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MongoDB and Python. Patterns and processes for the popular document-oriented database - Septem

MongoDB and Python. Patterns and processes for the popular document-oriented database
ebook
Autor: Niall O'Higgins
ISBN: 978-14-493-1709-6
stron: 70, Format: ebook
Data wydania: 2011-09-16
Księgarnia: Septem

Cena książki: 59,42 zł (poprzednio: 69,09 zł)
Oszczędzasz: 14% (-9,67 zł)

Dodaj do koszyka MongoDB and Python. Patterns and processes for the popular document-oriented database

Tagi: Bazy danych | Inne | Python

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. You’ll 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

Dodaj do koszyka MongoDB and Python. Patterns and processes for the popular document-oriented database

 

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Dodaj do koszyka MongoDB and Python. Patterns and processes for the popular document-oriented database

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Dodaj do koszyka MongoDB and Python. Patterns and processes for the popular document-oriented database

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