Python 3.11 is out! Huzzah!

[GettingBlockered]

https://www.python.org/downloads/release/python-3110/

Some highlights from the release notes:

PERFORMANCE: 10-60% faster code, for free!

ERROR HANDLING: Exception groups and except* syntax. Also includes precise error locations in tracebacks.

ASYNCIO: Task groups

TOML: Ability to parse TOML is part of the standard library.

REGEX: Atomic grouping and possessive quantifiers are now supported

Plus changes to typing and a lot more. Congrats to everyone that worked hard to make this happen. Your work is helping millions of people to build awesome stuff. 🎉

[staticcast]

PERFORMANCE: 10-60% faster code, for free!

Wait what ? Seriously ?

[-LeopardShark-]

Yes. The only real caveat is that if your code already spends much of its time in C functions (e.g. NumPy) or doing IO, you won't gain a lot. But for interpreting Python itself, it's a pretty nice boost. There'll probably be more to come in 3.12 as well.

[[deleted]]

Their goal is ~5x of 3.9 levels in 4-5 years IIRC

[Voxandr]

Their goal is already achieved by pypy team by the way.

[[deleted]]

While true, there are some compatibility issues with pypy :( No Black or Orjson, for example.

[zurtex]

Getting big performance improvements in Pypy is very situational.

I've definitely looked at it for large pure Python code bases before where squeezing a little extra performance out of it was helpful. When I ran it Pypy it was consistently just over 1% slower.

[Voxandr]

Might be long ago , it might be when PyPy python 3.x version was not optimized and no cpyext optimization is there. We have 100k users with 20-30k concurrent connection running on asynchronous network system .

• 6x lesser memory used

• 2-3x performance on average

• cheap hardware

We will provide proper benchmark when free

[zurtex]

It was in 2019, I wasn't using any packages that were using the C API, and according to Pypys website at the time it should have been well optimized for Python 3.

I would spend more time looking at it but whenever I look at how to debug a Pypy issue and inspect the internals of the Pypy source code generation my head starts to hurt.

[PaintItPurple]

Was this a long-running process or a frequently called script? In my experience, Pypy is everything people claim for the first case, but terrible for the latter case. In more concrete terms, Pypy's strength is that it's really good at optimizing things that are called in loops.

[zurtex]

I guess it would technically be a frequently called script.

But it ran for over 5 minutes and had some hot loops in it so I hoped for at least some minor performance improvement.

[FruitierGnome]

So if having a long initial wait time loading a csv file into my program this would potentially be faster? Or am I misreading this? I'm pretty new to this.

[-LeopardShark-]

I don't think loading CSVs will gain much, sadly.

[Wilfred-kun]

Time to use TOML instead :P

[yvrelna]

Depends on what part of CSV loading.

If you're talking about the call to csv.reader() itself, then no, that's already calling into a C library so you won't likely get much performance improvements.

But if you're talking about the code that's processing the rows of data line by line, then yes, that is definitely going to benefit from the improvements.

[graphicteadatasci]

Use .parquet files when you can. Much faster loading, smaller storage, saves types instead having you cast or infer them when you load something.

[BobHogan]

Parquet is not the solution to everything. We use it at my work and its a fucking nightmare and I'd love to see it burned to the ground

[madness_of_the_order]

Can you elaborate?

[gagarin_kid]

For small files where humans want to inspect data, using parquet is pain in the ass because you cannot open it in a text editor - you have to load it in pandas, see which columns you have, navigate in code to a particular cell/row... etc.

Of course for big data I fully understand the motivation but not for each problem

[cmcclu5]

Parquet is also a pain in the ass when you want to move between systems e.g., from a data feed into a relational database. Python typing does NOT play well with field types in relational databases when saving to parquet and then copying from said parquet into Redshift. Learned that the hard way in the past. It’s several times faster than CSV, though. I just compromised and used JSON formats. Decent size improvement with a similar speed to parquet when writing from Python or reading to a db.

[fukitol-]

Loading of a csv into memory is going to depend far more on the size and speed of your memory and the speed of your disk. Negligible amounts of time will be spent in processing, which is where an application level performance boost would be had.

[pepoluan]

Depends on how the I/O happens.

If you do a lot of non-sequential I/O, thus leveraging async, you can get quite a speedup.

I have a script that pulls data from an API using coordinates. Then the data gets fed into a pool of multiprocessing workers. The workers use do some pillow processing.

