Summary

In this chapter, we learned how to use Python to communicate with Twitter by using an open source library, Tweepy. We learned how to use Tweepy to send tweets. We also learned how to create a database, save and update data in it, and get some data from an existing database. Toward the end, we extended the capabilities of the weather station we built in Chapter 9, Grove Sensors and the Raspberry Pi and added tweeting and data-saving functionalities to it. We also added speech capabilities to it to make it easier to use.

In the next chapter, we will be exploring the interesting topic of parallel computing. We will be using multiple Raspberry Pis to create a cluster of computers that perform computations faster by working in tandem towards a single task. A master Pi will control other slave Pis and outsource its computations to them, so that the task is performed faster. We will use this setup to perform an n-body simulation, which is by itself a very computationally challenging task...