Earlier quoted context omitted.
When I'm that resource constrained, I don't use Python. The changes necessary to make regular Python code performant defeat the goal of making it readable. There's a reason NumPy's innards aren't Python code.
Both sides of this "readability vs. performance" debate can be argued ad absurdum but that's not my intention. All I know is that I try to conserve resources no matter what level of the stack I'm working on and those generated snippets certainly don't!
The Good and the Limitations of Github Copilot
141–144 of 144 posts
Re: The Good and the Limitations of Github Copilot
#142> Can help you with Email Validation and API Calls It generates a nastily complex regular expression that is hopelessly wrong. Visible at https://www.youtube.com/watch?v=9Pw-Roo_duE&t=404 , here transcribed: /^([\w-\.]+)@((\[[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.)|(([\w-]+\.)+))([a-zA-Z]{2,4}|[0-9]{1,3})(\]?)$/ For the local part, it requires [\w-\.]+, which excludes many valid characters like everyone’s favourite, +.…
Re: The Good and the Limitations of Github Copilot
#143Skimmed through this "review", nothing wowing me. > Hey Stephen, If you are reading this, please follow me on hashnode . God, that's obnoxious...
Re: The Good and the Limitations of Github Copilot
#144Earlier quoted context omitted.
This is exactly the problem. The regex issue isn’t that it’s not efficient, it’s that it’s wrong. Using this tool to generate code in a problem area you are not qualified to double-check and validate yourself is dangerous.
Very well put. Thank You. I know copilot is in alpha and will improve 100x but you will still need someone qualified to double check