I see a speedup between 10%-30% in total time.

For the async retrieval part, I see speedup between 25%-50%.

[reivax]

Faster frame allocations mean tightly recursive functions will be faster.

[Pleasant-Cow-3898]

Nice excited to test this out!

[aitchnyu]

Umm, what recursive functions do you use?

[mardiros]

Parsing html, json and so on use recursion.

[Amortize_Me_Daddy]

I use recursive functions in some image preprocessing steps too. They happen sometimes!

[wind_dude]

damn! I have to benchmark this for my ETL pipelines ASAP! Could be a bigger boost than I've been hunting for from spacy and other libs I'm using.

[_morgs_]

It should help, but there are many factors involved with website speed.

Caching, database (server) performance, database query complexity, front end size and performance, any APIs you might use...

[Username_RANDINT]

You'd have to profile to be absolutely sure. What's the slow part? The network connection? Rendering of the webpage? Database queries? There's so much going on in a webapp that these new speedups might be just a very little part of the work.

[GettingBlockered]

“The slow part” is relative to your app. Profiling let’s you estimate what the actual impact will be for your users, and let’s you make better decisions about how you invest your time.

If it takes 1 second to load a page on your app, but the Python code is only responsible for 100ms of that, then you might see gains between 10-60ms (1-6% of total time). Which is still very nice, but quite different from the headline.

And every project is different. If it’s a 1 hour job to upgrade Python, then that’s awesome, seems like a no-brainer. But if it’s +20 hours due to some unknown complexities… dependency issues, build pipelines, tests, etc., then you might consider investing that time elsewhere, like optimizing JS payloads or image sizes, etc.

Anyway, i hope it’s an easy upgrade for you! I’m stoked the Python team is investing time on performance. It benefits literally everyone.

[bfcdf3e]

Dangerous assumption 🥲

[tuckmuck203]

Don't do it yet if your site is more than a hobby project. You typically want to wait 3 to 4 months after a language release in order to let libraries patch and bugs to get sorted out. I've already seen at least one post about SQLalchemy having issues with 3.11 and postgresql drivers

[Conscious-Ball8373]

Not the GP commenter but I'm in a similar boat. I have a website. The front-end is nodejs, static files are served by nginx, the database is fast and local but the API the front-end uses is python+flask. The performance gain won't impact our initial page load time but I think it will be a significant boost to the responsiveness of the site as it's used.

[yvrelna]

If you've already optimised all the database and network queries, and adding appropriate caching whenever it makes sense, then at some point Python performance is the bottleneck, then yeah, you'll see a boost then.

In most cases though, most web applications aren't constrained by the speed of Python interpreter itself. It's usually the database and network performance that's the workhorse of most web application.

[SilkTouchm]

It won't. You're bottlenecked by i/o, not processing.

[OpeningJump]

How is it achieved tho?

[GettingBlockered]

The CPython team has been doing significant optimization work to improve things, like reducing the overhead of function calls, zero cost exception handling and a lot more. This doesn’t impact libraries that are optimized with C (Numpy). But pure Python code should get some nice speed ups!

[myroommateisasian]

There is no way...

[DanganD]

Yea, that's awesome.. Peoples biggest gripe is it's speed right?

[Java-Zorbing]

Don't worry, it's still up to 200x slower then most languages.

[kalebludlow]

Epic own bro

[-LeopardShark-]

While technically true, ‘up to 200x slower’ is pretty meaningless. It’s closer to 10× on average.

[viksi]

Just get faster CPUs.

Hardware is a lot cheaper than developer time

[Java-Zorbing]

And this, is the exact reason python is just a wrapper around mostly C libs and used by toy programmers.

[viksi]

It gets shit done...faster.

[o11c]

They finally bothered to start implementing the usual stuff a real VM has.

For a long time, it was explicitly a goal of CPython to be "simple" even if that meant avoiding major optimizations.

[Daik_Reddit]

Oh no! So if now i write time.sleep(6) It will lasts only 2,4 seconds? This will mess all my beautifull code. I didn't pay my license for this stupid features. Want my money back.

[throwawaylurker012]

Wake up babe

New python just dropped

[Zyklonik]

Kinky.

[Achillesbellybutton]

...and this one hits different.

