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27Aug/111

Python 3 Web Development Review

Python 3 Web DevelopmentThe problem with Python 3 Web Development Beginner's Guide, by Michel Anders, is one of expectations (disclaimer: I received a free eBook from Packt for review). Let's start with the title... First we have Python 3 Web Development. This immediately sets the wrong expectations because:

  1. There's almost as much jQuery & Javascript as there is Python.
  2. Most of the Python code is not Python 3 specific, and the code that is could easily be translate to Python 2.
  3. Much of the Python code either uses CherryPy or is for generating HTML. This is not immediately obvious, but becomes apparent in Chapter 3 (which is available as a free PDF download: Chapter 3 - Tasklist I Persistence).

Second, this book is also supposed to be a Beginner's Guide, but that is definitely not the case. To really grasp what's going on, you need to already know the basics of HTML, jQuery interaction, and how HTTP works. Chapter 1 is an excellent introduction to HTTP and web application development, but the book as a whole is not beginner material. I think that anything that uses Python metaclasses automatically becomes at least intermediate level, if not expert, and the main thrust of Chapter 7 is refactoring all your straightforward database code to use complicated metaclasses.

However, if you mentally rewrite the title to be "Web Framework Development from scratch using CherryPy and jQuery", then you've got the right idea. The book steps you through web app development with CherryPy, database models with sqlite3, and plenty of HTML and jQuery for interface generation and interaction. While creating example applications, you slowly build up a re-usable framework. It's an interesting approach, but unfortunately it gets muddied up with inline HTML rendering. I never thought a language as simple and elegant as Python could be reduced to the ugliness of common PHP, but generating HTML with string interpolation inside the same functions that are accessing the database gets pretty close. I kept expecting the author to introduce template rendering, which is a major part of most modern web development frameworks, but it never happened, despite the plethora of excellent Python templating libraries.

While reading this book, I often had the recurring thought "I'm so glad I use Django". If your aim is rapid application development, this is not the book for you. However, if you're interested in creating your own web development framework, or would at least like to understand how a framework like Django could be created, then buy a copy Python 3 Web Development.

18Jul/113

Python Testing Cookbook Review

Python Testing CookbookPython Testing Cookbook, by Greg L Turnquist (@gregturn), goes far beyond Unit Testing, but overall it's a mixed bag. Here's a breakdown for each chapter (disclaimer: I received a free eBook from Packt for review):

  1. Basic introduction to testing with unittest, which is great if you're just starting with Python and testing.
  2. Good coverage of nose. I was pleasantly surprised at how easy it is to write nose plugins.
  3. Deep coverage of using doctest and writing testable docstrings. You can download a free PDF of Chapter 3 here.
  4. BDD with a cool nose plugin, and how to use mock or mockito for testing with mock objects. I wish the author had expressed an opinion in favor of either mock or mockito, but he didn't, so I will: use Fudge. Chapter 4 also covers the Lettuce DSL, which I think is pretty neat, but since every step requires writing a function handler, I'm not convinced it's actually easier or better than writing doctests or unit tests.
  5. Acceptance testing with Pyccuracy and Robot Framework, which both give you a way to use Selenium from Python. I thought the DSLs used seemed too "magic", but I that's probably because I didn't know the command words, and they weren't highlighted or adequately explained.
  6. How to install and use Jenkins and TeamCity, and how to display XML reports produced using NoseXUnit. This is a very useful chapter for anyone thinking about or setting up continuous integration.
  7. This chapter is supposed to be about test coverage, and does introduce coverage, but the examples get needlessly complicated. Previous chapters used a simple shopping cart example, but this chapter uses network events, which really distracts from the tests. The author also writes unittests that just print the results intead of actually testing results with assertions.
  8. More network event complexity while trying to demonstrate smoke testing and load testing. This chapter would have made a lot more sense in a book about network programming and how to test network events. Pyro is used with very little explanation, and MySQL and SQLlite are brought in too, increasing the complexity even more.
  9. This chapter is filled with useful advice, but there's no actual code examples. Instead, the advice is shoehorned into the cookbook format, which I felt detracted from the otherwise great content.

Throughout the book, the author presents a kind of "main script" that he updates at the end of many of the chapters. However, the script also contains stub functions that are never touched and barely explained, making their existance completely unnecessary. There's also far too many import *, which can make it difficult to understand the code. But I did learn enough new things that I think Python Testing Cookbook is worth buying and reading. Leaving out Chapters 7 and 8, I think the book is a great resource if you're just getting started with testing, you want to do continuous integration, and/or you want to get non-programmers involved in the testing process. There's also a blog about the book, which has links to other reviews.

4Jul/110

Upcoming Python Book Reviews

Programming Collective IntelligenceProgramming Collective Intelligence

I recently finished reading Programming Collective Intellegince and will be posting a review soon. The TL;DR review is: get it if want an great introduction to machine learning with Python. It covers a lot of complex algorithms in a simple way, and provides some great example use cases.

Python Testing CookbookPython Testing Cookbook

Testing is something nearly every developer can do more of, and this Python Testing Cookbook looks to be full of techniques for integrating testing at various levels of a project. As a preview, you can download a PDF of Chapter 3 - Creating Testable Documentation with doctest.

Python 3 Web Development

Python 3 Web Development Beginner's Guide

I haven't used Python 3 yet, so Python 3 Web Development Beginner's Guide is a good excuse to do so. I also haven't done any web development outside of Django in a few years, and I'm interested to see how it compares to doing it from scratch. As a preview, you can download a PDF of Chapter 3 - Tasklist I Persistence.

