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Why Python keeps growing, explained

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Re: Why Python keeps growing, explained

#271

Post by rootusrootus »

arnvald wrote: post #32

I'm a bit surprised to see this article on GitHub blog, it feels more like something from dev.to - looking at the surface, with little actual insights. Most of the provided reasons behind Python's popularity are true also for other languages - portable, open source, productive, big community. This can be also said about PHP, Ruby, or Perl back in 2000s. Why isn't Perl as popular as Python? I don't think it's all abou…

> Why isn't Perl as popular as Python?

I don't think there is a single reason, but it sure didn't help that the community self-destructed by trying to make an entirely new language after version 5 and still call it Perl. It took a lot of years to resolve that nonsense, and in the meantime many people moved on.

It also does not help that Perl is a creative language, useful but very much open to many different interpretations. Hiring a perl guy and expecting them to read someone else's code is a crapshoot. The upside to Python's strong cultural opinions on coding style makes it easier for one developer to pick up someone else's code.

> Imagine that the boom in ML/AI didn't happen - would Python be #1 language right now?

Probably not. But it wouldn't be perl, either. Javascript most likely. But the core usage of python for scripting was never predicated on ML popularity, so it would still be a pretty commonly used language. and javascript has many annoying warts too, so I think plenty of people would still choose to write django apps instead of node, whether ML existed or not.

Re: Why Python keeps growing, explained

#272

Post by _aavaa_ »

ofrzeta wrote: post #156
_aavaa_ wrote: post #152

Earlier quoted context omitted.

But this is a false dichotomy. The space of options isn't C++/Rust or Python. There are languages which attempt to give the best of both worlds, e.g. Julia. > they're using a library where those issues have been abstracted away. I work in Python, and while libraries like numpy have certainly abstracted away some of those issues, there's still so much performance left of the table because Python is still Python.

I'd say if you do data-intenstive computation with Numpy you are not leaving much on the table due to Python.

Have gone through the exercise, I know this is false.

Not everything can be pushed into numpy, and you can still be left with lots of loops in python.

Re: Why Python keeps growing, explained

#273

Post by throwaway744678 »

kayodelycaon wrote: post #256
blensor wrote: post #173

Earlier quoted context omitted.

I hate to admit that I very often start the python repl to just do some simple calculations. I always have multiple terminals open so instead of opening a calculator I just use python in one of the terminals.

I don't see why that's something to be ashamed of. I frequently pop open a Ruby on Rails console for this purpose. (Basically ruby's repl + libraries and language extensions.)

Eh, I type basic operations in Spolight or Google, whichever is lying on my screen!

Re: Why Python keeps growing, explained

#274

Post by codethief »

kaba0 wrote: post #239
codethief wrote: post #216

Earlier quoted context omitted.

I don't think this is true: Other Python runtimes and compilers (e.g. Nuitka) won't magically speed up your code to the level of C++. Python is primarily slowed down because of the fact that each attribute and method access results in multiple CALL instructions since it's dictionaries and magic methods all the way down.

Which can be inlined/speculated away easily. It won’t be as fast as well-optimized C++ (mostly due to memory layout), but there is no reason why it couldn’t get arbitrarily close to that.

> Which can be inlined/speculated away easily.

How so? Python is dynamically typed after all and even type annotations are merely bolted on – they don't tell you anything about the "actual" type of an object, they merely restrict your view on that object (i.e. what operations you can do on the variable without causing a type error). For instance, if you add additional properties to an object of type A via monkey-patching, you can still pass it around as object of type A.

Re: Why Python keeps growing, explained

#275

Post by OJFord »

amelius wrote: post #66
pletnes wrote: post #11

Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything. By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves progr…

There are also programmers who are tired of chasing pointers and simply want to get stuff done. E.g. people who once wrote "robust" code in Rust but were "outcompeted" left and right by coworkers who churn out shiny new things at 10x the speed.

If you're 'tired of chasing pointers', Rust's a lot closer to (and I'd argue better than) Python than say Go - it'll tell you where the issue is and usually how to fix it; Go will just blow up at run time. (Python (where applicable) will do something unexpected and wrong but potentially not error (..great!))

(Fwiw I use all three, Python professionally.)

Re: Why Python keeps growing, explained

#276

Post by _aavaa_ »

VBprogrammer wrote: post #176
dagw wrote: post #163

Earlier quoted context omitted.

