cinder
FrameworkBenchmarks
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cinder | FrameworkBenchmarks | |
---|---|---|
43 | 366 | |
3,375 | 7,378 | |
0.8% | 1.1% | |
9.4 | 9.8 | |
about 17 hours ago | 6 days ago | |
Python | Java | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
cinder
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Meta Used Monolithic Architecture to Ship Threads in Only Five Months
Meta is actually contributing directly to upstream cpython. If you really wanted to, the internal fork is also open source: https://github.com/facebookincubator/cinder
- Meta pledges Three-Year sponsorship for Python if GIL removal is accepted
- Back end of Meta Threads is built with Python 3.10 with some interesting tweaks
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Lessons from Mojo for PHP 10+ ?
Just one example: last year Meta open-sourced Cinder, which powers Instagram and provides sizeable speedups compared to CPython.
- Python true static typing
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Best book on writing an optimizing compiler (inlining, types, abstract interpretation)?
I used to work on the Cinder JIT and can help document any passes you find interesting or confusing.
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Python-based compiler achieves orders-of-magnitude speedups
You might enjoy Cinder then. It's based on CPython so it is nearly 100% compatible.
https://github.com/facebookincubator/cinder/
Disclaimer: I used to work on it.
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beartype: It has documentation now. It only took two years, my last hair follicle, precious sanity points (SPs), and working with Sphinx. Don't be like @leycec. Go hard on documentation early.
I think Cinder's Static Python, which also performs runtime type checking, is more ambitious. Though it's not production ready yet.
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If there’s gonna be a Python 4.0 one day, what’s a breaking change you’d like to see? Let’s explore the ideas you have that can make Python even better!
Here's a fork that implements that https://github.com/facebookincubator/cinder - it might be nice to one day get that up streamed but obviously it'll be controversial and it certainly needs more time to bake. Hopefully at some point we can make it a pip installable extension though.
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Is it time for Python to have a statically-typed, compiled, fast superset?
The other thing that was interesting to me, was the potential of type annotations to help make for a faster, safer experience on the compiler end of things. One example is seen in Meta’s Cinder project, on the docs it explains how typing can be used to reduce the number of steps for the compiler ([cinder/static_python.rst at cinder/3.8 · facebookincubator/cinder · GitHub](https://github.com/facebookincubator/cinder/blob/cinder/3.8/CinderDoc/static_python.rst)), making it more effective.
FrameworkBenchmarks
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Why choose async/await over threads?
Neat. Thanks for sharing!
Interestingly, may-minihttp is faring very well in the TechEmpower benchmark [1], for whatever those benchmarks are worth. The code is also surprisingly straightforward [2].
[1] https://www.techempower.com/benchmarks/
[2] https://github.com/TechEmpower/FrameworkBenchmarks/blob/mast...
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Ntex: Powerful, pragmatic, fast framework for composable networking services
ntex was formed after a schism in actix-web and Rust safety/unsafety, with ntex allowing more unsafe code for better performance.
ntex is at the top of the TechEmpower benchmarks, although those benchmarks are not apples-to-apples since each uses its own tricks: https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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A decent VS Code and Ruby on Rails setup
Ruby is slow. Very slow. How much you may ask? https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s... fastest Ruby entry is at 272th place. Sure, top entries tend to have questionable benchmark-golfing implementations, but it gives you a good primer on the overhead imposed by Ruby.
It is also not early 00s anymore, when you pick an interpreted language, you are not getting "better productivity and tooling". In fact, most interpreted languages lag behind other major languages significantly in the form of JS/TS, Python and Ruby suffering from different woes when it comes to package management and publishing. I would say only TS/JS manages to stand apart with being tolerable, and Python sometimes too by a virtue of its popularity and the amount of information out there whenever you need to troubleshoot.
If you liked Go but felt it being a too verbose to your liking, give .NET a try. I am advocating for it here on HN mostly for fun but it is, in fact, highly underappreciated, considered unsexy and boring while it's anything but after a complete change of trajectory in the last 3-5 years. It is actually the* stack people secretly want but simply don't know about because it is bundled together with Java in the public perception.
*productive CLI tooling, high performance, works well in a really wide range of workloads from low to high level, by far the best ORM across all languages and back-end framework that is easier to work with than Node.JS while consuming 0.1x resources
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The Erlang Ecosystem [video]
Although that seems to have improved in recent years.
https://www.techempower.com/benchmarks/#hw=ph&test=json§...
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Ruby 3.3
RoR and whatever C++ based web backend there is count as a valid comparison in my book. But comparing the languages itself is maybe a bit off.
On a side note, you can actually compare their performance here if you’re really curious. But take it with a grain of salt since these are synthetic benchmarks.
https://www.techempower.com/benchmarks
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API: Go, .NET, Rust
Most benchmarks you'll find essentially have someone's thumb on the scale (intentionally or unintentionally). Most people won't know the different languages well enough to create comparable implementations and if you let different people create the implementations, cheating happens. The TechEmpower benchmarks aren't bad, but many implementations put their thumb on the scale (https://www.techempower.com/benchmarks). For example, a lot of the Go implementations avoid the GC by pre-allocating/reusing structs or allocate arrays knowing how big they need to be in advance (despite that being against the rules). At some point, it becomes "how many features have you turned off." Some Go http routers (like fasthttp and those built off it like Atreugo and Fiber) aren't actually correct and a lot of people in the Go community discourage their use, but they certainly top the benchmarks. Gin and Echo are usually the ones that are well-respected in the Go community.
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Rage: Fast web framework compatible with Rails
There is certainly a lot of speculation in Techempower benchmarks and top entries can utilize questionable techniques like simply writing a byte array literal to output stream instead of constructing a response, or (in the past) DB query coalescing to work around inherent limitations of the DB in case of Fortunes or DB quries.
And yet, the fastest Ruby entry is at 274th place while Rails is at 427th.
https://www.techempower.com/benchmarks/#hw=ph&test=fortune&s...
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Node.js – v20.8.1
oh what machine? with how many workers? doing what?
search for "node" on this page: https://www.techempower.com/benchmarks/#section=data-r21
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Strong typing, a hill I'm willing to die on
JustJS would like a word https://www.techempower.com/benchmarks/#section=data-r20&tes...
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Rust vs Go: A Hands-On Comparison
In terms of RPS, this web service is more-or-less the fortunes benchmark in the techempower benchmarks, once the data hits the cache: https://www.techempower.com/benchmarks/#section=data-r21
Or, at least, they would be after applying optimizations to them.
In short, both of these would serve more rps than you will likely ever need on even the lowest end virtual machines. The underlying API provider will probably cut you off from querying them before you run out of RPS.
What are some alternatives?
faster-cpython - How to make CPython faster.
zio-http - A next-generation Scala framework for building scalable, correct, and efficient HTTP clients and servers
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
drogon - Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows [Moved to: https://github.com/drogonframework/drogon]
Pyjion
django-ninja - 💨 Fast, Async-ready, Openapi, type hints based framework for building APIs
graalpython - A Python 3 implementation built on GraalVM
LiteNetLib - Lite reliable UDP library for Mono and .NET
MonkeyType - A Python library that generates static type annotations by collecting runtime types
C++ REST SDK - The C++ REST SDK is a Microsoft project for cloud-based client-server communication in native code using a modern asynchronous C++ API design. This project aims to help C++ developers connect to and interact with services.
hpy - HPy: a better API for Python
SQLBoiler - Generate a Go ORM tailored to your database schema.