Python and C++ for HFT

As we showed in the previous section, Python is too slow to be adequate for high-frequency trading. C++ is much faster and is the language of choice to get low latency. We are presenting in this section a means to integrate the two languages to unify both worlds. On one side, Python gives the developers ease and flexibility, and on the other side, C++ allows code to reach high performance and low latencies. In HFT, we need to have quantitative researchers and programmers build HFT strategies to run in the production environment. Having a Python ecosystem capable of using C++ libraries will allow quants (quantitative traders) to focus on their research and deploy code in production without the need for other resources. We will explain how to provide a standard interface to different C/C++ libraries. These C/C++ libraries will become Python modules. In other words, we will use them as dynamic libraries loaded in memory when we need them.

Let's first talk...