I've rewritten real world performance critical numpy code in C and easily gotten 2-5x speedup on several occasions, without having to do anything overly clever on the C side (ie no SIMD or multiprocessing C code for example).

Did you rewrite the whole thing or just drop into C for the relevant module(s)? Because the ability to chuck some C into the performance critical sections of your code is another big plus for Python.

Even if you do this, you're still paying a penalty whenever you move data Python->C and C->Python.

Plus that you now need to write performant (and safe) C code, which (to me) defeats part of the reason to use Python in the first place.

Re: Why Python keeps growing, explained

#277

Post by at_a_remove »

pavlov wrote: post #142

I wish I could wave a magic wand and replace all the Python in the world with JavaScript. The languages are practically equal in terms of features. They're both typeless with layered-on crutches available to make the runaway dynamism less painful. They both have weird footguns and ugly syntax and annoying design flaws, but these are different for each. So if you're forced to use both languages, it's an endless pain i…

Ah, but with Javascript you are forced to deal with approximately ten thousand libraries from which you must choose for a given task. I hate that.

Re: Why Python keeps growing, explained

#278

Post by bakuninsbart »

faizshah wrote: post #232
blensor wrote: post #173

Earlier quoted context omitted.

I hate to admit that I very often start the python repl to just do some simple calculations. I always have multiple terminals open so instead of opening a calculator I just use python in one of the terminals.

I also use a python repl as an alternative to excel or SQL. I find myself just downloading the data as a CSV and then quickly cooking up some pandas to get a graph or aggregate some stats, it’s just so much quick easier imo.

A bit off topic, but what would you use for data "mangling"? Like joining csvs on complex conditions, cleaning tables etc. Pandas seems to be the wrong tool for this, but I still often find myself using it as in contrast to something like Excel, my steps are at least clearly documented for future use or verification.

Re: Why Python keeps growing, explained

#279

Post by trymas »

polotics wrote: post #55
teekert wrote: post #47

Earlier quoted context omitted.

Ok, then I'm not programming. Call it anything you want, I call it "Being productive." Or, "Saving on time spent clicking around in Excel." or "Automating the boring things." And I find it to be quite pleasant. Maybe it also doesn't help that out there, in the C++, Rust, Javascript, Go world I'm going to run into people with usernames like "ihatepython".

Don't feed the trolls! Case in point, this is a quote: quote_from_user_ihatepython == """ ihatepython 1 day ago | parent | context | prev | next [–] | on: Moscow Metro launches longest metro circle line You realize that the Nazis still exist and are Ukrainian, right? """

Sometimes I wish for "block" function in HN for such trolls (I really hope it's no-life troll working for 5 rubles per comment and not a real person with genuine hateful opinions like that).

Re: Why Python keeps growing, explained

#280

Post by Filligree »

traverseda wrote: post #82
pletnes wrote: post #11

Python keeps growing in number of users because it’s easy to get started, has libraries to load basically any data, and to perform any task. It’s frequently the second best language but it’s the second best language for anything. By the time a python programmer has «graduated» to learning a second language, exponential growth has created a bunch of new python programmers, most of which don’t consider themselves progr…

>and they don’t care - or know about - concurrency, memory efficiency, L2 cache misses due to pointer chasing. Also if I (a programmer) want to write really really fast code I'm probably reaching for tools like tensorflow, numpy, or jax. So there's not much incentive for me to switch to a more efficient language when as near as I can tell the best tooling for dealing with SIMD or weird gpu bullshit seems to be being…

> Also if I (a programmer) want to write really really fast code I'm probably reaching for tools like tensorflow, numpy, or jax. So there's not much incentive for me to switch to a more efficient language when as near as I can tell the best tooling for dealing with SIMD or weird gpu bullshit seems to be being created for python developers. If you want to write fast code do it in c/rust/whatever, if you want to write really fast code do it in python with .

Rather unfortunately, my current bugbear is that Pytorch is... slow. On the CPU. One of the most common suggestions for people who want stable diffusion to be faster is, wait for it, "Try getting a recent Intel CPU, you'll see a real uplift in performance".

This despite the system only keeping a single CPU core busy. Of course, that's all you can do in Python most of the time.

(You can also use larger batch sizes. But that only partially papers over the issue, and also it uses more GPU memory.)

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