn't have the breadth of pre-built modules as older languages like Perl have.
It is if you have problems to solve and don't particularly care for the tools you're using now.
Ita erat quando hic adveni.
yeah, this is a good book. also it's released under the GNU Free Documentation License and is available to download in various formats here.
I'm not sure if this is maintaining legacy apps, but it certainly scared me!
:-).
;-).
;-).
Python jobs are hardly for legacy app maintenance. More like rapid development of cutting edge stuff, prototyping, exploring, enterprise application integration... and Agile development in general. I introduced Python to my previous workplace, and after the guys there learned it, they didn't switch back (even though their chief python advocate/fascist, i.e. your truly, left
Python can be used for very large problems (hundreds of modules, and much more classes), in addition to trivial scripts (0 functions). It is *fun* as hell. Python programmer is always an architect, there is very little monkey-level "grunt work", which tends to form most of your day-to-day C++/Java programming.
You really have no clue about OOP before you have tried one of the dynamic OOP languages: Python, Smalltalk, or Ruby. Smalltalk has fallen to a legacy role these days, while Ruby is much less mature and has a smaller community than Python. Additionally, Ruby is less "tasteful", in that it borrows more heavily from perl, but that is a matter of controversy
Additionally, Python is an embodiment of Open Source, because the code is actually readable and concise enough to lower the barrier of reading it. In fact I have taken a look at the source code of several Open Source projects that use Python "just for kicks", while I hardly bother in case of e.g. C programs. One line of Python is equivalent of 10-20 lines of C++, so you can digest more with the typical geek attention span (i.e. borderline ADD
Save your wrists today - switch to Dvorak
What do Slashdotters use python for?
:-). In the wider term that is. A Software Agent for scanning and retrieving certain information from different Inet Sources - a very serial process that's hard to 'objectivise'. Python did/does a great job at keeping things overseeable.
:-) (www.zope.org)
Software Agents / Content Syndication 'bots
Web/Internet Application Server (Zope)
3D (me: Blender, ILM for Maya and others)
I've used Python on various things one of the more abitious being, well, actually Text Processing
Zope is the other area I use Python in. Zope I consider the most sophsticated Application Server avaiable. It's GPLd of course
Just as with me Python is very popular within the 3D Field. ILM use it as their prime scripting language and I like Blenders built in Python controlled/based realtime engine.
What are its strengths and its weaknesses?
Shurely it's tab-based delimiting of blocks ('whitespace syntax') is a big feature. I can be shure to be able to read *any* code from anybody who did it in Python instantly. Think of how teamwork improves (especially in extreme programming) when bad indentation means your code is broken!
Python is completely GPLd, which means a lot to me and overall futuresafety of a PL. That's why I don't feel so good about Java (allthough I like it too in a way)
Python is very easy to learn. "Perl is executable line noise, Python is executable pseudocode" actually sums that one up.
The only *weakness* that comes to mind is that it's a younger language. But it's catching up rapidly in terms of breadth and width of the 'lib' availability - also due to Python being completely GPLd!
Why is it worth learning another programming language?
It's actually one of the most modern and sophisticated. I realizes what developers theorized as ideal some 20 years ago.
The obligatory famous quote:
|||We will perhaps eventually be writing only small modules which are identified by name as they are used to build larger ones, so that devices like indentation, rather than delimiters, might become feasible for expressing local structure in the source language
- Donald E. Knuth,1974|||
Oh, and, yet again, it's GPLd all the way through. Want a better PL? Use Python.
We suffer more in our imagination than in reality. - Seneca