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Python for Quantitative Finance / Testing, Debugging, and Style

Overview

Every earlier topic in this unit taught how to write a program; this topic teaches the engineering discipline that keeps a growing program trustworthy. docs/programme-profiles/library/introduction-to-python.md names this Stage 7, "engineering discipline" — the practical habits that separate code a quant can actually rely on from code that merely happens to produce an answer. Three ideas anchor this topic: testing, which finds bugs without ever proving their absence; debugging, the systematic search that turns a discovered symptom into a located, fixed fault; and reading algorithmic complexity informally, which builds the vocabulary (Big O, the standard complexity classes) needed to recognise when a piece of code will or won't scale, without yet deriving those bounds rigorously.

In this lesson

  1. Learning objectives
  2. Contents
  3. The big picture

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