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Python Text Processing with NTLK 2.0 CookbookPython 2.6 Text Processing Beginners Guide

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HBase Administration Cookbook by Yifeng Jiang : Review

 Packt publishers has announced a new book HBase Administration Cookbook by Yifeng Jiang. I think this is the first Big-Data book from Packt. The name suggest that the book HBase Administration Cookbook by Yifeng Jiang is essentially for people who is playing with HBase and would like to deep dive into HBase administration essentials. The book discusses various essential topics in HBase administration starting from installation to performance tuning. The book targets big-data administration professionals primarily. The author discusses the art and science of HBase administration in nine systematically arranged chapters. The initial chapter deals with installation of Habse in Amazone EC2 instance and discusses various setting . The chapter ends with High Availability master settings. The second chapter deals with migrating data to Habse. There is a detailed discussion on how to migrate MySQL data to HBase. This may be interesting for people who plans to migrate existing data to HBase. The third chapter mainly deals with HBase administration tools and over view of the tools. Data backup and restoration is one of the key concept when we discuss about data management. Fourth chapter of this book deals with data backup, restoration and replication in HBase. The fifth chapter deals with HBase cluster monitoring and diagnosis. The chapter comes with beautiful scripts for reporting cluster status. Security aspects of Habse is being discussed in chapter six. Security essentials for HBase and Hadoop with Kerberos is also discussed with detailed examples. Necessary troubleshooting aspects for HBase administration is discussed in chapter seven. Performance tuning and advanced configuration etc are discussed in chapter eight and nine.

The author has presented each topics in the book in lucid and digestive manner. Necessary examples and explanations were provided throughout the book; which helps the reader to gain a hands on experience in HBase administration. Even though some books are available on general aspects of Habse this is the first book which deals with HBase administration in detail. This book will be helpful for budding HBase and big-data administrators. Even though the book discusses the cluster setup and installation based on Amazone EC2 smart administrators can manage the same in their non Amazone clusters.
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New book by Packt:'Python Text Processing with NLTK2.0 Cookbook'

HBase Administration Cookbook by Yifeng Jiang new book from Packt

 Packt Publishers announces a new book "HBase Administration Cookbook by Yifeng Jiang".

I am reading it now; will bring a review soon.

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Python Testing Cookbook, by Greg L Turnquist : Review

  Python Testing Cookbook, by Greg L Turnquist is one of the latest books from Packt Publishing. It is the second book on Python Testing; the first one was Python Testing: Beginners Guide by Daniel. The Python Testing Cookbook is a collection of useful easy to learn tips and tricks. Even though this book is labeled as "cookbook" it is quite useful for the newbies in Python testing too. All the essential tips to play with Python testing is given in the introductory chapters with illustrative examples. The book can serve as a good resource to train Python newbies in the art of Software Testing.

The first chapter of the book deals with basics of unittest with Python. It gives step by step examples to understand unit-testing.

The second chapter helps you to put your nose in to testing with Python "nose" framework. The chapter gives insights on how to write nose-plugins to make the testers life easy. Third chapter of the book deals with doctest. The chapter gives good intro to writing docstring for doc-test. The art of doc-test is well covered in this chapter.  The fourth chapter deals with testing behavior driven development. The chapter introduces Mock, mockito and Lettuce testing tools. The fifth chapter deals with Acceptance Testing with Pyccuracy and Robot tools. This chapter gives some insight on selinium too. The sixth chapter speaks about test automation with Continuous Integration(CI). The chapter introduces Jenkins and NoseXunit. The chapter is very useful for the people who follows the waterfall model in Software Development. The seventh chapter discusses about test coverage.The chapter is bit complicated for beginners. Some play with database, springpython etc are there. In some examples I feel that the element of testing missed out ;-). The eighth chapter deals with Smoke and Load testing in Python. This chapter introduces the tool Pyro too.  The 9th chapter is a collection of general advices for automated testers. After making your hands dirty with testing u can relax and clear the doubts with advices in this chapter.

The book comes with extensive code samples. Even if the book is all about testing I found one bad practice in coding through out the examples; that is import * . This makes the learner to scratch his head to understand what comes from where. I think it is worth to buy and read the book to get good insights on Test Automation with Python. It is a good book for beginners to learn testing and good reference book for experienced professionals too.

disclaimer: I received a free eBook from Packt for review

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New Book from Packt: Python Testing Cookbook by Greg L. Turnquist

  Packt Publishing releases a new Python book "Python Testing Cookbook" by Greg L. Turnquist. I received review copy of the book today. I will put a review of the book here soon. A sample chapter from the book is available at Packt Web page.
Book Info
Language : English
Paperback : 364 pages [ 235mm x 191mm ]
Release Date : May 2011
ISBN : 1849514666
ISBN 13 : 978-1-84951-466-8
Author(s) : Greg L. Turnquist

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Book Review: Python 2.6 Text Processing Beginner's Guide by Jeff McNei

Python 2.6 Text Processing Beginner's Guide by Jeff McNeil is one of the latest books by Packt Publishers. I received the review copy of this book before one and half months or so. Due to busy schedule I was not able to finish the review process. Finally I got enough time to review it. The book gives good insight to on different technical aspects and use of Python standards and third party libraries for text processing. It is filled with lots of examples and practical projects. I think I might have took almost one year to gather knowledge in  the topic discussed in this book, when I started my career in Natural Language Processing domain. I am giving a bit detailed review on the book here.

