Tooling for Type Consistency and General Validations
Explore some tools in Python that are used to ensure type consistency and other general validations.
We'll cover the following...
In this section, we'll explore how to configure some basic tools and automatically run checks on code, with the goal of leveraging part of the repetitive verification checks.
Remember that code is for us, people, to understand, so only we can determine what is good or bad code. We should invest time in code reviews, thinking about what is good code, and how readable and understandable it is. When looking at the code written by a peer, we should ask questions such as:
Is this code easy to understand and follow for a fellow programmer?
Does it speak in terms of the domain of the problem?
Would a new person joining the team be able to understand it and work with it effectively?
Importance of tooling
Code formatting, consistent layout, and proper indentation are required but not sufficient traits to have in a code base. Moreover, these are things that we, as engineers with a high sense of quality, take for granted, so we read and write code far beyond the basic concepts of its layout. Therefore, we are not willing to waste time reviewing these kinds of items, so we can invest our time more effectively by looking at actual patterns in the code in order to understand its true meaning and provide valuable results.
All of these checks should be automated. They should be part of the tests or checklist, and this, in turn, should be part of the continuous integration build. If these checks do not pass, make the build fail. This is the only way to actually ensure the continuity of the structure of the code at all times. It also serves as an objective parameter for the team to have as a reference. Instead of some ...