Customer Reviews

Text Processing in Python

5 star:		(11)
4 star:		(4)
3 star:		(1)
2 star:		(2)
1 star:		(0)

 

 

Text Processing in Python, by David Mertz, 2003, Addison Wesley, 520 pages.

If you have read an introductory book or two about 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.

For, as you 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 "Charming Python" 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.

Ron Stephens

Yes, I mean it: this is a beautiful book. If your aesthetic sensibilities have been informed, directly or indirectly, by Kernighan and Ritchie's influential book on C, you'll know what I mean.

I've been programming computers in various capacities since I was in my early teens (the mid-1970s) and I've been through a number of languages. Not long ago I discovered Python, and I suspect I won't need to learn any other languages for quite a long time. Guido van Rossum is a wizard.

If you're interested in learning Python, don't start here. If you've got some programming background already, Guido's tutorial (which comes bundled with the Python download) will be enough to get you rolling. I personally recommend all of O'Reilly's books on the subject (_Learning Python_ for the absolute beginner, Mark Lutz's idiosyncratic but highly useful _Programming Python_ for the next level up, the magisterial _Python Cookbook_ for pretty much anybody, and the _Nutshell_ book to be placed permanently next to your keyboard). There are others as well, and after you've gotten started, you'll be a better judge than I am of what will be most useful to you. (But I'd skip the vastly overpriced and not-very-deep _Python Programming Patterns_ unless you can buy it used.)

This one's for later; although it does offer some beginning instruction in Python, it isn't really an introductory book. However, if you do any text processing with Python -- which you almost undoubtedly do if you use Python at all -- then you _do_ want this book even if you don't know it yet.

Most of what you'll want to know is in chapter two, which sets out the basics of string processing in Python. The other, fancier stuff in the later chapters may be handy sometimes, but author David Mertz himself will tell you not to overcomplicate things; if you can do what you need to do using string operations, do so.

Read the rest of it too, though. There's good stuff here on e.g. regular expressions and parsing that you'll find interesting and possibly useful. Just don't rush out and start trying to apply it when it isn't necessary.

Mertz is an excellent teacher. He tends to approach things from a foundation of "functional programming" -- of which I'm not particularly a fan, but he has a healthy sense of its limitations and his comments on the subject are refreshing. (If you're interested in functional programming, get a book on Haskell, which is actually a very cool language. But me, I like imperative languages just fine and I don't have any problem with "side effects" as long as they're deliberate or at least controlled.) At any rate, Mertz won't lock you in to a functional approach, but he will teach you some function-oriented stuff that will be useful to you no matter what your preferred programming style.

And his exposition is well organized and wonderfully lucid. If you're the sort of person who likes books that have a chapter zero, you'll enjoy his style.

Unless you have a strong programming background, then, you probably won't want to start your Python bookshelf with this one. But I recommend making it one of your first five.

This is the only book that really attacks the issue of string processing using Python. Unfortunately it didn't attack the text processing problems that I wanted discussed.

Also, in the area of Regular Expressions the examples didn't directly use the Python library, instead a wrap around function was used for the many examples and that detracted from using the book as a reference book for this purpose.

I found that Python has several different ways to do string processing. Also, some of those ways come up with conflicting results. At the time of this writing the authors of Python are re-organizing and improving this area.

What is truly great about the book is the discussion of state machines, parsers, and functional programming. Although these topics detract from the focus on string processing somewhat this book is perhaps the only popular Python book out there that does these topics justice. I thought they were very well written.

My overall complaint is that this book includes too many things outside of text processing using the core Python language. But other readers may appreciate this aspect more than I did. If you want coverage on handling email specifically, the author covers that. Same with HTML processing and other specialized topics. I just wanted to low down on using the full string processing capabilities of the core Python language -- not necessarily all the specialized libraries.

I found string processing to be messy with Python but found Ruby to be much easier. That is perhaps because Ruby is a newer language and it has some features of Perl built in. Ruby however does not have the extent of libraries available like Python, nor does it have as nice of Windows GUI.