The first chapter of this book gives some practical and interesting exercises like implementing cypher, some basic tricks with HTML. It also discusses how to setup a Python virtual environment for working with the examples in the book. The section of setting virtual environment is nice an well written one. It gives a clear idea of how to setup virtual environments.

The second chapter deals with Python IO module. It narrates the basic file operations with Python. The use of context manager(with function) for for file processing is discussed in this chapter. I am suing Python for text processing for lat three to four years. But after reading only I found that there is something called "fileinput" in Python programming language for multiple file access. The chapter discuss how to access remote files and StringIO() module in Python. At the end of this chapter there is a discussion about IO in Python 3 too.

The third chapter is about Python String Services. It deals with string formatting, templating, modulo formatting etc. Every concept is explained with necessary mini projects which followed from chapter two. The chapter gives a comprehensive view on advanced string services in Python.

The fourth chapter is entitled as Text Processing Using the Standard Library. This chapter deals with topic like reading wnd writing csv files(csv file processing), playing with application config files(.ini files), and working with JSON. The examples are bit long one but worth practicing for better understanding.

The fifth chapter deals with one of the key aspect in text processing "Regular Expressions". The chapter teaches basics syntax of regular expression in Python. The chapter also discusses about advanced processing like regex grouping, look ashed and look behind assertion in regular expressions. The look behind operation in regular expression is the most tricky part in dealing with regex. I think only masters in regex can do it effectively ;-) .The chapter dscuss basics of Unicode regular expressions too. The chapter is filled with enough examples for each and every concept discussed.

The sixth chapter deals with Markup Languages. The chapter discusses about XMl and HTML processing with Pytho standard libraries. xml.dom.minido, SAX,laxm and BeautifulSoup packages are discussed with illustrative examples.

The seventh chapter is entitled as Creating Templates. "Templating involves the creation of text files, or templates, that contain special markup. When a specialized parser encounters this markup, it replaces it with a computed value". The templating concept was quite new to me. But I got a good insight on the topic from this chapter. The chapter discusses some libraries like "Makeo" for templating task.

The eight chapter deals with localization (l1on) and encoding. If you are working with non-English data this chapter is a must read for you.The chapter discuses about character encoding, Unicode processing and Python3 too. Apart from mere Python stuff this chapter gives a good insight about charter encoding too.

The ninth chapter Advanced Output Formats is quite useful if you are trying to create output in PDF, CSV orExcel format. This chapter discuss about ReportLab a PDF generation library in Python.The only disadvantage which I found in ReportLab is its lack of complete Unicode Support. The chapter also discusses about creating excel files with xlwt module. Finally the chapter deals with handling OpenDocument format woth ODFPy module too. I used to read excel file from Python. But after going through this book I am able to even write Excel output too.

The tenth chapter deals with Advanced Parsing and Grammars. This is one of the key skill which required for Python text processing peoples. Creating custom grammars for parsing specific data. Through out my career I spent lot of time to train Engineers to understand parsing and BNF grammar. This time I got a good pointer for my people to start with BNF and Python programming. Also this chapter discusses about some parsing module in NLTK my favorite Python library. Some advanced topics in PyParsing also discussed in this chapter.

The eleventh and last chapter is the most interesting one in the book. The chapter deals with Searching and Indexing. PyLucene is the bset known Searching Index library in Python. But it is a wrapper to the apache Lucene. But his chapter discusses about another Python tool Nucular. Practical examples for creating search index etc are given in this chapter. This is the first time I am using the Nucular tool. I feel it as a nice and easy one compared to PyLucene. But I dont think this is superior than Lucene. I will play more with this tool and will update it in another blog post.

There are two appendix . The first appendix gives pointers to Python resources. The next one is answer o the pop quiz in the chapters.

I will give 9 out of 10 for this book. If you are dealing with rigorous text processing this book is a must have reference for you.

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New book from Packt: Python 2.6 Text Processing Beginners Guide

Packt Publishing releases new book "Python 2.6 Text Processing Beginners Guide" by Jeff McNeil. I received review copy of the book today. I will put a review of the book here soon. The book comes with lot of practical examples and tips.

Book Info:
Language : English
Paperback : 380 pages [ 235mm x 191mm ]
Release Date : December 2010
ISBN : 1849512124
ISBN 13 : 978-1-84951-212-1
Author(s) : Jeff McNeil

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Packet Python Month

Packt is offering a series of attractive discounts on all Python books.

    * Buy any Python print book and get 20% off
    * Buy any Python eBook and get 30% off

This offer will last for a limited period only. Grab your copy now !

