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Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by adrien-treuille on Saturday September 21, 2019 @05:46PM (#21038104)
This post combines pretty much every technology I'm obsessed with right now: Python, Rust, Pandas, Numpy, and LLVM. Yess!!!
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by superdimwit on Saturday September 21, 2019 @07:10PM (#21038479)
If these things interest you, check out Julia
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by mlevental on Sunday September 22, 2019 @03:16AM (#21040083)
how do you know someone uses Julia? don't worry they'll tell you.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by laichzeit0 on Sunday September 22, 2019 @03:36AM (#21040130)
The same could be said for every Rust fanboy that feels the need to mention Rust whenever an article about C or anything implemented in C is brought up.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by atoav on Sunday September 22, 2019 @06:33AM (#21040643)
Or every C fanboy brings up C whenever Rust is mentioned.

As somebody who uses both, I don’t understand the whole territorial conflicts in this space. Any C programmer can learn a ton by the paradigm Rust uses. Even if Rust would fade into oblivion tomorrow, the lessons I learned by using it will remain valueable enough for me not to regret having learned it.

C is always going to be needed, given the size of the codebase and the amount of embedded stuff written in it. It comes – however – with a waggon full of dangerous traps and gotchas and in practise very few people are good enough to always avoid them or mitigate the risks created by them. I don’t see any reason why C shouldn’t get better in these areas for the benefit of everyone involved.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by L0stLink on Sunday September 22, 2019 @04:03AM (#21040223)
lets generalize it further: People will take chances to bring up what they are passionate about.

I can relate to this, it is not unreasonable for me.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by tempguy9999 on Sunday September 22, 2019 @07:14AM (#21040767)
No disrespect to you but passion in people can come from deep knowledge of a subject but IME much more commonly comes from lack of experience with alternatives.

I've noticed the younger people are the more likely they are to be passionate, which I put down mainly to not knowing any better. Once one has more of the experience that places you higher up where you can see further, suddenly one's own plot of land doesn't seem so special.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by L0stLink on Sunday September 22, 2019 @02:23PM (#21042956)
Does that justify the snide remarks? We should show more tolerance, there might not be a tool in existence that does not have its disadvantages along with its advantages. Healthy discussion around facts is beneficial, dismissing people for being passionate is not.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by tempguy9999 on Sunday September 22, 2019 @02:45PM (#21043095)
That did sound snide but it wasn't meant that way. I'm not sure how I should have done it better.

> dismissing people for being passionate is not

Seems I didn't say that well either. Passion that comes from knowledge and experience is good. If it comes from inexperience then maybe not so good because it isn't "Healthy discussion around facts" but around existing biases.

Edit: genuinely no offence intended.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by L0stLink on Sunday September 22, 2019 @04:05PM (#21043596)
None taken :), and my comment was about the snide in great (x3) grand parent comment(s). The whole fanboy/vegan/how do you know chain.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by integricho on Sunday September 22, 2019 @07:00AM (#21040709)
The vegans of the programming community.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by whoevercares on Saturday September 21, 2019 @05:48PM (#21038114)
Just a word of caution, always obsess with product and customer needs first :) In ML/data science tech first normally won’t end up well
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by d33 on Saturday September 21, 2019 @07:00PM (#21038438)
It's important to enjoy your work, which is - among other causes - about having right tools. Also, some of us actually get to have some influence over what language we write our projects in.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by ekianjo on Saturday September 21, 2019 @10:43PM (#21039312)
I think you misunderstand the parent. The obsession to always focus on tools is I think, what they described. In the end of the day what matters is what you produce, not what tools you used. Nobody cares about what you used, apart from engineers.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by nojvek on Sunday September 22, 2019 @12:12AM (#21039622)
It’s not mutually exclusive. We are craftsmen and craftswomen. Definitely obsess over the problem but also obsess over the tools used to carve out the most usable elegant and efficient solution.

It’s really asking the same questions over and over again. Can we do better ? Does this tool allow me to be efficient, write safer and faster code, how good is the adjacent libraries and ecosystem ? What other kinds of things does it make it possible to solve?

