Table of contents
PyPy
PyPy is a fast, compliant alternative implementation of the Python language (2.7.1).
As PyPy is an open source project, you can find more
open source alternatives and stats
on LibHunt.
Performance
PyPy is known for its superior execution speed and performance, often outperforming the standard CPython interpreter for many workloads thanks to its Just-in-Time (JIT) compilation strategy.
Compatibility
PyPy aims to be compatible with standard Python, so many programs and libraries that run on CPython should work on PyPy without or with minimal changes.
Memory Efficiency
Due to its garbage collection mechanism, PyPy often results in lower memory usage as compared to CPython, which can be beneficial for memory-intensive applications.
Concurrency
PyPy provides better support for concurrency, including potentially avoiding some of the Global Interpreter Lock (GIL) performance issues present in CPython.
We have collected here some useful links to help you find out if PyPy is good.
Check the traffic stats of PyPy on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of PyPy on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of PyPy's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of PyPy on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about PyPy on Reddit. This can help you find out how popualr the product is and what people think about it.
Gains than using either compiler alone. This uses the PyPy JIT framework to speed up a RISC-V simulator. https://pypy.org/ https://github.com/pydrofoil/pydrofoil Pydrofoil: A fast RISC-V emulator generated from the Sail model, using PyPy's JIT. - Source: Hacker News / about 2 months ago
"On average, PyPy is 4.4 times faster than CPython 3.7." https://pypy.org/. - Source: Hacker News / 7 months ago
If you're going the pure Python route, don't forget to try PyPy[1], an alternative JITed implementation of the language. A seriously underrated project, IMHO. Most time it speeds up execution by a factor of 2x-4x, but improvements of about two orders of magnitude are not unheard of. See for example [2]. Numeric, long-running code shoud suit PyPy optimizations well. [1] https://pypy.org/ [2]... - Source: Hacker News / 8 months ago
Python: My Python-foo is limited, so I only ported the last problem (a simple while loop) and ran it with PyPy. It takes a bit less of time:. - Source: dev.to / about 1 year ago
If you r looking for performance with almost fully supported C Extensions , pypy.org for you , 20x faster than cpython still. Source: over 2 years ago
I think you never heard of PyPy it is drop in replacable python written in Python and It is jit avg 5x faster than Python , 20x faster in some cases. Https://pypy.org. Source: about 3 years ago
Well, pypy is a thing. Of course, your overall point still stands. Source: over 3 years ago
Why don't they just sponsor pypy.org ? Its already 4x faster in average , 20x in many cases. We are using in 4 of our projects with one of them 10k active concurrent connections max , and its absolutely amazing. Its a realtime telemedince/chatroom (OnDoctor check in playstore). And we host it on 40$ Digital ocean machine. A lot less memory usage and so much faster. Source: about 4 years ago
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