Kindle 3

Kindle 3

I'm reading all of these on a Kindle 3, which has worked out surprisingly well. It's obviously not good for copy & pasting code snippets, but that's generally a bad idea anyway. And if don't want to type code in yourself, you can always download it from the publisher's site.

4Feb/117

Python Text Processing with NLTK Cookbook Chapter 2 Errata

It has come to my attention that there are two errors in Chapter 2, Replacing and Correcting Words of Python Text Processing with NLTK Cookbook. My thanks to the reader who went out of their way to verify my mistakes and send in corrections.

In Lemmatizing words with WordNet, on page 29, under How it works..., I said that "cooking" is not a noun and does not have a lemma. In fact, cooking is a noun, and as such is its own lemma. Of course, "cooking" is also a verb, and the verb form has the lemma "cook".

In Removing repeating characters, on page 35, under How it works..., I explained the repeat_regexp match groups incorrectly. The actual match grouping of the word "looooove" is (looo)(o)o(ve) because the pattern matching is greedy. The end result is still correct.

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15Dec/102

Python Text Processing with NLTK Book Reviews

If you've been considering buying Python Text Processing with NLTK 2.0 Cookbook, but haven't yet, below are a couple reviews that may help convince you how awesome it is :)

Jaganadh says in his review of Python Text Processing with NLTK Cookbook at Jaggu's World:

The eight chapter a revolutionary one which deals with Distributed data processing and handling large scale data with NLTK. (...) This chapter will be really helpful for industry people who is looking for to adopt NLTK in to NLP projects.

I give 9 out of 10 for the book. Natural Language Processing students, teachers, professional hurry and bag a copy of this book.

Sum-Wai says in his review of Python Text Processing with NLTK Cookbook at Tips Tank:

I like it where in each recipe, the author provides extra knowledge on the particular problem, like how a problem can be enhance and solve in another way, or what we need to do if the problem on hand changed, and some extra technical tips, which is very nice and useful.

If you’re thinking about the O’Reilly’s NLTK book – Natural Language Processing with Python, IMHO this book and the O’Reilly NLTK book complements each other. The O’Reilly NLTK book focuses more on getting you to know NLP and the features and usage of NLTK , while Python Text Processing with NLTK teaches us how we would implement NLP/NLTK with tools like MongoDB into solving real world problems.

And Neil Kodner, @neilkod, says:

I'm loving python text processing with nltk cookbook by @japerk, its an excellent companion to the O'Reilly NLTK book

Christmas is coming up, and who doesn't think about python text processing during the holidays?

If you want a reviewer copy to write your own review, contact Packt at reviewrequest@packtpub.com. And if you do write a review and want to let me know about it, leave a comment here, or contact me on twitter.

15Nov/102

The Beginning of Python Text Processing with NLTK Cookbook

It all started with an email to the baypiggies mailing list. An acquisition editor for Packt was looking for authors to expand their line of python cookbooks. For some reason I can't remember, I thought they wanted to put together a multi-author cookbook, where each author contributes a few recipes. That sounded doable, because I'd already written a number of articles that could serve as the basis for a few recipes. So I replied with links to the following articles:

The reply back was:

The next step is to come up with around 8-14 topics/chapters and around 80-100 recipes for the book as a whole.

My first reaction was "WTF?? No way!" But luckily, I didn't send that email. Instead, I took a couple days to think it over, and realized that maybe I could come up with that many recipes, if I broke my knowledge down into small pieces. I also decided to choose recipes that I didn't already know how to write, and use them as motivation for learning & research. So I replied back with a list of 92 recipes, and got to work. Not surprisingly, the original list of 92 changed significantly while writing the book, and I believe the final recipe count is 81.

I was keenly aware that there'd be some necessary overlap with the original NLTK book, Natural Language Processing with Python. But I did my best to minimize that overlap, and to present a different take on similar content. And there's a number of recipes that (as far as I know) you can't find anywhere else, the largest group of which can be found in Chapter 6, Transforming Chunks and Trees. I'm very pleased with the result, and I hope everyone who buys the book is too. I'd like to think that Python Text Processing with NLTK 2.0 Cookbook is the practical companion to the more teaching oriented Natural Language Processing with Python.

If you'd like a taste of the book, checkout the online sample chapter (pdf) Chapter 3, Custom Corpora, which details how many of the included corpus readers work, how to use them, and how to create your own corpus readers. The last recipe shows you how to create a corpus reader on top of MongoDB, and it should be fairly easy to modify for use with any other database.

Packt has also published two excerpts from Chapter 8, Distributed Processing and Handling Large Datasets, which are partially based on those original 2 articles:

10Nov/103

Python Text Processing with NLTK Cookbook

My new book, Python Text Processing with NLTK 2.0 Cookbook, has been published. You can find it at both Packt and Amazon. For those of you that pre-ordered it, thank you, and I hope you receive your copy soon.

The Packt page has a lot more details, including the Table of Contents and a sample chapter (pdf). The sample chapter is Chapter 3, Creating Custom Corpora, which covers the following:

  • creating your own corpora
  • using many of the included corpus readers
  • creating custom corpus readers
  • creating a corpus reader on top of MongoDB

I hope you find Python Text Processing with NLTK Cookbook useful, informative, and maybe even fun.

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