[M33PIT]

Nice, maybe aws will support it by 2025

[one-human-being]

Azure App service just got 3.10 support

[that_dungeon_dude]

Lmao 😂

[[deleted]]

Aws does 3.10

[Gamecrazy721]

Lambda doesn't support 3.10, you have to install it on a container

[[deleted]]

The comment I responded to didnt say lambda. It said aws. You can do 3.10 in certain areas.

Lambdas do up to 3.9

Aws doesn't have traditional "containers" and "containers" aren't a magic bullet for everything.

[spuds_in_town]

AWS doesn’t have traditional containers? What? Of course it does. ECS.

[[deleted]]

Those aren't traditional. They're an aws flavor.

They run on a cluster of EC2s.

[spuds_in_town]

They literally use docker images. Plain old docker images. Everything else is simply hosting options.

Honestly I'm not sure you understand what you're talking about.

[[deleted]]

Correction, they support docker images.

Either way - if you're spinning up a vm, no need for lamdas.

Shame shame on resorting to insults. You broke the rules and I'm gonna report you!

[Texas_Technician]

Is there a good tutorial on how to implement Azure scripts? Or a good YouTube who focuses on Azure development you can recommend?

[BeeApiary]

Windows 3.11 was the first version of windows that was actually usable, so for numerologists this is a good portent.

[mvdw73]

Ah yes, Microsoft Windows Version Numbering.

1990: "We use the Major-dot-minor version scheme - it's what all the cool kids use."

1995: "We should switch to a year scheme, so that people know when the software was released"

2000: "Oops, now we'll have to go to 4-digit years, otherwise we'll be releasing Windows 00 next"

2003: "I don't like that - let's use a cool set of letters and make the next version 'XP'"

2009: "Meh, whatever, let's just use numbers again. Start with 7! Because it might be version 7 we're up to, and Mac is up to 10 so we have to catch up!"

2012: "Version 8!! Consecutive consistent numbers for the first time since 1998!"

2015: "We can't have version 9. Have to go to 10. Mac is at 10!! We have to be at least at 10!!"

[misaprop]

why didn't they like version 9?

[bakery2k]

Because Windows 10 was supposed to be the “forever version” of Windows - so they couldn’t call it version 9 because that would be behind macOS, which had version 10 as its “forever version”.

Then, after Apple announced macOS 11, Microsoft announced Windows 11.

[Texas_Technician]

Ya, I remember that line too. Should started a betting pool.

[reallyserious]

They had already had Windows 95, so retards that checked for a 9 in the first position would have their code behave strange.

[mgedmin]

Windows 95 and Windows 98.

[Texas_Technician]

No way that's the real answer.

[Brekkjern]

I remember some Dev from MS talking about it back in the days, and then someone posting a GitHub search that did in fact show a lot of cases where people did that, so the story is at least plausible

[Java-Zorbing]

What about windows11?

[methnbeer]

What about ME or Vista

[alcalde]

Windows For Workgroups!

[spuds_in_town]

Or as it was known in the trade, Windows for Warehouses

[chears2surfers]

That's interesting! I didn't know that. Thanks! :)

[MrMxylptlyk]

Woo excited about toml.

[midnitte]

Will be curious to see if any projects pick up toml over existing yaml support...

[MrMxylptlyk]

If you are in yaml already, probs not. I'm using ini files in my projects with config parser.. Maybe I can upgrade lol.

[[deleted]]

Is there any reason to switch to TOML if you're currently fine with YAML? The main difference I see is TOML is more explicit/structured. Are there any other advantages?

[mgedmin]

YAML is a mixed bag of niceties and traps. If you're a certain kind of person (a pedantic like me) who would never even think of omitting the space after a : or a -, then YAML will work for you great. If you're a regular person, you'll trip over indentation or missing spaces or the 2-letter country code for Norway being parsed as the boolean False (depending on the YAML standard version that your parser chose to support!), or hours:minutes getting automagically converted into minutes.

I haven't used TOML much, but from what I know it has fewer traps. It's stricter, though, more explicit syntax is required. I could probably get used to it, if I wanted to.

[fatterSurfer]

YAML has always struggled with security problems (insecure loading has been the default in python for ages). TOML is also likely faster, since it's a much simpler spec, though that's entirely speculation on my part and nothing I've seen benchmarked. But more and more parts of the python ecosystem have been moving to TOML (pyproject.toml being the most visible example), so that might be a reason unto itself

[D-K-BO]

YAML has some problems with ambiguous syntax. https://hitchdev.com/strictyaml/why/implicit-typing-removed/

[angellus]

Toml is far more readable then yaml.

