In Python, the concept of a “target” in the context of build systems or automation scripts often refers to the desired output or outcome of a specific operation. Unlike some strictly defined build systems, Python’s flexible nature allows for various approaches without rigid rules dictating how a target must be constructed. This offers developers freedom in defining and achieving their desired outcome, whether generating files, executing commands, or performing other actions. For example, a developer might write a script to compile code, package it into a distributable archive, and deploy it to a server. Each of these steps could be considered a separate, achievable objective within the script. The absence of strict rules allows for customization tailored to specific project needs.
This flexibility is highly beneficial as it enables developers to adapt to unique project requirements and employ diverse tools and libraries seamlessly. It fosters creativity and innovation by empowering developers to tailor their workflows and achieve complex build processes without being constrained by predefined structures. Historically, the evolution of Python’s build tooling has moved towards greater flexibility, starting from tools like `make` with rigid rules, and progressing to more flexible solutions based on scripting with tools such as `scons`, `waf`, and ultimately to very flexible build systems like `doit` and those based on `setuptools`. This shift reflects a broader trend in software development towards greater agility and adaptability.
