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Comment by bonestormii_ | Hacker News Reader

And on top of this, it's usually not "some idiot" calling the function from a REPL. It's "some idiot's code", which may not be executed until the program is running in production somewhere if it is rare. "Oh, someone uploaded THAT kind of file? Well, let me see... AttributeError: Type SomeObject does not have attribute append. Here's a list of 47 functions that were called between the action you took and this error being raised. None of them guarantee the types going in or out, so you should probably get going waking through all this logic. You're welcome! -Python <3, XOXOXO"

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Well if a functions first run is in production youve got other problems. The idiot ref would be right.

It ran fine with all the file types we tested! A dependency loads the file into a custom type, but it handles this file type differently! Now it's a stinky old NoneType. :( :( :(

“Compile-time and runtime are less relevant notions than before-shipping and after-shipping” - Rich Hickey

https://twitter.com/richhickey/status/1063086406980026370

Hehe. But has anyone ever shipped code that won't compile? I think not.

A compile time error is a caught error. A run time error may be, or perhaps not.

This!

Yeah Python has its points where it doesn't shine, but the stacktrace does a consistently good job of telling you exactly where the logic broke down.

I love Python, and generally I agree, but the place where an error is raised can be significantly distant from the event that occurred which caused it. The lack of static typing can really make it difficult to find such bugs sometimes.

A statically typed language with compile-time type checking would flag that immediately, and chances are your IDE will show the error before it even gets to that point.

Type hints are a thing, but then you are already moving in that direction while remaining in python.

Agree that there's a big difference between the error happening at compile time vs. happening at run time in prod, but I personally find the python stacktrace much more descriptive of how we got to the error than a lot of other languages.

A certain amount of it is probably a familiarity thing, but I do usually find myself able to parse it to the point of what line in which file things started to go wrong.

Other languages can do the same, they just deliberately make the decision not to because of performance. Ruby has the same nice stacktrace (even nicer).

There was some work that took ML compile time errors and created Python-like stacktraces of how this specific error could blow up at runtime in a Python-like fashion. Students found those concrete errors with concrete values easier to reason about than abstract compile time errors.

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