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Niall OHiggins - MongoDB and Python: Patterns and processes for the popular document-oriented database

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Learn how to leverage MongoDB with your Python applications, using the hands-on recipes in this book. You get complete code samples for tasks such as making fast geo queries for location-based apps, efficiently indexing your user documents for social-graph lookups, and many other scenarios.This guide explains the basics of the document-oriented database and shows you how to set up a Python environment with it. Learn how to read and write to MongoDB, apply idiomatic MongoDB and Python patterns, and use the database with several popular Python web frameworks. Youll discover how to model your data, write effective queries, and avoid concurrency problems such as race conditions and deadlocks. The recipes will help you:Read, write, count, and sort documents in a MongoDB collection Learn how to use the rich MongoDB query language Maintain data integrity in replicated/distributed MongoDB environments Use embedding to efficiently model your data without joins Code defensively to avoid keyerrors and other bugs Apply atomic operations to update game scores, billing systems, and more with the fast accounting pattern Use MongoDB with the Pylons 1.x, Django, and Pyramid web frameworks

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MongoDB and Python
Niall O'Higgins
Editor
Mike Loukides
Editor
Shawn Wallace

Copyright 2011 Niall O'Higgins

OReilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (.

Nutshell Handbook, the Nutshell Handbook logo, and the OReilly logo are registered trademarks of OReilly Media, Inc. MongoDB and Python , the image of a dwarf mongoose, and related trade dress are trademarks of OReilly Media, Inc.

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While every precaution has been taken in the preparation of this book, the publisher and author assume no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.

OReilly Media Preface Ive been building production database-driven - photo 1

O'Reilly Media

Preface

Ive been building production database-driven applications for about 10 years. Ive worked with most of the usual relational databases (MSSQL Server, MySQL, PostgreSQL ) and with some very interesting nonrelational databases (Freebase.coms Graphd/MQL, Berkeley DB, MongoDB). MongoDB is at this point the system I enjoy working with the most, and choose for most projects. It sits somewhere at a crossroads between the performance and pragmatism of a relational system and the flexibility and expressiveness of a semantic web database. It has been central to my success in building some quite complicated systems in a short period of time.

I hope that after reading this book you will find MongoDB to be a pleasant database to work with, and one which doesnt get in the way between you and the application you wish to build.

Conventions Used in This Book

The following typographical conventions are used in this book:

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Indicates new terms, URLs, email addresses, filenames, and file extensions.

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Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.

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Using Code Examples

This book is here to help you get your job done. In general, you may use the code in this book in your programs and documentation. You do not need to contact us for permission unless youre reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from OReilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your products documentation does require permission.

We appreciate, but do not require, attribution. An attribution usually includes the title, author, publisher, and ISBN. For example: MongoDB and Python by Niall OHiggins. Copyright 2011 OReilly Media Inc., 978-1-449-31037-0.

If you feel your use of code examples falls outside fair use or the permission given above, feel free to contact us at .

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Acknowledgments

I would like to thank Ariel Backenroth, Aseem Mohanty and Eugene Ciurana for giving detailed feedback on the first draft of this book. I would also like to thank the OReilly team for making it a great pleasure to write the book. Of course, thanks to all the people at 10gen without whom MongoDB would not exist and this book would not have been possible.

Chapter 1. Getting Started
Introduction

First released in 2009, MongoDB is relatively new on the database scene compared to contemporary giants like Oracle which trace their first releases to the 1970s. As a document-oriented database generally grouped into the NoSQL category, it stands out among distributed key value stores, Amazon Dynamo clones and Google BigTable reimplementations. With a focus on rich operator support and high performance Online Transaction Processing (OLTP), MongoDB is in many ways closer to MySQL than to batch-oriented databases like HBase.

The key differences between MongoDBs document-oriented approach and a traditional relational database are:

  1. MongoDB does not support joins.

  2. MongoDB does not support transactions. It does have some support for atomic operations, however.

  3. MongoDB schemas are flexible. Not all documents in a collection must adhere to the same schema.

1 and 2 are a direct result of the huge difficulties in making these features scale across a large distributed system while maintaining acceptable performance. They are tradeoffs made in order to allow for horizontal scalability. Although MongoDB lacks joins, it does introduce some alternative capabilites, e.g. embedding, which can be used to solve many of the same data modeling problems as joins. Of course, even if embedding doesnt quite work, you can always perform your join in application code, by making multiple queries.

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