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Restore missing __main__ logs #896

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merged 4 commits into from May 21, 2022
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7 changes: 3 additions & 4 deletions twine/cli.py
Expand Up @@ -52,6 +52,7 @@ def configure_output() -> None:
# test_main.py due to capsys not being cleared.
logging.config.dictConfig(
{
"disable_existing_loggers": False,
"version": 1,
"handlers": {
"console": {
Expand All @@ -61,10 +62,8 @@ def configure_output() -> None:
"highlighter": rich.highlighter.NullHighlighter(),
}
},
"loggers": {
"twine": {
"handlers": ["console"],
},
"root": {
"handlers": ["console"],
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@bhrutledge bhrutledge May 8, 2022

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@sigmavirus24 @jaraco I think this configuration means that any logs from dependencies will come through. By default, that would be WARNING and above; --verbose would enable INFO. I'm not sure if that's desired behavior or not; it could be useful, or it could be noisy/confusing.

Another option that maintains the current behavior of only enabling twine logs is to explicitly use the twine logger in __main__, which I started with, but reverted: 698f940

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Huh, that actually looks a bit nicer (hardcoding the logger's name to be "twine"). Whether you put that back or not, I've learned from this to always use a hardcoded logger name instead of __name__ if there's a chance of the file in question being executed as __main__...
This is one of those cases where Python's __name__ == '__main__' weirdness shows itself for the hack it is. 😛

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I've learned from this to always use a hardcoded logger name instead of __name__ if there's a chance of the file in question being executed as __main__

@bayersglassey-zesty I think it's okay to use __name__ in that situation, under most circumstances. The reason it was an issue here is because I disabled all the other existing loggers when setting up the twine logger.

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That's fair.
My thinking is, I don't think there's ever a case where I want to target the logger for __main__.
Like, it would be weird to do logging.getLogger('__main__').setLevel(logging.INFO), because then if one of the functions in __main__ were ever factored out, it would suddenly be using a different logger.
You know?
Anyway. Weird silly edge cases. But something tells me it's nicer to know for sure what your logger's name is. 🤷

That said, I have absolutely no preference in this case, and actually I guess I've also learned that maybe it's nicer to run things by their "entry points" (as defined by pip and installed into virtualenv's bin directory), since then none of the library's modules are being loaded as __main__ and possibly causing __name__ weirdness...

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Actually, I just looked at which twine and clued into the fact that it's not even twine/__init__.py which ends up being run, it's twine/__main__.py.
And if I make my own Python module with __init__.py and __main__.py in it, it's the __main__.py which gets run when I run the module with python -m.
I learned something today...

And here are the docs for that: https://docs.python.org/3/library/__main__.html#main-py-in-python-packages

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...so actually, I guess what I'll be taking away from this is... to keep __main__.py as short as possible, something like:

from my_library import main
main()

...so that all the code -- in particular, any code which creates loggers or uses __name__ for anything other than the == '__main__' check -- lives in a separate module. 🤔

Edit: the docs actually say __main__.py shouldn't even bother with an if __name__ == '__main__' check, so I updated my code snippet! https://docs.python.org/3/library/__main__.html#id1

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@bayersglassey-zesty I'm glad you learned something from this. 😉

I guess what I'll be taking away from this is... to keep __main__.py as short as possible

That's a good point. Most of Twine's CLI logic is in cli.dispatch, but this PR shows that there's some non-trivial setup that could be moved to something like cli.main. I might follow-up with that refactoring.

maybe it's nicer to run things by their "entry points" (as defined by pip and installed into virtualenv's bin directory)

I think this depends on the tool and the situation. One nice thing about using python -m package is that you know that you're using the package that's installed in the python environment that you're using. When you run the package entrypoint, it'll be whichever one is found first on your $PATH, which might not be the same as python. This is particularly relevant for pip, and why it's a good habit to always use python -m pip.

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@sigmavirus24 @jaraco I think this configuration means that any logs from dependencies will come through. By default, that would be WARNING and above; --verbose would enable INFO. I'm not sure if that's desired behavior or not; it could be useful, or it could be noisy/confusing.

Another option that maintains the current behavior of only enabling twine logs is to explicitly use the twine logger in __main__, which I started with, but reverted: 698f940

I suspect it would be undesirable to include output from dependencies if the context (logger name) isn't present. On the other hand, since twine is using logging as the mechanism for output, maybe that's what one would expect. I'm fine either way. Let's try it out and see how it behaves.

},
}
)
Expand Down