In the first part we looked at a few challenges involved when developing a Python project in a collaborative environment. In the second part we looked at how Pipenv addresses some of those issues. In this part of the series we are going to take a closer look at how one can use code linting tools. Specifically we are going to be looking in details at using pylint.

In the first post, we looked at what are typical issues in setting up Python project workflows and took an overview of the tools of the trade. In this post, we are going to be looking closely at pipenv a tool for managing Python project dependencies. In particular we are looking at how pipenv will help us solve the problems of reproducible builds and managing dev and production environments properly.

In a Python based development, tools like pylint, pipenv and virtualenv become important pieces of your development workflow. In the first part of the series of blog posts, we look at overview of the issues that become important as the scope of the project and size of the team working on project increases. In later posts in these series, we would try to address these issues one by one, we look at starting a project, identifying and resolving dependencies 'correctly', why reproducible builds matter, how to separate development and production environment and eventually how to containerize the application.