truffleruby
pyre-check
truffleruby | pyre-check | |
---|---|---|
25 | 24 | |
2,963 | 6,695 | |
0.1% | 0.5% | |
9.9 | 9.9 | |
4 days ago | 3 days ago | |
Ruby | OCaml | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
truffleruby
- TruffleRuby 24.0.0
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Mir: Strongly typed IR to implement fast and lightweight interpreters and JITs
I think it would be worth mentioning GraalVM and https://github.com/oracle/truffleruby in competitors section.
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GraalVM for JDK 21 is here
GitHub page has some info: https://github.com/oracle/truffleruby#current-status
My question is, how viable is TruffleRuby vs JRuby?
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Making Python 100x faster with less than 100 lines of Rust
I wonder why GraalVM is not more often used for these speed critical cases: https://www.graalvm.org/python/
Is the problem the Oracle involvement? (Same for ruby https://www.graalvm.org/ruby/)
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Ruby 3.2’s YJIT is Production-Ready
Looks like it’s still a WIP
https://github.com/oracle/truffleruby/commits?author=eregon
- Implement Pattern Matching in TruffleRuby (GSoC)
- TruffleRuby – GraalVM Community Edition 22.2.0
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Modern programming languages require generics
this comes at the cost of boxing ints inside Integer, though.
So, if you ignore for a moment primitives types, whenever you have generics, everything boils down to a single method accepting Objects and returning Objects. What the JVM does is to do runtime profiling of what actually you are passing to the generic method, and generate optimized routines for the "best case". In theory this is the best of the two worlds, because like in general you will have a single implementation of the method (avoiding duplication of the code), but if you use it in an hot spot you get the optimized code.
In a way, it is quite wasteful, because you throw away a lot of information at compile time, just to get it back (and maybe not all of it) at runtime through profiling, but in practice it works quite well.
A side effect of this is this makes the JVM a wonderful VM for running dynamic languages like Ruby and Python, because that information is _not_ there at compile time. In particular GraalVM/TruffleVM and exposes this functionality to dynamic language implementations, allowing very good performance (according to they website [1][2], Ruby and Python on TruffleVM are about 8x faster than the official implementation, and JS in line with V8)
[1] https://www.graalvm.org/ruby/
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GraalVM 22.1: Developer experience improvements, Apple Silicon builds, and more
I opened a ticket some time ago about performance with Jekyll and liquid templates. At least in that case, yjit was way faster. I'm happy to retest though. Anything that would make my jekyll builds faster would help.
https://github.com/oracle/truffleruby/issues/2363
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Ruby YJIT Ported to Rust
Here's a benchmark [1] done in Jan'22 against many ruby implementations, truffleRuby [2] seems to be way ahead in most, and at least ahead in all. Why truffleRuby isn't talk about much here?
[1] https://eregon.me/blog/2022/01/06/benchmarking-cruby-mjit-yj...
[2] https://github.com/oracle/truffleruby
pyre-check
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Pylyzer – A fast static code analyzer and language server for Python
Did you come across pyre in your search? MIT license and pretty fast.
https://github.com/facebook/pyre-check
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Enhance Your Project Quality with These Top Python Libraries
Pyre is a performant type-checker developed by Facebook. Pyre can analyse codebases with millions of lines of code incrementally – providing instantaneous feedback to developers as they write code.
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
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.
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Ruff v0.1.0
Have you seen Pyre[0]? Not Rust, OCaml, and pretty fast. Made by a team at Meta and open sourced on GitHub. If you use python-lsp, I wrote an extension[1] to enable integration (though I haven't tested it recently, been programming in rust; it is mostly a "for me" extension).
0: https://pyre-check.org/
1: https://github.com/cricalix/python-lsp-pyre
- Should I Rust or should I Go
- Writing Python like it's Rust
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Buck2, a large scale build tool written in Rust by Meta, is now available
Internally we use Pyre for Python type checking: https://github.com/facebook/pyre-check
- Are there any sectors that use Haskell as a main programming language?
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It is becoming difficult for me to be productive in Python
Before type hinting, work had intense rules and linters enforcing docstrings with types. Now, type hints and automatic pyre runs take care of all the heavy lifting.
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Ruby 3.2’s YJIT is Production-Ready
Python now has an optional type system and if you add one of them such as mypy or pyre to your CI process and you can configure GitHub to refuse the pull request until types are added you can make it somewhat strongly typed.
If you have a preexisting codebase I believe the way you can convert it is to add the types that you know on commits and eventually you will have enough types that adding the missing ones should be easy. For the missing ones Any is a good choice.
https://pyre-check.org and https://github.com/python/mypy are popular.
What are some alternatives?
JRuby - JRuby, an implementation of Ruby on the JVM
pyright - Static Type Checker for Python
artichoke - 💎 Artichoke is a Ruby made with Rust
mypy - Optional static typing for Python
graalpython - A Python 3 implementation built on GraalVM
pytype - A static type analyzer for Python code
ruby-packer - Packing your Ruby application into a single executable.
typeshed - Collection of library stubs for Python, with static types
graaljs - A ECMAScript 2023 compliant JavaScript implementation built on GraalVM. With polyglot language interoperability support. Running Node.js applications!
flake8
clj-kondo - Static analyzer and linter for Clojure code that sparks joy
typing - Python static typing home. Hosts the documentation and a user help forum.