[tabbott]

I would argue that the really big benefit of dynamic typing is that it enables a really nice interactive interpreter shell experience. I think it's also important from a prototyping standpoint that Python's static typing model does a lot of inference -- you don't have to add an explicit type annotation on every single variable.

[nyberg]

This is possible with statically typed languages with Haskell being one of the examples where it's encouraged to use the REPL to work towards a solution and/or qucikly test ideas without having to write unit tests or full program tests. Ocaml and friends fall within this category too and none require extensive type annotation due to type inference.

I feel that too much focus is on static languages like C/C++ where types become a chore and judging it on that rather than looking at the plenty of languages with type inference brought by ML-style languages.

[BeFlatXIII]

> languages like C/C++ where types become a chore

It's been a long while since I used those languages, but I remember the chore part wasn't so much of typing Int or String and more so having to care if it's an Int, Short, or Long or if the float is single or double precision. I believe that those micro-optimizations are no longer popular, but manually thinking low-level is not something I enjoy.

[loup-vaillant]

> I would argue that the really big benefit of dynamic typing is that it enables a really nice interactive interpreter shell experience.

I use the Python REPL quite often, and have non trivial experience with Lua’s. But the best experience I’ve ever got was with OCaml: I type the expression, or function definition, without giving type annotations, and I get the type of the result in the response.

You wouldn’t believe the number of bugs I caught just by looking at the type. Before I even start testing the function. And that’s when I don’t have an outright type error, which a dynamic language wouldn’t have caught — not before I start testing anyway.