A lot of people seem to believe that dynamically typed languages make development easier, because you don't have to worry about writing type annotations or going through the extra steps to fix compile-time errors.

This is arguably true for small scripts, but for anything non-trivial I find that static typing means I can be more productive, because type errors are caught straight away (rather than potentially in production), and I can be much more confident in refactoring code because I know certain kinds of errors will be caught by during type checking. This doesn't remove the need for automated testing, but does reduce the number of test cases you have to write.

Things have improved a lot in the Python ecosystem of late with the introduction of type annotations and mypy, so to the extent possible I treat Python as if it's a statically typed language, putting type annotations everywhere and always making sure the codebase passes type checking before pushing a commit.

However, the fact that this is optional sadly means that not everyone does it, and if you're working with parts of a codebase written without this level of discipline, you're basically back to square one. I've come to the conclusion that for medium to large projects, dynamic typing encourages sloppy programming, because it doesn't force people to think as carefully about what exactly their data types are, and whether they're being used correctly.