Efficient Python (100+ Pages of Notes)
Before I begin, I was reached out by coachquant.com, an open source quant preparation site to share their initiative. I thought it is a great idea, and encourage students to check it out.
As quantpylib move into hft infrastructures, I find it very necessary to bring up efficient python programming and sharpen our tools there.
As we forage through python’s tips and tricks on squeezing performance from a high-level language - over the coming weeks, we will compile, organize and synthesize both good resource materials and written notes on efficient (synonymous with scientific, numerical, performant) programming with Python.
With that, we would like to bring up an old paper and case study we wrote in 2022, and share with all reader tiers:
Over the coming weeks, we will evolve this piece of work with new knowledge, get it significantly more in-depth, and attempt to get a handbook of it on the market notes for paid readers.
Our last market notes was here (916 pages):
Be a paid reader here: