[yomismoaqui]

Also they used languages with dynamic typing like Python & JS. In my experience a statically typed codebase is easier to maintain for humans so maybe it is also for agents.

When using Codex/Claude Code with Go code I cannot count the times the agent does some change, runs a build to check for errors, find some and fix them.

[__mharrison__]

Just have your harness rules add types and run ty after every change. Models handle Python typing quite well these days.

[acbart]

It's crazy to me that people think of Python as dynamically typed by default. Strong static typing has been an option in Python for years now, and it should just be the default.

[mrob]

>Strong static typing has been an option in Python for years now, and it should just be the default.

https://docs.python.org/3/library/typing.html

"The Python runtime does not enforce function and variable type annotations. They can be used by third party tools such as type checkers, IDEs, linters, etc."

Which third-party enforcement mechanism do you propose become the default?

[shepherdjerred]

There are plenty of options for static type checking in Python. Choose your favorite or just use Ty

[epgui]

The python type hints are useful for static analysis (and yes, should be the default) but it’s a joke compared to the utility of types in a language like Haskell.

[shepherdjerred]

If you're comparing type systems against Haskell you're excluding all mainstream languages except maybe Scala and Rust

[epgui]

Yes.

[antonvs]

Typing with tools like Pyright doesn't come close to providing what a good statically typechecked language provides.

There are many reasons for this. A big one is that many libraries are only partially typed at best, and dynamic types tend to propagate, weakening the guarantees you get from type checking.

Dynamic idioms in general, including something as common as string-indexed dictionaries, negate type checking. Runtime metaprogramming is the same. All of these things have equivalents in a good statically checked language, but Python doesn't follow those models.

Fundamentally, in Python static typing is an optional analysis layer over a dynamic language, and the consequences of that can't be fully mitigated. The result is a big difference in what types can guarantee.

[shepherdjerred]

TypeScript had this _exact_ same problem when it started out. As more libraries add annotations, the ecosystem will become stronger, and it will eventually be about as good as a "real" statically typed language.

> Dynamic idioms in general, including something as common as string-indexed dictionaries, negate type checking.

Do you have any proof of this? It hasn't been a problem in TypeScript, and I doubt it's an issue in Python