181–190 of 224 posts
As someone who works with Python every day, this isn't surprising. I forget where I heard/read it, but someone made the claim that Python is the "second best language for everything" (paraphrasing) and I couldn't agree more. Need to create a web app that interfaces with a data pipeline? Python/Django/Flask is perfect. There are countless other examples too.
Earlier quoted context omitted.
The problem is that data science, often, isn't just data science. It might involve doing a bunch of activities that are strictly not data science - scraping data off the web (Python has requests), visualization for some understanding (Python has dozens of nifty libraries), store data in a small db (Python works nicely with sqllite, among others), convert all of this into an app (Python has Flask, again among others).…
Yes, in principle Julia should be able to do all of these things too, but it simply doesn't have the decades-old history of libraries to stand on yet.
Python 2 advocates were quite firm in telling us that Python 3 and its incompatibility with Python 2 had killed Python and people would abandon Python altogether in droves for other languages. This post is suggesting the opposite, that Python is more healthy than ever and growing incredibly fast.
Three of us (including me), in an academic lab, are making the jump from matlab to python. We use py3 (of Anaconda, on Windows10). We like it, but we are constantly screaming and bitching about the complications of 2 3 ("Ahhh X and Y module only works on py2!", "Ahhh device developer only provides example code for Labview and Matlab!", "Ahhh python isn't even supported for this device/application!"). Package manageme…
Earlier quoted context omitted.
Three of us (including me), in an academic lab, are making the jump from matlab to python. We use py3 (of Anaconda, on Windows10). We like it, but we are constantly screaming and bitching about the complications of 2 3 ("Ahhh X and Y module only works on py2!", "Ahhh device developer only provides example code for Labview and Matlab!", "Ahhh python isn't even supported for this device/application!"). Package manageme…
I think you're right, the biggest pain for a general developer for Python is determining which package manager to use. I'm thankfully insulated from it a bit due to using Docker for a lot of my development, but I hate the fact that Pip won't install to your home/project directory unless you coax it to (and sometimes still won't even if you give it all the proper environment variables), and I think virtual environment…
Earlier quoted context omitted.
Three of us (including me), in an academic lab, are making the jump from matlab to python. We use py3 (of Anaconda, on Windows10). We like it, but we are constantly screaming and bitching about the complications of 2 3 ("Ahhh X and Y module only works on py2!", "Ahhh device developer only provides example code for Labview and Matlab!", "Ahhh python isn't even supported for this device/application!"). Package manageme…
>I think the one thing we are all learning from this experience is: JUST USE UBUNTU, doing python with Windows is a headache. Meh. I use python on Windows all the time - it's not a problem. Mostly pip just works. Of course, I have over a decade of experience with Python - albeit only the last few years in Windows.
As someone who works with Python every day, this isn't surprising. I forget where I heard/read it, but someone made the claim that Python is the "second best language for everything" (paraphrasing) and I couldn't agree more. Need to create a web app that interfaces with a data pipeline? Python/Django/Flask is perfect. There are countless other examples too.
Which is the first?
The point, I guess, is that Python isn't really optimal at anything but is very good at a lot of things.
Realistically, there are enough software fields that Python just isn't applicable for this to be taken with a pinch of salt. However, as a language, it does have quite a large sweet spot: easy to pick up, expressive, integrates well with low level languages for heavy lifting and almost perl quantities of libraries.
IMO its popularity is justified although I'm not a fan myself.
Earlier quoted context omitted.
Those all seem like pretty basic developer best practices to me. Of course each project needs it's own virtualenv. In fact, each project should have it's own docker image. Why install an application library to the entire system? That is not a good idea in ANY language. And of course scripts need to use the right virtualenv. Or better yet - why not put each app in it's own docker? That bundles up everything into a sin…
> Those all seem like pretty basic developer best practices to me. Those are all bleeding edge developer best practices that didn't exist five years ago. Folks coming from matlab (an example I read above,) probably aren't in the industry and many likely don't even know docker exists OR why they would want to use it.
And the GP was saying that the ruby package manager is more magical then the python package manager... when pip solved all of the complaints mentioned.
Odd.
As someone who has been using Python since 2000 roughly, another minor factor (besides the obvious data science factors) might also be the decline in Ruby. Ruby (and Rails) growth in the 2005-2010 era, seemed to noticeably put the brakes on Python's previous growth up till that point. Back then Ruby had all the boosterism/hype and Python was the supposedly "boring/legacy" option. Even now, Python's growth doesn't see…
I don't think hype is the main factor. Ruby's decline is due to its narrow focus on web development and Rails in particular. Whilst there certainly are gems covering other areas of computing Ruby never seemed to diversify the way Python has. With Node.js eating Ruby's lunch in the web development sphere Ruby is left looking like the single-commodity Venezuelan economy. Let me add that I think Rails is a fantastic pie…
Python is mainly popular because of historical reasons. Not because of some magical functionality it has over ruby, here are a few key points:
Ruby was created in 1996 and Python in 1989. Python was the main language chosen by academia because at the time no one really knew about ruby, until its later explosion in popularity thanks to Rails in 2000's.
It was initially used at google which gave it a huge boost
It is also the go to language in the scientific community.
Ruby_can_ become a perfect candidate along side python should there ever be competitive enough scientific libraries just like NumPy, SciPy and so on.
That being said, I love both languages and communities!
As someone who works with Python every day, this isn't surprising. I forget where I heard/read it, but someone made the claim that Python is the "second best language for everything" (paraphrasing) and I couldn't agree more. Need to create a web app that interfaces with a data pipeline? Python/Django/Flask is perfect. There are countless other examples too.
Which is the first?
Earlier quoted context omitted.
>I think the one thing we are all learning from this experience is: JUST USE UBUNTU, doing python with Windows is a headache. Meh. I use python on Windows all the time - it's not a problem. Mostly pip just works. Of course, I have over a decade of experience with Python - albeit only the last few years in Windows.
What's the point of using Windows as a Dev or data science environment anyway? Everything is built and works well in Linux, scripting is powerful, it's free, etc.. seriously asking.
It's easier for me to install the Python libraries I need in Windows than to install them on Linux where I don't have root privileges.