5 ms·

I'm always asking it to stitch together ad hoc bash command lines for me, eg "find all the files called *.foo in directories called bar and search them for baz"

by flir 3y ago

I'm always asking it to stitch together ad hoc bash command lines for me, eg "find all the files called *.foo in directories called bar and search them for baz". (`find / -type d -name 'bar' -exec find {} -type f -name '*.foo' \; | xargs grep 'baz'` apparently.) I would have done that differently, but it's close enough for government work.

BlueTemplar 3y ago
Except you should at least try to write code for someone else (and probably of lower level of competence - this also helps for your own debugging later) - obscure one-liners like these should be rejected.
- Zababa 3y ago
  Assuming there is a comment just above the one-liner saying "find all directories named 'bar', find all files named '*.foo' in those directories, search those files for 'baz'", this code is perfectly clear. Even without the comment, it's not hard to understand.
- flir 3y ago
  I wouldn't call it obscure, just bog standard command line stuff. How would you have done it?
  - deleted 3y ago
    [deleted]
- radiator 3y ago
  To me, the only obscure thing about this is that it is a one-liner. If you write it in three lines, it is fine. Although, I guess the second find and the grep could be shortened, combined into one command.
  - BlueTemplar 3y ago
    I agree - but my point still stands.
- techbuttman 3y ago
  The lower level person need only plug that one liner into chatGPT and ask for a simple explanation. We're in a different era now.
  - maegul 3y ago
    Yep! It’s something some aren’t seeing. The AI coding assistant is now part of the abstraction layers over machine code. Higher level languages, scripting languages, all the happy paths we stick to (in bash, for example), memory management with GCs and borrow checkers, static analysis … now just add GPT. Like mastering memory management and assembly instructions … now you also don’t have to master the fiddly bits of core utils and bash and various other things. Like memory management, whole swathes of programming are being taken care of by another program now, a Garbage Collector, if you will, for all the crufty stuff that made computing hard and got in between intent and assessment.
    - Nullabillity 3y ago
      The difference is that all of them have theories and principles backing them, and we understand why they work. LLMs (and "AI" in general) are just bashing data together until you get something that looks correct (as long as you squint hard enough). Even putting them in the same category is incredibly insulting.
      - maegul 3y ago
        There are theories and principles behind what an AI is doing and a growing craft around how to best use AI that may very well form relatively established “best practices” over time. Yes there’s a significant statistical aspect involved in the workings of an AI, which distinguishes it from something more deterministic like syntactic sugar or a garbage collector. But I think one could argue that that’s the trade off for a more general tool like AI in the same way that giving a task to a junior dev is going to involve some noisiness in need of supervision. But in grand scheme of software development, is devs are in the end tools too, apart of the grand stack, and I think it’s reasonable to consider AI as just another tool in the stack. This is especially so if devs are already using it as a tool. Dwelling on the principled v statistical distinction, while salient, may very well be a fallacy or irrelevant to the extent that we want to talk about the stack of tools and techniques software development employs. How much does the average developer understand or employ said understanding of a principled component of their stack? How predictable is that component, at least in the hands of the average developer making average but real software? When the end of the pipeline is a human and it’s human organisation of other humans, whether a tool’s principled or statistical may not matter much so long as it’s useful or productive.
- emidln 3y ago
  If the someone elses on my team can't read a short shell pipeline then I failed during interviewing.
SavageBeast 3y ago