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Book Review:Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins

Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins is one of the latest books published by Packt in the Open Source series. The book is meant for people who started learning and practicing the Natural Language Tool Kit(NLTK).NLTK is an Open Source Python library to learn practice and implement Natural Language Processing techniques. The software is licensed under the Apache Software license. It is one of the most widely recommended tool kit for beginners in NLP to make their hands dirty. The toolkit is part of syllabus for many institutions around the globe where Natural Language Processing/ Computational Linguistics courses are offered. Perkins book work is the second book published on the toolkit NLTK. The first book is written by core developers of NLTK; Steven Bird, Ewan Klein, and Edward Loper, published by O'rielly. Steven et.all's book is a comprehensive introduction to the toolkit with basic Python lessons. People who has gone through the book may definitely like the new book by Perkin. The book is must have desktop reference for students, professionals, and faculty members interested in the area of NLP, Computational Linguistics and NLTK. Perkins handles the topic in an elegant way. Most of the people who searched for some NLTK tips might have gone through the author's blog. He maintains same simplicity and explanation style and hands-om approach throughout the book; which makes the reader to digest the topic with much easiness. The book is a collection of practical and working recipes related to NLTK.

The first chapter of the book "Tokenizing Text and WordNet Basics" deals with tokenizing text in to words sentences and paragraphs. The chapter also deals with tips and tricks with WordNet module in NLTK. Perkin discusses about Word Sense Disambiguation(WSD) techniques in this chapter. The missile part in WordNet is the use of wordnet 'ic' function. Tips for extracting collocations from a corpus is also included in the first chapter. The chapter "Replacing and Correcting Words"(IInd chapter) discusses stemming , lemmatization and spelling correction. He introduces another Python module named Python-Enchant for discussing about the spell checking technique. The chapter also discusses techniques like replaces negation with antonyms and replacement of repeating characters. The third chapter deals with Corpora. This chapter mainly discusses how to load user generated corpora in to NLTK with corpus readers implemented in NTLK. The most attracting part of this chapter is discussion about MonngoDB blackened for corpus reader in NLTK. MongoDB is a text based DB, which belongs to the NoSQL family. This part will be very useful for students in NLP and working professionals. The fourth chapter deals with POS Tagging techniques. It discusses mainly about training different POS taggers and using it. It is also quiet useful for people who would like to extend the functionality in NLTK for their projects and people who is interested to extend POS taggers in language other than English. Some part of this chapter content was published in the authors blog before one year. Chapter five of the book deals with Chunking and Chinking techniques with NLTK. Named Entity Identification and Extraction techniques are also discussed in this chapter. It gaves good insight to train NLTK chunking module for custom chunking tasks. With the help of this chapter I was able to create a small named entity extraction script with some Indian names. The sixth chapter is named as "Transforming Chunks and Trees" which deals with verb form correction, plural to singular correction, word filtering, and playing trees structures. Many time I saw that people used to raise question about handling tree data in NLTK. I think people can refer this chapter for getting good insight to play with NLTK parse tree data. The seventh chapter deals with most wanted topic of the time "Text Classification". Some part of this chapter appeared as blog post in Perkin's blog. There was many requests in freelancing web sites for text classification with NLTK. I found that some of them were not bided too. The chapter discusses the task of Text Classification in details with all the classification implementations available in NLTK. Training NLTK classifier is discussed very clearly. Apart form the classifier training, classification the chapter discusses classifier evaluation and tuning too. The eight chapter a revolutionary one which deals with Distributed data processing and handling large scale data with NLTK. I was not able to fully play with the total code in this chapter (Yes I worked out the code in other chapters and it was quite exciting. It contributed to my professional life too) . This chapter will be really helpful for industry people who is looking for to adopt NLTK in to NLP projects. Some basic insights of the contents in this chapter was also published in Perkin's blog. After Nithin Madanini's talk in US Python Conference on corpus processing with Dumbo and NLTK I think this is the only existing resource for practical large scale data processing with NLTK. The ninth and last chapter is about Parsing Scientific data with Python. This chapter deals with some Python modules rather than the NLTK tool. It discusses about URL extraction, timezone look-up, character conversion etc.. This chapter is good for people who plays with web data processing like harvesting. There is an appendix for the book which contains "Penn Treebank". It give list of all tags with its frequency in treebank corpus.

For the last three four years I am using NLTK to teach and develop prototypes of NLP applications. I was very much when I went through each of the recipes in this book. The author provides UML diagrams for the modules in NLTK which helps the reader to get good insight on the functionality of each module. This will be a good book not only for students and practitioners but also for people would like to contribute to NLTK project too. Also this book will help students in NLP and Computational Linguistics to do their projects with NLTK and Python. I give 9 out of 10 for the book. Natural Language Processing students, teachers, professional hurry and bag a copy of this book.

Thanks to Packt publihsres for the review copy of the book.

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New book by Packt:'Python Text Processing with NLTK2.0 Cookbook'

Packt Publishing releases a new book 'Python Text Processing with NLTK 2.0 Cookbook' by Jacob Perkins ( I received review copy of the book today. I will put a review of the book here soon. The book comes with lot of practical examples and tips.

An extracted chapter from the book is available for download at

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