Would python decorators be better for something like this?
I always get squeamish when I see magic comments
I always get squeamish when I see magic comments
You should be squeamish about running the code without reading it first, given that you're pair-programming with a bot.
It's funny, the first version of this project[0] let you do exactly that, e.g.,
def main(path: str):
#<<filenames = a list of filenames under path>>
for fn in filenames:
#<<size = size of fn in bytes>>
print(fn, size)
#<<use argparse and call main>>
$ python -m examples.file_sizes /etc
…
/etc/wgetrc 4942
/etc/nsswitch.conf 542
/etc/adduser.conf 3028
/etc/ethertypes 1816
The decorator invokes AI completion only the first time the function is run.
edit: I lost interest before I was able to get arguments to work ¯\_(ツ)_/¯
The potential issue I see here is that comments are valid anywhere while decorators may not be, but the parser is hopefully resilient to that. You could see a multi-phase LLM that uses the interpreter to ensure the code runs / works as expected
It’s completely different from a decorator that generates code at runtime? As in, when the code runs?
what if the output has comments?
in my question, there is no need for the decorator to be handled at runtime, the tool that does the LLM stuff has to parse the Python code to know what to generate. It can just key off of decorators rather than comments, or at least this is my question & hypothesis.
you can alternatively split generated code from human written code with files, keep the mapping in something more structured like a config file
I just normally see a better way to do the same thing a magic comment does, generally speaking. There is typically a better language construct if you limit yourself to that language (most common), and config files offer much more structure with existing tooling (mostly decode in your preferred language)