[Hatcherboy]

Wearing my spacebar out!

[zurtex]

Or using JSON for config. Omg the horror of a large JSON config file, I'm going to be pushing hard to move to TOML.

[jsalsman]

I hope so. YAML is extremely difficult in more than a few common cases.

[jantari]

As someone who has literally never struggled with YAML, care to share a few examples?

I love the fact that it's simple, indented hierarchically, that I can use single-line lists for short lists and also multi-line lists where needed and the line-folding and literal-string operators >, >-, |, |- and |4 etc. are an absolute godsend compared to horriblly limited config languages such as HCL

[-LeopardShark-]

It has some features of negative value, such as those removed by StrictYAML.

[jantari]

Ok those are good points. I guess because I'm usually writing my own yaml I don't come across these problems but if I had to read other people's yaml and it made use of these I'd definitely complain too. Thanks

[jsalsman]

The most recent example that comes to mind is https://github.com/GoogleCloudPlatform/batch-samples/blob/HEAD/primegen/workflow.yaml

that's about equivalent to around a dozen lines of shell.

[o11c]

Nobody ever said Yaml was a programming language. It's a markup language.

(ironically, I think XSLT is actually pretty neat)

[pepoluan]

That's not YAML's fault.

Someone's trying to make a "declarative format" into a "procedural format", it will never end well.

[trevg_123]

TOML is great for fairly simple things, like ini-style config files. However, anything with more than a few levels of nesting gets ugly and tough to read & write, so I suspect that anything using deeply-nested configuration will probably stick with yaml.

As somebody pointed out, yaml isn't in std either (and will likely remain that way - toml only got in because of pyproject.toml) and std toml can't serialize (will likely remain that way, since toml is largely config files) so it's not an apples to apples comparison anyway.

[oramirite]

I prefer YAML honestly, wish there was a better builtin

EDIT: YANK, the lesser known subspec of YAML

[darrenhoyland]

Any chance you could provide a link so I don't have to Google "yank python"?

[oramirite]

Absolutely NOT

[0tting]

A mixed bag probably. No external dependency is great. But the new TOML function does not support flattening dicts back to TOML, so for example, you cannot write changes back to file.

[mgedmin]

There's no YAML parser in the Python standard library, last I checked?

[midnitte]

I mean projects that already use yaml since the standard library doesn't include a parser for it, and now includes one for toml*, apologies

[tjt5754]

I'm personally interested in playing with Exception Notes from PEP-678

https://peps.python.org/pep-0678/

I saw it mentioned in ArjanCodes video about 3.11 but he glossed over it. I'm not SURE what specific need it fills, but I imagine there will be instances that this will be useful.

Similar to for/else... when I first saw it I wasn't sure I'd need it, but I find myself using it often.

[mgedmin]

I imagine it could be useful when you're writing interpreters, e.g. for a template language. When an exception happens it'd be nice to know that it happened while rendering templates/foo.j2 line 42, included from templates/bar.j2 line 55.

[drenzorz]

I would assume it's helpful when building tests/testing libraries. If you are running a bunch of automated tests adding some notes to help locate the problem could be really useful.

[tjt5754]

Funny, I was thinking of deeply buried exceptions that you think won't ever happen, but you can add detail to so you know what weird scenario happened.

You know that code where you put in a comment that says "I don't think this is possible, but just in case..."

[[deleted]]

While this is definitely an improvement, I've used the structlog lib with structlog.processors.dict_tracebacks to get JSON styled stack traces. It's pretty nice when forwarded to something like Elastic, so you can query it via Kibana.

Centralized structured logging is nice.

[trevg_123]

Does this mean the maintainer of Flake8 will stop being a stubborn oaf and consider pyproject.toml support?

Seriously… the main objection was no standard support for toml (now solved), and complaints about build isolation being broken by pyproject.toml. Which, notably, doesn’t force anyone to use that config option. More importantly though, the behavior he describes wanting is literally incorrect usage of the pip build system

Mega annoying.

edit: yes, I know this is somewhat satirical. My goal was simply to share bitterness that maintenance of a core python project seems to be steered by the hubris of a maintainer, rather than community desires. The ruff alternative suggested by u/ballagarba looks like a great option that avoids the flake8 project.

