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What's up in the Python community? – April 2023

129 points by BiteCode_dev 3y ago

tomrod 3y ago
This is a nice summary! Subscribed.
skilled 3y ago
I never saw this newsletter before but I must say I am impressed. Fantastic approach to writing style and a great showcase of domain knowledge. The Web could use more of this.
- frickinadorable 3y ago
  Reminds me of the Orbital Index but for Python. I’d love a similar Typescript oriented site for the day job, any recommendations?
Qem 3y ago
> Python 3.12 improves the language perf by 4% A bit shy of the original target of 50% improvement per release, totaling 5x speedup across four releases. Hope it catches up in the next couple releases.
- kzrdude 3y ago
  Python 3.12 also does not exist, because it has not been finished and released yet. So there's time.
  - mathisfun123 3y ago
    "my wife is pregnant but my kid doesn't exist yet" hmmm
    - arp242 3y ago
      "Your kid doesn't have fully functioning limbs!" "Yeah, but my wife is only two months pregnant"
gverrilla 3y ago
Question from a beginner: I'm deploying a python project to aws (beanstalk + lambda, among others), and I've noticed I can only use python versions 3.9 and 3.8. Why is that? Is 3.10 not considered stable?
- roflyear 3y ago
  I don't know why it is, but 3.10 and 3.11 are considered stable (and I would suggest you use 3.11 if you can).
  - modo_ 3y ago
    I was just looking into this earlier. A lot of major packages have explicitly stated 3.11 readiness, but we're still only at 45% of the top 360 packages. That's not to say the remaining 55% are broken on 3.11, just tread with caution. For comparison, 71% explicitly support 3.10. https://pyreadiness.org/3.11/ https://pyreadiness.org/3.11/
    - roflyear 3y ago
      It's a good point, but doesn't imply 3.11 is not stable. But could be an answer as to why Amazon doesn't support it.
  - bart_spoon 3y ago
    I would not use 3.11 yet. I’ve had lots of issues with packages not supporting it and other headaches that still need to be ironed out. I’ve had no issues with 3.10.
    - roflyear 3y ago
      Well yes you have to make sure all your requirements support it. 3.11 is stable tho.
- __s 3y ago
  Cloud providers tend to be pretty slow to provide up to date software versions, I wouldn't rely on them to signal what versions are stable I'm personally watching https://learn.microsoft.com/en-us/answers/questions/1191155/redis-7-0-support-in-azure https://learn.microsoft.com/en-us/answers/questions/1191155/... because Sidekiq 7 requires at least Redis 6.2, but Azure Cache decided only major version upgrades matter This should give you a better idea of Python version status: https://devguide.python.org/versions https://devguide.python.org/versions
qbasic_forever 3y ago
I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.
- Spivak 3y ago
  By volume of different projects probably not, but by usage probably. Once winners get decided and paths get treaded the ecosystem will probably be smaller but I bet the user count will be bigger. Look, even if you're the most biggest skeptic of all the AI stuff you can still do useful things with it that you couldn't before like present full-English interfaces and get embeddings for arbitrary text which is a leap compared to word2vec for search. I can dm my discord bot a picture of an appointment confirmation text and it with OCR + LLm it just schedules the event in my calendar. Also by gluing a v8 isolate to the LLm I can give it much more complicated date calculations. My favorite was "If f(n) is the nth Fibonacci number schedule an appointment in f(5) days."
  - nwiswell 3y ago
    > you can still do useful things with it that you couldn't before like > ... > If f(n) is the nth Fibonacci number schedule an appointment in f(5) days hmmm
    - IanCal 3y ago
      That's absolutely not what they said. Let's keep hn better than that.
      - nwiswell 3y ago
        It's obviously tongue-in-cheek, but it's also not not what they said.
        IanCal 3y ago
        It is not what they said. That was an example of complicated work with dates, which easily hits the level of "more complicated than you need". Before that, and before the cut in the quote was an obvious use case easily explained. I don't know why you want to go down this route but I won't engage further.
arunkant 3y ago
Python packaging is coming along quite good
jokoon 3y ago
I just tried some pre-trained models to classify images, using a CPU, it takes about 10s to 15s per image. I did not know it was so inefficient.
- chaostheory 3y ago
  Isn’t the problem that you were relying more on the CPU rather than a decent GPU?
- codethief 3y ago
  Would you share some details? This indeed sounds very slow, so I suppose there should be some easy ways to speed things up. Just to give you an idea of what's possible: A couple years ago I worked on live object recognition & classification (using Python and Tensorflow) and got to about ~30 FPS on an Nvidia Jetson Nano (i.e. using the GPU) and still ~12 FPS on an average laptop (using only the CPU).
