"Consider using an unstable package manager" is a really really rough start.
additional: "However, writing your own code that involves async functions", your code does use async functions, its just monkey patched into your program because you used green threads instead.
> "Consider using an unstable package manager" is a really really rough start.
You can use poetry instead.
Poetry is stable.
I wish `uv` was version 1.0 or later.
However, despite it not being version 1.0 yet, I do see that it provides a superior experience for me to switch from `poetry` to `uv` and to make that recommendation after adding the pre-version 1.0 caveat.
People get so hung up on the version number. These fools would rather use software with tons of bugs and security holes simply because the devs of that software dared to use a version number greater than 1.0.
I see the entire community gravitating towards uv because of its merits. I tried it, and I agree. I already started using it for every project. I’ve even converted older projects to it.
The fact is that language matters, and the version number is a way to communicate the developers’ perception of how suitable something is for use. If they refuse to label it as 1.0, it means either: they don’t think it’s in a stable state yet, or they don’t realize the importance of this type of communication. Either way, it’s a red flag for people who might otherwise be making a large investment in time/money into using something.
It’s not feasible for everyone to do a full evaluation of everything. At some point you need to rely on an expert to at least provide some basic assurances before spending time on digging deeper.
No. I’m speaking in the general sense not to get hung up on an arbitrary number as the sole indicator of whether software is suitable for use in a production environment.
Multithreading is not a prerequisite for async in Python. The default task executor runs in a single thread. So using async APIs should be safe as long as you stick to the single-threaded executor.
Well, you can even block event loop in `async def` if you are not careful. When you are using `async def` you need to do all your IO (disk, network) operations asynchronously or your are blocking the event loop.
It sounds like the author makes a blanket claim to avoid asynchronous functions, even when using an inherently asynchronous web framework (FastAPI), which would negate any FastAPI asynchronous concurrency gains.
> It sounds like the author makes a blanket claim to avoid asynchronous functions, even when using an inherently asynchronous web framework (FastAPI), which would negate any FastAPI asynchronous concurrency gains.
FastAPI is faster than the other popular framework, Flask (I posted data supporting that), even without using async.
I only suggested that one should use their discretion when using async.
But for certain use-cases, as mentioned in the article itself, it is unavoidable.
Further, you might be working at a company that has decided to use Python, and you can make Python more efficient and effective using these suggestions.
additional: "However, writing your own code that involves async functions", your code does use async functions, its just monkey patched into your program because you used green threads instead.
You can use poetry instead. Poetry is stable.
I wish `uv` was version 1.0 or later. However, despite it not being version 1.0 yet, I do see that it provides a superior experience for me to switch from `poetry` to `uv` and to make that recommendation after adding the pre-version 1.0 caveat.
I see the entire community gravitating towards uv because of its merits. I tried it, and I agree. I already started using it for every project. I’ve even converted older projects to it.
It’s not feasible for everyone to do a full evaluation of everything. At some point you need to rely on an expert to at least provide some basic assurances before spending time on digging deeper.
Can you share a scenario where this would happen?
I have deployed multiple machine learning and data analytics-focused web services, and this has never happened to me.
Blocking python can’t.
An example is running multiprocesses and parsing their output and looking for patterns. Async python does this sort of thing well.
FastAPI is faster than the other popular framework, Flask (I posted data supporting that), even without using async.
I only suggested that one should use their discretion when using async.
When did I suggest not to write async code?
A lot of the world runs just find on Python (see Django), async is mature and stable.
I never claimed that one should not use `async`, I am only suggesting that be careful about using `async`.
In my experience, a median Go programmer is more comfortable with Go routines than a median Python programmer is with async functions. YMMV.
But for certain use-cases, as mentioned in the article itself, it is unavoidable.
Further, you might be working at a company that has decided to use Python, and you can make Python more efficient and effective using these suggestions.
Presenting these opinions as truths will get the hackles up of those who have a different opinion.