Notes on Computer Organization and Python Programming
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Last market notes were here:
As mentioned in our last post update, we are going to compile some notes on Python and quant development, and update the market notes to contain a lot of the new material we published in the last quarter. This includes the content in QT101, where we demonstrated some more advanced techniques in Python programming.
In many of the concepts, we assumed prior knowledge or skimmed over the implementation details. The notes will help you to understand more in depth the reasoning behind some of the design choices and internal implementation behind our quant work, so that you too, can make these considerations in your work when developing your own quant tools.
To begin off, we are adding to Chapter 17, page 827 of our quant notes. The existing notes contain a small section on asyncio programming, but the content we have covered so far is alot more extensive. Before we explore optimizations in Python, we first have to understand the implementations that Python has abstracted away from us, minimally to the point of intuition.
We have therefore included a small primer on properties of Python - where we talk about code interpretation, dynamic typing, memory management, GIL, computer organization, data transfer and so on.
We will expand on this section over the coming posts. The next post, we will cover code and computer profiling. With these concepts outlined, they will form the building blocks for the design choices in the Russian Doll.
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