Same here! Thats the main use I have for ChatGPT in any practical sense today - generating Bash commands. I set about giving it prompts to do things that I've had to do in the past - it was great at it. Find all processes named '*-fpm' and kill the ones that have been active for more than 60 seconds - then schedule this as a Cron job to run every 60 seconds. It not only made me a working script rather than a single command but it explained its work. I was truly impressed. Yes it can generate some code wireframes that may be useful in a given project or feature. But I can do that too, usually in about the time it'd take me to adequately form my request into a prompt. Life could get dangerous in a hurry if product management got salty enough in the requirements phase that the specs for a feature could just be dropped into some code assistant and generate product. I don't see that happening ever though - not even with tooling - product people just don't seem to think that way in the first place in my experience. As developers we spend a lot of our time modifying existing product - and if the LLM knows about that product - all the better job it could do I suppose. Not saying that LLMs aren't useful now and won't become more useful in time - because they certainly will. What I am saying is that we all like to think of producing code as some mystical gift that only we as experienced (BRILLIANT, HANDSOME AND TALENTED TOO!!) developers are capable of. The reality is that once we reach a certain level of career maturity, if we were ever any good in the first place, writing code becomes the easiest part of the job. So theres a new tool that automates the easiest part of the job? Ok - autocomplete code editors we're cool too like that. The IDE was a game changer too. Automated unit tests were once black magic too (remember when the QA department was scared of this?). When some AI can look at a stack trace from a set of log files, being fully aware of the entire system architecture, locate the bug that compiled and passed testing all the way to production, recommend, implement, test and pre-deploy a fix while a human reviews the changes then we're truly onto something. Until then I'm not worried that it can write some really nice SQL against my schema with all kinds of crazy joins - because I can do that too - sometimes faster - sometimes not. So far ChatGPT isn't smarter than me but it is a very dutiful intern that does excellent work if you're patient and willing to adequately describe the problem, then make a few tweaks at the end. "Tweaks" up to seeing how the AI approached it, throwing it out and doing it your own way too.
LaGrange 3y ago
This is funny to me, because I would _always_ use -print0 and xargs -0, and for good reasons, I believe. But if you base your entire knowledge on what you find online, then yes, that's what you get - and what _most people will get too_. Also, I can still update that command if I want. So it's not any worse than good-old "go to stack overflow" approach, but still benefits from experience. FYI, this is the correct, as-far-as-I-can-tell "good" solution: find . -type d -name 'bar' -print0 | \ xargs -0 -I{} find {} -type f -name '*.foo' -print0 | \ xargs -0 grep -r baz This won't choke on a structure like this: ls -R .: bar foo ./bar: test.foo 'test test.foo' ./foo: bar bleb.foo ./foo/bar:
- LaGrange 3y ago
  ...actually find . -path '/bar/.foo' -print0 | xargs -0 grep baz ;-) no regex, no nested suff, much shorter. My brain went back to it ;-)
- lukeschlather 3y ago
  Using better languages like Powershell or Python becomes a lot more valuable here. I definitely think bash is going to be mostly useless in 5 years, you'll be able to generate legible code that does exactly what you want rather than having to do write-only stuff like that. Really we're already there. I've long switched from bash to something else at the first sign of trouble, but LLMs make it so easy. Poorly written python is better than well-written bash. Of course, LLMs can generate go or rust or whatever so I suspect such languages will become a lot more useful for things that would call for a scripting language today.
  - emporas 3y ago
    I would generalize even more and say that any scripting language is going to be deprecated very soon, like Python etc. They are going to be replaced by safe, type-checked, theorem-proved verbose code, like Rust or something similar. What do i care how many lines of code are necessary to solve a problem, if all of them are gonna be written automatically. 1 line of Bash/awk versus 10 lines of Python versus 100 lines of Rust? Are they any different to one another?
  - 3y ago
candiddevmike 3y ago
You can use gpt for government work??
- flir 3y ago
  Shh. What they don't know won't hurt me. (Serious answer: it's just an expression. https://grammarist.com/idiom/good-enough-for-government-work-and-close-enough-for-government-work/ https://grammarist.com/idiom/good-enough-for-government-work...).
sgarland 3y ago
$ find . -type f -regex '.*bar/[^/]*.foo' -exec grep baz {} + I wonder if you created a GPT and fed it the entirety of Linux man pages (not that it probably didn't consume them already, but perhaps this weights them higher), if it would get better at this kind of thing. I've found GPT-4 is shockingly good at sed, and to some extent awk; I suspect it's because there are good examples of them on SO.
- flir 3y ago
  If SO had known to block GPTBot before it was trained, GPT4 would be a lot less impressive.

by flir 3y ago

BlueTemplar 3y ago

Except you should at least try to write code for someone else (and probably of lower level of competence - this also helps for your own debugging later) - obscure one-liners like these should be rejected.