Overall, if you are looking for a book on text processing this is the only book out there, and a big plus with this book is what you will learn on function programming, state machines and parsers.

The author worked hard to produce a book in this specialized area. He has lots of code examples. Highly recommended for Python programmers.

John Dunbar
Sugar Land, TX

Added note: The review by phrodod was quite nice, IMO. One little thing: s/he mentions my little re_show() utility that I use in the regex tutorial. While phrodod grants leniency in allowing that it is fine if the utility is not of use beyond the examples... my little wrapper proves better than that even. Specifically, the rather nice Python library PEAK chose to incorporate the exact 3-line utility function (with acknowledgments to me) to help user explore regexen. PEAK, of course, is vastly more interesting than my miniscule and accidental contribution to it :-).
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I felt the review from "A reader from Germany" below rather missed the point of my book. Don't buy it if the book is not right for you, most certainly. But I wonder how that reader got such an entirely inaccurate set of expectations about the book.

For example, s/he wrote:

> This book is not for people that are new to programming.

However, if you buy the book from Amazon (here), the very first thing you see in the Editorial Reviews section is:

> Written for experienced programmers...

So it seems odd for the above reader to be negatively surprised by the target audience. If s/he bought it at a brick-and-morter store, the back cover pretty much says the same thing.

Moreover, the reader mentioned also seems not to understand the meaning of the title:

> The title of the book is very much missleading too.
> If you think that the book has anything to do with
> text processing in the sense of linguistics, you are
> mistaken.

I'm not sure how anyone would think that the phrase "text processing" is supposed to mean "computational linguistics." There are a couple overlaps between the fields. And you probably need a bit of text processing to extract useful corpora for computational linguistics. But the ordinary meaning of the words makes it clear that these are quite different areas of specialty. Actually, I just wrote an IBM developerWorks article introducing the Natural Language Toolkit (for Python). Anyone who is interested in computational linguistics and Python should take a look at that library.

I wonder if the "from Germany" description of the reader indicates the s/he translated the English title slightly wrongly. I can kinda imagine that across languages the field distinction could get lost.

And finally:

> ...really mad to find out that the book is available online too.

This one rather upsets me. I provide a service for readers--both those who pay for the printed copy and those who read it online for free (or make a voluntary donation online). The reader is *mad* that I give away something for free that I was under no obligation to (and even wrestled slightly with my publisher to make sure I could do so)!? If s/he doesn't want the free copy, I don't see how s/he's forced to download it!

This book covers many of the details of processing text files to extract and/or generate more textual information from them. The author covers quite a number of advanced techniques, starting with an introduction to functional programming paradigms in the first few pages.

Nothing in this book is truly new, but the author finds many ways of applying the things advanced Pythonistas already know to domains that they might otherwise not consider.

This book is very dense, so don't expect to read it and get it in a weekend. And certainly, don't pick this up as a first programming in Python book. If you're just learning to program, consider "Learning Python" by Lutz or "How to Think Like a Computer Scientist" (free web book -- search Google for it). If you already know programming, but need to learn Python, consider the Quick Python Book (old, but great) or "Dive into Python" (another free web book) for learning those.

When the time comes that you want to write a small language of your own for your users (or when you need to support an existing small language), this book will be invaluable for telling you how to do this using Python.

If you don't understand functional programming, but think you might like to learn it, use this book to teach you that.

If you want to understand the regular expression library, use this book for that as well. However, the RE library examples do wrap the output in a special macro that's only likely to be useful for the purposes of the book. Understand that you're not likely to use the macro, and you'll be fine.

The tremendous breadth and depth of this book makes me recommend it highly. But even if you're advanced, don't expect it to be light reading.

Enjoy.

There is a lot of good stuff in this book, but the presentation is lousy.

The first chapter dives into functional programming using obscure and terse high order functions including nested lambda expressions. He never does provide a "mere mortal" explanation for how these functions work. I was able to figure it out, but then I've been programming for 35 years in 20+ languages.