  - jokoon 3y ago
    https://replicate.com/pharmapsychotic/clip-interrogator https://replicate.com/pharmapsychotic/clip-interrogator using: cfg.apply_low_vram_defaults() interrogate_fast() I tried lighter models like vit32/laion400 and others etc all are very very slow to load or use (model list: https://github.com/mlfoundations/open_clip https://github.com/mlfoundations/open_clip) I'm desperately looking for something more modest and light.
- quickthrower2 3y ago
  I am trying to understand your point. Are you saying it could be more efficient on a CPU using a different language than Python? Or are you saying CPUs are slow, GPUs should be used? Or are you saying classifying images algorithms can be improved more?
- riotnrrd 3y ago
  The neural network inference (and training) is all done in compiled C libraries called by Python. The inefficiencies you're seeing are because you're doing it on a CPU, probably in one thread, rather than on a GPU with tens of thousands of "threads."
LispSporks22 3y ago
I’m bummed out about the ever expanding Python packaging scene.
pphysch 3y ago
Very bullish on Python. PyScript is coming along nicely as well, with the core devs having some clear ideas about how to tackle load times.
slicktux 3y ago
Even with hardware like the raspberry pi Pico I still find myself programming them using C…
ineedasername 3y ago
>Most new Python projects are still about AI Are there any that allow a user to run an LLM with GPT-3-ish capabilities on a single pc w/ <= 4GB GPU Ram in a reasonable amount of time? Where "reasonable" is something like no more than a few minutes to get the output. A little longer wouldn't be too bad either since you could script something that submits prompts automatically and let things run in the background or something. Trying to search for such a thing-- if it exists-- is nearly impossible right now with so much being done & talked about. Some content talks about running something on only 16GB GPU ram (!!!) which is far beyond many discrete cards. a 3080 has up to 16, some only 8 (I think 16 is the max?) and fairly decent entry level+ cards top out at 4GB. Any options out there?
- LanternLight83 3y ago
  If you're really alright with a few minutes delay, you might be able to run =<13b param. models on CPU
  - ineedasername 3y ago
    Any particular project that's prebuilt to not throw "out of ram" errors for it? I just want to play around with things without the restrictions ChatGPT. The OpenAI API is much less restrictive but can get pricey fast if I want quality above the lowest tier, at least for hobbyist purposes. I ran up a $10 charge in a few hours-- that's what I had budgeted for playing with a new "toy". It get's very tedious prompt engineering to convince ChatGPT to respond to some perfectly reasonable prompts without and an answer that amounts to "aww shucks, I'm just a simple LLM and couldn't possible generate an answer to that sort of thing". Recently I asked it-- after about 20 prompts back and forth-- tp "analyze the personality of the person submitting these prompts" (They were prompts about the nature of AI, and how did it know that it was not a simplified LLM being run & controlled by a true advanced AGI, etc). It took about a dozen tried to get it to (finally) "Generate a fictional bio in the form of and RPG character sheet based on the prompts". Even if it takes a few minutes and the quality is lacking a bit lacking and unpolished, I don't want to have to argue with the LLM to get a response.
nologic01 3y ago
While the hyperbole around AI might calm down a bit, the broader 'data science' domain is unlikely to diminish in importance and may generate new hypes. And in the short to medium term Python will certaintly play a core role in these developmemts. Yet what I am missing in the news is some hint of where Python is going longer term. What will 4.0 look like? Which of the know limitations will be addressed? Will it ever be performant on a standalone basis? Will it ever be native on mobile? Etc.
- ensignavenger 3y ago
  Some good questions, but many of them don't have answers yet. > What will 4.0 look like? Right now there has been no decisions made on a 4.0. It may be just another release, or it may remove some features, but it almost certainly won't be a major backwards compatability-breaking release like 3.0 was. > Which of the know limitations will be addressed? That depends on what the contributors want to put effort into. :) Speeding it up is currently getting a lot of attention. Each new release brings significant performance improvements. > Will it ever be performant on a standalone basis? As stated above, each new release is faster, but it is impossible to predict where it will end up, and even more impossible to know what you consider "performant". For many users, it is already performant :) > Will it ever be native on mobile? That is a question for the owners of the mobile platforms, as they generally decide what languages get first party "native" support on their platforms.

