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421 points briankelly | 1 comments | | HN request time: 0s | source
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necovek ◴[] No.43575664[source]
The premise might possibly be true, but as an actually seasoned Python developer, I've taken a look at one file: https://github.com/dx-tooling/platform-problem-monitoring-co...

All of it smells of a (lousy) junior software engineer: from configuring root logger at the top, module level (which relies on module import caching not to be reapplied), over not using a stdlib config file parser and building one themselves, to a raciness in load_json where it's checked for file existence with an if and then carrying on as if the file is certainly there...

In a nutshell, if the rest of it is like this, it simply sucks.

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milicat ◴[] No.43575953[source]
The more I browse through this, the more I agree. I feel like one could delete almost all comments from that project without losing any information – which means, at least the variable naming is (probably?) sensible. Then again, I don't know the application domain.

Also…

  def _save_current_date_time(current_date_time_file: str, current_date_time: str) -> None:
    with Path(current_date_time_file).open("w") as f:
      f.write(current_date_time)
there is a lot of obviously useful abstraction being missed, wasting lines of code that will all need to be maintained.

The scary thing is: I have seen professional human developers write worse code.

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1. FeepingCreature ◴[] No.43579037[source]
> there is a lot of obviously useful abstraction being missed, wasting lines of code that will all need to be maintained.

This is a human sentiment because we can fairly easily pick up abstractions during reading. AIs have a much harder time with this - they can do it, but it takes up very limited cognitive resources. In contrast, rewriting the entire software for a change is cheap and easy. So to a point, flat and redundant code is actually beneficial for a LLM.

Remember, the code is written primarily for AIs to read and only incidentally for humans to execute :)