[dagw]

I know you are being factious, but it is much worse than Electron apps. One advantage of JavaScript's focus on smaller libraries and aggressive tree shaking at build time is that it is pretty good at only shipping code that is actually called.

In the python world you have to do all the work by hand. I've literally spend time copying and pasting code out of libraries and into my code just so that my build wouldn't balloon by 100MB because I wanted to call a 100 line function.

[Wowfunhappy]

Is Python actually so poor though?

This is an extremely unscientific comparison, because I don't feel like creating custom binaries specifically to test with. But I happen to have a copy of youtube-dl on my hard drive, and it's 1.8 MB. I'm not sure whether youtube-dl creates their binaries with PyInstaller, but youtube-dl is written in Python, and the binary is a single file that can be run without a Python installation.

I also have a copy of docker-compose, which I know for a fact is created with Pyinstaller. That one clocks in at a significantly worse 10.8 MB (so perhaps Pyinstaller is the culprit and youtube-dl is doing something unique), but that's still relatively small for a considerably complex program.

Lastly, I have a binary called "toggle-switchmate3", which I created myself some years ago. I have a set of Switchmate light switches set up in my apartment, and the best way I could find to control them from a Mac was via this Node package: https://www.npmjs.com/package/node-switchmate3. NPM's dependency mess freaks me out, so I set everything up in a virtual machine, and then created a binary with "pkg", the Node equivalent of pyinstaller.

"Toggle-switchmate3" is 36.1 MB. And it's not a standalone binary—it requires a separate "binding.node" file to be in the same directory.

[dagw]

Is Python actually so poor though?

Perhaps not in the general case, but in many cases it absolutely is. The problem isn't python itself but libraries. While JavaScript tends towards dozens of small libraries that do only one thing, python tends towards one library that does everything. Which is really handy in most cases, but very painful when you want to package something that just uses one of those functions.

In a concrete case I had a small script that ran a particular edge detection algorithm on an image and returned the edges in geojson format. The whole script was less than 300 lines. But the built dist weighed in at several hundred MB as it pulled in the entirety of numpy, scipy, scikit-image, fiona, shapely and rasterio, despite needing only maybe a couple of percent of the functionality of each library.