MongoDB and Python

Going Further

In this book we have tried to give you a solid grasp of how to leverage MongoDB in real-world applications. You should have a decent understanding of how to go about modeling your data, writing effective queries and avoiding concurrency problems such as race conditions and deadlocks. There are a number of other advanced topics which we didn’t have space for in this book but are nonetheless worth looking into as you build your application. Notably, map-reduce enables computing aggregates efficiently. Sharding permits you to scale your application beyond the available memory of a single machine. GridFS allows you to store binary data in MongoDB. Capped Collections are a special type of collection, which look like a circular buffer and are great for log data. With these features at your disposal, Python and MongoDB are extremely powerful tools to have in your toolbox when developing an application.