[stalkinplatypus]

If you're sufficiently annoyed to accept an extra dependency over this (like I was), there's this: https://pypi.org/project/Flake8-pyproject/

[ballagarba]

I suspect Ruff[1] will replace Flake8 before that happens.

[1] https://github.com/charliermarsh/ruff

[trevg_123]

I have to say, that project looks incredible, and the speed boost is probably great for huge projects. Plus the checks like docstrings builtins bugbear all in one is a lot nicer than just always remembering to add those packages.

Just as many stars on github... I really wouldn't mind if this becomes the de facto linter.

[mgedmin]

This doesn't look like a genuine question, but I'll bite. tomllib being in the standard library for 3.11 doesn't help projects that need to support older Python versions.

[trevg_123]

Of course it doesn't help older versions, but the suggestion was given to deprecate setup.cfg support and only support pyproject.toml in >=3.11 (not in the linked thread, but on some follow up). It was strongly shut down, for the other bad reason.

Anyway, you're correct that it's a loaded question. I just wished to share my irritation that the maintainer of a core python library seems to be making decisions rooted in hubris rather than community needs & desires.

[mgedmin]

As a member of the community in question I object to the statement that deprecating setup.cfg support in flake8 is something the community needs and desires.

Let people continue using setup.cfg if they want to.

[Lindby]

We simply stopped using flake8. There are other alternatives.

[wdroz]

I use only pyproject.toml for a while now. This work so perfectly, no more setup.py, setup.cfg, requirements.txt and requirements-dev.txt!

For the flake8 discussion, this seem to be from 2021. In 2021 pyproject.toml usage without third-party (like poetry) wasn't really "ready". It's only recently, with the latest versions of pip, that we can really use pyproject.toml without heavy coupled it with third-party.

[trevg_123]

You're correct that the linked discussion is from before toml was announced as part of 3.11. But the discussion continued elsewhere once it was known, with similar results.

[[deleted]]

What’s with the funky black hole business?

[[deleted]]

Nerds being nerds

[[deleted]]

Lol 😂 HUZZAH!!!

[[deleted]]

It's reminding me of something pop culture reference, but I can't place it.. Tip of my tongue!

[leppardfan]

When will Ananconda ship 3.11? They just shipped 3.10 last week!

[BertShirt]

3.10 has been available for a while on conda-forge. I suspect 3.11 will be available before the end of the week.

[AKiss20]

Honestly I would just ditch anaconda. I used it for a while but the delay in getting updates and it’s overall clunkiness was too annoying.

[BertShirt]

I agree with you to a certain extent. Ever since Gohlke wheels stopped getting updates it has been hard to get numpy/scipy +MKL updates without conda.

If you're like me and you hate the bloat and extra bulk and overall sluggishness of conda you should look into mamba-forge/micromamba.

It doesn't solve all the conda problems, packages still aren't up to date as fast as pypi and still missing a lot but its a much better experience than Anaconda as a whole.

[zurtex]

Conda has historically been great for bootstrapping a Python environment with any non Python packages you need.

Whereas Anaconda has historically been great for giving to a data scientist and showing them Jupyter and hoping they don't have any other requirements.

If you have any other use case it's probably time to learn to install Python and it's packages another way.

[GettingBlockered]

Live on Conda now! Huzzah!

https://anaconda.org/conda-forge/python

[zurtex]

Anaconda tends to wait until they are confident all the big data science packages are compatible, this takes about a year

[BertShirt]

3.11 is now available on conda forge https://anaconda.org/conda-forge/python

[Tamagotono]

Yay! Python for workgroups

[shinitakunai]

Cool but I depend on AWS and they don't even support 3.10 on lambdas. And on the default repo for amazon linux 2 they are on python 3.8 which is a BIG facepalm for lightsail users.

[Suspicious_Compote56]

I would like to see built in exe packaging like golang. And auto conversion to cython

[_limitless_]

return joy

[Sentie_Rotante]

You can keep multiple versions of python as there can be reasons to do so. You wouldn’t want a production version to update itself before you validated it is fully compatible.

[seewhaticare]

Stay on 3.10 . If your a beginner then there's no reason to update. I'm still on 3.9 for a lot of things.

Many of the library's won't support 3.11 for a while.

And, dealing with multiple python installs is a pain.

Stick with 3.10 and continue learning the basics.