Zababa 3y ago
Assuming there is a comment just above the one-liner saying "find all directories named 'bar', find all files named '*.foo' in those directories, search those files for 'baz'", this code is perfectly clear. Even without the comment, it's not hard to understand.
flir 3y ago
I wouldn't call it obscure, just bog standard command line stuff. How would you have done it?
- deleted 3y ago
  [deleted]
radiator 3y ago
To me, the only obscure thing about this is that it is a one-liner. If you write it in three lines, it is fine. Although, I guess the second find and the grep could be shortened, combined into one command.
- BlueTemplar 3y ago
  I agree - but my point still stands.
techbuttman 3y ago
The lower level person need only plug that one liner into chatGPT and ask for a simple explanation. We're in a different era now.
- maegul 3y ago
  Yep! It’s something some aren’t seeing. The AI coding assistant is now part of the abstraction layers over machine code. Higher level languages, scripting languages, all the happy paths we stick to (in bash, for example), memory management with GCs and borrow checkers, static analysis … now just add GPT. Like mastering memory management and assembly instructions … now you also don’t have to master the fiddly bits of core utils and bash and various other things. Like memory management, whole swathes of programming are being taken care of by another program now, a Garbage Collector, if you will, for all the crufty stuff that made computing hard and got in between intent and assessment.
  - Nullabillity 3y ago
    The difference is that all of them have theories and principles backing them, and we understand why they work. LLMs (and "AI" in general) are just bashing data together until you get something that looks correct (as long as you squint hard enough). Even putting them in the same category is incredibly insulting.
    - maegul 3y ago
      There are theories and principles behind what an AI is doing and a growing craft around how to best use AI that may very well form relatively established “best practices” over time. Yes there’s a significant statistical aspect involved in the workings of an AI, which distinguishes it from something more deterministic like syntactic sugar or a garbage collector. But I think one could argue that that’s the trade off for a more general tool like AI in the same way that giving a task to a junior dev is going to involve some noisiness in need of supervision. But in grand scheme of software development, is devs are in the end tools too, apart of the grand stack, and I think it’s reasonable to consider AI as just another tool in the stack. This is especially so if devs are already using it as a tool. Dwelling on the principled v statistical distinction, while salient, may very well be a fallacy or irrelevant to the extent that we want to talk about the stack of tools and techniques software development employs. How much does the average developer understand or employ said understanding of a principled component of their stack? How predictable is that component, at least in the hands of the average developer making average but real software? When the end of the pipeline is a human and it’s human organisation of other humans, whether a tool’s principled or statistical may not matter much so long as it’s useful or productive.
emidln 3y ago
If the someone elses on my team can't read a short shell pipeline then I failed during interviewing.

