In this chapter, we explored introductory concepts about code efficiency and how to measure it. Equipped with the right tools, we optimized our code to make it run faster.

Instead of storing data into Python objects, we turned to SQL databases. We thereby enhanced our app with state-of-the-art filtering and got information in an efficient way.

Later, we came across a large amount of data that was impossible to import with ordinary computers. We optimized our code again, making it memory-efficient and stable, allowing us to import this data. Finally, we queried the data, testing the new feature capabilities.

In the next chapter, we will face similar speed and memory problems but with images (raster) data. This will require us to develop new and creative solutions.