|
|
|
|
|
by kerkeslager
2205 days ago
|
|
1. I don't agree with your conclusion that it's Python specific. You don't have evidence for that--you made that up. And no I'm not interested in whatever benchmark you're going to want to post, because it's not a test of this situation--it cannot possibly be, because when you introduce JS, you're also going to be introducing literally hundreds of other factors which could affect the performance. The assertion you are making is not one you can possibly know. 2. For this specific test, there is a downside to async, as shown by the test. Even if what's going on here were Python-specific (which is still something you made up), downsides to async which only occur in a Python environment are still downsides to async. The title of this post is "Async Python is not faster"--that conclusion is incorrect for many reasons, but none of those reasons include the words "NodeJS", "JS", or anything else that is not in the Python ecosystem. 3. What is going on is probably specific to the tools being used, which is why I said "those downsides certainly don't apply to every project". In fact, they probably don't apply to the idiomatic ways of implementing this in Tornado, for example. But note how I said "probably" because I don't know for sure, and I'm not comfortable with making things up and stating them as facts. |
|
That's rude.
Let's put it this way. NodeJS and nginx leveled the playing field. It destroyed the lamp stack and made async the standard way of handling high loads of IO. From that alone it should indicate to you that there is something very wrong with how you're thinking about things.
You know the theory of asyncio? Let me restate it for you: If coroutines are basically the SAME thing as routines but with the extra ability to allow tasks to be done in parallel with IO then what does that mean?
It means that 5 async workers in theory should be more performant than 5 sync workers FOR highly concurrent IO tasks.
The logic is inescapable.
So what does it mean, if you run tests and see that 5 async workers are NOT more performant than 5 sync workers ON PYTHON exclusively? The theory of asyncio makes perfect logical sense right? So what is logically the problem here?
The problem IS PYTHON. That's a theorem derived logically. No need for evidence or data driven techniques.
There's this idea that data drives the world and you need evidence to back everything up. How many data points do you need to prove 1 + 1 = 2? Put that in your calculator 200 times and you got 200 data points. Boom data driven buzzword. That's what you're asking from me btw. A benchmark, a datapoint to prove what is already logical. Then you hilariously decided to dismiss it before i even presented it.
Look, I say what I say not from evidence, but from logic. I can derive certain issues about the system from logic. You just follow the logic I gave you above and tell me where it went wrong and why do I need some dumb data point to prove 1+1=2 to you?
There is NOTHING made up above. It is pure logic derived from the assumption of what AsyncIO is doing.
>But note how I said "probably" because I don't know for sure, and I'm not comfortable with making things up and stating them as facts.
But you seem perfectly comfortable in being rude and accusing me of making stuff up. I'm not comfortable in going around the internet and trashing other peoples theories with accusations that they are making shit up. If you disagree say it, I respect that. I don't respect the part where you're saying I'm making stuff up.