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Ask HN: Why did Python win?

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Re: Ask HN: Why did Python win?

#401

Post by _fdsfs12123 »

Funny story:

When I took an "intro to programming for scientists" type course in early 2010s, it was taught in Ruby. This was at the height of ROR's popularity, and the instructor must have been curious about Ruby.

So Ruby became my first language, and for a year after taking the course I did all my scripting in Ruby. There was nobody around me (a lab full of C and Fortran coders) to tell me otherwise. Eventually, I switched to... MATLAB, and a couple years later to Python.

And in 2023, I don't remember a lick of Ruby. But I remember it was fun to code in it.

Re: Ask HN: Why did Python win?

#404

Post by mdbauman »

rout39574 wrote: post #250
Loeffelmann wrote: post #114

Earlier quoted context omitted.

> There should be one-- and preferably only one --obvious way to do it. This is so hilariously wrong in python though

So I imagine you have that perspective because you started less than 20 years ago. In some ways the idea of the Pythonic Way to do things evolved in opposition to Perl's vigorous advocacy of More Than One Way. Python has been really winning for some time, so it's natural that its ideological discipline has grown ragged. The crop of kids who value options above consistency don't have the scars of the Perl age to infor…

Back when I decided it was time to add a scripting language, Perl and Python seemed like the obvious choices, and in my mind were equally good options. I asked my best friend which I should choose, and he more or less said, "You can't go wrong with either one, but when you ask for help Perl people are assholes and Python people are nice."

I can't confirm his thoughts on Perl and I haven't interacted much with Ruby, but the Python community is definitely welcoming and patient in my experience. I wouldn't be surprised if this was a significant factor in Python's prevalence over Perl, Ruby, or anything else.

Re: Ask HN: Why did Python win?

#405

Post by aae42 »

skeletal88 wrote: post #251
dmazzoni wrote: post #91

Earlier quoted context omitted.

I think Python was popular as a general-purpose language first. After all, there was a reason people put so much effort into writing Numpy in the first place. I think a lot of people were attracted to the language design, as captured in the Zen of Python ( https://peps.python.org/pep-0020/ ), such as: Explicit is better than implicit. Readability counts. Errors should never pass silently (unless explicitly silenced)…

There are just too many ways to do things in Ruby. How many forms for an if-else or for loopin can you name in Ruby? Just as the simplest example. Monkeypatching is also awful for readability. Explicit imports are way more readable than things appearing into current namespace implicit kind of stuff like it happens with Ruby

I've been writing Ruby daily for years and never written a `for` loop

Re: Ask HN: Why did Python win?

#406

Post by BlueTemplar »

dekhn wrote: post #154
qsort wrote: post #76

Earlier quoted context omitted.

Numpy is certainly amazing, but there are tons of competitors in the data/scientific space, which pure "A-type" data scientists tend to prefer: R, SSPS, Matlab... The difference is that Python doesn't entirely suck as a general-purpose language. Sure, you might have better options, but it's still reasonable to write almost anything in Python. Other scripting languages like Ruby, JS and Lua are probably a little bit b…

numpy exists (somewhat indirectly) because matlab cost $$$. and now numpy is a far larger use of matlab's concepts than matlab will ever be. I haven't seen anything an "A-type" data scientist needs in R/SAS/SPSS that was intrinsic to the language and couldn't be ported to Python. I don't want a "data/scientific" language, or a "web" language, or a "UI" language- I want one language that explicitly supports all the us…

Well, why didn't the free alternatives to Matlab like Octave or Scilab win out then ?

Re: Ask HN: Why did Python win?

#407

Post by selcuka »

shpx wrote: post #239
thesuperbigfrog wrote: post #207

Earlier quoted context omitted.

As evidenced by the unified Python library / dependency management system.

I use pip 100% of the time

pip (with venvs, which is a built-in Python feature) covers 99% percent of all use cases.

Yes, its dependency resolution could have been better, and lock files are nice (which can be emulated using constraints [1]) but I don't understand why people are so busy writing alternatives. I work on pretty sophisticated codebases on a daily basis and haven't used anything but pip.

[1] https://pip.pypa.io/en/stable/user_guide/#constraints-files

Re: Ask HN: Why did Python win?

#408

Post by mgl »

r_thambapillai wrote: post #53

Python ended up 'specializing' in data contexts, thanks to Numpy / Pandas, and as a result, ended up becoming the first exposure to programming than anyone doing data stuff had. That was millions of people. In that space, it had no competitors. Ruby ended up 'specializing' in web dev, because of Rails. But when Node and React came out, Ruby on Rails had to compete with Nodejs + React / MERN as a way of building a web…

But still slower and more energy consuming than Javascript or Java unless you use it like a wrapper of C/C++ libraries:

https://stratoflow.com/efficient-and-environment-friendly-pr...

Re: Ask HN: Why did Python win?

#409

Post by bigger_cheese »

dekhn wrote: post #154
qsort wrote: post #76

Earlier quoted context omitted.

Numpy is certainly amazing, but there are tons of competitors in the data/scientific space, which pure "A-type" data scientists tend to prefer: R, SSPS, Matlab... The difference is that Python doesn't entirely suck as a general-purpose language. Sure, you might have better options, but it's still reasonable to write almost anything in Python. Other scripting languages like Ruby, JS and Lua are probably a little bit b…

numpy exists (somewhat indirectly) because matlab cost $$$. and now numpy is a far larger use of matlab's concepts than matlab will ever be. I haven't seen anything an "A-type" data scientist needs in R/SAS/SPSS that was intrinsic to the language and couldn't be ported to Python. I don't want a "data/scientific" language, or a "web" language, or a "UI" language- I want one language that explicitly supports all the us…

>I haven't seen anything an "A-type" data scientist needs in R/SAS/SPSS that was intrinsic to the language and couldn't be ported to Python.

I don't know what "A-Type" is so I might be misunderstanding you.

For SAS at least in my Org what keeps it entrenched is Enterprise Guide and the associated environment. Having a drag and drop GUI to do the data extraction and manipulation and the analytical tasks makes it very easy for non experts to be incredibly productive. The people that use it here are Engineers (Non-software variety) and Finance accountant types. These people would not be productive writing python code (or R) but still need to use something heavier then excel for data analysis.

Over the years we have chipped away at parts of SAS with things like Power BI and Azure ML Studio but I don't see python playing in the same space.

Re: Ask HN: Why did Python win?

#410

Post by cutler »

VerminOctopus1 wrote: post #235
cutler wrote: post #103

Whilst the design of Ruby is far superior, Python has a wider range of data structures which may explain why it managed to gain a foothold in the scientific world. Both are multi-paradigm languages but procedural Python is also a little more idiomatic than its equivalent in Ruby which maybe makes Python easier for scientists who don't want to go all-in learning a more elegant language. Pretty soon in Python's rise it…

What about the design of Ruby makes it far superior?

Blocks, Procs and lambdas compared with Python's crippled equivalent. Elegant built-in regex handling curated from Perl. Concise, expressive one-liners. Perlish list shorthand: %w(aa bb cc) => ['aa', 'bb', 'cc']. Everything an expression.
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