Ammonite-Ops VS pytype

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 open source! check out https://github.com/google/pytype and https://github.com/google/pytype/blob/main/docs/developers/t... for more on the multi-file runner

Pytype checks and infers types for your Python code - without requiring type annotations. Pytype can catch type errors in your Python code before you even run it.

Pyre from Meta, pyright from Microsoft and PyType from Google provide additional assistance. They can 'infer' types based on code flow and existing types within the code.

we've written a little bit about what pytype does differently here: https://google.github.io/pytype/

our main focus is to be able to work with unannotated and partially-annotated code, and treat it on par with fully annotated code.

So, I tried out pytype the other day, and it was a not a good experience. It doesn't support PEP 420 (implicit namespace packages), which means you have to litter __init__.py files everywhere, or it will create filename collisions. See https://github.com/google/pytype/issues/198 for more information. I've since started testing out pyre.

What is the smart money doing for type checking in Python? I've used mypy which seems to work well but is incredibly slow (3-4s to update linting after I change code). I've tried pylance type checking in VS Code, which seems to work well + fast but is less clear and comprehensive than mypy. I've also seen projects like pytype [1] and pyre [2] used by Google/Meta, but people say those tools don't really make sense to use unless you're an engineer for those companies.

Am just curious if mypy is really the best option right now?

[1] https://github.com/google/pytype

At Luma, we're using mypy to check nearly our entire code-base, including our Maya-related code, thanks to these latest changes. Fully adopting mypy (or an alternative like pytype) is no small feat, but working within a fully type-annotated code base with a type checker to enforce accuracy is like coding in a higher plane of existence: fewer bugs, easier code navigation, faster dev onboarding, easier refactoring, and dramatically increased confidence about every change. I wrote about some deeper insights in these posts.

Check out https://github.com/google/pytype

i work on https://github.com/google/pytype which is largely developed internally and then pushed to github every few days. the github commits are associated with the team's personal github accounts. pytype is not an "official google product" insofar as the open source version is presented as is without official google support, but it is "production code" in the sense that it is very much used extensively within google.

pytype dev here - thanks for the kind words :) whole-program analysis on unannotated or partially-annotated code is our particular focus, but there's surprisingly little dark PLT magic involved; in particular you don't need to be an academic type theory wizard to understand how it works. our developer docs[1] have more info, but at a high level we have an interpreter that virtually executes python bytecode, tracking types where the cpython interpreter would have tracked values.

it's worth exploring some of the other type checkers as well, since they make different tradeoffs - in particular, microsoft's pyright[2] (written in typescript!) can run incrementally within vscode, and tends to add new and experimentally proposed typing PEPs faster than we do.

[1] https://github.com/google/pytype/blob/main/docs/developers/i...