Ammonite-Ops VS mypy

The indent based syntax is only available in Scala 3, you have to download a matching ammonite version from https://github.com/com-lihaoyi/Ammonite/releases

That's funny, because this is what I really like about Scala; how quick and easy it is to get a project started.

> sbt new scala/scala3.g8

will just create an empty project. If you don't even want to bother with a project, use use scala-cli or ammonite (http://ammonite.io/) to just start banging out code.

Even the upgrading of a project from Scala2 to Scala3 is a breeze, thanks to very good backwards compatibility of new library releases.

Ammonite is a very good REPL for Scala. You can invoke it with amm and type expressions into it, or load a Scala “script file” whose name ends with .sc into it, or many other things. It’s documented at https://ammonite.io. 2. sbt is the dominant build tool for Scala projects. As others have commented, when you open a folder in Visual Studio Code and try to make Metals “aware of it,” it expects to find a “Scala project” in the folder. A “Scala project” isn’t just Scala source code. See https://www.scala-sbt.org for details. 3. Also be aware that Metals supports worksheets, so you can easily experiment with code in your project interactively, too.

Scripting API is quite limited, so the third option. - reuse the ammonite scripts https://github.com/com-lihaoyi/Ammonite or look how this is implemented (using internal compiler API),

Your exposure to Functional Programming with Haskell and Clojure suggest you will certainly pick up Scala quickly. With ZIO and cats, you can write robust software quickly. Consider the excellent Coursera Scala course. Get "the Red Book" https://www.manning.com/books/functional-programming-in-scala, and most important, play. Experiment to see how things work. Get https://ammonite.io/

Here's an example of a smaller project that added telemetry without suffering a fork:

https://github.com/com-lihaoyi/Ammonite/issues/607

Or ammonite - I've ran Gatling performance test from a simple script based on this gist it fetches all the dependencies, compiles and runs the test, producing nice html report..

Scala with the Typelevel ecosystem. Stay on the jVM, but have a much more pleasant and robust experience, including a great REPL.

It's got type annotations and mypy has a discussion about it here as well: https://github.com/python/mypy/issues/1282

There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.

And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.

And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.

[0] https://nuitka.net/

[1] https://github.com/python/mypy/tree/master/mypyc

In Python there is MyPy that can help with this. https://www.mypy-lang.org/

It's funny you should say this.

Reading this article prompted me to future-proof a program I maintain for fun that deals with time; it had one use of utcnow, which I fixed.

And then I tripped over a runtime type problem in an unrelated area of the code, despite the code being green under "mypy --strict". (and "100% coverage" from tests, except this particular exception only occured in a "# pragma: no-cover" codepath so it wasn't actually covered)

It turns out that because of some core decisions about how datetime objects work, `datetime.date.today() < datetime.datetime.now()` type-checks but gives a TypeError at runtime. Oops. (cause discussed at length in https://github.com/python/mypy/issues/9015 but without action for 3 years)

One solution is apparently to use `datetype` for type annotations (while continuing to use `datetime` objects at runtime): https://github.com/glyph/DateType

PEP 695 is great. I've been using mypy every day at work in last couple years or so with very strict parameters (no any type etc) and I have experience writing real life programs with Rust, Agda, and some Haskell before, so I'm familiar with strict type systems. I'm sure many will disagree with me but these are my very honest opinions as a professional who uses Python types every day:

* Some types are better than no types. I love Python types, and I consider them required. Even if they're not type-checked they're better than no types. If they're type-checked it's even better. If things are typed properly (no any etc) and type-checked that's even better. And so on...

* Having said this, Python's type system as checked by mypy feels like a toy type system. It's very easy to fool it, and you need to be careful so that type-checking actually fails badly formed programs.

* The biggest issue I face are exceptions. Community discussed this many times [1] [2] and the overall consensus is to not check exceptions. I personally disagree as if you have a Python program that's meticulously typed and type-checked exceptions still cause bad states and since Python code uses exceptions liberally, it's pretty easy to accidentally go to a bad state. E.g. in the linked github issue JukkaL (developer) claims checking things like "KeyError" will create too many false positives, I strongly disagree. If a function can realistically raise a "KeyError" the program should be properly written to accept this at some level otherwise something that returns type T but 0.01% of the time raises "KeyError" should actually be typed "Raises[T, KeyError]".

* PEP 695 will help because typing things particularly is very helpful. Often you want to pass bunch of Ts around but since this is impractical some devs resort to passing "dict[str, Any]"s around and thus things type-check but you still get "KeyError" left and right. It's better to have "SomeStructure[T]" types with "T" as your custom data type (whether dataclass, or pydantic, or traditional class) so that type system has more opportunities to reject bad programs.

* Overall, I'm personally very optimistic about the future of types in Python!

[1] https://github.com/python/mypy/issues/1773

# is fixed: https://github.com/python/mypy/issues/12987.

You probably already know but you can add type hints and then check for consistency with https://github.com/python/mypy in python.

Modern Python with things like https://learnpython.com/blog/python-match-case-statement/ + mypy + Ruff for linting https://github.com/astral-sh/ruff can get pretty good results.

I found typed dataclasses (https://docs.python.org/3/library/dataclasses.html) in python using mypy to give me really high confidence when building data representations.