Yet another "X faster than Y" where inside X all hot jobs are done by really good-tuned C or C++. Facepalm.
Without real problem-solving (business logic) written in Python, this is only lightweight wrapper on C/C++. When the number of Python code start growing in the hot path, then these blazing-amazing thruput numbers tremendously will be going down.
Why is it a sham? It's useful to know that x is faster. As a user of x I don't really care if the reason it's faster is it's C++ under the hood. That's really an implementation detail for me.
Because it's measuring a scenario that's not representative of real usages of X and is usually tweaked for the framework/tool the author is trying to showcase.
For example: all the deno/bun benchmarks often use the Node.js frameworks in an unnecessarily slow way and don't measure apples to apples. (like using uWS in bun but not uWS for Node in the benchmark).
This one in particular just measures the speed of "hello world" in plaintext and JSON with very specific parameters.
What happens when you use X because it's fast at one thing in a microbenchmark, but it locks you into an environment that is slow at the rest of your program?
The real thing will be some mix of your code and the library's code, and in cases like this where you'd be writing all your logic in Python vs Golang, that will have a significant effect on the results.
A while back I implemented a game rules engine and MCTS in Torch (the Lua library). The training loop spent like half of its time running the rules engine. Writing it in Python would have been a disaster in comparison. To really make good use of the hardware and spend more time in the optimized machine learning code provided by libraries, one would have to write their rules engine in some language other than Lua or Python.
Because the moment you actually write any server or business logic in Python performance drops off a cliff and it doesn't differ significantly from any of the other Python web frameworks.
> Yet another "X faster than Y" where inside X all hot jobs are done by really good-tuned C or C++. Facepalm.
This is the case for basically every programming language or performant library that exists. Yet, I never see this when discussions exists about node libraries or other languages for that matter. I mean you could argue that node itself is just a thin wrapper around fast C++ libraries.
Who the fuck cares if the request goes down to some compiled C++ library? I still write my logic in Python and get this benefit anyway. This is what makes it great.
> Yet, I never see this when discussions exists about node libraries or other languages for that matter.
Huh? It's the first comment for pretty much any of these stupid performance comparisons. Does someone really think node performance is great, or pick node because of its performance?
> I still write my logic in Python and get this benefit anyway.
That's part of the point. Writing your logic in Python is fine, but then your app performance isn't winning any comparisons. No one cares about the performance this article is explicitly talking about.
I think the issue is that there is three different types of people when it comes to performance.
There is the 1% that are in a need of hard realtime performance, that thinks about GC performance as an issue that needs to be adressed. Sure I can get that for these people, these kind of discussions seems stupid and confusing since they have to develop in C/C++, Rust etc to get the pure performance they need. These people probably aren't in this thread because they know that Python is not a language for them and will never be.
Then there is the 99% crowd, which I am a part of, that could use slow-as-shit frameworks like Rails or Laravel because the performance is just a nice-to-have. These people, like myself, compares Python perf to perhaps PHP or Node because they are fast enough languages and in this kind of league a framework like OPs can make a huge difference. No matter what language you pick here you are basically always using something "beneth" it. Node has been picked by many because it's faster than for example Python and Ruby.
Then there is the people who are part of the 99% crowd but are just have to comment and point the needs of the 1% out because they are negative people who probably produce little themselves and have to hate on what other people create and distribute for free. This group is where most haters on HN belong in. :)
I started in PHP, when I went to Node in the early beginning I was deeply impressed by the great performance and nice features it had. Sure it was built upon C++ libraries but I am never gonna use C++ to write my web api. Still, I could use Node and get 2-3x AT LEAST the performance in all of my endpoints because of this and all my code was in javascript.
What I am trying to say is that I don't care if you pack my code and run it on a computer in Minecraft or your calculator, if it runs faster for very little to no pain on my side that is pure joy to me.
NodeJS might be slow, but it still is orders of magnitude faster than any interpreted or JIT Python implementation. I agree that no one really chooses Node because it is fast, but I think they choose it because it is fast _enough_ whereas if using Python you'd probably find multiple performance bottlenecks that could be show-stoppers.
> Who the fuck cares if the request goes down to some compiled C++ library?
The way this is titled, you know someone will read this as "Python can be faster than go" and influence their decision when it comes to performance ; that's actually why I clicked on that, thinking "how the hell did they achieve faster speed with Python".
Well, it could be true IMHO. If I run my code that calls down to some ultra fast, mega well done C++ library that is much better than anything in the Go community my code then completes requests faster than the Go alternative.
If that is the case, that should influence the decision when it comes to performance. If performance is a very important deal in your app, you have to test this yourself so that you reach the performance you need.
Perhaps you can write C++ extensions to Python for the perf-heavy parts yourself instead of having to write the entire application in a language that takes much longer time to develop in?
I think this is correct and does demonstrate that these comparisons are not all that useful.
But I also think that writing Python and then dropping down into C or C++ for performance is perfectly valid and often a great idea. Of course, there's nothing wrong with just using a different language that's a sensible middle ground between Python and C (like Go). But hold on to the baby when that bathwater is being dumped: there's nothing wrong with writing a blend of Python and C++ for real uses.
Would golang interfaced with the C++ implemenation be as fast? IMO one of the nice features of Python is being able to seamlessly drop to numba, or a C++ module when you need an optimized fastpath, but the rest of your application, the bulk of it, need not.
Without real problem-solving (business logic) written in Python, this is only lightweight wrapper on C/C++. When the number of Python code start growing in the hot path, then these blazing-amazing thruput numbers tremendously will be going down.