Reliable code: What the Giants have taught us
Madhukar Mishra (~madhukar93) |
If you’ve been using python for any length of time, you know it as this versatile tool that can be used to build almost anything, and in a very friendly way. But Python use in the large codebase arena is very different from Python for a small service. What if you knew that that shift was due? What if you knew that the next project you started was definitely going to be collaborated on by a hundred developers? Let’s look at these differences and prepare ourselves and our codebases for that shift.
We’ll learn how:
- Maintaining large codebases isn’t free, and how the Python ecosystem supports you in your efforts.
- Testing a large application isn’t easy, and how to use the latest and greatest testing methods to make sure your code does what you expect it to.
- Immutable data structures aren’t just easier for humans to process, but also for machines to validate.
- Python has learnt from its neighbouring languages, and now has a type system that is here to help.
I am a full stack dev at Grofers where Python is our first choice for everything from backend services to infrastructure orchestration. I have worked on a wide range of solutions using Python, among them are APIs that power our consumer ecosystem at scale, inventory/content management systems, and other high throughput ETL services in Python.