wizer
hpy
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wizer | hpy | |
---|---|---|
10 | 20 | |
875 | 1,005 | |
3.4% | 1.3% | |
7.0 | 8.2 | |
13 days ago | about 2 months ago | |
Rust | Python | |
Apache License 2.0 | 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.
wizer
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RustPython
> once by the wasm runtime to compile the rust-python wasm
I'm not sure what you mean by that. The runtime doesn't compile WASM, it simply executes it.
There are tools for dealing with interpreter runtime overhead this by pre-initalizing the environment like Wizer[0]. ComponentizeJS[1] uses it to pre-initialize the Spidermoney engine it packages to gain fast startup times (and you can then prune the initialization only code with wasm-opt). As techniques like ComponentizeJS are also being applied for a specific set of interpreted files, you can even prune parts of the interpreter that would never be used for that specific program. If you want to go even further you could record specific execution profiles and optimize further by those.
[0]: https://github.com/bytecodealliance/wizer
[1]: https://github.com/bytecodealliance/ComponentizeJS
- Are V8 isolates the future of computing?
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Netlify Edge Functions: A new serverless runtime powered by Deno
Edge functions are typically run intermittently, with their runtime stopped to free up resources between runs. Therefore a big factor is startup and shutdown speed. Containers are pretty bad there. Deno is better, and WASM is unbeatable, especially with things like Wizer[0].
[0]https://github.com/bytecodealliance/wizer
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Building a WebAssembly-powered serverless platform
I imagine startup cost could be amortized by something like wizer: https://github.com/bytecodealliance/wizer
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Containerless! How to Run WebAssembly Workloads on Kubernetes with Rust
There are security benefits to running each request in its own instance, as it helps prevent accidental leaking of state between requests. To avoid doing lots of expensive initializations, we have a tool called wizer which lets users run their program's initialization once, create a snapshot, and then use that snapshot to do fast startups that don't rerun the whole initialization each time.
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Is it possible in Rust to save the complete state of a program and restore it later? Such as may be accomplished in some implementations of Common Lisp
See https://github.com/bytecodealliance/wizer for an implementation of this approach.
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Bytecode Alliance
It should probably be named "Making JavaScript to startup fast on WebAssembly", since the runtime speed is not really improved by the approach they exposed.
Besides that I think Wizer [1] is both an elegant and a simple solution to speed up startup speed with Wasm.
[1] - https://github.com/bytecodealliance/wizer#using-wizer-as-a-l...
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A JavaScript optimizing compiler
A similar project, for WebAssembly so with limited scope is this: https://github.com/bytecodealliance/wizer. And somehow similar but limited on LLVM IR a colleague worked on this for Cheerp (the compiler used here as backend): https://github.com/leaningtech/cheerp-meta/wiki/Cheerp-PreExecuter.
- Wizer: snapshot an initialized Wasm instance and save the result as a new, pre-initialized Wasm module. Up to 6x faster start up on my test workloads
- Wiser: snapshot an initialized Wasm instance and save the result as a new, pre-initialized Wasm module. Up to 6x faster start up on my test workloads
hpy
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RustPython
There is a merge request up to add autogen rust bindings to hpy
https://github.com/hpyproject/hpy/pull/457
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Ruby 3.2’s YJIT is Production-Ready
Are you referencing https://github.com/hpyproject/hpy?
I do hope it takes off.
- HPy - A better C API for Python
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Codon: A high-performance Python compiler
The HPy project [0] seems like a promising way out of this.
[0] https://hpyproject.org/
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New record breaking for Python in TechEmPower
socketify.py breaks the record for Python no other Python WebFramework/Server as able to reach 6.2 mi requests per second before in TechEmPower Benchmarks, this puts Python at the same level of performance that Golang, Rust and C++ for web development, in fact Golang got 5.2 mi req/s in this same round. Almost every server or web framework tries to use JIT to boost the performance, but only socketify.py deliveries this level of performance, and even without JIT socketify.py is twice as fast any other web framework/server in active development, and still can be much more optimized using HPy (https://hpyproject.org/). Python will get even faster and faster in future!
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Is it time to leave Python behind? (My personal rant)
I think Propose a better messaging for Python is the option and a lot of languages will learn it from Rust, because rust erros are the best described errors I see in my life lol. Cargo is amazing and I think we will need a better poetry/pip for sure, HPy project will modernize extensions and packages 📦 too https://hpyproject.org/
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A Look on Python Web Performance at the end of 2022
It also show that PyPy3 will not magically boost your performance, you need to integrate in a manner that PyPy3 can optimize and delivery CPU performance, with a more complex example maybe it can help more. But why socketify is so much faster using PyPy3? The answer is CFFI, socketify did not use Cython for integration and cannot delivery the full performance on Python3, this will be solved with HPy.
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socketify.py - Bringing WebSockets, Http/Https High Peformance servers for PyPy3 and Python3
HPy integration to better support CPython, PyPy and GraalPython
- HPy: A better C API for Python
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Your Data Fits in RAM
Absolutely everything in CPython is a PyObject, and that can’t be changed without breaking the C API. A PyObject contains (among other things) a type pointer, a reference count, and a data field; none of these things can be changed without (again) breaking the C API.
There have definitely been attempts to modernize; the HPy project (https://hpyproject.org/), for instance, moves towards a handle-oriented API that keeps implementation details private and thus enables certain optimizations.
What are some alternatives?
quickjs-emscripten - Safely execute untrusted Javascript in your Javascript, and execute synchronous code that uses async functions
nogil - Multithreaded Python without the GIL
TablaM - The practical relational programing language for data-oriented applications
graalpython - A Python 3 implementation built on GraalVM
wasmtime - A fast and secure runtime for WebAssembly
py2js
go - The Go programming language
cinder - Cinder is Meta's internal performance-oriented production version of CPython.
go-wasm-bake - Experimenting with eager evaluation of Go WASM code
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
wagi - Write HTTP handlers in WebAssembly with a minimal amount of work
pgcopy - fast data loading with binary copy