During the last decade the evolution of the computers has been much different than before. Instead of seeing acceleration in CPU clock speeds we are seeing more cores in CPUs, and instead of having plain simple architectures with a CPU, memory and hard disk, we are seeing computer facilities with several CPUs, several levels of caches and several persistent layers of storage.

It is unfortunate that not many libraries are being designed nowadays with this shift in mind. My intention is to explain how to tackle with this efficiently during the making of libraries for handling big datasets. We will see that the election of a good language is important too, and how Python, complemented with others (like Cyhton, C or Julia), is a good match for this.