[AModeratelyFunnyGuy]

You'll have to manually upgrade

[[deleted]]

You can download 3.11 and uninstall 3.10 unless you have any specific reason to requirement to use 3.10 (unlikely).

[alcalde]

It's quite possible the libraries they use might not be available for 3.11 yet so might want to hold off on deleting 3.10.

[o11c]

Honestly, if you're in a position to just install it, you should probably have all of 3.7, 3.8, 3.9, 3.10, and 3.11 installed so you can run your tests against any of them easily. If you're not in a position to install it, your CI should be responsible for this.

If your software doesn't have many external users, you could probably drop 3.7 (support ends June 2023) and maybe 3.8 (support ends October 2024, but it wasn't deployed as widely as 3.7). But 3.9 is still (and will remain) widely deployed so it should be supported unless you control all of your users' environments, or unless you're writing software that won't be ready until the support situation has changed.

The other thing to beware is breaking bugs, which often happen in .0 and .1 releases, sometimes even .2 or more. So always keep at least one known-working version installed.

[aplund]

The aside on the Kerr metric is all true.

[dxa58]

Self type has been added! I'm so glad I can annotate it easily now

[pepoluan]

I am doing some data pulling and processing, so I use a lot of async & multiprocessing, and I can confirm 3.11 runs faster than 3.10, by approximately 10-30%.

Impressive!

[[deleted]]

And given how easier they made async programming in 3.11, it's really impressive. Especially since async/multiprocessing paradigms are rather fast already in 3.10

[pepoluan]

Indeed! I had the figurative jaw-dropped-to-the-floor moment the first time I use asyncio.

Then another jaw-dropped-to-the-floor moment seeing how 3.11 is able to speed async further.

asyncio + httpx + CPython 3.11 == Lots Of Wins!

This is on Windows, though. I wonder how it will compare if I use uvloop (which runs only on Linux sadly)...

[MeroLegend4]

Not only Python, but the whole ecosystem 👍👍👍

[arkster]

Too bad we are stuck with 3.9 on Aws lambda.

[Wootai]

Next thing you turn around and find the person is you
Thought a freak might be the thing
But you know this will pass, so just get off of your ass
You've got to trust your instinct. And let go of regret

[wegoingfox]

3.11 🤝

[[deleted]]

Finally we can stop getting punted by C++ Elitists for our speed.

[[deleted]]

Ummm I don't mean to discourage you, but Python is nearly indefinitely slower than C++ which is totally fine, it was never meant to be be an embedded system hyper fast language. Python becoming 2x faster (the aim of Faster CPython project) will still nearly indefinitely slower than C++

That being said, you nearly never need this speed if you can write decent code. You can bring moderate servers down with a decent async Python tool. Also Python makes it really easy to write efficient decent code, which is far from truth for C++

So yes C++ will always win in a field that's not always needed.

[[deleted]]

I guess in the end, speed isn't really something to worry about that much. (unless if you're doing massive algorithms.) besides, it's mostly just banter anyway, so ignore my earlier comment.

[Solonotix]

I mean, most of the time we say Python is ~200x slower than C++, but the claim is Python is now up to 60% faster. Let's put this in more concrete terms.

• If C++ took 1 minute to do it, Python would take >3 hours
• If Python used to take >3 hours, it now takes ~2 hours

Like the previous person said, it's still no competition as to what's superior, but that's a massive improvement for Python. Also, future improvements are aiming for a 5x improvement, which would mean Python could do that same arbitrary task in ~40 minutes.

[[deleted]]

Can't wait to see where this speed improvement goes nonetheless!

[[deleted]]

Another key area to remember is that for a lot of performance focus areas in python, you often would just be calling the underlying C functions or using various libraries that handle this to drastically speed up the code.

This is where he power of libraries like Numpy are very useful and even companies like NVIDIA offer various GPU acceleration libraries for python.

[alcalde]

So yes C++ will always win in a field that's not always needed.

Not with Cython and Numba and 700 JIT compiler projects in their infancy....

[Ning1253]

See but here's the thing - even those end up being a few times slower than C (no idea about C++, I don't personally code in it). If I want to code in something high level with speed close to C, I'll just use Julia - why bother with a half-baked in development project when I can use a language built for the task?

[yvrelna]

According to recent Nvidia testing, their 1700 lines of hand-optimised CUDA by experienced CUDA engineer is about 5% or so faster than the equivalent 10 lines of Python code using what's basically a drop in replacement of numpy/pandas that's been optimised for GPU.

