spotless VS MonkeyType

Some code formatters such as Spotless (https://github.com/diffplug/spotless/tree/main/plugin-gradle...) allow you to format code only in files that have changes against some designated branch such as `master`. So, you check out your feature branch, make changes, do some commits, and run spotless. Only the files which have some changes between your workspace and the master branch will be formatted. This allows you to gradually format the project as and when files would be changed anyways.

As a Top-Level Apache open source project, ShardingSphere has 400 contributors as of today. Since most developers do not have the same coding style, it is not easy to standardize the project’s overall code format in a GitHub open collaboration model. To solve this issue, ShardingSphere uses Spotless to unify code formatting.

But please just use an code formatter like spotless. Or better yet set it as a pre commit hook. You will thank yourself later, and so will all of your coworkers.

I use Spotless but it’s not as opiniotated as Prettier or Black

I use Spotless and it works quite well, but there are many other options. Also good IDEs can reformat your code.

We are working on different ways to run diktat, however. For example, the integration into spotless is on its way. In the future we might consider adding support for Intellij, and if someone decides to contribute it - it will be very welcome as well.

MonkeyType collects runtime types of function arguments and return values, and can automatically generate stub files or add type annotations directly to your Python code based on the types collected at runtime.

To alleviate the burden of manual annotation, MonkeyType offers a clever solution. It dynamically observes the types entering and leaving functions during code execution. Based on this observation, it generates a preliminary draft of type annotations. This significantly reduces the effort needed to add type hints to legacy code.

https://github.com/instagram/MonkeyType can perform the call logging, and can export a static typing file which is used by mypy, but also e.g. PyCharm. It doesn't expose such fine grained types, but you could build that based on the logged data.

Which introduces MonkeyType, a python library that generatics static type annotations by collecting runtime types.

Not sure if you're joking but there is something similar for python developed by a rather well known company https://github.com/Instagram/MonkeyType