NumPy is incredible to me: it serves not only as a critical bare-metal layer, but also an essential tool in its own right, and I can’t imagine using Python without it. I do numerical work—ML/data science/statistics—and I simply couldn’t accomplish any of what I do without the functionality provided by NumPy. np.array alone is worth all the king’s gold.
It is interesting to me that in many respects it serves as “guts”. I definitely drop down to use numpy directly with regularity. But it’s also possible to do 80-90% of the job without ever explicitly using the module itself. It’s baked in everywhere, to the point that it feels like just another standard library.
Exciting to see progress! Keep up the good work, numpy team :)
Heh, I’m probably misusing that term—forgive me, I’m just a script kiddy! :D
I meant that it can serve the role of low-level, nitty gritty machinery, entirely separate from its use case as a module unto its own right.
Eg, pandas (in some sense) is just a convenience layer on top of numpy—but to me that’s like saying any piece of software is “just a convenience layer on top of python.” It’s partly a means to an end! Not just an end unto itself.
Numpy enables a whole new class of functionality, independent of its direct use as part of my software. Is there a better word for that?
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NumPy is incredible to me: it serves not only as a critical bare-metal layer, but also an essential tool in its own right, and I can’t imagine using Python without it. I do numerical work—ML/data science/statistics—and I simply couldn’t accomplish any of what I do without the functionality provided by NumPy. np.array alone is worth all the king’s gold.
It is interesting to me that in many respects it serves as “guts”. I definitely drop down to use numpy directly with regularity. But it’s also possible to do 80-90% of the job without ever explicitly using the module itself. It’s baked in everywhere, to the point that it feels like just another standard library.
Exciting to see progress! Keep up the good work, numpy team :)
I agree with everything you say, but I don't understand this part:
What's bare-metal about NumPy??
Heh, I’m probably misusing that term—forgive me, I’m just a script kiddy! :D
I meant that it can serve the role of low-level, nitty gritty machinery, entirely separate from its use case as a module unto its own right.
Eg, pandas (in some sense) is just a convenience layer on top of numpy—but to me that’s like saying any piece of software is “just a convenience layer on top of python.” It’s partly a means to an end! Not just an end unto itself.
Numpy enables a whole new class of functionality, independent of its direct use as part of my software. Is there a better word for that?
I think you sum it up nicely! The better word you're looking for might be cornerstone?
perhaps foundation, or base layer.
Sidebar: I originally used the word “gunmetal” and that...was even less correct.
Get this guy a dictionary!
Curious question - do you not use dataframes instead ? Is that not much nicer as a UX ?
Yeah! That’s what I mean...under the hood data frames use numpy arrays, but the abstractions of pandas are much easier to work with.