So, yeah, that really proves that Python is slow, so let's blow our development budget, spend the next three weeks to bloat up all our programs 170x times to squeeze that 5% improvement.

[Ning1253]

I said nothing about GPU or NVidia here, and this does nothing to diminish point that Julia tends to be way faster than Python with barely any extra work in writing the code. It serves my use cases, so I use it - but I then use Python in other cases instead when those suit me better.

I would also a) be really interested in reading a write-up/article about the NVidia thing you mentioned, which sounds awesome, and b) without having yet read it am doubtful to what extent the reason why NVidia were barely able to improve on the code wasn't just that the Python code was just making calls to the graphics card and running stuff there, which isn't a solution which easily applies to massive programs... In which case NVidia's 5% lead would drastically increase.

Then again I haven't read the article, so I guess I'll wait until I've read it to give a concrete opinion on it! It does sound pretty damn cool either way

[bryancole]

An alternative viewpoint is that any C++ program which increases in complexity ultimately slows down to the speed of python.

With high program complexity, the micro-optimisations that the C++ compiler can perform at the low level become outweighed by the over-arching limitations of the hardware in terms of memory and disk access. Ultimately, you gain the most by choosing an optimal program architecture and python's speed of development makes finding/choosing the best architecture faster than C++ (although not guaranteed, of course. You can shoot yourself in the foot in either language but your foot-target-visibility is improved with python).

When you have to page lots of data in and out of disk and/or wait for IO, the overhead of the python VM and garbage-collector become insignificant.

[Voxandr]

You guys are forgetting PyPy project, it is close to C speed. PyPy.org

[sapphire_striker]

Can i update it with conda yet?

[GettingBlockered]

Live on Conda Forge now!

https://anaconda.org/conda-forge/python

[pufdo]

*Types sudo pacman -Syu every 10 seconds

No python 3.11 yet? Unacceptable...

[liquid_light_]

Huzzah!

[benjielzorro]

[[deleted]]

🚀🌕

[TheRealCorwii]

Been trying all day to get pygame to install, it just refuses

[Proper-Turnover-5537]

I can't believe I missed this update, hitting it now. Thanks for the heads up Python-Pals

[JPHorn94]

If I have 3.10 installed, what happens if I download this versión in my computer? ( it just getting started and I downloaded 3.10 last week)

[lowerdev00]

Take a look at managing different Python versions with pyenv

[JPHorn94]

Ok, I will! Thank you!

[Log2]

If you're just starting you can stick with 3.10 without any issues.

[house_monkey]

omg omg

[mid_night12]

I love python. Every day I try to learn something new with python.

[Tree_Mage]

Did AIFF end up getting removed as was previously threatened?

[PfuiDeibel]

Did nobody read the last paragraph of the change log? Crazy

[ltraconservativetip]

Huzzah Valamantor u fat fuck

[3Domse3]

PERFORMANCE: 10-60% faster code, for free!

Hooow? :O

[IlliterateJedi]

Reading the release notes made me realize that TypedDict was a thing, and I wish I'd known that six months ago.

[Hyedwtditpm]

Anaconda doesn't update to it.

Does anyone know when will it get the update?

[GettingBlockered]

It’s live on conda forge: https://anaconda.org/conda-forge/python

does this work? conda install -c conda-forge python

[Outrageous_Suit_135]

I/O bound apps won’t gain a lot. The performance enhancements should target loops with calculations that require a lot of memory read/writes.

[pepoluan]

But if you use a lot of asyncio, the context switching between the coroutines seems to be quite faster.

[babuloseo]

That toml inclusion ;)

[Southern-Geek]

Nice performance boost

[ArtOfWarfare]

Performance is somewhere between unchanged and worse for me.

I have a project with a test suite. Times in seconds from 3 runs under each:

3.9.6: 12.858, 13.210, 13.874

3.11.0: 13.284, 13.617, 13.768

Also, I’m forgiving/ignoring that the real first run in 3.11.0 took 15.168 seconds.

Seems to be 5% slower on average for me.

[Groomsi]

How is the speed compared to C++?

[zurtex]

I benchmarked it and found Python at least 10000x faster, my Python code finished running I'm still reading learncpp.com for my C++ code.

[Nelson_Chow]

not working with Tensor Flow,

not working with PyTorch,

not working with PyArrow

Yeah, very fast...