[bbrunner]

To me, the core points seem like table stakes knowledge that one should have before jumping into development with ANY language, not just Python. Every language is a tool that is good at some things and not good at others. Cue the standard if all you have is a hammer, every problem looks like a nail.

A few core things:

The GIL problem is frustrating. I generally just try to avoid writing threaded code and instead execute calls asynchronously or run parallel instances and work with Celery or something similar. For web applications, this tends to work well enough for me personally but this is definitely a valid issue.

Python2 vs Python3 is sort of a done deal at this point, in my opinion. I was a big holdout on moving to 3 for a while but, for the past couple of years, I haven't had more than 1 or 2 cases where I had serious issues. I don't have to deal with legacy codebases though.

On a larger note, I would say that this all points to the fact that it is easy to do things the "wrong way" in Python. The accessibility of the language is great, but it is not without its issues if you go in expecting it to be a fenced-in playground with batteries included (to mix metaphors).

[btashton]

The "GIL" problem is so over exaggerated for most problems. A significant amount of threaded code is IO bound and in most of those cases the GIL gets out of the way. Checkout the cpython code around the calls to things like select, poll, epoll. If you are needing to do high performance number crunching across multiple cores, then yeah it's a little more work, but it's gotten easier and easier to write some C libraries for that or leverage something like numpy.

[bbrunner]

I would agree it's over-exaggerated. In my day to day work, the GIL has rarely, if ever, been the performance bottleneck. It usually traces back to something outside of Python (e.g. a slow DB query or a slow API call) or to something that has been implemented in python in an inefficient way (e.g. writing something O(n^2) when if you read your algos 101 book or even just searched stack overflow you could find an O(n) solution).

I also think that the whole "drop down to C argument" is sometimes viewed as a cop-out when criticizing python, but I personally believe that being proficient at high-level and low-level languages, knowing their strengths and weaknesses, and transitioning between them when it makes sense is stronger than just using purely high OR low-level. It's sort of like having multiple gears on a car: you need all of them, and they are all useful and most opportune in different scenarios.

[wslh]

My issue in favor of Python is the clarity and brevity I cannot find in other programming languages. For example, doing a web service with Flask is a relaxed task with minimum code that after months continues to be clear and without a lot of context needed. NodeJS/express? My stomach cannot pass callbacks nor promises (I am aging, sure).

In terms of progress I love what .NET has achieved and found that libs like Nancy [1] are good to explore.

Disclaimer: I am not working as a professional programmer anymore so I look for fun and "move faster" tools.

[1] http://nancyfx.org