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by sixhobbits
2213 days ago
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I've spent far too many hours fighting with these tools in two completely different scenarios * Developing and deploying production Python solutions * Helping beginners run their first script While it's great for beginners to use the same tools that are used in industry, I strongly believe that the problem nearly all of these tools face is that they can't decide whether they want to _manage_ complexity or _hide_ complexity. You can't do both. Some of them do a fairly good job at managing complexity. None of them do a good job of hiding it. The dream of getting Python to "just work" on any OS is close to impossible (online tools like repl.it are the closest I've found but introduce their own limtiations). I recently saw a place force their beginner students onto Conda in Docker because getting people started with Conda was too hard. If you're battling with the complexity of your current layer of abstraction, sometimes it's better to start removing abstraction rather than adding more. That said, I'm also a happy user of `pip` and `virtualenv` and while I'm sure that many people can use the others for more specific needs, I think defaulting to them because they aim to be "simpler" is nearly always a mistake. I still teach beginners to install packages system wide without touching venv at first - it's enough to get you through your first 2-3 years of programming usually. |
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I picked up Pipenv when a point-point release of a dependency broke a production deployment. Pipenv's dependency locking meant that I wouldn't get surprised like that again.
Part of why this topic comes up so much is the desire to run with a language before learning to walk with it, perhaps. I'm a big fan of Poetry, but I like it because I know what it gives me compared to vanilla pip and a setup.py file.
Installing dependencies at the OS level will get you far as a beginner. And when the time comes that you need a virtual environment, you'll probably know.