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by naniwaduni on Saturday September 21, 2019 @11:29PM (#21039473)
You care.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by toss1 on Sunday September 22, 2019 @12:15AM (#21039632)
Are you coding as a hobby or a profession?

If you are a professional, you will use the most effective tool for the job - to get results. What tool will produce the best results - schedule, budget, quality, maintainability, scalabi, portability, etc.?

Other than outliers that will crush your productivity, or multiply it, your feelings are pretty irrelevant.

Similarly, when you get into a racecar, your feelings about your preferred driving style are irrelevant - if you can change the setup to accommodate your style without slowing jt down, great = but if not, your job is to adapt to the situation and reliably get the best possible result.

Either way, you have fun and produce a crap result, you will not be congratulated (or re-hired), and if you have little fun and produce a great result, you'll get both.

If it's a hobby, do whatever you want.

Obviously, in terms of professional development, you want to use more forward looking tools, but what is the best measure of that - your feelings or results?

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by susano on Sunday September 22, 2019 @02:05AM (#21039927)
I am a professional and I do not choose my tools based on the job.

I choose the best tools for me, invest a lot of time in getting better at them, and choose jobs I can do with minimal changes to my toolset.

To expand your analogy, if I have spent the last few years of my life getting better at driving bulldozers, I will not take any job requiring me to get into a racecar.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by laichzeit0 on Sunday September 22, 2019 @03:39AM (#21040146)
> What tool will produce the best results - schedule, budget, quality, maintainability, scalabi, portability, etc.?

Old, boring, mature tools where the limitations are well understood.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by nothrabannosir on Sunday September 22, 2019 @03:42AM (#21040158)
> Are you coding as a hobby or a profession?

This isn’t mutually exclusive, surely. If anything you’d expect it to be quite closely correlated.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by turk73 on Sunday September 22, 2019 @11:30AM (#21041795)
I sort of disagree with your main assertion. I do big data for a living and what I have seen is that our architecture is dictated to us from above for reasons of "fashion" not really for any reasons of practicality.

I'm actually looking for a different job for that reason.

We are required to used Java on K8s, Kafka & Cassandra for every single solution big or small because it is fashionable, not because it gets the job done well or for any other reason. I can even demonstrate how a couple of Python scripts and Pandas could do all the same work with far less overhead and achieve the same results. Crickets. Python is not sexy where I am, it is the language of peasants, apparently. Not sure what to make of it all, but that is my reality right now.

Also, I don't think you know anything at all about driving race cars. The driver has a tremendous amount of input into the car's setup because it's his life on the line out on the track. "Adapting to the situation" gets finishes, not wins.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by toss1 on Sunday September 22, 2019 @06:32PM (#21044402)
Looks like we agree more than disagree. Seems like whoever is deciding on the tools, are failing to do so based on the job/project, instead opting for 'fashion' or whatever.

Good reason to seek a new situation, since you have neither appropriate tools selected for you nor input to select better ones.

Racecars? Yeah, I've only won some SCCA super-regional championships. Yes the driver does have a very large inptut into the setup, BUT it is within the constraint of the combination of the setup change and the improved driver feel must make the combination of car/driver faster. And yes, sometimes a change that makes the car technically a bit slower but gives the driver more confidence will result in faster net lap times -- and those are OK. But whatever the setup is, at the end of the test sessions, whether the car feels great or feels like crap, it's the driver's job to get the most out of it.

And I've had many situations both in the racecar and in international alpine ski racing where something felt weird/odd/unfamiliar/scary, but was fast as heck, so it was my job to adapt, rather than go back into my comfort zone.

Better to keep pushing outside your comfort zone, use tools/setups that get better results, and change your 'feel' to appreciate the better setup.

Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by mkl on Saturday September 21, 2019 @06:52PM (#21038395)
People aren't all or always working on products or serving customers.
Re:Weld: Accelerating numpy, scikit and pandas as much as 10... by cortesoft on Saturday September 21, 2019 @06:41PM (#21038345)
Unless they are just talking about personal projects?