Open up any serious Python project and you'll find significant dependencies. Math, graphics, IO, stats, ML... anything you really want to do requires dependencies. In fact, one of my biggest issues with Python is the cross-platform incompatibility of many packages which makes it a terrible choice for my deployment. (Even worse if the project has Cython components!)
I often end up having to scour github for forked pywheels that aren't vetted. Which are then cloned ad infinitum.
Its a tradeoff between extensibility and open source / free software, and robustness.
Math -> You use numpy, scipy, none of these have any significant dependencies. And libraries this complex are not even available for node.
Graphics -> Python comes with included Tkinter, and others are also one include away.
Stats -> Scipy does a lot of the stuff. There is a built in package for stats. Again, no stats package has 100 dependencies, and node doesn't even have anything with even 1/10th of the features
ML -> I mean node has nothing here, nothing, while pytorch has total of six dependencies. In node, left pad might have these many.
Python doesn't need left pad, isNumber, isInteger, isOdd, isPromise , take your pic.
> In fact, one of my biggest issues with Python is the cross-platform incompatibility of many packages which makes it a terrible choice for my deployment. (Even worse if the project has Cython components!)
But python has high performance libraries written in C, can you even use node for any of the cases where python has platform compat issues?
It is a tradeoff, and there is no comparison. Python needs far far less dependencies than node. e.g, Flask has 2 total dependencies, express has 48 direct dependencies, and even then flask comes out ahead on features, so much so that you would need many more packages to do the same stuff with express.
I'm not comparing functionality of Node and Python. They are different beasts. I was pointing out problems inherent with Python packaging, which you didn't even address in your fanboy rant.
Open up any serious Python project and you'll find significant dependencies. Math, graphics, IO, stats, ML... anything you really want to do requires dependencies. In fact, one of my biggest issues with Python is the cross-platform incompatibility of many packages which makes it a terrible choice for my deployment. (Even worse if the project has Cython components!)
I often end up having to scour github for forked pywheels that aren't vetted. Which are then cloned ad infinitum.
Its a tradeoff between extensibility and open source / free software, and robustness.