As a learning experience it was valuable debugging exercise for me, but as something for a programmer who was just getting to know Python, I can't think of a greater turn off.

Python as a rule is easy to read and easy to write. This book manages to make it unnecessarily hard.

Start with another Python book (or two, or three) then come back to this one when you have a lot of time and patience to spend. As I said there *is* some worthwhile information in there.

In any booksotre you'd probably find hundreds of titles of "Web programming in XXX language". What about "Text processing in XXX language"? From Amazon's similar items the only book that remotely resemble this is the "Python & XML". This is indeed a unique title.

Why do we care about text processing? The author said it is arguably what most programmer spend most time doing. Text is the basis of most Internet communications protocol. Most computer "data" often comes down to "text. And Python is a powerful language for this task.

What can you find in this book?

Advanced Python programming technique
Python is a simple language on the surface. As an expert programmer the author really show you great techniques in solving actual problems. This is in contrast to most other Python books that cover only the language basis. It is also one of a few book that covers functional programming style. The other book that you maybe interested in is the "Python Cookbook".

Algorithms
You'll find a number of useful algorithm here and there. There is only some brief introduction to computer language theory. On the other hand some third party parser tools are well covered.

Internet protocols and data format
Several standard Python modules as well as useful third party tools for handling Internet protocols and data format is introduced. (But not much about the protocol themselves).

There are places where author would jump into detail without giving enough introduction. In p.5 a number of higher-order functions are defined without explanation. The "smart ASCII" format is used to illustrate several different progamming tools but the format itself is never defined. What could be very interesting topics instead leave readers bewildered.

I find this book a bag of tricks where author's experience and opinion are most valuable. Despite some short coming this is one advanced book that help improve your progamming technique to a higher level.

David takes a fresh take on programming and esp. programming with python. He combines OO and functional styles to create programs that are shorter and easier to understand. In addition to providing documentation and examples of python modules related to text processing, David says just as much about good programming style. He shows how OO programming is more than just about smart data, i.e. it is more about what services objects provide, that your coding style should test for services the object provides rather than trying to find out what it is. David also addresses issues specific to Perl/Python like Schwartzian sort, which should greatly help if sorting is the bottleneck in your code. I must confess I have not read the state machine stuff yet as I am thoroughly enjoying all the other stuff little by little. If you are a professional Python programmer you should definitely get this book.

This book is not for everyone, but for "text processing", I know of nothing else that comes close; this book merits careful study. Note that "text processing" would include many web applications -- http is a text driven protocol. Do not be put off by the first chapter! It is the most abstract of any book I have read in decades. As the book says, you can skip it if it is a problem for you. As an illustration of how good this book is, I am now using regular expressions (selectively), and this was only possible with the help if this book! (If you do not even know what regular expressions are, you have not completed Text Processing 1.01.)

Confessedly, writing this little note was inspired by an article on authors who pseudonymously or anonymously review their own books. I find that a bit dishonest, so you should see my name here.

Maybe this is a quibble, but I found the review by jluc_ from Vancouver, BC Canada to miss one point. S/he has some criticisms of the organization and focus that I won't argue with (obviously, my own take is different). But there is also a remark that:

"For example, he uses smart ASCII formatting examples several times. Does he _clearly_ define that format somewhere? Nope, the reader is assumed to magically know/guess its syntax, though several entries for "smart ASCII" in the index will first lead him to believe a definition does exist in the book."

It is quite true--and quite deliberate--that I omit any formal description of smart ASCII from the book. For a real world example of the format, you can look at the online version of the whole book itself at [http://gnosis.cx/TPiP/], which is in this format. But there is no official grammar of the markup (though the parser chapters do this partially, as a way of explaining parsers, not the format.

In my real work experience, text formats I encounter are RARELY completely and accurately documented. Rather, the tools I have written in my life have treated formats in a heuristic and seat-of-the-pants way, typically based only on some examples of a format. In using the smart ASCII format for various examples, I want to put readers in a mind to exactly this sort of real-world experience. Don't sweat the lack of formal documentation, just get to work with the programming!