129 points by BiteCode_dev 3y ago

This is a nice summary! Subscribed.

I never saw this newsletter before but I must say I am impressed. Fantastic approach to writing style and a great showcase of domain knowledge. The Web could use more of this.

frickinadorable 3y ago
Reminds me of the Orbital Index but for Python. I’d love a similar Typescript oriented site for the day job, any recommendations?

Qem 3y ago

> Python 3.12 improves the language perf by 4% A bit shy of the original target of 50% improvement per release, totaling 5x speedup across four releases. Hope it catches up in the next couple releases.

kzrdude 3y ago
Python 3.12 also does not exist, because it has not been finished and released yet. So there's time.
- mathisfun123 3y ago
  "my wife is pregnant but my kid doesn't exist yet" hmmm
  - arp242 3y ago
    "Your kid doesn't have fully functioning limbs!" "Yeah, but my wife is only two months pregnant"

gverrilla 3y ago

Question from a beginner: I'm deploying a python project to aws (beanstalk + lambda, among others), and I've noticed I can only use python versions 3.9 and 3.8. Why is that? Is 3.10 not considered stable?

roflyear 3y ago
I don't know why it is, but 3.10 and 3.11 are considered stable (and I would suggest you use 3.11 if you can).
- modo_ 3y ago
  I was just looking into this earlier. A lot of major packages have explicitly stated 3.11 readiness, but we're still only at 45% of the top 360 packages. That's not to say the remaining 55% are broken on 3.11, just tread with caution. For comparison, 71% explicitly support 3.10. https://pyreadiness.org/3.11/ https://pyreadiness.org/3.11/
  - roflyear 3y ago
    It's a good point, but doesn't imply 3.11 is not stable. But could be an answer as to why Amazon doesn't support it.
- bart_spoon 3y ago
  I would not use 3.11 yet. I’ve had lots of issues with packages not supporting it and other headaches that still need to be ironed out. I’ve had no issues with 3.10.
  - roflyear 3y ago
    Well yes you have to make sure all your requirements support it. 3.11 is stable tho.
__s 3y ago
Cloud providers tend to be pretty slow to provide up to date software versions, I wouldn't rely on them to signal what versions are stable I'm personally watching https://learn.microsoft.com/en-us/answers/questions/1191155/redis-7-0-support-in-azure https://learn.microsoft.com/en-us/answers/questions/1191155/... because Sidekiq 7 requires at least Redis 6.2, but Azure Cache decided only major version upgrades matter This should give you a better idea of Python version status: https://devguide.python.org/versions https://devguide.python.org/versions

qbasic_forever 3y ago

I was browsing the most popular pip packages recently and was also downright shocked how much AI stuff is up at the top. I will be very curious if much of these things are still popular or relevant in a year.

Spivak 3y ago
By volume of different projects probably not, but by usage probably. Once winners get decided and paths get treaded the ecosystem will probably be smaller but I bet the user count will be bigger. Look, even if you're the most biggest skeptic of all the AI stuff you can still do useful things with it that you couldn't before like present full-English interfaces and get embeddings for arbitrary text which is a leap compared to word2vec for search. I can dm my discord bot a picture of an appointment confirmation text and it with OCR + LLm it just schedules the event in my calendar. Also by gluing a v8 isolate to the LLm I can give it much more complicated date calculations. My favorite was "If f(n) is the nth Fibonacci number schedule an appointment in f(5) days."
- nwiswell 3y ago
  > you can still do useful things with it that you couldn't before like > ... > If f(n) is the nth Fibonacci number schedule an appointment in f(5) days hmmm
  - IanCal 3y ago
    That's absolutely not what they said. Let's keep hn better than that.
    - nwiswell 3y ago
      It's obviously tongue-in-cheek, but it's also not not what they said.
      - IanCal 3y ago
        It is not what they said. That was an example of complicated work with dates, which easily hits the level of "more complicated than you need". Before that, and before the cut in the quote was an obvious use case easily explained. I don't know why you want to go down this route but I won't engage further.

arunkant 3y ago

Python packaging is coming along quite good

jokoon 3y ago

I just tried some pre-trained models to classify images, using a CPU, it takes about 10s to 15s per image. I did not know it was so inefficient.

