[sjducb]

VS Code and local Python virtual environments.

Packages managed with pip and versions pinned with pipcompile. One ML production environment forces us to use conda we inherit from the pip environment and try to have as much done by pip as possible.

Formatted with black and flake8

Unit tests with unittest

Azure Dev Ops for running tests, security screening, and CI

The happy path for deployment is build docker images in AzureDevOps unfortunately we can’t do that for good reasons

I’m not a fan of typed Python, it doesn’t work as smoothly as you expect if you’re coming from a statically typed language.

Be careful enforcing pylint quality. It can be a great way to kill your teams velocity.

I’m describing a boring stack that works. All of these tools are 5+ years old and very well supported.

[pimbrouwers]

Not a python developer, just casually curious about the discourse. But I wanted to say that I completely agree with the point on letting dynamic languages be dynamic. Otherwise, you reduce the benefit of a dynamic language to the point where I feel like the value proposition comes too close to disappearing. Really at that point, you're just trading performance for compile time or lack there of.

[sjducb]

People often forget the benefits of dynamic typing.