2022-06-28, 11:00–11:20, Hall 3
Linters are a great tool that enable developers to create static analysis rules for their code base, and the most popular one in the Python ecosystem is Pylint - and this talk will walk through some of its advanced features
Linters are a great tool that enable developers to create static analysis rules for their code base, and the most popular one in the Python ecosystem is Pylint. While most programmers use pre-built sets of rules baked into their linter of choice, these can also be adapted to custom needs.
Today's linters are highly evolved and make it possible to avoid static code and even to run static analysis checks through the development and CI cycles, but they are even more powerful and few developers take advantage of their many advanced features. With Pylint it is quite easy to create custom rules that can for both general usage––such as library guidelines and even security SAST, through more customized usage like maintaining clarity around internal frameworks, and enforcing organizational guidelines.
Often times Python is chosen as the language of choice due to its suitability for specific tasks such data pipelines, and system engineering, while those who code in the language are not always familiar with the language's underlying fundamentals and patterns. With custom lint rules, you can proactively help your developers write better code in their native IDEs, protect IaC repos through custom lint enforcement on config files, and even have security tools leverage them for manual vulnerability checks. This talk will demonstrate how you can apply all of this to your Python code with Pylint.