chaostheory 3y ago
Isn’t the problem that you were relying more on the CPU rather than a decent GPU?
codethief 3y ago
Would you share some details? This indeed sounds very slow, so I suppose there should be some easy ways to speed things up. Just to give you an idea of what's possible: A couple years ago I worked on live object recognition & classification (using Python and Tensorflow) and got to about ~30 FPS on an Nvidia Jetson Nano (i.e. using the GPU) and still ~12 FPS on an average laptop (using only the CPU).
- jokoon 3y ago
  https://replicate.com/pharmapsychotic/clip-interrogator https://replicate.com/pharmapsychotic/clip-interrogator using: cfg.apply_low_vram_defaults() interrogate_fast() I tried lighter models like vit32/laion400 and others etc all are very very slow to load or use (model list: https://github.com/mlfoundations/open_clip https://github.com/mlfoundations/open_clip) I'm desperately looking for something more modest and light.
quickthrower2 3y ago
I am trying to understand your point. Are you saying it could be more efficient on a CPU using a different language than Python? Or are you saying CPUs are slow, GPUs should be used? Or are you saying classifying images algorithms can be improved more?
riotnrrd 3y ago
The neural network inference (and training) is all done in compiled C libraries called by Python. The inefficiencies you're seeing are because you're doing it on a CPU, probably in one thread, rather than on a GPU with tens of thousands of "threads."

LispSporks22 3y ago

I’m bummed out about the ever expanding Python packaging scene.

pphysch 3y ago

Very bullish on Python. PyScript is coming along nicely as well, with the core devs having some clear ideas about how to tackle load times.

slicktux 3y ago

Even with hardware like the raspberry pi Pico I still find myself programming them using C…

ineedasername 3y ago

>Most new Python projects are still about AI Are there any that allow a user to run an LLM with GPT-3-ish capabilities on a single pc w/ <= 4GB GPU Ram in a reasonable amount of time? Where "reasonable" is something like no more than a few minutes to get the output. A little longer wouldn't be too bad either since you could script something that submits prompts automatically and let things run in the background or something. Trying to search for such a thing-- if it exists-- is nearly impossible right now with so much being done & talked about. Some content talks about running something on only 16GB GPU ram (!!!) which is far beyond many discrete cards. a 3080 has up to 16, some only 8 (I think 16 is the max?) and fairly decent entry level+ cards top out at 4GB. Any options out there?

LanternLight83 3y ago
If you're really alright with a few minutes delay, you might be able to run =<13b param. models on CPU
- ineedasername 3y ago
  Any particular project that's prebuilt to not throw "out of ram" errors for it? I just want to play around with things without the restrictions ChatGPT. The OpenAI API is much less restrictive but can get pricey fast if I want quality above the lowest tier, at least for hobbyist purposes. I ran up a $10 charge in a few hours-- that's what I had budgeted for playing with a new "toy". It get's very tedious prompt engineering to convince ChatGPT to respond to some perfectly reasonable prompts without and an answer that amounts to "aww shucks, I'm just a simple LLM and couldn't possible generate an answer to that sort of thing". Recently I asked it-- after about 20 prompts back and forth-- tp "analyze the personality of the person submitting these prompts" (They were prompts about the nature of AI, and how did it know that it was not a simplified LLM being run & controlled by a true advanced AGI, etc). It took about a dozen tried to get it to (finally) "Generate a fictional bio in the form of and RPG character sheet based on the prompts". Even if it takes a few minutes and the quality is lacking a bit lacking and unpolished, I don't want to have to argue with the LLM to get a response.

nologic01 3y ago

While the hyperbole around AI might calm down a bit, the broader 'data science' domain is unlikely to diminish in importance and may generate new hypes. And in the short to medium term Python will certaintly play a core role in these developmemts. Yet what I am missing in the news is some hint of where Python is going longer term. What will 4.0 look like? Which of the know limitations will be addressed? Will it ever be performant on a standalone basis? Will it ever be native on mobile? Etc.

ensignavenger 3y ago
Some good questions, but many of them don't have answers yet. > What will 4.0 look like? Right now there has been no decisions made on a 4.0. It may be just another release, or it may remove some features, but it almost certainly won't be a major backwards compatability-breaking release like 3.0 was. > Which of the know limitations will be addressed? That depends on what the contributors want to put effort into. :) Speeding it up is currently getting a lot of attention. Each new release brings significant performance improvements. > Will it ever be performant on a standalone basis? As stated above, each new release is faster, but it is impossible to predict where it will end up, and even more impossible to know what you consider "performant". For many users, it is already performant :) > Will it ever be native on mobile? That is a question for the owners of the mobile platforms, as they generally decide what languages get first party "native" support on their platforms.