Python gives you a lot of functionality straight out of the gates, but writing code is only part of the job. To actually develop, ship, maintain, and scale applications in production environments, you’re going to need the right tooling.
I’m sharing the top 5 tools that I will never stop using as part of my development workflow. These tools form a complete workflow, from development to deployment.
1. Git
Git is a free and open source version control system designed to track changes in your codebase. Instead of using the old college habit of sending your code to your coworker via email, you’ll leverage both Git and GitHub (a platform where teams share code) to synchronize your code with your coworkers.
You’ll be able to see the changes they made and collaborate on feature(s) without having to disrupt operations or other features that are being worked on.
This tool will likely never be removed from the #1 spot on this list. If you develop code of any sorts, you’re going to want to learn Git.
2. Docker
Docker allows you to pick up your code and deploy it elsewhere without the “it works on my machine” excuse. If your team is working on different operating systems, you’ll eventually run into issues (i.e. symlinks).
Seeing errors like this can be frustrating, and that’s where Docker comes in handy. Docker is designed to provide developers the minimal underlying files to run applications so the application can be run on any machine.
You’ll define how Docker builds the image through a Dockerfile. Once the image is built, you’ll run the application in a container on any machine.
» Alternative: Podman
3. VSCode
To even begin writing Python, you need an integrated development environment (IDE). Multiple IDE’s offer Python support, but I’ve found Visual Studio Code to suit what I’m looking for the best.
VSCode offers extensions written by 3rd party developers, an integrated terminal, and an easy-to-understand interface to write Python. I personally use extensions like DBCode, autoDocstring, and RainbowCSV.
4. Terraform
Terraform is an infrastructure-as-code tool that lets you define your cloud resources (AWS, GCP, Azure) in configuration files. This is important because we want to be able to know how our infrastructure is set up and be able to share it with our team.
Let’s be real: no one wants to spend time flipping through multiple tabs on their browser, trying to understand permissions, databases, virtual machines, networking, etc, especially if an operational issue arises.
Brandon’s note: Terraform does have a large learning curve. It’s quite confusing and intimidating, but once you understand it you’re not going to not use it.
5. Claude Code
With the rise of AI, it’s essential for developers to understand how to integrate AI-based developer tooling in their workflow. Claude Code works seamlessly in an integrated terminal in VSCode.
I can have it read all my files and tell me information about them, perform junior-level software development work as individual agents, and help me understand concepts I don’t know and help me implement them.
I personally use Claude Code very often for templating, simple algorithm development, and design development. It’s important to note that you should never let AI write code for you. Remember, it’s your name on the commit!
» Alternatives: Codex (note that this will get outdated quickly).
I’d recommend by downloading VSCode first, installing Claude Code, learning Git, developing your application, learning and integrating Docker, then building out your Terraform if deploying to a cloud provider.
Happy coding!
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