japronto
Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser. (by squeaky-pl)
hpy
HPy: a better API for Python (by hpyproject)
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| japronto | hpy | |
|---|---|---|
| 3 | 20 | |
| 8,624 | 1,005 | |
| - | 1.3% | |
| 0.0 | 8.2 | |
| 9 months ago | about 2 months ago | |
| C | Python | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
japronto
Posts with mentions or reviews of japronto.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-06.
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
100x faster than FastAPI seems easy. I wonder how it compares to other fast Python libraries like Japronto[1] and non-Python ones too.
1 - https://github.com/squeaky-pl/japronto
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A Look on Python Web Performance at the end of 2022
The source code from the project resides in the github, with more than 8.6k stars and 596 forks is a very popular github, but no new releases are made since 2018, looks pure much not maintained anymore, no PR's are accepted no Issues are closed, still without windows or macOS Silicon, or PyPy3 support. Japronto it self uses uvloop with more than 9k stars and 521 forks and different from japronto is seems to be well maintained.
- Screaming-fast, scalable, asynchronous Python 3.5 HTTP toolkit
hpy
Posts with mentions or reviews of hpy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-02-07.
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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 3.2βs 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 π¦ 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 canβt 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?
When comparing japronto and hpy you can also consider the following projects:
socketify.py - Bringing Http/Https and WebSockets High Performance servers for PyPy3 and Python3
nogil - Multithreaded Python without the GIL
vibora - Fast, asynchronous and elegant Python web framework.
graalpython - A Python 3 implementation built on GraalVM
yyjson - The fastest JSON library in C
py2js
oha - Ohayou(γγ―γγ), HTTP load generator, inspired by rakyll/hey with tui animation.
cinder - Cinder is Meta's internal performance-oriented production version of CPython.
json_benchmark - Python JSON benchmarking and "correctness".
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
json-buffet
pgcopy - fast data loading with binary copy