SavageBeast 3y ago

Same here! Thats the main use I have for ChatGPT in any practical sense today - generating Bash commands. I set about giving it prompts to do things that I've had to do in the past - it was great at it. Find all processes named '*-fpm' and kill the ones that have been active for more than 60 seconds - then schedule this as a Cron job to run every 60 seconds. It not only made me a working script rather than a single command but it explained its work. I was truly impressed. Yes it can generate some code wireframes that may be useful in a given project or feature. But I can do that too, usually in about the time it'd take me to adequately form my request into a prompt. Life could get dangerous in a hurry if product management got salty enough in the requirements phase that the specs for a feature could just be dropped into some code assistant and generate product. I don't see that happening ever though - not even with tooling - product people just don't seem to think that way in the first place in my experience. As developers we spend a lot of our time modifying existing product - and if the LLM knows about that product - all the better job it could do I suppose. Not saying that LLMs aren't useful now and won't become more useful in time - because they certainly will. What I am saying is that we all like to think of producing code as some mystical gift that only we as experienced (BRILLIANT, HANDSOME AND TALENTED TOO!!) developers are capable of. The reality is that once we reach a certain level of career maturity, if we were ever any good in the first place, writing code becomes the easiest part of the job. So theres a new tool that automates the easiest part of the job? Ok - autocomplete code editors we're cool too like that. The IDE was a game changer too. Automated unit tests were once black magic too (remember when the QA department was scared of this?). When some AI can look at a stack trace from a set of log files, being fully aware of the entire system architecture, locate the bug that compiled and passed testing all the way to production, recommend, implement, test and pre-deploy a fix while a human reviews the changes then we're truly onto something. Until then I'm not worried that it can write some really nice SQL against my schema with all kinds of crazy joins - because I can do that too - sometimes faster - sometimes not. So far ChatGPT isn't smarter than me but it is a very dutiful intern that does excellent work if you're patient and willing to adequately describe the problem, then make a few tweaks at the end. "Tweaks" up to seeing how the AI approached it, throwing it out and doing it your own way too.

LaGrange 3y ago

This is funny to me, because I would _always_ use -print0 and xargs -0, and for good reasons, I believe. But if you base your entire knowledge on what you find online, then yes, that's what you get - and what _most people will get too_. Also, I can still update that command if I want. So it's not any worse than good-old "go to stack overflow" approach, but still benefits from experience. FYI, this is the correct, as-far-as-I-can-tell "good" solution: find . -type d -name 'bar' -print0 | \ xargs -0 -I{} find {} -type f -name '*.foo' -print0 | \ xargs -0 grep -r baz This won't choke on a structure like this: ls -R .: bar foo ./bar: test.foo 'test test.foo' ./foo: bar bleb.foo ./foo/bar:

LaGrange 3y ago
...actually find . -path '/bar/.foo' -print0 | xargs -0 grep baz ;-) no regex, no nested suff, much shorter. My brain went back to it ;-)
lukeschlather 3y ago
Using better languages like Powershell or Python becomes a lot more valuable here. I definitely think bash is going to be mostly useless in 5 years, you'll be able to generate legible code that does exactly what you want rather than having to do write-only stuff like that. Really we're already there. I've long switched from bash to something else at the first sign of trouble, but LLMs make it so easy. Poorly written python is better than well-written bash. Of course, LLMs can generate go or rust or whatever so I suspect such languages will become a lot more useful for things that would call for a scripting language today.
- emporas 3y ago
  I would generalize even more and say that any scripting language is going to be deprecated very soon, like Python etc. They are going to be replaced by safe, type-checked, theorem-proved verbose code, like Rust or something similar. What do i care how many lines of code are necessary to solve a problem, if all of them are gonna be written automatically. 1 line of Bash/awk versus 10 lines of Python versus 100 lines of Rust? Are they any different to one another?
- 3y ago

candiddevmike 3y ago

You can use gpt for government work??

flir 3y ago
Shh. What they don't know won't hurt me. (Serious answer: it's just an expression. https://grammarist.com/idiom/good-enough-for-government-work-and-close-enough-for-government-work/ https://grammarist.com/idiom/good-enough-for-government-work...).

sgarland 3y ago

$ find . -type f -regex '.*bar/[^/]*.foo' -exec grep baz {} + I wonder if you created a GPT and fed it the entirety of Linux man pages (not that it probably didn't consume them already, but perhaps this weights them higher), if it would get better at this kind of thing. I've found GPT-4 is shockingly good at sed, and to some extent awk; I suspect it's because there are good examples of them on SO.

flir 3y ago
If SO had known to block GPTBot before it was trained, GPT4 would be a lot less impressive.