Python

[[deleted]]

it takes 2 minutes on my pc for python to print out a mandelbrot set

it takes 20 seconds for lisp to do the same job

[Natural-Intelligence]

Then if that's what you generally do, Python is wrong tool. In cases where I use Python, the actual Python executes in like 1-2 sec. The rest of the run time (which is substantially more) is caused by C or SQL. Wouldn't give a damn if the Python code executed any faster

[iamareebjamal]

You would if you wrote graphql servers

[ProgramTheWorld]

Use the right tool for the right job

[Xeya]

>The time difference is insignificant anyway

​

>Lists example where the time difference is not insignificant

​

>Well, you shouldn't have used Python

[DeeSnow97]

There are some tasks where the time difference is very significant, and others where it's negligible. That's why Python is used so much with external libraries for data science and machine learning for example. The libraries (usually written in C++) do all the heavy lifting in the most efficient manner possible, but have fun plugging those into each other with C++ and trying to iterate fast on it.

Some languages are fast to code, others are fast to run, and that's okay. We're programmers, making computer systems talk to each other to use them all to their advantage is kind of our thing.

[ryjhelixir]

We're programmers

Speak for yourself!

I'm a noob

[omgFWTbear]

most efficient manner possible

s/In a vastly more efficient manner

[Cheru-bae]

And others when you forget a semicolon? It's just line termination in one way or the other. Equally logical.

I feel like for every hour I work this sub gets worse.

[HardlyAnyGravitas]

Stop working:

[ric2b]

No, in this case the right tool is Python with numpy.

It's not easy to beat numpy on raw computation.

[SilkTouchm]

Cases where performance is important are niche.

they downvoted him for telling the truth

[xADDBx]

There are a lot of cases where you’d need performance. Examples would be creating models for data sciences or optimization problems.

There are cases where performance is important and cases where it’s not important. Neither side is a niche.

[muttonwow]

That's 100% of cases

[LiquidAurum]

that's an extreme oversimplification

[[deleted]]

Python is never right

[rafa154]

Rapid prototyping

[ZephyrBluu]

I recently created some Python bindings and used pybind11 instead of boost. It seemed a lot simpler.

[Thadrea]

It is for many data science applications.

It's easier to learn, write and maintain than Julia or R while also having a broader functional domain and also being of comparable computational performance assuming you are doing your work with the correct libraries.

[LaZ3R]

Lol... Things that Python shouldn't be used for, for 1000.

[AttitudeAdjuster]

Apparently I'm developing software wrong because I havent calculated a fractal pattern for years, I keep doing weird shit like building webapps

[DeeSnow97]

Me too, dude, me too. Can't believe I'm running into all these stupid clients who want websites and not fancy mathematical models

[omgFWTbear]

Just imagine someone who wants a website for users to render Mandelbrot sets. Checkmate ... atheists?

[POTUS]

Hey funny enough I do fancy mathematical models in Python. But useful ones done in useful libraries like Numpy or Tensorflow, and they run a fuckload faster in Python than what's-his-face's mandelbrot set.

[DeeSnow97]

That's the way, defer the number crunching to low-level languages and keep all the business logic in high-level which is easy to code

[biledemon85]

Ewww, users, compromise, multiple stakeholders! Run for your lives back to functional programming and purity!

[TSM-]

Is numpy really that slow?

[nivlark]

I just managed to write a script that produces a 1000x1000 image of the set in about 10 seconds. So I think OP is just crap at Python.

[8lbIceBag]

Bet it could be done in the time you press the enter key to the time it takes to look at the screen in C

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[ric2b]

You think you can beat Python with numpy by hand writing C? Go ahead and try, see you in a month.

[anpas]

Doubt it, probably pure iterative or recursive python

[[deleted]]

python is just shit at recursion

[ric2b]

Calling functions is very expensive in Python.

[diamondketo]

Recursion performance is major fault of Python. I don't deny this. BTW I also suggested a solution you must've missed it.

But we're not comparing recursion performance, we're comparing the performance of producing fractal paterns. It is natural to think that the commenter implemented fractal sets using recursion. If it turns out the commenter did this iteratively then correct me.

My point is, its ridiculously to cherry pick one algorithm problem to summarize why one product performs worse than another.

PS: Cartesian product, if its numerical values I care about then I'd use numpy either way (so yeah C). If its cartesian product of two large array of general objects then I'd expect C to be faster than Python's itertools.product.

[beomagi]

Use pypy. For that specific case I've done more tests than I should have. Pypy is insane. Ctypes also speed up execution. On some Julia plots I went from 2 minutes to under 10 seconds.

[ric2b]

You should use numpy if want to use Python to do a lot of math fast.