MongoDB and Python: Patterns and Processes for the Popular by Niall O'Higgins

By Niall O'Higgins

Find out how to leverage MongoDB along with your Python functions, utilizing the hands-on recipes during this e-book. You get entire code samples for initiatives reminiscent of making quick geo queries for location-based apps, successfully indexing your person files for social-graph lookups, and plenty of different scenarios.

This consultant explains the fundamentals of the document-oriented database and exhibits you the way to establish a Python surroundings with it. the right way to learn and write to MongoDB, observe idiomatic MongoDB and Python styles, and use the database with numerous well known Python net frameworks. You'll detect the right way to version your information, write potent queries, and keep away from concurrency difficulties akin to race stipulations and deadlocks.

The recipes can assist you:

*Read, write, count number, and kind files in a MongoDB collection

*Learn the way to use the wealthy MongoDB question language

*Maintain information integrity in replicated/distributed MongoDB environments

*Use embedding to successfully version your facts with no joins

*Code defensively to prevent keyerrors and different bugs

*Apply atomic operations to replace online game ratings, billing platforms, and extra with the short accounting pattern

*Use MongoDB with the Pylons 1.x, Django, and Pyramid

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Extra resources for MongoDB and Python: Patterns and Processes for the Popular Document-Oriented Database

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Writes of additional documents without a username property will raise an exception. If you try to add a unique index to a collection which already contains duplicates on the specified property, MongoDB will (unsurprisingly) raise an exception. However, if you don’t mind throwing away duplicate data, you can instruct MongoDB to drop all but the first document it finds using the dropDups or drop_dups parameter: # Create index with unique constraint on username property # instructing MongoDB to drop all duplicates after the first document it finds.

The Python dict class’ get method easily lets you specify a default value for a property should it be missing. Often it makes sense to use this defensively. For example, imagine we have a collection of user documents. Some users have a “score” property set to a number, while others do not. It would be safe to have a default fallback of zero (0) in the case that no score property is present. We can take a missing score to mean a zero score. get("score", 0) This approach can also work well when looping over embedded lists.

Thus it is easy to insert or update a numeric property with a value that is a string. The best way, of course, to avoid errors of this nature is to prevent the wrong type of data 38 | Chapter 3: Common MongoDB and Python Patterns ever being written to the database in the first place. Thus, in the context of a Web application, validating and/or coercing the types of any inputs to write queries before issuing them is strongly advised. You may consider using the FormEncode or Colander Python libraries to help with such validation.

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